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Grapov, D.

Publications and source records attributed to Grapov, D..

3 recordsLinked to original sources

Exploring the impacts of human breast milk functional lipidome on infant health and growth outcomes in early life using lipid bioinformatics

Human breast milk lipidome is complex, and how changes in the functional lipid metabolism converge systematically to alter infants health outcomes is poorly understood. We used human breast milk and infant-mother dyads as a test system to demonstrate how the application of improved lipid bioinformatics can be effective in discerning systematic changes in functional lipid metabolism providing novel discoveries of how lactational programming in early life can influence infant health and growth outcomes. The study consisted of 40 mother-infant dyads where breast milk, maternal diet, infant anthropometrics [fat mass index (FMI), length z score, BMI z score, fat-free mass index (FFMI)], and infant atopic disease outcome (ear infection, cold, wheezing, diarrhea, and eczema) were collected at one and four months postpartum. Integrated Lipid Bioinformatics analyses were conducted using XLSTAT, Metaboanalyst 5.0. R software, Lipid Search, Xcalibur, and Cytoscape software. The results showed breast milk lipidome ordinated into distinct clusters based on maternal BMI status, and differences in developmental and atopic disease outcomes following redundancy analysis. Specifically, lipids from obese mothers clustered with FMI and eczema, while lipids from non-obese mothers clustered with FFM and wheezing. Receiver operating analysis was effective in identifying potential lipid biomarkers that were significantly associated with infant FMI, FFMI, and eczema during early life. Sphingolipid and glycerophospholipid pathways were significantly associated with the altered breast milk lipidome impacting infant development and atopic disease outcome during the first year of life. The findings following the advanced lipid bioinformatics suggest that the breastmilk functional lipid metabolism appears to play a key role in lipid-mediated lactational programming influencing development and atopic disease outcome, and present opportunities for potential dietary intervention in early life.

bioinformatics↗

Adipocytes reprogram glucose metabolism in cancer cells promoting metastasis

In the tumor microenvironment, adipocytes function as an alternate fuel source for cancer cells. However, whether adipocytes influence macromolecular biosynthesis in cancer cells is unknown. Here, we systematically characterized the bi-directional interaction between primary human adipocytes and ovarian cancer (OvCa) cells using multi-platform metabolomics, imaging mass spectrometry, [13C]-glucose isotope tracing, and gene expression analysis. We report that omental tumor explants and OvCa cells co-cultured with adipocytes divert part of the glucose from glycolysis and TCA cycle towards glycerol-3-phosphate (G3P) synthesis. Normoxic HIF1 protein, stabilized by adipokines, regulate this altered flow of glucose-derived carbons in cancer cells, resulting in increased synthesis of glycerophospholipids (GPL) and triacylglycerols. Blocking adipocyte-induced HIF1 expression increases lipid peroxidation levels in cancer cells and sensitizes them to ferroptosis-mediated cell death. Subsequently, the knockdown of HIF1 or G3P acyltransferase 3 (a regulatory enzyme of GPL synthesis) reduced metastasis in xenograft models of OvCa. In summary, we show that in an adipose-rich tumor microenvironment, cancer cells generate G3P as a precursor for critical membrane and signaling components, thereby promoting metastasis. Targeting biosynthetic processes specific to adipose-rich tumor microenvironments might be an effective strategy against metastasis.

cancer biology↗

Plant lipid metabolism in susceptible and tolerant soybean (Glycine max) cultivars in response to Phytophthora sojae colonization and infection

Soybean is one of the most cultivated crops globally and a staple food for much of the worlds population. The annual global crop losses due to infection by the Phytophthora sojae are currently estimated at approximately $2B USD, yet we have limited understanding of the role of lipid metabolism in the adaptative strategies used to limit infection and crop loss. We employed a multi-modal lipidomics approach to investigate how soybean cultivars remodel their lipid metabolism to successfully limit infection by Phytophthora sojae. Both the tolerant and susceptible soybean cultivars showed alterations in lipid metabolism in response to Phytophthora sojae infection. Relative to non-inoculated controls, induced accumulation of stigmasterol was observed in the susceptible cultivar whereas, induced accumulation of phospholipids and glycerolipids occurred in tolerant soybean cultivar. We have generated a comprehensive metabolic map of susceptible and tolerant soybean root and stem lipid metabolism to identify lipid modulators of host immune or tolerance response to Phytophthora sojae infection and identified potential pathways and unique lipid biomarkers like TG(15:0/22:0/22:5), TG(10:0/10:0/10:0), TG(10:0/10:0/14:0), DG(18:3/18:3), DG(16:0/18:3) and DG(24:0/18:2) as possible targets for the development of future plant protection solutions.

pathology↗