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Abstract Background Implementation of clinical metagenomics and pathogen genomic surveillance can be particularly challenging due to the lack of bioinformatics tools and/or expertise. In order to face this challenge, we have previously developed INSaFLU, a free web-based bioinformatics platform for virus next-generation sequencing data analysis. Here, we considerably expanded its genomic surveillance component and developed a new module (TELEVIR) for metagenomic virus identification. Results The routine genomic surveillance component was strengthened with new workflows and functionalities, including (i) a reference-based genome assembly pipeline for Oxford Nanopore technologies (ONT) data; (ii) automated SARS-CoV-2 lineage classification; (iii) Nextclade analysis; (iv) Nextstrain phylogeographic and temporal analysis (SARS-CoV-2, human and avian influenza, monkeypox, respiratory syncytial virus (RSV A/B), as well as a “generic” build for other viruses); and (v) algn2pheno for screening mutations of interest. Both INSaFLU pipelines for reference-based consensus generation (Illumina and ONT) were benchmarked against commonly used command line bioinformatics workflows for SARS-CoV-2, and an INSaFLU snakemake version was released. In parallel, a new module (TELEVIR) for virus detection was developed, after extensive benchmarking of state-of-the-art metagenomics software and following up-to-date recommendations and practices in the field. TELEVIR allows running complex workflows, covering several combinations of steps (e.g., with/without viral enrichment or host depletion), classification software (e.g., Kaiju, Kraken2, Centrifuge, FastViromeExplorer), and databases (RefSeq viral genome, Virosaurus, etc.), while culminating in user- and diagnosis-oriented reports. Finally, to potentiate real-time virus detection during ONT runs, we developed findONTime, a tool aimed at reducing costs and the time between sample reception and diagnosis. Conclusions The accessibility, versatility, and functionality of INSaFLU-TELEVIR are expected to supply public and animal health laboratories and researchers with a user-oriented and pan-viral bioinformatics framework that promotes a strengthened and timely viral metagenomic detection and routine genomics surveillance. INSaFLU-TELEVIR is compatible with Illumina, Ion Torrent, and ONT data and is freely available at https://insaflu.insa.pt/ (online tool) and https://github.com/INSaFLU (code).

Abstract Machine learning (ML) algorithms were explored for the classification of the UV–Vis absorption spectrum of organic molecules based on molecular descriptors and fingerprints generated from 2D chemical structures. Training and test data (~ 75 k molecules and associated UV–Vis data) were assembled from a database with lists of experimental absorption maxima. They were labeled with positive class (related to photoreactive potential) if an absorption maximum is reported in the range between 290 and 700 nm (UV/Vis) with molar extinction coefficient (MEC) above 1000 Lmol−1 cm−1, and as negative if no such a peak is in the list. Random forests were selected among several algorithms. The models were validated with two external test sets comprising 998 organic molecules, obtaining a global accuracy up to 0.89, sensitivity of 0.90 and specificity of 0.88. The ML output (UV–Vis spectrum class) was explored as a predictor of the 3T3 NRU phototoxicity in vitro assay for a set of 43 molecules. Comparable results were observed with the classification directly based on experimental UV–Vis data in the same format.

Introdução/Objetivo: A epidemiologia das infecções por Staphylococcus aureus resistente a meticilina (MRSA) é dinâmica, havendo aumento na prevalência de MRSA ocasionando infecções adquiridas na comunidade (CA) ou relacionadas à assistência à saúde (IRAS). O objetivo deste estudo foi avaliar a epidemiologia de infecções de corrente sanguínea ocasionadas por MRSA e avaliar os fatores de risco associados a mortalidade. Métodos: Estudo de coorte, realizado em um complexo hospitalar da cidade de Porto Alegre (RS), entre abril de 2014 a junho de 2018. Os isolados foram avaliados por high-throughput sequencing (tecnologia Illumina) e as informações para tipagem foram obtidas. Teste de suscetibilidade aos antimicrobianos foram realizados por disco-difusão, conforme protocolos do EUCAST e a concentração inibitória mínima para vancomicina (CIM) foi determinada por fitas de gradiente. Dados clínicos e epidemiológicos dos pacientes foram obtidos através do prontuário eletrônico. Resultados: Foram incluídos 91 pacientes. A média de idade foi 52,4 anos (DP +-23,1) e as comorbidades mais frequentes foram hipertensão (39,6%), diabete mellitus (37,4%) e doença cardiovascular (18,7%). A mortalidade intra-hospitalar foi de 33,0%. Não houve diferenças significativas em características epidemiológicas considerando a origem das infecções (AC x IRAS). A CIM para vancomicina variou de 0,5mg/L a 2,0mg/L com 59,3% dos isolados apresentado CIM ≥ 1,5mg/L. Um total de 29 (31,9%) isolados foram classificados como multidrogarresistente, sendo mais prevalentes entre às IRAS (p = 0,001). Considerando as sequencias tipo (ST) e complexos clonais (CC), ambos ST30 e CC30 estavam associados a infecções AC (p = 0,022 e p = 0.006). O CC5 estava associado a IRAS (p = 0,008), com todas as suas STs (ST105, ST1176, ST1635 e ST5521) estando relacionadas a IRAS. Considerando os fatores de risco para mortalidade: idade (p < 0,001), doença cardiovascular (p = 0,005) e elevado Charlson Comorbidity Index (p = 0,001) estavam associados a mortalidade na análise univariada, mas somente idade foi um de risco independente para mortalidade (IC 1.004-1.043; p = 0,017). Não foi evidenciada associação de CC, nem de características fenotípicas ou genotípicos com a mortalidade. Conclusão: Foi observada elevada mortalidade intra-hospitalar e estava associada com a maiores idades. Além de não haver associação entre os CC e mortalidade, foi evidenciado que o CC30 (ST30-mecIVc-PVL+) foi o clone dominante entre as infeções AC.

Listeria monocytogenes sequence type 1247 clonal complex 8 caused a prolonged multicountry outbreak in five EU countries: Denmark, Estonia, Finland, France, and Sweden. A total of 22 disease cases were identified with onset of symptoms between July 2014 and February 2019. Five patients died due to, or with, the disease. The retrospective analysis of L. monocytogenes isolate VLTRLM2013 revealed the presence of an outbreak-related strain (cgMLST type L2-SL8-ST1247-CT4158) in ready-to-eat fish product more than a year prior to the first outbreak-related cases. Reference outbreak strain and VLTRLM2013 strain were compared using core genome and whole-genome multilocus sequence typing analyses. Genomic level differences of the persistent L. monocytogenes strains associated with a prolonged multicountry foodborne listeriosis outbreak are described. It was concluded that the persistent nature of the multicountry outbreak-related L. monocytogenes strain VLTRLM2013 together with stress island, virulence, and antibiotic resistance genes could potentially be the determining factors for the extensive and prolonged outbreak affecting five European Union countries. Our results support the systematic application of whole-genome sequencing in food and public health surveillance and further encourages its wide adoption.