Martynas Baltušis

Martynas Baltušis

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Martynas Baltušis

Technical University of Denmark

Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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2 October 2026 in Bioinformatics
Verified
Journal Article
Open access
MVMartina Vojtková
Martina Vojtková
MBMartynas Baltušis
Martynas Baltušis
HMHannah-Marie Martiny
Hannah-Marie Martiny
ABAmulya Baral
Amulya Baral
NPNikiforos Pyrounakis
Nikiforos Pyrounakis
PMPatrick Munk
Patrick Munk
Motivation: Antimicrobial resistance databases are central to genomic surveillance, but resistance determinants remain distributed across resources with different scopes, structures, and annotations. Results: We developed PanRes, a curated resistance database of 11 717 genes integrating acquired and latent determinants of antibiotic, biocide, and metal resistance within a unified ontology. We predicted representative protein structures and clustered them by structural similarity, grouping proteins into 505 high-confidence structurally conserved clusters coherent despite sequence divergence. Their structure-guided alignments were used to build Hidden Markov Models (HMMs) for remote homology search. In seven wastewater metagenomes from five European cities, PanRes 3D-based HMMs expanded detection beyond what was possible with BLAST, with 35.3% of retained hits identified only by the HMMs and generally showing greater divergence from known proteins. For beta-lactamases, several proteins retained beta-lactamase-like folds and catalytic geometry despite weak sequence similarity. Availability and implementation: PanRes is available through an interactive web platform (https://panres.rambio.dk/), a structure-informed resource for exploring the whole resistome. The database, HMM profiles, and ontology are available at Zenodo (10.5281/zenodo.22876216).

22 June 2026 in bioRxiv
Verified
Preprint
Open access
MVMartina Vojtková
Martina Vojtková
MBMartynas Baltušis
Martynas Baltušis
HMHannah-Marie Martiny
Hannah-Marie Martiny
ABAmulya Baral
Amulya Baral
NPNikiforos Pyrounakis
Nikiforos Pyrounakis
PMPatrick Munk
Patrick Munk
Antimicrobial resistance databases are central to genomic surveillance, but resistance determinants remain distributed across resources with different scopes, structures, and annotations. We developed PanRes, a curated resistance database of 11,717 genes integrating acquired and latent determinants of antibiotic, biocide, and metal resistance within a unified ontology. We predicted representative protein structures and clustered them by structural similarity, grouping proteins into 598 structurally conserved clusters coherent despite sequence divergence. Their structure-guided alignments were used to build Hidden Markov Models (HMMs) for remote homology search. In wastewater metagenomes from seven European cities, PanRes 3D-based HMMs expanded detection beyond high-confidence BLAST, with 35.2% of retained hits identified only by the HMMs and generally showing greater divergence from known proteins. For beta-lactamases, several proteins retained beta-lactamase-like folds and catalytic geometry despite weak sequence similarity. PanRes is available through an interactive web platform (https://panres.rambio.dk/), a structure-informed resource for exploring the whole resistome.