Host Immunity Alters Community Ecology and Stability of the Microbiome in a Caenorhabditis elegans Model

Taylor, Megan; Vega, Nicole M.

doi:10.1128/msystems.00608-20

Cited by 24 publications

(30 citation statements)

References 60 publications

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“…The results of this survey were then used to choose a subset of mutants for further analysis. The considered mutants either showed impaired immunity or impaired microbial uptake which potentially influences microbiota abundance [27,28,49,66]. We found that MYb11 colonisation was significantly higher in the mutants dbl-1, sma-6, phm-2, tnt-3 , and tir-1 compared to the wildtype N2 ( p < 0.05).…”

Section: Resultsmentioning

confidence: 96%

“…In nature, the nematode is associated with a species-rich microbiota [45,46], which includes immune-protective microbes, such as a variety of Pseudomonas species [47,48]. Moreover, innate immunity [27,28,49] and microbe-microbe interactions have been shown to influence C. elegans microbiota composition and function [46,50]. For the current study, we used different C. elegans mutants, which either affect the nematode’s immune system (e.g., p38 MAPK and TGF- β signalling) or microbial colonisation (i.e., through disruption of the grinder in the nematode’s pharynx).…”

Section: Introductionmentioning

confidence: 99%

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The intricate triangular interaction between protective microbe, pathogen, and host genetics determines fitness of the metaorganism

Griem-Krey,

Petersen,

Hamerich

et al. 2023

Preprint

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The microbiota shapes host biology in numerous ways. One example is protection against pathogens, which is likely critical for host fitness in consideration of the ubiquity of pathogens. The host itself can affect abundance of microbiota or pathogens, which has usually been characterised in separate studies. To date, however, it is unclear how the host influences the interaction with both simultaneously and how this triangular interaction determines fitness of the host-microbe assemblage, the so-called metaorganism. To address this current knowledge gap, we focused on a triangular model interaction, consisting of the nematode Caenorhabditis elegans, its immune-protective symbiont Pseudomonas lurida MYb11, and its pathogen Bacillus thuringiensis Bt679. We combined the two microbes with C. elegans mutants with altered immunity and/or microbial colonisation, and found that (i) under pathogen stress, immunocompetence has a larger influence on metaorganism fitness than colonisation with the protective microbe, (ii) in almost all cases, MYb11 still improves fitness, and (iii) disruption of p38 MAPK signalling, which contributes centrally to immunity against Bt679, completely reverses the protective effect of MYb11, which further reduces nematode survival and fitness upon infection with Bt679. Our study highlights the complex interplay between host genetics, protective microbe, and pathogen in shaping metaorganism biology.

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Section: Resultsmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

The intricate triangular interaction between protective microbe, pathogen, and host genetics determines fitness of the metaorganism

Griem-Krey,

Petersen,

Hamerich

et al. 2023

Preprint

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“…Indicated sets of CFU/worm data were previously published, and data and methods are available from the indicated manuscript (Taylor and Vega 2021).…”

Section: Methodsmentioning

confidence: 99%

Sample pooling inflates error rates in between-sample comparisons: an empirical investigation of the statistical properties of count-based data

Vega

Taylor

2022

Preprint

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Heterogeneity is ubiquitous across individuals in biological data, and sample batching, a form of biological averaging, inevitably loses information about this heterogeneity. The consequences for inference from biologically averaged data are frequently opaque. Here we investigate a case where biological averaging is common - count-based measurement of bacterial load in individual Caenorhabditis elegans - to empirically determine the consequences of batching. We find that both central measures and measures of variation on individual-based data contain biologically relevant information that is useful for distinguishing between groups, and that batch-based inference readily produces both false positive and false negative results in these comparisons. These results support the use of individual rather than batched samples when possible, illustrate the importance of understanding the distributions of individual-based data in experimental systems, and indicate the need to consider effect size when drawing conclusions from these data.

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“…'Common garden' experiments, in which different C. elegans strains and related species were raised in identical compost microcosms, identified a significant contribution of host genetics to determining microbiome composition (17). Subsequent studies identified conserved regulatory pathways, including insulin/insulin-like (IIS) signaling (18,19) and the DBL-1/BMP pathway (12), as contributing to shaping of the gut microbiome. DBL-1 signaling further came to the forefront as a mechanism that controls a specific subset of gut bacteria, which has the potential to cause detrimental effects when control was impaired (12).…”

Section: Introductionmentioning

confidence: 99%

Identification of intestinal mediators ofCaenorhabditis elegansDBL-1/BMP immune signaling shaping gut microbiome composition

Trang,

Pees,

Karimzadegan

et al. 2023

Preprint

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The composition of the gut microbiome is determined by a complex interplay of diet, host genetics, microbe-microbe competition, abiotic factors, and stochasticity. Previous studies have demonstrated the importance of host genetics in community assembly of the Caenorhabditis elegans gut microbiome and identified a pivotal role for DBL-1/BMP immune signaling in determining the abundance of gut Enterobacteriaceae, in particular of the genus Enterobacter. However, the effects of DBL-1 signaling on gut bacteria were found to depend on its activation in extra-intestinal tissues, suggesting that yet unidentified intestinal factors must mediate these effects. In the present study, we used RNA-seq gene expression analysis of wildtype, dbl-1 and sma-3 mutants, and dbl-1 over-expressors to identify genes regulated by DBL-1/BMP signaling that take part in interactions with gut commensals. Following confirmation of several putative targets by qRT-PCR, we carried out colonization experiments with respective mutants raised on monocultures as well as on defined bacterial communities. These experiments identified five intestinal DBL-1/BMP targets, predicted to be secreted, that showed increased Enterobacteriaceae abundance compared to wildtype. The extent of increases was for the most part lower than those seen in DBL-1 pathway mutants, suggesting that identified mediators are components of a DBL-1-regulated antibacterial cocktail, which may additively contribute to shaping of gut microbiome composition.

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Host Immunity Alters Community Ecology and Stability of the Microbiome in a Caenorhabditis elegans Model

Cited by 24 publications

References 60 publications

The intricate triangular interaction between protective microbe, pathogen, and host genetics determines fitness of the metaorganism

The intricate triangular interaction between protective microbe, pathogen, and host genetics determines fitness of the metaorganism

Sample pooling inflates error rates in between-sample comparisons: an empirical investigation of the statistical properties of count-based data

Identification of intestinal mediators ofCaenorhabditis elegansDBL-1/BMP immune signaling shaping gut microbiome composition

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