The M truncatula root microbiome composition

Further, we aimed to determine the bacterial community structure of the M. truncatula root microbiome though 454 pyrosequencing analysis. The amplification of bacterial 16S ribosomal RNA (rRNA), which contains nine hypervariable regions (V1-V9), has been used to determine bacterial species in diagnostic assays and in bacterial community structure (Chakravorty et al., 2007). Next generation DNA sequencing methods such as pyrosequencing 454 platform has contributed novel and valuable knowledge to explore microbial diversity (Margulies et al, 2005; Fabrice and Didier, 2009). We used 454 pyrosequencing to determine the bacterial community composition of M. truncatula plants used in this study. The antibiotic application shifted the bacterial dominance and community composition of Medicago roots four days after germination regardless of the presence of 3-oxo-C14-HSL. In our study, bacteria present in Medicago roots were mostly proteobacteria. Many bacteria belonging to this phylum use AHLs to control the expression of a diversity of specific genes (Christensen et al., 2013). The proteobacteria present in this study belong to the Enterobacteriacea family. Some species from this family are commonly known to cause human disease (Mahon et al., 1997; Tyler and Triplett, 2008). Different enteric bacteria such as Salmonella enterica serotype Typhimurium and Klebsiella pneumoniae that have been found in alfalfa sprouts (Medicago sativa) and M. truncatula had originated from seeds (Mahon et al., 1997; Dong et al., 2003). Several seed surface sterile methods have been tested in order to clean legume seeds, including Medicago sativa and M. truncatula (Hong et al., 2016; Choi et al., 2015). Exogenous applications of ethylene as well as 3-oxo-C14-HSL have reduced the occurence of human pathogens in plants, probably due to triggering plant defence responses (Iniguez et al., 2005; Hernández-Reyes et al., 2014). Therefore, it is not surprising that in this study M. truncatula seedlings harbour such a variety of

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bacteria as both organisms have co-adapted to develop specific mechanisms and strategies to orchestrate intimate interactions. It is also possible that another batch of Medicago seeds harbors a different bacterial population composition as it has been shown that the environmental effect (e.g. soil and air) can also contribute to the plant microbiome (Hardoim et al., 2012).

The most relative abundant genera of the M. truncatula microbiome, Kosakonia, Erwinia and Pantoea, appeared quite consistently in seedlings without antibiotic treatment. As it was shown in Chapter 3, the bacterial community present in Medicago seedlings originated from the seeds. The consistent pattern of bacterial genera in all samples of this study suggests that M. truncatula has a strong interaction with these genera, selecting the type of bacteria in a targeted process. This selection may play a critical role in plant survival as this bacterial community will be vertically transmitted to the next generation via a seed-borne microbiome (Johnston-Monje and Raizada, 2011; Hardoim et al., 2012). This microbial consortium can help the plant against abiotic and biotic factors e.g. while the seeds are on the soil waiting for the right conditions to germinate or when they have begun the germination process (Kaga et al., 2009). In consequence, the seed-borne microbiome can help to secure the establishment of the young seedling becoming the foundation of the bacterial community composition of the new seedling (Kaga et al., 2009; Johnston-Monje and Raizada, 2011). Plant colonisation by microorganisms has been shown to be specific (Bulgarelli et al., 2012; Cardinale et al., 2015). This is in line with the thought that plants invest energy and resources to select and nurture their microbiota as they play a crucial role in plant growth and health, particularly at the early stages of plant development. One reason for why the presence of the microbiome negatively affected nodule numbers of M. truncatula could be due to the lack of other environmental components that modulate the plant microbiome, like soil (Berendsen et al., 2012). Over the time, the seed-borne microbiome interacts with the soil microbiome where the seedling grows. Possibly, this interaction provides the adequate balance for the plant to grow and develop. Our experiments missed out this interaction as the plants were growing under controlled conditions on agar plates. Perhaps, this also influenced the suitable and delicate balance of Medicago associated bacteria causing the decrease in nodule numbers observed in the presence of the microbiome.

Interestingly, 3-oxo-C14-HSL addition to non-antibiotic exposed plants significantly decreased the relative abundance of Pantoea spp., and this effect was specific to this

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bacterial genus. Pantoea has been found to produce C6-HSL, 3-oxo-C6-HSL and 3-oxo- C8-HSL (Morohoshi et al., 2007; Jiang et al., 2015) and also it has been isolated from different crops like rice and pea (Kaga et al., 2009; Elvira-Recuenco and Van Vuurde, 2000). QS controls exopolysaccharide production and biofilm formation in Pantoea (Morohoshi et al., 2007). In addition, QS controls the release of extracellular hydrolytic enzyme in P ananatis (Jatt et al., 2015). As Pantoea spp. can be affected by 3-oxo-C14- HSL, it is possible that it can also perceive and respond to 3-oxo-C14-HSL, producing enzymes such as acylases or lactonases which would degrade 3-oxo-C14-HSL, which may explain why 3-oxo-C14-HSL did not increased nodule numbers in the presence of the antibiotic treatment. As reported for other rhizobacteria such as Salmonella (Subramoni and Venturi, 2009), Enterobacter and Erwinia (Sabag-Daigle and Ahmer, 2012), Pantoea possess a solo LuxR ortholog of Sdi system which, in turn, allows to ‘listen’ to an unusually large variety of AHLs synthetised by other organisms (Venturi and Ahmer, 2015). Thus, it would be possible for Pantoea to ‘listen to’ other AHLs. Another member of the M. truncatula microbiome identified in this study, Kosakonia sp., has been found to interfere with quorum sensing. For example, isolates of Kosakonia sp. from citrus leaves interfered with quorum signalling in Xanthomonas citri subsp. citri, the agent of citrus canker (Caicedo et al., 2015). Pseudomonas spp. also has been found to interfere with quorum sensing of Xanthomonas campestris pv. campestris (Newman et al., 2008).

It is also possible that the M. truncatula root microbiome modulates plant metabolism by interfering with ethylene signalling as it has been shown previously (Nonaka and, Ezura, 2014; Ribaudo et al., 2006). PGPRs can decrease ethylene concentration in plants by synthetising 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase, which reduces the ethylene precursor ACC into α-ketobutyrate and ammonia, resulting in decreased ethylene production (Nonaka and, Ezura, 2014). For instance, it has been reported that Pseudomonas putida GR12-2 can promote root elongation in canola seedlings most likely to due to reduced endogenous ethylene levels (Glick et al., 1994). However, the PGPR Azospirillum brasilense FT326, unable to produce ACC deaminase, promoted root hair and shoot development in tomato plants via increased ethylene levels (Ribaudo et al., 2006). Thus, it is difficult to draw firm conclusions about how the M. truncatula root microbiome or some members, might modulate nodulation responses to AHLs. It would be interesting to further investigate the mechanism by which the microbiome influences nodule numbers in M. truncatula by (i)

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quantifying the AHL concentration in the plant by mass spectrometry, (ii) detecting plant and bacterial enzymes that might degrade AHLs using a bioassay and (iii) measuring ethylene levels in the plant.

Seed-borne bacteria (rhizobial and non-rhizobial species) will eventually colonise other parts of the plant like roots and nodules, usually resulting in a plant growth-promoting effect (Dudeja et al., 2012). It has been proposed that different bacterial strains have contradictory effects on nodulation either to promote or to inhibit nodulation (Oehrle et al. 2000). Previous works have demonstrated that single strain co-inoculation of members of the bacterial nodule microbiome has had a positive effect on plant nodulation (Stajković et al., 2009; Ibáñez et al., 2009). For instance, co-inoculation of Bacillus and Rhizobium strains increased nodule numbers of pigeon pea (Cajanus cajan) (Rajendran et al., 2008). Conversely, Oehrle et al. (2000), reported that multiple species of seed-borne bacterial isolates reduced the attachment and infection of Bradyrhizobium japonicum in soybean (Glycine max). In the same study, germinating seeds were treated with antibiotic with no effects on plant development and the attachment of B. japonicum increased 200-325% after the antibiotic treatment. This might be another reason why the seed-borne microbiome of M. truncatula prevented an increase nodule numbers by 3-oxo-C14-HSL in our study as they might also inhibit the attachment of rhizobia. Thus, during plant growth, the community of plant associated bacteria can change, e.g. strains that inhibit nodulation overcome strains that enhance nodulation reducing the available sites for infection in Medicago roots.

The Rhizobium genus was found present in M. truncatula roots treated either with or without antibiotic treatment. None of the four different Rhizobium species identified were specific to nodulate M. truncatula. The genus Rhizobium has been able to colonise a range of plants promoting their growth through different mechanisms specially biocontrol (Mahdy et al., 2001; Klock et al., 2015). For instance, R. etli has been found to induce resistance towards root knot nematodes as well as to assist mycorrhizal colonisation in tomato as a helper bacterium (Reimann et al., 2008). It has been suggested that Rhizobium isolates from nodules that are incapable to nodulate legumes act as helper bacteria (Dudeja et al., 2012). R. leguminosarum bv. phaseoli, isolated from red clover nodules, promoted plant growth (Sturz and Christie, 1995). Thus, Rhizobium species found in our work could act as helpers.

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Pseudomonas was prevalent in roots treated with the antibiotic and became the most dominant bacterial genus in this study. This is presumably because Pseudomonas sp. can develop antibiotic resistance to a broad range of antibiotics. For instance, P. aeruginosa isolates from clinical samples were 100% resistant to augmentin, imipenem, and erythromycin (Breidenstein et al., 2011; Bibi et al., 2015).

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6

General Discussion

Previous studies established that plants are able to recognise AHLs, and differentiating AHL signals from pathogenic and symbiotic bacteria (Mathesius et al., 2003; Gao et al., 2003). Moreover, plants can also respond to AHLs by altering plant growth and development (Mathesius et al., 2003; Joseph and Phillips, 2003; von Rad et al. 2008; Klein et al. 2009). For example, in response to physiologically relevant concentrations of AHLs, the model legume Medicago truncatula have been shown to adjust the production levels of more than 150 proteins, including defense related proteins, metabolic enzymes, and enzymes of the flavonoid pathway (Mathesius et al., 2003). Legumes have co-adapted to interact with rhizobia in a fine-tuned process to allow rhizobial root colonisation, and because AHLs are necessary to regulate several bacterial behaviours linked to successful nodulation (González et al., 1996; Marketon and González, 2002; Hoang et al., 2008), it was interesting to examine if plant perception of AHLs affects nodulation. However, the effect of AHLs on the legume- rhizobia symbiosis, particularly nodulation has so far remained unexplored. The hypothesis of this work was that quorum sensing signals affect nodulation in M. truncatula.

This thesis explored the following questions:

i. Do quorum sensing signals affect plant nodulation and how specific is this effect?

ii. What are the mechanisms involved in the plant response towards quorum sensing signals during nodulation?

iii. Do plant associated bacteria influence plant responses to quorum sensing signals?