Biochemistry and Pharmacology - Research Publications

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    Trajectories of childhood immune development and respiratory health relevant to asthma and allergy.
    Tang, HH ; Teo, SM ; Belgrave, DC ; Evans, MD ; Jackson, DJ ; Brozynska, M ; Kusel, MM ; Johnston, SL ; Gern, JE ; Lemanske, RF ; Simpson, A ; Custovic, A ; Sly, PD ; Holt, PG ; Holt, KE ; Inouye, M (eLife Sciences Publications, Ltd, 2018-10-15)
    Events in early life contribute to subsequent risk of asthma; however, the causes and trajectories of childhood wheeze are heterogeneous and do not always result in asthma. Similarly, not all atopic individuals develop wheeze, and vice versa. The reasons for these differences are unclear. Using unsupervised model-based cluster analysis, we identified latent clusters within a prospective birth cohort with deep immunological and respiratory phenotyping. We characterised each cluster in terms of immunological profile and disease risk, and replicated our results in external cohorts from the UK and USA. We discovered three distinct trajectories, one of which is a high-risk 'atopic' cluster with increased propensity for allergic diseases throughout childhood. Atopy contributes varyingly to later wheeze depending on cluster membership. Our findings demonstrate the utility of unsupervised analysis in elucidating heterogeneity in asthma pathogenesis and provide a foundation for improving management and prevention of childhood asthma.
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    FastSpar: rapid and scalable correlation estimation for compositional data
    Watts, SC ; Ritchie, SC ; Inouye, M ; Holt, KE ; Stegle, O (OXFORD UNIV PRESS, 2019-03-15)
    A common goal of microbiome studies is the elucidation of community composition and member interactions using counts of taxonomic units extracted from sequence data. Inference of interaction networks from sparse and compositional data requires specialized statistical approaches. A popular solution is SparCC, however its performance limits the calculation of interaction networks for very high-dimensional datasets. Here we introduce FastSpar, an efficient and parallelizable implementation of the SparCC algorithm which rapidly infers correlation networks and calculates P-values using an unbiased estimator. We further demonstrate that FastSpar reduces network inference wall time by 2–3 orders of magnitude compared to SparCC.
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    Airway Microbiota Dynamics Uncover a Critical Window for Interplay of Pathogenic Bacteria and Allergy in Childhood Respiratory Disease
    Teo, SM ; Tang, HHF ; Mok, D ; Judd, LM ; Watts, SC ; Pham, K ; Holt, BJ ; Kusel, M ; Serralha, M ; Troy, N ; Bochkov, YA ; Grindle, K ; Lemanske, RF ; Johnston, SL ; Gern, JE ; Sly, PD ; Holt, PG ; Holt, KE ; Inouye, M (CELL PRESS, 2018-09-12)
    Repeated cycles of infection-associated lower airway inflammation drive the pathogenesis of persistent wheezing disease in children. In this study, the occurrence of acute respiratory tract illnesses (ARIs) and the nasopharyngeal microbiome (NPM) were characterized in 244 infants through their first five years of life. Through this analysis, we demonstrate that >80% of infectious events involve viral pathogens, but are accompanied by a shift in the NPM toward dominance by a small range of pathogenic bacterial genera. Unexpectedly, this change frequently precedes the detection of viral pathogens and acute symptoms. Colonization of illness-associated bacteria coupled with early allergic sensitization is associated with persistent wheeze in school-aged children, which is the hallmark of the asthma phenotype. In contrast, these bacterial genera are associated with "transient wheeze" that resolves after age 3 years in non-sensitized children. Thus, to complement early allergic sensitization, monitoring NPM composition may enable early detection and intervention in high-risk children.
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    The Infant Nasopharyngeal Microbiome Impacts Severity of Lower Respiratory Infection and Risk of Asthma Development
    Teo, SM ; Mok, D ; Pham, K ; Kusel, M ; Serralha, M ; Troy, N ; Holt, BJ ; Hales, BJ ; Walker, ML ; Hollams, E ; Bochkov, YA ; Grindle, K ; Johnston, SL ; Gern, JE ; Sly, PD ; Holt, PG ; Holt, KE ; Inouye, M (CELL PRESS, 2015-05-13)
    The nasopharynx (NP) is a reservoir for microbes associated with acute respiratory infections (ARIs). Lung inflammation resulting from ARIs during infancy is linked to asthma development. We examined the NP microbiome during the critical first year of life in a prospective cohort of 234 children, capturing both the viral and bacterial communities and documenting all incidents of ARIs. Most infants were initially colonized with Staphylococcus or Corynebacterium before stable colonization with Alloiococcus or Moraxella. Transient incursions of Streptococcus, Moraxella, or Haemophilus marked virus-associated ARIs. Our data identify the NP microbiome as a determinant for infection spread to the lower airways, severity of accompanying inflammatory symptoms, and risk for future asthma development. Early asymptomatic colonization with Streptococcus was a strong asthma predictor, and antibiotic usage disrupted asymptomatic colonization patterns. In the absence of effective anti-viral therapies, targeting pathogenic bacteria within the NP microbiome could represent a prophylactic approach to asthma.
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    SRST2: Rapid genomic surveillance for public health and hospital microbiology labs
    Inouye, M ; Dashnow, H ; Raven, L-A ; Schultz, MB ; Pope, BJ ; Tomita, T ; Zobel, J ; Holt, KE (BMC, 2014-11-20)
    Rapid molecular typing of bacterial pathogens is critical for public health epidemiology, surveillance and infection control, yet routine use of whole genome sequencing (WGS) for these purposes poses significant challenges. Here we present SRST2, a read mapping-based tool for fast and accurate detection of genes, alleles and multi-locus sequence types (MLST) from WGS data. Using >900 genomes from common pathogens, we show SRST2 is highly accurate and outperforms assembly-based methods in terms of both gene detection and allele assignment. We include validation of SRST2 within a public health laboratory, and demonstrate its use for microbial genome surveillance in the hospital setting. In the face of rising threats of antimicrobial resistance and emerging virulence among bacterial pathogens, SRST2 represents a powerful tool for rapidly extracting clinically useful information from raw WGS data. Source code is available from http://katholt.github.io/srst2/.
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    In silico serotyping of E. coli from short read data identifies limited novel O-loci but extensive diversity of O:H serotype combinations within and between pathogenic lineages
    Ingle, DJ ; Valcanis, M ; Kuzevski, A ; Tauschek, M ; Inouye, M ; Stinear, T ; Levine, MM ; Robins-Browne, RM ; Holt, KE (MICROBIOLOGY SOC, 2016-07)
    The lipopolysaccharide (O) and flagellar (H) surface antigens of Escherichia coli are targets for serotyping that have traditionally been used to identify pathogenic lineages. These surface antigens are important for the survival of E. coli within mammalian hosts. However, traditional serotyping has several limitations, and public health reference laboratories are increasingly moving towards whole genome sequencing (WGS) to characterize bacterial isolates. Here we present a method to rapidly and accurately serotype E. coli isolates from raw, short read WGS data. Our approach bypasses the need for de novo genome assembly by directly screening WGS reads against a curated database of alleles linked to known and novel E. coli O-groups and H-types (the EcOH database) using the software package srst2. We validated the approach by comparing in silico results for 197 enteropathogenic E. coli isolates with those obtained by serological phenotyping in an independent laboratory. We then demonstrated the utility of our method to characterize isolates in public health and clinical settings, and to explore the genetic diversity of >1500 E. coli genomes from multiple sources. Importantly, we showed that transfer of O- and H-antigen loci between E. coli chromosomal backbones is common, with little evidence of constraints by host or pathotype, suggesting that E. coli 'strain space' may be virtually unlimited, even within specific pathotypes. Our findings show that serotyping is most useful when used in combination with strain genotyping to characterize microevolution events within an inferred population structure.
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    Frequent transmission of the Mycobacterium tuberculosis Beijing lineage and positive selection for the EsxW Beijing variant in Vietnam
    Holt, KE ; McAdam, P ; Phan, VKT ; Nguyen, TTT ; Dang, TMH ; Nguyen, NL ; Nguyen, HL ; Nguyen, TQN ; Hoang, TH ; Vu, TNH ; Thwaites, G ; Edwards, DJ ; Nath, AP ; Pham, K ; Ascher, DB ; Farrar, J ; Khor, CC ; Teo, YY ; Inouye, M ; Caws, M ; Dunstan, SJ (NATURE PUBLISHING GROUP, 2018-06)
    To examine the transmission dynamics of Mycobacterium tuberculosis (Mtb) isolated from tuberculosis patients in Ho Chi Minh City, Vietnam, we sequenced the whole genomes of 1,635 isolates and compared these with 3,144 isolates from elsewhere. The data identify an underlying burden of disease caused by the endemic Mtb lineage 1 associated with the activation of long-term latent infection, and a threefold higher burden associated with the more recently introduced Beijing lineage and lineage 4 Mtb strains. We find that Beijing lineage Mtb is frequently transferred between Vietnam and other countries, and detect higher levels of transmission of Beijing lineage strains within this host population than the endemic lineage 1 Mtb. Screening for parallel evolution of Beijing lineage-associated SNPs in other Mtb lineages as a signal of positive selection, we identify an alteration in the ESX-5 type VII-secreted protein EsxW, which could potentially contribute to the enhanced transmission of Beijing lineage Mtb in Vietnamese and other host populations.
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    Elucidation of pathways driving asthma pathogenesis: development of a systems-level analytic strategy
    Walker, ML ; Holt, KE ; Anderson, GP ; Teo, SM ; Sly, PD ; Holt, PG ; Inouye, M (FRONTIERS MEDIA SA, 2014-09-23)
    Asthma is a genetically complex, chronic lung disease defined clinically as episodic airflow limitation and breathlessness that is at least partially reversible, either spontaneously or in response to therapy. Whereas asthma was rare in the late 1800s and early 1900s, the marked increase in its incidence and prevalence since the 1960s points to substantial gene × environment interactions occurring over a period of years, but these interactions are very poorly understood (1-6). It is widely believed that the majority of asthma begins during childhood and manifests first as intermittent wheeze. However, wheeze is also very common in infancy and only a subset of wheezy children progress to persistent asthma for reasons that are largely obscure. Here, we review the current literature regarding causal pathways leading to early asthma development and chronicity. Given the complex interactions of many risk factors over time eventually leading to apparently multiple asthma phenotypes, we suggest that deeply phenotyped cohort studies combined with sophisticated network models will be required to derive the next generation of biological and clinical insights in asthma pathogenesis.
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    Short read sequence typing (SRST): multi-locus sequence types from short reads
    Inouye, M ; Conway, TC ; Zobel, J ; Holt, KE (BMC, 2012-07-24)
    BACKGROUND: Multi-locus sequence typing (MLST) has become the gold standard for population analyses of bacterial pathogens. This method focuses on the sequences of a small number of loci (usually seven) to divide the population and is simple, robust and facilitates comparison of results between laboratories and over time. Over the last decade, researchers and population health specialists have invested substantial effort in building up public MLST databases for nearly 100 different bacterial species, and these databases contain a wealth of important information linked to MLST sequence types such as time and place of isolation, host or niche, serotype and even clinical or drug resistance profiles. Recent advances in sequencing technology mean it is increasingly feasible to perform bacterial population analysis at the whole genome level. This offers massive gains in resolving power and genetic profiling compared to MLST, and will eventually replace MLST for bacterial typing and population analysis. However given the wealth of data currently available in MLST databases, it is crucial to maintain backwards compatibility with MLST schemes so that new genome analyses can be understood in their proper historical context. RESULTS: We present a software tool, SRST, for quick and accurate retrieval of sequence types from short read sets, using inputs easily downloaded from public databases. SRST uses read mapping and an allele assignment score incorporating sequence coverage and variability, to determine the most likely allele at each MLST locus. Analysis of over 3,500 loci in more than 500 publicly accessible Illumina read sets showed SRST to be highly accurate at allele assignment. SRST output is compatible with common analysis tools such as eBURST, Clonal Frame or PhyloViz, allowing easy comparison between novel genome data and MLST data. Alignment, fastq and pileup files can also be generated for novel alleles. CONCLUSIONS: SRST is a novel software tool for accurate assignment of sequence types using short read data. Several uses for the tool are demonstrated, including quality control for high-throughput sequencing projects, plasmid MLST and analysis of genomic data during outbreak investigation. SRST is open-source, requires Python, BWA and SamTools, and is available from http://srst.sourceforge.net.