On graphical and numerical characterization of proteomics maps

We outlined a mathematical approach suitable for characterization of experimental data given by 2-D densitograms. In particular we consider numerical characterization of proteomics maps. The basis of our approach is to order "spots" of a 2-D map and assign them unique labels (that in general will depend on the criteria used for ordering). In this way a map is "translated" into a sequence. In the next step one associates with the generated sequence a geometrical path and views such a path as a mathematical object that needs characterization. We have ordered spots representing proteins in 2-D gel plates according to their relative intensities which results in a zigzag path that produces a complicated "fingerprint" pattern. Mathematical characterization of zigzag pattern follows similar mathematical characterizations of embedded patterns based on matrices, the elements of which are given as quotients of Euclidean distance between spots and the distance along the zigzag path. The leading eigenvalue of constructed matrices is taken to represent characterization of the original 2-D map. Comparison of different 2-D maps (simulated by using random generator) allows one to construct partial order, which although qualitative in nature gives some insight into perturbation induced by foreign agents to the proteome of the control cell.     

The cloning of human genes using cDNA phage display and small-molecule chemical probes

The cloning of genes based on protein function has become a powerful tool for protein discovery and should play an important role in proteomics in general. We have recently reported a technique for the functional identification of protein targets by combining traditional affinity chromatography with cDNA phage display. This procedure, referred to as display cloning, directly couples biologically active natural products to the gene of their protein cellular target. We now report the cloning of a human gene, the domain of F1 ATP synthase, using a synthetic scaffold molecule which serves as a prototype for a diverse chemical library. The ability to select genes from cDNA libraries using probes from combinatorial libraries would greatly increase the number of small molecule/protein interactions that can be identified. This method might prove valuable in furthering our understanding of biology and its application toward drug development.     

Overview of software options for processing,analysis and interpretation of mass spectrometric proteomic data

Recently, the interests in proteomics have been intensively increased, and the proteomic methods have been widely applied to many problems in cell biology. If the age of 1990s is considered to be a decade of genomics, we can claim that the following years of the new century is a decade of proteomics. The rapid evolution of proteomics has continued through these years, with a series of innovations in separation techniques and the core technologies of two‐dimensional gel electrophoresis and MS. Both technologies are fueled by automation and high throughput computation for profiling of proteins from biological systems. As Patterson ever mentioned, ‘data analysis is the Achilles heel of proteomics and our ability to generate data now outstrips our ability to analyze it’. The development of automatic and high throughput technologies for rapid identification of proteins is essential for large‐scale proteome projects and automatic protein identification and characterization is essential for high throughput proteomics. This review provides a snap shot of the tools and applications that are available for mass spectrometric high throughput biocomputation. The review starts with a brief introduction of proteomics and MS. Computational tools that can be employed at various stages of analysis are presented, including that for data processing, identification, quantification, and the understanding of the biological functions of individual proteins and their dynamic interactions. The challenges of computation software development and its future trends in MS‐based proteomics have also been speculated. Copyright © 2014 John Wiley & Sons, Ltd.     

Mass spectrometry based proteomic analysis of human stem cells: a brief review

Stem cells can give rise to various cell types and are capable of regenerating themselves over multiple cell divisions. Pluripotency and self-renewal potential of stem cells have drawn vast interest from different disciplines, with studies on the molecular properties of stem cells being one example. Current investigations on the molecular basis of stem cells pluripotency and self-renewal entail traditional techniques from chemistry and molecular biology. In this mini review, we discuss progress in stem cell research that employs proteomics approaches. Specifically, we focus on studies on human stem cells from proteomics perspective. To our best knowledge, only the following types of human stem cells have been examined via proteomics analysis: human neuronal stem cells, human mesenchymal stem cells, and human embryonic stem cells. Protein expression serves as biomarkers of stem cells and identification and expression level of such biomarkers are usually determined using two-dimensional electrophoresis coupled mass spectrometry or non-gel based mass spectrometry.     

Proteomics and Its Application in Biomarker Discovery and Drug Development

Proteomics is a research field aiming to characterize molecular and cellular dynamics in protein expression and function on a global level. The introduction of proteomics has been greatly broadening our view and accelerating our path in various medical researches. The most significant advantage of proteomics is its ability to examine a whole proteome or sub-proteome in a single experiment so that the protein alterations corresponding to a pathological or biochemical condition at a given time c…     

Identification of glycosylated marker proteins of epithelial polarity in MDCK cells by homology driven proteomics

Background

MDCK cells derived from canine kidney are an important experimental model system for investigating epithelial polarity in mammalian cells. Monoclonal antibodies against apical gp114 and basolateral p58 have served as important tools in these studies. However, the molecular identity of these membrane glycoproteins has not been known.

Results

We have identified the sialoglycoprotein gp114 as a dog homologue of the carcinoembryonic antigen-related cell adhesion molecule (CEACAM) family. Gp114 was enriched from tissue culture cells by subcellular fractionation and immunoaffinity chromatography. The identification was based on tandem mass spectrometry and homology based proteomics. In addition, the p58 basolateral marker glycoprotein was found to be the β subunit of Na⁺K⁺-ATPase.

Conclusion

Gp114 has been characterized previously regarding glycosylation dependent trafficking and lipid raft association. The identification as a member of the canine CEACAM family will enable synergy between the fields of epithelial cell biology and other research areas. Our approach exemplifies how membrane proteins can be identified from species with unsequenced genomes by homology based proteomics. This approach is applicable to any model system.     

Quantum effects in biology

The idea that quantum-mechanical phenomena can play nontrivial roles in biology has fascinated researchers for a century. Here we review some examples of such effects, including light-harvesting in photosynthesis, vision, electron- and proton-tunneling, olfactory sensing, and magnetoreception. We examine how experimental tests have aided this field in recent years and discuss the importance of developing new experimental probes for future work. We examine areas that should be the focus of future studies and touch on questions such as biological relevance of quantum-mechanical processes. To exemplify current research directions, we provide some detailed discussions of quantum-coherence in photosynthetic light-harvesting and highlight the crucial interplay between experiment and theory that has provided leaps in our understanding. We address questions about why coherence matters, what it is, how it can be identified, and how we should think about optimization of light-harvesting and the role coherence plays.     

An alternative approach to deal with geometric uncertainties in computer analysis of two-dimensional electrophoresis gels

With the growing importance of proteomics in biomedical and pharmaceutical sciences a need has emerged for computing tools that are capable of digitally visualizing and analyzing protein spot patterns within two-dimensional electrophoresis (2-DE) gel. Matching programs need to meet requirements such as interlaboratory comparison and the comparison of samples from different origins. For such research purposes, we have developed the CAROL system that implements new algorithms for spot detection and matching, which enable researchers to take a different approach to protein spot identification and comparison. The present short communication discusses how the system deals with uncertain geometric spot information that arises from streaks and complex spot regions and how this can be amplified for the matching procedure.     

Biomic study of human myeloid leukemia cells differentiation to macrophages using DNA array,proteomic, and bioinformatic analytical methods

A biomic approach by integrating three independent methods, DNA microarray, proteomics and bioinformatics, is used to study the differentiation of human myeloid leukemia cell line HL-60 into macrophages when induced by 12-O-tetradecanoyl-phorbol-13-acetate (TPA). Analysis of gene expression changes at the RNA level using cDNA against an array of 6033 human genes showed that 5950 (98.6%) of the genes were expressed in the HL-60 cells. A total of 624 genes (10.5%) were found to be regulated during HL-60 cell differentiation. Most of these genes have not been previously associated with HL-60 cells and include genes encoded for secreted proteins as well as genes involved in cell adhesion, signaling transduction, and metabolism. Protein analysis using two-dimensional gel electrophoresis showed a total of 682 distinct protein spots; 136 spots (19.9%) exhibited quantitative changes between HL-60 control and macrophages. These differentially expressed proteins were identified by mass spectrometry. We developed a bioinformatics program, the Bulk Gene Search System (BGSS, http://www.sinica.edu.tw:8900/perl/genequery.pl) to search for the functions of genes and proteins identified by cDNA microarrays and proteomics. The identified regulated proteins and genes were classified into seven groups according to subcellular locations and functions. This powerful holistic biomic approach using cDNA microarray, proteomics coupled to bioinformatics can provide in-depth information on the impact and importance of the regulated genes and proteins for HL-60 differentiation.     

Interrogation of MS/MS search data with an pI Filter algorithm to increase protein identification success

In high-throughput proteomics, the bottom-up approach has become a widely used method for the identification of proteins that is based on tryptic peptide MS/MS analysis. Separation methodologies that use IEF of tryptic peptides have recently been introduced and provide an extra dimension of peptide separation. In addition to its great fractionation capability, tryptic peptide prefractionation by IEF can also increase the protein identification success. The pI information of the peptide gained can be successfully used in a post-database search filtering step. We introduce a filtering algorithm that is based on the comparison of the experimental and theoretical pI's to validate peptide identifications by MS/MS data search engines.     

Screening and selection methods for large-scale analysis of protein function

High-throughput assays hold tremendous promise for protein engineering and proteomics. With powerful assays it should be possible to evolve, for example, a stereoselective esterase for the chemical synthesis or a site-specific endonuclease for biomedical research. Entire cDNA libraries, which encode all of the proteins expressed in a given organism or cell line, should simply be passed through a battery of biochemical assays to determine the function of each individual protein. Herein we look at the types of assays that have been developed and how close we are to our goals of engineering proteins with new activities as well as rapidly assigning function to the thousands of proteins that make up each genome.     

On 3-D graphical representation of proteomics maps and their numerical characterization

We consider numerical characterization of proteomics maps by representing a map as a three-dimensional graphical object based on x, y coordinates of the spots and using their relative abundance as the z coordinate. In our representation the protein spots are first ordered based on their relative abundance and labeled accordingly. In the next step a 3-D path is constructed connecting spots having adjacent labels. Finally a matrix is constructed by assigning to each pairs of labels (i, j) matrix element, the numerical value of which is based on the quotients of the Euclidean distance and the distance along the 3-D zigzag between the two points. The approach has been illustrated on a fragment of a proteomics map and compared with 2-D graphical representation of proteomics maps.     

Proteomics and peptidomics in neuroscience. Experience of capabilities and limitations in a neurochemical laboratory

The increasing use of proteomics has created a basis for new strategies to develop methodologies for rapid identification of protein patterns in living organisms. It has also become evident that proteomics has other potential applications than protein and peptide identification, e.g. protein characterization, with the aim of revealing their structure, function(s) and interactions of proteins. In comparative proteomics studies, the protein expression of a certain biological system is compared with another system or the same system under perturbed conditions. Global identification of proteins in neuroscience is extremely complex, owing to the limited availability of biological material and very low concentrations of the molecules. Moreover, in addition to proteins, there are number of peptides that must also be considered in global studies on the central nervous system. In this overview, we focus on and discuss problems related to the different sources of biological material and sample handling, which are part of all preparatory and analytical steps. Straightforward protocols are desirable to avoid excessive purification steps, since loss of material at each step is inevitable. We would like to merge the two worlds of proteomics/peptidomics and neuroscience, and finally we consider different practical and technical aspects, illustrated with examples from our laboratory.     

Identification of Proteins Interacting with Ubiquitin Chains

Ubiquitylation, the modification of proteins with ubiquitin (Ub), is one of the most versatile post‐translational modifications in eukaryotic cells. Since Ub also serves as its own substrate, proteins can be modified by numerous different Ub chains, in which the individual moieties are linked via one or several of the seven lysines of Ub. Homogeneous Ub chains, in which the moieties are sequentially linked via the same residue, have been most extensively studied. However, due to their restricted availability, the functions of Ub chains linked via K27, K29, or K33 are poorly understood. We have developed an approach that, for the first time, allows the generation of all seven homogeneous Ub chains in large quantities. The potential of our approach is demonstrated by the identification of previously unknown interaction partners of K27‐, K29‐, and K33‐linked Ub chains by affinity‐based proteomics.     

Development of an effective sample preparation approach for proteomic analysis of silkworm eggs using two-dimensional gel electrophoresis and mass spectrometry

Sample preparation is still the first and important step toward successful two-dimensional gel electrophoresis (2DE) and identification in proteomics study. The 2DE profiling of eggs of silkworm species by using conventional one-step extraction, however, is unsatisfactory because high-abundance proteins such as egg-specific protein (ESP) and No 30 family (30 KP) in the extract lead to difficulties in detecting most of biologically relevant proteins. Based on the tendency of these abundant proteins to be soluble in Tris-HCl buffer, we report herein a robust approach in which the extract enriched in ESP and 30 KP was fractionationed and mixed with the re-extract of residual pellet in an optimal proportion. In comparison with the one-step method, the 2DE pattern was improved by this new method with over one-third enhancement in spots. A total of 48 unique proteins obtained have been furthermore identified by mass spectrometry (MS) and MS/MS. The identified proteins are found to include heat shock proteins families, ribosomal proteins, disulfide isomerase proteins, Glutathione S-transferase, and elongation factor, etc., which are mainly involved in some important processes. To our knowledge, this is the first time that the several proteins have been detected in silkworm eggs by proteomics means. This simple and reproducible approach would raise the opportunity of discovering and identifying more biomarkers and determining their possible roles in further studies.     

Application of mass spectrometry in silkworm research—Review

In this first mass spectrometry‐focused review paper, we will review current applications of mass spectrometry in the area of silkworm research. We will focus our review on the following two most important areas as they are currently being researched by scientists. Firstly, the proteomics of proteins in the process of silkworm lifecycle has generated knowledge about previous undetected proteins, some of which might possess therapeutic effects. Secondly, fatty acids, which are the other major components in silkworm, have several potential medical applications. We will also highlight potential areas warranting further investigation.     

Applications of Molecular Imprinting Technology in the Study of Traditional Chinese Medicine

Traditional Chinese medicine (TCM) is one of the most internationally competitive industries. In the context of TCM modernization and internationalization, TCM-related research studies have entered a fast track of development. At the same time, research of TCM is also faced with challenges, such as matrix complexity, component diversity and low level of active components. As an interdisciplinary technology, molecular imprinting technology (MIT) has gained popularity in TCM study, owing to the produced molecularly imprinted polymers (MIPs) possessing the unique features of structure predictability, recognition specificity and application universality, as well as physical robustness, thermal stability, low cost and easy preparation. Herein, we comprehensively review the recent advances of MIT for TCM studies since 2017, focusing on two main aspects including extraction/separation and purification and detection of active components, and identification analysis of hazardous components. The fundamentals of MIT are briefly outlined and emerging preparation techniques for MIPs applied in TCM are highlighted, such as surface imprinting, nanoimprinting and multitemplate and multifunctional monomer imprinting. Then, applications of MIPs in common active components research including flavonoids, alkaloids, terpenoids, glycosides and polyphenols, etc. are respectively summarized, followed by screening and enantioseparation. Related identification detection of hazardous components from TCM itself, illegal addition, or pollution residues (e.g., heavy metals, pesticides) are discussed. Moreover, the applications of MIT in new formulation of TCM, chiral drug resolution and detection of growing environment are summarized. Finally, we propose some issues still to be solved and future research directions to be expected of MIT for TCM studies.     

蛋白质组研究中的多维液相色谱技术

对近年来蛋白质组研究中的多维液相色谱技术进行了系统综述,洋细介绍了在线及离线式阀切换接口的DALPC（direct analysis of large proein complexes）技术及整体式无接口的MudPIT（muhidimensional protein ideutification technology）系统,也系统阐述了其在蛋白质组研究中的应用。引用文献50篇。     

A comparative study of proteomics maps using graph theoretical biodescriptors

This paper reports the development of new methods for mathematical characterization of effects of different toxic agents on the cellular proteome. We describe numerical characterization of proteomics maps based on mathematical invariants. A graph is first associated with a proteomics map by considering partial ordering of spots on 2-D gels by ordering proteins with respect to the mass and the charge, the two properties by which proteins are separated. The graph is then embedded over the map, and several graph theoretical invariants have been constructed. In particular we consider invariants that can be extracted from the Euclidean distance-adjacency matrix of the embedded graph, in which only Euclidean distances between adjacent vertices of a graph are considered. The approach is illustrated using proteomics patterns of normal liver cells of rats and those derived from liver cells of animals exposed to four peroxisome proliferators. In contrast to direct comparison of spot abundance our approach incorporates information on spots locations. The difference between the two approaches is that in the first case only changes in abundances are considered as a measure of perturbation of the proteome map, but in the second case not only the charge but also the mass of proteins are used for ordering protein spots.     

Therapeutic Potential of Targeting the HMGB1/RAGE Axis in Inflammatory Diseases

High mobility group box 1 (HMGB1) is a nuclear protein that can interact with a receptor for advanced glycation end-products (RAGE; a multi-ligand immunoglobulin receptor) and mediates the inflammatory pathways that lead to various pathological conditions, such as cancer, diabetes, neurodegenerative disorders, and cardiovascular diseases. Blocking the HMGB1/RAGE axis could be an effective therapeutic approach to treat these inflammatory conditions, which has been successfully employed by various research groups recently. In this article, we critically review the structural insights and functional mechanism of HMGB1 and RAGE to mediate inflammatory processes. More importantly, current perspectives of recent therapeutic approaches utilized to inhibit the communication between HMGB1 and RAGE using small molecules are also summarized along with their clinical progression to treat various inflammatory disorders. Encouraging results are reported by investigators focusing on HMGB1/RAGE signaling leading to the identification of compounds that could be useful in further clinical studies. We highlight the current gaps in our knowledge and future directions for the therapeutic potential of targeting key molecules in HMGB1/RAGE signaling in the pathophysiology of inflammatory diseases.