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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Flying Blind, or Just Flying Under the Radar? The Underappreciated Power of De Novo Methods of Mass Spectrometric Peptide Identification

Mass spectrometry-based proteomics is a popular and powerful method for precise and highly multiplexed protein identification. The most common method of analyzing untargeted proteomics data is called database searching, where the database is simply a collection of protein sequences from the target organism, derived from genome sequencing. Experimental peptide tandem mass spectra are compared to simplified models of theoretical spectra calculated from the translated genomic sequences. However, in several interesting application areas, such as forensics, archaeology, venomics and others, a genome sequence may not be available, or the correct genome sequence to use is not known. In these cases, de novo peptide identification can play an important role. De novo peptide identification infers peptide sequence directly from the tandem mass spectrum without reference to a sequence database, usually using graph-based or machine learning algorithms. In this review, we provide a basic overview of de novo peptide identification methods and applications, briefly covering de novo algorithms and tools, and focusing in more depth on recent applications from venomics, metaproteomics, forensics, and characterization of antibody drugs.

proteomics, mass spectrometry, forensics, de novo ↗
DOE OSTI2021

Species- and site-specific genome editing in complex bacterial communities

Knowledge of microbial gene functions comes from manipulating the DNA of individual strains in isolation from their natural communities. While this approach to microbial genetics has been foundational, its requirement for culturable microorganisms has left the majority of microbes and their interactions genetically unexplored. Here, we describe a generalizable strategy for editing the genomes of specific organisms within microbial communities. We identified genetically tractable bacteria within a community using Environmental Transformation Sequencing (ET-Seq), an approach in which non-targeted transposon integrations are mapped and quantified following community delivery. We next developed and used DNA-editing All-in-one RNA-guided CRISPR-Cas Transposase (DART) systems for targeted DNA insertion into organisms identified as tractable by ET-Seq, enabling organism- and locus-specific genetic manipulation within the community context. To illustrate the utility of our approach, we selectively edited closely related strains, measured gene fitness, and enriched targeted members within soil and infant gut microbiota. These results establish a new paradigm for targeted community editing relevant to research and applications on medical, agricultural, and industrial microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Uptake of Phytoplankton-Derived Carbon and Cobalamins by Novel Acidobacteria Genera in Microcystis Blooms Inferred from Metagenomic and Metatranscriptomic Evidence

We report interactions between bacteria and phytoplankton can influence primary production, community composition, and algal bloom development. However, these interactions are poorly described for many consortia, particularly for freshwater bloom-forming cyanobacteria. Here, we assessed the gene content and expression of two uncultivated Acidobacteria from Lake Erie Microcystis blooms. These organisms were targeted because they were previously identified as important catalase producers in Microcystis blooms, suggesting that they protect Microcystis from H 2 O 2 . Metatranscriptomics revealed that both Acidobacteria transcribed genes for uptake of organic compounds that are known cyanobacterial products and exudates, including lactate, glycolate, amino acids, peptides, and cobalamins. Expressed genes for amino acid metabolism and peptide transport and degradation suggest that use of amino acids and peptides by Acidobacteria may regenerate nitrogen for cyanobacteria and other organisms. The Acidobacteria genomes lacked genes for biosynthesis of cobalamins but expressed genes for its transport and remodeling. This indicates that the Acidobacteria obtained cobalamins externally, potentially from Microcystis, which has a complete gene repertoire for pseudocobalamin biosynthesis; expressed them in field samples; and produced pseudocobalamin in axenic culture. Both Acidobacteria were detected in Microcystis blooms worldwide. Together, the data support the hypotheses that uncultured and previously unidentified Acidobacteria taxa exchange metabolites with phytoplankton during harmful cyanobacterial blooms and influence nitrogen available to phytoplankton. Thus, novel Acidobacteria may play a role in cyanobacterial physiology and bloom development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

From 2D to 4D: a containerized workflow and browser to explore dynamic chromatin architecture

Background Characterizing the physical organization of the genome is essential for understanding long-range gene regulation, chromatin compartmentalization, and epigenetic accessibility. Hi-C experiments generate two-dimensional (2D) genome-wide contact maps of chromatin interactions by capturing the spatial proximity between genomic loci, which reveal interaction frequencies but lack the spatial resolution needed to interpret the three-dimensional (3D) genome structure(s). Emerging evidence suggests that epigenetic regulation is closely linked to 3D genome architecture, and that structural changes over time (4D) drive key biological processes in development, disease, and environmental response. Thus, integrating 3D structure with functional data is critical for a more complete understanding of genome regulation. Previous work, most notably the 4DHiC chromosome modeling framework, has shown that physical multi-dimensional modeling approaches rooted in polymer physics and molecular dynamics can resolve these structures at biologically meaningful resolutions by integrating temporal Hi-C data with physical constraints to uncover dynamic chromosome reorganization. Thus, molecular dynamics simulations, constrained by Hi-C contact matrices, can resolve fine-scale structural changes and reveal functionally significant transitions in chromatin conformation. Results Herein, we present the 4D Genome Browser Workflow (4DGBWorkflow) and the 4D Genome Browser (4DGB). The algorithm is based on the 4DHiC method, and the containerized tool is an end-to-end workflow that can transform, filter, and view 4D epigenomics and chromatin datasets, allowing non-specialists to apply three-dimensional modeling principles to diverse datasets and experimental conditions. The software executes on a laptop running macOS, Linux or Windows. From input Hi-C files (.hic), the 4DGBWorkflow produces 3D reconstructions of chromosomes, integrates the reconstruction with track data (e.g., epigenetic marks, transcriptome profiles), and provides comparative visualization of the results in a single workflow. Conclusions The 4DGBWorkflow and 4D Genome Browser are open-source tools for comparative analysis and visualization of 4D chromosome datasets, including chromatin architecture and epigenomic signals. Automatic integration of Hi-C data with molecular dynamics democratizes the construction of time resolved 3D genome structures, simplifying complex simulations and data integration schemes.

3D Genome Browser↗
DOE OSTI2025

Chromatin structures from integrated AI and polymer physics model

The physical organization of the genome in three-dimensional space regulates many biological processes, including gene expression and cell differentiation. Three-dimensional characterization of genome structure is critical to understanding these biological processes. Direct experimental measurements of genome structure are challenging; computational models of chromatin structure are therefore necessary. We develop an approach that combines a particle-based chromatin polymer model, molecular simulation, and machine learning to efficiently and accurately estimate chromatin structure fromindirectmeasures of genome structure. More specifically, we introduce a new approach where the interaction parameters of the polymer model are extracted from experimental Hi-C data using a graph neural network (GNN). We train the GNN on simulated data from the underlying polymer model, avoiding the need for large quantities of experimental data. The resulting approach accurately estimates chromatin structures across all chromosomes and across several experimental cell lines despite being trained almost exclusively on simulated data. The proposed approach can be viewed as a general framework for combining physical modeling with machine learning, and it could be extended to integrate additional biological data modalities. Ultimately, we achieve accurate and high-throughput estimations of chromatin structure from Hi-C data, which will be necessary as experimental methodologies, such as single-cell Hi-C, improve.

Biochemistry & Molecular Biology↗
DOE OSTI2020

FeGenie: a comprehensive tool for the identification of iron genes and iron gene neighborhoods in genomes and metagenome assemblies

Iron is a micronutrient for nearly all life on Earth. It can be used as an electron donor and electron acceptor by iron-oxidizing and iron-reducing microorganisms and is used in a variety of biological processes, including photosynthesis and respiration. While it is the fourth most abundant metal in the Earth’s crust, iron is often limiting for growth in oxic environments because it is readily oxidized and precipitated. Much of our understanding of how microorganisms compete for and utilize iron is based on laboratory experiments. However, the advent of next-generation sequencing and surge in publicly available sequence data has made it possible to probe the structure and function of microbial communities in the environment. To bridge the gap between our understanding of iron acquisition, iron redox cycling, iron storage, and magnetosome formation in model microorganisms and the plethora of sequence data available from environmental studies, we have created a comprehensive database of hidden Markov models (HMMs) based on genes related to iron acquisition, storage, and reduction/oxidation in Bacteria and Archaea. Along with this database, we present FeGenie, a bioinformatics tool that accepts genome and metagenome assemblies as input and uses our comprehensive HMM database to annotate provided datasets with respect to iron-related genes and gene neighborhood. An important contribution of this tool is the efficient identification of genes involved in iron oxidation and dissimilatory iron reduction, which have been largely overlooked by standard annotation pipelines. We validated FeGenie against a selected set of 28 isolate genomes and showcase its utility in exploring iron genes present in 27 metagenomes, 4 isolate genomes from human oral biofilms, and 17 genomes from candidate organisms, including members of the candidate phyla radiation. We show that FeGenie accurately identifies iron genes in isolates. Furthermore, analysis of metagenomes using FeGenie demonstrates that the iron gene repertoire and abundance of each environment is correlated with iron richness. While this tool will not replace the reliability of culture-dependent analyses of microbial physiology, it provides reliable predictions derived from the most up-to-date genetic markers. FeGenie’s database will be maintained and continually updated as new genes are discovered.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A Two-Step PCR Protocol Enabling Flexible Primer Choice and High Sequencing Yield for Illumina MiSeq Meta-Barcoding

High-throughput amplicon sequencing that primarily targets the 16S ribosomal DNA (rDNA) (for bacteria and archaea) and the Internal Transcribed Spacer rDNA (for fungi) have facilitated microbial community discovery across diverse environments. A three-step PCR that utilizes flexible primer choices to construct the library for Illumina amplicon sequencing has been applied to several studies in forest and agricultural systems. The three-step PCR protocol, while producing high-quality reads, often yields a large number (up to 46%) of reads that are unable to be assigned to a specific sample according to its barcode. Here, we improve this technique through an optimized two-step PCR protocol. We tested and compared the improved two-step PCR meta-barcoding protocol against the three-step PCR protocol using four different primer pairs (fungal ITS: ITS1F-ITS2 and ITS1F-ITS4, and bacterial 16S: 515F-806R and 341F-806R). We demonstrate that the sequence quantity and recovery rate were significantly improved with the two-step PCR approach (fourfold more read counts per sample; determined reads ≈90% per run) while retaining high read quality (Q30 > 80%). Given that synthetic barcodes are incorporated independently from any specific primers, this two-step PCR protocol can be broadly adapted to different genomic regions and organisms of scientific interest.

16S rDNA↗
NASA NTRS1991

A deficiency of the homeotic complex of the beetle Tribolium

In Drosophila, the establishment of regional commitments along most of the anterior/posterior axis of the developing embryo depends on two clusters of homeotic genes: the Antennapedia complex (ANT-C) and the bithorax complex (BX-C). The red flour beetle has a single complex (HOM-C) representing the homologues of the ANT-C and BX-C in juxtaposition. Beetles trans-heterozygous for two particular HOM-C mutations spontaneously generate a large deficiency, presumably by an exchange within the common region of two overlapping inversions. Genetic and molecular results indicate that this deficiency spans at least the interval between the Deformed and abdominal-A homologues. In deficiency homozygous embryos, all gnathal, thoracic and abdominal segments develop antennal appendages, suggesting that a gene(s) has been deleted that acts to distinguish trunk from head. There is no evidence that beetles have a homologue of the segmentation gene fushi tarazu of similar genomic location and function. On the basis of the genetic tractability, convenient genome size and organization of Tribolium, and its relatively long phylogenetic divergence from Drosophila (>300 million years), we have integrated developmental genetic and molecular analyses of the HOM-C. We isolated about 70 mutations in the complex representing at least six complementation groups. The homeotic phenotypes of adults and lethal embryos lead us to believe that these beetle genes are homologous with the Drosophila genes indicated in Fig. 1 (see text).

NASA Program NSCORT↗
NASA NTRS1997

Conserved gene clusters in bacterial genomes provide further support for the primacy of RNA

Five complete bacterial genome sequences have been released to the scientific community. These include four (eu)Bacteria, Haemophilus influenzae, Mycoplasma genitalium, M. pneumoniae, and Synechocystis PCC 6803, as well as one Archaeon, Methanococcus jannaschii. Features of organization shared by these genomes are likely to have arisen very early in the history of the bacteria and thus can be expected to provide further insight into the nature of early ancestors. Results of a genome comparison of these five organisms confirm earlier observations that gene order is remarkably unpreserved. There are, nevertheless, at least 16 clusters of two or more genes whose order remains the same among the four (eu)Bacteria and these are presumed to reflect conserved elements of coordinated gene expression that require gene proximity. Eight of these gene orders are essentially conserved in the Archaea as well. Many of these clusters are known to be regulated by RNA-level mechanisms in Escherichia coli, which supports the earlier suggestion that this type of regulation of gene expression may have arisen very early. We conclude that although the last common ancestor may have had a DNA genome, it likely was preceded by progenotes with an RNA genome.

Non-NASA Center↗
DOE OSTI2023

A genomic data archive from the Network for Pancreatic Organ donors with Diabetes

The Network for Pancreatic Organ donors with Diabetes (nPOD) is the largest biorepository of human pancreata and associated immune organs from donors with type 1 diabetes (T1D), maturity-onset diabetes of the young (MODY), cystic fibrosis-related diabetes (CFRD), type 2 diabetes (T2D), gestational diabetes, islet autoantibody positivity (AAb+), and without diabetes. nPOD recovers, processes, analyzes, and distributes high-quality biospecimens, collected using optimized standard operating procedures, and associated de-identified data/metadata to researchers around the world. Herein describes the release of high-parameter genotyping data from this collection. 372 donors were genotyped using a custom precision medicine single nucleotide polymorphism (SNP) microarray. Data were technically validated using published algorithms to evaluate donor relatedness, ancestry, imputed HLA, and T1D genetic risk score. Additionally, 207 donors were assessed for rare known and novel coding region variants via whole exome sequencing (WES). These data are publicly-available to enable genotype-specific sample requests and the study of novel genotype:phenotype associations, aiding in the mission of nPOD to enhance understanding of diabetes pathogenesis to promote the development of novel therapies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Eukaryotic genomes from a global metagenomic data set illuminate trophic modes and biogeography of ocean plankton

ABSTRACT Metagenomics is a powerful method for interpreting the ecological roles and physiological capabilities of mixed microbial communities. Yet, many tools for processing metagenomic data are neither designed to consider eukaryotes nor are they built for an increasing amount of sequence data. EukHeist is an automated pipeline to retrieve eukaryotic and prokaryotic metagenome-assembled genomes (MAGs) from large-scale metagenomic sequence data sets. We developed the EukHeist workflow to specifically process large amounts of both metagenomic and/or metatranscriptomic sequence data in an automated and reproducible fashion. Here, we applied EukHeist to the large-size fraction data (0.8–2,000 µm) from Tara Oceans to recover both eukaryotic and prokaryotic MAGs, which we refer to as TOPAZ (Tara Oceans Particle-Associated MAGs). The TOPAZ MAGs consisted of >900 environmentally relevant eukaryotic MAGs and >4,000 bacterial and archaeal MAGs. The bacterial and archaeal TOPAZ MAGs expand upon the phylogenetic diversity of likely particle- and host-associated taxa. We use these MAGs to demonstrate an approach to infer the putative trophic mode of the recovered eukaryotic MAGs. We also identify ecological cohorts of co-occurring MAGs, which are driven by specific environmental factors and putative host-microbe associations. These data together add to a number of growing resources of environmentally relevant eukaryotic genomic information. Complementary and expanded databases of MAGs, such as those provided through scalable pipelines like EukHeist, stand to advance our understanding of eukaryotic diversity through increased coverage of genomic representatives across the tree of life. IMPORTANCE Single-celled eukaryotes play ecologically significant roles in the marine environment, yet fundamental questions about their biodiversity, ecological function, and interactions remain. Environmental sequencing enables researchers to document naturally occurring protistan communities, without culturing bias, yet metagenomic and metatranscriptomic sequencing approaches cannot separate individual species from communities. To more completely capture the genomic content of mixed protistan populations, we can create bins of sequences that represent the same organism (metagenome-assembled genomes [MAGs]). We developed the EukHeist pipeline, which automates the binning of population-level eukaryotic and prokaryotic genomes from metagenomic reads. We show exciting insight into what protistan communities are present and their trophic roles in the ocean. Scalable computational tools, like EukHeist, may accelerate the identification of meaningful genetic signatures from large data sets and complement researchers’ efforts to leverage MAG databases for addressing ecological questions, resolving evolutionary relationships, and discovering potentially novel biodiversity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

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↗
DOE OSTI2021

Integration of evidence across human and model organism studies: A meeting report

The National Institute on Drug Abuse and Joint Institute for Biological Sciences at the Oak Ridge National Laboratory hosted a meeting attended by a diverse group of scientists with expertise in substance use disorders (SUDs), computational biology, and FAIR (Findability, Accessibility, Interoperability, and Reusability) data sharing. The meeting's objective was to discuss and evaluate better strategies to integrate genetic, epigenetic, and 'omics data across human and model organisms to achieve deeper mechanistic insight into SUDs. Specific topics were to (a) evaluate the current state of substance use genetics and genomics research and fundamental gaps, (b) identify opportunities and challenges of integration and sharing across species and data types, (c) identify current tools and resources for integration of genetic, epigenetic, and phenotypic data, (d) discuss steps and impediment related to data integration, and (e) outline future steps to support more effective collaboration—particularly between animal model research communities and human genetics and clinical research teams. This review summarizes key facets of this catalytic discussion with a focus on new opportunities and gaps in resources and knowledge on SUDs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Genome Analysis of a Verrucomicrobial Endosymbiont With a Tiny Genome Discovered in an Antarctic Lake

Organic Lake in Antarctica is a marine-derived, cold (–13°C), stratified (oxic-anoxic), hypersaline (>200 gl –1 ) system with unusual chemistry (very high levels of dimethylsulfide) that supports the growth of phylogenetically and metabolically diverse microorganisms. Symbionts are not well characterized in Antarctica. However, unicellular eukaryotes are often present in Antarctic lakes and theoretically could harbor endosymbionts. Here, we describe Candidatus Organicella extenuata, a member of the Verrucomicrobia with a highly reduced genome, recovered as a metagenome-assembled genome with genetic code 4 (UGA-to-Trp recoding) from Organic Lake. It is closely related to Candidatus Pinguicocccus supinus (163,218 bp, 205 genes), a newly described cytoplasmic endosymbiont of the freshwater ciliate Euplotes vanleeuwenhoeki (Serra et al., 2020). At 158,228 bp (encoding 194 genes), the genome of Ca. Organicella extenuata is among the smallest known bacterial genomes and similar to the genome of Ca. Pinguicoccus supinus (163,218 bp, 205 genes). Ca. Organicella extenuata retains a capacity for replication, transcription, translation, and protein-folding while lacking any capacity for the biosynthesis of amino acids or vitamins. Notably, the endosymbiont retains a capacity for fatty acid synthesis (type II) and iron–sulfur (Fe-S) cluster assembly. Metagenomic analysis of 150 new metagenomes from Organic Lake and more than 70 other Antarctic aquatic locations revealed a strong correlation in abundance between Ca. Organicella extenuata and a novel ciliate of the genus Euplotes. Like Ca. Pinguicoccus supinus, we infer that Ca. Organicella extenuata is an endosymbiont of Euplotes and hypothesize that both Ca. Organicella extenuata and Ca. Pinguicocccus supinus provide fatty acids and Fe-S clusters to their Euplotes host as the foundation of a mutualistic symbiosis. The discovery of Ca. Organicella extenuata as possessing genetic code 4 illustrates that in addition to identifying endosymbionts by sequencing known symbiotic communities and searching metagenome data using reference endosymbiont genomes, the potential exists to identify novel endosymbionts by searching for unusual coding parameters.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

DRAM example narrative

DRAM example narrative DRAM on KBase let's anyone run annotations using DRAM in the cloud. DRAM is an annotation tool that can annotate bacterial, archaeal and viral genomes and distills those annotatios into represetations of the functional genomic potential of those organisms. If you want to read more about DRAM you can check out the GitHub, wiki and journal article. DRAM annotate assemblies In KBase Assembly objects contain nucleotide sequences from genomes or metagenomes. DRAM can predict genes and annotate their function from KBase Assembly objects which may be microbial isolate genomes, metagenome assembled genomes or metagenomes. This is done with the Annotate and Distill Assemblies with DRAM app. This app can also anntoate AssemblySet objects which contain collection of Assembly objects. It also generates a Genome object and a GenomeSet object which can be used for further analysis with other KBase apps. The full annotations and other DRAM files are also available for download in the app.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

UnigeneFinder: An Automated Pipeline for Gene Calling From Transcriptome Assemblies Without a Reference Genome

ABSTRACT For most species, transcriptome data are much more readily available than genome data. Without a reference genome, gene calling is cumbersome and inaccurate because of the high degree of redundancy in de novo transcriptome assemblies. To simplify and increase the accuracy of de novo transcriptome assembly in the absence of a reference genome, we developed UnigeneFinder. Combining several clustering methods, UnigeneFinder substantially reduces the redundancy typical of raw transcriptome assemblies. This pipeline offers an effective solution to the problem of inflated transcript numbers, achieving a closer representation of the actual underlying genome. UnigeneFinder performs comparably or better, compared with existing tools, on plant species with varying genome complexities. UnigeneFinder is the only available transcriptome redundancy solution that fully automates the generation of primary transcript, coding region, and protein sequences, analogous to those available for high‐quality reference genomes. These features, coupled with the pipeline’s cross‐platform implementation, focus on automation, and an accessible, user‐friendly interface, make UnigeneFinder a useful tool for many downstream sequence‐based analyses in nonmodel organisms lacking a reference genome, including differential gene expression analysis, accurate ortholog identification, functional enrichments, and evolutionary analyses. UnigeneFinder also runs efficiently both on high‐performance computing (HPC) systems and personal computers, further reducing barriers to use.

Xue, Bo [Plant Resilience Institute Michigan State↗
DOE OSTI2021

Extreme dimensions — how big (or small) can tailed phages be?

Bacteriophages (phages), that is, viruses that infect bacteria, represent an extremely diverse, yet under-characterized, group of viruses. Although most known phages harbour genomes that are shorter than 200 kb packaged into capsids with a diameter under 100 Å, more and more ‘extremely large’ phages are being discovered. Early reports of phages with genomes larger than 200 kb defined them as ‘jumbo phages’1. Phylogenetic analysis of these jumbo phages revealed that they form distinct and cohesive groups with multiple independent origins. This suggested that jumbo phages are not merely mistakes or aberrations of smaller phages that got too big, but that large genome size is generally a stable trait. In fact, a larger genome can be advantageous; almost all jumbo phages encode their own specific transcription factors, at least some parts of the replication machinery, and many also have their own tRNA genes, which enables increased independence from their host. Here, large genomes also provide more flexibility in terms of transcription strategy; smaller phage genomes tend to have a strict modular genome structure to increase efficiency, whereas jumbo phage genomes may be much less organized in the absence of a strong selection pressure to maintain a compact genome.

59 BASIC BIOLOGICAL SCIENCES↗