Bacterial evolution in high osmolarity environments

Cesar, Spencer; Anjur-Dietrich, Maya; Yu, Brian; Li, Ethan; Rojas, Enrique; Neff, Norma; Cooper, Tim F.; Huang, Kerwyn Casey

doi:10.1101/2020.05.07.081752

Cited by 3 publications

(3 citation statements)

References 53 publications

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“…It has been shown earlier that under non-stress conditions, bacteria favor phytohormone synthesis rather than osmolyte accumulation, whereas the opposite occurs under stress conditions. Such a shift in metabolic activity is common in bacterial cells, allowing them to maintain homeostasis when there is an increase in osmotic pressure in the extracellular medium (Varela et al, 2004;Lahtvee et al, 2014;Cesar et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

Application of data integration for rice bacterial strain selection by combining their osmotic stress response and plant growth-promoting traits

Devarajan

Truu²,

Gopalasubramaniam³

et al. 2022

Front. Microbiol.

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Agricultural application of plant-beneficial bacteria to improve crop yield and alleviate the stress caused by environmental conditions, pests, and pathogens is gaining popularity. However, before using these bacterial strains in plant experiments, their environmental stress responses and plant health improvement potential should be examined. In this study, we explored the applicability of three unsupervised machine learning-based data integration methods, including principal component analysis (PCA) of concatenated data, multiple co-inertia analysis (MCIA), and multiple kernel learning (MKL), to select osmotic stress-tolerant plant growth-promoting (PGP) bacterial strains isolated from the rice phyllosphere. The studied datasets consisted of direct and indirect PGP activity measurements and osmotic stress responses of eight bacterial strains previously isolated from the phyllosphere of drought-tolerant rice cultivar. The production of phytohormones, such as indole-acetic acid (IAA), gibberellic acid (GA), abscisic acid (ABA), and cytokinin, were used as direct PGP traits, whereas the production of hydrogen cyanide and siderophore and antagonistic activity against the foliar pathogens Pyricularia oryzae and Helminthosporium oryzae were evaluated as measures of indirect PGP activity. The strains were subjected to a range of osmotic stress levels by adding PEG 6000 (0, 11, 21, and 32.6%) to their growth medium. The results of the osmotic stress response experiments showed that all bacterial strains accumulated endogenous proline and glycine betaine (GB) and exhibited an increase in growth, when osmotic stress levels were increased to a specific degree, while the production of IAA and GA considerably decreased. The three applied data integration methods did not provide a similar grouping of the strains. Especially deviant was the ordination of microbial strains based on the PCA of concatenated data. However, all three data integration methods indicated that the strains Bacillus altitudinis PB46 and B. megaterium PB50 shared high similarity in PGP traits and osmotic stress response. Overall, our results indicate that data integration methods complement the single-table data analysis approach and improve the selection process for PGP microbial strains.

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Section: Discussionmentioning

confidence: 99%

Application of data integration for rice bacterial strain selection by combining their osmotic stress response and plant growth-promoting traits

Devarajan

Truu²,

Gopalasubramaniam³

et al. 2022

Front. Microbiol.

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“…The copyright holder for this preprint (which this version posted May 14, 2021. ; https://doi.org/10.1101/2021.05.13.444061 doi: bioRxiv preprint In general, our work demonstrates that it is feasible to reproduce time series statistics using consumer-resource models of microbiota dynamics, thereby generating mechanistic hypotheses for further investigation. In future work, more detailed hypotheses can be generated by investigating how time series statistics are affected by modifications to baseline CR dynamics, such as the incorporation of metabolic crossfeeding 6,31 , functional differentiation from genomic analysis [32][33][34] , and physical variables such as pH 35,36 , temperature 37 , and osmolality 38 . In addition, recent studies have shown that evolution can substantially affect the dynamics of human gut microbiotas [39][40][41] .…”

Section: Discussionmentioning

confidence: 99%

Competition for fluctuating resources reproduces statistics of species abundance over time across wide-ranging microbiotas

Huang

2021

Preprint

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Across diverse microbiotas, species abundances vary in time with distinctive statistical behaviors that appear to generalize across hosts, but the origins and implications of these patterns remain unclear. Here, we show that many of these patterns can be quantitatively recapitulated by a simple class of resource-competition models, in which the metabolic capabilities of different species are randomly drawn from a common statistical ensemble. Our coarse-grained model parametrizes the intrinsic consumer-resource properties of a community using a small number of macroscopic parameters, including the total number of resources, typical resource fluctuations over time, and the average overlap in resource-consumption profiles across species. We elucidate how variation in these parameters affects various time series statistics, enabling macroscopic parameter estimation and comparison across wide-ranging microbiotas, including the human gut, saliva, and vagina, as well as mouse gut and rice. The successful recapitulation of time series statistics across microbiotas suggests that resource competition generally acts as a dominant driver of community dynamics. Our work unifies numerous time series patterns under one model, clarifies their origins, and provides a framework to infer macroscopic parameters of resource competition from longitudinal studies of microbial communities.

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“…A final consideration is the role of osmotic pressure in altering the efficiency of eDNA uptake. Populations adapting to high osmolarity environments generally have a large fraction of mutations in genes associated with cell wall synthesis (Cesar et al 2020). Therefore, it could be that changes in the cell wall altered the pilus structure which captures eDNA from the environment (Graupner et al 2000).…”

Section: Discussionmentioning

confidence: 99%

Changes in natural transformation after salt adaptation

Kittredge

Evans

2021

Preprint

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The exchange of genes between potentially unrelated bacteria is termed horizontal gene transfer (HGT) and is a driving force in bacterial evolution. Natural transformation is one mechanism of HGT where extracellular DNA (eDNA) from the environment is recombined into a host genome. The widespread conservation of transformation in bacterial lineages implies there is a fitness benefit. However, the nature of these benefits and the evolutionary origins of transformation are still unknown. Here, I examine how ~330 generations or 100 days of serial passage in either constant or increasing salinities impacts the growth rate and transformation efficiency of Pseudomonas stutzeri. While the growth rate generally improved in response to serial transfer, the transformation efficiency of the evolved lineages varied extensively, with only 39-64% of populations undergoing transformation at the end of adaptive evolution. In comparison, 100% of the ancestral populations were able to undergo natural transformation. I also found that evolving P. stutzeri with different cell lysates (or populations of dead cells) minimally affected the growth rate and transformation efficiency, especially in comparison to the pervasiveness with which transformation capacity was lost across the evolved populations. Taken together, I show that the efficiency of eDNA uptake changes over relatively rapid timescales, suggesting that transformation is an adaptive and selectable trait that could be lost in environments where it is not beneficial.

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Bacterial evolution in high osmolarity environments

Cited by 3 publications

References 53 publications

Application of data integration for rice bacterial strain selection by combining their osmotic stress response and plant growth-promoting traits

Application of data integration for rice bacterial strain selection by combining their osmotic stress response and plant growth-promoting traits

Competition for fluctuating resources reproduces statistics of species abundance over time across wide-ranging microbiotas

Changes in natural transformation after salt adaptation

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