Depletion of the high-abundance plasma proteins

Summary. Body fluids, like plasma and urine, are comparatively easy to obtain and are useful for the detection of novel diagnostic markers by applying new technologies, like proteomics. However, in plasma, several high-abundance proteins are dominant and repress the signals of the lower-abundance proteins, which then become undetectable either by two-dimensional gels or chromatography. Therefore, depletion of the abundant proteins is a prerequisite for the detection of the low-abundance components. We applied affinity chromatography on blue matrix and Protein G and removed the most abundant human plasma proteins, albumin and the immunoglobulin chains. The plasma proteins, prior to albumin and immunoglobulin depletion, as well the eluates from the two chromatography steps were analyzed by two-dimensional electrophoresis and the proteins were identified by MALDI-TOF-MS. The analysis resulted in the identification of 83 different gene products in the untreated plasma. Removal of the high-abundance proteins resulted in the visualization of new protein signals. In the eluate of the two affinity steps, mostly albumin and immunoglobulin spots were detected but also spots representing several other abundant plasma proteins. The methodology is easy to perform and is useful as a first step in the detection of diagnostic markers in body fluids by applying proteomics technologies.Current address: Foundation for Biomedical Research of the Academy of Athens, Greece     

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Mutational Pattern in the Fourth Pandemic Phase in Greece

The aim of this study is to investigate the circulating variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from Athens and from rural areas in Greece during July and August 2021. We also present a rapid review of literature regarding significant SARS-CoV-2 mutations and their impact on public health. A total of 2500 nasopharyngeal swab specimens were collected from suspected COVID-19 cases (definition by WHO 2021b). Viral nucleic acid extraction was implemented using an automatic extractor and the RNA recovered underwent qRT-PCR in order to characterize the specimens as positive or negative for SARS-CoV-2. The positive specimens were then used to identify specific Spike gene mutations and characterize the emerging SARS-CoV-2 variants. For this step, various kits were utilized. From the 2500 clinical specimens, 220 were tested positive for SARS-CoV-2 indicating a prevalence of 8.8% among suspected cases. The RT-PCR Ct (Cycle threshold) Value ranged from 19 to 25 which corresponds to medium to high copy numbers of the virus in the positive samples. From the 220 positive specimens 148 (67.3%) were from Athens and 72 (32.7%) from Greek rural areas. As far as the Spike mutations investigated: N501Y appeared in all the samples, D614G mutation appeared in 212 (96.4%) samples with a prevalence of 87.2% in Athens and 98.6% in the countryside, E484K had a prevalence of 10.8% and 12.5% in Athens and the rural areas, respectively. K417N was found in 18 (12.2%) samples from Athens and four (5.6%) from the countryside, P681H was present in 51 (34.5%) Athenian specimens and 14 (19.4%) specimens from rural areas, HV69-70 was carried in 32.4% and 19.4% of the samples from Athens and the countryside, respectively. P681R had a prevalence of 87.2% in Athens and 98.6% in rural areas, and none of the specimens carried the L452R mutation. 62 (28.2%) samples carried the N501Y, P681H, D614G and HV69-70 mutations simultaneously and the corresponding variant was characterized as the Alpha (UK) variant (B 1.1.7). Only six (2.7%) samples from the center of Athens had the N501Y, E484K, K417N and D614G mutations simultaneously and the virus responsible was characterized as the Beta (South African) variant (B 1.351). Our study explored the SARS-CoV-2 variants using RT-PCR in a representative cohort of samples collected from Greece in July and August 2021. The prevalent mutations identified were N501Y (100%), D614G (96.4%), P681R (90.1%) and the variants identified were the Delta (90.1%), Alpha (28.2%) and Beta (2.7%).     

蛋白质组学-引领后基因组时代

蛋白质组学是建立在高通量筛选技术的基础上发展的方法学,用于研究细胞功能网络模块中蛋白相互作用及在疾病或病变中蛋白和蛋白相互作用所发生的系统动态的差异变化;其研究技术奠基于双向凝胶电泳。及至世纪之交,随着质谱及蛋白质芯片的引进,蛋白质组学已广泛应用在生命科学上。其在医学上的应用,主要旨在发现疾病的特异性蛋白质分子或其蛋白质纹印,以揭示疾病的发生机制,也作为早期诊断、分子分型、疗效及预后判断的依据,并找出可能成为新药物设计的分子靶点,为疾病提供新的治疗方案。随着人类基因序列的完成,蛋白质组学热浪掀起了后基因组年代的序幕,人类将更深入地了解疾病和生命的本源。现就蛋白质组学10年来的发展历程、研究技术、在人类疾病中的应用及未来展望等作出精简的评述。     

Defining the mandate of proteomics in the post-genomics era: workshop report

Research in proteomics is the next step after genomics in understanding life processes at the molecular level. In the largest sense proteomics encompasses knowledge of the structure, function and expression of all proteins in the biochemical or biological contexts of all organisms. Since that is an impossible goal to achieve, at least in our lifetimes, it is appropriate to set more realistic, achievable goals for the field. Up to now, primarily for reasons of feasibility, scientists have tended to concentrate on accumulating information about the nature of proteins and their absolute and relative levels of expression in cells (the primary tools for this have been 2D gel electrophoresis and mass spectrometry). Although these data have been useful and will continue to be so, the information inherent in the broader definition of proteomics must also be obtained if the true promise of the growing field is to be realized. Acquiring this knowledge is the challenge for researchers in proteomics and the means to support these endeavors need to be provided. An attempt has been made to present the major issues confronting the field of proteomics and two clear messages come through in this report. The first is that the mandate of proteomics is and should be much broader than is frequently recognized. The second is that proteomics is much more complicated than sequencing genomes. This will require new technologies but it is highly likely that many of these will be developed. Looking back 10 to 20 years from now, the question is: Will we have done the job wisely or wastefully? This report summarizes the presentations made at a symposium at the National Academy of Sciences on February 25, 2002.     

Dimensionality is the issue: use of photoaptamers in protein microarrays

The development of high-density arrays for proteomics has become a goal of SomaLogic, many other companies, and a wide variety of academic entities. Unfortunately, the word proteomics has come to mean virtually everything. We define proteomics as being derived from arrays of analyte-specific reagents (ASRs) used to measure (something about) proteins. As the density of the ASRs on a chip increases toward the number of proteins in an organism, the concept of proteomics moves toward comprehensive proteomics. At issue then, is what constitutes an ASR, and what differences between them lead toward more or less biological information from a high-density panel of ASRs.     

The 8th International Conference of the Canadian Proteomics Initiative

The 8th International Conference of the Canadian Proteomics Initiative (CPI) was held at the Hilton Vancouver Metrotown Hotel in Burnaby, British Columbia from 3–5 May, 2008. With nearly 200 delegates, 32 speakers and more than 50 poster presentations, CPI 2008 covered a wide range of topics, including novel technologies, human and clinical proteomics, structural proteomics, bioinformatics, post-translational modifications, membrane and receptor proteomics, and plant and animal proteomics. This year’s conference was also highlighted by hands-on proteomics workshops at the University of Victoria Genome BC Proteomics Centre and the University of British Columbia, an inaugural meeting of the British Columbia Proteomics Network and focus meetings exploring opportunities for the formation of a nationwide association for Canadian proteomics and Genome British Columbia’s efforts towards large-scale global genomics and proteomics projects.     

Advances in shotgun proteomics and the analysis of membrane proteomes

The emergence of shotgun proteomics has facilitated the numerous biological discoveries made by proteomic studies. However, comprehensive proteomic analysis remains challenging and shotgun proteomics is a continually changing field. This review details the recent developments in shotgun proteomics and describes emerging technologies that will influence shotgun proteomics going forward. In addition, proteomic studies of integral membrane proteins remain challenging due to the hydrophobic nature in integral membrane proteins and their general low abundance levels. However, there have been many strategies developed for enriching, isolating and separating membrane proteins for proteomic analysis that have moved this field forward. In summary, while shotgun proteomics is a widely used and mature technology, the continued pace of improvements in mass spectrometry and proteomic technology and methods indicate that future studies will have an even greater impact on biological discovery.     

蛋白质组学及其技术发展

蛋白质组学产生于20世纪90年代,发展至今已日趋成熟。蛋白质组学是以生物体的全部或部分蛋白为研究对象,研究它们在生命活动过程中的作用、功能。蛋白质组学较之前的基因组学对于生命现象的解释更直接、更准确,近年得到了快速发展,并受到世界各国学者的高度关注。我们简要综述了蛋白质组学及其技术,并简单概述了这项技术在生命科学领域的应用。     

Identifying the proteome: software tools

The interest in proteomics has recently increased dramatically and proteomic methods are now applied to many problems in cell biology. The method of choice in proteomics for identifying and characterizing proteins is mass spectrometry combined with database searching. Software tools have been improved to increase the sensitivity of protein identification and methods for evaluating the search results have been incorporated     

蛋白质组学及其在农业上的应用

论述了蛋白质组学与基因组学的关系,蛋白质组学的定义、功能、分类及其三大主要技术.详细评述了蛋白质组学技术在农业科学研究中的应用,如叶绿体蛋白质组,农作物与细菌的共生现象、植物叶绿体蛋白质组,作物抗旱性和雄性不育性等.最后展望了蛋白质组学这一生命科学中最新方法在农业科学中的应用前景.     

Batch effects correction improves the sensitivity of significance tests in spectral counting-based comparative discovery proteomics

Shotgun proteomics has become the standard proteomics technique for the large-scale measurement of protein abundances in biological samples. Despite quantitative proteomics has been usually performed using label-based approaches, label-free quantitation offers advantages related to the avoidance of labeling steps, no limitation in the number of samples to be compared, and the gain in protein detection sensitivity. However, since samples are analyzed separately, experimental design becomes critical. The exploration of spectral counting quantitation based on LC-MS presented here gathers experimental evidence of the influence of batch effects on comparative proteomics. The batch effects shown with spiking experiments clearly interfere with the biological signal. In order to minimize the interferences from batch effects, a statistical correction is proposed and implemented. Our results show that batch effects can be attenuated statistically when proper experimental design is used. Furthermore, the batch effect correction implemented leads to a substantial increase in the sensitivity of statistical tests. Finally, the applicability of our batch effects correction is shown on two different biomarker discovery projects involving cancer secretomes. We think that our findings will allow designing and executing better comparative proteomics projects and will help to avoid reaching false conclusions in the field of proteomics biomarker discovery.     

Exploring the post-genomic world: differing explanatory and manipulatory functions of post-genomic sciences

Richard Lewontin proposed that the ability of a scientific field to create a narrative for public understanding garners it social relevance. This article applies Lewontin's conceptual framework of the functions of science (manipulatory and explanatory) to compare and explain the current differences in perceived societal relevance of genetics/genomics and proteomics. We provide three examples to illustrate the social relevance and strong cultural narrative of genetics/genomics for which no counterpart exists for proteomics. We argue that the major difference between genetics/genomics and proteomics is that genomics has a strong explanatory function, due to the strong cultural narrative of heredity. Based on qualitative interviews and observations of proteomics conferences, we suggest that the nature of proteins, lack of public understanding, and theoretical complexity exacerbates this difference for proteomics. Lewontin's framework suggests that social scientists may find that omics sciences affect social relations in different ways than past analyses of genetics.     

蛋白质组学技术在精子蛋白研究中的应用

从蛋白质组学研究的技术手段、蛋白质组学在人类不育及精卵相互识别并结合的机理研究、免疫法开展男性避孕方法的研究及蛋白质组学研究方法在家畜繁殖环节中的应用等几个方面阐述了蛋白质组学在人类生殖及动物繁殖环节相关研究中的重要作用。说明蛋白质组学已经成为生命科学未来发展的主要分支之一,为揭示生命个体的蛋白质动态变化提供了技术手段和理论基础,并将在药物开发,生命活动机理研究等方面发挥巨大作用,也必将会在家畜繁殖学领域发挥其应有的作用。     

Computational methods for the comparative quantification of proteins in label-free LCn-MS experiments

Liquid chromatography (LC) coupled to electrospray mass spectrometry (MS) is well established in high-throughput proteomics. The technology enables rapid identification of large numbers of proteins in a relatively short time. Comparative quantification of identified proteins from different samples is often regarded as the next step in proteomics experiments enabling the comparison of protein expression in different proteomes. Differential labeling of samples using stable isotope incorporation or conjugation is commonly used to compare protein levels between samples but these procedures are difficult to carry out in the laboratory and for large numbers of samples. Recently, comparative quantification of label-free LC(n)-MS proteomics data has emerged as an alternative approach. In this review, we discuss different computational approaches for extracting comparative quantitative information from label-free LC(n)-MS proteomics data. The procedure for computationally recovering the quantitative information is described. Furthermore, statistical tests used to evaluate the relevance of results will also be discussed.     

Population proteomics: the concept, attributes, and potential for cancer biomarker research

This review outlines the concept of population proteomics and its implication in the discovery and validation of cancer-specific protein modulations. Population proteomics is an applied subdiscipline of proteomics engaging in the investigation of human proteins across and within populations to define and better understand protein diversity. Population proteomics focuses on interrogation of specific proteins from large number of individuals, utilizing top-down, targeted affinity mass spectrometry approaches to probe protein modifications. Deglycosylation, sequence truncations, side-chain residue modifications, and other modifications have been reported for myriad of proteins, yet little is know about their incidence rate in the general population. Such information can be gathered via population proteomics and would greatly aid the biomarker discovery efforts. Discovery of novel protein modifications is also expected from such large scale population proteomics, expanding the protein knowledge database. In regard to cancer protein biomarkers, their validation via population proteomics-based approaches is advantageous as mass spectrometry detection is used both in the discovery and validation process, which is essential for the detection of those structurally modified protein biomarkers.     

Automated reporting from gel-based proteomics experiments using the open source Proteios database application

The assembly of data from different parts of proteomics workflow is often a major bottleneck in proteomics. Furthermore, there is an increasing demand for the publication of details about protein identifications due to the problems with false-positive and false-negative identifications. In this report, we describe how the open-source Proteios software has been expanded to automate the assembly of the different parts of a gel-based proteomics workflow. In Proteios it is possible to generate protein identification reports that contain all the information currently required by proteomics journals. It is also possible for the user to specify maximum allowed false positive ratios, and reports are automatically generated with the corresponding score cut-offs calculated. When protein identification is conducted using multiple search engines, the score thresholds that correlate to the predetermined error rate are also explicitly calculated for proteins that appear on the result lists of more than one search engine.     

Adapting arrays and lab-on-a-chip technology for proteomics

The impact of proteomics as a discovery engine in life science and in drug discovery has increased tremendously over the last seven years. At the same time, proteomics has expanded from the initial trust as a two-dimensional gel based approach to cover more functional and structural properties of proteins. The development of lab-on-a-chip and protein arrays for proteomics will have to evolve with the changes in proteomics to stay relevant. Here, we review the changes in the field of proteomics and their impact on the development in protein arrays and lab-on-a-chip.     

SNAP-tag based proteomics approach for the study of the retrograde route

Proteomics is a powerful technique for protein identification at large scales. A number of proteomics approaches have been developed to study the steady state composition of intracellular compartments. Here, we report a novel vectorial proteomics strategy to identify plasma membrane proteins that undergo retrograde transport to the trans-Golgi network (TGN). This strategy is based on the covalent modification of the plasma membrane proteome with a membrane impermeable benzylguanine derivative. Benzylguanine-tagged plasma membrane proteins that are subsequently targeted to the retrograde route are covalently captured by a TGN-localized SNAP-tagged fusion protein, which allows for their identification. The approach was validated step-by-step using a well explored retrograde cargo protein, the B-subunit of Shiga toxin. It was then extended to the proteomics format. Among other hits we found one of the historically first identified cargo proteins that undergo retrograde transport, which further validated our approach. Most of the other hits were kinases, receptors or transporters. In conclusion, we have pioneered a vectorial proteomics approach that complements traditional methods for the study of retrograde protein trafficking. This approach is of generic nature and could in principle be extended to other endocytic pathways.