Abstract
Effective laboratory-based surveillance and public health response to bacterial meningitis depends on timely characterization of bacterial meningitis pathogens. Traditionally, characterizing bacterial meningitis pathogens such as Neisseria meningitidis (Nm) and Haemophilus influenzae (Hi) required several biochemical and molecular tests. Whole genome sequencing (WGS) has enabled the development of pipelines capable of characterizing the given pathogen with equivalent results to many of the traditional tests. Here, we present the Bacterial Meningitis Genomic Analysis Platform (BMGAP): a secure, web-accessible informatics platform that facilitates automated analysis of WGS data in public health laboratories. BMGAP is a pipeline comprised of several components, including both widely used, open-source third-party software and customized analysis modules for the specific target pathogens. BMGAP performs de novo draft genome assembly and identifies the bacterial species by whole-genome comparisons against a curated reference collection of 17 focal species including Nm, Hi, and other closely related species. Genomes identified as Nm or Hi undergo multi-locus sequence typing (MLST) and capsule characterization. Further typing information is captured from Nm genomes, such as peptides for the vaccine antigens FHbp, NadA, and NhbA. Assembled genomes are retained in the BMGAP database, serving as a repository for genomic comparisons. BMGAP’s species identification and capsule characterization modules were validated using PCR and slide agglutination from 446 bacterial invasive isolates (273 Nm from nine different serogroups, 150 Hi from seven different serotypes, and 23 from nine other species) collected from 2017 to 2019 through surveillance programs. Among the validation isolates, BMGAP correctly identified the species for all 440 isolates (100% sensitivity and specificity) and accurately characterized all Nm serogroups (99% sensitivity and 98% specificity) and Hi serotypes (100% sensitivity and specificity). BMGAP provides an automated, multi-species analysis pipeline that can be extended to include additional analysis modules as needed. This provides easy-to-interpret and validated Nm and Hi genome analysis capacity to public health laboratories and collaborators. As the BMGAP database accumulates more genomic data, it grows as a valuable resource for rapid comparative genomic analyses during outbreak investigations.
Highlights
Rapid characterization of bacteria isolated from meningitis cases is critical for implementing successful public health responses and treatment strategies
BMGAP is currently designed for isolate sequencing analysis and takes short (e.g., 250 bp), high quality paired-end FASTQ read files as input
The overall BMGAP workflow including each core module is illustrated in Figure 1. (For a summary of BMGAP’s quality control (QC) parameters, see Supplementary Table 1)
Summary
Rapid characterization of bacteria isolated from meningitis cases is critical for implementing successful public health responses and treatment strategies. Neisseria meningitidis [Nm] and Haemophilus influenzae [Hi], two important common causes of invasive bacterial meningitis worldwide, have traditionally been characterized by biochemical and molecular methods. Biochemical and molecular laboratory tests can be time consuming and labor-intensive, but the recent proliferation of whole genome sequencing [WGS] technology has created an opportunity for streamlining the characterization of bacterial meningitis pathogens. Automated sequence analysis pipelines that identify the bacterial species (Topaz et al, 2018), Nm serogroup (Marjuki et al, 2019), and Hi serotype (Potts et al, 2019) provide a proof of concept for using WGS to elucidate bacterial meningitis pathogens
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