About

My data science lab has been involved in various aspects of microbiome research. We have developed methods for analyzing microbiome data, and we have applied those methods in clinical studies to better diagnose and predict disease. We have also been involved in several data science projects related to sustainability.

Research topics

• Bioinformatics
• Biology
• Computational biology
• Medicine
• Computer Science
• Internal medicine
• Pathology
• Psychology
• Data science
• Immunology
• Genetics

Selected publications

• Assembly of the infant gut microbiome and resistome are linked to bacterial strains in mother's milk

  Zenodo (CERN European Organization for Nuclear Research) · 2026-02-02

  datasetOpen access

  Supplementary Tables for the publication: "Assembly of the infant gut microbiome and resistome are linked to bacterial strains in mother’s milk" - Ferretti and Allert et al. Nature Communications 2025 The establishment of the gut microbiome in early life is critical for healthy infant development. Although human milk is recommended as sole nutrition for the infant, little is known about how variation in the milk microbiome shapes the microbial communities in the infant gut. Here, we quantified the similarity between the maternal milk and the infant gut microbiomes using 507 metagenomic samples collected from 195 mother-infant pairs at one, three, and six months postpartum. Microbial taxonomic overlap between milk and the infant gut was driven by Bifidobacterium longum, and infant microbiomes dominated by B. longum showed greater temporal stability than those dominated by other species. We identified numerous instances of strain sharing between milk and the infant gut, involving both commensal (e.g. B. longum) and pathobiont species (e.g. K. pneumoniae). Shared strains also included typically oral species such as S. salivarius and V. parvula, suggesting possible transmission from the infant’s oral cavity to the mother’s milk. At one month, the infant gut microbiome was enriched in biosynthetic pathways, suggesting that early colonisers might be more metabolically independent than those present at six months. Lastly, we observed significant overlap in antimicrobial resistance gene carriage within mother-infant pairs. Together, our results suggest that the human milk microbiome has an important role in the assembly, composition, and stability of the infant gut microbiome. More info at: https://github.com/blekhmanlab/milk_infant_microbiome

  PublisherDOI

• Mechanistic insights into microbiome-dependent and personalized responses to dietary fibre in a randomized controlled trial

  medRxiv · 2025-11-21

  preprintOpen access

  Dietary fiber supplementation can reduce cardiometabolic risk, but its effective use is limited by incomplete understanding of fibre-microbiome interactions and highly individualized responses. We tested acacia gum (AG; fermentable fibre), resistant starch type 4 (RS4; fermentable fibre), and microcrystalline cellulose (MCC; non-fermentable control fibre) in a six-week randomized trial in adults with excess body weight. Multi-omics profiling revealed distinct, structure-specific microbiota and short-chain fatty acid shifts with AG and RS4, which were not directly linked to physiological outcomes. Improvements in inflammation, gut barrier function, and satiety occurred across all arms, indicating fermentation-independent effects. AG reduced plasma ghrelin, linked to microbial carbohydrate-active enzyme genes targeting its structures. Machine-learning models predicted individualized, fiber-specific effects on blood pressure (AG) and C-reactive protein (RS4) from microbial pathways and fecal bile acids. These findings delineate fermentation-dependent and independent mechanisms of fibre action and provide a mechanistic basis for personalized fibre supplementation. Trial registration: ClinicalTrials.gov NCT02322112.

  PublisherDOI

• A Randomized Pilot Study of Time-Restricted Eating Shows Minimal Microbiome Changes

  Nutrients · 2025-01-04 · 3 citations

  articleOpen access

  Objective: TRE is an emerging approach in obesity treatment, yet there is limited data on how it influences gut microbiome composition in humans. Our objective was to characterize the gut microbiome of human participants before and after a TRE intervention. This is a secondary analysis of a previously published clinical trial examining the effects of time-restricted eating (TRE). Methods: In a previously published, 12-week randomized controlled trial, Chow et al. evaluated the effects of an 8-h TRE intervention on body composition in human participants. Chow et al. demonstrated significant reductions in weight, lean mass, and visceral fat in the TRE group compared to those following time-unrestricted eating (non-TRE). Stool samples were collected by a subset of those participants using home kits at both baseline and post-intervention for shotgun metagenomic sequencing for this secondary analysis. Microbiome community composition was compared before and after intervention as alpha and beta diversity. Results: Sixteen participants provided stool samples (eight in the TRE group and eight in the non-TRE group). Stool samples were collected from all participants at at least one time point, but both pre- and post-treatment samples were available from only five participants who completed both baseline and post-treatment collections. In alignment with the findings of Chow et al., the participants in the TRE group of the secondary analysis who collected microbiome sample(s) successfully reduced their eating window from an average of 15.3 ± 0.8 h at baseline to 9.3 ± 1.7 h during the intervention (mean ± SD, p < 0.001) and the non-TRE group’s eating window remained unchanged. While the TRE group lost weight and visceral fat mass, no effect of the TRE intervention was observed on alpha diversity (Shannon index, Simpson index, and number of taxa, linear mixed models), beta diversity (Bray–Curtis, PERMANOVA), even after controlling for weight and visceral fat changes. Conclusions: Our analysis did not detect any significant differences in gut microbiome composition or diversity indices between participants undergoing a TRE intervention and those in the control group. The study’s findings are limited by a small sample size, short duration, and the collection of stool samples at only two time points. Future studies with larger sample sizes, longer durations, and more frequent sampling, and collection of detailed dietary data are needed to better understand the relationship between TRE and gut microbiome dynamics.

  PublisherOA PDFDOI

• Gut mycobiome maturation and its determinants during early childhood: a comparison of ITS2 amplicon and shotgun metagenomic sequencing approaches

  Frontiers in Microbiology · 2025-05-21 · 1 citations

  articleOpen access

  Introduction Microbial colonization of the gut in early life is important for the development of metabolism, immunity, and the brain. Fungi and bacteria both colonize the human infant gut. The relatively smaller contribution of fungi to the gut microbiome, as compared to bacteria, has posed technical challenges for the precise characterization of fungal communities (mycobiomes) and limited the ability to longitudinally examine mycobiome development. Background The aims of this study were to (1) characterize mycobiome maturation and identify clinical determinants of mycobiome compositional variation during the first 2 years of life and (2) compare two sequencing approaches (ITS2 amplicon and whole genome metagenomics) for characterizing mycobiome maturational features. Longitudinal fecal samples and associated clinical metadata were obtained from subjects enrolled as part of the MAGIC (Microbiome, Antibiotics and Growth Infant Cohort) study. Results Overall, fungal richness increased and mycobiome composition changed in a similar ordered pattern during the first 2 years of life utilizing either amplicon or metagenomic sequencing approaches. Less resolution of taxa to species and genera levels was observed for the metagenomic dataset. The predominant taxa identified by both sequencing approaches, Candida albicans , Saccharomyces / S. cerevisiae , and Malassezia restricta , each exhibited similar dynamics in abundances and prevalences over the first 2 years of life, irrespective of sequencing approach. Antibiotic exposure and breastfeeding status contributed to time-specific mycobiome compositional variation, results that were consistent for both types of sequence datasets. Candida albicans exhibited altered abundance dynamics in association with perinatal antibiotic exposure and birth mode for both sequencing approaches. Post hoc analyses suggested that the birth mode association could be driven by exposure to perinatal antibiotics in children delivered by cesarean section rather than by birth mode itself. Discussion In summary, amplicon and metagenomic sequencing approaches provide generally similar results with respect to mycobiome maturational dynamics and the contribution of clinical variables to variation. Differences in taxa identification by the two approaches likely due to sequence database differences, primer/genome sequence variation, and/or sequencing depth should be taken into consideration.

  PublisherDOI

• Shared environments can facilitate microbial transmission and alter metabolic outcomes

  Gut Microbes · 2025-09-30 · 1 citations

  articleOpen accessCorresponding

  ). Our findings show the complexity of microbiome adaptation to industrialization, revealing how environmental microbial exchange and diet interplay can shape gut communities and their metabolic consequences.

  PublisherDOI

• Cardiometabolic benefits of a non-industrialized-type diet are linked to gut microbiome modulation

  Cell · 2025-01-23 · 50 citations

  articleOpen access

  Industrialization adversely affects the gut microbiome and predisposes individuals to chronic non-communicable diseases. We tested a microbiome restoration strategy comprising a diet that recapitulated key characteristics of non-industrialized dietary patterns (restore diet) and a bacterium rarely found in industrialized microbiomes (Limosilactobacillus reuteri) in a randomized controlled feeding trial in healthy Canadian adults. The restore diet, despite reducing gut microbiome diversity, enhanced the persistence of L. reuteri strain from rural Papua New Guinea (PB-W1) and redressed several microbiome features altered by industrialization. The diet also beneficially altered microbiota-derived plasma metabolites implicated in the etiology of chronic non-communicable diseases. Considerable cardiometabolic benefits were observed independently of L. reuteri administration, several of which could be accurately predicted by baseline and diet-responsive microbiome features. The findings suggest that a dietary intervention targeted toward restoring the gut microbiome can improve host-microbiome interactions that likely underpin chronic pathologies, which can guide dietary recommendations and the development of therapeutic and nutritional strategies.

  PublisherDOI

• Metagenomic source tracking after microbiota transplant therapy

  Gut Microbes · 2025-04-14 · 4 citations

  articleOpen accessSenior authorCorresponding

  Reliable engraftment assessment of donor microbial communities and individual strains is an essential component of characterizing the pharmacokinetics of microbiota transplant therapies (MTTs). Recent methods for measuring donor engraftment use whole-genome sequencing and reference databases or metagenome-assembled genomes (MAGs) to track individual bacterial strains but lack the ability to disambiguate DNA that matches both donor and patient microbiota. Here, we describe a new, cost-efficient analytic pipeline, MAGEnTa, which compares post-MTT samples to a database comprised MAGs derived directly from donor and pre-treatment metagenomic data, without relying on an external database. The pipeline uses Bayesian statistics to determine the likely sources of ambiguous reads that align with both the donor and pre-treatment samples. MAGEnTa recovers engrafted strains with minimal type II error in a simulated dataset and is robust to shallow sequencing depths in a downsampled dataset. Applying MAGEnTa to a dataset from a recent MTT clinical trial for ulcerative colitis, we found the results to be consistent with 16S rRNA gene SourceTracker analysis but with added MAG-level specificity. MAGEnTa is a powerful tool to study community and strain engraftment dynamics in the development of MTT-based treatments that can be integrated into frameworks for functional and taxonomic analysis.

  PublisherDOI

• Assembly of the infant gut microbiome and resistome are linked to bacterial strains in mother’s milk

  bioRxiv (Cold Spring Harbor Laboratory) · 2024-01-28 · 6 citations

  preprintOpen access

  Abstract The establishment of the gut microbiome in early life is critical for healthy infant development. Although human milk is recommended as sole nutrition for the infant, little is known about how variation in the milk microbiome shapes the microbial communities in the infant gut. Here, we quantified the similarity between the maternal milk and the infant gut microbiome using 507 metagenomic samples collected from 195 mother-infant pairs at one, three, and six months postpartum. Microbial taxonomic overlap between milk and the infant gut was driven by Bifidobacterium longum , and infant microbiomes dominated by B. longum showed greater temporal stability than those dominated by other species. We identified numerous instances of strain sharing between milk and the infant gut, involving both commensal (e.g. B. longum ) and pathobiont species (e.g. K. pneumoniae ). Shared strains also included typically oral species such as S. salivarius and V. parvula , suggesting possible transmission from the infant’s oral cavity to the mother’s milk. At one month, the infant gut microbiome was enriched in biosynthetic pathways, suggesting that early colonisers might be more metabolically independent than later ones. Lastly, we observed significant overlap in antimicrobial resistance gene carriage within mother-infant pairs. Together, our results suggest that the human milk microbiome has an important role in the assembly, composition, and stability of the infant gut microbiome.

  PublisherOA PDFDOI

• Sugar-rich foods exacerbate antibiotic-induced microbiome injury

  bioRxiv (Cold Spring Harbor Laboratory) · 2024-10-17 · 5 citations

  preprintOpen access

  Intestinal microbiota composition is implicated in several diseases; understanding the factors that influence it are key to elucidating host-commensal interactions and to designing microbiome-targeted therapies. We quantified how diet influences microbiome dynamics in hospitalized patients. We recorded 9,419 meals consumed by 173 patients undergoing hematopoietic cell transplantation and profiled the microbiome in 1,009 longitudinally collected stool samples from 158 of them. Caloric intake was correlated with fecal microbiota diversity. Bayesian inference revealed associations between intake of sweets or sugars during antibiotic exposure with microbiome disruption, as assessed by low diversity or expansion of the pathobiont Enterococcus. We validated this observation experimentally, finding that sucrose exacerbated antibiotic-induced Enterococcus expansion in mice. Taken together, our results suggest that avoiding sugar-rich foods during antibiotic treatment may reduce microbiome injury.

  PublisherOA PDFDOI

• Maternal oral probiotic use is associated with decreased breastmilk inflammatory markers, infant fecal microbiome variation, and altered recognition memory responses in infants—a pilot observational study

  Frontiers in Nutrition · 2024-09-25 · 6 citations

  articleOpen access

  Introduction: Early life gut microbiomes are important for brain and immune system development in animal models. Probiotic use has been proposed as a strategy to promote health via modulation of microbiomes. In this observational study, we explore if early life exposure to probiotics via the mother during pregnancy and lactation, is associated with decreased inflammation in breastmilk, maternal and infant microbiome variation, and altered infant neurodevelopmental features. Methods: Exclusively breastfeeding mother-infant dyads were recruited as part of the "Mothers and Infants Linked for Healthy Growth (MILk) Study." Probiotic comparison groups were defined by exposure to maternal probiotics (NO/YES) and by timing of probiotic exposure (prenatal, postnatal, total). C-reactive protein (CRP) and IL-6 levels were determined in breastmilk by immunoassays, and microbiomes were characterized from 1-month milk and from 1- and 6-month infant feces by 16S rDNA sequencing. Infant brain function was profiled via electroencephalogram (EEG); we assessed recognition memory using event-related potential (ERP) responses to familiar and novel auditory (1 month) and visual (6 months) stimuli. Statistical comparisons of study outcomes between probiotic groups were performed using permutational analysis of variance (PERMANOVA) (microbiome) and linear models (all other study outcomes), including relevant covariables as indicated. Results: ). In addition, maternal probiotic exposure was associated with differences in infant ERP features at 6-months of age. Specifically, infants who were exposed to postnatal maternal probiotics (between the 1- and 6-month study visits) via breastfeeding/breastmilk, had larger differential responses between familiar and novel visual stimuli with respect to the late slow wave component of the EEG, which may indicate greater memory updating potential. The milk of mothers of this subgroup of infants had lower IL-6 levels and infants had different 6-month fecal microbiomes as compared to those in the "NO" maternal probiotics group. Discussion: These results support continued research into "Microbiota-Gut-Brain" connections during early life and the role of pre- and postnatal probiotics in mothers to promote healthy microbiome-associated outcomes in infants.

  PublisherOA PDFDOI

Recent grants

• Early life antibiotics, gut microbiome development, and risk of childhood obesity

  NIH · $3.7M · 2016–2022

Frequent coauthors

• Rob Knight

  University of California, San Diego

  103 shared

• Tonya Ward

  89 shared

• Gabriel A. Al‐Ghalith

  72 shared

• Robin R. Shields‐Cutler

  Macalester College

  68 shared

• Jonathan B. Clayton

  University of Nebraska at Omaha

  47 shared

• Curtis Huttenhower

  Harvard University

  47 shared

• Ramnik J. Xavier

  Broad Institute

  45 shared

• Luke Thompson

  Mississippi State University

  43 shared

Labs

• Knights LabPI

  Data mining and machine learning to understand the natural world and human microbiome

Awards & honors

• 2023: Charles E. Bowers Faculty Teaching Award
• 2015: McKnight Land-Grant Professorship