High-throughput cultivation of stable, diverse, fecal-derived microbial communities to model the intestinal microbiota

Aranda-Díaz, Andrés; Ng, Katharine M.; Thomsen, Tani; Real-Ramírez, Imperio; Dahan, Dylan; Dittmar, Susannah; González, Carlos Gutiérrez; Chavez, Taylor; Vasquez, Kimberly S.; Nguyen, Taylor H.; Yu, Feiqiao Brian; Higginbottom, Steven K.; Neff, Norma; Elias, Joshua E.; Sonnenburg, Justin L.; Huang, Kerwyn Casey

doi:10.1101/2020.07.06.190181

Cited by 15 publications

(34 citation statements)

References 59 publications

(67 reference statements)

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“…Inferences about intrinsic parameters of resource competition and external parameters of environmental fluctuations were also consistent with expectations for in vitro passaging of a complex community derived from humanized mice 30 . The resulting time series statistics were best fit by the smallest value of among the data sets studied, indicating that the in vitro environment has low noise across sampling times; the nonzero presumably arises from technical variations that result in effective noise in resource levels.…”

Section: Time Series Statistics Distinguish Wide-ranging Microbiotassupporting

confidence: 70%

Section: Time Series Statistics Distinguish Wide-ranging Microbiotassupporting

confidence: 70%

“…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 statistics were best fit by the smallest value of among the data sets studied, indicating that the in vitro environment has low noise across sampling times; the nonzero presumably arises from technical variations that result in effective noise in resource levels. The best fit value of was larger than the reservoir size , suggesting that there are many distinct resources in the complex medium used for passaging and consistent with the ability of more diverse inocula to support more diverse in vitro communities 30 .…”

Section: Time Series Statistics Distinguish Wide-ranging Microbiotasmentioning

confidence: 67%

“…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 carried out for = across ∈ [10,20,30,40,50,100,150,200,250] , ∈ [0.1, 0.9] in 0.1 increments, ∈ [0.05, 0.5] in 0.05 increments, and ∈ [0.1, 1] in 0.1 increments. .…”

Section: A-d) Illustrations Of Various Time Series Statistics In (E-l)mentioning

confidence: 99%

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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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Section: Time Series Statistics Distinguish Wide-ranging Microbiotassupporting

confidence: 70%

Section: Time Series Statistics Distinguish Wide-ranging Microbiotassupporting

confidence: 70%

Section: Time Series Statistics Distinguish Wide-ranging Microbiotasmentioning

confidence: 67%

Section: A-d) Illustrations Of Various Time Series Statistics In (E-l)mentioning

confidence: 99%

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

Huang

2021

Preprint

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“…All cultures were performed in technical triplicate with 2-6 biological replicates. For each growth curve, the interaction score was computed based on an additive null model (Aranda-Díaz et al, 2020):…”

Section: Pairwise Co-culture Growth Measurementsmentioning

confidence: 99%

Systematic dissection of a complex gut bacterial community

Aranda-Díaz

Jain

et al. 2021

Preprint

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Efforts to model the gut microbiome have yielded important insights into the mechanisms of interspecies interactions, the impact of priority effects on ecosystem dynamics, and the role of diet and nutrient availability in determining community composition. However, the model communities studied to date have been defined or complex but not both, limiting their utility. Here, we construct a defined community of 104 bacterial strains composed of the most common taxa from the human gut microbiota. By propagating this community in growth media missing one amino acid at a time, we show that branched-chain amino acids have an outsize impact on community structure and identify a pathway in Clostridium sporogenes for generating ATP from arginine. We constructed and propagated the complete set of single-strain dropout communities, revealing a sparse network of strain-strain interactions including a novel interaction between C. sporogenes and Lactococcus lactis driven by metabolism. This work forms a foundation for studying strain-strain and strain-nutrient interactions in highly complex defined communities, and it provides a starting point for interrogating the rules of synthetic ecology at the 100+ strain scale.

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