Biology subjects

Weimer, B. C.

Publications and source records attributed to Weimer, B. C..

9 recordsLinked to original sources

bioRxiv2026

Metatranscriptomic Profiling Reveals Species-Level Microbial Shifts and Metabolic Remodeling in Feline Oral Inflammatory Disease

Progressive oral mucosal inflammatory diseases are common among mammals. Cats are a valuable natural model for these conditions because they frequently develop oral diseases with varying severity, yet causative microbes remain unidentified in part because longitudinal studies are challenging and sampling is difficult. The lack of individual pathobionts suggests community-scale taxonomic and functional remodeling of the microbiome may be a contributor to oral disease. This study evaluated the microbiome composition and function of 33 cats across three cohorts with different levels of inflammation: healthy, aggressive periodontitis, and feline gingivostomatitis. Ultradeep metatranscriptomic sequencing was used to assign microbial taxonomy and examine functional changes via differential gene expression analysis to reveal genera that maintained stable relative abundance across all three disease states, including Porphyromonas and Treponema, while others had more subtle shifts in species activity, including multiple members of Moraxella and Mycoplasmopsis. Disease status was marked by co-occurring changes in low activity species accompanied by microbiome-level changes in protein, arginine, and nitrogen metabolism. Cats with aggressive periodontitis and gingivostomatitis displayed microbiome shifts in species that correlated to disease state. Microbial differential expression analysis revealed induction of stress-related genes and metabolic genes involved in amino acid metabolism, polyamine production, and nitric oxide production. Together, species identification and functional profiling suggest oral inflammation was correlated to shifts in the activity of multiple species that were involved with NO and polyamines. These coordinated metabolic signatures represent potential diagnostic targets for feline oral inflammatory disease.

microbiology↗

bioRxiv2025

Cellular Respiration and Amino Acid Metabolism Is Altered by Dietary Oligosaccharides in Salmonella During Epithelial Association

Dietary prebiotic oligosaccharides are common in peoples diets; however, little is known about how different prebiotics alter the enteric epithelium and microbiome. Here we show two structurally different prebiotic oligosaccharides, human milk oligosaccharides (HMO) and mannanoligosaccharides (MOS), alter the metabolism of colonic epithelial cells and Salmonella enterica sv. Typhimurium in ways specific to each prebiotic. Initially, HMO and MOS addition decreased S. Typhimurium association with epithelial cells. However, gene expression analysis revealed significantly induced expression of Specific Pathogenicity Island (SPI) 1 and 2 with HMO treatment opposed to increased fimbriae expression with MOS treatment. MOS treatment induced the expression of genes for amino acid metabolism in both the host cells and in S. Typhimurium, a metabolic shift that was not observed in the HMO treated cells. MOS treatment also altered respiration metabolism in S. Typhimurium to be more closely aligned to those observed in vivo during gut inflammation, which is opposed to colonization-type expression with HMO. Alteration of virulence observed was found to be prebiotic specific and dose dependent, indicating that some dietary substrates likely alter specific pathogens to change their virulence potential in unanticipated ways that lead to multiple outcomes to potentiate or attenuate enteric infections.

microbiology↗

bioRxiv2022

Characterization of rumen microbiome and metabolome from an oro-esophageal probe and fluid, particulate and fluid-particulate fractions from rumen fistula in Holstein dairy cow

Less invasive rumen sampling methods such as oro-esophageal probes became widely popular to explore the rumen microbiome and metabolome. However, it remains unclear if such methods represent well the rumen contents from fluid and particulate fractions. Herein, we characterized the microbiome and metabolome in rumen content collected by an oro-esophageal probe and fluid, particulate, and the combined fluid-particulate fractions collected by rumen fistula in ten multiparous Holstein dairy cows. The 16S rRNA gene was amplified and sequenced using the Illumina MiSeq platform. Untargeted metabolome was characterized using gas chromatography of a time-of-flight mass spectrometer. Although the pH of oro-esophageal samples was greater than those of fluid, fluid-particulate, and particulate ones, we found no difference in alpha and beta-diversity of their microbiomes. Bacteroidetes, Firmicutes, and Proteobacteria were consistently the top three most abundant phyla representing ~90% of all detected phyla across all samples. The overall metabolome PLS-DA of oro-esophageal samples was similar to the fluid-particulate samples but differed from fluid and particulate. Enrichment analysis pathways revealed few differences between oro-esophageal and fluid-particulate samples, such as the synthesis of unsaturated fatty acids. The results of the current study suggest that oro-esophageal sampling can be a proxy to screen the rumen microbiome with the 16S platform and overall fluid-particulate metabolome for a single-time and diet context. Nonetheless, studies focusing specifically on fluid and particulate metabolomes and specific metabolic pathways should carefully consider the sampling method used. IMPORTANCEThe techniques used to collect the rumen contents (oro-esophageal probe and rumen fistula) suggested potential differences in the populations of rumen microbes, and the implications of these techniques for high throughput studies characterizing the rumen microbiome and metabolome need further elucidation. Ten rumen-fistulated Holstein dairy cows were used to characterize the microbiome and metabolome of samples collected using an oro-esophageal probe and the rumen-fistula fluid, particulate, and fluid-particulate fractions. The results of the current study suggest that oro-esophageal sampling represents well the rumen microbiome and overall fluid-particulate metabolome. However, fluid and particulate metabolomes and specific metabolic pathways across all types of rumen samples differed, indicating that studies focused on the characterization of rumen metabolome variable fractions should carefully consider the sampling method used.

microbiology↗

bioRxiv2020

Drought duration determines the recovery dynamics of rice root microbiomes

As extreme droughts become more frequent, dissecting the responses of root-associated microbiomes to drying-wetting events is essential to understand their influence on plant performance. Here, we show that rhizosphere and endosphere communities associated with drought-stressed rice plants display compartment-specific recovery trends. Rhizosphere microorganisms were mostly affected during the stress period, whereas endosphere microorganisms remained altered even after irrigation was resumed. The duration of drought stress determined the stability of these changes, with more prolonged droughts leading to decreased microbiome resilience. Drought stress was also linked to a permanent delay in the temporal development of root microbiomes, mainly driven by a disruption of late colonization dynamics. Furthermore, a root-growth-promoting Streptomyces became the most abundant community member in the endosphere during drought and early recovery. Collectively, these results reveal that severe drought results in enduring impacts on root-associated microbiomes that could potentially reshape the recovery response of rice plants.

microbiology↗

bioRxiv2020

Monitoring the microbiome for food safety and quality using deep shotgun sequencing

In this work, we hypothesized that shifts in the food microbiome can be used as an indicator of unexpected contaminants or environmental changes. To test this hypothesis, we sequenced total RNA of 31 high protein powder (HPP) samples of poultry meal pet food ingredients. We developed a microbiome analysis pipeline employing a key eukaryotic matrix filtering step that improved microbe detection specificity to >99.96% during in silico validation. The pipeline identified 119 microbial genera per HPP sample on average with 65 genera present in all samples. The most abundant of these were Bacteroides, Clostridium, Lactococcus, Aeromonas, and Citrobacter. We also observed shifts in the microbial community corresponding to ingredient composition differences. When comparing culture-based results for Salmonella with total RNA sequencing, we found that Salmonella growth did not correlate with multiple sequence analyses. We conclude that microbiome sequencing is useful to characterize complex food microbial communities, while additional work is required for predicting specific species viability from total RNA sequencing.

microbiology↗

bioRxiv2020

Diazotrophic bacteria from maize exhibit multifaceted plant growth promotion traits in multiple hosts

Sierra Mixe maize is a geographically remote landrace variety grown on nitrogen-deficient fields in Oaxaca, Mexico that meets its nutritional requirements without synthetic fertilizer by associating with free-living diazotrophs comprising the microbiota of its aerial root mucilage. We selected nearly 500 diazotrophic bacteria isolated from Sierra Mixe maize mucilage and sequenced their genomes. Comparative genomic analysis demonstrated that isolates represented diverse genera and possessed multiple marker genes for mechanisms of direct plant growth promotion (PGP). In addition to nitrogen fixation, we examined deamination of 1-amino-1-cyclopropanecarboxylic acid, biosynthesis of indole-3-acetic acid, and phosphate solubilization. Implementing in vitro colorimetric assays revealed each isolates potential to confer the alternative PGP activities that corroborated genotype and pathway content. We examined the ability of mucilage diazotrophs to confer PGP by direct inoculation of clonally propagated potato plants in planta, which led to the identification of bio-stimulant candidates that were tested for PGP by inoculating a conventional maize variety. The results indicate that, while many diazotrophic isolates from Sierra Mixe maize possessed genotypes and in vitro phenotypes for targeted PGP traits, a subset of these organisms promoted the growth of potato and conventional maize using multiple promotion mechanisms.

microbiology↗

bioRxiv2020

Genomic characterization of a diazotrophic microbiota associated with maize aerial root mucilage

A geographically isolated maize landrace cultivated on nitrogen-depleted fields without synthetic fertilizer in the Sierra Mixe region of Oaxaca, Mexico utilizes nitrogen derived from the atmosphere and develops an extensive network of mucilage-secreting aerial roots that harbors a diazotrophic microbiota. Targeting these diazotrophs, we selected nearly 600 microbes from a collection isolated from these plants and confirmed their ability to incorporate heavy nitrogen (15N2) metabolites in vitro. Sequencing their genomes and conducting comparative bioinformatic analyses showed that these genomes had substantial phylogenetic diversity. We examined each diazotroph genome for the presence of nif genes essential to nitrogen fixation (nifHDKENB) and carbohydrate utilization genes relevant to the mucilage polysaccharide digestion. These analyses identified diazotrophs that possessed canonical nif gene operons, as well as many other operon configurations with concomitant fixation and release of >700 different 15N labeled metabolites. We further demonstrated that many diazotrophs possessed alternative nif gene operons and confirmed their genomic potential to derive chemical energy from mucilage polysaccharide to fuel nitrogen fixation. These results confirm that some diazotrophic bacteria associated with Sierra Mixe maize were capable of incorporating atmospheric nitrogen into their small molecule extracellular metabolites through multiple nif gene configurations while others were able to fix nitrogen without the canonical (nifHDKENB) genes. Data SummaryGenetic resources, including biological materials and nucleic acid sequences, were accessed under an Access and Benefit Sharing (ABS) Agreement between the Sierra Mixe community and the Mars Corporation, and with authorization from the Mexican government. An internationally recognized certificate of compliance has been issued by the Mexican government under the Nagoya Protocol for such activities (ABSCH-IRCC-MX-207343-3). Any party seeking access to the nucleic acid sequences underlying the analysis reported here is subject to the full terms and obligations of the ABS agreement and the authorization from the government of Mexico. Individuals wishing to access nucleic acid sequence data for scientific research activities should contact Mars Incorporated Chief Science Officer at CSO@effem.com.

genomics↗

bioRxiv2019

Salmonella Enhances Osteogenic Differentiation in Adipose-Derived Mesenchymal Stem Cells

The potential of mesenchymal stem cells (MSCs) for tissue repair and regeneration has garnered great attention. While MSC interaction with microbes at sites of tissue damage and inflammation is likely, especially in the gut, the consequences of bacterial association have yet to be elucidated. This study investigated the effect of Salmonella enterica ssp enterica serotype Typhimurium on MSC trilineage differentiation path and mechanism. Through examination of key markers of differentiation, immunomodulatory regulators, and inflammatory cytokines, we demonstrated that Salmonella altered osteogenic and chondrogenic differentiation pathways in human and goat adipose-derived MSCs. Gene expression profiles defined signaling pathway alterations in response to Salmonella association not observed in epithelial cells. We uncovered significant differential expression (P < 0.05) of genes associated with anti-apoptotic and pro-proliferative responses in MSCs during Salmonella challenge. These observations led us to conclude that bacteria, specifically Salmonella, induce pathways that influence functional differentiation trajectories in MSCs, thus implicating substantial microbial influence on MSC physiology and immune activity.

microbiology↗

bioRxiv2019

Biological machine learning combined with bacterial population genomics reveals common and rare allelic variants of genes to cause disease

Highly dimensional data generated from bacterial whole genome sequencing is providing unprecedented scale of information that requires appropriate statistical frameworks of analysis to infer biological function from bacterial genomic populations. Application of genome wide association study (GWAS) methods is an emerging approach with bacterial population genomics that yields a list of genes associated with a phenotype with an undefined importance among the candidates in the list. Here, we validate the combination of GWAS, machine learning, and pathogenic bacterial population genomics as a novel scheme to identify SNPs and rank allelic variants to determine associations for accurate estimation of disease phenotype. This approach parsed a dataset of 1.2 million SNPs that resulted in a ranked importance of associated alleles of Campylobacter jejuni porA using multiple spatial locations over a 30-year period. We validated this approach using previously proven laboratory experimental alleles from an in vivo guinea pig abortion model. This approach, termed BioML, defined intestinal and extraintestinal groups that have differential allelic variants that cause abortion. Divergent variants containing indels that defeated gene callers were rescued using biological context and knowledge that resulted in defining rare and divergent variants that were maintained in the population over two continents and 30 years. This study defines the capability of machine learning coupled to GWAS and population genomics to simultaneously identify and rank alleles to define their role in abortion, and more broadly infectious disease.

genomics↗