A Transcriptomic Analysis of Higher-Order Ecological Interactions in a Eukaryotic Model Microbial Ecosystem

Conacher, Cleo G.; Naidoo-Blassoples, R K; Rossouw, Debra; Bauer, Florian F.

doi:10.1128/msphere.00436-22

Cited by 9 publications

(12 citation statements)

References 74 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This indicates the importance of interactions in determining the effect of complex microbial communities on S. cerevisiae fermentation performance. Supporting this idea, a recent work of Conacher et al (2022) has evidenced the presence of high-order interactions in wine yeast consortia, demonstrating that the inoculation of S. cerevisiae with complex yeast communities disclose transcriptional responses not explained by the transcriptional responses observed in pairwise co-culture.…”

Section: Discussionmentioning

confidence: 87%

Predictability of the community‐function landscape in wine yeast ecosystems

Ruiz,

de Celis,

Diaz‐Colunga

et al. 2023

Molecular Systems Biology

View full text Add to dashboard Cite

Predictively linking taxonomic composition and quantitative ecosystem functions is a major aspiration in microbial ecology, which must be resolved if we wish to engineer microbial consortia. Here, we have addressed this open question for an ecological function of major biotechnological relevance: alcoholic fermentation in wine yeast communities. By exhaustively phenotyping an extensive collection of naturally occurring wine yeast strains, we find that most ecologically and industrially relevant traits exhibit phylogenetic signal, allowing functional traits in wine yeast communities to be predicted from taxonomy. Furthermore, we demonstrate that the quantitative contributions of individual wine yeast strains to the function of complex communities followed simple quantitative rules. These regularities can be integrated to quantitatively predict the function of newly assembled consortia. Besides addressing theoretical questions in functional ecology, our results and methodologies can provide a blueprint for rationally managing microbial processes of biotechnological relevance.

show abstract

Section: Discussionmentioning

confidence: 87%

Predictability of the community‐function landscape in wine yeast ecosystems

Ruiz,

de Celis,

Diaz‐Colunga

et al. 2023

Molecular Systems Biology

View full text Add to dashboard Cite

show abstract

“…This indicates the importance of interactions in determining the effect of complex microbial communities on S. cerevisiae fermentation performance. Supporting this idea, a recent work of Conacher et al (2022) has evidenced the presence of high-order interaction within the wine microbiome, demonstrating that the inoculation of S. cerevisiae with complex yeast communities disclose transcriptional responses not explained by the transcriptional responses observed in pairwise co-culture.…”

Section: Discussionmentioning

confidence: 87%

Predictability of the community-function landscape in wine yeast ecosystems

Ruíz

Celis

Díaz-Colunga

et al. 2022

Preprint

View full text Add to dashboard Cite

Predictively linking taxonomic composition and quantitative ecosystem functions is a major aspiration in microbial ecology, which must be resolved if we wish to engineer microbial consortia. Here, we have addressed this open question for an ecological function of major biotechnological relevance: alcoholic fermentation in wine yeast communities. By exhaustively phenotyping an extensive collection of naturally occurring wine yeast strains, we find that most enologically-relevant traits exhibit a strong phylogenetic signal, indicating that the most relevant functions in wine yeast communities can be predicted from taxonomy. Further, we demonstrate that the quantitative contributions of individual wine yeast strains to the community function followed simple quantitative rules. These regularities can be integrated to quantitatively predict the function of newly assembled consortia. Besides addressing a fundamental open question in functional ecology, our results and methodologies provide a blueprint for rationally managing microbial processes of biotechnological relevance.

show abstract

“…By using multiple fluorescence reporters with minimal spectral overlap, multiple unique microbes can be tracked in a complex sample. For example, the absolute abundances of three yeast species, encoded with either a red, green, or blue fluorescence protein, can be quantified simultaneously using multicolor flow cytometry (Conacher et al, 2020). To date, however, multicolor flow cytometry has not been used in any published studies to track multiple species for the purpose of bottom-up ecological modeling.…”

Section: Introductionmentioning

confidence: 99%

Tracking defined microbial communities by multicolor flow cytometry reveals tradeoffs between productivity and diversity

Midani

David

2023

Front. Microbiol.

View full text Add to dashboard Cite

Cross feeding between microbes is ubiquitous, but its impact on the diversity and productivity of microbial communities is incompletely understood. A reductionist approach using simple microbial communities has the potential to detect cross feeding interactions and their impact on ecosystem properties. However, quantifying abundance of more than two microbes in a community in a high throughput fashion requires rapid, inexpensive assays. Here, we show that multicolor flow cytometry combined with a machine learning-based classifier can rapidly quantify species abundances in simple, synthetic microbial communities. Our approach measures community structure over time and detects the exchange of metabolites in a four-member community of fluorescent Bacteroides species. Notably, we quantified species abundances in co-cultures and detected evidence of cooperation in polysaccharide processing and competition for monosaccharide utilization. We also observed that co-culturing on simple sugars, but not complex sugars, reduced microbial productivity, although less productive communities maintained higher community diversity. In summary, our multicolor flow cytometric approach presents an economical, tractable model system for microbial ecology using well-studied human bacteria. It can be extended to include additional species, evaluate more complex environments, and assay response of communities to a variety of disturbances.

show abstract

A Transcriptomic Analysis of Higher-Order Ecological Interactions in a Eukaryotic Model Microbial Ecosystem

Abstract: Higher-order interactions are one of the major blind spots in our understanding of microbial ecosystems. These systems remain largely unpredictable and are characterized by nonlinear dynamics, in particular when the system is comprised of more than two entities.

Cited by 9 publications

References 74 publications

Predictability of the community‐function landscape in wine yeast ecosystems

Predictability of the community‐function landscape in wine yeast ecosystems

Predictability of the community-function landscape in wine yeast ecosystems

Tracking defined microbial communities by multicolor flow cytometry reveals tradeoffs between productivity and diversity

Contact Info

Product

Resources

About