Whole genome sequencing of colonies derived from cannabis flowers and the impact of media selection on benchmarking total yeast and mold detection tools.

BACKGROUND: Cannabis products are subjected to microbial testing for human pathogenic fungi and bacteria. These testing requirements often rely on non-specific colony forming unit (CFU/g) specifications without clarity on which medium, selection or growth times are required. We performed whole genome sequencing to assess the specificity of colony forming units (CFU) derived from three different plating media: Potato Dextrose Agar (PDA), PDA with chloramphenicol and Dichloran Rose Bengal with chloramphenicol (DRBC). METHODS: Colonies were isolated from each medium type and their whole genomes sequenced to identify the diversity of microbes present on each medium selection. Fungal Internal Transcribed Spacer (ITS3) and Bacterial 16S RNA(16S) quantitative polymerase chain reactions (qPCR) were performed, to correlate these CFUs with fungi- and bacterial- specific qPCR. RESULTS: Each plating medium displayed a ten-fold difference in CFU counts. PDA with chloramphenicol showed the highest diversity and the highest concordance with whole genome sequencing. According to ITS3 and 16S qPCR confirmed with whole genome sequencing, DRBC under counted yeast and mold while PDA without chloramphenicol over counted CFUs due to bacterial growth without selection. CONCLUSIONS: Colony Forming Unit regulations lack specificity. Each medium produces significant differences in CFU counts. These are further dependent on subjective interpretation, failure to culture most microbes, and poor selection between bacteria and fungi. Given the most human pathogenic microbes found on cannabis are endophytes which culture fails to detect, molecular methods offer a solution to this long-standing quantification problem in the cannabis testing field.

Genome-wide SNP genotyping highlights the role of natural selection in Plasmodium falciparum population divergence.

BACKGROUND: The malaria parasite Plasmodium falciparum exhibits abundant genetic diversity, and this diversity is key to its success as a pathogen. Previous efforts to study genetic diversity in P. falciparum have begun to elucidate the demographic history of the species, as well as patterns of population structure and patterns of linkage disequilibrium within its genome. Such studies will be greatly enhanced by new genomic tools and recent large-scale efforts to map genomic variation. To that end, we have developed a high throughput single nucleotide polymorphism (SNP) genotyping platform for P. falciparum. RESULTS: Using an Affymetrix 3,000 SNP assay array, we found roughly half the assays (1,638) yielded high quality, 100% accurate genotyping calls for both major and minor SNP alleles. Genotype data from 76 global isolates confirm significant genetic differentiation among continental populations and varying levels of SNP diversity and linkage disequilibrium according to geographic location and local epidemiological factors. We further discovered that nonsynonymous and silent (synonymous or noncoding) SNPs differ with respect to within-population diversity, inter-population differentiation, and the degree to which allele frequencies are correlated between populations. CONCLUSIONS: The distinct population profile of nonsynonymous variants indicates that natural selection has a significant influence on genomic diversity in P. falciparum, and that many of these changes may reflect functional variants deserving of follow-up study. Our analysis demonstrates the potential for new high-throughput genotyping technologies to enhance studies of population structure, natural selection, and ultimately enable genome-wide association studies in P. falciparum to find genes underlying key phenotypic traits.