Characterization of the biofilm landscape of Bacillus subtilis by spatial microproteomics
Zemaitis, K. J.; Zhou, M.; Yannarell, S. M.; Fulcher, J. M.; Bhattacharjee, A.; Velickovic, M.; Degnan, D. J.; Shank, E. A.; Anderton, C. R.; Kew, W.; Pasa-Tolic, L.; Velickovic, D.
Show abstract
Bulk proteomics has been demonstrated to differentiate subpopulations within bacterial colonies, yet advanced analyses by mass spectrometry imaging (MSI) hold even greater promise for the future. This technology can enable high-throughput spatial phenotyping that can reshape biological discovery by providing visualization of components of various biomolecular mechanisms. With high mass resolving power and high spatial resolution analyses being routine, we can confidently enable intact protein imaging directly from samples with minimal preparation. Pairing those analyses with bulk experimental libraries can provide high confidence in annotations of post-translational modifications (PTMs) and truncations. Revealing PTM localization within the samples unlocks a direct window into unknown biology at the microscale. However, top-down proteomics (TDP) is not commonplace for microbial species, largely due to challenges in identifying detected peptides and proteins; considering the theoretical proteome of even the well-studied model bacterium Bacillus subtilis was only partially mapped recently. With little still known about the form and function of many of these proteins - let alone proteoforms, where PTMs and truncations of the same protein may possess unique physiological roles - there is a wealth of work to be done. Here we jointly apply TDP and MSI to describe the microscale spatial proteomic landscape within B. subtilis and further demonstrate the feasibility of detecting differentiated subpopulations through proteoforms across the biofilm landscape.
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Mapping a Toxoplasma gondii interactome by crosslinking mass spectrometry and machine learning 90%
- Fungal organic acid uptake of mineral derived K is dependent on distance from carbon hotspot 90%
- Inverse stable isotope labeling (InverSIL) links predicted catecholate siderophore gene clusters to their products in diverse bacteria 90%
Similar papers in this journal
- High Resolution Imaging Mass Spectrometry of Bacterial Microcolonies at Ecological Scales 95%
- Patch-Clamp Proteomics of Single Neuronal Somas in Tissue Using Electrophysiology and Subcellular Capillary Electrophoresis Mass Spectrometry 92%
- Lipid signatures and inter-cellular heterogeneity of naive and lipopolysaccharide-stimulated human microglia-like cells 92%
Similar papers in this journal
- NPOmix: a machine learning classifier to connect mass spectrometry fragmentation data to biosynthetic gene clusters 92%
- Lysinoalanine crosslinking is a conserved post-translational modification in the spirochete flagellar hook 90%
- Mass-selective and ice-free cryo-EM protein sample preparation via native electrospray ion-beam deposition 89%
Similar papers in this journal
- Structural O-Glycoform Heterogeneity of the SARS-CoV-2 Spike Protein Receptor-Binding Domain Revealed by Native Top-Down Mass Spectrometry 92%
- Chemoproteomics yields a selective molecular host for acetyl-CoA 91%
- An uncommon phosphorylation mode regulates the activity and protein-interactions of N-acetylglucosamine kinase 90%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.