Minos: variant adjudication and joint genotyping of cohorts of bacterial genomes

Short-read variant calling for bacterial genomics is a mature field, and there are many widely-used software tools. Different underlying approaches (eg pileup, local or global assembly, paired-read use, haplotype use) lend each tool different strengths, especially when considering non-SNP (single nucleotide polymorphism) variation or potentially distant reference genomes. It would therefore be valuable to be able to integrate the results from multiple variant callers, using a robust statistical approach to "adjudicate" at loci where there is disagreement between callers. To this end, we present a tool, Minos, for variant adjudication by mapping reads to a genome graph of variant calls. Minos allows users to combine output from multiple variant callers without loss of precision. Minos also addresses a second problem of joint genotyping SNPs and indels in bacterial cohorts, which can also be framed as an adjudication problem. We benchmark on 62 samples from 3 species (Mycobacterium tuberculosis, Staphylococcus aureus, Klebsiella pneumoniae) and an outbreak of 385 M. tuberculosis samples. Finally, we joint genotype a large M. tuberculosis cohort (N≈15k) for which the rifampicin phenotype is known. We build a map of non-synonymous variants in the RRDR (rifampicin resistance determining region) of the rpoB gene and extend current knowledge relating RRDR SNPs to heterogeneity in rifampicin resistance levels. We replicate this finding in a second M. tuberculosis cohort (N≈13k). Minos is released under the MIT license, available at https://github.com/iqbal-lab-org/minos.

Framing Bacterial Genomics for Public Health(care)

Advancements in comparative genomics have generated significant interest in defining applications for healthcare-associated pathogens. Clinical microbiology, however, relies on increasingly automated platforms to quickly identify pathogens, resistance mechanisms, and therapy options within CLIA- and FDA-approved frameworks. Additionally, and most notably, healthcare-associated pathogens, especially those that are resistant to antibiotics, represent a diverse spectrum of genera harboring complex genetic targets including antibiotic, biocide, and virulence determinants that can be highly transmissible and, at least for antibiotic resistance, serve as potential targets for containment efforts. U.S. public health investments have focused on rapidly detecting outbreaks and emerging resistance in healthcare-associated pathogens using reference, culture-based, and molecular methods that are distributed, for example, across national laboratory network infrastructures. Herein we describe the public health applications of genomic science that are built from the top-down for broad surveillance, as well as the bottom-up, starting with identification of infections and infectious clusters. For healthcare-associated, including antimicrobial-resistant, pathogens, we propose a combination of top-down and bottom-up genomic approaches leveraged across the public health spectrum, from local infection control, to regional and national containment efforts, to national surveillance for understanding emerging strain ecology and fitness of healthcare pathogens.

Reconstruction of Microbial Haplotypes by Integration of Statistical and Physical Linkage in Scaffolding

DNA sequencing technologies provide unprecedented opportunities to analyze within-host evolution of microorganism populations. Often, within-host populations are analyzed via pooled sequencing of the population, which contains multiple individuals or “haplotypes.” However, current next-generation sequencing instruments, in conjunction with single-molecule barcoded linked-reads, cannot distinguish long haplotypes directly. Computational reconstruction of haplotypes from pooled sequencing has been attempted in virology, bacterial genomics, metagenomics, and human genetics, using algorithms based on either cross-host genetic sharing or within-host genomic reads. Here, we describe PoolHapX, a flexible computational approach that integrates information from both genetic sharing and genomic sequencing. We demonstrated that PoolHapX outperforms state-of-the-art tools tailored to specific organismal systems, and is robust to within-host evolution. Importantly, together with barcoded linked-reads, PoolHapX can infer whole-chromosome-scale haplotypes from 50 pools each containing 12 different haplotypes. By analyzing real data, we uncovered dynamic variations in the evolutionary processes of within-patient HIV populations previously unobserved in single position-based analysis.

Synergizing the potential of bacterial genomics and metabolomics to find novel antibiotics

Antimicrobial resistance is a major public concern and novel antibiotics are largely based on natural products. We summarize recent analytical and genome based technological developments that gain increasing importance in the natural products field.

The impact of genetic diversity on gene essentiality within the E. coli species

Bacteria from the same species can differ widely in their gene content. In E. coli, the set of genes shared by all strains, known as the core genome, represents about half the number of genes present in any strain. While recent advances in bacterial genomics have enabled to unravel genes required for fitness in various experimental conditions at the genome scale, most studies have focused on model strains. As a result, the impact of this genetic diversity on core processes of the bacterial cell largely remains to be investigated. Here, we developed a new CRISPR interference platform for high-throughput gene repression that is compatible with most E. coli isolates and closely-related species. We applied it to assess the importance of ∼3,400 nearly ubiquitous genes in 3 growth media in 18 representative E. coli strains spanning most common phylogroups and lifestyles of the species. Our screens highlighted extensive variations in gene essentiality between strains and conditions. Unlike variations in gene expression level, variations in gene essentiality do not recapitulate the strains’ phylogeny. Investigation of the genetic determinants for these variations highlighted the importance of epistatic interactions with mobile genetic elements. In particular, we showed how mobile genetic elements can trigger the essentiality of core genes that are usually nonessential. This study provides new insights into the evolvability of gene essentiality and argues for the importance of studying various isolates from the same species in bacterial genomics.

AnnoTree: visualization and exploration of a functionally annotated microbial tree of life

Bacterial genomics has revolutionized our understanding of the microbial tree of life; however, mapping and visualizing the distribution of functional traits across bacteria remains a challenge. Here, we introduce AnnoTree - an interactive, functionally annotated bacterial tree of life that integrates taxonomic, phylogenetic, and functional annotation data from nearly 24,000 bacterial genomes. AnnoTree enables visualization of millions of precomputed genome annotations across the bacterial phylogeny, thereby allowing users to explore gene distributions as well as patterns of gene gain and loss across bacteria. Using AnnoTree, we examined the phylogenomic distributions of 28,311 gene/protein families, and measured their phylogenetic conservation, patchiness, and lineage-specificity. Our analyses revealed widespread phylogenetic patchiness among bacterial gene families, reflecting the dynamic evolution of prokaryotic genomes. Genes involved in phage infection/defense, mobile elements, and antibiotic resistance dominated the list of most patchy traits, as well as numerous intriguing metabolic enzymes that appear to have undergone frequent horizontal transfer. We anticipate that AnnoTree will be a valuable resource for exploring gene histories across bacteria, and will act as a catalyst for biological and evolutionary hypothesis generation.