Steven P. Gygi

Bio: Steven P. Gygi is an academic researcher from Harvard University. The author has contributed to research in topics: Phosphorylation & Proteome. The author has an hindex of 172, co-authored 704 publications receiving 129173 citations. Previous affiliations of Steven P. Gygi include University of Rochester Medical Center & Cell Signaling Technology.

Rixosomal RNA degradation contributes to silencing of Polycomb target genes

Abstract: Abstract Polycomb repressive complexes 1 and 2 (PRC1 and PRC2) are histone-modifying and -binding complexes that mediate the formation of facultative heterochromatin and are required for silencing of developmental genes and maintenance of cell fate 1–3 . Multiple pathways of RNA decay work together to establish and maintain heterochromatin in fission yeast, including a recently identified role for a conserved RNA-degradation complex known as the rixosome or RIX1 complex 4–6 . Whether RNA degradation also has a role in the stability of mammalian heterochromatin remains unknown. Here we show that the rixosome contributes to silencing of many Polycomb targets in human cells. The rixosome associates with human PRC complexes and is enriched at promoters of Polycomb target genes. Depletion of either the rixosome or Polycomb results in accumulation of paused and elongating RNA polymerase at Polycomb target genes. We identify point mutations in the RING1B subunit of PRC1 that disrupt the interaction between PRC1 and the rixosome and result in diminished silencing, suggesting that direct recruitment of the rixosome to chromatin is required for silencing. Finally, we show that the RNA endonuclease and kinase activities of the rixosome and the downstream XRN2 exoribonuclease, which degrades RNAs with 5′ monophosphate groups generated by the rixosome, are required for silencing. Our findings suggest that rixosomal degradation of nascent RNA is conserved from fission yeast to human, with a primary role in RNA degradation at facultative heterochromatin in human cells.

Mechanism of p38 MAPK-induced EGFR endocytosis and its crosstalk with ligand-induced pathways.

Abstract: Ligand binding triggers clathrin-mediated and, at high ligand concentrations, clathrin-independent endocytosis of EGFR Clathrin-mediated endocytosis (CME) of EGFR is also induced by stimuli activating p38 MAPK Mechanisms of both ligand- and p38-induced endocytosis are not fully understood, and how these pathways intermingle when concurrently activated remains unknown Here we dissect the mechanisms of p38-induced endocytosis using a pH-sensitive model of endogenous EGFR, which is extracellularly tagged with a fluorogen-activating protein, and propose a unifying model of the crosstalk between multiple EGFR endocytosis pathways We found that a new locus of p38-dependent phosphorylation in EGFR is essential for the receptor dileucine motif interaction with the σ2 subunit of clathrin adaptor AP2 and concomitant receptor internalization p38-dependent endocytosis of EGFR induced by cytokines was additive to CME induced by picomolar EGF concentrations but constrained to internalizing ligand-free EGFRs due to Grb2 recruitment by ligand-activated EGFRs Nanomolar EGF concentrations rerouted EGFR from CME to clathrin-independent endocytosis, primarily by diminishing p38-dependent endocytosis

Rixosomal RNA degradation contributes to silencing of Polycomb target genes

Abstract: Abstract Polycomb repressive complexes 1 and 2 (PRC1 and PRC2) are histone-modifying and -binding complexes that mediate the formation of facultative heterochromatin and are required for silencing of developmental genes and maintenance of cell fate 1–3 . Multiple pathways of RNA decay work together to establish and maintain heterochromatin in fission yeast, including a recently identified role for a conserved RNA-degradation complex known as the rixosome or RIX1 complex 4–6 . Whether RNA degradation also has a role in the stability of mammalian heterochromatin remains unknown. Here we show that the rixosome contributes to silencing of many Polycomb targets in human cells. The rixosome associates with human PRC complexes and is enriched at promoters of Polycomb target genes. Depletion of either the rixosome or Polycomb results in accumulation of paused and elongating RNA polymerase at Polycomb target genes. We identify point mutations in the RING1B subunit of PRC1 that disrupt the interaction between PRC1 and the rixosome and result in diminished silencing, suggesting that direct recruitment of the rixosome to chromatin is required for silencing. Finally, we show that the RNA endonuclease and kinase activities of the rixosome and the downstream XRN2 exoribonuclease, which degrades RNAs with 5′ monophosphate groups generated by the rixosome, are required for silencing. Our findings suggest that rixosomal degradation of nascent RNA is conserved from fission yeast to human, with a primary role in RNA degradation at facultative heterochromatin in human cells.

Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks

Abstract: Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

Machine learning

Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

The MIQE Guidelines: Minimum Information for Publication of Quantitative Real-Time PCR Experiments

Abstract: Background: Currently, a lack of consensus exists on how best to perform and interpret quantitative real-time PCR (qPCR) experiments. The problem is exacerbated by a lack of sufficient experimental detail in many publications, which impedes a reader’s ability to evaluate critically the quality of the results presented or to repeat the experiments. Content: The Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines target the reliability of results to help ensure the integrity of the scientific literature, promote consistency between laboratories, and increase experimental transparency. MIQE is a set of guidelines that describe the minimum information necessary for evaluating qPCR experiments. Included is a checklist to accompany the initial submission of a manuscript to the publisher. By providing all relevant experimental conditions and assay characteristics, reviewers can assess the validity of the protocols used. Full disclosure of all reagents, sequences, and analysis methods is necessary to enable other investigators to reproduce results. MIQE details should be published either in abbreviated form or as an online supplement. Summary: Following these guidelines will encourage better experimental practice, allowing more reliable and unequivocal interpretation of qPCR results.