Humans have co-speciated with their gut-resident microbes, but it is difficult to infer features of our ancestral microbiome. Here, we examine the microbiome profile of 350 stool samples collected longitudinally for over a year from the Hadza hunter-gatherers of Tanzania. The data reveal annual cyclic reconfiguration of the microbiome, in which some taxa become undetectable only to reappear in a subsequent season. Comparison of the Hadza dataset with data collected from 18 populations in 16 countries with varying lifestyles reveals that gut community membership corresponds to modernization: Notably, the taxa within the Hadza that are the most seasonally volatile similarly differentiate industrialized and traditional populations. These data indicate that some dynamic lineages of microbes have decreased in prevalence and abundance in modernized populations.

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Osmotic diarrhea is a prevalent condition in humans caused by food intolerance, malabsorption, and widespread laxative use. Here, we assess the resilience of the gut ecosystem to osmotic perturbation at multiple length and timescales using mice as model hosts. Osmotic stress caused reproducible extinction of highly abundant taxa and expansion of less prevalent members in human and mouse microbiotas. Quantitative imaging revealed decimation of the mucus barrier during osmotic perturbation, followed by recovery. The immune system exhibited temporary changes in cytokine levels and a lasting IgG response against commensal bacteria. Increased osmolality prevented growth of commensal strains in vitro, revealing one mechanism contributing to extinction. Environmental availability of microbiota members mitigated extinction events, demonstrating how species reintroduction can affect community resilience. Our findings (1) demonstrate that even mild osmotic diarrhea can cause lasting changes to the microbiota and host and (2) lay the foundation for interventions that increase system-wide resilience.

Although mass spectrometry is well-suited to identifying thousands of possible protein post-translational modifications (PTMs), it has historically been biased towards just a few. To measure the entire set of PTMs across diverse proteomes, software must overcome the dual challenges of searching enormous search spaces and distinguishing correct from incorrect spectrum interpretations. Here, we describe TagGraph, a computational tool that overcomes both challenges with an unrestricted string-based search method that is as much as 350-fold faster than existing approaches, and a probabilistic validation model we optimized for PTM assignments. We applied TagGraph to a published human proteomic data set of 25 million mass spectra and tripled confident spectrum identifications compared its original analysis. We identified thousands of modification types on almost one million sites in the proteome. We show new contexts for highly abundant yet understudied PTMs such as proline hydroxylation, and its unexpected association with cancer mutations. By enabling broad PTM characterization TagGraph informs how their functions and regulation intersect.

Persistent diarrhea in CDI correlates with intestinal inflammation and not fecal pathogen burden. These findings suggest that modulation of host response, rather than adjustments to antimicrobial regimens, might be a more effective approach to patients with unremitting disease.