Farm animals, including livestock and poultry, play essential economic, social, and cultural roles and are indispensable in human welfare. Farm Animal Connectome database (FACdb) is a comprehensive resource that includes the association networks among gene expression, gut microbiota, and metabolites in farm animals. Although some databases present the relationship between gut microbes, metabolites, and gene expression, these databases are limited to human and mouse species, with limited data for farm animals. In this database, we calculate the associations and summarize the connections among gene expression, gut microbiota, and metabolites in farm animals using six correlation or distance calculation (including Pearson, Spearman, Cosine, Euclidean, Bray–Curtis, and Mahalanobis). FACdb contains over 55 million potential interactions of 73,571 genes, 11,046 gut microbiota, and 4,540 metabolites. It provides an easy-to-use interface for browsing and searching the association information. Additionally, FACdb offers interactive visualization tools to effectively investigate the relationship among the genes, gut microbiota, and metabolites in farm animals. Overall, FACdb is a valuable resource for understanding interactions among gut microbiota, metabolites, and gene expression. It contributes to the further utilization of microbes in animal products and welfare promotion. Compared to mice, pigs or other farm animals share more similarities with humans in molecular, cellular, and organ-level responses, indicating that our database may offer new insights into the relationship among gut microbiota, metabolites, and gene expression in humans.

Farm animals, including livestock and poultry, play essential economic, social, and cultural roles and are indispensable in human welfare. Farm Animal Connectome database (FACdb) is a comprehensive resource that includes the association networks among gene expression, gut microbiota, and metabolites in farm animals. Although some databases present the relationship between gut microbes, metabolites, and gene expression, these databases are limited to human and mouse species, with limited data for farm animals. In this database, we calculate the associations and summarize the connections among gene expression, gut microbiota, and metabolites in farm animals using six correlation or distance calculation (including Pearson, Spearman, Cosine, Euclidean, Bray–Curtis, and Mahalanobis). FACdb contains over 55 million potential interactions of 73,571 genes, 11,046 gut microbiota, and 4,540 metabolites. It provides an easy-to-use interface for browsing and searching the association information. Additionally, FACdb offers interactive visualization tools to effectively investigate the relationship among the genes, gut microbiota, and metabolites in farm animals. Overall, FACdb is a valuable resource for understanding interactions among gut microbiota, metabolites, and gene expression. It contributes to the further utilization of microbes in animal products and welfare promotion. Compared to mice, pigs or other farm animals share more similarities with humans in molecular, cellular, and organ-level responses, indicating that our database may offer new insights into the relationship among gut microbiota, metabolites, and gene expression in humans.

Farm animals, including livestock and poultry, play essential economic, social, and cultural roles and are indispensable in human welfare. Farm Animal Connectome database (FACdb) is a comprehensive resource that includes the association networks among gene expression, gut microbiota, and metabolites in farm animals. Although some databases present the relationship between gut microbes, metabolites, and gene expression, these databases are limited to human and mouse species, with limited data for farm animals. In this database, we calculate the associations and summarize the connections among gene expression, gut microbiota, and metabolites in farm animals using six correlation or distance calculation (including Pearson, Spearman, Cosine, Euclidean, Bray–Curtis, and Mahalanobis). FACdb contains over 55 million potential interactions of 73,571 genes, 11,046 gut microbiota, and 4,540 metabolites. It provides an easy-to-use interface for browsing and searching the association information. Additionally, FACdb offers interactive visualization tools to effectively investigate the relationship among the genes, gut microbiota, and metabolites in farm animals. Overall, FACdb is a valuable resource for understanding interactions among gut microbiota, metabolites, and gene expression. It contributes to the further utilization of microbes in animal products and welfare promotion. Compared to mice, pigs or other farm animals share more similarities with humans in molecular, cellular, and organ-level responses, indicating that our database may offer new insights into the relationship among gut microbiota, metabolites, and gene expression in humans.

You will find here, the additional tables and figures of the article: "Milk metabolome reveals variations on enteric methane emissions from dairy cows fed a specific inhibitor of the methanogenesis pathway" by Bénédict Yanibada, Ulli Hohenester, Mélanie Pétéra, Cécile Canlet, Stéphanie Durand, Fabien Jourdan, Anne Ferlay, Diego P. Morgavi, and Hamid Boudra. The objective of this work is to explore changes in milk metabolic profiles associated with the reduction of methane emissions. In this study we performed, untargeted NMR and LC-MS metabolomics analysis, targeted LC-MS and GC-FID analysis. We identified 38 discriminant metabolites which affected 10 metabolic pathways including methane metabolism.

Farm animals, including livestock and poultry, play essential economic, social, and cultural roles and are indispensable in human welfare. Farm Animal Connectome database (FACdb) is a comprehensive resource that includes the association networks among gene expression, gut microbiota, and metabolites in farm animals. Although some databases present the relationship between gut microbes, metabolites, and gene expression, these databases are limited to human and mouse species, with limited data for farm animals. In this database, we calculate the associations and summarize the connections among gene expression, gut microbiota, and metabolites in farm animals using six correlation or distance calculation (including Pearson, Spearman, Cosine, Euclidean, Bray–Curtis, and Mahalanobis). FACdb contains over 55 million potential interactions of 73,571 genes, 11,046 gut microbiota, and 4,540 metabolites. It provides an easy-to-use interface for browsing and searching the association information. Additionally, FACdb offers interactive visualization tools to effectively investigate the relationship among the genes, gut microbiota, and metabolites in farm animals. Overall, FACdb is a valuable resource for understanding interactions among gut microbiota, metabolites, and gene expression. It contributes to the further utilization of microbes in animal products and welfare promotion. Compared to mice, pigs or other farm animals share more similarities with humans in molecular, cellular, and organ-level responses, indicating that our database may offer new insights into the relationship among gut microbiota, metabolites, and gene expression in humans.

Description of this data

Datasets used to run the linear mixed models (LMM) assessing the influence of the proportion of fruit in the diet (RFc), fruit exploration intensity (Bi), fruit availability index (RFa), and proportion of time devoted to moving (%mov) on fecal glucocorticoids (fGC) in six groups of brown howlers (Alouatta guariba clamitans) in southern Brazil (see full details on each predictor variable in Methods).

The results of these analyses will be published in the following paper:

Chaves, Ó.M., Fernandes, F.A., Oliveira, G.T.,Bicca-Marques, J.C. (2019). Assessing the influence of ecological, climatic, and social factors on the physiological stress of a large primate in Atlantic Forest fragments

1. The Metabolic Theory of Ecology (MTE) predicts observed patterns in ecology based on metabolic rates of individuals. The theory is influential but also criticized for a lack of firm empirical evidence confirming MTE's quantitative predictions of processes, e.g. outcome of competition, at population or community level. 2. Self-thinning is a well-known population level phenomenon among plants, but a much less studied phenomenon in animal populations and no consensus exists on what a universal thinning slope for animal populations might be, or if it exists. 3. The goal of this study was to use animal self-thinning as a tool to test population-level predictions from MTE, by analyzing (i) if self-thinning can be induced in populations of house crickets (Acheta domesticus) and (ii) if the resulting thinning trajectories can be predicted from metabolic theory, using estimates of the species-specific metabolic rate of A. domesticus 4. I performed a laboratory study where the growth of A. domesticus was followed, from hatching until emergence as adults, in 71 cohorts of five different starting densities. 5. 96% of all cohorts in the three highest starting densities showed evidence of self-thinning, with estimated thinning slopes in general being remarkably close to that expected under metabolic constraints: A cross-sectional analysis of all data showing evidence of self-thinning produced an OLS slope of -1.11, exactly that predicted from specific metabolic allometry of Acheta domesticus. This result is furthermore supported by longitudinal analyses, allowing for independent responses within cohorts, producing a mean OLS slope across cohorts of -1.13 and a fixed effect LMEM slope of -1.09. Sensitivity analysis showed that these results are robust to how the criterion for on-going self-thinning was defined. Finally, also as predicted by metabolic theory, temperature had a negative effect on the thinning intercept, producing an estimate of the activation energy identical to that suggested by MTE. 6. This study demonstrates a direct link between the metabolic rate of individuals and a population-level ecological process and as such provides strong support for research that aims to integrate body mass, via its effect on metabolism, consumption and competition, into models of populations and communities.

Climate change is forcing species to migrate to cooler temperatures at higher elevations, yet many taxa are dispersing slower than necessary. One yet-to-be-tested explanation for inadequate migration rates is that high-elevation environments pose physiological barriers to dispersal, particularly in species with high metabolic demands. Our global synthesis of >800 species supports this "physiological constraints" hypothesis: upslope migration is slower in insects that depend on nature's most expensive locomotor strategy—flight.

Genotypes, phenotypes, and metadata used to analyze seasonal hair shedding data. This project was supported by Agriculture and Food Research Initiative Competitive Grant no. 2016-68004-24827 from the USDA National Institute of Food and Agriculture. Data were collected by farmers and ranchers across the United States. For more information see the preprint or publication titled "Genomic loci involved in sensing environmental cues and metabolism affect seasonal coat shedding in Bos taurus and Bos indicus cattle".

Abstract: Bovine respiratory disease (BRD) is the most common and costly infectious disease affecting the well-being and productivity of beef cattle in North America. BRD is a complex disease whose development is dependent on environmental factors and host genetics. Due to the polymicrobial nature of BRD, our understanding of the genetic and molecular mechanisms underlying the disease is still limited. This knowledge would augment the development of better genetic/genomic selection strategies and more accurate diagnostic tools to reduce BRD prevalence. Therefore, this study aimed to utilize multi-omics data (genomics, transcriptomics, and metabolomics) analyses to study differences in BRD infection in feedlots. A total of 143 cattle (80 BRD; 63 non-BRD animals) were used in this study. Firstly, a genome-wide association study (GWAS) was performed for BRD susceptibility using 207,038 SNPs. Two SNPs (Chr5:25858264 and BovineHD1800016801) were significantly (P-value < 1×10-5) associated with BRD susceptibility. Secondly, differential gene expression between BRD and non-BRD animals was studied. At the significance threshold used (log2FC > 2, logCPM > 2, and FDR < 0.01), 101 differentially expressed (DE) genes were associated with BRD infection. These DE genes significantly (P-value < 0.05) enriched several immune responses related functions such as inflammatory response. Additionally, we performed expression quantitative trait loci (eQTL) analysis and identified 420 cis-eQTLs and 144 trans-eQTLs significantly (FDR < 0.05) associated with the expression of the DE genes. Interestingly, the eQTL results indicated the most significant SNP (Chr5:25858264) identified via GWAS was a cis-eQTL for the DE gene GPR84. This analysis also demonstrated that an important SNP (rs209419196) located in the promoter region of the DE gene BPI significantly influenced the expression of this gene. Finally, the abundance of 35 metabolites was significantly (FDR < 0.05) different between BRD and non-BRD animals, and 10 metabolites were positively or negatively correlated with DE genes, which shed light on the interactions between immune response and metabolism. This study identified associations between genome, transcriptome, metabolome, and BRD phenotype of feedlot crossbred cattle. The findings may be useful for the development of genomic selection strategies for BRD susceptibility, and for the development of new diagnostic and therapeutic tools.

Background: An animal’s metabolic rate, or energetic expenditure, both impacts and is impacted by interactions with its environment. However, techniques for obtaining measurements of metabolic rate are invasive, logistically difficult, and costly. Red-green-blue (RGB) imaging tools have been used in humans and select domestic mammals to accurately measure heart and respiration rate, as proxies of metabolic rate. The purpose of this study was to investigate if infrared thermography (IRT) coupled with Eulerian video magnification (EVM) would extend the applicability of imaging tools towards measuring vital rates in exotic wildlife species with different physical attributes. Results: We collected IRT and RGB video of 52 total species (39 mammalian, 7 avian, 6 reptilian) from 36 taxonomic families at zoological institutions and used EVM to amplify subtle changes in temperature associated with blood flow for respiration and heart rate measurements. IRT-derived respiration and heart rates wer..., See README.md and the article: Rzucidlo CL, Curry E, Shero MR. 2023. Non-invasive measurements of respiration and heart rate across wildlife species using Eulerian Video Magnification of infrared thermal imagery. BMC Biology., See README.md and the article: Rzucidlo CL, Curry E, Shero MR. 2023. Non-invasive measurements of respiration and heart rate across wildlife species using Eulerian Video Magnification of infrared thermal imagery. BMC Biology.

The framework of the plant economics spectrum advanced our understanding of plant ecology and proved as a unifying concept across plant taxonomy, growth forms and biomes. Similar approaches for animals mostly focus on linking life-history and metabolic theory, but not on their application in ecosystem research. To fill this gap, we propose the animal economics spectrum (AES) based on broadly available traits that describe organismal size, biological times and rates.

To exemplify the feasibility and general usefulness of constructing the AES, we compiled data on adult and offspring body mass, life span, age at first reproduction, reproductive and metabolic rate of 98 terrestrial taxa from seven selected animal classes and mapped these taxa into an exemplary quantitative trait space.

The AES consists of two principal axes related to reproductive strategies and the pace of life; both axes are linked by animal metabolism. The AES thus closely mirrors seminal ideas on fundamental life-history strategies and more recent discoveries and developments in the fields of life-history and metabolic theory. Furthermore, we find associations between the positions of animals within the AES and taxonomy, thermoregulation and body plan.

The AES shows that key dimensions describing different ecological strategies of animals can be depicted with functional traits that are relatively easily accessible for a broad spectrum of animal taxa. We suggest future steps towards an application of the AES in ecosystem research aiming at the understanding of ecological processes and ecosystem functions. Additionally, we urge for databases that compile comparable functional traits for a large proportion of animals but also for further groups of organisms with the ultimate goal to map the economics spectrum of life.

The framework of the AES will be relevant for understanding ecological processes across animal taxa at species, community and ecosystem level. We further discuss how it can facilitate predictions on how the functional composition and diversity of animal communities can be affected by global change.

1) Evaluating the fitness of organisms is an essential step towards understanding their responses to environmental change. Connections between energy expenditure and fitness have been postulated for nearly a century. However, testing this premise among wild animals is constrained by difficulties in measuring energy expenditure while simultaneously monitoring conventional fitness metrics such as survival and reproductive output. 2) We addressed this issue by exploring the functional links between field metabolic rate (FMR), body condition, sex, age and reproductive performance in a wild population. 3) We deployed 3D accelerometers on 115 Adélie penguins (Pygoscelis adeliae) during four breeding seasons at one of the largest colonies of this species, Cape Crozier, on Ross Island, Antarctica. The demography of this population has been studied for the past 18 years. From accelerometry recordings, collected for birds of known age and breeding history, we determined the vector of the dynamic body acceleration (VeDBA) and used it as a proxy for FMR. 4) This allowed us to demonstrate relationships between FMR, a breeding quality index (BQI), and body condition. Notably, we found a significant quadratic relationship between mean VeDBA during foraging and BQI for experienced breeders, and individuals in better body condition showed lower rates of energy expenditure. 5) We conclude that using FMR as a fitness component complementary to more conventional fitness metrics will yield greater understanding of evolutionary and conservation physiology.

1. The Metabolic Theory of Ecology (MTE) predicts observed patterns in ecology based on metabolic rates of individuals. The theory is influential but also criticized for a lack of firm empirical evidence confirming MTE's quantitative predictions of processes, e.g. outcome of competition, at population or community level. 2. Self-thinning is a well-known population level phenomenon among plants, but a much less studied phenomenon in animal populations and no consensus exists on what a universal thinning slope for animal populations might be, or if it exists. 3. The goal of this study was to use animal self-thinning as a tool to test population-level predictions from MTE, by analyzing (i) if self-thinning can be induced in populations of house crickets (Acheta domesticus) and (ii) if the resulting thinning trajectories can be predicted from metabolic theory, using estimates of the species-specific metabolic rate of A. domesticus 4. I performed a laboratory study where the growth of A. domesticus was followed, from hatching until emergence as adults, in 71 cohorts of five different starting densities. 5. 96% of all cohorts in the three highest starting densities showed evidence of self-thinning, with estimated thinning slopes in general being remarkably close to that expected under metabolic constraints: A cross-sectional analysis of all data showing evidence of self-thinning produced an OLS slope of -1.11, exactly that predicted from specific metabolic allometry of Acheta domesticus. This result is furthermore supported by longitudinal analyses, allowing for independent responses within cohorts, producing a mean OLS slope across cohorts of -1.13 and a fixed effect LMEM slope of -1.09. Sensitivity analysis showed that these results are robust to how the criterion for on-going self-thinning was defined. Finally, also as predicted by metabolic theory, temperature had a negative effect on the thinning intercept, producing an estimate of the activation energy identical to that suggested by MTE. 6. This study demonstrates a direct link between the metabolic rate of individuals and a population-level ecological process and as such provides strong support for research that aims to integrate body mass, via its effect on metabolism, consumption and competition, into models of populations and communities.

Research dates included food intake, water consumption, body weight measurement, FBG,OGTT, PCR and western blotting and so on.

The global metabolic cage racks market is experiencing robust growth, driven by increasing research activities in life sciences, expanding vivaria and research centers, and rising demand for accurate metabolic data in animal studies. The market size in 2025 is estimated at $150 million, exhibiting a Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033. This growth is fueled by advancements in cage design offering improved animal welfare and data collection capabilities, as well as a growing preference for automated data acquisition systems. Segmentation by cage type (8, 10, and 12 cages) reveals a preference for larger capacity systems, reflecting the needs of larger research facilities. Application-wise, research centers and vivaria are the major consumers, reflecting the significant role of metabolic cages in pre-clinical drug development and fundamental biological research. While the market faces constraints such as high initial investment costs and the need for specialized personnel, the overall growth trajectory remains positive due to the increasing importance of animal studies in various sectors. The market's geographical distribution shows a strong presence in North America and Europe, driven by established research infrastructure and funding. However, Asia Pacific is poised for significant growth in the coming years, spurred by increasing investments in research and development across countries like China and India. Key players like Braintree Scientific, UNOBV, Lab Products, Tecniplast Group, Ugo Basile, Orchid Scientific, Harvard Apparatus, and Ancare are actively competing through product innovation and strategic partnerships, further driving market expansion. The continued focus on improving animal welfare, coupled with technological advancements, will shape the future landscape of this market, ensuring its continued expansion. This comprehensive report provides an in-depth analysis of the global Metabolic Cage Racks market, projected to be worth over $250 million by 2028. It delves into market dynamics, competitive landscape, and future growth prospects, offering valuable insights for stakeholders across the research, pharmaceutical, and animal care sectors. The report utilizes rigorous data analysis and expert insights to provide a clear and actionable understanding of this specialized market.

Experimental data on growth and respiration of black soldier fly larvae grown on mixtures of chicken feed and brewery waste.

Faecal cortisol/corticosterone metabolites (FCMs) have become increasingly popular as an easy-to-sample, non-invasive and feedback-free alternative to assess glucocorticoid (GC) levels, key components of the neuroendocrine stress response and other physiological processes. While FCMs can be a powerful aid, for instance, for gaining insights into ecological and evolutionary processes, as well as to assess animal welfare or impacts of anthropogenic stressors on wildlife populations, this method comes with specific challenges. Because GCs are heavily metabolized before excretion, it is critical to validate the enzyme immunoassays (EIAs) used to measure FCMs. Additionally, because species may differ in metabolite profiles, assay validation must be performed separately for each focal species. Despite this, the use of unvalidated assays remains widespread. We performed a biological validation experiment to test a set of EIAs to measure FCMs and adrenocortical activity in free-living Alpine ma..., See Publication: Zenth et al., 2024 In Ecology and Evolution:Â Using faecal cortisol metabolites to assess adrenocortical activity in wild-living Alpine marmot Marmota marmota: A biological validation experiment, , # Data for: Using faecal cortisol metabolites to assess adrenocortical activity in wild-living Alpine marmot Marmota marmota: A biological validation experiment

https://doi.org/10.5061/dryad.3r2280gsc

Description of the data and file structure

Data used for the Analysis for the article “Using faecal cortisol metabolites to assess adrenocortical activity in wild-living Alpine marmot Marmota marmota: A biological validation experiment†published in Ecology and Evolution (2024).

Principal Investigator: Friederike Zenth, friederike.zenth@wildlife.uni.freiburg.de

Files and variables

File: FMC_marmot_validation_simplified.csv

Description: Data used for the Analysis for the article “Using faecal cortisol metabolites to assess adrenocortical activity in wild-living Alpine marmot Marmota marmota: A biological validation experiment†published in Ecology and Evolution (2...

Organismal energy budget is strongly related to resource consumption, performance, and fitness. Hence, understanding the evolution of key energetic traits, such as basal metabolic rate (BMR), in natural populations is central for understanding life-history evolution and ecological processes. Here we used quantitative genetic analyses to study evolutionary potential of BMR in two insular populations of the house sparrow (Passer domesticus). We obtained measurements of BMR and body mass (Mb) from 911 house sparrows on the islands of Leka and Vega along the coast of Norway. These two populations were the source populations for translocations to create an additional third, admixed “common garden†population in 2012. With the use of a novel genetic group animal model concomitant with a genetically determined pedigree, we differentiate genetic and environmental sources of variation, thereby providing insight into the effects of spatial population structure on evolutionary potential. We found ..., Phenotypic data were collected during winters (February-Marc) in 2012–2015. Wild house sparrows were captured, and their metabolic rates were measured as oxygen consumption rates (mL O2 h-1) during evening-night, and the lowest 20-minute running average oxygen consumption rate was recorded as the basal metabolic rate (BMR). Simultaneously, body mass was measured to the nearest 0.1 g. A blood sample (approx 25 μL) was obtained by brachial venipuncture and stored in absolute ethanol. The blood samples were used for genetic analyses, by genotyping 603 SNP markers that were used for pedigree reconstruction using the R package sequoia. The data and code sections provided in this archive provide further analyses of these data. , All analyses were performed in R (version 4.1.0), using the packages MCMCglmm, nadiv, pedantics, tidyverse and boot.Â

description: This data set includes individual animal data collected for various biological endpoints that are included in the manuscript. Miller DB, Snow SJ, Henriquez A, Schladweiler MC, Ledbetter AD, Richards JE, Andrews DL, Kodavanti UP. Systemic metabolic derangement, pulmonary effects, and insulin insufficiency following subchronic ozone exposure in rats. Toxicol Appl Pharmacol. 2016 Jun 28;306:47-57. The primary author Desinia Miller, an UNC-EPA co-opp Student has since completed her PhD and is no longer in EPA database. This dataset is associated with the following publication: Miller, D., S. Snow, A. Henriquez, M. Schladweiler, A. Ledbetter, J. Richards, D. Andrews, and U. Kodavanti. Systemic Metabolic Derangement, Pulmonary Effects, and Insulin Insufficiency following subchronic ozone exposure in rats. TOXICOLOGY AND APPLIED PHARMACOLOGY. Academic Press Incorporated, Orlando, FL, USA, 306: 47-57, (2016).; abstract: This data set includes individual animal data collected for various biological endpoints that are included in the manuscript. Miller DB, Snow SJ, Henriquez A, Schladweiler MC, Ledbetter AD, Richards JE, Andrews DL, Kodavanti UP. Systemic metabolic derangement, pulmonary effects, and insulin insufficiency following subchronic ozone exposure in rats. Toxicol Appl Pharmacol. 2016 Jun 28;306:47-57. The primary author Desinia Miller, an UNC-EPA co-opp Student has since completed her PhD and is no longer in EPA database. This dataset is associated with the following publication: Miller, D., S. Snow, A. Henriquez, M. Schladweiler, A. Ledbetter, J. Richards, D. Andrews, and U. Kodavanti. Systemic Metabolic Derangement, Pulmonary Effects, and Insulin Insufficiency following subchronic ozone exposure in rats. TOXICOLOGY AND APPLIED PHARMACOLOGY. Academic Press Incorporated, Orlando, FL, USA, 306: 47-57, (2016).