Protein Biomarker Identification for the Discrimination of Brucella melitensis Field Isolates From the Brucella melitensis Rev.1 Vaccine Strain by MALDI-TOF MS.

Brucella melitensis Rev.1 is a live attenuated vaccine strain that is widely used to control brucellosis in small ruminants. For successful surveillance and control programs, rapid identification and characterization of Brucella isolates and reliable differentiation of vaccinated and naturally infected animals are essential prerequisites. Although MALDI-TOF MS is increasingly applied in clinical microbiology laboratories for the diagnosis of brucellosis, species or even strain differentiation by this method remains a challenge. To detect biomarkers, which enable to distinguish the B. melitensis Rev.1 vaccine strain from B. melitensis field isolates, we initially searched for unique marker proteins by in silico comparison of the B. melitensis Rev.1 and 16M proteomes. We found 113 protein sequences of B. melitensis 16M that revealed a homologous sequence in the B. melitensis Rev.1 annotation and 17 of these sequences yielded potential biomarker pairs. MALDI-TOF MS spectra of 18 B. melitensis Rev.1 vaccine and 183 Israeli B. melitensis field isolates were subsequently analyzed to validate the identified marker candidates. This approach detected two genus-wide unique biomarkers with properties most similar to the ribosomal proteins L24 and S12. These two proteins clearly discriminated B. melitensis Rev.1 from the closely related B. melitensis 16M and the Israeli B. melitensis field isolates. In addition, we verified their discriminatory power using a set of B. melitensis strains from various origins and of different MLVA types. Based on our results, we propose MALDI-TOF MS profiling as a rapid, cost-effective alternative to the traditional, time-consuming approach to differentiate certain B. melitensis isolates on strain level.

Testing assembly strategies of Francisella tularensis genomes to infer an evolutionary conservation analysis of genomic structures.

BACKGROUND: We benchmarked sequencing technology and assembly strategies for short-read, long-read, and hybrid assemblers in respect to correctness, contiguity, and completeness of assemblies in genomes of Francisella tularensis. Benchmarking allowed in-depth analyses of genomic structures of the Francisella pathogenicity islands and insertion sequences. Five major high-throughput sequencing technologies were applied, including next-generation "short-read" and third-generation "long-read" sequencing methods. RESULTS: We focused on short-read assemblers, hybrid assemblers, and analysis of the genomic structure with particular emphasis on insertion sequences and the Francisella pathogenicity island. The A5-miseq pipeline performed best for MiSeq data, Mira for Ion Torrent data, and ABySS for HiSeq data from eight short-read assembly methods. Two approaches were applied to benchmark long-read and hybrid assembly strategies: long-read-first assembly followed by correction with short reads (Canu/Pilon, Flye/Pilon) and short-read-first assembly along with scaffolding based on long reads (Unicyler, SPAdes). Hybrid assembly can resolve large repetitive regions best with a "long-read first" approach. CONCLUSIONS: Genomic structures of the Francisella pathogenicity islands frequently showed misassembly. Insertion sequences (IS) could be used to perform an evolutionary conservation analysis. A phylogenetic structure of insertion sequences and the evolution within the clades elucidated the clade structure of the highly conservative F. tularensis.

Decentralized Investigation of Bacterial Outbreaks Based on Hashed cgMLST.

Whole-genome sequencing (WGS)-based outbreak investigation has proven to be a valuable method for the surveillance of bacterial pathogens. Its utility has been successfully demonstrated using both gene-by-gene (cgMLST or wgMLST) and single-nucleotide polymorphism (SNP)-based approaches. Among the obstacles of implementing a WGS-based routine surveillance is the need for an exchange of large volumes of sequencing data, as well as a widespread reluctance to share sequence and metadata in public repositories, together with a lacking standardization of suitable bioinformatic tools and workflows. To address these issues, we present chewieSnake, an intuitive and simple-to-use cgMLST workflow. ChewieSnake builds on the allele calling software chewBBACA and extends it by the concept of allele hashing. The resulting hashed allele profiles can be readily compared between laboratories without the need of a central allele nomenclature. The workflow fully automates the computation of the allele distance matrix, cluster membership, and phylogeny and summarizes all important findings in an interactive HTML report. Furthermore, chewieSnake can join allele profiles generated at different laboratories and identify shared clusters, including a stable and intercommunicable cluster nomenclature, thus facilitating a joint outbreak investigation. We demonstrate the feasibility of the proposed approach with a thorough method comparison using publically available sequencing data for Salmonella enterica. However, chewieSnake is readily applicable to all bacterial taxa, provided that a suitable cgMLST scheme is available. The workflow is freely available as an open-source tool and can be easily installed via conda or docker.

Direct identification and molecular characterization of zoonotic hazards in raw milk by metagenomics using Brucella as a model pathogen.

Metagenomics is a valuable diagnostic tool for enhancing microbial food safety because (i) it enables the untargeted detection of pathogens, (ii) it is fast since primary isolation of micro-organisms is not required, and (iii) it has high discriminatory power allowing for a detailed molecular characterization of pathogens. For shotgun metagenomics, total nucleic acids (NAs) are isolated from complex samples such as foodstuff. Along with microbial NAs, high amounts of matrix NAs are extracted that might outcompete microbial NAs during next-generation sequencing and compromise sensitivity for the detection of low abundance micro-organisms. Sensitive laboratory methods are indispensable for detecting highly pathogenic foodborne bacteria like Brucella spp., because a low infectious dose is sufficient to cause human disease through the consumption of contaminated dairy or meat products. In our study, we applied shotgun metagenomic sequencing for the identification and characterization of Brucella spp. in artificially and naturally contaminated raw milk from various ruminant species. With the depletion of eukaryotic cells prior to DNA extraction, Brucella was detectable at 10 bacterial cells ml-1, while at the same time microbiological culture and isolation of the fastidious bacteria commonly failed. Moreover, we were able to retrieve the genotype of a Brucella isolate from a metagenomic dataset, indicating the potential of metagenomics for outbreak investigations using SNPs and core-genome multilocus sequence typing (cgMLST). To improve diagnostic applications, we developed a new bioinformatics approach for strain prediction based on SNPs to identify the correct species and define a certain strain with only low numbers of genus-specific reads per sample. This pipeline turned out to be more sensitive and specific than Mash Screen. In raw milk samples, we simultaneously detected numerous other zoonotic pathogens, antimicrobial resistance genes and virulence factors. Our study showed that metagenomics is a highly sensitive tool for biological risk assessment of foodstuffs, particularly when pathogen isolation is hazardous or challenging.

Species-Specific Quality Control, Assembly and Contamination Detection in Microbial Isolate Sequences with AQUAMIS.

Sequencing of whole microbial genomes has become a standard procedure for cluster detection, source tracking, outbreak investigation and surveillance of many microorganisms. An increasing number of laboratories are currently in a transition phase from classical methods towards next generation sequencing, generating unprecedented amounts of data. Since the precision of downstream analyses depends significantly on the quality of raw data generated on the sequencing instrument, a comprehensive, meaningful primary quality control is indispensable. Here, we present AQUAMIS, a Snakemake workflow for an extensive quality control and assembly of raw Illumina sequencing data, allowing laboratories to automatize the initial analysis of their microbial whole-genome sequencing data. AQUAMIS performs all steps of primary sequence analysis, consisting of read trimming, read quality control (QC), taxonomic classification, de-novo assembly, reference identification, assembly QC and contamination detection, both on the read and assembly level. The results are visualized in an interactive HTML report including species-specific QC thresholds, allowing non-bioinformaticians to assess the quality of sequencing experiments at a glance. All results are also available as a standard-compliant JSON file, facilitating easy downstream analyses and data exchange. We have applied AQUAMIS to analyze ~13,000 microbial isolates as well as ~1000 in-silico contaminated datasets, proving the workflow's ability to perform in high throughput routine sequencing environments and reliably predict contaminations. We found that intergenus and intragenus contaminations can be detected most accurately using a combination of different QC metrics available within AQUAMIS.

MALDI-TOF MS and genomic analysis can make the difference in the clarification of canine brucellosis outbreaks.

Brucellosis is one of the most common bacterial zoonoses worldwide affecting not only livestock and wildlife but also pets. Canine brucellosis is characterized by reproductive failure in dogs. Human Brucella canis infections are rarely reported but probably underestimated due to insufficient diagnostic surveillance. To improve diagnostics, we investigated dogs in a breeding kennel that showed clinical manifestations of brucellosis and revealed positive blood cultures. As an alternative to the time-consuming and hazardous classical identification procedures, a newly developed species-specific intact-cell matrix-assisted laser desorption/ionization-time of flight mass spectrometry analysis was applied, which allowed for rapid identification of B. canis and differentiation from closely related B. suis biovar 1. High-throughput sequencing and comparative genomics using single nucleotide polymorphism analysis clustered our isolates together with canine and human strains from various Central and South American countries in a distinct sub-lineage. Hence, molecular epidemiology clearly defined the outbreak cluster and demonstrated the endemic situation in South America. Our study illustrates that MALDI-TOF MS analysis using a validated in-house reference database facilitates rapid B. canis identification at species level. Additional whole genome sequencing provides more detailed outbreak information and leads to a deeper understanding of the epidemiology of canine brucellosis.

Revisiting Francisella tularensis subsp. holarctica, Causative Agent of Tularemia in Germany With Bioinformatics: New Insights in Genome Structure, DNA Methylation and Comparative Phylogenetic Analysis.

Francisella (F.) tularensis is a highly virulent, Gram-negative bacterial pathogen and the causative agent of the zoonotic disease tularemia. Here, we generated, analyzed and characterized a high quality circular genome sequence of the F. tularensis subsp. holarctica strain 12T0050 that caused fatal tularemia in a hare. Besides the genomic structure, we focused on the analysis of oriC, unique to the Francisella genus and regulating replication in and outside hosts and the first report on genomic DNA methylation of a Francisella strain. The high quality genome was used to establish and evaluate a diagnostic whole genome sequencing pipeline. A genotyping strategy for F. tularensis was developed using various bioinformatics tools for genotyping. Additionally, whole genome sequences of F. tularensis subsp. holarctica isolates isolated in the years 2008-2015 in Germany were generated. A phylogenetic analysis allowed to determine the genetic relatedness of these isolates and confirmed the highly conserved nature of F. tularensis subsp. holarctica.

Yos9p assists in the degradation of certain nonglycosylated proteins from the endoplasmic reticulum.

The HRD ubiquitin ligase recognizes and ubiquitylates proteins of the endoplasmic reticulum that display structural defects. Here, we apply quantitative proteomics to characterize the substrate spectrum of the HRD complex. Among the identified substrates is Erg3p, a glycoprotein involved in sterol synthesis. We characterize Erg3p and demonstrate that the elimination of Erg3p requires Htm1p and Yos9p, two proteins that take part in the glycan-dependent turnover of aberrant proteins. We further show that the HRD ligase also mediates the breakdown of Erg3p and CPY* engineered to lack N-glycans. The degradation of these nonglycosylated substrates is enhanced by a mutant variant of Yos9p that has lost its affinity for oligosaccharides, indicating that Yos9p has a previously unrecognized role in the quality control of nonglycosylated proteins.