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Chewie Nomenclature Server (chewie-NS, https://chewbbaca.online/) allows users to share genome-based gene-by-gene typing schemas and to maintain a common nomenclature, simplifying the comparison of results. The combination between local analyses and a public repository of allelic data strikes a balance between potential confidentiality issues and the need to compare results. The possibility of deploying private instances of chewie-NS facilitates the creation of nomenclature servers with a restricted user base to allow compliance with the strictest data policies. Chewie-NS allows users to easily share their own schemas and to explore publicly available schemas, including informative statistics on schemas and loci presented in interactive charts and tables. Users can retrieve all the information necessary to run a schema locally or all the alleles identified at a particular locus. The integration with the chewBBACA suite enables users to directly upload new schemas to chewie-NS, download existing schemas and synchronize local and remote schemas from chewBBACA command line version, allowing an easier integration into high-throughput analysis pipelines. The same REST API linking chewie-NS and the chewBBACA suite supports the interaction of other interfaces or pipelines with the databases available at chewie-NS, facilitating the reusability of the stored data.

Computational algorithms have become an essential component of research, with great efforts by the scientific community to raise standards on development and distribution of code. Despite these efforts, sustainability and reproducibility are major issues since continued validation through software testing is still not a widely adopted practice. Here, we report seven recommendations that help researchers implement software testing in microbial bioinformatics. We have developed these recommendations based on our experience from a collaborative hackathon organised prior to the American Society for Microbiology Next Generation Sequencing (ASM NGS) 2020 conference. We also present a repository hosting examples and guidelines for testing, available from https://github.com/microbinfie-hackathon2020/CSIS.

Objectives Streptococcus agalactiae [group B streptococci (GBS)] have been considered uniformly susceptible to penicillin. However, increasing reports from Asia and North America are documenting penicillin-non-susceptible GBS (PRGBS) with mutations in pbp genes. Here we report, to the best of our knowledge, the first two PRGBS isolates recovered in Europe (AC-13238-1 and AC-13238-2), isolated from the same patient. Methods Two different colony morphologies of GBS were noted from a surgical abscess drainage sample. Both were serotyped and antimicrobial susceptibility testing was performed by different methodologies. High-throughput sequencing was done to compare the isolates at the genomic level, to identify their capsular type and ST, to evaluate mutations in the pbp genes and to compare the isolates with the genomes of other PRGBS isolates sharing the same serotype and ST. Results Isolates AC-13238-1 and AC-13238-2 presented MICs above the EUCAST and CLSI breakpoints for penicillin susceptibility. Both shared the capsular type Ia operon and ST23. Genomic analysis uncovered differences between the two isolates in seven genes, including altered pbp genes. Deduced amino acid sequences revealed critical substitutions in PBP2X in both isolates. Comparison with serotype Ia clonal complex 23 PRGBS from the USA reinforced the similarity between AC-13238-1 and AC-13238-2, and their divergence from the US strains. Conclusions Our results support the in-host evolution of β-lactam-resistant GBS, with two PRGBS variants being isolated from one patient.

Background Short-read shotgun metagenomics can offer comprehensive microbial detection and characterisation of complex clinical samples. The de novo assembly of this data into draft genomes is key in metagenomic analysis, yielding longer sequences that offer contextual information and afford a more complete picture of the microbial community. The assembly process represents a major bottleneck in obtaining trustworthy, reproducible results. Methods LMAS is an automated workflow developed as a flexible platform to evaluate traditional and metagenomic dedicated prokaryotic de novo assembly software performance given known standard communities. Its implementation in Nextflow ensures the transparency and reproducibility of the results obtained and the use of Docker containers provides further flexibility. The results are presented in an interactive HTML report where global and reference specific performance metrics can be explored. Currently, 10 assemblers are implemented in LMAS, with the possibility for expansion as novel algorithms are developed. Results The eight bacterial genomes and four plasmids of the ZymoBIOMICS Microbial Community Standards were used as reference. Raw sequence data of the mock communities, with an even and logarithmic distribution of species, and matching simulated samples were used as input. The resulting LMAS report is available at https://lmas-demo.herokuapp.com. Discussion Overall, k-mer De Bruijn graph assemblers outperform the alternative approaches but come with a greater computational cost. Metagenomic dedicated algorithms produce fewer misassembly errors than standard genomic assemblers. The performance of each assembler varied depending on the species of interest and its abundance in the sample, with less abundant species presenting a significant challenge for all assemblers. No assembler stood out as an undisputed all-purpose choice for short-read metagenomic prokaryote genome assembly, highlighting that efforts are still needed to further improve metagenomic assembly performance. Using LMAS could underpin this development process. The LMAS workflow is available at https://github.com/cimendes/LMAS., Presented at ICCMg6