Biology subjects

David, L. A.

Publications and source records attributed to David, L. A..

At least 19 recordsLinked to original sources

bioRxiv2026

Benchmarking Short-Read ITS2 and Full-Length ITS Sequencing Reveals Pipeline-Dependent Biases in Indoor Fungal Community Profiling

Short-read amplicon sequencing is widely used for fungal surveys but can limit taxonomic resolution. Long-read sequencing enables recovery of the full internal transcribed spacer (ITS) region and may improve ecological and taxonomic inference. Here, we conducted a paired comparison of Illumina ITS2 and PacBio HiFi full-length ITS sequencing using identical DNA extracts from built-environmental air and surface samples (n = 68) collected across homes, a dormitory, and laboratories. Both datasets were taxonomically assigned using the same algorithm and reference database. We performed paired statistics, in-silico ITS2 trimming of long-read sequences, and cross-platform mapping at multiple identity thresholds. Full-length ITS provided higher taxonomic resolution, assigning a greater fraction of ASVs at the family (98% vs. 88%) and species (42% vs. 32%) ranks than ITS2 (paired Wilcoxon q = 0.002). Alpha-diversity comparisons showed similar Shannon diversity across pipelines, whereas richness metrics were consistently higher for full-length ITS. Beta-diversity analyses indicated broadly comparable community-level patterns, although full-length ITS revealed stronger sample-type- and location-associated structure (PERMANOVA R{superscript 2} [≥] 0.06, p = 0.0001). In-silico ITS2 trimming reduced these differences, indicating that amplicon length is a major contributor to enhanced taxonomic resolution and ecological inference. Cross-platform mapping further showed extensive one-to-many relationships between ITS2 and full-length ITS ASVs, consistent with increased sequence resolution in long-read data. Together, these results show that ITS2 sequencing provides robust community-level profiling, while full-length ITS enables improved richness estimates and finer ecological and taxonomic resolution. This paired, bias-aware framework provides a practical template for selecting fungal amplicon sequencing strategies in built-environment mycobiome studies. ImportanceFungal communities in built environments influence indoor air quality and human exposure, yet their characterization depends strongly on sequencing strategy. This study provides a controlled, paired comparison of short-read ITS2 and long-read full-length ITS sequencing, showing that differences in amplicon length substantially contribute to variation in taxonomic resolution and ecological inference. While both approaches yield comparable community-level patterns, full-length ITS improves richness estimates, species-level assignment, and environmental discrimination by resolving sequence variation collapsed in ITS2 surveys. By integrating paired diversity analyses, in-silico ITS2 trimming, and cross-platform ASV mapping, this work offers a bias-aware framework for evaluating fungal amplicon pipelines. Importantly, improved species-level resolution enables functional interpretation of indoor fungi, for example the identification of taxa associated with pathogenic traits, allergen production, or toxin synthesis, supporting the development of more informative exposure metrics and targeted assays relevant to human health in built environments.

microbiology↗

bioRxiv2025

A foundation model for microbial growth dynamics

Microbial growth dynamics contain rich information about microbial populations, which support applications from antibiotic testing to microbiome engineering. However, the high dimensionality of growth data and the scarcity of large, task-specific datasets have limited generalizable modeling analysis across systems. Here, we develop a foundation model for microbial growth dynamics. It is a large-scale, self-supervised representation model trained on [~]370,000 experimental and simulated growth curves spanning diverse microbial species, environmental conditions, and community contexts. The model learns lower-dimensional latent embeddings that capture essential dynamical features of raw growth data and enable accurate reconstruction of these data. The concise representations enhance predictive performance in diverse downstream applications. Using these embedding, we achieve few-shot learning for antibiotic classification and concentration prediction, accurate forecasting of simulated and experimental communities, and inference of total abundance from relative-abundance data. By extracting transferable representations from heterogeneous datasets, our model provides a general framework for analyzing and predicting microbial community dynamics from limited measurements.

synthetic biology↗

bioRxiv2024

Glycolytic flux controls retinal progenitor cell differentiation via regulating Wnt signaling

Metabolic pathways are remodeled in response to energy and other homeostatic demands and are dynamically regulated during embryonic development, suggesting a role in guiding cellular differentiation. Here, we show that glycolytic flux is required and sufficient to bias multipotent retinal progenitor cells (RPCs) to acquire a rod photoreceptor fate in the murine retina. In RPC-specific Phosphatase and tensin homolog conditional knock-out (Pten-cKO) and RPC-specific conditional gain-of-function of dominant active PFKB3 (cytoPFKB3) mice, glycolytic gene expression and activity are elevated, correlating with precocious rod photoreceptor differentiation and outer segment maturation. Conversely, glycolytic inhibition in retinal explants suppresses RPC proliferation and photoreceptor differentiation, achieved either with 2-deoxy-d-glucose, a competitive inhibitor of glucose metabolism, by lowering media pH, which disables PKM2, a rate-limiting enzyme, or by inhibiting lactate/H+ symporters, which lowers intracellular pH. Mechanistically, we show that Wnt signaling, the top-upregulated pathway in Pten-cKO retinas, is a glycolysis-dependent pathway. Pharmacological and genetic perturbation of Wnt signaling by knocking-out Ctnnb1, encoding {beta}-catenin, phenocopies glycolytic inhibition, suppressing RPC proliferation, photoreceptor differentiation and outer segment maturation. Thus, developmental rewiring of glycolytic flux modulates Wnt signaling to drive rod photoreceptor differentiation and maturation, an instructive role that may be exploited therapeutically for cell replacement strategies. IMPACT STATEMENTTransgenic and pharmacological approaches reveal developmental elevations in glycolytic flux have an instructive role in promoting rod photoreceptor differentiation and maturation via activation of Wnt signaling.

developmental biology↗

bioRxiv2024

Interplay between particle size and microbial ecology in the gut microbiome

Physical particles can serve as critical abiotic factors that structure the ecology of microbial communities. For non-human vertebrate gut microbiomes, fecal particle size (FPS) has been known to be shaped by chewing efficiency and diet. However, little is known about what drives FPS in the human gut. Here, we analyzed FPS by laser diffraction across a total of 76 individuals and found FPS to be strongly individualized. Surprisingly, a behavioral intervention with 41 volunteers designed to increase chewing efficiency did not impact FPS. Dietary patterns could also not be associated with FPS. Instead, we found evidence that mammalian and human gut microbiomes shaped FPS. Fecal samples from germ-free and antibiotic-treated mice exhibited increased FPS relative to colonized mice. In humans, markers of longer transit time were correlated with smaller FPS. Gut microbiota diversity and composition were also associated with FPS. Finally, ex vivo culture experiments using human fecal microbiota from distinct donors showed that differences in microbiota community composition can drive variation in particle size. Together, our results support an ecological model in which the human gut microbiome plays a key role in reducing the size of food particles during digestion, and that the microbiomes of individuals vary in this capacity. These new insights also suggest FPS in humans to be governed by processes beyond those found in other mammals and emphasize the importance of gut microbiota in shaping their own abiotic environment.

microbiology↗

bioRxiv2024

Metaproteomics and DNA metabarcoding as tools to assess dietary intake in humans

Objective biomarkers of food intake are a sought-after goal in nutrition research. Most biomarker development to date has focused on metabolites detected in blood, urine, skin or hair, but detection of consumed foods in stool has also been shown to be possible via DNA sequencing. An additional food macromolecule in stool that harbors sequence information is protein. However, the use of protein as an intake biomarker has only been explored to a very limited extent. Here, we evaluate and compare measurement of residual food-derived DNA and protein in stool as potential biomarkers of intake. We performed a pilot study of DNA sequencing-based metabarcoding (FoodSeq) and mass spectrometry-based metaproteomics in five individuals stool sampled in short, longitudinal bursts accompanied by detailed diet records (n=27 total samples). Dietary data provided by stool DNA, stool protein, and written diet record independently identified a strong within-person dietary signature, identified similar food taxa, and had significantly similar global structure in two of the three pairwise comparisons between measurement techniques (DNA-to-protein and DNA-to-diet record). Metaproteomics identified proteins including myosin, ovalbumin, and beta-lactoglobulin that differentiated food tissue types like beef from dairy and chicken from egg, distinctions that were not possible by DNA alone. Overall, our results lay the groundwork for development of targeted metaproteomic assays for dietary assessment and demonstrate that diverse molecular components of food can be leveraged to study food intake using stool samples.

molecular biology↗

bioRxiv2023

Fecal pH and redox as functional markers in the premature infant gut microbiome

The infant gut microbiome is a crucial factor in health and development. In preterm infants, altered gut microbiome composition and function have been linked to serious neonatal complications such as necrotizing enterocolitis and sepsis, which can lead to long-term disability. Although many studies have described links between microbiome composition and disease risk, there is a need for biomarkers to identify infants at risk of these complications in practice. In this study, we obtained stool samples from preterm infant participants longitudinally during the first postnatal months, and measured pH and redox, as well as SCFA content and microbiome composition by 16S rRNA gene amplicon sequencing. These outcomes were compared to clinical data to better understand the role of pH and redox in infant gut microbiome development and overall health, and to assess the potential utility of pH and redox as biomarkers. We found that infants born earlier or exposed to antibiotics exhibited increased fecal pH, and that redox potential increased with postnatal age. These differences may be linked to changes in SCFA content, which was correlated with pH and increased with age. Microbiome composition was also related to birth weight, age, pH, and redox. Our findings suggest that pH and redox may serve as biomarkers of metabolic state in the preterm infant gut.

microbiology↗

bioRxiv2022

Pten regulates endocytic trafficking of cell adhesion and signaling molecules to pattern the retina

The retina is an exquisitely patterned tissue, with neuronal somata positioned at regular intervals to completely sample the visual field. Cholinergic amacrine cells are spectacular exemplars of precision, distributing in two radial layers and tangentially, forming regular mosaics. Here, we investigated how the intracellular phosphatase Pten and the cell adhesion molecule Dscam cooperate to regulate amacrine cell patterning. Using double mutants to test epistasis, we found that Pten and Dscam function in parallel pathways to regulate amacrine cell positioning. Mechanistically, Pten regulates endocytic remodeling of cell adhesion molecules (Dscam, Megf10, Fat3), which are aberrantly redistributed in Pten conditional-knock-out (cKO) amacrine cells. Furthermore, extracellular vesicles derived from multivesicular endosomes have altered proteomes in PtencKO retinas. Consequently, Wnt signaling is elevated in PtencKO retinal amacrine cells, the pharmacological disruption of which phenocopies PtencKO patterning defects. Pten thus controls endocytic trafficking of critical cell adhesion/signaling molecules to control amacrine cell spacing. HIGHLIGHTSO_LIPten and Dscam act in parallel pathways to regulate amacrine cell spacing C_LIO_LIEndocytic remodeling of cell adhesion molecules is perturbed in PtencKO retinas C_LIO_LIExtracellular vesicle content is altered in PtencKO retinas C_LIO_LIPerturbation of Wnt signaling phenocopies defects in amacrine cell positioning C_LI eTOC BLURBPatterns in nature range from stereotyped distributions of colored patches on butterfly wings to precise neuronal spacing in the nervous system. Waddington proposed that built-in constraints canalize developmental patterns. Touahri et al. identified Pten-mediated endocytic trafficking of cell adhesion/signaling molecules as a novel constraint measure controlling retinal amacrine cell patterning.

neuroscience↗

bioRxiv2021

Microbiota responses to different prebiotics are conserved within individuals and associated with habitual fiber intake

BackgroundShort-chain fatty acids (SCFAs) derived from gut bacteria are associated with protective roles in diseases ranging from obesity to colorectal cancers. Intake of microbially accessible dietary fibers (prebiotics) lead to varying effects on SCFA production in human studies, and gut microbial responses to nutritional interventions vary by individual. It is therefore possible that prebiotic therapies will require customizing to individuals. ResultsHere, we explored prebiotic personalization by conducting a three-way crossover study of three prebiotic treatments in healthy adults. We found that within individuals, metabolic responses were correlated across the three prebiotics. Individual identity, rather than prebiotic choice, was also the major determinant of SCFA response. Across individuals, prebiotic response was inversely related to basal fecal SCFA concentration, which, in turn, was associated with habitual fiber intake. Experimental measures of gut microbial SCFA production for each participant also negatively correlated with fiber consumption, supporting a model in which individuals gut microbiota are limited in their overall capacity to produce fecal SCFAs from fiber. ConclusionsOur findings support developing personalized prebiotic regimens that focus on selecting individuals who stand to benefit, and that such individuals are likely to be deficient in fiber intake.

microbiology↗

bioRxiv2021

Ecological memory of prior nutrient exposure in the human gut microbiome

Many ecosystems retain an ecological memory of past conditions that affects responses to future stimuli. However, it remains unknown what mechanisms and dynamics may govern such a memory in microbial communities. Here, in both a human dietary intervention cohort and an artificial gut, we show that the human gut microbiome encodes a memory of past carbohydrate exposures. Changes in the relative abundance of primary degraders were sufficient to enhance metabolism, and these changes were mediated by transcriptional changes within hours of initial exposure. We further found that ecological memory of one carbohydrate species impacted metabolism of others. These findings demonstrate that the human gut microbiomes metabolic potential reflects dietary exposures over preceding days and changes within hours of exposure to a novel nutrient. One Sentence SummaryRecent nutrient exposures are encoded into the structure and activity of human gut microbial communities, which enables more efficient future metabolic responses.

ecology↗

bioRxiv2021

Plagl1 is part of the mammalian retinal injury response and a critical regulator of Muller glial cell quiescence

Retinal damage triggers reactive gliosis in Muller glia across vertebrate species, but only in regenerative animals, such as teleost fish, do Muller glia initiate repair; proliferating and undergoing neurogenesis to replace lost cells. By mining scRNA-seq and bulk RNA-seq datasets, we found that Plagl1, a maternally imprinted gene, is dynamically regulated in reactive Muller glia post-insult, with transcript levels transiently increasing before stably declining. To study Plagl1 retinal function, we examined Plagl1+/-pat null mutants postnatally, revealing defects in retinal architecture, visual signal processing and a reactive gliotic phenotype. Plagl1+/-pat Muller glia proliferate ectopically and give rise to inner retinal neurons and photoreceptors. Transcriptomic and ATAC-seq profiles revealed similarities between Plagl1+/-pat retinas and neurodegenerative and injury models, including an upregulation of pro-gliogenic and pro-proliferative pathways, such as Notch, not observed in wild-type retinas Plagl1 is thus an essential component of the transcriptional regulatory networks that retain mammalian Muller glia in quiescence.

neuroscience↗

bioRxiv2020

Conserved anti-inflammatory effects and sensing of butyrate in zebrafish

Short chain fatty acids (SCFAs) are produced by microbial fermentation of dietary fiber in the gut. Butyrate is a particularly important SCFA with anti-inflammatory properties and is generally present at lower levels in inflammatory diseases associated with gut microbiota dysbiosis in mammals. We aimed to determine if SCFAs are produced by the zebrafish microbiome and if SCFAs exert conserved effects on zebrafish immunity as an example of the non-mammalian vertebrate immune system. We demonstrate that bacterial communities from adult zebrafish intestines synthesize all three main SCFA in vitro, although SCFA were below our detectable limits in zebrafish intestines in vivo. Immersion in butyrate, but not acetate or propionate, reduced the recruitment of neutrophils and M1-type pro-inflammatory macrophages to wounds. We found conservation of butyrate sensing by neutrophils via orthologs of the hydroxycarboxylic acid receptor 1 (hcar1) gene. Neutrophils from Hcar1-depeleted embryos were no longer responsive to the anti-inflammatory effects of butyrate, while macrophage sensitivity to butyrate was independent of Hcar1. Our data demonstrate conservation of anti-inflammatory butyrate effects and identify the presence of a conserved molecular receptor in fish.

immunology↗

bioRxiv2020

Short-chain fatty acid production by gut microbiota from children with obesity is linked to bacterial community composition and prebiotic choice

Pediatric obesity remains a public health burden and continues to increase in prevalence. The gut microbiota plays a causal role in obesity and is a promising therapeutic target. Specifically, the microbial production of short-chain fatty acids (SCFA) from the fermentation of otherwise indigestible dietary carbohydrates may protect against pediatric obesity and metabolic syndrome. Still, it has not been demonstrated that therapies involving microbiota-targeting carbohydrates, known as prebiotics, will enhance gut bacterial SCFA production in children and adolescents with obesity (age 10-18). Here, we used an in vitro system to examine the SCFA production by fecal microbiota from 17 children with obesity when exposed to five different commercially available over-the-counter (OTC) prebiotic supplements. We found microbiota from all 17 patients actively metabolized most prebiotics. Still, supplements varied in their acidogenic potential. Significant inter-donor variation also existed in SCFA production, which 16S rRNA sequencing supported as being associated with differences in the host microbiota composition. Last, we found that neither fecal SCFA concentration, microbiota SCFA production capacity, nor markers of obesity positively correlated with one another. Together, these in vitro findings suggest the hypothesis that OTC prebiotic supplements may be unequal in their ability to stimulate SCFA production in children and adolescents with obesity, and that the most acidogenic prebiotic may differ across individuals. IMPORTANCEPediatric obesity remains a major public health problem in the US, where 17% of children and adolescents are obese, and rates of pediatric severe obesity are increasing. Children and adolescents with obesity face higher health risks, and non-invasive therapies for pediatric obesity often have limited success. The human gut microbiome has been implicated in adult obesity, and microbiota-directed therapies can aid weight loss in adults with obesity. However, less is known about the microbiome in pediatric obesity, and microbiota-directed therapies are understudied in children and adolescents. Our research has two important findings: 1) dietary prebiotics (fiber) cause the microbiota from adolescents with obesity to produce more SCFA, and 2) the effectiveness of each prebiotic is donor-dependent. Together, these findings suggest that prebiotic supplements could help children and adolescents with obesity, but that these therapies may not be one-size-fits-all.

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↗

bioRxiv2019

High-throughput isolation and culture of human gut bacteria with droplet microfluidics

Isolation and culture of gut bacteria enable testing for microbial roles in disease and may also lead to novel therapeutics. However, the diversity of human gut microbial communities (microbiota) impedes comprehensive experimental studies of individual bacterial taxa. Here, we combine advances in droplet microfluidics and high-throughput DNA sequencing to develop a platform for isolating and assaying microbiota members in picoliter droplets (MicDrop). MicDrop can be used to create millions of distinct bacterial colonies in a single experiment while using off-the-shelf parts compact enough to fit in an anaerobic chamber. In proof-of-concept experiments, we used the platform to characterize inter-individual metabolic variation among hundreds of polysaccharide-degrading gut bacteria from nine stool donors. We also used MicDrop to test the hypothesis that growth kinetics of individual gut bacterial taxa are associated with longterm community dynamics in an artificial gut. These demonstrations suggest the MicDrop platform could support future diagnostic efforts to personalize microbiota-directed therapies, as well as to provide comprehensive new insights into the ecology of human gut microbiota.

microbiology↗

bioRxiv2019

Measuring and Mitigating PCR Bias in Microbiome Data

PCR amplification plays a central role in the measurement of mixed microbial communities via high-throughput sequencing. Yet PCR is also known to be a common source of bias in microbiome data. Here we present a paired modeling and experimental approach to characterize and mitigate PCR bias in microbiome studies. We use experimental data from mock bacterial communities to validate our approach and human gut microbiota samples to characterize PCR bias under real-world conditions. Our results suggest that PCR can bias estimates of microbial relative abundances by a factor of 2-4 but that this bias can be mitigated using simple Bayesian multinomial logistic-normal linear models.\n\nAuthor summaryHigh-throughput sequencing is often used to profile host-associated microbial communities. Many processing steps are required to transform a community of bacteria into a pool of DNA suitable for sequencing. One important step is amplification where, to create enough DNA for sequencing, DNA from many different bacteria are repeatedly copied using a technique called Polymerase Chain Reaction (PCR). However, PCR is known to introduce bias as DNA from some bacteria are more efficiently copied than others. Here we introduce an experimental procedure that allows this bias to be measured and computational techniques that allow this bias to be mitigated in sequencing data.

genomics↗

bioRxiv2018

Naught all zeros in sequence count data are the same

Genomic studies feature multivariate count data from high-throughput DNA sequencing experiments, which often contain many zero values. These zeros can cause artifacts for statistical analyses and multiple modeling approaches have been developed in response. Here, we apply common zero-handling models to gene-expression and microbiome datasets and show models disagree on average by 46% in terms of identifying the most differentially expressed sequences. Next, to rationally examine how different zero handling models behave, we developed a conceptual framework outlining four types of processes that may give rise to zero values in sequence count data. Last, we performed simulations to test how zero handling models behave in the presence of these different zero generating processes. Our simulations showed that simple count models are sufficient across multiple processes, even when the true underlying process is unknown. On the other hand, a common zero handling technique known as "zero-inflation" was only suitable under a zero generating process associated with an unlikely set of biological and experimental conditions. In concert, our work here suggests several specific guidelines for developing and choosing state-of-the-art models for analyzing sparse sequence count data.

bioinformatics↗

bioRxiv2018

Statistical Considerations in the Design and Analysis of Longitudinal Microbiome Studies

Longitudinal studies of microbial communities have emphasized that host-associated microbiota are highly dynamic as well as underscoring the potential biomedical relevance of understanding these dynamics. Despite this increasing appreciation, statistical challenges in the design and analysis of longitudinal microbiome studies such as sequence counting, technical variation, signal aliasing, contamination, sparsity, missing data, and algorithmic scalability remain. In this review we discuss these challenges and highlight current progress in the field. Where possible, we try to provide guidelines for best practices as well as discuss how to tailor design and analysis to the hypothesis and ecosystem under study. Overall, this review is intended to serve as an introduction to longitudinal microbiome studies for both statisticians new to the microbiome field as well as biologists with little prior experience with longitudinal study design and analysis.

microbiology↗

bioRxiv2018

Dynamic linear models guide design and analysis of microbiota studies within artificial human guts

Artificial gut models provide unique opportunities to study human-associated microbiota. Outstanding questions for these models fundamental biology include the timescales on which microbiota vary and the factors that drive such change. Answering these questions though requires overcoming analytical obstacles like estimating the effects of technical variation on observed microbiota dynamics, as well as the lack of appropriate benchmark datasets. To address these obstacles, we created a modeling framework based on multinomial logistic-normal dynamic linear models (MALLARDs) and performed dense longitudinal sampling of replicate artificial human guts over the course of 1 month. The resulting analyses revealed that when observed on an hourly basis, 76% of community variation could be ascribed to technical noise from sample processing, which could also skew the observed covariation between taxa. Our analyses also supported hypotheses that human gut microbiota fluctuate on sub-daily timescales in the absence of a host and that microbiota can follow replicable trajectories in the presence of environmental driving forces. Finally, multiple aspects of our approach are generalizable and could ultimately be used to facilitate the design and analysis of longitudinal microbiota studies in vivo.

genomics↗