Minna Vehkala

Genomic signatures of human and animal disease in the zoonotic pathogen Streptococcus suis

Streptococcus suis causes disease in pigs worldwide and is increasingly implicated in zoonotic disease in East and South-East Asia. To understand the genetic basis of disease in S. suis, we study the genomes of 375 isolates with detailed clinical phenotypes from pigs and humans from the United Kingdom and Vietnam. Here, we show that isolates associated with disease contain substantially fewer genes than non-clinical isolates, but are more likely to encode virulence factors. Human disease isolates are limited to a single-virulent population, originating in the 1920, s when pig production was intensified, but no consistent genomic differences between pig and human isolates are observed. There is little geographical clustering of different S. suis subpopulations, and the bacterium undergoes high rates of recombination, implying that an increase in virulence anywhere in the world could have a global impact over a short timescale.

Combined Analysis of Variation in Core, Accessory and Regulatory Genome Regions Provides a Super-Resolution View into the Evolution of Bacterial Populations

The use of whole-genome phylogenetic analysis has revolutionized our understanding of the evolution and spread of many important bacterial pathogens due to the high resolution view it provides. However, the majority of such analyses do not consider the potential role of accessory genes when inferring evolutionary trajectories. Moreover, the recently discovered importance of the switching of gene regulatory elements suggests that an exhaustive analysis, combining information from core and accessory genes with regulatory elements could provide unparalleled detail of the evolution of a bacterial population. Here we demonstrate this principle by applying it to a worldwide multi-host sample of the important pathogenic E. coli lineage ST131. Our approach reveals the existence of multiple circulating subtypes of the major drug–resistant clade of ST131 and provides the first ever population level evidence of core genome substitutions in gene regulatory regions associated with the acquisition and maintenance of different accessory genome elements.

Sequence element enrichment analysis to determine the genetic basis of bacterial phenotypes

Bacterial genomes vary extensively in terms of both gene content and gene sequence. This plasticity hampers the use of traditional SNP-based methods for identifying all genetic associations with phenotypic variation. Here we introduce a computationally scalable and widely applicable statistical method (SEER) for the identification of sequence elements that are significantly enriched in a phenotype of interest. SEER is applicable to tens of thousands of genomes by counting variable-length k-mers using a distributed string-mining algorithm. Robust options are provided for association analysis that also correct for the clonal population structure of bacteria. Using large collections of genomes of the major human pathogens Streptococcus pneumoniae and Streptococcus pyogenes, SEER identifies relevant previously characterized resistance determinants for several antibiotics and discovers potential novel factors related to the invasiveness of S. pyogenes. We thus demonstrate that our method can answer important biologically and medically relevant questions.

Global and regional dissemination and evolution of Burkholderia pseudomallei

The environmental bacterium Burkholderia pseudomallei causes an estimated 165,000 cases of human melioidosis per year worldwide and is also classified as a biothreat agent. We used whole genome sequences of 469 B. pseudomallei isolates from 30 countries collected over 79 years to explore its geographic transmission. Our data point to Australia as an early reservoir, with transmission to Southeast Asia followed by onward transmission to South Asia and East Asia. Repeated reintroductions were observed within the Malay Peninsula and between countries bordered by the Mekong River. Our data support an African origin of the Central and South American isolates with introduction of B. pseudomallei into the Americas between 1650 and 1850, providing a temporal link with the slave trade. We also identified geographically distinct genes/variants in Australasian or Southeast Asian isolates alone, with virulence-associated genes being among those over-represented. This provides a potential explanation for clinical manifestations of melioidosis that are geographically restricted.

Novel R Pipeline for Analyzing Biolog Phenotypic Microarray Data

Data produced by Biolog Phenotype MicroArrays are longitudinal measurements of cells’ respiration on distinct substrates. We introduce a three-step pipeline to analyze phenotypic microarray data with novel procedures for grouping, normalization and effect identification. Grouping and normalization are standard problems in the analysis of phenotype microarrays defined as categorizing bacterial responses into active and non-active, and removing systematic errors from the experimental data, respectively. We expand existing solutions by introducing an important assumption that active and non-active bacteria manifest completely different metabolism and thus should be treated separately. Effect identification, in turn, provides new insights into detecting differing respiration patterns between experimental conditions, e.g. between different combinations of strains and temperatures, as not only the main effects but also their interactions can be evaluated. In the effect identification, the multilevel data are effectively processed by a hierarchical model in the Bayesian framework. The pipeline is tested on a data set of 12 phenotypic plates with bacterium Yersinia enterocolitica. Our pipeline is implemented in R language on the top of opm R package and is freely available for research purposes.

Monomorphic genotypes within a generalist lineage of Campylobacter jejuni show signs of global dispersion

The decreased costs of genome sequencing have increased the capability to apply whole-genome sequencing to epidemiological surveillance of zoonotic Campylobacter jejuni. However, knowledge of the genetic diversity of this bacteria is vital for inferring relatedness between epidemiologically linked isolates and a necessary prerequisite for correct application of this methodology. To address this issue in C. jejuni we investigated the spatial and temporal signals in the genomes of a major clonal complex and generalist lineage, ST-45 CC, by analysing the population structure and genealogy as well as applying genome-wide association analysis of 340 isolates from across Europe collected over a wide time range. The occurrence and strength of the geographical signal varied between sublineages and followed the clonal frame when present, while no evidence of a temporal signal was found. Certain sublineages of ST-45 formed discrete and genetically isolated clades containing isolates with extremely similar genomes regardless of time and location of sampling. Based on a separate data set, these monomorphic genotypes represent successful C. jejuni clones, possibly spread around the globe by rapid animal (migrating birds), food or human movement. In addition, we observed an incongruence between the genealogy of the strains and multilocus sequence typing (MLST), challenging the existing clonal complex definition and the use of whole-genome gene-by-gene hierarchical nomenclature schemes for C. jejuni.

Identifying Multiple Potential Metabolic Cycles in Time-Series from Biolog Experiments

Biolog Phenotype Microarray (PM) is a technology allowing simultaneous screening of the metabolic behaviour of bacteria under a large number of different conditions. Bacteria may often undergo several cycles of metabolic activity during a Biolog experiment. We introduce a novel algorithm to identify these metabolic cycles in PM experimental data, thus increasing the potential of PM technology in microbiology. Our method is based on a statistical decomposition of the time-series measurements into a set of growth models. We show that the method is robust to measurement noise and captures accurately the biologically relevant signals from the data. Our implementation is made freely available as a part of an R package for PM data analysis and can be found at www.helsinki.fi/bsg/software/Biolog_Decomposition.

Convergent amino acid signatures in polyphyletic Campylobacter jejuni subpopulations suggest human niche tropism

Abstract Human infection with the gastrointestinal pathogen Campylobacter jejuni is dependent upon the opportunity for zoonotic transmission and the ability of strains to colonize the human host. Certain lineages of this diverse organism are more common in human infection but the factors underlying this overrepresentation are not fully understood. We analyzed 601 isolate genomes from agricultural animals and human clinical cases, including isolates from the multihost (ecological generalist) ST-21 and ST-45 clonal complexes (CCs). Combined nucleotide and amino acid sequence analysis identified 12 human-only amino acid KPAX clusters among polyphyletic lineages within the common disease causing CC21 group isolates, with no such clusters among CC45 isolates. Isolate sequence types within human-only CC21 group KPAX clusters have been sampled from other hosts, including poultry, so rather than representing unsampled reservoir hosts, the increase in relative frequency in human infection potentially reflects a genetic bottleneck at the point of human infection. Consistent with this, sequence enrichment analysis identified nucleotide variation in genes with putative functions related to human colonization and pathogenesis, in human-only clusters. Furthermore, the tight clustering and polyphyly of human-only lineage clusters within a single CC suggest the repeated evolution of human association through acquisition of genetic elements within this complex. Taken together, combined nucleotide and amino acid analysis of large isolate collections may provide clues about human niche tropism and the nature of the forces that promote the emergence of clinically important C. jejuni lineages.