Lecture
Current Potential of Proteomics in Infectious Disease Diagnostics
- at -
- ICM Saal 4a
- Type: Lecture
Lecture description
In recent years, proteomics has made tremendous progress towards deep and comprehensive large-scale analysis of proteins. Nevertheless, proteomics is still primarily a research tool rather than a diagnostic tool, despite great efforts being made
to change this. In infectious disease diagnostics a major challenge to translate proteomics data into clinical action is that conventional proteomics workflows cannot simply be applied to infectious disease investigations. At the Robert Koch Institute, the
German Public Health Institute, our work focuses on developing customised, mass spectrometry-based proteomics methods for infectious disease diagnostics in general and its application to exceptional biological hazards.
Our work has led to the development of a universal, rapid sample preparation strategy applicable to a wide variety of samples that effectively inactivates all types of pathogens [1]. Combined with dedicated software development [2,3], this enables the
taxonomic typing and antibiotic resistance prediction of clinical bacterial isolates with excellent specificity (>99%) and high sensitivity (>90%) [3,4]. Current work focuses on further improving sample throughput up to the level necessary for routine diagnostics.
Furthermore, we are introducing proteomics as a complementary approach to metagenomics for the untargeted identification of human-pathogenic viruses in patient samples [5]. The viral proteomics workflow (vPro-MS) is based on in silico spectral
library engineering, starting from sequence databases and covers the human virome. It can identify human-pathogenic viruses in patient samples with excellent specificity (>99.9%). Current developments of vPro-MS focus on widening the scope to include
animal viruses that may pose a threat to human health, as well as improving sensitivity.
Literature:
[1] Sample Preparation by Easy Extraction and Digestion (SPEED) - A Universal, Rapid, and Detergent-free Protocol for Proteomics Based on Acid Extraction. Doellinger, J., Mol Cell Proteomics. 2020.
[2] Identification of Microorganisms by Liquid Chromatography-Mass Spectrometry (LCMS(1)) and in Silico Peptide Mass Libraries. Lasch, P., Mol Cell Proteomics. 2020.
[3] Unbiased Antimicrobial Resistance Detection from Clinical Bacterial Isolates Using Proteomics. Blumenscheit, C., Anal Chem. 2021.
[4] Antibiotic resistance detection and concomitant species identification of ESKAPE pathogens by proteomics. Blumenscheit, C., bioRxiv. 2024.
[5] vPro-MS enables identification of human-pathogenic viruses from patient samples by untargeted proteomics. Grossegesse, M., Nat Comm. 2025.
to change this. In infectious disease diagnostics a major challenge to translate proteomics data into clinical action is that conventional proteomics workflows cannot simply be applied to infectious disease investigations. At the Robert Koch Institute, the
German Public Health Institute, our work focuses on developing customised, mass spectrometry-based proteomics methods for infectious disease diagnostics in general and its application to exceptional biological hazards.
Our work has led to the development of a universal, rapid sample preparation strategy applicable to a wide variety of samples that effectively inactivates all types of pathogens [1]. Combined with dedicated software development [2,3], this enables the
taxonomic typing and antibiotic resistance prediction of clinical bacterial isolates with excellent specificity (>99%) and high sensitivity (>90%) [3,4]. Current work focuses on further improving sample throughput up to the level necessary for routine diagnostics.
Furthermore, we are introducing proteomics as a complementary approach to metagenomics for the untargeted identification of human-pathogenic viruses in patient samples [5]. The viral proteomics workflow (vPro-MS) is based on in silico spectral
library engineering, starting from sequence databases and covers the human virome. It can identify human-pathogenic viruses in patient samples with excellent specificity (>99.9%). Current developments of vPro-MS focus on widening the scope to include
animal viruses that may pose a threat to human health, as well as improving sensitivity.
Literature:
[1] Sample Preparation by Easy Extraction and Digestion (SPEED) - A Universal, Rapid, and Detergent-free Protocol for Proteomics Based on Acid Extraction. Doellinger, J., Mol Cell Proteomics. 2020.
[2] Identification of Microorganisms by Liquid Chromatography-Mass Spectrometry (LCMS(1)) and in Silico Peptide Mass Libraries. Lasch, P., Mol Cell Proteomics. 2020.
[3] Unbiased Antimicrobial Resistance Detection from Clinical Bacterial Isolates Using Proteomics. Blumenscheit, C., Anal Chem. 2021.
[4] Antibiotic resistance detection and concomitant species identification of ESKAPE pathogens by proteomics. Blumenscheit, C., bioRxiv. 2024.
[5] vPro-MS enables identification of human-pathogenic viruses from patient samples by untargeted proteomics. Grossegesse, M., Nat Comm. 2025.
