John A. Lees

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.

Adults with suspected central nervous system infection: A prospective study of diagnostic accuracy

OBJECTIVES To study the diagnostic accuracy of clinical and laboratory features in the diagnosis of central nervous system (CNS) infection and bacterial meningitis. METHODS We included consecutive adult episodes with suspected CNS infection who underwent cerebrospinal fluid (CSF) examination. The reference standard was the diagnosis classified into five categories: 1) CNS infection; 2) CNS inflammation without infection; 3) other neurological disorder; 4) non-neurological infection; and 5) other systemic disorder. RESULTS Between 2012 and 2015, 363 episodes of suspected CNS infection were included. CSF examination showed leucocyte count >5/mm3 in 47% of episodes. Overall, 89 of 363 episodes were categorized as CNS infection (25%; most commonly viral meningitis [7%], bacterial meningitis [7%], and viral encephalitis [4%]), 36 (10%) episodes as CNS inflammatory disorder, 111 (31%) as systemic infection, in 119 (33%) as other neurological disorder, and 8 (2%) as other systemic disorders. Diagnostic accuracy of individual clinical characteristics and blood tests for the diagnosis of CNS infection or bacterial meningitis was low. CSF leucocytosis differentiated best between bacterial meningitis and other diagnoses (area under the curve [AUC] 0.95) or any neurological infection versus other diagnoses (AUC 0.93). CONCLUSIONS Clinical characteristics fail to differentiate between neurological infections and other diagnoses, and CSF analysis is the main contributor to the final diagnosis.

Benzalkonium tolerance genes and outcome in Listeria monocytogenes meningitis

Objectives Listeria monocytogenes is a food-borne pathogen that can cause meningitis. The listerial genotype ST6 has been linked to increasing rates of unfavourable outcome over time. We investigated listerial genetic variation and the relation with clinical outcome in meningitis. Methods We sequenced 96 isolates from adults with listerial meningitis included in two prospective nationwide cohort studies by whole genome sequencing, and evaluated associations between bacterial genetic variation and clinical outcome. We validated these results by screening listerial genotypes of 445 cerebrospinal fluid and blood isolates from patients over a 30-year period from the Dutch national surveillance cohort. Results We identified a bacteriophage, phiLMST6 co-occurring with a novel plasmid, pLMST6, in ST6 isolates to be associated with unfavourable outcome in patients (p 2.83e-05). The plasmid carries a benzalkonium chloride tolerance gene, emrC, conferring decreased susceptibility to disinfectants used in the food-processing industry. Isolates harbouring emrC were growth inhibited at higher levels of benzalkonium chloride (median 60 mg/L versus 15 mg/L; p <0.001), and had higher MICs for amoxicillin and gentamicin compared with isolates without emrC (both p <0.001). Transformation of pLMST6 into naive strains led to benzalkonium chloride tolerance and higher MICs for gentamicin. Conclusions These results show that a novel plasmid, carrying the efflux transporter emrC, is associated with increased incidence of ST6 listerial meningitis in the Netherlands. Suggesting increased disease severity, our findings warrant consideration of disinfectants used in the food-processing industry that select for resistance mechanisms and may, inadvertently, lead to increased risk of poor disease outcome.

Genome-wide identification of lineage and locus specific variation associated with pneumococcal carriage duration

Streptococcus pneumoniae is a leading cause of invasive disease in infants, especially in low-income settings. Asymptomatic carriage in the nasopharynx is a prerequisite for disease, but variability in its duration is currently only understood at the serotype level. Here we developed a model to calculate the duration of carriage episodes from longitudinal swab data, and combined these results with whole genome sequence data. We estimated that pneumococcal genomic variation accounted for 63% of the phenotype variation, whereas the host traits considered here (age and previous carriage) accounted for less than 5%. We further partitioned this heritability into both lineage and locus effects, and quantified the amount attributable to the largest sources of variation in carriage duration: serotype (17%), drug-resistance (9%) and other significant locus effects (7%). A pan-genome-wide association study identified prophage sequences as being associated with decreased carriage duration independent of serotype, potentially by disruption of the competence mechanism. These findings support theoretical models of pneumococcal competition and antibiotic resistance.

Large scale genomic analysis shows no evidence for pathogen adaptation between the blood and cerebrospinal fluid niches during bacterial meningitis

Recent studies have provided evidence for rapid pathogen genome diversification, some of which could potentially affect the course of disease. We have previously described such variation seen between isolates infecting the blood and cerebrospinal fluid (CSF) of a single patient during a case of bacterial meningitis. Here, we performed whole-genome sequencing of paired isolates from the blood and CSF of 869 meningitis patients to determine whether such variation frequently occurs between these two niches in cases of bacterial meningitis. Using a combination of reference-free variant calling approaches, we show that no genetic adaptation occurs in either invaded niche during bacterial meningitis for two major pathogen species, Streptococcus pneumoniae and Neisseria meningitidis. This study therefore shows that the bacteria capable of causing meningitis are already able to do this upon entering the blood, and no further sequence change is necessary to cross the blood–brain barrier. Our findings place the focus back on bacterial evolution between nasopharyngeal carriage and invasion, or diversity of the host, as likely mechanisms for determining invasiveness.

SuperDCA for genome-wide epistasis analysis

The potential for genome-wide modelling of epistasis has recently surfaced given the possibility of sequencing densely sampled populations and the emerging families of statistical interaction models. Direct coupling analysis (DCA) has previously been shown to yield valuable predictions for single protein structures, and has recently been extended to genome-wide analysis of bacteria, identifying novel interactions in the co-evolution between resistance, virulence and core genome elements. However, earlier computational DCA methods have not been scalable to enable model fitting simultaneously to 104–105 polymorphisms, representing the amount of core genomic variation observed in analyses of many bacterial species. Here, we introduce a novel inference method (SuperDCA) that employs a new scoring principle, efficient parallelization, optimization and filtering on phylogenetic information to achieve scalability for up to 105 polymorphisms. Using two large population samples of Streptococcus pneumoniae, we demonstrate the ability of SuperDCA to make additional significant biological findings about this major human pathogen. We also show that our method can uncover signals of selection that are not detectable by genome-wide association analysis, even though our analysis does not require phenotypic measurements. SuperDCA, thus, holds considerable potential in building understanding about numerous organisms at a systems biological level.

Large scale genomic analysis shows no evidence for repeated pathogen adaptation during the invasive phase of bacterial meningitis in humans

Recent studies have provided evidence for rapid pathogen genome variation, some of which could potentially affect the course of disease. We have previously detected such variation by comparing isolates infecting the blood and cerebrospinal fluid (CSF) of a single patient during a case of bacterial meningitis. To determine whether the observed variation repeatedly occurs in cases of disease, we performed whole genome sequencing of paired isolates from blood and CSF of 938 meningitis patients. We also applied the same techniques to 54 paired isolates from the nasopharynx and CSF. Using a combination of reference-free variant calling approaches we show that no genetic adaptation occurs in the invasive phase of bacterial meningitis for four major pathogen species: Streptococcus pneumoniae, Neisseria meningitidis, Listeria monocytogenes and Haemophilus influenzae. From nasopharynx to CSF, no adaptation was seen in S. pneumoniae, but in N. meningitidis mutations potentially mediating adaptation to the invasive niche were occasionally observed in the dca gene. This study therefore shows that the bacteria capable of causing meningitis are already able to do this upon entering the blood, and no further sequence change is necessary to cross the blood-brain barrier. The variation discovered from nasopharyngeal isolates suggest that larger studies comparing carriage and invasion may help determine the likely mechanisms of invasiveness. Author Summary We have analysed the entire DNA sequence from bacterial pathogen isolates from cases of meningitis in 938 Dutch adults, focusing on comparing pairs of isolates from the patient’s blood and their cerebrospinal fluid. Previous research has been on only a single patient, but showed possible signs of adaptation to treatment within the host over the course of a single case of disease. By sequencing many more such paired samples, and including four different bacterial species, we were able to determine that adaptation of the pathogen does not occur after bloodstream invasion during bacterial meningitis. We also analysed 54 pairs of isolates from pre- and post-invasive niches from the same patient. In N. meningitidis we found variation in the sequence of one gene which appears to provide bacteria with an advantage after invasion of the bloodstream. Overall, our findings indicate that evolution after invasion in bacterial meningitis is not a major contribution to disease pathogenesis. Future studies should involve more extensive sampling between the carriage and disease niches, or on variation of the host.

Bacterial GWAS: not just gilding the lily.

This months Genome Watch discusses recent improvements to bacterial GWAS methods that have been inspired by techniques developed for human genetics.

R–M systems go on the offensive

This months Genome Watch explores how genetic variation in restriction–modification systems from Streptococcus pneumoniae contributes to the defence against phages and to bacterial virulence.

Fast Hierarchical Bayesian Analysis of Population Structure

We present fastbaps, a fast solution to the genetic clustering problem. Fastbaps rapidly identifies an approximate fit to a Dirichlet Process Mixture model (DPM) for clustering multilocus genotype data. Our efficient model-based clustering approach is able to cluster datasets 10-100 times larger than the existing model-based methods, which we demonstrate by analysing an alignment of over 110,000 sequences of HIV-1 pol genes. We also provide a method for rapidly partitioning an existing hierarchy in order to maximise the DPM model marginal likelihood, allowing us to split phylogenetic trees into clades and subclades using a population genomic model. Extensive tests on simulated data as well as a diverse set of real bacterial and viral datasets show that fastbaps provides comparable or improved solutions to previous model-based methods, while generally being significantly faster. The method is made freely available under an open source MIT licence as an easy to use R package at https://github.com/gtonkinhill/fastbaps.