🐾NeKo: Automate Biological Network Construction🛠️,🧜♀️kMermaid: Ultrafast Metagenomic Read Assignment,👾PAQman: Reference-Free Long-Read Evaluation
Stay Updated with the Latest in Bioinformatics!
Issue: 104 | Date: 19 September 2025
👋 Welcome to the Bioinformer Weekly Roundup!
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🔬 Featured Research
This article talks about the discovery of tandem SH3-binding motifs that interact with p47phox-related proteins, revealing a novel motif pattern and binding mechanism. Using deep mutational scanning and protein complementation assays, the study shows that residues adjacent to canonical motifs significantly influence binding affinity and specificity. Structural predictions suggest these motifs bind outside traditional SH3 pockets, indicating a broader interaction interface. This expands our understanding of SH3 domain interactions and opens avenues for identifying new motif instances and therapeutic targets.
This article talks about a spatial transcriptomics study mapping aging across multiple mouse organs over time. It reveals organ-specific and shared gene dysregulation, with immune system activation being a prominent aging signature. The study compares aging with infection-induced changes, identifying shared molecular pathways like complement activation and Serpin expression. These findings highlight tissue-specific aging mechanisms and potential therapeutic targets.
This article talks about how cigarette smoke affects Crohn’s disease (CD) and ulcerative colitis (UC) differently through the GPR15 receptor. Smoke exposure worsens CD by increasing Th17 cells, while it alleviates UC by boosting Treg cells via GPR15. Deleting Gpr15 reversed these effects in mouse models, confirming its role in disease modulation. The study provides mechanistic insights into the divergent impact of smoking on IBD subtypes.
This article talks about a Phase II trial evaluating sintilimab plus anlotinib in treatment-naïve metastatic colorectal cancer (mCRC) patients. The combination showed promising efficacy with an objective response rate of ~47% and a disease control rate of ~87%. Median progression-free survival was 8.6 months, and overall survival reached 22.9 months. Liver metastases and FLT mutations were linked to poorer outcomes, while the safety profile remained manageable.
This study investigates the diversity of microbial communities within breast tumours and their potential roles in tumor development and treatment response. It examines spatial variation in microbial composition and its correlation with immune modulation and therapeutic outcomes. The findings suggest directions for future research on microbiome-based interventions.
Researchers conducted integrated transcriptomic and metabolomic profiling to identify IbADCL1 as a key gene regulating folate biosynthesis in sweet potato storage roots. The study analyses gene expression patterns and metabolite accumulation linked to folate pathways. Results contribute to understanding genetic control of nutrient content in root crops.
Chloroxylenol disrupts Rana chensinensis tadpoles metabolic homeostasis via gut microbiota-dysregulated: A multi-omics perspective | Aquatic Toxicology
This study explores the impact of chloroxylenol exposure on Rana chensinensis tadpoles using multi-omics approaches. It reports alterations in gut microbiota composition and associated metabolic disturbances. The findings highlight potential ecological risks of disinfectant exposure in aquatic environments.
Metabolic plasticity and gut microbiome synergy underlie high-altitude adaptation in the plateau frog Rana kukunoris: A multi-omics perspective | Ecotoxicology and Environmental Safety
Using multi-omics analysis, researchers examined how Rana kukunoris adapts to high-altitude environments through metabolic flexibility and gut microbiome interactions. The study identifies changes in energy metabolism and microbial composition linked to altitude stress. It provides insights into physiological and ecological adaptation mechanisms in amphibians.
🧰 Latest Tools
NeKo is a Python-based tool designed to automate biological network construction by integrating molecular interactions from multiple databases. It allows users to define molecular entities of interest and apply customizable strategies to build knowledge-driven networks. The tool supports filtering by interaction types and demonstrates its utility through applications in medulloblastoma transcriptomics and drug synergy modelling.
Source code is available here.
THLANet is a deep learning framework developed to predict T-cell receptor (TCR) binding to peptide-HLA complexes using sequence data. It incorporates ESM-2 embeddings and Transformer modules to enhance feature representation and generalization. The model is validated using scTCR-seq and clinical datasets, offering insights into TCR-pHLA interactions and structural binding mechanisms.
Source code is available here.
HyperACP introduces a hybrid computational framework for anticancer peptide classification, combining deep protein representation with adaptive sampling and interpretability modules. It utilizes the ESMC model for feature extraction and ANBS for addressing class imbalance. SHAP-Res provides residue-level insights, and evaluations demonstrate consistent performance across multiple datasets and metrics.
Source code is available here.
kMermaid: Ultrafast metagenomic read assignment to protein clusters by hashing of amino acid k-mer frequencies | PLOS Computational Biology
kMermaid is a method for ultrafast metagenomic read assignment to protein clusters using amino acid k-mer hashing. It maps reads to taxa-agnostic homologous protein groups, resolving multi-mapping issues and enabling functional analysis. The tool is evaluated on simulated and human faecal data, offering efficient classification with fixed memory usage.
Source code is available here.
Modanovo introduces a deep learning model for de novo peptide sequencing that incorporates post-translational modifications (PTMs). It uses experimental spectra from both in vivo and synthetic peptides to improve identification of modified peptides. The model is designed to handle diverse PTMs and supports accurate localization of modifications without relying on reference databases.
Source code is available here.
PAQman presents a framework for evaluating long-read eukaryotic genome assemblies without requiring a reference genome. It uses an ensemble of metrics to assess assembly quality across multiple dimensions, including contiguity, completeness, and structural accuracy. The tool is designed to support benchmarking of assemblers in complex genomic contexts.
Source code is available here.
DiscERN is a genome mining tool that identifies biosynthetic gene clusters (BGCs) based on evolutionary relationships. It enables discovery of natural products by analyzing gene cluster architectures and their conservation across species. The tool integrates comparative genomics and functional annotation to uncover novel biosynthetic pathways.
Source code is available here.
Recommended by LinkedIn
The Deodifier is a tool designed to detect peptide sequence changes caused by post-translational modifications such as deamidation and pyroglutamic acid formation. These changes can lead to incorrect taxonomic assignments in palaeoproteomic studies. Tested on archaeological datasets, the tool revealed that such misassignments are significantly under-reported and occur in multiple forms, affecting taxonomic specificity and accuracy.
Source code is available here.
🗞️ Community News
The 15th AACR Cancer Progress Report outlines recent developments in cancer research, including statistics on incidence, mortality, and survivorship. It highlights advances in blood cancer treatment that have influenced therapies for solid tumors and other diseases. The report discusses the impact of NIH funding instability on research progress and includes patient narratives to illustrate scientific outcomes. It concludes with a call for increased federal support for cancer-related agencies.
Researchers at the University of Rome La Sapienza assembled a reference-quality genome for the RPE-1 human epithelial cell line using long-read sequencing and Hi-C techniques. The study resolves centromeres and provides haplotype-resolved maternal and paternal genomes. This genome improves alignment accuracy and supports isogenomic mapping, enhancing the precision of genomic and epigenomic studies. The work contributes to efforts toward building a pangenome of experimental cell lines.
Researchers at the University of Illinois investigated the evolutionary relationship between dipeptide sequences, protein domains, and transfer RNA (tRNA). Their findings suggest a shared evolutionary timeline among these molecular components, offering insights into the emergence of the genetic code. The study supports a model where protein interactions preceded RNA-based mechanisms in early life. It also explores the dual coding systems of life—genetic and protein—and the role of aminoacyl tRNA synthetases in maintaining their connection.
Researchers at the German Center for Infection Research and Heidelberg University Hospital identified RNA:DNA hybrids (R-loops) as structural guides for HIV-1 integration into the human genome. The study mapped these hybrids in immune cells and found that HIV-1 preferentially integrates at these sites. The enzyme Aquarius was shown to facilitate this process by interacting with HIV-1 integrase and unwinding R-loops. Reduced Aquarius expression led to decreased integration at R-loop-rich regions, suggesting a mechanistic role in viral genome targeting.
A study from Shibaura Institute of Technology synthesized vitamin K analogues conjugated with retinoic acid to enhance neuroactive properties. These compounds showed approximately threefold increased potency in inducing neuronal differentiation compared to natural vitamin K. The analogues activated transcription via mGluR1 and demonstrated effective blood-brain barrier penetration in mice. The findings suggest a mechanism by which vitamin K analogues may influence neuronal regeneration relevant to neurodegenerative conditions.
🗓️ Upcoming Events
This event explores modular solutions for bispecific antibody (bsAb) development, covering design, screening, and functional characterization. It highlights platforms for rapid bsAb production, biology-driven lead identification, and in vitro assays across immune targets. The session also discusses PK/PD/Tox workflows and in vivo models supporting preclinical advancement of next-generation bsAb therapeutics.
This event discusses molecular profiling of gut epithelial tissue to understand disease mechanisms and identify biomarkers in inflammatory bowel diseases. It highlights challenges in dissociating primary cells from intestinal tissue and emphasizes the importance of maintaining cell viability for downstream analysis. The session also explores patient-derived organoid models and profiling strategies for clinically sourced samples.
This webinar presents Lab-in-the-Loop, an AI-integrated framework combining generative models, predictive analytics, and active learning with lab testing to accelerate therapeutic antibody discovery. The approach enables iterative optimization across targets like EGFR, IL-6, HER2, and OSM, improving binding affinity and reducing experimental workload. The session highlights how AI can streamline biologic drug development workflows.
🎓 Educational Corner
The {admiralneuro} R package, an extension of {admiral}, is designed for neurological disease data modeling, with initial focus on Alzheimer’s disease. It includes datasets for demographics, neurological exams, PET scan agents, and supplemental data for SUVR calculations. A key feature is compute_centiloid(), which standardizes amyloid PET imaging across tracers and pipelines. The package also provides templates and vignettes for creating ADaM datasets like ADTPET and ADAPET. Future updates aim to support Parkinson’s-related pathology and olfactory impairment analysis.
The article documents a hands-on exploration of DNA assembly, BLAST, and MLST using data from a Neisseria meningitidis outbreak. It covers assembling raw Illumina reads with SKESA, extracting 16S rRNA using barrnap, and identifying species via BLAST. MLST is used for strain typing, and capsule genes are examined for serogroup classification. The workflow integrates terminal and R-based tools, with emphasis on reproducibility and learning through real outbreak data.
Seqera AI is introduced as a bioinformatics agent tailored for the scientific lifecycle, integrating Nextflow development best practices. It supports pipeline generation, validation, and debugging, with built-in awareness of nf-core standards. The platform enables automatic testing and self-correction of code using sample data. Native integration with MultiQC is planned to allow in-line analysis of pipeline results. The tool aims to streamline bioinformatics workflows through contextual assistance and reproducibility.
This tutorial introduces uv, a Rust-based tool for Python project and package management. It details uv’s capabilities including fast dependency installation, virtual environment creation, Python version control, and project scaffolding. The article walks through initializing a project, managing dependencies via pyproject.toml and uv.lock, and handling development tools. It emphasizes uv’s integration of functionalities typically spread across multiple Python tools.
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