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Bitte verwenden Sie diesen Link, wenn Sie dieses Dokument zitieren oder verlinken wollen: https://nbn-resolving.org/urn:nbn:de:gbv:9-opus-40279

Improving Proteome Coverage for Small Sample Amounts: An Advanced Method for Proteomics Approaches with Low Bacterial Cell Numbers

  • Abstract Proteome analyses are often hampered by the low amount of available starting material like a low bacterial cell number obtained from in vivo settings. Here, the single pot solid‐phase enhanced sample preparation (SP3) protocol is adapted and combined with effective cell disruption using detergents for the proteome analysis of bacteria available in limited numbers only. Using this optimized protocol, identification of peptides and proteins for different Gram‐positive and Gram‐negative species can be dramatically increased and, reliable quantification can also be ensured. This adapted method is compared to already established strain‐specific sample processing protocols for Staphylococcus aureus, Streptococcus suis, and Legionella pneumophila. The highest species‐specific increase in identifications is observed using the adapted method with L. pneumophila samples by increasing protein and peptide identifications up to 300% and 620%, respectively. This increase is accompanied by an improvement in reproducibility of protein quantification and data completeness between replicates. Thus, this protocol is of interest for performing comprehensive proteomics analyses of low bacterial cell numbers from different settings ranging from infection assays to environmental samples.

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Metadaten
Author: Sascha Blankenburg, Christian Hentschker, Anna Nagel, Petra Hildebrandt, Stephan Michalik, Denise Dittmar, Kristin Surmann, Uwe VölkerORCiD
URN:urn:nbn:de:gbv:9-opus-40279
DOI:https://doi.org/10.1002/pmic.201900192
Parent Title (English):PROTEOMICS
Document Type:Article
Language:English
Date of first Publication:2019/12/02
Release Date:2020/12/01
Tag:SP3; bacterial cell disruption; internalization; proteomics; small cell numbers
GND Keyword:-
Volume:19
Issue:23
Faculties:Mathematisch-Naturwissenschaftliche Fakultät / Interfakultäres Institut für Genetik und Funktionelle Genomforschung (MNF)
Licence (German):License LogoCreative Commons - Namensnennung