Project description:We report next generation sequencing RNA-seq data of human gut commensal Bacteroides thetaiotaomicron strains deficient in inositol lipid synthesis, including dBT_1522 (phosphoinositol dihydroceramide synthase knockout) and its wild-type background strain, and iSPTdBT_1526 (myo-inositol-phosphate synthase) knockout with its background strain ("iSPT," inducible serine palmitoyltransferase).
Project description:Interventions: experimental group :PD-1 Knockout Engineered T Cells
Primary outcome(s): Number of participants with Adverse Events and/or Dose Limiting Toxicities as a Measure of Safety and tolerability of dose of PD-1 Knockout T cells using Common Terminology Criteria for Adverse Events (CTCAE v4.0) in patients
Study Design: historical control
Project description:This is the first report on fluoroalcohol-induced coacervation of lipid components in natural cell membranes and incorporation of this novel process for extraction, fractionation, and enrichment of proteins in proteomics workflow.
Project description:The first step in biomarkers discovery is to identify the best protocols for their purification and analysis. We have identified an optimal RNA extraction method of microRNAs from human plasma samples. We also report that the addition of low doses of carrier RNA before starting RNA extraction improves microRNA extraction and quantification.
Project description:Oleaginous microalgae are considered a promising platform for the sustainable production of high-value lipids and biofuel feedstocks. However, current lipid yields are too low to allow for an economically feasible production process. Lipid yields could be enhanced by improving microalgal strains through genetic engineering. Strain improvement strategies for the industrially relevant genus Nannochloropsis have met limited success because most genes of this genus lack a functional annotation, hindering our understanding of lipid metabolism and its regulation. To gain fundamental insights and to provide targets for genetic engineering of lipid metabolism, the aim of this study was to discover novel genes that are associated with higher neutral lipid (NL) content in Nannochloropsis oceanica. Therefore, we constructed a random gene knockout (KO) insertional mutagenesis library of N. oceanica, and we screened it by five rounds of fluorescence-activated cell sorting to select high lipid mutant (HLM) strains. Several strains showed increased NL contents compared to the wild type under favorable growth conditions. By using an adapted cassette PCR strategy involving the type IIS restriction endonuclease MmeI, we traced the responsible genetic KO of the five most promising mutant strains. One particularly promising mutant strain (HLM23) was disrupted in gene NO06G03670, which encodes a putative APETALA2-like transcription factor. HLM23 was not affected in growth rate, had increase d photosynthetic performance and a NL content of 30% dry cell weight^(-1), a 40% increase compared to the wild type. RNA sequencing revealed a transcriptional upregulation of genes related to plastidial fatty acid biosynthesis, glycolysis and the Calvin–Benson–Bassham cycle in this mutant.
Project description:Multi-omics integrates diverse types of biological information from genomic, proteomic, and metabolomics experiments to achieve a comprehensive understanding of complex cellular mechanisms. However, this approach is also challenging due to technical issues such as limited sample quantities, complexity of data pre-processing, and reproducibility concerns. Although conventional pre-processing methods in multi-omics research are standardized to ensure consistency; their simultaneous application can obscure specific details. Here, findings obtained from various omics approaches were profiled using various extraction methods (methanol extraction, Folch method, and Matyash methods for metabolites and lipids) and two digestion methods (Filter-aided sample preparation (FASP) and suspension traps (S-Trap)) for resuspended proteins. FASP was found to be more effective for separation of membrane-related proteins, whereas S-Trap excelled in isolating nuclear-related and RNA processing proteins. Thus, ASP may be suitable for investigating the immune response and bacterial infection pathways, whereas S-Trap may be more effective for studies focused on the mechanisms of neurodegenerative diseases. Moreover, the choice of extraction method, either single-phase MeOH or two-phase using Folch and Matyash methods, significantly influences the types of compounds identified, reflecting distinct profiles in different omics data sets. Among metabolites, the single-phase methd identified organic compounds and compounds related to fatty acids, whereas the two-phase extraction identified more hydrophilic compounds such as nucleotides. Lipids with strong hydrophobicity, such as ChE and TG, were identified in the two-phase extraction results. These findings highlight that significant differences between small molecules identified are primarily due to varying polarities of extraction solvents. To address human error and batch effects, a strategy that optimizes the balance between efficiency and the quality of the results is also proposed here. Our study reaffirms the impact of choice of pre-processing method in multi-omics, and also provides specific profiles of several protein and metabolite clusters as well as lipid classes.