Biology subjects

Fortes, M. R. S.

Publications and source records attributed to Fortes, M. R. S..

5 recordsLinked to original sources

bioRxiv2026

Epigenetic Patterns of Xylanibacter ruminicola in Bovine Rumen Across Seasons and Pregnancy

Ruminants obtain nutrients through the microbial fermentation of plant material in the rumen. Xylanibacter ruminicola is a highly abundant bacterial species in the rumen. During fermentation, X. ruminicola utilizes diverse carbohydrates from plant materials to synthesize propionate, a volatile fatty acid providing energy to ruminants. However, variation in pasture quality (e.g, nutrient and fibre content) across seasons and host pregnancy status can alter the rumen microenvironment, potentially affecting microbial activity. Bacteria in culture display distinct methylation (a reversible epigenetic modification capable of gene regulation) changes in response to the growth environment. We hypothesized that the changes to the rumen environment would affect the DNA methylation patterns within the X. ruminicola genome. Rumen fluid from 37 female Brahman cattle (17 pregnant) were sampled across four seasons. DNA methylation profiles (N6-methyladenine, N4-methylcytosine, and 5-methylcytosine) of X. ruminicola across seasons (varying pasture quality) and pregnancy statuses characterized using Oxford Nanopore sequencing. After correcting for relative abundance, DNA methylation levels within the coding DNA sequences of several X. ruminicola genes differed between seasons and pregnancy status. Most of these genes were classified as ExbD/TolR family proteins and related to the protein transport process. Our study demonstrates that the DNA methylation profiles of rumen X. ruminicola genes vary with host environment factors. These results provide insight into the role of bacterial DNA methylation in mediating interactions between bacteria and their environments. Lay SummaryRuminants rely on rumen microbes to convert plants into nutrients. Xylanibacter ruminicola is a bacterial species in the rumen that produces nutrients for ruminants during plant fermentation. Changes in pasture quality and host pregnancy status can influence the activity of X. ruminicola, as reflected in the DNA methylation profile across its genome. DNA methylation is a reversible DNA modification that can affect gene activity and help bacterial adaptation to changing environments. Rumen fluid from 37 female Brahman cattle (17 pregnant) across four seasons were used to evaluate the pasture quality and host pregnancy effects on the DNA methylation profile of X. ruminicola. The relative abundances of X. ruminicola were influenced by pasture quality, but not by host pregnancy. However, host pregnancy status and changes in pasture quality influenced the DNA methylation signatures of X. ruminicola. Genes with DNA methylation changes were associated with the protein transport process. These findings suggest that the DNA methylation profiles of rumen X. ruminicola vary with host environment factors. Teaser TextThis study demonstrates that the DNA methylation profiles of rumen Xylanibacter ruminicola vary with host environment factors. These findings provide insight into the role of bacterial DNA methylation in mediating interactions between rumen bacteria and their environment.

microbiology↗

bioRxiv2026

Short communication: Oral microbiome as a potential proxy for grazing livestock methane emissions

Enteric methane emissions from ruminant livestock contribute to global warming, creating an urgent need for effective mitigation strategies that do not compromise animal productivity and welfare. Methanogenic archaea within the rumen microbiome drive enteric methane emissions. However, large-scale rumen-fluid sampling in commercial production systems is impractical, due to its invasive nature and the associated logistical challenges. This study hypothesised that rumination enables the capture of rumen microbial signals within the oral cavity and using oral microbiome profiles to provide a practical, non-invasive alternative method for proxy methane phenotyping in commercial production systems. To test the hypothesis, we estimated the oral microbiability, defined as the proportion of phenotypic variance in methane emissions explained by oral microbiome variation. Samples were collected from 209 animals across two trials in Queensland, Australia. Oral microbiome samples were obtained from all animals, with paired rumen samples in one trial, and methane emissions were measured using either the sulphur hexafluoride (SF6) tracer technique or the GreenFeed system. Microbial features were characterised using taxonomic and functional annotations, and microbiability was estimated using mixed linear models incorporating microbiome-based relationship matrices. Although the small sample size limited strong conclusions, the oral microbiability estimates reported in this study were comparable to those derived from rumen samples. Functional microbial profiles generally explained a greater proportion of methane variation than taxonomic profiles, suggesting that microbial function is more closely linked to methane production than community composition alone. However, these differences were not statistically significant due to large standard errors. These findings suggest that oral microbiome sampling potentially provides a practical, minimally invasive, scalable proxy method for methane emissions of individual cattle in grazing systems, where direct methane gas measurements are labour-intensive and difficult to implement. Integrating oral microbiome profiles in the existing breeding model with the host genetics, weight and environmental factors could provide a promising pathway for enabling selection for low emissions and advancing reduced emissions livestock farming under real-world production conditions. Lay summaryCattle produce methane as part of their normal digestion and this contributes to climate change. Reducing methane emission in grazing livestock systems is therefore important. However, measuring methane from individual grazing animals is difficult, costly, and often impractical under commercial conditions. The rumen microbiome has been used as a proxy for estimating methane emissions, but collecting rumen samples is invasive and impractical for large-scale use. Because rumination transfers material from the rumen to the mouth, we investigated whether microbes found in cattle mouths could also be used to estimate how much methane an individual animal produced. We suggest that mouth-swab sampling method can be an alternative to rumen fluid sampling because it was less invasive, relatively quick and practically applicable in commercial conditions. Importantly, the microbiome explained a meaningful proportion of the between-animal variation for methane emission. This suggests that collection of mouth swabs is a potentially scalable alternative proxy method to identify cattle that naturally produce less methane. Overall, our findings support the potential use of oral ruminant microbial information to improve breeding and management strategies aimed at reducing methane emissions while maintaining productive livestock systems. Teaser TextThis study demonstrates that collecting oral swabs from the mouths of grazing beef cattle could provide a scalable method to estimate individual methane emissions in commercial production systems, offering a practical alternative to invasive rumen sampling and complex gas measurement systems. These findings support the development of scalable breeding and management strategies for methane mitigation in large-scale livestock production systems.

microbiology↗

bioRxiv2020

Genome-wide co-expression distributions as a metric to prioritize genes of functional importance

Genome-wide gene expression is routinely used as a tool to gain a systems-level understanding of complex, biological processes. Numerical approaches that have been used to highlight influential genes include abundance, differential expression, differential variation, network connectivity and differential connectivity. Network connectivity tends to be built on a small subset of extremely high co-expression signals that are deemed significant, but this overlooks the vast majority of pairwise signals. Here, we aimed to assess a complementary strategy, namely whether the entire shape of the distribution of genome-wide co-expression values contains a meaningful biological signal that has hitherto remained hidden from view. We have developed a computational pipeline to assign one of 8 distributions (including normal, skewed, bimodal, kurtotic, inverted) to every gene. We then used a hypergeometric enrichment process to determine if particular genes (regulators versus non-regulators) and properties (differentially expressed or not) tend to be associated with particular distributions greater than would be expected by chance. Examination of several distinct data sets spanning 4 species indicates that there is indeed an additional biological signal present in the genome-wide distribution of co-expression values which would be overlooked by currently adopted approaches. Author summaryHigh-throughput technologies, such as RNA-Seq, enables access to a vast amount of data. Here, we describe a new approach to interrogate these data and extract further information to help researchers to understand complex phenotypes. Our method is based on gene-level co-expression distributions which were compared to eight possible template shapes to group genes with similar behaviours. The method was tested using five different datasets and the consistency of the results indicate it can be used as a complementary strategy to analyse transcriptomic data.

bioinformatics↗

bioRxiv2019

Genetic regulators of mineral amount in Nelore cattle muscle predicted by a new co-expression and regulatory impact factor approach

Mineral amount in bovine muscle affect meat quality, growth, health and reproductive traits in beef cattle. To better understand the genetic basis of this phenotype, we implemented new applications of use for two complementary algorithms: the partial correlation and information theory (PCIT) and the regulatory impact factor (RIF), by including GEBVs as part of the input. We used PCIT to determine putative regulatory relationships based on significant associations between gene expression and mineral amount. Then, RIF was used to determine the regulatory impact of genes and miRNA expression over mineral amount. We also investigated over-represented pathways, as well as evidences from previous studies carried in the same population, to determine regulatory genes for mineral amount e.g. NOX1, whose expression was positively correlated to Zn and was described as regulated by this mineral in humans. With this methodology, we were able to identify genes, miRNAs and pathways not yet described as important for mineral amount. The results support the hypothesis that extracellular matrix interactions are the core regulator of mineral amount in muscle cells. Putative regulators described here add information to this hypothesis, expanding the molecular relationships between gene expression and minerals.

genomics↗

bioRxiv2018

Proteomics reveals profound metabolic changes in the alcohol use disorder brain

Changes in brain metabolism are a hallmark of Alcohol Use Disorder (AUD). Determining how AUD changes the brain proteome is critical for understanding the effects of alcohol consumption on biochemical processes in the brain. We used data-independent acquisition mass spectrometry proteomics to study differences in the abundance of proteins associated with AUD in pre-frontal lobe and motor cortex from autopsy brain. AUD had a substantial effect on the overall brain proteome exceeding the inherent differences between brain regions. Proteins associated with glycolysis, trafficking, the cytoskeleton, and excitotoxicity were altered in abundance in AUD. We observed extensive changes in the abundance of key metabolic enzymes, consistent with a switch from glucose to acetate utilization in the AUD brain. We propose that metabolic adaptations allowing efficient acetate utilization contribute to ethanol dependence in AUD.

biochemistry↗