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bioRxiv2018

Effect of Live Attenuated Influenza Vaccine on Pneumococcal Carriage

The widely used nasally-administered Live Attenuated Influenza Vaccine (LAIV) alters the dynamics of naturally occurring nasopharyngeal carriage of Streptococcus pneumoniae in animal models. Using a human experimental model (serotype 6B) we tested two hypotheses: 1) LAIV increased the density of S. pneumoniae in those already colonised; 2) LAIV administration promoted colonisation. Randomised, blinded administration of LAIV or nasal placebo either preceded bacterial inoculation or followed it, separated by a 3-day interval. The presence and density of S. pneumoniae was determined from nasal washes by bacterial culture and PCR. Overall acquisition for bacterial carriage were not altered by prior LAIV administration vs. controls (25/55 [45.5%] vs 24/62 [38.7%] respectively, p=0.46). Transient increase in acquisition was detected in LAIV recipients at day 2 (33/55 [60.0%] vs 25/62 [40.3%] in controls, p=0.03). Bacterial carriage densities were increased approximately 10-fold by day 9 in the LAIV recipients (2.82 vs 1.81 log10 titers, p=0.03). When immunisation followed bacterial acquisition (n=163), LAIV did not change area under the bacterial density-time curve (AUC) at day 14 by conventional microbiology (primary endpoint), but significantly reduced AUC to day 27 by PCR (p=0.03). These studies suggest that LAIV may transiently increase nasopharyngeal density of S. pneumoniae. Transmission effects should therefore be considered in the timing design of vaccine schedules.\n\nTrial registrationThe study was registered on EudraCT (2014-004634-26)\n\nFundingThe study was funded by the Bill and Melinda Gates Foundation and the UK Medical Research Council.

immunology↗

bioRxiv2018

Development of an interactive open source software application (RadaR) for infection management / antimicrobial stewardship

ObjectivesAnalysing process and outcome measures for patients suspected of or having an infection in an entire hospital requires processing large datasets and accounting for numerous patient parameters and treatment guidelines. Rapid, reproducible and adaptable analyses usually need substantial technical expertise but can yield valuable insight for infection management and antimicrobial stewardship (AMS) teams. We describe a software application (RadaR - Rapid analysis of diagnostic and antimicrobial patterns in R) for infection management allowing user-friendly, intuitive and interactive analysis of large datasets without prior in-depth statistical or software knowledge.\n\nMethods and ResultsRadaR was built in R, an open source programming language, making it free to use and adaptable to different settings. Shiny, an additional open source package to implement web-application frameworks in R, was used to develop the application. RadaR was developed in the context of a 1339-bed academic tertiary referral hospital to handle data of more than 180,000 admissions.\n\nRadaR visualizes analytical graphs and statistical summaries in an interactive manner within seconds. Users can filter large patient groups by 17 different criteria and investigate antimicrobial use, microbiological diagnostic use and results, and outcome in length of stay. Results can easily be stratified and grouped to compare individually defined patient groups. Finally, datasets of identified patients / groups can be downloaded for further analyses.\n\nConclusionRadaR facilitates understanding and communication of trends in antimicrobial use, diagnostic use and patient outcome by linking and aggregating individual patient data in one user-friendly application. RadaR can produce aggregated data analysis while preserving patients features in the data to adjust and stratify results in detail. AMS teams can use RadaR to identify areas, both for diagnostic and therapeutic procedures, within their institutions that might benefit from increased support and to target their interventions.

bioinformatics↗

bioRxiv2018

Multi-Method Characterisation of the Human Circulating Microbiome

The term microbiome describes the genetic material encoding the various microbial populations that inhabit our body. Whilst colonisation of various body niches (e.g. the gut) by dynamic communities of microorganisms is now universally accepted, the existence of microbial populations in other \"classically sterile\" locations, including the blood, is a relatively new concept. The presence of bacteria-specific DNA in the blood has been reported in the literature for some time, yet the true origin of this is still the subject of much deliberation. The aim of this study was to investigate the phenomenon of a \"blood microbiome\" by providing a comprehensive description of bacterially-derived nucleic acids using a range of complementary molecular and classical microbiological techniques. For this purpose we utilised a set of plasma samples from healthy subjects (n = 5) and asthmatic subjects (n = 5). DNA-level analyses involved the amplification and sequencing of the 16S rRNA gene. RNA-level analyses were based upon the de novo assembly of unmapped mRNA reads and subsequent taxonomic identification. Molecular studies were complemented by viability data from classical aerobic and anaerobic microbial culture experiments. At the phylum level, the blood microbiome was predominated by Proteobacteria, Actinobacteria, Firmicutes and Bacteroidetes. The key phyla detected were consistent irrespective of molecular method (DNA vs RNA), and consistent with the results of other published studies. In silico comparison of our data with that of the Human Microbiome Project revealed that members of the blood microbiome were most likely to have originated from the oral or skin communities. To our surprise, aerobic and anaerobic cultures were positive in eight of out the ten donor samples investigated, and we reflect upon their source. Our data provide further evidence of a core blood microbiome, and provide insight into the potential source of the bacterial DNA / RNA detected in the blood. Further, data reveal the importance of robust experimental procedures, and identify areas for future consideration.

molecular biology↗

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

Impact of 10-valent pneumococcal conjugate vaccine on invasive pneumococcal disease and nasopharyngeal carriage in Kenya

Background10-valent pneumococcal conjugate vaccine (PCV10), delivered at 6, 10 and 14 weeks of age, was introduced in Kenya in January 2011, accompanied by a catch-up campaign in Kilifi County for children <5 years. Coverage with [≥]2 PCV10 doses in children 2-11 months was 80% in 2011 and 84% in 2016; coverage with [≥]1 dose in children 12-59 months was 66% and 87%, respectively.\n\nMethodsClinical and microbiological surveillance for invasive pneumococcal disease (IPD) among admissions of all ages at Kilifi County Hospital was linked to the Kilifi Health and Demographic Surveillance System from 1999-2016. We calculated the incidence rate ratio (IRR) comparing the pre-vaccine and post-vaccine eras, adjusted for confounding, and reported percent reduction in IPD as 1-IRR. Annual cross-sectional surveys of nasopharyngeal carriage were conducted from 2009-2016.\n\nFindingsSurveillance identified 667 IPD cases in 3,211,403 person-years of observation. IPD incidence in children <5 years fell sharply in 2011 following PCV10 introduction, and remained low (PCV10-type IPD: 60{middle dot}8 vs 3{middle dot}2/100,000 [92% reduction; 95%CI: 78, 97]; overall IPD: 81{middle dot}6 vs 15{middle dot}3/100,000 [68% reduction; 95%CI: 40, 83]; 1999-2010 vs 2012-2016). PCV10-type IPD also declined significantly in unvaccinated age groups (<2 months, 5-14 years, [≥]15 years), with estimated reductions of 100%, 74%, and 81%, respectively. There was no significant change in the incidence of non-PCV10 type IPD. In children aged <5 years, PCV10-type carriage declined by 74% and non-PCV10-type carriage increased by 71%.\n\nInterpretationIntroduction of PCV10 in Kenya resulted in a substantial reduction in PCV10-type IPD in children and adults without significant replacement disease. These findings suggest that routine infant PCV10 immunization programmes with catch-up campaigns will provide substantial direct and indirect protection in low-income settings in tropical Africa.

epidemiology↗

bioRxiv2018

Resolving the individual contribution of key microbial populations to enhanced biological phosphorus removal with Raman-FISH

Enhanced biological phosphorus removal (EBPR) is a globally important biotechnological process and relies on the massive accumulation of phosphate within special microorganisms. Candidatus Accumulibacter conform to classical physiology model for polyphosphate accumulating organisms and are widely believed to be the most important player for the process in full-scale EBPR systems. However, it was impossible till now to quantify the contribution of specific microbial clades to EBPR. In this study, we have developed a new tool to directly link the identity of microbial cells to the absolute quantification of intracellular poly-P and other polymers under in situ conditions, and applied it to eight full-scale EBPR plants. Besides Ca. Accumulibacter, members of the genus Tetrasphaera were found to be important microbes for P accumulation, and in six plants they were the most important. As these Tetrasphaera cells did not exhibit the classical phenotype of poly-P accumulating microbes, our entire understanding of the microbiology of the EBPR process has to be revised. Furthermore, our new single-cell approach can now also be applied to quantify storage polymer dynamics in individual populations in situ in other ecosystems and might become a valuable tool for many environmental microbiologists.

ecology↗

bioRxiv2018

Easybiotics: a GUI for 3D physical modelling of multi-species bacterial populations

Motivation3D physical modelling is a powerful computational technique which allows for the simulation of complex systems such as consortia of mixed bacterial species. The complexities in physical modelling reside in the knowledge intensive model building process and the computational expense in calculating their numerical solutions. These models can offer insights into microbiology, both in understanding natural systems and as design tools for developing novel synthetic bacteria. Developing a robust synthetic system typically requires multiple iterations around the specify->design->build->test cycle to meet specifications. This process is laborious and expensive for both the computational and laboratory aspects, hence any improvement in any of the workflow steps would be welcomed. We have previously introduced Simbiotics (Naylor, 2017) a powerful and flexible platform for designing and analysing three-dimensional simulations of mixed species bacterial populations. Simbiotics requires programming experience to use which creates barriers to entry for use of the tool.\n\nResultsIn the spirit of enabling biologists who may not have programming skills to install and utilise Simbiotics, we present in this application note Easybiotics, a user-friendly graphical user interface for Simbiotics. Users may design, simulate and analyse models from within the GUI, with features such as live graph plotting and parameter sweeps. Easybiotics provides full access to all of Simbiotics simulation features, such as cell growth, motility and gene regulation.\n\nAvailabilityEasybiotics and Simbiotics are free to use under the GPL3.0 license, and can be found at: https://bitbucket.org/simbiotics/simbiotics/wiki/Home\n\nContactnatalio.krasnogor@newcastle.ac.uk

bioinformatics↗

bioRxiv2018

Trimitomics: An efficient pipeline for mitochondrial assembly from transcriptomic reads in non-model species

Mitochondrial resources are of known utility to many fields of phylogenetic, population and molecular biology. Their combination of faster and slower-evolving regions and high copy number enables them to be used in many situations where other loci are unsuitable, with degraded samples and after recent speciation events.\n\nThe advent of next-generation sequencing technologies (and notably the Illumina platform) has led to an explosion in the number of samples that can be studied at transcriptomic level, at relatively low cost. Here we describe a robust pipeline for the recovery of mitochondrial genomes from these RNA-seq resources. This pipeline can be used on sequencing of a variety of depths, and reliably recovers the protein coding and ribosomal gene complements of mitochondria from almost any transcriptomic sequencing experiment. The complete sequence of the mitochondrial genome can also be recovered when sequencing is performed in sufficient depth. We evidence the efficacy of our pipeline using data from a number of non-model invertebrates of four disparate phyla, namely Porifera, Nemertea, Mollusca and Annelida. Interestingly, among our poriferan data, where microbiological symbionts are known empirically to make mitochondrial assembly difficult, this pipeline proved especially useful.\n\nOur pipeline will allow the recovery of mitochondrial data from a variety of previously-sequenced samples, and add an additional angle of enquiry to future RNA-seq efforts, simplifying the process of mitochondrial genome assembly for even the most recalcitrant clades and adding this data to the scientific record for a range of future uses.

genomics↗

bioRxiv2018

Limited marginal utility of deep sequencing for HIV drug resistance testing in the age of integrase inhibitors

HIV drug resistance genotyping is a critical tool in the clinical management of HIV infections. Although resistance genotyping has traditionally been conducted using Sanger sequencing, next-generation sequencing (NGS) is emerging as a powerful tool due to its ability to detect lower frequency alleles. However, the value added from NGS approaches to antiviral resistance testing remains to be demonstrated. We compared the variant detection capacity of NGS versus Sanger sequencing methods for resistance genotyping of 144 drug resistance tests (105 protease-reverse transcriptase tests and 39 integrase tests) submitted to our clinical virology laboratory over a four-month period in 2016 for Sanger-based HIV drug resistance testing. NGS detected all true high frequency drug resistance mutations (>20% frequency) found by Sanger sequencing, with greater accuracy in one instance of a Sanger-detected false positive. Freely available online NGS variant callers Hydra and PASeq were superior to Sanger methods for interpretations of allele linkage and automated variant calling. NGS additionally detected low frequency mutations (1-20% frequency) associated with higher levels of drug resistance in 30/105 (29%) of protease-reverse transcriptase tests and 4/39 (10%) of integrase tests. Clinical follow-up of 69 individuals for a median of 674 days found no difference in rates of virological failure between individuals with and without low frequency mutations, although rates of virological failure were higher for individuals with drug-relevant low frequency mutations. However, all 27 individuals who experienced virological failure reported poor adherence to their drug regimen during preceding follow-up time, and all 19 who subsequently improved their adherence achieved viral suppression at later time points consistent with a lack of clinical resistance. In conclusion, in a population with low antiviral resistance emergence, NGS methods detected numerous instances of minor alleles that did not result in subsequent bona fide virological failure due to antiviral resistance.\n\nImportanceGenotypic antiviral resistance testing for HIV is an essential component of the clinical microbiology and virology laboratory. Next-generation sequencing (NGS) has emerged as a powerful tool for the detection of low frequency sequence variants (allele frequencies <20%). Whether detecting these low frequency mutations in HIV contributes to improved patient health, however, remains unclear. We compared NGS to conventional Sanger sequencing for detecting resistance mutations for 144 HIV drug resistance tests submitted to our clinical virology laboratory and detected low frequency mutations in 24% of tests. Over approximately two years of follow-up for 69 patients for which we had access to electronic health records, no patients had virological failure due to antiviral resistance. Instead, virological failure was entirely explained by medication non-adherence. While larger studies are required, we suggest that detection of low frequency variants by NGS presents limited marginal clinical utility when compared to standard of care.

epidemiology↗

bioRxiv2018

The Swiss Primary Ciliary Dyskinesia registry: objectives, methods and first results

Primary Ciliary Dyskinesia (PCD) is a rare hereditary, multi-organ disease caused by defects in ciliary structure and function. It results in a wide range of clinical manifestations, most commonly in the upper and lower airways. Central data collection in national and international registries is essential to studying the epidemiology of rare diseases and filling in gaps in knowledge of diseases such as PCD. For this reason, the Swiss Primary Ciliary Dyskinesia Registry (CH-PCD) was founded in 2013 as a collaborative project between epidemiologists and adult and paediatric pulmonologists.\n\nThe registry records patients of any age, suffering from PCD, who are treated and resident in Switzerland. It collects information from patients identified through physicians, diagnostic facilities, and patient organisations. The registry dataset contains data on diagnostic evaluations, lung function, microbiology and imaging, symptoms, treatments, and hospitalizations.\n\nBy May 2018, CH-PCD has contacted 566 physicians of different specialties and identified 134 patients with PCD. At present this number represents an overall 1 in 63,000 prevalence of people diagnosed with PCD in Switzerland. Prevalence differs by age and region; it is highest in children and adults younger than 30 years, and in Espace Mittelland. The median age of patients in the registry is 25 years (range 5-73), and 49 patients have a definite PCD diagnosis based on recent international guidelines. Data from CH-PCD are contributed to international collaborative studies and the registry facilitates patient identification for nested studies.\n\nCH-PCD has proven to be a valuable research tool that already has highlighted weaknesses in PCD clinical practice in Switzerland. Development of centralised diagnostic and management centres and adherence to international guidelines are needed to improve diagnosis and management--particularly for adult PCD patients.

epidemiology↗

bioRxiv2015

Nested Russian Doll-like Genetic Mobility Drives Rapid Dissemination of the Carbapenem Resistance Gene blaKPC

The recent widespread emergence of carbapenem resistance in Enterobacteriaceae is a major public health concern, as carbapenems are a therapy of last resort in this family of common bacterial pathogens. Resistance genes can mobilize via various mechanisms including conjugation and transposition, however the importance of this mobility in short-term evolution, such as within nosocomial outbreaks, is currently unknown. Using a combination of short- and long-read whole genome sequencing of 281 blaKPC-positive Enterobacteriaceae isolated from a single hospital over five years, we demonstrate rapid dissemination of this carbapenem resistance gene to multiple species, strains, and plasmids. Mobility of blaKPC occurs at multiple nested genetic levels, with transmission of blaKPC strains between individuals, frequent transfer of blaKPC plasmids between strains/species, and frequent transposition of the blaKPC transposon Tn4401 between plasmids. We also identify a common insertion site for Tn4401 within various Tn2-like elements, suggesting that homologous recombination between Tn2-like elements has enhanced the spread of Tn4401 between different plasmid vectors. Furthermore, while short-read sequencing has known limitations for plasmid assembly, various studies have attempted to overcome this with the use of reference-based methods. We also demonstrate that as a consequence of the genetic mobility observed herein, plasmid structures can be extremely dynamic, and therefore these reference-based methods, as well as traditional partial typing methods, can produce very misleading conclusions. Overall, our findings demonstrate that non-clonal resistance gene dissemination can be extremely rapid, presenting significant challenges for public health surveillance and achieving effective control of antibiotic resistance.\n\nImportanceIncreasing antibiotic resistance is a major threat to human health, as highlighted by the recent emergence of multi-drug resistant \"superbugs\". Here, we tracked how one important multi-drug resistance gene spread in a single hospital over five years. This revealed high levels of resistance gene mobility to multiple bacterial species, which was facilitated by various different genetic mechanisms. The mobility occurred at multiple nested genetic levels, analogous to a Russian doll set where smaller dolls may be carried along inside larger dolls. Our results challenge traditional views that drug-resistance outbreaks are due to transmission of a single pathogenic strain. Instead, outbreaks can be \"gene-based\", and we must therefore focus on tracking specific resistance genes and their context rather than only specific bacteria.

Microbiology↗

bioRxiv2017

Genomic epidemiology of global Klebsiella pneumoniae carbapenemase (KPC)-producing E. coli

The dissemination of carbapenem resistance in Escherichia coli has major implications for the management of common human infections. blaKPC, encoding a transmissible carbapenemase (KPC), has historically largely been associated with Klebsiella pneumoniae, a predominant plasmid (pKpQIL), and a specific transposable element (Tn4401, ~10kb). Here we characterize the genetic features of the emergence of blaKPC in global E. coli, 2008-2013, using both long-and short-read whole genome sequencing.\n\nAmongst 43/45 successfully sequenced blaKPC-E. coli strains, we identified high strain (n=21 sequence types, 18% of annotated genes in the core genome); plasmid ([≥]9 replicon types); and blaKPC-associated, mobile genetic element (MGE) diversity (50% not within complete Tn4401 elements). We also found evidence of interspecies, regional and international plasmid spread. In several cases blaKPC was found on high copy number, small Col-like plasmids, previously associated with horizontal transmission of resistance genes in the absence of antimicrobial selection pressures.\n\nE. coli is a common human pathogen, but also a commensal in a multiple environmental and animal reservoirs, and easily transmissible. The association of blaKPC with a range of MGEs previously linked to the successful spread of widely endemic resistance mechanisms (e.g. blaTEM, blaCTX-M) suggests that it is likely to become similarly prevalent.

microbiology↗

bioRxiv2013

Virulence in a Pseudomonas syringae Strain with a Small Repertoire of Predicted Effectors

Both type III effector proteins and non-ribosomal peptide toxins play important roles for Pseudomonas syringae pathogenicity in host plants, but whether and how these virulence pathways interact to promote infection remains unclear. Genomic evidence from one clade of P. syringae suggests a tradeoff between the total number of type III effector proteins and presence of syringomycin, syringopeptin, and syringolin A toxins. Here we report the complete genome sequence from P. syringae CC1557, which contains the lowest number of known type III effectors to date and has also acquired genes similar to sequences encoding syringomycin pathways from other strains. We demonstrate that this strain is pathogenic on Nicotiana benthamiana and that both the type III secretion system and a new type III effector family, hopBJ1, contribute to virulence. We further demonstrate that virulence activity of HopBJ1 is dependent on similar catalytic sites as the E. coli CNF1 toxin. Taken together, our results provide additional support for a negative correlation between type III effector repertoires and the potential to produce syringomycin-like toxins while also highlighting how genomic synteny and bioinformatics can be used to identify and characterize novel virulence proteins.

Microbiology↗

bioRxiv2013

High Genetic Diversity and Adaptive Potential of Two Simian Hemorrhagic Fever Viruses in a Wild Primate Population

Key biological properties such as high genetic diversity and high evolutionary rate enhance the potential of certain RNA viruses to adapt and emerge. Identifying viruses with these properties in their natural hosts could dramatically improve disease forecasting and surveillance. Recently, we discovered two novel members of the viral family Arteriviridae: simian hemorrhagic fever virus (SHFV)-krc1 and SHFV-krc2, infecting a single wild red colobus (Procolobus rufomitratus tephrosceles) in Kibale National Park, Uganda. Nearly nothing is known about the biological properties of SHFVs in nature, although the SHFV type strain, SHFV-LVR, has caused devastating outbreaks of viral hemorrhagic fever in captive macaques. Here we detected SHFV-krc1 and SHFV-krc2 in 40% and 47% of 60 wild red colobus tested, respectively. We found viral loads in excess of 106 - 107 RNA copies per milliliter of blood plasma for each of these viruses. SHFV-krc1 and SHFV-krc2 also showed high genetic diversity at both the inter- and intra-host levels. Analyses of synonymous and non-synonymous nucleotide diversity across viral genomes revealed patterns suggestive of positive selection in SHFV open reading frames (ORF) 5 (SHFV-krc2 only) and 7 (SHFV-krc1 and SHFV-krc2). Thus, these viruses share several important properties with some of the most rapidly evolving, emergent RNA viruses.

Microbiology↗

bioRxiv2013

Extensive Phenotypic Changes Associated with Large-scale Horizontal Gene Transfer

Horizontal gene transfer often leads to phenotypic changes within recipient organisms independent of any immediate evolutionary benefits. While secondary phenotypic effects of horizontal transfer (i.e. changes in growth rates) have been demonstrated and studied across a variety of systems using relatively small plasmid and phage, little is known about how size of the acquired region affects the magnitude or number of such costs. Here we describe an amazing breadth of phenotypic changes which occur after a large-scale horizontal transfer event (~1Mb megaplasmid) within Pseudomonas stutzeri including sensitization to various stresses as well as changes in bacterial behavior. These results highlight the power of horizontal transfer to shift pleiotropic relationships and cellular networks within bacterial genomes. They also provide an important context for how secondary effects of transfer can bias evolutionary trajectories and interactions between species. Lastly, these results and system provide a foundation to investigate evolutionary consequences in real time as newly acquired regions are ameliorated and integrated into new genomic contexts.

Microbiology↗

bioRxiv2014

Modelling and analysis of bacterial tracks suggest an active reorientation mechanism in Rhodobacter sphaeroides

Most free-swimming bacteria move in approximately straight lines, interspersed with random reorientation phases. A key open question concerns varying mechanisms by which reorientation occurs. We combine mathematical modelling with analysis of a large tracking dataset to study the poorly-understood reorientation mechanism in the monoflagellate species Rhodobacter sphaeroides. The flagellum on this species rotates counterclockwise to propel the bacterium, periodically ceasing rotation to enable reorientation. When rotation restarts the cell body usually points in a new direction. It has been assumed that the new direction is simply the result of Brownian rotation. We consider three variants of a self-propelled particle model of bacterial motility. The first considers rotational diffusion only, corresponding to a non-chemotactic mutant strain. A further two models also include stochastic reorientations, describing run-and-tumble motility. We derive expressions for key summary statistics and simulate each model using a stochastic computational algorithm. We also discuss the effect of cell geometry on rotational diffusion. Working with a previously published tracking dataset, we compare predictions of the models with data on individual stopping events in R. sphaeroides. This provides strong evidence that this species undergoes some form of active reorientation rather than simple reorientation by Brownian rotation.

Microbiology↗

bioRxiv2014

Metabolic composition of anode community predicts electrical power in microbial fuel cells

Microbial Fuel Cells (MFCs) are a promising technology for organic waste treatment and sustainable bioelectricity production. Inoculated with natural communities, they present a complex microbial ecosystem with syntrophic interactions between microbes with different metabolic capabilities. From this point of view, they are similar to anaerobic digesters, however with methanogenesis replaced by anaerobic respiration with the anode as terminal electron acceptor. Bio-electrochemically they are similar to classical fuel cells where however the electrogenic redox reaction is part of the microbial metabolism rather than mediated by an inorganic catalyst.\n\nIn this paper, we analyse how electric power production in MFCs depends on the composition of the anodic biofilm in terms of metabolic capabilities of identified sets of species. MFCs were started with a natural inoculum and continuously fed with sucrose, a fermentable carbohydrate. The composition of the community, power and other environmental data were sampled over a period of a few weeks during the maturation of the anodic biofilm, and the community composition was determined down to the species level including relevant metabolic capabilities.\n\nOur results support the hypothesis that an MFCs with natural inoculum and fermentable feedstock is essentially a two stage system with fermentation followed by anode-respiration. Our results also show that under identical starting and operating conditions, MFCs with comparable power output can develop different anodic communities with no particular species dominant across all replicas. It is only important for good power production that all cells contain a sufficient fraction of low-potential anaerobic respirators, that is respirators that can use terminal electron acceptors with a low redox potential. We conclude with a number of hypotheses and recommendations for the operation of MFCs to ensure good electric yield.

Microbiology↗

bioRxiv2014

High Bacterial Load Predicts Poor Outcomes in Patients with Idiopathic Pulmonary Fibrosis

BackgroundRepetitive alveolar damage and aberrant repair may be important in the development of the fatal condition Idiopathic Pulmonary Fibrosis (IPF). The role played by microorganisms in this cycle is unknown.\n\nMethodsWe consecutively enrolled patients diagnosed with IPF according to international criteria together with healthy smokers, non-smokers and subjects with moderate Chronic Obstructive Pulmonary Disease (COPD) as controls. Subjects underwent bronchoalveolar lavage (BAL) from which genomic DNA was isolated. The V3-V5 region of the bacterial 16S rRNA gene was amplified, allowing quantification of bacterial load and identification of communities by 16S rRNA qPCR and pyrosequencing.\n\nResultsOur 65 IPF patients had 3.9x109 copies of the 16S rRNA gene per ml of BAL, two-fold more than the 1.8x109 copies in 44 sex- and smoking-matched controls (P<0.0001). Baseline BAL bacterial burden predicted Forced Vital Capacity (FVC) decline (P=0.02). Patients in the highest tertile of bacterial burden were at a higher risk of mortality compared to subjects in the lowest tertile (hazard ratio 4.59 (95% CI, 1.05-20); P=0.04).\n\nSequencing yielded 912,883 high quality reads from all subjects. Operational Taxonomic Units (OTUs) representing Haemophilus, Streptococcus, Neisseria and Veillonella were 1.5 to 3.5 fold more abundant in cases than controls (P<0.05). Regression analyses indicated that these specific OTUs as well as bacterial burden associated independently with IPF.\n\nConclusionsIPF is characterised by an increased bacterial burden in BAL that predicts decline in lung function and death. Clinical trials of antimicrobial therapy may determine if microbial burden is causal or not in IPF progression.

Microbiology↗