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Spatial Proteomics

This service and research topic deals with the spatially resolved field of proteomics which allows targetet and untargeted host-pathogen interaction studies.
Please get into contact with Franziska Hoffmann and Ferdinand von Eggeling if you are interested in spatial proteomics.

SEEK ID: https://funginet.hki-jena.de/investigations/16

Projects: Z2

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Created: 17th Feb 2021 at 09:59

Last updated: 17th Feb 2021 at 12:13

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Franziska Hoffmann

Projects: Z2

Institutions: University Hospital Jena

https://orcid.org/0000-0002-6872-924X
Ferdinand Von Eggeling

Projects: Z2, FungiNet total

Institutions: University Hospital Jena, Friedrich-Schiller-University

https://orcid.org/0000-0002-8062-6999
Z2

In project Z2 a sophisticated proteome analysis platform will be provided based on 2D-gel electrophoresis (2D-GE), MALDI-TOF and LC-MS/MS techniques to specific A and Cprojects.

Programme: Collaborative Research Center / Transregio 124 "Pathogenic fungi and their human host: Networks of Interaction - FungiNet"

Public web page: http://www.funginet.de/project-z2.html

Identification of fungal species in patient tissue using MALDI-Imaging and Deep Learning approaches
Z2
No description specified

Person responsible: Franziska Hoffmann

Snapshots: No snapshots

Visualization and detection of CwhA in Aspergillus infection
Z2
No description specified

Person responsible: Franziska Hoffmann

Snapshots: No snapshots

Visualization of HsbA in murine and human Lichtheimia infection
Z2
No description specified

Person responsible: Franziska Hoffmann

Snapshots: No snapshots

Microdissection-An Essential Prerequisite for Spatial Cancer Omics.
Z2

Abstract (Expand)

The problem with cancer tissue is that its intratumoral heterogeneity and its complexity is extremely high as cells possess, depending on their location and function, different mutations, different … mRNA expression and the highest intricacy in the protein pattern. Prior to genomic and proteomic analyses, it is therefore indispensable to identify the exact part of the tissue or even the exact cell. Laser-based microdissection is a tried and tested technique able to produce pure and well-defined cell material for further analysis with proteomic and genomic techniques. It sheds light on the heterogeneity of cancer or other complex diseases and enables the identification of biomarkers. This review aims to raise awareness for the reconsideration of laser-based microdissection and seeks to present current state-of-the-art combinations with omic techniques.

Authors: Ferdinand Von Eggeling, Franziska Hoffmann

Date Published: 25th Jun 2020

Journal: Proteomics

Identification of Proteomic Markers in Head and Neck Cancer Using MALDI-MS Imaging, LC-MS/MS, and Immunohistochemistry.
Z2

Abstract (Expand)

PURPOSE: The heterogeneity of squamous cell carcinoma tissue greatly complicates diagnosis and individualized therapy. Therefore, characterizing the heterogeneity of tissue spatially and identifying … appropriate biomarkers is crucial. MALDI-MS imaging (MSI) is capable of analyzing spatially resolved tissue biopsies on a molecular level. EXPERIMENTAL DESIGN: MALDI-MSI is used on snap frozen and formalin-fixed and paraffin-embedded (FFPE) tissue samples from patients with head and neck cancer (HNC) to analyze m/z values localized in tumor and nontumor regions. Peptide identification is performed using LC-MS/MS and immunohistochemistry (IHC). RESULTS: In both FFPE and frozen tissue specimens, eight characteristic masses of the tumor's epithelial region are found. Using LC-MS/MS, the peaks are identified as vimentin, keratin type II, nucleolin, heat shock protein 90, prelamin-A/C, junction plakoglobin, and PGAM1. Lastly, vimentin, nucleolin, and PGAM1 are verified with IHC. CONCLUSIONS AND CLINICAL RELEVANCE: The combination of MALDI-MSI, LC-MS/MS, and subsequent IHC furnishes a tool suitable for characterizing the molecular heterogeneity of tissue. It is also suited for use in identifying new representative biomarkers to enable a more individualized therapy.

Authors: Franziska Hoffmann, C. Umbreit, Thomas Krüger, D. Pelzel, G. Ernst, Olaf Kniemeyer, O. Guntinas-Lichius, A. Berndt, Ferdinand Von Eggeling

Date Published: 10th Nov 2018

Journal: Proteomics Clin Appl

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