Some JPR highlights (JPR 2019 March)
Journal Name：Journal of Proteome Research
Issue：2019 March
Shared by: Weining Zhao
1. Acetylome:
Zhuo Zhou et al from Zhejiang University profiled the lysine acetylome as protein acetylation which is believed to play a key role in autophagy. Employing a SILIC method in human cell culture, they found 421 acetylation sites significantly altered on 296 proteins. 80.8% of sites were downregulated while only 19.2% upregulated suggesting a deacetylation-preponderant profile during autophagy.1 Lysine acetylation occurs not only in eukaryotic cells but also prokaryotic ones. Lysine succinylome and acetylome of the extracellular compartment of clinically important pathogen P. aeruginosa was reported for the first time. The key virulence factors LasB and CbpD from Pseudomonas aeruginosa were found to be multi-modified on lysine residues. Moreover, Charlotte et al demonstrate lysine is prone to be modified and various modifications (9 kinds of modifications were tested) can take place in vitro. However, these modification patterns still need further in vivo verification.2
2.
a) Milk Protein-Derived Peptides:
One piece of milk related work was published in JPR 2019 March issue which may raise our interest and aid our in-house milk formula project. This work focuses on preterm infants and provides a comprehensive profile of milk peptides released during gastric digestion over time.3
b) Cystic Fibrosis Newborns:
Cystic fibrosis (CF) is one of the most common fatal genetic diseases and the patients can benefit from early therapeutic interventions. The current CF screening method for newborns suffer from low positive predictive value although it is sensitive. Nontargeted metabolite profiling experiments with highthroughput capillary electrophoresis-mass spectrometry (MS) platform reveal 32 metabolites are differentially expressed in CF newborns and normal ones (q < 0.05) while 6 CF-specific biomarker candidates satisfying a Bonferroni adjustment (p < 7.25 × 10–5).4 Nevertheless, the application of this discovery into clinical labs still needs more efforts and unlikely to replace the current screening methods due to its current sensitivity.
3. Method Development:
a) Immunogen Structure Generation:
One crosslinking mass spectrometry (XL-MS) based approach was developed for structure generation and delineation of immunogens. This approach is demonstrated by case study of host transferrin (Tf) and bacterial vaccine target transferrin binding protein B (TbpB). Nonetheless, since this approach is based on crosslinking mass spectrometry data, the cross-linkers are vital for successful modeling. As suggested by Daniel et al, photoactivatable diazirine containing cross-linker allows fast snapshot of the protein interactions while the commonly used N-hydroxysuccinimide ester traps dynamic states in the ensemble.5 This work actually highlights the proper selection of cross-linkers in XL-MS research as well as the importance of developing new methodologies.
b) Proteoform Identifications:
TopMCMC method was developed for accurately estimating the statistical significance of proteoform identifications with modifications in Top-down mass spec data. This is a good complement since most current top-down data analysis softwares employ estimation methods designed for proteoform identifications without modifications. With TopMCMC, more spectra were identified and the data is shown by Xiaowen Liu et al.6
c) DIA Tutorial:
Data-Independent Acquisition (DIA) is one important mass-spec technique and a number of scientific groups perform DIA experiments with orbitrap analyzer. Léon et al proposed one DIA method development strategy for Orbitrap Q Exactive HF in their tutorial. In this tutorial, the authors do not provide optimal settings but show the steps in construction and optimization of the DIA method. The method discussion inside further points out possible tailoring.7 This method is quite beneficial for fresh DIA researchers.
4. Simple Ideas:
a) Hybrid Insulin Peptides:
Hybrid insulin peptides (HIPs) were discovered as a novel class of post-translationally modified peptides in murine-derived beta cell tumors, and Aaron et al identified the presence of these peptide in mouse and human islets with mass-spec.8
b) Exosome and macrophage:
The proteome of THP-1-derived macrophages and their exosomes secreted with or without IFN-α treatment were analyzed via label-free liquid chromatography–tandem mass spectrometry quantitation technologies. The analysis of the proteomic data indicates the exosomes can act as cargos of IFN-α-induced antiviral molecules.9
c) Protein Function and Interaction Network:
The pathogen resistance phenotype of Arabidopsis to Pseudomonas syringae pv tomato (Pst) DC3000 is verified with the biological assays when MAP kinase 4 (MPK4) is overexpressed. Further systems level analysis of how MPK4 regulates plant immunity is achieved via immunoprecipitation coupled with mass spectrometry (IP-MS) by comparing the interaction network in the presence and absence of MPK4 activator flg22.10
1. Zhou, Z.; Chen, Y.; Jin, M.; He, J.; Guli, A.; Yan, C.; Ding, S., Comprehensive Analysis of Lysine Acetylome Reveals a Site-Specific Pattern in Rapamycin-Induced Autophagy. J Proteome Res 2019, 18 (3), 865-877.
2. Gaviard, C.; Cosette, P.; Jouenne, T.; Hardouin, J., LasB and CbpD Virulence Factors of Pseudomonas aeruginosa Carry Multiple Post-Translational Modifications on Their Lysine Residues. J Proteome Res 2019, 18 (3), 923-933.
3. Beverly, R. L.; Underwood, M. A.; Dallas, D. C., Peptidomics Analysis of Milk Protein-Derived Peptides Released over Time in the Preterm Infant Stomach. J Proteome Res 2019, 18 (3), 912-922.
4. DiBattista, A.; McIntosh, N.; Lamoureux, M.; Al-Dirbashi, O. Y.; Chakraborty, P.; Britz-McKibbin, P., Metabolic Signatures of Cystic Fibrosis Identified in Dried Blood Spots For Newborn Screening Without Carrier Identification. J Proteome Res 2019, 18 (3), 841-854.
5. Ziemianowicz, D. S.; Ng, D.; Schryvers, A. B.; Schriemer, D. C., Photo-Cross-Linking Mass Spectrometry and Integrative Modeling Enables Rapid Screening of Antigen Interactions Involving Bacterial Transferrin Receptors. J Proteome Res 2019, 18 (3), 934-946.
6. Kou, Q.; Wang, Z.; Lubeckyj, R. A.; Wu, S.; Sun, L.; Liu, X., A Markov Chain Monte Carlo Method for Estimating the Statistical Significance of Proteoform Identifications by Top-Down Mass Spectrometry. J Proteome Res 2019, 18 (3), 878-889.
7. Reubsaet, L.; Sweredoski, M. J.; Moradian, A., Data-Independent Acquisition for the Orbitrap Q Exactive HF: A Tutorial. J Proteome Res 2019, 18 (3), 803-813.
8. Aaron Wiles, T.; Powell, R.; Michel, C. R.; Scott Beard, K.; Hohenstein, A.; Bradley, B.; Reisdorph, N.; Haskins, K.; Delong, T., Identification of Hybrid Insulin Peptides (HIPs) in Mouse and Human Islets by Mass Spectrometry. J Proteome Res 2019, 18 (3), 814-825.
9. Yao, Z.; Jia, X.; Megger, D. A.; Chen, J.; Liu, Y.; Li, J.; Sitek, B.; Yuan, Z., Label-Free Proteomic Analysis of Exosomes Secreted from THP-1-Derived Macrophages Treated with IFN-alpha Identifies Antiviral Proteins Enriched in Exosomes. J Proteome Res 2019, 18 (3), 855-864.
10. Zhang, T.; Schneider, J. D.; Lin, C.; Geng, S.; Ma, T.; Lawrence, S. R.; Dufresne, C. P.; Harmon, A. C.; Chen, S., MPK4 Phosphorylation Dynamics and Interacting Proteins in Plant Immunity. J Proteome Res 2019, 18 (3), 826-840.
