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

Stephan FuchsSusanne Engelmann
Published in: Proteomics (2023)
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.
Keyphrases
  • mass spectrometry
  • machine learning
  • amino acid
  • healthcare
  • multiple sclerosis
  • mental health
  • high resolution
  • liquid chromatography
  • gene expression
  • ms ms
  • current status
  • nucleic acid