Qingrun Li

Effect of Peptide-to-TiO2 Beads Ratio on Phosphopeptide Enrichment Selectivity

Titanium dioxide (TiO(2)) has been proven to be a highly efficient strategy and widely used for phosphopeptide enrichment. Many advances have been made recently, including online/offline mode and optimization of sample loading/elution buffer; however, beads usage has rarely been explored. In the current study, we found that the peptide-to-TiO(2) beads ratio was a significant factor for phosphopeptide enrichment, and insufficient or excessive beads could decrease the selectivity. Specifically, for HeLa total cell lysate, the optimum peptide-to-beads ratio is about 1:2-1:8 (mass/mass) to obtain the highest enrichment selectivity and the maximum phosphopeptides identification with single incubation. Pre-experiments are recommended to decide an optimum peptide-to-TiO(2) beads ratio when it comes to different samples. Interestingly, deficient beads can help identify much more multiphosphorylated peptides than the optimum peptide-to-beads ratio by consecutive incubations. Therefore, if multiphosphorylated peptides identification is desired, deficient beads amount is preferred. In addition, consecutive incubation using deficient beads could be used as a fractionation of phosphopeptides besides as an enrichment method.

SysPTM: A Systematic Resource for Proteomic Research on Post-translational Modifications

With the rapid expansion of protein post-translational modification (PTM) research based on large-scale proteomic work, there is an increasing demand for a suitable repository to analyze PTM data. Here we present a curated, web-accessible PTM data base, SysPTM. SysPTM provides a systematic and sophisticated platform for proteomic PTM research equipped not only with a knowledge base of manually curated multi-type modification data but also with four fully developed, in-depth data mining tools. Currently, SysPTM contains data detailing 117,349 experimentally determined PTM sites on 33,421 proteins involving nearly 50 PTM types, curated from public resources including five data bases and four web servers and more than one hundred peer-reviewed mass spectrometry papers. Protein annotations including Pfam domains, KEGG pathways, GO functional classification, and ortholog groups are integrated into the data base. Four online tools have been developed and incorporated, including PTMBlast, to compare a users PTM dataset with PTM data in SysPTM; PTMPathway, to map PTM proteins to KEGG pathways; PTMPhylog, to discover potentially conserved PTM sites; and PTMCluster, to find clusters of multi-site modifications. The workflow of SysPTM was demonstrated by analyzing an in-house phosphorylation dataset identified by MS/MS. It is shown that in SysPTM, the role of single-type and multi-type modifications can be systematically investigated in a full biological context. SysPTM could be an important contribution to modificomics research. SysPTM is freely available online at www.sysbio.ac.cn/SysPTM.

Localized-Statistical Quantification of Human Serum Proteome Associated with Type 2 Diabetes

Background Recent advances in proteomics have shed light to discover serum proteins or peptides as biomarkers for tracking the progression of diabetes as well as understanding molecular mechanisms of the disease. Results In this work, human serum of non-diabetic and diabetic cohorts was analyzed by proteomic approach. To analyze total 1377 high-confident serum-proteins, we developed a computing strategy called localized statistics of protein abundance distribution (LSPAD) to calculate a significant bias of a particular protein-abundance between these two cohorts. As a result, 68 proteins were found significantly over-represented in the diabetic serum (p<0.01). In addition, a pathway-associated analysis was developed to obtain the overall pathway bias associated with type 2 diabetes, from which the significant over-representation of complement system associated with type 2 diabetes was uncovered. Moreover, an up-stream activator of complement pathway, ficolin-3, was observed over-represented in the serum of type 2 diabetic patients, which was further validated with statistic significance (p = 0.012) with more clinical samples. Conclusions The developed LSPAD approach is well fit for analyzing proteomic data derived from biological complex systems such as plasma proteome. With LSPAD, we disclosed the comprehensive distribution of the proteins associated with diabetes in different abundance levels and the involvement of ficolin-related complement activation in diabetes.

A comprehensive and non-prefractionation on the protein level approach for the human urinary proteome: touching phosphorylation in urine

Increasing attention has been paid to the urinary proteome because it holds the promise of discovering various disease biomarkers. However, most of the urine proteomics studies routinely relied on protein pre-fractionation and so far did not present characterization on phosphorylation status. Two robust approaches, integrated multidimensional liquid chromatography (IMDL) and Yin-yang multidimensional liquid chromatography (MDLC) tandem mass spectrometry, were recently developed in our laboratory, with high-coverage identification of peptide mixtures. In this study, we adopted a strategy without pre-fractionation on the protein level for urinary proteome identification, using both the IMDL and the Yin-yang MDLC methods for peptide fractionation followed by identification using a linear ion trap-orbitrap (LTQ-Orbitrap) mass spectrometer with high resolution and mass accuracy. A total of 1310 non-redundant proteins were highly confidently identified from two experiments, significantly including 59 phosphorylation sites. More than half the annotated identifications were membrane-related proteins. In addition, the lysosomal as well as kidney-associated proteins were detected. Compared with the six largest datasets of urinary proteins published previously, we found our data included most of the reported proteins. Our study developed a robust approach for exploring the human urinary proteome, which would provide a catalogue of urine proteins on a global scale. It is the first report, to our best knowledge, to profile the urinary phosphoproteome. This work significantly extends current comprehension of urinary protein modification and its potential biological significance. Moreover, the strategy could further serve as a reference for biomarker discovery.

Large Scale Phosphoproteome Profiles Comprehensive Features of Mouse Embryonic Stem Cells

Embryonic stem cells are pluripotent and capable of unlimited self-renewal. Elucidation of the underlying molecular mechanism may contribute to the advancement of cell-based regenerative medicine. In the present work, we performed a large scale analysis of the phosphoproteome in mouse embryonic stem (mES) cells. Using multiplex strategies, we detected 4581 proteins and 3970 high confidence distinct phosphosites in 1642 phosphoproteins. Notably, 22 prominent phosphorylated stem cell marker proteins with 39 novel phosphosites were identified for the first time by mass spectrometry, including phosphorylation sites in NANOG (Ser-65) and RE1 silencing transcription factor (Ser-950 and Thr-953). Quantitative profiles of NANOG peptides obtained during the differentiation of mES cells revealed that the abundance of phosphopeptides and non-phosphopeptides decreased with different trends. To our knowledge, this study presents the largest global characterization of phosphorylation in mES cells. Compared with a study of ultimately differentiated tissue cells, a bioinformatics analysis of the phosphorylation data set revealed a consistent phosphorylation motif in human and mouse ES cells. Moreover, investigations into phosphorylation conservation suggested that phosphoproteins were more conserved in the undifferentiated ES cell state than in the ultimately differentiated tissue cell state. However, the opposite conclusion was drawn from this conservation comparison with phosphosites. Overall, this work provides an overview of phosphorylation in mES cells and is a valuable resource for the future understanding of basic biology in mES cells.

Fractionation of complex protein mixture by virtual three-dimensional liquid chromatography based on combined pH and salt steps

The complexity and diversity of biological samples in proteomics require intensive fractionation ahead of mass spectrometry identification. This work developed a chromatographic method called virtual three-dimensional chromatography to fractionate complex protein mixtures. By alternate elution with different pHs and salt concentrations, we implemented pH and salt steps by turns on a single strong cation exchange column to fully exploit its chromatographic ability. Given standard proteins that were not resolved solely by pH or salt gradient elution could be successfully separated using this combined mode. With a reversed phase column tandem connected behind, we further fractionated as well as desalted proteins as the third dimension. This present strategy could readily be adapted with respect to special complexity of biological samples. Crude plasma without depleting high abundance proteins were fractionated by this three-dimensional mode and then analyzed by reversed phase liquid chromatography coupled with LTQ mass spectrometry. In total, 1933 protein groups with wide dynamic ranges were identified from a single experiment. Some characteristics that correlated to the behavior of proteins on strong cation exchange columns are also discussed.

The discovery of novel protein-coding features in mouse genome based on mass spectrometry data

Identifying protein-coding genes in eukaryotic genomes remains a challenge in post-genome era due to the complex gene models. We applied a proteogenomics strategy to detect un-annotated protein-coding regions in mouse genome. High-accuracy tandem mass spectrometry (MS/MS) data from diverse mouse samples were generated by LTQ-Orbitrap mass spectrometer in house. Two searchable diagnostic proteomic datasets were constructed, one with all possible encoding exon junctions, and the other with all putative encoding exons, for the discovery of novel exon splicing events and novel uninterrupted protein-coding regions. Altogether 29,586 unique peptides were identified. Aligning backwards to the mouse genome, the translation of 4471 annotated genes was validated by the known peptides; and 172 genic events were defined in mouse genome by the novel peptides. The approach in the current work can provide substantial evidences for eukaryote genome annotation in encoding genes.

CCNYL1, but Not CCNY, Cooperates with CDK16 to Regulate Spermatogenesis in Mouse.

Cyclin Y-like 1 (Ccnyl1) is a newly-identified member of the cyclin family and is highly similar in protein sequences to Cyclin Y (Ccny). However, the function of Ccnyl1 is poorly characterized in any organism. Here we found that Ccnyl1 was most abundantly expressed in the testis of mice and was about seven times higher than the level of Ccny. Male Ccnyl1-/- mice were infertile, whereas both male and female Ccny-/- mice displayed normal fertility. These results suggest that Ccnyl1, but not Ccny, is indispensable for male fertility. Spermatozoa obtained from Ccnyl1-/- mice displayed significantly impaired motility, and represented a thinned annulus region and/or a bent head. We found that the protein, but not the mRNA, level of cyclin-dependent kinase 16 (CDK16) was decreased in the testis of Ccnyl1-/- mice. Further study demonstrated that CCNYL1 interacted with CDK16 and this interaction mutually increased the stability of these two proteins. Moreover, the interaction increased the kinase activity of CDK16. In addition, we observed an alteration of phosphorylation levels of CDK16 in the presence of CCNYL1. We identified the phosphorylation sites of CDK16 by mass spectrometry and revealed that several phosphorylation modifications on the N-terminal region of CDK16 were indispensable for the CCNYL1 binding and the modulation of CDK16 kinase activity. Our results therefore reveal a previously unrecognized role of CCNYL1 in regulating spermatogenesis through the interaction and modulation of CDK16.

Proteomic mining in the dysplastic liver of WHV⁄c-myc mice - insights and indicators for early hepatocarcinogenesis

Because of the asymptomatic process of carcinogenesis, the early detection of cancers such as hepatocellular carcinoma (HCC) is very challenging. Tumor‐prone transgenic mouse models of oncogenesis can provide a stable and powerful tool for the analysis of cancer initiation, and are therefore promising for the discovery of early putative biomarkers of HCC. Using a label‐free proteomic quantification strategy, we comprehensively investigated the protein expression profile in the livers of three 2‐month‐old WHV/c‐myc mice at the dysplastic stage, with age‐matched wt‐C57 mice as controls. We identified 2781 proteins, 540 of which were differentially expressed. These proteins successfully characterized certain precancerous biological processes and alterations in transcriptional regulators before tumor onset. Two candidates, FK506‐binding protein 4 (FKBP52) and ferritin heavy chain, were taken as examples for a search from the mouse model to clinical human tissues. Their levels in serum samples were determined by western blotting, and showed a noteworthy ability to distinguish between HCC and control cases. Immunohistochemical analysis with tissue microarrays confirmed the differential expression of FKBP52 between HCC and the paired controls (P < 0.001). The regulation of FKBP52 was also discovered to be relevant to HCC staging, with a dramatic decline at stage III (P < 0.05). The potentials of the candidate pool in this study were discussed in terms of delineating c‐myc‐induced hepatocarcinogenesis and facilitating biomarker discovery for early HCC diagnosis.

Dysfunction of PLA2G6 and CYP2C44-associated network signals imminent carcinogenesis from chronic inflammation to hepatocellular carcinoma

Abstract Little is known about how chronic inflammation contributes to the progression of hepatocellular carcinoma (HCC), especially the initiation of cancer. To uncover the critical transition from chronic inflammation to HCC and the molecular mechanisms at a network level, we analyzed the time-series proteomic data of woodchuck hepatitis virus/c-myc mice and age-matched wt-C57BL/6 mice using our dynamical network biomarker (DNB) model. DNB analysis indicated that the 5th month after birth of transgenic mice was the critical period of cancer initiation, just before the critical transition, which is consistent with clinical symptoms. Meanwhile, the DNB-associated network showed a drastic inversion of protein expression and coexpression levels before and after the critical transition. Two members of DNB, PLA2G6 and CYP2C44, along with their associated differentially expressed proteins, were found to induce dysfunction of arachidonic acid metabolism, further activate inflammatory responses through inflammatory mediator regulation of transient receptor potential channels, and finally lead to impairments of liver detoxification and malignant transition to cancer. As a c-Myc target, PLA2G6 positively correlated with c-Myc in expression, showing a trend from decreasing to increasing during carcinogenesis, with the minimal point at the critical transition or tipping point. Such trend of homologous PLA2G6 and c-Myc was also observed during human hepatocarcinogenesis, with the minimal point at high-grade dysplastic nodules (a stage just before the carcinogenesis). Our study implies that PLA2G6 might function as an oncogene like famous c-Myc during hepatocarcinogenesis, while downregulation of PLA2G6 and c-Myc could be a warning signal indicating imminent carcinogenesis.