Frontiers in bioinformatics最新文献

{"title":"Molecular dynamic simulations to assess the structural variability of ClpV from <i>Enterobacter cloacae</i>.","authors":"Tehrim Motiwala, Babalwa Nyide, Thandeka Khoza","doi":"10.3389/fbinf.2025.1498916","DOIUrl":"https://doi.org/10.3389/fbinf.2025.1498916","url":null,"abstract":"<p><p>The <i>Enterobacter cloacae</i> complex (ECC) consists of six <i>Enterobacter</i> species (<i>E. cloacae</i>, <i>hormaechei</i>, <i>kobei</i>, <i>ludwigii</i>, <i>nimipressuralis</i> and <i>asburiae</i>) that have emerged as nosocomial pathogens of interest, with <i>E. cloacae</i> and <i>Enterobacter hormachei</i> being the most frequently isolated ECC species in human clinical specimens and intensive care unit (ICU) patients. Many nosocomial outbreaks of <i>E. cloacae</i> have been related to transmission through contaminated surgical equipment and operative cleaning solutions. As this pathogen evades the action of antibiotics, it is important to find alternative targets to limit the devastating effects of these pathogens. ClpV is a Clp ATPase which dissociates and recycles the contracted sheath of the bacterial type VI secretion system (T6SS), thereby regulating bacterial populations and facilitating environmental colonization. Seventy-one <i>Enterobacter</i> strains were mined for Clp ATPase proteins. All the investigated strains contained ClpA, ClpB, ClpX and ClpV while only 20% contained ClpK. All the investigated strains contained more than one ClpV protein, and the ClpV proteins showed significant variations. Three ClpV proteins from <i>E. cloacae</i> strain E3442 were then investigated to determine the structural difference between each protein. Homology modelling showed the proteins to be structurally similar to each other, however the physicochemical characteristics of the proteins vary. Additionally, physicochemical analysis and molecular dynamic simulations showed that the proteins were highly dynamic and not significantly different from each other. Further investigation of the proteins <i>in silico</i> and <i>in vitro</i> in the presence and absence of various ligands and proteins could be performed to determine whether the proteins all interact with their surroundings in the same manner. This would allow one to determine why multiple homologs of the same protein are expressed by pathogens.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"5 ","pages":"1498916"},"PeriodicalIF":2.8,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11975955/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143812907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Divergent evolution of low-complexity regions in the vertebrate CPEB protein family.","authors":"Serena Vaglietti, Stefania Boggio Bozzo, Mirella Ghirardi, Ferdinando Fiumara","doi":"10.3389/fbinf.2025.1491735","DOIUrl":"10.3389/fbinf.2025.1491735","url":null,"abstract":"<p><p>The <i>cytoplasmic polyadenylation element-binding proteins</i> (CPEBs) are a family of translational regulators involved in multiple biological processes, including memory-related synaptic plasticity. In vertebrates, four paralogous genes (CPEB1-4) encode proteins with phylogenetically conserved C-terminal RNA-binding domains and variable N-terminal regions (NTRs). The CPEB NTRs are characterized by low-complexity regions (LCRs), including homopolymeric amino acid repeats (AARs), and have been identified as mediators of liquid-liquid phase separation (LLPS) and prion-like aggregation. After their appearance following gene duplication, the four paralogous CPEB proteins functionally diverged in terms of activation mechanisms and modes of mRNA binding. The paralog-specific NTRs may have contributed substantially to such functional diversification but their evolutionary history remains largely unexplored. Here, we traced the evolution of vertebrate CPEBs and their LCRs/AARs focusing on primary sequence composition, complexity, repetitiveness, and their possible functional impact on LLPS propensity and prion-likeness. We initially defined these composition- and function-related quantitative parameters for the four human CPEB paralogs and then systematically analyzed their evolutionary variation across more than 500 species belonging to nine major clades of different stem age, from Chondrichthyes to Euarchontoglires, along the vertebrate lineage. We found that the four CPEB proteins display highly divergent, paralog-specific evolutionary trends in composition- and function-related parameters, primarily driven by variation in their LCRs/AARs and largely related to clade stem ages. These findings shed new light on the molecular and functional evolution of LCRs in the CPEB protein family, in both quantitative and qualitative terms, highlighting the emergence of CPEB2 as a proline-rich prion-like protein in younger vertebrate clades, including Primates.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"5 ","pages":"1491735"},"PeriodicalIF":2.8,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11965684/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143782177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ORF1ab codon frequency model predicts host-pathogen relationship in orthocoronavirinae.","authors":"Phillip E Davis, Joseph A Russell","doi":"10.3389/fbinf.2025.1562668","DOIUrl":"10.3389/fbinf.2025.1562668","url":null,"abstract":"<p><p>Predicting phenotypic properties of a virus directly from its sequence data is an attractive goal for viral epidemiology. Here, we focus narrowly on the Orthocoronavirinae clade and demonstrate models that are powerfully predictive for a human-pathogen phenotype with 76.74% average precision and 85.96% average recall on the withheld test set groups, using only Orf1ab codon frequencies. We show alternative examples for other viral coding sequences and feature representations that do not perform well and discuss what distinguishes the models that are performant. These models point to a small subset of features, specifically 5 codons, that are critical to the success of the models. We discuss and contextualize how this observation may fit within a larger model for the role of translation in virus-host agreement.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"5 ","pages":"1562668"},"PeriodicalIF":2.8,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11958986/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143766059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using short-read 16S rRNA sequencing of multiple variable regions to generate high-quality results to a species level.","authors":"Amy S Graham, Fadheela Patel, Francesca Little, Andre van der Kouwe, Mamadou Kaba, Martha J Holmes","doi":"10.3389/fbinf.2025.1484113","DOIUrl":"10.3389/fbinf.2025.1484113","url":null,"abstract":"<p><strong>Introduction: </strong>Short-read amplicon sequencing studies have typically focused on 1-2 variable regions of the 16S rRNA gene. Species-level resolution is limited in these studies, as each variable region enables the characterisation of a different subsection of the microbiome. Although long-read sequencing techniques can take advantage of all 9 variable regions by sequencing the entire 16S rRNA gene, short-read sequencing has remained a commonly used approach in 16S rRNA research. This work assessed the feasibility of accurate species-level resolution and reproducibility using a relatively new sequencing kit and bioinformatics pipeline developed for short-read sequencing of multiple variable regions of the 16S rRNA gene. In addition, we evaluated the potential impact of different sample collection methods on our outcomes.</p><p><strong>Methods: </strong>Using xGen™ 16S Amplicon Panel v2 kits, sequencing of all 9 variable regions of the 16S rRNA gene was carried out on an Illumina MiSeq platform. Mock cells and mock DNA for 8 bacterial species were included as extraction and sequencing controls respectively. Within-run and between-run replicate samples, and pairs of stool and rectal swabs collected at 0-5 weeks from the same infants, were incorporated. Observed relative abundances of each species were compared to theoretical abundances provided by ZymoBIOMICS. Paired Wilcoxon rank sum tests and distance-based intraclass correlation coefficients were used to statistically compare alpha and beta diversity measures, respectively, for pairs of replicates and stool/rectal swab sample pairs.</p><p><strong>Results: </strong>Using multiple variable regions of the 16S ribosomal Ribonucleic Acid (rRNA) gene, we found that we could accurately identify taxa to a species level and obtain highly reproducible results at a species level. Yet, the microbial profiles of stool and rectal swab sample pairs differed substantially despite being collected concurrently from the same infants.</p><p><strong>Conclusion: </strong>This protocol provides an effective means for studying infant gut microbial samples at a species level. However, sample collection approaches need to be accounted for in any downstream analysis.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"5 ","pages":"1484113"},"PeriodicalIF":2.8,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11955629/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143756363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cyclic peptide membrane permeability prediction using deep learning model based on molecular attention transformer.","authors":"Dawei Jiang, Zixi Chen, Hongli Du","doi":"10.3389/fbinf.2025.1566174","DOIUrl":"10.3389/fbinf.2025.1566174","url":null,"abstract":"<p><p>Membrane permeability is a critical bottleneck in the development of cyclic peptide drugs. Experimental membrane permeability testing is costly, and precise <i>in silico</i> prediction tools are scarce. In this study, we developed CPMP (https://github.com/panda1103/CPMP), a cyclic peptide membrane permeability prediction model based on the Molecular Attention Transformer (MAT) frame. The model demonstrated robust predictive performance, achieving determination coefficients (<i>R</i> ^<i>2</i> ) of 0.67 for PAMPA permeability prediction, and <i>R</i> ^<i>2</i> values of 0.75, 0.62, and 0.73 for Caco-2, RRCK, and MDCK cell permeability predictions, respectively. Its performance outperforms traditional machine learning methods and graph-based neural network models. In ablation experiments, we validated the effectiveness of each component in the MAT architecture. Additionally, we analyzed the impact of data pre-training and cyclic peptide conformation optimization on model performance.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"5 ","pages":"1566174"},"PeriodicalIF":2.8,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11933047/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143712533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving acne severity detection: a GAN framework with contour accentuation for image deblurring.","authors":"Philomina Princiya Mascarenhas, M S Sannidhan, Ancilla J Pinto, Dabis Camero, Jason Elroy Martis","doi":"10.3389/fbinf.2025.1485797","DOIUrl":"10.3389/fbinf.2025.1485797","url":null,"abstract":"<p><p>Teledermatology, a growing field of telemedicine, is widely used to diagnose skin conditions like acne, especially in young adults. Accurate diagnosis depends on clear images, but blurring is a common issue in most images. In particular, for acne images, it obscures acne spots and facial contours, leading to inaccurate diagnosis. Traditional methods to address blurring fail to recover fine details, making them unsuitable for teledermatology. To resolve this issue, the study proposes a framework based on generative networks. It comprises three main steps: the Contour Accentuation Technique, which outlines facial features to create a blurred sketch; a deblurring module, which enhances the sketch's clarity; and an image translator, which converts the refined sketch into a color photo that effectively highlights acne spots. Tested on Acne Recognition Dataset, the framework achieved an SSIM of 0.83, a PSNR of 22.35 dB, and an FID score of 10.77, demonstrating its ability to produce clear images for accurate acne diagnosis. Further, the details of research can be found on the project homepage at: https://github.com/Princiya1990/CATDeblurring.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"5 ","pages":"1485797"},"PeriodicalIF":2.8,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11931032/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143702385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Urinary based biomarkers identification and genetic profiling in Parkinson's disease: a systematic review of metabolomic studies.","authors":"Neetu Rani Dhiman, Surbhi Singh, Royana Singh, Anand Kumar, Varun Kumar Singh, Abhishek Pathak, Rameshwar Nath Chaurasia, Vijay Nath Mishra, Niraj Kumar Srivastava, Swati Sahu, Nikhil Pandey, Deepika Joshi","doi":"10.3389/fbinf.2025.1513790","DOIUrl":"10.3389/fbinf.2025.1513790","url":null,"abstract":"<p><strong>Background: </strong>Parkinson's disease is a complex, age-related, neurodegenerative disease associated with dopamine deficiency and both motor and nonmotor deficits. Therapeutic pathways remain challenging in Parkinson's disease due to the low accuracy of early diagnosis, the difficulty in monitoring disease progression, and the limited availability of treatment options.</p><p><strong>Objectives: </strong>Few data are present to identify urinary biomarkers for various ailments, potentially aiding in the diagnosis and tracking of illness progression in individuals with Parkinson's disease. Thus, the analysis of urinary metabolomic biomarkers (UMB) for early and mid-stage idiopathic Parkinson's disease (IPD) is the main goal of this systematic review.</p><p><strong>Methods: </strong>For this study, six electronic databases were searched for articles published up to 23 February 2024: PubMed, Ovid Medline, Embase, Scopus, Science Direct, and Cochrane. 5,377 articles were found and 40 articles were screened as per the eligibility criteria. Out of these, 7 controlled studies were selected for this review. Genetic profiling for gene function and biomarker interactions between urinary biomarkers was conducted using the STRING and Cytoscape database.</p><p><strong>Results: </strong>A total of 40 metabolites were identified to be related to the early and mid-stage of the disease pathology out of which three metabolites, acetyl phenylalanine (a subtype of phenylalanine), tyrosine and kynurenine were common and most significant in three studies. These metabolites cause impaired dopamine synthesis along with mitochondrial disturbances and brain energy metabolic disturbances which are considered responsible for neurodegenerative disorders. Furoglycine, Cortisol, Hydroxyphenylacetic acid, Glycine, Tiglyglycine, Aminobutyric acid, Hydroxyprogesterone, Phenylacetylglutamine, and Dihydrocortisol were also found commonly dysregulated in two of the total 7 studies. 158 genes were found which are responsible for the occurrence of PD and metabolic regulation of the corresponding biomarkers from our study.</p><p><strong>Conclusion: </strong>The current review identified acetyl phenylalanine (a subtype of phenylalanine), tyrosine and kynurenine as potential urinary metabolomic biomarkers for diagnosing PD and identifying disease progression.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"5 ","pages":"1513790"},"PeriodicalIF":2.8,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11931117/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143702390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A standards perspective on genomic data reusability and reproducibility.","authors":"Ishi Keenum, Scott A Jackson, Emiley Eloe-Fadrosh, Lynn M Schriml","doi":"10.3389/fbinf.2025.1572937","DOIUrl":"10.3389/fbinf.2025.1572937","url":null,"abstract":"<p><p>Genomic and metagenomic sequence data provides an unprecedented ability to re-examine findings, offering a transformative potential for advancing research, developing computational tools, enhancing clinical applications, and fostering scientific collaboration. However, effective and ethical reuse of genomics data is hampered by numerous technical and social challenges. The International Microbiome and Multi'Omics Standards Alliance (IMMSA, https://www.microbialstandards.org/) and the Genomic Standards Consortium (GSC, https://gensc.org) hosted a 5-part seminar series \"A Year of Data Reuse\" in 2024 to explore challenges and opportunities of data reuse and reproducibility across disparate domains of the genomic sciences. Addressing these challenges will require a multifaceted approach, including common metadata reporting, clear communication, standardized protocols, improved data management infrastructure, ethical guidelines, and collaborative policies that prioritize transparency and accessibility. We offer strategies to enable responsible and technically feasible data reuse, recognition of data reproducibility challenges, and emphasizing the importance of cross-disciplinary efforts in the pursuit of open science and data-driven innovation.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"5 ","pages":"1572937"},"PeriodicalIF":2.8,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11931119/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143702369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An extended miRNA repertoire in <i>Rattus norvegicus</i>.","authors":"Julienne Lehmann, Ali Yazbeck, Jörg Hackermüller, Sebastian Canzler","doi":"10.3389/fbinf.2025.1545680","DOIUrl":"10.3389/fbinf.2025.1545680","url":null,"abstract":"","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"5 ","pages":"1545680"},"PeriodicalIF":2.8,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11931075/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143702381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MetaComBin: combining abundances and overlaps for binning metagenomics reads.","authors":"Francesco Tomasella, Cinzia Pizzi","doi":"10.3389/fbinf.2025.1504728","DOIUrl":"10.3389/fbinf.2025.1504728","url":null,"abstract":"<p><strong>Introduction: </strong>Metagenomics is the discipline that studies heterogeneous microbial samples extracted directly from their natural environment, for example, from soil, water, or the human body. The detection and quantification of species that populate microbial communities have been the subject of many recent studies based on classification and clustering, motivated by being the first step in more complex pipelines (e.g., for functional analysis, de novo assembly, or comparison of metagenomes). Metagenomics has an impact on both environmental studies and precision medicine; thus, it is crucial to improve the quality of species identification through computational tools.</p><p><strong>Methods: </strong>In this paper, we explore the idea of improving the overall quality of metagenomics binning at the read level by proposing a computational framework that sequentially combines two complementary read-binning approaches: one based on species abundance determination and another one relying on read overlap in order to cluster reads together. We called this approach MetaComBin (metagenomics combined binning).</p><p><strong>Results and discussion: </strong>The results of our experiments with the MetaComBin approach showed that the combination of two tools, based on different approaches, can improve the clustering quality in realistic conditions where the number of species is not known beforehand.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"5 ","pages":"1504728"},"PeriodicalIF":2.8,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11912761/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143652436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}