Pseudomonas putida Bet001 and Delftia tsuruhatensis Bet002, isolated from palm oil mill effluent, accumulated poly(3-hydroxyalkanoates) (PHAs) when grown on aliphatic fatty acids, sugars, and glycerol. The substrates were supplied at 20:1 C/N mole ratio. Among C-even n-alkanoic acids, myristic acid gave the highest PHA content 26 and 28 wt% in P. putida and D. tsuruhatensis, respectively. Among C-odd n-alkanoic acids, undecanoic gave the highest PHA content at 40 wt% in P. putida and 46 wt% in D. tsuruhatensis on pentadecanoic acid. Sugar and glycerol gave <10 wt% of PHA content for both bacteria. Interestingly, D. tsuruhatensis accumulated both short- and medium-chain length PHA when supplied with n-alkanoic acids ranging from octanoic to lauric, sucrose, and glycerol with 3-hydroxybutyrate as the major monomer unit. In P. putida, the major hydroxyalkanoates unit was 3-hydroxyoctanoate and 3-hydroxydecanoate when grown on C-even acids. Conversely, 3-hydroxyheptanoate, 3-hydrxoynonanoate, and 3-hydroxyundecanoate were accumulated with C-odd acids. Weight-averaged molecular weight (M ) was in the range of 53-81 kDa and 107-415 kDa for P. putida and D. tsuruhatensis, respectively. Calorimetric analyses indicated that both bacteria synthesized semicrystalline polymer with good thermal stability with degradation temperature (T ) ranging from 178 to 282 °C.
Gliomas are highly lethal tumours characterised by heterogeneous molecular features, producing various metabolic phenotypes leading to therapeutic resistance. Lipid metabolism reprogramming is predominant and has contributed to the metabolic plasticity in glioma. This systematic review aims to discover lipids alteration and their biological roles in glioma and the identification of potential lipids biomarker. This systematic review was conducted using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Extensive research articles search for the last 10 years, from 2011 to 2021, were conducted using four electronic databases, including PubMed, Web of Science, CINAHL and ScienceDirect. A total of 158 research articles were included in this study. All studies reported significant lipid alteration between glioma and control groups, impacting glioma cell growth, proliferation, drug resistance, patients’ survival and metastasis. Different lipids demonstrated different biological roles, either beneficial or detrimental effects on glioma. Notably, prostaglandin (PGE2), triacylglycerol (TG), phosphatidylcholine (PC), and sphingosine-1-phosphate play significant roles in glioma development. Conversely, the most prominent anti-carcinogenic lipids include docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), and vitamin D3 have been reported to have detrimental effects on glioma cells. Furthermore, high lipid signals were detected at 0.9 and 1.3 ppm in high-grade glioma relative to low-grade glioma. This evidence shows that lipid metabolisms were significantly dysregulated in glioma. Concurrent with this knowledge, the discovery of specific lipid classes altered in glioma will accelerate the development of potential lipid biomarkers and enhance future glioma therapeutics.
Background Glioblastoma multiforme (GBM) are the major death contributor in primary brain tumour. Despite having an improved diagnostic criterion by integrating both histological and molecular features such as Isocitrate Dehydrogenase (IDH) detection, the prognosis of GBM patients still remain poor. Lipid metabolism is an essential pathway that fuel GBM aggressiveness. IDH1 one of the key enzyme that regulates it. Long non-coding RNAs (lncRNAs) act as competing endogenous RNAs (ceRNAs) in tumour initiation and progression. In parallel, miRNA-mediate ceRNA crosstalk between lncRNAs and mRNAs. In this study, we aim to investigate the IDH1 subgroup lncRNA associated ceRNA network hub gene responsible in the coordination of glioblastoma multiforme lipid metabolism using bioinformatics approach. Methods TCGA-GBM dataset consist of 168 GBM RNA-seq (159 IDH1 wt and 9 IDH1 mutation) were downloaded. Differentially expressed genes (DEG) were then obtained using Limma. Gene sets related with lipid metabolism from GSEA-MSigDB were overlapped with DEG using Venn diagram to identify the DEmRNA that are related with lipid metabolism. Construction of mRNA-miRNA and lncRNA-miRNA interaction networks were performed using miRNet. The ceRNA interaction network were later combined in the Cytoscape software. Potential lncRNA hub genes were identified by CytoHubba analysis. Results From 1389 DEG, 67 genes were identified to be significant in the regulation of lipid metabolism. By analysing the lncRNA-miRNA-mRNA interaction network, candidate hub lncRNAs consists of three genes with highest connective nodes; CYTOR, LOXL1-AS1 and HOTAIR. These genes are significantly upregulated in glioma. LOXL1-AS1 serve as an excellent prognostic biomarker for both glioma and glioblastoma as the effect of high and low LOXL1-AS1 expression on patients’ survival is significant (p<0.05). Conclusions Data mining and bioinformatics approach guided the identification of the potential hub lncRNAs associated ceRNA network in GBM lipid metabolism. This allows us to uncover the novel role of lncRNA in GBM tumorigenesis.
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