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Volume 5,
Issue 4,
2019
Volume 5, Issue 4, 2019
- Editorial
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- Research Article
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- Microbial Evolution and Epidemiology
- Mechanisms of Evolution
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Rapid phenotypic evolution in multidrug-resistant Klebsiella pneumoniae hospital outbreak strains
Carbapenem-resistant Klebsiella pneumoniae (CRKP) increasingly cause high-mortality outbreaks in hospital settings globally. Following a patient fatality at a hospital in Beijing due to a bla KPC-2-positive CRKP infection, close monitoring was put in place over the course of 14 months to characterize all bla KPC-2-positive CRKP in circulation in the hospital. Whole genome sequences were generated for 100 isolates from bla KPC-2-positive isolates from infected patients, carriers and the hospital environment. Phylogenetic analyses identified a closely related cluster of 82 sequence type 11 (ST11) isolates circulating in the hospital for at least a year prior to admission of the index patient. The majority of inferred transmissions for these isolates involved patients in intensive care units. Whilst the 82 ST11 isolates collected during the surveillance effort all had closely related chromosomes, we observed extensive diversity in their antimicrobial resistance (AMR) phenotypes. We were able to reconstruct the major genomic changes underpinning this variation in AMR profiles, including multiple gains and losses of entire plasmids and recombination events between plasmids, including transposition of bla KPC-2. We also identified specific cases where variation in plasmid copy number correlated with the level of phenotypic resistance to drugs, suggesting that the number of resistance elements carried by a strain may play a role in determining the level of AMR. Our findings highlight the epidemiological value of whole genome sequencing for investigating multi-drug-resistant hospital infections and illustrate that standard typing schemes cannot capture the extraordinarily fast genome evolution of CRKP isolates.
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- Population Genomics
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PANINI: Pangenome Neighbour Identification for Bacterial Populations
The standard workhorse for genomic analysis of the evolution of bacterial populations is phylogenetic modelling of mutations in the core genome. However, a notable amount of information about evolutionary and transmission processes in diverse populations can be lost unless the accessory genome is also taken into consideration. Here, we introduce panini (Pangenome Neighbour Identification for Bacterial Populations), a computationally scalable method for identifying the neighbours for each isolate in a data set using unsupervised machine learning with stochastic neighbour embedding based on the t-SNE (t-distributed stochastic neighbour embedding) algorithm. panini is browser-based and integrates with the Microreact platform for rapid online visualization and exploration of both core and accessory genome evolutionary signals, together with relevant epidemiological, geographical, temporal and other metadata. Several case studies with single- and multi-clone pneumococcal populations are presented to demonstrate the ability to identify biologically important signals from gene content data. panini is available at http://panini.pathogen.watch and code at http://gitlab.com/cgps/panini.
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- Microbe-Niche Interactions
- Mutualism, Commensalism and Parasitism
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Sucrose 6F-phosphate phosphorylase: a novel insight in the human gut microbiome
The human gut microbiome plays an essential role in maintaining human health including in degradation of dietary fibres and carbohydrates further used as nutrients by both the host and the gut bacteria. Previously, we identified a polysaccharide utilization loci (PUL) involved in sucrose and raffinose family oligosaccharide (RFO) metabolism from one of the most common Firmicutes present in individuals, Ruminococcus gnavus E1. One of the enzymes encoded by this PUL was annotated as a putative sucrose phosphate phosphorylase (RgSPP). In the present study, we have in-depth characterized the heterologously expressed RgSPP as sucrose 6F-phosphate phosphorylase (SPP), expanding our knowledge of the glycoside hydrolase GH13_18 subfamily. Specifically, the enzymatic characterization showed a selective activity on sucrose 6F-phosphate (S6FP) acting both in phosphorolysis releasing alpha-d-glucose-1-phosphate (G1P) and alpha-d-fructose-6-phosphate (F6P), and in reverse phosphorolysis from G1P and F6P to S6FP. Interestingly, such a SPP activity had never been observed in gut bacteria before. In addition, a phylogenetic and synteny analysis showed a clustering and a strictly conserved PUL organization specific to gut bacteria. However, a wide prevalence and abundance study with a human metagenomic library showed a correlation between SPP activity and the geographical origin of the individuals and, thus, most likely linked to diet. Rgspp gene overexpression has been observed in mice fed with a high-fat diet suggesting, as observed for humans, that intestine lipid and carbohydrate microbial metabolisms are intertwined. Finally, based on the genomic environment analysis, in vitro and in vivo studies, results provide new insights into the gut microbiota catabolism of sucrose, RFOs and S6FP.
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- Host Adaptation
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Genomic and transcriptomic characterization of Pseudomonas aeruginosa small colony variants derived from a chronic infection model
Phenotypic change is a hallmark of bacterial adaptation during chronic infection. In the case of chronic Pseudomonas aeruginosa lung infection in patients with cystic fibrosis, well-characterized phenotypic variants include mucoid and small colony variants (SCVs). It has previously been shown that SCVs can be reproducibly isolated from the murine lung following the establishment of chronic infection with mucoid P. aeruginosa strain NH57388A. Using a combination of single-molecule real-time (PacBio) and Illumina sequencing we identify a large genomic inversion in the SCV through recombination between homologous regions of two rRNA operons and an associated truncation of one of the 16S rRNA genes and suggest this may be the genetic switch for conversion to the SCV phenotype. This phenotypic conversion is associated with large-scale transcriptional changes distributed throughout the genome. This global rewiring of the cellular transcriptomic output results in changes to normally differentially regulated genes that modulate resistance to oxidative stress, central metabolism and virulence. These changes are of clinical relevance because the appearance of SCVs during chronic infection is associated with declining lung function.
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- Method
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- Genomic Methodologies
- Data Clustering Methods
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rPinecone: Define sub-lineages of a clonal expansion via a phylogenetic tree
The ability to distinguish different circulating pathogen clones from each other is a fundamental requirement to understand the epidemiology of infectious diseases. Phylogenetic analysis of genomic data can provide a powerful platform to identify lineages within bacterial populations, and thus inform outbreak investigation and transmission dynamics. However, resolving differences between pathogens associated with low-variant (LV) populations carrying low median pairwise single nucleotide variant (SNV) distances remains a major challenge. Here we present rPinecone, an R package designed to define sub-lineages within closely related LV populations. rPinecone uses a root-to-tip directional approach to define sub-lineages within a phylogenetic tree according to SNV distance from the ancestral node. The utility of this software was demonstrated using both simulated outbreaks and real genomic data of two LV populations: a hospital outbreak of methicillin-resistant Staphylococcus aureus and endemic Salmonella Typhi from rural Cambodia. rPinecone identified the transmission branches of the hospital outbreak and geographically confined lineages in Cambodia. Sub-lineages identified by rPinecone in both analyses were phylogenetically robust. It is anticipated that rPinecone can be used to discriminate between lineages of bacteria from LV populations where other methods fail, enabling a deeper understanding of infectious disease epidemiology for public health purposes.
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