BioSciences

We present a full genome sequence for the thermophilic denitrifier Geobacillus thermodenitrificans subsp. calidus DSM 22629T (3,408,575 bp, 48.94% GC). This genome includes 3,615 predicted genes, including those needed to reduce nitrate to nitrogen gas. This organism and genome sequence provide valuable resources for future phylogenetic, genomic, and biotechnological research.

The decrease in sequencing expenses has facilitated the creation of reference genomes and proteomes for an expanding array of organisms. Nevertheless, no established repository that details organism-specific genomic and proteomic sequences of specific lengths, referred to as kmers, exists to our knowledge. In this article, we present kmerDB, a database accessible through an interactive web interface that provides kmer-based information from genomic and proteomic sequences in a systematic way. kmerDB currently contains 202,340,859,107 base pairs and 19,304,903,356 amino acids, spanning 54,039 and 21,865 reference genomes and proteomes, respectively, as well as 6,905,362 and 149,305,183 genomic and proteomic species-specific sequences, termed quasi-primes. Additionally, we provide access to 5,186,757 nucleic and 214,904,089 peptide sequences absent from every genome and proteome, termed primes. kmerDB features a user-friendly interface offering various search options and filters for easy parsing and searching. The service is available at: www.kmerdb.com.

Phyllosticta citricarpa is an important citrus-pathogen and a quarantine organism in the European Union. Its recently described relative, P. paracitricarpa, is very closely related and not listed as a quarantine organism. P. paracitricarpa is very difficult to distinguish from P. citricarpa, since its morphological features overlap and the barcoding gene sequences that were originally used to delimit them as distinct species have a low number of species-specific polymorphisms that have subsequently been shown to overlap between the two clades. Therefore, we performed extensive genomic analyses to determine whether the genetic variation between P. citricarpa and P. paracitricarpa strains should be considered to represent infraspecific variation within P. citricarpa, or whether it is indicative of distinct species. Using a phylogenomic analysis with 3,000 single copy ortholog genes and whole-genome comparisons, we determined that the variation between P. citricarpa and P. paracitricarpa can be considered as infraspecies variation within P. citricarpa. We also determined the level of variation in mitochondrial assemblies of several Phyllosticta species and concluded there are only minimal differences between the assemblies of P. citricarpa and P. paracitricarpa. Thus, using several orthogonal approaches, we here demonstrate that variation within the nuclear and mitochondrial genomes of other Phyllosticta species is larger than variation between genomes obtained from P. citricarpa and P. paracitricarpa strains. Thus, P. citricarpa and P. paracitricarpa should be considered as conspecific.

With advancements in genomics technologies, a vast diversity of 'atypical' phages, that is, with single-stranded DNA or RNA genomes, are being uncovered from different ecosystems. Though these efforts have revealed the existence and prevalence of these nonmodel phages, computational approaches often fail to associate these phages with their specific bacterial host(s), while the lack of methods to isolate these phages has limited our ability to characterize infectivity pathways and new gene function. In this review, we call for the development of generalizable experimental methods to better capture this understudied viral diversity via isolation and study them through gene-level characterization and engineering. Establishing a diverse set of new 'atypical' phage model systems has the potential to provide many new biotechnologies, including potential uses of these atypical phages in halting the spread of antibiotic resistance and engineering of microbial communities for beneficial outcomes.

The process of navigating through the landscape of biomedical literature and performing searches or combining them with bioinformatics analyses can be daunting, considering the exponential growth of scientific corpora and the plethora of tools designed to mine PubMed(®) and related repositories. Herein, we present BioTextQuest v2.0, a tool for biomedical literature mining. BioTextQuest v2.0 is an open-source online web portal for document clustering based on sets of selected biomedical terms, offering efficient management of information derived from PubMed abstracts. Employing established machine learning algorithms, the tool facilitates document clustering while allowing users to customize the analysis by selecting terms of interest. BioTextQuest v2.0 streamlines the process of uncovering valuable insights from biomedical research articles, serving as an agent that connects the identification of key terms like genes/proteins, diseases, chemicals, Gene Ontology (GO) terms, functions, and others through named entity recognition, and their application in biological research. Instead of manually sifting through articles, researchers can enter their PubMed-like query and receive extracted information in two user-friendly formats, tables and word clouds, simplifying the comprehension of key findings. The latest update of BioTextQuest leverages the EXTRACT named entity recognition tagger, enhancing its ability to pinpoint various biological entities within text. BioTextQuest v2.0 acts as a research assistant, significantly reducing the time and effort required for researchers to identify and present relevant information from the biomedical literature.

The fields of Metagenomics and Metatranscriptomics involve the examination of complete nucleotide sequences, gene identification, and analysis of potential biological functions within diverse organisms or environmental samples. Despite the vast opportunities for discovery in metagenomics, the sheer volume and complexity of sequence data often present challenges in processing analysis and visualization. This article highlights the critical role of advanced visualization tools in enabling effective exploration, querying, and analysis of these complex datasets. Emphasizing the importance of accessibility, the article categorizes various visualizers based on their intended applications and highlights their utility in empowering bioinformaticians and non-bioinformaticians to interpret and derive insights from meta-omics data effectively.

Accessible and easy-to-use standardized bioinformatics workflows are necessary to advance microbiome research from observational studies to large-scale, data-driven approaches. Standardized multi-omics data enables comparative studies, data reuse, and applications of machine learning to model biological processes. To advance broad accessibility of standardized multi-omics bioinformatics workflows, the National Microbiome Data Collaborative (NMDC) has developed the Empowering the Development of Genomics Expertise (NMDC EDGE) resource, a user-friendly, open-source web application (https://nmdc-edge.org). Here, we describe the design and main functionality of the NMDC EDGE resource for processing metagenome, metatranscriptome, natural organic matter, and metaproteome data. The architecture relies on three main layers (web application, orchestration, and execution) to ensure flexibility and expansion to future workflows. The orchestration and execution layers leverage best practices in software containers and accommodate high-performance computing and cloud computing services. Further, we have adopted a robust user research process to collect feedback for continuous improvement of the resource. NMDC EDGE provides an accessible interface for researchers to process multi-omics microbiome data using production-quality workflows to facilitate improved data standardization and interoperability.

Sex chromosomes have evolved hundreds of times across the flowering plant tree of life; their recent origins in some members of this clade can shed light on the early consequences of suppressed recombination, a crucial step in sex chromosome evolution. Amborella trichopoda, the sole species of a lineage that is sister to all other extant flowering plants, is dioecious with a young ZW sex determination system. Here we present a haplotype-resolved genome assembly, including highly contiguous assemblies of the Z and W chromosomes. We identify a ~3-megabase sex-determination region (SDR) captured in two strata that includes a ~300-kilobase inversion that is enriched with repetitive sequences and contains a homologue of the Arabidopsis METHYLTHIOADENOSINE NUCLEOSIDASE (MTN1-2) genes, which are known to be involved in fertility. However, the remainder of the SDR does not show patterns typically found in non-recombining SDRs, such as repeat accumulation and gene loss. These findings are consistent with the hypothesis that dioecy is derived in Amborella and the sex chromosome pair has not significantly degenerated.