Biology subjects

White, J. R.

Publications and source records attributed to White, J. R..

12 recordsLinked to original sources

bioRxiv2026

Warm temperature impedes the spread of a heritable manipulative symbiont community in spider populations

Heritable bacterial symbionts are pervasive in terrestrial arthropods, often imposing reproductive manipulations to promote their own spread within host populations. Co-infections are common, potentially allowing symbiont co-infectors to hitchhike through a host population. However, adverse thermal conditions can disrupt these communities, particularly when co-infectors vary in their thermal sensitivity. We used a multi-generation experiment to test whether warm (29 {degrees}C) conditions disrupted spread of heritable symbionts through uninfected populations of the spider, Mermessus fradeorum. We tested two common infection combinations: a single infection with a cytoplasmic incompatibility (CI) inducing Rickettsiella or a feminizing co-infection that included a feminizing Wolbachia, the same Rickettsiella, and up to three apparent hitchhikers (two additional Wolbachia strains and Tisiphia). We initiated replicate populations with 1/3 of one infection type and 2/3 uninfected spiders, evaluating population infection rate over 5 spider generations under different temperature regimes. Under cool (21{degrees}C) conditions, Wolbachia feminization drove co-infection to 88% and Rickettsiella CI drove single infection to 83% of host populations. Vertical transmission for all symbionts was high (97-99%) and hitchhiking symbionts also spread effectively. Under warm conditions, feminization and CI efficacy were reduced, and symbionts suffered variably reduced vertical transmission. Warm conditions ultimately destroyed the co-infecting symbiont consortium and impeded symbiont spread. On its own, though, Rickettsiella was still able to increase, despite reduced strength of CI. We hypothesize that contrasting tensions between feminizing spread of the symbiont consortium versus environmentally driven loss of function and transmission may explain observed patterns of mixed infections in field populations of this spider.

ecology↗

bioRxiv2026

Reference-free microsatellite instability detection from tumor sequencing using intrasample variability modeling

Microsatellite instability (MSI) is a key predictive biomarker across multiple tumor types, but current next-generation sequencing (NGS)-based callers oftendependon matched normals, large reference panels, or pretrained machine-learning models, which limits portability across assays and sequencing centers. We developed PROMIS (PROfiling of Microsatellite InStability), a tumor-only, reference-free pipeline that detects MSI by leveraging intrasample variability at predefined microsatellite loci. PROMIS models repeat-length distributions with a discrete mixture framework to distinguish stable germline configurations from unstable loci with additional allele populations. Locus-level classifications are aggregated into a continuous MSI score, defined as the fraction of unstable loci, which can then be used to classify samples as MSI-high or microsatellite-stable. We benchmarked PROMIS in colorectal (CRC), endometrial (UCEC), and gastric (STAD) cancers from The Cancer Genome Atlas (TCGA). PROMIS achieved an overall AUC of 0.995 and cohort-specific AUCs of 1.00 in CRC and STAD and 0.999 in UCEC, comparable to establi shed tools despite not using matched normals or pretrained models. Subsampling and in silico dilutions showed robust performance with substantially fewer loci and down to 3% tumor fraction. Finally, in prostate and CRC cell-free DNA (cfDNA) cohorts, including Illumina TSO500 data and an 18-gene panel, PROMIS yielded assay-agnostic MSI scores concordant with orthogonal tissue- and panel-based classifications.

bioinformatics↗

bioRxiv2025

Fusobacterium nucleatum is enriched in invasive biofilms in colorectal cancer

Fusobacterium nucleatum is an oral bacterium known to colonize colorectal tumors, where it is thought to play an important role in cancer progression. Recent advances in sequencing and phenotyping of F. nucleatum have revealed important differences at the subspecies level, but whether these differences impact the overall tumor ecology, and tumorigenesis itself, remain poorly understood. In this study, we sought to characterize Fusobacteria in the tumor microbiome of a cohort of individuals with CRC through a combination of molecular, spatial, and microbiologic analyses. We assessed for relative abundance of F. nucleatum in tumors compared to paired normal tissue, and correlated abundance with clinical and pathological features. We demonstrate striking enrichment of F. nucleatum and the recently discovered subspecies animalis clade 2 (Fna C2) specifically in colon tumors that have biofilms, highlighting the importance of complex community partnerships in the pathogenesis of this important organism.

microbiology↗

bioRxiv2024

Understanding genetic architecture overcomes tradeoffs between seed quality and insect resistance

The sunflower (Helianthus annuus) pericarp protects the seed within from both abiotic and biotic stresses. Achenes with stronger pericarps are less susceptible to damage from insect feeding. Complicating the genetic improvement of pericarp strength is the negative correlation between pericarp thickness (a component of strength) and oil content. As breeding efforts have increased oil content, there has been a concomitant decrease in pericarp thickness. A logical sunflower improvement goal is to improve oil content while preserving pericarp strength through genetic mechanisms independent of the tradeoffs with pericarp thickness. To determine the genetic basis of oil content, pericarp strength, and thickness, we identified QTL in two populations; the Sunflower Association Mapping panel (Mandel et al., 2011) and a recombinant inbred line (RIL) population derived from a thin pericarp oilseed inbred (HA 467) crossed to a thick pericarp open pollinated variety from Turkiye (PI 170415). A region on chromosome 15 was associated with neighboring QTL for banded moth resistance, oil content, and pericarp thickness, partially underlying the trade-offs among these traits. Additional QTL on chromosome 5 and 14 for pericarp strength provide fewer trade-offs with oil content. QTL for pericarp strength on chromosome 5 and pericarp thickness on chromosome 16 were associated with large structural variants, with candidate gene presence/absence variation between the haplotypes on chromosome 5. Understanding the origin and nature of phenotypic tradeoffs is beneficial to plant biologists and sunflower breeders as they seek to understand the origin and genetic architecture of adaptive and maladaptive traits.

genetics↗

bioRxiv2024

Cognate Antigen Engagement Induces HIV-1 Expression In CD4+ T Cells From People On Long-Term ART

Despite antiretroviral therapy (ART), HIV-1 persists in latently-infected CD4+ T cells, preventing cure. Antigens drive the proliferation of infected cells, precluding latent reservoir decay. However, the relationship between antigen recognition and HIV-1 gene expression is poorly understood since most studies of latency reversal use agents that induce non-specific global T cell activation. Here, we isolated rare CD4+ T cells responding to cytomegalovirus (CMV) or HIV-1 Gag antigens from participants on long-term ART and assessed T cell activation and HIV-1 RNA expression upon co-culture with autologous dendritic cells (DCs) presenting cognate antigens. Physiological presentation of cognate antigens induced broad T cell activation (median 42-fold increase in CD154+CD69+ cells) and significantly increased HIV-1 transcription (median 4-fold), mostly through the induction of rare cells with higher viral expression. Thus, despite low proviral inducibility, physiologic antigen recognition can promote HIV-1 expression, potentially contributing to spontaneous reservoir activity on ART and viral rebound upon ART interruption.

immunology↗

bioRxiv2023

Elucidating the heterogeneity of immunotherapy response and immune-related toxicities by longitudinal ctDNA and immune cell compartment tracking in lung cancer

PurposeAlthough immunotherapy is the mainstay of therapy for advanced non-small cell lung cancer (NSCLC), robust biomarkers of clinical response are lacking. The heterogeneity of clinical responses together with the limited value of radiographic response assessments to timely and accurately predict therapeutic effect -especially in the setting of stable disease-call for the development of molecularly-informed real-time minimally invasive predictive biomarkers. In addition to capturing tumor regression, liquid biopsies may be informative in evaluating immune-related adverse events (irAEs). Experimental designWe investigated longitudinal changes in circulating tumor DNA (ctDNA) in patients with metastatic NSCLC who received immunotherapy-based regimens. Using ctDNA targeted error-correction sequencing together with matched sequencing of white blood cells and tumor tissue, we tracked serial changes in cell-free tumor load (cfTL) and determined molecular response for each patient. Peripheral T-cell repertoire dynamics were serially assessed and evaluated together with plasma protein expression profiles. ResultsMolecular response, defined as complete clearance of cfTL, was significantly associated with progression-free (log-rank p=0.0003) and overall survival (log-rank p=0.01) and was particularly informative in capturing differential survival outcomes among patients with radiographically stable disease. For patients who developed irAEs, peripheral blood T-cell repertoire reshaping, assessed by significant TCR clonotypic expansions and regressions were noted on-treatment. ConclusionsMolecular responses assist with interpretation of heterogeneous clinical responses especially for patients with stable disease. Our complementary assessment of the tumor and immune compartments by liquid biopsies provides an approach for monitoring of clinical benefit and immune-related toxicities for patients with NSCLC receiving immunotherapy. Statement of translational relevanceLongitudinal dynamic changes in cell-free tumor load and reshaping of the peripheral T-cell repertoire capture clinical outcomes and immune-related toxicities during immunotherapy for patients with non-small cell lung cancer.

genomics↗

bioRxiv2023

Co-enrichment of cancer-associated bacterial taxa is correlated with immune cell infiltrates in esophageal tumor tissue

Esophageal carcinoma (ESCA) is a leading cause of cancer-related death worldwide, and Barretts esophagus (BE) is a strong risk factor along with smoking. Smoking is well-known to induce microbial dysbiosis and we asked if BE and esophageal microbiomes had shared microbial alterations that could provide novel biomarkers. We extracted DNA from BE tissues (n=5) and tumors of 158 patients in the NCI-MD case control study and sequenced the 16S rRNA gene (V3-4), with TCGA ESCA RNAseq (n = 173) and WGS (n = 139) non-human reads used as validation. We identified four taxa, Campylobacter, Prevotella, Streptococcus, and Fusobacterium as highly enriched in esophageal cancer across all cohorts. Using SparCC, we discovered that Fusobacterium and Prevotella were also co-enriched across all cohorts. We then analyzed immune cell infiltration to determine if these dysbiotic taxa were associated with immune signatures. Using xCell to obtain predicted immune infiltrates, we identified a depletion of megakaryocyte-erythroid progenitor (MEP) cells in tumors with presence of any of the four taxa, along with enrichment of platelets in tumors with Campylobactor or Fusobacterium. Taken together, our results suggest that intratumoral presence of these co-occurring bacterial genera may confer tumor promoting immune alternations that allow disease progression in esophageal cancer.

cancer biology↗

bioRxiv2021

Batch effects removal for microbiome data via conditional quantile regression (ConQuR)

Batch effects in microbiome data arise from differential processing of specimens and can lead to spurious findings and obscure true signals. Most existing strategies for mitigating batch effects rely on approaches designed for genomic analysis, failing to address the zero-inflated and over-dispersed microbiome data. Strategies tailored for microbiome data are restricted to association testing, failing to allow other analytic goals such as visualization. We develop the Conditional Quantile Regression (ConQuR) approach to remove microbiome batch effects using a two-part quantile regression model. It is a fundamental advancement in the field because it is the first comprehensive method that accommodates the complex distributions of microbial read counts, and it generates batch-removed zero-inflated read counts that can be used in and benefit all usual subsequent analyses. We apply ConQuR to real microbiome data sets and demonstrate its state-of-the-art performance in removing batch effects while preserving or even amplifying the signals of interest.

bioinformatics↗

bioRxiv2021

Incorporation of data from multiple hypervariable regions when analyzing bacterial 16S rRNA sequencing data

Short read 16S rRNA amplicon sequencing is a common technique used in microbiome research. However, inaccuracies in estimated bacterial community composition can occur due to amplification bias of the targeted hypervariable region. A potential solution is to sequence and assess multiple hypervariable regions in tandem, yet there is currently no consensus as to the appropriate method for analyzing this data. Additionally, there are many sequence analysis resources for data produced from the Illumina platform, but fewer open-source options available for data from the Ion Torrent platform. Herein, we present an analysis pipeline using an open-source analysis platform that integrates data from multiple hypervariable regions and is compatible with data produced from the Ion Torrent platform. We used the ThermoFisher Ion 16S Metagenomics Kit and a mock community of 20 bacterial strains to assess taxonomic classification of amplicons from 6 separate hypervariable regions (V2, V3, V4, V6-7, V8, V9) using our analysis pipeline. We report that different hypervariable regions have different specificities for taxonomic classification, which also had implications for global level analyses such as alpha and beta diversity. Finally, we utilize a generalized linear modeling approach to statistically integrate the results from multiple hypervariable regions and apply this methodology to data from a small clinical cohort. We conclude that scrutinizing sequencing results separately by hypervariable region provides a more granular view of the taxonomic classification achieved by each primer set as well as the concordance of results across hypervariable regions. However, the data across all hypervariable regions can be combined using generalized linear models to statistically evaluate overall differences in community structure and relatedness among sample groups.

bioinformatics↗

bioRxiv2019

Commensal-derived succinate enhances tuft cell specification and suppresses ileal inflammation

Longitudinal analysis of Crohn's disease (CD) incidence has identified an inverse correlation with helminth infestation and recent studies have revealed that intestinal tuft cell hyperplasia is critical for helminth response. Tuft cell frequency was decreased in the inflamed ilea of CD patients and a mouse model of TNF-induced Crohn's-like ileitis (TNF{Delta}ARE). Single-cell RNA sequencing paired with unbiased differential trajectory analysis of the tuft cell lineage in a genetic model of tuft cell hyperplasia (AtohKO) demonstrated that the tuft cell lineage had increased tricarboxylic acid (TCA) cycle gene signatures. Commensal microbiome-derived succinate was detected in the ileal lumen of these animals while microbiome depletion suppressed tuft cell hyperplasia. Therapeutic succinate treatment in TNF{Delta}ARE animals reduced pathology in correlation with induced tuft cell specification. We provide evidence implicating the modulatory role of intestinal tuft cells in chronic intestinal inflammation, which could facilitate leveraging this rare and elusive cell type for CD treatment.

cell biology↗

bioRxiv2018

Gut microbiome meta-analysis reveals dysbiosis is independent of body mass index in predicting risk of obesity-associated CRC

Obesity is a risk factor for colorectal cancer (CRC), accounting for more than 14% of CRC incidence. Microbial dysbiosis and chronic inflammation are common characteristics in both obesity and CRC. Human and murine studies, together, demonstrate the significant impact of the microbiome on governing energy metabolism and CRC development; yet, little is understood about the contribution of the microbiome to development of obesity-associated CRC as compared to non-obese individuals. In this study, we conducted a meta-analysis using five publicly available stool and tissue-based 16S rRNA and whole genome sequencing (WGS) data sets of CRC microbiome studies. High-resolution analysis was employed for 16S rRNA data using Resphera Insight, which allowed us to achieve species-level information to compare with WGS. Characterization of the confounders between studies, 16S rRNA variable region, and sequencing method, did not reveal any significant effect on alpha diversity in CRC prediction. Both 16S rRNA and WGS were equally variable in their ability to predict CRC. Results from community structure and composition analysis confirmed lower diversity in obese individuals without CRC; however, no universal differences were found in diversity between obese and non-obese individuals with CRC. When examining taxonomic differences, the probability of being classified as CRC did not change significantly in obese individuals for all taxa tested. However, random forest classification was able to distinguish CRC and non-CRC stool when body mass index was added to the model. Overall, microbial dysbiosis was not a significant factor in explaining the higher risk of colon cancer among individuals with obesity.

cancer biology↗

bioRxiv2018

Microbiome-TP53 Gene Interaction in Human Lung Cancer

BackgroundLung cancer is the leading cancer diagnosis worldwide and the number one cause of cancer deaths. Exposure to cigarette smoke, the primary risk factor in lung cancer, reduces epithelial barrier integrity and increases susceptibility to infections. Herein, we hypothesized that somatic mutations together with cigarette smoke generate a dysbiotic microbiota that is associated with lung carcinogenesis. Using lung tissue from controls (n=33) and cancer cases (n=143), we conducted 16S rRNA bacterial gene sequencing, with RNA-seq data from lung cancer cases in The Cancer Genome Atlas (n=1112) serving as the validation cohort.\n\nResultsOverall, we demonstrate a lower alpha diversity in normal lung as compared to non-tumor adjacent or tumor tissue. In squamous cell carcinoma (SCC) specifically, a separate group of taxa were identified, in which Acidovorax was enriched in smokers (P =0.0013). Acidovorax temporans was identified by fluorescent in situ hybridization within tumor sections, and confirmed by two separate 16S rRNA strategies. Further, these taxa, including Acidovorax, exhibited higher abundance among the subset of SCC cases with TP53 mutations, an association not seen in adenocarcinomas (AD).\n\nConclusionsThe results of this comprehensive study show both a microbiome-gene and microbiome-exposure interactions in SCC lung cancer tissue. Specifically, tumors harboring TP53 mutations, which can damage epithelial function, have a unique bacterial consortia which is higher in relative abundance in smoking-associated SCC. Given the significant need for clinical diagnostic tools in lung cancer, this study may provide novel biomarkers for early detection.

cancer biology↗