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At least 595 records · Page 33

Exceptional subgenome stability and functional divergence in the allotetraploid Ethiopian cereal teff

Teff (Eragrostis tef) is a cornerstone of food security in the Horn of Africa, where it is prized for stress resilience, grain nutrition, and market value. Here, we report a chromosome-scale assembly of allotetraploid teff (variety Dabbi) and patterns of subgenome dynamics. The teff genome contains two complete sets of homoeologous chromosomes, with most genes maintaining as syntenic gene pairs. TE analysis allows us to estimate that the teff polyploidy event occurred ~1.1 million years ago (mya) and that the two subgenomes diverged ~5.0 mya. Despite this divergence, we detect no large-scale structural rearrangements, homoeologous exchanges, or biased gene loss, in contrast to many other allopolyploids. The two teff subgenomes have partitioned their ancestral functions based on divergent expression across a diverse expression atlas. Together, these genomic resources will be useful for accelerating breeding of this underutilized grain crop and for fundamental insights into polyploid genome evolution.

54 ENVIRONMENTAL SCIENCES↗

Chemoproteogenomic stratification of the missense variant cysteinome

Abstract Cancer genomes are rife with genetic variants; one key outcome of this variation is widespread gain-of-cysteine mutations. These acquired cysteines can be both driver mutations and sites targeted by precision therapies. However, despite their ubiquity, nearly all acquired cysteines remain unidentified via chemoproteomics; identification is a critical step to enable functional analysis, including assessment of potential druggability and susceptibility to oxidation. Here, we pair cysteine chemoproteomics—a technique that enables proteome-wide pinpointing of functional, redox sensitive, and potentially druggable residues—with genomics to reveal the hidden landscape of cysteine genetic variation. Our chemoproteogenomics platform integrates chemoproteomic, whole exome, and RNA-seq data, with a customized two-stage false discovery rate (FDR) error controlled proteomic search, which is further enhanced with a user-friendly FragPipe interface. Chemoproteogenomics analysis reveals that cysteine acquisition is a ubiquitous feature of both healthy and cancer genomes that is further elevated in the context of decreased DNA repair. Reference cysteines proximal to missense variants are also found to be pervasive, supporting heretofore untapped opportunities for variant-specific chemical probe development campaigns. As chemoproteogenomics is further distinguished by sample-matched combinatorial variant databases and is compatible with redox proteomics and small molecule screening, we expect widespread utility in guiding proteoform-specific biology and therapeutic discovery.

Desai, Heta (ORCID:0000000343621707)↗

Single nucleotide variants drive evolutionary phage-host arms race in anaerobic carbon dioxide-converting microbiome

Microbial bioconversions are shaped by environmental perturbations and the adaptation of resident microbiomes. Prokaryotes coexist with bacteriophages, yet their coevolutionary trajectories remain underexplored. Here, we investigate the effects of a cultivation vessel leak on an anaerobic consortium performing carbon dioxide reduction. Using time-series shotgun metagenomic sequencing, we reconstruct microbial and viral genomes to track community shifts. We further apply single-nucleotide variant profiling and CRISPR array analysis to monitor viral microdiversity and host defense mechanisms. After bioaugmentation restores bioconversion efficiency, the consortium undergoes pronounced restructuring, with new dominant taxa emerging from the rare biosphere. We identify patterns consistent with phage predation selectively removing certain species, while others exhibit resilience to infection. This shift aligns with a widespread viral outbreak and a transient increased frequency of single nucleotide variants in bacterial CRISPR–Cas defense genes. Expansion of CRISPR spacers further supports that CRISPR-mediated processes influence microbial resilience. Concurrently, phages infecting resilient hosts exhibited adaptive evolution, marked by high genetic heterogeneity. Selective pressure varies across their genomes, targeting infectivity genes and protospacer-adjacent motifs. These findings highlight a dynamic evolutionary arms race driven by the selection of beneficial genetic variants, providing a mechanistic framework for multi-omics investigations, and informing biotechnological applications, including phage-based microbiome manipulation.

Ghiotto, G↗

Expanded Archaeal Genomes Shed New Light on the Evolution of Isoprenoid Biosynthesis

Isoprenoids and their derivatives, essential for all cellular life on Earth, are particularly crucial in archaeal membrane lipids, suggesting that their biosynthesis pathways have ancient origins and play pivotal roles in the evolution of early life. Despite all eukaryotes, archaea, and a few bacterial lineages being known to exclusively use the mevalonate (MVA) pathway to synthesize isoprenoids, the origin and evolutionary trajectory of the MVA pathway remain controversial. Here, we conducted a thorough comparison and phylogenetic analysis of key enzymes across the four types of MVA pathway, with the particular inclusion of metagenome assembled genomes (MAGs) from uncultivated archaea. Our findings support an archaeal origin of the MVA pathway, likely postdating the divergence of Bacteria and Archaea from the Last Universal Common Ancestor (LUCA), thus implying the LUCA’s enzymatic inability for isoprenoid biosynthesis. Notably, the Asgard archaea are implicated in playing central roles in the evolution of the MVA pathway, serving not only as putative ancestors of the eukaryote- and Thermoplasma-type routes, but also as crucial mediators in the gene transfer to eukaryotes, possibly during eukaryogenesis. Overall, this study advances our understanding of the origin and evolutionary history of the MVA pathway, providing unique insights into the lipid divide and the evolution of early life.

59 BASIC BIOLOGICAL SCIENCES↗

EDGE COVID-19: a web platform to generate submission-ready genomes from SARS-CoV-2 sequencing efforts

Abstract Summary Genomics has become an essential technology for surveilling emerging infectious disease outbreaks. A range of technologies and strategies for pathogen genome enrichment and sequencing are being used by laboratories worldwide, together with different and sometimes ad hoc, analytical procedures for generating genome sequences. A fully integrated analytical process for raw sequence to consensus genome determination, suited to outbreaks such as the ongoing COVID-19 pandemic, is critical to provide a solid genomic basis for epidemiological analyses and well-informed decision making. We have developed a web-based platform and integrated bioinformatic workflows that help to provide consistent high-quality analysis of SARS-CoV-2 sequencing data generated with either the Illumina or Oxford Nanopore Technologies (ONT). Using an intuitive web-based interface, this workflow automates data quality control, SARS-CoV-2 reference-based genome variant and consensus calling, lineage determination and provides the ability to submit the consensus sequence and necessary metadata to GenBank, GISAID and INSDC raw data repositories. We tested workflow usability using real world data and validated the accuracy of variant and lineage analysis using several test datasets, and further performed detailed comparisons with results from the COVID-19 Galaxy Project workflow. Our analyses indicate that EC-19 workflows generate high-quality SARS-CoV-2 genomes. Finally, we share a perspective on patterns and impact observed with Illumina versus ONT technologies on workflow congruence and differences. Availability and implementation https://edge-covid19.edgebioinformatics.org, and https://github.com/LANL-Bioinformatics/EDGE/tree/SARS-CoV2. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗

Knowledge-matching based computational framework for genome-scale metabolic model refinement

Genome-scale metabolic models (GEMs) are mathematically structured knowledge base reconstructed from annotated genome of different organisms. With the advancement of next-generation sequencing technology, many organisms have had their genomes sequenced. However, obtaining a high-quality GEM is highly time-consuming, even with the introduction of several genome-scale reconstruction tools that offer automated draft network generation and gap filling. It has been recognized that the iterative process of manual curation and refinement is the limiting step of GEM development, and how to expedite the GEM refinement is still an open question. As cellular metabolism is a complex system with very high degree of freedom and redundancy, the principles and techniques developed in process systems engineering can be adapted to expedite GEM refinement. In this paper we present a knowledge-matching based computation framework for GEM refinement, and demonstrate the effectiveness of the proposed solution using the refinement of a GEM for Clostridium tyrobutyricum.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Genetic determinants of endophytism in the Arabidopsis root mycobiome

The roots of Arabidopsis thaliana host diverse fungal communities that affect plant health and disease states. Here, we sequence the genomes of 41 fungal isolates representative of the A. thaliana root mycobiota for comparative analysis with other 79 plant-associated fungi. Our analyses indicate that root mycobiota members evolved from ancestors with diverse lifestyles and retain large repertoires of plant cell wall-degrading enzymes (PCWDEs) and effector-like small secreted proteins. We identify a set of 84 gene families associated with endophytism, including genes encoding PCWDEs acting on xylan (family GH10) and cellulose (family AA9). Transcripts encoding these enzymes are also part of a conserved transcriptional program activated by phylogenetically-distant mycobiota members upon host contact. Recolonization experiments with individual fungi indicate that strains with detrimental effects in mono-association with the host colonize roots more aggressively than those with beneficial activities, and dominate in natural root samples. Furthermore, we show that the pectin-degrading enzyme family PL1_7 links aggressiveness of endophytic colonization to plant health.

59 BASIC BIOLOGICAL SCIENCES↗

Catabolism and interactions of uncultured organisms shaped by eco-thermodynamics in methanogenic bioprocesses

We currently understand the carbon cycle in methanogenic environments as trophic interactions revolving around interspecies H 2 transfer between organotrophs and methanogens. However, many H 2 -generating processes are thermodynamically sensitive to H 2 accumulation and can be inhibited by high H 2 concentrations produced by other metabolisms. To uncover how anaerobes combat this H 2 conflict in situ, we employ metagenomics and metatranscriptomics to revisit a model ecosystem that has inspired many foundational discoveries in anaerobic ecology – methanogenic bioreactors. Through analysis of 15 anaerobic digesters, we recover 1343 high-quality metagenome-assembled genomes (MAGs) and corresponding gene expression profiles for diverse uncultured lineages spanning 66 phyla and reconstruct their individual metabolic capacities. We discover that diverse uncultured organotrophic populations can drive H 2 -sensitive degradation through (i) metabolic coupling with concurrent H 2 -tolerant catabolism, (ii) unprecedented shifts from H 2 generation to CO 2 -reducing formate transfer and cytochrome/pili-mediated direct interspecies electron transfer for avoiding thermodynamic conflict, and (iii) integration of low-concentration O 2 as an ancillary thermodynamics-enhancing electron sink. Archaeal populations in situ support the above processes through novel metabolisms distinct from conventional methanogenesis – high-affinity H 2 oxidation driven by methyl-reducing methanogenesis and concomitant uptake of formate, electrons, and acetate from HS metabolism by Methanothrix. In total, synthesis of omics analyses and eco-thermodynamics reveals overlooked metabolic behavior and interactions of uncultured organisms that address a central issue in methanogenic carbon cycling, thermodynamic conflict among diverse concurrent metabolic processes.

59 BASIC BIOLOGICAL SCIENCES↗

Antimicrobial resistance and genomic characterization of Salmonella Dublin isolates in cattle from the United States

Salmonella enterica subspecies enterica serotype Dublin is a host-adapted serotype in cattle, associated with enteritis and systemic disease. The primary clinical manifestation of Salmonella Dublin infection in cattle, especially calves, is respiratory disease. While rare in humans, it can cause severe illness, including bacteremia, with hospitalization and death. In the United States, S . Dublin has become one of the most multidrug-resistant serotypes. The objective of this study was to characterize S . Dublin isolates from sick cattle by analyzing phenotypic and genotypic antimicrobial resistance (AMR) profiles, the presence of plasmids, and phylogenetic relationships. S . Dublin isolates (n = 140) were selected from submissions to the NVSL for Salmonella serotyping (2014–2017) from 21 states. Isolates were tested for susceptibility against 14 class-representative antimicrobial drugs. Resistance profiles were determined using the ABRicate with Resfinder and NCBI databases, AMRFinder and PointFinder. Plasmids were detected using ABRicate with PlasmidFinder. Phylogeny was determined using vSNP. We found 98% of the isolates were resistant to more than 4 antimicrobials. Only 1 isolate was pan-susceptible and had no predicted AMR genes. All S . Dublin isolates were susceptible to azithromycin and meropenem. They showed 96% resistance to sulfonamides, 97% to tetracyclines, 95% to aminoglycosides and 85% to beta-lactams. The most common AMR genes were: sulf2 and tetA (98.6%), aph(6)-Id (97.9%), aph(3’’)-Ib, (97.1%), floR (94.3%), and blaCMY-2 (85.7%). All quinolone resistant isolates presented mutations in gyr A. Ten plasmid types were identified among all isolates with IncA/C2, IncX1, and IncFII(S) being the most frequent. The S . Dublin isolates show low genomic genetic diversity. This study provided antimicrobial susceptibility and genomic insight into S . Dublin clinical isolates from cattle in the U.S. Further sequence analysis integrating food and human origin S . Dublin isolates may provide valuable insight on increased virulence observed in humans.

60 APPLIED LIFE SCIENCES↗

A Microbe Associated with Sleep Revealed by a Novel Systems Genetic Analysis of the Microbiome in Collaborative Cross Mice

The microbiome influences health and disease through complex networks of host genetics, genomics, microbes, and environment. Identifying the mechanisms of these interactions has remained challenging. Systems genetics in laboratory mice (Mus musculus) enables data-driven discovery of biological network components and mechanisms of host–microbial interactions underlying disease phenotypes. To examine the interplay among the whole host genome, transcriptome, and microbiome, we mapped QTL and correlated the abundance of cecal messenger RNA, luminal microflora, physiology, and behavior in a highly diverse Collaborative Cross breeding population. One such relationship, regulated by a variant on chromosome 7, was the association of Odoribacter (Bacteroidales) abundance and sleep phenotypes. In a test of this association in the BKS.Cg-Dock7 m +/+ Lepr db /J mouse model of obesity and diabetes, known to have abnormal sleep and colonization by Odoribacter, treatment with antibiotics altered sleep in a genotype-dependent fashion. The many other relationships extracted from this study can be used to interrogate other diseases, microbes, and mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗

Genetic dissection of cardiac growth control pathways

Cardiac muscle cells exhibit two related but distinct modes of growth that are highly regulated during development and disease. Cardiac myocytes rapidly proliferate during fetal life but exit the cell cycle irreversibly soon after birth, following which the predominant form of growth shifts from hyperplastic to hypertrophic. Much research has focused on identifying the candidate mitogens, hypertrophic agonists, and signaling pathways that mediate these processes in isolated cells. What drives the proliferative growth of embryonic myocardium in vivo and the mechanisms by which adult cardiac myocytes hypertrophy in vivo are less clear. Efforts to answer these questions have benefited from rapid progress made in techniques to manipulate the murine genome. Complementary technologies for gain- and loss-of-function now permit a mutational analysis of these growth control pathways in vivo in the intact heart. These studies have confirmed the importance of suspected pathways, have implicated unexpected pathways as well, and have led to new paradigms for the control of cardiac growth.

NASA Program Biomedical Research and Countermeasur↗

A metagenome-level analysis of a microbial community fermenting ultra-filtered milk permeate

Fermentative microbial communities have the potential to serve as biocatalysts for the conversion of low-value dairy coproducts into renewable chemicals, contributing to a more sustainable global economy. To develop predictive tools for the design and operation of industrially relevant strategies that utilize fermentative microbial communities, there is a need to determine the genomic features of community members that are characteristic to the accumulation of different products. To address this knowledge gap, we performed a 282-day bioreactor experiment with a microbial community that was fed ultra-filtered milk permeate, a low-value coproduct from the dairy industry. The bioreactor was inoculated with a microbial community from an acid-phase digester. A metagenomic analysis was used to assess microbial community dynamics, construct metagenome-assembled genomes (MAGs), and evaluate the potential for lactose utilization and fermentation product synthesis of community members represented by the assembled MAGs. This analysis led us to propose that, in this reactor, members of the Actinobacteriota phylum are important in the degradation of lactose, via the Leloir pathway and the bifid shunt, and the production of acetic, lactic, and succinic acids. In addition, members of the Firmicutes phylum contribute to the chain-elongation-mediated production of butyric, hexanoic, and octanoic acids, with different microbes using either lactose, ethanol, or lactic acid as the growth substrate. We conclude that genes encoding carbohydrate utilization pathways, and genes encoding lactic acid transport into the cell, electron confurcating lactate dehydrogenase, and its associated electron transfer flavoproteins, are genomic features whose presence in Firmicutes needs to be established to infer the growth substrate used for chain elongation.

59 BASIC BIOLOGICAL SCIENCES↗

Saccharomycopsis sp. KB-2023a isolate UFMG-CM-Y6991, whole genome shotgun sequencing project

Three yeast isolates were obtained from soil and rotting wood samples collected in an Amazonian rainforest biome in Brazil. Comparison of the intergenic spacer 5.8S region and the D1/D2 domains of the large subunit rRNA gene showed that the isolates represent a novel species of the genus Saccharomycopsis. A tree inferred from the D1/D2 sequences placed the novel species near a subclade containing Saccharomycopsis lassenensis, Saccharomycopsis fermentans, Saccharomycopsis javanensis, Saccharomycopsis babjevae, Saccharomycopsis schoenii and Saccharomycopsis oosterbeekiorum, but with low bootstrap support. In terms of sequence divergence, the novel species had the highest identity in the D1/D2 domains with Saccharomycopsis capsularis, from which it differed by 36 substitutions. In contrast, a phylogenomic analysis based on 1061 single-copy orthologs for a smaller set of Saccharomycopsis species whose whole genome sequences are available indicated that the novel species represented by strain UFMG-CM-Y6991 is phylogenetically closer to Saccharomycopsis fodiens and Saccharomycopsis sp. TF2021a (=Saccharomycopsis phalluae). The novel yeast is homothallic and produces asci with one spheroidal ascospore with an equatorial or subequatorial ledge. The name Saccharomycopsis praedatoria sp. nov. is proposed to accommodate the novel species. The holotype of Saccharomycopsis praedatoria is CBS 16589(T). The MycoBank number is MB849369. S. praedatoria was able to kill cells of Saccharomyces cerevisiae by means of penetration with infection pegs, a trait common to most species of Saccharomycopsis.

Amazonian Forest↗

The Hyperthermophilic Restriction-Modification Systems of Thermococcus kodakarensis Protect Genome Integrity

Thermococcus kodakarensis (T. kodakarensis), a hyperthermophilic, genetically accessible model archaeon, encodes two putative restriction modification (R-M) defense systems, TkoI and TkoII. TkoI is encoded by TK1460 while TkoII is encoded by TK1158. Bioinformative analysis suggests both R-M enzymes are large, fused methyltransferase (MTase)-endonuclease polypeptides that contain both restriction endonuclease (REase) activity to degrade foreign invading DNA and MTase activity to methylate host genomic DNA at specific recognition sites. In this work, we demonsrate T. kodakarensis strains deleted for either or both R-M enzymes grow more slowly but display significantly increased competency compared to strains with intact R-M systems, suggesting that both TkoI and TkoII assist in maintenance of genomic integrity in vivo and likely protect against viral- or plasmid-based DNA transfers. Pacific Biosciences single molecule real-time (SMRT) sequencing of T. kodakarensis strains containing both, one or neither R-M systems permitted assignment of the recognition sites for TkoI and TkoII and demonstrated that both R-M enzymes are TypeIIL; TkoI and TkoII methylate the N 6 position of adenine on one strand of the recognition sequences GTGAAG and TTCAAG, respectively. Further in vitro biochemical characterization of the REase activities reveal TkoI and TkoII cleave the DNA backbone GTGAAG(N) 20 /(N) 18 and TTCAAG(N) 10 /(N) 8 , respectively, away from the recognition sequences, while in vitro characterization of the MTase activities reveal transfer of tritiated S-adenosyl methionine by TkoI and TkoII to their respective recognition sites. Together these results demonstrate TkoI and TkoII restriction systems are important for protecting T. kodakarensis genome integrity from invading foreign DNA.

59 BASIC BIOLOGICAL SCIENCES↗

Workflow for High-throughput Screening of Enzyme Mutant Libraries Using Matrix-assisted Laser Desorption/Ionization Mass Spectrometry Analysis of Escherichia coli Colonies

High-throughput molecular screening of microbial colonies and DNA libraries are critical procedures that enable applications such as directed evolution, functional genomics, microbial identification, and creation of engineered microbial strains to produce high-value molecules. A promising chemical screening approach is the measurement of products directly from microbial colonies via optically guided matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). Measuring the compounds from microbial colonies bypasses liquid culture with a screen that takes approximately 5 s per sample. We describe a protocol combining a dedicated informatics pipeline and sample preparation method that can prepare up to 3,000 colonies in under 3 h. The screening protocol starts from colonies grown on Petri dishes and then transferred onto MALDI plates via imprinting. The target plate with the colonies is imaged by a flatbed scanner and the colonies are located via custom software. The target plate is coated with MALDI matrix, MALDI-MS analyzes the colony locations, and data analysis enables the determination of colonies with the desired biochemical properties. This workflow screens thousands of colonies per day without requiring additional automation. The wide chemical coverage and the high sensitivity of MALDI-MS enable diverse screening projects such as modifying enzymes and functional genomics surveys of gene activation/inhibition libraries.

Choe, Kisurb↗

Machine learning analysis of RB-TnSeq fitness data predicts functional gene modules in Pseudomonas putida KT2440

ABSTRACT There is growing interest in engineering Pseudomonas putida KT2440 as a microbial chassis for the conversion of renewable and waste-based feedstocks, and metabolic engineering of P. putida relies on the understanding of the functional relationships between genes. In this work, independent component analysis (ICA) was applied to a compendium of existing fitness data from randomly barcoded transposon insertion sequencing (RB-TnSeq) of P. putida KT2440 grown in 179 unique experimental conditions. ICA identified 84 independent groups of genes, which we call fModules (“functional modules”), where gene members displayed shared functional influence in a specific cellular process. This machine learning-based approach both successfully recapitulated previously characterized functional relationships and established hitherto unknown associations between genes. Selected gene members from fModules for hydroxycinnamate metabolism and stress resistance, acetyl coenzyme A assimilation, and nitrogen metabolism were validated with engineered mutants of P. putida . Additionally, functional gene clusters from ICA of RB-TnSeq data sets were compared with regulatory gene clusters from prior ICA of RNAseq data sets to draw connections between gene regulation and function. Because ICA profiles the functional role of several distinct gene networks simultaneously, it can reduce the time required to annotate gene function relative to manual curation of RB-TnSeq data sets. IMPORTANCE This study demonstrates a rapid, automated approach for elucidating functional modules within complex genetic networks. While Pseudomonas putida randomly barcoded transposon insertion sequencing data were used as a proof of concept, this approach is applicable to any organism with existing functional genomics data sets and may serve as a useful tool for many valuable applications, such as guiding metabolic engineering efforts in other microbes or understanding functional relationships between virulence-associated genes in pathogenic microbes. Furthermore, this work demonstrates that comparison of data obtained from independent component analysis of transcriptomics and gene fitness datasets can elucidate regulatory-functional relationships between genes, which may have utility in a variety of applications, such as metabolic modeling, strain engineering, or identification of antimicrobial drug targets.

09 BIOMASS FUELS↗