Biology subjects

White, B.

Publications and source records attributed to White, B..

29 records · Page 2Linked to original sources

bioRxiv2021

Acyloxyacyl Hydrolase is a Host Determinant of Gut Microbiome-Mediated Pelvic Pain

Dysbiosis of gut microbiota is associated with many pathologies, yet host factors modulating microbiota remain unclear. Interstitial cystitis/bladder pain syndrome (IC/BPS or "IC") is a debilitating condition of chronic pelvic pain often with co-morbid urinary dysfunction and anxiety/depression, and recent studies find fecal dysbiosis in IC/BPS patients. We previously identified the locus encoding acyloxyacyl hydrolase, Aoah, as a modulator of pelvic pain severity in a murine IC/BPS model. AOAH-deficient mice spontaneously develop rodent correlates of pelvic pain, increased responses to induced pelvic pain models, voiding dysfunction, and anxious/depressive behaviors. Here, we report that AOAH-deficient mice exhibit dysbiosis of GI microbiota. AOAH-deficient mice exhibit an enlarged cecum, a phenotype long associated with germ-free rodents, and reduced trans-epithelial electrical resistance consistent with a "leaky gut" phenotype. AOAH-deficient ceca showed altered gene expression consistent with inflammation, Wnt signaling, and urologic disease. 16S rRNA sequencing of stool revealed altered microbiota in AOAH-deficient mice, and GC-MS identified altered metabolomes. Co-housing AOAH-deficient mice with wild type mice resulted in converged microbiota and altered predicted metagenomes. Co-housing also abrogated the pelvic pain phenotype of AOAH-deficient mice, which was corroborated by oral gavage of AOAH-deficient mice with stool slurry of wild type mice. Converged microbiota also alleviated comorbid anxiety-like behavior in AOAH-deficient mice. Oral gavage of AOAH-deficient mice with anaerobes cultured from IC/BPS stool resulted in exacerbation of pelvic allodynia. Together, these data indicate that AOAH is a host determinant of normal gut microbiota, and the dysbiosis associated with AOAH deficiency contributes to pelvic pain. These findings suggest that the gut microbiome is a potential therapeutic target for IC/BPS.

systems biology↗

bioRxiv2020

Genome analyses reveal the hybrid origin of the staple food crop white Guinea yam

White Guinea yam (Dioscorea rotundata) is an important staple tuber crop of West Africa. However, its origin remains unclear. In this study, we re-sequenced 336 accessions of white Guinea yam and compared them with the sequences of the wild Dioscorea species using an improved reference genome sequence of D. rotundata. Our results suggest a hybrid origin of white Guinea yam from crosses between the rainforest wild species D. praehensilis and the savannah-adapted D. abyssinica. We identified a higher genomic contribution from D. abyssinica in the sex chromosome of Guinea yam and an extensive introgression around the SWEETIE gene. Our findings point to a complex domestication scenario for Guinea yam and highlight the importance of wild species as gene donors for improvement of this crop through molecular breeding.

evolutionary biology↗

bioRxiv2020

Integrative transcriptomic analysis of SLE reveals IFN-driven cross-talk between immune cells

The systemic lupus erythematosus (SLE) is an incurable autoimmune disease disproportionately affecting women and may lead to damage in multiple different organs. The marked heterogeneity in its clinical manifestations is a major obstacle in finding targeted treatments and involvement of multiple immune cell types further increases this complexity. Thus, identifying molecular subtypes that best correlate with disease heterogeneity and severity as well as deducing molecular cross-talk among major immune cell types that lead to disease progression are critical steps in the development of more informed therapies for SLE. Here we profile and analyze gene expression of six major circulating immune cell types from patients with well-characterized SLE (classical monocytes (n=64), T cells (n=24), neutrophils (n=24), B cells (n=20), conventional (n=20) and plasmacytoid (n=22) dendritic cells) and from healthy control subjects. Our results show that the interferon (IFN) response signature was the major molecular feature that classified SLE patients into two distinct groups: IFN-signature negative (IFNneg) and positive (IFNpos). We show that the gene expression signature of IFN response was consistent (i) across all immune cell types, (ii) all single cells profiled from three IFNpos donors using single-cell RNA-seq, and (iii) longitudinal samples of the same patient. For a better understanding of molecular differences of IFNpos versus IFNneg patients, we combined differential gene expression analysis with differential Weighted Gene Co-expression Network Analysis (WGCNA), which revealed a relatively small list of genes from classical monocytes including two known immune modulators, one the target of an approved therapeutic for SLE (TNFSF13B/BAFF: belimumab) and one itself a therapeutic for Rheumatoid Arthritis (IL1RN: anakinra). For a more integrative understanding of the cross-talk among different cell types and to identify potentially novel gene or pathway connections, we also developed a novel gene co-expression analysis method for joint analysis of multiple cell types named integrated WGNCA (iWGCNA). This method revealed an interesting cross-talk between T and B cells highlighted by a significant enrichment in the expression of known markers of T follicular helper cells (Tfh), which also correlate with disease severity in the context of IFNpos patients. Interestingly, higher expression of BAFF from all myeloid cells also shows a strong correlation with enrichment in the expression of genes in T cells that may mark circulating Tfh cells or related memory cell populations. These cell types have been shown to promote B cell class-switching and antibody production, which are well-characterized in SLE patients. In summary, we generated a large-scale gene expression dataset from sorted immune cell populations and present a novel computational approach to analyze such data in an integrative fashion in the context of an autoimmune disease. Our results reveal the power of a hypothesis-free and data-driven approach to discover drug targets and reveal novel cross-talk among multiple immune cell types specific to a subset of SLE patients. This approach is immediately useful for studying autoimmune diseases and is applicable in other contexts where gene expression profiling is possible from multiple cell types within the same tissue compartment.

genomics↗

bioRxiv2019

Diachronic monitoring of snow leopards at Sarychat-Ertash State Reserve (Kyrgyzstan) through scat genotyping: a pilot study

Snow leopards (Panthera uncia) are a keystone species of Central Asias high mountain ecosystem. The species is listed as vulnerable and is elusive, preventing accurate population assessments that could inform conservation actions. Non-invasive genetic monitoring conducted by citizen scientists offers avenues to provide key data on this species that would otherwise be inaccessible. From 2011 to 2015, OSI-Panthera citizen science expeditions tracked signs of presence of snow leopards along transects in the main valleys and crests of the Sarychat-Ertash State Reserve (Kyrgyzstan). Scat samples were genotyped at seven autosomal microsatellite loci and at a X/Y locus for sex identification, which allowed estimating a minimum of 11 individuals present in the reserve from 2011 to 2015. The genetic recapture of 7 of these individuals enabled diachronic monitoring, providing indications of individuals movements throughout the reserve. We found putative family relationships between several individuals. Our results demonstrate the potential of this citizen science program to get a precise description of a snow leopard population through time.

genetics↗

bioRxiv2019

Cre-assisted Fine-mapping of Neural Circuits using Orthogonal Split Inteins

Summary:Genetic methods for targeting small numbers of neurons of a specific type are critical for mapping the brain circuits underlying behavior. Existing methods can provide exquisite targeting precision in favorable cases, but for many cases alternative techniques will be required. Here, we introduce a new step-wise combinatorial method for sequentially refining neuronal targeting: Depending on the restriction achieved at the first step, a second step can be easily implemented to further refine expression. For both steps, the new method relies on two independent intersections. The primary intersection targets neurons based on their developmental origins (i.e. lineage) and terminal identities, while the second intersection limits the number of lineages represented in the primary intersection by selecting lineages with overlapping activity of two distinct enhancers during neurogenesis. Our method relies critically on two libraries of 134 transgenic fly lines that express fragments of a split Cre recombinase under the control of distinct neuroblast enhancers. The split Cre fragments are fused to non-interacting pairs of split inteins, which ensure reconstitution of full-length and active Cre when all fragments are expressed in the same cell. Our split Cre system, together with its open source libraries, represent off-the-shelf components that should facilitate the targeting and characterization of brain circuits in Drosophila. Our methodology may also prove useful in other genetic model organisms.

neuroscience↗

bioRxiv2019

Cerebral atherosclerosis contributes to Alzheimer’s dementia independently of its hallmark amyloid and tau pathologies

Cerebral atherosclerosis is a leading cause of stroke and an important contributor to dementia. However, little is known about its molecular effects on the human brain and how these alterations may contribute to dementia. Here, we investigated these questions using large-scale quantification of over 8300 proteins from 438 post-mortem brains from a discovery and replication cohort. A proteome-wide association study and protein network analysis of cerebral atherosclerosis found 114 proteins and 5 protein co-expression modules associated with cerebral atherosclerosis. Enrichment analysis of these proteins and modules revealed that cerebral atherosclerosis was associated with reductions in synaptic signaling and RNA splicing and increases in oligodendrocyte development and myelination. A subset of these proteins (n=23) and protein modules (n=2) were also associated with Alzheimers disease (AD) dementia, implicating a shared mechanism with AD through decreased synaptic signaling and regulation and increased myelination. Notably, neurofilament light (NEFL) and medium (NEFM) chain proteins were among these 23 proteins, and our data suggest they contribute to AD dementia through cerebral atherosclerosis. Together, our findings offer insights into effects of cerebral atherosclerosis on the human brain proteome, and how cerebral atherosclerosis contributes to dementia risk.

neuroscience↗

bioRxiv2019

A Consensus Proteomic Analysis of Alzheimer’s Disease Brain and Cerebrospinal Fluid Reveals Early Changes in Energy Metabolism Associated with Microglia and Astrocyte Activation

Our understanding of the biological changes in the brain associated with Alzheimers disease (AD) pathology and cognitive impairment remains incomplete. To increase our understanding of these changes, we analyzed dorsolateral prefrontal cortex of control, asymptomatic AD, and AD brains from four different centers by label-free quantitative mass spectrometry and weighted protein co-expression analysis to obtain a consensus protein co-expression network of AD brain. This network consisted of 13 protein co-expression modules. Six of these modules correlated with amyloid-{beta} plaque burden, tau neurofibrillary tangle burden, cognitive function, and clinical functional status, and were altered in asymptomatic AD, AD, or in both disease states. These six modules reflected synaptic, mitochondrial, sugar metabolism, extracellular matrix, cytoskeletal, and RNA binding/splicing biological functions. The identified protein network modules were preserved in a community-based cohort analyzed by a different quantitative mass spectrometry approach. They were also preserved in temporal lobe and precuneus brain regions. Some of the modules were influenced by aging, and showed changes in other neurodegenerative diseases such as frontotemporal dementia and corticobasal degeneration. The module most strongly associated with AD pathology and cognitive impairment was the sugar metabolism module. This module was enriched in AD genetic risk factors, and was also highly enriched in microglia and astrocyte protein markers associated with an anti-inflammatory state, suggesting that the biological functions it represents serve a protective role in AD. Proteins from the sugar metabolism module were increased in cerebrospinal fluid from asymptomatic AD and AD cases, highlighting their potential as biomarkers of the altered brain network. In this study of >2000 brains and nearly 400 cerebrospinal fluid samples by quantitative proteomics, we identify proteins and biological processes in AD brain that may serve as therapeutic targets and fluid biomarkers for the disease.

systems biology↗

bioRxiv2019

Population-scale prediabetic assessment using HbA1c from menstrual blood

CDC-recommended diabetes prevention programs aim to detect and reverse disease in the one-third of Americans with prediabetes, but high-compliance serial assessment of percent hemoglobin A1c (HbA1c) remains a barrier to delivering this vision at population scale. Venous phlebotomy is challenging for busy or resource-constrained patients.\n\nIn this paper, we introduce the first-ever quantitative diagnostic test based on menstrual fluid, which allows HbA1c quantification from self-collected mailed tampons.We demonstrate that menstrual HbA1c is comparable to venous HbA1c in the diagnosis of prediabetes with the standard threshold of 5.7. We also demonstrate accuracy, precision, stability, and interference testing. Finally, surveying subjects reveals strong preference for menstrual HbA1c in quarterly testing. These findings suggest that menstrual HbA1c can be a key tool in addressing prediabetes at population scale.

pathology↗

bioRxiv2018

Machine learning enables detection of early-stage colorectal cancer by whole-genome sequencing of plasma cell-free DNA

BackgroundBlood-based methods using cell-free DNA (cfDNA) are under development as an alternative to existing screening tests. However, early-stage detection of cancer using tumor-derived cfDNA has proven challenging because of the small proportion of cfDNA derived from tumor tissue in early-stage disease. A machine learning approach to discover signatures in cfDNA, potentially reflective of both tumor and non-tumor contributions, may represent a promising direction for the early detection of cancer.\n\nMethodsWhole-genome sequencing was performed on cfDNA extracted from plasma samples (N=546 colorectal cancer and 271 non-cancer controls). Reads aligning to protein-coding gene bodies were extracted, and read counts were normalized. cfDNA tumor fraction was estimated using IchorCNA. Machine learning models were trained using k-fold cross-validation and confounder-based cross-validation to assess generalization performance.\n\nResultsIn a colorectal cancer cohort heavily weighted towards early-stage cancer (80% stage I/II), we achieved a mean AUC of 0.92 (95% CI 0.91-0.93) with a mean sensitivity of 85% (95% CI 83-86%) at 85% specificity. Sensitivity generally increased with tumor stage and increasing tumor fraction. Stratification by age, sequencing batch, and institution demonstrated the impact of these confounders and provided a more accurate assessment of generalization performance.\n\nConclusionsA machine learning approach using cfDNA achieved high sensitivity and specificity in a large, predominantly early-stage, colorectal cancer cohort. The possibility of systematic technical and institution-specific biases warrants similar confounder analyses in other studies. Prospective validation of this machine learning method and evaluation of a multi-analyte approach are underway.

cancer biology↗

bioRxiv2017

Highly efficient site-specific mutagenesis in Malaria mosquitoes using CRISPR

Anopheles mosquitoes transmit at least 200 million annual malaria infections worldwide. Despite considerable genomic resources, mechanistic understanding of biological processes in Anopheles has been hampered by a lack of tools for reverse genetics. Here, we report successful application of the CRISPR/Cas9 system for highly efficient, site-specific mutagenesis in the diverse malaria vectors Anopheles albimanus, Anopheles coluzzii, and Anopheles funestus. When guide RNAs and Cas9 are injected at high concentration, germline mutations are common and usually bi-allelic allowing for the rapid creation of stable, mutant lines for reverse genetic analysis. Our protocol should enable researchers to dissect the molecular and cellular basis of anopheline traits critical to successful disease transmission, potentially exposing new targets for malaria control.

genetics↗

bioRxiv2017

Germline Cas9 Expression Yields Highly Efficient Genome Engineering in a Major Worldwide Disease Vector, Aedes aegypti

The development of CRISPR/Cas9 technologies has dramatically increased the accessibility and efficiency of genome editing in many organisms. In general, in vivo germline expression of Cas9 results in substantially higher activity than embryonic injection. However, no transgenic lines expressing Cas9 have been developed for the major mosquito disease vector Aedes aegypti. Here, we describe the generation of multiple stable, transgenic Ae. aegypti strains expressing Cas9 in the germline, resulting in dramatic improvements in both the consistency and efficiency of genome modifications using CRISPR. Using these strains, we disrupted numerous genes important for normal morphological development, and even generated triple mutants from a single injection. We have also managed to increase the rates of homology directed repair by more than an order of magnitude. Given the exceptional mutagenic efficiency and specificity of the Cas9 strains we built, they can be used for high-throughput reverse genetic screens to help functionally annotate the Ae. aegypti genome. Additionally, these strains represent a first step towards the development of novel population control technologies targeting Ae. aegypti that rely on Cas9-based gene drives.\n\nSignificance StatementAedes aegypti is the principal vector of multiple arboviruses that significantly affect human health including dengue, chikungunya, and zika. Development of tools for efficient genome engineering in this mosquito will not only lay the foundation for the application of novel genetic control strategies that do not rely on insecticides, but will also accelerate basic research on key biological processes involved in disease transmission. Here, we report the development of a transgenic CRISPR approach for rapid gene disruption in this organism. Given their high editing efficiencies, the Cas9 strains we developed can be used to quickly generate novel genome modifications allowing for high-throughput gene targeting, and can possibly facilitate the development of gene drives, thereby accelerating comprehensive functional annotation and development of innovative population control strategies for Ae. aegypti.

bioengineering↗