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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

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↗
DOE OSTI2023

The genome-scale metabolic model for the purple non-sulfur bacterium Rhodopseudomonas palustris Bis A53 accurately predicts phenotypes under chemoheterotrophic, chemoautotrophic, photoheterotrophic, and photoautotrophic growth conditions

The purple non-sulfur bacterium Rhodopseudomonas palustris is recognized as a critical microorganism in the nitrogen and carbon cycle and one of the most common members in wastewater treatment communities. This bacterium is metabolically extremely versatile. It is capable of heterotrophic growth under aerobic and anaerobic conditions, but also able to grow photoautotrophically as well as mixotrophically. Therefore R . palustris can adapt to multiple environments and establish commensal relationships with other organisms, expressing various enzymes supporting degradation of amino acids, carbohydrates, nucleotides, and complex polymers. Moreover, R . palustris can degrade a wide range of pollutants under anaerobic conditions, e.g., aromatic compounds such as benzoate and caffeate, enabling it to thrive in chemically contaminated environments. However, many metabolic mechanisms employed by R . palustris to breakdown and assimilate different carbon and nitrogen sources under chemoheterotrophic or photoheterotrophic conditions remain unknown. Systems biology approaches, such as metabolic modeling, have been employed extensively to unravel complex mechanisms of metabolism. Previously, metabolic models have been reconstructed to study selected capabilities of R . palustris under limited experimental conditions. Here, we developed a comprehensive metabolic model (M-model) for R . palustris Bis A53 ( i DT1294) consisting of 2,721 reactions, 2,123 metabolites, and comprising 1,294 genes. We validated the model using high-throughput phenotypic, physiological, and kinetic data, testing over 350 growth conditions. i DT1294 achieved a prediction accuracy of 90% for growth with various carbon and nitrogen sources and close to 80% for assimilation of aromatic compounds. Moreover, the M-model accurately predicts dynamic changes of growth and substrate consumption rates over time under nine chemoheterotrophic conditions and demonstrated high precision in predicting metabolic changes between photoheterotrophic and photoautotrophic conditions. This comprehensive M-model will help to elucidate metabolic processes associated with the assimilation of multiple carbon and nitrogen sources, anoxygenic photosynthesis, aromatic compound degradation, as well as production of molecular hydrogen and polyhydroxybutyrate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

jialiu232/MetaFunPrimer_paper_info

Genes belonging to the same functional group may include numerous and variable gene sequences, making characterizing and quantifying difficult. Therefore, high-throughput design tools are needed to simultaneously create primers for improved quantification of target genes. We developed MetaFunPrimer, a bioinformatic pipeline, to design primers for numerous genes of interest. This tool also enables gene target prioritization based on ranking the presence of genes in user-defined references, such as environment-specific metagenomes. Given inputs of protein and nucleotide sequences for gene targets of interest and an accompanying set of reference metagenomes or genomes, MetaFunPrimer generates primers for ranked genes of interest. To demonstrate the usage and benefits of MetaFunPrimer, a total of 78 primer pairs were designed to target observed ammonia monooxygenase subunit A (amoA) genes of ammonia-oxidizing bacteria (AOB) in 1,550 publicly available soil metagenomes. We demonstrate computationally that these amoA-AOB primers can cover 94% of the amoA-AOB genes observed in the 1,550 soil metagenomes compared with a 49% estimated coverage by previously published primers. Finally, we verified the utility of these primer sets in incubation experiments that used long-term nitrogen fertilized or unfertilized soils. High-throughput quantitative PCR (qPCR) results and statistical analyses showed significant differences in relative quantification patterns between the two soils, and subsequent absolute quantifications also confirmed that target genes enumerated by six selected primer pairs were significantly more abundant in the nitrogen-fertilized soils. This new tool gives microbial ecologists a new approach to assess functional gene abundance and related microbial community dynamics quickly and affordably.

Liu, Jia↗
DOE OSTI2020

Quality-Control Mechanism for Telomerase RNA Folding in the Cell

Long non-coding RNAs can often fold into different conformations. Telomerase RNA, an essential component of the telomerase ribonucleoprotein (RNP) enzyme, must fold into a defined structure to fulfill its function with the protein catalytic subunit (TERT) and other accessory factors. However, the mechanism by which the correct folding of telomerase RNA is warranted in a cell is still unknown. Here we show that La-related protein Pof8 specifically recognizes the conserved pseudoknot region of telomerase RNA and instructs the binding of the Lsm2-8 complex to its mature 3' end, thus selectively protecting the correctly folded RNA from exonucleolytic degradation. In the absence of Pof8, TERT assembles with misfolded RNA and produces little telomerase activity. Therefore, Pof8 plays a key role in telomerase RNA folding quality control, ensuring that TERT only assembles with functional telomerase RNA to form active telomerase. Our finding reveals a mechanism for non-coding RNA folding quality control.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Suppressor Mutations in Type II Secretion Mutants of Vibrio cholerae : Inactivation of the VesC Protease

The type II secretion system (T2SS) is a conserved transport pathway responsible for the secretion of a range of virulence factors by many pathogens, including Vibrio cholerae. Disruption of the T2SS genes in V. cholerae results in loss of secretion, changes in cell envelope function, and growth defects. While T2SS mutants are viable, high-throughput genomic analyses have listed these genes among essential genes. To investigate whether secondary mutations arise as a consequence of T2SS inactivation, we sequenced the genomes of six V. cholerae T2SS mutants with deletions or insertions in either the epsG, epsL, or epsM genes and identified secondary mutations in all mutants. Two of the six T2SS mutants contain distinct mutations in the gene encoding the T2SS-secreted protease VesC. Other mutations were found in genes coding for V. cholerae cell envelope proteins. Subsequent sequence analysis of the vesC gene in 92 additional T2SS mutant isolates identified another 19 unique mutations including insertions or deletions, sequence duplications, and single-nucleotide changes resulting in amino acid substitutions in the VesC protein. Analysis of VesC variants and the X-ray crystallographic structure of wild-type VesC suggested that all mutations lead to loss of VesC production and/or function. One possible mechanism by which V. cholerae T2SS mutagenesis can be tolerated is through selection of vesC-inactivating mutations, which may, in part, suppress cell envelope damage, establishing permissive conditions for the disruption of the T2SS. Other mutations may have been acquired in genes encoding essential cell envelope proteins to prevent proteolysis by VesC.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

MIBiG 3.0: a community-driven effort to annotate experimentally validated biosynthetic gene clusters

Abstract With an ever-increasing amount of (meta)genomic data being deposited in sequence databases, (meta)genome mining for natural product biosynthetic pathways occupies a critical role in the discovery of novel pharmaceutical drugs, crop protection agents and biomaterials. The genes that encode these pathways are often organised into biosynthetic gene clusters (BGCs). In 2015, we defined the Minimum Information about a Biosynthetic Gene cluster (MIBiG): a standardised data format that describes the minimally required information to uniquely characterise a BGC. We simultaneously constructed an accompanying online database of BGCs, which has since been widely used by the community as a reference dataset for BGCs and was expanded to 2021 entries in 2019 (MIBiG 2.0). Here, we describe MIBiG 3.0, a database update comprising large-scale validation and re-annotation of existing entries and 661 new entries. Particular attention was paid to the annotation of compound structures and biological activities, as well as protein domain selectivities. Together, these new features keep the database up-to-date, and will provide new opportunities for the scientific community to use its freely available data, e.g. for the training of new machine learning models to predict sequence-structure-function relationships for diverse natural products. MIBiG 3.0 is accessible online at https://mibig.secondarymetabolites.org/.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

DNA Viral Diversity, Abundance, and Functional Potential Vary across Grassland Soils with a Range of Historical Moisture Regimes

Soil viruses are abundant, but the influence of the environment and climate on soil viruses remains poorly understood. Here, we addressed this gap by comparing the diversity, abundance, lifestyle, and metabolic potential of DNA viruses in three grassland soils with historical differences in average annual precipitation, low in eastern Washington (WA), high in Iowa (IA), and intermediate in Kansas (KS). Bioinformatics analyses were applied to identify a total of 2,631 viral contigs, including 14 complete viral genomes from three deep metagenomes (1 terabase [Tb] each) that were sequenced from bulk soil DNA. An additional three replicate metagenomes (~0.5 Tb each) were obtained from each location for statistical comparisons. Identified viruses were primarily bacteriophages targeting dominant bacterial taxa. Both viral and host diversity were higher in soil with lower precipitation. Viral abundance was also significantly higher in the arid WA location than in IA and KS. More lysogenic markers and fewer clustered regularly interspaced short palindromic repeats (CRISPR) spacer hits were found in WA, reflecting more lysogeny in historically drier soil. More putative auxiliary metabolic genes (AMGs) were also detected in WA than in the historically wetter locations. The AMGs occurring in 18 pathways could potentially contribute to carbon metabolism and energy acquisition in their hosts. Structural equation modeling (SEM) suggested that historical precipitation influenced viral life cycle and selection of AMGs. The observed and predicted relationships between soil viruses and various biotic and abiotic variables have value for predicting viral responses to environmental change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Mixed waste contamination selects for a mobile genetic element population enriched in multiple heavy metal resistance genes

Abstract Mobile genetic elements (MGEs) like plasmids, viruses, and transposable elements can provide fitness benefits to their hosts for survival in the presence of environmental stressors. Heavy metal resistance genes (HMRGs) are frequently observed on MGEs, suggesting that MGEs may be an important driver of adaptive evolution in environments contaminated with heavy metals. Here, we report the meta-mobilome of the heavy metal-contaminated regions of the Oak Ridge Reservation subsurface. This meta-mobilome was compared with one derived from samples collected from unimpacted regions of the Oak Ridge Reservation subsurface. We assembled 1615 unique circularized DNA elements that we propose to be MGEs. The circular elements from the highly contaminated subsurface were enriched in HMRG clusters relative to those from the nearby unimpacted regions. Additionally, we found that these HMRGs were associated with Gamma and Betaproteobacteria hosts in the contaminated subsurface and potentially facilitate the persistence and dominance of these taxa in this region. Finally, the HMRGs were associated with conjugative elements, suggesting their potential for future lateral transfer. We demonstrate how our understanding of MGE ecology, evolution, and function can be enhanced through the genomic context provided by completed MGE assemblies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Transport of metformin metabolites by guanidinium exporters of the small multidrug resistance family

Proteins from the small multidrug resistance (SMR) family are frequently associated with horizontally transferred multidrug resistance gene arrays found in bacteria from wastewater and the human-adjacent biosphere. Recent studies suggest that a subset of SMR transporters might participate in the metabolism of the common pharmaceutical metformin by bacterial consortia. Here, we show that both genomic and plasmid-associated transporters of the SMRGdx functional subtype export byproducts of microbial metformin metabolism, with particularly high export efficiency for guanylurea. We use solid-supported membrane electrophysiology to evaluate the transport kinetics for guanylurea and native substrate guanidinium by four representative SMRGdx homologs. Using an internal reference to normalize independent electrophysiology experiments, we show that transport rates are comparable for genomic and plasmid-associated SMRGdx homologs, and using a proteoliposome-based transport assay, we show that 2 proton:1 substrate transport stoichiometry is maintained. Additional characterization of guanidinium and guanylurea export properties focuses on the structurally characterized homolog, Gdx-Clo, for which we examined the pH dependence and thermodynamics of substrate binding and solved an x-ray crystal structure with guanylurea bound. Together, these experiments contribute in two main ways. By providing the first detailed kinetic examination of the structurally characterized SMRGdx homolog Gdx-Clo, they provide a functional framework that will inform future mechanistic studies of this model transport protein. Second, this study casts light on a potential role for SMRGdx transporters in microbial handling of metformin and its microbial metabolic byproducts, providing insight into how native transport physiologies are co-opted to contend with new selective pressures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

3D reconstruction identifies loci linked to variation in angle of individual sorghum leaves

Selection for yield at high planting density has reshaped the leaf canopy of maize, improving photosynthetic productivity in high density settings. Further optimization of canopy architecture may be possible. However, measuring leaf angles, the widely studied component trait of leaf canopy architecture, by hand is a labor and time intensive process. Here, we use multiple, calibrated, 2D images to reconstruct the 3D geometry of individual sorghum plants using a voxel carving based algorithm. Automatic skeletonization and segmentation of these 3D geometries enable quantification of the angle of each leaf for each plant. The resulting measurements are both heritable and correlated with manually collected leaf angles. This automated and scaleable reconstruction approach was employed to measure leaf-by-leaf angles for a population of 366 sorghum plants at multiple time points, resulting in 971 successful reconstructions and 3,376 leaf angle measurements from individual leaves. A genome wide association study conducted using aggregated leaf angle data identified a known large effect leaf angle gene, several previously identified leaf angle QTL from a sorghum NAM population, and novel signals. Genome wide association studies conducted separately for three individual sorghum leaves identified a number of the same signals, a previously unreported signal shared across multiple leaves, and signals near the sorghum orthologs of two maize genes known to influence leaf angle. Automated measurement of individual leaves and mapping variants associated with leaf angle reduce the barriers to engineering ideal canopy architectures in sorghum and other grain crops.

3D reconstruction↗
DOE OSTI2020

Structural characterization and computational analysis of PDZ domains in Monosiga brevicollis

Abstract Identification of the molecular networks that facilitated the evolution of multicellular animals from their unicellular ancestors is a fundamental problem in evolutionary cellular biology. Choanoflagellates are recognized as the closest extant nonmetazoan ancestors to animals. These unicellular eukaryotes can adopt a multicellular‐like “rosette” state. Therefore, they are compelling models for the study of early multicellularity. Comparative studies revealed that a number of putative human orthologs are present in choanoflagellate genomes, suggesting that a subset of these genes were necessary for the emergence of multicellularity. However, previous work is largely based on sequence alignments alone, which does not confirm structural nor functional similarity. Here, we focus on the PDZ domain, a peptide‐binding domain which plays critical roles in myriad cellular signaling networks and which underwent a gene family expansion in metazoan lineages. Using a customized sequence similarity search algorithm, we identified 178 PDZ domains in the Monosiga brevicollis proteome. This includes 11 previously unidentified sequences, which we analyzed using Rosetta and homology modeling. To assess conservation of protein structure, we solved high‐resolution crystal structures of representative M. brevicollis PDZ domains that are homologous to human Dlg1 PDZ2, Dlg1 PDZ3, GIPC, and SHANK1 PDZ domains. To assess functional conservation, we calculated binding affinities for mbGIPC, mbSHANK1, mbSNX27, and mbDLG‐3 PDZ domains from M. brevicollis . Overall, we find that peptide selectivity is generally conserved between these two disparate organisms, with one possible exception, mbDLG‐3. Overall, our results provide novel insight into signaling pathways in a choanoflagellate model of primitive multicellularity.

Gao, Melody↗
DOE OSTI2021

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↗
DOE OSTI2020

High-throughput mapping of the phage resistance landscape in E. coli

Bacteriophages (phages) are critical players in the dynamics and function of microbial communities and drive processes as diverse as global biogeochemical cycles and human health. Phages tend to be predators finely tuned to attack specific hosts, even down to the strain level, which in turn defend themselves using an array of mechanisms. However, to date, efforts to rapidly and comprehensively identify bacterial host factors important in phage infection and resistance have yet to be fully realized. Here, we globally map the host genetic determinants involved in resistance to 14 phylogenetically diverse double-stranded DNA phages using two model Escherichia coli strains (K-12 and BL21) with known sequence divergence to demonstrate strain-specific differences. Using genome-wide loss-of-function and gain-of-function genetic technologies, we are able to confirm previously described phage receptors as well as uncover a number of previously unknown host factors that confer resistance to one or more of these phages. We uncover differences in resistance factors that strongly align with the susceptibility of K-12 and BL21 to specific phage. We also identify both phage specific mechanisms, such as the unexpected role of cyclic-di-GMP in host sensitivity to phage N4, and more generic defenses, such as the overproduction of colanic acid capsular polysaccharide that defends against a wide array of phages. Our results indicate that host responses to phages can occur via diverse cellular mechanisms. Our systematic and high-throughput genetic workflow to characterize phage-host interaction determinants can be extended to diverse bacteria to generate datasets that allow predictive models of how phage-mediated selection will shape bacterial phenotype and evolution. The results of this study and future efforts to map the phage resistance landscape will lead to new insights into the coevolution of hosts and their phage, which can ultimately be used to design better phage therapeutic treatments and tools for precision microbiome engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Dead but Not Forgotten: How Extracellular DNA, Moisture, and Space Modulate the Horizontal Transfer of Extracellular Antibiotic Resistance Genes in Soil

Antibiotic-resistant bacteria and the spread of antibiotic resistance genes (ARGs) pose a serious risk to human and veterinary health. While many studies focus on the movement of live antibiotic-resistant bacteria to the environment, it is unclear whether extracellular ARGs (eARGs) from dead cells can transfer to live bacteria to facilitate the evolution of antibiotic resistance in nature. Here, we use eARGs from dead, antibiotic-resistant Pseudomonas stutzeri cells to track the movement of eARGs to live P. stutzeri cells via natural transformation, a mechanism of horizontal gene transfer involving the genomic integration of eARGs. In sterile, antibiotic-free agricultural soil, we manipulated the eARG concentration, soil moisture, and proximity to eARGs. We found that transformation occurred in soils inoculated with just 0.25 μg of eDNA g –1 soil, indicating that even low concentrations of soil eDNA can facilitate transformation (previous estimates suggested ~2 to 40 μg eDNA g –1 soil). When eDNA was increased to 5 μg g –1 soil, there was a 5-fold increase in the number of antibiotic-resistant P. stutzeri cells. We found that eARGs were transformed under soil moistures typical of terrestrial systems (5 to 30% gravimetric water content) but inhibited at very high soil moistures (>30%). Altogether, this work demonstrates that dead bacteria and their eARGs are an overlooked path to antibiotic resistance. More generally, the spread of eARGs in antibiotic-free soil suggests that transformation allows genetic variants to establish in the absence of antibiotic selection and that the soil environment plays a critical role in regulating transformation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Molecular basis of hemoglobin binding and heme removal in Corynebacterium diphtheriae

To successfully mount infections, nearly all bacterial pathogens must acquire iron, a key metal cofactor that primarily resides within human hemoglobin. Corynebacterium diphtheriae causes the life-threatening respiratory disease diphtheria and captures hemoglobin for iron scavenging using the surface-displayed receptor HbpA. Here, we show using X-ray crystallography, NMR, and in situ binding measurements that C. diphtheriae selectively captures iron-loaded hemoglobin by partially ensconcing the heme molecules of its α subunits. Quantitative growth and heme release measurements are compatible with C. diphtheriae acquiring heme passively released from hemoglobin’s β subunits. We propose a model in which HbpA and heme-binding receptors collectively function on the C. diphtheriae surface to capture hemoglobin and its spontaneously released heme. Acquisition mechanisms that exploit the propensity of hemoglobin’s β subunit to release heme likely represent a common strategy used by bacterial pathogens to obtain iron during infections.

NMR↗
DOE OSTI2022

Characterization of a 2016-2017 Human Seasonal H3 Influenza A Virus Spillover Now Endemic to U.S. Swine

In 2017, the Iowa State University Veterinary Diagnostic Laboratory detected a reverse-zoonotic transmission of a human seasonal H3 influenza A virus into swine (IAV-S) in Oklahoma. Pairwise comparison between the recently characterized human seasonal H3 IAV-S (H3.2010.2) hemagglutinin (HA) sequences detected in swine and the most similar 2016–2017 human seasonal H3 revealed 99.9% nucleotide identity. To elucidate the origin of H3.2010.2 IAV-S, 45 HA and 27 neuraminidase (NA) sequences from 2017 to 2020 as well as 11 whole-genome sequences (WGS) were genetically characterized. Time to most recent common human ancestor was estimated between August and September 2016. The N2 NA was of human origin in all but one strain from diagnostic submissions with NA sequences, and the internal gene segments from WGS consisted of matrix genes originating from the 2009 pandemic H1N1 and another 5 internal genes of triple reassortant swine origin (TTTTPT). Pigs experimentally infected with H3.2010.2 demonstrated efficient nasal shedding and replication in the lungs, mild pneumonia, and minimal microscopic lung lesions and transmitted the virus to indirect contact swine. Antigenically, H3.2010.2 viruses were closer to a human seasonal vaccine strain, A/Hong Kong/4801/2014, than to the H3.2010.1 human seasonal H3 viruses detected in swine in 2012. This was the second sustained transmission of a human seasonal IAV into swine from the 2010 decade after H3.2010.1. Monitoring the spillover and detection of novel IAV from humans to swine may help vaccine antigen selection and could impact pandemic preparedness.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Integration of genome-scale metabolic model with biorefinery process model reveals market-competitive carbon-negative sustainable aviation fuel utilizing microbial cell mass lipids and biogenic CO 2

Producing scalable, economically viable, low-carbon biofuels or biochemicals hinges on more efficient bioconversion processes. While microbial conversion can offer robust solutions, the native microbial growth process often redirects a large fraction of carbon to CO 2 and cell mass. By integrating genome-scale metabolic models with techno-economic and life cycle assessment models, this study analyzes the effects of converting cell mass lipids to hydrocarbon fuels, and CO 2 to methanol on the facility’s costs and life-cycle carbon footprint. Results show that upgrading microbial lipids or both microbial lipids and CO 2 using renewable hydrogen produces carbon-negative bisabolene. Additionally, on-site electrolytic hydrogen production offers a supply of pure oxygen to use in place of air for bioconversion and fuel combustion in the boiler. To reach cost parity with conventional jet fuel, renewable hydrogen needs to be produced at less than $\$2.2$ to $\$3.1$/kg, with a bisabolene yield of 80% of the theoretical yield, along with cell mass and CO 2 yields of 22 wt% and 54 wt%, respectively. The economic combination of cell mass, CO 2 , and bisabolene yields demonstrated in this study provides practical insights for prioritizing research, selecting suitable hosts, and determining necessary engineered production levels.

09 BIOMASS FUELS↗
DOE OSTI2019

Architecture of the chromatin remodeler RSC and insights into its nucleosome engagement

Eukaryotic DNA is packaged into nucleosome arrays, which are repositioned by chromatin remodeling complexes to control DNA accessibility. The Saccharomyces cerevisiae RSC (Remodeling the Structure of Chromatin) complex, a member of the SWI/SNF chromatin remodeler family, plays critical roles in genome maintenance, transcription, and DNA repair. Here, we report cryo-electron microscopy (cryo-EM) and crosslinking mass spectrometry (CLMS) studies of yeast RSC complex and show that RSC is composed of a rigid tripartite core and two flexible lobes. The core structure is scaffolded by an asymmetric Rsc8 dimer and built with the evolutionarily conserved subunits Sfh1, Rsc6, Rsc9 and Sth1. The flexible ATPase lobe, composed of helicase subunit Sth1, Arp7, Arp9 and Rtt102, is anchored to this core by the N-terminus of Sth1. Our cryo-EM analysis of RSC bound to a nucleosome core particle shows that in addition to the expected nucleosome-Sth1 interactions, RSC engages histones and nucleosomal DNA through one arm of the core structure, composed of the Rsc8 SWIRM domains, Sfh1 and Npl6. Our findings provide structural insights into the conserved assembly process for all members of the SWI/SNF family of remodelers, and illustrate how RSC selects, engages, and remodels nucleosomes.

59 BASIC BIOLOGICAL SCIENCES↗