A Dual Barcoding Approach to Bacterial Strain Nomenclature: Genomic Taxonomy of Klebsiella pneumoniae Strains.

Sublineages (SLs) within microbial species can differ widely in their ecology and pathogenicity, and their precise definition is important in basic research and for industrial or public health applications. Widely accepted strategies to define SLs are currently missing, which confuses communication in population biology and epidemiological surveillance. Here, we propose a broadly applicable genomic classification and nomenclature approach for bacterial strains, using the prominent public health threat Klebsiella pneumoniae as a model. Based on a 629-gene core genome multilocus sequence typing (cgMLST) scheme, we devised a dual barcoding system that combines multilevel single linkage (MLSL) clustering and life identification numbers (LINs). Phylogenetic and clustering analyses of >7,000 genome sequences captured population structure discontinuities, which were used to guide the definition of 10 infraspecific genetic dissimilarity thresholds. The widely used 7-gene multilocus sequence typing (MLST) nomenclature was mapped onto MLSL SLs (threshold: 190 allelic mismatches) and clonal group (threshold: 43) identifiers for backwards nomenclature compatibility. The taxonomy is publicly accessible through a community-curated platform (https://bigsdb.pasteur.fr/klebsiella), which also enables external users' genomic sequences identification. The proposed strain taxonomy combines two phylogenetically informative barcode systems that provide full stability (LIN codes) and nomenclatural continuity with previous nomenclature (MLSL). This species-specific dual barcoding strategy for the genomic taxonomy of microbial strains is broadly applicable and should contribute to unify global and cross-sector collaborative knowledge on the emergence and microevolution of bacterial pathogens.

Multiplexed Metagenomic Deep Sequencing To Analyze the Composition of High-Priority Pathogen Reagents.

Laboratories studying high-priority pathogens need comprehensive methods to confirm microbial species and strains while also detecting contamination. Metagenomic deep sequencing (MDS) inventories nucleic acids present in laboratory stocks, providing an unbiased assessment of pathogen identity, the extent of genomic variation, and the presence of contaminants. Double-stranded cDNA MDS libraries were constructed from RNA extracted from in vitro-passaged stocks of six viruses (La Crosse virus, Ebola virus, canine distemper virus, measles virus, human respiratory syncytial virus, and vesicular stomatitis virus). Each library was dual indexed and pooled for sequencing. A custom bioinformatics pipeline determined the organisms present in each sample in a blinded fashion. Single nucleotide variant (SNV) analysis identified viral isolates. We confirmed that (i) each sample contained the expected microbe, (ii) dual indexing of the samples minimized false assignments of individual sequences, (iii) multiple viral and bacterial contaminants were present, and (iv) SNV analysis of the viral genomes allowed precise identification of the viral isolates. MDS can be multiplexed to allow simultaneous and unbiased interrogation of mixed microbial cultures and (i) confirm pathogen identity, (ii) characterize the extent of genomic variation, (iii) confirm the cell line used for virus propagation, and (iv) assess for contaminating microbes. These assessments ensure the true composition of these high-priority reagents and generate a comprehensive database of microbial genomes studied in each facility. MDS can serve as an integral part of a pathogen-tracking program which in turn will enhance sample security and increase experimental rigor and precision. IMPORTANCE Both the integrity and reproducibility of experiments using select agents depend in large part on unbiased validation to ensure the correct identity and purity of the species in question. Metagenomic deep sequencing (MDS) provides the required level of validation by allowing for an unbiased and comprehensive assessment of all the microbes in a laboratory stock.

GFP-tagged E. coli shows bacterial distribution in mouse organs: pathogen tracking using fluorescence signal.

PURPOSE: In vaccine efficacy evaluation, visualization of pathogens in whole organism at each time point would be able to reduce the consuming animals and provide the in vivo information within consistent background with identical organism. MATERIALS AND METHODS: Using IVIS spectrum whole live-animal imaging system, fluorescent intensity was optimized and visualized proportionately by concentrating Escherichia coli MC1061 strain which expresses GFP (E. coli-GFP) in BALB/C mice after injection. RESULTS: Local distribution of disseminated E. coli-GFP was traced in each organ by fluorescence. Detached organ showed more obvious fluorescent signal, and intestine showed strongest fluorescent signal. CONCLUSION: This in vivo imaging method using GFP-tagged pathogen strain suggest quantified infected pathogens by fluorescence intensity in whole animals can provide the information about the localization and distribution after infection.

GFP-tagged E. coli shows bacterial distribution in mouse organs: pathogen tracking using fluorescence signal

PURPOSE: In vaccine efficacy evaluation, visualization of pathogens in whole organism at each time point would be able to reduce the consuming animals and provide the in vivo information within consistent background with identical organism. MATERIALS AND METHODS: Using IVIS spectrum whole live-animal imaging system, fluorescent intensity was optimized and visualized proportionately by concentrating Escherichia coli MC1061 strain which expresses GFP (E. coli-GFP) in BALB/C mice after injection. RESULTS: Local distribution of disseminated E. coli-GFP was traced in each organ by fluorescence. Detached organ showed more obvious fluorescent signal, and intestine showed strongest fluorescent signal. CONCLUSION: This in vivo imaging method using GFP-tagged pathogen strain suggest quantified infected pathogens by fluorescence intensity in whole animals can provide the information about the localization and distribution after infection.