No abstract

The gut microbiota contributes to host health and fitness, and imbalances in its composition are associated with pathology. However, what shapes microbiota composition is not clear, in particular the role of genetic factors. Previous work in Caenorhabditis elegans defined a characteristic worm gut microbiota significantly influenced by host genetics. The current work explores the role of central regulators of host immunity and stress resistance, employing qPCR and CFU counts to measure abundance of core microbiota taxa in mutants raised on synthetic communities of previously-isolated worm gut commensals. This revealed a bloom, specifically of Enterobacter species, in immune-compromised TGFβ/BMP mutants. Imaging of fluorescently labeled Enterobacter showed that TGFβ/BMP-exerted control operated primarily in the anterior gut and depended on multi-tissue contributions. Enterobacter commensals are common in the worm gut, contributing to infection resistance. However, disruption of TGFβ/BMP signaling turned a normally beneficial Enterobacter commensal to pathogenic. These results demonstrate specificity in gene-microbe interactions underlying gut microbial homeostasis and highlight the pathogenic potential of their disruption.

SNPs (Single Nucleotide Polymorphisms) are genetic markers whose precise identification is a prerequisite for association studies. Methods to identify them are currently well developed for model species, but rely on the availability of a (good) reference genome, and therefore cannot be applied to non-model species. They are also mostly tailored for whole genome (re-)sequencing experiments, whereas in many cases, transcriptome sequencing can be used as a cheaper alternative which already enables to identify SNPs located in transcribed regions. In this paper, we propose a method that identifies, quantifies and annotates SNPs without any reference genome, using RNA-seq data only. Individuals can be pooled prior to sequencing, if not enough material is available from one individual. Using pooled human RNA-seq data, we clarify the precision and recall of our method and discuss them with respect to other methods which use a reference genome or an assembled transcriptome. We then validate experimentally the predictions of our method using RNA-seq data from two non-model species. The method can be used for any species to annotate SNPs and predict their impact on the protein sequence. We further enable to test for the association of the identified SNPs with a phenotype of interest.

Symbiotic interactions are ubiquitous in nature and play a major role in driving the evolution of life. Interactions between partners are often mediated by shared signalling pathways, which strongly influence both partners' biology and the evolution of the association in various environments. As an example of 'common language', the regulation of the oxidative environment plays an important role in driving the evolution of symbiotic associations. Such processes have been occurring for billions of years, including the increase in Earth's atmospheric oxygen and the subsequent evolution of mitochondria. The effect of reactive oxygen species and reactive nitrogen species (RONS) has been characterized functionally, but the molecular dialogue between partners has not been integrated within a broader evolutionary context yet. Given the pleiotropic role of RONS in cell-cell communication, development and immunity, but also their associated physiological costs, we discuss here how their regulation can influence the establishment, the maintenance and the breakdown of various symbiotic associations. By synthesizing recent developments in redox biology, we aim to provide an interdisciplinary understanding of the influence of such mediators of interspecies communication on the evolution and stability of symbioses, which in turn can shape ecosystems and play a role in health and disease.