Using molecular methods to delineate norovirus outbreaks: a systematic review

Noroviruses are among the major causative agents of human acute gastroenteritis, and the nature of norovirus outbreaks can differ considerably. The number of single-nucleotide polymorphisms (SNPs) between strains is used to assess their relationships. There is currently no universally accepted cutoff value for clustering strains that define an outbreak or linking the individuals involved. This study was conducted to estimate the threshold value of genomic variations among related strains within norovirus outbreaks. We carried out a literature search in the PubMed and Web of Science databases. SNP rates were defined as the number of SNPs/sequence length (bp) × 100%. The Mann-Whitney U-test was used in comparisons of the distribution of SNP rates for different sequence regions, genogroups (GI and GII), transmission routes, and sequencing methods. A total of 25 articles reporting on 108 norovirus outbreaks were included. In 99.1% of the outbreaks, the SNP rates were below 0.50%, and in 89.8%, the SNP rates were under 0.20%. Outbreak strains showed higher SNP rates when the P2 domain was used for sequence analysis (Z = -2.652, p = 0.008) and when an NGS method was used (Z = -3.686, p < 0.001). Outbreaks caused by different norovirus genotypes showed no significant difference in SNP rates. Compared with person-to-person outbreaks, SNP rates were lower in common-source outbreaks, but no significant difference was found when differences in sequencing methods were taken into consideraton. SNP rates under 0.20% and 0.50% could be considered as the rigorous and relaxed threshold, respectively, of strain similarity within a norovirus outbreak. More data are needed to evaluate differences within and between various norovirus outbreaks.

Trich-tracker - a practical tool to trace Trichinella spiralis transmission based on rapid, cost-effective sampling of genome-wide genetic variation

Molecular epidemiology using traditional sequencing has been notoriously difficult in inbred parasites due to a lack of genetic variation available for discriminating among parasites. Next generation sequencing techniques offer a solution to this problem by increasing the number of loci that can be sequenced. Here, we introduce Trich-tracker, a tool that makes efficient use of diagnostic variation distributed throughout the genome of Trichinella spiralis to more rapidly, and conclusively, resolve connections and distinctions among focal outbreaks of T. spiralis. In particular, we rapidly characterised genetic variation among a sample of parasites from Polish farms and wildlife, sampling genomic variation using double digest restriction site-associated DNA sequencing (ddRADseq). Approximately 400,000 bases of sequence were generated from each sample and shown to be distributed across the genome with single nucleotide polymorphisms occurring at a frequency of approximately one base in 10,000. Both phylogenetic and Bayesian clustering analyses indicated that ddRADseq genotypes formed distinct clusters for specific outbreaks and were quite distinct from wild boar samples. Two of the investigated outbreaks were more similar to each other than to other outbreak samples, suggesting a link between these outbreaks. Hence, the Trich-tracker procedure identified informative genomic variation which afforded unprecedented epidemiological resolution. Trich-tracker is very flexible tool, quickly and inexpensively mining genomes of even highly inbred populations of T. spiralis to support outbreak investigations. The simplicity of the entire procedure, and time and cost effectiveness of Trich-tracker support its practical application in ongoing Trichinella outbreaks. The discriminating power of this tool is tunable and scalable, allowing application in a variety of epidemiological contexts, and is easily adapted to other parasite systems.