MyMedR

Displaying publications 21 - 26 of 26 in total

Abstract:

Sort:

Fulltext NeisseriaBase: a specialised Neisseria genomic resource and analysis platform

Zheng W, Mutha NV, Heydari H, Dutta A, Siow CC, Jakubovics NS, et al.

PeerJ, 2016;4:e1698.
PMID: 27017950 DOI: 10.7717/peerj.1698

Background. The gram-negative Neisseria is associated with two of the most potent human epidemic diseases: meningococcal meningitis and gonorrhoea. In both cases, disease is caused by bacteria colonizing human mucosal membrane surfaces. Overall, the genus shows great diversity and genetic variation mainly due to its ability to acquire and incorporate genetic material from a diverse range of sources through horizontal gene transfer. Although a number of databases exist for the Neisseria genomes, they are mostly focused on the pathogenic species. In this present study we present the freely available NeisseriaBase, a database dedicated to the genus Neisseria encompassing the complete and draft genomes of 15 pathogenic and commensal Neisseria species. Methods. The genomic data were retrieved from National Center for Biotechnology Information (NCBI) and annotated using the RAST server which were then stored into the MySQL database. The protein-coding genes were further analyzed to obtain information such as calculation of GC content (%), predicted hydrophobicity and molecular weight (Da) using in-house Perl scripts. The web application was developed following the secure four-tier web application architecture: (1) client workstation, (2) web server, (3) application server, and (4) database server. The web interface was constructed using PHP, JavaScript, jQuery, AJAX and CSS, utilizing the model-view-controller (MVC) framework. The in-house developed bioinformatics tools implemented in NeisseraBase were developed using Python, Perl, BioPerl and R languages. Results. Currently, NeisseriaBase houses 603,500 Coding Sequences (CDSs), 16,071 RNAs and 13,119 tRNA genes from 227 Neisseria genomes. The database is equipped with interactive web interfaces. Incorporation of the JBrowse genome browser in the database enables fast and smooth browsing of Neisseria genomes. NeisseriaBase includes the standard BLAST program to facilitate homology searching, and for Virulence Factor Database (VFDB) specific homology searches, the VFDB BLAST is also incorporated into the database. In addition, NeisseriaBase is equipped with in-house designed tools such as the Pairwise Genome Comparison tool (PGC) for comparative genomic analysis and the Pathogenomics Profiling Tool (PathoProT) for the comparative pathogenomics analysis of Neisseria strains. Discussion. This user-friendly database not only provides access to a host of genomic resources on Neisseria but also enables high-quality comparative genome analysis, which is crucial for the expanding scientific community interested in Neisseria research. This database is freely available at http://neisseria.um.edu.my.
1 H-NMR metabolomics for evaluating the protective effect of Clinacanthus nutans (Burm. f) Lindau water extract against nitric oxide production in LPS-IFN-γ activated RAW 264.7 macrophages

Khoo LW, Kow ASF, Maulidiani M, Ang MY, Chew WY, Lee MT, et al.

Phytochem Anal, 2019 Jan;30(1):46-61.
PMID: 30183131 DOI: 10.1002/pca.2789

INTRODUCTION: Clinacanthus nutans, a small shrub that is native to Southeast Asia, is commonly used in traditional herbal medicine and as a food source. Its anti-inflammation properties is influenced by the metabolites composition, which can be determined by different binary extraction solvent ratio and extraction methods used during plant post-harvesting stage.
OBJECTIVE: Evaluate the relationship between the chemical composition of C. nutans and its anti-inflammatory properties using nuclear magnetic resonance (NMR) metabolomics approach.
METHODOLOGY: The anti-inflammatory effect of C. nutans air-dried leaves extracted using five different binary extraction solvent ratio and two extraction methods was determined based on their nitric oxide (NO) inhibition effect in lipopolysaccharide-interferon-gamma (LPS-IFN-γ) activated RAW 264.7 macrophages. The relationship between extract bioactivity and metabolite profiles and quantifications were established using 1 H-NMR metabolomics and liquid chromatography-tandem mass spectrometry (LC-MS/MS). The possible metabolite biosynthesis pathway was constructed to further strengthen the findings.
RESULTS: Water and sonication prepared air-dried leaves possessed the highest NO inhibition activity (IC50 = 190.43 ± 12.26 μg/mL, P
Fulltext Parvimonas micra, Peptostreptococcus stomatis, Fusobacterium nucleatum and Akkermansia muciniphila as a four-bacteria biomarker panel of colorectal cancer

Osman MA, Neoh HM, Ab Mutalib NS, Chin SF, Mazlan L, Raja Ali RA, et al.

Sci Rep, 2021 02 03;11(1):2925.
PMID: 33536501 DOI: 10.1038/s41598-021-82465-0

Dysbiosis of the gut microbiome has been associated with the pathogenesis of colorectal cancer (CRC). We profiled the microbiome of gut mucosal tissues from 18 CRC patients and 18 non-CRC controls of the UKM Medical Centre (UKMMC), Kuala Lumpur, Malaysia. The results were then validated using a species-specific quantitative PCR in 40 CRC and 20 non-CRC tissues samples from the UMBI-UKMMC Biobank. Parvimonas micra, Fusobacterium nucleatum, Peptostreptococcus stomatis and Akkermansia muciniphila were found to be over-represented in our CRC patients compared to non-CRC controls. These four bacteria markers distinguished CRC from controls (AUROC = 0.925) in our validation cohort. We identified bacteria species significantly associated (cut-off value of > 5 fold abundance) with various CRC demographics such as ethnicity, gender and CRC staging; however, due to small sample size of the discovery cohort, these results could not be further verified in our validation cohort. In summary, Parvimonas micra, Fusobacterium nucleatum, Peptostreptococcus stomatis and Akkermansia muciniphila were enriched in our local CRC patients. Nevertheless, the roles of these bacteria in CRC initiation and progression remains to be investigated.
Fulltext Draft Genome Sequences of Four Methicillin-Resistant Staphylococcus aureus Strains (M080_2017, M106_2017, M181_2017, and M191_2017), Isolated from a Malaysian Teaching Hospital

Ang MY, Binti Mohamad Farook NA, Kamarudin N, Lam SD, Di Gregorio S, Tengku Jamaluddin TZM, et al.

Microbiol Resour Announc, 2022 Dec 15;11(12):e0086722.
PMID: 36413024 DOI: 10.1128/mra.00867-22

Draft genome sequences were obtained for four methicillin-resistant Staphylococcus aureus (MRSA) strains isolated from various wards of the Hospital Canselor Tuanku Muhriz (HCTM), Kuala Lumpur, Malaysia, in 2017. Using different bioinformatics tools, we annotated the draft genomes and identified multiple antimicrobial resistance genes.
Fulltext YersiniaBase: a genomic resource and analysis platform for comparative analysis of Yersinia

Tan SY, Dutta A, Jakubovics NS, Ang MY, Siow CC, Mutha NV, et al.

BMC Bioinformatics, 2015;16:9.
PMID: 25591325 DOI: 10.1186/s12859-014-0422-y

Yersinia is a Gram-negative bacteria that includes serious pathogens such as the Yersinia pestis, which causes plague, Yersinia pseudotuberculosis, Yersinia enterocolitica. The remaining species are generally considered non-pathogenic to humans, although there is evidence that at least some of these species can cause occasional infections using distinct mechanisms from the more pathogenic species. With the advances in sequencing technologies, many genomes of Yersinia have been sequenced. However, there is currently no specialized platform to hold the rapidly-growing Yersinia genomic data and to provide analysis tools particularly for comparative analyses, which are required to provide improved insights into their biology, evolution and pathogenicity.
A collective statement in support of saving pangolins

Choo SW, Chong JL, Gaubert P, Hughes AC, O'Brien S, Chaber AL, et al.

Sci Total Environ, 2022 Feb 14.
PMID: 35176378 DOI: 10.1016/j.scitotenv.2022.153666