Two plastidial lysophosphatidic acid acyltransferases differentially mediate the biosynthesis of membrane lipids and triacylglycerols in Phaeodactylum tricornutum.

Lysophosphatidic acid acyltransferases (LPAATs) catalyze the formation of phosphatidic acid (PA), a central metabolite in both prokaryotic and eukaryotic organisms for glycerolipid biosynthesis. Phaeodactylum tricornutum contains at least two plastid-localized LPAATs (ptATS2a and ptATS2b), but their roles in lipid synthesis remain unknown. Both ptATS2a and ptATS2b could complement the high temperature sensitivity of the bacterial plsC mutant deficient in LPAAT. In vitro enzyme assays showed that they prefer lysophosphatidic acid over other lysophospholipids. ptATS2a is localized in the plastid inner envelope membrane and CRISPR/Cas9-generated ptATS2a mutants showed compromised cell growth, significantly changed plastid and extra-plastidial membrane lipids at nitrogen-replete condition and reduced triacylglycerols (TAGs) under nitrogen-depleted condition. ptATS2b is localized in thylakoid membranes and its knockout led to reduced growth rate and TAG content but slightly altered molecular composition of membrane lipids. The changes in glycerolipid profiles are consistent with the role of both LPAATs in the sn-2 acylation of sn-1-acyl-glycerol-3-phosphate substrates harboring 20:5 at the sn-1 position. Our findings suggest that both LPAATs are important for membrane lipids and TAG biosynthesis in P. tricornutum and further highlight that 20:5-Lyso-PA is likely involved in the massive import of 20:5 back to the plastid to feed plastid glycerolipid syntheses.

Prediction of standard cell types and functional markers from textual descriptions of flow cytometry gating definitions using machine learning.

BACKGROUND: A key step in clinical flow cytometry data analysis is gating, which involves the identification of cell populations. The process of gating produces a set of reportable results, which are typically described by gating definitions. The non-standardized, non-interpreted nature of gating definitions represents a hurdle for data interpretation and data sharing across and within organizations. Interpreting and standardizing gating definitions for subsequent analysis of gating results requires a curation effort from experts. Machine learning approaches have the potential to help in this process by predicting expert annotations associated with gating definitions. METHODS: We created a gold-standard dataset by manually annotating thousands of gating definitions with cell type and functional marker annotations. We used this dataset to train and test a machine learning pipeline able to predict standard cell types and functional marker genes associated with gating definitions. RESULTS: The machine learning pipeline predicted annotations with high accuracy for both cell types and functional marker genes. Accuracy was lower for gating definitions from assays belonging to laboratories from which limited or no prior data was available in the training. Manual error review ensured that resulting predicted annotations could be reused subsequently as additional gold-standard training data. CONCLUSIONS: Machine learning methods are able to consistently predict annotations associated with gating definitions from flow cytometry assays. However, a hybrid automatic and manual annotation workflow would be recommended to achieve optimal results.

Presenting and sharing clinical data using the eTRIKS Standards Master Tree for tranSMART.

MOTIVATION: Standardization and semantic alignment have been considered one of the major challenges for data integration in clinical research. The inclusion of the CDISC SDTM clinical data standard into the tranSMART i2b2 via a guiding master ontology tree positively impacts and supports the efficacy of data sharing, visualization and exploration across datasets. RESULTS: We present here a schema for the organization of SDTM variables into the tranSMART i2b2 tree along with a script and test dataset to exemplify the mapping strategy. The eTRIKS master tree concept is demonstrated by making use of fictitious data generated for four patients, including 16 SDTM clinical domains. We describe how the usage of correct visit names and data labels can help to integrate multiple readouts per patient and avoid ETL crashes when running a tranSMART loading routine. AVAILABILITY AND IMPLEMENTATION: The eTRIKS Master Tree package and test datasets are publicly available at https://doi.org/10.5281/zenodo.1009098 and a functional demo installation at https://public.etriks.org/transmart/datasetExplorer/ under eTRIKS-Master Tree branch, where the discussed examples can be visualized.

Characterization of immune cell subsets during the active phase of multiple sclerosis reveals disease and c-Jun N-terminal kinase pathway biomarkers.

BACKGROUND: Autoimmune activation and deregulated apoptosis of T lymphocytes are involved in multiple sclerosis (MS). c-Jun N-terminal kinase (JNK) plays a role in T-cell survival and apoptosis. OBJECTIVES: The aim of this work was to investigate the role of the JNK-dependent apoptosis pathway in relapsing-remitting MS (RRMS). METHODS: The immunomodulatory effect of AS602801, a JNK inhibitor, was firstly evaluated on activated peripheral blood mononuclear cells (PBMCs) from healthy volunteers (HVs) and secondly in unstimulated purified CD4+, CD8+ and CD11b+ cells from RRMS patients and HVs. Moreover JNK/inflammation/apoptosis related genes were investigated in RRMS and HV samples. RESULTS: In activated PBMCs from HVs, we showed that AS602801 blocked T-lymphocyte proliferation and induced apoptosis. In RRMS CD4+ and CD8+ cells, AS602801 induced apoptosis genes and expression of surface markers, while in RRMS CD11b+ cells it induced expression of innate immunity receptors and co-stimulatory molecules. Untreated cells from RRMS active-phase patients significantly released interleukin-23 (IL-23) and interferon-gamma (IFN-γ) and expressed less apoptosis markers compared to the cells of HVs. Moreover, gene expression was significantly different in cells from RRMS active-phase patients vs. HVs. By comparing RRMS PBMCs in the active and stable phases, a specific genomic signature for RRMS was indentified. Additionally, CASP8AP2, CD36, ITGAL, NUMB, OLR1, PIAS-1, RNASEL, RTN4RL2 and THBS1 were identified for the first time as being associated to the active phase of RRMS. CONCLUSIONS: The analysis of the JNK-dependent apoptosis pathway can provide biomarkers for activated lymphocytes in the active phase of RRMS and a gene expression signature for disease status. The reported results might be useful to stratify patients, thereby supporting the development of novel therapies.

Rescue of intracellularly trapped lutropin receptor exodomain by endodomain and reconstitution of a functional membrane receptor: interaction between exo- and endodomains.

The lutropin receptor consists of an extracellular N-terminal half and a membrane-associated C-terminal half. hCG initially binds the exodomain with a high affinity and the resulting complex is thought to interact with the endodomain through a secondary contact generating a hormonal signal. Therefore, the exodomain and endodomain are likely to associate directly or indirectly with each other, but lack of fruitful materials and technology has hampered knowledge about their physical relationship and contact sites. In this work, we engineered a double-recombinant (separate exodomain and endodomain) baculovirus system successfully expressing on the surface of insect cells high levels of split LH receptor, binding the hormone with high affinity and inducing cAMP synthesis. In contrast, the exodomain and endodomain expressed separately were mostly trapped in cells. Our data indicate that the exodomain and endodomain are disulfide linked in the split receptor. When the disulfide links were reduced, the split receptor still induced cAMP up to 60%, which raises the intriguing possibility of a residual induction activity of the endodomain in the absence of high-affinity ligand binding. Our results also underscore that the targeting and transport of the LH receptor to plasma membrane require both domains, whereas each domain is independently sufficient for folding. The expression level of functional lutropin receptors is the highest ever reported. Our system may also be useful for future studies requiring a high amount of soluble secreted exodomain.