Biology subjects

Callahan, C.

Publications and source records attributed to Callahan, C..

11 recordsLinked to original sources

bioRxiv2026

Contributions of human-caused climate change and individual emitters to global coral bleaching

Coral bleaching is among the most infamous climate impacts. Yet the extent of bleaching due to human-caused climate change, as opposed to natural El Nino variability, and the contributions of individual countries and carbon majors (fossil fuel and cement producers) remains unquantified. Here, we leverage coral monitoring globally across 4,479 sites from 1985-2024 to link specific emitters to marine heat stress and bleaching. For events with >10% of corals bleached at a site, we find that 99% (95% CI: 88-100%) were attributable to human-caused climate change. Even during major El Ninos, 97-100% of bleaching events were attributable to human-caused climate change and the extent of damage increases over time from 23% of sites bleached (95% CI: 3-35%) during 1998 to 71% of sites (95% CI: 37-85%) during 2023-2024. Emissions of the United States, the largest historical emitter, contributed to 51% (95% CI: 39-65%) of bleaching events. Emissions linked to Chevron, Saudi Aramco, Gazprom, and ExxonMobil each contributed to 14% (95% CI: 11-19%) of bleaching events -- roughly double the contribution of the 39 countries of the Alliance for Small Island States. It is virtually certain emissions of China, the United States, and Indonesia caused bleaching in their coastal waters. Strong inequalities exist where countries with high socioeconomic dependence on coral reefs experienced 54% of bleaching yet contributed only 5% to bleaching. As global warming rapidly nears levels catastrophic for warm-water corals, our results show the massive contribution from anthropogenic emissions to historical coral beaching and help fill an important evidentiary gap on accountability for non-economic loss and damage from climate change.

ecology↗

bioRxiv2026

Sex and Alternative Splicing in Disease: a meta-analytic approach to identify interactions

How cell type, sex and disease interact and affect gene expression and splicing is an important, but complicated question. Visualizing and testing specific hypotheses around these complex interactions is an important first step to identifying molecular components underpinning complex disease. Using a meta-analytical framework, we develop an analytical path for identifying testable molecular hypotheses of complex interactions between splicing, sex, disease and cell type. We focus on type 1 diabetes (T1D) but the approach is generalizable to any complex disease with defined candidate loci. Previous studies report T1D-associated splicing in candidate genes, differences in disease effects across immune cell types, sex effects on splicing and cell-type-specific splicing. However, identifying and interpreting complex interactions between sex, splicing and disease are challenging. Here we demonstrate how a gene expression study of T1D, designed to evaluate these interactions can be analyzed in a straightforward manner. We find that sex-dependent T1D-associated splicing is markedly more prevalent in CD4 T cells than in CD8 T cells, affecting 72% of T1D candidate genes in CD4 cells compared to 30% in CD8 cells. We pinpoint exons whose rate of inclusion is affected by the interaction of sex and disease. We use long-read RNAseq to identify novel intron retention events and splice sites which are quantified with short-reads leading to a richer description of the regulatory impact of T1D on alternative splicing. We identify a set of candidate isoforms for follow-up molecular studies in BACH2, a transcription factor known to be relevant in disease prevalence.

genomics↗

bioRxiv2025

Cell Barcoding Reveals Lineage-dependent Outcomes in hiPSC Cardiac Differentiation

Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have potential applications in treating cardiovascular disease but are currently limited in their clinical translation. A primary limitation is the poor clinical scalability of hiPSC-CMs, with the heterogeneity of hiPSC cardiac differentiation significantly contributing to this limitation. We hypothesize that clinical scalability can be improved by tracking and controlling hiPSC clonal heterogeneity, a variable often overlooked in current differentiation approaches. "Fate priming", wherein clonal lineage identity determines differentiation fate, has been demonstrated in other stem cell differentiation pathways. We investigated fate priming in hiPSC cardiac differentiation using the ClonMapper cell barcoding platform to label, track, and isolate distinct hiPSC lineages from the same cell line. We show that certain hiPSC lineages preferentially differentiate into hiPSC-CMs or non-CMs. After isolating lineages with apparent fate priming, we found significant differences in cardiac differentiation outcomes between these single-clone populations and heterogeneous, multi-clone hiPSC populations. These findings indicate that lineage identity influences hiPSC cardiac differentiation outcomes. SIGNIFICANCE STATEMENTCardiovascular disease is a significant global health concern that can be addressed by engineering artificial tissues to develop new treatments for heart disease or to directly replace damaged heart tissue. Stem cells are a useful tool for engineering these tissues because of their ability to become cardiomyocytes. However, their clinical translation is limited by variability in the process of differentiating stem cells into cardiomyocytes. This article reports findings that show different lineages of genetically identical human induced pluripotent stem cells have different capacities for differentiating into cardiomyocytes, which may contribute to the variability observed.

bioengineering↗

bioRxiv2025

RamanOmics Decodes Spatial Vibrational-Molecular Architecture and Rewiring in Aging and Repair

Aging and tissue repair involve multilayered and spatially heterogeneous remodeling across transcriptional, biochemical, and cellular dimensions, yet prevailing definitions rely on isolated molecular markers that obscure how biochemical and transcriptional states co-evolve in tissues. Here we present RamanOmics, a multimodal framework that integrates single-nucleus RNA sequencing (snRNA-seq), spatial transcriptomics, and label-free Raman imaging to map the spatial vibrational-biochemical and molecular architecture of aging and senescence directly in intact tissues. Applied to mouse lung and skin, RamanOmics generates spatially resolved biochemical-molecular maps revealing tissue-specific programs: lung senescent cells are enriched for extracellular matrix (ECM) remodeling and TGF-{beta} signaling (Serpine1, Dab2, Igfbp7), whereas skin senescence is dominated by keratinization and barrier homeostasis modules (Krt10, Lor, Sbsn). Across tissues, we identify a conserved branched-chain fatty-acid-linked biochemical profile and Raman signature (1131-1135 cm-{superscript 1}) that robustly marks p21 senescent cells. To unify these layers, we develop a machine learning derived "multimodal barcode" that quantitatively integrates biochemical and transcriptional features, enabling non-destructive identification of senescence in situ. In a wound-healing model, RamanOmics further reveals coordinated reactivation of barrier-repair programs in senescent cells, marked by upregulation of Krt10, Lor, Sbsn, Sfn, and Dmkn together with matching increases in lipid-associated Raman signatures, confirming biological generalizability beyond steady-state aging. By directly integrating gene programs to spatial vibrational-biochemical states, RamanOmics provides a general framework and resource for scalable, multimodal profiling of cellular states.

systems biology↗

bioRxiv2025

Donor Age Impairs Vasculogenic Potential of hiPSC-Derived Endothelial Progenitors

BackgroundHuman induced pluripotent stem cells (hiPSCs) hold promise for vascular regeneration, but preliminary research often relies on neonatal donors, whereas clinical applications will use cells derived from older adults. Although the impact of donor age on reprogramming efficiency has been studied, its effect on the functionality of hiPSC-derived endothelial progenitors (hiPSC-EPs) remains unclear. This question is the focus of the current study. Methods and ResultsWe derived EPs from iPSCs sourced from three neonatal donors (ND) and three mature donors (MD) matched 1:1 for sex and somatic cell origin. We assessed their functional, epigenetic, and transcriptomic characteristics. Despite higher CD34 yields from MD-iPSCs, MD-hiPSC-EPs formed poorly interconnected and non-lumenized vascular structures in 3D hydrogels, compared to neonatal donor (ND) lines. In 2D culture, MD-hiPSC-EPs exhibited reduced cell density and aberrant VE-Cadherin localization. DNA methylation analysis revealed that somatic cell origin was the dominant driver of variance, but consistent differences in methylation of mesoderm commitment, angiogenesis, ECM remodeling, and cytoskeleton-related genes were observed between age groups. Epigenetic age prediction showed MD-hiPSC-EPs had more developmentally advanced signatures, potentially explaining their shift away from vasculogenic competence. Our RNA-sequencing findings confirm trends seen in the DNA methylation data and show differential expression of pathways linked to mitochondrial regulation and nitric oxide signaling. ConclusionsDonor age significantly alters the vasculogenic function of hiPSC-EPs. These findings underscore the necessity of donor-specific considerations in hiPSC-based vascular engineering and highlight potential barriers to translating hiPSC-derived therapeutics into older patient populations.

bioengineering↗

bioRxiv2023

Different complex regulatory phenotypes underlie hybrid male sterility in divergent rodent crosses

Hybrid incompatibilities are a critical component of species barriers and may arise due to negative interactions between divergent regulatory elements in parental species. We used a comparative approach to identify common themes in the regulatory phenotypes associated with hybrid male sterility in two divergent rodent crosses, dwarf hamsters and house mice. We investigated three potential characteristic gene expression phenotypes in hybrids including the propensity of transgressive differentially expressed genes towards over or underexpression, the influence of developmental stage on patterns of misexpression, and the role of the sex chromosomes on misexpression phenotypes. In contrast to near pervasive overexpression in hybrid house mice, we found that misexpression in hybrid dwarf hamsters was dependent on developmental stage. In both house mouse and dwarf hamster hybrids, however, misexpression increased with the progression of spermatogenesis, although to varying extents and with potentially different consequences. In both systems, we detected sex-chromosome specific overexpression in stages of spermatogenesis where inactivated X chromosome expression was expected, but the hybrid overexpression phenotypes were fundamentally different. Importantly, misexpression phenotypes support the presence of multiple developmental blocks to spermatogenesis in dwarf hamster hybrids, including a potential role of meiotic stalling or breakdown early in spermatogenesis. Collectively, we demonstrate that while there are some similarities in hybrid expression phenotypes of house mice and dwarf hamsters, there are also clear differences that point towards unique mechanisms underlying hybrid male sterility. Our results highlight the potential of comparative approaches in helping to understand the causes and consequences of disrupted gene expression in speciation.

evolutionary biology↗

bioRxiv2023

Bering: joint cell segmentation and annotation for spatial transcriptomics with transferred graph embeddings

Single-cell spatial transcriptomics such as in-situ hybridization or sequencing technologies can provide subcellular resolution that enables the identification of individual cell identities, locations, and a deep understanding of subcellular mechanisms. However, accurate segmentation and annotation that allows individual cell boundaries to be determined remains a major challenge that limits all the above and downstream insights. Current machine learning methods heavily rely on nuclei or cell body staining, resulting in the significant loss of both transcriptome depth and the limited ability to learn latent representations of spatial colocalization relationships. Here, we propose Bering, a graph deep learning model that leverages transcript colocalization relationships for joint noise-aware cell segmentation and molecular annotation in 2D and 3D spatial transcriptomics data. Graph embeddings for the cell annotation are transferred as a component of multi-modal input for cell segmentation, which is employed to enrich gene relationships throughout the process. To evaluate performance, we benchmarked Bering with state-of-the-art methods and observed significant improvement in cell segmentation accuracies and numbers of detected transcripts across various spatial technologies and tissues. To streamline segmentation processes, we constructed expansive pre-trained models, which yield high segmentation accuracy in new data through transfer learning and self-distillation, demonstrating the generalizability of Bering.

bioinformatics↗

bioRxiv2023

Contrasting Effects of SARS-CoV-2 Vaccination vs. Infection on Antibody and TCR Repertoires

Antibodies and helper T cells play important roles in SARS-CoV-2 infection and vaccination. We sequenced B- and T-cell receptor repertoires (BCR/TCR) from the blood of 251 infectees, vaccinees, and controls to investigate whether features of these repertoires could predict subjects SARS-CoV-2 neutralizing antibody titer (NAbs), as measured by enzyme-linked immunosorbent assay (ELISA). We sequenced recombined immunoglobulin heavy-chain (IGH), TCR{beta} (TRB), and TCR{delta} (TRD) genes in parallel from all subjects, including select B- and T-cell subsets in most cases, with a focus on their hypervariable CDR3 regions, and correlated this AIRRseq data with demographics and clinical findings from subjects electronic health records. We found that age affected NAb levels in vaccinees but not infectees. Intriguingly, we found that vaccination and infection have an effect on non-productively recombined IGHs, suggesting an effect that precedes clonal selection. We found that repertoires binding capacity to known SARS-CoV-2-specific CD4+ TRBs performs as well as the best hand-tuned approximate or "fuzzy" matching at predicting a protective level of NAbs, while also being more robust to repertoire sample size and not requiring hand-tuning. The overall conclusion from this large, unbiased, clinically well annotated dataset is that B- and T-cell adaptive responses to SARS-CoV-2 infection and vaccination are surprising, subtle, and diffuse. We discuss methodological and statistical challenges faced in attempting to define and quantify such strong-but-diffuse repertoire signatures and present tools and strategies for addressing these challenges.

immunology↗

bioRxiv2021

Molecular Evolution across Mouse Spermatogenesis

Genes involved in spermatogenesis tend to evolve rapidly, but we still lack a clear understanding of how different components of molecular evolution vary across this complex developmental process. We used fluorescence activated cell sorting (FACS) to generate expression data for both early (meiotic) and late (postmeiotic) cell types across thirteen inbred strains of mice (Mus) spanning ~7 million years of evolution. We used these comparative developmental data to investigate the evolution of lineage-specific expression, protein-coding sequences, and expression levels. We found increased lineage specificity and more rapid protein-coding and expression divergence during late spermatogenesis, suggesting that signatures of rapid testis molecular evolution are punctuated across sperm development. Despite strong overall developmental parallels in these components of molecular evolution, protein and expression divergences were only weakly correlated across genes. We detected more rapid protein evolution on the X chromosome relative to the autosomes, while X-linked gene expression tended to be relatively more conserved likely reflecting chromosome-wide regulatory constraints. Using allele-specific FACS expression data from crosses between four strains, we found that the relative contributions of different regulatory mechanisms also differed between cell-types. Genes showing cis-regulatory changes were more common late in spermatogenesis, and tended to be associated with larger differences in expression levels and greater expression divergence between species. In contrast, genes with trans-acting changes were more common early and tended to be more conserved across species. Our findings advance understanding of gene evolution across spermatogenesis and underscore the fundamental importance of developmental context in molecular evolutionary studies.

evolutionary biology↗

bioRxiv2020

SARS-CoV2 Testing: The Limit of Detection Matters

Resolving the COVID-19 pandemic requires diagnostic testing to determine which individuals are infected and which are not. The current gold standard is to perform RT-PCR on nasopharyngeal samples. Best-in-class assays demonstrate a limit of detection (LoD) of ~100 copies of viral RNA per milliliter of transport media. However, LoDs of currently approved assays vary over 10,000-fold. Assays with higher LoDs will miss more infected patients, resulting in more false negatives. However, the false-negative rate for a given LoD remains unknown. Here we address this question using over 27,500 test results for patients from across our healthcare network tested using the Abbott RealTime SARS-CoV-2 EUA. These results suggest that each 10-fold increase in LoD is expected to increase the false negative rate by 13%, missing an additional one in eight infected patients. The highest LoDs on the market will miss a majority of infected patients, with false negative rates as high as 70%. These results suggest that choice of assay has meaningful clinical and epidemiological consequences. The limit of detection matters.

microbiology↗

bioRxiv2017

Neuronal brain region-specific DNA methylation andchromatin accessibility are associated with neuropsychiatric disease heritability

Epigenetic modifications confer stable transcriptional patterns in the brain, and both normal and abnormal brain function involve specialized brain regions, yet little is known about brain region-specific epigenetic differences. Here, we compared prefrontal cortex, anterior cingulate gyrus, hippocampus and nucleus accumbens from 6 individuals, performing whole genome bisulfite sequencing for DNA methylation. In addition, we have performed ATAC-seq for chromatin accessibility, and RNA-seq for gene expression in the nucleus accumbens and prefrontal cortex from 6 additional individuals. We found substantial neuron- and brain region-specific differences in both DNA methylation and chromatin accessibility which were largely non-overlapping, and were greatest between nucleus accumbens and the other regions. In contrast, glial methylation and chromatin were relatively homogeneous across brain regions, although neuron/glia ratios varied greatly, demonstrating the necessity for cellular fractionation. Gene expression was also largely the same across glia from different brain regions and substantially different for neurons. Expression was correlated with methylation and accessibility across promoters and known enhancers. Several classes of transcription factor binding sites were enriched at regions of differential methylation and accessibility, including many that respond to synaptic activity. Finally, both regions of differential methylation and those of differential accessibility showed a surprising >10-fold enrichment of explained heritability associated with addictive behavior, as well as schizophrenia- and neuroticism-associated regions, suggesting that common psychiatric illness is mediated through brain region-specific epigenetic marks.

neuroscience↗