Biology subjects

Smith, M. E.

Publications and source records attributed to Smith, M. E..

15 recordsLinked to original sources

bioRxiv2026

Type 2 diabetes increases susceptibility to invasive Salmonella Typhimurium despite butyrate supplementation

Non-typhoidal Salmonella is a major cause of bacterial foodborne illness leading to acute gastroenteritis. In individuals with type 2 diabetes (T2D), Salmonella infection is more likely to cause life-threatening extraintestinal infections. The mechanism underlying this susceptibility remains unclear. In this study, 8-week-old TALLYHO mice were fed either a chow or high-fat diet (HFD, 45% fat) for 8 weeks to induce the T2D. As expected, HFD-fed mice gained more weight and developed diabetic-range blood glucose levels by 16 weeks of age. Next, mice from each diet group were orally infected with a fully virulent bioluminescent Salmonella Typhimurium to monitor infection spread by in-vivo imaging. Although both groups developed clinical signs of salmonellosis, Salmonella spread was accelerated and followed an unusual pattern in T2D mice compared with healthy animals. Additionally, hyperglycemia increased gut-derived lipopolysaccharide leakage into the bloodstream. Based on the link between T2D and altered levels of butyrate-producing bacteria in the gut, we analyzed the intestinal short-chain fatty acid (SCFA) profiles in the TALLYHO mice. As expected, intestinal SCFA concentrations, including butyrate, were lower in HFD mice than in chow-fed animals. Given butyrate?s role in gut health and its ability to downregulate Salmonella invasion genes, mice received oral butyrate supplementation. We found that butyrate supplementation reduced the extraintestinal spread of Salmonella in normoglycemic chow-fed animals. Unexpectedly, although butyrate improved intestinal health in hyperglycemic mice, it failed to decrease Salmonella spread in diabetic animals. Taken together, these findings provide novel insights into the pathogenesis of enteric salmonellosis in the context of T2D.

microbiology↗

bioRxiv2026

HippoGenes: A robust workflow for subregional transcriptomic profiling of the human hippocampus

The human hippocampus is a unique cortical structure central to brain function, plasticity, and disease. Unravelling its complex organization requires the integration of multiscale data, linking molecular features to mesoscale anatomy and macroscale functional patterns. Gene expression is a fundamental microscale phenotype, and its profiling can provide a reference description of how molecular features are distributed across the brain. Capitalizing on recent imaging-transcriptomic analyses, we introduce HippoGenes, a repository of fine-grained gene expression patterns across human hippocampal subregions. We leveraged spatial statistical models and hippocampal surface mapping to reconstruct dense transcriptomic maps from sparse post-mortem tissue samples of the Allen Human Brain Atlas, generating continuous expression estimates for thousands of genes aligned to a common surface-based coordinate system. We illustrate the utility of HippoGenes to (i) map medial-lateral and anterior-posterior transcriptomic gradients that align with subfield and tripartite subdivisions of the hippocampal formation, (ii) examine associations between gene expression and canonical microstructural and functional features of the hippocampus, and (iii) perform a molecular decoding of subregional alterations in neurological patients with hippocampal pathology. HippoGenes provides a framework for exploring the molecular organization of the hippocampus, opening avenues for multiscale integration in health and disease, and is openly available on https://hippogenes.readthedocs.io/.

neuroscience↗

bioRxiv2026

The "dark magic mushroom" co-produces amatoxins and psilocybin

The most famous chemicals produced by mushrooms are the psychedelic compound psilocybin from "magic mushrooms" and amatoxins from deadly poisonous mushrooms. These compounds are known to occur in multiple phylogenetically disjunct fungal lineages but have never been shown to co-occur within a single species. Here we show that the "dark magic mushroom" Galerina indica produces both psilocybin and amatoxins. Mass spectrometry revealed psilocybin and amatoxins in mushroom tissues, and genomic analyses identified corresponding biosynthetic genes. Phylogenetic analyses suggest that G. indica acquired psilocybin biosynthesis via horizontal gene transfer after amatoxin biosynthesis was already established, and that psilocybin biosynthesis was acquired twice independently within Galerina. Intriguingly, acquisition of psilocybin biosynthesis in G. indica may have coincided with reduced amatoxin potency. These findings reveal how horizontal gene transfer can combine powerful bioactive systems in a single species, potentially altering the ecological roles of both compound classes and the evolutionary fitness of the species.

evolutionary biology↗

bioRxiv2026

Hierarchical Signatures of Language in the Human Brain

Language relies on a hierarchy of sensory and cognitive processes, yet how different levels of this hierarchy are supported by distinct neural architectures remains unclear. Here we show that semantic processing, compared with phonological processing, is associated with higher-level brain networks, as characterized by resting-state fMRI connectivity, in vivo measures of cortical myelin, and cortical types derived from a cytoarchitecture-defined reference atlas. These relationships were established using individualized ultra-high field fMRI in both English and French speakers leveraging a multi-session, multi-modal 7T MRI protocol including a language localizer. For comparison, we developed an artificial neural network, in which a representational hierarchy spontaneously emerged where phonological information was captured in earlier layers and semantic information in later layers. By integrating individualized functional mapping, neuroanatomical characterization and artificial intelligence, this study advances understanding of the neural basis of language and provides a framework for linking biological and artificial systems of communication. Significance StatementLanguage is widely described as hierarchical, yet how this functional organization is implemented in the brains biological architecture remains unclear. By combining ultra-high field, individualized neuroimaging with in vivo measures of cortical microstructure and large-scale connectivity, this study establishes a framework for linking distinct levels of linguistic computation to the brains structural and functional organization. Integrating these findings with artificial neural network modeling further reveals shared principles between biological and machine systems. Together, this work advances a biologically grounded account of language, bridges cognitive neuroscience and artificial intelligence, and provides a roadmap for understanding how complex cognition emerges from structured brain architecture.

neuroscience↗

bioRxiv2025

Patterns of intersubject correlations parallel organizational gradients during naturalistic viewing

Recent studies have robustly demonstrated that human cortical function can be described through sensory-transmodal gradients of cortical function, while naturalistic movie watching paradigms have been leveraged to index cortical synchronization. We leveraged two independent 7T movie fMRI datasets to assess correlations between intersubject correlation and functional gradients across movies, datasets, and spatial scales. At the whole-brain level, we observed robust relationships between intersubject correlations and a visual-transmodal connectivity gradient which was independent of movie content. Within functional networks, correlations were particularly pronounced for the visual, dorsal attention, and default mode networks. Our results demonstrate that naturalistic paradigms can provide targeted insight into multiscale processing hierarchies. Robust relationships across movies suggest that movie-watching can be viewed as a brain state that is independent of movie-content. Overall, this work suggests an important confluence of within-subject functional organizational axes and inter-subject synchronization when the brain is engaged in the processing of naturalistic stimuli.

neuroscience↗

bioRxiv2025

A cross model spatial and single-cell atlas reveals the conserved involvement of osteopontin in polycystic kidney disease

Polycystic kidney disease (PKD) arises from mutations in cilia-associated genes, such as PKD1 and PKD2, expressed in renal epithelial cells, leading to progressive kidney dysfunction and end- stage kidney disease (ESKD). PKD patients exhibit significant heterogeneity in disease progression, largely due to genetic and environmental modifiers. Like patients, mouse models of PKD also exhibit significant heterogeneity with regards to the gene mutated, age of disease onset, and rate of disease progression. To elucidate the cellular and molecular consequences of these variables, we constructed an integrated single-cell and spatial transcriptomics atlas across mouse models of PKD, mapping changes in cell type composition, gene expression, and intercellular signaling networks across the whole atlas and within individual models. Consistently across models, single cell RNA sequencing (scRNAseq) data revealed increased Spp1 (osteopontin) expression and signaling from PKD-enriched clusters to Ly6clo monocytes. Global deletion of Spp1 in Pkd1RC/RC mice resulted in reduced cyst severity, improved kidney function, and reduced Ly6clo monocyte numbers, suggesting that SPP1 signaling to Ly6clo monocytes promotes PKD progression. We also created a freely available, searchable website (https://bmblx.bmi.osumc.edu/scPKD/) that can be used to identify cross- and intra-model specific changes in gene expression, guiding researchers to new therapeutic targets for treating PKD.

bioinformatics↗

bioRxiv2025

Diverse crop rotations off-set yield-scaled nitrogen losses via denitrification

Denitrification, a major source of gaseous nitrogen (N) emissions from agricultural soils, is influenced by management. Practices promoting belowground diversity are suggested to support sustainable agriculture, but their ability to modulate gaseous N-losses via denitrification remains inconclusive. To fill this knowledge gap, we sampled 106 cereal fields spanning a 3,000 km North-South gradient across Europe and compiled 56 associated climatic, soil, microbial and management variables. We found that increased denitrification was associated with higher proportion of time with crop cover over the last ten years. Denitrification rates were best predicted by microbial biomass and microbial functional guilds involved in N cycling, in particular denitrification. We also show that several diversification practices affect the variation in denitrification predictors, suggesting a trade-off between agricultural diversification and gaseous N-losses via denitrification. However, increased crop diversity in rotations improved yield-scaled denitrification, highlighting the potential of this practice to minimize N losses while contributing to sustainable food production.

ecology↗

bioRxiv2025

Uncovering functional deterioration in the rhizosphere microbiome associated with wheat dwarfing

BackgroundOne of the biggest developments of wheat domestication was the development of semi-dwarf cultivars that respond well to fertilisers and produce higher yields without lodging. Consequently, this change has also impacted the wheat microbiome, often resulting in reduced selection of taxa and a loss of network complexity in the rhizospheres of semi-dwarf cultivars. Given the importance of rhizosphere microbiomes for plant health and performance, it is imperative that we understand if and how these changes have affected their function. Here, we use shotgun metagenomics to classify the functional potential of prokaryote communities from the rhizospheres of tall and semi-dwarf cultivars to compare the impact of wheat dwarfing on rhizosphere microbiome functions. ResultsWe found distinct taxonomic and functional differences between tall and semi-dwarf wheat rhizosphere communities and identified that semi-dwarf wheat microbiomes were less distinct from bulk soil communities. Of the 113 functional genes that were differentially abundant between tall and semi-dwarf cultivars, 95 % were depleted in semi-dwarf cultivars and 65 % of differentially abundant reads best mapped to genes involved in staurosporine biosynthesis (antibiotic product), plant cell wall degradation (microbial mediation of plant root architecture, overwintering energy source for microbes) and sphingolipid metabolism (signal bioactive molecules). ConclusionsOverall, our findings indicate that green revolution breeding has developed wheat cultivars with a reduced rhizosphere effect. The consequences of this are likely detrimental to the development of microbiome-assisted agriculture which will require a strong rhizosphere selective environment for the establishment of a beneficial plant root microbiome. We believe our results are of striking importance and highlight that implementation of microbiome facilitated agriculture as part of a sustainable crop production strategy will require an overhaul of wheat breeding programmes to consider plant-microbe interactions, especially in the root environment.

microbiology↗

bioRxiv2022

Divergent evolution of early terrestrial fungi reveals the evolution of Mucormycosis pathogenicity factors

Fungi have evolved over millions of years and their species diversity is predicted to be the second largest on the earth. Fungi have cross-kingdom interactions with many organisms which have mutually shaped their evolutionary trajectories. Zygomycete fungi hold a pivotal position in the fungal tree of life and provide important perspectives on the early evolution of fungi from aquatic to terrestrial environments. Phylogenomic analyses have found that zygomycete fungi diversified into two separate clades, the Mucoromycota which are frequently associated with plants and Zoopagomycota that are commonly animal-associated fungi. Genetic elements that contributed to the fitness and divergence of these lineages may have been shaped by the varied interactions these fungi have had with plants, animals, bacteria and other microbes. To investigate this, we performed comparative genomic analyses of the two clades in the context of Kingdom Fungi, benefiting from our generation of a new collection of zygomycete genomes. We identified lineage-specific genomic content which may contribute to the disparate biology observed in these zygomycetes. Our findings include the discovery of undescribed diversity in CotH, a Mucormycosis pathogenicity factor, which was found in a broad set of zygomycetes. Reconciliation analysis identified multiple duplication events and an expansion of CotH copies throughout Mucoromycotina, Mortierellomycotina, Neocallimastigomycota, and Basidiobolus lineages. A kingdom-level phylogenomic analysis also identified new evolutionary relationships within the sub-phyla of Mucoromycota and Zoopagomycota.

evolutionary biology↗

bioRxiv2021

Genetic Sex Validation for Sample Tracking in Clinical Testing

BackgroundNext generation DNA sequencing (NGS) has been rapidly adopted by clinical testing laboratories for detection of germline and somatic genetic variants. The complexity of sample processing in a clinical DNA sequencing laboratory creates multiple opportunities for sample identification errors, demanding stringent quality control procedures. MethodsWe utilized DNA genotyping via a 96-SNP PCR panel applied at sample acquisition in comparison to the final sequence, for tracking of sample identity throughout the sequencing pipeline. The 96-SNP PCR panels inclusion of sex SNPs also provides a mechanism for a genotype-based comparison to recorded sex at sample collection for identification. This approach was implemented in the clinical genomic testing pathways, in the multi-center Electronic Medical Records and Genomics (eMERGE) Phase III program ResultsWe identified 110 inconsistencies from 25,015 (0.44%) clinical samples, when comparing the 96-SNP PCR panel data to the test requisition-provided sex. The 96-SNP PCR panel genetic sex predictions were confirmed using additional SNP sites in the sequencing data or high-density hybridization-based genotyping arrays. Results identified clerical errors, samples from transgender participants and stem cell or bone marrow transplant patients and undetermined sample mix-ups. ConclusionThe 96-SNP PCR panel provides a cost-effective, robust tool for tracking samples within DNA sequencing laboratories, while the ability to predict sex from genotyping data provides an additional quality control measure for all procedures, beginning with sample collections. While not sufficient to detect all sample mix-ups, the inclusion of genetic versus reported sex matching can give estimates of the rate of errors in sample collection systems.

genomics↗

bioRxiv2021

Genome-wide association study reveals an independent genetic basis of zinc and cadmium concentrations in fresh sweet corn kernels

Despite being one of the most consumed vegetables in the United States, the elemental profile of sweet corn (Zea mays L.) is limited in its dietary contributions. To address this through genetic improvement, a genome-wide association study was conducted for the concentrations of 15 elements in fresh kernels of a sweet corn association panel. In concordance with mapping results from mature maize kernels, we detected a probable pleiotropic association of zinc and iron concentrations with nicotianamine synthase5 (nas5), which purportedly encodes an enzyme involved in synthesis of the metal chelator nicotianamine. Additionally, a pervasive association signal was identified for cadmium concentration within a recombination suppressed region on chromosome 2. The likely causal gene underlying this signal was heavy metal ATPase3 (hma3), whose counterpart in rice, OsHMA3, mediates vacuolar sequestration of cadmium and zinc in roots, whereby regulating zinc homeostasis and cadmium accumulation in grains. In our association panel, hma3 associated with cadmium but not zinc accumulation in fresh kernels. This finding implies that selection for low cadmium will not affect zinc levels in fresh kernels. Although less resolved association signals were detected for boron, nickel, and calcium, all 15 elements were shown to have moderate predictive abilities via whole-genome prediction. Collectively, these results help enhance our genomics-assisted breeding efforts centered on improving the elemental profile of fresh sweet corn kernels.

genetics↗

bioRxiv2020

Trajectory analysis of cardiovascular phenotypes from biobank data uncovers novel genetic associations

Approximately 6 million adults in the US have heart failure (HF). HF progression is variable due in part to differences in sex, age, and genetic ancestry. Previous population-based genetic studies have largely focused on cross-sectional data related to HF, a disease known to change over time. Utilizing longitudinal data trajectory probabilities as a continuous trait may increase the likelihood of finding significant, biologically relevant associations in a genome-wide association (GWA) analysis. We analyzed data from the electronic health record in a medical biobank from a single, metropolitan US center to gather clinically pertinent data for analyses. We evaluated whole genome sequencing of 896 unrelated biobank participants, including 494 with at least 1 electrocardiogram and 324 who had more than 1 echocardiogram ([~]3 observations per person). A censored normal distribution multivariable mixture model was used to cluster phenotype measures for genome-wide analyses. GWA analysis on the trajectory probability of the corrected QT measurement (QTc) taken from electrocardiograms identified significant associations with variants in regulatory regions proximal to the WLS gene, which encodes the Wnt ligand secretion mediator, Wntless. WLS was previously associated with QT length using of approximately 16,000 participants supporting the utility of this method to uncover significant genetic associations in small datasets. GWA analysis on the trajectory probability of left ventricular diameter as taken from echocardiograms identified novel significant associations with variants in regulatory regions near MYO10, which encodes the unconventional Myosin-10. We found that trajectory probabilities improved the ability to discover significant and relevant genetic associations. This novel approach increased yield from smaller, well-phenotyped cohorts with longitudinal data from a medical biobank. AUTHOR SUMMARYApproximately 6 million adults in the US have heart failure, a disease known to change over time. In a hospital based electronic health record, electrocardiograms and echocardiograms, used to evaluate heart failure, can be tracked over time. We utilized these data to create a novel trait that can be applied to genetic analyses. We analyzed genome sequence of 896 biobank participants from diverse racial/ethnic backgrounds. Genome-wide association (GWA) analyses were performed on a subset of these individuals for heart failure outcomes. A statistical model that incorporates cardiac data that are tracked over time was used to cluster these data using a probabilistic approach. These probabilities were used for a GWA analysis for corrected QT measurement (QTc) and left ventricular diameter (LVID). The QTc interval analysis identified significant correlations with variants in regulatory regions near the WLS gene which encodes the Wnt ligand secretion mediator, Wntless. Analysis of LVID identified significant associations with variants in regulatory regions near the MYO10 gene which encodes the unconventional Myosin-10. Through these analyses, we found that using the trajectory probabilities can facilitate the discovery of novel significant, biologically relevant associations. This method reduces the need for larger cohorts, and increases yield from smaller, well-phenotyped cohorts.

genomics↗

bioRxiv2019

Predicting lymphatic filariasis elimination in data-limited settings: a reconstructive computational framework for combining data generation and model discovery

Although there is increasing recognition of the importance of mathematical models in the effective design and management of long-term parasite elimination, it is also becoming clear that to be most useful parasite transmission models must accurately reflect the processes pertaining to local infection dynamics. These models must also be identified even when the data required for characterizing the local transmission process are limited or incomplete, as is often the case for neglected tropical diseases, including the disease system studied in this work, viz. lymphatic filariasis (LF). Here, we draw on progress made in the field of computational knowledge discovery to present a reconstructive simulation framework that addresses these challenges by facilitating the discovery of data and models concurrently in order to deliver reliable location-specific predictions pertaining to LF elimination in areas where we have insufficient observational data. Using available data from eight sites from Nigeria and elsewhere, we demonstrate that our data-model discovery system is able to identify local transmission models using a generalized knowledge of filarial transmission dynamics, monitoring survey data, and details of historical interventions, which in turn can also generate information regarding the pre-control endemic status of LF in each study site. Forecasts of the impacts of interventions made by the models discovered using the reconstructed baseline data not only matched temporal infection observations, but also provided critical information regarding when transmission interruption is likely to have occurred. Assessments of elimination and recrudescence probabilities based on these models also suggested a protective effect of vector control against the reemergence of transmission after stopping drug treatments. The reconstructive computational framework for model and data discovery developed here highlights how coupling models with available data can generate new knowledge about complex, data-limited systems, and ultimately support the effective management of disease programs in the face of critical data gaps.\n\nAuthor summaryAs modelling becomes commonly used in the design and evaluation of parasite elimination programs, the need for well-defined models and datasets describing the nature of transmission processes in endemic settings is becoming pronounced. For many neglected tropical diseases, including the disease investigated in this study, lymphatic filariasis (LF), however, data for model identification are typically sparse or incomplete. In this study, we present a new data-model computational discovery system that couples data-assimilation methods based on existing monitoring survey data with model-generated data about baseline conditions, in order to discover the local LF transmission models required for simulating the impacts of interventions for achieving parasite elimination in typical endemic locations. Using data from eight study sites in Nigeria and elsewhere, we show that our reconstructive computational knowledge discovery system is able to combine information contained within partially-available site-specific monitoring data with knowledge of parasite transmission dynamics embedded in process-based models to generate the missing data required for inducing reliable locally applicable LF models. We also show that the models so discovered are able to generate the intervention forecasts required for supporting management-relevant decisions in parasite elimination.

ecology↗

bioRxiv2019

Pathogenic and uncertain genetic variants have clinical cardiac correlates in diverse biobank participants

BackgroundGenome sequencing coupled with electronic heath record data can uncover medically important genetic variation. Interpretation of rare genetic variation and its role in mediating cardiovascular phenotypes is confounded by variants of uncertain significance.\n\nMethods and ResultsWe analyzed the whole genome sequence of 900 racially and ethnically diverse biobank participants selected from a single US center. Participants were equally divided among European, African, Hispanic, and mixed race/ethnicities. We evaluated the American College of Medical Genetics and Genomics medically actionable list of 59 genes focusing on the cardiac genes. Variation was interpreted using the most recent reports in ClinVar, a database of medically relevant human variation. We identified 19 individuals with pathogenic/likely pathogenic variants in cardiac actionable genes (2%) and found evidence for clinical correlates in the electronic health record. African ancestry participants had more variants of uncertain significance in the medically actionable genes including the 30 cardiac actionable genes, even when normalized to total variant count per person. Longitudinal measures of left ventricle size, corrected for body surface area, from approximately 400 biobank participants (1,723 patient years) correlated with genetic findings. The presence of one or more uncertain variants in the actionable cardiac genes and a cardiomyopathy diagnosis correlated with increased left ventricular internal diameter in diastole and in systole. In particular, MYBPC3 was identified as a gene with excess variants of uncertain significance.\n\nConclusionsThese data indicate a subset of uncertain variants may confer risk and should not be considered benign.

genomics↗

bioRxiv2018

Economic performance and cost-effectiveness of using a DEC-salt social enterprise for eliminating the major neglected tropical disease, lymphatic filariasis

BackgroundSalt fortified with the drug, diethylcarbamazine (DEC), and introduced into a competitive market has the potential to overcome the obstacles associated with tablet-based Lymphatic Filariasis (LF) elimination programs. Questions remain, however, regarding the economic viability, production capacity, and effectiveness of this strategy as a sustainable means to bring about LF elimination in resource poor settings.\n\nMethodology and Principal FindingsWe evaluated the performance and effectiveness of a novel social enterprise-based approach developed and tested in Leogane, Haiti, as a strategy to sustainably and cost-efficiently distribute DEC-medicated salt into a competitive market at quantities sufficient to bring about the elimination of LF. We undertook a cost-revenue analysis to evaluate the production capability and financial feasibility of the developed DEC salt social enterprise, and a modeling study centered on applying a dynamic mathematical model localized to reflect local LF transmission dynamics to evaluate the cost-effectiveness of using this intervention versus standard annual Mass Drug Administration (MDA) for eliminating LF in Leogane. We show that the salt enterprise because of its mixed product business strategy may have already reached the production capacity for delivering sufficient quantities of edible DEC-medicated salt to bring about LF transmission in the Leogane study setting. Due to increasing revenues obtained from the sale of DEC salt over time, expansion of its delivery in the population, and greater cumulative impact on the survival of worms, this strategy could also represent a significantly more cost-effective option than annual DEC tablet-based MDA for accomplishing LF elimination.\n\nSignificanceA social enterprise approach can offer an innovative market-based strategy by which edible salt fortified with DEC could be distributed to communities both on a financially sustainable basis and at sufficient quantity to eliminate LF. Deployment of similarly fashioned intervention strategies would improve current efforts to successfully accomplish the goal of LF elimination, particularly in difficult-to-control settings.\n\nAuthor summaryWith less than three years remaining for meeting the 2020 target set by WHO for accomplishing the global elimination of Lymphatic Filariasis (LF), concerns are emerging regarding the feasibility of meeting this goal using the current tablet-based Mass Drug Administration strategy. Salt fortified with the antifilarial drug, diethylcarbamazine (DEC), could offer an intervention that avoids many of the barriers connected with tablet-based elimination programs. We analyzed the economic performance and cost-effectiveness of a novel DEC-salt social enterprise developed and tested in Leogane arrondissement, Haiti, as a particularly significant strategy for accomplishing sustainable LF elimination in such complex settings. We show that because of increasing revenue from the sale of the DEC salt over time, expansion of its delivery in the population, and the adverse effect of continuous consumption of the drug on worms, the delivery of DEC through a salt enterprise can represent a significantly more cost-effective option than annual DEC tablet-based MDA for accomplishing LF elimination in settings, like Leogane. We indicate that development of policy and research into how to deploy similarly-fashioned interventions, or work with the salt industry to increase population use of medicated salt, would improve present efforts to successfully accomplish the elimination of LF.

epidemiology↗