Since the first two complete bacterial genome sequences were published in 1995, the science of bacteria has dramatically changed. Using third-generation DNA sequencing, it is possible to completely sequence a bacterial genome in a few hours and identify some types of methylation sites along the genome as well. Sequencing of bacterial genome sequences is now a standard procedure, and the information from tens of thousands of bacterial genomes has had a major impact on our views of the bacterial world. In this review, we explore a series of questions to highlight some insights that comparative genomics has produced. To date, there are genome sequences available from 50 different bacterial phyla and 11 different archaeal phyla. However, the distribution is quite skewed towards a few phyla that contain model organisms. But the breadth is continuing to improve, with projects dedicated to filling in less characterized taxonomic groups. The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas system provides bacteria with immunity against viruses, which outnumber bacteria by tenfold. How fast can we go? Second-generation sequencing has produced a large number of draft genomes (close to 90 % of bacterial genomes in GenBank are currently not complete); third-generation sequencing can potentially produce a finished genome in a few hours, and at the same time provide methlylation sites along the entire chromosome. The diversity of bacterial communities is extensive as is evident from the genome sequences available from 50 different bacterial phyla and 11 different archaeal phyla. Genome sequencing can help in classifying an organism, and in the case where multiple genomes of the same species are available, it is possible to calculate the pan- and core genomes; comparison of more than 2000 Escherichia coli genomes finds an E. coli core genome of about 3100 gene families and a total of about 89,000 different gene families. Why do we care about bacterial genome sequencing? There are many practical applications, such as genome-scale metabolic modeling, biosurveillance, bioforensics, and infectious disease epidemiology. In the near future, high-throughput sequencing of patient metagenomic samples could revolutionize medicine in terms of speed and accuracy of finding pathogens and knowing how to treat them.
Motivation: Metagenomic sequencing of clinical samples provides a promising technique for direct pathogen detection and characterization in biosurveillance. Taxonomic analysis at the strain level can be used to resolve serotypes of a pathogen in biosurveillance. Sigma was developed for strain-level identification and quantification of pathogens using their reference genomes based on metagenomic analysis.Results: Sigma provides not only accurate strain-level inferences, but also three unique capabilities: (i) Sigma quantifies the statistical uncertainty of its inferences, which includes hypothesis testing of identified genomes and confidence interval estimation of their relative abundances; (ii) Sigma enables strain variant calling by assigning metagenomic reads to their most likely reference genomes; and (iii) Sigma supports parallel computing for fast analysis of large datasets. The algorithm performance was evaluated using simulated mock communities and fecal samples with spike-in pathogen strains.Availability and Implementation: Sigma was implemented in C++ with source codes and binaries freely available at http://sigma.omicsbio.org.Contact: panc@ornl.govSupplementary information: Supplementary data are available at Bioinformatics online.
Detailed characterization of post-translational modifications (PTMs) of proteins in microbial communities remains a significant challenge. Here we directly identify and quantify a broad range of PTMs (hydroxylation, methylation, citrullination, acetylation, phosphorylation, methylthiolation, S-nitrosylation and nitration) in a natural microbial community from an acid mine drainage site. Approximately 29% of the identified proteins of the dominant Leptospirillum group II bacteria are modified, and 43% of modified proteins carry multiple PTM types. Most PTM events, except S-nitrosylations, have low fractional occupancy. Notably, PTM events are detected on Cas proteins involved in antiviral defense, an aspect of Cas biochemistry not considered previously. Further, Cas PTM profiles from Leptospirillum group II differ in early versus mature biofilms. PTM patterns are divergent on orthologues of two closely related, but ecologically differentiated, Leptospirillum group II bacteria. Our results highlight the prevalence and dynamics of PTMs of proteins, with potential significance for ecological adaptation and microbial evolution.
Implemented in C++ with source code and binaries freely available at http://omega.omicsbio.org.
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