bioRxiv Science⌕ Search

Biology subjects

Gensbigler, P.

Publications and source records attributed to Gensbigler, P..

3 recordsLinked to original sources

Muscle Loss as a Foundational Step in the Development and Evolution of the Turtle Shell

Modern biodiversity is built on a series of disparate body plans whose origins are obscured by deep time. Our most direct source of clarifying data is the fossilized skeleton, where morphology reflects an evolving functionality realized through the development of associated tissues. We apply this dualistic perspective to the shelled body plan of turtles whose Paleozoic initiation is marked by a derived relationship between ribs and dermis (Lyson & Bever, 2020). Current developmental models remain in conflict with an increasingly informative fossil record, suggesting critical steps remain unrecognized. Here we explore the hypothesis that the breakdown of rib-spanning muscles--an evolutionary transformation mirrored in embryogenesis--is one such step. Multi-modal imaging of turtle embryos, including a novel application of histology-based deep learning (Kiemen et al., 2022; Matos-Romero et al., 2025; Forjaz et al., 2026), establishes intercostal muscle degradation as preceding turtle-specific rib development and highlights the heuristic power of 3D, whole-embryo analysis (Forjaz et al., 2026). Quantified divergence from mouse pinpoints the timing and tempo of this organized, apoptotic breakdown. Initial evidence suggests an associated non-pathological inflammatory response, which has been shown capable of driving evolutionarily stable hyperossification (Rashid et al., 2023). These patterns support trunk muscles as a critical signalling centre whose ontogenetic loss set the phylogenetic stage for a morphogenetic transformation remarkable in a non-metamorphic species.

evolutionary biology↗

3D multi-omic mapping of whole nondiseased human fallopian tubes at cellular resolution reveals a large incidence of ovarian cancer precursors

Uncovering the spatial and molecular landscape of precancerous lesions is essential for developing meaningful cancer prevention and early detection strategies. High-Grade Serous Carcinoma (HGSC), the most lethal gynecologic malignancy, often originates from Serous Tubal Intraepithelial Carcinomas (STICs) in the fallopian tubes, yet their minute size and our historical reliance on standard 2D histology contribute to their underreporting. Here, we present a spatially resolved, multi-omics framework that integrates whole-organ 3D imaging at cellular resolution with targeted proteomic, metabolomic, and transcriptomic profiling to detect and characterize microscopic tubal lesions. Using this platform, we identified a total of 99 STICs and their presumed precursors that harbor TP53 mutations in morphologically unremarkable tubal epithelium in all five specimens obtained from cancer-free organ donors with average-risk of developing ovarian cancer. Although these lesions comprised only 0.2% of the epithelial compartment, they displayed geographic diversity, immune exclusion, metabolic rewiring, and DNA copy number changes among lesions and normal fallopian tube epithelium discovered alterations in STIC-associated genes and the pathways they control. In sum, this platform provides a comprehensive 3D atlas of early neoplastic transformation, yielding mechanistic insights into tumor initiation and informing clinical screening strategies for detecting cancer precursors in whole organs at cellular resolution.

bioinformatics↗

Major trends and environmental correlates of spatiotemporal shifts in the distribution of genes compared to a biogeochemical model simulation in the Chesapeake Bay

Microorganisms mediate critical biogeochemical transformations that affect the productivity and health of aquatic ecosystems. Metagenomic sequencing can be used to identify how the taxonomic and functional potential of microbial communities change in response to environmental variables by investigating changes in microbial genes. However, few studies directly compare gene changes to biogeochemical model predictions of corresponding processes, especially in dynamic estuarine ecosystems. We aim to understand the major drivers of spatiotemporal shifts in microbial genes and genomes within the water column of the Chesapeake and highlight the largest discrepancies of these observations with model predictions. We used a previously published shotgun metagenomic dataset from multiple months, sites, and depths within Chesapeake Bay in 2017 and a metatranscriptomic dataset from 2010-2011. We compared metagenomic observations with rates predicted with a comprehensive physical-biogeochemical model of the Bay. We found the largest changes in the relative abundance of genes involved in carbon, nitrogen, and sulfur metabolism associated with variables that change with depth and season. Several genes associated with the largest changes in gene abundance are significantly correlated to corresponding modeled processes. Yet, several discrepancies in key genes were identified, such as differences between genes mediating nitrification, higher than expected abundance and expression of denitrification genes in aerobic waters, and nitrogen fixation genes in environments with relatively high ammonia but low oxygen concentrations. This study identifies processes that align with model expectations and others that require additional investigation to determine the biogeochemical consequences of these discrepancies and their impact within an important estuarine ecosystem.

microbiology↗