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At least 91 records · Page 5

Identification of shared viral sequences in peat moss metagenomes reveals elements of a possible Sphagnum core virome

Viruses are an understudied component of plant microbiomes. Identifying viruses that are shared between individual plants, or members of the “core virome”, could reveal stable viral populations with the potential to modulate the composition and function of the microbiome. Here, we examined the virome associated with Sphagnum mosses, a keystone species that has direct influence over the fate of peatland carbon stores. We analyzed bulk metagenomes and metatranscriptomes generated from Sphagnum field samples collected over a ten-month period to identify virus-like sequences shared among plants. Individual Sphagnum samples harbored distinct DNA and RNA viromes where only a small percentage (< 1%) of the total number of identified viral contigs were shared among all samples. Based on taxonomic classification, the shared viral contigs represent bacterial viruses, or phage (Caudoviricetes), as well as viruses of eukaryotes, namely nucleocytoplasmic large DNA viruses (Nucleocytoviricota) and RNA viruses (Riboviria). We linked the shared phage-like contigs to viral regions within sequenced genomes of bacterial taxa that are members of the Sphagnum core microbiome, suggesting that these contigs represent temperate phage or degraded prophage. The putative nucleocytoplasmic large DNA viruses and RNA viruses were phylogenetically diverse and showed sequence similarity to viruses associated with a broad range of hosts and environmental sources. The identification of shared viral contigs suggested that, despite the compositional heterogeneity between samples, Sphagnum mosses may harbor a core virome. Future work validating the presence of the core virome is warranted as it may aid in understanding how persistent viruses impact microbiome ecology and symbiont evolution within this climatically relevant keystone species.

Metagenomics↗

Luteolibacter sp. strain Populi

Luteolibacter sp. strain Populi is bacterium from the phylum Verrucomicrobiota, isolated from the rhizosphere of a black cottonwood tree, Populus trichocarpa, from the Cascade mountains in Washington. Its 6.6 Mb chromosome was completely sequenced using Oxford Nanopore long-reads and is predicted to encode 5301 proteins and 60 RNAs. The bacteria was isolated from the rhizosphere of a mature Populus trichocarpa from the Tieton riverwatershed of Washington state, USA (Lat: 46°42’9” N, Lon: 120°25 39’36” W). A rhizosphere sample (fine roots and adhering soil) was used to obtain a microbial fraction by centrifugation on Histodenz (12) and stained with 5µM Syto59 (Thermo Fisher Scientific Inc). A Cytopeia Influx cell sorter (BD, Franklin Lakes, NJ) was used to sort and array single cells (100 per plate) based on forward-side scatter and fluorescence intensity on asparagine-glucose nutrient agar (ATCC medium 184). The Luteolibacter sp. Populi genome sequence has been deposited in GenBank under the accession number CP161812. A draft genome annotated with Prokka and DRAM is available in this Narrative as Luteolibacter_sp_Prokka.240711.

59 BASIC BIOLOGICAL SCIENCES↗

The genomic footprints of wild Saccharum species trace domestication, diversification, and modern breeding of sugarcane

Sugarcane is a major crop of unclear origins due to its complex polyploid interspecific genome. We analyzed genome ancestries using whole-genome sequence data from 390 representative accessions based on repeated k-mers and chloroplast phylogeny. The results provided evidence that Saccharum officinarum was domesticated in the New Guinea region from the S. robustum wild species and revealed that its genome is a mosaic involving different S. robustum subgroups. We discovered a wild Saccharum contributor to most modern cultivars, likely originating from East Melanesia. We highlighted two early centers of sugarcane diversification associated with human transport, one in continental Asia through hybridization with different S. spontaneum subgroups and one in the Melanesian and Polynesian islands via hybridization with the discovered ancestor and Miscanthus. Finally, we revealed the genome ancestry of modern cultivars, highlighting untapped wild Saccharum diversity as a source of alleles for breeding programs.

Garsmeur, Olivier [CIRAD, Montpellier (France). Ag↗

The genome of the polyextremophilic yeast, Naganishia friedmannii, reveals adaptations involved in stress response pathways, carbohydrate metabolism expansion, and a limited DNA repair repertoire

Here we report the draft genome sequence of Naganishia friedmannii (formerly Cryptococcus friedmannii) isolate, a Basidiomycota yeast commonly found in some of the most extreme environments of the Earth's cryosphere. We isolated N. friedmannii strain Llullensis from soils at 6000 m above sea level on Volcán Llullaillaco, Argentina. The genome was 22.2 Mb with 6251 identified protein coding genes. Proteins known to be associated with thermal, osmotic, and radiation stress were identified in the genome. Comparative analysis with seven other Naganishia genomes revealed unique features underlying its polyextremophilic lifestyle. Naganishia friedmannii showed an expansion of genes involved in breaking down plant-derived carbohydrates, supporting the hypothesis that it survives at high elevations by metabolizing wind-deposited organic matter. Surprisingly, many genes involved in cell-cycle checkpoints and DNA repair were missing, as in several other Naganishia species. This extensive loss may be adaptive in extreme environments prone to abiotic stress, where a high mutation rate could generate advantageous traits, and reduced cell-cycle control may allow for faster reproduction that would be advantageous for rapid growth during brief periods of soil wetting following rare snow events.

Vimercati, Lara↗

Comparative Analysis of DNA LLM Classification Techniques Using Intra-Layer Feature Extraction with Autoencoder Stacks [Poster]

This project conducts a comparative analysis of DNA LLM classification techniques using Evo2, Grover, and UTRML, focusing on intra-layer feature extraction in Evo2. By extracting features from multiple layers of Evo2 and integrating them into an autoencoder stack with a binary classification head, we evaluate its effectiveness in classifying genomic sequences compared to smaller DNA language models. My findings demonstrate that Evo2 outperforms Grover and UTRML in classification accuracy on a dataset provided by department 08625, CAO2021, while UTRML offers competitive performance with lower computational costs. This study highlights the potential of advanced embedding techniques in enhancing genomic data analysis and informs future research in bioinformatics.

59 BASIC BIOLOGICAL SCIENCES↗

Myco-Ed: Mycological curriculum for education and discovery

Fungi are important and hyperdiverse organisms, yet chronically understudied. Most fungal clades have no reference genomes, impeding our understanding of their ecosystem functions and use as solutions in health and biotechnology. Also, opportunities for training in fungal biology and genomics are lacking, creating a bottleneck that hinders the recruitment and cultivation of a talented future mycological workforce. To address these issues, we developed Myco-Ed, an educational program offering training and scientific contributions through genome sequencing and analysis. Myco-Ed empowers students to pursue careers in fungal biology while improving fungal resources. Myco-Ed has been piloted at 12 institutions (15 classrooms) ranging from online e-Campuses to R1 universities, resulting in hundreds of fungal observations and many new high-quality reference genomes.

Branco, Sara↗

Leptothrix ochracea genomes reveal potential for mixotrophic growth on Fe(II) and organic carbon

ABSTRACT Leptothrix ochracea creates distinctive iron-mineralized mats that carpet streams and wetlands. Easily recognized by its iron-mineralized sheaths, L. ochracea was one of the first microorganisms described in the 1800s. Yet it has never been isolated and does not have a complete genome sequence available, so key questions about its physiology remain unresolved. It is debated whether iron oxidation can be used for energy or growth and if L. ochracea is an autotroph, heterotroph, or mixotroph. To address these issues, we sampled L. ochracea -rich mats from three of its typical environments (a stream, wetlands, and a drainage channel) and reconstructed nine high-quality genomes of L. ochracea from metagenomes. These genomes contain iron oxidase genes cyc2 and mtoA, showing that L. ochracea has the potential to conserve energy from iron oxidation. Sox genes confer potential to oxidize sulfur for energy. There are genes for both carbon fixation (RuBisCO) and utilization of sugars and organic acids (acetate, lactate, and formate). In silico stoichiometric metabolic models further demonstrated the potential for growth using sugars and organic acids. Metatranscriptomes showed a high expression of genes for iron oxidation; aerobic respiration; and utilization of lactate, acetate, and sugars, as well as RuBisCO, supporting mixotrophic growth in the environment. In summary, our results suggest that L. ochracea has substantial metabolic flexibility. It is adapted to iron-rich, organic carbon-containing wetland niches, where it can thrive as a mixotrophic iron oxidizer by utilizing both iron oxidation and organics for energy generation and both inorganic and organic carbon for cell and sheath production. IMPORTANCE Winogradsky's observations of L. ochracea led him to propose autotrophic iron oxidation as a new microbial metabolism, following his work on autotrophic sulfur-oxidizers. While much culture-based research has ensued, isolation proved elusive, so most work on L. ochracea has been based in the environment and in microcosms. Meanwhile, the autotrophic Gallionella became the model for freshwater microbial iron oxidation, while heterotrophic and mixotrophic iron oxidation is not well-studied. Ecological studies have shown that Leptothrix overtakes Gallionella when dissolved organic carbon content increases, demonstrating distinct niches. This study presents the first near-complete genomes of L. ochracea , which share some features with autotrophic iron oxidizers, while also incorporating heterotrophic metabolisms. These genome, metabolic modeling, and transcriptome results give us a detailed metabolic picture of how the organism may combine lithoautotrophy with organoheterotrophy to promote Fe oxidation and C cycling and drive many biogeochemical processes resulting from microbial growth and iron oxyhydroxide formation in wetlands.

59 BASIC BIOLOGICAL SCIENCES↗

OrthoPhyl—streamlining large-scale, orthology-based phylogenomic studies of bacteria at broad evolutionary scales

Abstract There are a staggering number of publicly available bacterial genome sequences (at writing, 2.0 million assemblies in NCBI's GenBank alone), and the deposition rate continues to increase. This wealth of data begs for phylogenetic analyses to place these sequences within an evolutionary context. A phylogenetic placement not only aids in taxonomic classification but informs the evolution of novel phenotypes, targets of selection, and horizontal gene transfer. Building trees from multi-gene codon alignments is a laborious task that requires bioinformatic expertise, rigorous curation of orthologs, and heavy computation. Compounding the problem is the lack of tools that can streamline these processes for building trees from large-scale genomic data. Here we present OrthoPhyl, which takes bacterial genome assemblies and reconstructs trees from whole genome codon alignments. The analysis pipeline can analyze an arbitrarily large number of input genomes (>1200 tested here) by identifying a diversity-spanning subset of assemblies and using these genomes to build gene models to infer orthologs in the full dataset. To illustrate the versatility of OrthoPhyl, we show three use cases: E. coli/Shigella, Brucella/Ochrobactrum and the order Rickettsiales. We compare trees generated with OrthoPhyl to trees generated with kSNP3 and GToTree along with published trees using alternative methods. We show that OrthoPhyl trees are consistent with other methods while incorporating more data, allowing for greater numbers of input genomes, and more flexibility of analysis.

59 BASIC BIOLOGICAL SCIENCES↗

Genomes OnLine Database (GOLD) v.10: new features and updates

The Genomes OnLine Database (GOLD; https://gold.jgi.doe.gov/) at the Department of Energy Joint Genome Institute is a comprehensive online metadata repository designed to catalog and manage information related to (meta)genomic sequence projects. GOLD provides a centralized platform where researchers can access a wide array of metadata from its four organization levels namely Study, Organism/Biosample, Sequencing Project and Analysis Project. GOLD continues to serve as a valuable resource and has seen significant growth and expansion since its inception in 1997. With its expanded role as a collaborative platform, it not only actively imports data from other primary repositories like National Center for Biotechnology Information but also supports contributions from researchers worldwide. This collaborative approach has enriched the database with diverse datasets, creating a more integrated resource to enhance scientific insights. As genomic research becomes increasingly integral to various scientific disciplines, more researchers and institutions are turning to GOLD for their metadata needs. To meet this growing demand, GOLD has expanded by adding diverse metadata fields, intuitive features, advanced search capabilities and enhanced data visualization tools, making it easier for users to find and interpret relevant information. This manuscript provides an update and highlights the new features introduced over the last 2 years.

59 BASIC BIOLOGICAL SCIENCES↗

Linking Spatiotemporal Biological Data to Predict Harmful Algal Blooms

Cyanobacterial Harmful Algal Blooms (cHABs) have significant impacts on an affected region’s economy, ecology, and human health. The blooms can release toxins that kill fish and poison water for people and animals. The global adverse effects of cHABs are exacerbated by the consequences of climate change and increased pollution. Though the phenomena are well documented, scientists’ efforts to mitigate the damage are hampered by insufficient predictive models and incomplete granular knowledge of cHAB community structure. With a goal of leveraging bioinformatics and machine learning tools to better understand and predict cHABs, we are first exploring water sample data sets. Using nearly four thousand samples from the National Center for Biotechnology Information Sequence Read Archive (NCBI-SRA) across 16 years with latitude and longitude embedded in the metadata, we mapped the location of the samples onto a Lake Erie shape file. We combined information about location, date, and community taxa in the NCBI samples to discover factors that determine cHAB features. The data are separated into three distinct zones, with the majority pooled at the southwest end of the lake and occurring in 2017. The samples are rich in biological data; our next steps are to carry out whole genome sequence analysis and use the community profiles as part of our predictive machine learning model.

59 BASIC BIOLOGICAL SCIENCES↗

Genome evolution and transcriptome plasticity is associated with adaptation to monocot and dicot plants in Colletotrichum fungi

Colletotrichum fungi infect a wide diversity of monocot and dicot hosts, causing diseases on almost all economically important plants worldwide. Colletotrichum is also a suitable model for studying gene family evolution on a fine scale to uncover events in the genome associated with biological changes. Here we present the genome sequences of 30 Colletotrichum species covering the diversity within the genus. Evolutionary analyses revealed that the Colletotrichum ancestor diverged in the late Cretaceous in parallel with the diversification of flowering plants. We provide evidence of independent host jumps from dicots to monocots during the evolution of Colletotrichum, coinciding with a progressive shrinking of the plant cell wall degradative arsenal and expansions in lineage-specific gene families. Comparative transcriptomics of 4 species adapted to different hosts revealed similarity in gene content but high diversity in the modulation of their transcription profiles on different plant substrates. Combining genomics and transcriptomics, we identified a set of core genes such as specific transcription factors, putatively involved in plant cell wall degradation. These results indicate that the ancestral Colletotrichum were associated with dicot plants and certain branches progressively adapted to different monocot hosts, reshaping the gene content and its regulation.

59 BASIC BIOLOGICAL SCIENCES↗

Cultivation of novel Atribacterota from oil well provides new insight into their diversity, ecology, and evolution in anoxic, carbon-rich environments

Background: The Atribacterota are widely distributed in the subsurface biosphere. Recently, the first Atribacterota isolate was described and the number of Atribacterota genome sequences retrieved from environmental samples has increased significantly; however, their diversity, physiology, ecology, and evolution remain poorly understood. Results: We report the isolation of the second member of Atribacterota, Thermatribacter velox gen. nov., sp. nov., within a new family Thermatribacteraceae fam. nov., and the short-term laboratory cultivation of a member of the JS1 lineage, Phoenicimicrobium oleiphilum HX-OS.bin.34 TS , both from a terrestrial oil reservoir. Physiological and metatranscriptomics analyses showed that Thermatribacter velox B11 T and Phoenicimicrobium oleiphilum HX-OS.bin.34 TS ferment sugars and n-alkanes, respectively, producing H 2 , CO 2 , and acetate as common products. Comparative genomics showed that all members of the Atribacterota lack a complete Wood-Ljungdahl Pathway (WLP), but that the Reductive Glycine Pathway (RGP) is widespread, indicating that the RGP, rather than WLP, is a central hub in Atribacterota metabolism. Ancestral character state reconstructions and phylogenetic analyses showed that key genes encoding the RGP (fdhA, fhs, folD, glyA, gcvT, gcvPAB, pdhD) and other central functions were gained independently in the two classes, Atribacteria (OP9) and Phoenicimicrobiia (JS1), after which they were inherited vertically; these genes included fumarate-adding enzymes (faeA; Phoenicimicrobiia only), the CODH/ACS complex (acsABCDE), and diverse hydrogenases (NiFe group 3b, 4b and FeFe group A3, C). Finally, we present genome-resolved community metabolic models showing the central roles of Atribacteria (OP9) and Phoenicimicrobiia (JS1) in acetate- and hydrocarbon-rich environments. Conclusion: Our findings expand the knowledge of the diversity, physiology, ecology, and evolution of the phylum Atribacterota. This study is a starting point for promoting more incisive studies of their syntrophic biology and may guide the rational design of strategies to cultivate them in the laboratory.

59 BASIC BIOLOGICAL SCIENCES↗

Status on Genetic Resistance to Rice Blast Disease in the Post-Genomic Era

Rice blast, caused by Magnaporthe oryzae, is a major threat to global rice production, necessitating the development of resistant cultivars through genetic improvement. Breakthroughs in rice genomics, including the complete genome sequencing of japonica and indica subspecies and the availability of various sequence-based molecular markers, have greatly advanced the genetic analysis of blast resistance. To date, approximately 122 blast-resistance genes have been identified, with 39 of these genes cloned and molecularly characterized. The application of these findings in marker-assisted selection (MAS) has significantly improved rice breeding, allowing for the efficient integration of multiple resistance genes into elite cultivars, enhancing both the durability and spectrum of resistance. Pangenomic studies, along with AI-driven tools like AlphaFold2, RoseTTAFold, and AlphaFold3, have further accelerated the identification and functional characterization of resistance genes, expediting the breeding process. Future rice blast disease management will depend on leveraging these advanced genomic and computational technologies. Emphasis should be placed on enhancing computational tools for the large-scale screening of resistance genes and utilizing gene editing technologies such as CRISPR-Cas9 for functional validation and targeted resistance enhancement and deployment. These approaches will be crucial for advancing rice blast resistance, ensuring food security, and promoting agricultural sustainability.

Pedrozo, Rodrigo↗

Bulk segregant and QTL analysis of maltose metabolism in Saccharomyces eubayanus

This study investigates natural variation in maltose utilization among Saccharomyces eubayanus strains isolated from different tree hosts. An F2 population was generated from a cross between strain QC18 (Quercus-associated) and strain CL467.1 (Nothofagus-associated). Bulk segregant analysis (BSA) was performed on the F2 offspring, and QTL mapping was conducted by whole-genome sequencing of two pools of 30 segregants each, representing the lowest and highest growth in high maltose concentrations. For QTL analysis, the parental strains QC18 and CL467.1 were also sequenced.

evolutionary plasticity↗

Uncovering heterogeneous intercommunity disease transmission from neutral allele frequency time series

The COVID-19 pandemic has underscored the need for accurate epidemic forecasting to predict pathogen spread, evolution, and evaluate intervention strategies. Forecast reliability hinges on detailed knowledge of disease transmission across population segments, which may be inferred from contact surveys or mobility data. However, these indirect approaches make it difficult to estimate rare transmissions between socially or geographically distant communities. We show that the steep ramp-up of genome sequencing surveillance during the pandemic can be leveraged to directly identify transmission patterns between geographically defined communities. Our approach uses a hidden Markov model to infer the fraction of infections a community imports from others based on how rapidly allele frequencies in the focal community converge to those in the donor communities. Applying this method to SARS-CoV-2 sequencing data from England and the United States, we uncover networks of intercommunity transmission that reflect geographical relationships while exposing significant long-range interactions. The scaling of importation rate with distance is consistent across both countries, yet weaker than expected based on mobility data, highlighting limitations of indirect inference. We show that transmission patterns can change between waves of variants of concern and analyze how the inferred heterogeneity in intercommunity transmission impacts evolutionary forecasts. While applied here to geographically defined communities, our approach could be applied to those defined by other traits (e.g., age, socioeconomic status), provided time-series data can be stratified accordingly. Overall, our study highlights population genomic time series data as a crucial record of epidemiological interactions, which can be deciphered using tree-free inference methods.

Okada, Takashi [Department of Physics; University ↗

Survey of Thirteen Novel Pseudomonas putida Bacteriophages

Bacteriophages have been widely investigated as a promising treatment of food, medical equipment, and humans colonized by antibiotic-resistant bacteria. Phages pose particular interest in combating those bacteria which form biofilms, such as the medically important human pathogen Pseudomonas aeruginosa and several plant pathogens, including P. syringae . In an undergraduate lab course, P. putida was used as the host to isolate novel anti-pseudomonal bacteriophages. Environmental samples of soil and water were collected, and purified phage isolates were obtained. After Illumina sequencing, genomes of these phages were assembled de novo and annotated. Assembled genomes were compared with known genomes in the literature and GenBank to identify taxonomic relations and to refine their functional annotations. The thirteen phages described are sipho-, myo-, and podoviruses in several families of Caudoviricetes , spanning several novel genera, with genomes ranging from 40,000 to 96,000 bp. One phage (DDSR119) is unique and is the first reported P. putida siphovirus. The remaining 12 can be clustered into four distinct groups. Six are highly related to each other and to previously described Autotranscriptaviridae phages: Waldo5, PlaquesPlease, and Laces98 all belong to the Waldovirus genus, whereas Stalingrad, Bosely, and Stamos belong to the Troedvirus genus. Zuri was previously classified as the founding member of a new genus Zurivirus within the family Schitoviridae . Ebordelon and Holyagarpour each represent different species within Zurivirus , whereas Meara is a more distantly related member of the Schitoviridae . Dolphis and Jeremy are similar enough to form a genus but have only a few distant relatives among sequenced phages and are notable for being temperate. We identified the lysis cassettes in all 13 phages, compared tail spike structures, and found auxiliary metabolic genes in several. Studies like these, which isolate and characterize infectious virions, enable the identification of novel proteins and molecular systems and also provide the raw materials for further study, evaluation, and manipulation of phage proteins and their hosts.

Pseudomonas putida↗

Three pairs of fungal Trametes strains isolated from distinct geographic origins show conserved genomic features and adaptive response to plant biomass

The genomes of white-rot fungi hold extended repertoires of enzymes active on virtually all the chemical bonds that intertwine lignocellulose polymers, and several Trametes species have been identified as powerful tools for biorefinery or bioremediation. However, only few studies have addressed the intra-species polymorphism one would expect from fungal strains collected in contrasted environments. We compared the genome sequence of pairs of strains collected in different geographic areas, for each of three fungal species. Using an updated list of the predicted functions for fungal ligno- and cellulolytic enzymes (CAZymes), we observed a high conservation of the gene repertoires among the six strains. We compared the adaptative response of the fungi grown on crystalline cellulose, wheat straw, aspen or pine sawdust by transcriptomics and secretomics. The gene regulation profiles were determined by the species and the substrates, rather than the strain. The secretomes did not show marked differences in the sets of secreted CAZymes after 3 day-growth on the substrates. We identified five transcription factor genes and two sesquiterpenoid synthesis genes induced during growth on lignocellulose. Wider studies using larger sets of strains will be necessary to evaluate the genericity of our findings, and to assess the phenotype diversity one could expect from geographic diversity as compared to taxonomic diversity in Trametes fungi.

Drula, E. [French National Research Institute for ↗

Development and characterization of a wild emmer wheat backcross introgression population for hard winter wheat improvement

Abstract Wild emmer wheat (Triticum turgidumsubsp.dicoccoides) is the tetraploid progenitor of hexaploid bread wheat (Triticum aestivumL.) and is known to be a valuable source of genetic variation for wheat improvement. However, direct evaluation of wild emmer diversity for agronomic potential has limited value unless performed in the backgrounds of adapted cultivars. Here, we present a genetic characterization of a population of 1601 backcross recombinant inbred lines, with an average genome composition of 75% bread wheat and 25% wild emmer. Low‐coverage whole‐genome sequencing allowed introgressions and aneuploidies to be identified at a relatively low cost per sample. We identified a relatively large proportion of small introgressions (median length 38 Mb), and we found introgressions to be distributed across all chromosomes. Approximately 44% of genotyped progeny carried at least one aneuploidy, with monosomies being by far the most common. This population, which we have denoted as the Great Plains Wild Emmer/Hard Winter Wheat introgression population (GPWEW‐IP), is, to our knowledge, the first introgression population developed through the direct hybridization of wild emmer wheat and US‐adapted hard winter wheat. We believe that this population represents a valuable resource for wheat breeders and will accelerate the discovery and integration of useful variation from wild emmer wheat.

Genetics & Heredity↗