Negative interactions determine
            <i>Clostridioides difficile</i>
            growth in synthetic human gut communities

Hromada, Susan; Qian, Yili; Jacobson, Tyler B.; Clark, Ryan L.; Watson, Lauren; Safdar, Nasia; Amador‐Noguez, Daniel; Venturelli, Ophelia S.

doi:10.15252/msb.202110355

Cited by 33 publications

(74 citation statements)

References 66 publications

(101 reference statements)

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“…Further, pairwise inter-species interactions are easier to decipher in lower order communities due to potential co-variation among parameters (correlations between parameters) as a consequence of model structure or methods of data collection. A similar training/test partitioning was used to generate predictive models of complex community behaviors ( Venturelli et al, 2018 ; Clark et al, 2021 ; Hromada et al, 2021 ).…”

Section: Resultsmentioning

confidence: 99%

Recurrent neural networks enable design of multifunctional synthetic human gut microbiome dynamics

Baranwal

Clark

Thompson

et al. 2022

eLife

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Predicting the dynamics and functions of microbiomes constructed from the bottom-up is a key challenge in exploiting them to our benefit. Current models based on ecological theory fail to capture complex community behaviors due to higher order interactions, do not scale well with increasing complexity and in considering multiple functions. We develop and apply a long short-term memory (LSTM) framework to advance our understanding of community assembly and health-relevant metabolite production using a synthetic human gut community. A mainstay of recurrent neural networks, the LSTM learns a high dimensional data-driven non-linear dynamical system model. We show that the LSTM model can outperform the widely used generalized Lotka-Volterra model based on ecological theory. We build methods to decipher microbe-microbe and microbe-metabolite interactions from an otherwise black-box model. These methods highlight that Actinobacteria, Firmicutes and Proteobacteria are significant drivers of metabolite production whereas Bacteroides shape community dynamics. We use the LSTM model to navigate a large multidimensional functional landscape to design communities with unique health-relevant metabolite profiles and temporal behaviors. In sum, the accuracy of the LSTM model can be exploited for experimental planning and to guide the design of synthetic microbiomes with target dynamic functions.

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Section: Resultsmentioning

confidence: 99%

Recurrent neural networks enable design of multifunctional synthetic human gut microbiome dynamics

Baranwal

Clark

Thompson

et al. 2022

eLife

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“…The following methods are adapted Hromada 2021, Clark 2021 and Venturelli 2018 25,28,66 . All anaerobic culturing was carried out in a custom anaerobic chamber (Coy Laboratory Products, Inc) with an atmosphere of 2.5 ± 0.5% H2, 15 ± 1% CO2 and balance N2.…”

Section: Strain Maintenance Precultures and Growth Mediamentioning

confidence: 99%

“…DNA extraction, library preparation, and sequencing were performed according to methods described in Hromada 2021 and Clark 2021 25,66 . In brief, cell pellets from about 150 uL of culture were stored at -80C following experiments.…”

Section: Genomic Dna Extraction Dna Library Preparation Sequencing Pr...mentioning

confidence: 99%

Model-guided design of the diversity of a synthetic human gut community

Connors

Ertmer

Clark

et al. 2022

Preprint

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Microbial communities have tremendous potential as therapeutics. However, a major bottleneck is manufacturing high-diversity microbial communities with desired species compositions. We develop a two-stage, model-guided framework to produce microbial communities with target species compositions. We apply this method to optimize the diversity of a synthetic human gut community. The first stage exploits media components to enable uniform growth responses of individual species and the second stage uses a design-test-learn cycle with initial species abundance as a control point to manipulate community composition. Our designed culture conditions yield 91% of the maximum possible diversity. Leveraging these data, we construct a dynamic ecological model to guide the design of lower-order communities with desired temporal properties over a longer timescale. In sum, a deeper understanding of how microbial community assembly responds to changes in environmental factors, initial species abundances, and inter-species interactions can enable the predictable design of community dynamics.

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“…Typically, the complexities of a mammalian host pose challenges for disentangling possible direct effects of the perturbation on the microbiota versus indirect effects of an altered host environment. Recent studies have shown that in vitro microbial communities can be used to model the gut microbiota’s response to antibiotics (Aranda-Díaz et al, 2020), other drugs (Javdan et al, 2020), and colonization resistance (Aranda-Díaz et al ., 2020; Hromada et al, 2021), but it remains unclear to what extent in vitro communities can model other conditions, particularly ones that have especially profound effects on host cells.…”

Section: Introductionmentioning

confidence: 99%

Deconstructing the role of iron and heme in the structure of healthy human gut microbial communities

Celis

Relman

Huang

2022

Preprint

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The response of the human gut microbiome to disruptions is often difficult to discern without model systems that remove the complexity of the host environment. Fluctuations in iron availability provide a case in point: the responses of pathogenic bacteria to iron in vitro are much better understood than those of the indigenous human gut commensal microbiota. In a clinical study of iron supplementation in healthy humans, we identified gradual, participant-specific microbiota shifts correlated with bacterial iron internalization. To identify direct effects due to taxon-specific iron sensitivity, we used stool samples from these participants as inocula to derive in vitro communities. Iron supplementation of these communities caused small shifts in structure, similar to in vivo, whereas iron deprivation dramatically inhibited growth with irreversible and cumulative reduction in diversity and replacement of some dominant species. Sensitivity of individual species to iron deprivation during growth in axenic culture generally predicted iron dependency in a community context. Finally, exogenous heme acted as a source of inorganic iron to prevent depletion of some community members. Our results highlight the complementarity of in vivo and in vitro studies in deconstructing how environmental factors affect gut microbiome structure.

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Negative interactions determine Clostridioides difficile growth in synthetic human gut communities

Cited by 33 publications

References 66 publications

Recurrent neural networks enable design of multifunctional synthetic human gut microbiome dynamics

Recurrent neural networks enable design of multifunctional synthetic human gut microbiome dynamics

Model-guided design of the diversity of a synthetic human gut community

Deconstructing the role of iron and heme in the structure of healthy human gut microbial communities

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