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At least 271 records · Page 15

Tn-seq of Caulobacter crescentus under uranium stress reveals genes essential for detoxification and stress tolerance

Ubiquitous aquatic bacterium Caulobacter crescentus is highly resistant to uranium (U) and facilitates U biomineralization and thus holds promise as an agent of U bioremediation. In order to gain an understanding of how C. crescentus tolerates U, we employed transposon (Tn) mutagenesis paired with deep sequencing (Tn-seq) in a global screen for genomic elements required for U resistance. Of the 3,879 annotated genes in the C. crescentus genome, 37 were found to be specifically associated with fitness under U stress, 15 of which were subsequently tested through mutational analysis. Systematic deletion analysis revealed that mutants lacking outer membrane transporters (rsaFa and rsaFb), a stress-responsive transcription factor (cztR), or a ppGpp synthetase/hydrolase (spoT) exhibited a significantly lower survival rate under U stress. RsaFa and RsaFb, which are homologues of TolC in Escherichia coli, have previously been shown to mediate S-layer export. Transcriptional analysis revealed upregulation of rsaF a and rsaF b by 4- and 10-fold, respectively, in the presence of U. We additionally show that rsaFa mutants accumulated higher levels of U than the wild type, with no significant increase in oxidative stress levels. These results suggest a function for RsaF a and RsaF b in U efflux and/or maintenance of membrane integrity during U stress. In addition, we present data implicating CztR and SpoT in resistance to U stress. Together, our findings reveal novel gene targets that are key to understanding the molecular mechanisms of U resistance in C. crescentus.

59 BASIC BIOLOGICAL SCIENCES↗

Biostimulation and microbial community profiling reveal insights on RDX transformation in groundwater

Abstract Hexahydro‐1,3,5‐trinitro‐1,3,5‐triazine (RDX) is a high explosive released to the environment as a result of weapons manufacturing and testing worldwide. At Los Alamos National Laboratory, the Technical Area (TA) 16 260 Outfall discharged high‐explosives‐bearing water from a high‐explosives‐machining facility to Cañon de Valle during 1951 through 1996. These discharges served as a primary source of high‐explosives and inorganic‐element contamination in the area. Data indicate that springs, surface water, alluvial groundwater, and perched‐intermediate groundwater contain explosive compounds, including RDX (hexahydro‐1,3,5‐trinitro‐1,3,5‐triazine); HMX (octahydro‐1,3,5,7‐tetranitro‐1,3,5,7‐tetrazocine); and TNT (2,4,6‐trinitrotoluene). RDX has been detected in the regional aquifer in several wells, and a corrective measures evaluation is planned to identify remedial alternatives to protect the regional aquifer. Perched‐intermediate groundwater at Technical Area 16 is present at depths from 650 ft to 1200 ft bgs. In this study, we examined the microbial diversity in a monitoring well completed in perched‐intermediate groundwater contaminated by RDX, and examined the response of the microbial population to biostimulation under varying geochemical conditions. Results show that the groundwater microbiome was dominated by Actinobacteria and Proteobacteria . A total of 1,605 operational taxonomic units (OTUs) in 96 bacterial genera were identified. Rhodococcus was the most abundant genus (30.6%) and a total of 46 OTUs were annotated as Rhodococcus . One OTU comprising 25.2% of total sequences was closely related to a RDX ‐degrading strain R. erythropolis HS4. A less abundant OTU from the Pseudomonas family closely related to RDX‐degrading strain P. putida II‐B was also present. Biostimulation significantly enriched Proteobacteria but decreased/eliminated the population of Actinobacteria . Consistent with RDX degradation, the OTU closely related to the RDX‐degrading P. putida strain II‐B was specifically enriched in the RDX‐degrading samples. Analysis of the accumulation of RDX‐degradation products reveals that during active RDX degradation, there is a transient increase in the concentration of the degradation products MNX, DNX, TNX, and NDAB. The accumulation of these degradation products suggests that RDX is degraded via sequential reduction of the nitro functional groups followed by abiotic ring‐cleavage. The results suggest that strict anaerobic conditions are needed to stimulate RDX degradation under the TA‐16 site‐specific conditions.

59 BASIC BIOLOGICAL SCIENCES↗

Guided construction of single cell reference for human and mouse lung

Accurate cell type identification is a key and rate-limiting step in single-cell data analysis. Single-cell references with comprehensive cell types, reproducible and functionally validated cell identities, and common nomenclatures are much needed by the research community for automated cell type annotation, data integration, and data sharing. Here, we develop a computational pipeline utilizing the LungMAP CellCards as a dictionary to consolidate single-cell transcriptomic datasets of 104 human lungs and 17 mouse lung samples to construct LungMAP single-cell reference (CellRef) for both normal human and mouse lungs. CellRefs define 48 human and 40 mouse lung cell types catalogued from diverse anatomic locations and developmental time points. We demonstrate the accuracy and stability of LungMAP CellRefs and their utility for automated cell type annotation of both normal and diseased lungs using multiple independent methods and testing data. We develop user-friendly web interfaces for easy access and maximal utilization of the LungMAP CellRefs.

59 BASIC BIOLOGICAL SCIENCES↗

Genome-scale analysis of regulatory protein acetylation enzymes from photosynthetic eukaryotes

Background: Reversible protein acetylation occurring on Lys-Ne has emerged as a key regulatory post-translational modification in eukaryotes. It is mediated by two groups of enzymes: lysine acetyltransferases (KATs) and lysine deacetylases (KDACs) that catalyze the addition and removal of acetyl groups from target proteins. Estimates indicate that protein acetylation is second to protein phosphorylation in abundance, with thousands of acetylated sites now identified in different subcellular compartments. Considering the important regulatory role of protein phosphorylation, elucidating the diversity of KATs and KDACs across photosynthetic eukaryotes is essential in furthering our understanding of the impact of reversible protein acetylation on plant cell processes. Results: We report a genome-scale analysis of lysine acetyltransferase (KAT)- and lysine deacetylase (KDAC)-families from 53 photosynthetic eukaryotes. KAT and KDAC orthologs were identified in sequenced genomes ranging from glaucophytes and algae to land plants and then analyzed for evolutionary relationships. Based on consensus molecular phylogenetic and subcellular localization data we found new sub-classes of enzymes in established KAT- and KDAC-families. Specifically, we identified a non-photosynthetic origin of the HD-tuin family KDACs, a new monocot-specific Class I HDA-family sub-class, and a phylogenetically distinct Class II algal/heterokont sub-class which maintains an ankyrin domain not conserved in land plant Class II KDACs. Protein structure analysis showed that HDA- and SRT-KDACs exist as bare catalytic subunits with highly conserved median protein length, while all KATs maintained auxiliary domains, with CBP- and TAFII250-KATs displaying protein domain gain and loss over the course of photosynthetic eukaryote evolution in addition to variable protein length. Lastly, promoter element enrichment analyses across species revealed conserved cis-regulatory sequences that support KAT and KDAC involvement in the regulation of plant development, cold/drought stress response, as well as cellular processes such as the circadian clock. Conclusions: Our results reveal new evolutionary, structural, and biological insights into the KAT- and KDAC-families of photosynthetic eukaryotes, including evolutionary parallels to protein kinases and protein phosphatases. Further, we provide a comprehensive annotation framework through our extensive phylogenetic analysis, from which future research investigating aspects of protein acetylation in plants can use to position new findings in a broader context.

59 BASIC BIOLOGICAL SCIENCES↗

PaperBLAST: Text Mining Papers for Information about Homologs

With the recent explosion of genome sequencing data, there are now millions of uncharacterized proteins. If a scientist becomes interested in one of these proteins, it can be very difficult to find information as to its likely function. Often a protein whose sequence is similar, and which is likely to have a similar function, has been studied already, but this information is not available in any database. To help find articles about similar proteins, PaperBLAST searches the full text of scientific articles for protein identifiers or gene identifiers, and it links these articles to protein sequences. Then, given a protein of interest, it can quickly find similar proteins in its database by using standard software (BLAST), and it can show snippets of text from relevant papers. We hope that PaperBLAST will make it easier for biologists to predict proteins’ functions.

59 BASIC BIOLOGICAL SCIENCES↗

Glycan Reader is improved to recognize most sugar types and chemical modifications in the Protein Data Bank

Motivation: Glycans play a central role in many essential biological processes. Glycan Reader was originally developed to simplify the reading of Protein Data Bank (PDB) files containing glycans through the automatic detection and annotation of sugars and glycosidic linkages between sugar units and to proteins, all based on atomic coordinates and connectivity information. Carbohydrates can have various chemical modifications at different positions, making their chemical space much diverse. Unfortunately, current PDB files do not provide exact annotations for most carbohydrate derivatives and more than 50% of PDB glycan chains have at least one carbohydrate derivative that could not be correctly recognized by the original Glycan Reader. Results: Glycan Reader has been improved and now identifies most sugar types and chemical modifications (including various glycolipids) in the PDB, and both PDB and PDBx/mmCIF formats are supported. CHARMM-GUI Glycan Reader is updated to generate the simulation system and input of various glycoconjugates with most sugar types and chemical modifications. It also offers a new functionality to edit the glycan structures through addition/deletion/modification of glycosylation types, sugar types, chemical modifications, glycosidic linkages, and anomeric states. The simulation system and input files can be used for CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Glycan Fragment Database in GlycanStructure. Org is also updated to provide an intuitive glycan sequence search tool for complex glycan structures with various chemical modifications in the PDB.

Park, Sang-Jun↗

KBase Narrative - Porphyromonadaceae sp. W3.11 genome

Narratives for The phenotype and genotype of fermentative prokaryotes This is the Narrative for Porphyromonadaceae sp. W3.11. A complementary Narrative for Lachnospiraceae sp. C1.1 is available here. This is the Narrative for Lachnospiraceae sp. C1.1. A complementary Narrative for Porphyromonadaceae sp. W3.11 is available here. Background and Isolation This Narrative and its complementary Narrative contain assembly and annotation of two bacterial isolates that were isolated by our laboratory from the rumen of a Holstein heifer. All procedures with animals have been approved by University of California Davis’s Institutional Animal Care and Use Committee. Rumen contents were collected through a rumen fistula and strained through two layers of cheesecloth into a bottle. The bottle was sealed to exclude air and maintained at 39°C. Contents were brought to the laboratory and bubbled under O2-free CO2 within 15 min. At the laboratory, serial dilutions were made with anaerobic dilution solution for Lachnospiraceae sp. C1.1 and propionibacterium diluent for Porphyromonadaceae sp. W3.11 (table S2). Aliquots (0.1 ml) of each dilution were injected into anaerobic bottle plates (1) containing 9 ml of LH medium (table S2). After incubation at 37°C for 7 days, isolated colonies were picked. Lachnospiraceae sp. C1.1 was picked from a bottle inoculated with a 104 dilution of rumen contents, and Porphyromonadaceae sp. W3.11 was picked from a bottle inoculated with a 103 dilution. After initial isolation, these organisms were purified by growing on anaerobic roll tubes (2) and picking isolated colonies. We performed de novo sequencing of Lachnospiraceae sp. C1.1 and Porphyromonadaceae sp. W3.11. Aliquots of liquid culture (9 and 1.5 ml, respectively) were collected by syringe and centrifuged (21,000g for 10 min at 4°C). Cell pellets were submitted to Molecular Research LP for DNA extraction, library preparation, and sequencing. After resuspending pellets in 180 µl of ATL buffer (Qiagen), DNA was extracted using the MagAttract HMW DNA Kit (Qiagen). DNA was eluted in 100 µl of AE buffer (Qiagen) and then cleaned using the DNEasy PowerClean Pro Cleanup Kit (Qiagen). DNA was then sheared using the Covaris g-TUBE (Covaris). Sequencing libraries were prepared using the SMRTbell Express Template Prep Kit 2.0 (Pacific Biosciences) and 1500 ng of the sheared and purified DNA. The SMRTbell libraries were size-selected (>6 Kb) using a BluePippin instrument (Sage Science) and 0.75% agarose gel. Libraries were then sequenced using the PacBio Sequel II (Pacific Biosciences) platform and a 30-hour movie time. Narrative Summary In these Narratives, we filtered low-quality reads using Trimmomatic (v0.36), assembled filtered reads with SPAdes (v3.15.3), and then checked completeness and contamination of the assembled genomes with CheckM (v1.0.18). Statistics for sequencing and assembly are in table S3. Using the assembled contigs (genomes), we called genes and annotated them. Protein-coding genes were called using Prodigal (v2.6.3) (3) locally or using KBase via RASTtk (v1.073), with identical results. Genes were annotated with KO IDs using KAAS (4). They were further annotated with pfam and TIGRFAM IDs using KBase and the Annotate Domains in a Genome app. We classified putative genes for hydrogenases using HydDB. Genes for 16S ribosomal RNA (rRNA) were called using RASTtk (v1.073) in KBase. The contigs (genomes) were analyzed to determine whether they belonged to new species. Taxonomy was assigned using GTDB-Tk (v1.7.0) in KBase. The identity of 16S rRNA genes to other organisms was found using EzBioCloud (5). Values of digital DNA-DNA hybridization (dDDH) were found with Type (Strain) Genome Server (6). These analyses suggest that Lachnospiraceae sp. C1.1 and Porphyromonadaceae sp. W3.11 represent novel species or genera. GTDB-Tk assigned Lachnospiracae sp. C1.1 to family Lachnospiraceae and genus NK4A144, which contains no type strains. It assigned Porphyromonadaceae sp. W3.11 to Porphyromonadaceae and genus Porphyromonas_A. Values of 16S rRNA identity and dDDH with respect to type strains were low (table S4). Although more phenotypic data are needed, available evidence supports assignment of genomes to new species or genera. Related publication Hackmann TJ, Zhang B. The phenotype and genotype of fermentative prokaryotes. Sci Adv. 2023 Sep 29;9(39):eadg8687. doi: 10.1126/sciadv.adg8687. Epub 2023 Sep 27. PMID: 37756392; PMCID: PMC10530074.

Hackmann, Timothy↗

KBase Narrative - Lachnospiraceae sp. C1.1 genome

Narratives for The phenotype and genotype of fermentative prokaryotes This is the Narrative for Porphyromonadaceae sp. W3.11. A complementary Narrative for Lachnospiraceae sp. C1.1 is available here. This is the Narrative for Lachnospiraceae sp. C1.1. A complementary Narrative for Porphyromonadaceae sp. W3.11 is available here. Background and Isolation This Narrative and its complementary Narrative contain assembly and annotation of two bacterial isolates that were isolated by our laboratory from the rumen of a Holstein heifer. All procedures with animals have been approved by University of California Davis’s Institutional Animal Care and Use Committee. Rumen contents were collected through a rumen fistula and strained through two layers of cheesecloth into a bottle. The bottle was sealed to exclude air and maintained at 39°C. Contents were brought to the laboratory and bubbled under O2-free CO2 within 15 min. At the laboratory, serial dilutions were made with anaerobic dilution solution for Lachnospiraceae sp. C1.1 and propionibacterium diluent for Porphyromonadaceae sp. W3.11 (table S2). Aliquots (0.1 ml) of each dilution were injected into anaerobic bottle plates (1) containing 9 ml of LH medium (table S2). After incubation at 37°C for 7 days, isolated colonies were picked. Lachnospiraceae sp. C1.1 was picked from a bottle inoculated with a 104 dilution of rumen contents, and Porphyromonadaceae sp. W3.11 was picked from a bottle inoculated with a 103 dilution. After initial isolation, these organisms were purified by growing on anaerobic roll tubes (2) and picking isolated colonies. We performed de novo sequencing of Lachnospiraceae sp. C1.1 and Porphyromonadaceae sp. W3.11. Aliquots of liquid culture (9 and 1.5 ml, respectively) were collected by syringe and centrifuged (21,000g for 10 min at 4°C). Cell pellets were submitted to Molecular Research LP for DNA extraction, library preparation, and sequencing. After resuspending pellets in 180 µl of ATL buffer (Qiagen), DNA was extracted using the MagAttract HMW DNA Kit (Qiagen). DNA was eluted in 100 µl of AE buffer (Qiagen) and then cleaned using the DNEasy PowerClean Pro Cleanup Kit (Qiagen). DNA was then sheared using the Covaris g-TUBE (Covaris). Sequencing libraries were prepared using the SMRTbell Express Template Prep Kit 2.0 (Pacific Biosciences) and 1500 ng of the sheared and purified DNA. The SMRTbell libraries were size-selected (>6 Kb) using a BluePippin instrument (Sage Science) and 0.75% agarose gel. Libraries were then sequenced using the PacBio Sequel II (Pacific Biosciences) platform and a 30-hour movie time. Narrative Summary In these Narratives, we filtered low-quality reads using Trimmomatic (v0.36), assembled filtered reads with SPAdes (v3.15.3), and then checked completeness and contamination of the assembled genomes with CheckM (v1.0.18). Statistics for sequencing and assembly are in table S3. Using the assembled contigs (genomes), we called genes and annotated them. Protein-coding genes were called using Prodigal (v2.6.3) (3) locally or using KBase via RASTtk (v1.073), with identical results. Genes were annotated with KO IDs using KAAS (4). They were further annotated with pfam and TIGRFAM IDs using KBase and the Annotate Domains in a Genome app. We classified putative genes for hydrogenases using HydDB. Genes for 16S ribosomal RNA (rRNA) were called using RASTtk (v1.073) in KBase. The contigs (genomes) were analyzed to determine whether they belonged to new species. Taxonomy was assigned using GTDB-Tk (v1.7.0) in KBase. The identity of 16S rRNA genes to other organisms was found using EzBioCloud (5). Values of digital DNA-DNA hybridization (dDDH) were found with Type (Strain) Genome Server (6). These analyses suggest that Lachnospiraceae sp. C1.1 and Porphyromonadaceae sp. W3.11 represent novel species or genera. GTDB-Tk assigned Lachnospiracae sp. C1.1 to family Lachnospiraceae and genus NK4A144, which contains no type strains. It assigned Porphyromonadaceae sp. W3.11 to Porphyromonadaceae and genus Porphyromonas_A. Values of 16S rRNA identity and dDDH with respect to type strains were low (table S4). Although more phenotypic data are needed, available evidence supports assignment of genomes to new species or genera. Related publication Hackmann TJ, Zhang B. The phenotype and genotype of fermentative prokaryotes. Sci Adv. 2023 Sep 29;9(39):eadg8687. doi: 10.1126/sciadv.adg8687. Epub 2023 Sep 27. PMID: 37756392; PMCID: PMC10530074.

Hackmann, Timothy↗

P finder: genomic and metagenomic annotation of RNase P RNA gene (rnpB)

Abstract Background The rnpB gene encodes for an essential catalytic RNA (RNase P). Like other essential RNAs, RNase P’s sequence is highly variable. However, unlike other essential RNAs (i.e. tRNA, 16 S, 6 S,...) its structure is also variable with at least 5 distinct structure types observed in prokaryotes. This structural variability makes it labor intensive and challenging to create and maintain covariance models for the detection of RNase P RNA in genomic and metagenomic sequences. The lack of a facile and rapid annotation algorithm has led to the rnpB gene being the most grossly under annotated essential gene in completed prokaryotic genomes with only a 24% annotation rate. Here we describe the coupling of the largest RNase P RNA database with the local alignment scoring algorithm to create the most sensitive and rapid prokaryote rnpB gene identification and annotation algorithm to date. Results Of the 2772 completed microbial genomes downloaded from GenBank only 665 genomes had an annotated rnpB gene. We applied P Finder to these genomes and were able to identify 2733 or nearly 99% of the 2772 microbial genomes examined. From these results four new rnpB genes that encode the minimal T-type P RNase P RNAs were identified computationally for the first time. In addition, only the second C-type RNase P RNA was identified in Sphaerobacter thermophilus . Of special note, no RNase P RNAs were detected in several obligate endosymbionts of sap sucking insects suggesting a novel evolutionary adaptation. Conclusions The coupling of the largest RNase P RNA database and associated structure class identification with the P Finder algorithm is both sensitive and rapid, yielding high quality results to aid researchers annotating either genomic or metagenomic data. It is the only algorithm to date that can identify challenging RNAse P classes such as C-type and the minimal T-type RNase P RNAs. P Finder is written in C# and has a user-friendly GUI that can run on multiple 64-bit windows platforms (Windows Vista/7/8/10). P Finder is free available for download at https://github.com/JChristopherEllis/P-Finder as well as a small sample RNase P RNA file for testing.

59 BASIC BIOLOGICAL SCIENCES↗

Reekeekee- and roodoodooviruses, two different Microviridae clades constituted by the smallest DNA phages

Small circular single-stranded DNA viruses of the Microviridae family are both prevalent and diverse in all ecosystems. They usually harbor a genome between 4.3 and 6.3 kb, with a microvirus recently isolated from a marine Alphaproteobacteria being the smallest known genome of a DNA phage (4.248 kb). A subfamily, Amoyvirinae, has been proposed to classify this virus and other related small Alphaproteobacteria-infecting phages. Here, we report the discovery, in meta-omics data sets from various aquatic ecosystems, of sixteen complete microvirus genomes significantly smaller (2.991–3.692 kb) than known ones. Phylogenetic analysis reveals that these sixteen genomes represent two related, yet distinct and diverse, novel groups of microviruses—amoyviruses being their closest known relatives. We propose that these small microviruses are members of two tentatively named subfamilies Reekeekeevirinae and Roodoodoovirinae. As known microvirus genomes encode many overlapping and overprinted genes that are not identified by gene prediction software, we developed a new methodology to identify all genes based on protein conservation, amino acid composition, and selection pressure estimations. Surprisingly, only four to five genes could be identified per genome, with the number of overprinted genes lower than that in phiX174. These small genomes thus tend to have both a lower number of genes and a shorter length for each gene, leaving no place for variable gene regions that could harbor overprinted genes. Even more surprisingly, these two Microviridae groups had specific and different gene content, and major differences in their conserved protein sequences, highlighting that these two related groups of small genome microviruses use very different strategies to fulfill their lifecycle with such a small number of genes. The discovery of these genomes and the detailed prediction and annotation of their genome content expand our understanding of ssDNA phages in nature and are further evidence that these viruses have explored a wide range of possibilities during their long evolution.

59 BASIC BIOLOGICAL SCIENCES↗

Strategies to improve reference databases for soil microbiomes

A database of curated genomes is needed to better assess soil microbial communities and their processes associated with differing land management and environmental impacts. Interpreting soil metagenomic datasets with existing sequence databases is challenging because these datasets are biased towards medical and biotechnology research and can result in misleading annotations. We have curated a database of 928 genomes of soil-associated organisms (888 bacteria, 34 archaea, and 6 fungi). Using this database as a representation of the current state of knowledge of soil microbes that are well-characterized, we evaluated its composition and compared it to broader microbial databases, specifically NCBI’s RefSeq, as well as 3,035 publicly available soil amplicon datasets. These comparisons identified phyla and functions that are enriched in soils as well as those that may be underrepresented in RefSoil. For example, RefSoil was observed to have increased representation of Firmicutes despite its low abundance in soil environments and also lacked representation of Acidobacteria and Verrucomicrobia, which are abundant in soils. Our comparison of RefSoil to soil amplicon datasets allowed us to identify targets that if cultured or sequenced would significantly increase the biodiversity represented within RefSoil. To demonstrate the opportunities to access these underrepresented targets, we employed single cell genomics in a pilot experiment to recover 14 genomes from the "most wanted" list, which improved RefSoil's representation of EMP sequences by 7% by abundance. This effort demonstrates the value of RefSoil in the guidance of future research efforts and the capability of single cell genomics as a practical means to fill the existing genomic data gaps.

59 BASIC BIOLOGICAL SCIENCES↗

Structural and Functional Characterization of YdjI, an Aldolase of Unknown Specificity in Escherichia coli K12

The ydj gene cluster is found in 80% of sequenced Escherichia coli genomes and other closely related species in the human microbiome. On the basis of the annotations of the enzymes located in this cluster, it is expected that together they catalyze the catabolism of an unknown carbohydrate. The focus of this investigation is on YdjI, which is in the ydj gene cluster of E. coli K-12. It is predicted to be a class II aldolase of unknown function. Here we describe a structural and functional characterization of this enzyme. YdjI catalyzes the hydrogen/deuterium exchange of the pro- S hydrogen at C3 of dihydroxyacetone phosphate (DHAP). In the presence of DHAP, YdjI catalyzes an aldol condensation with a variety of aldo sugars. YdjI shows a strong preference for higher-order (seven-, eight-, and nine-carbon) monosaccharides with specific hydroxyl stereochemistries and a negatively charged terminus (carboxylate or phosphate). The best substrate is l -arabinuronic acid with an apparent k cat of 3.0 s –1 . The product, l - glycero - l - galacto -octuluronate-1-phosphate, has a k cat / K m value of 2.1 × 10 3 M –1 s –1 in the retro-aldol reaction with YdjI. This is the first recorded synthesis of l - glycero - l - galacto -octuluronate-1-phosphate and six similar carbohydrates. The crystal structure of YdjI, determined to a nominal resolution of 1.75 Å (Protein Data Bank entry 6OFU ), reveals unusual positions for two arginine residues located near the active site. Furthermore, computational docking was utilized to distinguish preferable binding orientations for l - glycero - l - galacto -octuluronate-1-phosphate. These results indicate a possible alternative binding orientation for l - glycero - l - galacto -octuluronate-1-phosphate compared to that observed in other class II aldolases, which utilize shorter carbohydrate molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The landscape of Chlamydomonas histone H3 lysine 4 methylation reveals both constant features and dynamic changes during the diurnal cycle

Chromatin modifications are epigenetic regulatory features with major roles in various cellular events, yet they remain understudied in algae. Here, we interrogated the genome-wide distribution pattern of mono- and trimethylated histone H3 lysine 4 (H3K4) using chromatin-immunoprecipitation followed by deep-sequencing (ChIP-seq) during key phases of the Chlamydomonas cell cycle: early G 1 phase, Zeitgeber Time 1 (ZT1), when cells initiate biomass accumulation, S/M phase (ZT13) when cells are replicating DNA and undergoing mitosis, and late G 0 phase (ZT23) when they are quiescent. Tri-methylated H3K4 was predominantly enriched at transcription start sites of the majority of protein coding genes (85%). The likelihood of a gene being marked by H3K4me3 correlated with it being transcribed at some point during the life cycle but not necessarily by continuous active transcription, as exemplified by early zygotic genes, which may remain transcriptionally dormant for thousands of generations between sexual cycles. The exceptions to this rule were around 120 loci, some of which encode non-poly-adenylated transcripts, such as small nuclear RNAs and replication-dependent histones that had H3K4me3 peaks only when they were being transcribed. Mono-methylated H3K4 was the default state for the vast majority of histones that were bound outside of transcription start sites and terminator regions of genes. A small fraction of the genome that was depleted of any H3 lysine 4 methylation was enriched for DNA cytosine methylation and the genes within these DNA methylation islands were poorly expressed. Besides marking protein coding genes, H3K4me3 ChIP-seq data served also as a annotation tool for validation of hundreds of long non-coding RNA genes.

59 BASIC BIOLOGICAL SCIENCES↗

Semi-supervised permutation invariant particle-level anomaly detection

The development of analysis methods to distinguish potential beyond the Standard Model phenomena in a model-agnostic way can significantly enhance the discovery reach in collider experiments. However, the typical machine learning (ML) algorithms employed for this task require fixed length and ordered inputs that break the natural permutation invariance in collision events. To address this, a semi-supervised anomaly detection tool is presented that takes a variable number of particle-level inputs and leverages a signal model to encode this information into a permutation invariant, event-level representation via supervised training with a Particle Flow Network (PFN). Data events are then encoded into this representation and given as input to an autoencoder for unsupervised ANomaly deTEction on particLe flOw latent sPacE (ANTELOPE), classifying anomalous events based on a low-level and permutation invariant input modeling. Performance of the ANTELOPE architecture is evaluated on simulated samples of hadronic processes in a high energy collider experiment, showing good capability to distinguish disparate models of new physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Evaluation of genetic diversity, agronomic traits, and anthracnose resistance in the NPGS Sudan Sorghum Core collection

The United States Department of Agriculture (USDA) National Plant Germplasm System (NPGS) sorghum core collection contains 3011 accessions randomly selected from 77 countries. Genomic and phenotypic characterization of this core collection is necessary to encourage and facilitate its utilization in breeding programs and to improve conservation efforts. In this study, we examined the genome sequences of 318 accessions belonging to the NPGS Sudan sorghum core set, and characterized their agronomic traits and anthracnose resistance response. We identified 183,144 single nucleotide polymorphisms (SNPs) located within or in proximity of 25,124 annotated genes using the genotyping-by-sequencing (GBS) approach. The core collection was genetically highly diverse, with an average pairwise genetic distance of 0.76 among accessions. Population structure and cluster analysis revealed five ancestral populations within the Sudan core set, with moderate to high level of genetic differentiation. In total, 171 accessions (54%) were assigned to one of these populations, which covered 96% of the total genomic variation. Genome scan based on Tajima’s D values revealed two populations under balancing selection. Phenotypic analysis showed differences in agronomic traits among the populations, suggesting that these populations belong to different ecogeographical regions. A total of 55 accessions were resistant to anthracnose; these accessions could represent multiple resistance sources. Genome-wide association study based on fixed and random model Circulating Probability (farmCPU) identified genomic regions associated with plant height, flowering time, panicle length and diameter, and anthracnose resistance response. Integrated analysis of the Sudan core set and sorghum association panel indicated that a large portion of the genetic variation in the Sudan core set might be present in breeding programs but remains unexploited within some clusters of accessions. The NPGS Sudan core collection comprises genetically and phenotypically diverse germplasm with multiple anthracnose resistance sources. Population genomic analysis could be used to improve screening efforts and identify the most valuable germplasm for breeding programs. The new GBS data set generated in this study represents a novel genomic resource for plant breeders interested in mining the genetic diversity of the NPGS sorghum collection.

59 BASIC BIOLOGICAL SCIENCES↗

A high-resolution single-molecule sequencing-based Arabidopsis transcriptome using novel methods of Iso-seq analysis

Accurate and comprehensive annotation of transcript sequences is essential for transcript quantification and differential gene and transcript expression analysis. Single-molecule long-read sequencing technologies provide improved integrity of transcript structures including alternative splicing, and transcription start and polyadenylation sites. However, accuracy is significantly affected by sequencing errors, mRNA degradation, or incomplete cDNA synthesis. We present a new and comprehensive Arabidopsis thaliana Reference Transcript Dataset 3 (AtRTD3). AtRTD3 contains over 169,000 transcripts—twice that of the best current Arabidopsis transcriptome and including over 1500 novel genes. Seventy-eight percent of transcripts are from Iso-seq with accurately defined splice junctions and transcription start and end sites. We develop novel methods to determine splice junctions and transcription start and end sites accurately. Mismatch profiles around splice junctions provide a powerful feature to distinguish correct splice junctions and remove false splice junctions. Stratified approaches identify high-confidence transcription start and end sites and remove fragmentary transcripts due to degradation. AtRTD3 is a major improvement over existing transcriptomes as demonstrated by analysis of an Arabidopsis cold response RNA-seq time-series. AtRTD3 provides higher resolution of transcript expression profiling and identifies cold-induced differential transcription start and polyadenylation site usage. AtRTD3 is the most comprehensive Arabidopsis transcriptome currently. It improves the precision of differential gene and transcript expression, differential alternative splicing, and transcription start/end site usage analysis from RNA-seq data. The novel methods for identifying accurate splice junctions and transcription start/end sites are widely applicable and will improve single-molecule sequencing analysis from any species.

transcription start and end sites↗

Gene co-expression network analysis in Rhodobacter capsulatus and application to comparative expression analysis of Rhodobacter sphaeroides

The genus Rhodobacter contains purple nonsulfur bacteria found mostly in freshwater environments. Representative strains of two Rhodobacter species, R. capsulatus and R. sphaeroides, have had their genomes fully sequenced and both have been the subject of transcriptional profiling studies. Gene co-expression networks can be used to identify modules of genes with similar expression profiles. Functional analysis of gene modules can then associate co-expressed genes with biological pathways, and network statistics can determine the degree of module preservation in related networks. In this paper, we constructed an R. capsulatus gene co-expression network, performed functional analysis of identified gene modules, and investigated preservation of these modules in R. capsulatus proteomics data and in R. sphaeroides transcriptomics data. Results: The analysis identified 40 gene co-expression modules in R. capsulatus. Investigation of the module gene contents and expression profiles revealed patterns that were validated based on previous studies supporting the biological relevance of these modules. We identified two R. capsulatus gene modules preserved in the protein abundance data. We also identified several gene modules preserved between both Rhodobacter species, which indicate that these cellular processes are conserved between the species and are candidates for functional information transfer between species. Many gene modules were non-preserved, providing insight into processes that differentiate the two species. In addition, using Local Network Similarity (LNS), a recently proposed metric for expression divergence, we assessed the expression conservation of between-species pairs of orthologs, and within-species gene-protein expression profiles. Conclusions: Our analyses provide new sources of information for functional annotation in R. capsulatus because uncharacterized genes in modules are now connected with groups of genes that constitute a joint functional annotation. We identified R. capsulatus modules enriched with genes for ribosomal proteins, porphyrin and bacteriochlorophyll anabolism, and biosynthesis of secondary metabolites to be preserved in R. sphaeroides whereas modules related to RcGTA production and signalling showed lack of preservation in R. sphaeroides. In addition, we demonstrated that network statistics may also be applied within-species to identify congruence between mRNA expression and protein abundance data for which simple correlation measurements have previously had mixed results.

Comparative transcriptomics, Module preservation, ↗

Integrative Modeling and Analysis of Fungal Central Carbon Metabolism

Over a thousand fungal genomes have been sequenced, yet manually curated genome-scale metabolic models (GEMs) are available for only a limited number of species. Moreover, these models have often been developed independently, leading to inconsistencies in namespaces, compartment definitions, and pathway representations that hinder comparative analysis, the systematic reuse of prior curation efforts, and the integration of consolidated metabolic knowledge. Here, we present the Consolidated Fungal Core Metabolism Model (CFCMM), constructed by integrating thirteen published fungal models spanning Ascomycota, Mucoromycota, and both Crabtree-positive and Crabtree-negative yeasts. We harmonized metabolites and reactions into a non-redundant shared ModelSEED ontological space, standardized compartmentalization, and refined gene–protein–reaction (GPR) rules. Using pathway-level visualization and systematic gap detection, we further improved the integrated network through literature-guided curation to correct stoichiometry, stereospecificity, and pathway architecture. Orthologous protein family reconstruction and functional annotation workflows were used to validate and inform GPR associations, with particular emphasis on ambiguous enzyme superfamilies and membrane-associated components. Using the resulting CFCMM, we built high-quality central carbon core models for each fungus and performed flux balance analysis to quantify ATP-yield variation under aerobic and anaerobic conditions, explicitly evaluating scenarios driven by differences in electron transport chain (ETC) composition. Simulations reproduced the expected fermentative yield of approximately 2 mmol ATP per mmol glucose under anaerobic conditions and separated the thirteen fungi into two bioenergetic groups under aerobic respiration based on Complex I status, with predicted yields of approximately 30 versus 22 mmol ATP per mmol glucose. Forcing flux through the alternative oxidase bypass further reduced ATP yields to approximately 12 and 4 mmol ATP per mmol glucose in Complex I-containing and Complex I-lacking fungi, respectively. Collectively, this work provides a manually curated, ModelSEED-consistent, and extensible fungal core metabolic template, deployed in DOE KBase as a resource for automated reconstruction of central carbon core models from any sequenced fungal genome. In addition, the CFCMM provides modular components for developing GEMs with more accurate energy predictions and enables robust comparative analyses of fungal bioenergetics and core metabolic diversity

59 BASIC BIOLOGICAL SCIENCES↗