Adam Jenney

Bio: Adam Jenney is an academic researcher from Monash University. The author has contributed to research in topics: Population & Medicine. The author has an hindex of 31, co-authored 92 publications receiving 3832 citations. Previous affiliations of Adam Jenney include Alfred Hospital & Fiji National University.

Genomic analysis of diversity, population structure, virulence, and antimicrobial resistance in Klebsiella pneumoniae, an urgent threat to public health

Abstract: Klebsiella pneumoniae is now recognized as an urgent threat to human health because of the emergence of multidrug-resistant strains associated with hospital outbreaks and hypervirulent strains associated with severe community-acquired infections. K. pneumoniae is ubiquitous in the environment and can colonize and infect both plants and animals. However, little is known about the population structure of K. pneumoniae, so it is difficult to recognize or understand the emergence of clinically important clones within this highly genetically diverse species. Here we present a detailed genomic framework for K. pneumoniae based on whole-genome sequencing of more than 300 human and animal isolates spanning four continents. Our data provide genome-wide support for the splitting of K. pneumoniae into three distinct species, KpI (K. pneumoniae), KpII (K. quasipneumoniae), and KpIII (K. variicola). Further, for K. pneumoniae (KpI), the entity most frequently associated with human infection, we show the existence of >150 deeply branching lineages including numerous multidrug-resistant or hypervirulent clones. We show K. pneumoniae has a large accessory genome approaching 30,000 protein-coding genes, including a number of virulence functions that are significantly associated with invasive community-acquired disease in humans. In our dataset, antimicrobial resistance genes were common among human carriage isolates and hospital-acquired infections, which generally lacked the genes associated with invasive disease. The convergence of virulence and resistance genes potentially could lead to the emergence of untreatable invasive K. pneumoniae infections; our data provide the whole-genome framework against which to track the emergence of such threats.

Identification of Klebsiella capsule synthesis loci from whole genome data.

Abstract: Klebsiella pneumoniae is a growing cause of healthcare-associated infections for which multi-drug resistance is a concern. Its polysaccharide capsule is a major virulence determinant and epidemiological marker. However, little is known about capsule epidemiology since serological typing is not widely accessible and many isolates are serologically non-typeable. Molecular typing techniques provide useful insights, but existing methods fail to take full advantage of the information in whole genome sequences. We investigated the diversity of the capsule synthesis loci (K-loci) among 2503 K. pneumoniae genomes. We incorporated analyses of full-length K-locus nucleotide sequences and also clustered protein-encoding sequences to identify, annotate and compare K-locus structures. We propose a standardized nomenclature for K-loci and present a curated reference database. A total of 134 distinct K-loci were identified, including 31 novel types. Comparative analyses indicated 508 unique protein-encoding gene clusters that appear to reassort via homologous recombination. Extensive intra- and inter-locus nucleotide diversity was detected among the wzi and wzc genes, indicating that current molecular typing schemes based on these genes are inadequate. As a solution, we introduce Kaptive, a novel software tool that automates the process of identifying K-loci based on full locus information extracted from whole genome sequences (https://github.com/katholt/Kaptive). This work highlights the extensive diversity of Klebsiella K-loci and the proteins that they encode. The nomenclature, reference database and novel typing method presented here will become essential resources for genomic surveillance and epidemiological investigations of this pathogen.

Gastrointestinal Carriage Is a Major Reservoir of Klebsiella pneumoniae Infection in Intensive Care Patients.

Abstract: Background: Klebsiella pneumoniae is an opportunistic pathogen and leading cause of hospital-associated infections. Intensive care unit (ICU) patients are particularly at risk. Klebsiella pneumoniae is part of the healthy human microbiome, providing a potential reservoir for infection. However, the frequency of gut colonization and its contribution to infections are not well characterized. Methods: We conducted a 1-year prospective cohort study in which 498 ICU patients were screened for rectal and throat carriage of K. pneumoniae shortly after admission. Klebsiella pneumoniae isolated from screening swabs and clinical diagnostic samples were characterized using whole genome sequencing and combined with epidemiological data to identify likely transmission events. Results: Klebsiella pneumoniae carriage frequencies were estimated at 6% (95% confidence interval [CI], 3%-8%) among ICU patients admitted direct from the community, and 19% (95% CI, 14%-51%) among those with recent healthcare contact. Gut colonization on admission was significantly associated with subsequent infection (infection risk 16% vs 3%, odds ratio [OR] = 6.9, P < .001), and genome data indicated matching carriage and infection isolates in 80% of isolate pairs. Five likely transmission chains were identified, responsible for 12% of K. pneumoniae infections in ICU. In sum, 49% of K. pneumoniae infections were caused by the patients' own unique strain, and 48% of screened patients with infections were positive for prior colonization. Conclusions: These data confirm K. pneumoniae colonization is a significant risk factor for infection in ICU, and indicate ~50% of K. pneumoniae infections result from patients' own microbiota. Screening for colonization on admission could limit risk of infection in the colonized patient and others.

MrkH, a Novel c-di-GMP-Dependent Transcriptional Activator, Controls Klebsiella pneumoniae Biofilm Formation by Regulating Type 3 Fimbriae Expression

Abstract: Klebsiella pneumoniae causes significant morbidity and mortality worldwide, particularly amongst hospitalized individuals. The principle mechanism for pathogenesis in hospital environments involves the formation of biofilms, primarily on implanted medical devices. In this study, we constructed a transposon mutant library in a clinical isolate, K. pneumoniae AJ218, to identify the genes and pathways implicated in biofilm formation. Three mutants severely defective in biofilm formation contained insertions within the mrkABCDF genes encoding the main structural subunit and assembly machinery for type 3 fimbriae. Two other mutants carried insertions within the yfiN and mrkJ genes, which encode GGDEF domain- and EAL domain-containing c-di-GMP turnover enzymes, respectively. The remaining two isolates contained insertions that inactivated the mrkH and mrkI genes, which encode for novel proteins with a c-di-GMP-binding PilZ domain and a LuxR-type transcriptional regulator, respectively. Biochemical and functional assays indicated that the effects of these factors on biofilm formation accompany concomitant changes in type 3 fimbriae expression. We mapped the transcriptional start site of mrkA, demonstrated that MrkH directly activates transcription of the mrkA promoter and showed that MrkH binds strongly to the mrkA regulatory region only in the presence of c-di-GMP. Furthermore, a point mutation in the putative c-di-GMP-binding domain of MrkH completely abolished its function as a transcriptional activator. In vivo analysis of the yfiN and mrkJ genes strongly indicated their c-di-GMP-specific function as diguanylate cyclase and phosphodiesterase, respectively. In addition, in vitro assays showed that purified MrkJ protein has strong c-di-GMP phosphodiesterase activity. These results demonstrate for the first time that c-di-GMP can function as an effector to stimulate the activity of a transcriptional activator, and explain how type 3 fimbriae expression is coordinated with other gene expression programs in K. pneumoniae to promote biofilm formation to implanted medical devices.

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

Clinical Practice Guidelines by the Infectious Diseases Society of America for the Treatment of Methicillin-Resistant Staphylococcus aureus Infections in Adults and Children

Abstract: Evidence-based guidelines for the management of patients with methicillin-resistant Staphylococcus aureus (MRSA) infections were prepared by an Expert Panel of the Infectious Diseases Society of America (IDSA). The guidelines are intended for use by health care providers who care for adult and pediatric patients with MRSA infections. The guidelines discuss the management of a variety of clinical syndromes associated with MRSA disease, including skin and soft tissue infections (SSTI), bacteremia and endocarditis, pneumonia, bone and joint infections, and central nervous system (CNS) infections. Recommendations are provided regarding vancomycin dosing and monitoring, management of infections due to MRSA strains with reduced susceptibility to vancomycin, and vancomycin treatment failures.

Staphylococcus aureus Infections: Epidemiology, Pathophysiology, Clinical Manifestations, and Management

Abstract: Staphylococcus aureus is a major human pathogen that causes a wide range of clinical infections. It is a leading cause of bacteremia and infective endocarditis as well as osteoarticular, skin and soft tissue, pleuropulmonary, and device-related infections. This review comprehensively covers the epidemiology, pathophysiology, clinical manifestations, and management of each of these clinical entities. The past 2 decades have witnessed two clear shifts in the epidemiology of S. aureus infections: first, a growing number of health care-associated infections, particularly seen in infective endocarditis and prosthetic device infections, and second, an epidemic of community-associated skin and soft tissue infections driven by strains with certain virulence factors and resistance to β-lactam antibiotics. In reviewing the literature to support management strategies for these clinical manifestations, we also highlight the paucity of high-quality evidence for many key clinical questions.

Fast Tree: Computing Large Minimum-Evolution Trees with Profiles instead of a Distance Matrix

Abstract: Gene families are growing rapidly, but standard methods for inferring phylogenies do not scale to alignments with over 10,000 sequences. We present FastTree, a method for constructing large phylogenies and for estimating their reliability. Instead of storing a distance matrix, FastTree stores sequence profiles of internal nodes in the tree. FastTree uses these profiles to implement neighbor-joining and uses heuristics to quickly identify candidate joins. FastTree then uses nearest-neighbor interchanges to reduce the length of the tree. For an alignment with N sequences, L sites, and a different characters, a distance matrix requires O(N^2) space and O(N^2 L) time, but FastTree requires just O( NLa + N sqrt(N) ) memory and O( N sqrt(N) log(N) L a ) time. To estimate the tree's reliability, FastTree uses local bootstrapping, which gives another 100-fold speedup over a distance matrix. For example, FastTree computed a tree and support values for 158,022 distinct 16S ribosomal RNAs in 17 hours and 2.4 gigabytes of memory. Just computing pairwise Jukes-Cantor distances and storing them, without inferring a tree or bootstrapping, would require 17 hours and 50 gigabytes of memory. In simulations, FastTree was slightly more accurate than neighbor joining, BIONJ, or FastME; on genuine alignments, FastTree's topologies had higher likelihoods. FastTree is available at http://microbesonline.org/fasttree.