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Olga Vvedenskaya

About Olga Vvedenskaya:

Postdoc, Andrej Shevchenko's lab , biological mass spectrometry, MPI-CBG, Dresden

SEEK ID: https://seek.lisym.org/people/84

Location:  Germany

Expertise: Not specified

Tools: Not specified

ORCID: Not specified

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LiSyM network

This comprises the whole LiSyM network

Programme: LiSyM: Liver Systems Medicine

Public web page: http://www.lisym.org

Start date: 1st Jan 2016

LiSyM-Krebs Partnering

This generic project is intended to be a forum for all LiSyM partner and external stakeholders interested in participating in the BMBF initiative LiSyM-Krebs.

Programme: LiSyM-Krebs

Public web page: https://www.ptj.de/projektfoerderung/gesundheitsforschung/lisym-krebs

LiSyM Pillar I: Early Metabolic Injury (LiSyM-EMI)

One of the tasks of the healthy liver is to store fat. Yet, at some stage, too much fat makes the liver sick. One critical time point occurs when a healthy fatty liver becomes inflamed and progresses to steatohepatitis, or NASH.
LiSyM-Pillar I will identify what events lead to this transition. Does it occur in all parts of the liver? Which molecules indicate that it is taking place? Can the degeneration be stopped or undone - and if so, how?

Programme: LiSyM: Liver Systems Medicine

Public web page: http://www.lisym.org/our-work/pillar-research/zones-of-the-liver

Start date: 1st Jan 2016

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Loss of hepatic Mboat7 leads to liver fibrosis.
LiSyM Pillar I: Early Metabolic Injury (LiSyM-EMI), LiSyM network

Abstract (Expand)

OBJECTIVE: The rs641738C>T variant located near the membrane-bound O-acyltransferase domain containing 7 (MBOAT7) locus is associated with fibrosis in liver diseases, including non-alcoholic fatty … liver disease (NAFLD), alcohol-related liver disease, hepatitis B and C. We aim to understand the mechanism by which the rs641738C>T variant contributes to pathogenesis of NAFLD. DESIGN: Mice with hepatocyte-specific deletion of MBOAT7 (Mboat7(Deltahep)) were generated and livers were characterised by histology, flow cytometry, qPCR, RNA sequencing and lipidomics. We analysed the association of rs641738C>T genotype with liver inflammation and fibrosis in 846 NAFLD patients and obtained genotype-specific liver lipidomes from 280 human biopsies. RESULTS: Allelic imbalance analysis of heterozygous human liver samples pointed to lower expression of the MBOAT7 transcript on the rs641738C>T haplotype. Mboat7(Deltahep) mice showed spontaneous steatosis characterised by increased hepatic cholesterol ester content after 10 weeks. After 6 weeks on a high fat, methionine-low, choline-deficient diet, mice developed increased hepatic fibrosis as measured by picrosirius staining (p<0.05), hydroxyproline content (p<0.05) and transcriptomics, while the inflammatory cell populations and inflammatory mediators were minimally affected. In a human biopsied NAFLD cohort, MBOAT7 rs641738C>T was associated with fibrosis (p=0.004) independent of the presence of histological inflammation. Liver lipidomes of Mboat7(Deltahep) mice and human rs641738TT carriers with fibrosis showed increased total lysophosphatidylinositol levels. The altered lysophosphatidylinositol and phosphatidylinositol subspecies in MBOAT7(Deltahep) livers and human rs641738TT carriers were similar. CONCLUSION: Mboat7 deficiency in mice and human points to an inflammation-independent pathway of liver fibrosis that may be mediated by lipid signalling and a potentially targetable treatment option in NAFLD.

Authors: V. R. Thangapandi, O. Knittelfelder, M. Brosch, E. Patsenker, O. Vvedenskaya, S. Buch, S. Hinz, A. Hendricks, M. Nati, A. Herrmann, D. R. Rekhade, T. Berg, M. Matz-Soja, K. Huse, E. Klipp, J. K. Pauling, J. A. Wodke, J. Miranda Ackerman, M. V. Bonin, E. Aigner, C. Datz, W. von Schonfels, S. Nehring, S. Zeissig, C. Rocken, A. Dahl, T. Chavakis, F. Stickel, A. Shevchenko, C. Schafmayer, J. Hampe, P. Subramanian

Date Published: 26th Jun 2020

Publication Type: Journal

Kinetic modelling of quantitative proteome data predicts metabolic reprogramming of liver cancer
LiSyM Pillar IV: Liver Function Diagnostics (LiSyM-LiFuDi)

Abstract

Not specified

Authors: Nikolaus Berndt, Antje Egners, Guido Mastrobuoni, Olga Vvedenskaya, Athanassios Fragoulis, Aurélien Dugourd, Sascha Bulik, Matthias Pietzke, Chris Bielow, Rob van Gassel, Steven W. Olde Damink, Merve Erdem, Julio Saez-Rodriguez, Hermann-Georg Holzhütter, Stefan Kempa, Thorsten Cramer

Date Published: 10th Dec 2019

Publication Type: Not specified

Analytical challenges in human plasma lipidomics: A winding path towards the truth
LiSyM Pillar I: Early Metabolic Injury (LiSyM-EMI)

Abstract (Expand)

Human plasma lipidome has been extensively studied in many pathophysiological contexts with the hope of identifying biomarkers for early diagnostics and monitoring the progression and treatment of a … broad spectrum of diseases. However, despite remarkable progress in lipidomics technologies, the concordance of lipidomics measurements between independent laboratories remains limited and not fulfilling the criteria of common laboratory diagnostics. Here we highlighted a few critical aspects of epidemiological studies of the plasma lipidome, including the selection of study cohorts, collection of plasma samples as well as extraction, identification and quantification of lipids. We argue that reporting the abundances of plasma lipids as molar concentrations is a key turning point during the transition of research lipidomics into a common tool of clinical diagnostics.

Authors: Olga Vvedenskaya, Yuting Wang, Jacobo Miranda Ackerman, Oskar Knittelfelder, Andrej Shevchenko

Date Published: 20th Oct 2018

Publication Type: Not specified

Shotgun Lipidomics Combined with Laser Capture Microdissection: A Tool To Analyze Histological Zones in Cryosections of Tissues.
LiSyM Pillar I: Early Metabolic Injury (LiSyM-EMI)

Abstract (Expand)

Shotgun analysis provides a quantitative snapshot of the lipidome composition of cells, tissues, or model organisms; however, it does not elucidate the spatial distribution of lipids. Here we demonstrate … that shotgun analysis could quantify low-picomole amounts of lipids isolated by laser capture microdissection (LCM) of hundred micrometer-sized histological zones visualized at the cryosections of tissues. We identified metabolically distinct periportal (pp) and pericentral (pc) zones by immunostaining of 20 mum thick cryosections of a healthy mouse liver. LCM was used to ablate, catapult, and collect the tissue material from 10 to 20 individual zones covering a total area of 0.3-0.5 mm(2) and containing ca. 500 cells. Top-down shotgun profiling relying upon computational stitching of 61 targeted selective ion monitoring ( t-SIM) spectra quantified more than 200 lipid species from 17 lipid classes including glycero- and glycerophospholipids, sphingolipids, cholesterol esters, and cholesterol. Shotgun LCM revealed the overall commonality of the full lipidome composition of pp and pc zones along with significant ( p < 0.001) difference in the relative abundance of 13 lipid species. Follow-up proteomics analyses of pellets recovered from an aqueous phase saved after the lipid extraction identified 13 known and 7 new protein markers exclusively present in pp or in pc zones and independently validated the specificity of their visualization, isolation, and histological assignment.

Authors: O. Knittelfelder, S. Traikov, O. Vvedenskaya, A. Schuhmann, S. Segeletz, A. Shevchenko, A. Shevchenko

Date Published: 30th Jul 2018

Publication Type: Not specified

Social media for Academics
LiSyM network

Workshop from LiSyM retreat in January 2020. Additional slides devoted to Social Media for Academics. Developed by Peter Krinenberg from https://naturalscience.careers/

Creator: Olga Vvedenskaya

Submitter: Olga Vvedenskaya

Download
LiSyM Midterm Evaluation 2018 poster 9 Shevchenko group
LiSyM Pillar I: Early Metabolic Injury (LiSyM-EMI), LiSyM network

Shotgun lipidomics of microdissected periportal and pericentral zones; Characterization of NAFLD in Human Liver Biopsies by Shotgun Lipidomics

Creators: Oskar Knittelfelder, Olga Vvedenskaya

Submitter: Oskar Knittelfelder

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