Summary: Pathogenic Escherichia coli cause over 160 million cases of dysentery and one million deaths per year, whereas non‐pathogenic E. coli constitute part of the normal intestinal flora of healthy mammals and birds. The evolutionary pathways underlying this dichotomy in bacterial lifestyle were investigated by multilocus sequence typing of a global collection of isolates. Specific pathogen types [enterohaemorrhagic E. coli, enteropathogenic E. coli, enteroinvasive E. coli, K1 and Shigella] have arisen independently and repeatedly in several lineages, whereas other lineages contain only few pathogens. Rates of evolution have accelerated in pathogenic lineages, culminating in highly virulent organisms whose genomic contents are altered frequently by increased rates of homologous recombination; thus, the evolution of virulence is linked to bacterial sex. This long‐term pattern of evolution was observed in genes distributed throughout the genome, and thereby is the likely result of episodic selection for strains that can escape the host immune response.

Helicobacter pylori , a chronic gastric pathogen of human beings, can be divided into seven populations and subpopulations with distinct geographical distributions. These modern populations derive their gene pools from ancestral populations that arose in Africa, Central Asia, and East Asia. Subsequent spread can be attributed to human migratory fluxes such as the prehistoric colonization of Polynesia and the Americas, the neolithic introduction of farming to Europe, the Bantu expansion within Africa, and the slave trade.

Listeria monocytogenes is a model organism for cellular microbiology and host–pathogen interaction studies and an important food-borne pathogen widespread in the environment, thus representing an attractive model to study the evolution of virulence. The phylogenetic structure of L. monocytogenes was determined by sequencing internal portions of seven housekeeping genes (3,288 nucleotides) in 360 representative isolates. Fifty-eight of the 126 disclosed sequence types were grouped into seven well-demarcated clonal complexes (clones) that comprised almost 75% of clinical isolates. Each clone had a unique or dominant serotype (4b for clones 1, 2 and 4, 1/2b for clones 3 and 5, 1/2a for clone 7, and 1/2c for clone 9), with no association of clones with clinical forms of human listeriosis. Homologous recombination was extremely limited (r/m<1 for nucleotides), implying long-term genetic stability of multilocus genotypes over time. Bayesian analysis based on 438 SNPs recovered the three previously defined lineages, plus one unclassified isolate of mixed ancestry. The phylogenetic distribution of serotypes indicated that serotype 4b evolved once from 1/2b, the likely ancestral serotype of lineage I. Serotype 1/2c derived once from 1/2a, with reference strain EGDe (1/2a) likely representing an intermediate evolutionary state. In contrast to housekeeping genes, the virulence factor internalin (InlA) evolved by localized recombination resulting in a mosaic pattern, with convergent evolution indicative of natural selection towards a truncation of InlA protein. This work provides a reference evolutionary framework for future studies on L. monocytogenes epidemiology, ecology, and virulence. Listeria monocytogenes is a pathogen transmitted through contaminated food and is responsible for severe infections, including meningitis and abortion in animals and humans. It is known that many distinct strains of this pathogen exist, and that they differ in their virulence and epidemic potential. Unfortunately, there is currently no standard definition of strains and no comprehensive overview of their evolution. To tackle these serious limitations to the control of listeriosis and to improve knowledge of how virulence evolves, we characterized a large collection of isolates with sequence-based genotyping methods. We were thus able to identify precisely the most prevalent clones of L. monocytogenes, i.e., groups of isolates that descend from a single ancestral bacterium, which can now be characterized further for diagnostic purposes and determination of their precise ecology and virulence potential. We also determined how these clones evolved from their common ancestor and the evolutionary history by which they acquired their phenotypic characteristics, such as antigenic structures. Finally, we show that some particular strains tend to lose a virulence factor that plays a crucial role in infection in humans. This is a rare example of evolution towards reduced virulence of pathogens, and the discovery of the selective forces behind this phenomenon may have important epidemiological and biological implications.

Mark Achtman and colleagues report the whole-genome sequencing of 11 Yersinia pestis isolates, the causative agent of the plague. Their phylogeographic analysis on a larger dataset of Y. pestis global isolates suggests historical routes of transmission. Plague is a pandemic human invasive disease caused by the bacterial agent Yersinia pestis. We here report a comparison of 17 whole genomes of Y. pestis isolates from global sources. We also screened a global collection of 286 Y. pestis isolates for 933 SNPs using Sequenom MassArray SNP typing. We conducted phylogenetic analyses on this sequence variation dataset, assigned isolates to populations based on maximum parsimony and, from these results, made inferences regarding historical transmission routes. Our phylogenetic analysis suggests that Y. pestis evolved in or near China and spread through multiple radiations to Europe, South America, Africa and Southeast Asia, leading to country-specific lineages that can be traced by lineage-specific SNPs. All 626 current isolates from the United States reflect one radiation, and 82 isolates from Madagascar represent a second radiation. Subsequent local microevolution of Y. pestis is marked by sequential, geographically specific SNPs.

Understanding Mycobacterium tuberculosis (Mtb) transmission is essential to guide efficient tuberculosis control strategies. Traditional strain typing lacks sufficient discriminatory power to resolve large outbreaks. Here, we tested the potential of using next generation genome sequencing for identification of outbreak-related transmission chains. During long-term (1997 to 2010) prospective population-based molecular epidemiological surveillance comprising a total of 2,301 patients, we identified a large outbreak caused by an Mtb strain of the Haarlem lineage. The main performance outcome measure of whole genome sequencing (WGS) analyses was the degree of correlation of the WGS analyses with contact tracing data and the spatio-temporal distribution of the outbreak cases. WGS analyses of the 86 isolates revealed 85 single nucleotide polymorphisms (SNPs), subdividing the outbreak into seven genome clusters (two to 24 isolates each), plus 36 unique SNP profiles. WGS results showed that the first outbreak isolates detected in 1997 were falsely clustered by classical genotyping. In 1998, one clone (termed “Hamburg clone”) started expanding, apparently independently from differences in the social environment of early cases. Genome-based clustering patterns were in better accordance with contact tracing data and the geographical distribution of the cases than clustering patterns based on classical genotyping. A maximum of three SNPs were identified in eight confirmed human-to-human transmission chains, involving 31 patients. We estimated the Mtb genome evolutionary rate at 0.4 mutations per genome per year. This rate suggests that Mtb grows in its natural host with a doubling time of approximately 22 h (400 generations per year). Based on the genome variation discovered, emergence of the Hamburg clone was dated back to a period between 1993 and 1997, hence shortly before the discovery of the outbreak through epidemiological surveillance. Our findings suggest that WGS is superior to conventional genotyping for Mtb pathogen tracing and investigating micro-epidemics. WGS provides a measure of Mtb genome evolution over time in its natural host context. Please see later in the article for the Editors' Summary Tuberculosis—a contagious bacterial disease that usually infects the lungs—is a major public health problem, particularly in low- and middle-income countries. In 2011, an estimated 8.7 million people developed tuberculosis globally, and 1.4 million people died from the disease. Tuberculosis is second only to HIV/AIDS in terms of global deaths from a single infectious agent. Mycobacterium tuberculosis, the bacterium that causes tuberculosis, is readily spread in airborne droplets when people with active disease cough or sneeze. The characteristic symptoms of tuberculosis include persistent cough, weight loss, fever, and night sweats. Diagnostic tests for the disease include sputum smear analysis (examination of mucus coughed up from the lungs for the presence of M. tuberculosis), mycobacterial culture (growth of M. tuberculosis from sputum), and chest X-rays. Tuberculosis can be cured by taking several antibiotics daily for at least six months, although the recent emergence of multidrug-resistant M. tuberculosis is making tuberculosis harder to treat. Although efforts to reduce the global burden of tuberculosis are showing some improvements, the annual decline in the number of people developing tuberculosis continues to be slow. To develop optimized control strategies, experts need to be able to accurately track M. tuberculosis transmission within human populations. Because M. tuberculosis, like all bacteria, accumulates genetic changes over time, there are many different strains (genetic variants) of M. tuberculosis. Genotyping methods have been developed that identify different bacterial strains by examining specific regions of the bacterial genome (blueprint), but because these methods examine only a small part of the genome, they may not distinguish between related transmission chains. That is, traditional strain genotyping methods may not be able to determine accurately where a tuberculosis outbreak started or how it spread through a population. In this longitudinal cohort study, the researchers compare the ability of whole genome sequencing (WGS), which is rapidly becoming widely available, and traditional genotyping to provide information about a recent German tuberculosis outbreak. In a longitudinal cohort study, a population is followed over time to analyze the occurrence of a specific disease. During long-term (1997–2010) population-based molecular epidemiological surveillance (disease surveillance that uses molecular techniques rather than reports of illness) in Hamburg and Schleswig-Holstein, the researchers identified a large tuberculosis outbreak caused by M. tuberculosis isolates of the Haarlem lineage using classical strain typing. The researchers examined each of the 86 isolates from this outbreak using WGS and classical genotyping and asked whether the results of these two approaches correlated with contact tracing data (information is routinely collected about the people a patient with tuberculosis has recently met so that these contacts can be tested for tuberculosis and treated if necessary) and with the spatio-temporal distribution of outbreak cases. WGS of the isolates identified 85 single nucleotide polymorphisms (SNPs; genomic sequence variants in which single building blocks, or nucleotides, are altered) that subdivided the outbreak into seven clusters of isolates and 36 unique isolates. The WGS results showed that the first isolates of the outbreak were incorrectly clustered by classical genotyping and that one strain—the “Hamburg clone”—started expanding in 1998. Notably, the genome-based clustering patterns were in better accordance with contact tracing data and with the geographical distribution of cases than clustering patterns based on classical genotyping, and they identified eight confirmed human-to-human transmission chains that involved 31 patients and a maximum of three SNPs. Finally, the researchers used their WGS results to estimate that the Hamburg clone emerged between 1993 and 1997, shortly before the discovery of the tuberculosis outbreak through epidemiological surveillance. These findings show that WGS can be used to identify specific strains within large tuberculosis outbreaks more accurately than classical genotyping. They also provide new information about the evolution of M. tuberculosis during outbreaks and indicate how WGS data should be interpreted in future genome-based molecular epidemiology studies. WGS has the potential to improve the molecular epidemiological surveillance and control of tuberculosis and of other infectious diseases. Importantly, note the researchers, ongoing reductions in the cost of WGS, the increased availability of “bench top” genome sequencers, and bioinformatics developments should all accelerate the implementation of WGS as a standard method for the identification of transmission chains in infectious disease outbreaks. Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001387.