定量蛋白质组学中的同位素标记技术

定量蛋白质组学的目的是对复杂的混合体系中所有的蛋白质进行鉴定,并对蛋白质的量及量的变化进行准确的测定,是当前系统生物科学研究的重要内容。近年来,由于质谱技术和生物信息学的进步,定量蛋白质组学在分析蛋白质组或亚蛋白质组方面已取得了令人瞩目的成就,但其最显著的成就应该归功于稳定同位素标记技术的应用。该技术使用针对某一类蛋白具有特异性的化学探针来标记目的蛋白质或肽段,同时化学探针要求含有用以精确定量的稳定同位素信号。在此基础上,实现了对表达的蛋白质差异和翻译后修饰的蛋白质差异进行精确定量分析。综述了在定量蛋白质组学中使用的各种同位素标记技术及其应用。     

Proteome-Level Analysis Indicates Global Mechanisms for Post-Translational Regulation of RRM Domains

RRM, or RNA-recognition motif, domains are the largest class of single-stranded RNA binding domains in the human proteome and play important roles in RNA processing, splicing, export, stability, packaging, and degradation. Using a current database of post-translational modifications (PTMs), ProteomeScout, we found that RRM domains are also one of the most heavily modified domains in the human proteome. Here, we present two interesting findings about RRM domain modifications, found by mapping known PTMs onto RRM domain alignments and structures. First, we find significant overlap of ubiquitination and acetylation within RRM domains, suggesting the possibility for ubiquitination-acetylation crosstalk. Additionally, an analysis of quantitative study of ubiquitination changes in response to proteasome inhibition highlights the uniqueness of RRM domain ubiquitination – RRM domain ubiquitination decreases in response to proteasome inhibition, whereas the majority of sites increase. Second, we found conservation of tyrosine phosphorylation within the RNP1 and RNP2 consensus sequences, which coordinate RNA binding – suggesting a possible role for regulation of RNA binding by tyrosine kinase signaling. These observations suggest there are unique regulatory mechanisms of RRM function that have yet to be uncovered and that the RRM domain represents a model system for further studies on understanding PTM crosstalk.     

Integrated knowledge mining,genome-scale modeling,and machine learning for predicting Yarrowia lipolytica bioproduction

Predicting bioproduction titers from microbial hosts has been challenging due to complex interactions between microbial regulatory networks, stress responses, and suboptimal cultivation conditions. This study integrated knowledge mining, feature extraction, genome-scale modeling (GSM), and machine learning (ML) to develop a model for predicting Yarrowia lipolytica chemical titers (i.e., organic acids, terpenoids, etc.). First, Y. lipolytica production data, including cultivation conditions, genetic engineering strategies, and product information, was manually collected from literature (~100 papers) and stored as either numerical (e.g., substrate concentrations) or categorical (e.g., bioreactor modes) variables. For each case recorded, central pathway fluxes were estimated using GSMs and flux balance analysis (FBA) to provide metabolic features. Second, a ML ensemble learner was trained to predict strain production titers. Accurate predictions on the test data were obtained for instances with production titers >1 g/L (R² = 0.87). However, the model had reduced predictability for low performance strains (0.01–1 g/L, R² = 0.29) potentially due to biosynthesis bottlenecks not captured in the features. Feature ranking indicated that the FBA fluxes, the number of enzyme steps, the substrate inputs, and thermodynamic barriers (i.e., Gibbs free energy of reaction) were the most influential factors. Third, the model was evaluated on other oleaginous yeasts and indicated there were conserved features for some hosts that can be potentially exploited by transfer learning. The platform was also designed to assist computational strain design tools (such as OptKnock) to screen genetic targets for improved microbial production in light of experimental conditions.     

AutoMotif Server for prediction of phosphorylation sites in proteins using support vector machine: 2007 update

We present here the recent update of AutoMotif Server (AMS 2.0) that predicts post-translational modification sites in protein sequences. The support vector machine (SVM) algorithm was trained on data gathered in 2007 from various sets of proteins containing experimentally verified chemical modifications of proteins. Short sequence segments around a modification site were dissected from a parent protein, and represented in the training set as binary or profile vectors. The updated efficiency of the SVM classification for each type of modification and the predictive power of both representations were estimated using leave-one-out tests for model of general phosphorylation and for modifications catalyzed by several specific protein kinases. The accuracy of the method was improved in comparison to the previous version of the service (Plewczynski et al., “AutoMotif server: prediction of single residue post-translational modifications in proteins”, Bioinformatics 21: 2525–7, 2005). The precision of the updated version reached over 90% for selected types of phosphorylation and was optimized in trade of lower recall value of the classification model. The AutoMotif Server version 2007 is freely available at . Additionally, the reference dataset for optimization of prediction of phosphorylation sites, collected from the UniProtKB was also provided and can be accessed at .     

A knowledgebase resource for interleukin-17 family mediated signaling

Interleukin-17 (IL-17) belongs to a relatively new family of cytokines that has garnered attention as the signature cytokine of Th17 cells. This cytokine family consists of 6 ligands, which bind to 5 receptor subtypes and induce downstream signaling. Although the receptors are ubiquitously expressed, cellular responses to ligands vary across tissues. The cytokine family is associated with various autoimmune disorders including rheumatoid arthritis, multiple sclerosis, inflammatory bowel disease, asthma and psoriasis in addition to being implicated in the pathogenesis of cancer. In addition, this family plays a role in host defense against bacterial and fungal infections. The signaling mechanisms of the IL-17 family of proinflammatory cytokines are not well explored. In this study, we present a resource of literature-annotated reactions induced by IL-17. The reactions are catalogued under 5 categories, namely; molecular association, catalysis, transport, activation/inhibition and gene regulation. A total of 93 molecules and 122 reactions have been annotated. The IL-17 pathway is freely available through NetPath, a resource of signal transduction pathways previously developed by our group.     

A Noncatalytic Domain of Glycogen Synthase Kinase-3 (GSK-3) Is Essential for Activity

Glycogen synthase kinase-3 (GSK-3) isoforms, GSK-3α and GSK-3β, are serine/threonine kinases involved in numerous cellular processes and diverse diseases, including Alzheimer disease, cancer, and diabetes. GSK-3 isoforms function redundantly in some settings, while, in others, they exhibit distinct activities. Despite intensive investigation into the physiological roles of GSK-3 isoforms, the basis for their differential activities remains unresolved. A more comprehensive understanding of the mechanistic basis for GSK-3 isoform-specific functions could lead to the development of isoform-specific inhibitors. Here, we describe a structure-function analysis of GSK-3α and GSK-3β in mammalian cells. We deleted the noncatalytic N and C termini in both GSK-3 isoforms and generated point mutations of key regulatory residues. We examined the effect of these mutations on GSK-3 activity toward Tau, activity in Wnt signaling, interaction with Axin, and GSK-3α/β Tyr^279/216 phosphorylation. We found that the N termini of both GSK-3 isoforms were dispensable, whereas progressive C-terminal deletions resulted in protein misfolding exhibited by deficient activity, impaired ability to interact with Axin, and a loss of Tyr^279/216 phosphorylation. Our data predict that small molecules targeting the divergent C terminus may lead to isoform-specific GSK-3 inhibition through destabilization of the GSK-3 structure.     

A Systems Biology Analysis of Apoptosome Formation and Apoptosis Execution Supports Allosteric Procaspase-9 Activation

The protease caspase-9 is activated on the apoptosome, a multiprotein signal transduction platform that assembles in response to mitochondria-dependent apoptosis initiation. Despite extensive molecular research, the assembly of the holo-apoptosome and the process of caspase-9 activation remain incompletely understood. Here, we therefore integrated quantitative data on the molecular interactions and proteolytic processes during apoptosome formation and apoptosis execution and conducted mathematical simulations to investigate the resulting biochemical signaling, quantitatively and kinetically. Interestingly, when implementing the homodimerization of procaspase-9 as a prerequisite for activation, the calculated kinetics of apoptosis execution and the efficacy of caspase-3 activation failed to replicate experimental data. In contrast, assuming a scenario in which procaspase-9 is activated allosterically upon binding to the apoptosome backbone, the mathematical simulations quantitatively and kinetically reproduced all experimental data. These data included a XIAP threshold concentration at which apoptosis execution is suppressed in HeLa cervical cancer cells, half-times of procaspase-9 processing, as well as the molecular timer function of the apoptosome. Our study therefore provides novel mechanistic insight into apoptosome-dependent apoptosis execution and suggests that caspase-9 is activated allosterically by binding to the apoptosome backbone. Our findings challenge the currently prevailing dogma that all initiator procaspases require homodimerization for activation.     

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

The aim of de novo protein design is to find the amino acid sequences that will fold into a desired 3-dimensional structure with improvements in specific properties, such as binding affinity, agonist or antagonist behavior, or stability, relative to the native sequence. Protein design lies at the center of current advances drug design and discovery. Not only does protein design provide predictions for potentially useful drug targets, but it also enhances our understanding of the protein folding process and protein-protein interactions. Experimental methods such as directed evolution have shown success in protein design. However, such methods are restricted by the limited sequence space that can be searched tractably. In contrast, computational design strategies allow for the screening of a much larger set of sequences covering a wide variety of properties and functionality. We have developed a range of computational de novo protein design methods capable of tackling several important areas of protein design. These include the design of monomeric proteins for increased stability and complexes for increased binding affinity.To disseminate these methods for broader use we present Protein WISDOM (http://www.proteinwisdom.org), a tool that provides automated methods for a variety of protein design problems. Structural templates are submitted to initialize the design process. The first stage of design is an optimization sequence selection stage that aims at improving stability through minimization of potential energy in the sequence space. Selected sequences are then run through a fold specificity stage and a binding affinity stage. A rank-ordered list of the sequences for each step of the process, along with relevant designed structures, provides the user with a comprehensive quantitative assessment of the design. Here we provide the details of each design method, as well as several notable experimental successes attained through the use of the methods.     

MSDA,a proteomics software suite for in‐depth Mass Spectrometry Data Analysis using grid computing

One of the major bottlenecks in the proteomics field today resides in the computational interpretation of the massive data generated by the latest generation of high‐throughput MS instruments. MS/MS datasets are constantly increasing in size and complexity and it becomes challenging to comprehensively process such huge datasets and afterwards deduce most relevant biological information. The Mass Spectrometry Data Analysis (MSDA, https://msda.unistra.fr ) online software suite provides a series of modules for in‐depth MS/MS data analysis. It includes a custom databases generation toolbox, modules for filtering and extracting high‐quality spectra, for running high‐performance database and de novo searches, and for extracting modified peptides spectra and functional annotations. Additionally, MSDA enables running the most computationally intensive steps, namely database and de novo searches, on a computer grid thus providing a net time gain of up to 99% for data processing.     

A third metal is required for catalytic activity of the signal-transducing protein phosphatase M tPphA

Protein phosphatase M (PPM) regulates key signaling pathways in prokaryotes and eukaryotes. Novel structures of bacterial PPM members revealed three divalent metal ions in their catalytic centers. The function of metal 3 (M3) remained unclear. To reveal its function, we created variants of tPphA from Thermosynechococcus elongatus in all metal-coordinating residues, and multiple variants were created for the M3 coordinating Asp-119 residue. The structures of variants D119A and D193A were resolved, showing loss of M3 binding but unaffected binding of M1 and M2 in the catalytic center of D119A, with the nucleophilic water molecule in the correct place. The catalytic activity of this variant was highly impaired. This and further structure-function analyses showed that M3 is required for catalysis by providing a water molecule as a proton donor during catalysis. Mutation of the homologue Asp residue in human PP2Cα also caused loss of function, suggesting a general requirement of M3 in PPM-catalyzed reactions.     

A Simple Protocol for Platelet-mediated Clumping of Plasmodium falciparum-infected Erythrocytes in a Resource Poor Setting

P. falciparum causes the majority of severe malarial infections. The pathophysiological mechanisms underlying cerebral malaria (CM) are not fully understood and several hypotheses have been put forward, including mechanical obstruction of microvessels by P. falciparum-parasitized red blood cells (pRBC). Indeed, during the intra-erythrocytic stage of its life cycle, P. falciparum has the unique ability to modify the surface of the infected erythrocyte by exporting surface antigens with varying adhesive properties onto the RBC membrane. This allows the sequestration of pRBC in multiple tissues and organs by adhesion to endothelial cells lining the microvasculature of post-capillary venules ¹. By doing so, the mature forms of the parasite avoid splenic clearance of the deformed infected erythrocytes ² and restrict their environment to a more favorable low oxygen pressure ³. As a consequence of this sequestration, it is only immature asexual parasites and gametocytes that can be detected in peripheral blood.Cytoadherence and sequestration of mature pRBC to the numerous host receptors expressed on microvascular beds occurs in severe and uncomplicated disease. However, several lines of evidence suggest that only specific adhesive phenotypes are likely to be associated with severe pathological outcomes of malaria. One example of such specific host-parasite interactions has been demonstrated in vitro, where the ability of intercellular adhesion molecule-1 to support binding of pRBC with particular adhesive properties has been linked to development of cerebral malaria ^4,5. The placenta has also been recognized as a site of preferential pRBC accumulation in malaria-infected pregnant women, with chondrotin sulphate A expressed on syncytiotrophoblasts that line the placental intervillous space as the main receptor ⁶. Rosetting of pRBC to uninfected erythrocytes via the complement receptor 1 (CD35)^7,8 has also been associated with severe disease ⁹.One of the most recently described P. falciparum cytoadherence phenotypes is the ability of the pRBC to form platelet-mediated clumps in vitro. The formation of such pRBC clumps requires CD36, a glycoprotein expressed on the surface of platelets. Another human receptor, gC1qR/HABP1/p32, expressed on diverse cell types including endothelial cells and platelets, has also been shown to facilitate pRBC adhesion on platelets to form clumps ¹⁰. Whether clumping occurs in vivo remains unclear, but it may account for the significant accumulation of platelets described in brain microvasculature of Malawian children who died from CM ¹¹. In addition, the ability of clinical isolate cultures to clump in vitro was directly linked to the severity of disease in Malawian ¹² and Mozambican patients ¹³, (although not in Malian ¹⁴).With several aspects of the pRBC clumping phenotype poorly characterized, current studies on this subject have not followed a standardized procedure. This is an important issue because of the known high variability inherent in the assay ¹⁵. Here, we present a method for in vitro platelet-mediated clumping of P. falciparum with hopes that it will provide a platform for a consistent method for other groups and raise awareness of the limitations in investigating this phenotype in future studies. Being based in Malawi, we provide a protocol specifically designed for a limited resource setting, with the advantage that freshly collected clinical isolates can be examined for phenotype without need for cryopreservation.     

A Booststrap Adaptive Test for Two-way Analysis of Variance

We propose a method to construct adaptive tests based on a bootstrap technique. The procedure leads to a nearly exact adaptive test depending on the size of the sample. With the use of the estimated Pitman's relative efficacy as selector statistic, we show that the adaptive test has a power that is asymptotically equal to the power of it's better component. We apply the idea to construct an adaptive test for two-way analysis of variance model. Finally, we use simulations to observe the behaviour of the method for small sample sizes.     

TSNAdb: A Database for Tumor-specific Neoantigens from Immunogenomics Data Analysis

Tumor-specific neoantigens have attracted much attention since they can be used as biomarkers to predict therapeutic effects of immune checkpoint blockade therapy and as potential targets for cancer immunotherapy. In this study, we developed a comprehensive tumor-specific neoantigen database (TSNAdb v1.0), based on pan-cancer immunogenomic analyses of somatic mutation data and human leukocyte antigen (HLA) allele information for 16 tumor types with 7748 tumor samples from The Cancer Genome Atlas (TCGA) and The Cancer Immunome Atlas (TCIA). We predicted binding affinities between mutant/wild-type peptides and HLA class I molecules by NetMHCpan v2.8/v4.0, and presented detailed information of 3,707,562/1,146,961 potential neoantigens generated by somatic mutations of all tumor samples. Moreover, we employed recurrent mutations in combination with highly frequent HLA alleles to predict potential shared neoantigens across tumor patients, which would facilitate the discovery of putative targets for neoantigen-based cancer immunotherapy. TSNAdb is freely available at http://biopharm.zju.edu.cn/tsnadb.     

Integrated Analysis of Transcriptomic,miRNA and Proteomic Changes of a Novel Hybrid Yellow Catfish Uncovers Key Roles for miRNAs in Heterosis

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Highlights

• •mRNA-seq, miRNA-seq, proteomes of P. fulvidraco, P. vachelli, hybrid Huangyou-1.
• •Predicted miRNA-mRNA-protein pairs were found and validated by qRT-PCR and PRM.
• •Immune, metabolism, digestion, absorption, proliferation, development generate heterosis.
• •High parental gene/protein with low parental miRNAs inherit from the mother or father.