Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Linfeng Wu is active.

Publication


Featured researches published by Linfeng Wu.


Nature | 2012

Architecture of the human regulatory network derived from ENCODE data

Mark Gerstein; Anshul Kundaje; Manoj Hariharan; Stephen G. Landt; Koon Kiu Yan; Chao Cheng; Xinmeng Jasmine Mu; Ekta Khurana; Joel Rozowsky; Roger P. Alexander; Renqiang Min; Pedro Alves; Alexej Abyzov; Nick Addleman; Nitin Bhardwaj; Alan P. Boyle; Philip Cayting; Alexandra Charos; David Chen; Yong Cheng; Declan Clarke; Catharine L. Eastman; Ghia Euskirchen; Seth Frietze; Yao Fu; Jason Gertz; Fabian Grubert; Arif Harmanci; Preti Jain; Maya Kasowski

Transcription factors bind in a combinatorial fashion to specify the on-and-off states of genes; the ensemble of these binding events forms a regulatory network, constituting the wiring diagram for a cell. To examine the principles of the human transcriptional regulatory network, we determined the genomic binding information of 119 transcription-related factors in over 450 distinct experiments. We found the combinatorial, co-association of transcription factors to be highly context specific: distinct combinations of factors bind at specific genomic locations. In particular, there are significant differences in the binding proximal and distal to genes. We organized all the transcription factor binding into a hierarchy and integrated it with other genomic information (for example, microRNA regulation), forming a dense meta-network. Factors at different levels have different properties; for instance, top-level transcription factors more strongly influence expression and middle-level ones co-regulate targets to mitigate information-flow bottlenecks. Moreover, these co-regulations give rise to many enriched network motifs (for example, noise-buffering feed-forward loops). Finally, more connected network components are under stronger selection and exhibit a greater degree of allele-specific activity (that is, differential binding to the two parental alleles). The regulatory information obtained in this study will be crucial for interpreting personal genome sequences and understanding basic principles of human biology and disease.


Science Signaling | 2009

Quantitative Phosphoproteomic Analysis of T Cell Receptor Signaling Reveals System-Wide Modulation of Protein-Protein Interactions

Mayya; Deborah H. Lundgren; Sun-Il Hwang; Karim Rezaul; Linfeng Wu; Jimmy K. Eng; Rodionov; David K. Han

Serine-threonine phosphorylation plays a role in regulating the interactions among proteins involved in T cell responses. Further Interactions The binding of antigen to the T cell receptor (TCR) complex triggers a cascade of responses that culminate in T cell activation. Key to the initial stages of this cascade is the phosphorylation of tyrosine residues in proteins proximal to the TCR, which enables the recruitment of other proteins that contain phosphotyrosine-binding domains. Given its importance to TCR signaling, tyrosine phosphorylation of target proteins has received considerable attention. To view protein phosphorylation from a larger perspective, Mayya et al. performed a system-level phosphoproteomics analysis of the events triggered by TCR activation in the human Jurkat T cell line. They found that the status of hundreds of phosphorylation sites was modulated in response to stimulation of the TCR. In addition to identifying previously unknown TCR-responsive phosphorylation events, this analysis also suggests a role for phosphorylated serine and threonine residues in modulating protein-protein interactions between many proteins involved in T cell responses. Protein phosphorylation events during T cell receptor (TCR) signaling control the formation of complexes among proteins proximal to the TCR, the activation of kinase cascades, and the activation of transcription factors; however, the mode and extent of the influence of phosphorylation in coordinating the diverse phenomena associated with T cell activation are unclear. Therefore, we used the human Jurkat T cell leukemia cell line as a model system and performed large-scale quantitative phosphoproteomic analyses of TCR signaling. We identified 10,665 unique phosphorylation sites, of which 696 showed TCR-responsive changes. In addition, we analyzed broad trends in phosphorylation data sets to uncover underlying mechanisms associated with T cell activation. We found that, upon stimulation of the TCR, phosphorylation events extensively targeted protein modules involved in all of the salient phenomena associated with T cell activation: patterning of surface proteins, endocytosis of the TCR, formation of the F-actin cup, inside-out activation of integrins, polarization of microtubules, production of cytokines, and alternative splicing of messenger RNA. Further, case-by-case analysis of TCR-responsive phosphorylation sites on proteins belonging to relevant functional modules together with network analysis allowed us to deduce that serine-threonine (S-T) phosphorylation modulated protein-protein interactions (PPIs) in a system-wide fashion. We also provide experimental support for this inference by showing that phosphorylation of tubulin on six distinct serine residues abrogated PPIs during the assembly of microtubules. We propose that modulation of PPIs by stimulus-dependent changes in S-T phosphorylation state is a widespread phenomenon applicable to many other signaling systems.


Expert Review of Proteomics | 2010

Role of spectral counting in quantitative proteomics

Deborah H. Lundgren; Sun-Il Hwang; Linfeng Wu; David K. Han

Spectral count, defined as the total number of spectra identified for a protein, has gained acceptance as a practical, label-free, semiquantitative measure of protein abundance in proteomic studies. In this review, we discuss issues affecting the performance of spectral counting relative to other label-free methods, as well as its limitations. Possible consequences of modifications, which are commonly applied to raw spectral counts to improve abundance estimations, are considered. The use of spectral counting for different types of quantitation studies is explored and critiqued. Different statistical methods and underlying frameworks that have been applied to spectral count analysis are described and compared, and problem areas that undermine confident statistical analysis are considered. Finally, the issue of accurate estimation of false-discovery rates is addressed and identified as a major current challenge in quantitative proteomics.


Nature | 2013

Variation and genetic control of protein abundance in humans.

Linfeng Wu; Sophie I. Candille; Yoonha Choi; Dan Xie; Lihua Jiang; Jennifer Li-Pook-Than; Hua Tang; Michael Snyder

Gene expression differs among individuals and populations and is thought to be a major determinant of phenotypic variation. Although variation and genetic loci responsible for RNA expression levels have been analysed extensively in human populations, our knowledge is limited regarding the differences in human protein abundance and the genetic basis for this difference. Variation in messenger RNA expression is not a perfect surrogate for protein expression because the latter is influenced by an array of post-transcriptional regulatory mechanisms, and, empirically, the correlation between protein and mRNA levels is generally modest. Here we used isobaric tag-based quantitative mass spectrometry to determine relative protein levels of 5,953 genes in lymphoblastoid cell lines from 95 diverse individuals genotyped in the HapMap Project. We found that protein levels are heritable molecular phenotypes that exhibit considerable variation between individuals, populations and sexes. Levels of specific sets of proteins involved in the same biological process covary among individuals, indicating that these processes are tightly regulated at the protein level. We identified cis-pQTLs (protein quantitative trait loci), including variants not detected by previous transcriptome studies. This study demonstrates the feasibility of high-throughput human proteome quantification that, when integrated with DNA variation and transcriptome information, adds a new dimension to the characterization of gene expression regulation.


Proceedings of the National Academy of Sciences of the United States of America | 2010

Close association of RNA polymerase II and many transcription factors with Pol III genes

Debasish Raha; Zhong Wang; Zarmik Moqtaderi; Linfeng Wu; Guoneng Zhong; Mark Gerstein; Kevin Struhl; Michael Snyder

Transcription of the eukaryotic genomes is carried out by three distinct RNA polymerases I, II, and III, whereby each polymerase is thought to independently transcribe a distinct set of genes. To investigate a possible relationship of RNA polymerases II and III, we mapped their in vivo binding sites throughout the human genome by using ChIP-Seq in two different cell lines, GM12878 and K562 cells. Pol III was found to bind near many known genes as well as several previously unidentified target genes. RNA-Seq studies indicate that a majority of the bound genes are expressed, although a subset are not suggestive of stalling by RNA polymerase III. Pol II was found to bind near many known Pol III genes, including tRNA, U6, HVG, hY, 7SK and previously unidentified Pol III target genes. Similarly, in vivo binding studies also reveal that a number of transcription factors normally associated with Pol II transcription, including c-Fos, c-Jun and c-Myc, also tightly associate with most Pol III-transcribed genes. Inhibition of Pol II activity using α-amanitin reduced expression of a number of Pol III genes (e.g., U6, hY, HVG), suggesting that Pol II plays an important role in regulating their transcription. These results indicate that, contrary to previous expectations, polymerases can often work with one another to globally coordinate gene expression.


Molecular & Cellular Proteomics | 2006

Absolute Quantification of Multisite Phosphorylation by Selective Reaction Monitoring Mass Spectrometry Determination of Inhibitory Phosphorylation Status of Cyclin-Dependent Kinases

Viveka Mayya; Karim Rezual; Linfeng Wu; Michael B. Fong; David K. Han

Multisite phosphorylation is an important mechanism for achieving intricate regulation of protein function. Here we extended the absolute quantification of abundance (AQUA) methodology and validated its applicability to quantitatively study multisite phosphorylation. As a test case, we chose the conserved inhibitory site of the cyclin-dependent kinases (CDKs), Cdk1, Cdk2, and Cdk3, which are important regulators of cell cycle transitions and apoptosis. Inhibitory phosphorylation at Thr14 and Tyr15 of the CDKs is modulated by complex regulatory mechanisms involving multiple kinases and phosphatases. Yet the resulting quantitative dynamics among the four possible phosphorylated and non-phosphorylated versions of CDKs (T14p-Y15p, T14p-Y15, T14-Y15p, and T14-Y15) has not been investigated to date. Hence we used the heavy isotope-labeled tryptic peptides spanning the inhibitory site as internal standards and quantified all four versions by LC-selected reaction monitoring. Quantification of the phosphorylation status of the inhibitory site in the cell extracts provided novel quantitative insights. 1) The transition to mitotic phase was dominated by the conversion of “T14p-Y15p” to the “T14-Y15” form, whereas the two monophosphorylated forms were considerably lower in abundance. 2) The amount of all four forms decreased during the progression of apoptosis but with differing kinetics. Analysis of immunoprecipitated Cdk1 and Cdk2 revealed that the inhibitory site phosphorylation state of both kinases at different stages of the cell cycle followed the same trend. Quantitative immunoblotting using antibodies to Cdk1 and Cdk2 and to the T14-Y15p form suggested that quantification by AQUA was reliable and accurate. These results highlight the utility of internal standard peptides to achieve accurate quantification of multisite phosphorylation status.


Molecular & Cellular Proteomics | 2005

A Systematic Characterization of Mitochondrial Proteome from Human T Leukemia Cells

Karim Rezaul; Linfeng Wu; Viveka Mayya; Sun-Il Hwang; David K. Han

Global understanding of tissue-specific differences in mitochondrial signal transduction requires comprehensive mitochondrial protein identification from multiple cell and tissue types. Here, we explore the feasibility and efficiency of protein identification using the one-dimensional gel electrophoresis in combination with the nano liquid-chromatography tandem mass spectrometry (GeLC-MS/MS). The use of only 40 μg of purified mitochondrial proteins and data analysis using stringent scoring criteria and the molecular mass validation of the gel slices enables the identification of 227 known mitochondrial proteins (membrane and soluble) and 453 additional proteins likely to be associated with mitochondria. Replicate analyses of 60 μg of mitochondrial proteins on the faster scanning LTQ mass spectrometer validate all the previously identified proteins and most of the single hit proteins except the 81 single hit proteins. Among the identified proteins, 466 proteins are known to functionally participate in various processes such as respiration, tricarboxylic acid cycle (TCA cycle), amino acid and nucleotide metabolism, glycolysis, protection against oxidative stress, mitochondrial assembly, molecular transport, protein biosynthesis, cell cycle control, and many known cellular processes. The distribution of identified proteins in terms of size, pI, and hydrophobicity reveal that the present analytical strategy is largely unbiased and very efficient. Thus, we conclude that this approach is suitable for characterizing subcellular proteomes form multiple cells and tissues.


Cell | 2013

Dynamic trans-Acting Factor Colocalization in Human Cells

Dan Xie; Alan P. Boyle; Linfeng Wu; Jie Zhai; Trupti Kawli; Michael Snyder

Different trans-acting factors (TFs) collaborate and act in concert at distinct loci to perform accurate regulation of their target genes. To date, the cobinding of TF pairs has been investigated in a limited context both in terms of the number of factors within a cell type and across cell types and the extent of combinatorial colocalizations. Here, we use an approach to analyze TF colocalization within a cell type and across multiple cell lines at an unprecedented level. We extend this approach with large-scale mass spectrometry analysis of immunoprecipitations of 50 TFs. Our combined approach reveals large numbers of interesting TF-TF associations. We observe extensive change in TF colocalizations both within a cell type exposed to different conditions and across multiple cell types. We show distinct functional annotations and properties of different TF cobinding patterns and provide insights into the complex regulatory landscape of the cell.


Nature Immunology | 2013

Defective sphingosine 1-phosphate receptor 1 (S1P1) phosphorylation exacerbates TH17-mediated autoimmune neuroinflammation

Christopher Garris; Linfeng Wu; Swati Acharya; Ahmet Arac; Victoria A. Blaho; Yingxiang Huang; Byoung San Moon; Robert C. Axtell; Peggy P. Ho; Gary K. Steinberg; David B. Lewis; Raymond A. Sobel; David K. Han; Lawrence Steinman; Michael Snyder; Timothy Hla; May H. Han

Sphingosine 1-phosphate (S1P) signaling regulates lymphocyte egress from lymphoid organs into systemic circulation. The sphingosine phosphate receptor 1 (S1P1) agonist FTY-720 (Gilenya) arrests immune trafficking and prevents multiple sclerosis (MS) relapses. However, alternative mechanisms of S1P-S1P1 signaling have been reported. Phosphoproteomic analysis of MS brain lesions revealed S1P1 phosphorylation on S351, a residue crucial for receptor internalization. Mutant mice harboring an S1pr1 gene encoding phosphorylation-deficient receptors (S1P1(S5A)) developed severe experimental autoimmune encephalomyelitis (EAE) due to autoimmunity mediated by interleukin 17 (IL-17)–producing helper T cells (TH17 cells) in the peripheral immune and nervous system. S1P1 directly activated the Jak-STAT3 signal-transduction pathway via IL-6. Impaired S1P1 phosphorylation enhances TH17 polarization and exacerbates autoimmune neuroinflammation. These mechanisms may be pathogenic in MS.


Expert Review of Proteomics | 2006

Overcoming the dynamic range problem in mass spectrometry-based shotgun proteomics

Linfeng Wu; David K. Han

Protein profiling using mass spectrometry technology has emerged as a powerful method for analyzing large-scale protein-expression patterns in cells and tissues. However, a number of challenges are present in proteomics research, one of the greatest being the high degree of protein complexity and huge dynamic range of proteins expressed in the complex biological mixtures, which exceeds six orders of magnitude in cells and ten orders of magnitude in body fluids. Since many important signaling proteins have low expression levels, methods to detect the low-abundance proteins in a complex sample are required. This review will focus on the fundamental fractionation and mass spectrometry techniques currently used for large-scale shotgun proteomics research.

Collaboration


Dive into the Linfeng Wu's collaboration.

Top Co-Authors

Avatar

David K. Han

University of Connecticut

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Sun-Il Hwang

Carolinas Healthcare System

View shared research outputs
Top Co-Authors

Avatar

Karim Rezaul

University of Connecticut Health Center

View shared research outputs
Top Co-Authors

Avatar

Viveka Mayya

University of Connecticut Health Center

View shared research outputs
Top Co-Authors

Avatar

Deborah H. Lundgren

University of Connecticut Health Center

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Jimmy K. Eng

University of Washington

View shared research outputs
Researchain Logo
Decentralizing Knowledge