Biology subjects

Costa, E. K.

Publications and source records attributed to Costa, E. K..

7 recordsLinked to original sources

bioRxiv2026

Sexual reproduction impacts vertebrate organ aging

Sexual reproduction is a central component of life. Yet, an unanswered question remains: how does sexual reproduction shape physiology and health across an individual's lifetime? Unlike other external factors such as diet and exercise, the impact of sexual reproduction on organ health during aging is far less studied, particularly in vertebrates. Here, we develop the short-lived killifish as a vertebrate model to study how lifelong mating affects organ aging. We discover that mating regulates liver aging in a cell-type and sex-specific manner. In old female livers, mating dampened hepatocyte inflammation and reduced myeloid cell levels, and machine-learning models predicted that mating led to a 'younger' transcriptomic age in several liver cell types. Functionally, mating reduced hepatic accumulation of several lipid classes and was associated with enhanced female resilience against the liver toxin acetaminophen. More broadly, mating induced anti-inflammatory and metabolic rewiring transcriptomic signatures in the brain and gut, indicating that mating may affect vertebrate organ aging more globally. Using publicly available human datasets and plasma proteomics aging clocks, we observed an association between sexual experience and a 'younger' plasma proteomic age of several cell types, including hepatocytes. Our work provides evidence that lifelong mating reshapes the physiological context during aging in a vertebrate, highlighting an understudied connection between vertebrate sexual history, health, and aging.

genomics↗

bioRxiv2026

MKMC enables reference-free transcriptomic analysis using k-mer representations

Traditional RNA-seq analysis depends heavily on genome alignment and gene annotation, limiting its utility in non-model organisms and introducing biases that can obscure regulatory complexity. We present MKMC (Multi-sample Kmer Counter), a scalable, reference-free toolkit for RNA-seq analysis that leverages k-mer-based statistics to detect biological variation without requiring alignment. MKMC integrates fast k-mer counting, abundance matrix generation, normalization, dimensionality reduction, and differential analysis into a unified workflow. Across diverse datasets, MKMC recapitulates key biological signals--including sex differences in killifish liver--and matches alignment-based pipelines in differential expression analysis and transcriptomic age prediction. Notably, MKMC detects isoform-specific events missed by traditional methods, one of which we validated using in situ hybridization. These results reveal previously hidden isoform-level regulatory events that contribute to sex-and age-associated transcriptional programs. MKMC offers a robust, extensible alternative to alignment-based approaches, enabling transcriptomic discovery across both model and non-model systems. While we focus here on RNA-seq as a primary application, MKMC is broadly applicable to any k-mer-based analysis of next-generation sequencing data.

bioinformatics↗

bioRxiv2026

Engulfment by brain macrophages in a short-lived vertebrate

Engulfment by macrophages is critical for waste clearance in the vertebrate brain. Understanding clearance mechanisms may open new therapeutic possibilities to counter brain aging and neurodegenerative diseases. However, few in vivo models exist to study engulfment in the brain and characterize this process during aging and across species. Here we present a genetic model for secretion of a fluorescent protein by neurons in the brain of the African turquoise killifish, the shortest-lived vertebrate that can be bred in captivity. We use this model to identify a population of brain macrophages in the killifish responsible for engulfment of material from the brain extracellular space. Intriguingly, many of these cells bear similarities to mammalian border-associated and monocyte-derived macrophages, rare subsets of macrophages in mouse and human brains noted for their engulfment capabilities. We also find that in our model, killifish brain macrophages decline in engulfment capacity with age. This work highlights how vertebrate brain macrophages, particularly those at brain border regions, can play a critical role in clearance and provides an opportunity to test interventions that can boost engulfment by these macrophages to promote brain resilience in old age and disease.

cell biology↗

bioRxiv2025

Spatial and molecular insights into microglial roles in cerebellar aging

Aging induces region-specific functional decline across the brain. The cerebellum, critical for motor coordination and cognitive function, undergoes significant structural and functional changes with age. The molecular mechanisms driving cerebellar aging--particularly the role of cerebellar glia, including microglia--remain poorly understood. Here, we used single-nuclei RNA sequencing (snRNA-seq), microglial bulk RNA-seq, and multiplexed error-robust fluorescence in situ hybridization (MERFISH) to characterize transcriptional changes associated with cellular aging in the mouse cerebellum. We discovered that microglia exhibited the most pronounced age-related changes of all cell types and that their transcriptional signatures pointed to enhanced neuroprotective immune activation and reduced lipid-droplet accumulation compared to hippocampal microglia. Furthermore, cerebellar microglia in aged mice, compared to young mice, were found in closer proximity to granule cells. This relationship was characterized using the newly defined neuron-associated microglia score, which captures proximity-dependent transcriptional changes and suggests a novel microglial responsiveness. These findings underscore the unique adaptations of the cerebellum during aging and its potential resilience to Alzheimers disease (AD) related pathology, providing crucial insight into region-specific mechanisms that may shape disease susceptibility.

neuroscience↗

bioRxiv2025

Multi-tissue transcriptomic aging atlas reveals predictive aging biomarkers in the killifish

Aging is associated with progressive tissue dysfunction, leading to frailty and mortality. Characterizing aging features, such as changes in gene expression and dynamics, shared across tissues or specific to each tissue, is crucial for understanding systemic and local factors contributing to the aging process. We performed RNA-sequencing on 13 tissues at 6 different ages in the African turquoise killifish, the shortest-lived vertebrate that can be raised in captivity. This comprehensive, sex-balanced atlas dataset reveals the varying strength of sex-age interactions across killifish tissues and identifies age-altered biological pathways that are evolutionarily conserved. Demonstrating the utility of this resource, we discovered that the killifish head kidney exhibits a myeloid bias during aging, a phenomenon more pronounced in females than in males. In addition, we developed tissue-specific transcriptomic clocks and identified biomarkers predictive of chronological age. We show the importance of sex-specific clocks for selected tissues and use the tissue clocks to evaluate a dietary intervention in the killifish. Our work provides a comprehensive resource for studying aging dynamics across tissues in the killifish, a powerful vertebrate aging model.

genomics↗

bioRxiv2024

BayesAge 2.0: A Maximum Likelihood Algorithm To Predict Transcriptomic Age

Aging is a complex biological process influenced by various factors, including genetic and environmental influences. In this study, we present BayesAge 2.0, an improved version of our maximum likelihood algorithm designed for predicting transcriptomic age (tAge) from RNA-seq data. Building on the original BayesAge framework, which was developed for epigenetic age prediction, BayesAge 2.0 integrates a Poisson distribution to model count-based gene expression data and employs LOWESS smoothing to capture non-linear gene-age relationships. BayesAge 2.0 provides significant improvements over traditional linear models, such as Elastic Net regression. Specifically, it addresses issues of age bias in predictions, with minimal age-associated bias observed in residuals. Its computational efficiency further distinguishes it from traditional models, as reference construction and cross-validation are completed more quickly compared to Elastic Net regression, which requires extensive hyperparameter tuning. Overall, BayesAge 2.0 represents a notable advance in transcriptomic age prediction, offering a robust, accurate, and efficient tool for aging research and biomarker development.

bioinformatics↗

bioRxiv2019

Expansion Microscopy of Lipid Membranes

Lipids are fundamental building blocks of cells and their organelles, yet nanoscale resolution imaging of lipids has been largely limited to electron microscopy techniques. We introduce and validate a chemical tag that enables lipid membranes to be imaged optically at nanoscale resolution via a lipid-optimized form of expansion microscopy, which we call membrane expansion microscopy (mExM). mExM, via a novel post-expansion antibody labeling protocol, enables protein-lipid relationships to be imaged in organelles such as mitochondria, the endoplasmic reticulum, the nuclear membrane, and the Golgi apparatus. mExM may be of use in a variety of biological contexts, including the study of cell-cell interactions, intracellular transport, and neural connectomics.

bioengineering↗