Biology subjects

Holmes, S. P.

Publications and source records attributed to Holmes, S. P..

15 recordsLinked to original sources

bioRxiv2024

Sex differences and immune correlates of Long COVID development, persistence, and resolution

Sex differences have been observed in acute COVID-19 and Long COVID (LC) outcomes, with greater disease severity and mortality during acute infection in males and a greater proportion of females developing LC. We hypothesized that sex-specific immune dysregulation contributes to the pathogenesis of LC. To investigate the immunologic underpinnings of LC development and persistence, we used single-cell transcriptomics, single-cell proteomics, and plasma proteomics on blood samples obtained during acute SARS-CoV-2 infection and at 3 and 12 months post-infection in a cohort of 45 patients who either developed LC or recovered. Several sex-specific immune pathways were associated with LC. Specifically, males who would develop LC at 3 months had widespread increases in TGF-{beta} signaling during acute infection in proliferating NK cells. Females who would develop LC demonstrated increased expression of XIST, an RNA gene implicated in autoimmunity, and increased IL1 signaling in monocytes at 12 months post infection. Several immune features of LC were also conserved across sexes. Both males and females with LC had reduced co-stimulatory signaling from monocytes and broad upregulation of NF-{kappa}B transcription factors. In both sexes, those with persistent LC demonstrated increased LAG3, a marker of T cell exhaustion, reduced ETS1 transcription factor expression across lymphocyte subsets, and elevated intracellular IL-4 levels in T cell subsets, suggesting that ETS1 alterations may drive an aberrantly elevated Th2-like response in LC. Altogether, this study describes multiple innate and adaptive immune correlates of LC, some of which differ by sex, and offers insights toward the pursuit of tailored therapeutics. One Sentence SummaryThis multi-omic analysis of Long COVID reveals sex differences and immune correlates of Long COVID development, persistence, and resolution.

immunology↗

bioRxiv2023

Disrupted memory T cell expansion in HIV-exposed uninfected infants is preceded by premature skewing of T cell receptor clonality.

While preventing vertical HIV transmission has been very successful, the increasing number of HIV-exposed uninfected infants (iHEU) experience an elevated risk to infections compared to HIV-unexposed and uninfected infants (iHUU). Immune developmental differences between iHEU and iHUU remains poorly understood and here we present a longitudinal multimodal analysis of infant immune ontogeny that highlights the impact of HIV/ARV exposure. Using mass cytometry, we show alterations and differences in the emergence of NK cell populations and T cell memory differentiation between iHEU and iHUU. Specific NK cells observed at birth were also predictive of acellular pertussis and rotavirus vaccine-induced IgG and IgA responses, respectively, at 3 and 9 months of life. T cell receptor V{beta} clonotypic diversity was significantly and persistently lower in iHEU preceding the expansion of T cell memory. Our findings show that HIV/ARV exposure disrupts innate and adaptive immunity from birth which may underlie relative vulnerability to infections.

immunology↗

bioRxiv2022

Longitudinal dynamics of the human vaginal ecosystem across the reproductive cycle

The vaginal ecosystem is closely tied to human health and reproductive outcomes. However, its dynamics in the wake of childbirth remain poorly characterized. Here, we profiled the vaginal microbiota and cytokine milieu of subjects sampled throughout pregnancy (two cohorts; n = 196 pregnancies) and, in a subset, for one year postpartum (one cohort; n = 72 pregnancies). Delivery was associated with a vaginal pro-inflammatory cytokine response and the depletion of dominant taxa - typically, Lactobacillus species. By contrast, neither the progression of gestation nor the approach of labor strongly altered the vaginal ecosystem. At ~9.5 months postpartum (the latest timepoint at which cytokines were analyzed), elevated inflammation was associated with vaginal bacterial communities that had remained perturbed (i.e., highly diverse) from the time of delivery. Using time-to-event analysis, we found that the one-year postpartum probability of transitioning to Lactobacillus dominance was 49.4% (95% confidence interval (CI) [33.6%, 61.5%]; n = 58 at-risk cases, 86.2% of whom experienced this state prior to delivery). As diversity and inflammation declined postpartum, dominance by L. crispatus, the quintessential health-associated state, failed to recover: its prevalence before, immediately after, and one year after delivery was 41%, 4%, and 9%, respectively. Over the same period, states quasi-dominated by non-Lactobacillus species grew more common. Prompted by these findings, we revisited our pre-delivery data, discovering that a history of prior live birth was associated with a lower odds of L. crispatus dominance in pregnant subjects (odds ratio (OR) 0.14; 95% CI [0.06, 0.32]; P < 0.001) - an outcome modestly tempered by a longer (>18-month) interpregnancy interval. Our results suggest that reproductive history and childbirth in particular remodel the vaginal ecosystem and that the timing and degree of recovery from delivery may help determine the subsequent health of the woman and of future pregnancies.

microbiology↗

bioRxiv2022

Comparative analysis of cell-cell communication at single-cell resolution

Inference of cell-cell communication (CCC) from single-cell RNA-sequencing data is a powerful technique to uncover putative axes of multicellular coordination, yet existing methods perform this analysis at the level of the cell type or cluster, discarding single-cell level information. Here we present Scriabin - a flexible and scalable framework for comparative analysis of CCC at single-cell resolution. We leverage multiple published datasets to show that Scriabin recovers expected CCC edges and use spatial transcriptomic data, genetic perturbation screens, and direct experimental manipulation of receptor-ligand interactions to validate that the recovered edges are biologically meaningful. We then apply Scriabin to uncover co-expressed programs of CCC from atlas-scale datasets, validating known communication pathways required for maintaining the intestinal stem cell niche and revealing species-specific communication pathways. Finally, we utilize single-cell communication networks calculated using Scriabin to follow communication pathways that operate between timepoints in longitudinal datasets, highlighting bystander cells as important initiators of inflammatory reactions in acute SARS-CoV-2 infection. Our approach represents a broadly applicable strategy to leverage single-cell resolution data maximally toward uncovering CCC circuitry and rich niche-phenotype relationships in health and disease.

cell biology↗

bioRxiv2022

Profiling of the human intestinal microbiome and bile acids under physiologic conditions using an ingestible sampling device

The spatiotemporal structure of the human microbiome and metabolome reflects and determines regional intestinal physiology and may have implications for disease. Yet, we know little about the distribution of microbes and their products in the gut because of reliance on stool samples and limited access only to some regions of the gut using endoscopy in fasting or sedated individuals. To address these deficiencies, we developed and evaluated a safe, ingestible device that collects samples from multiple regions of the human intestinal tract during normal digestion. The collection of 240 intestinal samples from 15 healthy individuals using the device revealed significant differences between microbes and metabolites present in the intestines versus stool. Certain microbial taxa were differentially enriched, and bile acid profiles varied along the intestines and were highly distinct from those of stool. Correlations between gradients in bile acid concentrations and microbial abundance predicted species that altered the bile acid pool through deconjugation. Overall, we identified heterogeneous intestinal profiles of bacterial taxa and metabolites indicating that non-invasive multi-regional sampling of the intestinal tract under physiological conditions can help elucidate the roles of the gut microbiome and metabolome in human physiology and disease.

microbiology↗

bioRxiv2021

Sub-communities of the vaginal ecosystem in pregnant and non-pregnant women.

Diverse and non-Lactobacillus-dominated vaginal microbial communities are associated with adverse health outcomes such as preterm birth and the acquisition of sexually transmitted infections. Despite the importance of recognizing and understanding the key risk-associated features of these communities, their heterogeneous structure and properties remain ill-defined. Clustering approaches are commonly used to characterize vaginal communities, but they lack sensitivity and robustness in resolving substructures and revealing transitions between potential sub-communities. Here, we address this need with an approach based on mixed membership topic models, using longitudinal data from cohorts of pregnant and non-pregnant study participants. We identify several non-Lactobacillus-dominated sub-communities common to both cohorts and independent of reproductive status. In non-pregnant individuals, we find that the menstrual cycle modulates transitions between and within sub-communities. In addition, a specific non-Lactobacillus-dominated sub-community, which was associated with preterm delivery in pregnant participants, was also more common during menses, a time of elevated vaginal inflammation in non-pregnant participants. Overall, our analyses based on mixed membership models reveal substructures of vaginal ecosystems which may have important clinical and biological associations.

microbiology↗

bioRxiv2021

Stereotypic expansion of Tregulatory and Th17 cells during infancy is disrupted by HIV exposure and gut epithelial damage.

Few studies have investigated immune cell ontogeny throughout the neonatal and early paediatric period, where there is often increased vulnerability to infections. Here, we evaluated the dynamics of two critical T cell populations, regulatory (Treg) cells and Th17 cells, over the first 36 weeks of life. Firstly, we observed distinct CD4+ T cells phenotypes between cord blood and peripheral blood, collected within 12 hours of birth, showing that cord blood is not a surrogate for newborn blood. Secondly, both Treg and Th17 cells expanded in a synchronous fashion over 36 weeks of life. However, comparing infants exposed to HIV in utero, but remaining uninfected (iHEU), with HIV-unexposed uninfected control infants (iHUU), there was a lower frequency of peripheral blood Treg cells at birth, resulting in a delayed expansion, and then declining again at 36 weeks. Focusing on birth events, we found that Treg cells co-expressing CCR4 and 4{beta}7 inversely correlated with plasma concentrations of CCL17 (the ligand for CCR4) and intestinal fatty acid binding protein (iFABP), IL-7 and CCL20. This was in contrast to Th17 cells, which showed a positive association with these plasma analytes. Thus, despite the stereotypic expansion of both cell subsets over the first few months of life, there was a disruption in the balance of Th17 to Treg cells at birth likely being a result of gut damage and homing of newborn Treg cells from the blood circulation to the gut. Key pointsO_LIPhenotypic differences between cord and birth peripheral blood CD4 cells. C_LIO_LISynchronous increase of Th17-Treg cells is disrupted by HIV/ART exposure. C_LIO_LIIntrauterine HIV exposure was associated with epithelial gut damage. C_LI

immunology↗

bioRxiv2019

Characterization of the impact of daclizumab beta on circulating natural killer cells by mass cytometry

Daclizumab beta is a humanized monoclonal antibody that binds to CD25 and selectively inhibits high-affinity IL-2 receptor signaling. As a former treatment for relapsing forms of multiple sclerosis (RMS), daclizumab beta induces robust expansion of the CD56bright subpopulation of NK cells that is correlated with the drugs therapeutic effects. As NK cells represent a heterogeneous population of lymphocytes with a range of phenotypes and functions, the goal of this study was to better understand how daclizumab beta altered the NK cell repertoire to provide further insight into the possible mechanism(s) of action in RMS. We used mass cytometry to evaluate expression patterns of NK cell markers and provide a comprehensive assessment of the NK cell repertoire in individuals with RMS treated with daclizumab beta or placebo over the course of one year. Treatment with daclizumab beta significantly altered the NK cell repertoire compared to placebo treatment. As previously reported, daclizumab beta significantly increased expression of CD56 on total NK cells. Within the CD56bright NK cells, treatment was associated with multiple phenotypic changes, including increased expression of NKG2A and NKp44, and diminished expression of CD244, CD57, and NKp46. While the changes were less dramatic, CD56dim NK cells responded distinctly to daclizumab beta treatment, with higher expression of CD2 and NKG2A, and lower expression of FAS-L, HLA-DR, NTB-A, NKp30, and Perforin. Together, these data indicate that the expanded NK cells share features of both immature and mature NK cells. These findings show that daclizumab beta treatment is associated with unique changes in NK cells that may enhance their ability to kill autoreactive T cells or to exert immunomodulatory functions.

immunology↗

bioRxiv2019

Analysis of unusual and signature APOBEC-mutations in HIV-1 pol next-generation sequences

IntroductionAt low mutation-detection thresholds, next generation sequencing (NGS) for HIV-1 genotypic resistance testing is susceptible to artifactual detection of mutations arising from PCR error and APOBEC-mediated G-to-A hypermutation.\n\nMethodsWe analyzed published HIV-1 pol Illumina NGS data to characterize the distribution of mutations at eight NGS thresholds: 20%, 10%, 5%, 2%, 1%, 0.5%, 0.2%, and 0.1%. At each threshold, we determined the proportion of amino acid mutations that were unusual (defined as having a prevalence <0.01% in HIV-1 group M sequences) or were signature APOBEC mutations.\n\nResultsEight studies, containing 855 samples, in the NCBI Sequence Read Archive were analyzed. As detection thresholds were lowered, there was a progressive increase in the proportion of positions with both usual and unusual mutations and in the proportion of all mutations that were unusual. The median proportion of positions with an unusual mutation increased gradually from 0% at the 20% threshold to 0.3% at the 1% threshold and then exponentially to 1.3% (0.5% threshold), 6.9% (0.2% threshold), and 23.2% (0.1% threshold). In two of three studies with available plasma HIV-1 RNA levels, the proportion of positions with unusual mutations was negatively associated with virus levels. Although the complete set of signature APOBEC mutations was much smaller than that of unusual mutations, the former outnumbered the latter in one-sixth of the samples at the 0.5%, 1%, and 2% thresholds.\n\nConclusionsThe marked increase in the proportion of positions with unusual mutations at thresholds below 1% and in samples with lower virus loads suggests that, at low thresholds, many unusual mutations are artifactual, reflecting PCR error or G-to-A hypermutation. Profiling the numbers of unusual and signature APOBEC pol mutations at different NGS thresholds may be useful to avoid selecting a threshold that is too low and poses an unacceptable risk of identifying artifactual mutations.

bioinformatics↗

bioRxiv2019

Microbiota Assembly, Structure, and Dynamics Among Tsimane Horticulturalists of the Bolivian Amazon

Little is known about the relative contributions of selective and neutral forces on human-associated microbiota assembly. Here, we characterize microbial community assembly in 52 Tsimane infant-mother pairs, using longitudinally collected stool and tongue swab samples profiled with 16S rRNA gene amplicon sequencing. The Tsimane are an indigenous Bolivian population who practice infant care associated behaviors expected to increase mother-infant dispersal. Infant consumption of dairy products, vegetables, and chicha (a fermented drink inoculated with oral microbes) was significantly associated with gut microbiota composition. At both body sites, maternal microbes at higher relative abundance were more likely to be shared. Shared microbes were also higher in abundance in infants at both body sites, but decreased in average relative abundance with age and were not significantly higher by 12 months of age. Infant microbiotas were modeled using a neutral community model of assembly, which showed that the prevalence of more than two thirds of infant-colonizing microbes could be explained using neutral processes alone. The same method was applied to datasets from Finnish and Bangladeshi infants, confirming that the majority of microbes colonizing infants from different countries were neutrally distributed. Among the Tsimane infant and adult gut microbiota samples, neutral processes were less prominent in villages with more market access. These results underscore the importance of neutral processes during infant microbiota assembly, and suggest that cultural changes associated with market integration may be affecting traditional modes of microbiota assembly by decreasing the role of these neutral processes, perhaps through changes in diet, sanitation, or access to medical care.

microbiology↗

bioRxiv2019

Gut microbiota plasticity is correlated with sustained weight loss on a low-carb or low-fat dietary intervention

BackgroundObesity is a complex global health challenge. Although both low-carbohydrate (low-carb) and low-fat diets can lead to weight loss, there is typically substantial variability in weight and related outcomes for both diet approaches among obese but otherwise healthy adults. Elucidating individual characteristics that might contribute to sustained weight loss is critical to developing effective dietary intervention strategies. We hypothesized that structural differences in the gut microbiota explained some portion of the weight loss variability among people randomized to either a low-carb or low-fat diet, possibly related to its effects on dietary compliance.\n\nResultsOur study included two staggered cohorts of obese adults enrolled in the Diet Intervention Examining The Factors Interacting with Treatment Success (DIETFITS) study - a randomized clinical trial of either a low-fat or low-carb diet. In the discovery cohort (n=66), 161 pre-diet fecal samples were sequenced in addition to 157 samples collected after 10-weeks of dietary intervention. In the validation cohort (n = 56), 106 pre-diet fecal samples were sequenced. Pre-diet taxonomic features, such as the Prevotella/Bacteroides ratio, correlated to weight loss in the discovery cohort were not confirmed in the validation cohort. The most robust finding in the discovery cohort indicated that gut microbiota plasticity was linked to 12-month weight loss in a diet-dependent manner; subjects with higher sustained weight loss on a low-fat diet had higher pre-diet daily plasticity, whereas those most successful on the low-carb diet had greater microbiota plasticity over 10 weeks of dietary intervention. Unfortunately, because sample frequency and timing was quite different in the validation cohort, the relationship between plasticity and weight loss could not be studied in this group.\n\nConclusionsThese findings suggest the potential importance of gut microbiota plasticity in sustained weight loss. We highlight the importance of evaluating kinetic trends and in assessing reproducibility in studies of the gut microbiota.

microbiology↗

bioRxiv2018

Metagenomic analysis with strain-level resolution reveals fine-scale variation in the human pregnancy microbiome

Recent studies suggest that the microbiome has an impact on gestational health and outcome. However, characterization of the pregnancy-associated microbiome has largely relied on 16S rRNA gene amplicon-based surveys. Here, we describe an assembly-driven, metagenomics-based, longitudinal study of the vaginal, gut, and oral microbiomes in 292 samples from ten subjects sampled every three weeks throughout pregnancy. 1.53 Gb of non-human sequence was assembled into scaffolds, and functional genes were predicted for gene-and pathway-based analyses. Vaginal assemblies were binned into 97 draft quality genomes. Redundancy analysis (RDA) of microbial community composition at all three body sites revealed gestational age to be a significant source of variation in patterns of gene abundance. In addition, health complications were associated with variation in community functional gene composition in the mouth and gut. The diversity of Lactobacillus iners-dominated communities in the vagina, unlike most other vaginal community types, significantly increased with gestational age. The genomes of co-occurring Gardnerella vaginalis strains with predicted distinct functions were recovered in samples from two subjects. In seven subjects, gut samples contained strains of the same Lactobacillus species that dominated the vaginal community of that same subject, and not other Lactobacillus species; however, these within-host strains were divergent. CRISPR spacer analysis suggested shared phage and plasmid populations across body sites and individuals. This work underscores the dynamic behavior of the microbiome during pregnancy and suggests the potential importance of understanding the sources of this behavior for fetal development and gestational outcome.

microbiology↗

bioRxiv2017

Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data

BackgroundThe accuracy of microbial community surveys based on marker-gene and metagenomic sequencing (MGS) suffers from the presence of contaminants -- DNA sequences not truly present in the sample. Contaminants come from various sources, including reagents. Appropriate laboratory practices can reduce contamination, but do not eliminate it. Here we introduce decontam (https://github.com/benjjneb/decontam), an open-source R package that implements a statistical classification procedure that identifies contaminants in MGS data based on two widely reproduced patterns: contaminants appear at higher frequencies in low-concentration samples, and are often found in negative controls.\n\nResultsdecontam classified amplicon sequence variants (ASVs) in a human oral dataset consistently with prior microscopic observations of the microbial taxa inhabiting that environment and previous reports of contaminant taxa. In metagenomics and marker-gene measurements of a dilution series, decontam substantially reduced technical variation arising from different sequencing protocols. The application of decontam to two recently published datasets corroborated and extended their conclusions that little evidence existed for an indigenous placenta microbiome, and that some low-frequency taxa seemingly associated with preterm birth were contaminants.\n\nConclusionsdecontam improves the quality of metagenomic and marker-gene sequencing by identifying and removing contaminant DNA sequences. decontam integrates easily with existing MGS workflows, and allows researchers to generate more accurate profiles of microbial communities at little to no additional cost.

bioinformatics↗

bioRxiv2017

Strain-Specific Human Natural Killer Cell Recognition of Influenza A Virus

AbstractInnate Natural killer (NK) cells employ an array of surface receptors to detect altered self induced by infection or malignancy. Despite their decisive role in early antiviral immunity, the cellular mechanisms governing if or how they discriminate between viral infections remain unresolved. Here, we demonstrate that while human NK cells are capable of reducing infection levels of distinct influenza A strains, the A/California/07/2009 (pH1N1) strain induces a significantly more robust IFN-{gamma} response than A/Victoria/361/2011 (H3N2) and all other strains tested. This surprising degree of strain specificity results in part from the inability of the pH1N1 strain to downregulate the activating ligands CD112 (Nectin-2) and CD54 (ICAM-1) as efficiently as the H3N2 strain, leading to enhanced NK cell detection and IFN-{gamma} secretion. A network analysis of differentially expressed transcripts identifies the interferon /{beta} receptor (IFNAR) pathway as an additional, critical determinant of this strain-specific response. Strain-specific downregulation of NK cell activating ligands and modulation of type I IFN production represents a previously unrecognized influenza immunoevasion tactic and could present new opportunities to modulate the quality and quantity of the innate antiviral response for therapeutic benefit.\n\nOne Sentence SummaryHuman natural killer cells distinguish between Influenza A strains using a combinatorial cytokine priming and receptor-ligand signaling mechanism.

immunology↗

bioRxiv2017

Exact sequence variants should replace operational taxonomic units in marker gene data analysis

Recent advances have made it possible to analyze high-throughput marker-gene sequencing data without resorting to the customary construction of molecular operational taxonomic units (OTUs): clusters of sequencing reads that differ by less than a fixed dissimilarity threshold. New methods control errors sufficiently that sequence variants (SVs) can be resolved exactly, down to the level of single-nucleotide differences over the sequenced gene region. The benefits of finer taxonomic resolution are immediately apparent, and arguments for SV methods have focused on their improved resolution. Less obvious, but we believe more important, are the broad benefits deriving from the status of SVs as consistent labels with intrinsic biological meaning identified independently from a reference database. Here we discuss how those features grant SVs the combined advantages of closed-reference OTUs -- including computational costs that scale linearly with study size, simple merging between independently processed datasets, and forward prediction -- and of de novo OTUs -- including accurate diversity measurement and applicability to communities lacking deep coverage in reference databases. We argue that the improvements in reusability, reproducibility and comprehensiveness are sufficiently great that SVs should replace OTUs as the standard unit of marker gene analysis and reporting.

microbiology↗