Protein Engineering

for Enzyme Catalysis with Microgels

Lehrstuhl für Biotechnologie, RWTH Aachen University und DWI-Leibniz Institut für Interaktive Materialien

Prof. Dr. Ulrich Schwaneberg

Monschau SFB Mikrogele Summer School 2018, 11.7.2018

Microgels as Versatile Containers for

Immobilisation of Enzymes

Motivation: Enhance performance of enzymes

- Avoid deactivations e.g. in organic solvents

- Avoid degradation e.g. proteolytic digest

- Recovery in processes for reuse

- Efficient diffusion

- General applicable

- High compound loads possible

Immobilisation of Enzymes

3Chem. Soc. Rev., 2013, 42, 6223-6235

4

Polymer-Biomacromolecule

Conjugates

-fast reactions in water

-no toxic by-products

-formation of stable covalent bonds

-orthogonal reactions

Sortase-Mediated Surface Functionalization of Stimuli-Responsive Microgels

5Internal manuscript No. 188 Gau‡, Mate‡, Zou, Oppermann, Töpel, Jakob, Schwaneberg* and Pich* . Biomacromolecules. 2017;18,2789–2798.

Sortase-mediated conjugation of eGFP on the surface of PVCL/GMA

AFM images and confocal images of (a) PVCL/GMA-LPETG-microgels (no sortase) and (b) PVCL/GMA-LPETG-eGFP hybrid (withsortase ligation)

Conclusions:

• SrtA-mediated ligation enabled the efficient andcontrollable decoration of the PVCL microgel surfacewith the model protein GGG-eGFP

• Sortase-mediated ligation is a very promising andpowerful tool for the surface functionalization ofmicrogels with biomolecules which opens upnumerous possibilities to develop microgels withtailored properties for biomedical and otherapplications

Acknowledgements: EG, AT and AP thank Volkswagen Foundation and DFG Collaborative Research Center 985 “Functional Microgels and Microgel Systems” for financial support. ZZ gratefully acknowledges the Chinese Scholarship Council (CSC) for his PhD fellowship.

Elisabeth Gau Diana M. Mate

Facile approach for encapsulation of enzymes in nanogels

Tunable Enzymatic Activity and Enhanced Stability of Cellulase Immobilized in Biohybrid Nanogels

6167 Peng, H., Rübsam, K., Jakob, F., Schwaneberg, U., Pich, A. BioMacromolecules, 2016

Synthetic Procedure To Obtain Biohybrid Nanogels via Cross-Linking in w/o emulsion

poly(N-vinylpyrrolidone-co-N-methacryloxysuccinimide)

How is the biocatalytic activity and stability of trapped protein

influenced by the chemical structure of nanogel network?

7167 Peng, H., Rübsam, K., Jakob, F., Schwaneberg, U., Pich, A. BioMacromolecules, 2016

Tunable Enzymatic Activity and Enhanced Stability of Cellulase Immobilized in Biohybrid Nanogels

CD spectra of cellulase biohybridnanogels CNG4, CNG6, CNG8, and CNG10

Secondary structures of the immobilized cellulase is altered with increase of crosslink

density

Cellulase nanogels show decreased activity compared to free cellulase

Cryo-FESEM of biohybrid nanogels CNG4

Specific activities of biohybrid nanogels CNGn (n = 4, 6, 8, and 10)

Residual activities of free cellulase, CNG4, CNG6, CNG8, and CNG10, incubated with organic solvents

Cellulase nanogels demonstrate compared to free cellulase

significantly improved stability

organic solvents chaotropic agents storage stability

Biohybrid nanogels with varied degree of crosslinking density (CNG4, CNG6, CNG8, and CNG10) were generated

Reversible Deactivation of Enzymes (Cellulase) by Redox-Responsive Nanogel Carriers

8165 Peng, H., Rübsam, K., Jakob, F., Pazdzior, P., Schwaneberg, U., Pich, A. Macromol. Rapid Commun., 2016

Highly efficient enzyme encapsulation and reversible modulation of enzyme activity by novel redox-responsive polymeric nanogels

Figure 1. Enzyme encapsulation/deactivation in polymeric nanogels followed by release/activation under reducing conditions. DDT: dithiothreitol, PMT: pentaerythritol tetrakis (3-mercaptopropionate), EED: 2,2′-(ethylenedioxy)diethanethiol

co-polymer

self-assembly

add cross-linker

add DTT

cross-linker

proteins

Aggregate formation (trapping of enzyme)

Protein encapsulated nanogels (inactive)

Protein encapsulated nanogels (active)

9165 Peng, H., Rübsam, K., Jakob, F., Pazdzior, P., Schwaneberg, U., Pich, A. Macromol. Rapid Commun., 2016

Reduced activity of cellulase, when it is encapsulated in the

nanogels

Cellulase activity is rapidly recovered in DTT solution

Reversible Deactivation of Enzymes by Redox-Responsive Nanogel Carriers

Ligh

t sc

atte

rin

g in

ten

sity

RH/nm

DLS meassurement of PNG1 degradability in presence of 10 mM DTT

Degradation of generated protein nanogels by addition of

DTT

Particle size remains the same when no DTT was

supplemented

PNG – protein nanogel; NG - nanogel

Cellulase activity is determined by substrate diffusion process

in nonreductive conditions

Increased acitivity of PNG incubated with DTT can be

attributed to release of cellulase from nanogel

Incubation timeSpec

ific

nan

oge

l act

ivit

y [U

/mg]

Determination of protein nanogel cellulase activity (4-MUC assay) w/o 10 mM DDT

FRET: Chromophore release from 2 differently loaded nanogels; upon addtion

of DTT emmision intensity shifts immediately

Wavelength [nm]

No

rmal

ized

em

mis

sio

n

inte

nsi

ty

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Protein Engineering Worlds

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Protein Engineering: Focused vs Random mutagenesis

Shivange, A., Marienhagen, J., Schenk, A and Schwaneberg, U. (2009). Advances in Generating Functional Diversity, Curr. Opin. Biotechnol., 13, 19-25.

Localized & rationally addressable properties• Activity / Selectivity• Substrate profile• Thermal resistance

• ?pH profile?

Non-understood properties• Organic solvent• Ionic liquid• pH stability• Molar substrate/product

concentrations….

Mutagenesis methods for diversity generation in directed evolution

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Why is focused mutagenesis necessary?

● Methods for ideal diversity generation: 100 aa: 20100= 1.267*10124 variants

● 1.000.000 variants screening: represents in [%] of sequence space

<0.0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001 %

● Peptide with 6 aa= 20*20*20*20*20*20= 64 000 000 variants

Screening limit of state of the art technologies

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Random mutagenesis

● Key technologies are diversity generation and high throughput screening

● Traditional directed evolution:● Low mutagenesis frequency: 1 to 5 mutations per 1000 bp usually 1 to 3 amino acid exchanges● Small library size sampled: 1000-3000 clones

● Three to six iterative cycles often >6 amino acid substitutions in most beneficial variants

● Usually no molecular understanding of improved property

● Time requirements usually 1 to 2 years including screening development

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Directed protein evolution

15

Classification of random mutagenesis methods

Wong, T. S., Zhurina, D. and Schwaneberg, U. (2006). The diversity challenge in directed protein evolution, Combinatorial Chemistry and High Throughput Screening, 9, 271-289.

Limitations of epPCR

Polymerase bias Only one nt of a codon is mutated

Organisation of the genetic code

63 of 100 mutations areA to G or T to C mutations

150 of 380 possible amino acid exchanges

1.67 codons per “aromatic” amino acid

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Why is throughput important?

MAP benchmarking on the protein level!

12

Consequences of bias on the protein levelExample: Subtilisin from Bacillus lentus (1GCI), epPCR (balanced dNTPs + Mn2+)

From: ● Schenk, A., Wong, T. S., Roccatano, D., Hauer, B. and Schwaneberg, U. (2006). SeSaM (Sequence Saturation

Mutagenesis): Eine Methode zur Sättigungsmutagenese eines Genes, BIOspektrum, 3 , 277-279.● Wong, T. S., Roccatano, D., Zacharias, M. and Schwaneberg, U. (2006). A statistical analysis of current random

mutagenesis methods for directed protein evolution, J. Mol. Biol. 355, 858-871 (cover page).

● Mutagenic hot spots and barely

mutated regions

● Low diversity and preference

for aa-substitutions to chemically

similar ones

13

MAP 3D

Verma,R., Schwaneberg, U., and Roccatano, D. (2012). MAP2.03D: A sequence/structure based server for protein engineering. Synth. Biol., 1, 139-150.

State of the art

What do we find in a traditional directed evolution experiment?

14

BSLA lipase (181 aas): State of the art random mutagenesis by epPCR

• epPCR library with low mutations frequency (3.1 per kb) sequencing of 1000 mutations

• epPCR library with high mutations frequency (11.7 per kb) sequencing of 1000 mutations

How many of the 181 amino acid positions are found to improve ionic liquid resistance BMIM-Cl?

15 positions epPCR-low18 positions epPCR-high

Zhao J, Kardashliev T, Joëlle Ruff A, Bocola M, Schwaneberg U. (2014). Lessons from diversity of directed evolution experiments by an analysis

of 3,000 mutations. Biotechnol Bioeng, 111(12), 2380-2389.

epPCR-high

epPCR-low

What do you find?

0-4 amino acid substitutions of 19 possible substitutions

15

22

What potential of improvement is obtainable?

What potential for improvement is obtainable?

Library of BSLA variants is generated in which

• every variants habors one amino acid exchange

• the FULL natural diversity is covered (20*181= 3620 variants)

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Case study BSLA lipase (181 aas): focused mutagenesis (with KE Jaeger)

• Saturation mutagenesis library of each position• Extensive sequencing • All 341 missing substitutions were manually

prepared via site directed mutagenesis• Screening of eight properties• Sequencing of the best 20 clones per position to

gain a molecular understanding of interactions

For eight properties we can have the information on how many positions contribute to property improvement and what improvement is obtainable with ONE amino acid exchange

How many of the 181 amino acid positions contribute to improve ionic liquid resistance BMIM-Cl?

104 positions>50 %

Bacillus subtilis BSLA181 amino acids = 181 tripletts

64 x 181 = 11,584 mutant genes

19 x 181 = 3,440 variant proteins

VJ Frauenkron-Machedjou, A Fulton, L Zhu, C Anker, M Bocola, KE Jaeger and U Schwaneberg, ChemBioChem, 2015,

16(6):937-945

20

Similar trends for other properties: Organic solvent resistance: out 181 positions

No. of beneficial positionsDMSO Dioxane TFE

SSM 107 75 74

epPCR-low 24 11 14

epPCR-high 29 13 19

104 positions40 to 59 % of positions

contribute again!

Location of beneficial positions for dioxaneexposed buried

WT all positions 71% 29%

SSM 81% 19%

epPCR-low 82% 18%

epPCR- high 92% 8%

a) SSM TFE

Strong preference forcharged and aromatic

substitutions

Exposed positionspreferred

21

26

Number of substitutions

Markel*, U., Zhu*, L., Frauenkron-Machedjou, V. J., Zhao, J., Bocola, M., Davari, M. D., Jaeger, K.-E., Schwaneberg, U.

(2017). Are Directed Evolution Approaches Efficient in Exploring Nature’s Potential to Stabilize a Lipase in Organic

Cosolvents? Catalysts, 7, 142

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Coverage of amino acid substitutions patterns for P450 BM3 heme domain

error-prone PCR SeSaM-TV SeSaM-TV-III

See: www.sesam-biotech.com

Main conclusions

III. A higher throughput and smarter evolution strategies are required!

II.Libraries with one amino acid substitution per variant thatcovers all natural diversity are a prerequiste to understandgeneral principles to stabilize enzymes

I. State of the art directed evolution experiments identify only a small fraction of beneficial positions (<20 %)

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Key: Balance throughput and time requirement (5 to 6 aas)

Thursday, July 26, 2018

29

Time efficient protein engineeringKey: Balance throughput and time requirement (5 to 6 aas)

in Concepts: Knowledge gaining directed evolution: KnowVolution

Cheng, F, Zhu, L, Schwaneberg, U (2015) Directed evolution 2.0: improving and deciphering enzyme properties, ChemComm, 51(48):9760-72.

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Focused mutagenesis

State of the art

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Focused Mutagenesis

0

500000

1000000

1500000

2000000

2500000

3000000

3500000

1 AS 2 AS 3 AS 4 AS 5 AS

20 400 8000 160000

3200000

Pro

tein

var

ian

ts

Fragment Amplification Primer Name Primer Sequence (5’-3’)

A2-Vector-A1 E31Fw

E31Rv

ctagtgcttcagCGTAAGGGGCAAG

gataaccactcgMNNCAAAGTGTAACCCGTC

B T77Fw

T77Rv

cgagtggttatcTTGAGCCGCCATG

catagaagccgccCATCAGMNNCACTAATTGCGC

C K139Fw

K139Rv

ggcggcttctatgGTGATTATTTCCG

gaaacagtggatcAACCTTMNNCAAATCAGCCTG

D G187Fw

G187Rv

gatccactgtttcACCCCGTCGAAG

cagtgaaattgagAATCTCMNNCATCTGGGCAAATG

E V298Fw

V298Rv

ctcaatttcactgCTTCCCCCTATTGC

ctgaagcactagCGCCGTMNNAATCTGTTGCAAC

C/D/E/A2-Vector-A1 K139Fw

D52Rv

ggcggcttctatgGTGATTATTTCCG

ccacttatccggTGTGACMNNATTCATTAACTCTG

B’ D77Fw’

T77Rv’

ccggataagtggCCTCAATGGCCGGTAC

catagaagccgccCATCAGMNNCACTAATTGCGC

Colony PCR Forward primer

Reverse primer

TAATACGACTCACTATAGGG

TCCAAAAGAAGTCGAGTGG

1

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OmniChange: Focused mutant library generation (EU patent granted)

Vector A1A2 EDB C

Vector A1 A2EDB C Vector

D52Rv T77Rv K139Rv G187Rv V298Rv

Vector A1A2 EDB C

Amplification by PCR, DpnI digestion and pufication

Cleavage (6 mM I2/EtOH; 5 min at 70 C)

Hybridization (5 min at 20 C)

Transformation

V

V

V

V

V

V

START

START

START

STOP

STOP

STOP

* * * * *

* * *

* * * * *

D52FwT77Fw K139Fw G187Fw V298Fw

*

*

**

*

*

* **

*

*

* **

*

*

Step 1

Step 3

Step 2

Step 4

*

Position G31 T77 K139 G187 V298 1 aag aag aaa aat aat 2 aag aat aag aag aat 3 aat acg aag aag aat

4 aat acg aag aag aat 5 acg act aat acg act 6 acg agt acg acg act 7 acg agt acg act agt

8 acg agt agg act atg 9 acg atg agg act att

10 acg att agg act cag

11 acg cag agg agg cag 12 act cag agt agt cat 13 atg cat agt agt cat 14 cat cat agt atg ccg

15 ccg ccg agt att cct 16 ccg ccg atg cag cct 17 ccg ccg att cag cct 18 ccg cgg att cag ctg

19 ccg cgg cag cat ctg 20 cct ctg cag ccg ctt 21 cct ctg ccg cct ctt 22 cct ctg ccg cgg gag

23 cct ctt ccg cgt gag 24 cct gat cct ctg gag 25 cct gcg ctg ctg gag

26 cct gcg ctt ctg gat 27 cgg gcg gag ctt gcg 28 ctg gcg gag gag gct 29 ctg gct gtg gag ggg

30 ctg ggg gcg gat ggg 31 gag ggt gcg gat ggt 32 gag ggt gcg gct ggt 33 gat gtg gct gct gtg

34 gat gtg gct ggc gtg 35 gcg gtt ggg ggt gtt 36 gct tag tat ggt tag 37 gtt tag tat gtg tat

38 tag tat tcg gtt tcg 39 tat tat tcg tct tct 40 tat tcg tcg tgg tgg

41 tat tcg tcg tgg tgg 42 tat tcg tct ttg tgt Dennig, A., Shivange, A.V., Marienhagen, J., and Schwaneberg, U. (2011). OmniChange: The Sequence

Independent Method for Simultaneous Site-Saturation of Five Codons, PLoS ONE 6(10): 26222.bt.

No gel extraction stepNo final PCR applification stepNo additional sequencesNo limitation by aa-positions

3 200 000 variants generated in one afternoon

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Can those numbers be screened?

35

iVDT-Basistechnologie-Platform High throughput screening by flow cytometry

BDInflux

• Analyzing of 200.000 and sorting of 70.000 events per s-1

( running at a few thousands per s-1)

• Sorting of 10.000.0000 events per hour

• Analysis and sorting based on fluorescence

• Enrichment in the active enzyme population as abenchmark

Enables novel directed evolution strategies withhigh mutational loads for efficient identification of beneficial amino acid positions

Best use as PRESCREENING system: sorting of ~2000 beneficial variants in MTPs/agar plates

36

BMBF Basistechnologie Project iVDT:

Highlights

• Coupled enzymatic reaction (phytase – glucose oxidase)

• E. coli cells expressing active phytase form a fluorescent hydrogel aroundStrategy

Scanning force

microscopy

Confocal

microscopy

E. coli cells

phytase (-)

E. coli cells

phytase (+)

Phytase activity

before sorting

Phytase

activity after

sorting

Activity distribution

Whole cell: Fluorescent hydrogel-based FACS platform for hydrolytic enzymes

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A fluorescent hydrogel-based FACS screening platform for hydrolytic enzymes

Pitzler, C., Wirtz, G., Vojcic, L., Hiltl, S., Böker, A., Martinez, R.,

Schwaneberg, U., Chem Biol. (2014) 21 (12):1733-42

BMBF Basistechnologie Project iVDT

Proof of concept for phytases:

Fur-Shell technology was advanced for three additional hydrolases: cellulase, esterase, and lipase

Simple handing

High throughput screening toolbox for directed hydrolase evolution

Esterase variant with 7-fold increase in kcat and 2-fold reduced KM

Traditional directed evolution yield often 1.5-2.5-fold improvement per round

Toolbox for hydrolases

Lülsdorf, N., Pitzler, C. Biggel, M., Martinez, R., Vojcic, L. and

Schwaneberg, U. A flow cytometer-based whole cell screening toolbox

for directed hydrolase evolution through fluorescent hydrogels, Chem.

Commun., 2015, 51(41):8679-82.

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From whole cell to cell free

39

Part I – Optimization of in vitro cellulase production in emulsions

Amount of

DNA

25°C lin. DNA

(30°C)

4 h

pIX3.0RMT7

vector°C

Substrate

concentration

0.328 µM DNA

0.656 µM DNA

0.656 µM

DNA

0 mg/ml BSA 1 mg/ml BSA

2 mg/ml BSA

Additives e.g.

BSA

1 mg/ml

BSA

0.46 mM FDC

Substrate

concentration

40

Validation of the uHTS-IVC platform for directed cellulase evolution

- Screening of >1,2 Mio. events- MTP analysis of 528 variants with 4-MUC assay revealed 33 cellulase variants improved

activity compared to parent- Most promising variants were selected for rescreening- Best identified variant CelA2-H288F-M1 (N273D/N468S) was purified and kinetically

characterized

Characterization in MTP format revealed the 13-fold improved cellulase variant M1 Flow cytometer-based uHTS-IVC technology platform successfully validated

kcat

[min-1]KM

[µM]kcat/KM

[min-1 µM-1]

Specific activity[U mg-1]

Amino acid substitutions

CelA2-WT 0.11 (± 0.02) 48.37 (± 24.30) 0.002 16.57 (± 3.13) -

CelA2-H288F 0.50 (± 0.02) 8.95 (± 1.62) 0.056 72.62 (± 3.21) H288F

CelA2-H288F-M1 1.52 (± 0.04) 9.66 (± 1.19) 0.157 220.6 (± 6.71) N273D/H288F/N468S

Körfer, G., Pitzler, C., Vojcic, L., Martinez, R., Schwaneberg, U. (2016) In vitro flow cytometry-based screening platform for cellulase engineering,

Scientific Reports, 6, 1-12. DOI: 10.1038/srep26128.

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iVDTv2:Cellulase evolution: OmniChange library using in vitro flow cytometer platform

Georgette

Körfer

-In vitro expression in (w/o/w) emulsion and screening of 36,757,972 events by flow cytometer-Sorting of 395,229 events

Reanalysis of sorted sample revealed 30-fold enrichment of active fraction

Variantskcat

[min-1]KM

[µM]

kcat/KM

[min-1

µM-1]

Specific activity[U mg-1]

Amino acid substitution

CelA2-WT 0.11 (± 0.01) 22.53 (± 4.78) 0.005 16.27 (± 1.04) -

CelA2-H288F 0.58 (± 0.02) 7.66 (± 1.12) 0.075 83.87 (± 2.89) H288F

CelA2-H288F-M3 4.65 (± 0.26) 51.19 (± 7.55) 0.091 674.50 (± 38.17) H288F/H524Q

M3 shows 41-fold higher specific activity compared to CelA2-WT Combinatorial effect between F288 and Q524 (N524, M524) successfully identified

Kinetic characterization:

Summary

KnowVolution a strategy to balance throughput and time requirement (5 to 6 aas)

Barely exploit the potential of protein sequence space

Main technical limitation: throughput screening technologies

Microgels enable to the converge the worlds of biocatalysis and chemical catalysis

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Towards understanding structure-function relationships ~60 PhD, post-docs, staff

Thank you!

Questions?