High-throughput method for Peptide mapping and Amino acid sequencing for Calcitonin Salmon in Calcitonin Salmon injection using Ultra High Performance Liquid Chromatography - High Resolution Mass Spectrometry (UHPLC-HRMS) with the application of Bioinformatic tools

BACKGROUND

Tandem mass spectrometry (MS/MS) can provide direct and accurate sequence characterization of synthetic peptide drugs, and peptide drug products including side chain modifications in the Peptide drugs. This article explains a step-by-step guide to developing a high-throughput method using high resolution mass spectrometry for characterization of Calcitonin Salmon injection containing high proportion of UV-active excipients.

METHODS

The major challenge in the method development of Amino acid sequencing and Peptide mapping was presence of phenol in drug product. Phenol is a UV-active excipient and reacts with both Dithiothreitol (DTT) and Trypsin. Hence Calcitonin Salmon was extracted from the Calcitonin Salmon injection using solid phase extraction after the extraction, Amino acid sequencing and peptide mapping study was performed. Upon incubation of Calcitonin Salmon with Trypsin and DTT, digested fragments were generated which were separated by mass compatible reverse phase chromatography and the molecular mass of each fragment was determined using HRMS.

RESULTS

A reverse phase chromatographic method was developed using UHPLC-HRMS for the determination of direct mass, peptide mapping and to determine the amino acid sequencing in the Calcitonin Salmon injection. The method was found Specific and fragments after trypsin digest are well resolved from each other and the molecular mass of each fragment was determined using HRMS. Sequencing was performed using automated identification of b and y ions annotation and identifications based on MS/MS spectra using Biopharma finder and Proteome discoverer software.

CONCLUSION

Using this approach 100% protein coverage was obtained and protein was identified as Calcitonin Salmon and the observed masses of tryptic digest of peptide was found similar with theoretical masses. The method can be used for both UV and MS based Peptide mapping and whereas the UV based peptide mapping method can be used as identification test for Calcitonin Salmon drug substance and drug product in quality control.

Plant Phosphopeptide Identification and Label-Free Quantification by MaxQuant and Proteome Discoverer Software

Both the phosphorylation and dephosphorylation of plant proteins is involved in multiple biological processes, especially in regard to signal transduction. The identification of phosphopeptides from MS (mass spectrometry)-based methods and their subsequent quantification play an important role in plant phosphoproteomics analysis. Phosphopeptide(s) identification and label-free quantification can determine dynamic changes of phosphorylation events in plants. Both MaxQuant and Proteome Discoverer are professional software tools used to identify and quantify large-scale MS-based phosphoproteomic data. This chapter gives a detailed workflow of MaxQuant and Proteome Discoverer software to analyze large amounts of phosphoproteomic-related MS data for the identification and quantification of label-free plant phosphopeptides.

Proteomic profiling of Serratia marcescens by high-resolution mass spectrometry

Introduction: Serratia marcescens, an opportunistic human pathogen, is reported as an important cause of nosocomial infection and outbreaks. Although the genome of S. marcescens (ATCC 13880) was completely sequenced by 2014, there are no studies on the proteomic profile of the organism. The objective of the present study is to analyze the protein profile of S. marcescens (ATCC 13880) using a high resolution mass spectrometry (MS). Methods: Serratia marcescens ATCC 13880 strain was grown in Luria-Bertani broth and the protein extracted was subjected to trypsin digestion, followed by basic reverse phase liquid chromatography fractionation. The peptide fractions were then analysed using Orbitrap Fusion Mass Spectrometry and the raw MS data were processed in Proteome Discoverer software. Results: The proteomic analysis identified 15 009 unique peptides mapping to 2541 unique protein groups, which corresponds to approximately 54% of the computationally predicted protein-coding genes. Bioinformatic analysis of these identified proteins showed their involvement in biological processes such as cell wall organization, chaperone-mediated protein folding and ATP binding. Pathway analysis revealed that some of these proteins are associated with bacterial chemotaxis and beta-lactam resistance pathway. Conclusion: To the best of our knowledge, this is the first high-throughput proteomics study of S. marcescens (ATCC 13880). These novel observations provide a crucial baseline molecular profile of the S. marcescens proteome which will prove to be helpful for the future research in understanding the host-pathogen interactions during infection, elucidating the mechanism of multidrug resistance, and developing novel diagnostic markers or vaccine for the disease.

Novel interconnections of HOG signaling revealed by combined use of two proteomic software packages

Modern quantitative mass spectrometry (MS)-based proteomics enables researchers to unravel signaling networks by monitoring proteome-wide cellular responses to different stimuli. MS-based analysis of signaling systems usually requires an integration of multiple quantitative MS experiments, which remains challenging, given that the overlap between these datasets is not necessarily comprehensive. In a previous study we analyzed the impact of the yeast mitogen-activated protein kinase (MAPK) Hog1 on the hyperosmotic stress-affected phosphorylome. Using a combination of a series of hyperosmotic stress and kinase inhibition experiments, we identified a broad range of direct and indirect substrates of the MAPK. Here we re-evaluate this extensive MS dataset and demonstrate that a combined analysis based on two software packages, MaxQuant and Proteome Discoverer, increases the coverage of Hog1-target proteins by 30%. Using protein-protein proximity assays we show that the majority of new targets gained by this analysis are indeed Hog1-interactors. Additionally, kinetic profiles indicate differential trends of Hog1-dependent versus Hog1-independent phosphorylation sites. Our findings highlight a previously unrecognized interconnection between Hog1 signaling and the RAM signaling network, as well as sphingolipid homeostasis.

Proteomic analysis of human vitreous humor

Background

The vitreous humor is a transparent, gelatinous mass whose main constituent is water. It plays an important role in providing metabolic nutrient requirements of the lens, coordinating eye growth and providing support to the retina. It is in close proximity to the retina and reflects many of the changes occurring in this tissue. The biochemical changes occurring in the vitreous could provide a better understanding about the pathophysiological processes that occur in vitreoretinopathy. In this study, we investigated the proteome of normal human vitreous humor using high resolution Fourier transform mass spectrometry.

Results

The vitreous humor was subjected to multiple fractionation techniques followed by LC-MS/MS analysis. We identified 1,205 proteins, 682 of which have not been described previously in the vitreous humor. Most proteins were localized to the extracellular space (24%), cytoplasm (20%) or plasma membrane (14%). Classification based on molecular function showed that 27% had catalytic activity, 10% structural activity, 10% binding activity, 4% cell and 4% transporter activity. Categorization for biological processes showed 28% participate in metabolism, 20% in cell communication and 13% in cell growth. The data have been deposited to the ProteomeXchange with identifier PXD000957.

Conclusion

This large catalog of vitreous proteins should facilitate biomedical research into pathological conditions of the eye including diabetic retinopathy, retinal detachment and cataract.