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Aho, V. T. E.

Publications and source records attributed to Aho, V. T. E..

7 recordsLinked to original sources

Rumen transfaunation between low- and high-methane-yielding dairy cows reveals asymmetric microbiome reconstitution patterns: a pilot study

BackgroundThis study investigated rumen microbiome reconstitution and methane (CH4) emissions following a complete exchange of rumen contents between low- and high-CH4-yielding Norwegian Red dairy cows. Twenty cows were screened for CH4 yield, and two low and two high emitters were selected for rumen cannulation and content swap. Total rumen contents were swapped after complete evacuation and washing of both the rumen and omasum. Rumen samples were collected twice in weeks -1, 1, 3, and 7 for fermentation analysis, metagenomics, and metaproteomics, and at week 8 CH4 production was measured. ResultsPrior to the swap, low and high emitters produced 21.2 {+/-} 0.7 and 26.3 {+/-} 1.4 g CH4/kg dry-matter intake (DMI), respectively. Eight weeks after swap, CH4 yields were 12.7 {+/-} 0.3 and 28.9 {+/-} 0.3 g CH4/kg DMI, respectively, showing that the CH4 phenotype of each cow was maintained. Analysis of metagenome-derived 16S rRNA gene sequences showed that low emitters gradually re-established their original microbial community, whereas high emitters retained donor-like microbiota. Metaproteomic mapping suggested higher expression of Prevotella-associated succinate-propionate pathway enzymes in low emitters at week 7, though these differences were modest. ConclusionThese findings suggest that host factors influence CH4 output and microbial reconstitution, with low emitters restoring their native microbiome while high emitters retained a donor-associated community yet continued to emit high CH4. Results should be interpreted with caution given the small sample size (n = 2 per phenotype) and require confirmation in larger studies. ImportanceReducing enteric methane from cattle requires understanding whether the rumen microbiome or the host animal is the primary driver of methane output. We exchanged the entire rumen contents between low- and high-methane-yielding dairy cows and measured methane production alongside metagenomic and metaproteomic profiling over two months. Despite receiving each others microbiomes, each cows methane phenotype persisted--low emitters stayed low and high emitters stayed high. Microbiome reconstitution was asymmetric: low emitters restored their original microbial community, while high emitters retained the donor microbiota. Methanogen communities did not differ between phenotypes, pointing to host-level rather than microbial-level control of methane yield. These pilot findings suggest that breeding for favorable host traits may be essential for lasting methane reduction, and that microbiome transfer alone is unlikely to shift an animals methane phenotype. Larger studies are needed to confirm these observations.

microbiology↗

Intricate microbiome differences observed in lactating cows across methane intensity phenotypes

Methane emissions from ruminants can be expressed through several metrics as total production, yield, or intensity, each reflecting distinct aspects of energy utilization. Among these, methane intensity defined as grams of methane emitted per kilograms of energy-corrected milk, directly links emissions to productive efficiency; however, the microbial mechanisms underlying variation in this trait remain unclear. Here, we applied genome-resolved metagenomics and metatranscriptomics to characterize rumen microbial identity, functional potential, and transcriptional activity in lactating cows differing in methane intensity while sharing breed and diet. Microbial community composition and diversity were comparable across phenotypes. However, rumen microbial gene expression revealed marked functional divergence. The rumen content of low-methane intensity cows showed enriched transcription of fructan-degrading carbohydrate-active enzymes and butyrate-forming pathways, primarily encoded by RUG440 (Atopobiaceae) and Sodaliphilus-affiliated metagenome-assembled genomes. These functions suggest a fructan-butyrate metabolic axis supported by potential cross-feeding between primary degraders and butyrate producers. Conversely, the high-methane intensity rumen exhibited greater transcription of pectin-degrading carbohydrate-active enzymes, mainly carried by Prevotella metagenome-assembled genomes, suggesting methyl-ester hydrolysis and methanol release. Despite higher methanogenesis transcript levels in high-methane intensity cows, total methane production did not differ between groups. Together, these findings reveal two contrasting functional configurations of the rumen microbiome in Norwegian Red dairy cattle: a fructan-butyrate-oriented metabolism in low-methane intensity cows and a pectin-methanol-oriented metabolism in high-methane intensity counterparts. This study provides genome-resolved, multi-omic evidence that microbial carbohydrate specialization and fermentation routing contribute to methane intensity phenotypes in dairy cows, offering mechanistic insights for improving ruminant climate efficiency.

microbiology↗

OmniCorr: An R-package for visualizing putative host-microbiota interactions using multi-omics data

Holo-omics leverages omics datasets to explore the interactions between hosts and their associated microbiomes. Although the generation of omics data from matching host and microbiome samples is steadily increasing, there remains a scarcity of computational tools capable of integrating and visualizing this data to facilitate the interpretation and prediction of host-microbiota interactions. We present OmniCorr, an R package designed to: (1) manage the complexity of omics data by clustering similar observations into modules, (2) visualize correlations of these modules across different omics layers, host-microbiota interfaces, and meta-data, and (3) identify statistically significant associations indicative of putative host-microbiota interactions. OmniCorrs utility is demonstrated using datasets from two systems: (i) Atlantic salmon, integrating host transcriptomics with metagenomics and metatranscriptomics to explore dietary impacts, and (ii) cattle, combining host proteomics with metaproteomics and metabolomics to investigate methane emission variability. Availability and ImplementationOmniCorr is freely available at: https://github.com/shashank-KU/OmniCorr.

bioinformatics↗

Integrated multi-omics highlights alterations of gut microbiome functions in prodromal and idiopathic Parkinson's disease

Parkinsons disease (PD) is associated with gut microbiome shifts, but the functional consequences remain unclear. Here, we use an integrated multi-omics approach to compare the gut microbiomes of individuals with PD and prodromal PD as well as healthy individuals. After analyzing each omics, meta-metabolomic was selected to inform the analysis as it represents the most discriminatory and robust ome. We identified 11 metabolites that were differentially abundant between the groups, amongst which {beta}-glutamate was increased in PD and prodromal PD, and correlated with the transcriptional activities of Methanobrevibacter smithii and Clostridium spp. We identified decreases in transcripts, but not in gene abundances, related to glutamate metabolism, bile acids, chemotaxis and flagellar assembly in PD, particularly in keystone genera such as Roseburia, Agathobacter and Blautia. Our findings, integrated into the Expobiome map, reveal multifactorial microbiome alterations which converge with PD pathways. Our study highlights the importance of investigating the gut microbiomes functional dimensions to better resolve microbiome-host interactions in health and disease.

systems biology↗

Protozoal populations drive system-wide variation in the rumen microbiome

While rapid progress has been made to characterize the bacterial and archaeal populations of the rumen microbiome, insight into how they interact with keystone protozoal species remains elusive. Here, we reveal two distinct rumen community types (RCT-A and RCT-B) that are not strongly associated with host phenotype nor genotype but instead linked to protozoal community patterns. We leveraged a series of multi-omic datasets to show that the dominant Epidinium spp. in animals with RCT-B employ a plethora of fiber-degrading enzymes that present enriched Prevotella spp. a favorable carbon landscape to forage upon. Conversely, animals with RCT-A, dominated by genera Isotricha and Entodinium, harbor a more even distribution of fiber, protein, and amino acid metabolizers, reflected by higher detection of metabolites from both protozoal and bacterial activity. We reveal microbiome variation across key protozoal and bacterial populations is interlinked, which should act as an important consideration for future development of microbiome-based technologies.

microbiology↗

CompareM2 is a genomes-to-report pipeline for comparing microbial genomes

Here, we present CompareM2, a genomes-to-report pipeline for comparative analysis of bacterial and archaeal genomes derived from isolates and metagenomic assemblies. CompareM2 is easy to install and operate, and integrates community-adopted tools to perform genome quality control and annotation, taxonomic and functional predictions, as well as comparative analyses of core- and pan-genome partitions and phylogenetic relations. The central results generated via the CompareM2 workflow are emphasized in a portable dynamic report document. CompareM2 is free software and welcomes modifications and pull requests from the community on its Git repository at https://github.com/cmkobel/comparem2.

bioinformatics↗

Gut microbiome signatures of risk and prodromal markers of Parkinson's disease

ObjectivesAlterations of the gut microbiome in Parkinsons disease (PD) have been repeatedly demonstrated. However, little is known about whether such alterations precede disease onset and how they may be related to risk and prodromal markers of PD. We investigated associations of these features with gut microbiome composition. MethodsEstablished risk and prodromal markers of PD as well as factors related to diet/lifestyle, bowel function and medication were studied in relation to bacterial -/{beta}-diversity, enterotypes, and taxonomic composition in stool samples of 666 elderly TREND study participants. ResultsAmong risk and prodromal markers, physical inactivity, constipation and age showed associations with - and {beta}-diversity, and for both measures subthreshold parkinsonism and physical inactivity showed interaction effects. Moreover, male sex, possible REM-sleep behavior disorder (RBD), smoking as well as body-mass-index, antidiabetic and urate-lowering medication were associated with {beta}-diversity. Physical inactivity and constipation severity were increased in individuals with the Firmicutes-enriched enterotype. Subthreshold parkinsonism was least frequently observed in individuals with the Prevotella-enriched enterotype. Differentially abundant taxa were linked to constipation, physical inactivity, possible RBD, and subthreshold parkinsonism. Substantia nigra hyperechogenicity, olfactory loss, depression, orthostatic hypotension, urinary/erectile dysfunction, PD family history and the overall prodromal PD probability showed no significant microbiome associations. InterpretationSeveral risk and prodromal markers of PD are associated with changes in gut microbiome composition. However, the impact of the gut microbiome on PD risk and potential microbiome-dependent subtypes in the prodrome of PD need further investigation based on prospective clinical and (multi)omics data in incident PD cases.

neuroscience↗