Biology subjects

Midani, F. S.

Publications and source records attributed to Midani, F. S..

6 recordsLinked to original sources

bioRxiv2026

Infant gut microbiomes contribute to metabolic states that impact brain function

Alterations in the gut microbiome are associated with neurodevelopmental disorders, but causal mechanisms and therapeutic strategies remain undefined. Here, we demonstrate that human infant microbiomes isolated during the first six months of life drive behavioral impairments in mice and that microbiota-based interventions restore mice to normal behavior. Early-life microbiomes from twelve infants who later exhibited cognitive deficits at 2 years old (low-scoring) transferred adverse metabolic, brain, and behavioral phenotypes to mice, in contrast to microbiomes from twenty-three cognitively typical or high-scoring infants. Deficits in mice were rescued by fecal microbiota transplant from high-scoring infants or a rationally designed consortium that promoted amino acid levels. We confirmed lower fecal amino acid concentrations in low-scoring infants and replicated the association between early-life microbiome composition and cognitive outcomes in a second geographically independent infant cohort. Altogether, we discovered an early-life microbiome-mediated metabolic state causally linked to cognitive deficits and amenable to microbial intervention.

microbiology↗

bioRxiv2024

Emerging Clostridioides difficile ribotypes have divergent metabolic phenotypes

Clostridioides difficile is a gram-positive spore-forming pathogen that commonly causes diarrheal infections in the developed world. Although C. difficile is a genetically diverse species, certain ribotypes are overrepresented in human infections. It is unknown if metabolic adaptations are essential for the emergence of these epidemic ribotypes. Here, we tested carbon substrate utilization by 88 C. difficile isolates and looked for differences in growth between 22 ribotypes. By profiling clinical isolates, we assert that C. difficile is a generalist species capable of growing on a variety of carbon substrates. Further, C. difficile strains clustered by phylogenetic relationship and displayed ribotype-specific and clade-specific metabolic capabilities. Surprisingly, we observed that two emerging lineages, ribotypes 023 and 255, have divergent metabolic phenotypes. In addition, although C. difficile Clade 5 is the most evolutionary distant clade and often detected in animals, it displayed more robust growth on simple dietary sugars than Clades 1-4. Altogether, our results corroborate the generalist metabolic strategy of C. difficile and demonstrate lineage-specific metabolic capabilities. In addition, our approach can be adapted to the study of additional pathogens to ascertain their metabolic niches in the gut. IMPORTANCEThe gut pathogen Clostridioides difficile utilizes a wide range of carbon sources. Microbial communities can be rationally designed to combat C. difficile by depleting its preferred nutrients in the gut. However, C. difficile is genetically diverse with hundreds of identified ribotypes and most of its metabolic studies were performed with lab-adapted strains. Here, we profiled carbon metabolism by a myriad of C. difficile clinical isolates. While the metabolic capabilities of these isolates clustered by their genetic lineage, we observed surprising metabolic divergence between two emerging lineages. We also found that the most genetically distant clade grew robustly on simple dietary sugars, posing intriguing questions about the adaptation of C. difficile to the human gut. Altogether, our results underscore the importance of considering the metabolic diversity of pathogens in the study of their evolution and the rational design of therapeutic interventions.

microbiology↗

bioRxiv2024

Early life microbial succession in the gut follows common patterns in humans across the globe

Characterizing the dynamics of microbial community succession in the infant gut microbiome is crucial for understanding child health and development, but no normative model currently exists. Here, we estimate child age using gut microbial taxonomic relative abundances from metagenomes, with high temporal resolution ({+/-}3 months) for the first 1.5 years of life. Using 3,154 samples from 1,827 infants across 12 countries, we trained a random forest model, achieving a root mean square error of 2.61 months. We identified key taxonomic predictors of age, including declines in Bifidobacterium spp. and increases in Faecalibacterium prausnitzii and Lachnospiraceae. Microbial succession patterns are conserved across infants from diverse human populations, suggesting universal developmental trajectories. Functional analysis confirmed trends in key microbial genes involved in feeding transitions and dietary exposures. This model provides a normative benchmark of "microbiome age" for assessing early gut maturation that can be used alongside other measures of child development.

microbiology↗

bioRxiv2021

Impact of a human gut microbe on Vibrio cholerae host colonization through biofilm enhancement

Recent studies indicate that the human intestinal microbiota could impact the outcome of infection by Vibrio cholerae, the etiological agent of the diarrheal disease cholera. A commensal bacterium, Paracoccus aminovorans, was previously identified in high abundance in stool collected from individuals infected with V. cholerae when compared to stool from uninfected persons. However, if and how P. aminovorans interacts with V. cholerae has not been experimentally determined; moreover, whether any association between this bacterium alters the behaviors of V. cholerae to affect the disease outcome is unclear. Here we show that P. aminovorans and V. cholerae together form dual-species biofilm structures at the air-liquid interface, with previously uncharacterized novel features. Importantly, the presence of P. aminovorans within the murine small intestine enhances V. cholerae colonization in the same niche that is dependent on the Vibrio exopolysaccharide (VPS) and other major components of mature V. cholerae biofilm. These studies illustrate that dual-species biofilm formation is a plausible mechanism used by a gut microbe to increase the virulence of the pathogen, and this interaction may alter outcomes in enteric infections. Significance StatementWhile ample evidence suggests that the outcome of some enteric infections can be affected by the intestinal microbiota, how specific gut microbes change the behaviors of a pathogen is unclear. Here we characterize the interaction between Vibrio cholerae and Paracoccus aminovorans, a gut microbe known to increase in abundance in the intestines during active V. cholerae infection in humans. These two bacteria form a dual-species biofilm structure at the air-liquid interface, and the gut microbe increases the host colonization efficiency of V. cholerae. Importantly, our study identifies a previously unknown mechanism of gut microbe-pathogen interaction that has the potential to alter the disease outcome.

microbiology↗

bioRxiv2020

AMiGA: software for automated Analysis of Microbial Growth Assays

The analysis of microbial growth is one of the central methods in the field of microbiology. Microbial growth dynamics can be characterized by growth parameters including carrying capacity, exponential growth rate, and growth lag. However, growth assays with clinical isolates, fastidious organisms, or microbes under stress often produce atypical growth shapes that do not follow the classical microbial growth pattern. Here, we introduce the Analysis of Microbial Growth Assays (AMiGA) software which streamlines the analysis of growth curves without any assumptions about their shapes. AMiGA can pool replicates of growth curves and infer summary statistics for biologically meaningful growth parameters. In addition, AMiGA can quantify death phases and characterize diauxic shifts. It can also statistically test for differential growth under distinct experimental conditions. Altogether, AMiGA streamlines the organization, analysis, and visualization of microbial growth assays. IMPORTANCEOur current understanding of microbial physiology relies on the simple method of measuring microbial populations size over time and under different conditions. Many advances have increased the throughput of those assays and enabled the study of non-lab adapted microbes under diverse conditions that widely affect their growth dynamics. Our software provides an all-in-one tool for estimating the growth parameters of microbial cultures and testing for differential growth in a high-throughput and user-friendly fashion without any underlying assumptions about how microbes respond to their growth conditions.

microbiology↗

bioRxiv2020

Predicting Vibrio cholerae infection and disease severity using metagenomics in a prospective cohort study

BackgroundSusceptibility to Vibrio cholerae infection is impacted by blood group, age, and pre-existing immunity, but these factors only partially explain who becomes infected. A recent study used 16S rRNA amplicon sequencing to quantify the composition of the gut microbiome and identify predictive biomarkers of infection with limited taxonomic resolution. MethodsTo achieve increased resolution of gut microbial factors associated with V. cholerae susceptibility and identify predictors of symptomatic disease, we applied deep shotgun metagenomic sequencing to a cohort of household contacts of patients with cholera. ResultsUsing machine learning, we resolved species, strains, gene families, and cellular pathways in the microbiome at the time of exposure to V. cholerae to identify markers that predict infection and symptoms. Use of metagenomic features improved the precision and accuracy of prediction relative to 16S sequencing. We also predicted disease severity, although with greater uncertainty than our infection prediction. Species within the genera Prevotella and Bifidobacterium predicted protection from infection, and genes involved in iron metabolism also correlated with protection. ConclusionOur results highlight the power of metagenomics to predict disease outcomes and suggest specific species and genes for experimental testing to investigate mechanisms of microbiome-related protection from cholera. SUMMARYCholera infection and disease severity can be predicted using metagenomic sequencing of the gut microbiome pre-infection in a prospective cohort, and suggests potentially protective bacterial species and genes.

microbiology↗