Biology subjects

Warren, A.

Publications and source records attributed to Warren, A..

18 recordsLinked to original sources

bioRxiv2026

Circadian Dysregulation in Aging Alters Senescence and Inflammatory Pathways in a Sex- and Time-of-Day Dependent Manner

The circadian rhythm orchestrates gene expression and critical physiological processes but becomes disrupted with aging, contributing to disease. How this disruption interacts with cellular senescence--a key driver of aging pathology--remains poorly defined. We studied renal gene expression at four timepoints over 24hrs in 6- and 24-month-old genetically diverse UM-HET3 mice of both sexes and performed complementary analyses in synchronized fibroblasts sampled at seven timepoints. Aging dysregulated core clock relationships, including loss of the canonical anti-phase expression between Bmal1 and Per2. Senescence-associated genes were not static but exhibited pronounced oscillations, with senescence phenotypes varying by sex and time of day. Differential expression analysis revealed immune activation, metabolic rewiring, and epigenetic changes that were sex- and time-dependent. Variance analysis uncovered increased transcriptional noise in aging, particularly in circadian-regulated pathways such as RNA splicing, ribosome biogenesis, and TOR signaling. Single-nucleus RNA-Seq identified two cell populations lacking the normal Bmal1-Cdkn1a expression relationship: one senescent-like and another profibrotic, revealing distinct cell states linked to circadian dysregulation. Fibroblasts recapitulated key age-related circadian changes seen in the kidneys, including phase shifts in mTOR and oxidative phosphorylation. Together, this work demonstrates that senescence phenotypes are dynamic, sex-specific, and time-of-day dependent, and introduces a new framework for detecting senescent cells based on circadian gene relationships. These findings underscore the need to integrate temporal context into aging research and therapeutic strategies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=185 HEIGHT=200 SRC="FIGDIR/small/709919v1_ufig1.gif" ALT="Figure 1"> View larger version (86K): org.highwire.dtl.DTLVardef@247e70org.highwire.dtl.DTLVardef@1e8f66borg.highwire.dtl.DTLVardef@18a0673org.highwire.dtl.DTLVardef@ad91d7_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

bioRxiv2025

Estrogens protect bone mass by inhibiting NAD+ metabolism in osteoclasts

Estrogens protect against bone loss by reducing osteoclast number and bone resorption, primarily via direct actions on osteoclast precursors. In these cells, estrogens attenuate RANKL-induced stimulation of mitochondrial complex I, which is crucial for ATP generation through NADH oxidation. NAD+ promotes redox reactions and activates NAD+-dependent enzymes, including the mitochondrial deacetylase SIRT3. However, the contribution of NAD+ to the skeletal effects of estrogens remains unknown. We show that NAD+ levels and SIRT3 activity are upregulated by RANKL and inhibited by 17{beta}-estradiol (E2) in mouse and human osteoclast precursors. Increasing NAD+ or the mitochondrial NAD+/NADH ratio reverses the inhibitory effects of E2 on SIRT3 activity and osteoclastogenesis in vitro. Deletion of Nampt, a key NAD salvage enzyme, reduces NAD+ and prevents bone loss in ovariectomized mice. Similarly, deletion of Sirt3 in osteoclast precursors mitigates estrogen deficiency-induced bone resorption. These findings indicate that suppression of NAD+ levels and mitochondrial redox metabolism by estrogens contributes to their anti-resorptive effects via inhibition of SIRT3.

molecular biology↗

bioRxiv2025

Using semantic search to find publicly available gene-expression datasets

Millions of high-throughput, molecular datasets have been shared in public repositories. have been shared in public repositories. Researchers can reuse such data to validate their own findings and explore novel questions. A frequent goal is to find multiple datasets that address similar research topics and to either combine them directly or integrate inferences from them. However, a major challenge is finding relevant datasets due to the vast number of candidates, inconsistencies in their descriptions, and a lack of semantic annotations. This challenge is first among the FAIR principles for scientific data. Here we focus on dataset discovery within Gene Expression Omnibus (GEO), a repository containing 100,000s of data series. GEO supports queries based on keywords, ontology terms, and other annotations. However, reviewing these results is time-consuming and tedious, and it often misses relevant datasets. We hypothesized that language models could address this problem by summarizing dataset descriptions as numeric representations (embeddings). Assuming a researcher has previously found some relevant datasets, we evaluated the potential to find additional relevant datasets. For six human medical conditions, we used 30 models to generate embeddings for datasets that human curators had previously associated with the conditions and identified other datasets with the most similar descriptions. This approach was often, but not always, more effective than GEOs search engine. Our top-performing models were trained on general corpora, used contrastive-learning strategies, and used relatively large embeddings. Our findings suggest that language models have the potential to improve dataset discovery, perhaps in combination with existing search tools.

genomics↗

bioRxiv2024

Sugar-rich foods exacerbate antibiotic-induced microbiome injury

Intestinal microbiota composition is implicated in several diseases; understanding the factors that influence it are key to elucidating host-commensal interactions and to designing microbiome-targeted therapies. We quantified how diet influences microbiome dynamics in hospitalized patients. We recorded 9,419 meals consumed by 173 patients undergoing hematopoietic cell transplantation and profiled the microbiome in 1,009 longitudinally collected stool samples from 158 of them. Caloric intake was correlated with fecal microbiota diversity. Bayesian inference revealed associations between intake of sweets or sugars during antibiotic exposure with microbiome disruption, as assessed by low diversity or expansion of the pathobiont Enterococcus. We validated this observation experimentally, finding that sucrose exacerbated antibiotic-induced Enterococcus expansion in mice. Taken together, our results suggest that avoiding sugar-rich foods during antibiotic treatment may reduce microbiome injury. One Sentence SummaryAnalyses of hematopoietic cell transplant patients and of mice uncover links between foods and microbiome disruption.

microbiology↗

bioRxiv2023

Disrupted endosomal trafficking of the Vangl-Celsr polarity complex causes congenital anomalies in trachea-esophageal separation

Disruptions in foregut morphogenesis can result in life-threatening conditions where the trachea and esophagus fail to separate properly, such as esophageal atresia (EA) and tracheoesophageal fistulas (TEF). The developmental basis of these congenital anomalies is poorly understood, but recent genome sequencing reveals that de novo variants in intracellular trafficking genes are enriched in EA/TEF patients. Here, we confirm that mutation of orthologous genes in Xenopus disrupts trachea-esophageal separation similar to EA/TEF patients. We show that the Rab11a recycling endosome pathway is required to localize Vangl-Celsr polarity complexes at the luminal cell surface where opposite sides of the foregut tube fuse. Partial loss of endosome trafficking or Vangl-Celsr complexes disrupts epithelial polarity and mutant cells accumulate at the fusion point, fail to downregulate Cadherin, and do not separate into distinct trachea and esophagus. These data provide insights into the mechanisms of congenital anomalies and general paradigms of tissue fusion during organogenesis.

developmental biology↗

bioRxiv2021

eIF6 rebinding dynamically couples ribosome maturation and translation

Protein synthesis is a cyclical process consisting of translation initiation, elongation, termination and ribosome recycling. The release factors SBDS and EFL1 (both mutated in the leukaemia predisposition disorder Shwachman-Diamond syndrome) license entry of nascent 60S ribosomal subunits into active translation by evicting the anti-association factor eIF6 from the 60S intersubunit face. Here, we show that in mammalian cells, eIF6 holds all free cytoplasmic 60S subunits in a translationally inactive state and that SBDS and EFL1 are the minimal components required to recycle these 60S subunits back into additional rounds of translation by evicting eIF6. Increasing the dose of eIF6 in mice in vivo impairs terminal erythropoiesis by sequestering post-termination 60S subunits in the cytoplasm, disrupting subunit joining and attenuating global protein synthesis. Our data reveal that ribosome maturation and recycling are dynamically coupled by a mechanism that is disrupted in an inherited leukaemia predisposition disorder.

cell biology↗

bioRxiv2021

Mmp-13 deletion in cells of the mesenchymal lineage increases bone mass, decreases endocortical osteoclast number, and attenuates the cortical bone loss caused by estrogen deficiency in mice

The protective effect of estrogens against cortical bone loss is mediated via direct actions on mesenchymal lineage cells, but functional evidence for the precise molecular mechanism(s) and the mediators of these effects has only recently began to emerge. We report that the matrix metalloproteinase 13 (MMP-13) is the highest up-regulated gene in calvaria or bone marrow cells from mice lacking the estrogen receptor (ER) alpha in osteoprogenitors. We, therefore, generated mice with conditional Mmp-13 deletion in Prrx1 expressing cells (Mmp-13{Delta}Prrx1) and compared the effect of estrogen deficiency on their bone phenotype to that of control littermates (Mmp-13f/f). Femur and tibia length was decreased in sham-operated Mmp-13{Delta}Prrx1 mice as compared to Mmp-13f/f. Cortical thickness and trabecular bone volume in the femur and tibia were increased and osteoclast number at the endocortical surfaces was decreased in the sham-operated female Mmp-13{Delta}Prrx1 mice; whereas bone formation rate was unaffected. Ovariectomy (OVX) caused a decrease of cortical thickness in the femur and tibia of Mmp-13f/f control mice. This effect was attenuated in the Mmp-13{Delta}Prrx1 mice; but the decrease of trabecular bone caused by OVX was not affected. These results reveal that mesenchymal cell-derived MMP-13 regulates osteoclast number, bone resorption, and bone mass. We have recently reported that the loss of cortical, but not trabecular bone, caused by OVX is also attenuated in Cxcl12{Delta}Prrx1 mice. Together with the present report, this functional genetic evidence provides proof of principle that increased production of mesenchymal cell-derived factors, such as CXCL12 and MMP-13, are important mediators of the adverse effect of estrogen deficiency on cortical, but not trabecular, bone. Therefore, the mechanisms responsible for the protective effect of estrogens on these two major bone compartments are different.

molecular biology↗

bioRxiv2020

Phosphate dysregulation via the XPR1:KIDINS220 protein complex is a therapeutic vulnerability in ovarian cancer

Clinical outcomes for patients with ovarian and uterine cancers have not improved greatly in the past twenty years. To identify ovarian and uterine cancer vulnerabilities, we analyzed genome-scale CRISPR/ Cas9 loss-of-function screens across 739 human cancer cell lines. We found that many ovarian cancer cell lines overexpress the phosphate importer SLC34A2, which renders them sensitive to loss of the phosphate exporter XPR1. We extensively validated the XPR1 vulnerability in cancer cell lines and found that the XPR1 dependency was retained in vivo. Overexpression of SLC34A2 is frequently observed in tumor samples and is regulated by PAX8 -a transcription factor required for ovarian cancer survival. XPR1 overexpression and copy number amplifications are also frequently observed. Mechanistically, SLC34A2 overexpression and impaired phosphate efflux leads to the accumulation of intracellular phosphate and cell death. We further show that proper localization and phosphate efflux by XPR1 requires a novel binding partner, KIDINS220. Loss of either XPR1 or KIDINS220 results in acidic vacuolar structures which precede cell death. These data point to the XPR1:KIDINS220 complex - and phosphate dysregulation more broadly -as a therapeutic vulnerability in ovarian cancer.

cancer biology↗

bioRxiv2020

The latitudinal diversity gradient in brush-footed butterflies (Nymphalidae): conserved ancestral tropical niche but different continental histories.

The latitudinal diversity gradient (LDG) is arguably one of the most striking patterns in nature. The global increase in species richness toward the tropics across continents and taxonomic groups stimulated the formulation of many hypotheses to explain the underlying mechanisms of this pattern. We evaluated several of these hypotheses to explain spatial diversity patterns in the butterfly family, Nymphalidae, by assessing the contributions of speciation, extinction, and dispersal to the LDG, and also the extent to which these processes differ among regions at the same latitude. We generated a new, time-calibrated phylogeny of Nymphalidae based on 10 gene fragments and containing ca. 2,800 species ([~]45% of extant diversity). Neither speciation nor extinction rate variations consistently explain the LDG among regions because temporal diversification dynamics differ greatly across longitude. For example, we found that Neotropical nymphalid diversity results from low extinction rates, not high speciation rates, and that biotic interchanges with other regions were rare. Southeast Asia was also characterized by a low speciation rate but, unlike the Neotropics, was the main source of dispersal events through time. Our results suggest that global climate change throughout the Cenozoic, particularly during the Eocene-Oligocene transition, combined with the conserved ancestral tropical niches, played a major role in generating the modern LDG of butterflies.

ecology↗

bioRxiv2020

ProtTox: Toxin identification from Protein Sequences

Toxin classification of protein sequences is a challenging task with real world applications in healthcare and synthetic biology. Due to an ever expanding database of proteins and the inordinate cost of manual annotation, automated machine learning based approaches are crucial. Approaches need to overcome challenges of homology, multi-functionality, and structural diversity among proteins in this task. We propose a novel deep learning based method ProtTox, that aims to address some of the shortcomings of previous approaches in classifying proteins as toxins or not. Our method achieves a performance of 0.812 F1-score which is about 5% higher than the closest performing baseline.

bioinformatics↗

bioRxiv2020

Global computational alignment of tumor and cell line transcriptional profiles

Cell lines are key tools for preclinical cancer research, but it remains unclear how well they represent patient tumor samples. Identifying cell line models that best represent the features of particular tumor samples, as well as tumor types that lack in vitro model representation, remain important challenges. Gene expression has been shown to provide rich information that can be used to identify tumor subtypes, as well as predict the genetic dependencies and chemical vulnerabilities of cell lines. However, direct comparisons of tumor and cell line transcriptional profiles are complicated by systematic differences, such as the presence of immune and stromal cells in tumor samples and differences in the cancer-type composition of cell line and tumor expression datasets. To address these challenges, we developed an unsupervised alignment method (Celligner) and applied it to integrate several large-scale cell line and tumor RNA-Seq datasets. While our method aligns the majority of cell lines with tumor samples of the same cancer type, it also reveals large differences in tumor/cell line similarity across disease types. Furthermore, Celligner identifies a distinct group of several hundred cell lines from diverse lineages that present a more mesenchymal and undifferentiated transcriptional state and which exhibit distinct chemical and genetic dependencies. This method could thus be used to guide the selection of cell lines that more closely resemble patient tumors and improve the clinical translation of insights gained from cell line models.

cancer biology↗

bioRxiv2020

Cellular mRNA signals in human kidney tumors

The cellular transcriptome may provide clues into the differentiation state and origin of human cancer, as tumor cells may retain patterns of gene expression similar to the cell they derive from. Here, we studied the differentiation state and cellular origin of human kidney tumors, by assessing mRNA signals in 1,300 childhood and adult renal tumors, spanning seven different tumor types. Using single cell mRNA reference maps of normal tissues generated by the Human Cell Atlas project, we measured the abundance of reference "cellular signals" in each tumor. Quantifying global differentiation states, we found that, irrespective of tumor type, childhood tumors exhibited fetal cellular signals, thus replacing the long-held presumption of "fetalness" with a precise, quantitative readout of immaturity. By contrast, in adult cancers our assessment refuted the suggestion of dedifferentiation towards a fetal state in the overwhelming majority of cases, with the exception of lethal variants of clear cell renal cell carcinoma. Examining the specific cellular phenotype of each tumor type revealed an intimate connection between the different mesenchymal populations of the developing kidney and childhood renal tumors, whereas adult tumors mostly represented specific mature tubular cell types. RNA signals of each tumor type were remarkably uniform and specific, indicating a possible therapeutic and diagnostic utility. We demonstrated this utility with a case study of a cryptic renal tumor. Whilst not classifiable by clinical pathological work-up, mRNA signals revealed the diagnosis. Our findings provide a cellular definition of human renal tumors through an approach that is broadly applicable to human cancer.

cancer biology↗

bioRxiv2020

Gene expression has more power for predicting in vitro cancer cell vulnerabilities than genomics

Achieving precision oncology requires accurate identification of targetable cancer vulnerabilities in patients. Generally, genomic features are regarded as the state-of-the-art method for stratifying patients for targeted therapies. In this work, we conduct the first rigorous comparison of DNA- and expression-based predictive models for viability across five datasets encompassing chemical and genetic perturbations. We find that expression consistently outperforms DNA for predicting vulnerabilities, including many currently stratified by canonical DNA markers. Contrary to their perception in the literature, the most accurate expression-based models depend on few features and are amenable to biological interpretation. This work points to the importance of exploring more comprehensive expression profiling in clinical settings.

cancer biology↗

bioRxiv2019

Multiplexed single-cell profiling of post-perturbation transcriptional responses to define cancer vulnerabilities and therapeutic mechanism of action

Assays to study cancer cell responses to pharmacologic or genetic perturbations are typically restricted to using simple phenotypic readouts such as proliferation rate or the expression of a marker gene. Information-rich assays, such as gene-expression profiling, are generally not amenable to efficient profiling of a given perturbation across multiple cellular contexts. Here, we developed MIX-Seq, a method for multiplexed transcriptional profiling of post-perturbation responses across a mixture of samples with single-cell resolution, using SNP-based computational demultiplexing of single-cell RNA-sequencing data. We show that MIX-Seq can be used to profile responses to chemical or genetic perturbations across pools of 100 or more cancer cell lines, and combine it with Cell Hashing to further multiplex additional experimental conditions, such as multiple post-treatment time points or drug doses. Analyzing the high-content readout of scRNA-seq reveals both shared and context-specific transcriptional response components that can identify drug mechanism of action and can be used to predict long-term cell viability from short-term transcriptional responses to treatment.

cancer biology↗

bioRxiv2019

Independence of HIF1a and androgen signaling pathways in prostate cancer

Androgen signaling drives prostate cancer progression and is a therapeutic target. Hypoxia/HIF1a signaling is associated with resistance to hormone therapy and a poor prognosis in patients treated with surgery or radiotherapy. It is not known whether the pathways operate in cooperation or independently. Using LNCaP cells with and without stable transfection of a HIF1a expression vector, we show that combined AR and HIF1a signaling promotes tumor growth in vitro and in vivo, and the capacity of HIF1a to promote tumor growth in the absence of endogenous androgen in vivo. Gene expression analysis identified 7 genes that were upregulated by both androgen and HIF1a. ChIP-Seq analysis showed that the AR and HIF/hypoxia signaling pathways function independently regulating the transcription of different genes with few shared targets. In clinical datasets elevated expression of 5 of the 7 genes was associated with a poor prognosis. Our findings suggest that simultaneous therapeutic inhibition of AR and HIF1a signaling pathways should be explored as a potential therapeutic strategy.

cancer biology↗

bioRxiv2019

Pan-cancer single cell RNA-seq uncovers recurring programs of cellular heterogeneity

Cultured cell lines are the workhorse of cancer research, but it is unclear to what extent they recapitulate the cellular heterogeneity observed among malignant cells in tumors, given the absence of a native tumor microenvironment. Here, we used multiplexed single cell RNA-seq to profile ~200 cancer cell lines. We uncovered expression programs that are recurrently heterogeneous within many cancer cell lines and are largely independent of observed genetic diversity. These programs of heterogeneity are associated with diverse biological processes, including cell cycle, senescence, stress and interferon responses, epithelial-to-mesenchymal transition, and protein maturation and degradation. Notably, some of these recurrent programs recapitulate those seen in human tumors, suggesting a prominent role of intrinsic plasticity in generating intra-tumoral heterogeneity. Moreover, the data allowed us to prioritize specific cell lines as model systems of cellular plasticity. We used two such models to demonstrate the dynamics, regulation and drug sensitivities associated with a cancer senescence program also observed in human tumors. Our work describes the landscape of cellular heterogeneity in diverse cancer cell lines, and identifies recurrent patterns of expression heterogeneity that are shared between tumors and specific cell lines and can thus be further explored in follow up studies.

cancer biology↗

bioRxiv2019

Direct measurement of X-ray induced heating of microcrystals

Temperature control is a key aspect of macromolecular crystallography, with the technique of cryocooling routinely used to mitigate X-ray induced damage. Beam induced heating could cause the temperature of crystals to rise above the glass transition temperature, greatly increasing the rate of damage. X-ray induced heating of ruby crystals 20-40 microns in size has been quantified non-invasively by monitoring the emission wavelengths of X-ray induced fluorescence during exposure to the X-ray beam. For beamsizes and dose-rates typically used in macromolecular crystallography the temperature rises are of order 20 K. The temperature changes observed are compared with models in the literature and can be used as a validation tool for future models.\n\nSynopsisX-ray induced heating of micro-crystals is quantified through the temperature-dependent shift in X-ray induced fluorescence from ruby crystals.

biophysics↗

bioRxiv2018

Habitat heterogeneity drives scale-dependent biodiversity loss in a temperate marine ecosystem

Biodiversity loss is driven by interacting factors operating at different spatial scales. Yet, there remains uncertainty as to how fine-scale environmental conditions mediate biological responses to broad-scale stressors. We surveyed mid-latitude kelp bed habitats to determine whether local habitat heterogeneity has mediated changes in community diversity after more than two decades of extreme temperature events, most notably the 2013-2016 heat wave. Local wave exposure conditions were key in determining responses, with some habitats remaining stable and others experiencing near complete diversity loss, leading to local declines without regional extinctions. Wave-sheltered shores, which saw the largest declines, are a very common habitat type in the Northeast Pacific and may be especially sensitive to climate-related losses in kelp diversity and abundance. Our findings highlight how local gradients can interact with global drivers to facilitate diversity loss and demonstrate how incorporating differences between habitat patches can be essential to capturing scale-dependent biodiversity loss across the landscape.

ecology↗