Meng-Qiu Dong

Bio: Meng-Qiu Dong is an academic researcher from Tsinghua University. The author has contributed to research in topics: Caenorhabditis elegans & Biology. The author has an hindex of 45, co-authored 169 publications receiving 9657 citations. Previous affiliations of Meng-Qiu Dong include Chinese Academy of Sciences & Peking Union Medical College.

RIP3, an energy metabolism regulator that switches TNF-induced cell death from apoptosis to necrosis

Abstract: Necrosis can be induced by stimulating death receptors with tumor necrosis factor (TNF) or other agonists; however, the underlying mechanism differentiating necrosis from apoptosis is largely unknown. We identified the protein kinase receptor-interacting protein 3 (RIP3) as a molecular switch between TNF-induced apoptosis and necrosis in NIH 3T3 cells and found that RIP3 was required for necrosis in other cells. RIP3 did not affect RIP1-mediated apoptosis but was required for RIP1-mediated necrosis and the enhancement of necrosis by the caspase inhibitor zVAD. By activating key enzymes of metabolic pathways, RIP3 regulates TNF-induced reactive oxygen species production, which partially accounts for RIP3's ability to promote necrosis. Our data suggest that modulation of energy metabolism in response to death stimuli has an important role in the choice between apoptosis and necrosis.

Automated approach for quantitative analysis of complex peptide mixtures from tandem mass spectra

Abstract: To take advantage of the potential quantitative benefits offered by tandem mass spectrometry, we have modified the method in which tandem mass spectrum data are acquired in 'shotgun' proteomic analyses. The proposed method is not data dependent and is based on the sequential isolation and fragmentation of precursor windows (of 10 m/z) within the ion trap until a desired mass range has been covered. We compared the quantitative figures of merit for this method to those for existing strategies by performing an analysis of the soluble fraction of whole-cell lysates from yeast metabolically labeled in vivo with 15N. To automate this analysis, we modified software (RelEx) previously written in the Yates lab to generate chromatograms directly from tandem mass spectra. These chromatograms showed improvements in signal-to-noise ratio of approximately three- to fivefold over corresponding chromatograms generated from mass spectrometry scans. In addition, to demonstrate the utility of the data-independent acquisition strategy coupled with chromatogram reconstruction from tandem mass spectra, we measured protein expression levels in two developmental stages of Caenorhabditis elegans.

Identification of cross-linked peptides from complex samples

Abstract: pLink, software for data analysis of cross-linked proteins coupled with mass spectrometry, estimates false discovery rate and enables analysis of protein complexes without extensive purification. We have developed pLink, software for data analysis of cross-linked proteins coupled with mass-spectrometry analysis. pLink reliably estimates false discovery rate in cross-link identification and is compatible with multiple homo- or hetero-bifunctional cross-linkers. We validated the program with proteins of known structures, and we further tested it on protein complexes, crude immunoprecipitates and whole-cell lysates. We show that it is a robust tool for protein-structure and protein-protein–interaction studies.

Structure of the voltage-gated calcium channel Ca v 1.1 at 3.6 Å resolution

Abstract: The voltage-gated calcium (Cav) channels convert membrane electrical signals to intracellular Ca2+-mediated events. Among the ten subtypes of Cav channel in mammals, Cav1.1 is specified for the excitation–contraction coupling of skeletal muscles. Here we present the cryo-electron microscopy structure of the rabbit Cav1.1 complex at a nominal resolution of 3.6 A. The inner gate of the ion-conducting α1-subunit is closed and all four voltage-sensing domains adopt an ‘up’ conformation, suggesting a potentially inactivated state. The extended extracellular loops of the pore domain, which are stabilized by multiple disulfide bonds, form a windowed dome above the selectivity filter. One side of the dome provides the docking site for the α2δ-1-subunit, while the other side may attract cations through its negative surface potential. The intracellular I–II and III–IV linker helices interact with the β1a-subunit and the carboxy-terminal domain of α1, respectively. Classification of the particles yielded two additional reconstructions that reveal pronounced displacement of β1a and adjacent elements in α1. The atomic model of the Cav1.1 complex establishes a foundation for mechanistic understanding of excitation–contraction coupling and provides a three-dimensional template for molecular interpretations of the functions and disease mechanisms of Cav and Nav channels. The cryo-electron microscopy structure of the rabbit voltage-gated calcium channel Cav1.1 complex at a nominal resolution of 3.6 angstroms. Voltage-gated calcium (Cav) channels translate membrane electrical signals into intracellular Ca2+-mediated events. For example, Cav1.1 is expressed in skeletal muscle and serves as the voltage sensor for excitation–contraction coupling. These authors report a 3.6 A resolution cryo-electron microscopy structure of rabbit Cav1.1. The high resolution of the core ɑ1-subunit makes it possible to examine the ion permeation path in detail, and the structure reveals that several extended extracellular loops unexpectedly form a 'windowed dome' above the selectivity filter. The near-atomic structure of Cav1.1 complex establishes a foundation for mechanistic understanding of excitation–contraction coupling and provides a three-dimensional template for molecular interpretations of function and disease mechanism of Cav and Nav channels.

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

Abstract: In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure flux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagy-related protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular assays, we hope to encourage technical innovation in the field.

“Bioinformatics” 특집을 내면서

Abstract: BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

The impact of microRNAs on protein output

Abstract: MicroRNAs are endogenous ∼23-nucleotide RNAs that can pair to sites in the messenger RNAs of protein-coding genes to downregulate the expression from these messages. MicroRNAs are known to influence the evolution and stability of many mRNAs, but their global impact on protein output had not been examined. Here we use quantitative mass spectrometry to measure the response of thousands of proteins after introducing microRNAs into cultured cells and after deleting mir-223 in mouse neutrophils. The identities of the responsive proteins indicate that targeting is primarily through seed-matched sites located within favourable predicted contexts in 3′ untranslated regions. Hundreds of genes were directly repressed, albeit each to a modest degree, by individual microRNAs. Although some targets were repressed without detectable changes in mRNA levels, those translationally repressed by more than a third also displayed detectable mRNA destabilization, and, for the more highly repressed targets, mRNA destabilization usually comprised the major component of repression. The impact of microRNAs on the proteome indicated that for most interactions microRNAs act as rheostats to make fine-scale adjustments to protein output. MicroRNAs can regulate gene expression by either inhibiting translation of a messenger RNA, or inducing its degradation. While previous studies have measured regulation at the mRNA level, it was unknown how much regulation occurred at the protein level. Now two groups led by David Bartel and Nikolaus Rajewsky have used variants of the technique known as SILAC (stable isotope labelling with amino acids in cell culture) to measure proteome-wide changes in protein level as a function of expression of endogenous and exogenous microRNAs. They find that while microRNAs can directly repress the translation of hundreds of genes, additional indirect effects result in changes in expression of thousands of genes. Many of the changes observed are less than twofold in magnitude, however, indicating either directly or indirectly, microRNAs can act as rheostats to fine-tune protein synthesis to match the needs of the cell at any given time. In one of two studies, a technique known as SILAC is used to measure, on a large scale, changes in protein level as a function of expression of endogenous and exogenous miRNAs. It is found that although miRNAs directly repress the translation of hundreds of genes, additional indirect effects result in changes in expression of thousands of genes.