8 research outputs found
The effect of recombination on the evolution of a population of Neisseria meningitidis
Neisseria meningitidis (the meningococcus) is a major human pathogen with a history of high invasive disease burden, particularly in sub-Saharan Africa. Our current understanding of the evolution of meningococcal genomes is limited by the rarity of large-scale genomic population studies and lack of in-depth investigation of the genomic events associated with routine pathogen transmission. Here, we fill this knowledge gap by a detailed analysis of 2839 meningococcal genomes obtained through a carriage study of over 50,000 samples collected systematically in Burkina Faso, West Africa, before, during, and after the serogroup A vaccine rollout, 2009-2012. Our findings indicate that the meningococcal genome is highly dynamic, with highly recombinant loci and frequent gene sharing across deeply separated lineages in a structured population. Furthermore, our findings illustrate how population structure can correlate with genome flexibility, as some lineages in Burkina Faso are orders of magnitude more recombinant than others. We also examine the effect of selection on the population, in particular how it is correlated with recombination. We find that recombination principally acts to prevent the accumulation of deleterious mutations, although we do also find an example of recombination acting to speed the adaptation of a gene. In general, we show the importance of recombination in the evolution of a geographically expansive population with deep population structure in a short timescale. This has important consequences for our ability to both foresee the outcomes of vaccination programs and, using surveillance data, predict when lineages of the meningococcus are likely to become a public health concern.Peer reviewe
Producing polished prokaryotic pangenomes with the Panaroo pipeline
Population-level comparisons of prokaryotic genomes must take into account the substantial differences in gene content resulting from horizontal gene transfer, gene duplication and gene loss. However, the automated annotation of prokaryotic genomes is imperfect, and errors due to fragmented assemblies, contamination, diverse gene families and mis-assemblies accumulate over the population, leading to profound consequences when analysing the set of all genes found in a species. Here, we introduce Panaroo, a graph-based pangenome clustering tool that is able to account for many of the sources of error introduced during the annotation of prokaryotic genome assemblies. Panaroo is available at https://github.com/gtonkinhill/panaroo.Peer reviewe
Genome-wide epistasis and co-selection study using mutual information
Covariance-based discovery of polymorphisms under co-selective pressure or epistasis has received considerable recent attention in population genomics. Both statistical modeling of the population level covariation of alleles across the chromosome and model-free testing of dependencies between pairs of polymorphisms have been shown to successfully uncover patterns of selection in bacterial populations. Here we introduce a model-free method, SpydrPick, whose computational efficiency enables analysis at the scale of pan-genomes of many bacteria. SpydrPick incorporates an efficient correction for population structure, which adjusts for the phylogenetic signal in the data without requiring an explicit phylogenetic tree. We also introduce a new type of visualization of the results similar to the Manhattan plots used in genome-wide association studies, which enables rapid exploration of the identified signals of co-evolution. Simulations demonstrate the usefulness of our method and give some insight to when this type of analysis is most likely to be successful. Application of the method to large population genomic datasets of two major human pathogens, Streptococcus pneumoniae and Neisseria meningitidis, revealed both previously identified and novel putative targets of co-selection related to virulence and antibiotic resistance, highlighting the potential of this approach to drive molecular discoveries, even in the absence of phenotypic data.Peer reviewe
The global meningitis genome partnership.
Genomic surveillance of bacterial meningitis pathogens is essential for effective disease control globally, enabling identification of emerging and expanding strains and consequent public health interventions. While there has been a rise in the use of whole genome sequencing, this has been driven predominately by a subset of countries with adequate capacity and resources. Global capacity to participate in surveillance needs to be expanded, particularly in low and middle-income countries with high disease burdens. In light of this, the WHO-led collaboration, Defeating Meningitis by 2030 Global Roadmap, has called for the establishment of a Global Meningitis Genome Partnership that links resources for: N. meningitidis (Nm), S. pneumoniae (Sp), H. influenzae (Hi) and S. agalactiae (Sa) to improve worldwide co-ordination of strain identification and tracking. Existing platforms containing relevant genomes include: PubMLST: Nm (31,622), Sp (15,132), Hi (1935), Sa (9026); The Wellcome Sanger Institute: Nm (13,711), Sp (>Â 24,000), Sa (6200), Hi (1738); and BMGAP: Nm (8785), Hi (2030). A steering group is being established to coordinate the initiative and encourage high-quality data curation. Next steps include: developing guidelines on open-access sharing of genomic data; defining a core set of metadata; and facilitating development of user-friendly interfaces that represent publicly available data
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Exploring the Population Structure, Recombination Landscape, and Pan-Genome of the Global Neisseria meningitidis Population
Neisseria meningitidis is a gram-negative species of bacteria
which causes meningitis, septicaemia, urethritis, and pneumonia
worldwide. Infections are typically asymptomatic carriage, but
those which cause disease are extremely difficult to treat, leading to a high case-fatality rate. As such, there is considerable
interest in studying N. meningitidis to understand its spread,
what causes development from carriage to invasive disease, and
how its evolution impacts efforts to control the disease. The
latter has been of particular concern in regions where there have
been outbreaks, particularly the ‘meningitis belt’ that spans
from West Africa to East Africa, where there is greater disease
burden and periodic epidemics which can span the region. Due
to difficulties in treatment, the primary method of controlling invasive meningococcal disease is vaccination. Currently, available
vaccines target five of the extant serogroups of N. meningitidis, chosen through study of the serogroups most frequently
found in disease. However, either the replacement of disease
lineages with those of different serogroups or capsular switching
within disease-associated lineages may undermine the success
of mass vaccination efforts and create the need for additional
campaigns. N. meningitidis specifically possesses characteristics
which make vaccine escape likely and unpredictable. The most
important are the adaptions which allow frequent homologous
recombination with other Neisseria. The evolutionary consequences of this sporadic partial chromosomal recombination are not well understood, but the transfer of alleles between distant lineages – including those associated with virulence – has been observed. Another gap in our understanding of bacterial
evolution is in the evolutionary effect of population structure.
Obilgately human-parasitic species such as N. meningitids have
a global distribution and opportunities for rapid migration, and
therefore may have a complex population structure. To study
these problems, I have assembled a collection of over 15,000
whole-genome sequenced N. meningitids isolates from 70 distinct
countries with isolation dates spanning over a hundred years.
These data consist of a mixture of publicly published data, and
three collections of newly sequenced isolates. Using these data,
I determine the global population structure of N. meningitids.
Subsequently, I infer phylogenetic trees for and find patterns of
recombination within major lineages in the global population.
Separately, I also infer and analyse the species-wide pan-genome.
The results of these analyses indicate that N. meningitidis has a
deep well of generally unsampled diversity in an extremely complex population structure which is primarily made up of a few
globally distributed lineages. Within these lineages, population
bottlenecks are a frequent occurrence. The 25 major lineages
differ significantly in both their rates of recombination and the
distribution of recombination across their genomes, but evidence
suggest that most recombination occurs within N. meningitidis.
In a local population, recombination generally acts to reduce
the effect of deleterious mutations, although an example also
exists of recombination acting in concert with positive selection. The pan-genome reveals the extent to which recombination
can disrupt tree-like evolution, with most major lineages containing patterns of relatedness in their accessory gene content
inconsistent with their whole-genome phylogenies. Trends in
the pan-genome indicate that most gene gain is from other N.
meningitidis isolates, but is governed primarily by evolutionary forces and not recombination rate. Together, these results
demonstrate the profound complexity present in the population
structure of N. meningitidis, and distinct evolutionary trends in
individual lineages. This work also underscores the importance
of carriage sampling and the value of a global perspective when studying a globally-distributed species. Further sampling in regions which are under-sampled and ongoing carriage surveillance
will be a crucial part of any long-term efforts to successfully
control the disease through vaccination.Wellcome Sanger Institute PhD studentshi
Diversification in immunogenicity genes caused by selective pressures in invasive meningococci
We studied population genomics of 486 Neisseria meningitidis isolates causing meningitis in the Netherlands during the period 1979–2003 and 2006–2013 using whole-genome sequencing to evaluate the impact of a hyperendemic period of serogroup B invasive disease. The majority of serogroup B isolates belonged to ST-41/44 (41 %) and ST-32 complex (16 %). Comparing the time periods, before and after the decline of serogroup B invasive disease, there was a decrease of ST-41/44 complex sequences (P=0.002). We observed the expansion of a sub-lineage within ST-41/44 complex sequences being associated with isolation from the 1979–2003 time period (P=0.014). Isolates belonging to this sub-lineage expansion within ST-41/44 complex were marked by four antigen allele variants. Presence of these allele variants was associated with isolation from the 1979– 2003 time period after correction for multiple testing (Wald test, P=0.0043 for FetA 1–5; P=0.0035 for FHbp 14; P=0.012 for PorA 7–2.4 and P=0.0031 for NHBA two peptide allele). These sequences were associated with 4CMenB vaccine coverage (Fisher’s exact test, P<0.001). Outside of the sub-lineage expansion, isolates with markedly lower levels of predicted vaccine coverage clustered in phylogenetic groups showing a trend towards isolation in the 2006–2013 time period (P=0.08). In conclusion, we show the emergence and decline of a sub-lineage expansion within ST-41/44 complex isolates concurrent with a hyperendemic period in meningococcal meningitis. The expansion was marked by specific antigen peptide allele combinations. We observed preliminary evidence for decreasing 4CMenB vaccine coverage in the post-hyperendemic period