Method For Identification Of Proteins Research Articles

Fishing out Methionine-Containing Proteins from Complex Biological Systems Based on a Non-Enzymatic Biochemical Reaction.

Nowadays, it still remains a great challenge to develop a simple, fast, and low-toxic method for identification and separation of proteins from complex biological systems. Herein, a nanocomposite (Fe3O4@Au-Se-peptide) was designed and synthesized to fish out methionine-containing proteins based on a non-enzymatic biochemical reaction, which couples amino groups of lysine with the S-methyl group of methionine in the presence of HOBr. Peptides which contain four lysine residues (Lys-Lys-Lys-Lys-{Se-Cys}) linked to the Fe3O4@Au nanocomposites were used to capture methionine residues efficiently via a S═N cross-linking. The methionine-containing protein was obtained by magnetic separation and released from the Fe3O4@Au-Se-peptide nanocomposites with the influence of H2Se. The HRMS and SDS-PAGE results confirmed the methionine-containing protein could be successfully fished out from a mixture solution. This work provides a useful strategy for recognition and separation of a category of proteins from complex biological systems.

In Vivo Cross-Linking Followed by polyA Enrichment to Identify Yeast mRNA Binding Proteins.

mRNA binding proteins regulate gene expression by controlling the processing, localization, decay, and translation of messenger RNAs (mRNAs). To fully understand these mechanisms of posttranscriptional gene regulation, it is necessary to identify the complete set of mRNA binding proteins. In recent years, several assays have been developed to accomplish this goal in a wide variety of organisms. This work describes a method for the systematic identification of mRNA binding proteins in Saccharomyces cerevisiae. This method applies in vivo UV cross-linking, affinity pull-down of polyA(+) mRNAs, and analysis by mass spectrometry to identify proteins that directly bind to mRNAs.

Method for identification of heme-binding proteins and quantification of their interactions

The standard assay for characterization of interaction of heme with proteins is absorbance spectroscopy. However, this approach demands relatively large quantities of proteins and it is difficult to perform in high-throughput manner. Here, we describe an immunosorbent assay based on the covalent in situ conjugation of heme to a pre-coated carrier. Advantage of this assay is that it allows both identification of heme-binding proteins and quantification of their binding avidity, using only minimal amounts of protein (1–10 μg). Importantly, the same approach can be used for covalent linkage of other natural or synthetic compounds and analyzing their interactions with proteins.

Inferring essential proteins from centrality in interconnected multilayer networks

Computational tool for inferring essential genes and their coding essential proteins based on its topological features in biological network is crucial for insights into vital and disease mechanism of organisms. The problem of how to quantify this correspondence via network centralities in an incomplete protein interaction network (PIN), such as that of human, remains open. Here we develop Random Walk Occupation (RWO) augmented method in interconnected multilayer network model to disclose topological characteristics of essential proteins. The peculiar non-hub essential proteins can be revealed in yeast–human interconnected networks. Statistically RWO augmented method performs well, and improves the prediction results in incomplete human PIN and maintains noticeable performance in well-tested yeast PIN. Biologically, the detected non-hub essential proteins really participate in some vital biological function. Overall, we present a systematic method for deeper understanding and effective identification of essential proteins.

MealTime-MS: A Machine Learning-Guided Real-Time Mass Spectrometry Analysis for Protein Identification and Efficient Dynamic Exclusion.

Mass spectrometry-based proteomics technologies are prime methods for the high-throughput identification of proteins in complex biological samples. Nevertheless, there are still technical limitations that hinder the ability of mass spectrometry to identify low abundance proteins in complex samples. Characterizing such proteins is essential to provide a comprehensive understanding of the biological processes taking place in cells and tissues. Still today, most mass spectrometry-based proteomics approaches use a data-dependent acquisition strategy, which favors the collection of mass spectra from proteins of higher abundance. Since the computational identification of proteins from proteomics data is typically performed after mass spectrometry analysis, large numbers of mass spectra are typically redundantly acquired from the same abundant proteins, and little to no mass spectra are acquired for proteins of lower abundance. We therefore propose a novel supervised learning algorithm, MealTime-MS, that identifies proteins in real-time as mass spectrometry data are acquired and prevents further data collection from confidently identified proteins to ultimately free mass spectrometry resources to improve the identification sensitivity of low abundance proteins. We use real-time simulations of a previously performed mass spectrometry analysis of a HEK293 cell lysate to show that our approach can identify 92.1% of the proteins detected in the experiment using 66.2% of the MS2 spectra. We also demonstrate that our approach outperforms a previously proposed method, is sufficiently fast for real-time mass spectrometry analysis, and is flexible. Finally, MealTime-MS' efficient usage of mass spectrometry resources will provide a more comprehensive characterization of proteomes in complex samples.

Prion diseases and the biosecurity problems.

The review presents the current state of the problem of prions and prion diseases with an emphasis on theepidemiological and epizootological risks of pathogens that cause fatal neurodegenerative diseases in humans and animals. The results of molecular genetic studies of the conversion of normal PrPc prion protein molecules to infectious forms of PrPd, resistance to physical disinfection methods, in particular exceptional thermal stability, and their ability to overcome interspecific barriers, while increasing virulence, are described. The possibility of infection not only by nutrition, when eating even heat-treated meat of sick animals, but also due to surgical interventions, especially neurosurgical and ophthalmic, as well as the use of immunobiological preparations, are emphasized. Since there are currently no means for the effective treatment of prion diseases in the world, attention is drawn to the high degree of relevance for the biosafety of the country to develop domestic highly sensitive test systems that can effectively detect prion infectious protein in vivo at the preclinical stage of the disease. The latest methods of automatic protein amplification and identification of prion proteins are briefly described as the most promising areas of research in the field of diagnosis of prion diseases.

In situ 3D visualization of biomineralization matrix proteins

Calcium biominerals occur in all major animal phyla, and through biomolecular control, exhibit such diverse structures as exoskeletons, shells, bones, teeth and earstones (otoliths). Determining the three-dimensional expression of key biomineral proteins, however, has proven challenging as typical protein identification methods either lose spatial resolution during dissolution of the mineral phase or are costly and limited to two-dimensional expression of high abundance proteins. Here we present a modification of the CLARITY and ACT-PRESTO protocols to visualize and confirm, for the first time, the timing of expression and function of two key regulators of biomineralization.

Identification of Target Protein for Bio-active Small Molecule Using Photo-cross Linked Beads and MALDI-TOF Mass Spectrometry

Development of methods for protein identification is one of the important aspects of proteomics. Here, we report a protocol for the preparation of compound conjugated beads by photo-crosslinking, affinity purification, gel electrophoresis, and highly sensitive mass spectrometric assay for drug-target identification. Although there are several other methods used for drug-target identification, such as biochemical fractionation or radioactive ligand binding assay, affinity purification is widely used for its straight-forward and easy approach. To identify the target protein of an inhibitor of cancer cell-accelerated fibroblast migration, we prepared the inhibitor-conjugated beads by photo-crosslinking. Proteins were pulled down from cell lysates by the compound beads and separated by SDS-PAGE, and a specifically pulled down protein was cut out, trypsin-digested, analyzed using matrix-assisted laser desorption ionization/time of flight mass spectrometry (MALDI-TOF-MS) and identified by peptide mass fingerprinting (PMF) method. Since the photo-crosslinking enables the immobilization of ligands on an affinity matrix in a functional group-independent manner, we do not have to determine the functional group of the compound to conjugate the matrix. In addition, as compared to other MS techniques such as electrospray ionization, MALDI offers a less complex sample preparation procedure and higher sensitivity, and thus is better suited for the rapid identification of proteins isolated by gel electrophoresis.

Electroblotting through a tryptic membrane for LC-MS/MS analysis of proteins separated in electrophoretic gels.

Digestion of proteins separated via sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) remains a popular method for protein identification using mass-spectrometry based proteomics. Although robust and routine, the in-gel digestion procedure is laborious and time-consuming. Electroblotting to a capture membrane prior to digestion reduces preparation steps but requires on-membrane digestion that yields fewer peptides than in-gel digestion. This paper develops direct electroblotting through a trypsin-containing membrane to a capture membrane to simplify extraction and digestion of proteins separated by SDS-PAGE. Subsequent liquid chromatography-tandem mass spectrometry (LC-MS/MS) identifies the extracted peptides. Analysis of peptides from different capture membrane pieces shows that electrodigestion does not greatly disturb the spatial resolution of a standard protein mixture separated by SDS-PAGE. Electrodigestion of an Escherichia coli (E. coli) cell lysate requires four hours of total sample preparation and results in only 13% fewer protein identifications than in-gel digestion, which can take 24 h. Compared to simple electroblotting and protein digestion on a poly(vinylidene difluoride) (PVDF) capture membrane, adding a trypsin membrane to the electroblot increases the number of protein identifications by 22%. Additionally, electrodigestion experiments using capture membranes coated with polyelectrolyte layers identify a higher fraction of small proteolytic peptides than capture on PVDF or in-gel digestion.

Development of a Differential Multiplex PCR Assay for the Supplemental Identification of Different Sources of Proteins

Differentiation of proteins from multiple sources provides challenges in the accuracy using multiple and often disputed protein identification methods. The U.S. Pharmacopeia Food Chemical Codex does not include monographs for many protein sources, including milk proteins and soy protein isolate. Monographs that are included for proteins do not list a single comprehensive identification method but instead rely on a combined assessment of ash (total), fat, lactose, loss on drying, and protein content. A fast, inexpensive, and accurate protein source assay is tantamount to prevention of economic adulteration in protein powders. This study describes the development of a novel method to identify and differentiate animal proteins (cow protein powders as milk protein and whey protein) and plant proteins (soy protein powders). These proteins powders are of high importance to the food and dietary supplement industries, as they encompass the highest grossing and fastest growing protein sources in the global protein powder market. The developed method uses PCR amplification and gel electrophoresis of short chain DNA fragments found in processed protein powders to identify and differentiate the source of each powder. The original development was performed using reference materials of known identity and tested against an inclusivity panel of protein powders from commercial sources. Bands were identified using the Agilent Tapestation 4200 and Tapestation Analysis Software A.02.02 (SR1) using proprietary band analysis. The developed method was found to be specific for the identification of each protein source, passing a computational (National Center for Biotechnology Information Basic Local Alignment Search Tool) exclusivity panel and an experimental inclusivity panel. The method was also able to detect multiple adulterants in concentrations as low as 1% (w/w). The developed method is fast, inexpensive, and accurate (100%) for the supplemental identification of cow and soy proteins and able to detect adulteration as low as 1% (w/w). A new method can identify cow and soy proteins, and detect low levels of adulteration using DM-PCR.

Chemical Proteomic Profiling of Lysophosphatidic Acid-Binding Proteins.

Lysophosphatidic acid (LPA) is an endogenous cell signaling molecule, and dysregulation of LPA signaling pathways is accompanied by several types of cancer. Herein, we developed a chemical proteomic method for the proteome-wide identification of LPA-binding proteins. The method involves the synthesis of a desthiobiotin-conjugated LPA acyl phosphate probe for the covalent labeling, enrichment, and subsequent LC-MS/MS identification of LPA-binding proteins at the proteome-wide level. By conducting labeling reactions at two different probe concentrations (10 and 100 μM) in conjunction with an SILAC (stable isotope labeling by amino acids in cell culture)-based workflow, we characterized the LPA-binding capabilities of these proteins at the entire proteome scale, which led to the identification of 86 candidate LPA-binding proteins in HEK293T cells. Moreover, we validated that two of these proteins, annexin A5 and phosphoglycerate kinase 1, can bind directly with LPA. Together, we developed a novel LPA probe for the identification and characterizations of LPA-binding proteins from the entire human proteome. The method should be adaptable for the identification of other lipid-binding proteins.

Cell-SELEX, an Effective Way to the Discovery of Biomarkers and Unexpected Molecular Events.

Cell-SELEX can not only generate aptamers for specific cell isolation/detection, diagnosis, and therapy, but also lead to the discovery of biomarkers and unexpected molecular events. However, most cell-SELEX research is concentrated on aptamer generation and applications. In this progress report, recent research progress with cell-SELEX in terms of the discovery of biomarkers and unexpected molecular events is highlighted. In particular, the key technical challenges for cell-SELEX-based biomarker discovery, namely, the methods for identification and validation of target proteins of aptamers, are discussed in detail. Finally, the prospects of the applications of cell-SELEX in this field now and in the near future are described. It is expected that this report will attract attention to the benefit of cell-SELEX and provide a practical reference for biomedical researchers.

Amyloidosis: diagnosis and new therapies for a misunderstood and misdiagnosed disease.

Amyloidosis is a group of diseases characterized by extracellular deposition of amyloid fibril complexes. Fibril deposition results in organ dysfunction and possible failure. Amyloidosis is regarded as a rare disease, but in general is underdiagnosed. The two main types of systemic amyloidosis are immunoglobulin light chain and transthyretin amyloidosis. The increased availability of noninvasive cardiac imaging, genetic testing and improved laboratory assays and protein identification methods have led to increased diagnosis. However, in many cases, the diagnosis is not made until the patient develops organ impairment. Earlier diagnosis is required to prevent irreversible organ failure. Novel treatments for immunoglobulin light chain and transthyretin amyloidosis that halt disease progression, prolong and increase quality of life have recently become available.

Comparative Proteomics Analysis of Four Commonly Used Methods for Identification of Novel Plasma Membrane Proteins.

Plasma membrane proteins perform a variety of important tasks in the cells. These tasks can be diverse as carrying nutrients across the plasma membrane, receiving chemical signals from outside the cell, translating them into intracellular action, and anchoring the cell in a particular location. When these crucial roles of plasma membrane proteins are considered, the need for their characterization becomes inevitable. Certain characteristics of plasma membrane proteins such as hydrophobicity, low solubility, and low abundance limit their detection by proteomic analyses. Here, we presented a comparative proteomics study in which the most commonly used plasma membrane protein enrichment methods were evaluated. The methods that were utilized include biotinylation, selective CyDye labeling, temperature-dependent phase partition, and density-gradient ultracentrifugation. Western blot analysis was performed to assess the level of plasma membrane protein enrichment using plasma membrane and cytoplasmic protein markers. Quantitative evaluation of the level of enrichment was performed by two-dimensional electrophoresis (2-DE) and benzyldimethyl-n-hexadecylammonium chloride/sodium dodecyl sulfate polyacrylamide gel electrophoresis (16-BAC/SDS-PAGE) from which the protein spots were cut and identified. Results from this study demonstrated that density-gradient ultracentrifugation method was superior when coupled with 16-BAC/SDS-PAGE. This work presents a valuable contribution and provides a future direction to the membrane sub-proteome research by evaluating commonly used methods for plasma membrane protein enrichment.

Simulation of single-protein nanopore sensing shows feasibility for whole-proteome identification

Single-molecule techniques for protein sequencing are making headway towards single-cell proteomics and are projected to propel our understanding of cellular biology and disease. Yet, single cell proteomics presents a substantial unmet challenge due to the unavailability of protein amplification techniques, and the vast dynamic-range of protein expression in cells. Here, we describe and computationally investigate the feasibility of a novel approach for single-protein identification using tri-color fluorescence and plasmonic-nanopore devices. Comprehensive computer simulations of denatured protein translocation processes through the nanopores show that the tri-color fluorescence time-traces retain sufficient information to permit pattern-recognition algorithms to correctly identify the vast majority of proteins in the human proteome. Importantly, even when taking into account realistic experimental conditions, which restrict the spatial and temporal resolutions as well as the labeling efficiency, and add substantial noise, a deep-learning protein classifier achieves 97% whole-proteome accuracies. Applying our approach for protein datasets of clinical relevancy, such as the plasma proteome or cytokine panels, we obtain ~98% correct protein identification. This study suggests the feasibility of a method for accurate and high-throughput protein identification, which is highly versatile and applicable.

Glycoproteomics Method to Discover Reliable Biomarkers from Human Plasma of Lung Cancer Patients for MS‐based Clinical Studies

In clinical and diagnostic proteomics, it is important to discover significant biomarkers from biosamples. Thus, a reliable proteomics methodology is required for the development and standardization of an MS‐based protein identification and quantification method in biosamples. In particular, plasma is one of the most complex fluids in the human body and is commonly used in hospitals to diagnose disease. The purpose of this study was to develop a reliable and reproducible proteomics method using lung cancer plasma for biomarker discovery and diagnostic kits for screening. Glycoproteins are well‐known to be associated with diseases (especially cancers) so in this study glycoproteomics was used for discovering biomarkers from lung cancer plasma. Thirty‐five lung cancer plasma were pooled, and glycoproteins were separated using lectin affinity chromatography (LAC). After affinity selection, trypsin‐digestion, and deglycosylation with PNGase F, the resulting deglycosylated peptides were analyzed with nLC–MS/MS runs twice. The corresponding parent proteins were identified separately through two database search engines and then analyzed individually. The identified proteins from each set were compared, combined, and then categorized for analysis. The combined total identified number of proteins were about 50% increased than in a single run and some proteins seemed to be more reproducible and reliable biomarker candidates because they were always identified in every run. From this research, method‐optimized proteomics can be applied to biomarker discovery for diagnosis and prognosis of disease such as cancer for better MS‐based clinical studies. The identified plasma proteins from this research will also be lung cancer biomarker candidates and can be utilized for the development of in vitro lung cancer diagnostic kits.

Methods for Systematic Identification of Membrane Proteins for Specific Capture of Cancer-Derived Extracellular Vesicles

SUMMARYAnalysis of cancer-derived extracellular vesicles (EVs) in biofluids potentially provides a source of disease biomarkers. At present there is no procedure to systematically identify which antigens should be targeted to differentiate cancer-derived from normal host cell-derived EVs. Here, we propose a computational framework that integrates information about membrane proteins in tumors and normal tissues from databases: UniProt, The Cancer Genome Atlas, the Genotype-Tissue Expression Project, and the Human Protein Atlas. We developed two methods to assess capture of EVs from specific cell types. (1) We used palmitoylated fluorescent protein (palmtdTomato) to label tumor-derived EVs. Beads displaying antibodies of interest were incubated with conditioned medium from palmtdTomato-expressing cells. Bound EVs were quantified using flow cytometry. (2) We also showed that membrane-bound Gaussia luciferase allows the detection of cancer-derived EVs in blood of tumor-bearing animals. Our analytical and validation platform should be applicable to identify antigens on EVs from any tumor type.

Proteomic Identification of Protein Glutathionylation in Cardiomyocytes.

Reactive oxygen species (ROS) are important signaling molecules, but their overproduction is associated with many cardiovascular diseases, including cardiomyopathy. ROS induce various oxidative modifications, among which glutathionylation is one of the significant protein oxidations that occur under oxidative stress. Despite previous efforts, direct and site-specific identification of glutathionylated proteins in cardiomyocytes has been limited. In this report, we used a clickable glutathione approach in a HL-1 mouse cardiomyocyte cell line under exposure to hydrogen peroxide, finding 1763 glutathionylated peptides with specific Cys modification sites, which include many muscle-specific proteins. Bioinformatic and cluster analyses found 125 glutathionylated proteins, whose mutations or dysfunctions are associated with cardiomyopathy, many of which include sarcomeric structural and contractile proteins, chaperone, and other signaling or regulatory proteins. We further provide functional implication of glutathionylation for several identified proteins, including CSRP3/MLP and complex I, II, and III, by analyzing glutathionylated sites in their structures. Our report establishes a chemoselective method for direct identification of glutathionylated proteins and provides potential target proteins whose glutathionylation may contribute to muscle diseases.

In silico method for identification of novel copper and iron metabolism proteins in various neurodegenerative disorders

Copper (Cu) and Iron (Fe) has been the subject of intensive research over several decades as numerous seminal studies robustly support the involvement of Cu and Fe metabolism dyshomeostasis as a common denominator in several neurodegenerative disorders (particularly Alzheimer’s disease and Parkinson’s disease); however, till date, the exact “cause-effect” association has not been elucidated. Thus, there is urgent need to look for newer association/pathways of these redox active elements in different neuropathological conditions. Therefore, in this study, we have used bioinformatics based approach to identify novel Cu and Fe metabolism proteins in neurodegenerative disorders using Cytoscape software. The network biology data demonstrated the association of secreted protein acidic and rich in cysteine (SPARC/osteonectin) protein with Alzheimer’s disease, Parkinson’s disease, Huntington’s disease and neurodegeneration with brain iron accumulation (NBIA) disease, whereas Coagulation factor V may have a role in Brunner Syndrome, Obsessive-Compulsive Disorder, Febrile seizures and Schizophrenia diseases. Further analysis revealed Coagulation factor VII possible role in L1 Syndrome and Congenital hydrocephalus disorders. In conclusion, the present study shows the first evidence in silico that SPARC/osteonectin, Coagulation factor V and VII proteins may have plausible role in the pathogenesis of various neurodegenerative diseases.

Purification and Proteomic Analysis of Alphavirus Particles from Sindbis Virus Grown in Mammalian and Insect Cells.

Current mass spectrometry (MS) methods and new instrumentation now allow for more accurate identification of proteins in low abundance than previous protein fractionation and identification methods. It was of interest if this method could serve to define the virus proteome of a membrane-containing virus. To evaluate the efficacy of mass spec to determine the proteome of medically important viruses, Sindbis virus (SINV), the prototypical alphavirus was chosen for evaluation. This model system was chosen specifically because the alphaviruses contain members which are human pathogens, this virus is well defined biochemically and structurally, and grows to high titers in both vertebrate and non-vertebrate host cells. The SINV proteome was investigated using this method to determine if host proteins are specifically packaged into infectious virions. It was also of interest if the SINV proteome, when grown in multiple host cells representing vertebrate and mosquito hosts, incorporated specific host proteins from all hosts. Observation of recurrent or distinctive proteins in the virus proteome aided in the determination of proteins incorporated into the virion as opposed to those bound to the particle exterior. Mass spectrometry analysis identified the total protein content of purified virions within limits of detection. The most significant finding was that in addition to the host proteins, SINV non-structural protein 2 (nsP2) was detected within virions grown in all host cells examined. This analysis identified host factors not previously associated with alphavirus entry, replication, or egress, identifying at least one host factor integrally involved in alphavirus replication. Key to the success of this analysis is the method of virus purification which must deliver measurably infectious virus free of high levels of contaminants. For SINV and other members of the alphavirus family, this is accomplished by isopycnic centrifugation through potassium tartrate, followed by a high salt wash.