Biology subjects

Stravopodis, D. J.

Publications and source records attributed to Stravopodis, D. J..

7 recordsLinked to original sources

bioRxiv2026

ArthroVerse: mapping protein family diversity across arthropod-associated microbiomes

Metagenomic studies of arthropod-associated microbiomes have generated vast amounts of sequence data, yet the functional and structural organization of these proteins remains largely unexplored. Here, we present ArthroVerse, the first comprehensive database of protein families derived from arthropod-associated metagenomes. Non-redundant protein families were generated after rigorous filtering, deduplication, and clustering. The protein families were further annotated with microbial taxonomy, host associations, protein structural information, and Carbohydrate-active enzymes (CAZyme) predictions. The resulting dataset integrates both metagenomic and reference genome-derived proteins, enabling systematic exploration of functional diversity, evolutionary relationships, and host-microbe interactions in insect microbiomes. ArthroVerse provides a valuable resource for the study of microbial ecology and arthropod physiology, offering unprecedented insight into the protein landscape of insect-associated microbial communities.

bioinformatics↗

bioRxiv2025

A UNIQUOME BASED METHOD FOR THE PROTEIN IDENTIFICATION BY MASS SPECTROMETRY

Protein identification by mass spectrometry is a pivotal step in proteomics. Numerous methods have been developed to securely and effectively identify proteins derived from experimentally detected peptides by mass spectrometry. The dominant approach is based on the assumption that each experimentally identified peptide can be matched with a peptide included in a database of peptide sequences, generated by in silico digestion of proteins with a specific proteolytic enzyme. In this way, the protein containing the peptide can be identified. In a more advanced approach, the proteins and their in silico-digested peptides in the database are transformed into theoretical mass spectrometry spectra, and search engines match the experimentally obtained spectra to these theoretical spectra generated from protein and peptide sequences. We developed an alternative method for protein identification using Core Unique Peptides (CrUPs) and the Uniquome, termed as Uniquome-Based Protein Identification Method (UB-PIM). According to this method, instead of searching for peptides in the database of in silico-digested peptides, we search for CrUPs within the experimentally obtained peptides by mass spectrometry. If a peptide contains at least one CrUP, it can be directly correlated to the protein from which the CrUP is derived. Because of the unique nature of CrUPs, peptides obtained by MS can securely and uniquely identify the protein of origin. This provides a reference space in which even single-peptide identifications can achieve high specificity, reducing the ambiguity caused by shared or homologous sequences and improving the interpretability of MS data. Furthermore, UB-PIM can be applied to any type of peptide and is effective with both Data-Independent Acquisition (DIA) and Data-Dependent Acquisition (DDA) approaches, as well as with top-down and bottom-up proteomics. This allows confident protein identification from minimal evidence, expands the scope of detectable proteins, and remains computationally efficient, rapid, and universally applicable.

bioinformatics↗

bioRxiv2025

metagRoot: A comprehensive database of protein families associated with plant root microbiomes

The plant root microbiome is vital in plant health, nutrient uptake, and environmental resilience. To explore and harness this diversity, we present metagRoot, a specialized and enriched database focused on the protein families of the plant root microbiome. MetagRoot integrates metagenomic, metatranscriptomic, and reference genome-derived protein data to characterize 71,091 enriched protein families, each containing at least 100 sequences. These families are annotated with multiple sequence alignments, CRISPR elements, Hidden Markov Models, taxonomic and functional classifications, ecosystem and geolocation metadata, and predicted 3D structures using AlphaFold2. MetagRoot is a powerful tool for decoding the molecular landscape of root-associated microbial communities and advancing microbiome-informed agricultural practices by enriching protein family information with ecological and structural context. The database is available at https://pavlopoulos-lab.org/metagroot/ or https://www.metagroot.org

bioinformatics↗

bioRxiv2024

ARID1A-induced transcriptional reprogramming rewires signalling responses to drug treatment in melanoma

Resistance to BRAF and MAPK inhibitors is a significant challenge in melanoma treatment, driven by adaptive and acquired mechanisms that allow tumour cells to evade therapy. Here, we examined early signalling responses to single and combined BRAF and MAPK inhibition in a BRAFV600E, drug-sensitive melanoma cell line and a drug-resistant ARID1A-knockout (KO) derivative. ARID1A, frequently mutated in melanoma, is associated with resistance and immune evasion. Using an innovative systems biology approach that integrates transcriptomics, proteomics, phosphoproteomics, and functional kinomics through matrix factorization and network analysis, we identified key signalling alterations and resistance mechanisms. We found that ARID1A-KO cells exhibited transcriptional rewiring, sustaining MAPK1/3 and JNK activity post-treatment, bypassing feedback sensitivity observed in parental cells. This rewiring suppressed PRKD1 activation, increased JUN activity--a central resistance network node--and disrupted PKC dynamics through elevated basal RTKs (e.g., EGFR, ROS1) and Ephrin receptor activity post-treatment. ARID1A mutations also reduced HLA-related protein expression and enriched extracellular matrix components, potentially limiting immune infiltration and reducing immunotherapy efficacy. Our graph-theoretical multi-omics approach uncovered novel resistance-associated signalling pathways, identifying PRKD1, JUN, and NCK1 as critical nodes. While receptor activation redundancies complicate single-target therapies, they also present opportunities for combination strategies. This study highlights ARID1As role in reshaping signalling and immune interactions, offering new insights into melanoma resistance mechanisms. By identifying actionable targets, including JUN and immune pathways, we provide a foundation for developing integrated therapeutic strategies to overcome resistance in BRAF/MAPK inhibitor-treated melanoma. One sentence summaryThis study reveals how ARID1A-mediated transcriptional rewiring drives resistance to MAPK inhibitors in melanoma by altering signalling pathways, immune interactions, and receptor dynamics, highlighting potential targets for combinatorial therapies.

systems biology↗

bioRxiv2024

Uniquome: Construction and Decoding of a Novel Proteomic Atlas that Contains New Peptide Entities

Cellular and molecular uniqueness has recently gained eminent importance, due to the large amount of data produced by "-omics" technologies. Herein, we have constructed and decoded the "Uniquome", by introduction of the new peptide entities: (a) "Core Unique Peptide" (CrUP), defined as the peptide whose sequence is accommodated, specifically and exclusively, only in one protein in a given proteome, and also bears the minimum length of amino acid sequence; (b) "Composite Unique Peptide" (CmUP), defined as the peptide composed by the linear unification of CrUPs, when two or more successive in order CrUPs overlap one another; (c) "Family Unique Peptide" (FUP), defined as the CrUPs that are common between all members of a given family, but unique only for the protein members of the particular family, and (d) "Universal Unique Peptides" (UUPs), which are the common CrUPs in a given protein across organisms, carrying the important ability to securely identify a protein independently of an organism. By these entities as tool-box, we have analyzed the human and model organisms, respective, proteomes. We demonstrate that these novel peptide entities play a crucial role for protein identification, protein-function prediction, cell physiology, tissue pathology, therapeutic oncology and translational medicine. Finally, we suggest that across species the conserved sequences are not DNA nucleotides but CrUPs entities. One-Sentence SummaryWe constructed and decoded the "Uniquome", by introducing the new peptide entities Core Unique Peptide, Composite Unique Peptide, Family Unique Peptide and Universal Unique Peptide

molecular biology↗

bioRxiv2023

Biological aging of two innate behaviors of Drosophila melanogaster: escape climbing versus courtship learning and memory

Motor and cognitive aging can severely affect life quality of elderly people and burden health care systems. In search for diagnostic behavioral biomarkers, it has been suggested that walking speed can predict forms of cognitive decline, but in humans, it remains challenging to separate the effects of biological aging and lifestyle. We examined a possible association of motor and cognitive decline in Drosophila, a genetic model organism of healthy aging. Long term courtship memory is present in young flies but absent already during mid life (4-8 weeks). By contrast, courtship learning index and short term memory (STM) are surprisingly robust and remain stable through mid (4-8 weeks) and healthy late life (>8 weeks), until courtship performance collapses suddenly at [~]4.5 days prior to death. By contrast, climbing speed declines gradually during late life (>8 weeks). The collapse of courtship performance and short term memory close to the end of life are not related to the gradual late life decline in climbing speed. Thus, during healthy aging in Drosophila, climbing and courtship motor behaviors decline differentially, unlikely share a common cause, and motor and cognitive performance decline are not closely associated to each other.

animal behavior and cognition↗

bioRxiv2021

FLAME: a web tool for functional and literature enrichment analysis of multiple gene lists

Functional enrichment is a widely used method for interpreting experimental results by identifying classes of proteins/genes associated with certain biological functions, pathways, diseases or phenotypes. Despite the variety of existing tools, most of them can process a single list per time, thus making a more combinatorial analysis more complicated and prone to errors. In this article, we present FLAME, a web tool for combining multiple lists prior to enrichment analysis. Users can upload several lists of preference and use interactive UpSet plots, as an alternative to Venn diagrams, to handle unions or intersections among the given input files. Functional and literature enrichment along with gene conversions are offered by g:Profiler and aGOtool applications for 197 organisms. In its current version, FLAME can analyze genes/proteins for related articles, Gene Ontologies, pathways, annotations, regulatory motifs, domains, diseases, phenotypes while it can also generate protein-protein interactions derived from STRING. We have herein validated FLAME by interrogating gene expression data associated with the sensitivity of the distal part of the large intestine to experimental colitis-propelled colon cancer. The FLAME application comes with an interactive user-friendly interface which allows easy list manipulation and exploration, while results can be visualized as interactive and parameterizable heatmaps, barcharts, Manhattan plots, networks and tables. AvailabilityFLAME application: http://flame.pavlopouloslab.info Codehttps://github.com/PavlopoulosLab/FLAME

bioinformatics↗