Biology subjects

Kimmel, A.

Publications and source records attributed to Kimmel, A..

4 recordsLinked to original sources

bioRxiv2026

Expanded stoichiometric model of chondrocyte metabolism: response to cyclical shear and compressive loading

Cartilage deterioration is a hallmark osteoarthritis, and there is substantial interest in developing strategies for cartilage repair. Cyclical mechanical stimulation has been known for decades to drive synthesis of cartilage matrix proteins. Matrix synthesis requires activation of central metabolism for producing precursors to non-essential amino acids required for protein translation. However, there are gaps in knowledge regarding how mechanical stimuli affect chondrocyte central metabolism. Here, we find that cyclical shear and compression drive differences in chondrocyte central metabolism in a sex-dependent manner. Based on established biochemistry, we developed and tested a stoichiometric model containing 139 metabolites and 172 reactions from central metabolism that includes production of key cartilage matrix proteins. We then used experimental metabolomics data from shear and compressive stimulation of osteoarthritic chondrocytes to constrain this model and ran multiple simulations examining the potential for producing matrix proteins and ATP. Our results show that both shear and compression can stimulate osteoarthritic chondrocyte metabolism in a manner consistent with production of cartilage matrix proteins, with notable differences between male and female chondrocytes. Additionally, and importantly, our simulation results suggest that nitrogen availability is a key limitation to chondrocyte synthesis of matrix proteins. These results are a starting point for using central metabolism of chondrocytes to optimize synthesis of matrix proteins for cartilage repair. For example, increasing glutamine levels in the presence of cyclical compression has potential to increase production of both types II and VI collagen. These strategies have potential for improving cartilage tissue engineering and repair.

bioengineering↗

bioRxiv2025

CRISPR screening reveals genetic regulators associated with the evolution of eye degeneration

Determining the genetic factors contributing to trait evolution is critical for understanding how and why traits evolve; however, establishing which genes underlie the evolution of complex traits remains challenging. The freshwater fish Astyanax mexicanus, a species that includes blind, cave-dwelling and eyed, surface-dwelling fish, is a powerful model for evolutionary genetics. While genetic mapping studies in this species previously identified genomic regions associated with cave-derived traits, few causative genes and genetic changes have been identified. Here, we develop methods to identify and rapidly functionally assess candidate genes in A. mexicanus, focusing on a defining trait of cave animals, eye loss. Candidate genes were identified based on whether they fell within an eye-related quantitative trait locus, were differentially expressed between surface and cave eyes, and showed evidence of positive selection in cavefish. Single-nucleus RNA-sequencing revealed that these candidate genes were expressed in multiple cell types during development, including those in different tissues of the eye. CRISPR-Cas9-based mutagenesis demonstrated that disruption of nine of these candidate genes in surface fish resulted in altered eye size. Perturbation of one of these genes, fibulin-7 (fbln7), revealed changes in eye size across multiple stages of eye development. Together, this work identified multiple genes associated with the evolution of eye degeneration in A. mexicanus. Further, this study represents a roadmap for rapid identification and functional assessment of candidate genes implicated in the evolution of traits in cavefish that can be applied to other evolutionary genetic models.

genetics↗

bioRxiv2025

Analysis of multi-trait evolution across independently evolved cavefish populations reveals shared and independent evolution of suites of cave-associated traits

Environmental perturbations often lead to the evolution of multiple traits. Determining whether shared genetic factors underlie multi-trait evolution is a central question in evolutionary biology. In the Mexican tetra, Astyanax mexicanus, cave-dwelling populations have repeatedly evolved multiple traits. The repeated evolution of these traits, paired the robust environmental differences between the surface and cave habitats, provide an opportunity to investigate the genetic basis of multi-trait evolution. Here, we investigate the extent to which shared genetic mechanisms underlie the repeated evolution of multiple traits in cavefish. Across cave populations, we find evidence for shared and distinct genetic mechanisms contributing to the evolution of individual traits. Further, multiple traits covary in cave-surface F2 hybrids and many of the same trait correlations are found across independently evolved cave populations. Finally, we assessed traits that differ between pigmented and albino F2 fish in surface fish with mutations in the albinism gene oculocutaneous albinism 2 (oca2). This revealed that mutations in oca2 reduce bottom-dwelling behavior in A. mexicanus. Together, these findings suggest that multi-trait evolution occurs repeatedly through shared genetic factors across A. mexicanus cave populations. These results are consistent with pleiotropy or linkage playing a large role in multi-trait evolution in this species.

evolutionary biology↗

bioRxiv2025

Automated profiling of social behaviors to assess the genetic basis of evolution of aggressive behaviors in A. mexicanus

Across the animal kingdom, social behaviors such as aggression are critical for survival and reproductive success. While there is significant variation in social behaviors within and between species, the genetic mechanisms underlying natural variation in social behaviors are poorly understood. A central challenge to investigating the mechanisms contributing to the evolution of social behaviors is that these behaviors are typically complex, making them a challenge to quantify. The Mexican tetra, Astyanax mexicanus, is a powerful model for investigating the evolution of traits, as it is a single species that exists as populations of eyed, river-dwelling surface fish and blind cave-dwelling fish. The blind cavefish have evolved morphological and behavioral differences compared to surface fish, including reduced aggression. Here, we developed and validated an automated machine learning pipeline that integrates pose-estimation and supervised behavioral classification to track and quantify aggression-associated behaviors--striking, following, and circling. Using this pipeline, we established that these behaviors are quantitatively different between surface and cave fish during juvenile stages in A. mexicanus, similar to what was observed previously in adults. Moreover, assessment of these aggressive behaviors in surface-cave F2 hybrid fish revealed that striking and following are strongly positively correlated, while striking and circling are negatively correlated, suggesting that these behaviors evolved through some shared genetic mechanisms. These findings demonstrate the power of automated tracking and behavioral phenotyping in multiple fish in A. mexicanus and establish a foundation for future studies investigating the genetic basis of evolution of social behaviors.

evolutionary biology↗