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At least 595 records · Page 33

Ultrahigh-resolution mass spectrometry data associated with the manuscript “A functional microbiome catalog crowdsourced from North American rivers"

This data package is associated with the publication “A functional microbiome catalog crowdsourced from North American rivers” submitted to Nature (Borton et al., 2024); (https://www.biorxiv.org/content/10.1101/2023.07.22.550117v1). Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires understanding the spatial drivers of river microbiomes. However, the unifying microbial determinants governing river biogeochemistry are hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we employed a community science effort to accelerate the sampling of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). GROWdb is a publicly available resource that paves the way for watershed predictive modeling and microbiome-based management practices. This resource profiled the identity, distribution, function, and expression of thousands of microbial genomes across rivers covering 90% of United States watersheds. We identified the most cosmopolitan microbiome members, while also revealing local drivers of strain endemism across ecological dimensions. We provide the first evidence that microbial functional trait expression followed the tenets of the River Continuum Concept, suggesting the structure and function of river microbiomes is predictable. The Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) data were one of many different data types used in establishing the ecological dimensions along which different microbes were detected .This data package only contains the processed FTICR-MS data associated with this manuscript; all other data is accessible via Zenodo (https://zenodo.org/records/8173287), GitHub (https://github.com/jmikayla1991/Genome-Resolved-Open-Watersheds-database-GROWdb), KBase (https://doi.org/10.25982/109073.30/1895615), and NCBI via Bioproject PRJNA946291.This dataset consists of (1) a file-level metadata (flmd) file; (2) a data dictionary (dd) file; (3) a readme; (4) three Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) processed data files (a ‘data’ file containing peak-by-sample observations, a ‘mol’ file containing peak metadata, and a transformation profile containing transformation-by-sample observations). All files are .csv or .pdf.

54 ENVIRONMENTAL SCIENCES↗

Biomolecular and Characterization Imaging Science Program: 2023 Principal Investigator Meeting Proceedings

The 2023 U.S. Department of Energy (DOE) Biological and Environmental Research (BER) program’s Biomolecular Characterization and Imaging Science (BCIS) Principal Investigator Meeting expanded in scope from previous Bioimaging Science Program (BSP) meetings to include BER Structural Biology and Imaging Resources, which are located largely at DOE Office of Science national laboratories. The BCIS meeting was part of BER’s Biological Systems Science Division (BSSD) annual PI meeting, which was held April 17–19, 2023, and featured parallel meetings of the BCIS and Genomic Science programs (GSP). The meetings were held together to encourage networking and idea exchange across technologies and biological application areas, forging new multidisciplinary collaborations among researchers from adjacent BSSD programmatic areas. Two joint BCIS-GSP sessions were held: “BCIS Technologies for Investigating the Rhizosphere” and “Joint Emerging Topics and Technologies.” The rhizosphere session focused on scientific findings from BCIS and GSP PIs, including national laboratory collaborations. The intent was to identify new opportunities to measure and understand the complex community of microbes, roots, and soils that support plant growth under challenging environmental conditions. The emerging technologies session highlighted forward-looking approaches and tools to tackle challenges within the scope of BSSD research on investigating and modifying genomic and molecular function. A final interactive discussion of the BCIS program was led by plenary session chairs.

59 BASIC BIOLOGICAL SCIENCES↗

Promoter deletion in the soybean Compact mutant leads to overexpression of a gene with homology to the C 20 -gibberellin 2-oxidase family

Height is a critical component of plant architecture, significantly affecting crop yield. The genetic basis of this trait in soybean remains unclear. In this study, we report the characterization of the Compact mutant of soybean, which has short internodes. The candidate gene was mapped to chromosome 17, and the interval containing the causative mutation was further delineated using biparental mapping. Whole-genome sequencing of the mutant revealed an 8.7 kb deletion in the promoter of the Glyma.17g145200 gene, which encodes a member of the class III gibberellin (GA) 2-oxidases. The mutation has a dominant effect, likely via increased expression of the GA 2-oxidase transcript observed in green tissue, as a result of the deletion in the promoter of Glyma.17g145200. We further demonstrate that levels of GA precursors are altered in the Compact mutant, supporting a role in GA metabolism, and that the mutant phenotype can be rescued with exogenous GA3. We also determined that overexpression of Glyma.17g145200 in Arabidopsis results in dwarfed plants. Thus, gain of promoter activity in the Compact mutant leads to a short internode phenotype in soybean through altered metabolism of gibberellin precursors. Furthermore, these results provide an example of how structural variation can control an important crop trait and a role for Glyma.17g145200 in soybean architecture, with potential implications for increasing crop yield.

59 BASIC BIOLOGICAL SCIENCES↗

Coupling extracellular glycan composition with metagenomic data in papermill and brewery anaerobic granular sludges

Glycans are crucial for the structure and function of anaerobic granular sludge in wastewater treatment. Yet, there is limited knowledge regarding the microorganisms and biosynthesis pathways responsible for glycan production. In this study, we analysed samples from anaerobic granular sludges treating papermill and brewery wastewater, examining glycans composition and using metagenome-assembled genomes (MAGs) to explore potential biochemical pathways associated with their production. Uronic acids were the predominant constituents of the glycans in extracellular polymeric substances (EPS) produced by the anaerobic granular sludges, comprising up to 60 % of the total polysaccharide content. MAGs affiliated with Anaerolineacae, Methanobacteriaceae and Methanosaetaceae represented the majority of the microbial community (30–50 % of total reads per MAG). Based on the analysis of MAGs, it appears that Anaerolinea sp. and members of the Methanobacteria class are involved in the production of exopolysaccharides within the analysed granular sludges. These findings shed light on the functional roles of microorganisms in glycan production in industrial anaerobic wastewater treatment systems.

59 BASIC BIOLOGICAL SCIENCES↗

A Representation Fusion Framework for Decoupling Diagnostic Information in Multimodal Learning

Modern medicine increasingly relies on multimodal data, ranging from clinical notes to imaging and genomics, to guide diagnosis and treatment. However, integrating these heterogeneous data sources in a principled and interpretable manner remains a major challenge. We present MODES (Multi-mOdal Disentangled Embedding Space), a representation fusion framework that explicitly separates shared and modality-specific factors of variation, offering a structured latent space for multimodal information that improves both prediction and interpretability. By leveraging pre-trained unimodal foundation models, MODES mitigates the dependency on extensive paired datasets, crucial in data-scarce clinical settings. We introduce a masking strategy that optimizes representation dimensionality by eliminating low-information dimensions, to achieve compact, information-rich representations. Our framework demonstrates superior performance in predicting diagnoses and phenotypes compared to unimodal and conventional fusion models. MODES also enables robust diagnostic inference in missing data scenarios, offering an opportunity toward interpretable and efficient multimodal diagnostics in personalized healthcare.

60 APPLIED LIFE SCIENCES↗

Factors underlying a latitudinal gradient in the S/G lignin monomer ratio in natural poplar variants

The chemical composition of wood plays a pivotal role in the adaptability and structural integrity of trees. However, few studies have investigated the environmental factors that determine lignin composition and its biological significance in plants. Here, we examined the lignin syringyl-to-guaiacyl (S/G) ratio in members of a Populus trichocarpa population sourced from their native habitat and conducted a genome wide association study to identify genes linked to lignin formation. Our results revealed many significant associations, suggesting that lignin biosynthesis is a complex polygenic trait. Additionally, we found an increase in the S/G ratio from northern to southern geographic origin of the trees sampled, along with a corresponding metabolic and transcriptional reprogramming of xylem cell wall biosynthesis. Further molecular analysis identified a mutation in a cell wall laccase genetically associated with higher S/G ratios that predominate in trees from warmer lower latitudes. Collectively, our findings suggest that lignin heterogeneity arises from an evolutionary process enabling poplar adaptation to different climatic challenges.

adaptation↗

Biophysical and biochemical studies support TP0094 as a phosphotransacetylase in an acetogenic energy-conservation pathway in Treponema pallidum

The mechanisms of energy generation and carbon-source utilization in the syphilis spirochete Treponema pallidum have remained enigmatic despite complete genomic sequence information. Whereas the bacterium harbors enzymes for glycolysis, the apparatus for more efficient use of glucose catabolites, namely the citric-acid cycle, is apparently not present. Yet, the organism’s energy needs likely exceed the modest output from glycolysis alone. Recently, building on our structure-function studies of T . pallidum lipoproteins, we proposed a “flavin-centric” metabolic lifestyle for the organism that partially resolves this conundrum. As a part of the hypothesis, we have proposed that T . pallidum contains an acetogenic energy-conservation pathway that catabolizes D-lactate, yielding acetate, reducing equivalents for the generation and maintenance of chemiosmotic potential, and ATP. We already have confirmed the D-lactate dehydrogenase activity in T . pallidum necessary for this pathway to operate. In the current study, we focused on another enzyme ostensibly involved in treponemal acetogenesis, phosphotransacetylase (Pta). This enzyme is putatively identified as TP0094 and, in this study, we determined a high-resolution (1.95 Å) X-ray crystal structure of the protein, finding that its fold comports with other known Pta enzymes. Further studies on its solution behavior and enzyme activity confirmed that it has the properties of a Pta. These results are consistent with the proposed acetogenesis pathway in T . pallidum , and we propose that the protein be referred to henceforth as TpPta.

59 BASIC BIOLOGICAL SCIENCES↗

Metabolic model-based ecological modeling for probiotic design

The microbial community composition in the human gut has a profound effect on human health. This observation has lead to extensive use of microbiome therapies, including over-the-counter ‘probiotic’ treatments intended to alter the composition of the microbiome. Despite so much promise and commercial interest, the factors that contribute to the success or failure of microbiome-targeted treatments remain unclear. We investigate the biotic interactions that lead to successful engraftment of a novel bacterial strain introduced to the microbiome as in probiotic treatments. We use pairwise genome-scale metabolic modeling with a generalized resource allocation constraint to build a network of interactions between taxa that appear in an experimental engraftment study. We create induced sub-graphs using the taxa present in individual samples and assess the likelihood of invader engraftment based on network structure. To do so, we use a generalized Lotka-Volterra model, which we show has strong ability to predict if a particular invader or probiotic will successfully engraft into an individual’s microbiome. Furthermore, we show that the mechanistic nature of the model is useful for revealing which microbe-microbe interactions potentially drive engraftment.

59 BASIC BIOLOGICAL SCIENCES↗

Proteome specialization of anaerobic fungi during ruminal degradation of recalcitrant plant fiber

The rumen harbors a complex microbial mixture of archaea, bacteria, protozoa, and fungi that efficiently breakdown plant biomass and its complex dietary carbohydrates into soluble sugars that can be fermented and subsequently converted into metabolites and nutrients utilized by the host animal. While rumen bacterial populations have been well documented, only a fraction of the rumen eukarya are taxonomically and functionally characterized, despite the recognition that they contribute to the cellulolytic phenotype of the rumen microbiota. To investigate how anaerobic fungi actively engage in digestion of recalcitrant fiber that is resistant to degradation, we resolved genome-centric metaproteome and metatranscriptome datasets generated from switchgrass samples incubated for 48 h in nylon bags within the rumen of cannulated dairy cows. Across a gene catalog covering anaerobic rumen bacteria, fungi and viruses, a significant portion of the detected proteins originated from fungal populations. Intriguingly, the carbohydrate-active enzyme (CAZyme) profile suggested a domain-specific functional specialization, with bacterial populations primarily engaged in the degradation of hemicelluloses, whereas fungi were inferred to target recalcitrant cellulose structures via the detection of a number of endo- and exo-acting enzymes belonging to the glycoside hydrolase (GH) family 5, 6, 8, and 48. Notably, members of the GH48 family were amongst the highest abundant CAZymes and detected representatives from this family also included dockerin domains that are associated with fungal cellulosomes. A eukaryote-selected metatranscriptome further reinforced the contribution of uncultured fungi in the ruminal degradation of recalcitrant fibers. These findings elucidate the intricate networks of in situ recalcitrant fiber deconstruction, and importantly, suggest that the anaerobic rumen fungi contribute a specific set of CAZymes that complement the enzyme repertoire provided by the specialized plant cell wall degrading rumen bacteria.

Hagen, Live↗

Mechanism of Rad26-assisted rescue of stalled RNA polymerase II in transcription-coupled repair

Transcription-coupled repair is essential for the removal of DNA lesions from the transcribed genome. The pathway is initiated by CSB protein binding to stalled RNA polymerase II. Mutations impairing CSB function cause severe genetic disease. Yet, the ATP-dependent mechanism by which CSB powers RNA polymerase to bypass certain lesions while triggering excision of others is incompletely understood. Here we build structural models of RNA polymerase II bound to the yeast CSB ortholog Rad26 in nucleotide-free and bound states. This enables simulations and graph-theoretical analyses to define partitioning of this complex into dynamic communities and delineate how its structural elements function together to remodel DNA. We identify an allosteric pathway coupling motions of the Rad26 ATPase modules to changes in RNA polymerase and DNA to unveil a structural mechanism for CSB-assisted progression past less bulky lesions. Our models allow functional interpretation of the effects of Cockayne syndrome disease mutations.

59 BASIC BIOLOGICAL SCIENCES↗

Resolving the structure of phage–bacteria interactions in the context of natural diversity

Microbial communities are shaped by viral predators. Yet, resolving which viruses (phages) and bacteria are interacting is a major challenge in the context of natural levels of microbial diversity. Thus, fundamental features of how phage-bacteria interactions are structured and evolve in the wild remain poorly resolved. Here we use large-scale isolation of environmental marine Vibrio bacteria and their phages to obtain estimates of strain-level phage predator loads, and use all-by-all host range assays to discover how phage and host genomic diversity shape interactions. We show that lytic interactions in environmental interaction networks (as observed in agar overlay) are sparse—with phage predator loads being low for most bacterial strains, and phages being host-strain-specific. Paradoxically, we also find that although overlap in killing is generally rare between tailed phages, recombination is common. Together, these results suggest that recombination during cryptic co-infections is an important mode of phage evolution in microbial communities. In the development of phages for bioengineering and therapeutics it is important to consider that nucleic acids of introduced phages may spread into local phage populations through recombination, and that the likelihood of transfer is not predictable based on lytic host range.

59 BASIC BIOLOGICAL SCIENCES↗

Machine learning sheds light on microbial dark proteins

In this article, metagenomics projects have revealed more than 8 billion non-redundant microbial protein sequences from across the Earth’s biosphere. Of these, 1.17 billion proteins do not have recognizable homologues in any of the more than 100,000 reference genomes available1. Understanding the function of these microbial proteins is a daunting task. Fortunately, machine learning has recently achieved unprecedented accuracy in modelling complex biological data and making predictions. At the forefront of these advancements are machine learning-based approaches that can confidently predict atomic-level protein structures for many (but not all) amino acid sequences.

59 BASIC BIOLOGICAL SCIENCES↗

Poplar

SAND2025-00683O Poplar is a software tool that generates a phylogenetic tree from input gene and genome sequences. It integrates established tools to identify genes within genomes, group sequences, construct gene trees, and infer a species tree. Poplar processes nucleotide sequences, identifies similar sequences using Nucleotide BLAST, groups them with DBSCAN, aligns sequences with MAFFT, constructs gene trees with RAxML-NG, and infers a species tree using ASTRAL-Pro3. This pipeline provides a structured approach to phylogenetic analysis, facilitating the study of evolutionary relationships among species. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Krishnakumar, Raga↗

Artificial cells: prospects for biotechnology

A variety of techniques can now be used to alter the genome of a cell. Although these techniques are very powerful, they have limitations related to cost and efficiency of scale. Artificial cells designed for specific applications combine properties of biological systems such as nanoscale efficiency, self-organization and adaptability at relatively low cost. Individual components needed for such structures have already been developed, and now the main challenge is to integrate them in functional microscopic compartments. It will then become possible to design and construct communities of artificial cells that can perform different tasks related to therapeutic and diagnostic applications.

Review↗

Structural basis for proficient oxidized ribonucleotide insertion in double strand break repair

Reactive oxygen species (ROS) oxidize cellular nucleotide pools and cause double strand breaks (DSBs). Non-homologous end-joining (NHEJ) attaches broken chromosomal ends together in mammalian cells. Ribonucleotide insertion by DNA polymerase (pol) μ prepares breaks for end-joining and this is required for successful NHEJ in vivo. We previously showed that pol μ lacks discrimination against oxidized dGTP (8-oxo-dGTP), that can lead to mutagenesis, cancer, aging and human disease. Here we reveal the structural basis for proficient oxidized ribonucleotide (8-oxo-rGTP) incorporation during DSB repair by pol μ. Time-lapse crystallography snapshots of structural intermediates during nucleotide insertion along with computational simulations reveal substrate, metal and side chain dynamics, that allow oxidized ribonucleotides to escape polymerase discrimination checkpoints. Abundant nucleotide pools, combined with inefficient sanitization and repair, implicate pol μ mediated oxidized ribonucleotide insertion as an emerging source of widespread persistent mutagenesis and genomic instability.

60 APPLIED LIFE SCIENCES↗

cGAS-like receptors sense RNA and control 3'2'-cGAMP signalling in Drosophila

Cyclic GMP–AMP synthase (cGAS) is a cytosolic DNA sensor that produces the second messenger cG[2'–5']pA[3'–5']p (2'3'-cGAMP) and controls activation of innate immunity in mammalian cells. Animal genomes typically encode multiple proteins with predicted homology to cGAS, but the function of these uncharacterized enzymes is unknown. Here we show that cGAS-like receptors (cGLRs) are innate immune sensors that are capable of recognizing divergent molecular patterns and catalysing synthesis of distinct nucleotide second messenger signals. Crystal structures of human and insect cGLRs reveal a nucleotidyltransferase signalling core shared with cGAS and a diversified primary ligand-binding surface modified with notable insertions and deletions. We demonstrate that surface remodelling of cGLRs enables altered ligand specificity and used a forward biochemical screen to identify cGLR1 as a double-stranded RNA sensor in the model organism Drosophila melanogaster. We show that RNA recognition activates Drosophila cGLR1 to synthesize the novel product cG[3'–5']pA[2'–5']p (3'2'-cGAMP). A crystal structure of Drosophila stimulator of interferon genes (dSTING) in complex with 3'2'-cGAMP explains selective isomer recognition, and 3'2'-cGAMP induces an enhanced antiviral state in vivo that protects from viral infection. Similar to radiation of Toll-like receptors in pathogen immunity, our results establish cGLRs as a diverse family of metazoan pattern recognition receptors.

59 BASIC BIOLOGICAL SCIENCES↗

Extrapolation of the dna fragment-size distribution after high-dose irradiation to predict effects at low doses

The patterns of DSBs induced in the genome are different for sparsely and densely ionizing radiations: In the former case, the patterns are well described by a random-breakage model; in the latter, a more sophisticated tool is needed. We used a Monte Carlo algorithm with a random-walk geometry of chromatin, and a track structure defined by the radial distribution of energy deposition from an incident ion, to fit the PFGE data for fragment-size distribution after high-dose irradiation. These fits determined the unknown parameters of the model, enabling the extrapolation of data for high-dose irradiation to the low doses that are relevant for NASA space radiation research. The randomly-located-clusters formalism was used to speed the simulations. It was shown that only one adjustable parameter, Q, the track efficiency parameter, was necessary to predict DNA fragment sizes for wide ranges of doses. This parameter was determined for a variety of radiations and LETs and was used to predict the DSB patterns at the HPRT locus of the human X chromosome after low-dose irradiation. It was found that high-LET radiation would be more likely than low-LET radiation to induce additional DSBs within the HPRT gene if this gene already contained one DSB.

NASA Discipline Radiation Health↗

Developing Personalized Sensorimotor Adaptability Countermeasures for Spaceflight

Astronauts experience sensorimotor disturbances during their initial exposure to microgravity and during the re-adaptation phase following a return to an Earth-gravitational environment. Interestingly, astronauts who return from spaceflight show substantial differences in their abilities to readapt to a gravitational environment. The ability to predict the manner and degree to which individual astronauts would be affected would improve the effectiveness of countermeasure training programs designed to enhance sensorimotor adaptability. In this paper we will be presenting results from our ground-based study that show how behavioral, brain imaging and genomic data may be used to predict individual differences in sensorimotor adaptability to novel sensorimotor environments. This approach will allow us to better design and implement sensorimotor adaptability training countermeasures against decrements in post-mission adaptive capability that are customized for each crewmember's sensory biases, adaptive capacity, brain structure, functional capacities, and genetic predispositions. The ability to customize adaptability training will allow more efficient use of crew time during training and will optimize training prescriptions for astronauts to ensure expected outcomes.

Mulavara, A. P.↗