Mark D. Preston

Rapid determination of anti-tuberculosis drug resistance from whole-genome sequences

Mycobacterium tuberculosis drug resistance (DR) challenges effective tuberculosis disease control. Current molecular tests examine limited numbers of mutations, and although whole genome sequencing approaches could fully characterise DR, data complexity has restricted their clinical application. A library (1,325 mutations) predictive of DR for 15 anti-tuberculosis drugs was compiled and validated for 11 of them using genomic-phenotypic data from 792 strains. A rapid online ‘TB-Profiler’ tool was developed to report DR and strain-type profiles directly from raw sequences. Using our DR mutation library, in silico diagnostic accuracy was superior to some commercial diagnostics and alternative databases. The library will facilitate sequence-based drug-susceptibility testing.

Dystromirs as Serum Biomarkers for Monitoring the Disease Severity in Duchenne Muscular Dystrophy

Duchenne muscular Dystrophy (DMD) is an inherited disease caused by mutations in the dystrophin gene that disrupt the open reading frame, while in frame mutations result in Becker muscular dystrophy (BMD). Ullrich congenital muscular dystrophy (UCMD) is due to mutations affecting collagen VI genes. Specific muscle miRNAs (dystromirs) are potential non-invasive biomarkers for monitoring the outcome of therapeutic interventions and disease progression. We quantified miR-1, miR-133a,b, miR-206 and miR-31 in serum from patients with DMD, BMD, UCMD and healthy controls. MiR-1, miR-133a,b and miR-206 were upregulated in DMD, but unchanged in UCMD compared to controls. Milder DMD patients had higher levels of dystromirs than more severely affected patients. Patients with low forced vital capacity (FVC) values, indicating respiratory muscle weakness, had low levels of serum miR-1 and miR-133b. There was no significant difference in the level of the dystromirs in BMD compared to controls. We also assessed the effect of dystrophin restoration on the expression of the five dystromirs in serum of DMD patients treated systemically for 12 weeks with antisense oligomer eteplirsen that induces skipping of exon 51 in the dystrophin gene. The dystromirs were also analysed in muscle biopsies of DMD patients included in a single dose intramuscular eteplirsen clinical trial. Our analysis detected a trend towards normalization of these miRNA between the pre- and post-treatment samples of the systemic trial, which however failed to reach statistical significance. This could possibly be due to the small number of patients and the short duration of these clinical trials. Although longer term studies are needed to clarify the relationship between dystrophin restoration following therapeutic intervention and the level of circulating miRNAs, our results indicate that miR-1 and miR-133 can be considered as exploratory biomarkers for monitoring the progression of muscle weakness and indirectly the remaining muscle mass in DMD.

SpolPred: rapid and accurate prediction of Mycobacterium tuberculosis spoligotypes from short genomic sequences

Summary: Spoligotyping is a well-established genotyping technique based on the presence of unique DNA sequences in Mycobacterium tuberculosis (Mtb), the causal agent of tuberculosis disease (TB). Although advances in sequencing technologies are leading to whole-genome bacterial characterization, tens of thousands of isolates have been spoligotyped, giving a global view of Mtb strain diversity. To bridge the gap, we have developed SpolPred, a software to predict the spoligotype from raw sequence reads. Our approach is compared with experimentally and de novo assembly determined strain types in a set of 44 Mtb isolates. In silico and experimental results are identical for almost all isolates (39/44). However, SpolPred detected five experimentally false spoligotypes and was more accurate and faster than the assembling strategy. Application of SpolPred to an additional seven isolates with no laboratory data led to types that clustered with identical experimental types in a phylogenetic analysis using single-nucleotide polymorphisms. Our results demonstrate the usefulness of the tool and its role in revealing experimental limitations. Availability and implementation: SpolPred is written in C and is available from www.pathogenseq.org/spolpred. Contact: francesc.coll@lshtm.ac.uk Supplementary information: Supplementary data are available at Bioinformatics Online.

PolyTB: A genomic variation map for Mycobacterium tuberculosis

Summary Tuberculosis (TB) caused by Mycobacterium tuberculosis (Mtb) is the second major cause of death from an infectious disease worldwide. Recent advances in DNA sequencing are leading to the ability to generate whole genome information in clinical isolates of M. tuberculosis complex (MTBC). The identification of informative genetic variants such as phylogenetic markers and those associated with drug resistance or virulence will help barcode Mtb in the context of epidemiological, diagnostic and clinical studies. Mtb genomic datasets are increasingly available as raw sequences, which are potentially difficult and computer intensive to process, and compare across studies. Here we have processed the raw sequence data (>1500 isolates, eight studies) to compile a catalogue of SNPs (n = 74,039, 63% non-synonymous, 51.1% in more than one isolate, i.e. non-private), small indels (n = 4810) and larger structural variants (n = 800). We have developed the PolyTB web-based tool (http://pathogenseq.lshtm.ac.uk/polytb) to visualise the resulting variation and important meta-data (e.g. in silico inferred strain-types, location) within geographical map and phylogenetic views. This resource will allow researchers to identify polymorphisms within candidate genes of interest, as well as examine the genomic diversity and distribution of strains. PolyTB source code is freely available to researchers wishing to develop similar tools for their pathogen of interest.

Elucidating emergence and transmission of multidrug-resistant tuberculosis in treatment experienced patients by whole genome sequencing

Background Understanding the emergence and spread of multidrug-resistant tuberculosis (MDR-TB) is crucial for its control. MDR-TB in previously treated patients is generally attributed to the selection of drug resistant mutants during inadequate therapy rather than transmission of a resistant strain. Traditional genotyping methods are not sufficient to distinguish strains in populations with a high burden of tuberculosis and it has previously been difficult to assess the degree of transmission in these settings. We have used whole genome analysis to investigate M. tuberculosis strains isolated from treatment experienced patients with MDR-TB in Uganda over a period of four years. Methods and Findings We used high throughput genome sequencing technology to investigate small polymorphisms and large deletions in 51 Mycobacterium tuberculosis samples from 41 treatment-experienced TB patients attending a TB referral and treatment clinic in Kampala. This was a convenience sample representing 69% of MDR-TB cases identified over the four year period. Low polymorphism was observed in longitudinal samples from individual patients (2-15 SNPs). Clusters of samples with less than 50 SNPs variation were examined. Three clusters comprising a total of 8 patients were found with almost identical genetic profiles, including mutations predictive for resistance to rifampicin and isoniazid, suggesting transmission of MDR-TB. Two patients with previous drug susceptible disease were found to have acquired MDR strains, one of which shared its genotype with an isolate from another patient in the cohort. Conclusions Whole genome sequence analysis identified MDR-TB strains that were shared by more than one patient. The transmission of multidrug-resistant disease in this cohort of retreatment patients emphasises the importance of early detection and need for infection control. Consideration should be given to rapid testing for drug resistance in patients undergoing treatment to monitor the emergence of resistance and permit early intervention to avoid onward transmission.

Population genomic structure and adaptation in the zoonotic malaria parasite Plasmodium knowlesi.

Significance Genome sequence analysis reveals that the zoonotic malaria parasite Plasmodium knowlesi consists of three highly divergent subpopulations. Two, commonly seen in sympatric human clinical infections in Malaysian Borneo, were identified in a previous study as corresponding to parasites seen in long-tailed and pig-tailed macaque hosts, respectively. A third type has been detected in a few laboratory-maintained isolates originally derived in the 1960s elsewhere in Southeast Asia. Divergence between the subpopulations varies significantly across the genome but overall is at a level indicating different subspecies. Analysis of the diversity within the most common type in human infections shows strong signatures of natural selection, including balancing selection and directional selection, on loci distinct from those under selection in endemic human malaria parasites. Malaria cases caused by the zoonotic parasite Plasmodium knowlesi are being increasingly reported throughout Southeast Asia and in travelers returning from the region. To test for evidence of signatures of selection or unusual population structure in this parasite, we surveyed genome sequence diversity in 48 clinical isolates recently sampled from Malaysian Borneo and in five lines maintained in laboratory rhesus macaques after isolation in the 1960s from Peninsular Malaysia and the Philippines. Overall genomewide nucleotide diversity (π = 6.03 × 10−3) was much higher than has been seen in worldwide samples of either of the major endemic malaria parasite species Plasmodium falciparum and Plasmodium vivax. A remarkable substructure is revealed within P. knowlesi, consisting of two major sympatric clusters of the clinical isolates and a third cluster comprising the laboratory isolates. There was deep differentiation between the two clusters of clinical isolates [mean genomewide fixation index (FST) = 0.21, with 9,293 SNPs having fixed differences of FST = 1.0]. This differentiation showed marked heterogeneity across the genome, with mean FST values of different chromosomes ranging from 0.08 to 0.34 and with further significant variation across regions within several chromosomes. Analysis of the largest cluster (cluster 1, 38 isolates) indicated long-term population growth, with negatively skewed allele frequency distributions (genomewide average Tajima’s D = −1.35). Against this background there was evidence of balancing selection on particular genes, including the circumsporozoite protein (csp) gene, which had the top Tajima’s D value (1.57), and scans of haplotype homozygosity implicate several genomic regions as being under recent positive selection.

estMOI: estimating multiplicity of infection using parasite deep sequencing data

Summary: Individuals living in endemic areas generally harbour multiple parasite strains. Multiplicity of infection (MOI) can be an indicator of immune status and transmission intensity. It has a potentially confounding effect on a number of population genetic analyses, which often assume isolates are clonal. Polymerase chain reaction-based approaches to estimate MOI can lack sensitivity. For example, in the human malaria parasite Plasmodium falciparum, genotyping of the merozoite surface protein (MSP1/2) genes is a standard method for assessing MOI, despite the apparent problem of underestimation. The availability of deep coverage data from massively parallizable sequencing technologies means that MOI can be detected genome wide by considering the abundance of heterozygous genotypes. Here, we present a method to estimate MOI, which considers unique combinations of polymorphisms from sequence reads. The method is implemented within the estMOI software. When applied to clinical P.falciparum isolates from three continents, we find that multiple infections are common, especially in regions with high transmission. Availability and implementation: estMOI is freely available from http://pathogenseq.lshtm.ac.uk. Contact: samuel.assefa@lshtm.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

Genomic Epidemiology of a Protracted Hospital Outbreak Caused by a Toxin A-Negative Clostridium difficile Sublineage PCR Ribotype 017 Strain in London, England

ABSTRACT Clostridium difficile remains the leading cause of nosocomial diarrhea worldwide, which is largely considered to be due to the production of two potent toxins: TcdA and TcdB. However, PCR ribotype (RT) 017, one of five clonal lineages of human virulent C. difficile, lacks TcdA expression but causes widespread disease. Whole-genome sequencing was applied to 35 isolates from hospitalized patients with C. difficile infection (CDI) and two environmental ward isolates in London, England. The phylogenetic analysis of single nucleotide polymorphisms (SNPs) revealed a clonal cluster of temporally variable isolates from a single hospital ward at University Hospital Lewisham (UHL) that were distinct from other London hospital isolates. De novo assembled genomes revealed a 49-kbp putative conjugative transposon exclusive to this hospital clonal cluster which would not be revealed by current typing methodologies. This study identified three sublineages of C. difficile RT017 that are circulating in London. Similar to the notorious RT027 lineage, which has caused global outbreaks of CDI since 2001, the lineage of toxin-defective RT017 strains appears to be continually evolving. By utilization of WGS technologies to identify SNPs and the evolution of clonal strains, the transmission of outbreaks caused by near-identical isolates can be retraced and identified.

Evolutionary optimality in stochastic search problems

‘Optimal’ behaviour in a biological system is not simply that which maximizes a mean, or temporally and spatially averaged, fitness function. Rather, population dynamics and demographic and environmental stochasticity are fundamental evolutionary ingredients. Here, we revisit the problem of optimal foraging, where some recent studies claim that organisms should forage according to Lévy walks. We show that, in an ecological scenario dominated by uncertainty and high mortality, Lévy walks can indeed be evolutionarily favourable. However, this conclusion is dependent on the definition of efficiency and the details of the simulations. We analyse measures of efficiency that incorporate population-level characteristics, such as variance, superdiffusivity and heavy tails, and compare the results with those generated by simple maximizing of the average encounter rate. These results have implications on stochastic search problems in general, and also on computational models of evolutionary optima.

Development of a candidate reference material for adventitious virus detection in vaccine and biologicals manufacturing by deep sequencing

Abstract Background Unbiased deep sequencing offers the potential for improved adventitious virus screening in vaccines and biotherapeutics. Successful implementation of such assays will require appropriate control materials to confirm assay performance and sensitivity. Methods A common reference material containing 25 target viruses was produced and 16 laboratories were invited to process it using their preferred adventitious virus detection assay. Results Fifteen laboratories returned results, obtained using a wide range of wet-lab and informatics methods. Six of 25 target viruses were detected by all laboratories, with the remaining viruses detected by 4–14 laboratories. Six non-target viruses were detected by three or more laboratories. Conclusion The study demonstrated that a wide range of methods are currently used for adventitious virus detection screening in biological products by deep sequencing and that they can yield significantly different results. This underscores the need for common reference materials to ensure satisfactory assay performance and enable comparisons between laboratories.