The insight in to the human liver proteome

Comunicaciones a congreso

The 2006 Human Liver Proteome Project (HLPP) Workshops

In 2006, scientists participating to the Human Liver Proteome Project (HLPP) launched by the Human Proteome Organisation (HUPO) convened on two occasions to present and discuss their progress. A workshop was held over two days in May in Bilbao, Spain, and a brief 3-hour meeting was held in October in conjunction with the 5th HUPO World Congress in Long Beach, California. Highlights included progress on the construction of the human normal liver proteome expression profile and of subcellular proteomes, establishment of a liver ORFeome bank and of a liver antibody bank, identifications of protein-protein interaction maps in the liver, application of a robust strategy for quantitative proteomics and the characterization of fatty liver diseases using mouse models

Nomogram predicting overall survival after surgical resection for retroperitoneal leiomyosarcoma patients

BackgroundSurgery is the best way to cure the retroperitoneal leiomyosarcoma (RLMS), and there is currently no prediction model on RLMS after surgical resection. The objective of this study was to develop a nomogram to predict the overall survival (OS) of patients with RLMS after surgical resection.MethodsPatients who underwent surgical resection from September 2010 to December 2020 were included. The nomogram was constructed based on the COX regression model, and the discrimination was assessed using the concordance index. The predicted OS and actual OS were evaluated with the assistance of calibration plots.Results118 patients were included. The median OS for all patients was 47.8 (95% confidence interval (CI), 35.9-59.7) months. Most tumor were completely resected (n=106, 89.8%). The proportions of French National Federation of Comprehensive Cancer Centres (FNCLCC) classification were equal as grade 1, grade 2, and grade 3 (31.4%, 30.5%, and 38.1%, respectively). The tumor diameter of 73.7% (n=85) patients was greater than 5 cm, the lesions of 23.7% (n=28) were multifocal, and 55.1% (n=65) patients had more than one organ resected. The OS nomogram was constructed based on the number of resected organs, tumor diameter, FNCLCC grade, and multifocal lesions. The concordance index of the nomogram was 0.779 (95% CI, 0.659-0.898), the predicted OS and actual OS were in good fitness in calibration curves.ConclusionThe nomogram prediction model established in this study is helpful for postoperative consultation and the selection of patients for clinical trial enrollment

SigFlux: A novel network feature to evaluate the importance of proteins in signal transduction networks

BACKGROUND: Measuring each protein's importance in signaling networks helps to identify the crucial proteins in a cellular process, find the fragile portion of the biology system and further assist for disease therapy. However, there are relatively few methods to evaluate the importance of proteins in signaling networks. RESULTS: We developed a novel network feature to evaluate the importance of proteins in signal transduction networks, that we call SigFlux, based on the concept of minimal path sets (MPSs). An MPS is a minimal set of nodes that can perform the signal propagation from ligands to target genes or feedback loops. We define SigFlux as the number of MPSs in which each protein is involved. We applied this network feature to the large signal transduction network in the hippocampal CA1 neuron of mice. Significant correlations were simultaneously observed between SigFlux and both the essentiality and evolutionary rate of genes. Compared with another commonly used network feature, connectivity, SigFlux has similar or better ability as connectivity to reflect a protein's essentiality. Further classification according to protein function demonstrates that high SigFlux, low connectivity proteins are abundant in receptors and transcriptional factors, indicating that SigFlux candescribe the importance of proteins within the context of the entire network. CONCLUSION: SigFlux is a useful network feature in signal transduction networks that allows the prediction of the essentiality and conservation of proteins. With this novel network feature, proteins that participate in more pathways or feedback loops within a signaling network are proved far more likely to be essential and conserved during evolution than their counterparts

A nonparametric model for quality control of database search results in shotgun proteomics

<p>Abstract</p> <p>Background</p> <p>Analysis of complex samples with tandem mass spectrometry (MS/MS) has become routine in proteomic research. However, validation of database search results creates a bottleneck in MS/MS data processing. Recently, methods based on a randomized database have become popular for quality control of database search results. However, a consequent problem is the ignorance of how to combine different database search scores to improve the sensitivity of randomized database methods.</p> <p>Results</p> <p>In this paper, a multivariate nonlinear discriminate function (DF) based on the multivariate nonparametric density estimation technique was used to filter out false-positive database search results with a predictable false positive rate (FPR). Application of this method to control datasets of different instruments (LCQ, LTQ, and LTQ/FT) yielded an estimated FPR close to the actual FPR. As expected, the method was more sensitive when more features were used. Furthermore, the new method was shown to be more sensitive than two commonly used methods on 3 complex sample datasets and 3 control datasets.</p> <p>Conclusion</p> <p>Using the nonparametric model, a more flexible DF can be obtained, resulting in improved sensitivity and good FPR estimation. This nonparametric statistical technique is a powerful tool for tackling the complexity and diversity of datasets in shotgun proteomics.</p

A miniaturized sandwich immunoassay platform for the detection of protein-protein interactions

<p>Abstract</p> <p>Background</p> <p>Analysis of protein-protein interactions (PPIs) is a valuable approach for the characterization of huge networks of protein complexes or proteins of unknown function. Co-immunoprecipitation (coIP) using affinity resins coupled to protein A/G is the most widely used method for PPI detection. However, this traditional large scale resin-based coIP is too laborious and time consuming. To overcome this problem, we developed a miniaturized sandwich immunoassay platform (MSIP) by combining antibody array technology and coIP methods.</p> <p>Results</p> <p>Based on anti-FLAG antibody spotted aldehyde slides, MSIP enables simple, rapid and large scale detection of PPIs by fluorescent labeling anti-myc antibody. By analyzing well-known interacting and non-interacting protein pairs, MSIP was demonstrated to be highly accurate and reproducible. Compared to traditional resin-based coIP, MSIP results in higher sensitivity and enhanced throughput, with the additional benefit of digital read-outs. In addition, MSIP was shown to be a highly useful validation platform to confirm PPI candidates that have been identified from yeast two hybrid systems.</p> <p>Conclusions</p> <p>In conclusion, MSIP is proved to be a simple, cost-saving and highly efficient technique for the comprehensive study of PPIs.</p

Drug Target Prediction Based on the Herbs Components: The Study on the Multitargets Pharmacological Mechanism of Qishenkeli Acting on the Coronary Heart Disease

In this paper, we present a case study of Qishenkeli (QSKL) to research TCM's underlying molecular mechanism, based on drug target prediction and analyses of TCM chemical components and following experimental validation. First, after determining the compositive compounds of QSKL, we use drugCIPHER-CS to predict their potential drug targets. These potential targets are significantly enriched with known cardiovascular disease-related drug targets. Then we find these potential drug targets are significantly enriched in the biological processes of neuroactive ligand-receptor interaction, aminoacyl-tRNA biosynthesis, calcium signaling pathway, glycine, serine and threonine metabolism, and renin-angiotensin system (RAAS), and so on. Then, animal model of coronary heart disease (CHD) induced by left anterior descending coronary artery ligation is applied to validate predicted pathway. RAAS pathway is selected as an example, and the results show that QSKL has effect on both rennin and angiotensin II receptor (AT1R), which eventually down regulates the angiotensin II (AngII). Bioinformatics combing with experiment verification can provide a credible and objective method to understand the complicated multitargets mechanism for Chinese herbal formula

Computational identification of rare codons of Escherichia coli based on codon pairs preference

<p>Abstract</p> <p>Background</p> <p>Codon bias is believed to play an important role in the control of gene expression. In <it>Escherichia coli</it>, some rare codons, which can limit the expression level of exogenous protein, have been defined by gene engineering operations. Previous studies have confirmed the existence of codon pair's preference in many genomes, but the underlying cause of this bias has not been well established. Here we focus on the patterns of rarely-used synonymous codons. A novel method was introduced to identify the rare codons merely by codon pair bias in <it>Escherichia coli</it>.</p> <p>Results</p> <p>In <it>Escherichia coli</it>, we defined the "rare codon pairs" by calculating the frequency of occurrence of all codon pairs in coding sequences. Rare codons which are disliked in genes could make great contributions to forming rare codon pairs. Meanwhile our investigation showed that many of these rare codon pairs contain termination codons and the recognized sites of restriction enzymes. Furthermore, a new index (F_rare) was developed. Through comparison with the classical indices we found a significant negative correlation between F_rareand the indices which depend on reference datasets.</p> <p>Conclusions</p> <p>Our approach suggests that we can identify rare codons by studying the context in which a codon lies. Also, the frequency of rare codons (F_rare) could be a useful index of codon bias regardless of the lack of expression abundance information.</p

Efficient gene editing in adult mouse livers via adenoviral delivery of CRISPR/Cas9

AbstractWe developed an adenovirus-based CRISPR/Cas9 system for gene editing in vivo. In the liver, we demonstrated that the system could reach the level of tissue-specific gene knockout, resulting in phenotypic changes. Given the wide spectrum of cell types susceptible to adenoviral infection, and the fact that adenoviral genome rarely integrates into its host cell genome, we believe the adenovirus-based CRISPR/Cas9 system will find applications in a variety of experimental settings