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Fulltext Stepwise evolution of pandrug-resistance in Klebsiella pneumoniae

Zowawi HM, Forde BM, Alfaresi M, Alzarouni A, Farahat Y, Chong TM, et al.

Sci Rep, 2015;5:15082.
PMID: 26478520 DOI: 10.1038/srep15082

Carbapenem resistant Enterobacteriaceae (CRE) pose an urgent risk to global human health. CRE that are non-susceptible to all commercially available antibiotics threaten to return us to the pre-antibiotic era. Using Single Molecule Real Time (SMRT) sequencing we determined the complete genome of a pandrug-resistant Klebsiella pneumoniae isolate, representing the first complete genome sequence of CRE resistant to all commercially available antibiotics. The precise location of acquired antibiotic resistance elements, including mobile elements carrying genes for the OXA-181 carbapenemase, were defined. Intriguingly, we identified three chromosomal copies of an ISEcp1-bla(OXA-181) mobile element, one of which has disrupted the mgrB regulatory gene, accounting for resistance to colistin. Our findings provide the first description of pandrug-resistant CRE at the genomic level, and reveal the critical role of mobile resistance elements in accelerating the emergence of resistance to other last resort antibiotics.

Matched MeSH terms: Genes, Regulator
Fulltext Computational prediction of miR130a target genes in cancer

Nur Ainina Abdollah, Nurulisa Zulkifle, Siti Razila Abdul Razak

Malaysian Journal of Medicine and Health Sciences, 2020;16(102):51-59.
MyJurnal

Introduction: Cancer is one of the main causes of mortality globally and the incidence has been rising over the years. Studies have shown that miRNAs have the potential as cancer biomarkers. The miR-130a has been reported to be upregulated in several types of cancer, which indicate the important roles of miR-130a in cancer development and metastasis. The aim of this study is to identify potential target genes and to predict the regulatory function of miR- 130a-3p and 5p in cancer. Methods: Three bioinformatics platforms namely miRWalk, the Database for annotations, visualization and integrated discovery (DAVID) Gene Functional Classification Tool and miRanda-miRSVR analysis tools were used to identify possible interaction between miR-130a and its target. Protein-protein interaction (PPI) network for the predicted target genes was then constructed. Results: The analyses have identified nine predicted target genes for miR-130a-3p (RAPGEF4, SOS2, NRP1, RPS6KB1, MET, IL15, ACVR1, RYR2 and ITPR1), and ten for miR-130a-5p (BCL11A, SPOPL, NLK, PPARGC1A, POU4F2, CPEB4, ST18, RSBN1L, ELF5 and ARID4B), that might
play an important role in the development of cancer. Findings from this report suggest that miR-130a may involves in controlling cancer related genes; MET, ACVR1 and BCL11A. miR-130a-3p may regulates MET which involves in apoptosis and metastasis, and ACVR1 which involves in metastasis and angiogenesis. miR-130a-5p may regulates BCL11A which involves in apoptosis, proliferation and tumorigenesis. Conclusion: This study has highlighted the molecular interaction of miR-130a with associated genes and pathways, suggesting therapeutic potential of miR- 130a as personalised targeted therapy for cancer.

Matched MeSH terms: Genes, Regulator
Fulltext Research trends in microarray data analysis: modelling gene regulatory network by integrating transcription factors data

Farzana Kabir Ahmad, Siti Sakira Kamaruddin

Scientific Research Journal, 2015;12(1):1-10.
MyJurnal

The invention of microarray technology has enabled expression levels of thousands of genes to be monitored at once. This modernized approach has created large amount of data to be examined. Recently, gene regulatory network has been an interesting topic and generated impressive research goals in computational biology. Better understanding of the genetic regulatory processes would bring significant implications in the biomedical fields and many other pharmaceutical industries. As a result, various mathematical and computational methods have been used to model gene regulatory network from microarray data. Amongst those methods, the Bayesian network model attracts the most attention and has become the prominent technique since it can capture nonlinear and stochastic relationships between variables. However, structure learning of this model is NP-hard and computationally complex as the number of potential edges increase drastically with the number of genes. In addition, most of the studies only focused on the predicted results while neglecting the fact that microarray data is a fragmented information on the whole biological process. Hence this study proposed a network-based inference model that combined biological knowledge in order to verify the constructed gene regulatory relationships. The gene regulatory network is constructed using Bayesian network based on low-order conditional independence approach. This technique aims to identify from the data the dependencies to construct the network structure, while addressing the structure learning problem. In addition, three main toolkits such as Ensembl, TFSearch and TRANSFAC have been used to determine the false positive edges and verify reliability of regulatory relationships. The experimental results show that by integrating biological knowledge it could enhance the precision results and reduce the number of false positive edges in the trained gene regulatory network.

Matched MeSH terms: Genes, Regulator
Fulltext NFIX as a Master Regulator for Lung Cancer Progression

Rahman NIA, Abdul Murad NA, Mollah MM, Jamal R, Harun R

Front Pharmacol, 2017;8:540.
PMID: 28871224 DOI: 10.3389/fphar.2017.00540

About 40% of lung cancer cases globally are diagnosed at the advanced stage. Lung cancer has a high mortality and overall survival in stage I disease is only 70%. This study was aimed at finding a candidate of transcription regulator that initiates the mechanism for metastasis by integrating computational and functional studies. The genes involved in lung cancer were retrieved using in silico software. 10 kb promoter sequences upstream were scanned for the master regulator. Transient transfection of shRNA NFIXs were conducted against A549 and NCI-H1299 cell lines. qRT-PCR and functional assays for cell proliferation, migration and invasion were carried out to validate the involvement of NFIX in metastasis. Genome-wide gene expression microarray using a HumanHT-12v4.0 Expression BeadChip Kit was performed to identify differentially expressed genes and construct a new regulatory network. The in silico analysis identified NFIX as a master regulator and is strongly associated with 17 genes involved in the migration and invasion pathways including IL6ST, TIMP1 and ITGB1. Silencing of NFIX showed reduced expression of IL6ST, TIMP1 and ITGB1 as well as the cellular proliferation, migration and invasion processes. The data was integrated with the in silico analyses to find the differentially expressed genes. Microarray analysis showed that 18 genes were expressed differentially in both cell lines after statistical analyses integration between t-test, LIMMA and ANOVA with Benjamini-Hochberg adjustment at p-value < 0.05. A transcriptional regulatory network was created using all 18 genes, the existing regulated genes including the new genes PTCH1, NFAT5 and GGCX that were found highly associated with NFIX, the master regulator of metastasis. This study suggests that NFIX is a promising target for therapeutic intervention that is expected to inhibit metastatic recurrence and improve survival rate.

Matched MeSH terms: Genes, Regulator
Fulltext Comparative effects of overproducing the AraC-type transcriptional regulators MarA, SoxS, RarA and RamA on antimicrobial drug susceptibility in Klebsiella pneumoniae

Jiménez-Castellanos JC, Wan Ahmad Kamil WN, Cheung CH, Tobin MS, Brown J, Isaac SG, et al.

J Antimicrob Chemother, 2016 Jul;71(7):1820-5.
PMID: 27029850 DOI: 10.1093/jac/dkw088

OBJECTIVES: In Klebsiella pneumoniae, overproduction of RamA and RarA leads to increased MICs of various antibiotics; MarA and SoxS are predicted to perform a similar function. We have compared the relative effects of overproducing these four AraC-type regulators on envelope permeability (a combination of outer membrane permeability and efflux), efflux pump and porin production, and antibiotic susceptibility in K. pneumoniae.
METHODS: Regulators were overproduced using a pBAD expression vector. Antibiotic susceptibility was measured using disc testing. Envelope permeability was estimated using a fluorescent dye accumulation assay. Porin and efflux pump production was quantified using proteomics and validated using real-time quantitative RT-PCR.
RESULTS: Envelope permeability and antibiotic disc inhibition zone diameters both reduced during overproduction of RamA and to a lesser extent RarA or SoxS, but did not change following overproduction of MarA. These effects were associated with overproduction of the efflux pumps AcrAB (for RamA and SoxS) and OqxAB (for RamA and RarA) and the outer membrane protein TolC (for all regulators). Effects on porin production were strain specific.
CONCLUSIONS: RamA is the most potent regulator of antibiotic permeability in K. pneumoniae, followed by RarA then SoxS, with MarA having very little effect. This observed relative potency correlates well with the frequency at which these regulators are reportedly overproduced in clinical isolates.

Matched MeSH terms: Genes, Regulator*
Fulltext Investigation into the effects of antioxidant-rich extract of Tamarindus indica leaf on antioxidant enzyme activities, oxidative stress and gene expression profiles in HepG2 cells

Razali N, Abdul Aziz A, Lim CY, Mat Junit S

PeerJ, 2015;3:e1292.
PMID: 26557426 DOI: 10.7717/peerj.1292

The leaf extract of Tamarindus indica L. (T. indica) had been reported to possess high phenolic content and showed high antioxidant activities. In this study, the effects of the antioxidant-rich leaf extract of the T. indica on lipid peroxidation, antioxidant enzyme activities, H2O2-induced ROS production and gene expression patterns were investigated in liver HepG2 cells. Lipid peroxidation and ROS production were inhibited and the activity of antioxidant enzymes superoxide dismutase, catalase and glutathione peroxidase was enhanced when the cells were treated with the antioxidant-rich leaf extract. cDNA microarray analysis revealed that 207 genes were significantly regulated by at least 1.5-fold (p < 0.05) in cells treated with the antioxidant-rich leaf extract. The expression of KNG1, SERPINC1, SERPIND1, SERPINE1, FGG, FGA, MVK, DHCR24, CYP24A1, ALDH6A1, EPHX1 and LEAP2 were amongst the highly regulated. When the significantly regulated genes were analyzed using Ingenuity Pathway Analysis software, "Lipid Metabolism, Small Molecule Biochemistry, Hematological Disease" was the top biological network affected by the leaf extract, with a score of 36. The top predicted canonical pathway affected by the leaf extract was the coagulation system (P < 2.80 × 10(-6)) followed by the superpathway of cholesterol biosynthesis (P < 2.17 × 10(-4)), intrinsic prothrombin pathway (P < 2.92 × 10(-4)), Immune Protection/Antimicrobial Response (P < 2.28 × 10(-3)) and xenobiotic metabolism signaling (P < 2.41 × 10(-3)). The antioxidant-rich leaf extract of T. indica also altered the expression of proteins that are involved in the Coagulation System and the Intrinsic Prothrombin Activation Pathway (KNG1, SERPINE1, FGG), Superpathway of Cholesterol Biosynthesis (MVK), Immune protection/antimicrobial response (IFNGR1, LEAP2, ANXA3 and MX1) and Xenobiotic Metabolism Signaling (ALDH6A1, ADH6). In conclusion, the antioxidant-rich leaf extract of T. indica inhibited lipid peroxidation and ROS production, enhanced antioxidant enzyme activities and significantly regulated the expression of genes and proteins involved with consequential impact on the coagulation system, cholesterol biosynthesis, xenobiotic metabolism signaling and antimicrobial response.

Matched MeSH terms: Genes, Regulator