Biology subjects

Coin, L. J.

Publications and source records attributed to Coin, L. J..

5 recordsLinked to original sources

bioRxiv2023

MERITS: a web-based integrated MycobacterialPE/PPE protein database

MotivationPE/PPE proteins, highly abundant in the Mycobacterium genome, play a vital role in virulence and immune modulation. Understanding their functions is key to comprehending the internal mechanisms of Mycobacterium. However, a lack of dedicated resources has limited research into PE/PPE proteins. ResultsAddressing this gap, we introduce MERITS, a comprehensive 3D structure database specifically designed for PE/PPE proteins. MERITS hosts 22,353 non-redundant PE/PPE proteins, encompassing details like physicochemical properties, subcellular localisation, post-translational modification sites, protein functions, and measures of antigenicity, toxicity, and allergenicity. MERITS also includes data on their secondary and tertiary structure, along with other relevant biological information. MERITS is designed to be user-friendly, offering interactive search and data browsing Features to aid researchers in exploring the potential functions of PE/PPE proteins. MERITS is expected to become a crucial resource in the field, aiding in developing new diagnostics and vaccines by elucidating the sequence-structure-functional relationships of PE/PPE proteins. Availability and implementationMERITS is freely accessible at http://merits.unimelb-biotools.cloud.edu.au/.

bioinformatics↗

bioRxiv2019

High-throughput multiplexed tandem repeat genotyping using targeted long-read sequencing

Tandem repeats (TRs) are highly prone to variation in copy numbers due to their repetitive and unstable nature, which makes them a major source of genomic variation between individuals. However, population variation of TRs have not been widely explored due to the limitations of existing tools, which are either low-throughput or restricted to a small subset of TRs. Here, we used SureSelect targeted sequencing approach combined with Nanopore sequencing to overcome these limitations. We achieved an average of 3062-fold target enrichment on a panel of 142 TR loci, generating an average of 97X sequence coverage on 7 samples utilizing 2 MinION flow-cells with 200ng of input DNA per sample. We identified a subset of 110 TR loci with length less than 2kb, and GC content greater than 25% for which we achieved an average genotyping rate of 75% and increasing to 91% for the highest-coverage sample. Alleles estimated from targeted long-read sequencing were concordant with gold standard PCR sizing analysis and moreover highly correlated with alleles estimated from whole genome long-read sequencing. We demonstrate a targeted long-read sequencing approach that enables simultaneous analysis of hundreds of TRs and accuracy is comparable to PCR sizing analysis. Our approach is feasible to scale for more targets and more samples facilitating large-scale analysis of TRs.

genomics↗

bioRxiv2019

Identification of reduced host transcriptomic signatures for tuberculosis and digital PCR-based validation and quantification

Recently, host whole blood gene expression signatures have been identified for diagnosis of tuberculosis (TB). Absolute quantification of the concentrations of signature transcripts in blood have not been reported, but would facilitate the development of diagnostic tests.\n\nTo identify minimal transcript signatures, we applied a novel transcript selection procedure to microarray data from African adults comprising 536 patients with TB, other diseases (OD) and latent TB (LTBI), divided into training and test sets. Signatures were validated using reverse transcriptase (RT) - digital PCR (dPCR).\n\nA four-transcript signature (GBP6, TMCC1, PRDM1, ARG1) measured using RT-dPCR distinguished TB patients from those with OD (area under the curve (AUC) 93.8% (CI95% 82.2 - 100%). A three-transcript signature (FCGR1A, ZNF296, C1QB) differentiated TB from LTBI (AUC 97.3%, CI95%: 93.3 - 100%), regardless of HIV.\n\nThese signatures have been validated across platforms and across samples offering strong, quantitative support for their use as diagnostic biomarkers for TB.

molecular biology↗

bioRxiv2018

Estimating parasite load dynamics to reveal novel resistance mechanisms to human malaria

Improved methods are needed to identify host mechanisms which directly protect against human infectious diseases in order to develop better vaccines and therapeutics1,2. Pathogen load determines the outcome of many infections3, and is a consequence of pathogen multiplication rate, duration of the infection, and inhibition or killing of pathogen by the host (resistance). If these determinants of pathogen load could be quantified then their mechanistic correlates might be determined. In humans the timing of infection is rarely known and treatment cannot usually be withheld to monitor serial changes in pathogen load and host response. Here we present an approach to overcome this and identify potential mechanisms of resistance which control parasite load in Plasmodium falciparum malaria. Using a mathematical model of longitudinal infection dynamics for orientation, we made individualized estimates of parasite multiplication and growth inhibition in Gambian children at presentation with acute malaria and used whole blood RNA-sequencing to identify their correlates. We identified novel roles for secreted proteases cathepsin G and matrix metallopeptidase 9 (MMP9) as direct effector molecules which inhibit P. falciparum growth. Cathepsin G acts on the erythrocyte membrane, cleaving surface receptors required for parasite invasion, whilst MMP9 acts on the parasite. In contrast, the type 1 interferon response and expression of CXCL10 (IFN-{gamma}-inducible protein of 10 kDa, IP-10) were detrimental to control of parasite growth. Natural variation in iron status and plasma levels of complement factor H were determinants of parasite multiplication rate. Our findings demonstrate the importance of accounting for the dynamic interaction between host and pathogen when seeking to identify correlates of protection, and reveal novel mechanisms controlling parasite growth in humans. This approach could be extended to identify additional mechanistic correlates of natural- and vaccine-induced immunity to malaria and other infections.

systems biology↗

bioRxiv2017

Integrated pathogen load and dual transcriptome analysis of systemic host-pathogen interactions in severe malaria

The pathogenesis of severe Plasmodium falciparum malaria is incompletely understood. Since the pathogenic stage of the parasite is restricted to blood, dual RNA-sequencing of host and parasite transcripts in blood can reveal their interactions at a systemic scale. Here we identify human and parasite gene expression associated with severe disease features in Gambian children. Differences in parasite load explained up to 99% of differential expression of human genes but only a third of the differential expression of parasite genes. Co-expression analyses showed a remarkable co-regulation of host and parasite genes controlling translation, and host granulopoiesis genes uniquely co-regulated and differentially expressed in severe malaria. Our results indicate that high parasite load is the proximal stimulus for severe P. falciparum malaria, that there is an unappreciated role for many parasite genes in determining virulence, and hint at a molecular arms-race between host and parasite to synthesise protein products.

systems biology↗