SignificanceOrganisms frequently exchange costly resources with other species. Theory suggests that this paradoxical cooperation between species might have its origins in waste consumption. When a species benefits from the waste of another, the recipient can evolve to aid the waste producer. The waste producer could then be selected to provide costly resources in return. We previously demonstrated the first step of this theorized process: Salmonella enterica evolved to secrete a costly amino acid to increase access to a byproduct generated by Escherichia coli. Here, we provide demonstration of a waste producer switching to costly cooperation. E. coli repeatedly evolved novel secretion of sugar to feed S. enterica. The results validate long-standing theory about the evolutionary origins of costly mutualism.

Microbes frequently rely on metabolites excreted by other bacterial species, but little is known about how this cross-feeding influences the effect of antibiotics. We hypothesized that when species rely on each other for essential metabolites, the minimum inhibitory concentration (MIC) for all species will drop to that of the “weakest link”—the species least resistant in monoculture. We tested this hypothesis in an obligate cross-feeding system that was engineered between Escherichia coli, Salmonella enterica, and Methylobacterium extorquens. The effect of tetracycline and ampicillin were tested on both liquid and solid media. In all cases, resistant species were inhibited at significantly lower antibiotic concentrations in the cross-feeding community than in monoculture or a competitive community. However, deviation from the “weakest link” hypothesis was also observed in cross-feeding communities apparently as result of changes in the timing of growth and cross-protection. Comparable results were also observed in a clinically relevant system involving facultative cross-feeding between Pseudomonas aeruginosa and an anaerobic consortium found in the lungs of cystic fibrosis patients. P. aeruginosa was inhibited by lower concentrations of ampicillin when cross-feeding than when grown in isolation. These results suggest that cross-feeding significantly alters tolerance to antibiotics in a variety of systems.

While gut microbiome and host gene regulation independently contribute to gastrointestinal disorders, it is unclear how the two may interact to influence host pathophysiology. Here we developed a machine learning-based framework to jointly analyse paired host transcriptomic (n = 208) and gut microbiome (n = 208) profiles from colonic mucosal samples of patients with colorectal cancer, inflammatory bowel disease and irritable bowel syndrome. We identified associations between gut microbes and host genes that depict shared as well as disease-specific patterns. We found that a common set of host genes and pathways implicated in gastrointestinal inflammation, gut barrier protection and energy metabolism are associated with disease-specific gut microbes. Additionally, we also found that mucosal gut microbes that have been implicated in all three diseases, such as Streptococcus, are associated with different host pathways in each disease, suggesting that similar microbes can affect host pathophysiology in a disease-specific manner through regulation of different host genes. Our framework can be applied to other diseases for the identification of host gene–microbiome associations that may influence disease outcomes.

The importance of sampling from globally representative populations has been well established in human genomics. In human microbiome research, however, we lack a full understanding of the global distribution of sampling in research studies. This information is crucial to better understand global patterns of microbiome-associated diseases and to extend the health benefits of this research to all populations. Here, we analyze the country of origin of all 444,829 human microbiome samples that are available from the world’s 3 largest genomic data repositories, including the Sequence Read Archive (SRA). The samples are from 2,592 studies of 19 body sites, including 220,017 samples of the gut microbiome. We show that more than 71% of samples with a known origin come from Europe, the United States, and Canada, including 46.8% from the US alone, despite the country representing only 4.3% of the global population. We also find that central and southern Asia is the most underrepresented region: Countries such as India, Pakistan, and Bangladesh account for more than a quarter of the world population but make up only 1.8% of human microbiome samples. These results demonstrate a critical need to ensure more global representation of participants in microbiome studies.

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Microbes frequently rely on metabolites excreted by other bacterial species, but little is known 1 about how this cross-feeding influences the effect of antibiotics. We hypothesized that when 2 species rely on each other for essential metabolites, the minimum inhibitory concentration (MIC) 3 for all species will drop to that of the "weakest link" -the species least resistant in monoculture. 4We tested this hypothesis in an obligate cross-feeding system that was engineered between 5Escherichia coli, Salmonella enterica, and Methylobacterium extorquens. The effect of 6 tetracycline and ampicillin were tested on both liquid and solid media. In all cases, resistant 7 species were inhibited at significantly lower antibiotic concentrations in the cross-feeding 8 community than in monoculture or a competitive community. However, deviation from the 9 "weakest link" hypothesis was also observed in cross-feeding communities apparently as result 10 of changes in the timing of growth and cross-protection. Comparable results were also observed 11 in a clinically relevant system involving facultative cross-feeding between Pseudomonas 12 aeruginosa and an anaerobic consortium found in the lungs of cystic fibrosis patients. P. 13 aeruginosa was inhibited by lower concentrations of ampicillin when cross-feeding than when 14 grown in isolation. These results suggest that cross-feeding significantly alters tolerance to 15 antibiotics in a variety of systems. 16 18All rights reserved. No reuse allowed without permission.was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.

Preprints are becoming well established in the life sciences, but relatively little is known about the demographics of the researchers who post preprints and those who do not, or about the collaborations between preprint authors. Here, based on an analysis of 67,885 preprints posted on bioRxiv, we find that some countries, notably the United States and the United Kingdom, are overrepresented on bioRxiv relative to their overall scientific output, while other countries (including China, Russia, and Turkey) show lower levels of bioRxiv adoption. We also describe a set of ‘contributor countries’ (including Uganda, Croatia and Thailand): researchers from these countries appear almost exclusively as non-senior authors on international collaborations. Lastly, we find multiple journals that publish a disproportionate number of preprints from some countries, a dynamic that almost always benefits manuscripts from the US.

With antibiotic resistance rates on the rise, it is critical to understand how microbial species interactions influence the evolution of resistance. In obligate mutualisms, the survival of any one species (regardless of its intrinsic resistance) is contingent on the resistance of its cross-feeding partners. This sets the community antibiotic sensitivity at that of the 'weakest link' species. In this study, we tested the hypothesis that weakest link dynamics in an obligate cross-feeding relationship would limit the extent and mechanisms of antibiotic resistance evolution. We experimentally evolved an obligate co-culture and monoculture controls along gradients of two different antibiotics. We measured the rate at which each treatment increased antibiotic resistance, and sequenced terminal populations to question whether mutations differed between mono-and co-cultures. In both rifampicin and ampicillin treatments, we observed that resistance evolved more slowly in obligate co-cultures of E. coli and S. enterica than in monocultures. While we observed similar mechanisms of resistance arising under rifampicin selection, under ampicillin selection different resistance mechanisms arose in co-cultures and monocultures. In particular, mutations in an essential cell division protein, ftsI, arose in S. enterica only in co-culture. A simple mathematical model demonstrated that reliance on a partner is sufficient to slow the rate of adaptation, and can change the distribution of adaptive mutations that are acquired. Our results demonstrate that cooperative metabolic interactions can be an important modulator of resistance evolution in microbial communities.