TIPPo: A User-Friendly Tool for De Novo Assembly of Organellar Genomes with High-Fidelity Data.

Plant cells have two major organelles with their own genomes: chloroplasts and mitochondria. While chloroplast genomes tend to be structurally conserved, the mitochondrial genomes of plants, which are much larger than those of animals, are characterized by complex structural variation. We introduce TIPPo, a user-friendly, reference-free assembly tool that uses PacBio high-fidelity long-read data and that does not rely on genomes from related species or nuclear genome information for the assembly of organellar genomes.

PTMVision: An Interactive Visualization Webserver for Post-translational Modifications of Proteins.

Recent improvements in methods and instruments used in mass spectrometry have greatly enhanced the detection of protein post-translational modifications (PTMs). On the computational side, the adoption of open modification search strategies now allows for the identification of a wide variety of PTMs, potentially revealing hundreds to thousands of distinct modifications in biological samples. While the observable part of the proteome is continuously growing, the visualization and interpretation of this vast amount of data in a comprehensive fashion is not yet possible.

Transformations to Simplify Phylogenetic Networks.

The evolutionary relationships between species are typically represented in the biological literature by rooted phylogenetic trees. However, a tree fails to capture ancestral reticulate processes, such as the formation of hybrid species or lateral gene transfer events between lineages, and so the history of life is more accurately described by a rooted phylogenetic network. Nevertheless, phylogenetic networks may be complex and difficult to interpret, so biologists sometimes prefer a tree that summarises the central tree-like trend of evolution.

Corrigendum: Interplay of various evolutionary modes in genome diversification and adaptive evolution of the family .

[This corrects the article DOI: 10.3389/fmicb.2021.

STOUT V2.0: SMILES to IUPAC name conversion using transformer models.

Naming chemical compounds systematically is a complex task governed by a set of rules established by the International Union of Pure and Applied Chemistry (IUPAC). These rules are universal and widely accepted by chemists worldwide, but their complexity makes it challenging for individuals to consistently apply them accurately. A translation method can be employed to address this challenge.

Transposon-triggered epigenetic chromatin dynamics modulate EFR-related pathogen response.

Infectious diseases drive wild plant evolution and impact crop yield. Plants, like animals, sense biotic threats through pattern recognition receptors (PRRs). Overly robust immune responses can harm plants; thus, understanding the tuning of defense response mechanisms is crucial for developing pathogen-resistant crops.

Systematic assessment of COVID-19 host genetics using whole genome sequencing data.

Courses of SARS-CoV-2 infections are highly variable, ranging from asymptomatic to lethal COVID-19. Though research has shown that host genetic factors contribute to this variability, cohort-based joint analyses of variants from the entire allelic spectrum in individuals with confirmed SARS-CoV-2 infections are still lacking. Here, we present the results of whole genome sequencing in 1,220 mainly vaccine-naïve individuals with confirmed SARS-CoV-2 infection, including 827 hospitalized COVID-19 cases.

TSS-Captur: a user-friendly pipeline for characterizing unclassified RNA transcripts.

RNA-seq and its 5'-enrichment methods for prokaryotes have enabled the precise identification of transcription start sites (TSSs), improving gene expression analysis. Computational methods are applied to these data to identify TSSs and classify them based on proximal annotated genes. While some TSSs cannot be classified at all (orphan TSSs), other TSSs are found on the reverse strand of known genes (antisense TSSs) but are not associated with the direct transcription of any known gene.

The Cultivable Bacteria Colonizing Canine Vagina During Proestrus and Estrus: A Large-Scale Retrospective Study of Influencing Factors.

Background: The evaluation of canine vaginal bacteria during proestrus and estrus and the chosen parameters will help to prevent the misuse of antibiotics in veterinary medicine.

Methods: This study carried out a retrospective analysis to obtain microbiological examination results for vaginal swabs from 696 healthy dogs, all of whom were patients from one clinic. Age, body weight, fur length (long or short hair), the time of sampling of vaginal swabs, the duration of proestrus/estrus, progesterone (P4) concentration (the first and last samples), and bacteriological findings were evaluated.

Inferring stability and persistence in the vaginal microbiome: A stochastic model of ecological dynamics.

The interplay of stochastic and ecological processes that govern the establishment and persistence of host-associated microbial communities is not well understood. Here we illustrate the conceptual and practical advantages of fitting stochastic population dynamics models to multi-species bacterial time series data. We show how the stability properties, fluctuation regimes and persistence probabilities of human vaginal microbial communities can be better understood by explicitly accommodating three sources of variability in ecological stochastic models of multi-species abundances: 1) stochastic biotic and abiotic forces, 2) ecological feedback and 3) sampling error.

Neonatal apnea and hypopnea prediction in infants with Robin sequence with neural additive models for time series.

Neonatal apneas and hypopneas present a serious risk for healthy infant development. Treating these adverse events requires frequent manual stimulation by skilled personnel, which can lead to alarm fatigue. This study aims to develop and validate an interpretable model that can predict apneas and hypopneas.

A privacy-preserving approach for cloud-based protein fold recognition.

The complexity and cost of training machine learning models have made cloud-based machine learning as a service (MLaaS) attractive for businesses and researchers. MLaaS eliminates the need for in-house expertise by providing pre-built models and infrastructure. However, it raises data privacy and model security concerns, especially in medical fields like protein fold recognition.

Using machine learning to predict neurologic injury in venovenous extracorporeal membrane oxygenation recipients: An ELSO Registry analysis.

Background: Venovenous extracorporeal membrane oxygenation (VV-ECMO) is associated with acute brain injury (ABI), including central nervous system (CNS) ischemia (defined as ischemic stroke or hypoxic-ischemic brain injury [HIBI]) and intracranial hemorrhage (ICH). Data on prediction models for neurologic outcomes in VV-ECMO are limited.

Methods: We analyzed adult (age ≥18 years) VV-ECMO patients in the Extracorporeal Life Support Organization (ELSO) Registry (2009-2021) from 676 centers.

A multiorgan map of metabolic, signaling, and inflammatory pathways that coordinately control fasting glycemia in mice.

To identify the pathways that are coordinately regulated in pancreatic β cells, muscle, liver, and fat to control fasting glycemia we fed C57Bl/6, DBA/2, and Balb/c mice a regular chow or a high fat diet for 5, 13, and 33 days. Physiological, transcriptomic and lipidomic data were used in a data fusion approach to identify organ-specific pathways linked to fasting glycemia across all conditions investigated. In pancreatic islets, constant insulinemia despite higher glycemic levels was associated with reduced expression of hormone and neurotransmitter receptors, OXPHOS, cadherins, integrins, and gap junction mRNAs.

Glut3 promotes cellular O-GlcNAcylation as a distinctive tumor-supportive feature in Treg cells.

Regulatory T cells (Tregs) establish dominant immune tolerance but obstruct tumor immune surveillance, warranting context-specific mechanistic insights into the functions of tumor-infiltrating Tregs (TIL-Tregs). We show that enhanced posttranslational O-linked N-acetylglucosamine modification (O-GlcNAcylation) of cellular factors is a molecular feature that promotes a tumor-specific gene expression signature and distinguishes TIL-Tregs from their systemic counterparts. We found that altered glucose utilization through the glucose transporter Glut3 is a major facilitator of this process.

Influence of different sample preparation approaches on proteoform identification by top-down proteomics.

Top-down proteomics using mass spectrometry facilitates the identification of intact proteoforms, that is, all molecular forms of proteins. Multiple past advances have lead to the development of numerous sample preparation workflows. Here we systematically investigated the influence of different sample preparation steps on proteoform and protein identifications, including cell lysis, reduction and alkylation, proteoform enrichment, purification and fractionation.

Building pangenome graphs.

Pangenome graphs can represent all variation between multiple reference genomes, but current approaches to build them exclude complex sequences or are based upon a single reference. In response, we developed the PanGenome Graph Builder, a pipeline for constructing pangenome graphs without bias or exclusion. The PanGenome Graph Builder uses all-to-all alignments to build a variation graph in which we can identify variation, measure conservation, detect recombination events and infer phylogenetic relationships.

Inferring ancestry with the hierarchical soft clustering approach tangleGen.

Understanding the genetic ancestry of populations is central to numerous scientific and societal fields. It contributes to a better understanding of human evolutionary history, advances personalized medicine, aids in forensic identification, and allows individuals to connect to their genealogical roots. Existing methods, such as ADMIXTURE, have significantly improved our ability to infer ancestries.