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.

Identification of UHRF2 as a novel DNA interstrand crosslink sensor protein.

Abstract: The Fanconi Anemia (FA) pathway is important for repairing interstrand crosslinks (ICLs) between the Watson-Crick strands of the DNA double helix. An initial and essential stage in the repair process is the detection of the ICL. Here, we report the identification of UHRF2, a paralogue of UHRF1, as an ICL sensor protein. UHRF2 is recruited to ICLs in the genome within seconds of their appearance. We show that UHRF2 cooperates with UHRF1, to ensure recruitment of FANCD2 to ICLs. A direct protein-protein interaction is formed between UHRF1 and UHRF2, and between either UHRF1 and UHRF2, and FANCD2. Importantly, we demonstrate that the essential monoubiquitination of FANCD2 is stimulated by UHRF1/UHRF2. The stimulation is mediating by a retention of FANCD2 on chromatin, allowing for its monoubiquitination by the FA core complex. Taken together, we uncover a mechanism of ICL sensing by UHRF2, leading to FANCD2 recruitment and retention at ICLs, in turn facilitating activation of FANCD2 by monoubiquitination.

A peroxisomal ubiquitin ligase complex forms a retrotranslocation channel

Abstract: Abstract Peroxisomes are ubiquitous organelles that house various metabolic reactions and are essential for human health 1–4 . Luminal peroxisomal proteins are imported from the cytosol by mobile receptors, which then recycle back to the cytosol by a poorly understood process 1–4 . Recycling requires receptor modification by a membrane-embedded ubiquitin ligase complex comprising three RING finger domain-containing proteins (Pex2, Pex10 and Pex12) 5,6 . Here we report a cryo-electron microscopy structure of the ligase complex, which together with biochemical and in vivo experiments reveals its function as a retrotranslocation channel for peroxisomal import receptors. Each subunit of the complex contributes five transmembrane segments that co-assemble into an open channel. The three ring finger domains form a cytosolic tower, with ring finger 2 (RF2) positioned above the channel pore. We propose that the N terminus of a recycling receptor is inserted from the peroxisomal lumen into the pore and monoubiquitylated by RF2 to enable extraction into the cytosol. If recycling is compromised, receptors are polyubiquitylated by the concerted action of RF10 and RF12 and degraded. This polyubiquitylation pathway also maintains the homeostasis of other peroxisomal import factors. Our results clarify a crucial step during peroxisomal protein import and reveal why mutations in the ligase complex cause human disease.

The biochemical basis of mitochondrial dysfunction in Zellweger Spectrum Disorder.

Abstract: Peroxisomal biogenesis disorders (PBDs) are genetic disorders of peroxisome biogenesis and metabolism that are characterized by profound developmental and neurological phenotypes. The most severe class of PBDs-Zellweger spectrum disorder (ZSD)-is caused by mutations in peroxin genes that result in both non-functional peroxisomes and mitochondrial dysfunction. It is unclear, however, how defective peroxisomes contribute to mitochondrial impairment. In order to understand the molecular basis of this inter-organellar relationship, we investigated the fate of peroxisomal mRNAs and proteins in ZSD model systems. We found that peroxins were still expressed and a subset of them accumulated on the mitochondrial membrane, which resulted in gross mitochondrial abnormalities and impaired mitochondrial metabolic function. We showed that overexpression of ATAD1, a mitochondrial quality control factor, was sufficient to rescue several aspects of mitochondrial function in human ZSD fibroblasts. Together, these data suggest that aberrant peroxisomal protein localization is necessary and sufficient for the devastating mitochondrial morphological and metabolic phenotypes in ZSDs.

Targeting the cyclin-dependent kinase 5 in metastatic melanoma.

Abstract: The cyclin-dependent kinase 5 (CDK5), originally described as a neuronal-specific kinase, is also frequently activated in human cancers. Using conditional CDK5 knockout mice and a mouse model of highly metastatic melanoma, we found that CDK5 is dispensable for the growth of primary tumors. However, we observed that ablation of CDK5 completely abrogated the metastasis, revealing that CDK5 is essential for the metastatic spread. In mouse and human melanoma cells CDK5 promotes cell invasiveness by directly phosphorylating an intermediate filament protein, vimentin, thereby inhibiting assembly of vimentin filaments. Chemical inhibition of CDK5 blocks the metastatic spread of patient-derived melanomas in patient-derived xenograft (PDX) mouse models. Hence, inhibition of CDK5 might represent a very potent therapeutic strategy to impede the metastatic dissemination of malignant 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.