Biology subjects

Turner, P.

Publications and source records attributed to Turner, P..

9 recordsLinked to original sources

bioRxiv2018

Transmission dynamics and between-species interactions of multidrug-resistant Enterobacteriaceae

Widespread resistance to antibiotics is among the gravest threats to modern medicine, and controlling the spread of multi-drug resistant Enterobacteriaceae has been given priority status by the World Health Organization. Interventions to reduce transmission within hospital wards may be informed by modifiable patient-level risk factors for becoming colonised, however understanding of factors that influence a patients risk of acquisition is limited. We analyse data from a one year prospective carriage study in a neonatal intensive care unit in Cambodia using Bayesian hierarchical models to estimate the daily probability of acquiring multi-drug resistant organisms, while accounting for patient-level time-varying covariates, including interactions between species, and interval-censoring of transmission events. We estimate the baseline daily probability for becoming colonised with third generation cephalosporin resistant (3GC-R) Klebsiella pneumoniae as 0.142 (95% credible interval [CrI] 0.066, 0.27), nearly ten times higher than the daily probability of acquiring 3GC-R Escherichia coli (0.016 [95% CrI 0.0038, 0.049]). Prior colonization with 3GC-R K. pneumoniae was associated with a greatly increased risk of a patient acquiring 3GC-R E. coli (odds ratio [OR] 6.4 [95% CrI 2.8, 20.9]). Breast feeding was associated with a reduced risk of colonization with both 3GC-R K. pneumoniae (OR 0.73 [95% CrI 0.38, 1.5]) and E. coli (OR 0.62 [95% CrI 0.28, 1.6]). The use of an oral probiotic (Lactobacillus acidophilus) did not show clear evidence of protection against colonization with either 3GC-R K. pneumoniae (OR 0.83 [95% CrI 0.51, 1.3]) or 3GC-R E. coli (OR 1.3 [95% CrI 0.77, 2.1]). Antibiotic consumption within the past 48 hours did not strongly influence the risk of acquiring 3GC-R K. pneumoniae. For 3GC-R E. coli, ceftriaxone showed the strongest effect for increasing the risk of acquisition (OR 2.2 [95% CrI 0.66, 6.2]) and imipenem was associated with a decreased risk (OR 0.31 [95% CrI 0.099, 0.76). Using 317 whole-genome assemblies of K. pneumoniae, we determined putatively related clusters and used a range of models to infer transmission rates. Model comparison strongly favored models with a time-varying force of infection term that increased in proportion with the number of colonized patients, providing evidence of patient-to-patient transmission, including among a cluster of Klebsiella quasipneumoniae. Our findings provide support for the hypothesis that K. pneumoniae can be spread person-to-person within ward settings. Subsequent horizontal gene transfer within patients from K. pneumoniae provides the most parsimonious explanation for the strong association between colonization with 3GC-R K. pneumoniae and acquisition of 3GC-R E. coli.

epidemiology↗

bioRxiv2018

Panton-Valentine leukocidin is the key determinant of Staphylococcus aureus pyomyositis in a bacterial genome-wide association study

Pyomyositis is a severe bacterial infection of skeletal muscle, commonly affecting children in tropical regions and predominantly caused by Staphylococcus aureus. To understand the contribution of bacterial genomic factors to pyomyositis, we conducted a genome-wide association study of S. aureus cultured from 101 children with pyomyositis and 417 children with asymptomatic nasal carriage attending the Angkor Hospital for Children in Cambodia. We found a strong relationship between bacterial genetic variation and pyomyositis, with estimated heritability 63.8% (95% CI 49.2-78.4%). The presence of the Panton-Valentine leucocidin (PVL) locus increased the odds of pyomyositis 130-fold (p =10-17.9). The signal of association mapped both to the PVL-coding sequence and the sequence immediately upstream. Together these regions explained > 99.9% of heritability. Our results establish staphylococcal pyomyositis, like tetanus and diphtheria, as critically dependent on expression of a single toxin and demonstrate the potential for association studies to identify specific bacterial genes promoting severe human disease.

microbiology↗

bioRxiv2018

Using machine learning to guide targeted and locally-tailored empiric antibiotic prescribing in a children’s hospital in Cambodia

BackgroundEarly and appropriate empiric antibiotic treatment of patients suspected of having sepsis is associated with reduced mortality. The increasing prevalence of antimicrobial resistance risks eroding the benefits of such empiric therapy. This problem is particularly severe for children in developing country settings. We hypothesized that by applying machine learning approaches to readily collected patient data, it would be possible to obtain actionable and patient-specific predictions for antibiotic-susceptibility. If sufficient discriminatory power can be achieved, such predictions could lead to substantial improvements in the chances of choosing an appropriate antibiotic for empiric therapy, while minimizing the risk of increased selection for resistance due to use of antibiotics usually held in reserve.\n\nMethods and FindingsWe analyzed blood culture data collected from a 100-bed childrens hospital in North-West Cambodia between February 2013 and January 2016. Clinical, demographic and living condition information for each child was captured with 35 independent variables. Using these variables, we used a suite of machine learning algorithms to predict Gram stains and whether bacterial pathogens could be treated with standard empiric antibiotic therapies: i) ampicillin and gentamicin; ii) ceftriaxone; iii) at least one of the above.\n\n243 cases of bloodstream infection were available for analysis. We used 195 (80%) to train the algorithms, and 48 (20%) for evaluation. We found that the random forest method had the best predictive performance overall as assessed by the area under the receiver operating characteristic curve (AUC), though support vector machine with radial kernel had similar performance for predicting Gram stain and ceftriaxone susceptibility. Predictive performance of logistic regression, simple and boosted decision trees and k-nearest neighbors were poor in comparison. The random forest method gave an AUC of 0.91 (95%CI 0.81-1.00) for predicting susceptibility to ceftriaxone, 0.75 (0.60-0.90) for susceptibility to ampicillin and gentamicin, 0.76 (0.59-0.93) for susceptibility to neither, and 0.69 (0.53-0.85) for Gram stain result. The most important variables for predicting susceptibility were time from admission to blood culture, patient age, hospital versus community-acquired infection, and age-adjusted weight score.\n\nConclusionsApplying machine learning algorithms to patient data that are readily available even in resource-limited hospital settings can provide highly informative predictions on susceptibilities of pathogens to guide appropriate empiric antibiotic therapy. Used as a decision support tool, such approaches have the potential to lead to better targeting of empiric therapy, improve patient outcomes and reduce the burden of antimicrobial resistance.\n\nAuthor summaryO_LSTWhy was this study done?C_LSTO_LIEarly and appropriate antibiotic treatment of patients with life-threatening bacterial infections is thought to reduce the risk of mortality.\nC_LIO_LIIn hospitals that have a microbiology laboratory, it takes 3-4 days to get results which indicate which antibiotics are likely to be effective; before this information is available antibiotics have to be prescribed empirically i.e. without knowledge of the causative organism.\nC_LIO_LIIncreasing resistance to antibiotics amongst bacteria makes finding an appropriate antibiotic to use empirically difficult; this problem is particularly severe for children in developing country settings.\nC_LIO_LIIf we could predict which antibiotics were likely to be effective at the time of starting antibiotic therapy, we might be able to improve patient outcomes and reduce resistance.\nC_LI\n\nO_LSTWhat Did the Researchers Do and Find?C_LSTO_LIWe evaluated the ability of a number of different algorithms (i.e. sets of step-by-step instructions) to predict susceptibility to commonly-used antibiotics using routinely available patient data from a childrens hospital in Cambodia.\nC_LIO_LIWe found that an algorithm called random forests enabled surprisingly accurate predictions, particularly for predicting whether the infection was likely to be treatable with ceftriaxone, the most commonly used empiric antibiotic at the study hospital.\nC_LIO_LIUsing this approach it would be possible to correctly predict when a different antibiotic would be needed for empiric treatment over 80% of the time, while recommending a different antibiotic when ceftriaxone would suffice less than 20% of the time.\nC_LI\n\nO_LSTWhat Do These Findings Mean?C_LSTO_LIUsing readily available patient information, sophisticated algorithms can enable good predictions of whether antibiotics are likely to be effective several days before laboratory tests are available.\nC_LIO_LIAlgorithms would need to be trained with local hospital data, but our study shows that even with relatively limited data from a small hospital, good predictions can be obtained.\nC_LIO_LIUsed as part of a decision support system such algorithms could help choose appropriate antibiotics for empiric therapy; this would be expected to translate into better patient outcomes and may help to reduce resistance.\nC_LIO_LISuch as a decision support system would have very low costs and be easy to implement in low- and middle-income countries.\nC_LI

epidemiology↗

bioRxiv2018

Candidatus Ornithobacterium hominis sp. nov.: insights gained from draft genomes obtained from nasopharyngeal swabs

Candidatus Ornithobacterium hominis sp. nov. represents a new member of the Flavobacteriaceae detected in 16S rRNA gene surveys from Southeast Asia, Africa and Australia. It frequently colonises the infant nasopharynx at high proportional abundance, and we demonstrate its presence in 42% of nasopharyngeal swabs from 12 month old children in the Maela refugee camp in Thailand. The species, a Gram negative bacillus, has not yet been cultured but the cells can be identified in mixed samples by fluorescent hybridisation. Here we report seven genomes assembled from metagenomic data, two to improved draft standard. The genomes are approximately 1.9Mb, sharing 62% average amino acid identity with the only other member of the genus, the bird pathogen Ornithobacterium rhinotracheale. The draft genomes encode multiple antibiotic resistance genes, competition factors, Flavobacterium johnsoniae-like gliding motility genes and a homolog of the Pasteurella multocida mitogenic toxin. Intra- and inter-host genome comparison suggests that colonisation with this bacterium is both persistent and strain exclusive.

genomics↗

bioRxiv2017

Transmission patterns of hyper-endemic multi-drug resistant Klebsiella pneumoniae in a Cambodian neonatal unit: a longitudinal study with whole genome sequencing

BackgroundKlebsiella pneumoniae is an important and increasing cause of life-threatening disease in hospitalised neonates. Third generation cephalosporin resistance (3GC-R) is frequently a marker of multi-drug resistance, and can complicate management of infections. 3GC-R K. pneumoniae is hyper-endemic in many developing country settings, but its epidemiology is poorly understood and prospective studies of endemic transmission are lacking. We aimed to determine the transmission dynamics of 3GC-R K. pneumoniae in a newly opened neonatal unit (NU) in Cambodia.\n\nMethodsWe performed a prospective longitudinal study between September and November 2013. Rectal swabs from 37 consented patients were collected upon NU admission and every three days thereafter. Morphologically different colonies from swabs growing cefpodoxime-resistant K. pneumoniae were selected for whole-genome sequencing (WGS).\n\nResults32/37 (86%) patients screened positive for 3GC-R K. pneumoniae and 93 colonies from 119 swabs were sequenced. Isolates were resistant to a median of six (range 3-9) antimicrobials. WGS revealed high diversity; pairwise distances between isolates from the same patient were either 0-1 SNV or >1,000 SNVs; 19/32 colonized patients harboured K. pneumoniae colonies differing by >1000 SNVs. Diverse lineages accounted for 18 probable importations to the NU and nine probable transmission clusters involving 19/37 (51%) of screened patients. Median cluster size was 5 patients (range 3-9).\n\nConclusionsThe epidemiology of 3GC-R K. pneumoniae was characterised by multiple introductions and a dense network of cross-infection, with half of screened neonates part of a transmission cluster. Efforts to reduce the 3GC-R K. pneumoniae disease burden should consider targeting both processes.

epidemiology↗

bioRxiv2017

Epidemiology of paediatric gastrointestinal colonisation by extended spectrum cephalosporin-resistant Escherichia coli and Klebsiella pneumoniae isolates in north-west Cambodia

Extended-spectrum cephalosporin resistance (ESC-R) in Escherichia coli and Klebsiella pneumoniae is a healthcare threat; high gastrointestinal carriage rates are reported from South-east Asia. Colonisation prevalence data in Cambodia are lacking. We determined gastrointestinal colonisation prevalence of ESC-resistant E. coli (ESC-R-EC) and K. pneumoniae (ESC-R-KP) in Cambodian children/adolescents and associated risk factors; characterised relevant resistance genes, their genetic contexts, and the genetic relatedness of ESC-R strains using whole genome sequencing (WGS). Faeces and questionnaire data were obtained from individuals <16 years in northwestern Cambodia, 2012. WGS of cultured ESC-R-EC/KP was performed (Illumina). Maximum likelihood phylogenies were used to characterise relatedness of isolates; ESC-R-associated resistance genes and their genetic contexts were identified from de novo assemblies using BLASTn and automated/manual annotation. 82/148 (55%) of children/adolescents were ESC-R-EC/KP colonised; 12/148 (8%) were co-colonised with both species. Independent risk factors for colonisation were hospitalisation (OR: 3.12, 95%, CI [1.52-6.38]) and intestinal parasites (OR: 3.11 [1.29-7.51]); school attendance conferred decreased risk (OR: 0.44 [0.21-0.92]. ESC-R strains were diverse; the commonest ESC-R mechanisms were blaCTX-M 1 and 9 sub-family variants. Structures flanking these genes were highly variable, and for blaCTX-M-15, -55 and -27, frequently involved IS26. Chromosomal blaCTX-M integration was common in E. coli. Gastrointestinal ESC-R-EC/KP colonisation is widespread in Cambodian children/adolescents; hospital admission and intestinal parasites are independent risk factors. The genetic contexts of blaCTX-M are highly mosaic, consistent with rapid horizontal exchange. Chromosomal integration of blaCTX-M may result in stable propagation in these community-associated pathogens.

microbiology↗

bioRxiv2017

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, and the duration of carriage is an important consideration in modelling transmission dynamics and vaccine response. Existing studies of carriage duration variability are based at the serotype level only, and do not probe variation within lineages or fully quantify interactions with other environmental factors.\n\nHere we developed a model to calculate the duration of carriage episodes from longitudinal swab data. By combining these results with whole genome sequence data we estimate that pneumococcal genomic variation accounted for 63% of the phenotype variation, whereas host traits 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%). For the locus effects, a genome-wide association study identified 16 loci which may have an effect on carriage duration independent of serotype. Hits at a genome-wide level of significance were to prophage sequences, suggesting infection by such viruses substantially affects carriage duration.\n\nThese results show that both serotype and non-serotype specific effects alter carriage duration in infants and young children and are more important than other environmental factors such as host genetics. This has implications for models of pneumococcal competition and antibiotic resistance, and leads the way for the analysis of heritability of complex bacterial traits.\n\nSignificance statementOther than serotype, the genetic determinants of pneumococcal carriage duration are unknown. In this study we used longitudinal sampling to measure the duration of carriage in infants, and searched for any associated variation in the pan-genome. While we found that the pathogen genome explains most of the variability in duration, serotype did not fully account for this. Recent theoretical work has proposed the existence of alleles which alter carriage duration to explain the puzzle of continued coexistence of antibiotic-resistant and sensitive strains. Here we have shown that these alleles do exist in a natural population, and also identified candidates for the loci which fulfil this role. Together these findings have implications for future modelling of pneumococcal epidemiology and resistance.

genomics↗

bioRxiv2017

Effects of Historical Coinfection on Host Shift Abilities of Exploitative and Competitive Viruses

Rapid evolution contributes to frequent emergence of RNA viral pathogens on novel hosts. However, accurately predicting which viral genotypes will emerge has been elusive. Prior work with lytic RNA bacteriophage f6 (family Cystoviridae) suggested that evolution under low multiplicity of infection (MOI; proportion of viruses to susceptible cells) selected for greater host exploitation, while evolution under high MOI selected for better intracellular competition against co-infecting viruses. We predicted that phage genotypes that experienced 300 generations of low MOI ecological history would be relatively advantaged in growth on two novel hosts. We inferred viral growth through changes in host population density, specifically by analyzing five attributes of growth curves of infected bacteria. Despite equivalent growth of evolved viruses on the original host, low MOI evolved clones were generally advantaged relative to high MOI clones in exploiting novel hosts. We also observed genotype-specific differences in clone infectivity: High fitness genotypes on the original host also performed better on novel hosts. Our results indicated that traits allowing greater exploitation of the original host correlated positively with performance on novel hosts. Based on infectivity differences of viruses from high versus low MOI histories, we suggest that prior MOI selection can later affect emergence potential.

evolutionary biology↗

bioRxiv2017

Frequent recombination of pneumococcal capsule highlights future risks of emergence of novel serotypes.

Capsular diversity of Streptococcus pneumoniae constitutes a major obstacle in eliminating the pneumococcal disease. Such diversity is genetically encoded by almost 100 variants of the capsule polysaccharide locus (cps). However, the evolutionary dynamics of the capsule - the target of the currently used vaccines - remains not fully understood. Here, using genetic data from 4,469 bacterial isolates, we found cps to be an evolutionary hotspot with elevated substitution and recombination rates. These rates were a consequence of altered selection at this locus, supporting the hypothesis that the capsule has an increased potential to generate novel diversity compared to the rest of the genome. Analysis of twelve serogroups revealed their complex evolutionary history, which was principally driven by recombination with other serogroups and other streptococci. We observed significant variation in recombination rates between different serogroups. This variation could only be partially explained by the lineage-specific recombination rate, the remaining factors being likely driven by serogroup-specific ecology and epidemiology. Finally, we discovered two previously unobserved mosaic serotypes in the densely sampled collection from Mae La, Thailand, here termed 10X and 21X. Our results thus emphasise the strong adaptive potential of the bacterium by its ability to generate novel serotypes by recombination.

evolutionary biology↗