Displaying publications 1 - 20 of 90 in total

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  1. Fulltext Computational prediction of changes in brain metabolic fluxes during Parkinson's disease from mRNA expression
    Supandi F, van Beek JHGM
    PLoS One, 2018;13(9):e0203687.
    PMID: 30208076 DOI: 10.1371/journal.pone.0203687
    BACKGROUND: Parkinson's disease is a widespread neurodegenerative disorder which affects brain metabolism. Although changes in gene expression during disease are often measured, it is difficult to predict metabolic fluxes from gene expression data. Here we explore the hypothesis that changes in gene expression for enzymes tend to parallel flux changes in biochemical reaction pathways in the brain metabolic network. This hypothesis is the basis of a computational method to predict metabolic flux changes from post-mortem gene expression measurements in Parkinson's disease (PD) brain.

    RESULTS: We use a network model of central metabolism and optimize the correspondence between relative changes in fluxes and in gene expression. To this end we apply the Least-squares with Equalities and Inequalities algorithm integrated with Flux Balance Analysis (Lsei-FBA). We predict for PD (1) decreases in glycolytic rate and oxygen consumption and an increase in lactate production in brain cortex that correspond with measurements (2) relative flux decreases in ATP synthesis, in the malate-aspartate shuttle and midway in the TCA cycle that are substantially larger than relative changes in glucose uptake in the substantia nigra, dopaminergic neurons and most other brain regions (3) shifts in redox shuttles between cytosol and mitochondria (4) in contrast to Alzheimer's disease: little activation of the gamma-aminobutyric acid shunt pathway in compensation for decreased alpha-ketoglutarate dehydrogenase activity (5) in the globus pallidus internus, metabolic fluxes are increased, reflecting increased functional activity.

    CONCLUSION: Our method predicts metabolic changes from gene expression data that correspond in direction and order of magnitude with presently available experimental observations during Parkinson's disease, indicating that the hypothesis may be useful for some biochemical pathways. Lsei-FBA generates predictions of flux distributions in neurons and small brain regions for which accurate metabolic flux measurements are not yet possible.

    Matched MeSH terms: Metabolic Networks and Pathways
  2. Fulltext Using bioconductor package BiGGR for metabolic flux estimation based on gene expression changes in brain
    Gavai AK, Supandi F, Hettling H, Murrell P, Leunissen JA, van Beek JH
    PLoS One, 2015;10(3):e0119016.
    PMID: 25806817 DOI: 10.1371/journal.pone.0119016
    Predicting the distribution of metabolic fluxes in biochemical networks is of major interest in systems biology. Several databases provide metabolic reconstructions for different organisms. Software to analyze flux distributions exists, among others for the proprietary MATLAB environment. Given the large user community for the R computing environment, a simple implementation of flux analysis in R appears desirable and will facilitate easy interaction with computational tools to handle gene expression data. We extended the R software package BiGGR, an implementation of metabolic flux analysis in R. BiGGR makes use of public metabolic reconstruction databases, and contains the BiGG database and the reconstruction of human metabolism Recon2 as Systems Biology Markup Language (SBML) objects. Models can be assembled by querying the databases for pathways, genes or reactions of interest. Fluxes can then be estimated by maximization or minimization of an objective function using linear inverse modeling algorithms. Furthermore, BiGGR provides functionality to quantify the uncertainty in flux estimates by sampling the constrained multidimensional flux space. As a result, ensembles of possible flux configurations are constructed that agree with measured data within precision limits. BiGGR also features automatic visualization of selected parts of metabolic networks using hypergraphs, with hyperedge widths proportional to estimated flux values. BiGGR supports import and export of models encoded in SBML and is therefore interoperable with different modeling and analysis tools. As an application example, we calculated the flux distribution in healthy human brain using a model of central carbon metabolism. We introduce a new algorithm termed Least-squares with equalities and inequalities Flux Balance Analysis (Lsei-FBA) to predict flux changes from gene expression changes, for instance during disease. Our estimates of brain metabolic flux pattern with Lsei-FBA for Alzheimer's disease agree with independent measurements of cerebral metabolism in patients. This second version of BiGGR is available from Bioconductor.
    Matched MeSH terms: Metabolic Networks and Pathways*
  3. Identification of gene knockout strategies using a hybrid of an ant colony optimization algorithm and flux balance analysis to optimize microbial strains
    Lu SJ, Salleh AH, Mohamad MS, Deris S, Omatu S, Yoshioka M
    Comput Biol Chem, 2014 12;53PB:175-183.
    PMID: 25462325 DOI: 10.1016/j.compbiolchem.2014.09.008
    Reconstructions of genome-scale metabolic networks from different organisms have become popular in recent years. Metabolic engineering can simulate the reconstruction process to obtain desirable phenotypes. In previous studies, optimization algorithms have been implemented to identify the near-optimal sets of knockout genes for improving metabolite production. However, previous works contained premature convergence and the stop criteria were not clear for each case. Therefore, this study proposes an algorithm that is a hybrid of the ant colony optimization algorithm and flux balance analysis (ACOFBA) to predict near optimal sets of gene knockouts in an effort to maximize growth rates and the production of certain metabolites. Here, we present a case study that uses Baker's yeast, also known as Saccharomyces cerevisiae, as the model organism and target the rate of vanillin production for optimization. The results of this study are the growth rate of the model organism after gene deletion and a list of knockout genes. The ACOFBA algorithm was found to improve the yield of vanillin in terms of growth rate and production compared with the previous algorithms.
    Matched MeSH terms: Metabolic Networks and Pathways
  4. Fulltext Leptin and Associated Mediators of Immunometabolic Signaling: Novel Molecular Outcome Measures for Neurostimulation to Treat Chronic Pain
    Kinfe TM, Buchfelder M, Chaudhry SR, Chakravarthy KV, Deer TR, Russo M, et al.
    Int J Mol Sci, 2019 Sep 24;20(19).
    PMID: 31554241 DOI: 10.3390/ijms20194737
    Chronic pain is a devastating condition affecting the physical, psychological, and socioeconomic status of the patient. Inflammation and immunometabolism play roles in the pathophysiology of chronic pain disorders. Electrical neuromodulation approaches have shown a meaningful success in otherwise drug-resistant chronic pain conditions, including failed back surgery, neuropathic pain, and migraine. A literature review (PubMed, MEDLINE/OVID, SCOPUS, and manual searches of the bibliographies of known primary and review articles) was performed using the following search terms: chronic pain disorders, systemic inflammation, immunometabolism, prediction, biomarkers, metabolic disorders, and neuromodulation for chronic pain. Experimental studies indicate a relationship between the development and maintenance of chronic pain conditions and a deteriorated immunometabolic state mediated by circulating cytokines, chemokines, and cellular components. A few uncontrolled in-human studies found increased levels of pro-inflammatory cytokines known to drive metabolic disorders in chronic pain patients undergoing neurostimulation therapies. In this narrative review, we summarize the current knowledge and possible relationships of available neurostimulation therapies for chronic pain with mediators of central and peripheral neuroinflammation and immunometabolism on a molecular level. However, to address the needs for predictive factors and biomarkers, large-scale databank driven clinical trials are needed to determine the clinical value of molecular profiling.
    Matched MeSH terms: Metabolic Networks and Pathways*
  5. Fulltext Transcriptome analysis of chicken intraepithelial lymphocyte natural killer cells infected with very virulent infectious bursal disease virus
    Boo SY, Tan SW, Alitheen NB, Ho CL, Omar AR, Yeap SK
    Sci Rep, 2020 10 27;10(1):18348.
    PMID: 33110122 DOI: 10.1038/s41598-020-75340-x
    The infectious bursal disease (IBD) is an acute immunosuppressive viral disease that significantly affects the economics of the poultry industry. The IBD virus (IBDV) was known to infect B lymphocytes and activate macrophage and T lymphocytes, but there are limited studies on the impact of IBDV infection on chicken intraepithelial lymphocyte natural killer (IEL-NK) cells. This study employed an mRNA sequencing approach to investigate the early regulation of gene expression patterns in chicken IEL-NK cells after infection with very virulent IBDV strain UPM0081. A total of 12,141 genes were expressed in uninfected chicken IEL-NK cells, and most of the genes with high expression were involved in the metabolic pathway, whereas most of the low expressed genes were involved in the cytokine-cytokine receptor pathway. A total of 1,266 genes were differentially expressed (DE) at 3 day-post-infection (dpi), and these DE genes were involved in inflammation, antiviral response and interferon stimulation. The innate immune response was activated as several genes involved in inflammation, antiviral response and recruitment of NK cells to the infected area were up-regulated. This is the first study to examine the whole transcriptome profile of chicken NK cells towards IBDV infection and provides better insight into the early immune response of chicken NK cells.
    Matched MeSH terms: Metabolic Networks and Pathways
  6. Temporal proteomic profiling of Chlamydia trachomatis-infected HeLa-229 human cervical epithelial cells
    Tan GM, Lim HJ, Yeow TC, Movahed E, Looi CY, Gupta R, et al.
    Proteomics, 2016 05;16(9):1347-60.
    PMID: 27134121 DOI: 10.1002/pmic.201500219
    Chlamydia trachomatis is the leading causative agent of bacterial sexually transmitted infections worldwide which can lead to female pelvic inflammatory disease and infertility. A greater understanding of host response during chlamydial infection is essential to design intervention technique to reduce the increasing incidence rate of genital chlamydial infection. In this study, we investigated proteome changes in epithelial cells during C. trachomatis infection by using an isobaric tags for relative and absolute quantitation (iTRAQ) labeling technique coupled with a liquid chromatography-tandem mass spectrometry (LC-MS(3) ) analysis. C. trachomatis (serovar D, MOI 1)-infected HeLa-229 human cervical carcinoma epithelial cells (at 2, 4 and 8 h) showed profound modifications of proteome profile which involved 606 host proteins. MGST1, SUGP2 and ATXN10 were among the top in the list of the differentially upregulated protein. Through pathway analysis, we suggested the involvement of eukaryotic initiation factor 2 (eIF2) and mammalian target of rapamycin (mTOR) in host cells upon C. trachomatis infection. Network analysis underscored the participation of DNA repair mechanism during C. trachomatis infection. In summary, intense modifications of proteome profile in C. trachomatis-infected HeLa-229 cells indicate complex host-pathogen interactions at early phase of chlamydial infection.
    Matched MeSH terms: Metabolic Networks and Pathways/genetics
  7. Iron-associated protein interaction networks reveal the key functional modules related to survival and virulence of Pasteurella multocida
    Jatuponwiphat T, Chumnanpuen P, Othman S, E-Kobon T, Vongsangnak W
    Microb Pathog, 2019 Feb;127:257-266.
    PMID: 30550841 DOI: 10.1016/j.micpath.2018.12.013
    Pasteurella multocida causes respiratory infectious diseases in a multitude of birds and mammals. A number of virulence-associated genes were reported across different strains of P. multocida, including those involved in the iron transport and metabolism. Comparative iron-associated genes of P. multocida among different animal hosts towards their interaction networks have not been fully revealed. Therefore, this study aimed to identify the iron-associated genes from core- and pan-genomes of fourteen P. multocida strains and to construct iron-associated protein interaction networks using genome-scale network analysis which might be associated with the virulence. Results showed that these fourteen strains had 1587 genes in the core-genome and 3400 genes constituting their pan-genome. Out of these, 2651 genes associated with iron transport and metabolism were selected to construct the protein interaction networks and 361 genes were incorporated into the iron-associated protein interaction network (iPIN) consisting of nine different iron-associated functional modules. After comparing with the virulence factor database (VFDB), 21 virulence-associated proteins were determined and 11 of these belonged to the heme biosynthesis module. From this study, the core heme biosynthesis module and the core outer membrane hemoglobin receptor HgbA were proposed as candidate targets to design novel antibiotics and vaccines for preventing pasteurellosis across the serotypes or animal hosts for enhanced precision agriculture to ensure sustainability in food security.
    Matched MeSH terms: Metabolic Networks and Pathways/genetics
  8. Fulltext Infection of Burkholderia cepacia induces homeostatic responses in the host for their prolonged survival: the microarray perspective
    Mariappan V, Vellasamy KM, Thimma J, Hashim OH, Vadivelu J
    PLoS One, 2013;8(10):e77418.
    PMID: 24116227 DOI: 10.1371/journal.pone.0077418
    Burkholderia cepacia is an opportunistic human pathogen associated with life-threatening pulmonary infections in immunocompromised individuals. Pathogenesis of B. cepacia infection involves adherence, colonisation, invasion, survival and persistence in the host. In addition, B. cepacia are also known to secrete factors, which are associated with virulence in the pathogenesis of the infection. In this study, the host factor that may be the cause of the infection was elucidated in human epithelial cell line, A549, that was exposed to live B. cepacia (mid-log phase) and its secretory proteins (mid-log and early-stationary phases) using the Illumina Human Ref-8 microarray platform. The non-infection A549 cells were used as a control. Expression of the host genes that are related to apoptosis, inflammation and cell cycle as well as metabolic pathways were differentially regulated during the infection. Apoptosis of the host cells and secretion of pro-inflammatory cytokines were found to be inhibited by both live B. cepacia and its secretory proteins. In contrast, the host cell cycle and metabolic processes, particularly glycolysis/glycogenesis and fatty acid metabolism were transcriptionally up-regulated during the infection. Our microarray analysis provided preliminary insights into mechanisms of B. cepacia pathogenesis. The understanding of host response to an infection would provide novel therapeutic targets both for enhancing the host's defences and repressing detrimental responses induced by the invading pathogen.
    Matched MeSH terms: Metabolic Networks and Pathways
  9. Fulltext Elucidation of the Metabolic Network of Helicobacter pylori J99 and Malaysian Clinical Strains by Phenotype Microarray
    Lee WC, Goh KL, Loke MF, Vadivelu J
    Helicobacter, 2017 Feb;22(1).
    PMID: 27258354 DOI: 10.1111/hel.12321
    Helicobacter pylori colonizes almost half of the human population worldwide. H. pylori strains are genetically diverse, and the specific genotypes are associated with various clinical manifestations including gastric adenocarcinoma, peptic ulcer disease (PUD), and nonulcer dyspepsia (NUD). However, our current knowledge of the H. pylori metabolism is limited. To understand the metabolic differences among H. pylori strains, we investigated four Malaysian H. pylori clinical strains, which had been previously sequenced, and a standard strain, H. pylori J99, at the phenotypic level.
    Matched MeSH terms: Metabolic Networks and Pathways*
  10. Fulltext Tocotrienol-Rich Fraction of Palm Oil Improves Behavioral Impairments and Regulates Metabolic Pathways in AβPP/PS1 Mice
    Durani LW, Hamezah HS, Ibrahim NF, Yanagisawa D, Nasaruddin ML, Mori M, et al.
    J Alzheimers Dis, 2018;64(1):249-267.
    PMID: 29889072 DOI: 10.3233/JAD-170880
    We have recently shown that the tocotrienol-rich fraction (TRF) of palm oil, a mixture of vitamin E analogs, improves amyloid pathology in vitro and in vivo. However, precise mechanisms remain unknown. In this study, we examined the effects of long-term (10 months) TRF treatment on behavioral impairments and brain metabolites in (15 months old) AβPP/PS1 double transgenic (Tg) Alzheimer's disease (AD) mice. The open field test, Morris water maze, and novel object recognition tasks revealed improved exploratory activity, spatial learning, and recognition memory, respectively, in TRF-treated Tg mice. Brain metabolite profiling of wild-type and Tg mice treated with and without TRF was performed using ultrahigh performance liquid chromatography (UHPLC) coupled to high-resolution accurate mass (HRAM)-orbitrap tandem mass spectrometry (MS/MS). Metabolic pathway analysis found perturbed metabolic pathways that linked to AD. TRF treatment partly ameliorated metabolic perturbations in Tg mouse hippocampus. The mechanism of this pre-emptive activity may occur via modulation of metabolic pathways dependent on Aβ interaction or independent of Aβ interaction.
    Matched MeSH terms: Metabolic Networks and Pathways/drug effects*; Metabolic Networks and Pathways/physiology
  11. Fulltext Variable Responses to Carbon Utilization between Planktonic and Biofilm Cells of a Human Carrier Strain of Salmonella enterica Serovar Typhi
    Kalai Chelvam K, Yap KP, Chai LC, Thong KL
    PLoS One, 2015;10(5):e0126207.
    PMID: 25946205 DOI: 10.1371/journal.pone.0126207
    Salmonella enterica serovar Typhi (S. Typhi) is a foodborne pathogen that causes typhoid fever and infects only humans. The ability of S. Typhi to survive outside the human host remains unclear, particularly in human carrier strains. In this study, we have investigated the catabolic activity of a human carrier S. Typhi strain in both planktonic and biofilm cells using the high-throughput Biolog Phenotype MicroArray, Minimum Biofilm Eradication Concentration (MBEC) biofilm inoculator (96-well peg lid) and whole genome sequence data. Additional strains of S. Typhi were tested to further validate the variation of catabolism in selected carbon substrates in the different bacterial growth phases. The analyzes of the carbon utilization data indicated that planktonic cells of the carrier strain, S. Typhi CR0044 could utilize a broader range of carbon substrates compared to biofilm cells. Pyruvic acid and succinic acid which are related to energy metabolism were actively catabolised in the planktonic stage compared to biofilm stage. On the other hand, glycerol, L-fucose, L-rhamnose (carbohydrates) and D-threonine (amino acid) were more actively catabolised by biofilm cells compared to planktonic cells. Notably, dextrin and pectin could induce strong biofilm formation in the human carrier strain of S. Typhi. However, pectin could not induce formation of biofilm in the other S. Typhi strains. Phenome data showed the utilization of certain carbon substrates which was supported by the presence of the catabolism-associated genes in S. Typhi CR0044. In conclusion, the findings showed the differential carbon utilization between planktonic and biofilm cells of a S. Typhi human carrier strain. The differences found in the carbon utilization profiles suggested that S. Typhi uses substrates mainly found in the human biliary mucus glycoprotein, gallbladder, liver and cortex of the kidney of the human host. The observed diversity in the carbon catabolism profiles among different S. Typhi strains has suggested the possible involvement of various metabolic pathways that might be related to the virulence and pathogenesis of this host-restricted human pathogen. The data serve as a caveat for future in-vivo studies to investigate the carbon metabolic activity to the pathogenesis of S. Typhi.
    Matched MeSH terms: Metabolic Networks and Pathways
  12. Enhanced biogas production from municipal solid waste via co-digestion with sewage sludge and metabolic pathway analysis
    Ghosh P, Kumar M, Kapoor R, Kumar SS, Singh L, Vijay V, et al.
    Bioresour Technol, 2020 Jan;296:122275.
    PMID: 31683109 DOI: 10.1016/j.biortech.2019.122275
    The present study intends to evaluate the potential of co-digestion for utilizing Organic fraction of Municipal Solid Waste (OFMSW) and sewage sludge (SS) for enhanced biogas production. Metagenomic analysis was performed to identify the dominant bacteria, archaea and fungi, changes in their communities with time and their functional roles during the course of anaerobic digestion (AD). The cumulative biogas yield of 586.2 mL biogas/gVS with the highest methane concentration of 69.5% was observed under an optimum ratio of OFMSW:SS (40:60 w/w). Bacteria and fungi were found to be majorly involved in hydrolysis and initial stages of AD. Probably, the most common archaea Methanosarsina sp. primarily followed the acetoclastic pathway. The hydrogenotrophic pathway was less followed as indicated by the reduction in abundance of syntrophic acetate oxidizers. An adequate understanding of microbial communities is important to manipulate and inoculate the specific microbial consortia to maximize CH4 production through AD.
    Matched MeSH terms: Metabolic Networks and Pathways
  13. Fulltext Integrative Roles of Dopamine Pathway and Calcium Channels Reveal a Link between Schizophrenia and Opioid Use Disorder
    Thiagarajan SK, Mok SY, Ogawa S, Parhar IS, Tang PY
    Int J Mol Sci, 2023 Feb 17;24(4).
    PMID: 36835497 DOI: 10.3390/ijms24044088
    Several theories have been proposed to explain the mechanisms of substance use in schizophrenia. Brain neurons pose a potential to provide novel insights into the association between opioid addiction, withdrawal, and schizophrenia. Thus, we exposed zebrafish larvae at 2 days post-fertilization (dpf) to domperidone (DPM) and morphine, followed by morphine withdrawal. Drug-induced locomotion and social preference were assessed, while the level of dopamine and the number of dopaminergic neurons were quantified. In the brain tissue, the expression levels of genes associated with schizophrenia were measured. The effects of DMP and morphine were compared to vehicle control and MK-801, a positive control to mimic schizophrenia. Gene expression analysis revealed that α1C, α1Sa, α1Aa, drd2a, and th1 were up-regulated after 10 days of exposure to DMP and morphine, while th2 was down-regulated. These two drugs also increased the number of positive dopaminergic neurons and the total dopamine level but reduced the locomotion and social preference. The termination of morphine exposure led to the up-regulation of th2, drd2a, and c-fos during the withdrawal phase. Our integrated data implicate that the dopamine system plays a key role in the deficits in social behavior and locomotion that are common in the schizophrenia-like symptoms and opioid dependence.
    Matched MeSH terms: Metabolic Networks and Pathways
  14. The cellular and molecular processes associated with scopolamine-induced memory deficit: A model of Alzheimer's biomarkers
    Tang KS
    Life Sci, 2019 Sep 15;233:116695.
    PMID: 31351082 DOI: 10.1016/j.lfs.2019.116695
    Alzheimer's disease (AD) is neurodegenerative disorder that is associated with memory and cognitive decline in the older adults. Scopolamine is commonly used as a behavioral model in studying cognitive disorders including AD. Many studies have also concurrently examined the neurochemical mechanisms underlying the behavioral modifications by scopolamine treatment. Nonetheless, the scopolamine model has not become a standard tool in the early assessment of drugs. Furthermore, the use of scopolamine as a pharmacological model to study AD remains debatable. This report reviews the scopolamine-induced cellular and molecular changes and discusses how these changes relate to AD pathogenesis.
    Matched MeSH terms: Metabolic Networks and Pathways/drug effects*
  15. Fulltext RNA sequencing of kidney and liver transcriptome obtained from wild cynomolgus macaque (Macaca fascicularis) originating from Peninsular Malaysia
    Ee Uli J, Yong CS, Yeap SK, Alitheen NB, Rovie-Ryan JJ, Mat Isa N, et al.
    BMC Res Notes, 2018 Dec 22;11(1):923.
    PMID: 30577850 DOI: 10.1186/s13104-018-4014-1
    OBJECTIVE: Using high-throughput RNA sequencing technology, this study aimed to sequence the transcriptome of kidney and liver tissues harvested from Peninsular Malaysia cynomolgus macaque (Macaca fascicularis). M. fascicularis are significant nonhuman primate models in the biomedical field, owing to the macaque's biological similarities with humans. The additional transcriptomic dataset will supplement the previously described Peninsular Malaysia M. fascicularis transcriptomes obtained in a past endeavour.

    RESULTS: A total of 75,350,240 sequence reads were obtained via Hi-seq 2500 sequencing technology. A total of 5473 significant differentially expressed genes were called. Gene ontology functional categorisation showed that cellular process, catalytic activity, and cell part categories had the highest number of expressed genes, while the metabolic pathways category possessed the highest number of expressed genes in the KEGG pathway analysis. The additional sequence dataset will further enrich existing M. fascicularis transcriptome assemblies, and provide a dataset for further downstream studies.

    Matched MeSH terms: Metabolic Networks and Pathways
  16. Fulltext Recent Understanding of Soil Acidobacteria and Their Ecological Significance: A Critical Review
    Kalam S, Basu A, Ahmad I, Sayyed RZ, El-Enshasy HA, Dailin DJ, et al.
    Front Microbiol, 2020;11:580024.
    PMID: 33193209 DOI: 10.3389/fmicb.2020.580024
    Acidobacteria represents an underrepresented soil bacterial phylum whose members are pervasive and copiously distributed across nearly all ecosystems. Acidobacterial sequences are abundant in soils and represent a significant fraction of soil microbial community. Being recalcitrant and difficult-to-cultivate under laboratory conditions, holistic, polyphasic approaches are required to study these refractive bacteria extensively. Acidobacteria possesses an inventory of genes involved in diverse metabolic pathways, as evidenced by their pan-genomic profiles. Because of their preponderance and ubiquity in the soil, speculations have been made regarding their dynamic roles in vital ecological processes viz., regulation of biogeochemical cycles, decomposition of biopolymers, exopolysaccharide secretion, and plant growth promotion. These bacteria are expected to have genes that might help in survival and competitive colonization in the rhizosphere, leading to the establishment of beneficial relationships with plants. Exploration of these genetic attributes and more in-depth insights into the belowground mechanics and dynamics would lead to a better understanding of the functions and ecological significance of this enigmatic phylum in the soil-plant environment. This review is an effort to provide a recent update into the diversity of genes in Acidobacteria useful for characterization, understanding ecological roles, and future biotechnological perspectives.
    Matched MeSH terms: Metabolic Networks and Pathways
  17. Biodegradation of poly (vinyl alcohol) by an orychophragmus rhizosphere-associated fungus Penicillium brevicompactum OVR-5, and its proposed PVA biodegradation pathway
    Mohamed H, Shah AM, Nazir Y, Naz T, Nosheen S, Song Y
    World J Microbiol Biotechnol, 2021 Dec 06;38(1):10.
    PMID: 34866162 DOI: 10.1007/s11274-021-03197-x
    In recent years, the utilisation of endophytes has emerged as a promising biological treatment technology for the degradation of plastic wastes such as biodegradation of synthetic plastics. This study, therefore, aimed to explore and extensively screen endophytic fungi (from selected plants) for efficient in vitro polyvinyl alcohol (PVA) biodegradation. In total, 76 endophytic fungi were isolated and cultivated on a PVA screening agar medium. Among these fungi, 10 isolates showed potential and were subsequently identified based on phenotypical characteristics, ITS ribosomal gene sequences, and phylogenetic analyses. Four strains exhibited a maximum level of PVA-degradation in the liquid medium when cultivated for 10 days at 28 °C and 150 rpm. These strains showed varied PVA removal rates of 81% (Penicillium brevicompactum OVR-5), 67% (Talaromyces verruculosus PRL-2), 52% (P. polonicum BJL-9), and 41% (Aspergillus tubingensis BJR-6) respectively. The most promising PVA biodegradation isolate 'OVR-5', with an optimal pH at 7.0 and optimal temperature at 30 °C, produced lipase, manganese peroxidase, and laccase enzymes. Based on analyses of its metabolic intermediates, as identified with GC-MS, we proposed the potential PVA degradation pathway of OVR-5. Biodegradation results were confirmed through scanning electron microscopy and Fourier transform infrared spectroscopy. This study provides the first report on an endophytic P. brevicompactum strain (associated with Orychophragmus violaceus) that has a great ability for PVA degradation providing more insight on potential fungus-based applications in plastic waste degradation.
    Matched MeSH terms: Metabolic Networks and Pathways
  18. Fulltext Comparison of Optimization-Modelling Methods for Metabolites Production in Escherichia coli
    Lee MK, Mohamad MS, Choon YW, Mohd Daud K, Nasarudin NA, Ismail MA, et al.
    J Integr Bioinform, 2020 May 06;17(1).
    PMID: 32374287 DOI: 10.1515/jib-2019-0073
    The metabolic network is the reconstruction of the metabolic pathway of an organism that is used to represent the interaction between enzymes and metabolites in genome level. Meanwhile, metabolic engineering is a process that modifies the metabolic network of a cell to increase the production of metabolites. However, the metabolic networks are too complex that cause problem in identifying near-optimal knockout genes/reactions for maximizing the metabolite's production. Therefore, through constraint-based modelling, various metaheuristic algorithms have been improvised to optimize the desired phenotypes. In this paper, PSOMOMA was compared with CSMOMA and ABCMOMA for maximizing the production of succinic acid in E. coli. Furthermore, the results obtained from PSOMOMA were validated with results from the wet lab experiment.
    Matched MeSH terms: Metabolic Networks and Pathways
  19. Fulltext Expression of fatty acid and triacylglycerol synthesis genes in interspecific hybrids of oil palm
    Ting NC, Sherbina K, Khoo JS, Kamaruddin K, Chan PL, Chan KL, et al.
    Sci Rep, 2020 10 01;10(1):16296.
    PMID: 33004875 DOI: 10.1038/s41598-020-73170-5
    Evaluation of transcriptome data in combination with QTL information has been applied in many crops to study the expression of genes responsible for specific phenotypes. In oil palm, the mesocarp oil extracted from E. oleifera × E. guineensis interspecific hybrids is known to have lower palmitic acid (C16:0) content compared to pure African palms. The present study demonstrates the effectiveness of transcriptome data in revealing the expression profiles of genes in the fatty acid (FA) and triacylglycerol (TAG) biosynthesis processes in interspecific hybrids. The transcriptome assembly yielded 43,920 putative genes of which a large proportion were homologous to known genes in the public databases. Most of the genes encoding key enzymes involved in the FA and TAG synthesis pathways were identified. Of these, 27, including two candidate genes located within the QTL associated with C16:0 content, showed differential expression between developmental stages, populations and/or palms with contrasting C16:0 content. Further evaluation using quantitative real-time PCR revealed that differentially expressed patterns are generally consistent with those observed in the transcriptome data. Our results also suggest that different isoforms are likely to be responsible for some of the variation observed in FA composition of interspecific hybrids.
    Matched MeSH terms: Metabolic Networks and Pathways/genetics
  20. Genes involved in alkane degradation in the Alcanivorax hongdengensis strain A-11-3
    Wang W, Shao Z
    Appl Microbiol Biotechnol, 2012 Apr;94(2):437-48.
    PMID: 22207216 DOI: 10.1007/s00253-011-3818-x
    Alcanivorax hongdengensis A-11-3 is a newly identified type strain isolated from the surface water of the Malacca and Singapore Straits that can degrade a wide range of alkanes. To understand the degradation mechanism of this strain, the genes encoding alkane hydroxylases were obtained by PCR screening and shotgun sequencing of a genomic fosmid library. Six genes involved in alkane degradation were found, including alkB1, alkB2, p450-1, p450-2, p450-3 and almA. Heterogeneous expression analysis confirmed their functions as alkane oxidases in Pseudomonas putida GPo12 (pGEc47ΔB) or Pseudomonas fluorescens KOB2Δ1. Q-PCR revealed that the transcription of alkB1 and alkB2 was enhanced in the presence of n-alkanes C(12) to C(24); three p450 genes were up-regulated by C(8)-C(16) n-alkanes at different levels, whereas enhanced expression of almA was observed when strain A-11-3 grew with long-chain alkanes (C(24) to C(36)). In the case of branched alkanes, pristane significantly enhanced the expression of alkB1, p450-3 and almA. The six genes enable strain A-11-3 to degrade short (C(8)) to long (C(36)) alkanes that are straight or branched. The ability of A. hongdengensis A-11-3 to thrive in oil-polluted marine environments may be due to this strain's multiple systems for alkane degradation and its range of substrates.
    Matched MeSH terms: Metabolic Networks and Pathways/genetics*
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