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Normal operating range of the microbial community under potatoInceoğlu, Özgul

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Chapter 8

General Discussion

134

Impact of plants (including GM plants) on the soil microbiota

It has been suggested that each soil harbors its own characteristic microflora (28, 63).

Furthermore, it has been shown that the community structure and diversity of the soil

microbiota are important determinants of the stability of key functions of agro-

ecosystems, even though the relationship between the functioning of agro-ecosystems

and soil microbial diversity is not well defined yet (51). Soil type, nutrient status, pH,

moisture and plant factors (e.g. plant species and age) can affect the abundance,

community composition and activities of soil microorganisms (31). In fact, plants are the

most important contributors to the formation of organic matter in soil, as a result of their

release of nutrients, mucilages and complex polymers. Thus, "hot spots" for microbial

growth and activity form in zones around plant roots, which are collectively called the

rhizosphere. However, the local interactions between plant roots and the soil microbiota

are still poorly understood (11), in spite of the fact that the composition and quantity of

particular carbonaceous substrates in root exudates are important. These may vary

depending on plant species, rhizosphere microsite location and plant growth stage (91).

Due to changes in the exudation patterns over the time of plant growth, the composition

and activity of the rhizosphere microflora can also be altered as a function of time (36,

91). The rhizosphere microbiota is further influenced by plant species type as well as by

the genetic make-up of a plant species (15, 53, 68, 74, 94).

Depending on the objective of the modification, genetically modified (GM) plants

can have great potential to advance agriculture. On the other hand, there are concerns

about the potential ecological effects of GM plants intended for routine cropping. For

instance, GM plants might exert undesirable effects on soil organisms, in comparison to

the parent plant. Such effects might be related to changes in root exudation patterns,

plant residues and even to changed agricultural management practices that go with the

genetic modification (49). In previous studies, transgenic potatoes carrying traits for

antibacterial activities or altered starch composition have been shown to affect the

rhizosphere microbial community (57, 71, 72). However, the effects were found to be of a

magnitude that was comparable with other factors such as soil type and plant genotype

(57, 71).

GM plants have been shown to exert variable effects on the soil ecosystem, which

are often relatively minor compared with the impacts of differences in cultivars or those

associated with biotic and abiotic factors. Thus, determinations of the natural variation in

a cropping system, in which effects of cultivar differences are also considered, provide

valuable baseline reference data (47). The effects of GM plants should ideally be

considered in comparison to the baseline, establishing the so-called normal operating

conditions of functioning (the normal operating range or NOR) of the living soil under

cultivation.

135

This study

The main idea behind the work executed in the context of this thesis was to (1) determine

the variation among soil microbiological parameters as a result of cropping of a series of

different potato cultivars, and (2) weigh the putative effects of GM potato plants to those

of the selected cultivars. This way, as a first outcome, an assessment of the NOR of potato

cropping would become tangible. In addition, the question whether the putative effects of

the GM plant remained within or reached outside the NOR would receive an answer. We

placed an emphasis on the assessment of the overall bacterial community composition as

well as on that of individual microbial populations as these are affected by plants (42).

For the experiments, six different potato cultivars (Aveka [A], Aventra [Av], Karnico

[K], Modena [M; modified from Karnico for low amylose content of the tubers] (16),

Premiere [P] and Désirée [D]) were used. Cultivars A, Av, K and M produced tubers with

high starch contents and had a low and/or medium growth rate, whereas cultivars P and D

yielded tubers with relatively low starch contents and had high growth rates. The different

cultivars had different parental cultivars in the first generation, so that their overall

pedigree was complex. For instance, cultivar A was related to D in the fifth generation and

to K in the third generation (90).

Which bacterial community DNA extraction method gives the most representative results?

For the current study, we tried to establish a soil DNA extraction method with minimal

bias with regard to the yield of DNA pertaining to the key bacterial communities studied.

The soil DNA extraction method has been suggested to be the major determinant of the

apparent bacterial diversity and community structure in a soil sample (4, 5). Thus, at the

beginning of each study, the best extraction method for the purpose of the study should

be determined. Next, standardized methods must be used for all subsequent elements of

the study. The suitability of four selected soil DNA extraction methods to obtain

representative DNA from three agricultural soils of divergent texture, organic matter (OM)

content and pH was thus assessed. We confirmed that the soil DNA extraction method

was indeed a major determinant of the apparent bacterial diversity and community

structure. Strikingly, different new or already known bacterial groups were found in the

same soil as a result of something as simple as the application of a different soil DNA

extraction method. Specifically, the so-called Powersoil (P) method was shown to directly

extract large amounts of DNA of sufficient purity from the three soils, enabling direct PCR-

based molecular analyses. Across methods and samples, the superior yields produced by

method P over the enzymatic lysis based C (CIAT) method confirmed previous data on soil

DNA extraction biases (46, 57, 59). Method P was thus suggested to offer a good choice

for the purpose of the current study in two soils, as it quite consistently yielded high

amounts of DNA and the resulting PCR-DGGE patterns revealed high apparent bacterial

diversities.

136

Is PCR-DGGE sensitive enough to show the effect of environmental factors on the soil bacterial community?

During the work, PCR-DGGE was used as a standard tool to assess the soil microbial

community structures across soils and potato cultivars. In previous studies, PCR-DGGE had

been shown to represent a reliable tool for the assessment of differences or changes in

microbial community structures, especially when those occur in the most abundant

organisms (34, 60). On the other hand, there are limitations of the approach, as it detects

primarily the most abundant ribotypes (62). Moreover, the possible existence of multiple

gene copies in a single organism could present problems of interpretation. As our research

questions addressed the relative changes in the community structures of dominant

organisms, these caveats were considered to not strongly influence the overall results and

interpretations obtained in the study. Indeed, assays like PCR-DGGE have previously

proven to be sensitive enough to reveal changes in a soil community as a result of a

perturbation (13, 61, 87). In the current study, PCR-DGGE also provided a useful indicator

of changes arising from different environmental factors, i.e. the presence of a rhizosphere,

the plant growth stage and time in the season. Indeed, our aim was to find indicators that

are sensitive to such environmental impacts, allowing us to monitor the cropping system

in respect of influences from the plant (cultivar) and the environment.

What are the major drivers of the bacterial communities associated with different potato cultivars?

As indicated earlier, soil bacterial communities are affected by factors like soil

characteristics, environmental conditions and crop management practices like rotation

and crop residue removal (30, 54). This complexity of factors is almost prohibitive to a

detailed understanding of the impact of each single factor. In some cases, plant species

type may have a greater influence on the bacterial community composition of a soil than

soil type (31, 95). On the other hand, the effect of soil type on the bacterial community

may be superior to the effects from plant species type in other cases (24, 86). In Chapters

3-5 and 7, we assessed the dynamics in the abundance, diversity and community structure

of selected soil bacterial communities as a function of plant cultivar type, plant growth

stage and soil type, using six potato cultivars in two soils of different texture.

Accordingly, in Chapter 3 the bacterial community changes were observed over

time in the bulk soil of two fields (B-low organic, V-high organic). Such community changes

in bulk soil, especially between the pre-planting and young plant stages, have previously

been suggested to occur (44). Interestingly, in our study more drastic changes were

observed in the V soil after one year. We cogitated that this change might have been

caused by the heavy water accumulation in this field the year after harvesting, which was

related to a water-impermeable layer that was present at about 80 cm depth in this soil

(Chapter 3). Thus, in this particular case, the changes in the bacterial community

structures that were observed might be explained by differences in water contents and

oxygen limitations that had occurred during the water logging.

137

Besides, both the B and V fields were under crop rotation. The B soil was under

short rotation, including barley and potato. In order to better understand the effect of

seasonal variation on the bacterial diversity in the B soil, clone libraries of bulk soils from

six different time points (spanning three years) were compared. The time points were

April 2008- before potato planting, May 2008 – young potato plant, June 2008 – flowering,

September 2008 - senescence, December 2008 – after removal of plants, July 2009 –

barley flowering, May 2010 - young potato plant, June 2010 – flowering and September

2010 – senescence (Chapter 7). The six libraries varied in the estimates of bacterial

richness based on the CHAO1 richness estimator. Specifically, the richness in the bulk soil -

December 2008 sample revealed the highest value (86), whereas bulk soil collected in

June 2008 had the lowest richness estimation (49). Overall, the libraries had not sampled

the extant diversity to completion. Furthermore, the data showed that the soil bacterial

community make-up was changing over the time as the concomitant PCR-DGGE analyses

revealed the occurrence of shifted patterns. Since each band in such pattern might

represent a bacterial species, the appearance of different species was time-dependent.

What implications these differences and changes have for soil functioning is as yet

unknown. In soil, a range of species may contribute, in equivalent or different ways, to a

particular soil function. This phenomenon has been denoted “functional redundancy”.

Thus, one species may substitute for another one that eventually got lost due to a local

perturbation. Although for many soil functions there is no clear evidence of any

relationship between soil functioning and bacterial diversity, there may be impacts of the

shifts. For instance, in our work phyla like the Proteobacteria showed trends in becoming

more, or less, dominant over time (for example increasing from the flowering to the

senescence stages in the rhizosphere). These changes might be important in functional or

stability terms, but an assessment of this possible linkage to function or resilience has to

await further work. It is logical to posit here that the observed shifts resulted from the

combined effects of the presence of a plant, the plant type and the reigning

environmental conditions such as temperature and moisture.

Moreover, soil type was found to be a key determinant of the bacterial community

composition in the rhizospheres of the potato plants that were grown across soils, as

evidenced by PCR-DGGE and phenotype microarray analysis (Chapters 3 and 5). For

instance, when analyzing the effect of the different cultivars on the bacterial abundance

and community structure, significant differences were observed between the

communities in both fields at all growth stages. Expectedly, increases were noted in the

bacterial abundances in the rhizospheres of all potato cultivars in comparison to those in

the bulk soil. In the V soil, however, the bacterial abundance was not strongly affected by

the presence of a potato plant, and it remained roughly constant over the growth season.

It is possible that, due to the higher nutritional status (OM content and level of other

nutrients), the bacterial abundance in the V soil was affected to a much lower extent by

any root exudates that eventually became available (Chapter 3).

In Chapter 5, the microbial communities from selected samples were analyzed in

phenotype microarrays for their capacities to use different carbon, sulfur and phosphorus

sources. PCR-DGGE analysis was then applied to fingerprint those communities that

allowed high consumption of carbon and sulfur sources. Clearly, soil type affected the

structure of the communities that were active on the selected sulfur and carbon sources.

138

In previous studies, it was also shown that soil type is a key factor that determines the

bacterial community composition in the rhizospheres of plants grown across soils (10, 29).

In the current study, an overall main finding was that soil type exerted the most profound

influence on the analyzed functional bacterial communities in both bulk and rhizosphere

settings. This clearly revealed that the soil bacterial communities differed between the

two soils analyzed and that the communities in the respective rhizospheres were also

different, most likely as a result of the selection of different bacterial consortia by the

same plants growing in different soils.

Indeed, plants are thought to selectively attract particular soil microorganisms to

their rhizospheres, under which avid consumers of root-excreted compounds may be

dominant (13, 64). The abundance and make-up of the rhizosphere bacterial communities

are also known to be governed by the often complex interactions of soil type, plant

species (genotypes) and plant growth (48, 51, 55, 56, 89). In our observations, the

rhizosphere bacterial and betaproteobacterial communities were indeed significantly

different from their respective bulk soil counterparts (Chapter 3). Besides, the plant

growth stages also strongly influenced the community make-ups. Root exudation patterns

may change over time, inciting changes in the microbial community composition in the

rhizosphere (19). In Chapter 5, we found that the bacterial communities from the B and V

bulk soils with plants in the senescence stage either consumed different C sources than

those from the corresponding rhizospheres or the utilization rates were lower than those

in the latter. However, in this study, potential rather than actual utilization of each

substrate was measured, which may only remotely reflect what is going on in situ.

Furthermore, the PCR-DGGE bacterial community analyses that were performed on

selected substrates of the phenotype microarray revealed the bulk soil communities to

cluster apart from the corresponding rhizosphere ones. Some of the compounds that were

analyzed are possibly important as key determinants of plant-bacterium interactions and

these were therefore selected for closer analysis (77). For instance, L-malic acid is known

to be secreted by the roots of varied plants and apparently provides an effective signaling

molecule that modulates the establishment of beneficial rhizobacteria in the plant

rhizosphere, suggesting it has a regulatory role (77). Besides, α-ketobutyric acid, D-alanine

and L-ornithine have also been found to be specific to the rhizosphere, in this case of

white potato (26). In our study, L-malic acid, next to three other compounds i.e., L-aspartic

acid, γ-amino butyric acid and glycyl-L-proline, might indeed be a specific modulator of the

potato root-associated bacterial communities, since organisms with clear utilization

capacities were apparently selected by the rhizosphere.

Also, the amount and types of compounds in the root exudates might show

genotype-specific variations. Different potato cultivars with different rates of growth and

root development are likely to release organic compounds to different extents, and the

bacterial populations in the rhizospheres of the two cultivar groups with different tuber

starch contents likely consisted of species that utilize different carbon sources. A plant

genotype-specific selective effect of plant root type on the root-associated rhizobacterial

community structures was also observed in previous studies (24, 25, 56, 71). In order to

better understand the effects of the differences in plant physiology (related to tuber

starch content and root development) on the rhizospheric bacterial diversity, clone

libraries from the rhizospheres of two cultivars growing in the B soil during flowering stage

139

were compared to those of the respective bulk soil (Chapter 3). Surprisingly, the three

libraries varied remarkably in the estimated diversity of the Betaproteobacteria.

Specifically, the rhizosphere of the cultivar with high-starch-content tubers (Aveka)

showed the highest betaproteobacterial diversity, whereas the communities associated

with the low-starch-tuber cultivar (Premiere) were the least diverse. We currently ignore

why the two cultivars apparently selected communities with such divergent diversities and

can only speculate on how niches might be shaped by both.

Besides, to allow a more high-throughput analysis of the soil bacterial communities,

we used, as a second approach, soil DNA-based pyrosequencing to assess the bacterial

community dynamics (Chapter 4). Around 350,000 sequences were obtained (5,700 to

38,000 per sample). The cultivars analyzed were grouped based on their starch contents

(A, Av, K- high starch tuber, P and D- low starch tuber). The bacterial community make-up

changed in conjunction with the tuber starch content of the host plants. In some cases,

even the rhizosphere effect was different based on plant tuber starch content and,

presumably, plant physiology. In this study, the communities at the GM plant (M) were

compared against the collective data. Interestingly, no significant differentiating effect on

the bacterial community was found for cultivar M. To be able to weigh the effect of

cultivar M against the NOR defined by the communities in the rhizosphere of all cultivars

and bulk soil over three growth stages, the borders of the NOR were established by the

maxima and minima, i.e. the upper (75%) and the lower (25%) percentiles of the relative

abundances of phyla and/or classes. This was accomplished using the average of five

cultivars, GM plant and bulk soil, including all sampling times (Chapter 4). From this

assessment, the values obtained for the GM plant fitted in the overall NOR (in relation to

the rhizosphere or the bulk soil). Strikingly, here, the fluctuations of Betaproteobacteria

and of different orders and genera within this class, observed at the GM plant, slightly

exceeded the NOR for the collective rhizospheres (Fig. 1). Here, orders or genera that are

important for soil functioning were chosen for the analyses. Unfortunately, the data

revealed many unclassified bacteria and, in addition, important genera such Polaromonas

and Acidovorax were not detectable. Given the foregoing, the order Burkholderiales and

the genera Burkholderia, Variovorax, Achromobacter and Nitrosospira were chosen to

serve as potential key indicators (Chapter 4). The data from the clone library analysis

(Chapter 6) and pyrosequencing (Chapter 4) were thus examined to establish the NOR

with respect to these taxa. Since the data obtained from the clone library were (five- to

seven-fold) lower than those of the pyrosequencing (indicating a possible cloning bias),

data from clone library for Betaproteobacteria and Burkholderiales were corrected with

factors 7 and 5 respectively, to allow comparison with the pyrosequencing data. The

resulting NOR for the various taxonomic levels is depicted in figure 1. Considerable

variation in the fractions over the total of the different taxonomic levels was observed in

the potato cropping system over time.

From the results obtained, we distill that the Betaproteobacteria and subgroups

therein might serve as indicator classes for the establishment of a NOR (baseline) of key

bacterial species in soil under potato. The main argument supporting this thesis is that

many members of the betaproteobacterial group are important mediators in steps of

the cycling of nitrogen, sulfur and carbon through the soil ecosystem (43, 81). Secondly,

they were found to be sensitive to shifts induced by potato cultivar type. Not only in the

140

work done under Chapter 4, but also in that of Chapter 6, it was shown that the

community make-up of the Betaproteobacteria is strongly responsive to the presence of

plants, which relates to cultivar type and plant growth stage. The study on potential

function (Chapter 5) also showed a clear rhizosphere and cultivar effect on the

betaproteobacterial communities. However, we could not discern a particular effect of the

GM plant. Thus, cultivar M, as compared to the other cultivars (including K), did not exert

any specific effect on the utilization patterns of the carbon, phosphorus and sulfur sources

by its associated microflora. The responses of the soil/rhizosphere microbial communities

to these nutrient sources were investigated individually. However, one needs to realize

that root exudates normally contain diverse compounds in fluctuating concentrations in

an integrated environment. Hence, due to the resulting complexity, pinpointing the effects

on the real in situ microbial populations at the potato root surface is inherently difficult.

What about the unclassified bacteria?

Pyrosequencing offered us a chance to explore the bacterial community and their

interactions at a more thorough level. However, a large fraction of the soil bacterial

communities studied was found to abide in unknown territory, much as what was found in

the clone libraries. The DNA obtained from the bacterial community in the bulk soil

collected during the young plant and flowering stages was actually dominated by

sequences of as-yet-unclassified bacteria (15-35%). Hence, this part of the soil community

remains a challenging reservoir of novel bacterial diversity. Subsamples, consisting of 100

sequences each, were taken from the as-yet-unclassified sequences of three bulk and

three rhizosphere soil samples. Per subsample (soil or rhizosphere), phylogenetic trees

were built and the clustering was analyzed. In all cases, most (>95%) of the sequences fell

in 7-10 branches, in which individual reads often showed deep branching. “Flat” branches

containing more than 5 sequences were never observed using the 97% cut-off level,

indicating that none of the tested sequences showed overall dominance (i.e. roughly >

1.3% of the total). High percentages of the as-yet-unclassified bacteria have also been

found in other relevant studies (2, 89). There is a strong need to identify such as-yet-

unclassified bacteria and ideally organisms should be cultured in order to start to

understand their ecology. This pleas strongly for the position that the new and highly

powerful culture-independent techniques should go hand-in-hand with advanced culture-

dependent ones.

141

0

0,05

0,1

0,15

0,2

0,25

0,3

0,35

0 1 2 3 4 5 6

relative abundance

of V

ariovorax [%

]

bulk rhizosphere GM

0

1

2

3

4

5

6

0 5 10 15 20 25 30

relative abundance of Betaproteobacteria [%]

bulk-pyroseq

rhizosphere-pyroseq

GM-pyroseq

clone library

0

1

2

3

4

5

0 5 10 15 20 25 30

relative abundance of Burkholderiales [%]

bulk-pyroseq

rhizosphere-pyroseq

GM-pyroseq

clone library

A

B

C

0

0,05

0,1

0,15

0,2

0,25

0,3

0,35

0 1 2 3 4 5 6

relative abundance

of V

ariovorax [%

]

bulk rhizosphere GM

0

1

2

3

4

5

6

0 5 10 15 20 25 30

relative abundance of Betaproteobacteria [%]

bulk-pyroseq

rhizosphere-pyroseq

GM-pyroseq

clone library

0

1

2

3

4

5

0 5 10 15 20 25 30

relative abundance of Burkholderiales [%]

bulk-pyroseq

rhizosphere-pyroseq

GM-pyroseq

clone library

A

B

C

142

Figure 1 - Normal

operating range

(NOR) of the bulk and

rhizosphere soil

against the

genetically modified

plant (M) across the

season 2008 for (A)

Betaproteobacteria

(B) Burkholderiales

(C) Variovorax. (D)

Nitrosospira (E)

Burkholderia (F)

Achromobacter. 1-

before planting (April

2008) 2- young plant

potato (May 2008), 3-

flowering (June

2008), 6-senescence

(September 2008), 9-

after removal of

plants (December

2008), 15 – barley

during flowering of

potato plants (June

2009), 28 – flowering

(July 2010), 30 –

senescence

(September 2010).

Rhizosphere indicates

the average of 5

cultivars. Blue lines

indicate the NOR for

bulk soil. The pink

area represents the

NOR for rhizosphere

and the green area

represents the range

for the GM plant

(Chapter 4). Data in

(A) and (B) from

clone libraries were

harmonized with

number 7 and 5

respectively.

0,01

0,02

0,03

0,04

0,05

0,06

0,07

0 1 2 3 4 5 6

relative abundance of Nitrosospira [%

]

bulk rhizosphere GM

0,00

0,05

0,10

0,15

0,20

0,25

0,30

0 1 2 3 4 5 6

Relative abundance of Burkholderia [%

]

bulk rhizosphere GM

0,00

0,02

0,04

0,06

0,08

0,10

0 1 2 3 4 5 6

Relative abundance of Achromobacter [%]

bulk rhizosphere GM

D

F

E

0,01

0,02

0,03

0,04

0,05

0,06

0,07

0 1 2 3 4 5 6

relative abundance of Nitrosospira [%

]

bulk rhizosphere GM

0,00

0,05

0,10

0,15

0,20

0,25

0,30

0 1 2 3 4 5 6

Relative abundance of Burkholderia [%

]

bulk rhizosphere GM

0,00

0,02

0,04

0,06

0,08

0,10

0 1 2 3 4 5 6

Relative abundance of Achromobacter [%]

bulk rhizosphere GM

D

F

E

143

Can microbial diversity be related to ecological behavior?

The large pyrosequencing-based data set also gave us the opportunity to assess the

ecological behavior, in terms of the dynamics of relative abundance, of particular pre-

specified bacterial phyla and classes. Here, I would like to posit that the general

prevalence of many members of, e.g., the Acidobacteria in bulk soils (as opposed to

rhizosphere soils) may relate to their generally oligotrophic (K strategist) lifestyle (22).

Acidobacterium has appeared as a highly recalcitrant phylum for a long time, in terms of

understanding behavior, due to the difficulty of isolation of its member strains. The

phylum consists of a wide range of species, with presumably diverse ecological behavior

(65). Contradictory information has been provided on the occurrence of different

members of the Acidobacteria in the plant-soil environment (38, 40, 65). In contrast, many

of the Betaproteobacteria (22) as well as Pseudomonas species (88) are known as typical

copiotrophs (r strategists) which tend to be strongly favored in soil under nutrient-rich

conditions. It is possible that each plant growth stage is characterized by a specific but

different root exudation pattern which drives different bacterial communities. During the

young, flowering and senescence stages of plant growth, the rhizosphere may offer

varying niches that are characterized by different levels and compositions of root

exudates. Besides, in the bulk soil, the early (young) growth stage was preferred by

Acidobacteria (oligotroph) whereas the late (senescence) stage was abundant with

copiotrophs (e.g. Beta-, Alpha-proteobacteria and Pseudomonas). An explanation might be

that, in the senescence stage, the bulk soil experienced more pronounced nutrient

supplies, in this case from senescent (“leaky”) plant roots than at earlier stages. Thus, the

root tissue may have started to enrich the surrounding soil environment with nutrients. In

our observations, Pseudomonas was found in similar amounts across all potato cultivars

(so independently of cultivar type), whereas the prevalence of the class

Betaproteobacteria was likely cultivar-dependent. The latter might also provide an

argument in favor of the use of Betaproteobacteria as a group of indicator organisms.

In a recent opinion paper by Philippot et al. (69), it was claimed that many high

taxonomic levels of bacteria show 'ecological coherence' (22, 70). It was argued that the

ecological coherence within a taxon is greater than across taxa. Ecological coherence here

is the fact that members of a given taxon share general life strategies or traits that

distinguish them from members of other taxa (69). The authors assumed that during the

course of evolution, adaptations to different ecological niches have shaped and

differentiated bacterial lineages, and then the divergences are reflected not only at the

strain or species level but also or mainly at higher taxonomic ranks. There are studies that

support the idea of ecological coherence of bacterial groups at taxonomic ranks higher

than the species (8, 14, 45, 88). Other studies report either site- or time-specific

community structures at high taxonomic levels (9, 23, 32), as well as differential responses

of bacterial lineages to changing environmental factors (9, 37). On the other hand,

Philippot et al suggested to keep in mind the imperfection in recognizing ecological

cohesiveness of high bacterial taxa; they advocated a focus on unifying principles (69).

One might compare this to the dietary preferences of people based on regional

conditions. For instance, if you check different regions of Turkey, the climate and land

144

conditions define the dietary habits of people. In the southeast, people have meat- and

grain-based diets, whereas the diet is more fish-based in the north. In the Netherlands,

diets are completely different and based mainly on potato. However, there are also

exceptions, like in a country where they use hot spices. There might be people who do not

like the spices, the other way around for countries which do not know any spices other

than salt. These examples lead us to general dietary predictions, based on region. In soil,

one might cogitate the existence of such local diet-determined communities: strains of the

same taxon might show similar behaviour as determined by site. Thus, once the ecology of

single species can be described, one might start to discern unified ecological traits at

higher ranks.

How does the level of aromatic sulfonates affect the bacterial community in soil?

In Chapter 6, the effect of different concentrations of linear alkyl benzenesulfonate (LAS)

and sulfate in soil on which the potato cultivars Aveka (high starch tuber) and Premiere

(low starch tuber) were growing, was studied in a microcosm experiment. The idea was

that (1) soils may become deprived of inorganic sulfur turning the transformation of other

(organic) sulfur sources indispensable for microbes and plants, (2) aromatic sulfonates in

soil are potentially important sulfur sources for plant nutrition and (3) many organic sulfur

sources are biodegraded by microorganisms in the soil. Therefore, the degradation of LAS

by particular microbial desulfonators in soil was predicted, however their ecology was

unknown.

In previous work, changes in the community structures of Alphaproteobacteria and

Actinobacteria in bulk soil as a result of the addition of LAS (78) have been noted.

Moreover, short-term effects of sulfate on the diversity of Betaproteobacteria in the

Agrostis stolonifera rhizosphere have also been shown (83). However, other studies have

shown no effects of added LAS on the diversity or community structures of bacteria in

soils (7, 78, 92). In the current study, for the first time, an effect of LAS on the soil

betaproteobacterial community make-up was revealed.

We also found that there are desulfonators active under sulfate-containing

conditions in soil. The desulfonating enzymes produced by such organisms are often not

constitutive, but only become expressed under low-sulfate conditions as part of a broader

sulfate starvation response (39). On the other hand, desulfonation of aromatic sulfonates

has been found to occur in natural soil (81). Also, a previous study suggested that some

desulfonating bacteria, evidenced via detection of Cupriavidus sp. like asfA sequences, can

also take advantage of elevated sulfate levels (83). In our work, we did find rapid

desulfonation in the sulfate-containing soil. The sulfate level in this soil had initially been

underestimated (performed using water extraction). How can we explain the

simultaneous occurrence of desulfonation and sulfate? Possibly, the sulfate may have

been heterogeneously distributed. Hence, it might have been less available to local

desulfonators, which perceived LAS as their prime sulfur (and/or carbon) source.

Together, these factors might have resulted in the activation of desulfonators in sulfate-

containing soil.

145

Overall, our results suggest that particular bacterial phylotypes that are involved in

desulfonation and/or carbon mineralization quickly utilized LAS in the soil. The

composition of this desulfonating guild is utterly unknown, but Variovorax paradoxus may

have played a role – and thus become selected – at high LAS levels in the potato

rhizosphere, as was clearly indicated from the clone library analysis for LAS-50-treated

rhizosphere in the flowering stage.

Concluding remarks

Since the ecosystems on Earth differ in their buffering capacity against perturbation as a

function of biotic and abiotic factors, natural variations within a system inciting

community changes are to be considered as determinants of the NOR of that system (41).

This argument holds for both natural and man-made systems, such as agricultural ones. In

the latter, effects of all (agronomic) measures that are normal in the system need to be

included in the NOR. We here argued this NOR should place a strong focus on the soil

microbiota, which underpins soil functioning. Afterwards, the NOR can be used to assess

the effect of a GM plant on the soil microbial community. In our study, we used the GM

cultivar M, which has been derived from the parent cultivar K. Cultivar K was thus

modified to prevent the formation of amylase in the tubers. We cogitated that the

modification might have altered the root exudation pattern of cultivar M. To allow

assessing the putative effects of the modification, its effects are ideally weighed against a

NOR that was built on the variation among the other (unmodified) cultivars used in this

study. A baseline was thus built up with selected potato cultivars that differed in the

starch content of their tubers. Overall, the facet tuber starch content turned out to be an

important factor impacting on the community structure of the potato associated

microbiota. Overall, most assessments performed showed the absence of a significant

effect of the modification that gave origin to cultivar M. In fact, the collective data

obtained with all cultivars established the NOR of potato cropping in the used soils. The

putative effects of future genetic modifications in potato should be weighed against the

NOR provided by this suite of cultivars.

However, the assessed NOR may not be of use for another crop or even for same

crop in different soils, since the environmental factors may be too varied. For instance,

one study assessed the community structure of the microbiota in agricultural soil under

four systems and found Actinobacteria, Bacteriodetes and Firmicutes to be the most

dominant phyla (2). In our study, Actinobacteria and Alphaproteobacteria comprised the

most dominant phylum and class, respectively, whereas the prevalences of members of

the Bacteriodetes and Firmicutes were found to be relatively low. This appears consistent

with the contention that each soil may have its own characteristic community make-up

(28). Moreover, another study from Acosta-Martinez (1) showed that the effects of

grazing on pasture by cattle were significant for the Actinobacteria, Proteobacteria and

Chlorofexi, indicating that the particular use of a soil can affect particular bacterial groups

in a soil. Besides, soil pH was shown to explain a significant portion of the variability

associated with changes in the community structures that were observed (63), indicating

the key role exerted by pH in shaping the community make-up of soil.

146

Growing GM or conventional plants in the field has raised concerns about the

potential risk of effects on non-target organisms. The possibility of long-term effects from

GM plants obviously cannot be excluded and must be examined on a case-by-case basis.

There are currently a range of studies on the effects of differently-modified plants on the

soil microbial community (3, 6, 17, 19-21, 27, 33, 48, 50, 57, 66, 67, 72, 73, 79, 82, 85, 93).

In certain cases, the degree of difference between the modified and parent cultivar (or

any other cultivar of the same plant species) was not defined (35, 58). In regulatory terms,

a GM plant is ideally characterized as “substantially equivalent” (with the exception of the

modification) to its parent, and concerns are whether there is any reason to suppose it

poses an unacceptable risk to soil health, including the soil microbiota and its functioning

(47). One key bacterial group involved in soil functioning is represented by the

Betaproteobacteria, as members of this group are important mediators in key steps of

the cycling of nitrogen, sulfur and carbon through soil (43, 81). For instance, the

Nitrosomonadaceae form an important cluster of betaproteobacterial ammonia oxidizers,

whereas Burkholderia types play important roles in soil transformations, the

mycorrhization of plants as well as in symbiotic nitrogen fixation (12, 75). Other members

of the Betaproteobacteria promote plant growth by virtue of their synthesis of

phytohormones and vitamins (18). For instance, B. phytofirmans typically produces

aminocyclopropane-1-carboxylate (ACC) deaminase, which assists in the lowering of the

level of the stress hormone ethylene at plants. Accordingly, the growth of plant roots may

increase when B. phytofirmans is present, by virtue of the reduction of this root

elongation inhibitor (84). Furthermore, other Burkholderia species are important

producers of antibiotics that antagonize bacterial and fungal phytopathogens (52).

Recently, the betaproteobacterial genera Variovorax and Polaromonas have been found

to be capable of desulfonating aromatic sulfonates in the wheat rhizosphere (80).

Encouragingly, our study showed that several members of the Betaproteobacteria are

sensitive to effects from different potato cultivars as well as soil and time, allowing their

potential use as bioindicators that define the NOR (baseline) for potato cropping.

Moreover, in our study, high-throughput pyrosequencing on the basis of directly

extracted soil DNA was used. In spite of its limitations, e.g. read length (76), it gave us an

angle at the entire microbial community, and showed the clear effect of cultivar type per

different level of taxa. This also enabled to see the ecological coherence of different

taxonomic levels.

Plant-soil systems are highly heterogeneous and dynamic, and here we supplied

data concerning the NOR of soil microbial community properties in response to potato

plant-induced variables. The effects of the GM plant were minor compared with the

variation seen across all cultivars or those associated with season. Concerning potato

cropping, we advocate the use of particular Betaproteobacteria as sensitive indicators for

the assessment of the quality of the potato-cropped soils (47). Thus, members of the soil

Betaproteobacteria can be monitored to assess perturbations, resulting in a framework

that may monitor changes and provide a framework for risk assessment. Furthermore, in

the current study, the asfA gene of species belonging to the Betaproteobacteria was also

found to be “sensitive” to soil type, the presence of a plant and plant growth stage.

However, it needs further study to assess the validity of the use of asfA as an indicator. In

this respect, in case of detection of a change, the question is how we should handle it

147

(42). This will require a strengthening of the theoretical link between the soil microbial

community structure and its functions, including the aspect of resilience/resistance of the

system (42).

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