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Thidathip Wongsurawat

Genome-Based Comparison of Clostridioides difficile : Average Amino Acid Identity Analysis of Core Genomes

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Adriana Cabal, Se-Ran Jun, Piroon Jenjaroenpun, Visanu Wanchai, Intawat Nookaew, Thidathip Wongsurawat, Mary J. Burgess, Atul Kothari, Trudy M. Wassenaar1, David W. Ussery

Received: 30 August 2017 /Accepted: 2 February 2018 # The Author(s) 2018. This article is an open access publication


Infections due to Clostridioides difficile (previously known as Clostridium difficile) are a major problem in hospitals, where cases can be caused by community-acquired strains as well as by nosocomial spread. Whole genome sequences from clinical samples contain a lot of information but that needs to be analyzed and compared in such a way that the outcome is useful for clinicians or epidemiologists. Here, we compare 663 public available complete genome sequences of C. difficile using average amino acid identity (AAI) scores. This analysis revealed that most of these genomes (640, 96.5%) clearly belong to the same species, while the remaining 23 genomes produce four distinct clusters within the Clostridioides genus. The main C. difficile cluster can be further divided into sub-clusters, depending on the chosen cutoff. We demonstrate that MLST, either based on partial or full gene-length, results in biased estimates of genetic differences and does not capture the true degree of similarity or differences of complete genomes. Presence of genes coding for C. difficile toxins A and B (ToxA/B), as well as the binary C. difficile toxin (CDT), was deduced from their unique PfamA domain architectures. Out of the 663 C. difficile genomes, 535 (80.7%) contained at least one copy of ToxA or ToxB, while these genes were missing from 128 genomes. Although some clusters were enriched for toxin presence, these genes are variably present in a given genetic background. The CDT genes were found in 191 genomes, which were restricted to a few clusters only, and only one cluster lacked the toxin A/B genes consistently. A total of 310 genomes contained ToxA/B without CDT (47%). Further, published metagenomic data from stools were used to assess the presence of C. difficile sequences in blinded cases of C. difficile infection (CDI) and controls, to test if metagenomic analysis is sensitive enough to detect the pathogen, and to establish strain relationships between cases from the same hospital. We conclude that metagenomics can contribute to the identification of CDI and can assist in characterization of the most probable causative strain in CDI patients.

Keywords C. difficile, AAI .MLST, Community-acquired infections, Comparative genomics

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Distinctive molecular signature and activated signaling pathways in aortic smooth muscle cells of patients with myocardial infarction

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Atherosclerosis, manuscript in the press, accepted 16 January, 2028

Thidathip Wongsurawat, Chin Cheng Woo, Antonis Giannakakis, Xiao Yun Lin, Esther Sok Hwee Cheow, Chuen Neng Lee, Mark Richards, Siu Kwan Sze, Intawat Nookaew, Vladimir A. Kuznetsov’Correspondence information about the author Vladimir A. Kuznetsov, Vitaly Sorokin


Background and aims: We aim to identify significant transcriptome alterations of vascular smooth muscle cells (VSMCs) in the aortic wall of myocardial infarction (MI) patients. Providing a robust transcriptomic signature, we aim to highlight the most likely aberrant pathway(s) in MI VSMCs. Methods and results: Laser-captured microdissection (LCM) was used to obtain VSMCs from aortic wall tissues harvested during coronary artery bypass surgery. Microarray gene analysis was applied to analyse VSMCs from 17 MI and 19 non-MI patients. Prediction Analysis of Microarray (PAM) identified 370 genes that significantly discriminated MI and non-MI samples and were enriched in genes responsible for muscle development, differentiation and phenotype regulation. Incorporation of gene ontology (GO) led to the identification of a 21-gene VSMCs-associated classifier that discriminated between MI and non-MI patients with 92% accuracy. The mass spectrometry-based iTRAQ analysis of the MI and non-MI samples revealed 94 proteins significantly differentiating these tissues. Ingenuity Pathway Analysis (IPA) of 370 genes revealed top pathways associated with hypoxia signaling in the cardiovascular system. Enrichment analysis of these proteins suggested an activation of the superoxide radical degradation pathway. An integrated transcriptome-proteome pathway analysis revealed that superoxide radical degradation pathway remained the most implicated pathway. The intersection of the top candidate molecules from the transcriptome and proteome highlighted superoxide dismutase (SOD1) overexpression

Conclusions: We provided a novel 21-gene VSMCs-associated MI classifier in reference to significant VSMCs transcriptome alterations that, in combination with proteomics data, suggests the activation of superoxide radical degradation pathway in VSMCs of MI patients.