Biology subjects

Nikolopoulos, N.

Publications and source records attributed to Nikolopoulos, N..

3 recordsLinked to original sources

bioRxiv2025

High-precision Biomedical Text Corpora for Multi-Entity Recognition: A CoDiet study

We present here five biomedical, multi-entity corpora that can be used as benchmarks for named-entity recognition (NER), targeted to literature on metabolic syndrome. The CoDiet-Gold corpus contains annotations for 500 full-text publications and 348,406 annotations. It is divided into CoDiet-Gold-public (450 documents) and CoDiet-Gold-private (50 documents). Each document was independently annotated by two human experts, with disagreements fully adjudicated by a third expert. The CoDiet-Electrum corpus (2,998,273 annotations) contains 4,423 publications that were annotated using case-insensitive matching of the surface forms with punctuation ignored, found in CoDiet-Gold-public. Finally, for the same 4,423 documents, two fully machine annotated corpora CoDiet-Bronze (2,938,738 annotations) and CoDiet-Silver (2,298,988 annotations), were created by utilising existing NER algorithms to annotate these. These corpora contain categories (organisms, disease, genes, proteins, metabolites) that add depth to existing corpora, as well as new categories that do not appear in other corpora (food, dietary methods, sample types, computational methods, study methodology, population characteristics, data types, and microbiome).

bioinformatics↗

bioRxiv2023

Structure and methyl-lysine binding selectivity of the HUSH complex subunit MPP8

The Human Silencing Hub (HUSH) guards the genome from the pathogenic effects of retroelement expression. Composed of MPP8, TASOR, and Periphilin-1, HUSH recognizes actively transcribed retrotransposed sequences by the presence of long (>1.5-kb) nascent transcripts without introns. HUSH recruits effectors that alter chromatin structure, degrade transcripts, and deposit transcriptionally repressive epigenetic marks. Here, we report the crystal structure of the C-terminal domain (CTD) of MPP8 necessary for HUSH activity. The MPP8 CTD consists of five ankyrin repeats followed by a domain with structural homology to the PINIT domains of Siz/PIAS-family SUMO E3 ligases. AlphaFold-Multimer modeling predicts that the MPP8 CTD forms extended interaction interfaces with a SPOC domain and a domain with a novel fold in TASOR. The MPP8 chromodomain, known to bind the repressive mark H3K9me3, binds with similar or higher affinity to sequences in the H3K9 methyltransferase subunits SETDB1, ATF7IP, G9a, and GLP. Hence, MPP8 promotes heterochromatinization by recruiting H3K9 methyltransferases. Our work identifies novel structural elements in MPP8 required for HUSH complex assembly and silencing, thereby fulfilling vital functions in controlling retrotransposons.

biochemistry↗

bioRxiv2022

Structure-Function analysis of Lactiplantibacillus plantarum DltE reveals D-alanylated lipoteichoic acids as direct symbiotic cues supporting Drosophila juvenile growth

Metazoans establish mutually beneficial interactions with their resident microorganisms. However, our understanding of the microbial cues contributing to host physiology remains elusive. Previously, we identified a bacterial machinery encoded by the dlt operon involved in Drosophila melanogasters juvenile growth promotion by Lactiplantibacillus plantarum. Here, using crystallography combined with biochemical and cellular approaches, we investigate the physiological role of an uncharacterized protein (DltE) encoded by this operon. We show that LTAs but not WTAs are D-alanylated in Lactiplantibacillus plantarumNC8 cell envelope and demonstrate that DltE is a D-Ala carboxyesterase removing D-Ala from LTA. Using the mutualistic association of L. plantarumNC8 and Drosophila melanogaster as a symbiosis model, we establish that D-Ala-LTAs are direct symbiotic cues supporting intestinal peptidase expression and juvenile growth in Drosophila. Our results pave the way to probing the contribution of D-Ala-LTA to host physiology in other symbiotic models.

microbiology↗