Biology subjects

Amato, K. R.

Publications and source records attributed to Amato, K. R..

5 recordsLinked to original sources

bioRxiv2026

An Aging Risk-Factor Scale: Biomarkers of Renal Disease and Anemia are Primary Predictors of Three-Year Survival in Common Marmosets (Callithrix jacchus)

Valid animal models are needed to evaluate how age-related changes in kidney function influence healthspan. Aging marmosets frequently develop renal insufficiency with anemia and exhibit reductions in body mass and metabolic rate. However, it remains unclear which age-related changes predict survival and which thresholds indicate increased mortality risk. We prospectively evaluated age, body composition, resting energy expenditure, hematology, and blood chemistry as predictors of 3-year survival in female and male marmosets (n = 66), 2-16 years of age. Objectives were to identify prognostic markers, define high-risk thresholds, and to develop and test a composite risk-factor scale for mortality screening in captivity. A 10-variable model showed the best predictive performance in multivariable Cox proportional hazards modeling, and was retained for further analysis (concordance = 0.881, p < 0.001). ROC curves using Youdens Index and AUC identified high-risk thresholds for predictors in the multivariable model, and threshold-defined categories were evaluated by Kaplan-Meier survival analysis. The 10 binary risk-factors were combined into a composite scale scored from 0 to 10 and tested with Cox regression. The scale explained approximately 42% of variance in survival and each additional risk factor increased mortality risk 1.75-fold (95% CI: 1.43-2.14, p < 0.001). Marmosets with [≥]7 risk factors exhibited a 19-month reduction in survival, and this high-risk threshold predicted 3-year survival with 89.4% accuracy. Results support the scale as a screening tool for mortality risk and highlight the high prevalence of age-associated renal disease and anemia in marmosets.

physiology↗

bioRxiv2026

Contrasting effects of forest fragmentation on the genetics and microbiomes of an endangered arboreal primate

Landscape fragmentation, one of the leading drivers of biodiversity loss, can reshape both the genetics and microbiomes of wild populations. Although fragmentation is generally expected to limit gene flow and erode genetic diversity, and to disrupt host-associated microbial communities, these responses arise via different pathways and may therefore diverge within the same population. To understand how fragmentation simultaneously shapes population genetics and gut microbiomes, we analyzed fecal-derived host genomic and microbiome data from endangered, arboreal black howler monkeys (Alouatta pigra) across a fragmentation gradient. We then integrated these data with measures of ecological connectivity, habitat quality, and demography to identify the drivers of genetic and microbiome variation and structure. Multivariate analyses indicated that genetic patterns were shaped by both connectivity and habitat quality, whereas microbiome variation was driven mainly by habitat quality. Contrary to expectations under reduced realized connectivity with increasing isolation, monkeys showed the strongest gene flow signal in the most fragmented region, and higher genetic diversity and lower inbreeding than monkeys in continuous forest. Relatedness and isolation-by-distance patterns suggested that fragmentation has sex-specific effects on movement, disrupting the usual pattern of short-range male dispersal in the most fragmented region. Gut microbiomes, however, showed predicted negative responses to fragmentation: individuals in highly fragmented habitat had lower microbial diversity and compositional shifts consistent with lower-quality diets and increased exposure to disturbed environments. These results show contrasting biological responses to fragmentation within a single population, with genetic patterns likely resulting from compensatory behavioral flexibility and microbiome patterns reflecting local habitat degradation. Our findings underscore the need for conservation assessments that integrate multiple dimensions of population health rather than relying on any single indicator of fragmentation impact.

ecology↗

bioRxiv2026

An expansive animal gut microbiome dataset elucidates major compositional shifts across bilaterian evolution

Animal gut microbiomes provide key physiological functions and are critical for host health. They vary dramatically across the animal kingdom, and are shaped by factors including host diet, evolutionary history and environment. However, analyses of gut microbiomes spanning the entire metazoan clade are lacking, limiting our understanding of the fundamental principles governing gut microbiomes. Here we present the Gut Microbiome Tree of Life (GMToL), a curated 16S amplicon dataset of 17,366 samples from 1,553 host species across 26 host classes from 284 studies, enabling analysis of large-scale evolutionary trends. Using ancestral state reconstruction, we provide a critical baseline calculation of major compositional shifts in gut microbiomes throughout animal evolution. We show that the ancestral animal gut was likely dominated by Pseudomonadota. A major shift to Bacteroidota occurred during the evolution of tetrapods, followed by the emergence of Bacillota-dominated guts in mammals and birds. We identify conserved core gut microbes and demonstrate how GMToL can be leveraged to contextualize the evolutionary history of specific microbial taxa. Ultimately, this framework enables the predictive mapping of microbial symbionts across uncharacterized host lineages, and establishes a quantitative baseline for comparative microbiome research at scale.

microbiology↗

bioRxiv2025

Validation of Body Condition Scoring as a Screening Test for Low Body Condition and Obesity in Common Marmosets (Callithrix jacchus)

Assessing body weight is common practice for monitoring health in common marmosets (Callithrix jacchus). Body composition analysis via quantitative magnetic resonance (QMR) is a more in-depth assessment allowing measurements of lean and fat mass, but it is expensive and remains unavailable to most. Alternatively, body condition scoring (BCS) is an instrument-free method for visually inspecting and palpating lean and fat tissue. Animals are rated for lean and fat mass abundance, using an ordinal scale with species-specific descriptions as reference. However, modified BCS systems developed for other species are being used, because no BCS system has been fully validated for marmosets. The accuracy of BCS in identifying marmosets with poor body condition or obesity remains unknown. We assessed an adapted BCS for marmosets (n=68, 2-16 years). Objectives were to 1) determine whether BCS predicts body weight and body composition, and 2) evaluate the performance of BCS as a screening test for low body condition and obesity in marmosets, in comparison to QMR body composition analysis. BCS predicted body weight and body composition (F(15, 166)=7.51, Wilks {Lambda}=0.240, p<0.001), and was better at predicting low lean mass and obesity, than at predicting low adiposity. Marmosets with low BCS had higher odds of low lean mass (B=3.37, (95% CI, 0.95-5.78), OR=29.0, p=0.006). Marmosets with excessively high BCS had higher odds of obesity (B=2.72, (95% CI, 1.07-4.38), OR=15.23, p=0.001). The accuracy of BCS suggests it can serve as an instrument-free method to screen for low body condition (79.4%-91.2%) and obesity (77.9%) in marmosets. Research highlightsO_LIWe evaluated body condition scoring (BCS) as a screening tool for detecting low body condition and obesity in marmosets by comparing it to diagnoses based on quantitative magnetic resonance, the gold-standard method for body composition analysis. C_LIO_LIBCS was more accurate at detecting low lean mass and obesity than low adiposity, with marmosets having low BCS showing higher odds of low lean mass and those with excessively high BCS having higher odds of obesity. C_LIO_LIResults suggest that BCS can serve as an instrument-free method to screen for low body condition and obesity in marmosets, enabling early detection of health decline and guiding the need for further diagnostic testing and treatment. C_LI

physiology↗

bioRxiv2025

The microbiome of the human facial skin is unique compared to that of other hominids

The human facial skin microbiome is remarkably similar across all people sampled to date, dominated by facultative anaerobe Cutibacterium. The origin of this genus is unknown, with no close relatives currently described from samples of primate skin. This apparent human-specific bacterial taxon could reflect the unique nature of human skin, which is significantly more oily than that of our closest primate relatives. However, previous studies have not sampled the facial skin microbiome of our closest primates. Here, we profiled the skin microbiome of zoo-housed chimpanzees (Pan troglodytes), and gorillas (Gorilla gorilla gorilla), alongside their human care staff, using both 16S and shotgun sequencing. We showed that facial skin microbiomes differ significantly across host species, with humans having the lowest diversity and most unique community among the three species. We were unable to find a close relative of Cutibacterium on either chimpanzee or gorilla facial skin, consistent with human-specificity. Hominid skin microbiome functional profiles were more functionally similar compared to their taxonomic profiles. However, we still found notable functional differences including lower proportions of fatty acid biosynthesis on humans, consistent with microbes reliance on host-derived lipids. Our study highlights the uniqueness of the human facial skin microbiome and supports a horizontal acquisition of its dominant resident from a yet unknown source. ImportanceUnderstanding how and why human skin bacteria differ from our closest animal relatives provides crucial insights into human evolution and health. While we have known that human facial skin hosts distinct bacteria--particularly Cutibacterium acnes--we did not know if these bacteria and their associated genes were also present on the faces of our closest relatives, chimpanzees and gorillas. Our study shows that human facial skin hosts markedly different bacteria than other primates, with C. acnes being uniquely abundant on human faces. This finding suggests that this key bacterial species may have adapted specifically to human skin, which produces more oils than other primates.

microbiology↗