Small proteins in bacteria - Big challenges in prediction and identification.

Stephan Fuchs, Susanne Engelmann

Journal: Proteomics 2023;23(23-24):e2200421

PMID: 37609810

Abstract

Proteins with up to 100 amino acids have been largely overlooked due to the challenges associated with predicting and identifying them using traditional methods. Recent advances in bioinformatics and machine learning, DNA sequencing, RNA and Ribo-seq technologies, and mass spectrometry (MS) have greatly facilitated the detection and characterisation of these elusive proteins in recent years. This has revealed their crucial role in various cellular processes including regulation, signalling and transport, as toxins and as folding helpers for protein complexes. Consequently, the systematic identification and characterisation of these proteins in bacteria have emerged as a prominent field of interest within the microbial research community. This review provides an overview of different strategies for predicting and identifying these proteins on a large scale, leveraging the power of these advanced technologies. Furthermore, the review offers insights into the future developments that may be expected in this field.

© 2023 The Authors. Proteomics published by Wiley-VCH GmbH.

Address: Genome Competence Center (MF1), Department MFI, Robert-Koch-Institut, Berlin, Germany.; Institute for Microbiology, Technische Universität Braunschweig, Braunschweig, Germany.; Microbial Proteomics, Helmholtzzentrum für Infektionsforschung GmbH, Braunschweig, Germany.

Link outs

Subscription / membership required

Bant logo

© Copyright 2026, Nutrition Evidence

NED wishes to thank the following organisations for their support:

We use cookies to improve your experience and analyze site traffic with Google Analytics. By continuing to use our site, you agree to our use of cookies. Learn more.