Displaying publications 181 - 200 of 340 in total

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  1. Fulltext Investigating meta-approaches for reconstructing gene networks in a mammalian cellular context
    Nazri A, Lio P
    PLoS One, 2012;7(1):e28713.
    PMID: 22253694 DOI: 10.1371/journal.pone.0028713
    The output of state-of-the-art reverse-engineering methods for biological networks is often based on the fitting of a mathematical model to the data. Typically, different datasets do not give single consistent network predictions but rather an ensemble of inconsistent networks inferred under the same reverse-engineering method that are only consistent with the specific experimentally measured data. Here, we focus on an alternative approach for combining the information contained within such an ensemble of inconsistent gene networks called meta-analysis, to make more accurate predictions and to estimate the reliability of these predictions. We review two existing meta-analysis approaches; the Fisher transformation combined coefficient test (FTCCT) and Fisher's inverse combined probability test (FICPT); and compare their performance with five well-known methods, ARACNe, Context Likelihood or Relatedness network (CLR), Maximum Relevance Minimum Redundancy (MRNET), Relevance Network (RN) and Bayesian Network (BN). We conducted in-depth numerical ensemble simulations and demonstrated for biological expression data that the meta-analysis approaches consistently outperformed the best gene regulatory network inference (GRNI) methods in the literature. Furthermore, the meta-analysis approaches have a low computational complexity. We conclude that the meta-analysis approaches are a powerful tool for integrating different datasets to give more accurate and reliable predictions for biological networks.
    Matched MeSH terms: Computational Biology/methods*
  2. Utilizing shared interacting domain patterns and Gene Ontology information to improve protein-protein interaction prediction
    Roslan R, Othman RM, Shah ZA, Kasim S, Asmuni H, Taliba J, et al.
    Comput Biol Med, 2010 Jun;40(6):555-64.
    PMID: 20417930 DOI: 10.1016/j.compbiomed.2010.03.009
    Protein-protein interactions (PPIs) play a significant role in many crucial cellular operations such as metabolism, signaling and regulations. The computational methods for predicting PPIs have shown tremendous growth in recent years, but problem such as huge false positive rates has contributed to the lack of solid PPI information. We aimed at enhancing the overlap between computational predictions and experimental results in an effort to partially remove PPIs falsely predicted. The use of protein function predictor named PFP() that are based on shared interacting domain patterns is introduced in this study with the purpose of aiding the Gene Ontology Annotations (GOA). We used GOA and PFP() as agents in a filtering process to reduce false positive pairs in the computationally predicted PPI datasets. The functions predicted by PFP() were extracted from cross-species PPI data in order to assign novel functional annotations for the uncharacterized proteins and also as additional functions for those that are already characterized by the GO (Gene Ontology). The implementation of PFP() managed to increase the chances of finding matching function annotation for the first rule in the filtration process as much as 20%. To assess the capability of the proposed framework in filtering false PPIs, we applied it on the available S. cerevisiae PPIs and measured the performance in two aspects, the improvement made indicated as Signal-to-Noise Ratio (SNR) and the strength of improvement, respectively. The proposed filtering framework significantly achieved better performance than without it in both metrics.
    Matched MeSH terms: Computational Biology/methods*
  3. In silico identification and characterization of a putative phosphatidylinositol 4-phosphate 5-kinase (PIP5K) gene in Eimeria tenella
    Ling KH, Loo SS, Rosli R, Shamsudin MN, Mohamed R, Wan KL
    In Silico Biol. (Gedrukt), 2007;7(1):115-21.
    PMID: 17688436
    Phosphatidylinositol 4-phosphate 5-kinases (PIP5Ks) play diverse roles in the cellular biology of many organisms, including signal transduction, secretion and vesicular trafficking, and regulation of cytoskeleton assembly. Discovery of the PIP5K gene in Eimeria tenella may shed light on its role in the biology of this avian protozoan, and afford further understanding of the cell-host interaction, particularly during the invasion process. In this study, we report the identification of the PIP5K coding region in the genome sequence of Eimeria tenella using in silico gene prediction approaches. Prediction of the PIP5K coding sequence was confirmed by mapping the full-length cDNA sequence, generated via the Rapid Amplification of cDNA Ends (RACE) method, to the genomic sequence. The putative PIP5K gene of Eimeria tenella is located on the complementary strand of the E1080B12.b1 contig, and comprises 12 exons. Further analysis showed that the coding region spans from exon 1 to exon 7, with all exons obeying the adopted 'gt...ag' splicing rule of intronic sequences. Consensus of the hexameric 5' donor-splice site was deduced as GTRDBB... and the consensus for the 3' acceptor-splice sites as ...BHDYAG. The gene encodes a 252-amino acid residue protein. Domain search and protein fold recognition analyses provide compelling evidences that the deduced protein is a PIP5K.
    Matched MeSH terms: Computational Biology/methods*
  4. Fulltext Identification of four functionally important microRNA families with contrasting differential expression profiles between drought-tolerant and susceptible rice leaf at vegetative stage
    Cheah BH, Nadarajah K, Divate MD, Wickneswari R
    BMC Genomics, 2015;16:692.
    PMID: 26369665 DOI: 10.1186/s12864-015-1851-3
    Developing drought-tolerant rice varieties with higher yield under water stressed conditions provides a viable solution to serious yield-reduction impact of drought. Understanding the molecular regulation of this polygenic trait is crucial for the eventual success of rice molecular breeding programmes. microRNAs have received tremendous attention recently due to its importance in negative regulation. In plants, apart from regulating developmental and physiological processes, microRNAs have also been associated with different biotic and abiotic stresses. Hence here we chose to analyze the differential expression profiles of microRNAs in three drought treated rice varieties: Vandana (drought-tolerant), Aday Sel (drought-tolerant) and IR64 (drought-susceptible) in greenhouse conditions via high-throughput sequencing.
    Matched MeSH terms: Computational Biology/methods
  5. Computational Analysis and In silico Predictive Modeling for Inhibitors of PhoP Regulon in S. typhi on High-Throughput Screening Bioassay Dataset
    Kaur H, Ahmad M, Scaria V
    Interdiscip Sci, 2016 Mar;8(1):95-101.
    PMID: 26298582 DOI: 10.1007/s12539-015-0273-x
    There is emergence of multidrug-resistant Salmonella enterica serotype typhi in pandemic proportions throughout the world, and therefore, there is a necessity to speed up the discovery of novel molecules having different modes of action and also less influenced by the resistance formation that would be used as drug for the treatment of salmonellosis particularly typhoid fever. The PhoP regulon is well studied and has now been shown to be a critical regulator of number of gene expressions which are required for intracellular survival of S. enterica and pathophysiology of disease like typhoid. The evident roles of two-component PhoP-/PhoQ-regulated products in salmonella virulence have motivated attempts to target them therapeutically. Although the discovery process of biologically active compounds for the treatment of typhoid relies on hit-finding procedure, using high-throughput screening technology alone is very expensive, as well as time consuming when performed on large scales. With the recent advancement in combinatorial chemistry and contemporary technique for compounds synthesis, there are more and more compounds available which give ample growth of diverse compound library, but the time and endeavor required to screen these unfocused massive and diverse library have been slightly reduced in the past years. Hence, there is demand to improve the high-quality hits and success rate for high-throughput screening that required focused and biased compound library toward the particular target. Therefore, we still need an advantageous and expedient method to prioritize the molecules that will be utilized for biological screens, which saves time and is also inexpensive. In this concept, in silico methods like machine learning are widely applicable technique used to build computational model for high-throughput virtual screens to prioritize molecules for advance study. Furthermore, in computational analysis, we extended our study to identify the common enriched structural entities among the biologically active compound toward finding out the privileged scaffold.
    Matched MeSH terms: Computational Biology/methods*
  6. Fulltext The genome of newly classified Ochroconis mirabilis: Insights into fungal adaptation to different living conditions
    Yew SM, Chan CL, Kuan CS, Toh YF, Ngeow YF, Na SL, et al.
    BMC Genomics, 2016 Feb 03;17:91.
    PMID: 26842951 DOI: 10.1186/s12864-016-2409-8
    Ochroconis mirabilis, a recently introduced water-borne dematiaceous fungus, is occasionally isolated from human skin lesions and nails. We identified an isolate of O. mirabilis from a skin scraping with morphological and molecular studies. Its genome was then sequenced and analysed for genetic features related to classification and biological characteristics.
    Matched MeSH terms: Computational Biology/methods
  7. Detection of copy number variations in epilepsy using exome data
    Tsuchida N, Nakashima M, Kato M, Heyman E, Inui T, Haginoya K, et al.
    Clin Genet, 2018 03;93(3):577-587.
    PMID: 28940419 DOI: 10.1111/cge.13144
    Epilepsies are common neurological disorders and genetic factors contribute to their pathogenesis. Copy number variations (CNVs) are increasingly recognized as an important etiology of many human diseases including epilepsy. Whole-exome sequencing (WES) is becoming a standard tool for detecting pathogenic mutations and has recently been applied to detecting CNVs. Here, we analyzed 294 families with epilepsy using WES, and focused on 168 families with no causative single nucleotide variants in known epilepsy-associated genes to further validate CNVs using 2 different CNV detection tools using WES data. We confirmed 18 pathogenic CNVs, and 2 deletions and 2 duplications at chr15q11.2 of clinically unknown significance. Of note, we were able to identify small CNVs less than 10 kb in size, which might be difficult to detect by conventional microarray. We revealed 2 cases with pathogenic CNVs that one of the 2 CNV detection tools failed to find, suggesting that using different CNV tools is recommended to increase diagnostic yield. Considering a relatively high discovery rate of CNVs (18 out of 168 families, 10.7%) and successful detection of CNV with <10 kb in size, CNV detection by WES may be able to surrogate, or at least complement, conventional microarray analysis.
    Matched MeSH terms: Computational Biology/methods
  8. Computational Analysis of Protein-Protein Interactions in Motile T-Cells
    Kumar S, Fazil MHUT, Ahmad K, Tripathy M, Rajapakse JC, Verma NK
    Methods Mol Biol, 2019;1930:149-156.
    PMID: 30610609 DOI: 10.1007/978-1-4939-9036-8_18
    Analysis of protein-protein interactions is important for better understanding of molecular mechanisms involved in immune regulation and has potential for elaborating avenues for drug discovery targeting T-cell motility. Currently, only a small fraction of protein-protein interactions have been characterized in T-lymphocytes although there are several detection methods available. In this regard, computational approaches garner importance, with the continued explosion of genomic and proteomic data, for handling protein modeling and protein-protein interactions in large scale. Here, we describe a computational method to identify protein-protein interactions based on in silico protein design.
    Matched MeSH terms: Computational Biology/methods*
  9. Genomic characterization of Vibrio parahaemolyticus from Pacific white shrimp and rearing water in Malaysia reveals novel sequence types and structural variation in genomic regions containing the Photorhabdus insect-related (Pir) toxin-like genes
    Yan CZY, Austin CM, Ayub Q, Rahman S, Gan HM
    FEMS Microbiol Lett, 2019 09 01;366(17).
    PMID: 31589302 DOI: 10.1093/femsle/fnz211
    The Malaysian and global shrimp aquaculture production has been significantly impacted by acute hepatopancreatic necrosis disease (AHPND) typically caused by Vibrio parahaemolyticus harboring the pVA plasmid containing the pirAVp and pirBVp genes, which code for Photorhabdus insect-related (Pir) toxin. The limited genomic resource for V. parahaemolyticus strains from Malaysian aquaculture farms precludes an in-depth understanding of their diversity and evolutionary relationships. In this study, we isolated shrimp-associated and environmental (rearing water) V. parahaemolyticus from three aquaculture farms located in Northern and Central Malaysia followed by whole-genome sequencing of 40 randomly selected isolates on the Illumina MiSeq. Phylogenomic analysis and multilocus sequence typing (MLST) reveal distinct lineages of V. parahaemolyticus that harbor the pirABVp genes. The recovery of pVA plasmid backbone devoid of pirAVp or pirABVp in some V. parahaemolyticus isolates suggests that the toxin genes are prone to deletion. The new insight gained from phylogenomic analysis of Asian V. parahaemolyticus, in addition to the observed genomic instability of pVa plasmid, will have implications for improvements in aquaculture practices to diagnose, treat or limit the impacts of this disease.
    Matched MeSH terms: Computational Biology/methods
  10. Fulltext Mapping a Circular RNA-microRNA-mRNA-Signaling Regulatory Axis That Modulates Stemness Properties of Cancer Stem Cell Populations in Colorectal Cancer Spheroid Cells
    Rengganaten V, Huang CJ, Tsai PH, Wang ML, Yang YP, Lan YT, et al.
    Int J Mol Sci, 2020 Oct 23;21(21).
    PMID: 33114016 DOI: 10.3390/ijms21217864
    Spheroidal cancer cell cultures have been used to enrich cancer stem cells (CSC), which are thought to contribute to important clinical features of tumors. This study aimed to map the regulatory networks driven by circular RNAs (circRNAs) in CSC-enriched colorectal cancer (CRC) spheroid cells. The spheroid cells established from two CRC cell lines acquired stemness properties in pluripotency gene expression and multi-lineage differentiation capacity. Genome-wide sequencing identified 1503 and 636 circRNAs specific to the CRC parental and spheroid cells, respectively. In the CRC spheroids, algorithmic analyses unveiled a core network of mRNAs involved in modulating stemness-associated signaling pathways, driven by a circRNA-microRNA (miRNA)-mRNA axis. The two major circRNAs, hsa_circ_0066631 and hsa_circ_0082096, in this network were significantly up-regulated in expression levels in the spheroid cells. The two circRNAs were predicted to target and were experimentally shown to down-regulate miR-140-3p, miR-224, miR-382, miR-548c-3p and miR-579, confirming circRNA sponging of the targeted miRNAs. Furthermore, the affected miRNAs were demonstrated to inhibit degradation of six mRNA targets, viz. ACVR1C/ALK7, FZD3, IL6ST/GP130, SKIL/SNON, SMAD2 and WNT5, in the CRC spheroid cells. These mRNAs encode proteins that are reported to variously regulate the GP130/Stat, Activin/Nodal, TGF-β/SMAD or Wnt/β-catenin signaling pathways in controlling various aspects of CSC stemness. Using the CRC spheroid cell model, the novel circRNA-miRNA-mRNA axis mapped in this work forms the foundation for the elucidation of the molecular mechanisms of the complex cellular and biochemical processes that determine CSC stemness properties of cancer cells, and possibly for designing therapeutic strategies for CRC treatment by targeting CSC.
    Matched MeSH terms: Computational Biology/methods
  11. Health Equity Assessment Toolkit (HEAT): software for exploring and comparing health inequalities in countries
    Hosseinpoor AR, Nambiar D, Schlotheuber A, Reidpath D, Ross Z
    BMC Med Res Methodol, 2016 10 19;16(1):141.
    PMID: 27760520
    BACKGROUND: It is widely recognised that the pursuit of sustainable development cannot be accomplished without addressing inequality, or observed differences between subgroups of a population. Monitoring health inequalities allows for the identification of health topics where major group differences exist, dimensions of inequality that must be prioritised to effect improvements in multiple health domains, and also population subgroups that are multiply disadvantaged. While availability of data to monitor health inequalities is gradually improving, there is a commensurate need to increase, within countries, the technical capacity for analysis of these data and interpretation of results for decision-making. Prior efforts to build capacity have yielded demand for a toolkit with the computational ability to display disaggregated data and summary measures of inequality in an interactive and customisable fashion that would facilitate interpretation and reporting of health inequality in a given country.

    METHODS: To answer this demand, the Health Equity Assessment Toolkit (HEAT), was developed between 2014 and 2016. The software, which contains the World Health Organization's Health Equity Monitor database, allows the assessment of inequalities within a country using over 30 reproductive, maternal, newborn and child health indicators and five dimensions of inequality (economic status, education, place of residence, subnational region and child's sex, where applicable).

    RESULTS/CONCLUSION: HEAT was beta-tested in 2015 as part of ongoing capacity building workshops on health inequality monitoring. This is the first and only application of its kind; further developments are proposed to introduce an upload data feature, translate it into different languages and increase interactivity of the software. This article will present the main features and functionalities of HEAT and discuss its relevance and use for health inequality monitoring.

    Matched MeSH terms: Computational Biology/methods*
  12. Fulltext Evolutionary and genomic analysis of the caleosin/peroxygenase (CLO/PXG) gene/protein families in the Viridiplantae
    Rahman F, Hassan M, Rosli R, Almousally I, Hanano A, Murphy DJ
    PLoS One, 2018;13(5):e0196669.
    PMID: 29771926 DOI: 10.1371/journal.pone.0196669
    Bioinformatics analyses of caleosin/peroxygenases (CLO/PXG) demonstrated that these genes are present in the vast majority of Viridiplantae taxa for which sequence data are available. Functionally active CLO/PXG proteins with roles in abiotic stress tolerance and lipid droplet storage are present in some Trebouxiophycean and Chlorophycean green algae but are absent from the small number of sequenced Prasinophyceaen genomes. CLO/PXG-like genes are expressed during dehydration stress in Charophyte algae, a sister clade of the land plants (Embryophyta). CLO/PXG-like sequences are also present in all of the >300 sequenced Embryophyte genomes, where some species contain as many as 10-12 genes that have arisen via selective gene duplication. Angiosperm genomes harbour at least one copy each of two distinct CLO/PX isoforms, termed H (high) and L (low), where H-forms contain an additional C-terminal motif of about 30-50 residues that is absent from L-forms. In contrast, species in other Viridiplantae taxa, including green algae, non-vascular plants, ferns and gymnosperms, contain only one (or occasionally both) of these isoforms per genome. Transcriptome and biochemical data show that CLO/PXG-like genes have complex patterns of developmental and tissue-specific expression. CLO/PXG proteins can associate with cytosolic lipid droplets and/or bilayer membranes. Many of the analysed isoforms also have peroxygenase activity and are involved in oxylipin metabolism. The distribution of CLO/PXG-like genes is consistent with an origin >1 billion years ago in at least two of the earliest diverging groups of the Viridiplantae, namely the Chlorophyta and the Streptophyta, after the Viridiplantae had already diverged from other Archaeplastidal groups such as the Rhodophyta and Glaucophyta. While algal CLO/PXGs have roles in lipid packaging and stress responses, the Embryophyte proteins have a much wider spectrum of roles and may have been instrumental in the colonisation of terrestrial habitats and the subsequent diversification as the major land flora.
    Matched MeSH terms: Computational Biology/methods
  13. Comparative genomic and phylogenetic analysis of a toxigenic clinical isolate of Corynebacterium diphtheriae strain B-D-16-78 from Malaysia
    Hong KW, Asmah Hani AW, Nurul Aina Murni CA, Pusparani RR, Chong CK, Verasahib K, et al.
    Infect Genet Evol, 2017 Oct;54:263-270.
    PMID: 28711373 DOI: 10.1016/j.meegid.2017.07.015
    In this study, we report the comparative genomics and phylogenetic analysis of Corynebacterium diphtheriae strain B-D-16-78 that was isolated from a clinical specimen in 2016. The complete genome of C. diphtheriae strain B-D-16-78 was sequenced using PacBio Single Molecule, Real-Time sequencing technology and consists of a 2,474,151-bp circular chromosome with an average GC content of 53.56%. The core genome of C. diphtheriae was also deduced from a total of 74 strains with complete or draft genome sequences and the core genome-based phylogenetic analysis revealed close genetic relationship among strains that shared the same MLST allelic profile. In the context of CRISPR-Cas system, which confers adaptive immunity against re-invading DNA, 73 out of 86 spacer sequences were found to be unique to Malaysian strains which harboured only type-II-C and/or type-I-E-a systems. A total of 48 tox genes which code for the diphtheria toxin were retrieved from the 74 genomes and with the exception of one truncated gene, only nucleotide substitutions were detected when compared to the tox gene sequence of PW8. More than half were synonymous substitution and only two were nonsynonymous substitutions whereby H24Y was predicted to have a damaging effect on the protein function whilst T262V was predicted to be tolerated. Both toxigenic and non-toxigenic toxin-gene bearing strains have been isolated in Malaysia but the repeated isolation of toxigenic strains with the same MLST profile suggests the possibility of some of these strains may be circulating in the population. Hence, efforts to increase herd immunity should be continued and supported by an effective monitoring and surveillance system to track, manage and control outbreak of cases.
    Matched MeSH terms: Computational Biology/methods
  14. Insight into the molecular mechanism of P-glycoprotein mediated drug toxicity induced by bioflavonoids: an integrated computational approach
    Wongrattanakamon P, Lee VS, Nimmanpipug P, Sirithunyalug B, Chansakaow S, Jiranusornkul S
    Toxicol. Mech. Methods, 2017 May;27(4):253-271.
    PMID: 27996361 DOI: 10.1080/15376516.2016.1273428
    In this work, molecular docking, pharmacophore modeling and molecular dynamics (MD) simulation were rendered for the mouse P-glycoprotein (P-gp) (code: 4Q9H) and bioflavonoids; amorphigenin, chrysin, epigallocatechin, formononetin and rotenone including a positive control; verapamil to identify protein-ligand interaction features including binding affinities, interaction characteristics, hot-spot amino acid residues and complex stabilities. These flavonoids occupied the same binding site with high binding affinities and shared the same key residues for their binding interactions and the binding region of the flavonoids was revealed that overlapped the ATP binding region with hydrophobic and hydrophilic interactions suggesting a competitive inhibition mechanism of the compounds. Root mean square deviations (RMSDs) analysis of MD trajectories of the protein-ligand complexes and NBD2 residues, and ligands pointed out these residues were stable throughout the duration of MD simulations. Thus, the applied preliminary structure-based molecular modeling approach of interactions between NBD2 and flavonoids may be gainful to realize the intimate inhibition mechanism of P-gp at NBD2 level and on the basis of the obtained data, it can be concluded that these bioflavonoids have the potential to cause herb-drug interactions or be used as lead molecules for the inhibition of P-gp (as anti-multidrug resistance agents) via the NBD2 blocking mechanism in future.
    Matched MeSH terms: Computational Biology/methods*
  15. Fulltext TranCEP: Predicting the substrate class of transmembrane transport proteins using compositional, evolutionary, and positional information
    Alballa M, Aplop F, Butler G
    PLoS One, 2020;15(1):e0227683.
    PMID: 31935244 DOI: 10.1371/journal.pone.0227683
    Transporters mediate the movement of compounds across the membranes that separate the cell from its environment and across the inner membranes surrounding cellular compartments. It is estimated that one third of a proteome consists of membrane proteins, and many of these are transport proteins. Given the increase in the number of genomes being sequenced, there is a need for computational tools that predict the substrates that are transported by the transmembrane transport proteins. In this paper, we present TranCEP, a predictor of the type of substrate transported by a transmembrane transport protein. TranCEP combines the traditional use of the amino acid composition of the protein, with evolutionary information captured in a multiple sequence alignment (MSA), and restriction to important positions of the alignment that play a role in determining the specificity of the protein. Our experimental results show that TranCEP significantly outperforms the state-of-the-art predictors. The results quantify the contribution made by each type of information used.
    Matched MeSH terms: Computational Biology/methods*
  16. Synthesis, antioxidant activity and bioinformatics studies of L-3-hydroxytyrosine templated N-alkyl/aryl substituted urea/thioureas
    Kollu U, Avula VKR, Vallela S, Pasupuleti VR, Zyryanov GV, Neelam YS, et al.
    Bioorg Chem, 2021 06;111:104837.
    PMID: 33812281 DOI: 10.1016/j.bioorg.2021.104837
    A new series of urea/thiourea derivatives have been efficiently synthesized from the reaction of L-3-hydroxytyrosine with selective isocyanates/isothiocyanates and characterized by Infra-red, proton & carbon-13 nuclear magnetic resonance spectral and mass spectrometry studies. All the synthesized compounds have been screened for their antioxidant activity by 1,1-diphenyl1-2-picrylhydrazyl radical assay, ferric reducing antioxidant power assay and also studied their molecular docking interaction profiles against 1N8Q and 3NRZ enzymatic proteins. The in vitro antioxidant activity has further supported by quantitative structure activity relationship, absorption, distribution, metabolism, and excretion & toxicity studies, bioactivity studies & enzyme inhibition assay and identified that they were potentially bound to ASP490 & ASP361 aminoacid residue in chain A of 1N8Q protein and GLN1194 aminoacid residue in chain L of 3NRZ protein and are responsible for potential antioxidant activity. It is proved that urea derivatives linked with 4-fluoro & 4-nitro and thiourea derivatives linked with 3-chloro & 4-fluoro have exhibited promising antioxidant activity. In eventual synthesized compounds have been identified as potential blood-brain barrier penetrable compounds and proficient central nervous system active neuro-protective antioxidant agents as they have envisaged as easily penetrable to blood-brain barrier thresholds, a neuroprotective property.
    Matched MeSH terms: Computational Biology*
  17. Fulltext Comparative genome-wide analysis of WRKY, MADS-box and MYB transcription factor families in Arabidopsis and rice
    Abdullah-Zawawi MR, Ahmad-Nizammuddin NF, Govender N, Harun S, Mohd-Assaad N, Mohamed-Hussein ZA
    Sci Rep, 2021 10 04;11(1):19678.
    PMID: 34608238 DOI: 10.1038/s41598-021-99206-y
    Transcription factors (TFs) form the major class of regulatory genes and play key roles in multiple plant stress responses. In most eukaryotic plants, transcription factor (TF) families (WRKY, MADS-box and MYB) activate unique cellular-level abiotic and biotic stress-responsive strategies, which are considered as key determinants for defense and developmental processes. Arabidopsis and rice are two important representative model systems for dicot and monocot plants, respectively. A comprehensive comparative study on 101 OsWRKY, 34 OsMADS box and 122 OsMYB genes (rice genome) and, 71 AtWRKY, 66 AtMADS box and 144 AtMYB genes (Arabidopsis genome) showed various relationships among TFs across species. The phylogenetic analysis clustered WRKY, MADS-box and MYB TF family members into 10, 7 and 14 clades, respectively. All clades in WRKY and MYB TF families and almost half of the total number of clades in the MADS-box TF family are shared between both species. Chromosomal and gene structure analysis showed that the Arabidopsis-rice orthologous TF gene pairs were unevenly localized within their chromosomes whilst the distribution of exon-intron gene structure and motif conservation indicated plausible functional similarity in both species. The abiotic and biotic stress-responsive cis-regulatory element type and distribution patterns in the promoter regions of Arabidopsis and rice WRKY, MADS-box and MYB orthologous gene pairs provide better knowledge on their role as conserved regulators in both species. Co-expression network analysis showed the correlation between WRKY, MADs-box and MYB genes in each independent rice and Arabidopsis network indicating their role in stress responsiveness and developmental processes.
    Matched MeSH terms: Computational Biology/methods
  18. Cupriavidus malaysiensis sp. nov., a novel poly(3-hydroxybutyrate-co-4-hydroxybutyrate) accumulating bacterium isolated from the Malaysian environment
    Ramachandran H, Shafie NAH, Sudesh K, Azizan MN, Majid MIA, Amirul AA
    Antonie Van Leeuwenhoek, 2018 Mar;111(3):361-372.
    PMID: 29022146 DOI: 10.1007/s10482-017-0958-8
    Bacterial classification on the basis of a polyphasic approach was conducted on three poly(3 hydroxybutyrate-co-4-hydroxybutyrate) [P(3HB-co-4HB)] accumulating bacterial strains that were isolated from samples collected from Malaysian environments; Kulim Lake, Sg. Pinang river and Sg. Manik paddy field. The Gram-negative, rod-shaped, motile, non-sporulating and non-fermenting bacteria were shown to belong to the genus Cupriavidus of the Betaproteobacteria on the basis of their 16S rRNA gene sequence analyses. The sequence similarity value with their near phylogenetic neighbour, Cupriavidus pauculus LMG3413T, was 98.5%. However, the DNA-DNA hybridization values (8-58%) and ribotyping analysis both enabled these strains to be differentiated from related Cupriavidus species with validly published names. The RiboPrint patterns of the three strains also revealed that the strains were genetically related even though they displayed a clonal diversity. The major cellular fatty acids detected in these strains included C15:0 ISO 2OH/C16:1 ω7c, hexadecanoic (16:0) and cis-11-octadecenoic (C18:1 ω7c). Their G+C contents ranged from 68.0  to 68.6 mol%, and their major isoprenoid quinone was Ubiquinone Q-8. Of these three strains, only strain USMAHM13 (= DSM 25816 = KCTC 32390) was discovered to exhibit yellow pigmentation that is characteristic of the carotenoid family. Their assembled genomes also showed that the three strains were not identical in terms of their genome sizes that were 7.82, 7.95 and 8.70 Mb for strains USMAHM13, USMAA1020 and USMAA2-4, respectively, which are slightly larger than that of Cupriavidus necator H16 (7.42 Mb). The average nucleotide identity (ANI) results indicated that the strains were genetically related and the genome pairs belong to the same species. On the basis of the results obtained in this study, the three strains are considered to represent a novel species for which the name Cupriavidus malaysiensis sp. nov. is proposed. The type strain of the species is USMAA1020T (= DSM 19416T = KCTC 32390T).
    Matched MeSH terms: Computational Biology/methods
  19. From discovery to spread: The evolution and phylogeny of Getah virus
    Li YY, Liu H, Fu SH, Li XL, Guo XF, Li MH, et al.
    Infect Genet Evol, 2017 11;55:48-55.
    PMID: 28827175 DOI: 10.1016/j.meegid.2017.08.016
    Getah virus (GETV) was first isolated in Malaysia in 1955. Since then, epidemics in horses and pigs caused by GETV have resulted in huge economic losses. At present, GETV has spread across Eurasia and Southeast Asia, including mainland China, Korea, Japan, Mongolia, and Russia. Data show that the Most Recent Common Ancestor (MRCA) of GETV existed about 145years ago (95% HPD: 75-244) and gradually evolved into four distinct evolutionary populations: Groups I-IV. The MRCA of GETVs in Group III, which includes all GETVs isolated from mosquitoes, pigs, horses, and other animals since the 1960s (from latitude 19°N to 60°N), existed about 51years ago (95% HPD: 51-72). Group III is responsible for most viral epidemics among domestic animals. An analysis of the GETV E2 protein sequence and structure revealed seven common amino acid mutation sites. These sites are responsible for the structural and electrostatic differences detected between widespread Group III isolates and the prototype strain MM2021. These differences may account for the recent geographical radiation of the virus. Considering the economic significance of GETV infection in pigs and horses, we recommend the implementation of strict viral screening and monitoring programs.
    Matched MeSH terms: Computational Biology/methods
  20. Gene isolation using degenerate primers targeting protein motif: A laboratory exercise
    Yeo BPH, Foong LC, Tam SM, Lee V, Hwang SS
    Biochem Mol Biol Educ, 2018 01;46(1):47-53.
    PMID: 29131478 DOI: 10.1002/bmb.21089
    Structures and functions of protein motifs are widely included in many biology-based course syllabi. However, little emphasis is placed to link this knowledge to applications in biotechnology to enhance the learning experience. Here, the conserved motifs of nucleotide binding site-leucine rich repeats (NBS-LRR) proteins, successfully used for the isolation and characterization of many plant resistance gene analogues (RGAs), is featured in the development of a series of laboratory experiments using important molecular biology techniques. A set of previously isolated RGA sequences is used as the model for performing sequence alignment and visualising 3D protein structure using current bioinformatics programs (Clustal Omega and Argusdock software). A pair of established degenerate primer sequences is provided for the prediction of targeted amino acids sequences in the RGAs. Reverse transcription-polymerase chain reaction (RT-PCR) is used to amplify RGAs from total RNA samples extracted from the tropical wild relative of black pepper, Piper colubrinum (Piperaceae). This laboratory exercise enables students to correlate specific DNA sequences with respective amino acid codes and the interaction between conserved motifs of resistance genes with putatively targeted proteins. © 2017 by The International Union of Biochemistry and Molecular Biology, 46(1):47-53, 2018.
    Matched MeSH terms: Computational Biology/education
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