Biology subjects

Tierney, B. T.

Publications and source records attributed to Tierney, B. T..

11 recordsLinked to original sources

bioRxiv2026

Diverse high-fat diets drive multi-omic reprogramming that persists after dietary reversal

Dietary fat composition modulates host physiology and the gut microbiome, but the long-term effects of specific fat sources and the extent to which these changes resolve after dietary reversal remain incompletely defined. Here, we present a longitudinal multi-omic resource of mice maintained for one year on a purified control diet, seven high-fat diets differing in predominant fat source, or reversal regimens in which animals were switched from high-fat to control diet after 4 or 9 months. We further incorporated two cohorts with distinct pre-existing microbiome configurations to determine how baseline community structure shapes diet-induced remodeling of the gut microbiome ecosystem. By integrating longitudinal phenotyping, fecal metagenomics, fecal metabolomics, plasma metabolomics and lipidomics, and intestinal single-cell RNA sequencing, we defined the shared and dietary fat-specific responses across host and microbiome compartments. Baseline microbiome composition strongly influenced microbial responses to diet, indicating that pre-existing community structure is a major determinant of dietary ecosystem remodeling. Although many altered features shifted toward baseline after dietary reversal, only approximately half of diet-associated microbial changes recovered within the study window. A subset of taxa exhibited persistent alterations, including sustained depletion of Lactobacillus johnsonii and Bifidobacterium pseudolongum and sustained enrichment of Alistipes finegoldii, consistent with a "microbiome memory" of prior high-fat diet exposure. This memory effect is mirrored in the host, by sustained suppression of major histocompatibility complex class II (MHC-II) gene expression in intestinal epithelial cells after dietary reversal. These findings indicate that dietary fats leave a lasting imprint on the host-microbiome interactome that survives dietary intervention. Together, these data establish a resource for defining how dietary fat source, baseline microbiome composition, and dietary history shape host-microbiome states. The entire resource is available online as an RShiny app.

systems biology↗

bioRxiv2026

The Oral Microbiome Is a Population-Scale Readout of the Exposome, Age, and Systemic Health

The oral microbiome interfaces humans and the environment and is implicated in diseases from caries to cardiovascular conditions. Yet, few studies systematically interrogate oral taxa associations with the host phenome and exposome in diverse populations. We developed a comprehensive oral microbiome atlas, deploying a Microbiome Association Study (MAS) evaluating relationships between host features including exposome, disease, and physiology and the microbiome in a 10,000-person representative US population. Evaluating demographics, 133 phenotypes, 473 exposures, and 20 disease outcomes across 1,349 taxa yielded >800k relationships and 45,757 FDR-significant associations. Age emerged as a major organizing axis, with genera following non-linear life-course patterns. Oral disease, smoking, and dietary sugar correlated with aciduric and anaerobic taxa, whereas oral health featured oxygen-tolerant Proteobacteria. The exposome and cardiovascular/respiratory disease linked to diverse taxa. These results establish the oral microbiome as a sensitive, population-scale indicator of the exposome, phenome, and systemic health.

microbiology↗

bioRxiv2026

Use of Metagenomic Reference Materials to Compare Lysis and Extraction Methods Against a Known Input

Inconsistent cellular lysis is a major source of inaccuracy in microbial analysis; there is a need to develop objective and standardized evaluation of lysis efficiency across diverse methods. Using a mock microbial community as a ground truth, we built a bioinformatic and experimental toolkit for this purpose, comparing the performance of chemical, thermal, enzymatic, and various physical lysis protocols. We evaluated over 150 lysis conditions and observed the highest performance from mechanically- and materially-optimized bead-based approaches. To extend these findings to a practical setting, we demonstrated that the Firmicutes to Bacteroides ratio, a frequently used compositional metric in gut microbiome analysis is biased heavily by insufficient lysis, indicating the importance of benchmarking ongoing methodological development.

microbiology↗

bioRxiv2025

The Two Frontiers Project Field Handbook and OpenTools: Standardizing microbial fieldwork for biobank-scale sequencing and culturomics

From medicines to materials, our planets microbial diversity comprises an enormous wellspring of biotechnological potential. For centuries, microbiologists have developed tools for interrogating microbial function, ranging from microscopy and culturing to, more recently, metagenomics. However, deploying these tools during fieldwork requires substantial forward planning, interdisciplinary technical expertise, and plans for navigating permitting and the ethical implications of bioprospecting. To address these challenges, we built The Two Frontiers Project Handbook and OpenTools Resource, which aggregates our expertise in high-throughput sampling, sequencing, and culturing of microbes from thousands of samples. We provide our full suite of fieldwork methods as well as relevant software and hardware. We lay our standards for team roles and construction, general expedition planning, sample transport, permitting, and numerous other key aspects of executing a successful field campaign. The version-controlled resource is available at https://two-frontiers-project.github.io/ and is open for non-commercial use.

microbiology↗

bioRxiv2025

XTree enables memory-efficient, accurate short and long sequence alignment to millions of genomes across the tree of life

XTree is a k-mer-based aligner enabling rapid, memory-efficient alignment of sequencing reads to whole-genome reference databases with up to millions of genomes. Here, we detail XTrees performance on short and long read sequencing data and demonstrate its high accuracy across diverse bacterial, viral, and eukaryotic genomes. Benchmarking demonstrates superior and/or comparable precision and recall over existing tools, with more scalable indexing and efficient memory mapping. We additionally provide pre-indexed databases, including (1) the Genome Taxonomy Database (versions r214-r226), (2) representative GenBank fungi and protozoan genomes and (3) the Pan-Viral-Compendium, a bespoke data resource spanning 6.6 million, quality-controlled, viral genomes.

bioinformatics↗

bioRxiv2025

Modular metagenomic analysis of pan-domain symbioses with MAGUS

Metagenomic analysis of deeply sequenced, eukaryotic-dominant symbiotic communities can be difficult for many metagenomic workflows. Here, we present MAGUS, a bioinformatic toolkit that uses a suite of custom bioinformatic methods for iterative genome assembly and filtering of pan-domain communities, where eukaryotes, bacteria, viruses, and functionally annotated gene catalogs are resolved and analyzed over a series of interconnected, modular software components. We evaluated MAGUS using deeply sequenced (median depth: 579 million reads) ten samples of hard corals, soft corals, and hydrozoans, which comprise complex, eukaryote-dominated symbiotic communities. We successfully resolved phylogenetically comparable host (N = 10), algal (N = 6), bacterial (N = 55), and viral (N = 160,925) genomes, as well as a gene catalog comprising 15,369,684 non-redundant genes (7.6% functionally annotated). MAGUS is available on GitHub (https://github.com/two-frontiers-project/2FP_MAGUS/).

bioinformatics↗

bioRxiv2024

Spaceflight alters host-gut microbiota interactions

The rodent habitat on the International Space Station has provided crucial insights into the impact of spaceflight on mammals, including observation of symptoms characteristic of liver disease, insulin resistance, osteopenia and myopathy. Although these physiological responses can involve the microbiome when observed on Earth, changes in host-microbiota interactions during spaceflight are still being elucidated. Here, NASA GeneLab multiomic data from the Rodent Research 6 mission are used to determine changes to gut microbiota and murine host colon and liver gene expression after 29 and 56-days of spaceflight. Using hybrid amplicon and whole metagenome sequencing analysis, significant spaceflight-associated alterations to 42 microbiome species were identified. These included relative reductions of bacteria associated with bile acid and butyrate metabolism, such as Extibacter muris and Dysosmobacter welbionis. Functional prediction suggested over-representation of fatty acid and bile acid metabolism, extracellular matrix interactions, and antibiotic resistance genes within the gut microbiome, while host intestinal and hepatic gene expression described corresponding changes to host bile acid and energy metabolism, and immune suppression from spaceflight. Taken together, these changes imply that interactions at the host-gut microbiome interface contribute to spaceflight pathology and highlight how these interactions might critically influence human health and the feasibility of long-duration spaceflight.

genomics↗

bioRxiv2023

Cyanobacteria newly isolated from marine volcanic seeps display rapid sinking and robust, high density growth

Cyanobacteria are photosynthetic organisms that play important roles in carbon cycling as well as promising bioproduction chassis. Here, we isolate two novel cyanobacteria, UTEX 3221 and UTEX 3222, from a unique marine environment with naturally elevated CO2. We describe complete genome sequences for both isolates and, focusing on UTEX 3222 due to its planktonic growth in liquid, characterize biotechnologically-relevant growth and biomass characteristics. UTEX 3222 outpaces other fast-growing model strains on solid medium. It can double every 2.35 hours in a liquid medium and grows to high density (>31g/L biomass dry weight) in batch culture, nearly double that of Synechococcus sp. PCC 11901, whose high-density growth was recently reported. In addition, UTEX 3222 sinks readily, settling more quickly than other fast-growing strains, suggesting improved de-watering of UTEX 3222 biomass. This settling behavior can be explained in part by larger cell volume. These traits may make UTEX 3222 a compelling choice for photosynthetic bioproduction from CO2. Overall, we find that bio-prospecting in environments with naturally elevated CO2 may uncover novel CO2-metabolizing organisms with unique characteristics.

microbiology↗

bioRxiv2022

Supervised Machine Learning Enables Geospatial Microbial Provenance

The recent increase in publicly available metagenomic datasets with geospatial metadata has made it possible to determine location-specific, microbial fingerprints from around the world. Such fingerprints can be useful for comparing microbial niches for environmental research, as well as for applications within forensic science and public health. To determine the regional specificity for environmental metagenomes, we examined 4305 shotgun-sequenced samples from the MetaSUB Consortium dataset - the most extensive public collection of urban microbiomes, spanning 60 different cities, 30 countries, and 6 continents. We were able to identify city-specific microbial fingerprints using supervised machine learning (SML) on the taxonomic classifications, and we also compared the performance of ten SML classifiers. We then further evaluated the five algorithms with the highest accuracy, with the city and continental accuracy ranging from 85-89% to 90-94%, respectively. We then used these results to develop Cassandra, a random-forest-based classifier that identifies indicator species to aid in fingerprinting and can infer higher-order microbial interactions at each site. We further tested the Cassandra algorithm on the Tara Oceans dataset, the largest collection of marine-based microbial genomes, where it classified the oceanic sample locations with 83% accuracy. These results and code show the utility of SML methods and Cassandra to identify bioindicator species across both oceanic and urban environments, which can help guide ongoing efforts in biotracing, environmental monitoring, and microbial forensics (MF).

microbiology↗

bioRxiv2020

The predictive power of the microbiome exceeds that of genome-wide association studies in the discrimination of complex human disease

Over the past decade, studies of the human genome and microbiome have deepened our understanding of the connections between human genes, environments, microbes, and disease. For example, the sheer number of indicators of the microbiome and human genetic common variants associated with disease has been immense, but clinical utility has been elusive. Here, we compared the predictive capabilities of the human microbiome versus human genomic common variants across 13 common diseases. We concluded that microbiomic indicators outperform human genetics in predicting host phenotype (overall Microbiome-Association-Study [MAS] area under the curve [AUC] = 0.79 [SE = 0.03], overall Genome-Wide-Association-Study [GWAS] AUC = 0.67 [SE = 0.02]). Our results, while preliminary and focused on a subset of the totality of disease, demonstrate the relative predictive ability of the microbiome, indicating that it may outperform human genetics in discriminating human disease cases and controls. They additionally motivate the need for population-level microbiome sequencing resources, akin to the UK Biobank, to further improve and reproduce metagenomic models of disease.

bioinformatics↗

bioRxiv2017

Aether: Leveraging Linear Programming For Optimal Cloud Computing In Genomics

Across biology we are seeing rapid developments in scale of data production without a corresponding increase in data analysis capabilities. Here, we present Aether (http://aether.kosticlab.org), an intuitive, easy-to-use, cost-effective, and scalable framework that uses linear programming (LP) to optimally bid on and deploy combinations of underutilized cloud computing resources. Our approach simultaneously minimizes the cost of data analysis while maximizing its efficiency and speed. As a test, we used Aether to de novo assemble 1572 metagenomic samples, a task it completed in merely 13 hours with cost savings of approximately 80% relative to comparable methods.

bioinformatics↗