RNAi-mediated gene silencing by small non-coding RNAs in ...

RNAi-mediated gene silencing by small non-coding

RNAs in protoplasts of Arabidopsis thaliana

Inaugural-Dissertation zur Erlangung der Doktorwürde

an der

Fakultät für Biologie der

Albert-Ludwigs-Universität Freiburg

vorgelegt von

Claude Becker

Dezember 2009

Dekan: Prof. Dr. Ad Aertsen

Vorsitzender des Promotionsausschusses: Prof. Dr. Eberhard Schäfer

Betreuer der Doktorarbeit: Prof. Dr. Klaus Palme

Zweitgutachter: Prof. Dr. Wolfgang Hess

Datum der Promotionsprüfung: 19. Februar 2010

Claude Becker i

Table of Contents

Aims of the project 1

Summary 3

General Conclusion 5

Chapter I – General introduction: 7

Gene regulation by small non-coding RNAs

Abstract 9

Small non-coding RNAs as regulators of gene expression 9

A short history of RNAi research 9

Small non-coding RNAs – origin and biogenesis 10

Target regulation by ncRNAs on the example of miRNAs 16

Regulation of miRNA activity 20

Origins and functions of RNAi mechanisms 21

Interconnection of RNAi pathways 22

RNA interference as a tool 22

Strategies for targeted gene silencing in plants 22

RNAi-based screening approaches 24

Experimental RNAi in single plant cells 25

References 26

Chapter II – Analysis of gene silencing by artificial microRNAs in 37

Arabidopsis thaliana protoplasts

Abstract 39

Introduction 39

Results 41

Discussion 52

Materials and Methods 55

References 58

Claude Becker ii

Chapter III – Efficient transfection with gene-specific short interfering 61

RNAs induces gene silencing in Arabidopsis protoplasts

Abstract 63

Introduction 63

Results 64

Discussion 72


References 78

Chapter IV – A novel platform for high-throughput protoplast 81

transformation and cell feature analysis

Abstract 83

Introduction 83

Results 84

Discussion 93


References 98

Acknowledgements 99

Appendix 103

Claude Becker AIMS OF THE PROJECT 1

- AIMS OF THE PROJECT -

This thesis addresses two major questions in the context of gene regulation by small

non-coding RNAs (ncRNAs) in the model plant Arabidopsis thaliana.

First, presented in Chapter II, the topic of targeted gene silencing by artificial microRNAs

(amiRNAs) in a single cell system was investigated. In previous experiments, gene

suppression in planta using amiRNAs had been found to be unreliable and inefficient in

many cases. The objective was therefore to develop a transient expression system in

Arabidopsis protoplasts for the rapid and quantitative assessment of amiRNA-mediated

gene silencing. These experiments aimed at (i) showing amiRNA-mediated gene silencing

in plant single cells, (ii) allowing pre-selection of amiRNAs for further in planta studies

and (iii) enabling the investigation of structure and sequence parameters influencing target

gene suppression by amiRNAs.

The second project, presented in Chapter III, was directed towards the development of

systematic RNA interference (RNAi) studies in single plant cells. To date, no platform for

a large-scale analysis of the effect of RNAi-mediated gene silencing on cellular behavior is

available. Therefore the possibility and the potential of gene silencing by short interfering

RNAs (siRNAs) in combination with high-content imaging in Arabidopsis protoplasts

were investigated. The aims of this project were (i) the establishment of protocols for

efficient cell transfection, (ii) the proof-of-principle of RNAi-mediated gene silencing in

Arabidopsis single cells and (iii) the assessment of the applicability of this technique for

large-scale RNAi experiments.

Both these projects required development and/or optimization of different protocols for the

experimental set-up, the cell treatment and culture, the vector design, the image acquisition

and the data analysis. An experimental pipeline for efficient protoplast analysis is

presented in Chapter IV.

Claude Becker SUMMARY 3

- SUMMARY -

The present thesis concentrated on the regulation of gene expression by small non-coding

RNAs (ncRNAs) in the model plant Arabidopsis thaliana. These short, 20-25 nucleotide-

long RNA molecules divide into different groups according to their biogenesis pathways

and their mode of target regulation. They are key players in transcriptional and post-

transcriptional gene regulation. The aim of this work was directed towards a better

understanding of the mechanisms underlying small ncRNA-mediated gene silencing and

the development of methods for efficient targeted inhibition of gene expression.

State of knowledge at the beginning of the thesis:

MicroRNAs (miRNAs) are endogenously encoded small ncRNAs involved in many plant

developmental processes, which suppress the expression of their target genes by induction

of mRNA cleavage or inhibition of mRNA translation. Their intracellular processing from

a primary transcript and their sequence complementarity to the target gene constituted the

basis for the development of artificial microRNAs (amiRNAs) for targeted gene knock-

down in loss-of-function experiments. However, for unknown reasons, amiRNA

expression often resulted in little or no alteration of target gene expression levels.

Short interfering RNAs (siRNAs) are 20-24 nucleotide-long ncRNAs, which can have

various origins. Delivery of synthetic siRNA duplexes has been established as a standard

technique in RNA interference (RNAi) studies in animal systems; siRNAs are routinely

applied as RNAi-inducing agents in reverse-genetic screens performed on single cells from

humans, mice, flies and nematodes. However, systematic gene silencing by delivery of

siRNAs in plant systems has not been thoroughly investigated.

Approaches and results of the thesis:

In this thesis a single-cell system for the analysis of amiRNA efficacy was established.

This involved protoplast transformation using minimal plasmid DNA amounts, automated

microscopy for high-content analysis and computational image analysis for cell

identification and fluorescence intensity measurements. A novel vector system was

designed for simultaneous transient expression of a transformation marker, an amiRNA

and its respective target gene in Arabidopsis protoplasts. Based on this test system, proof-

of-principle experiments were possible, showing efficient amiRNA-mediated silencing of a

stably expressed fluorescent reporter in Arabidopsis protoplasts and transgenic plants.

Claude Becker SUMMARY 4

Subsequently, it could be demonstrated that the inhibition of transiently expressed target

genes can be achieved by the simultaneous expression of functional amiRNAs.

In order to systematically investigate amiRNA efficacy, a large set of amiRNAs directed

against the same target gene was generated. The degrees of gene silencing induced by

these amiRNAs were variable in the transient protoplast system and correlated with

observations in stable transgenic lines of Arabidopsis. Analysis of the target mRNA

structure in the region of the amiRNA binding site and of the amiRNA-target hybrid was

performed in collaboration with the group of Prof. Dr. Rolf Backofen, Institute for

Informatics, University of Freiburg. First results indicated that stable secondary structures

of the target mRNA in the region of the target site were favorable to amiRNA

functionality. Additionally, so-far unconsidered basepairing situations in the amiRNA-

target hybrid seemed to influence amiRNA-mediated gene silencing.

In a second approach, a protocol for the transfection of Arabidopsis protoplasts with

siRNAs for targeted gene silencing was established. Through fluorescent conjugates, the

uptake of the siRNAs into intracellular compartments could be observed. The protocol was

optimized in order to achieve transfection of a significant fraction of the cell population. In

proof-of-principle experiments it was demonstrated that sequence-specific siRNAs directed

against the reporter gene mGFP5 (monomeric Green Fluorescent Protein 5) induced a

decrease of the GFP signal intensity in transfected protoplast populations. Similar results

were obtained in experiments on the silencing of a firefly luciferase reporter. Together,

these experiments constitute the first successful siRNA-mediated gene silencing in

Arabidopsis protoplasts and prepare the ground for large-scale analysis of gene function in

plant single cells.

Claude Becker GENERAL CONCLUSION 5

- GENERAL CONCLUSION -

Artificial microRNAs (amiRNAs) directed against a specific gene or a combination of

genes offer the possibility to study loss-of-function effects in stable transgenic lines.

However, amiRNA efficacy is highly variable and the parameters for amiRNA design are

not fully understood. The analysis of gene regulation by artificial microRNAs presented in

this study (Chapter II) has led to two major results. First, the efficiency with which a given

amiRNA silences its respective target gene could be assessed in a transient assay in plant

protoplasts. Hence, efficient amiRNAs can be pre-selected in a rapid and simple transient

assay; amiRNAs leading to only weak reduction of target gene expression can be

specifically selected in cases where mild silencing effects are desired. This constitutes a

major improvement in the generation of transgenic RNAi lines and leads to higher ease in

gene silencing studies. Second, using the single-cell system presented in this work, the

influence of target mRNA structure and amiRNA-target hybrid constellation on amiRNA

efficacy was systematically analyzed. A stable secondary structure of the target mRNA in

the region of the amiRNA binding site thus seemed to favor amiRNA-mediated gene

silencing whereas an open, flexible structure was inhibiting to the amiRNA activity. These

results offer the possibility of (i) an improved amiRNA design and (ii) a mechanistic

insight into miRNA-mediated inhibition of gene expression.

In experiments on single animal cells, RNAi can be induced by transfecting the cells with

short interfering RNAs (siRNAs). Reverse genetic screens and functional gene analysis

have thus been performed. However, RNAi studies in single plant cells have so-far played

a marginal role. Two advances in the directed gene silencing by siRNA transfection of

single plant cells are described in this thesis (Chapter III). First, a protocol for the efficient

transfection of Arabidopsis mesophyll protoplasts was established and siRNA uptake was

monitored. Labeled siRNAs marked areas in the cytosol; the identification of the latter

might give new information on endocytic trafficking pathways and/or on a potential link

between RNAi machinery and intracellular compartments. The second advance reported in

this part of the thesis is the first observation of siRNA-mediated gene knock-down in

single cells from Arabidopsis thaliana. The independent efficient knock-down of two

different reporter genes in mesophyll protoplasts constituted the proof-of-principle

experiment for gene silencing by siRNA transfection into these cells and prepares the

ground for RNAi screening experiments. The silencing of endogenous genes by siRNA

Claude Becker GENERAL CONCLUSION 6

transfection and a putative non-specific silencing of off-target genes still need to be further

investigated.

Additionally to the conclusions on amiRNA- and siRNA-mediated gene silencing

presented above, this study has also led to a number of technical advances in the context of

single cell analysis in the plant field (presented in Chapter IV). The generation of novel

vectors for simultaneous transient expression of multiple constructs facilitates protoplast

transformation by making multiple transformations obsolete while simultaneously

guaranteeing identical copy numbers for all templates. The optimization of protoplast

transformation protocols allowed the parallel transformation of multiple samples with low

amounts of plasmid DNA. For the first time, a platform for long-term observation via high-

content microscopy is presented. In combination with novel pipelines for the systematic

image-based identification and analysis of cellular features, it constitutes a powerful tool

for high-throughput screens on plant single cells.

In summary, the present work has contributed to the comprehension of small ncRNA-

mediated gene silencing and to the advance of RNAi techniques as well as single cell

analysis in plants. It (i) hints at a potential mechanistic explanation to miRNA-target

recognition, (ii) introduces a pipeline for validation of RNAi-inducing constructs and

presents (iii) a method for siRNA-mediated gene silencing in plant protoplasts as well as

(iv) a versatile technical platform for plant single-cell analysis.

Claude Becker CHAPTER I 7

- CHAPTER I -

General Introduction:

Gene regulation by small non-coding RNAs with a focus on RNA

interference in plants


Abstract

Small non-coding RNAs (ncRNAs) are key players in transcriptional and post-

transcriptional gene regulation in all eukaryotic organisms analyzed to date. Small

ncRNAs can be grouped into different families according to their size and biogenesis

pathway, their mode of target gene regulation or the biological pathways they are

involved in. This overview gives a summary of the most important ncRNA-related

mechanisms and RNA interference (RNAi) pathways and provides a description of

the classes of small ncRNAs in higher organisms, especially in plants. The focus lies

on the different biogenesis pathways and gene regulatory mechanisms. Finally, this

introduction summarizes applications of experimental RNAi in functional gene

analysis.

I. Small RNAs as regulators of gene expression

The differential regulation of gene expression is a complex process that controls the

development of an organism and its response to the environment. Besides the canonical

protein-based gene regulation by e.g. transcription factors, gene expression can be

influenced by different classes of short RNA molecules, generally referred to as small non-

coding RNAs (ncRNAs). They can be of different origin and size and are involved in

diverse pathways that finally lead to the transcriptional or post-transcriptional regulation of

target gene expression.

I.1. A short history of RNAi research

In 1998, Andrew Fire and Craig Mello reported that the directed silencing of a gene in the

nematode Caenorhabditis elegans was most efficient when mixtures of double-stranded

RNA (dsRNA) were applied and that only a few molecules were required to induce this

effect 1. They proposed an amplification mechanism leading to suppression of target gene

expression and thereby established RNAi as the silencing trigger, a work for which they

were awarded the Nobel Prize in Physiology and Medicine in 2006.

In plants, gene silencing by antisense RNA or by highly abundant sense transcripts of the

same gene had been previously observed 2,3

. Experiments performed on tomato and

tobacco plants finally indentified small, 20-25 nucleotide-long RNAs as the active

component inducing gene silencing 4. Shortly after, it was shown that these short

interfering RNAs (siRNAs) induced the cleavage of a sequence-complementary target


messenger RNA (mRNA) 5,6

. It was recognized that these siRNAs acted as duplexes with

2-nucleotide overhangs at the 3´ end and were produced by the RNase III enzyme Dicer 7-9

.

Another ground-breaking discovery was the identification of a class of small ncRNAs

endogenously encoded in the genome. These so-called microRNAs (miRNAs) were first

discovered in the nematode C. elegans 10,11

. They suppress the expression of their target

genes through different mechanisms 12

and are closely associated to developmental and

environmental response pathways in metazoans and plants.

I.2. Small ncRNAs – origin and biogenesis

Although small ncRNAs can be subdivided into different classes, their production and

gene regulatory pathways share several common features 13

. First, all small ncRNA

biogenesis pathways involve dsRNA, which gives rise to small, 20-30 nucleotide dsRNA

molecules. Second, these small ncRNAs are associated to effector complexes and guide the

silencing of one or several genes by (partial) sequence complementarity. Finally, the

biochemical machineries involved in each pathway show similarities: each RNAi pathway

involves an RNase III-type ribonuclease of the Dicer family 7 and the active small ncRNA

is incorporated into an RNA-Induced Silencing Complex (RISC). The latter invariably

contains a member of the Argonaute (AGO) protein family involved in the final target

RNA degradation 14

.

In the following, a more detailed description of the different small ncRNA classes is given.

It follows the most common classification, which is based on the different biogenesis

pathways 15

.

I.2.1. microRNAs

MicroRNAs constitute the best characterized and most intensely analyzed class of small

ncRNAs involved in post-transcriptional gene regulation. The first miRNA was discovered

in a mutant screen for post-embryonic development in the nematode C. elegans.

Characterization of the identified lin4 locus revealed that it gave rise to a small ncRNA

regulating the level of the lin14 gene product through binding to the 3´ UTR of the lin14

transcript 10,11

. This process was later recognized as a common gene regulatory mechanism

in many organisms. The first large-scale experiments for the identification of miRNA

genes were performed in C. elegans and Drosophila melanogaster 16-18

. To date, the

number of identified miRNAs has reached close to 700 for humans, while in the

Arabidopsis genome, 187 miRNAs have been annotated (according to miRBase, 19

).


The biogenesis of miRNAs differs between animals and plants, a fact which might be

explained by the respective evolution of the miRNA pathways in these kingdoms (see I.5).

In animal cells, miRNA genes are often organized in clusters and transcription occurs from

a single polycistronic transcription unit 20

. Many animal miRNAs originate from intronic

regions 21

. The majority of primary transcripts (pri-miRNA) are generated by RNA

Polymerase II (RNA Pol II) 22,23

, in some cases by RNA Pol III 24

. Animal miRNAs are

generally processed in two steps: first, the RNase III enzyme Drosha and its associated

protein DiGeorge syndrome Critical Region gene 8 (DGCR8) form the so-called

Microprocessor Complex. This complex processes the pri-miRNA to a 60-70 nucleotide

precursor miRNA (pre-miRNA) 20,25-29

. Some miRNAs have been shown to derive Drosha-

independently from shorter transcripts 21,30,31

. Recent data suggest that pri-miRNA

processing occurs co-transcriptionally 32-34

. The resulting pre-miRNA typically forms a

hairpin structure with a 2-nucleotide overhang at the 3´ end and a phosphate group at the

5´ end. Export of the pre-miRNA from the nucleus to the cytosol involves Exportin5, co-

operatively bound to a Ran-GTPase 35-38

.

The second processing step occurs in the cytosol and is catalyzed by Dicer, another

RNase III enzyme, comprising a PIWI-AGO-ZWILLE (PAZ) domain which enables it to

bind to the 2-nucleotide 3´ overhang of the pre-miRNA 39-41

. Whereas mammals have only

one Dicer gene, which is responsible for the processing of miRNAs and siRNAs, the

Drosophila genome contains two Dicer homologues. Drosophila Dicer-1 (DCR-1), bound

to its helper protein Loquacious (LOQS), is involved in miRNA processing; DCR-2 is

responsible for the production of siRNAs 42-45

. Dicer cleavage of the pre-miRNA produces

a 21-nucleotide long RNA duplex, generally referred to as the miRNA/miRNA* duplex.

Both strands in the miRNA/miRNA* duplex hybridize on a length of 19 basepairs, leaving

a 2-nucleotide overhang at each 3´ end. In the duplex, “miRNA” designates the target-

specific or “guide” strand, whereas “miRNA*” designates the non-used or “passenger”

strand.

Plant miRNAs are in general synthesized according to the same principles as their animal

counterparts. However, plants have developed a more diversified genetic framework to

regulate the different small ncRNA pathways. In Arabidopsis, miRNA genes (MIR genes)

are intergenic, usually organized as single genes with own promoters 46,47

. Clustering of

MIR genes has been found in some species, such as soy bean 48

. After transcription,

Arabidopsis pri-miRNAs are processed by the nuclear RNase III-type enzyme DICER-

LIKE 1 (DCL1) to pre-miRNAs, which are more variable in size and typically larger than


animal pre-miRNAs 49

. Arabidopsis possesses four different DCL genes but only DCL1 is

involved in miRNA processing 50

. In contrast to the animal miRNA biogenesis pathway,

DCL1 also performs the second cleavage step in the nucleus and converts the pre-miRNA

stem-loop to a mature miRNA/miRNA* duplex 49,51-53

. DCL1 activity and accuracy are

increased when it is associated with the dsRNA binding-domain (dsRBD) containing

protein HYPONASTIC LEAVES 1 (HYL1) 54

. DCL1 interacts with HYL1 and the zinc-

finger protein SERRATE (SE) in nuclear processing centers, so-called D-bodies 55

. SE,

like CBP80 (CAP-BINDING-PROTEIN 80) and CBP20, is a component of the nuclear

cap binding complex (CBC); all three proteins play a role in mRNA metabolism as well as

in pri-to-pre-miRNA processing 56,57

, indicating close links between the different RNA

synthesis pathways. The interaction of DCL1 with DAWDLE (DDL), another nuclear

RNA binding protein, increases pri-miRNA stability 58

. Fully processed miRNA/miRNA*

duplexes are exported from the nucleus in a yet not completely understood mechanism

involving the Exportin5 homolog HASTY (HST) 59

. Contrary to animal miRNAs, in the

cytosol both strands of the duplex are 2´-O-methylated at their 3´ end by the

methyltransferase HUA ENHANCER 1 (HEN1). This modification increases the stability

of the miRNA duplex by preventing 3´ uridylation. This modification generally marks

RNAs for degradation and has been shown to occur on plant miRNAs and pre-

miRNAs 52,60,61

. A summary of plant miRNA biogenesis is depicted in Fig. 1.

I.2.2. Short interfering RNAs of endogenous origin (endo-siRNAs)

Endo-siRNAs appear to be ubiquitous among higher eukaryotes. After having been first

described in C. elegans 62

and Arabidopsis thaliana 63

, they were shown to be also present

in mammals and in Drosophila melanogaster 15

.

In Arabidopsis, with its numerous, highly diversified small ncRNA pathways, endo-

siRNAs can be further subdivided into different groups according to their origin and the

way they are processed. These groups are presented here in an overview with the most

important mechanistic details; Fig. 1 illustrates the different pathways in Arabidopsis.

cis-acting siRNAs (casi-RNAs)

In Arabidopsis, casi-RNAs (also referred to as repeat-associated siRNAs or rasi-RNAs)

originate from transposons, repetitive elements and tandem repeats in the genome 63,64

.

They are considered as cis-acting agents as they target the DNA loci they originate from.

casi-RNAs are transcribed by the plant-specific RNA Polymerase IV 65-67

. Their biogenesis

implies the generation of dsRNA from the original transcript, a process necessitating the


activity of RNA-dependent RNA polymerases (RDRs; see also Fig. 2). Arabidopsis

possesses six RDR genes (RDR1-RDR6); in the synthesis of casi-RNAs, only RDR2 plays

a role 51

. The dsRNA molecules are then “diced” by the RNase III enzyme DICER-LIKE 3

(DCL3) into small, 24-nucleotide long RNA duplexes and methylated by HEN1 51,68

.

Loaded into either AGO4 or AGO6 69,70

, these siRNAs mediate heterochromatin formation

through DNA methylation and histone modification, thereby acting in transcriptional gene

silencing (TGS) 70-73

.

trans-acting siRNAs (tasi-RNAs)

As a point of convergence between siRNA and miRNA pathways, trans-acting siRNAs

represent a highly complex class of siRNAs 74-77

. As their name implies, tasi-RNAs target

mRNAs that originate from loci different from their own, thereby acting in trans. The so-

called TAS loci give rise to long, non-coding RNAs. These transcripts are targeted by a

miRNA which hybridizes to the TAS RNA and induces its cleavage. Ensuing recruitment

of RDR6 leads to the formation of dsRNA. By the action of DICER-LIKE 4 (DCL4), this

dsRNA is cleaved into 21-nucleotide tasi-RNAs; the cleavage is phased and starts exactly

at the miRNA cleavage site, resulting in a precisely defined population of siRNAs 77

which

are then loaded into AGO1 and/or AGO7. The feature that differentiates TAS transcripts

from other miRNA-targeted transcripts and thereby predisposes them for tasi-RNA

generation seems to be a second miRNA binding site within the TAS RNA sequence 78,79

.

natural antisense transcript-derived siRNAs (nat-siRNAs)

This term describes a class of siRNAs that are very often stress-responsive. Environmental

stimuli, such as nutrient deficiency, trigger the antisense transcription of a gene or

pseudogene, leading to the formation of dsRNA 80,81

. The processing of nat-siRNAs

requires the RNase III enzyme DICER-LIKE 2 (DCL2) (and maybe DCL1), the RNA-

dependent RNA Polymerase 6 (RDR6) and RNA Polymerase IV 80,81

.

The genomes of flies and mammals so far did not reveal any RDR genes (in contrast to

C. elegans), still these organisms show synthesis of endo-siRNAs 15

. The first reported

human endo-siRNA was traced back to a retrotransposon origin, hinting at a function in the

repression of retrotransposon transcription 82

. However, the mechanism by which this is

achieved has not been resolved yet. In Drosophila, populations of 21-nucleotide endo-

siRNAs that originate from different kinds of DNA regions (transposons, sense-antisense

transcripts, long stem-loop structures) could be identified 83-88

. Although it is known that


their processing is DCR-2-dependent 83,84,86

and that they bind to AGO2 84,86

, their exact

function is still unclear in most cases.

I.2.3. Piwi-binding RNAs (piRNAs)

piRNAs bind to a subgroup of AGO proteins referred to as the Piwi clade based on

sequence homology. piRNAs are the most recently discovered class of small ncRNAs 15

.

So far, they have been discovered in flies, mammals and nematodes, but not in plants.

They were first described in Drosophila germ line cells 89

and differ from siRNAs and

miRNAs by the fact that their generation is independent from DCR-1 and DCR-2 90

.

Although piRNAs have been studied in many organisms, they are best studied in flies,

where they seem to be crucial for germ line development 91

in accordance with Piwi

proteins being expressed exclusively in the germ cells and the surrounding somatic

Fig. 1 Small RNA pathways in the model plant Arabidopsis thaliana (adapted from Vazquez, 2006).


cells 92,93

. Mutants in piRNA biogenesis or action show strong phenotypes; still the exact

function of this class of small ncRNAs requires further investigation.

I.2.4. Exogenously triggered short interfering RNAs (exo-siRNAs)

RNAi-inducing small ncRNAs can derive from experimentally introduced DNA

sequences. The first observations on post-transcriptional gene silencing (PTGS) were made

in Petunia plants where an introduced transgene led to its own silencing as well as to

silencing of the endogenous homolog 94

. This effect was associated with dsRNA

generation from juxtaposed sense and antisense integrations of the transgene into the

genome. This resulted in the systematic use of inverted-repeat (IR) constructs for

IR-PTGS, which today constitute the most common technique for experimental RNAi in

plants 95-97

. Studies in combinatorial DCL-knockout mutants in Arabidopsis hint at

redundant DCL function in the production of siRNAs during IR-PTGS 98,99

.

Another origin of exo-siRNAs was detected when it became clear that high copy numbers

of a transgene sense transcript could induce PTGS in plants through the formation of

dsRNA. Forward-genetic screens to unravel this sense-PTGS (S-PTGS) pathway identified

the RNA-Dependent RNA polymerase 6 (RDR6) as a key component 100

. Another study

showed that mutations in the 5´-3´ exonuclease EXORIBONUCLEASE 4 (XRN4),

responsible for the degradation of uncapped RNAs, favored the production of transgene-

derived siRNAs. It was postulated that RDR6 converts aberrant RNA to dsRNA and

thereby initiates gene silencing 101

(see also Fig. 2).

Apart from experimentally introduced transgenes, naturally occurring sources can give rise

to exo-siRNAs. Viruses, whose genomes very often consist of ssRNA or dsRNA, are the

most prominent example 102

. The host produces small antiviral RNAs (viRNAs) either by

RDR-dependent dsRNA-synthesis from the viral genome or by making use of hairpin

structures in the viral RNA that serves as substrate for Dicer-mediated cleavage into 21- to

30-nucleotide RNAs. In Drosophila, infections with (+)ssRNA insect viruses lead to the

DCR-2-dependent formation of viRNAs 103-105

whereas in the context of dsRNA virus

infections, production of viRNAs seems to rely on DCR-1 function 106

. In the nematode

C. elegans, so far no natural viral infection has been described. Still, artificial viral

infections of adult worms and embryonic cells have led to the production of viRNAs and to

the conclusion that RNAi is an antiviral defense mechanism in C. elegans 107-109

. Most viral

defense responses via the RNAi pathway are known from the plant field. Upon viral

infection, viRNAs are produced by one or several of the three Dicer enzymes DCL2,


DCL3 and DCL4, depending on whether the viral genome consists of ssRNA, dsRNA or

dsDNA 102

. Biogenesis of viRNAs in plants depends on RDR1 and RDR6 110

. Co-evolution

of the virus and its host has led to the appearance of viral proteins that interfere with the

host’s RNAi machinery in order to weaken the defense response and allow the propagation

of the virus 111

. A model of the RDR-dependent amplification mechanism is depicted in

Fig. 2.

I.3. Target regulation by small ncRNAs on the example of miRNAs

In the context of target gene regulation, the underlying mechanisms are less heterogeneous

than for small ncRNA biogenesis. Apart from casi-RNA-mediated transcriptional silencing

through DNA methylation and histone modification, already described above, most other

small ncRNAs regulate their target post-transcriptionally. The best-studied and also most

complex regulation of target genes is mediated by miRNAs and can occur via one of three

Fig. 2 The amplification of the RNAi signal by the activity of RNA-dependent RNA polymerases in

the model organisms Arabidopsis thaliana and C. elegans (adapted from Ghildiyal and Zamore, 2009).


possible mechanisms: translational inhibition, accelerated exonucleolytic decay or site-

specific cleavage of the mRNA 12

.

The processing of the pre-miRNA ends in the cytosol with the generation of small dsRNA

duplexes with 2-nucleotide overhangs at the 3´ ends. These duplexes consist of the guide

strand (miRNA), which will mediate silencing of the target gene, and the passenger strand

(miRNA*), which will be ultimately discarded. The identity of the respective strands is

defined by the thermostability of their 5´ end, the strand of lower stability usually being

recognized as the guide strand 112,113

. The differentiation between both strands occurs after

the loading of the duplex into the RISC 5, a large cytosolic protein complex comprising a

member of the AGO protein family. In Drosophila, the RISC component R2D2 senses the

5’ thermostability 114,115

and confers the passenger strand to AGO2. There the passenger

strand is cleaved (“sliced”) between positions 10 and 11 and ultimately discarded 116

. More

recent data suggest that a second mechanism exists and that RNA helicases could unwind

the miRNA/miRNA* duplex in order to help remove the passenger strand in RISCs

containing AGO proteins that lack slicing activity 46

. The release of the passenger strand

converts the pre-RISC to a mature RISC. These principles of small ncRNA processing also

apply to siRNA duplexes.

The nature of the AGO protein which binds the small ncRNA within the RISC varies

between different small ncRNA classes. The fact that 27 members of the AGO protein

family have been identified in C. elegans hints at the high degree of diversity provided by

this interaction 117

. In Drosophila, AGO1 and AGO2 seem to bind miRNA and siRNA

duplexes, respectively, according to the pairing properties of the small ncRNA

duplex 118,119

. Arabidopsis has 10 AGO family members 120

and sorting of miRNAs in

Arabidopsis often relies on the 5´ nucleotide identity. It was shown that AGO1 and AGO2

preferentially bind miRNAs starting with a uridine and an adenosine, respectively, while

AGO4 favors heterochromatic, 24-nucleotide siRNAs starting with an adenosine 78,121,122

.

Upon loading, the mature RISC is directed to the target RNA by sequence

complementarities to the small ncRNA 123

. Animal miRNAs bind to target sites most often

located in the 3´ UTR of target mRNAs 124

. However, it has to be considered that recently,

several miRNA target sites could be identified in the open reading frames (ORFs) of

animal genes, maybe reflecting a bias of existing algorithms towards 3´ UTR searches 125-

127. Most animal miRNAs show high sequence complementarity to their target only at their

5´ end, more precisely between nucleotides 2-7, the so-called “seed” region 128,129

. The

seed contributes largely to target recognition 130,131

, which explains how a single animal


miRNA can have hundreds of different target genes 132,133

. The exact mode of target

regulation by miRNAs in animal systems is currently undergoing revision. miRNAs with

high target complementarities and central pairing to the target at positions 10 and 11 have

so-far been considered to act by mRNA cleavage, a process which occurs rather rarely in

animals 134

. miRNAs with lower sequence complementarities to the target RNA, especially

those miRNA-mRNA hybrids forming a central bulge (positions 9-12), have been thought

to act via translational repression. In this case the translation is inhibited either at the

initiation or the elongation step. However, more recent data indicate that many miRNA

pairing sites do not follow this “seed-rule” and that higher complementarity does not

necessarily lead to target mRNA cleavage 12

.

In plants, miRNAs usually have single, highly complementary target sites that mostly

locate to coding regions. Although the overall sequence complementarity is higher than for

animal miRNAs, the seed region still plays an important role in target regulation and

mismatches in this region impair miRNA functionality 135

. Target cleavage is the main

mechanism of plant miRNA-mediated gene regulation and is provided by the slicing

activity of AGO1 136

. However, AGO1-bound plant miRNAs can also inhibit

translation 137,138

and recent studies have established translational repression as a common

mechanism in plants 139

. Pairing at central nucleotides is important for efficient

slicing 140,141

but plant miRNAs with weak seed pairing also exist 142

. The seed region

could play the role of a nucleation site for base pairing between the miRNA and the

mRNA 129

. However, it has to be considered that apparent differences in target recognition

between animal and plant miRNAs could be due to biased data acquisition. As Brodersen

and Voinnet state in their latest review 12

, no systematic search for miRNA target sites with

imperfect complementarity has been performed to date. Slicing, which is considered the

common RNA degradation mechanism in plants, could eventually represent a rather

specialized process in the biogenesis of small ncRNAs (tasi-RNAs) and other non-coding

RNAs (ncRNAs). The observed miRNA-mediated mRNA decay could also be explained

by enhanced exonucleolytic decay 12

.

One factor which can decide whether a target mRNA undergoes cleavage or translational

repression consists in the type of AGO a miRNA is loaded to 143

. Similarly, messenger

ribonucleoprotein (mRNP) composition and promoter identity of the target gene can

influence this process 144

. Ultimately, different binding partners of AGO can influence its

repressing or slicing activity. This would open a possibility for the co-existence of both


mechanisms in dependence of developmental stage, tissue identity or environmental

stimulus 46

.

A crucial factor in target regulation is the target site accessibility, influenced by secondary

structures of the RNA as well as the presence or absence of RNA binding proteins 130,145

.

Engineered miRNA target sites in stem-loop structures inhibit miRNA-mediated

regulation 145

. In zebrafish and human cells, inhibition by overlap of miRNA target sites

with RNA Binding Protein (RBP) binding sites could be shown 146,147

. Similarly, in human

HEK cells, structural motives in the miRNA target site were shown to have an effect on the

binding of AGO to the mRNA and thereby on the level of translational inhibition 148

.

These findings have to be considered in the light of recent crystallographic data on AGO-

miRNA and AGO-mRNA interaction, summarized in Fig. 3. In the ternary complex, the

miRNA is bound at its 3’ end by the PAZ domain of the AGO protein 149,150

while its

5’ end inserts between the MID (MIDDLE) and PIWI (P ELEMENT INDUCED WIMPY

TESTIS) domains 151

. When bound to AGO, positions 2-8 of the miRNA, i.e. the seed

region, are exposed in a helical conformation to facilitate base-pairing with the target

RNA 152

. AGO then undergoes a conformational change to accommodate the target RNA

in that region 153

. Recent data with a DNA molecule as target of a miRNA-loaded bacterial

RISC indicated that AGO accommodates a 15-basepair stretch (positions 2-16 of the

miRNA) of the miRNA-target hybrid. After initial binding of the miRNA-target duplex at

Fig. 3 Interaction of AGO with miRNA and target RNA. When the miRNA (red) is bound by AGO,

nucleotides 2-8 are exposed (A) and can accommodate an 8mer of the target mRNA (B). While AGO

undergoes conformational changes, the pairing extends to the central region of the miRNA and the miRNA

3’ end is released (C). After complete pairing, the active site of AGO (black arrow) is positioned to cleave the

mRNA (D). Alternatively, the mRNA can pair to nucleotides 13–16 in a short helical segment without major

perturbation of the AGO protein or the remainder of the miRNA. In this mode, the miRNA and mRNA are not

wrapped around each other (E). Adapted from Bartel, 2009.


both ends, the 3’ end is released from the PAZ domain for the AGO to change its position

relative to the nucleic acid and to position itself to exhibit its slicing activity 154

.

I.4. Regulation of miRNA activity

MicroRNAs are a common and very efficient means of gene regulation at the post-

transcriptional level. However, miRNAs are themselves subject to regulation, best

illustrated by the fact that numerous miRNAs are tissue-specific and/or expressed at

precisely defined developmental stages 155,156

.

Transcriptional regulation represents the first level of miRNA activity control. As many

animal miRNA genes are organized as polycistronic transcripts or located in introns of

protein-coding genes, their transcription is potentially tied to other transcriptional control

mechanisms. Plant miRNA genes (MIR genes), on the other side, are mostly independent

genes with their own promoters 47

. Most common features identified in promoters of plant

MIR genes are stress- and hormone response elements 157

.

Post-transcriptional control is another way of spatio-temporal modulation of miRNA

activity. It has been shown in C. elegans that 3´ uridylation of a pre-miRNA inhibits Dicer

processing and leads to faster decay of the fragment 158

. In plants the identification of small

ncRNA degrading nucleases (SDNs) affecting miRNA stability was recently reported 159

.

These examples illustrate the possibility of regulation by interfering with RNA stability. In

addition, miRNA processing can be modulated by the interaction of the processing

enzymes with different accessory proteins 160

. A third possible mechanism for post-

transcriptional regulation consists in RNA editing. The exchange of nucleotides within the

pri-miRNA can either change the substrate properties for the dicing enzymes and regulate

the level of fully-processed miRNAs 161,162

or it can alter the target-specificity of the

mature miRNA 163

. Alternatively, variable processing of miRNAs under different

conditions can occur. In plants, different forms of the same miRNA have been detected

which diverge by 2-3 nucleotides in length, indicating different dicing of the pre-miRNA.

These miRNA variants could be loaded into different AGO complexes with implications

on their gene regulatory function 46

. Finally, a novel regulatory mechanism based on

sequestration of the miRNA has been recently described in Arabidopsis thaliana 164

. Upon

an environmental stimulus, a non-cleavable RNA with a miRNA 399 binding site is

expressed. It sequesters the mature miRNA and prevents degradation of the true miR399

target 164

. It is still unknown if more such “target mimicry” regulatory mechanisms exist.


Widespread miRNA regulation occurs through different kinds of feedback loops 165

.

Strikingly, components of the miRNA biogenesis machinery are regulated by their product

in single-negative feedback loops that lead to stable or oscillatory expression of both

components. In animal cells, Drosha regulates the level of its accessory protein DGCR8,

necessary for its own function, by cleaving the DGCR8 mRNA 166

. Dicer, responsible for

pre-miRNA processing, is regulated by the let-7 miRNA 127,167

. A similar loop has been

observed in Arabidopsis where DCL1 and AGO1 gene product levels are regulated by

miR162 and miR168, respectively 168,169

.

I.5. Origins and functions of the RNAi mechanisms

Small RNA biogenesis and regulation as well as small ncRNA-mediated gene silencing are

very complex. Origins, principles and reasons for the diversity of RNAi pathways become

clearer from the biological context of these processes.

As already mentioned above, RNAi has been linked to antiviral defense in several

organisms of different kingdoms, indicating a general role in immunity response 102

. A

highly adaptive RNAi machinery constitutes a very efficient barrier against viral attacks.

This is in accordance with the finding that DCR-2 and AGO-2 are among the fastest

evolving genes in Drosophila 170

, reflecting a need to adapt to viral pathogens. DCR-1,

which is responsible for miRNA biogenesis and therefore does not participate in the

immune response, has been subjected to less evolutionary pressure. In mammals, which

have an elaborate protein-based immune system, antiviral defense via RNAi could not be

shown so far. Endo-siRNAs have been shown to be involved, amongst other functions, in

the silencing of transposable elements in C. elegans 171,172

, Drosophila and Arabidopsis 173

.

The fact that siRNAs exist in all eukaryotic kingdoms (animals, plants and fungi) leads to

the conclusion that the last common ancestor must have possessed components of the

RNAi machinery 15

. In contrast, miRNAs have been detected in algae 174,175

, land plants

and metazoan animals 176

, but not in fungi. Furthermore, sequence comparisons have

shown that no single miRNA is shared by plants and animals. This indicates that the

miRNA pathways most likely have evolved independently in these two kingdoms, a fact

which might explain the differences in the biogenesis and regulation mechanisms. Some

plant miRNAs are highly conserved from mosses to angiosperms and play a role in

essential developmental processes 177

. However, recent deep sequencing approaches have

revealed that many Arabidopsis miRNAs are species- or even ecotype-specific and thereby

represent recent genes on an evolutionary scale. Strikingly, many of these recent MIR


genes (if not all) seem to have developed from duplicated genes that undergo antisense

transcription and sequence modification 178,179

.

I.6. Interconnection of RNAi pathways

Despite all the diversity in the different RNAi pathways, they should not be considered as

unrelated, independent processes. One of the best illustrations of crosstalk between the

RNAi mechanisms is the biogenesis of tasi-RNAs in Arabidopsis, where a miRNA-

mediated cleavage of a substrate is required for the synthesis of dsRNA which finally gives

rise to tasi-RNAs (see above) 74-76,78

. Whereas this situation reflects cooperation between

small ncRNA pathways, competition between the siRNA- and miRNA-related machinery

can occur. In Drosophila, siRNAs are generally loaded into AGO2, miRNA duplexes enter

the AGO1 complex. Both complexes seem to select their cargo based on the pairing

properties of the respective duplexes: AGO2 prefers perfectly paired siRNA duplexes

whereas loading into AGO1 appears to be related to the bulges and mismatches common in

miRNA duplexes. In situations with less obvious pairing properties, both complexes are

competing for the substrate; the loading affects the final target regulation by the small

ncRNA 118,119

.

In addition to these direct interactions, regulatory crosstalk also takes place. For example,

the negative regulation of Dicer by the let-7 miRNA in C. elegans affects the synthesis of

other small ncRNA classes 127,167

. Ultimately, these interconnections reflect a high level of

regulation and allow the fine-tuning of RNAi responses to specific cues.

II. RNA interference as a tool

II.1. Strategies for targeted gene silencing in plants

As mentioned above (see I.2.4), RNAi has been established as a standard tool in molecular

biology research. In the plant field, the use of antisense and inverted repeat constructs led

to the successful targeted gene down-regulation in different plant species 96,97

. These

strategies always include the formation of dsRNA fragments and hence the generation of

siRNAs targeting the gene of interest. Progressively refined vector designs have increased

the accuracy, the strength or the efficiency in suppressing specific genes 180,181

.

In the model plant Arabidopsis thaliana, gene function can often be analyzed with the help

of T-DNA insertion lines leading to the knock-out of the gene of interest 182

. However,

T-DNA insertions were and are still not available for all genes of the Arabidopsis genome


and the complete loss-of-function of numerous genes proved to be lethal to the plant.

Experimental RNAi helped solving these problems to some extent as it can be designed

against virtually any gene of interest. Furthermore, RNAi very often leads to a

knock-down, but not a complete knock-out of a gene, eventually resulting in residual gene

activity sufficient for plant survival. However, RNAi strategies also present some

drawbacks in terms of specificity, off-target silencing and restricted selection of the target

sequence. In addition, siRNAs can give rise to populations of secondary siRNAs by acting

as primers for RNA-dependent RNA polymerases. These secondary siRNAs in their turn

can target other genes, a mechanism referred to as transitivity 183

(see also Fig. 2 and I.2.4).

This risk of unpredictable off-target silencing is intensified by the lack of proper controls

via phenotype rescue. The loss of gene function in T-DNA knock-out mutants can be

compensated by the re-introduction of the gene, thereby proving the accuracy of the initial

gene suppression. The introduction of the coding sequence of the suppressed gene into the

RNAi background does not lead to reestablishment of gene function but rather emphasizes

the RNA silencing effect by adding more templates to the RNAi machinery 183,184

.

A new strategy developed using the knowledge on miRNA biology offered the

combination of the advantages of RNAi and T-DNA insertion techniques. As plant

miRNAs tend to show a high degree of sequence complementarity to their target

RNA, several research groups assumed that miRNAs could be used for gene silencing

studies. Based on different endogenous miRNA precursor sequences, they designed

strategies to replace the 21-nucleotide stretch of the mature miRNA against a 21-nucleotide

sequence complementary to a given target gene. By simultaneously exchanging the 21

nucleotides of the miRNA* strand, the stem-loop structure of the precursor was preserved

and the processing resulted in a novel miRNA/miRNA* duplex against a chosen target

gene. Several studies successfully used these artificial miRNAs (amiRNAs) for knock-

down experiments 141,185,186

. Their advantage lies in the specificity of sequence homology,

based on the short length of only 21 nucleotides. They could therefore be applied for the

knock-down of single as well as multiple genes with a single construct 185

. Additionally, it

has been postulated that miRNAs do not induce the generation of secondary siRNA

populations via RDR enzyme activity 60

, which reduces the risk of off-target silencing by

amiRNAs. Another advantage compared to inverted repeat or antisense constructs lies in

the possibility to rescue amiRNA gene knock-downs. amiRNA-resistant target genes can

be designed by altering the amiRNA binding site in order to prevent amiRNA binding

and/or mRNA cleavage 141

. This amiRNA-resistant gene can then be introduced into the


silenced background. amiRNAs have been used for efficient gene silencing in diverse plant

organisms, ranging from algae 187,188

to mosses 189

to higher plants 185,186

. Ultimately,

Weigel and colleagues developed a design tool for amiRNAs to be used for gene silencing

in Arabidopsis and other species 190

and amiRNAs nowadays constitute a standard

technique for targeted gene knock-down in plant and animal organisms.

II.2. RNAi-based screening approaches

In 2001, ground-breaking work by the Tuschl lab on Drosophila and mammalian cells 8,191

gave the final proof that siRNAs act as guide RNAs for sequence-specific mRNA

degradation and prepared the ground for experimental RNAi using siRNA duplexes.

Among the many RNAi techniques that have evolved over the last decade, the transfection

of animal cells with siRNAs to conduct reverse genetic studies is by far the most

widespread and the most developed. Genes can be silenced by transfecting cells with

chemically or enzymatically synthesized siRNAs or by expression of DNA constructs

encoding short hairpin RNAs (shRNAs) which are then processed to siRNAs.

Cell transfection techniques have been adapted for all kinds of cell lines. Commercial

reagents for the successful transfection on mammalian cell lines are often lipid-based and

rely on the facilitated active uptake of the siRNA-lipid complexes into the cell.

Alternatively, siRNA uptake rates can be increased by electroporation of the cells, by

chemical treatment or by mechanical injection 192

.

The sequencing and annotation of the complete genomes of several model organisms have

prepared the ground for a new era in RNAi-based research. In first genome-wide screens,

genes involved in early embryogenesis in C. elegans 193

or cell viability in Drosophila 194

were identified. Shortly after, the first successful screens were conducted in human

cells 195,196

. Today, genome-wide and more restricted siRNA screens on only a subset of

genes belong to the standard procedure for the functional characterization of genes and the

identification of missing links in molecular cascades. Appropriate siRNA collections,

many of them validated, are available from different companies.

However, numerous challenges are inherent in siRNA screens and require many

considerations prior and after the actual experiment: after having established an efficient

delivery protocol of the siRNAs to a specific cell line, correct experimental setup to

address the biological question as well as appropriate positive and negative controls need

to be selected. Additionally, identification of false positives originating from off-target

silencing has to be guaranteed and follow-up experiments for the validation of potential

candidates have to be designed. Correct statistical evaluation of the screen is indispensable


for the correct interpretation of the results 197-199

. These points are all the more important as

in recent years, siRNA screens on animal cell cultures have reached a new level of

complexity in the context of high content screens (HCS) 200

. HCS is defined as multiplexed

functional screening based on imaging multiple targets in the physiologic context of intact

cells by extraction of multicolor fluorescence information 201

. Such siRNA screens consist

of monitoring high numbers of cell populations, transfected with siRNAs from a defined or

genome-wide library, by multi-channel (confocal) microscopy in a time course. From

alterations in cell or organelle behavior, conclusions to the function of the targeted gene

can be drawn. In recent HCS, genes involved in mammalian cell division 202

or

apoptosis 203

could be identified.

These screens typically lead to the generation of massive data loads and therefore require

major investments into instrumentation, IT infrastructure and image analysis tools. These

efforts are rewarded by an unprecedented possibility to directly link gene loss-of-function

effects and observable cellular modifications at high resolution in medium- to high-

throughput and therefore the systematic analysis of whole gene networks and families.

II.3. Experimental RNAi in single plant cells

It has been described in the previous sections that many aspects of RNAi biology have first

been observed and investigated in plants and that efficient strategies for experimental

RNAi in plants are available. It is therefore noteworthy that no systematic RNAi-based

reverse genetic screen in a plant model organism has been presented to date. Additionally,

while studies on single cell systems in the animal field have made major contributions to

biological research, such systems have so-far played only a marginal role in the plant field.

Among others, the goal of the present thesis was to test the suitability of single plant cells

as a system to (i) gain information on small ncRNA pathways and (ii) conduct RNAi-

mediated loss-of-function studies.


III. References

1. Fire, A. et al. Potent and specific genetic interference by double-stranded RNA in

Caenorhabditis elegans. Nature 391, 806-811 (1998).

2. Vaucheret, H. et al. Transgene-induced gene silencing in plants. Plant J 16, 651-9

(1998).

3. Vaucheret, H. et al. Inhibition of tobacco nitrite reductase activity by expression of

antisense RNA. Plant J 2, 559-69 (1992).

4. Hamilton, A.J. & Baulcombe, D.C. A species of small antisense RNA in post-

transcriptional gene silencing in plants. Science 286, 950-952 (1999).

5. Hammond, S.M., Bernstein, E., Beach, D. & Hannon, G.J. An RNA-directed

nuclease mediates post-transcriptional gene silencing in Drosophila cells. Nature

404, 293-296 (2000).

6. Zamore, P.D., Tuschl, T., Sharp, P.A. & Bartel, D.P. RNAi: double-stranded RNA

directs the ATP-dependent cleavage of mRNA at 21 to 23 nucleotide intervals. Cell

101, 25-33 (2000).

7. Bernstein, E., Caudy, A.A., Hammond, S.M. & Hannon, G.J. Role for a bidentate

ribonuclease in the initiation step of RNA interference. Nature 409, 363-366

(2001).

8. Elbashir, S.M., Lendeckel, W. & Tuschl, T. RNA interference is mediated by 21-

and 22-nucleotide RNAs. Genes Dev. 15, 188-200 (2001).

9. Elbashir, S.M., Martinez, J., Patkaniowska, A., Lendeckel, W. & Tuschl, T.

Functional anatomy of siRNAs for mediating efficient RNAi in Drosophila

melanogaster embryo lysate. EMBO J. 20, 6877-6888 (2001).

10. Lee, R.C., Feinbaum, R.L. & Ambros, V. The C. elegans heterochronic gene lin-4

encodes small RNAs with antisense complementarity to lin-14. Cell 75, 843-854

(1993).

11. Wightman, B., Ha, I. & Ruvkun, G. Posttranscriptional regulation of the

heterochronic gene lin-14 by lin-4 mediates temporal pattern formation in C.

elegans. Cell 75, 855-862 (1993).

12. Brodersen, P. & Voinnet, O. Revisiting the principles of microRNA target

recognition and mode of action. Nature Reviews Molecular Cell Biology 10, 141-

148 (2009).

13. Brodersen, P. & Voinnet, O. The diversity of RNA silencing pathways in plants.

Trends in Genetics 22, 268-280 (2006).

14. Song, J.J., Smith, S.K., Hannon, G.J. & Joshua-Tor, L. Crystal structure of

Argonaute and its implications for RISC slicer activity. Science 305, 1434-1437

(2004).

15. Ghildiyal, M. & Zamore, P.D. Small silencing RNAs: an expanding universe.

Nature Reviews Genetics 10, 94-108 (2009).

16. Lagos-Quintana, M., Rauhut, R., Lendeckel, W. & Tuschl, T. Identification of

novel genes coding for small expressed RNAs. Science 294, 853-858 (2001).

17. Lee, R.C. & Ambros, V. An extensive class of small RNAs in Caenorhabditis

elegans. Science 294, 862-864 (2001).

18. Lau, N.C., Lim, L.P., Weinstein, E.G. & Bartel, D.P. An abundant class of tiny

RNAs with probable regulatory roles in Caenorhabditis elegans. Science 294, 858-

862 (2001).

19. Griffiths-Jones, S., Saini, H.K., van Dongen, S. & Enright, A.J. miRBase: tools for

microRNA genomics. Nucleic Acids Res. 36, D154-D158 (2008).

20. Lee, Y., Jeon, K., Lee, J.T., Kim, S. & Kim, V.N. MicroRNA maturation: stepwise

processing and subcellular localization. EMBO J. 21, 4663-4670 (2002).


21. Okamura, K., Hagen, J.W., Duan, H., Tyler, D.M. & Lai, E.C. The mirtron

pathway generates microRNA-class regulatory RNAs in Drosophila. Cell 130, 89-

100 (2007).

22. Lee, Y. et al. MicroRNA genes are transcribed by RNA polymerase II. Embo J 23,

4051-60 (2004).

23. Cai, X., Hagedorn, C.H. & Cullen, B.R. Human microRNAs are processed from

capped, polyadenylated transcripts that can also function as mRNAs. RNA 10,

1957-1966 (2004).

24. Borchert, G.M., Lanier, W. & Davidson, B.L. RNA polymerase III transcribes

human microRNAs. Nature Struct. Mol. Biol. 13, 1097-1101 (2006).

25. Lee, Y. et al. The nuclear RNase III Drosha initiates microRNA processing. Nature

425, 415-9 (2003).

26. Denli, A.M., Tops, B.B., Plasterk, R.H., Ketting, R.F. & Hannon, G.J. Processing

of primary microRNAs by the Microprocessor complex. Nature 432, 231-235

(2004).

27. Gregory, R.I. et al. The Microprocessor complex mediates the genesis of

microRNAs. Nature 432, 235-40 (2004).

28. Han, J. et al. The Drosha-DGCR8 complex in primary microRNA processing.

Genes Dev 18, 3016-27 (2004).

29. Landthaler, M., Yalcin, A. & Tuschl, T. The human DiGeorge syndrome critical

region gene 8 and its D. melanogaster homolog are required for miRNA biogenesis.

Curr. Biol. 14, 2162-2167 (2004).

30. Ruby, J.G., Jan, C.H. & Bartel, D.P. Intronic microRNA precursors that bypass

Drosha processing. Nature 448, 83-86 (2007).

31. Berezikov, E., Chung, W.J., Willis, J., Cuppen, E. & Lai, E.C. Mammalian mirtron

genes. Mol. Cell 28, 328-336 (2007).

32. Kim, Y.K. & Kim, V.N. Processing of intronic microRNAs. EMBO J. 26, 775-783

(2007).

33. Morlando, M. et al. Primary microRNA transcripts are processed co-

transcriptionally. Nat Struct Mol Biol 15, 902-9 (2008).

34. Pawlicki, J.M. & Steitz, J.A. Primary microRNA transcript retention at sites of

transcription leads to enhanced microRNA production. J. Cell Biol. 182, 61-76

(2008).

35. Yi, R., Qin, Y., Macara, I.G. & Cullen, B.R. Exportin-5 mediates the nuclear export

of pre-microRNAs and short hairpin RNAs. Genes Dev. 17, 3011-3016 (2003).

36. Bohnsack, M.T., Czaplinski, K. & Gorlich, D. Exportin 5 is a RanGTP-dependent

dsRNA-binding protein that mediates nuclear export of pre-miRNAs. RNA 10, 185-

191 (2004).

37. Lund, E., Guttinger, S., Calado, A., Dahlberg, J.E. & Kutay, U. Nuclear export of

microRNA precursors. Science 303, 95-98 (2004).

38. Zeng, Y. & Cullen, B.R. Structural requirements for pre-microRNA binding and

nuclear export by Exportin 5. Nucleic Acids Res. 32, 4776-4785 (2004).

39. Hutvagner, G. et al. A cellular function for the RNA-interference enzyme Dicer in

the maturation of the let-7 small temporal RNA. Science 293, 834-838 (2001).

40. Grishok, A. et al. Genes and mechanisms related to RNA interference regulate

expression of the small temporal RNAs that control C. elegans developmental

timing. Cell 106, 23-34 (2001).

41. Ketting, R.F. et al. Dicer functions in RNA interference and in synthesis of small

RNA involved in developmental timing in C. elegans. Genes Dev 15, 2654-9

(2001).


42. Lee, Y.S. et al. Distinct Roles for Drosophila Dicer-1 and Dicer-2 in the

siRNA/miRNA Silencing Pathways. Cell 117, 69-81 (2004).

43. Forstemann, K. et al. Normal microRNA maturation and germ-line stem cell

maintenance requires loquacious, a double-stranded RNA-binding domain protein.

Plos Biology 3, 1187-1201 (2005).

44. Jiang, F. et al. Dicer-1 and R3D1-L catalyze microRNA maturation in Drosophila.

Genes Dev 19, 1674-9 (2005).

45. Saito, K., Ishizuka, A., Siomi, H. & Siomi, M.C. Processing of pre-microRNAs by

the Dicer-1-Loquacious complex in Drosophila cells. PLoS Biol. 3, e235 (2005).

46. Voinnet, O. Origin, Biogenesis, and Activity of Plant MicroRNAs. Cell 136, 669-

687 (2009).

47. Xie, Z.X. et al. Expression of Arabidopsis MIRNA genes. Plant Physiology 138,

2145-2154 (2005).

48. Zhang, B., Pan, X. & Stellwag, E.J. Identification of soybean microRNAs and their

targets. Planta 229, 161-82 (2008).

49. Reinhart, B.J., Weinstein, E.G., Rhoades, M.W., Bartel, B. & Bartel, D.P.

MicroRNAs in plants. Genes Dev. 16, 1616-1626 (2002).

50. Kurihara, Y. & Watanabe, Y. Arabidopsis microRNA biogenesis through Dicer-

like 1 protein functions. Proc. Natl. Acad. Sci. USA 101, 12753-12758 (2004).

51. Xie, Z.X. et al. Genetic and functional diversification of small RNA pathways in

plants. Plos Biology 2, 642-652 (2004).

52. Park, W., Li, J., Song, R., Messing, J. & Chen, X. CARPEL FACTORY, a Dicer

homolog, and HEN1, a novel protein, act in microRNA metabolism in Arabidopsis

thaliana. Curr. Biol. 12, 1484-1495 (2002).

53. Papp, I. et al. Evidence for nuclear processing of plant micro RNA and short

interfering RNA precursors. Plant Physiol 132, 1382-90 (2003).

54. Kurihara, Y., Takashi, Y. & Watanabe, Y. The interaction between DCL1 and

HYL1 is important for efficient and precise processing of pri-miRNA in plant

microRNA biogenesis. RNA 12, 206-212 (2006).

55. Fang, Y. & Spector, D.L. Identification of nuclear dicing bodies containing proteins

for microRNA biogenesis in living Arabidopsis plants. Curr Biol 17, 818-23

(2007).

56. Gregory, B.D. et al. A link between RNA metabolism and silencing affecting

Arabidopsis development. Dev Cell 14, 854-66 (2008).

57. Laubinger, S. et al. Dual roles of the nuclear cap-binding complex and SERRATE

in pre-mRNA splicing and microRNA processing in Arabidopsis thaliana. Proc

Natl Acad Sci U S A 105, 8795-800 (2008).

58. Yu, B. et al. The FHA domain proteins DAWDLE in Arabidopsis and SNIP1 in

humans act in small RNA biogenesis. Proc Natl Acad Sci U S A 105, 10073-8

(2008).

59. Park, M.Y., Wu, G., Gonzalez-Sulser, A., Vaucheret, H. & Poethig, R.S. Nuclear

processing and export of microRNAs in Arabidopsis. Proc. Natl Acad. Sci. USA

102, 3691-3696 (2005).

60. Yu, B. et al. Methylation as a crucial step in plant microRNA biogenesis. Science

307, 932-5 (2005).

61. Yang, Z., Ebright, Y.W., Yu, B. & Chen, X. HEN1 recognizes 21-24 nt small RNA

duplexes and deposits a methyl group onto the 2[prime] OH of the 3[prime]

terminal nucleotide. Nucleic Acids Res. 34, 667-675 (2006).

62. Ambros, V., Lee, R.C., Lavanway, A., Williams, P.T. & Jewell, D. MicroRNAs

and other tiny endogenous RNAs in C. elegans. Curr. Biol. 13, 807-818 (2003).


63. Hamilton, A., Voinnet, O., Chappell, L. & Baulcombe, D. Two classes of short

interfering RNA in RNA silencing. EMBO J. 21, 4671-4679 (2002).

64. Tang, G.L., Reinhart, B.J., Bartel, D.P. & Zamore, P.D. A biochemical framework

for RNA silencing in plants. Genes & Development 17, 49-63 (2003).

65. Herr, A.J., Jensen, M.B., Dalmay, T. & Baulcombe, D.C. RNA polymerase IV

directs silencing of endogenous DNA. Science 308, 118-120 (2005).

66. Onodera, Y. et al. Plant nuclear RNA polymerase IV mediates siRNA and DNA

methylation-dependent heterochromatin formation. Cell 120, 613-22 (2005).

67. Pontier, D. et al. Reinforcement of silencing at transposons and highly repeated

sequences requires the concerted action of two distinct RNA polymerases IV in

Arabidopsis. Genes Dev 19, 2030-40 (2005).

68. Boutet, S. et al. Arabidopsis HEN1: a genetic link between endogenous miRNA

controlling development and siRNA controlling transgene silencing and virus

resistance. Curr Biol 13, 843-8 (2003).

69. Zheng, X., Zhu, J., Kapoor, A. & Zhu, J.K. Role of Arabidopsis AGO6 in siRNA

accumulation, DNA methylation and transcriptional gene silencing. EMBO J. 26,

1691-1701 (2007).

70. Zilberman, D., Cao, X. & Jacobsen, S.E. ARGONAUTE4 control of locus-specific

siRNA accumulation and DNA and histone methylation. Science 299, 716-719

(2003).

71. Chan, S.W.L. et al. RNA silencing genes control de novo DNA methylation.

Science 303, 1336-1336 (2004).

72. Llave, C., Kasschau, K.D., Rector, M.A. & Carrington, J.C. Endogenous and

silencing-associated small RNAs in plants. Plant Cell 14, 1605-1619 (2002).

73. Mette, M.F., Aufsatz, W., van der Winden, J., Matzke, M.A. & Matzke, A.J.

Transcriptional silencing and promoter methylation triggered by double-stranded

RNA. EMBO J. 19, 5194-5201 (2000).

74. Vazquez, F. et al. Endogenous trans-acting siRNAs regulate the accumulation of

Arabidopsis mRNAs. Molecular Cell 16, 69-79 (2004).

75. Peragine, A., Yoshikawa, M., Wu, G., Albrecht, H.L. & Poethig, R.S. SGS3 and

SGS2/SDE1/RDR6 are required for juvenile development and the production of

trans-acting siRNAs in Arabidopsis. Genes Dev. 18, 2368-2379 (2004).

76. Yoshikawa, M., Peragine, A., Park, M.Y. & Poethig, R.S. A pathway for the

biogenesis of trans-acting siRNAs in Arabidopsis. Genes Dev. 19, 2164-2175

(2005).

77. Allen, E., Xie, Z.X., Gustafson, A.M. & Carrington, J.C. microRNA-directed

phasing during trans-acting siRNA biogenesis in plants. Cell 121, 207-221 (2005).

78. Montgomery, T.A. et al. Specificity of ARGONAUTE7-miR390 interaction and

dual functionality in TAS3 trans-acting siRNA formation. Cell 133, 128-141

(2008).

79. Axtell, M.J., Jan, C., Rajagopalan, R. & Bartel, D.P. A two-hit trigger for siRNA

biogenesis in plants. Cell 127, 565-577 (2006).

80. Katiyar-Agarwal, S. et al. A pathogen-inducible endogenous siRNA in plant

immunity. Proc Natl Acad Sci U S A 103, 18002-7 (2006).

81. Borsani, O., Zhu, J., Verslues, P.E., Sunkar, R. & Zhu, J.K. Endogenous siRNAs

derived from a pair of natural cis-antisense transcripts regulate salt tolerance in

Arabidopsis. Cell 123, 1279-1291 (2005).

82. Yang, N. & Kazazian, H.H.J. L1 retrotransposition is suppressed by endogenously

encoded small interfering RNAs in human cultured cells. Nature Struct. Mol. Biol.

13, 763-771 (2006).


83. Ghildiyal, M. et al. Endogenous siRNAs derived from transposons and mRNAs in

Drosophila somatic cells. Science 320, 1077-1081 (2008).

84. Czech, B. et al. An endogenous small interfering RNA pathway in Drosophila.

Nature 453, 798-802 (2008).

85. Okamura, K. et al. The Drosophila hairpin RNA pathway generates endogenous

short interfering RNAs. Nature 453, 803-U8 (2008).

86. Kawamura, Y. et al. Drosophila endogenous small RNAs bind to Argonaute 2 in

somatic cells. Nature 453, 793-7 (2008).

87. Okamura, K., Balla, S., Martin, R., Liu, N. & Lai, E.C. Two distinct mechanisms

generate endogenous siRNAs from bidirectional transcription in Drosophila

melanogaster. Nature Struct. Mol. Biol. 15, 581-590 (2008).

88. Chung, W.J., Okamura, K., Martin, R. & Lai, E.C. Endogenous RNA interference

provides a somatic defense against Drosophila transposons. Curr. Biol. 18, 795-802

(2008).

89. Aravin, A.A. et al. Double-stranded RNA-mediated silencing of genomic tandem

repeats and transposable elements in the D. melanogaster germline. Curr Biol 11,

1017-27 (2001).

90. Vagin, V.V. et al. A distinct small RNA pathway silences selfish genetic elements

in the germline. Science 313, 320-324 (2006).

91. Aravin, A.A. Dissection of a natural RNA silencing process in the Drosophila

melanogaster germ line. Mol. Cell. Biol. 24, 6742-6750 (2004).

92. Cox, D.N. et al. A novel class of evolutionarily conserved genes defined by piwi

are essential for stem cell self-renewal. Genes Dev 12, 3715-27 (1998).

93. Cox, D.N., Chao, A. & Lin, H. piwi encodes a nucleoplasmic factor whose activity

modulates the number and division rate of germline stem cells. Development 127,

503-514 (2000).

94. Napoli, C., Lemieux, C. & Jorgensen, R. Introduction of a chimeric chalcone

synthase gene into Petunia results in reversible co-suppression of homologous

genes in trans. Plant Cell 2, 279-289 (1990).

95. Metzlaff, M., O'Dell, M., Cluster, P.D. & Flavell, R.B. RNA-mediated RNA

degradation and chalcone synthase A silencing in petunia. Cell 88, 845-54 (1997).

96. Waterhouse, P.M., Graham, M.W. & Wang, M.B. Virus resistance and gene

silencing in plants can be induced by simultaneous expression of sense and

antisense RNA. Proc Natl Acad Sci U S A 95, 13959-64 (1998).

97. Chuang, C.F. & Meyerowitz, E.M. Specific and heritable genetic interference by

double-stranded RNA in Arabidopsis thaliana. Proc Natl Acad Sci U S A 97, 4985-

90 (2000).

98. Gasciolli, V., Mallory, A.C., Bartel, D.P. & Vaucheret, H. Partially redundant

functions of Arabidopsis DICER-like enzymes and a role for DCL4 in producing

trans-acting siRNAs. Curr. Biol. 15, 1494-1500 (2005).

99. Xie, Z.X., Allen, E., Wilken, A. & Carrington, J.C. DICER-LIKE 4 functions in

trans-acting small interfering RNA biogenesis and vegetative phase change in

Arabidopsis thaliana. Proceedings of the National Academy of Sciences of the

United States of America 102, 12984-12989 (2005).

100. Dalmay, T., Hamilton, A., Rudd, S., Angell, S. & Baulcombe, D.C. An RNA-

dependent RNA polymerase gene in Arabidopsis is required for posttranscriptional

gene silencing mediated by a transgene but not by a virus. Cell 101, 543-553

(2000).

101. Gazzani, S., Lawrenson, T., Woodward, C., Headon, D. & Sablowski, R. A link

between mRNA turnover and RNA interference in Arabidopsis. Science 306, 1046-

1048 (2004).


102. Ding, S.W. & Voinnet, O. Antiviral immunity directed by small RNAs. Cell 130,

413-426 (2007).

103. Galiana-Arnoux, D., Dostert, C., Schneemann, A., Hoffmann, J.A. & Imler, J.L.

Essential function in vivo for Dicer-2 in host defense against RNA viruses in

drosophila. Nat Immunol 7, 590-7 (2006).

104. van Rij, R.P. et al. The RNA silencing endonuclease Argonaute 2 mediates specific

antiviral immunity in Drosophila melanogaster. Genes Dev 20, 2985-95 (2006).

105. Wang, X.H. et al. RNA interference directs innate immunity against viruses in adult

Drosophila. Science 312, 452-4 (2006).

106. Zambon, R.A., Vakharia, V.N. & Wu, L.P. RNAi is an antiviral immune response

against a dsRNA virus in Drosophila melanogaster. Cell Microbiol 8, 880-9 (2006).

107. Lu, R. et al. Animal virus replication and RNAi-mediated antiviral silencing in


108. Schott, D.H., Cureton, D.K., Whelan, S.P. & Hunter, C.P. An antiviral role for the

RNA interference machinery in Caenorhabditis elegans. Proc Natl Acad Sci U S A

102, 18420-4 (2005).

109. Wilkins, C. et al. RNA interference is an antiviral defence mechanism in


110. Voinnet, O. Use, tolerance and avoidance of amplified RNA silencing by plants.

Trends Plant Sci. 13, 317-328 (2008).

111. Li, F. & Ding, S.W. Virus counterdefense: diverse strategies for evading the RNA-

silencing immunity. Annu. Rev. Microbiol. 60, 503-531 (2006).

112. Schwarz, D.S. et al. Asymmetry in the assembly of the RNAi enzyme complex.

Cell 115, 199-208 (2003).

113. Khvorova, A., Reynolds, A. & Jayasena, S.D. Functional siRNAs and miRNAs

exhibit strand bias. Cell 115, 209-216 (2003).

114. Liu, Q. et al. R2D2, a bridge between the initiation and effector steps of the

Drosophila RNAi pathway. Science 301, 1921-5 (2003).

115. Tomari, Y., Matranga, C., Haley, B., Martinez, N. & Zamore, P.D. A protein sensor

for siRNA asymmetry. Science 306, 1377-1380 (2004).

116. Rand, T.A., Petersen, S., Du, F. & Wang, X. Argonaute2 cleaves the anti-guide

strand of siRNA during RISC activation. Cell 123, 621-629 (2005).

117. Yigit, E. et al. Analysis of the C. elegans Argonaute family reveals that distinct

Argonautes act sequentially during RNAi. Cell 127, 747-57 (2006).

118. Tomari, Y., Du, T. & Zamore, P.D. Sorting of Drosophila small silencing RNAs.

Cell 130, 299-308 (2007).

119. Forstemann, K., Horwich, M.D., Wee, L.M., Tomari, Y. & Zamore, P.D.

Drosophila microRNAs are sorted into functionally distinct Argonaute protein

complexes after their production by Dicer-1. Cell 130, 287-297 (2007).

120. Vaucheret, H. Plant ARGONAUTES. Trends Plant Sci. 13, 350-358 (2008).

121. Mi, S. et al. Sorting of small RNAs into Arabidopsis argonaute complexes is

directed by the 5' terminal nucleotide. Cell 133, 116-27 (2008).

122. Takeda, A., Iwasaki, S., Watanabe, T., Utsumi, M. & Watanabe, Y. The

mechanism selecting the guide strand from small RNA duplexes is different among

argonaute proteins. Plant Cell Physiol 49, 493-500 (2008).

123. Eulalio, A., Huntzinger, E. & Izaurralde, E. Getting to the root of miRNA-mediated

gene silencing. Cell 132, 9-14 (2008).

124. Carthew, R.W. & Sontheimer, E.J. Origins and Mechanisms of miRNAs and

siRNAs. 136, 642-655 (2009).

125. Duursma, A.M., Kedde, M., Schrier, M., le Sage, C. & Agami, R. miR-148 targets

human DNMT3b protein coding region. RNA 14, 872-877 (2008).


126. Lal, A. et al. p16(INK4a) translation suppressed by miR-24. PLoS One 3, e1864

(2008).

127. Forman, J.J., Legesse-Miller, A. & Coller, H.A. A search for conserved sequences

in coding regions reveals that the let-7 microRNA targets Dicer within its coding

sequence. Proc. Natl Acad. Sci. USA 105, 14879-14884 (2008).

128. Brennecke, J., Stark, A., Russell, R.B. & Cohen, S.M. Principles of microRNA-

target recognition. PLoS Biol. 3, e85 (2005).

129. Lewis, B.P., Shih, I.H., Jones-Rhoades, M.W., Bartel, D.P. & Burge, C.B.

Prediction of mammalian microRNA targets. Cell 115, 787-798 (2003).

130. Ameres, S.L., Martinez, J. & Schroeder, R. Molecular basis for target RNA

recognition and cleavage by human RISC. Cell 130, 101-112 (2007).

131. Haley, B. & Zamore, P.D. Kinetic analysis of the RNAi enzyme complex. Nature

Struct. Mol. Biol. 11, 599-606 (2004).

132. Baek, D. et al. The impact of microRNAs on protein output. Nature 455, 64-71

(2008).

133. Selbach, M. et al. Widespread changes in protein synthesis induced by microRNAs.

Nature 455, 58-63 (2008).

134. Yekta, S., Shih, I.H. & Bartel, D.P. MicroRNA-directed cleavage of HOXB8

mRNA. Science 304, 594-596 (2004).

135. Mallory, A.C. et al. MicroRNA control of PHABULOSA in leaf development:

importance of pairing to the microRNA 5 ' region. Embo Journal 23, 3356-3364

(2004).

136. Baumberger, N. & Baulcombe, D.C. Arabidopsis ARGONAUTE1 is an RNA

Slicer that selectively recruits microRNAs and short interfering RNAs. Proc. Natl.

Acad. Sci. USA 102, 11928-11933 (2005).

137. Chen, X. A microRNA as a translational repressor of APETALA2 in Arabidopsis

flower development. Science 303, 2022-2025 (2004).

138. Aukerman, M.J. & Sakai, H. Regulation of flowering time and floral organ identity

by a microRNA and its APETALA2-like target genes. Plant Cell 15, 2730-2741

(2003).

139. Brodersen, P. et al. Widespread translational inhibition by plant miRNAs and

siRNAs. Science 320, 1185-1190 (2008).

140. Schwab, R. et al. Specific effects of microRNAs on the plant transcriptome. Dev

Cell 8, 517-27 (2005).

141. Parizotto, E.A., Dunoyer, P., Rahm, N., Himber, C. & Voinnet, O. In vivo

investigation of the transcription, processing, endonucleolytic activity, and

functional relevance of the spatial distribution of a plant miRNA. Genes Dev. 18,

2237-2242 (2004).

142. Jones-Rhoades, M.W. & Bartel, D.P. Computational identification of plant

microRNAs and their targets, including a stress-induced miRNA. Mol. Cell 14,

787-799 (2004).

143. Wu, L., Fan, J. & Belasco, J.G. Importance of translation and nonnucleolytic Ago

proteins for on-target RNA interference. Curr. Biol. 18, 1327-1332 (2008).

144. Kong, Y.W. et al. The mechanism of micro-RNA-mediated translation repression is

determined by the promoter of the target gene. Proc Natl Acad Sci U S A 105,

8866-71 (2008).

145. Kertesz, M., Iovino, N., Unnerstall, U., Gaul, U. & Segal, E. The role of site

accessibility in microRNA target recognition. Nature Genet. 39, 1278-1284 (2007).

146. Kedde, M. et al. RNA-binding protein Dnd1 inhibits microRNA access to target

mRNA. Cell 131, 1273-86 (2007).


147. Bhattacharyya, S.N., Habermacher, R., Martine, U., Closs, E.I. & Filipowicz, W.

Relief of microRNA-mediated translational repression in human cells subjected to

stress. Cell 125, 1111-1124 (2006).

148. Hausser, J., Landthaler, M., Jaskiewicz, L., Gaidatzis, D. & Zavolan, M. Relative

contribution of sequence and structure features to the mRNA binding of

Argonaute/EIF2C-miRNA complexes and the degradation of miRNA targets.

Genome Res (2009).

149. Lingel, A., Simon, B., Izaurralde, E. & Sattler, M. Nucleic acid 3'-end recognition

by the Argonaute2 PAZ domain. Nature Struct. Mol. Biol. 11, 576-577 (2004).

150. Ma, J.B., Ye, K. & Patel, D.J. Structural basis for overhang-specific small

interfering RNA recognition by the PAZ domain. Nature 429, 318-322 (2004).

151. Ma, J.B. Structural basis for 5[prime]-end-specific recognition of guide RNA by

the A. fulgidus Piwi protein. Nature 434, 666-670 (2005).

152. Wang, Y., Sheng, G., Juranek, S., Tuschl, T. & Patel, D.J. Structure of the guide-

strand-containing argonaute silencing complex. Nature 456, 209-213 (2008).

153. Wang, Y. et al. Structure of an argonaute silencing complex with a seed-containing

guide DNA and target RNA duplex. Nature 456, 921-6 (2008).

154. Wang, H.W. et al. Structural insights into RNA processing by the human RISC-

loading complex. Nat Struct Mol Biol 16, 1148-53 (2009).

155. Landgraf, P. et al. A mammalian microRNA expression atlas based on small RNA

library sequencing. Cell 129, 1401-14 (2007).

156. Valoczi, A., Varallyay, E., Kauppinen, S., Burgyan, J. & Havelda, Z. Spatio-

temporal accumulation of microRNAs is highly coordinated in developing plant

tissues. Plant J 47, 140-51 (2006).

157. Megraw, M. et al. MicroRNA promoter element discovery in Arabidopsis. Rna 12,

1612-9 (2006).

158. Heo, I. et al. Lin28 mediates the terminal uridylation of let-7 precursor MicroRNA.

Mol Cell 32, 276-84 (2008).

159. Ramachandran, V. & Chen, X. Degradation of microRNAs by a family of

exoribonucleases in Arabidopsis. Science 321, 1490-1492 (2008).

160. Guil, S. & Caceres, J.F. The multifunctional RNA-binding protein hnRNP A1 is

required for processing of miR-18a. Nature Struct. Mol. Biol. 14, 591-596 (2007).

161. Yang, W. et al. Modulation of microRNA processing and expression through RNA

editing by ADAR deaminases. Nat Struct Mol Biol 13, 13-21 (2006).

162. Kawahara, Y., Zinshteyn, B., Chendrimada, T.P., Shiekhattar, R. & Nishikura, K.

RNA editing of the microRNA-151 precursor blocks cleavage by the Dicer-TRBP

complex. EMBO Rep. 8, 763-769 (2007).

163. Kawahara, Y. et al. Frequency and fate of microRNA editing in human brain.

Nucleic Acids Res 36, 5270-80 (2008).

164. Franco-Zorrilla, J.M. et al. Target mimicry provides a new mechanism for

regulation of microRNA activity. Nat Genet 39, 1033-7 (2007).

165. Martinez, N.J. et al. A C. elegans genome-scale microRNA network contains

composite feedback motifs with high flux capacity. Genes Dev 22, 2535-49 (2008).

166. Han, J. et al. Posttranscriptional crossregulation between Drosha and DGCR8. Cell

136, 75-84 (2009).

167. Tokumaru, S., Suzuki, M., Yamada, H., Nagino, M. & Takahashi, T. let-7 regulates

Dicer expression and constitutes a negative feedback loop. Carcinogenesis 29,

2073-2077 (2008).

168. Xie, Z., Kasschau, K.D. & Carrington, J.C. Negative feedback regulation of Dicer-

like1 in Arabidopsis by microRNA-guided mRNA degradation. Curr. Biol. 13,

784-789 (2003).


169. Vaucheret, H., Vazquez, F., Crete, P. & Bartel, D.P. The action of ARGONAUTE1

in the miRNA pathway and its regulation by the miRNA pathway are crucial for

plant development. Genes Dev. 18, 1187-1197 (2004).

170. Obbard, D.J., Jiggins, F.M., Halligan, D.L. & Little, T.J. Natural selection drives

extremely rapid evolution in antiviral RNAi genes. Curr. Biol. 16, 580-585 (2006).

171. Tabara, H., Yigit, E., Siomi, H. & Mello, C.C. The dsRNA binding protein RDE-4

interacts with RDE-1, DCR-1, and a DExH-box helicase to direct RNAi in C.

elegans. Cell 109, 861-871 (2002).

172. Ketting, R.F., Haverkamp, T.H., van Luenen, H.G. & Plasterk, R.H. mut-7 of C.

elegans, required for transposon silencing and RNA interference, is a homolog of

Werner syndrome helicase and RNaseD. Cell 99, 133-141 (1999).

173. Slotkin, R.K. et al. Epigenetic reprogramming and small RNA silencing of

transposable elements in pollen. Cell 136, 461-72 (2009).

174. Molnar, A., Schwach, F., Studholme, D.J., Thuenemann, E.C. & Baulcombe, D.C.

miRNAs control gene expression in the single-cell alga Chlamydomonas

reinhardtii. Nature 447, 1126-1129 (2007).

175. Zhao, T. et al. A complex system of small RNAs in the unicellular green alga

Chlamydomonas reinhardtii. Genes Dev 21, 1190-203 (2007).

176. Grimson, A. Early origins and evolution of microRNAs and Piwi-interacting RNAs

in animals. Nature 455, 1193-1197 (2008).

177. Garcia, D. A miRacle in plant development: role of microRNAs in cell

differentiation and patterning. Semin Cell Dev Biol 19, 586-95 (2008).

178. Allen, E. et al. Evolution of microRNA genes by inverted duplication of target gene

sequences in Arabidopsis thaliana. Nature Genetics 36, 1282-1290 (2004).

179. Fahlgren, N. et al. High-throughput sequencing of Arabidopsis microRNAs:

evidence for frequent birth and death of MIRNA genes. PLoS One 2, e219 (2007).

180. Lu, S. et al. RNA silencing in plants by the expression of siRNA duplexes. Nucleic

Acids Res 32, e171 (2004).

181. Lu, R., Martin-Hernandez, A.M., Peart, J.R., Malcuit, I. & Baulcombe, D.C. Virus-

induced gene silencing in plants. Methods 30, 296-303 (2003).

182. Alonso, J.M. et al. Genome-wide insertional mutagenesis of Arabidopsis thaliana.

Science 301, 653-7 (2003).

183. Baulcombe, D.C. Amplified silencing. Science 315, 199-200 (2007).

184. Sijen, T. et al. On the role of RNA amplification in dsRNA-triggered gene

silencing. Cell 107, 465-76 (2001).

185. Schwab, R., Ossowski, S., Riester, M., Warthmann, N. & Weigel, D. Highly

specific gene silencing by artificial microRNAs in Arabidopsis. Plant Cell 18,

1121-33 (2006).

186. Alvarez, J.P. et al. Endogenous and synthetic microRNAs stimulate simultaneous,

efficient, and localized regulation of multiple targets in diverse species. Plant Cell

18, 1134-51 (2006).

187. Molnar, A. et al. Highly specific gene silencing by artificial microRNAs in the

unicellular alga Chlamydomonas reinhardtii. Plant Journal 58, 165-174 (2009).

188. Zhao, T., Wang, W., Bai, X. & Qi, Y.J. Gene silencing by artificial microRNAs in

Chlamydomonas. Plant Journal 58, 157-164 (2009).

189. Khraiwesh, B., Ossowski, S., Weigel, D., Reski, R. & Frank, W. Specific gene

silencing by artificial MicroRNAs in Physcomitrella patens: an alternative to

targeted gene knockouts. Plant Physiol 148, 684-93 (2008).

190. Ossowski, S., Schwab, R. & Weigel, D. Gene silencing in plants using artificial

microRNAs and other small RNAs. Plant J 53, 674-90 (2008).


191. Elbashir, S.M. Duplexes of 21-nucleotide RNAs mediate RNA interference in

cultured mammalian cells. Nature 411, 494-498 (2001).

192. Li, C.X. et al. Delivery of RNA Interference. Cell Cycle 5, 2103-2109 (2006).

193. Fraser, A.G. et al. Functional genomic analysis of C. elegans chromosome I by

systematic RNA interference. Nature 408, 325-30 (2000).

194. Boutros, M. et al. Genome-wide RNAi analysis of growth and viability in

Drosophila cells. Science 303, 832-5 (2004).

195. Paddison, P.J. et al. A resource for large-scale RNA-interference-based screens in

mammals. Nature 428, 427-31 (2004).

196. Zheng, L. et al. An approach to genomewide screens of expressed small interfering

RNAs in mammalian cells. Proc Natl Acad Sci U S A 101, 135-40 (2004).

197. Sachse, C. et al. High-throughput RNA interference strategies for target discovery

and validation by using synthetic short interfering RNAs: functional genomics

investigations of biological pathways. Methods Enzymol 392, 242-77 (2005).

198. Echeverri, C.J. et al. Minimizing the risk of reporting false positives in large-scale

RNAi screens. Nat Methods 3, 777-9 (2006).

199. Echeverri, C.J. & Perrimon, N. High-throughput RNAi screening in cultured cells:

a user's guide. Nat Rev Genet 7, 373-84 (2006).

200. Krausz, E. High-content siRNA screening. Mol Biosyst 3, 232-40 (2007).

201. Giuliano, K.A. et al. High-Content Screening: A New Approach to Easing Key

Bottlenecks in the Drug Discovery Process. Vol. 2 249-259 (1997).

202. Neumann, B. et al. High-throughput RNAi screening by time-lapse imaging of live

human cells. Nat Methods 3, 385-90 (2006).

203. Antczak, C., Takagi, T., Ramirez, C.N., Radu, C. & Djaballah, H. Live-Cell

Imaging of Caspase Activation for High-Content Screening. Vol. 14 956-969

(2009).

Figure references

Fig. 1: Reprinted from Cell, 136 (2), Bartel, D.P., MicroRNAs: Target Recognition and

Regulatory Functions, Copyright 2009, with permission from Elsevier.

Fig. 2: Reprinted by permission from Macmillan Publishers Ltd: Nature Reviews Genetics,

10 (2) pp94-108, Ghildiyal, M. and Zamore, P.D., Small silencing RNAs: an expanding

universe, Copyright 2009.

Fig. 3: Reprinted from Trends in Plant Science, 11 (9), Vazquez, F., Arabidopsis

endogenous small RNAs: highways and byways, Copyright 2006, with permission from

Elsevier.

Claude Becker CHAPTER II 37

- CHAPTER II -

Analysis of gene silencing by artificial microRNAs in Arabidopsis thaliana

protoplasts


Abstract

MicroRNAs (miRNAs) are key players in post-transcriptional gene regulation in

plants and animals. Targeted gene knock-down by artificial microRNAs (amiRNAs)

uses the endogenous miRNA machinery and is a powerful tool in characterizing gene

function in planta. However, (a)miRNA-target interaction is still poorly understood

and amiRNA design lacks precision. Here we present a system in Arabidopsis thaliana

protoplasts for the identification of efficient amiRNAs and the quantification of gene

silencing by a fluorescent read-out. By combination of a new vector system for

transient amiRNA and target gene expression with automated microscopy and

computational image analysis, highly efficient amiRNAs for in planta studies could be

selected from a pool of designed candidates. A detailed analysis of structural

characteristics of the target RNA indicated that so-far unknown parameters play a

role in miRNA-target interaction and miRNA-mediated gene silencing.

Introduction

MicroRNAs are 20-24-nucleotide small RNAs endogenously encoded in the genome. In

plants, they are involved in the regulation of numerous developmental processes and play a

role in stage transition 1, organ development

2,3, hormone response

4 and stress adaptation

5.

miRNAs are processed from a primary transcript to a circa 21-nucleotide double-stranded

RNA duplex consisting of the so-called guide and passenger strands. After integration into

the multiprotein RNA-Induced Silencing Complex (RISC), the guide strand is preserved

and directs the RISC, now referred to as ternary complex, to the target mRNA based on

sequence complementarity. The expression of the target gene is inhibited by either mRNA

degradation or translational repression or a combination of both 6,7

. The mechanisms of

target recognition as well as the parameters influencing the interaction between miRNAs

and their target transcripts are still elusive. Plant miRNAs tend to target mRNAs

containing highly complementary miRNA binding sites 8 but it remains unclear whether

sequence complementarity alone is sufficient for miRNA-mediated gene regulation. In

Drosophila cells, the accessibility of the target site strongly influenced the level of

miRNA-mediated gene suppression 9. Similarly, in human HEK cells, structural motives in

the miRNA target site were shown to have an effect on the binding of ARGONAUTE

(AGO), a component of the RISC, to the mRNA and thereby on the level of translational

inhibition 10

. Recent crystallographic studies have revealed the structure of the

ARGONAUTE-RNA interaction 11

. In the ternary complex the miRNA is bound at its


3’ end by the PAZ (Piwi, Argonaut and Zwille) domain of the AGO protein 12,13

while its

5’ end inserts between the MID (MIDDLE) and PIWI (P ELEMENT INDUCED WIMPY

TESTIS) domains 14

. Less is known about the interaction between the ternary complex and

the target RNA. When bound to AGO, positions 2-8 of the miRNA, the so-called seed

region, are exposed in a helical conformation to facilitate base-pairing with the target

RNA 15

. AGO then undergoes a conformational change to accommodate the target RNA in

that region 16

.

It was proposed that the plant miRNA machinery could be used for gene silencing by

replacing the 21 nucleotides of the mature miRNA in a primary transcript sequence for a

sequence complementary to a given target gene. In several studies, these artificial

microRNAs (amiRNAs) were successfully established in knock-down experiments 17,18

.

Eventually, a design tool for amiRNAs (WMD) to be used for gene silencing in

Arabidopsis thaliana and other species 19

was presented. Compared to conventional

antisense or hairpin constructs for RNA interference (RNAi), amiRNAs provide several

advantages. They can easily be generated in large numbers due to the simple underlying

cloning strategy. Their short length enables them for the simultaneous knock-down of

multiple genes through targeting of highly homologous parts of the sequence 18

. For the

same reason, genes with only short unique sequence stretches and which might be elusive

to conventional RNAi can be targeted by amiRNAs. Furthermore, complementation of an

amiRNA-mediated knock-down is possible using amiRNA-resistant target genes 20

.

However, we and others have experienced that numerous amiRNAs generated by the

design tool for amiRNAs (WMD) and its algorithms resulted in no or little alteration of the

target gene expression level. Still unknown requirements for correct and efficient target

recognition and interaction were a possible explanation for this variability.

The aim of this work was (i) the setup of an experimental strategy for testing amiRNA

efficacy and (ii) its use in identifying parameters that define amiRNA functionality. Using

microscopy-based screening of Arabidopsis protoplasts, we evaluated large numbers of

amiRNAs designed against a specific target gene by quantitatively following the change in

fluorescence intensity of a reporter. We showed that amiRNAs can be rapidly classified via

computational image analysis with respect to their efficacy in down-regulating the target

gene expression; the protoplast-based classification was also assessed in transgenic plants.

A systematic computational analysis of the target mRNA structure revealed that a stable

secondary structure in the region of the amiRNA binding site correlates with amiRNA

efficacy. Certain constellations in the amiRNA-target hybrid were identified as


unfavorable to gene silencing. Our results can be integrated into an improved amiRNA

design and provide insights into target recognition by endogenous miRNAs.

Results

Proof-of-principle for amiRNA-mediated gene silencing in Arabidopsis protoplasts

In order to analyze amiRNA-mediated gene knock-down in single plant cells, high-

throughput protoplast transformation, automated image analysis and computational cell

analysis was developed and is described in detail elsewhere (see Chapter IV).

First we tested whether amiRNA-mediated gene silencing can be observed in Arabidopsis

mesophyll protoplasts. Although RNAi studies had been performed in a similar set-up

using double-stranded RNA 21,22

, no data on gene regulation by miRNAs was available.

We designed several amiRNAs against the green fluorescent reporter mGFP5 and

transiently expressed them in protoplasts isolated from a 35S::mGFP5 line to monitor

knock-down of GFP expression 23

(Fig. 1). We generated a novel vector (pELWMS; see

Chapter IV for details) to simultaneously express the amiRNA as well as the red

fluorescent protein (RFP) mCherry 24

. Transformed protoplasts expressing the amiRNA

were thus labeled by a RFP signal and distinguished in the cell population. By measuring

the pixel intensities of the GFP signal in transformed cells over time, we observed a signal

increase in untransformed cells (not shown) and in cells over-expressing the endogenous

miR319a

(25)

. This miRNA has no sequence homology to GFP or RFP and served as

negative control (Fig. 1B). When anti-GFP amiRNAs (amiRGFP-x

) were expressed in

protoplasts, reporter fluorescence intensities stayed low over the whole time course.

Merged images of RFP and GFP channels showed a clear overlapping signal for miR319a

-

expressing cells six days after transformation, indicating high GFP levels in the

transformed cells (Fig. 1A). For cells expressing amiRGFP-x

, merged images showed only

RFP signal, corresponding to low GFP levels.

Altogether, these results indicated a suppression of the mGFP5 expression in cells

transformed with anti-GFP amiRNA constructs and proved that amiRNA-mediated gene

silencing can occur in mesophyll protoplasts.

Next, we investigated whether the efficiency of amiRNAs in protoplasts was reflected on a

whole-plant level. We transformed 35S::mGFP5 plants to stably over-express anti-GFP

amiRNAs amiRGFP-7

and amiRGFP-10

, which had resulted in down-regulation of GFP in the

protoplast assay (Fig 1A+B). Small RNA Northern blot analysis showed that the respective

amiRNAs were expressed and processed to a mature 21-nucleotide miRNA (Fig. 1C).


Fig. 1 Knock-down of a stable reporter gene by artificial microRNAs. A: Epifluorescence

microscopy of protoplasts isolated from 35S::mGFP5 seedlings, transiently expressing the transformation

marker mCherry and either the endogenous miR319a

or an anti-GFP amiRNA (amiRGFP-x

). Merged images

of GFP and RFP channels 6 days after transformation; arrowheads point at merged signal; scale bar =

100µm. B: Mean absolute GFP pixel intensity of transformed cells over time (57 ± 20 cells per sample

per day) C: Northern blot analysis of amiRNA expression and processing in 35S::mGFP5 plants

untransformed (wt) or expressing a 35S::amiRGFP-X

construct; respective antisense probes are indicated.

M: size standard microRNA marker (NEB). 5S rRNA served as loading control. D: Leaves of

35S::mGFP5 seedlings (wild-type or expressing either amiRGFP-7

or amiRGFP-10

) under bright field (BF)

and blue light irradiation (BL) (scale bar = 1mm). E: Western blot with anti-GFP antibody for detection

of GFP protein in total protein extracts from the respective lines (upper panel, GFP) and loading control

by Ponceau S staining of the membrane (lower panel, P). F: Semi-quantitative RT-PCR on mGFP5

(GFP) and actin transcripts and control with no reverse transcriptase added (no RT).

A C

B

D

E

F


Upon blue light irradiation, these plants showed markedly lower GFP signal intensity

compared to the untransformed control (Fig. 1D). Western blot analysis for the detection of

GFP protein in leaves confirmed the microscopy data; GFP was not detectable in total

protein extracts from plants expressing amiRGFP-7

or amiRGFP-10

(Fig. 1E). Semi-

quantitative RT-PCR revealed reduced GFP transcript levels in these plants (Fig. 1F).

Our results demonstrate the value of Arabidopsis protoplasts to study the regulation of

target genes by amiRNA-mediated cleavage before performing long term studies in stably

transformed plants.

Down-regulation of transiently expressed target genes

Based on the pELWMS plasmid presented above and described in details in Chapter IV,

we constructed vectors for the simultaneous expression, from the same backbone, of an

amiRNA, a fluorescently labeled target gene and the transformation marker mCherry. The

TCCGGACCTGCTCATATGATTTATCATAAGAGCAGGTCCTGAmockCAAGGATGTTTTCCCCCAACTTGTTGGGCGAAAACATCCGTGP35

ACACTGCGGCATATACCGTTTTAACGGTTTATGCCGCAGCGTP34

CACGACACGTGCTCAAGTCATTTGACTTCAGCACGTGTCTTGGFP-11GGACTCATGGTTCTAATCGTTTACGATTTGAACCATGAGGCCP33

CGACGTGCAACTCCCTGATCTTGATCAGCGAGTTGCACGCCGGFP-10GCCGGGATGTTTTGGCCCAATTTTGGGCGAAAACATCCCTGCP32

CGACCACAAGTTGCAATACATTTGTATTCCAACTTGTGGCCGGFP-9GAACAGTTTAGTTACGGTAATTTTACCGAAACTAAACTGCTCP31

GTACAACTCGCTGTTCATTATTTAATGATCAGCGAGTTGCACGFP-7CTAGTTCGACCTGGCGTCATTTATGACGGCAGGTCGAACGAGP30

GGACCTGTCCTTTAACCAGATTTCTGGTAAAAGGACAGGGCCGFP-6AACGGCATGTATGCTAATTTTTAAATTACCATACATGCCTTTP29

CCACGTCGCTCTACTTTTAATTTTAAAACTAGAGCGACGCGGP28

AGCCGTCTCTTTCGACTTCATTTGAAGTGGAAAGAGACGACTP62GAACTGGGAGGTTACATTATTTATAATGAAACCTCCCAGGTCP27

TAAGCATGGCTATCTTCAGTTTACTGAACATAGCCATGCCTAP61GCAGCTGTAGTTTAAATCATTTATGATTAAAACTACAGCCGCP26

CTACCGACCAATGGTCCGGATTTCCGGAGCATTGGTCGGGAGP60AGACCTATGGTTCGGTTATATTTATAACGGAACCATAGGCCTP25

AGCCCTGTCTTTCGACTTCATTTGAAGTGGAAAGACAGGACTP59CGCCGCAACTCTATCTTTGGTTCCAAAGTTAGAGTTGCGACGP24

CCACCAACAAGTGAGATGACTTGTCATCACACTTGTTGGCGGP58GAAGAAACTTATTGGTAATCTTGATTACGAATAAGTTTCCTCP23

TGCCGCCGTCTTCCCCGTCCTTGGACGGCGAAGACGGCGACAP57CTACAGTTTATTCCGCATCATTTGATGCCGAATAAACTGCAGP22

CGCCCCACTCCTCACTTTCCTTGGAAAGAGAGGAGTGGGACGP56AGAGCTATGGTTCGGTTATATTTATAACGGAACCATAGCCCTP21

CCACGCACTTCTAGCACGTTTTAACGTGGTAGAAGTGCGCGGP55CGACACGTGGCTCAAGTTTTTTAAAACTAGAGCCACGTGCCGP20

GCAGTCCGAACTCAAACTTTTTAAAGTTAGAGTTCGGACCGCP54CCACGGACTTCTAGCACGTTTTAACGTGGTAGAAGTCCGCGGP19

CAAGGACGTTTTCCCCCAACTTGTTGGGCGAAAACGTCCGTGP53CCACTGCATGTTGGCATTATTTATAATGGCAACATGCAGGGGP18

AGAGCCTGATATTAACTCGATTTCGAGTAAATATCAGGCCCTP52CCACCCCATGTTGGCATTATTTATAATGGCAACATGGGGGGGP17

CGAGGGACTTCTAGCACGTTTTAACGTGGTAGAAGTCCCGCGP51GCAGTCGGAACTCAAACTTTTTAAAGTTAGAGTTCCGACCGCP16

AGCCGTAGACCTTGGAATCTTTAGATTCGAAGGTCTACGTCTP50GTCCCACGTTATGTCGGCTATTTAGCCGTCATAACGTGGTACP15

CGAGTCGCCCATATCTCTTCTTGAAGAGTTATGGGCGACCCGP49CTACCACGTTATGTCGGCTATTTAGCCGTCATAACGTGGCAGP14

CCACCGAACACTCAAGTCATTTATGACTAGAGTGTTCGGGGGP48CCCCCACGTTATGTCGGCTATTTAGCCGTCATAACGTGGTGGP13

CAACACGCCGATTTCTCCACTTGTGGAGTAATCGGCGTGCTGP47GCCCCAGTTTATTGGGCATCTTGATGCCGAATAAACTGGAGCP12

CCAGTTGCCCATATCTCTTCTTGAAGAGTTATGGGCAACGGGP46CCACGCACTTCTAGCACGTTTTAACGTGGTAGAAGTGCGCGGP11

GCAGTTCGACCTGGCGTCATTTATGACGGCAGGTCGAACGGCP45GCACCGAGATATAATCGCTTTTAAGCGAATATATCTCGGCGCP10

GTAGACCGCGTTGGCCATAATTTTATGGGCAACGCGGTCGACP44CAAGAAACTTATTGGTAATCTTGATTACGAATAAGTTTCCTGP9

CGCCAGGGGAATACTAACGATTTCGTTACTATTCCCCTGACGP43GTAGTCGGAACTCAAACTTTTTAAAGTTAGAGTTCCGACGACP8

AGCCCGAGACCTTGCAACTATTTAGTTGGAAGGTCTCGGACTP42CCACGTGGCTCTACTTTTAATTTTAAAACTAGAGCCACGCGGP7

CCACGCAACACTCAAGTCATTTATGACTAGAGTGTTGCGGGGP41AAAGTCTGATATTAACTCGATTTCGAGTAAATATCAGACGTTP6

ACACTTGAAGGTCAGATATTTTAATATCAGACCTTCAAGCGTP40AAAGTCCGATATTAACTCGATTTCGAGTAAATATCGGACGTTP5

ACACTCGGGCATATACCGTTTTAACGGTTTATGCCCGAGCGTP39CGCGGGATGTTTTGGCCCAATTTTGGGCGAAAACATCCCTCGP4

GTAGGTCGCGTTGGCCATAATTTTATGGGCAACGCGACCGACP38AGCGGCATGTATGCTAATTTTTAAATTACCATACATGCCTCTP3

CGCCGGAACTCTATCTTTGGTTCCAAAGTTAGAGTTCCGACGP37ACACTGAGATATAATCGCTTTTAAGCGAATATATCTCAGGGTP2

ACACTCCAAGGTCAGATATTTTAATATCAGACCTTGGAGCGTP36GCACTGAGATATAATCGCTTTTAAGCGAATATATCTCAGCGCP1

amiR* (5´-3´)amiR (5´-3´)amiR* (5´-3´)amiR (5´-3´)

TCCGGACCTGCTCATATGATTTATCATAAGAGCAGGTCCTGAmockCAAGGATGTTTTCCCCCAACTTGTTGGGCGAAAACATCCGTGP35

ACACTGCGGCATATACCGTTTTAACGGTTTATGCCGCAGCGTP34

CACGACACGTGCTCAAGTCATTTGACTTCAGCACGTGTCTTGGFP-11GGACTCATGGTTCTAATCGTTTACGATTTGAACCATGAGGCCP33

CGACGTGCAACTCCCTGATCTTGATCAGCGAGTTGCACGCCGGFP-10GCCGGGATGTTTTGGCCCAATTTTGGGCGAAAACATCCCTGCP32

CGACCACAAGTTGCAATACATTTGTATTCCAACTTGTGGCCGGFP-9GAACAGTTTAGTTACGGTAATTTTACCGAAACTAAACTGCTCP31

GTACAACTCGCTGTTCATTATTTAATGATCAGCGAGTTGCACGFP-7CTAGTTCGACCTGGCGTCATTTATGACGGCAGGTCGAACGAGP30

GGACCTGTCCTTTAACCAGATTTCTGGTAAAAGGACAGGGCCGFP-6AACGGCATGTATGCTAATTTTTAAATTACCATACATGCCTTTP29

CCACGTCGCTCTACTTTTAATTTTAAAACTAGAGCGACGCGGP28

AGCCGTCTCTTTCGACTTCATTTGAAGTGGAAAGAGACGACTP62GAACTGGGAGGTTACATTATTTATAATGAAACCTCCCAGGTCP27

TAAGCATGGCTATCTTCAGTTTACTGAACATAGCCATGCCTAP61GCAGCTGTAGTTTAAATCATTTATGATTAAAACTACAGCCGCP26

CTACCGACCAATGGTCCGGATTTCCGGAGCATTGGTCGGGAGP60AGACCTATGGTTCGGTTATATTTATAACGGAACCATAGGCCTP25

AGCCCTGTCTTTCGACTTCATTTGAAGTGGAAAGACAGGACTP59CGCCGCAACTCTATCTTTGGTTCCAAAGTTAGAGTTGCGACGP24

CCACCAACAAGTGAGATGACTTGTCATCACACTTGTTGGCGGP58GAAGAAACTTATTGGTAATCTTGATTACGAATAAGTTTCCTCP23

TGCCGCCGTCTTCCCCGTCCTTGGACGGCGAAGACGGCGACAP57CTACAGTTTATTCCGCATCATTTGATGCCGAATAAACTGCAGP22

CGCCCCACTCCTCACTTTCCTTGGAAAGAGAGGAGTGGGACGP56AGAGCTATGGTTCGGTTATATTTATAACGGAACCATAGCCCTP21

CCACGCACTTCTAGCACGTTTTAACGTGGTAGAAGTGCGCGGP55CGACACGTGGCTCAAGTTTTTTAAAACTAGAGCCACGTGCCGP20

GCAGTCCGAACTCAAACTTTTTAAAGTTAGAGTTCGGACCGCP54CCACGGACTTCTAGCACGTTTTAACGTGGTAGAAGTCCGCGGP19

CAAGGACGTTTTCCCCCAACTTGTTGGGCGAAAACGTCCGTGP53CCACTGCATGTTGGCATTATTTATAATGGCAACATGCAGGGGP18

AGAGCCTGATATTAACTCGATTTCGAGTAAATATCAGGCCCTP52CCACCCCATGTTGGCATTATTTATAATGGCAACATGGGGGGGP17

CGAGGGACTTCTAGCACGTTTTAACGTGGTAGAAGTCCCGCGP51GCAGTCGGAACTCAAACTTTTTAAAGTTAGAGTTCCGACCGCP16

AGCCGTAGACCTTGGAATCTTTAGATTCGAAGGTCTACGTCTP50GTCCCACGTTATGTCGGCTATTTAGCCGTCATAACGTGGTACP15

CGAGTCGCCCATATCTCTTCTTGAAGAGTTATGGGCGACCCGP49CTACCACGTTATGTCGGCTATTTAGCCGTCATAACGTGGCAGP14

CCACCGAACACTCAAGTCATTTATGACTAGAGTGTTCGGGGGP48CCCCCACGTTATGTCGGCTATTTAGCCGTCATAACGTGGTGGP13

CAACACGCCGATTTCTCCACTTGTGGAGTAATCGGCGTGCTGP47GCCCCAGTTTATTGGGCATCTTGATGCCGAATAAACTGGAGCP12

CCAGTTGCCCATATCTCTTCTTGAAGAGTTATGGGCAACGGGP46CCACGCACTTCTAGCACGTTTTAACGTGGTAGAAGTGCGCGGP11

GCAGTTCGACCTGGCGTCATTTATGACGGCAGGTCGAACGGCP45GCACCGAGATATAATCGCTTTTAAGCGAATATATCTCGGCGCP10

GTAGACCGCGTTGGCCATAATTTTATGGGCAACGCGGTCGACP44CAAGAAACTTATTGGTAATCTTGATTACGAATAAGTTTCCTGP9

CGCCAGGGGAATACTAACGATTTCGTTACTATTCCCCTGACGP43GTAGTCGGAACTCAAACTTTTTAAAGTTAGAGTTCCGACGACP8

AGCCCGAGACCTTGCAACTATTTAGTTGGAAGGTCTCGGACTP42CCACGTGGCTCTACTTTTAATTTTAAAACTAGAGCCACGCGGP7

CCACGCAACACTCAAGTCATTTATGACTAGAGTGTTGCGGGGP41AAAGTCTGATATTAACTCGATTTCGAGTAAATATCAGACGTTP6

ACACTTGAAGGTCAGATATTTTAATATCAGACCTTCAAGCGTP40AAAGTCCGATATTAACTCGATTTCGAGTAAATATCGGACGTTP5

ACACTCGGGCATATACCGTTTTAACGGTTTATGCCCGAGCGTP39CGCGGGATGTTTTGGCCCAATTTTGGGCGAAAACATCCCTCGP4

GTAGGTCGCGTTGGCCATAATTTTATGGGCAACGCGACCGACP38AGCGGCATGTATGCTAATTTTTAAATTACCATACATGCCTCTP3

CGCCGGAACTCTATCTTTGGTTCCAAAGTTAGAGTTCCGACGP37ACACTGAGATATAATCGCTTTTAAGCGAATATATCTCAGGGTP2

ACACTCCAAGGTCAGATATTTTAATATCAGACCTTGGAGCGTP36GCACTGAGATATAATCGCTTTTAAGCGAATATATCTCAGCGCP1

amiR* (5´-3´)amiR (5´-3´)amiR* (5´-3´)amiR (5´-3´)

Table 1 amiRNAs and their passenger strands used in this study


advantage of this strategy was to simultaneously monitor gene silencing of transiently

expressed target genes while avoiding the need for double or triple transformation.

Fig. 2 amiRNA-mediated knock-down of a transient reporter gene. A: Epifluorescence microscopy of

protoplasts isolated from Col-0 wild-type seedlings, transiently transformed with pELWMSGFP

.

Transformed cells express the transformation marker mCherry, the reporter mGFP5 and either the

endogenous miR319a

or an anti-GFP amiRNA (amiRGFP-X

) from the same plasmid backbone. Images were

taken 2 days after transformation; scale bar = 100µm. B: Box plot of mean GFP pixel intensity of

transformed cells (74 ± 6 cells per sample). Solid line indicates median, dotted line mean pixel intensity of

the population. Box borders define 25th

and 75th

percentiles; whiskers define 10th

and 90th

percentiles.

Double asterisks (**) indicate highly significant difference (p < 0.0005) to miR319a

sample. C: Western Blot

analysis using an anti-GFP antibody indicates levels of transiently expressed GFP in protoplast total protein

extracts 2 days after transformation (upper panel, GFP). Equal loading is indicated by Ponceau S staining of

the membrane (lower panel, P).

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A

B C


First, we tested the inhibition of the transiently expressed mGFP5 reporter by transient

amiRNA expression in Arabidopsis Col-0 protoplasts. To this purpose, a 35S::mGFP5

expression cassette was cloned into the pELWMS backbone before inserting the respective

amiRNA into the plasmid backbone. This way, cells transformed with the plasmid were

labeled by the expression of the mCherry marker while simultaneously expressing the

target gene mGFP5 as well as an anti-GFP amiRNA. Two days after transformation, a

strong GFP signal could be observed in cells transiently expressing miR319a

or amiRmock

which had no sequence homology to mGFP5. In contrast, all anti-GFP amiRNAs

(amiRGFP-x

) suppressed the expression of GFP (Fig. 2A+B). In order to confirm our

image-based data, we conducted experiments in a larger setup (5x105 cells) with

comparable transformation efficiencies for all samples. Western blot analysis confirmed

the low level of GFP protein in cells expressing amiRGFP-7

and amiRGFP-10

compared to

those expressing miR319a

or amiRmock

(Fig. 2C). From this we conclude that transient

expression of target genes can be suppressed by the simultaneous expression of the

corresponding amiRNAs.

Fig. 3 Validation of amiRNA-

mediated knock-down of

PIN1::mGFP5. Anti-PIN1::mGFP5

amiRNAs were transiently co-

expressed with PIN1::mGFP5 and

the transformation marker mCherry

(pELWMSPIN1::GFP

) in Col-0 wild-

type protoplasts. “wt” indicates cells

expressing only mCherry. A: Box

plot of mean GFP pixel intensity in

transformed cells 2 days after

transformation (174 ± 24 cells per

sample. Solid line indicates median,

dotted line mean pixel intensity of

the population. Lower and upper

box borders define 25th

and 75th

percentiles, respectively; lower and

upper whiskers define 10th

and 90th

percentiles, respectively. Asterisks

indicate significant (*, p < 0.05) or

highly significant (**, p < 0.0005)

difference to miR319a

sample).

B: Analysis of PIN1::GFP gene

product level by Western blot on

total protein extract from protoplasts

2 days after transformation using

anti-GFP antibody (upper panel,

GFP). Lower panel shows equal

loading by Ponceau S staining of the

membrane (P).

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B


A systematic analysis of features defining amiRNA efficacy required a larger dataset. We

therefore constructed a set of different amiRNAs designed against the auxin efflux

facilitator AtPIN1 fused to GFP (Table 1). These amiRNAs were selected to target sites

distributed over the whole length of the PIN1::mGFP5 transcript in order to analyze effects

of the position and sequence environment of the target site on amiRNA functionality. We

transiently expressed these amiRNAs together with the target gene from the pELWMS

plasmid backbone in Arabidopsis Col-0 protoplasts and assessed the level of target gene

product by pixel intensity measurements of the fluorescent reporter (Fig. 3 and Fig. 4). The

level of gene product varied considerably depending on the amiRNA. Western blots on

total protein extracts from protoplast populations (5x105 cells) transformed with equal

efficiency showed high correlation between the measured pixel intensities and the actual

gene product level in the protoplasts (Fig 3B). Fig. 4 shows the reporter fluorescence

analysis for all 61 anti-PIN1 amiRNAs. Quantitative analysis revealed that only 10% of the

analyzed anti-PIN1 amiRNAs led to a down-regulation comparable to that induced by

amiRGFP-7

which was complementary to the mGFP5, but not the PIN1 sequence. For

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Fig. 4 Mean GFP pixel intensity of protoplasts transformed with pELWMSPIN1::GFP

. Transformed cells

express the marker mCherry, PIN1::mGFP5 and an amiRNA; wt represents cells expressing only mCherry.

Images were taken 2 days after transformation, asterisks indicate significant (*, p < 0.05) or highly significant

(**, p < 0.0005) difference to miR319a

sample; bars represent median pixel intensity values of the respective

cell population; error bars correspond to s.e.


another 10 %, we measured pixel intensity values comparable to those of

miR319a

-expressing cells, indicating no decrease in the level of gene product (Fig. 3).

Validation of the single-cell approach on a whole-plant level

Next, we asked whether the variability in target gene regulation could be extrapolated to

the whole-plant level. We generated transgenic lines expressing anti-PIN1 amiRNAs

which had presented different efficiencies in the single-cell system. We selected several

independent lines for each of these constructs and verified amiRNA expression and

processing by small RNA Northern blot (Fig. 5A). Phenotypes observed in these transgenic

lines were slightly variable and representative phenotypes are shown in Fig. 5B. Plants

expressing amiRP35

, which had been inefficient in protoplasts, appeared like wild-type,

similar to plants expressing amiRGFP-7

, which has no sequence homology to the

Arabidopsis genome. On the contrary, plants expressing amiRP1

, amiRP2

and amiRP33

,

Fig. 5 Expression of amiRPIN1

in stable transgenic lines (Col-0 wild-type background). A: Northern Blot

analysis shows expression and processing of amiRNAs in several independent lines (upper panel). 5S rRNA

serves as loading control (lower panel). DNA oligonucleotides antisense to the respective amiRNA and end-

labelled with γ–ATP were used as probes. B-C: Representative phenotypes observed among independent lines

transformed with the same construct. B: Altered phyllotaxis pattern of rosette leaves (arrows) in plants

expressing amiRP1

, amiRP2

, amiRP3

and amiRP33

2 weeks after germination; scale bar = 10mm. C: Altered

shoot phyllotaxis and pin1-like shoot phenotypes (arrows) in lines expressing amiRP1

, amiRP2

and amiRP33

(scale bar = 10mm). D: Immunolocalization using an anti-PIN1 antibody indicates PIN1 protein levels in root

tissue of 4 day-old seedlings.

A

B

C


which had shown the strongest down-regulation of PIN1::GFP in protoplasts, presented

severe phenotypical changes resembling those of the pin1 loss-of-function mutant 26,27

. The

most striking defects were altered rosette phyllotaxis (Fig. 5B), branching phenotypes and

the formation of pin-like structures at the shoot termini (Fig. 5C and Fig 6). Plants

expressing amiRP3

with intermediate efficacy in protoplasts showed a slower growth rate

and weak phyllotactic alterations. We observed the described phenotypes in more than two

thirds of the independent lines for each amiRNA (Table 2). A strong correlation between

the level of amiRNA detected by Northern blot analysis and the strength of the observed

phenotype could be noticed (data not shown).

In order to verify the decrease of the target gene product in the transgenic lines, we

checked PIN1 expression via immunolocalization on roots of young seedlings (Fig. 7). A

second antibody was used in the immunolocalization to check against unequal fixation and

penetrance of the antibodies for the different seedlings and to allow relative quantification

Fig. 6 Phenotypical defects in plants expressing a functional anti-PIN1 amiRNA (amiRP1

, amiRP2

or

amiRP33

) A-D: Shoot phyllotaxis was altered with one node giving rise to several side branches (A-C). The

absolute number of side branches was reduced (D). E-H: Silique formation was altered. Several siliques

originated from one node (E-G) and siliques tended to be misshaped (G, H). I-L: Shoot termini regularly

formed pin-like structures with no or only very few flowers developing from the shoot apex. (A, B, E, F, I and

J: amiRP1

; C, G and K: amiRP2

; D, H and L: amiRP33

)


of the signal intensity observed for PIN1. We used an anti-H+-ATPase antibody to compare

seedlings expressing amiRGFP-7

, amiRP1

, amiRP3

, amiRP33

and amiRP35

to wild-type

seedlings (Fig. 7A). In an independent run, an anti-callose antibody was used for the

standard signal in amiRP2

and wild-type seedlings (Fig. 7B). In plants expressing amiRP1

or

amiRP2

, PIN1 signal in cells of the stele was conspicuously lower than in wild-type

seedlings. Expression of amiRP3

and amiRP33

led to a reduction in PIN1 signal intensity,

although not as severe as for amiRP1

and amiRP2

. Plants expressing either amiRP35

, which

had been inefficient against PIN1::GFP in the protoplast assay, or amiRGFP-7

, which was

lacking sequence homology to the Arabidopsis genome, showed no alteration in the

strength of PIN1 signal (Fig. 7A+B). From the correlation of these results and the

phenotypes observed in the transgenic lines (Fig. 5 and 6) with the data from the protoplast

assays, we concluded that the variability of amiRNA efficacy is reflected on the whole-

plant level and that functional amiRNAs can be pre-selected in the protoplast system.

Investigation of features influencing amiRNA functionality

Although the amiRNAs used in this study had all been designed according to the same

criteria with the WMD2 tool 19

, their expression induced a wide range of target gene

suppression. We asked whether it was possible to identify parameters defining this

A

B Fig. 7 Immunolocalization of AtPIN1 in roots of

2-3-week-old seedlings from transgenic lines expressing anti-

PIN1 amiRNAs. PIN1 is polarly localised at the plasma

membrane in the stele of the root and was detected using an

anti-PIN1 antibody. Homogenous fixation of the tissue and

penetration of the antibody was verified by immunostaining

with a second antibody. A: For amiRGFP-7

, amiRP1

, amiRP3

,

amiRP33

and amiRP35

seedlings, PIN1-specific signal was

compared to wt seedlings using an anti-H+-ATPase antibody

as control. B: For antiP2

-expressing seedlings, an antibody

detecting callose was used as control. Images were acquired

with a confocal laser scanning microscope; scale

bar = 50 µm


variability. In a first step, a set of 3x104 structure- and sequence-related features was

generated. These features described characteristics of the amiRNAs, their precursors and

their respective target site in the mRNA. They were generated empirically based on their

potential direct or indirect influence on miRNA-target interaction. The features could be

classified into the following categories: accessibility of the target site, hybridization

properties of the amiRNA and the target site, position-specific nucleotide frequencies of

the amiRNA and the target site, self-basepairing of the amiRNA precursor, GC content of

the target site and the energy inherent to the target mRNA in the region of amiRNA

binding.

We attributed a quality coefficient (QC) to each amiRNA based on the fluorescence

measurements (Fig. 4), ranging from 0 (strongest gene silencing) to 1 (no gene silencing).

Apart from the anti-PIN1 amiRNA dataset, another dataset independently generated and

validated by R. Schwab was included into the further analysis. This set comprised 19

amiRNAs against the brassinosteroid receptor BRASSINOSTEROID RECEPTOR 1

(BRI1) 28

, 7 amiRNAs against each of the transcription factors TRANSPARENT TESTA

GLABRA 1 (TTG1) 29

and LEAFY (LFY) 30

and 6 amiRNAs against the flowering

inducing gene FLOWERING LOCUS T (FT) 31

Sequences of these amiRNAs cannot be

presented here for confidentiality reasons, information can be asked directly from R.

Schwab. Altogether, 100 validated amiRNA-target pairs were considered in the analysis.

We checked for correlation between any of the previously described features and the QC of

the amiRNAs. The features were then ranked according to the absolute Spearman’s

correlation coefficient; all correlations with p values ≥ 0.25 were considered as significant.

The highest-ranking correlations concerned the number of neighboring basepairs in the

amiRNA-target hybrid and, to a smaller extent, the free energy of this hybrid. Intriguingly,

the amiRNA QC correlated positively with the average accessibility of the amiRNA target

site. This meant that functional amiRNAs tended to bind to target sites which basepaired

with elements of the target mRNA whereas inefficient amiRNAs more often bound to

target sites that were more easily accessible. In order to investigate this feature in more

detail, we used RNAfold 32

to simulate the secondary structure around the amiRNA target

site with different lengths of flanking sequence (20-100 nucleotides) upstream and

downstream; calculations based on a context of 20 flanking nucleotides are shown in

Fig. 8A-B. Three classes of amiRNA-target site combinations became apparent. First,

target sites of efficient amiRNAs (QC < 0.4) were found in closed secondary structures,

often resembling stem-loop-like patterns (Fig. 8A). The second class comprised target sites


of amiRNAs with weak or no silencing efficiency (QC > 0.6) and appeared to be located in

relatively open, easily accessible regions of the mRNA (Fig. 8B). These results thus

confirmed the positive correlation between the accessibility of the target site and the QC of

the amiRNA. Target sites of a third class presented a relatively closed structure,

comparable to those of the functional amiRNAs. However, the different amiRNAs binding

to the same target site of this class diverged considerably in their efficacy. In order to

identify a second level of discriminating features, we calculated the energy and alignments

of amiRNA-target hybrids for these pairs using the IntaRNA 33

software. The energy

model and structural parameters used in the calculation gave results that differed from

purely sequence-based alignments. Based on these calculations, three independent features

separated inefficient from efficient amiRNAs when both were targeting the same target site

of low accessibility (Fig. 8C). Concerning inefficient amiRNAs, two to three consecutive

non-pairing bases at the 3´ end (of the amiRNA) were found in 60 % of amiRNA-target

Fig. 8 Analysis of RNA structural features

influencing the efficiency of amiRNA-mediated

gene regulation. A+B: Simulation of the secondary

structure of the target mRNA in the region of the

respective amiRNA binding site as calculated by

RNAfold. All structures presented here were

calculated for contexts of 20 flanking nucleotides on

both sides of the target site; the sequence

corresponding to the target site is highlighted in red.

A: Structures for target sites of efficient anti-

PIN1amiRNAs with a quality coefficient (QC) < 0.4.

B: Representative amiRNA target site structures of

inefficient anti-PIN1::GFP amiRNAs with a QC > 0.6.

C: IntaRNA amiRNA-target alignments of inefficient

anti-PIN1 amiRNAs (QC > 0.6) with target sites

resembling those shown in (A). The upper strand

corresponds to the target mRNA in

5’ to 3’ orientation; the lower strand corresponds to

the amiRNA in 3’ to 5’ orientation.

B A

C


hybrids and an asymmetrical bulge at position 16 or 17 of the amiRNA in 12 % of

amiRNA-hybrids. The number of neighboring basepairs not interrupted by a mismatch

(counted from the 5´ end of the amiRNA) was < 15 in 28 % of the amiRNA-target site

alignments. Of these features, none could be identified in amiRNA-target hybrids of

efficient amiRNAs. Altogether, these results indicated that the presence of a secondary

structure in the region of the amiRNA binding site was favorable to amiRNA efficacy.

Furthermore, unpaired bases at the terminal region of the amiRNA-hybrid, asymmetrical

bulges as well as interrupted basepairing appeared to hinder amiRNA-mediated gene

silencing.

Discussion

Gene silencing by amiRNAs in Arabidopsis protoplasts

Small RNA-mediated gene silencing is one of the most rapidly evolving fields of research

and many of the main mechanisms underlying the biogenesis of and the

(post)transcriptional regulation by different small non-coding RNAs (ncRNAs) have been

elucidated over the last decade 6. Still, recognition of and interaction with the target nucleic

acid has remained poorly understood. We have developed a highly compliant system that

allows the systematic analysis of miRNA-target interaction in plant single cells and an easy

read-out of amiRNA efficiency. Knock-down of a stable reporter by transient amiRNA

expression in Arabidopsis protoplasts proved the functionality of amiRNA-mediated gene

regulation in isolated single plant cells (Fig. 1). A clear increase in GFP fluorescence

intensity could be observed in cells derived from the 35S::GFP line and expressing the

unrelated endogenous miR319a

(Fig. 1B) as well as in untransformed protoplasts derived

from the same line (data not shown). We speculate that a general increase in transcriptional

activity during the recovery after protoplasting and ensuing de-differentiation is

Table 2 Frequency of phenotypes observed in independent amiRPIN1

-expressing lines.

(16/16)100 % like wild-typeP35

(11/16)69 % reduced branching, pin-like shoot termini, altered

phyllotaxis

P33

(15/16)94 % reduced growth, weakly altered phyllotaxisP3


phyllotaxis

P2

(6/8)75 % reduced branching, pin-like shoot terminiP1

(16/16)100 % like wild-typeGFP

frequencyphenotypeamiRNA

(16/16)100 % like wild-typeP35


phyllotaxis

P33

(15/16)94 % reduced growth, weakly altered phyllotaxisP3


phyllotaxis

P2

(6/8)75 % reduced branching, pin-like shoot terminiP1

(16/16)100 % like wild-typeGFP

frequencyphenotypeamiRNA


responsible for this effect. Cells expressing an anti-GFP amiRNA did not accumulate GFP

gene product over time suggesting that expression of the amiRNA led to a successful gene

knock-down.

We were able to suppress the transient expression of a fluorescent reporter by

simultaneously expressing an appropriate amiRNA (Fig. 2). This showed that if amiRNA

and target transcript were generated at the same time, the RNA silencing machinery in

Arabidopsis protoplasts was able to suppress the synthesis of the target gene product. The

fact that transiently expressed target genes were immediately suppressed after

transformation by simultaneously expressed amiRNAs proved the suitability of our system

to analyze miRNA-target interactions with any target gene that can be expressed fused to a

fluorescent tag in protoplasts. This further indicated that the down-regulatory effect on

stably expressed GFP observed only from 4 days after transformation onwards (Fig. 1B)

was due to high protein stability of the GFP rather than a delayed activity of the amiRNA.

Pre-selection of amiRNAs in a transient system

The variability in amiRNA efficacy observed when using the auxin efflux facilitator PIN1

as target confirmed our previous observations on the non-functionality of several amiRNA

constructs in planta (data not shown). We noticed variable size in the mature amiRNAs

detected via Northern blot; e.g. amiRP2

and amiRP35

gave rise to signals at 22-23

nucleotides rather than at the expected 21 nucleotides (Fig 5A). As these two amiRNAs

represented a very efficient and a non-working construct, respectively, we excluded this

variability in length as source of differential efficacy.

By the correlation between high efficacy in protoplasts and strong gene down-regulation in

transgenic plants (Fig. 1D, Fig. 5B-C, Fig. 6 and Fig. 7), we could prove the accuracy of

the single cell system in predicting amiRNA efficacy. The presence of the GFP tag linked

to the PIN1 sequence in the transient protoplast system seemed not to alter amiRNA

efficacy compared to the endogenous PIN1 gene in the transgenic amiRNA-expressing

lines. Hence we conclude that the protoplast platform is reliable for the systematic analysis

of miRNA-target interaction features.

Impact of target mRNA structure on amiRNA efficacy

In accordance with previous studies 9,10

, we found the accessibility of the miRNA binding

site to be important for efficient miRNA-mediated gene silencing. However, we were

intrigued to observe that a high probability to be in a paired (i.e. closed) conformation was

favorable to amiRNA efficacy (Fig. 8), which was contradictory to studies from the animal


field where a high probability of the target site to be unpaired correlated with efficient gene

silencing by endogenous miRNAs 9. According to our data, binding sites of the most

efficient amiRNAs all presented a conspicuous secondary structure whereas those of

inefficient amiRNAs were comprised in more relaxed structures and appeared unpaired on

most of their positions (Fig. 8A-B). Although highly paired structures could also be

identified for binding sites of inefficient amiRNAs, the majority of these could be

explained by one of three features related to the amiRNA-target hybrid. It thus seemed that

interruptions of the basepairing between the amiRNA and its binding site by mismatches

and asymmetric bulges as well as several unpaired nucleotides in the terminal region of the

hybrid were unfavorable to amiRNA-mediated gene silencing (Fig. 8C).

We tried to tie these findings to the resolved structure of the AGO complex. Positions 2-8

of the miRNA guide strand, the so-called seed region, are exposed in the AGO-miRNA

complex and might initiate target RNA binding 15

. Conformational change of the AGO

protein upon seed binding could then accommodate the central part of the target RNA 16

,

which would not necessarily have to be accessible from the start. One can imagine a

process in which the target mRNA needs to be presented in a specific conformation to the

AGO complex in order to be properly recognized as a substrate. Such a hypothetical

mechanism could explain why target sites of efficient amiRNAs were found to be

comprised in stable secondary structures while those of inefficient amiRNAs very often

presented a high amount of unpaired nucleotides and therefore a weak structural

specificity. It has to be considered, though, that most crystallographic data has been

generated on bacterial AGO proteins loaded with artificial target and guide strands and

might therefore not be representative for the plant AGO system.

This first systematic analysis of target RNA features has led to the identification of novel

parameters that influence the activity of miRNAs on their target transcript. We are

currently probing a mutational approach in order to validate and confirm the importance of

these features. Insertion of silent mutations in the flanking regions of the target site in the

PIN1 mRNA can modify the structural context and thereby the accessibility of the target

site. We are currently investigating whether increasing/reducing the accessibility will have

the predicted effect on the efficacy of the respective amiRNA. The identification of

features such as those described here will help to improve amiRNA design and thus allow

a more precise and predictable gene down-regulation in planta. Furthermore, our results

contribute to the better understanding of endogenous miRNA activity and target

recognition.


Materials and Methods

Exact compositions of media and solutions used in this study can be found in the appendix.

Plant culture

Seedlings for protoplast isolation were sterilized by incubation in chlorine gas for 16h and

grown on SCA medium in a 16-8h light-dark cycle at 25°C. Arabidopsis thaliana plants

were grown under constant conditions in a 16-8 h light-dark cycle at 22°C.

Generation of transgenic lines

Arabidopsis plants were transformed by floral dip using the Agrobacterium strains

GV3101 (pMP90 RK+) and GV3101 (pMP90 RK

-) for pAM-PAT (Genbank accession

AY436765.1) and pMDC32 34

plasmids, respectively. Plants transformed with pAM-PAT

and pMDC32 vectors were selected on Basta (Bayer AG) and hygromycin B (Roth),

respectively. Anti-GFP amiRNAs were cloned into the pMDC32 plasmid and transformed

into 35S::mGFP5 plants in C24 background 23

to be expressed under the control of a 35S

Cauliflower Mosaic Virus (CaMV) promoter. Anti-PIN1 amiRNAs were expressed from

the same promoter from a pAM-PAT plasmid backbone transformed into Columbia-0

wild-type background.

Protoplast isolation and transformation

We followed a method modified from the protocol published by Dovzhenko et al. 35

.

Protoplasts were isolated under sterile conditions from leaves of 2-3 week-old seedlings.

Aerial parts were cut from the roots and imbibed with MMC solution. Plant material was

cut with a scalpel and left in MMC for 1 h at room temperature. Enzymatic digestion of the

cell wall was performed by incubating the plant material in [MMC, 0.5% cellulase

(Duchefa), 0.5% macerozyme (Duchefa)] for 16h at 25°C in the dark. Cell suspension was

centrifuged 10 min at 100g and resuspended in 8ml MCS, the suspension was overlaid

with 2 ml transformation medium. After centrifugation for 10 min at 100g, cells were

collected at the interphase between MCS and transformation media. Cells were

subsequently washed in 10 ml W5 and total cell number was assessed in a Fuchs-Rosenthal

hæmocytometer. After final centrifugation for 10 min at 50g, the final cell density in

transformation medium was adjusted according to experimental needs.

Protoplast transformation was performed using 3x104 and 5x10

5 cells for small- and large-

scale transformations, respectively. Cells were mixed with 1-15µg of plasmid DNA,

depending on the cell number. Polyethylenglycol 1500 (40%) (PEG, Carl ROTH) in a

volume corresponding to the combined volumes of cell suspension and DNA was added.

Transformation was stopped after 8 min by addition of transformation medium to a final

volume of 10 volumes of the initially added cell solution. Protoplasts were left to sediment

for 1 h and transformation medium was exchanged for PCA solution including 3,6-dichlor-

2-methoxybenzoic acid (3 mg/l, Sigma-Aldrich) and 1-Naphthaleneacetic acid (1-NAA,

0.5 mg/l, Sigma-Aldrich).

Vector construction

PIN1::mGFP5 was designed according to previous PIN1::GFP constructs 36

by cloning the

mGFP5 coding sequence without stop codon into the cytoplasmic loop region of the PIN1

coding sequence between residues S218 and R219.

pELWMS is based on the pAM-PAT vector backbone. A rolD::mCherry::pA35S

cassette 24,37

was inserted into the PmeI site. For the construction of pELWMSGFP

and

pELWMSPIN1::GFP

, the respective cassettes for the expression of mGFP5 or PIN1::mGFP5

under control of the CaMV35S promoter were inserted at the PfoI site. amiRNAs were


inserted into the pELWMSGFP

and pELWMSPIN1::GFP

backbones by Gateway™ cloning

(Invitrogen) according to manufacture’s instruction.

Artificial microRNA (amiRNA) design

AmiRNAs were designed using the WMD2 tool 19

available at

http://wmd2.weigelworld.org/cgi-bin/mirnatools.pl. AmiRNAs against the non-annotated

mGFP5 gene were designed by using the mGFP5 38

coding sequence as a reference.

AmiRNAs P1-P50 against AtPIN1 were based on the At1g73590 accession. AmiRNAs

P51-P62 were designed against combinations of AtPIN1 with other AtPIN genes. All

amiRNAs were designed based on the “Arabidopsis thaliana TAIR7 transcripts” database;

no off-targets were accepted.

amiRNA generation and cloning

Synthesis and cloning of amiRNAs was done according to Schwab et al. 18

. We used

Gateway™ cloning by adding attB sites to the oligoA and oligoB primers indicated in the

original publication. amiRNA PCR fragments were cloned into the pDONR207 plasmid

(Invitrogen) by BP reaction and further into pMDC32 , pAM-PAT and pELWMS plasmids

by LR reaction.

Protein extraction

Total protein from protoplasts was extracted by spinning down the protoplast solution for

5 min at 300x g. Supernatant was discarded and cells were resuspended in 100µl

homogenization buffer and 50µl 6x Laemmli buffer with protease inhibitor (Sigma-

Aldrich) added.

Total protein from 35S::mGFP5 plants was extracted from leaves of 3-weeks old seedlings.

RNA extraction

Total RNA was extracted using Trizol (Invitrogen) according to manufacturer’s manual

from 100 mg of tissue (fresh weight). Precipitation of RNA after chloroform phase

separation was done by adding 0.5 vol of 3M sodium acetate and 0.5 vol of isopropanol.

We measured RNA concentration using a NanoDrop instrument (ThermoFischer) and

checked RNA quality by denaturing agarose gel electrophoresis.

Small RNA Northern blot

Detection of miRNAs was performed according to the protocol published by the Hamilton

lab 39

.

RT-PCR

Reverse transcription on mGFP5 transcript was done using the primers

5’ ATGAGTAAAGGAGAAGAACTTTTCACTGGAGT 3’(for) and

5’ ACAAGTGTTGGCCAAGGAACAGGTAGTTTTCCA 3’(rev) leading to a 200 basepair fragment. A 400

basepair fragment from the actin2 gene transcript was amplified with the primers

5’ TGTTCACCACTACCGCAGAA 3’ (for) and 5’ GGTGCAACCACCTTGATCTT 3’ (rev).

Immunolocalization

For whole-mount immunolocalizations of PIN1 in not plasmolysed root cells, four days old

seedlings were fixed with 3% (w/v) paraformaldehyde and 0.02% Triton X-100 in MTSB

(pH 7.0) for 45 min and washed three times with dH2O. The subsequent steps were

performed in an InsituPro VS robot (Intavis). Briefly, tissue permeabilisation was achieved

by 30 min incubation in 0.15% (w/v) driselase (Sigma) and 0.15% (w/v) macerozyme

(Sigma) in 10 mM MES (pH 5.3) at 37°C, followed by four washes in MTSB and two

http://wmd2.weigelworld.org/cgi-bin/mirnatools.pl


subsequent treatments of 20 min each with 10% (v/v) DMSO, 3% (v/v) Nonidet P40

(Fluka) in MTSB. After five washes in MTSB, blocking was performed with 3% BSA

(Carl Roth, Germany) in MTSB for one hour. Antibodies were used in the following

concentrations: rabbit anti-PIN1 26

at 1:400; mouse anti-H+-ATPase

40 at 1:400 and mouse

anti-callose (Biosupplies Australia, Cat. No. 400-2) at 1:100. We applied primary

antibodies in 3% BSA in MTSB for 4 hours at RT followed by seven washes in MTSB.

Alexa488- and Alexa555-conjugated (1:600) secondary antibodies (Invitrogen) were

applied for 3 h at RT, followed by ten washes in MTSB. Samples were mounted in Prolong

Gold antifade reagent (Molecular probes).

Microscopy

Manual image acquisition was done on an Axiovert 200M MAT system (Zeiss) using Zeiss

Plan APOCHROMAT 10x/0.45 air and Zeiss Plan-APOCHROMAT 20x/0.75 air

objectives. All GFP images and all RFP images were acquired with the same settings using

Metamorph v6.2r4. For automated image acquisition we used an iMIC instrument (Till

Photonics) controlled by Till Photonics Live Acquisition 1.2.2.12. Objectives used were a

Zeiss Plan-NEOFLUAR 10x/0.30 air and a Zeiss Plan-APOCHROMAT 20x/0.75 air. We

acquired up to 63 viewing fields per well in both fluorescent channels using the “tile”

module. Confocal images were acquired using a Zeiss LSM 510 NLO confocal scanning

microscope with a 20x/0.75 air objective. Excitation wavelengths were 488 nm (argon

laser) for Alexa488-conjugated antibodies and 543 nm (Helium-Neon-Laser) for

Alexa555-conjugated antibodies. Emission was detected at 500-550 nm for Alexa488-

conjugated antibodies and above 575 nm for Alexa555-conjugated antibodies. DAPI was

imaged using a 2-Photon module with excitation at 730 nm and emission at 435-485 nm.

All multi-labelling signals were detected in multitracking mode to avoid fluorescence

crosstalk. Images were analyzed with the LSM image browser (Carl Zeiss MicroImaging)

and MacBiophotonics ImageJ.

Image analysis

We used CellProfiler version 1.0.5811 41,42

. Transformed, RFP-positive cells were

identified as objects using RidlerCalvart Global 43

for segmentation; objects outside a

diameter range from 40 to 100 pixels and not reaching a roundness minimal value of 0.7

were discarded. Object areas and background intensities in a three-pixel wide ring

surrounding the object were measured on the corresponding GFP-channel image. Average

background intensity was subtracted from the object pixel intensity.

Statistical analysis

Graphs were generated using SigmaPlot 9.0 (Systat Software Inc.). t-test analysis was

performed using Microsoft® Excel 2003™; all t-test calculations were two-tailed and

paired.

Attribution of quality coefficients (QCs) to amiRNAs

QCs were attributed based on the median fluorescence intensity per cell of the protoplast

population expressing the respective amiRNA. Autofluorescence intensity as measured in

wild-type protoplasts was subtracted; the lowest score was attributed a QC of 0, the highest

was attributed a QC of 1. All other scores were ranked on this 0-1 scale.


References

1. Poethig, R.S. Small RNAs and developmental timing in plants. Curr Opin Genet

Dev 19, 374-8 (2009).

2. Nogueira, F.T., Sarkar, A.K., Chitwood, D.H. & Timmermans, M.C. Organ polarity

in plants is specified through the opposing activity of two distinct small regulatory

RNAs. Cold Spring Harb Symp Quant Biol 71, 157-64 (2006).

3. Dugas, D.V. & Bartel, B. MicroRNA regulation of gene expression in plants.

Current Opinion in Plant Biology 7, 512-520 (2004).

4. Mallory, A.C., Bartel, D.P. & Bartel, B. MicroRNA-directed regulation of

Arabidopsis AUXIN RESPONSE FACTOR17 is essential for proper development

and modulates expression of early auxin response genes. Plant Cell 17, 1360-1375

(2005).

5. Ruiz-Ferrer, V. & Voinnet, O. Roles of plant small RNAs in biotic stress responses.

Annu Rev Plant Biol 60, 485-510 (2009).

6. Voinnet, O. Origin, Biogenesis, and Activity of Plant MicroRNAs. Cell 136, 669-

687 (2009).

7. Brodersen, P. et al. Widespread translational inhibition by plant miRNAs and

siRNAs. Science 320, 1185-1190 (2008).

8. Mallory, A.C. et al. MicroRNA control of PHABULOSA in leaf development:

importance of pairing to the microRNA 5 ' region. Embo Journal 23, 3356-3364

(2004).

9. Kertesz, M., Iovino, N., Unnerstall, U., Gaul, U. & Segal, E. The role of site

accessibility in microRNA target recognition. Nature Genet. 39, 1278-1284 (2007).

10. Hausser, J., Landthaler, M., Jaskiewicz, L., Gaidatzis, D. & Zavolan, M. Relative

contribution of sequence and structure features to the mRNA binding of

Argonaute/EIF2C-miRNA complexes and the degradation of miRNA targets.

Genome Res (2009).

11. Jinek, M. & Doudna, J.A. A three-dimensional view of the molecular machinery of

RNA interference. Nature 457, 405-412 (2009).

12. Lingel, A., Simon, B., Izaurralde, E. & Sattler, M. Nucleic acid 3'-end recognition

by the Argonaute2 PAZ domain. Nature Struct. Mol. Biol. 11, 576-577 (2004).

13. Ma, J.B., Ye, K. & Patel, D.J. Structural basis for overhang-specific small

interfering RNA recognition by the PAZ domain. Nature 429, 318-322 (2004).

14. Ma, J.B. Structural basis for 5[prime]-end-specific recognition of guide RNA by

the A. fulgidus Piwi protein. Nature 434, 666-670 (2005).

15. Wang, Y., Sheng, G., Juranek, S., Tuschl, T. & Patel, D.J. Structure of the guide-

strand-containing argonaute silencing complex. Nature 456, 209-213 (2008).

16. Wang, Y. et al. Structure of an argonaute silencing complex with a seed-containing

guide DNA and target RNA duplex. Nature 456, 921-6 (2008).

17. Alvarez, J.P. et al. Endogenous and synthetic microRNAs stimulate simultaneous,

efficient, and localized regulation of multiple targets in diverse species. Plant Cell

18, 1134-51 (2006).

18. Schwab, R., Ossowski, S., Riester, M., Warthmann, N. & Weigel, D. Highly

specific gene silencing by artificial microRNAs in Arabidopsis. Plant Cell 18,

1121-33 (2006).

19. Ossowski, S., Schwab, R. & Weigel, D. Gene silencing in plants using artificial

microRNAs and other small RNAs. Plant J 53, 674-90 (2008).

20. Parizotto, E.A., Dunoyer, P., Rahm, N., Himber, C. & Voinnet, O. In vivo

investigation of the transcription, processing, endonucleolytic activity, and

functional relevance of the spatial distribution of a plant miRNA. Genes Dev. 18,

2237-2242 (2004).


21. An, C.I., Sawada, A., Fukusaki, E. & Kobayashi, A. A transient RNA interference

assay system using Arabidopsis protoplasts. Biosci Biotechnol Biochem 67, 2674-7

(2003).

22. Zhai, Z., Sooksa-nguan, T. & Vatamaniuk, O.K. Establishing RNA Interference as

a Reverse-Genetic Approach for Gene Functional Analysis in Protoplasts. PLANT

PHYSIOLOGY 149, 642-652 (2009).




(2000).

24. Shaner, N.C. et al. Improved monomeric red, orange and yellow fluorescent

proteins derived from Discosoma sp. red fluorescent protein. Nat Biotechnol 22,

1567-72 (2004).

25. Palatnik, J.F. et al. Control of leaf morphogenesis by microRNAs. Nature 425, 257-

263 (2003).

26. Galweiler, L. et al. Regulation of polar auxin transport by AtPIN1 in Arabidopsis

vascular tissue. Science 282, 2226-30 (1998).

27. Okada, K., Ueda, J., Komaki, M.K., Bell, C.J. & Shimura, Y. Requirement of the

Auxin Polar Transport-System in Early Stages of Arabidopsis Floral Bud

Formation. Plant Cell 3, 677-684 (1991).

28. Wang, Z.Y., Seto, H., Fujioka, S., Yoshida, S. & Chory, J. BRI1 is a critical

component of a plasma-membrane receptor for plant steroids. Nature 410, 380-3

(2001).

29. Galway, M.E. et al. The TTG gene is required to specify epidermal cell fate and

cell patterning in the Arabidopsis root. Dev Biol 166, 740-54 (1994).

30. Schultz, E.A. & Haughn, G.W. LEAFY, a Homeotic Gene That Regulates

Inflorescence Development in Arabidopsis. Plant Cell 3, 771-781 (1991).

31. Kobayashi, Y., Kaya, H., Goto, K., Iwabuchi, M. & Araki, T. A pair of related

genes with antagonistic roles in mediating flowering signals. Science 286, 1960-2

(1999).

32. Hofacker, I.L. et al. Fast folding and comparison of RNA secondary structures.

Monatsh. Chem. 125, 167-188 (1994).

33. Busch, A., Richter, A.S. & Backofen, R. IntaRNA: efficient prediction of bacterial

sRNA targets incorporating target site accessibility and seed regions.

Bioinformatics 24, 2849-56 (2008).

34. Curtis, M.D. & Grossniklaus, U. A gateway cloning vector set for high-throughput

functional analysis of genes in planta. Plant Physiol 133, 462-9 (2003).

35. Dovzhenko, A., Dal Bosco, C., Meurer, J. & Koop, H.U. Efficient regeneration

from cotyledon protoplasts in Arabidopsis thaliana. Protoplasma 222, 107-11

(2003).

36. Benkova, E. et al. Local, efflux-dependent auxin gradients as a common module for

plant organ formation. Cell 115, 591-602 (2003).

37. Elmayan, T. & Tepfer, M. Evaluation in tobacco of the organ specificity and

strength of the rolD promoter, domain A of the 35S promoter and the 35S2

promoter. Transgenic Res 4, 388-96 (1995).

38. Siemering, K.R., Golbik, R., Sever, R. & Haseloff, J. Mutations that suppress the

thermosensitivity of green fluorescent protein. Curr Biol 6, 1653-63 (1996).

39. Pall, G.S. & Hamilton, A.J. Improved northern blot method for enhanced detection

of small RNA. Nat Protoc 3, 1077-84 (2008).

40. Langhans, M. et al. Immunolocalization of plasma-membrane H+-ATPase and

tonoplast-type pyrophosphatase in the plasma membrane of the sieve element-


companion cell complex in the stem of Ricinus communis L. Planta 213, 11-9

(2001).

41. Lamprecht, M.R., Sabatini, D.M. & Carpenter, A.E. CellProfiler: free, versatile

software for automated biological image analysis. Biotechniques 42, 71-5 (2007).

42. Carpenter, A.E. et al. CellProfiler: image analysis software for identifying and

quantifying cell phenotypes. Genome Biol 7, R100 (2006).

43. Ridler, T.W. & Calvard, S. Picture thresholding using an iterative selection method.

Transactions on Systems, Man and Cybernetics 8, 630-632 (1978).

Claude Becker CHAPTER III 61

- CHAPTER III -

Efficient transfection with gene-specific short interfering RNAs induces

gene silencing in Arabidopsis protoplasts


Abstract

Short interfering RNAs (siRNAs) are the active component of most RNAi pathways

and can be directly transfected into single cells to induce targeted gene silencing.

Their application in biomedical research has led to the development of genome-wide

siRNA screens to unravel gene function. Here we report on siRNA-mediated gene

knock-down in single plant cells. We have developed a protocol for the efficient

transfection of siRNAs into Arabidopsis thaliana mesophyll protoplasts. The uptake of

the siRNA duplex by the cells could be monitored by fluorescent conjugates to the

siRNA duplex. Transfection of gene-specific siRNAs led to the successful knock-down

of two different reporter genes. Our work constitutes the proof-of-principle for

standard application of siRNA-mediated gene silencing in reverse genetic studies in

plant protoplasts.

Introduction

In 1998, Fire et al. were the first to show that the uptake of double-stranded RNA (dsRNA)

by the nematode Caenorhabditis elegans induced the specific suppression of a gene 1. This

phenomenon was found to rely on a ubiquitous mechanism, termed RNA interference

(RNAi). In this type of gene silencing, the dsRNA, independent from its origin, is

processed into short 20-25 nucleotide RNA duplexes with 2-nucleotide overhangs at both

3’ ends 2,3

. The silencing activity was finally shown to be inherent to these short interfering

RNAs (siRNAs) 4. siRNAs are generated from dsRNA by the RNase III-type enzyme

Dicer 5. Upon being loaded into the RNA-Induced Silencing Complex (RISC), they guide

the RISC to the target RNA by sequence complementarity. Subsequently, the target RNA

is cleaved by a slicing enzyme of the ARGONAUTE family 6. It was also demonstrated

that siRNAs bound to their target RNA can act as priming elements for the generation of

more dsRNA molecules, which are in their turn processed to siRNAs, thereby amplifying

the gene silencing 7. Ground-breaking experiments in Drosophila and in mammalian cell

cultures demonstrated that transfection of cells with siRNA duplexes induced sequence-

specific gene silencing 8,9

, thereby opening opportunities for RNAi-based biomedical

research.

The identification of siRNAs as RNAi-inducing agents was first made in the model plant

Arabidopsis thaliana 4. Similarly, the generation of endogenous siRNAs from repetitive

sequences 10,11

, the production of trans-acting siRNAs (tasiRNAs) from non-coding

transcripts 12-15

as well as the amplification of the RNAi signal by RNA-dependent RNA


polymerases 7, were described in this model organism. It is therefore all the more

surprising that the most wide-spread tool in RNAi-based research, i.e. the transfection of

organisms or cells with siRNAs, has found very little resonance in the plant field. In the

animal field, the transfection of cultured single cells with siRNAs has become a routine

technique for functional gene analysis in reverse genetic studies. Numerous reagents for

transfecting mammalian cell lines, often based on positively charged liposomes, are

commercially available 16

. The potential of siRNA duplexes to induce gene silencing when

directly introduced into the plant cell was shown in experiments with biolistically delivered

siRNAs in Nicotiana benthamiana and Nicotiana tabacum plants 17

. In experiments on

tobacco BY2 cells, transfection with sequence-specific siRNA duplexes led to a reduction

in reporter gene expression and viral replication 18

. Other studies on RNAi in plant single

cells have concentrated on the use of long dsRNA fragments as silencing-inducing agents

and demonstrated the successful knock-down of reporter genes in Arabidopsis

protoplasts 19,20

. However, to date no systematic exploration of the potential of siRNAs to

be used in reverse genetic experiments in plants has been presented.

The aim of this study was (i) the development of protocols for the successful transfection

of Arabidopsis mesophyll protoplasts with commercial siRNA duplexes and (ii) the

evaluation of siRNA-induced gene suppression in these cells. We have monitored the

uptake of fluorescently tagged siRNA molecules and have optimized transfection protocols

in order to reach detectable gene silencing on protoplast populations. The uptake of

siRNAs antisense to reporter gene sequences has induced a distinct decrease in detectable

reporter gene product levels. The present study constitutes the first report on gene knock-

down in Arabidopsis protoplasts using standard siRNAs and marks the initial step towards

RNAi screens in single plant cells.

Results

Establishing siRNA transfection into Arabidopsis protoplasts

Although siRNA transfection into animal cells is a standard technique used in many labs

and has been used on tobacco BY2 cells, delivery of small RNAs into Arabidopsis

protoplasts still had to be established. We first asked whether it was possible to transfect

mesophyll protoplasts isolated from young leaves with standard commercial siRNA

duplexes of 21 nucleotides with dTdT DNA overhangs at the 3’ ends. To visualize

successful transfection, a mock siRNA with no sequence homology to the Arabidopsis

genome, labeled with an Alexa555 fluorophor attached to the 3’ end of both strands of the


siRNA duplex, was used. After adaptation of a protocol for transient transformation of

protoplasts with plasmid DNA, protoplasts were successfully transfected using 0.1 nmol of

siRNA on 3x104 cells (Fig. 1A). We followed a standard polyethylenglycol transformation

protocol and avoided all pausing after the cell suspension and the siRNA solution had been

mixed, thereby limiting RNA degradation by RNases.

Although initial transfection efficiency was low (<5%), the Alexa555 fluorophor could be

detected in distinct punctate structures (Fig. 1A). To check whether these structures were

dependent on the nucleic acid, we treated the labeled siRNAs with RNase prior to

transfection. No punctate pattern was visible in the cells after RNase treatment; we could

Fig. 1 Transfection of a labeled siRNA into Arabidopsis protoplasts. A: Epifluorescence microscopy of

a negative control siRNA duplex tagged with an Alexa555 fluorophor into Arabidopsis Col-0 protoplasts.

Cells (30 µl of a cell suspension, 106/ml) were transfected with different amounts of siRNA. RNase was

added to the siRNA prior to transfection (very right) to observe uptake of the Alexa dye alone. Images were

taken 2 hours after transfection in Cy3 and bright field (BF) channels; scale bar = 30 µm. B: Confocal

microscopy of an Arabidopsis protoplast 2 h after transfection with Alexa555-conjugated siRNAs. Images

from left to right show Alexa555 fluorescence, bright field and merge; scale bar = 10 µm.

A

B


therefore assign these structures to the labeled siRNAs but not to the Alexa dye alone.

Images acquired by confocal microscopy showed that the fluorescence signal was

distributed around the chloroplasts (Fig. 1B). Additionally, confocal z-stack images (not

shown) indicated the intracellular localization of the punctuate structures. It could therefore

be excluded that the observed structures were merely attached to the cell surface and we

concluded that they were localized inside the cell, most likely in the cytosol.

To further investigate the nature of the punctate structures giving rise to the Alexa555

fluorescence, we recorded confocal images of transfected cells in time series (Fig. 2). In a

time-lapse of several minutes, it became apparent that at least part of the Alexa555-positive

objects were mobile within the cell as some of them disappeared from view while others

(re)appeared at other locations (Fig. 2, arrows).

Fig. 2 Mobility of siRNA-labeled structures in the cell. Images show a time series of an Arabidopsis

Col-0 protoplast upon transfection with an Alexa555-labeled negative control siRNA duplex, relative time

points are indicated in seconds. Image series was acquired with a 63x/1.2 water immersion lens and is

depicted in range indicator false colors. Areas occupied by chloroplasts and deprived of Alexa555 signal are

indicated by asterisks. Arrows point out several mobile Alexa555-positive punctate structures. Scale

bar = 10µm.


After successful transfection of the cells, biological activity of the siRNAs needed to be

assessed. We were faced with the choice to use either labeled or non-conjugated siRNAs in

gene knock-down experiments. Although a fluorescent tag would have had the advantage

to label transfected cells in a protoplast population, we opted for non-labeled siRNAs due

to possible side-effects and potential inhibition of siRNA activity by the dye. This meant

that the gene silencing effect had to be analyzed on a population of transfected and non-

transfected cells and that higher transfection efficiency was required. Only by ascertaining

that a significant proportion of the population had been transfected could we investigate

siRNA-mediated knock-down in protoplast populations. In order to further optimize the

transfection, we tried different siRNA amounts and modifications to the protocol.

Dimethylsulfoxide (DMSO), a cytotoxin, has been widely used in transformation of yeast

and bacterial cells to increase the uptake of DNA 21

. We observed that addition of DMSO

during siRNA transfection had a strong positive effect on the transfection rate with

Alexa555-labelled siRNAs, without altering cell viability if immediately removed from the

cell suspension afterwards (Fig. 3). We could observe a conspicuously higher Alexa555

signal when using 2, 5 or 10 % DMSO during the PEG-mediated transfection. Intriguingly,

DMSO seemed to have a negative effect on the activity of siRNAs in gene silencing

experiments (see below) and we therefore avoided its use when studying siRNA effects on

gene product levels. The amount of siRNA introduced into the reaction also appeared to be

of importance for successful transfection. By increasing the siRNA amount from 0.1 nmol

to 0.5 nmol, transfection efficiency of 3x104

protoplasts was clearly increased when

considering the fluorescence intensity of the cells 2 h after transfection (Fig. 3). We

observed punctate structures originating from Alexa555-siRNAs in approximately 50 % of

the cells when applying DMSO at 5% or higher and in approximately 30 % of the cells

when no DMSO was applied. By further increasing the siRNA amount to 1 nmol per

transfection, we detected Alexa555 fluorescence in 50 % of the protoplasts without the

application of DMSO (data not shown). We considered this transfection rate as sufficient

for gene silencing experiments.

Knock-down of the fluorescent reporter mGFP5

In a first attempt, we tried to silence the expression of a green fluorescent reporter protein

(mGFP5) in mesophyll protoplasts derived from a 35S::mGFP5 Arabidopsis line (C24

background). No commercial validated siRNA against the mGFP5 gene was available; the

siRNA was designed according to previous experiments on suppression of mGFP5


expression by artificial microRNAs (amiRNAs) in the same type of cells (see Chapter II).

Assuming that functional amiRNAs and siRNAs should fulfill identical criteria, we used

the sequence of amiRGFP-7

, which had led to a strong decrease in GFP signal intensity upon

transient expression in protoplasts. siRNAs were used as duplexes with dTdT overhangs at

the 3’ ends. As mock treatment we used a negative control siRNA which showed no

sequence homology to the Arabidopsis transcriptome or to mGFP5; siRNA and target site

sequences are indicated in Table 1.

Upon transfection, protoplasts were embedded in a gel-like matrix and observed over time

(see Chapter IV for details). Images were acquired in bright field and GFP fluorescence

channels using an automated iMIC instrument (Till Photonics). Using the CellProfiler™

Fig. 3 Efficiency of siRNA transfection into Arabidopsis protoplasts. Arabidopsis Col-0 protoplasts were

transfected with an Alexa555-labeled negative control siRNA duplex in different amounts. 0.1 or 0.5 nmol

of a 100 µM siRNA solution were added to 30 µl of cell suspension (106/ml). Dimethylsulfoxide (DMSO)

was added to different final concentration, values indicated refer to the DMSO concentration in the

siRNA + cell + DMSO mix before addition of PEG. Images were acquired 2 h after transfection in the Cy3

and bright field (BF) channels, respectively. Cy3 images are shown in range indicator false colors to

emphasize differences in signal strength; elevated background fluorescence in the lower panel is due to

higher residual Alexa555 dye in the medium. Scale bar = 100 µm.

Table 1. siRNAs applied in this study and their respective target sequences


software, living cells were identified on the bright field image and the GFP signal intensity

was measured on the corresponding fluorescence image (see Materials and Methods and

Chapter IV for details). We observed similar fluorescence intensities in all samples at

day 1 after transformation (Fig. 4A). Starting from day 2, untransfected and siRNAmock

-

transfected samples showed a strong increase in fluorescence intensity with a doubling of

the signal strength from day 1 to day 3. This observation had been made previously on

protoplasts derived from the same line (see Chapter II). GFP signal intensity in the

siRNAGFP

-transfected sample only increased by 10 % in the same time interval. From

day 3 to day 5, signal intensity in the untransformed sample reached a plateau while it

slightly decreased in the siRNAmock

-transfected cells. The siRNAGFP

-transfected cells

showed a constant but weak increase in GFP signal intensity over the whole duration of the

experiment (Fig. 4A). Images taken 4 days after transfection indicated a conspicuously

lower GFP signal intensity in cells transfected with anti-GFP siRNA when compared to

cells transfected with no or mock siRNA (Fig. 4B). We generated histograms from the

fluorescent data of all individual cells identified on the images (Fig. 4C). Following the

distribution of mean fluorescence per cell in each sample over time, it became apparent

that all samples started with equal frequencies of weakly and highly fluorescent cells.

While in untransfected and siRNAmock

-transfected samples the histogram was shifted

towards high fluorescence values per cell in the course of time, most identified objects in

the siRNAGFP

-transfected sample remained gathered at low signal intensity values at late

time points (Fig. 4C). From the combination of these data we concluded that the

transfection of anti-GFP siRNA duplexes into 35S::mGFP5 protoplasts led to a suppression

of GFP expression.

Knock-down of a luciferase reporter

In order to validate our results, we attempted the knock-down of a second gene and

decided to use commercially available and validated siRNAs against the luciferase GL3

gene (Luc+). We used mesophyll protoplasts isolated from a 35S::Luc

+ line in

Wassilewskija (Ws) ecotype background and transfected them with two commercial anti-

Luc+ siRNAs from Qiagen® (Q) and Ambion® (A) and two respective negative control

siRNAs as mock controls. While sequences of Qiagen® siRNAs were available and the

target site could therefore be identified, Ambion® siRNAs were of unknown sequence.

Available sequences are indicated in Table 1.


Experiments using Alexa555-labeled siRNAs had shown the same uptake rate for

protoplasts isolated from Col-0 and Ws wild-type seedlings (data not shown). We

transfected 35S::Luc+ and Ws wild-type protoplasts with mock and anti-Luc

+ siRNAs and

aliquoted the transformed cells in order to do luciferase activity measurements on the same

samples over time. On day 1 after transfection, luciferase activity in anti-Luc+(A) and anti-

B

Fig. 4 Knock-down of a green fluorescent reporter

(GFP) by siRNAs. A: Quantification of mGFP5

expression in protoplasts derived from a 35S::mGFP5

line (C24 background) either untransfected or upon

transfection with an anti-GFP and a mock siRNA.

Pixel intensities in the GFP channel were measured in

866 ± 282 living cells over time using CellProfiler-

based automated cell identification. Data were

generated from mean pixel intensity values per cell.

The graph depicts the median of the cell population;

error bars indicate standard error. B: Cells transfected

with no, mock or anti-GFP siRNAs in bright field

(BF) and GFP channels. Fluorescence images are

shown in range indicator false colors; scale

bar = 50 µm. C: Histogram of fluorescence intensity

distribution in the cell population. Graphs show

frequency of mean pixel intensity (GFP) per cell in

untransfected, mock-siRNA-treated and anti-GFP-

siRNA treated samples over time.

3000

5000

7000

9000

11000

0 1 2 3 4 5 6

days after transfection

pix

el in

tensity (

GF

P)

+/-

s.e

.untransformed

mock siRNA

anti-GFP siRNA

A

C


Fig. 5 Knock-down of a stably expressed luciferase reporter in Arabidopsis protoplasts. Protoplasts

isolated from a 35S::Luc+(GL3) line (Wassilewskija background; 30µl of a 10

6 cells/ml suspension)

were transfected with 1 nmol of different commercial negative control and anti-Luc+ siRNAs. (Q:

Qiagen®, A: Ambion®). Luciferase activity was measured at different time points after transfection. A:

Absolute luciferase activity at 1, 2 and 4 days after transfection, measured in 6x103 35S::Luc

+ leaf

protoplasts per sample. Ws wild-type control is included as reference. B: Data from measurements

presented in (A) expressed as relative value to the untransformed control, which was set to 100% for

each time point. A+B: Errors bars indicate standard deviation between three independent measurements.

A

B

days after transfection


Luc+(Q) samples was distinctly lower than in the untransformed and the respective

siRNAmock

samples (Fig. 5A). Similar observations were made on measurements at 3 and

4 days after transfection. For better resolution of the differences between samples and

elimination of effects caused by reduced cell numbers at later time points due to cell death

events, we plotted the data relative to the untransformed control for each day (Fig. 5B). It

thus became visible that Luc+ activity in anti-Luc

+(A) samples corresponded to 55 % of the

untransformed control on day 1; this value was further reduced to 45 % on day 4. The

mock(A) sample was variable along the different measurements and took values of

80-95 % of the control but gave a conspicuously higher signal than the anti-Luc+(A)

sample. For the anti-Luc+(Q) sample, the reduction in luciferase activity was not as distinct

as for the anti-Luc+(A). However, the signal was 30 % and 40 % lower than the control

and 30 % and 25 % lower than the mock(Q) sample on day 1 and day 4 after transfection,

respectively. Although a decrease in luciferase activity in the siRNAmock

-treated samples

compared to the control could be observed, which was more pronounced during the time

course, the difference between untransformed and siRNALuc+-treated samples was more

severe. We conclude from this that the transfection of 35S::Luc+ protoplasts with anti-

Luc+-siRNAs led to silencing of luciferase expression.

Discussion

Arabidopsis protoplasts can be transfected with conventional siRNAs

We have shown in this study that siRNA duplexes can be transfected into Arabidopsis

Columbia-0 and Wassilewskija protoplasts. Successful transfection occurred using a

protocol adapted from a standard method to transiently transform protoplasts with plasmid

DNA (Fig. 1). On the contrary, the use of several commercial lipid-based transfection

agents led to no detectable uptake of the siRNA and was in most cases detrimental to cell

fitness (data not shown). We conclude from this that membrane properties of Arabidopsis

protoplasts are different from those of mammalian cells and render the use of lipid-based

transfection reagents inadequate. All components used so-far were positively charged, the

use of neutral lipid-based reagents, which are currently emerging on the market, still has to

be explored. Alternatively, non-lipid reagents, such as polyethylenimine-based (PEI)

components, could lead to improvement of transfection rates and their use needs to be

investigated.

The transformation efficiency was distinctly improved by the use of high amounts of

siRNA (0.5-1 nmol/3x104 cells) and the application of DMSO in relatively high


concentrations (2-10%) during the PEG-mediated transfection (Fig. 3). However, in later

knock-down experiments, we had the impression that DMSO – although without visible

effect on cell morphology – was detrimental to siRNA-mediated gene inhibition (data not

shown). Knock-down assays presented here were therefore conducted without DMSO and

further experiments investigating the effect of DMSO on the down-regulation of genes by

siRNAs are required. When transfecting cells using a PEG-based protocol, we avoided

adding RNase inhibitors in the process. Although RNA stability could have been increased

by addition of such inhibitors, we assumed that their potential uptake by the cells could

interfere with the activity of RNase III-type enzymes like Dicer, necessary for siRNA

processing and loading 5,9,22

. This issue requires further investigation.

Localization of labeled siRNAs upon uptake into protoplasts

The uptake of a siRNA duplex labeled with an Alexa555 fluorophor by Arabidopsis

protoplasts could be monitored. We could prove that the punctate structures giving rise to

Alexa555 fluorescence were dependent on the siRNA- and not the Alexa dye because pre-

treatment of the siRNA-Alexa555 complex with RNase did not lead to a similar

fluorescence signal (Fig. 1A). The nature of the punctate structures, which could be shown

to be localized and mobile inside the cell and not attached to the outer membrane (Fig. 1B

and Fig. 2), remains elusive. Preliminary data on labeled siRNAs transfected into

protoplasts derived from several organelle marker lines 23

indicated that Golgi apparatus,

peroxisomes and endoplasmic reticulum have to be excluded from the list of possible

candidates (data not shown). We hypothesize that the Alexa555-siRNA signal arises from

an endocytic or endosomal compartment. Recent data from the animal field on associations

of components of the RNA-induced silencing complex with specific endosomal

compartments such as multivesicular bodies or late endosomes 24

indicates possible

mechanistic links. Co-localization studies using protoplasts of appropriate marker lines are

currently ongoing.

siRNA transfection into protoplasts leads to specific gene knock-down

Based on two different reporter constructs with two different read-outs, we could show for

the first time that gene-specific siRNAs lead to down-regulation of genes in Arabidopsis

protoplasts within one to several days. Protoplasts isolated from a 35S::mGFP5 line

showed a limited increase in GFP signal intensity over time when transfected with anti-

GFP siRNAs (Fig. 4A). The signal increase observed in untransfected and mock-


transfected cells had been observed previously for protoplasts derived from this line (see

Chapter II). We speculate that de-differentiation of protoplasts after isolation leads to a

general increase in transcriptional and translational activities and thereby to an increase in

GFP signal intensity. Histogram analysis of the fluorescence distribution in the sample

clearly indicated that the ratio of cells with high to cells with low GFP signal intensity was

lower in the siRNAGFP

-transfected sample compared to the two control samples 2-5 days

after transfection (Fig. 4C). We determined cell viability in all samples in order to exclude

secondary effects as source of loss of GFP signal. The rate of decrease in the number of

identified objects per sample per day, which is explained by a fraction of the protoplasts

undergoing cell death in the course of time, was identical for all samples (data not shown).

From the microscopic data, no alteration in cell morphology or behavior could be detected

among the samples. We therefore conclude that the decrease in GFP signal was a specific

effect of the anti-GFP siRNA transfection.

Our results on the down-regulation of GFP were confirmed by the knock-down of a

luciferase reporter in 35S::Luc+ protoplasts. Here, the effect of gene-specific siRNAs could

be observed at an earlier time-point compared to the GFP silencing experiment; the

siRNALuc+

-transfected samples showed a distinctly lower luciferase activity already 24 h

after transfection. This observation can be explained by the high turnover rate of the

luciferase of only 3 h (in mammalian cells) 25

which makes a transcriptional inhibition

more rapidly detectable on the protein level compared to GFP.

It has to be noted that for both assays, GFP and Luc, values could only be measured for the

whole protoplast population. We can only speculate about transfection efficiencies of cells

with unlabelled siRNAs based on our assays with Alexa555-siRNAs and therefore the

number of untransfected cells in the respective samples can only be estimated. It is obvious

that these cells contribute disproportionately to the average GFP signal intensity or

luciferase activity of the protoplast population. On the basis of an estimated transfection

rate of 50 %, a decrease in luciferase activity to 50 % of the control sample, as observed

for the anti-Luc+(A) siRNA, would correspond to a complete knock-out in all transfected

cells whereas the other half of the population would give rise to an unaltered luciferase

signal. At this point, actual knock-down levels in siRNA-transfected protoplasts can only

be assumed and will have to be verified in further experiments.

We noticed that, compared to the untransformed sample, GFP signal intensity decreased in

cells transfected with mock siRNAs that had no sequence homology to either mGFP5 or

the Arabidopsis genome. Although this effect became visible at a later time point and was


less dramatic than with the anti-GFP siRNA, it was nevertheless too distinct to be ignored.

Most intriguingly, a similar effect with the same mock(Q) siRNA was observed in the

luciferase assay. While on day 1 after transformation the mock sample was identical to the

untransformed control, the mock-to-untransformed ratio decreased over time and reached

80 % on day 4. Although purely hypothetical, we assume that the high concentration of

this kind of siRNA stimulated the RNAi machinery in the cells and activated a cascade that

eventually had an impact on the over-expression of the GFP and luciferase genes with a

time delay compared to specific anti-GFP and anti-Luc+ siRNA effects. The silencing of

over-expressed genes is a common observation and could in these cases have been

triggered as a secondary effect of the siRNA transfection.

This study is the first report on targeted gene silencing by siRNA transfection in single

plant cells. We have shown that siRNAs can be successfully transfected into plant

protoplasts at high transfection rates and that the siRNA uptake per se is not detrimental to

cell viability or behavior. By the independent knock-down of two reporter genes in

different ecotype backgrounds of the model plant Arabidopsis thaliana it was shown that

gene silencing occurs efficiently and can be measured on whole protoplast populations. We

are currently investigating the knock-down of endogenous targets and the possibilities to

monitor consequences of gene silencing by tracking morphological, cellular and molecular

changes. Plant protoplasts thereby enter the collection of biological systems apt for RNAi-

based screening procedures by the systematic suppression of genes via siRNA transfection.



Plant culture

Seedlings for protoplast isolation were grown on SCA medium in a 16-8h dark-light cycle

at 25°C. The 35S::mGFP5 line was first presented by Dalmay et al. 2000 26

. The 35S::Luc+

over-expressor line was a donation from F. Nagy.

Protoplast isolation, transfection and culture

We followed a method modified from the protocol published by Sheen and colleagues 27,28

.

Protoplasts were isolated under sterile conditions from aerial tissues of 2-3 week-old

seedlings. Aerial parts were cut from the roots and imbibed with MMC solution. Plant

material was cut with a scalpel and left in MMC for 1 h at room temperature for pre-

plasmolysis. Enzymatic digestion of the cell wall was performed by incubating the plant

material in [MMC, 0.5% cellulase (Duchefa), 0.5% macerozyme (Duchefa)] for 16 h at

25 °C in the dark. Cell suspension was centrifuged 10 min at 100g and resuspended in 8 ml

MCS, the suspension was overlaid with 2 ml transformation medium. After centrifugation

for 10 min at 100g, cells were collected at the interphase between MCS and transformation

media. Cells were subsequently washed in 10 ml W5 and total cell number was assessed in


a Fuchs-Rosenthal hæmocytometer. After final centrifugation for 10 min at 50g, the final

cell density in transformation medium was adjusted according to experimental needs.

Protoplast transfection was performed in 2 ml-round-bottom tubes using 3x104

cells. Cells

were mixed with 0.1 to 1 nmol siRNA in RNase free dH2O (100 µM). Polyethylenglycol

1500 (40%) (PEG, Carl ROTH) in a volume corresponding to the combined volumes of

cell suspension and RNA was added. Transformation was stopped after 8 min by addition

of transformation medium to a final volume of 500 µl. Cells were centrifuged at 100g for

5 min, supernatant was discarded and PCA solution including 3,6-dichlor-2-

methoxybenzoic acid (Dicamba, 3 mg/l, Sigma-Aldrich) and 1-Naphthaleneacetic acid (1-

NAA, 0.5 mg/l, Sigma-Aldrich) was added to 500 µl. In case of Alexa555-siRNA

transfection, cells were washed three times by centrifugation at 100g and addition of

transformation medium in order to wash away excess fluorophor. After transfection,

protoplasts were kept at 25 °C in the dark for 16 h, then transferred to a 16/8 dark/light

cycle at 25 °C

For protoplast embedding, transformation medium was removed and cells were

resuspended in 200 µl of a 1:1 mix of alginic acid (2.8 %) and calcium-free W5M. They

were then transferred to an appropriate microscopy plate and left to sediment for 1 h.

Solidification was initiated by addition of 200 µl W5 in small droplets on top of the cell

suspension. After 30 min, supernatant W5 was removed and cells were washed twice by

overlaying the gel with 200 µl PCA for 20 min to wash away excess calcium ions. After

removal of the second washing solution, 250 µl PCA (Dicamba 3mg/l; 1-NAA 0.5 mg/l)

was added. After transformation, protoplasts were kept at 25 °C in the dark for 16 h, then

transferred to a 16/8 dark/light cycle at 25 °C

Microscopy


Plan-APOCHROMAT 20x/0.75 air and Zeiss Plan-APOCHROMAT 63x/1.3 water

immersion objectives. All GFP images and all RFP images were acquired with the same

settings using Metamorph v6.2r4. For automated image acquisition we used an iMIC

instrument (Till Photonics) controlled by Till Photonics Live Acquisition 1.2.2.12.

Objectives used were a Zeiss Plan-NEOFLUAR 10x/0.30 air and a Zeiss Plan-

APOCHROMAT 20x/0.75 air. We acquired up to 80 viewing fields per well using the

“tile” module. Confocal images were acquired using a Zeiss LSM 510 NLO confocal

scanning microscope with a 63x/1.3 water immersion objective. Excitation wavelength for

Alexa555-conjugated siRNAs was 543 nm (Helium-Neon-Laser). Emission was detected

at 550-610 nm Alexa555-conjugated siRNAs. Images were analyzed with the LSM image

browser (Carl Zeiss MicroImaging™) and MacBiophotonics ImageJ.

Image analysis

We used CellProfiler™ version 1.0.5811 29,30

. The “LoadImages” module was set to “Text-

ExactMatch” and GFP and BF images were recognized by their respective file name. As

the cameras acquired images in 12 bit, all images were rescaled to 16 bit using the

“Rescale Intensity” module. Cells on bright field images were identified using the

“FindEdges” module with a threshold correction factor of 0.6. As edge-finding method we

used the Sobel algorithm, applying the “RATIO” method with a filter size of 8 pixels.

Edge thinning was applied and the program was set to find all edges in a binary grayscale

image. Objects outside a diameter range from 40 to 300 pixels were discarded, as were

objects in contact with the image border. No merging of small objects in contact with each

other occurred. As segmentation algorithm, “MoG global” was used; no correction factor

or threshold boundaries were applied. Holes in identified objects were filled.

“MeasureObjectAreaShape” was applied on identified objects. Using the


“FilterByObjectMeasurement” module, objects that did not fulfill the “FormFactor (7)” to

a minimum value of 0.7 were discarded. By applying the “MeasureObjectIntensity”

module to the corresponding GFP-channel image, pixel intensities in the primary object

were measured. Data were exported to a “.txt” file using the “DataExport” function of

CellProfiler™, then imported into Microsoft® Excel 2003™ for further processing.

Luciferase activity measurements

Luciferase activity was measured in a EG&G Berthold MicroLumat LB96P luminometer.

100 µl of protoplast suspension (6000 cells) were mixed with 50 µl LucII buffer in an

opaque 96-well plate. The luminometer was set to inject 100 µl 1x luciferin solution, light

emission was quantified during 20 s. Composition of the LucII buffer was as follows:

80 mM glycyl-glycine (pH 7.8), 40 mM MgSO4, 60 mM adenosine-5’-triphosphate (ATP).

For a 5x stock of luciferin solution, D-luciferin (Biosynth) was dissolved in 100 mM

TRIS-H3PO4 (pH 8.0) to a final concentration of 50 mM.

Statistical analysis

Graphs were generated using SigmaPlot 9.0 (Systat Software Inc.). Histograms were

generated with a user-defined transform function with defined upper limits for the

respective bins. Bins were equal for all data series.


References

1. Fire, A. et al. Potent and specific genetic interference by double-stranded RNA in


2. Hammond, S.M., Bernstein, E., Beach, D. & Hannon, G.J. An RNA-directed

nuclease mediates post-transcriptional gene silencing in Drosophila cells. Nature

404, 293-296 (2000).

3. Zamore, P.D., Tuschl, T., Sharp, P.A. & Bartel, D.P. RNAi: double-stranded RNA

directs the ATP-dependent cleavage of mRNA at 21 to 23 nucleotide intervals. Cell

101, 25-33 (2000).

4. Hamilton, A.J. & Baulcombe, D.C. A species of small antisense RNA in post-

transcriptional gene silencing in plants. Science 286, 950-952 (1999).

5. Bernstein, E., Caudy, A.A., Hammond, S.M. & Hannon, G.J. Role for a bidentate

ribonuclease in the initiation step of RNA interference. Nature 409, 363-366

(2001).

6. Liu, J. et al. Argonaute2 is the catalytic engine of mammalian RNAi. Science 305,

1437-41 (2004).

7. Baulcombe, D.C. Amplified silencing. Science 315, 199-200 (2007).

8. Elbashir, S.M. Duplexes of 21-nucleotide RNAs mediate RNA interference in

cultured mammalian cells. Nature 411, 494-498 (2001).

9. Elbashir, S.M., Lendeckel, W. & Tuschl, T. RNA interference is mediated by 21-

and 22-nucleotide RNAs. Genes Dev. 15, 188-200 (2001).

10. Hamilton, A., Voinnet, O., Chappell, L. & Baulcombe, D. Two classes of short

interfering RNA in RNA silencing. EMBO J. 21, 4671-4679 (2002).

11. Tang, G.L., Reinhart, B.J., Bartel, D.P. & Zamore, P.D. A biochemical framework

for RNA silencing in plants. Genes & Development 17, 49-63 (2003).

12. Vazquez, F. et al. Endogenous trans-acting siRNAs regulate the accumulation of

Arabidopsis mRNAs. Molecular Cell 16, 69-79 (2004).

13. Peragine, A., Yoshikawa, M., Wu, G., Albrecht, H.L. & Poethig, R.S. SGS3 and

SGS2/SDE1/RDR6 are required for juvenile development and the production of

trans-acting siRNAs in Arabidopsis. Genes Dev. 18, 2368-2379 (2004).

14. Yoshikawa, M., Peragine, A., Park, M.Y. & Poethig, R.S. A pathway for the

biogenesis of trans-acting siRNAs in Arabidopsis. Genes Dev. 19, 2164-2175

(2005).

15. Allen, E., Xie, Z.X., Gustafson, A.M. & Carrington, J.C. microRNA-directed

phasing during trans-acting siRNA biogenesis in plants. Cell 121, 207-221 (2005).

16. Li, C.X. et al. Delivery of RNA Interference. Cell Cycle 5, 2103-2109 (2006).

17. Klahre, U., Crete, P., Leuenberger, S.A., Iglesias, V.A. & Meins, F., Jr. High

molecular weight RNAs and small interfering RNAs induce systemic

posttranscriptional gene silencing in plants. Proc Natl Acad Sci U S A 99, 11981-6

(2002).

18. Vanitharani, R., Chellappan, P. & Fauquet, C.M. Short interfering RNA-mediated

interference of gene expression and viral DNA accumulation in cultured plant cells.

Vol. 100 9632-9636 (2003).

19. An, C.I., Sawada, A., Fukusaki, E. & Kobayashi, A. A transient RNA interference

assay system using Arabidopsis protoplasts. Biosci Biotechnol Biochem 67, 2674-7

(2003).

20. Zhai, Z., Sooksa-nguan, T. & Vatamaniuk, O.K. Establishing RNA Interference as

a Reverse-Genetic Approach for Gene Functional Analysis in Protoplasts. PLANT

PHYSIOLOGY 149, 642-652 (2009).

21. Kawai, S. & Nishizawa, M. New procedure for DNA transfection with polycation

and dimethyl sulfoxide. Mol Cell Biol 4, 1172-4 (1984).


22. Elbashir, S.M., Martinez, J., Patkaniowska, A., Lendeckel, W. & Tuschl, T.

Functional anatomy of siRNAs for mediating efficient RNAi in Drosophila

melanogaster embryo lysate. EMBO J. 20, 6877-6888 (2001).

23. Nelson, B.K., Cai, X. & Nebenfuhr, A. A multicolored set of in vivo organelle

markers for co-localization studies in Arabidopsis and other plants. Plant J 51,

1126-36 (2007).

24. Lee, Y.S. et al. Silencing by small RNAs is linked to endosomal trafficking. Nat

Cell Biol 11, 1150-6 (2009).

25. Thompson, J.F., Hayes, L.S. & Lloyd, D.B. Modulation of firefly luciferase

stability and impact on studies of gene regulation. Gene 103, 171-7 (1991).




(2000).

27. He, P., Shan, L. & Sheen, J. The use of protoplasts to study innate immune

responses. Methods Mol Biol 354, 1-9 (2007).

28. Yoo, S.D., Cho, Y.H. & Sheen, J. Arabidopsis mesophyll protoplasts: a versatile

cell system for transient gene expression analysis. Nat Protoc 2, 1565-72 (2007).





Claude Becker CHAPTER IV 81

- CHAPTER IV -

A novel platform for high-throughput protoplast transformation and cell

feature analysis


Abstract

Single cells constitute an ideal biological object for the study of molecular, cellular

and biochemical processes in a system of reduced complexity under defined and

controllable environmental conditions. Long-term microscopic observation, cell

tracking and feature analysis have been shown on animal cell cultures but have not

been established for single plant cells. Here we present a novel platform for high-

throughput analysis of Arabidopsis thaliana protoplasts. We have developed a novel

single-vector system for the simultaneous transient expression of up to three

independent constructs and present a method for multiple parallel transformations.

Our pipeline combines cell preparation for long-term observation with automated

high-content microscopy and implements the systematic analysis of cellular features

by computational image analysis.

Introduction

Protoplasts are bacterial, fungal or plant cells that have been partially or completely

deprived of their cell wall. Removal of the cell wall can be achieved either mechanically 1

or by enzymatic treatment of the plant tissue 2 and results in the release of spherical single

cells. Plant protoplasts have been successfully isolated from more than 200 species,

including monocotyledonous and dicotyledonous crops 3. Protoplast isolation from

different tissues (roots, hypocotyls, cotyledons, leaves or flowers) has been most successful

with a mix of fungal enzymes comprising cellulases and pectinases 4. After isolation,

protoplasts can be cultured either in liquid or solid media. Depending on the source tissue

and the species, these media may vary in composition of inorganic salts and organic

nutrients, such as sugars, vitamins and plant growth regulators 5. For short-term

observations, protoplasts are cultured in liquid medium. In order to observe single

protoplasts over time, cells can be immobilized by embedding them in gels with semi-

solidifying compounds such as alginate 6 or agarose

7. In plant research, protoplasts

constitute the simplest biological entity and experimental system for analyzing basic

biological questions.

One main advantage of plant protoplasts in the context of molecular biological research is

the fact that they can be transiently transformed with plasmid DNA and express genes of

interest over several days after transformation. Transient expression assays in plant

protoplasts have proven to be very useful for dissecting a broad range of molecular


mechanisms, such as signaling and metabolic pathways as well as transcriptional

regulatory networks 4,8

.

Over the last decades, platforms have been established that allow high-throughput analyses

of single cells on behavioral alterations, e.g. during cell division 9. Findings in these well-

defined, simplified biological systems could often help to explain processes on the

organism level. In the plant field however, experiments on single cells have long played a

merely marginal role. In the last years, the true potential of plant protoplasts has been

shown by studies on protein-protein interactions 10,11

, transcriptional profiling of root cell

files 12,13

, signal pathway analysis 14

, proteomic profiling 15

and over-expression analysis of

fluorescently labeled constructs 16

. Although plant protoplasts have thus entered the list of

cellular systems exploited for large-scale and systematic analyses, to date no platform for

the investigation of cellular features on transformed plant protoplasts via high-throughput

microscopy has been presented.

Here we report on a platform that combines isolation of Arabidopsis protoplasts, large-

scale transient transformation with minimal amounts of plasmid DNA, culture of

protoplasts optimized for long-term observation, automated high-throughput microscopy

and cell feature determination by computational image analysis. With this platform it has

been possible to observe cells in a large number of samples over time and to qualitatively

and quantitatively assess cell viability, transformation efficiency and fluorescence

intensity. Due to the versatility of its separate components, the set-up of this pipeline can

be adapted to the respective experimental needs.

Results

Optimizing protoplast transformation

Our aim was to establish a reliable system for plant protoplast transformation with minimal

complexity in the experimental setup. In order to handle multiple samples in parallel, we

developed protoplast transformation in multi-well format using 3x104-5x10

4 cells per well.

A robotic method for the parallel transformation of multiple samples using tobacco

protoplasts had been published earlier 14

. We focused on a method applicable using

standard lab equipment and optimized the different steps for use with 8- to 12-channel

pipettes to manually handle large sample numbers. In order to achieve higher throughput,

we used 96-well round-bottom plates for transformation and transferred cells to 96-well

microscopy plates for observation using automated microscopy. A schematic outline of the

pipeline is given in Fig. 1.


We used mesophyll protoplasts from Arabidopsis thaliana isolated following a protocol

modified from Dovzhenko et al. 17

. From one standard 10 cm Petri dish of 2-3 week-old

Arabidopsis Columbia-0 seedlings (Fig. 1) we isolated 5-10x106 cells, sufficient for more

than 300 parallel transformations. Using 10µg of plasmid DNA on 3x104 cells, we reached

transformation efficiencies of 35% or higher, depending on the plasmid used (data not

shown).

Our approach offers the possibility to use a considerable number of different plasmid

constructs for parallel transformations. Isolation of large amounts of DNA, as they had

been used in previous studies, using standard maxi- or midiprep plasmid DNA kits is

costly and time-intensive. We were able to reduce the necessary plasmid DNA amounts to

Fig. 1 Experimental pipeline for protoplast analysis. 2-3-week old seedlings were harvested and

protoplasts were isolated from the aerial tissues by enzymatic digestion (1, 2). Cells were transformed in 96-

well plates using multi-channel pipettes (3). Depending on the experimental setup, the cell population could

be split after transformation: one part could be used, e.g., for protein analysis on Western blot (4a) while the

second part was analyzed microscopically. We used an automated iMic system (Till Photonics) for

epifluorescence and bright field microscopy on 96-well plates (4b). Images were processed before being fed

into the CellProfiler-based image analysis pipeline (5, 6). Finally, data from the image analysis underwent

processing and statistical evaluation.


1 µg per transformation. Efficiency tests with a plasmid for the expression of a red

fluorescent marker (mCherry) revealed a saturation of transformation efficiency at 45 %

using 0.5 to 1 µg of plasmid DNA on 3x104 cells (Fig. 2A). This allowed DNA preparation

using cheap and easy-to-handle small-scale plasmid isolation (e.g. commercial miniprep

kits) and thereby the use of a high number of different plasmids in one assay.

In experiments based on transient transformation, reproducibility had to be guaranteed. In

order to assure the same plate setup and the same quality of DNA from one experiment to

the next, we developed a strategy to transform cells with pre-dried plasmid DNA. DNA

was prepared at the bottom of the wells of a 96-well plate and air-dried under sterile

conditions. Plates could be kept at -20 °C for several weeks and used for later

transformation. When using pre-dried DNA, we left the cells to sediment to the bottom of

the well for 10 min before adding a 40 % polyethylenglycol 1500 (PEG) solution in order

resuspend the DNA in the cell suspension. Transformation efficiency remained at the same

level comparing pre-dried to freshly prepared DNA as well as after longer storage of the

plates under appropriate conditions (Fig. 2B). We have stored plates for up to 2 weeks

without detrimental effects and we assume that longer storage times are possible.

Fig. 2 Efficiency of transient transformation of Arabidopsis protoplasts with plasmid DNA for the

expression of a red fluorescent reporter protein (mCherry) under the control of the rolD promoter. A:

Transformation efficiency in dependence on the amount of plasmid DNA added to the sample. 3x104 cells

(106/ml) were incubated with 10 µl of DNA in the respective concentration. The cells’ fluorescence signal

24 h after transformation was analyzed. B: Effect on transformation efficiency of pre-drying and storing

plasmid DNA for different time periods. 1 µg of DNA was dried at the bottom of the wells of a 96-well

transformation plate and stored at -20 °C for the indicated time. Cells were then added and transformed;

images for the analysis of fluorescence intensities were taken 24 h after transformation. As a control, 1 µg

DNA in suspension (0.2 µg/µl) was used (0 days). A+B: Data represents mean values of three independent

experiments, error bars indicate standard deviation.

A B


Immobilization of living plant protoplasts for long-term observation

Post-transformation treatment of protoplasts is a crucial point to consider if cells should be

observed over longer time periods. Through addition of growth substances (3,6-dichlor-

2-methoxybenzoic acid, 1-Naphthaleneacetic acid) to the culture medium, protoplasts kept

their viability for one week after transformation (Fig. 3A); we have observed cells up to

three weeks after transformation if the culture medium was renewed every 5-6 days (data

not shown). As we intended to perform long-term tracking of the same cells under the

microscope, we adapted a method to immobilize the cells at the bottom of the well by

fixing them in a gel-like matrix 6. To this purpose, we kept the cells in calcium-free

Fig. 3 Long-term observation of Arabidopsis protoplasts after embedding. A: After embedding in a gel-

like matrix, the behavior and development of Arabidopsis protoplasts could be followed by imaging the same

viewing fields over time (embedded numbers indicate days after transformation; scale bar = 50 µm)

B+C: Size increase of protoplasts over time. B: A single cell was observed over a time period of 8 days (1-8)

to monitor its morphological changes (embedded numbers indicate days after transformation; scale

bar = 50 µm). C: Relative size increase of protoplasts from day 1 to day 8 after transformation followed by

immediate embedding. Data represents mean values of 30 analyzed single cells, error bars indicate standard

error.

C

A

B


medium until after transformation. We mixed the cell suspension with a solution of alginic

acid and let the cells sediment to the bottom of the plate. The suspension was then

progressively overlaid with calcium-containing W5 medium. This last step started the

polymerization of the alginate and embedded the cells in the gel at the bottom of the well.

Most importantly, cells were thus trapped in a monolayer at the bottom of a slide and could

be analyzed by high-resolution microscopy using inverted microscopes. Although the

embedding inhibited the lateral movement of the protoplast, it did not interfere with cell

growth and cell division (Fig. 3B+C). Embedded Arabidopsis protoplasts increased by

50% in diameter within 1 week after protoplasting, which corresponds to more than a

tripling of the volume if one considers the cell being spherical in shape (Fig. 3C). We

could thus follow the same cells over several days to several weeks and monitor their

morphological changes, division or fluorescence signal intensity.

Fig. 4 Comparison of image acquisition using the iMic and Zeiss Axiovert systems. A: Illustration of

the difference in identified cells in images acquired with the automated iMic and the manual Zeiss Axiovert

microscopes in identical time frames of 10 min. Bars represent means of 7 samples, error bars indicate

standard deviation. For the iMic system, 40 viewing fields were acquired per sample versus 7 viewing fields

per sample using the Axiovert system. B: Comparison of cell analysis using images of the same samples

acquired with the automated iMic and the manual Zeiss systems. In Arabidopsis protoplasts expressing

artificial microRNAs (amiRNAs) against a specific target gene tagged with the green fluorescent protein

GFP, pixel intensities were measured in order to define amiRNA efficacy (see Chapter II for details). Upon

cell identification based on a red fluorescent marker (mCherry), pixel intensities were measured on the

corresponding GFP image in the identified areas. Data corresponds to mean values of three independent

experiments; values are presented as pixel intensity relative to the mock sample. Error bars indicate

standard deviation between the different experiments.

A

0

0,2

0,4

0,6

0,8

1

1,2

mock GFP P2 P3 P5 P22 P33

amiRNAPIN1::GFP

no

rma

lize

d m

ea

n p

ixe

l in

ten

sity (

GF

P)

+/-

s.d

.

iMic

Zeiss Axiovert

B


Automated microscopy of transformed cells

Increase of sample numbers inevitably led to an increase in the number of images to be

acquired. In order to speed up image acquisition and to increase objectivity, we opted for

automated microscopy. Using an iMIC instrument (Till Photonics), a complete 96-well

plate could be measured in very short time intervals (Fig. 1). As an example, with a 10x

magnification and using tiles of 70 viewing fields per well, we were able to acquire more

than 6700 images in bright field in less than 1 h. For higher resolution we used a 20x

objective; complete coverage of a well could then be achieved in 150 single viewing fields.

Although image acquisition in epifluorescence mode took considerably longer because of

longer exposure times, we were able to reduce microscopy time by 70 % compared to

manual acquisition using a Zeiss Axiovert system. Apart from an increase in comfort,

automated microscopy allowed the unbiased acquisition of considerably higher numbers of

images per well, thereby increasing the number of cells to be analyzed and leading to more

robust statistical evaluation (Fig. 4A). Comparison of fluorescence measurements based on

images acquired with the Zeiss system to data based on acquisition with the iMIC system

showed high correlation (Fig. 4B). In addition, the automated selection of viewing fields

discarded the risk of subjectivity in this process.

A novel vector system for multiple expressions

In a study relying on a fluorescent read-out as indicator for gene suppression efficiency

(see Chapter II for details), our main interest was the assessment of fluorescence signal

intensities of transformed cells over time or at specific time points after transformation.

Although transformation efficiencies were high, it still had to be considered that a great

number of the protoplast population did not take up the plasmid DNA. In order to

differentiate between transformed and non-transformed cells, a vector system was

developed that allowed the expression of a fluorescent marker and the gene of interest from

the same plasmid backbone. By this strategy, the need for double transformation with two

different plasmids for the transformation marker and the gene of interest, respectively,

could be avoided. As backbone we selected the pAM-PAT plasmid (GenBank accession:

AY436765.1), which was small in size and provided the advantage of a binary vector to be

used for both transient and stable transformations. A cassette for the expression of a

fluorescent reporter, the red fluorescent protein mCherry 18

, was inserted into the T-DNA

region of the plasmid. Expression of this reporter marked transformed cells in the

population. Testing different promoters and different orientations in the vector backbone


led to the expression of mCherry from the constitutive promoter rolD in sense direction to

the Gateway™ expression cassette. We refer to this vector as pELWMS

(pEierLegendeWollMilchSau) and it constituted the basis of further vector design

(Fig. 5A).

In a study on artificial microRNA efficacy in protoplasts (see Chapter II for details), an

amiRNA was inserted into the Gateway™ expression cassette and got expressed as second

gene from the pELWMS backbone. The respective target gene of the amiRNA, fused to

another fluorescent reporter (mGFP5), was inserted outside the T-DNA region as third

component to be expressed from the same plasmid (Fig. 5B). By this approach we not only

eluded the need for multiple transformations of the same cells with several plasmids, but

Fig. 5 A novel vector system for the simultaneous expression of multiple constructs. A: The pELWMS

plasmid is based on a Gateway-compatible version of the pAM-PAT vector and contains a mCherry

expression cassette for cell labeling after transformation. B: Based on the pELWMS plasmid, pELWMSGFP

and pELWMSPIN1::GFP

(see Chapter II for details) contain additional expression cassettes for a fluorescently

tagged gene under control of the viral CaMV 35S promoter. C: Transient expression of both fluorescent

markers from the pELWMSGFP

(upper row) and pELWMSPIN1::GFP

(lower row) plasmids upon transient

transformation into Arabidopsis Col-0 protoplasts. Images were acquired 24 h after transformation; scale

bar = 30 µm).

pELWMS

9079 bp

mCherry

RB

AmpR

LB

rolD

35S

attR2

attR1

Gateway

BastaR

pELWMS GFP

10702 bp

mCherryRB

mGFP5

AmpR

LB

rolD

35S 35S

attR2

attR1

Gateway

BastaR

pELWMS PIN1:GFP

12571 bp

mCherry

RB

PIN1: :GFP

AmpR

LB

rolD

35S

35S

attR2

attR1

Gateway

BastaRmCherry GFPmCherry GFPmCherry GFP

C

A B


also assured that all three DNA templates were present in equal amounts in one cell.

Successful expression of both fluorescent constructs from the pELWMSGFP

plasmid can be

seen in Fig. 5C. Expression of the amiRNA from the Gateway™ cassette could be

monitored by knock-down of the respective target gene (see Chapter II). We had thus

developed a novel vector system that allowed simple and reliable transformation of

protoplasts for the monitoring of fluorescent signal intensities.

Automated cell analysis

With the protoplast isolation and transformation and the image acquisition fitted to the

needs of a high-throughput platform, we developed protocols for the automated analysis of

the acquired image data. We used the cell analysis software CellProfiler™ 19,20

for the

automated segmentation of cells, the differentiation between transformed and non-

transformed cells and the measurement of fluorescent signal intensities within the cells.

The fluorescence signal provided by the transformation marker mCherry was used for

automated identification in the image of transformed cells by segmentation of areas

corresponding to RFP-positive cells (Fig. 6A+B). In order to discard false positive results,

which could consist of fluorescent debris or dead cells recognized as RFP-positive objects,

these areas underwent a selection based on size and shape criteria. All objects outside a

defined area range and deviating to a certain degree from perfect roundness were discarded

(Fig. 6B-D). Finally, the filtered areas were transferred to the corresponding image

acquired in the GFP channel and pixel intensities in this image were measured (Fig. 6).

In some experiments we had to deal with weak intensities of the fluorescent signal. This

resulted in the background signal and the camera off-set contributing disproportionately to

the overall signal and made differences between signal intensities hard to detect. We

measured the background fluorescence around each identified object to determine the real

pixel intensity value to be attributed to the proper signal. The area identified as

transformed cell was increased in diameter by 6 pixels, resulting in an object referred to as

[cell+6]. In a subsequent step, a second enlargement by 3 pixels of the [cell+6] object

occurred, resulting in a [cell+9] object (Fig. 6E). Subtraction of the area of [cell+6] from

the area of [cell+9] using the “Identify Tertiary Subregion” module led to a 3-pixel-wide

ring surrounding the initial object in a 6-pixel-distance from its border (Fig. 6F). By

measuring pixel intensities within this ring, we could determine the background intensity

for each individual object, the mean of this individual background indicated the mean

background intensity of the image. By subtracting the background from the total signal, a


higher resolution of differences in signal intensity could be reached. This strategy

especially proved to be important when dealing with long-term acquisitions, mainly when

doing manual microscopy, as it allowed the correction of falsifying influences, like

fluctuating lamp intensity.

Fig. 6 CellProfiler pipeline for the identification of transformed protoplasts and pixel intensity

measurements. A: Identification of transformed cells in the protoplast population was based on a red

fluorescent signal (mCherry). 12-bit black and white TIFF images acquired in the RFP channel were fed into

the pipeline (scale bar = 100 µm). B: Based on pixel intensity boundaries, transformed cells were recognized

as objects. These were separated into objects within (green) and objects outside (red) a defined diameter range

C: Areas recognized as occupied by fluorescent objects fulfilling the size criteria were segmented. D: Objects

deviating to a defined degree from a certain shape were discarded. In the indicated experiment, we used

roundness as a criterion. E: In order to measure the fluorescence intensity of the background surrounding each

individual object, all objects were expanded by 6 pixels ([object+6]), the expanded object was then expanded

a second time by 3 pixels ([object+9]). F: By subtracting the area of [object+6] from [object+9], a ring-like

area was generated in which the background fluorescence for each single object could be measured.


In order to verify homogenous conditions during cell transformation and microscopy and

to check for plate effects, we included repeats of several control samples distributed over

the 96-well plate. Images of samples transformed with the same constructs and acquired at

different time points during the overall acquisition could thus be compared (Fig. 7) and the

consistency of the data set could be validated.

Discussion

A protocol for the parallel transformation of multiple protoplast populations

We have established a pipeline which allows simple and large-scale transformation of

protoplasts with a high number of different plasmids with minimal investments into

instrumentation and consumables. By reducing the plasmid DNA amount necessary to

reach high transformation efficiency by one order of magnitude, it was possible to use

standard small-scale plasmid DNA extraction and purification protocols for the successful

transformation of protoplasts, thus reducing costs and time investment. With an average

transformation efficiency of 45 % (Fig. 2), we reached slightly higher values than

previously reported for mesophyll protoplasts 10,14

. Furthermore, we succeeded in

optimizing the plasmid DNA to cell number ratio. As our system is based on relatively

small cell numbers, standard protoplast isolation with material grown on one Petri dish

(Fig. 1) was sufficient for multiple transformation assays.

Fig. 7 Evaluation of experimental consistency by internal controls in the experimental setup. Shown is

an experiment designed for the quantification of a fluorescent reporter (GFP) upon expression of anti-GFP

artificial microRNAs. A: Repeats of transformations with the same plasmid DNA at different locations on the

plate. Negative control (green), positive control (red) and autofluorescence control (yellow) were repeated 3,

4 and 2 times, respectively B: Pixel intensity measurements on images from the respective samples indicate

variability within one experiment. Bars correspond to median pixel intensity of the cells within one sample;

error bars correspond to standard errors.

1

A

B

C

D

E

F

G

H

2 3 4 5 6 7 8 9 10 11 121

A

B

C

D

E

F

G

H

2 3 4 5 6 7 8 9 10 11 12

A B


The fact that we reached saturation in transformation efficiency at 0.5-1 µg of plasmid

DNA and that the number of transformed cells could not be increased by using a ten-fold

amount of DNA led us to conclude that a part of the protoplast population is recalcitrant to

transfection with plasmid DNA. We can exclude cell size as the defining parameter as we

could see no difference in transformation rates of bigger or smaller cells. A second

possibility is that after DNA uptake, transient expression of the encoded genes is inhibited

in a certain number of cells. At this point the reasons for the divergence within the

population remain elusive.

High-content microscopy of single plant cells

The embedding of protoplasts in a monolayer at the bottom of a microscopic multi-well

slide for the first time offered the possibility to observe and follow plant protoplasts over a

long time interval. Cells embedded in the alginate matrix were unaffected in their viability

and could undergo radial expansion and/or division. The embedding procedure is reliable

and can be applied manually to several samples in parallel. To render the embedding more

suitable for high-throughput approaches with large numbers of samples, semi-automation

of the different steps is necessary. First experiments with a novel nanodrop dispenser

system have been promising in this respect (A. Dovzhenko, K. Voigt, unpublished results).

The iMIC system for image acquisition constituted a crucial component in this

experimental strategy. Due to its precise stage movement and the versatile programming of

the acquisition, this system was ideal for the monitoring of large sample numbers in either

bright field or epifluorescence mode over longer time periods. It has to be pointed out that

due to the massive data loads generated during the imaging process high-throughput

approaches require respective computing capacities. During our experiments, acquisition

of tiles covering the whole plate were not possible and had to be sub-divided into different

parts, limiting the level of automation of the pipeline.

Image-based analysis of cell features in Arabidopsis protoplasts

The CellProfiler™ software offered versatile possibilities to adapt the analysis pipeline to

our specific needs. The automated segmentation of RFP-positive cells worked reliably,

thus increasing the total cell number to be identified and the objectivity of the selection

compared to manual image analysis. The reliability of the selection is depicted in Fig. 4B,

where we compared fluorescence intensities of cells analyzed in an automated

segmentation to that of cells identified manually from the same images.


When dealing with weak fluorescence intensities, quantification of the signal was difficult

due to relatively high background intensity. We had to find a compromise in the

acquisition settings: as the iMIC system we used ran on halogen lamps, lamp intensity was

fixed and could not be adjusted in intensity as in laser- or LED-based systems. An elevated

exposure time would have increased the resolution of the fluorescent signal for the prize of

a prolonged acquisition time. This would have been detrimental when dealing with large

sample numbers. In order to resolve weak fluorescence signals against the background, we

developed a protocol for the measurement of individual background signal around each

identified object. This not only allowed better resolution of weak signals but also led to the

possibility to discard potential changes in lamp intensity over time. However, this method

only applies to weak changes in lamp intensity and cannot compensate more severe

fluctuations.

Although widely used in the animal field, single cell analysis so far has played only a

minor role in plant research. This study presents the first platform for the systematic

microscopic analysis of single plant cells. Our pipeline can be adapted to experimental

needs with respect to the nature of the transiently expressed constructs, the image

acquisition as well as the cell analysis; it therefore constitutes a versatile tool to be used in

addressing questions of cell and molecular biology.



Plant culture

Seedlings for protoplast isolation were grown on SCA medium in a 16-8h dark-light cycle

at 25°C.

Protoplast isolation

Protoplasts were isolated under sterile conditions from leaves of 2-3 week-old seedlings

following a protocol modified from Dovzhenko et al. 17

. In brief, aerial parts were cut

from the roots and imbibed with MMC solution. Plant material was cut with a scalpel and

left in MMC for 1 h at room temperature for pre-plasmolysis. Enzymatic digestion of the

cell wall was performed by incubating the plant material in [MMC, 0.5% cellulase

(Duchefa), 0.5% macerozyme (Duchefa)] for 16 h at 25 °C in the dark. The cell suspension

was centrifuged 10 min at 100g and resuspended in 8 ml MCS, the suspension was

overlaid with 2 ml transformation medium. After centrifugation for 10 min at 100g, cells

were collected at the interphase between MCS and transformation media. Cells were

subsequently washed in 10 ml W5 and total cell number was assessed in a Fuchs-Rosenthal

hæmocytometer. After final centrifugation for 10 min at 50g, the final cell density in

transformation medium was adjusted according to experimental needs.


Protoplast transformation

We used 3x104 to 5x10

4 cells per transformation. The plasmid DNA (dissolved in sterile

dH2O) was placed at the bottom of the well of 96-well 1 ml plates (Greiner Bio-One

Uniblock 1ml) in the respective amounts. Protoplast suspension (30-50 µl, 106 cells/ml)

were added and mixed with the plasmid DNA. Polyethylenglycol

(PEG) 1500 (40%) (Carl ROTH) in a volume equal to the combined volumes of cell

suspension and DNA was added, the mix was incubated at room temperature.

Transformation was stopped after 8 min by addition of transformation medium to a final

volume of 10x volume of the initially added cell solution. When using pre-dried DNA, we

left the cells to settle to the bottom of the well (10 min) and resuspend the DNA before

adding PEG.

Protoplast culture

After the final addition of transformation medium, protoplasts were left to sediment for

1 h. If cells were to be kept in liquid culture after transformation, the transformation

medium was exchanged for the same volume of PCA solution including 3,6-dichlor-2-

methoxybenzoic acid (Dicamba, 3 mg/l, Sigma-Aldrich) and 1-Naphthaleneacetic acid (1-

NAA, 0.5 mg/l, Sigma-Aldrich). For protoplast embedding, transformation medium was

removed and cells were resuspended in 200 µl of a 1:1 mix of alginic acid (2.8 %) and

calcium-free W5M. They were then transferred to an appropriate microscopy plate and left

to sediment for 1 h. Solidification was initiated by addition of 200 µl W5 in small droplets

on top of the cell suspension. After 30 min, supernatant W5 was removed and cells were

washed twice by overlaying the gel with 200 µl PCA for 20 min to wash away excess

calcium ions. After removal of the second washing solution, 250 µl PCA (Dicamba 3mg/l;

1-NAA 0.5 mg/l) was added. After transformation, protoplasts were kept at 25 °C in the

dark for 16h, then returned to a 16/8 dark/light cycle at 25 °C.

Transformation efficiency measurements

We transformed protoplasts with a 5 kb-plasmid comprising a rolD::mCherry expression

cassette and acquired images in bright field and RFP channels 24 h after transformation.

We determined transformation rates by counting living cells on the bright field image and

RFP-positive cells on the RFP image. Statistical relevance was achieved by triple repeats

of the experiment under identical conditions.

Vector construction

pELWMS is based on the pAM-PAT vector backbone (GenBank accession: AY436765.1)

in a Gateway™-compatible form. To gain unique restriction sites, we partially removed the

multiple cloning site by cutting the pAM-PAT plasmid with HindIII and SpeI, then blunted

and re-ligated the vector. We generated pELWMS by inserting a rolD::mCherry::pA35S

cassette into the PmeI site in sense to the Gateway™ expression cassette. Additional

expression cassettes for expression of reporter and target genes were inserted into the

blunted PfoI site outside the T-DNA region.

Microscopy


Plan-APOCHROMAT 10x/0.45 air and Zeiss Plan-APOCHROMAT 20x/0.75 air

objectives. All GFP images and all RFP images were acquired with identical settings using

Metamorph v6.2r4. For automated image acquisition we used an iMIC instrument (Till

Photonics) controlled by Till Photonics Live Acquisition 1.2.2.12. Objectives used were a

Zeiss Plan-NEOFLUAR 10x/0.30 air and a Zeiss Plan-APOCHROMAT 20x/0.75 air. We

acquired up to 63 viewing fields per well in both fluorescent channels using the “tile”


module. For microscopic analysis, cells were transferred to a 96-well plate with extra-thin

bottom (ibidi 15µ-plate 96-well).

Image analysis

We used CellProfiler™ version 1.0.5811 19,20

. For images acquired manually with the Zeiss

Axiovert 200M MAT, the “LoadImages” module was set to “Text-ExactMatch” and GFP

and RFP images were recognized by their respective file name. For images acquired with

the iMIC system, the “LoadImages” module was set to “Order” and GFP and RFP images

were recognized by sequence. As all cameras recorded images in 12 bit depth, images were

rescaled to 16 bit using the “Rescale Intensity” module. Transformed, RFP-positive cells

were identified as objects using the “IdentifyPrimAutomatic” module; objects outside a

diameter range from 40 to 100 pixels were discarded, as were objects in contact with the

image border. No merging of small objects in contact with each other occurred. As

segmentation algorithm, “RidlerCalvart Global” was used 21

; no correction factor or

threshold boundaries were applied. Holes in identified objects were filled.

“MeasureObjectAreaShape” was applied on identified objects. Using the

“FilterByObjectMeasurement” module, objects that did not fulfill the “FormFactor (7)” to

a minimum value of 0.7 were discarded. In order to account for changes in lamp intensity

or background illumination during the experiment, individual background intensities for

each object were measured. To this end, the “ExpandObject” module was used to increase

the identified objects by pixels, this step was repeated on the expanded object. Using the

“IdentifyTertiarySubregion”, the “Object+6pixels” was subtracted from the

“Object+9pixel” area, resulting in a ring that corresponded to the background surrounding

the actual object. By applying the “MeasureObjectIntensity” module to the corresponding

GFP-channel image, pixel intensities in the primary object as well as the net background

signal in the newly defined surrounding ring were measured. Data were exported to a “.txt”

file using the “DataExport” function of CellProfiler™, then imported into Microsoft®

Excel 2003™ for further processing.


References

1. Binding, H. Regeneration und Verschmelzung nackter Laubmoosprotoplasten. Z.

Pflanzenphysiol. 55, 305–321 (1966).

2. Cocking, E.C. A method for isolation of plant protoplasts. Nature 187(1960).

3. Davey, M.R., Anthony, P., Power, J.B. & Lowe, K.C. Plant protoplasts: status and

biotechnological perspectives. Biotechnol Adv 23, 131-71 (2005).

4. Yoo, S.D., Cho, Y.H. & Sheen, J. Arabidopsis mesophyll protoplasts: a versatile

cell system for transient gene expression analysis. Nat Protoc 2, 1565-72 (2007).

5. Davey, M.R., Anthony, P., Power, J.B. & Lowe, K.C. Protoplast Applications in

Biotechnology. 1061 - 1064 (Taylor & Francis, 2004).

6. Aoyagi, H. & Tanaka, H. Development of simple methods for preparation of yeast

and plant protoplasts immobilized in alginate gel beads. Biotechnology Techniques

13, 253-258 (1999).

7. Nagata, T. & Takebe, I. Plating of isolated tobacco mesophyll protoplasts on agar

medium. Planta 99, 12-20 (1971).

8. Sheen, J. Signal transduction in maize and Arabidopsis mesophyll protoplasts.

Plant Physiol 127, 1466-75 (2001).

9. Harder, N. et al. Automatic analysis of dividing cells in live cell movies to detect

mitotic delays and correlate phenotypes in time. Genome Res 19, 2113-24 (2009).

10. Fujikawa, Y. & Kato, N. Split luciferase complementation assay to study protein-

protein interactions in Arabidopsis protoplasts. Plant J 52, 185-95 (2007).

11. Ehlert, A. et al. Two-hybrid protein-protein interaction analysis in Arabidopsis

protoplasts: establishment of a heterodimerization map of group C and group S

bZIP transcription factors. Plant J 46, 890-900 (2006).

12. Birnbaum, K. et al. Cell type-specific expression profiling in plants via cell sorting

of protoplasts from fluorescent reporter lines. Nat Methods 2, 615-9 (2005).

13. Birnbaum, K. et al. A gene expression map of the Arabidopsis root. Science 302,

1956-60 (2003).

14. De Sutter, V. et al. Exploration of jasmonate signalling via automated and

standardized transient expression assays in tobacco cells. Plant J 44, 1065-76

(2005).

15. Jaquinod, M. et al. A proteomics dissection of Arabidopsis thaliana vacuoles

isolated from cell culture. Mol Cell Proteomics 6, 394-412 (2007).

16. Bargmann, B.O. & Birnbaum, K.D. Positive fluorescent selection permits precise,

rapid, and in-depth overexpression analysis in plant protoplasts. Plant Physiol 149,

1231-9 (2009).

17. Dovzhenko, A., Dal Bosco, C., Meurer, J. & Koop, H.U. Efficient regeneration

from cotyledon protoplasts in Arabidopsis thaliana. Protoplasma 222, 107-11

(2003).

18. Shaner, N.C. et al. Improved monomeric red, orange and yellow fluorescent

proteins derived from Discosoma sp. red fluorescent protein. Nat Biotechnol 22,

1567-72 (2004).





21. Ridler, T.W. & Calvard, S. Picture thresholding using an iterative selection method.

Transactions on Systems, Man and Cybernetics 8, 630-632 (1978).

Claude Becker ACKNOWLEDGEMENTS 99

- ACKNOWLEDGEMENTS -

This work could not have been accomplished without the help of colleagues, collaborators

and friends. I would like to thank the following people for the respective part they

contributed to the work:

- Prof. Dr. Klaus Palme for his support, suggestions and guidance, for giving me the

freedom to test new ideas in the development of the project, for providing the

technical and financial means as well as for many helpful discussions

- Dr. Alexander Dovzhenko for contributing his expertise in the protoplast work, for

numerous discussions and helpful suggestions

- Karsten Voigt for the IT support and his dedicated work on the CellProfiler

pipelines

- Dr. Dominik Lenz for sharing his expertise in image-based cytometry

- Francesco Pinosa for being a “friendcito” and for his work on the

immunolocalizations

- Prof. Dr. Rolf Backofen, Dr. Anke Busch and Sita Lange for their dedicated work

on the bioinformatics side, for many discussions and critical analysis of the data

- Katja Rapp for excellent technical support

- Dr. Filipa Santos Schröter for critical reading of the manuscript

- Margitta Eismann for help with the plant-related work

- Dr. Christina Neu for helpful suggestions and many fruitful discussions

- Dr. Cristina dal Bosco for help in the protein work

- all members of the Palme lab for the agreeable working atmosphere and helpful

suggestions

- my parents for their support, both moral and financial

I am grateful for the financial support received over the years to conduct this thesis. This

work was funded by the following institutions:

- Landesstiftung Baden-Württemberg (Forschungsprogramm “RNS/RNAi“)

- GRK 1305 “Signal Systems in Plant Model Organisms” at the University of

Freiburg

- BIOSS excellence cluster at the University of Freiburg

- Fonds National de la Recherche, Luxembourg

- Ministère de la Culture, de la Recherche et de l’Enseignement Supérieur,

Luxembourg

Claude Becker ACKNOWLEDGEMENTS 101

To Anja

For your infinite patience, your understanding and your never-ending support.

Thank you for being there.

Claude Becker APPENDIX 103

- APPENDIX -

Media and solutions

Component Company Final concentration

SCA (pH 5.8, autoclaved)

B5 salts Duchefa 3.052 g/l

B5 vitamins (100x) to 1x final concentration

MgSO4 Carl ROTH 4 mM

sucrose Carl ROTH 2 % (w/v)

gelrite Carl ROTH 0.4 % (w/v)

MMC (pH 5.8, autoclaved)

MES Sigma-Aldrich 1 mM

CaCl2 Merck 10 mM

mannitol Sigma-Aldrich 0.48 M

MCS (pH 5.8, autoclaved)

MES Sigma-Aldrich 1 mM

CaCl2 x 2H2O Merck 20 mM

sucrose Carl ROTH 14.5 % (w/v)

Transformation medium (pH 5.8, autoclaved)

MgCl2 Merck 15 mM

MES (salt-free) Sigma-Aldrich 0.5 mM


W5 (pH 5.8, filter-sterilized)

CaCl2 Merck 125 mM

NaCl Carl ROTH 150 mM

KCl Sigma-Aldrich 5 mM

glucose Sigma-Aldrich 5 mM

W5M (pH 5.8, filter-sterilized)

MgCl2 Merck 125 mM

NaCl Carl ROTH 150 mM

KCl Sigma-Aldrich 5 mM

glucose Sigma-Aldrich 5 mM

Alginic acid (pH 5.8, autoclaved)

MES (salt-free) Sigma-Aldrich 1 mM

MgCl2 Merck 10 mM



alginic acid Sigma-Aldrich 2.8 % (w/v)

Claude Becker APPENDIX 104

B5 vitamins (100x)

myo-inositol Merck 1 % (w/v)

pyridoxine-HCl Duchefa 0.01 % (w/v)

thiamin-HCl Duchefa 0.1 % (w/v)

nicotinic acid Duchefa 0.01 % (w/v)

PCA (pH 5.83, filter-sterilized)

B5 salts macro Duchefa 3.052 g/l


CaCl2 Merck 0.7 mM

MES Sigma-Aldrich 0.5 mM

casein hydrolysat Sigma-Aldrich 0.01 %

glutamine Sigma-Aldrich 50 mg/l

sucrose Carl ROTH 2 % (w/v)

glucose Sigma-Aldrich 80 g/l (to 550 mOsm)

Dicamba Sigma-Aldrich 3 mg/l

1-NAA Sigma-Aldrich 0.5 mg/l

PEG (40%, filter-sterilized)

Ca(NO3)2 Sigma-Aldrich 413 mg

mannitol Sigma-Aldrich 1275 mg

dissolve in 17.5 ml H2O

PEG (1500) 10 g

adjust pH with 0.1M KOH to 9.75

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