LegionProfiler: a computational tool for the identification of virulence factors and classification of Legionella pneumophila serogroup 1 isolates.

{"sci_version": "1.0", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40726111", "kind": "science-record", "revision": 2, "content_hash": "sha256:408975bab626f3905e3c1e332ac69241e434e4b2d3b59fcb582d9af22dc4b883", "created_at": "2026-11-01T20:30:49Z", "updated_at": "2026-11-01T21:35:32Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "LegionProfiler: a computational tool for the identification of virulence factors and classification of Legionella pneumophila serogroup 1 isolates.", "doi": "10.1093/bioinformatics/btaf398", "pmid": "40726111", "authors": ["Oluwafemi A Sarumi", "Wilhelm Bertrams", "Oliver Schwengers", "Jan-Paul Herrmann", "Torsten Hain", "Laurine Kieper", "Markus Petzold", "Alexander Goesmann", "Bernd T Schmeck", "Dominik Heider"], "journal": "Bioinformatics (Oxford, England)", "year": 2025, "abstract": "SUMMARY: Legionella pneumophila has significantly contributed to multiple cases of pneumonia with a high rate of mortality globally. Its ability to exploit host mechanisms through several expressed virulence factors poses challenges for diagnosis, treatment, and outbreak control. To address this, we developed LegionProfiler, a computational tool that swiftly identifies virulence factor protein domains within genome assemblies of Legionella pneumophila serogroup 1 isolates and classifies them into high- or low-virulence groups. LegionProfiler automates the probing of genome assemblies for virulence-associated protein domains and determines the isolate's potential to cause severe pneumonia infection. The LegionProfiler workflow is made available through a user-friendly interface to enhance technical control of infectious sources and adds important insights to the general epidemiology of clinical isolates. It could also support the development of targeted therapeutic strategies that will improve patient treatment.\nAVAILABILITY AND IMPLEMENTATION: LegionProfiler is freely accessible as a web service at https://legionprofiler.uni-muenster.de, and can also be run locally in a Docker container. The source code can be found at https://imigitlab.uni-muenster.de/heiderlab/legionprofiler or at Zenodo (DOI: 10.5281/zenodo.15592325).", "claims": [{"id": "claim-method", "statement": "Thus, we used the Huber regressor model to develop a predictive model that effectively captures the relationship between the identified virulence factors in the Sg 1 isolates and their corresponding virulence groups as described in Fig. 1.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40726111", "locator": "sections[6] \"2.4 Predictive model\" paragraph 2", "quote": "Thus, we used the Huber regressor model to develop a predictive model that effectively captures the relationship between the identified virulence factors in the Sg 1 isolates and their corresponding virulence groups as described in Fig. 1."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data underlying this article are available at https://imigitlab.uni-muenster.de/heiderlab/legionprofiler.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40726111", "locator": "sections[14] \"Data availability\" paragraph 2", "quote": "The data underlying this article are available at https://imigitlab.uni-muenster.de/heiderlab/legionprofiler."}], "state": "complete"}, {"id": "claim-target-result", "statement": "As shown in Table 1, Huber regression outperformed the other models, achieving the highest accuracy of 0.72 and MCC of 0.44.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40726111", "locator": "sections[7] \"3 Results\" paragraph 2", "quote": "As shown in Table 1, Huber regression outperformed the other models, achieving the highest accuracy of 0.72 and MCC of 0.44."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "As shown in Table 1, Huber regression outperformed the other models, achieving the highest accuracy of 0.72 and MCC of 0.44.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:40726111"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "blocked", "blocked_on": "data:accession_absent", "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": [], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": [], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:obtain_source_data blocked on data:accession_absent"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40726111", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1093/bioinformatics/btaf398", "sha256": "sha256:37879249dab1de2a731f0bb894024c6db18f0d2da300d1483d8dde73fe0554ce", "bytes": 21721, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1093/bioinformatics/btaf398", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC12304514", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}], "gaps": []}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": null, "specific": null, "label": "Huber regressor", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Thus, we used the Huber regressor model to develop a predictive model that effectively captures the relationship between the identified virulence factors in the Sg 1 isolates and their corresponding virulence groups as described in Fig. 1."}}], "targets": [], "gaps": ["method.reader_named_unmapped"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "blocked", "tier": "R4", "blocking_axis": "data", "blocked_on": "data:accession_absent", "axes": {"method": {"tier": "R4", "expressible": false, "required_operations": [], "missing_operations": [], "basis": "The reader quoted the method the paper names (Huber regressor), but the corpus's method extractor could not map it onto a DSL operation, so the method is published but not expressible."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R4", "reachable": false, "accessions": [], "resolved_accessions": [], "statements": ["The data underlying this article are available at https://imigitlab.uni-muenster.de/heiderlab/legionprofiler."], "basis": "The paper names no accession to its source data, so the data has to come from the authors."}}, "can_run": {"dsl_operations": [], "assets": ["source:pmid:40726111"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:None"]}, "gaps": ["data:accession_absent"]}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:57:58Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 6685, "completion_tokens": 1567, "cached_tokens": 264}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:40726111", "type": "paper", "label": "pmid:40726111"}, {"id": "source:pmid:40726111", "type": "manuscript", "label": "PMID 40726111 full text"}, {"id": "data:geo:None", "type": "dataset", "label": "GEO None"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:40726111", "type": "paper", "label": "pmid:40726111"}, {"id": "source:pmid:40726111", "type": "manuscript", "label": "PMID 40726111 full text"}, {"id": "data:geo:None", "type": "dataset", "label": "GEO None"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-40726111", "type": "extraction", "used": ["source:pmid:40726111"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-None", "type": "accession_resolution", "used": ["data:geo:None"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:40726111", "parent_hash": "sha256:b0302e53e76f033aed1ec08dd66a62753706146d94af47f1ccb68b2b8e7d8532", "fork_of": null, "generation": 1}, "gaps": ["execution.not_run", "method.reader_named_unmapped", "review.human_critique", "review.independent_reader", "review.machine_critique", "step:obtain_source_data blocked on data:accession_absent"]}