Biology subjects

Ghezzi, H.

Publications and source records attributed to Ghezzi, H..

5 recordsLinked to original sources

bioRxiv2026

Growth capacity and mortality burden shape microbial persistence under osmotic stress in Bacteroides thetaiotaomicron

Microbial persistence in the gut is central to sustaining beneficial host-microbiota interactions; however, characterizing determinants of persistence in vivo can be challenging due to the complexity of native microbial communities interacting with the host. Here, we used a defined microbial consortium to demonstrate that intrinsic in vitro growth capacity becomes increasingly predictive of in vivo relative abundance as intestinal osmolality increases. In Bacteroides thetaiotaomicron, in vivo abundance was higher than predicted from growth capacity alone, indicating that additional physiological factors contribute to persistence. We identify mortality as one such determinant: adaptation to prolonged osmotic stress markedly reduced cell loss without enhancing growth capacity. This adaptive phenotype was associated with rapid and reversible phase variation in cell surface-associated PUL78/80 rather than fixed de novo mutations, with the PUL78/80-OFF state becoming progressively enriched among surviving cells as mortality increased. Our findings demonstrate that in addition to growth capacity, reduced cell loss can provide a distinct route to microbial persistence during environmental perturbation.

microbiology↗

bioRxiv2026

The effect of cell death on DNA-replication-based estimates of microbial population growth

Inferring bacterial growth rates is fundamental to understanding microbial interactions and community dynamics, but remains difficult in natural settings where time points are limited or organisms are unculturable. In these cases, a widely used method is the origin-to-terminus ratio, or peak-to-trough ratio (PTR), which estimates DNA replication activity from origin and terminus copy numbers. Although PTR is theoretically related to bacterial growth rate, it is frequently benchmarked against population growth rate, which reflects the balance between cell division and loss. Understanding when and why these measures diverge is therefore important for validating PTR-based approaches. To quantify how departures from steady growth affect PTR, population growth rate, and bacterial growth rate, we developed a stochastic, cell-based model that explicitly tracks DNA replication, cell division, and cell death. We show that transient stress-induced mortality and heterogeneous survival can cause PTR to fail to reflect population growth rate while still reflecting bacterial growth rate. We experimentally validated these predictions by exposing \textit{Escherichia coli} to osmotic shock or antibiotics, and measuring population growth rate and DNA replication activity. We further show that initial physiological state, lag before replication resumes, and abrupt growth arrest can alter the relationship between PTR and population growth rate. In the presence of mortality, lag can increase PTR's correspondence with population growth rate while decreasing its correspondence with bacterial growth rate. These results provide a mechanistic and quantitative framework for interpreting PTR across changing growth states, mortality regimes, and environmental perturbations.

microbiology↗

bioRxiv2025

Uniform bacterial genetic diversity along the guts of mice inoculated with human stool

Environmental gradients throughout the digestive tract shape spatial variation in the composition and abundance of bacterial species along the gut. However, much less is known about how genetic diversity within bacterial species is distributed along the gut. Understanding this distribution is important because bacterial genetic variants confer traits that influence both microbiome function and host physiology, including local inflammation and nutrient metabolism. Thus, to understand how the microbiome functions at a mechanistic level, it is essential to understand how genetic diversity is organized along the gut. In this study, we profiled genetic diversity of approximately 30 common gut commensal bacteria in five regions along the gut lumen in germ-free mice colonized with the same healthy human stool sample. Although species composition varied considerably along the gut, genetic diversity within species was substantially more uniform. Driving this uniformity were similar strain frequencies along the gut, implying that multiple, genetically divergent strains of the same species can coexist within a host without spatially segregating. Additionally, the approximately 60 unique evolutionary adaptations arising within mice tended to sweep throughout the gut, showing little gut region specificity. We then analyzed metagenomic samples collected along the guts of conventional mice and healthy humans and found similar dynamics with their natural microbiomes, suggesting that uniform bacterial genetic diversity may be common to multiple host species. Together, our findings demonstrate that uniform spatial distribution of genetic diversity along the gastrointestinal tract is a robust feature of mammalian gut ecosystems.

microbiology↗

bioRxiv2024

Early life intestinal inflammation alters gut microbiome, impairing gut-brain communication and reproductive behavior in mice

Despite recent advances in understanding the connection between the gut microbiota and the adult brain, there remains a wide knowledge gap in how gut inflammation impacts brain development. We hypothesized that intestinal inflammation in early life would negatively affect neurodevelopment through dysregulation of microbiota communication to the brain. We therefore developed a novel pediatric chemical model of inflammatory bowel disease (IBD), an incurable condition affecting millions of people worldwide. IBD is characterized by chronic intestinal inflammation, and has comorbid symptoms of anxiety, depression and cognitive impairment. Significantly, 25% of patients with IBD are diagnosed during childhood, and the effect of chronic inflammation during this critical period of development is largely unknown. This study investigated the effects of early-life gut inflammation induced by DSS (dextran sulfate sodium) on a range of microbiota, endocrine, and behavioral outcomes, focusing on sex-specific impacts. DSS-treated mice exhibited increased intestinal inflammation, altered microbiota membership, and changes in microbiota-mediated circulating metabolites. The majority of behavioral measures were unaffected, with the exception of impaired mate-seeking behaviors in DSS-treated males. DSS-treated males also showed significantly smaller seminal vesicles, lower circulating androgens, and decreased intestinal hormone-activating enzyme activity. In the brain, microglia morphology was chronically altered with DSS treatment in a sex-specific manner. The results suggest that early-life gut inflammation causes changes in gut microbiota composition, affecting short-chain fatty acid (SCFA) producers and glucuronidase (GUS) activity, correlating with altered SCFA and androgen levels. The findings emphasize the developmental sensitivity to inflammation-induced changes in endocrine signalling and underscore long-lasting physiological and microbiome changes associated with juvenile IBD. HighlightsEarly-life gut inflammation produces sex-specific effects on i) microbiome, ii) sex hormones and iii) behaviour. Both sexes show disrupted gut bacterial members that regulate sex hormone levels. Male mice demonstrate deficits in mate seeking, which may be mediated by reduced androgen levels. Both male and female mice demonstrate shifts in hippocampal microglial morphology.

neuroscience↗

bioRxiv2023

PUPpy: a primer design pipeline for substrain-level microbial detection and absolute quantification.

Characterizing microbial communities at high-resolution and with absolute quantification is crucial to unravel the complexity and diversity of microbial ecosystems. This can be achieved with PCR assays, which enable highly selective detection and absolute quantification of microbial DNA. However, a major challenge that has hindered PCR applications in microbiome research is the design of highly specific primer sets that exclusively amplify intended targets. Here, we introduce Phylogenetically Unique Primers in python (PUPpy), a fully automated pipeline to design microbe- and group-specific primers within a given microbial community. PUPpy can be executed from a user-friendly GUI, or two simple terminal commands, and it only requires coding sequence files of the community members as input. PUPpy-designed primers enable the detection of individual microbes and quantification of absolute microbial abundance in defined communities below the strain level. We experimentally evaluated the performance of PUPpy-designed primers using two bacterial communities as benchmarks. Each community was comprised of 10 members, exhibiting a range of genetic similarities that spanned from different phyla to substrains. PUPpy-designed primers also enable the detection of groups of bacteria in an undefined community, such as the detection of a gut bacterial family in a complex stool microbiota sample. Taxon-specific primers designed with PUPpy showed 100% specificity to their intended targets, without unintended amplification, in each community tested. Lastly, we show absolute quantification of microbial abundance using PUPpy-designed primers in ddPCR, benchmarked against 16S rRNA and shotgun sequencing. Our data shows that PUPpy-designed microbe-specific primers can be used to quantify substrain-level absolute counts, providing more resolved and accurate quantification in defined communities than short-read 16S rRNA and shotgun sequencing. ImportanceProfiling microbial communities at high resolution and with absolute quantification is essential to uncover hidden ecological interactions within microbial ecosystems. Nevertheless, achieving resolved and quantitative investigations has been elusive due to methodological limitations in distinguishing and quantifying highly related microbes. Here, we describe PUPpy, an automated computational pipeline to design taxon-specific primers within defined microbial communities. Taxon-specific primers can be used to selectively detect and quantify individual microbes and larger taxa within a microbial community. PUPpy achieves substrain-level specificity without the need for computationally intensive databases and prioritises user-friendliness by enabling both terminal and graphical user interface (GUI) applications. Altogether, PUPpy enables fast, inexpensive, and highly accurate perspectives into microbial ecosystems, supporting the characterization of bacterial communities in both in vitro and complex microbiota settings.

microbiology↗