Showing papers by "Institute for Systems Biology published in 2009"
TL;DR: It is demonstrated that specific microRNA species, such as mir-122 and mir-192, both are enriched in the liver tissue and exhibit dose- and exposure duration-dependent changes in the plasma that parallel serum aminotransferase levels and the histopathology of liver degeneration, but their changes can be detected significantly earlier.
Abstract: Drug-induced liver injury is a frequent side effect of many drugs, constitutes a significant threat to patient health and has an enormous economic impact on health care expenditures. Numerous efforts have been made to identify reliable and predictive markers to detect the early signs of drug-induced injury to the liver, one of the most vulnerable organs in the body. These studies have, however, not delivered any more informative candidates than the serum aminotransferase markers that have been available for ≈30 years. Using acetaminophen overdose-induced liver injury in the mouse as a model system, we have observed highly significant differences in the spectrum and levels of microRNAs in both liver tissues and in plasma between control and overdosed animals. Based on our survey of microRNA expression among normal tissues, some of the microRNAs, like messenger RNAs, display restricted tissue distributions. A number of elevated circulating microRNAs in plasma collected from acetaminophen-overdosed animals are highly expressed in the liver. We have demonstrated that specific microRNA species, such as mir-122 and mir-192, both are enriched in the liver tissue and exhibit dose- and exposure duration-dependent changes in the plasma that parallel serum aminotransferase levels and the histopathology of liver degeneration, but their changes can be detected significantly earlier. These findings suggest the potential of using specific circulating microRNAs as sensitive and informative biomarkers for drug-induced liver injury.
1,123 citations
TL;DR: It is shown that interleukin-1 (IL-1) signaling on T cells is critically required for the early programming of Th 17 cell lineage and Th17 cell-mediated autoimmunity and this pathway may serve as a unique target for Th17cell-mediated immunopathology.
1,102 citations
TL;DR: This article used a system biology approach to identify early gene signatures that predicted immune responses in humans vaccinated with the yellow fever vaccine YF-17D, with up to 90% accuracy in an independent, blinded trial.
Abstract: A major challenge in vaccinology is to prospectively determine vaccine efficacy. Here we have used a systems biology approach to identify early gene 'signatures' that predicted immune responses in humans vaccinated with yellow fever vaccine YF-17D. Vaccination induced genes that regulate virus innate sensing and type I interferon production. Computational analyses identified a gene signature, including complement protein C1qB and eukaryotic translation initiation factor 2 alpha kinase 4-an orchestrator of the integrated stress response-that correlated with and predicted YF-17D CD8(+) T cell responses with up to 90% accuracy in an independent, blinded trial. A distinct signature, including B cell growth factor TNFRS17, predicted the neutralizing antibody response with up to 100% accuracy. These data highlight the utility of systems biology approaches in predicting vaccine efficacy.
1,004 citations
TL;DR: The exacerbated release of exosomes in tumor cells, as evidenced by their increased levels in blood during the late stage of a disease and their overexpression of certain tumor cell biomarkers, suggests an important role of exOSomes in diagnosis and biomarker studies.
Abstract: Exosomes are 40-100-nm diameter membrane vesicles of endocytic origin that are released by most cell types upon fusion of multivesicular bodies with the plasma membrane, presumably as a vehicle for cell-free intercellular communication. While early studies focused on their secretion from diverse cell types in vitro, exosomes have now been identified in body fluids such as urine, amniotic fluid, malignant ascites, bronchoalveolar lavage fluid, synovial fluid, breast milk, saliva and blood. Exosomes have pleiotropic biological functions, including immune response, antigen presentation, intracellular communication and the transfer of RNA and proteins. While they have also been implicated in the transport and propagation of infectious cargo, such as prions, and retroviruses, including HIV, suggesting a role in pathological situations, recent studies suggest that the presence of such infectious cargo may be artefacts of exosome-purification strategies. Improvements in mass spectrometry-based proteomic tools, both hardware and software, coupled with improved purification schemes for exosomes, has allowed more in-depth proteome analyses, contributing immensely to our understanding of the molecular composition of exosomes. Proteomic cataloguing of exosomes from diverse cell types has revealed a common set of membrane and cytosolic proteins, suggesting the evolutionary importance of these membrane particles. Additionally, exosomes express an array of proteins that reflect the originating host cell. Recent findings that exosomes contain inactive forms of both mRNA and microRNA that can be transferred to another cell and be functional in that new environment, have initiated many microRNA profiling studies of exosomes circulating in blood. These studies highlight the potential of exosomal microRNA profiles for use as diagnostic biomarkers of disease through a noninvasive blood test. The exacerbated release of exosomes in tumor cells, as evidenced by their increased levels in blood during the late stage of a disease and their overexpression of certain tumor cell biomarkers, suggests an important role of exosomes in diagnosis and biomarker studies. The aim of this article is to provide a brief overview of exosomes, including methods used to isolate and characterize exosomes. New advances in proteomic methods, and both mass spectrometry hardware and informatics tools will be covered briefly.
960 citations
TL;DR: It is shown that BAF complexes are required for the self-renewal and pluripotency of mouse ES cells but not for the proliferation of fibroblasts or other cells, suggesting that esBAF complexes are specialized to interact with ES cell-specific regulators, providing a potential explanation for the requirement of BAF complex in pluripOTency.
Abstract: Mammalian SWI/SNF [also called BAF (Brg/Brahma-associated factors)] ATP-dependent chromatin remodeling complexes are essential for formation of the totipotent and pluripotent cells of the early embryo. In addition, subunits of this complex have been recovered in screens for genes required for nuclear reprogramming in Xenopus and mouse embryonic stem cell (ES) morphology. However, the mechanism underlying the roles of these complexes is unclear. Here, we show that BAF complexes are required for the self-renewal and pluripotency of mouse ES cells but not for the proliferation of fibroblasts or other cells. Proteomic studies reveal that ES cells express distinctive complexes (esBAF) defined by the presence of Brg (Brahma-related gene), BAF155, and BAF60A, and the absence of Brm (Brahma), BAF170, and BAF60C. We show that this specialized subunit composition is required for ES cell maintenance and pluripotency. Our proteomic analysis also reveals that esBAF complexes interact directly with key regulators of pluripotency, suggesting that esBAF complexes are specialized to interact with ES cell-specific regulators, providing a potential explanation for the requirement of BAF complexes in pluripotency.
523 citations
TL;DR: A snapshot view of the cell surface N- glycoproteins will enable detection of panels of N-glycoprotein as potential differentiation markers that are currently not accessible by other means.
Abstract: Although the classification of cell types often relies on the identification of cell surface proteins as differentiation markers, flow cytometry requires suitable antibodies and currently permits detection of only up to a dozen differentiation markers in a single measurement. We use multiplexed mass-spectrometric identification of several hundred N-linked glycosylation sites specifically from cell surface-exposed glycoproteins to phenotype cells without antibodies in an unbiased fashion and without a priori knowledge. We apply our cell surface-capturing (CSC) technology, which covalently labels extracellular glycan moieties on live cells, to the detection and relative quantitative comparison of the cell surface N-glycoproteomes of T and B cells, as well as to monitor changes in the abundance of cell surface N-glycoprotein markers during T-cell activation and the controlled differentiation of embryonic stem cells into the neural lineage. A snapshot view of the cell surface N-glycoproteins will enable detection of panels of N-glycoproteins as potential differentiation markers that are currently not accessible by other means.
518 citations
TL;DR: Three papers provide a comprehensive and quantitative analysis of the proteome, the metabolic network, and the transcriptome of M. pneumoniae to reveal that this “simple” organism makes extensive use of noncoding RNAs and has exon- and intron-like structure within transcriptional operons that allows complex gene regulation resembling that of eukaryotes.
Abstract: The genome of Mycoplasma pneumoniae is among the smallest found in self-replicating organisms. To study the basic principles of bacterial proteome organization, we used tandem affinity purification-mass spectrometry (TAP-MS) in a proteome-wide screen. The analysis revealed 62 homomultimeric and 116 heteromultimeric soluble protein complexes, of which the majority are novel. About a third of the heteromultimeric complexes show higher levels of proteome organization, including assembly into larger, multiprotein complex entities, suggesting sequential steps in biological processes, and extensive sharing of components, implying protein multifunctionality. Incorporation of structural models for 484 proteins, single-particle electron microscopy, and cellular electron tomograms provided supporting structural details for this proteome organization. The data set provides a blueprint of the minimal cellular machinery required for life.
443 citations
TL;DR: This work presents a mass-spectrometry-based strategy to determine the absolute quantity, that is, the average number of protein copies per cell in a cell population, for a large fraction of the proteome in genetically unperturbed cells and expects it to become a cornerstone of quantitative biology and systems biology.
Abstract: Mass-spectrometry-based methods for relative proteome quantification have broadly affected life science research. However, important research directions, particularly those involving mathematical modelling and simulation of biological processes, also critically depend on absolutely quantitative data--that is, knowledge of the concentration of the expressed proteins as a function of cellular state. Until now, absolute protein concentration measurements of a considerable fraction of the proteome (73%) have only been derived from genetically altered Saccharomyces cerevisiae cells, a technique that is not directly portable from yeast to other species. Here we present a mass-spectrometry-based strategy to determine the absolute quantity, that is, the average number of protein copies per cell in a cell population, for a large fraction of the proteome in genetically unperturbed cells. Applying the technology to the human pathogen Leptospira interrogans, a spirochete responsible for leptospirosis, we generated an absolute protein abundance scale for 83% of the mass-spectrometry-detectable proteome, from cells at different states. Taking advantage of the unique cellular dimensions of L. interrogans, we used cryo-electron tomography morphological measurements to verify, at the single-cell level, the average absolute abundance values of selected proteins determined by mass spectrometry on a population of cells. Because the strategy is relatively fast and applicable to any cell type, we expect that it will become a cornerstone of quantitative biology and systems biology.
406 citations
TL;DR: This report reviews recently developed platform technologies for emerging applications of clinical proteomics and biomarker development and highlights the capability of using a "universal" approach to perform quantitative assays for a wide spectrum of proteins with minimum restrictions.
Abstract: The recent advance in technology for mass spectrometry-based targeted protein quantification has opened new avenues for a broad range of proteomic applications in clinical research. The major breakthroughs are highlighted by the capability of using a “universal” approach to perform quantitative assays for a wide spectrum of proteins with minimum restrictions and the ease of assembling multiplex detections in a single measurement. The quantitative approach relies on the use of synthetic stable isotope labeled peptides or proteins, which precisely mimic their endogenous counterparts and act as internal standards to quantify the corresponding candidate proteins. This report reviews recently developed platform technologies for emerging applications of clinical proteomics and biomarker development.
377 citations
TL;DR: It is recommended that systems medicine should be developed through an international network of systems biology and medicine centers dedicated to inter-disciplinary training and education, to help reduce the gap in healthcare between developed and developing countries.
Abstract: High-throughput technologies for DNA sequencing and for analyses of transcriptomes, proteomes and metabolomes have provided the foundations for deciphering the structure, variation and function of the human genome and relating them to health and disease states. The increased efficiency of DNA sequencing opens up the possibility of analyzing a large number of individual genomes and transcriptomes, and complete reference proteomes and metabolomes are within reach using powerful analytical techniques based on chromatography, mass spectrometry and nuclear magnetic resonance. Computational and mathematical tools have enabled the development of systems approaches for deciphering the functional and regulatory networks underlying the behavior of complex biological systems. Further conceptual and methodological developments of these tools are needed for the integration of various data types across the multiple levels of organization and time frames that are characteristic of human development, physiology and disease. Medical genomics has attempted to overcome the initial limitations of genome-wide association studies and has identified a limited number of susceptibility loci for many complex and common diseases. Iterative systems approaches are starting to provide deeper insights into the mechanisms of human diseases, and to facilitate the development of better diagnostic and prognostic biomarkers for cancer and many other diseases. Systems approaches will transform the way drugs are developed through academy-industry partnerships that will target multiple components of networks and pathways perturbed in diseases. They will enable medicine to become predictive, personalized, preventive and participatory, and, in the process, concepts and methods from Western and oriental cultures can be combined. We recommend that systems medicine should be developed through an international network of systems biology and medicine centers dedicated to inter-disciplinary training and education, to help reduce the gap in healthcare between developed and developing countries.
367 citations
TL;DR: The N‐glycoprotein based biomarker discovery and validation workflow reviewed here allows for the robust identification of protein candidate panels that can finally be selectively monitored in the blood plasma at high sensitivity in a reliable, non‐invasive and quantitative fashion.
TL;DR: Assessment of the rapamycin-sensitive phosphoproteomes in various genetic backgrounds revealed both documented and novel TORC1 effectors and allowed us to partition phosphorylation events between Tap42 and Sch9, demonstrating that Sch9 is a master regulator of protein synthesis.
Abstract: The target of rapamycin complex 1 (TORC1) is an essential multiprotein complex conserved from yeast to humans. Under favorable growth conditions, and in the absence of the macrolide rapamycin, TORC1 is active, and influences virtually all aspects of cell growth. Although two direct effectors of yeast TORC1 have been reported (Tap42, a regulator of PP2A phosphatases and Sch9, an AGC family kinase), the signaling pathways that couple TORC1 to its distal effectors were not well understood. To elucidate these pathways we developed and employed a quantitative, label-free mass spectrometry approach. Analyses of the rapamycin-sensitive phosphoproteomes in various genetic backgrounds revealed both documented and novel TORC1 effectors and allowed us to partition phosphorylation events between Tap42 and Sch9. Follow-up detailed characterization shows that Sch9 regulates RNA polymerases I and III, the latter via Maf1, in addition to translation initiation and the expression of ribosomal protein and ribosome biogenesis genes. This demonstrates that Sch9 is a master regulator of protein synthesis.
McGill University1, Institute for Systems Biology2, University of British Columbia3, National Institutes of Health4, Invitrogen5, Allergan6, Northeastern University7, Ruhr University Bochum8, Massachusetts Institute of Technology9, Discovery Institute10, Fred Hutchinson Cancer Research Center11, Georgetown University12, University of Gothenburg13, Harvard University14, Thermo Fisher Scientific15, Laval University16, Walter and Eliza Hall Institute of Medical Research17, University of Toronto18, Scripps Research Institute19, University of Alberta20, University of California, Los Angeles21, University College Dublin22, University of Michigan23, University of Pittsburgh24, University of Victoria25, University of Western Ontario26, Wistar Institute27, Yamaguchi University28, Yonsei University29, Agilent Technologies30, Applied Biosystems31, Waters Corporation32
TL;DR: Central analysis determined missed identifications, environmental contamination, database matching and curation of protein identifications as sources of problems in liquid chromatography–mass spectrometry–based proteomics.
Abstract: We performed a test sample study to try to identify errors leading to irreproducibility, including incompleteness of peptide sampling, in liquid chromatography-mass spectrometry-based proteomics. We distributed an equimolar test sample, comprising 20 highly purified recombinant human proteins, to 27 laboratories. Each protein contained one or more unique tryptic peptides of 1,250 Da to test for ion selection and sampling in the mass spectrometer. Of the 27 labs, members of only 7 labs initially reported all 20 proteins correctly, and members of only 1 lab reported all tryptic peptides of 1,250 Da. Centralized analysis of the raw data, however, revealed that all 20 proteins and most of the 1,250 Da peptides had been detected in all 27 labs. Our centralized analysis determined missed identifications (false negatives), environmental contamination, database matching and curation of protein identifications as sources of problems. Improved search engines and databases are needed for mass spectrometry-based proteomics.
TL;DR: A novel large multiprotein assembly, referred to as the striatin-interacting phosphatase and kinase (STRIPAK) complex, which contains the PP2A catalytic and scaffolding subunits, and members of the germinal center kinase III family of Ste20 kinases.
TL;DR: This study demonstrates that combining global gene expression analysis with detailed annotated pathway resources applied to highly enriched normal and malignant stem cell populations, can yield an understanding of the critical pathways regulating cancer stem cells.
Abstract: We performed the first genome-wide expression analysis directly comparing the expression profile of highly enriched normal human hematopoietic stem cells (HSC) and leukemic stem cells (LSC) from patients with acute myeloid leukemia (AML). Comparing the expression signature of normal HSC to that of LSC, we identified 3,005 differentially expressed genes. Using 2 independent analyses, we identified multiple pathways that are aberrantly regulated in leukemic stem cells compared with normal HSC. Several pathways, including Wnt signaling, MAP Kinase signaling, and Adherens Junction, are well known for their role in cancer development and stem cell biology. Other pathways have not been previously implicated in the regulation of cancer stem cell functions, including Ribosome and T Cell Receptor Signaling pathway. This study demonstrates that combining global gene expression analysis with detailed annotated pathway resources applied to highly enriched normal and malignant stem cell populations, can yield an understanding of the critical pathways regulating cancer stem cells.
TL;DR: This work mathematically modeled transcriptional regulation of the genes encoding interleukin 6 and C/EBPδ and experimentally confirmed the prediction that the combination of an initiate, an amplifier and an attenuator forms a regulatory circuit that discriminates between transient and persistent Toll-like receptor 4–induced signals.
Abstract: The innate immune system is like a double-edged sword: it is absolutely required for host defense against infection, but when uncontrolled, it can trigger a plethora of inflammatory diseases. Here we use systems-biology approaches to predict and confirm the existence of a gene-regulatory network involving dynamic interaction among the transcription factors NF-kappaB, C/EBPdelta and ATF3 that controls inflammatory responses. We mathematically modeled transcriptional regulation of the genes encoding interleukin 6 and C/EBPdelta and experimentally confirmed the prediction that the combination of an initiator (NF-kappaB), an amplifier (C/EBPdelta) and an attenuator (ATF3) forms a regulatory circuit that discriminates between transient and persistent Toll-like receptor 4-induced signals. Our results suggest a mechanism that enables the innate immune system to detect the duration of infection and to respond appropriately.
TL;DR: This work tracked global gene expression in the brains of eight distinct mouse strain–prion strain combinations throughout the progression of the disease to capture the effects of prion strain, host genetics, and PrP concentration on disease incubation time and suggests some possible therapeutic approaches.
Abstract: Prions cause transmissible neurodegenerative diseases and replicate by conformational conversion of normal benign forms of prion protein (PrPC) to disease-causing PrPSc isoforms. A systems approach to disease postulates that disease arises from perturbation of biological networks in the relevant organ. We tracked global gene expression in the brains of eight distinct mouse strain–prion strain combinations throughout the progression of the disease to capture the effects of prion strain, host genetics, and PrP concentration on disease incubation time. Subtractive analyses exploiting various aspects of prion biology and infection identified a core of 333 differentially expressed genes (DEGs) that appeared central to prion disease. DEGs were mapped into functional pathways and networks reflecting defined neuropathological events and PrPSc replication and accumulation, enabling the identification of novel modules and modules that may be involved in genetic effects on incubation time and in prion strain specificity. Our systems analysis provides a comprehensive basis for developing models for prion replication and disease, and suggests some possible therapeutic approaches.
TL;DR: It is found that the abundances of orthologous proteins in metazoans correlate remarkably well, better than protein abundance versus transcript abundance within each organism or transcript abundances across organisms; this suggests that changes in transcript abundance may have been partially offset during evolution by opposing changes in protein abundance.
Abstract: The nematode Caenorhabditis elegans is a popular model system in genetics, not least because a majority of human disease genes are conserved in C. elegans. To generate a comprehensive inventory of its expressed proteome, we performed extensive shotgun proteomics and identified more than half of all predicted C. elegans proteins. This allowed us to confirm and extend genome annotations, characterize the role of operons in C. elegans, and semiquantitatively infer abundance levels for thousands of proteins. Furthermore, for the first time to our knowledge, we were able to compare two animal proteomes (C. elegans and Drosophila melanogaster). We found that the abundances of orthologous proteins in metazoans correlate remarkably well, better than protein abundance versus transcript abundance within each organism or transcript abundances across organisms; this suggests that changes in transcript abundance may have been partially offset during evolution by opposing changes in protein abundance.
TL;DR: A method of computing P-values based on tail approximation, where the tail of the distribution of permutation values is approximated by a generalized Pareto distribution, and a good fit and thus accurate P-value estimates can be obtained with a drastically reduced number of permutations when compared with the standard empirical way of computingP-values.
Abstract: Motivation: Permutation tests have become a standard tool to assess the statistical significance of an event under investigation. The statistical significance, as expressed in a P-value, is calculated as the fraction of permutation values that are at least as extreme as the original statistic, which was derived from non-permuted data. This empirical method directly couples both the minimal obtainable P-value and the resolution of the P-value to the number of permutations. Thereby, it imposes upon itself the need for a very large number of permutations when small P-values are to be accurately estimated. This is computationally expensive and often infeasible.
Results: A method of computing P-values based on tail approximation is presented. The tail of the distribution of permutation values is approximated by a generalized Pareto distribution. A good fit and thus accurate P-value estimates can be obtained with a drastically reduced number of permutations when compared with the standard empirical way of computing P-values.
Availability: The Matlab code can be obtained from the corresponding author on request.
Contact: tknijnenburg@systemsbiology.org
Supplementary information: Supplementary data are available at Bioinformatics online.
TL;DR: A novel method, Lirnet, is presented that automatically learns a regulatory potential for each sequence polymorphism, estimating how likely it is to have a significant effect on gene expression, and produces significantly better regulatory programs than other recent approaches.
Abstract: Genome-wide RNA expression data provide a detailed view of an organism's biological state; hence, a dataset measuring expression variation between genetically diverse individuals (eQTL data) may provide important insights into the genetics of complex traits. However, with data from a relatively small number of individuals, it is difficult to distinguish true causal polymorphisms from the large number of possibilities. The problem is particularly challenging in populations with significant linkage disequilibrium, where traits are often linked to large chromosomal regions containing many genes. Here, we present a novel method, Lirnet, that automatically learns a regulatory potential for each sequence polymorphism, estimating how likely it is to have a significant effect on gene expression. This regulatory potential is defined in terms of “regulatory features”—including the function of the gene and the conservation, type, and position of genetic polymorphisms—that are available for any organism. The extent to which the different features influence the regulatory potential is learned automatically, making Lirnet readily applicable to different datasets, organisms, and feature sets. We apply Lirnet both to the human HapMap eQTL dataset and to a yeast eQTL dataset and provide statistical and biological results demonstrating that Lirnet produces significantly better regulatory programs than other recent approaches. We demonstrate in the yeast data that Lirnet can correctly suggest a specific causal sequence variation within a large, linked chromosomal region. In one example, Lirnet uncovered a novel, experimentally validated connection between Puf3—a sequence-specific RNA binding protein—and P-bodies—cytoplasmic structures that regulate translation and RNA stability—as well as the particular causative polymorphism, a SNP in Mkt1, that induces the variation in the pathway.
TL;DR: This chapter discusses what Cytoscape does, why it was developed, and the extensions numerous groups have made available to the public and describes the development of a plugin to investigate a particular research question in systems biology.
Abstract: Cytoscape is a general network visualization, data integration, and analysis software package. Its development and use has been focused on the modeling requirements of systems biology, though it has been used in other fields. Cytoscape's flexibility has encouraged many users to adopt it and adapt it to their own research by using the plugin framework offered to specialize data analysis, data integration, or visualization. Plugins represent collections of community-contributed functionality and can be used to dynamically extend Cytoscape functionality. This community of users and developers has worked together since Cytoscape's initial release to improve the basic project through contributions to the core code and public offerings of plugin modules. This chapter discusses what Cytoscape does, why it was developed, and the extensions numerous groups have made available to the public. It also describes the development of a plugin used to investigate a particular research question in systems biology and walks through an example analysis using Cytoscape.
TL;DR: It is demonstrated that calcineurin and NFAT are essential for neuregulin and ErbB signaling, neural crest diversification, and differentiation of Schwann cells.
Abstract: Schwann cells develop from multipotent neural crest cells and form myelin sheaths around axons that allow rapid transmission of action potentials. Neuregulin signaling through the ErbB receptor regulates Schwann cell development; however, the downstream pathways are not fully defined. We find that mice lacking calcineurin B1 in the neural crest have defects in Schwann cell differentiation and myelination. Neuregulin addition to Schwann cell precursors initiates an increase in cytoplasmic Ca2+, which activates calcineurin and the downstream transcription factors NFATc3 and c4. Purification of NFAT protein complexes shows that Sox10 is an NFAT nuclear partner and synergizes with NFATc4 to activate Krox20, which regulates genes necessary for myelination. Our studies demonstrate that calcineurin and NFAT are essential for neuregulin and ErbB signaling, neural crest diversification, and differentiation of Schwann cells.
TL;DR: It is found that Bur1 phosphorylates the Spt5 C-terminal repeat domain (CTD) both in vivo and in isolated elongation complexes in vitro.
Abstract: The Saccharomyces cerevisiae kinase Bur1 is involved in coupling transcription elongation to chromatin modification, but not all important Bur1 targets in the elongation complex are known. Using a chemical genetics strategy wherein Bur1 kinase was engineered to be regulated by a specific inhibitor, we found that Bur1 phosphorylates the Spt5 C-terminal repeat domain (CTD) both in vivo and in isolated elongation complexes in vitro. Deletion of the Spt5 CTD or mutation of the Spt5 serines targeted by Bur1 reduces recruitment of the PAF complex, which functions to recruit factors involved in chromatin modification and mRNA maturation to elongating polymerase II (Pol II). Deletion of the Spt5 CTD showed the same defect in PAF recruitment as rapid inhibition of Bur1 kinase activity, and this Spt5 mutation led to a decrease in histone H3K4 trimethylation. Brief inhibition of Bur1 kinase activity in vivo also led to a significant decrease in phosphorylation of the Pol II CTD at Ser-2, showing that Bur1 also contributes to Pol II Ser-2 phosphorylation. Genetic results suggest that Bur1 is essential for growth because it targets multiple factors that play distinct roles in transcription.
TL;DR: Evidence is presented that macrophages in vivo activated an innate immune response to a double-stranded DNA virus, adenovirus (Ad), independently of TLR9 or NLRP3 inflammasome, identifying IL-1 alpha-IL-1RI as a key pathway allowing for the activation of proinflammatory responses to the virus, independently of its genomic nucleic acid recognition.
TL;DR: These results provide the first evidence of associations of TLR5 and TLR1 variants with altered risks of acquiring rUTI and pyelonephritis, respectively.
Abstract: Background: Although behavioral risk factors are strongly associated with urinary tract infection (UTI) risk, the role of genetics in acquiring this disease is poorly understood. Methodology/Principal Findings: To test the hypothesis that polymorphisms in Toll-like receptor (TLR) pathway genes are associated with susceptibility to UTIs, we conducted a population-based case-control study of women ages 18–49 years. We examined DNA variants in 9 TLR pathway genes in 431 recurrent cystitis (rUTI) cases, 400 pyelonephritis cases, and 430 controls with no history of UTIs. In the Caucasian subgroup of 987 women, polymorphism TLR4_A896G was associated with protection from rUTI, but not pyelonephritis, with an odds ratio (OR) of 0.54 and a 95% confidence interval (CI) of 0.31 to 0.96. Polymorphism TLR5_C1174T, which encodes a variant that abrogates flagellin-induced signaling, was associated with an increased risk of rUTI (OR(95%CI): 1.81 (1.00–3.08)), but not pyelonephritis. Polymorphism TLR1_G1805T was associated with protection from pyelonephritis (OR(95%CI): 0.53 (0.29–0.96)). Conclusions: These results provide the first evidence of associations of TLR5 and TLR1 variants with altered risks of acquiring rUTI and pyelonephritis, respectively. Although these data suggest that TLR polymorphisms are associated with adult susceptibility to UTIs, the statistical significance was modest and will require further study including validation with independent cohorts.
TL;DR: A novel and simple approach is described to purify intact vacuoles formed by L. pneumophila within Dictyostelium discoideum by using magnetic immunoseparation with an antibody against SidC, followed by density gradient centrifugation to promote the recruitment of Legionella effectors by regulating the level of PtdIns(4)P.
Abstract: Legionella pneumophila, the causative agent of Legionnaires’ disease, replicates in macrophages and amoebae within ‘Legionella-containing vacuoles’ (LCVs), which communicate with the early secretory pathway and the endoplasmic reticulum Formation of LCVs requires the bacterial Icm/Dot type IV secretion system The Icm/Dot-translocated effector protein SidC selectively anchors to LCVs by binding the host lipid phosphatidylinositol-4-phosphate (PtdIns(4)P) Here, we describe a novel and simple approach to purify intact vacuoles formed by L pneumophila within Dictyostelium discoideum by using magnetic immunoseparation with an antibody against SidC, followed by density gradient centrifugation To monitor LCV purification by fluorescence microscopy, we used Dictyostelium producing the LCV marker calnexin-GFP and L pneumophila labeled with the red fluorescent protein DsRed A proteome analysis of purified LCVs by liquid chromatography coupled to tandem mass spectrometry revealed 566 host proteins, including known LCV components, such as the small GTPases Arf1, Rab1 and Rab7 Rab8, an endosomal regulator of the late secretory pathway originating from the trans Golgi network, and the endosomal GTPase Rab14 were identified as novel LCV components, which were found to be present on vacuoles harboring wild-type but not Icm/Dot-deficient L pneumophila Thus, LCVs also communicate with the late secretory and endosomal pathways Depletion of Rab8 or Arf1 by RNA interference reduced the amount of SidC on LCVs, indicating that the GTPases promote the recruitment of Legionella effectors by regulating the level of PtdIns(4)P
TL;DR: A high-throughput microfluidic imaging platform for single-cell studies of network response under hundreds of combined genetic perturbations and time-varying stimulant sequences and comprehensive analysis of 11 deletion mutants reveals both distinct thresholds for morphological switching and new dynamic phenotypes that are not observed in static conditions.
Abstract: Cells have evolved biomolecular networks that process and respond to changing chemical environments. Understanding how complex protein interactions give rise to emergent network properties requires time-resolved analysis of cellular response under a large number of genetic perturbations and chemical environments. To date, the lack of technologies for scalable cell analysis under well-controlled and time-varying conditions has made such global studies either impossible or impractical. To address this need, we have developed a high-throughput microfluidic imaging platform for single-cell studies of network response under hundreds of combined genetic perturbations and time-varying stimulant sequences. Our platform combines programmable on-chip mixing and perfusion with high-throughput image acquisition and processing to perform 256 simultaneous time-lapse live-cell imaging experiments. Nonadherent cells are captured in an array of 2,048 microfluidic cell traps to allow for the imaging of eight different genotypes over 12 h and in response to 32 unique sequences of stimulation, generating a total of 49,000 images per run. Using 12 devices, we carried out >3,000 live-cell imaging experiments to investigate the mating pheromone response in Saccharomyces cerevisiae under combined genetic perturbations and changing environmental conditions. Comprehensive analysis of 11 deletion mutants reveals both distinct thresholds for morphological switching and new dynamic phenotypes that are not observed in static conditions. For example, kss1Δ, fus3Δ, msg5Δ, and ptp2Δ mutants exhibit distinctive stimulus-frequency-dependent signaling phenotypes, implicating their role in filtering and network memory. The combination of parallel microfluidic control with high-throughput imaging provides a powerful tool for systems-level studies of single-cell decision making.
TL;DR: A new study reveals a functional rule for N-terminal acetylation in higher eukaryotes called the (X)PX rule and describes a generic method that prevents this modification to allow the study of N- terminal acetylations in any given protein.
Abstract: Protein modifications play a major role for most biological processes in living organisms. Amino-terminal acetylation of proteins is a common modification found throughout the tree of life: the N-terminus of a nascent polypeptide chain becomes co-translationally acetylated, often after the removal of the initiating methionine residue. While the enzymes and protein complexes involved in these processes have been extensively studied, only little is known about the biological function of such N-terminal modification events. To identify common principles of N-terminal acetylation, we analyzed the amino-terminal peptides from proteins extracted from Drosophila Kc167 cells. We detected more than 1,200 mature protein N-termini and could show that N-terminal acetylation occurs in insects with a similar frequency as in humans. As the sole true determinant for N-terminal acetylation we could extract the (X)PX rule that indicates the prevention of acetylation under all circumstances. We could show that this rule can be used to genetically engineer a protein to study the biological relevance of the presence or absence of an acetyl group, thereby generating a generic assay to probe the functional importance of N-terminal acetylation. We applied the assay by expressing mutated proteins as transgenes in cell lines and in flies. Here, we present a straightforward strategy to systematically study the functional relevance of N-terminal acetylations in cells and whole organisms. Since the (X)PX rule seems to be of general validity in lower as well as higher eukaryotes, we propose that it can be used to study the function of N-terminal acetylation in all species.
TL;DR: In this paper, the authors combined quantitative mass spectrometry and cryo-electron tomography to detect, count and localize specific protein complexes in the cytoplasm of the human pathogen Leptospira interrogans.
Abstract: Systems biology conceptualizes biological systems as dynamic networks of interacting elements, whereby functionally important properties are thought to emerge from the structure of such networks. Owing to the ubiquitous role of complexes of interacting proteins in biological systems, their subunit composition and temporal and spatial arrangement within the cell are of particular interest. 'Visual proteomics' attempts to localize individual macromolecular complexes inside of intact cells by template matching reference structures into cryo-electron tomograms. Here we combined quantitative mass spectrometry and cryo-electron tomography to detect, count and localize specific protein complexes in the cytoplasm of the human pathogen Leptospira interrogans. We describe a scoring function for visual proteomics and assess its performance and accuracy under realistic conditions. We discuss current and general limitations of the approach, as well as expected improvements in the future.
TL;DR: This review discusses innate immunity in the context of the systems biology concepts, emergence, robustness, and modularity, and describes emerging technologies the authors are applying in their systems‐level analyses.
Abstract: Systems biology is the comprehensive and quantitative analysis of the interactions between all of the components of biological systems over time. Systems biology involves an iterative cycle, in which emerging biological problems drive the development of new technologies and computational tools. These technologies and tools then open new frontiers that revolutionize biology. Innate immunity is well suited for systems analysis, because the relevant cells can be isolated in various functional states and their interactions can be reconstituted in a biologically meaningful manner. Application of the tools of systems biology to the innate immune system will enable comprehensive analysis of the complex interactions that maintain the difficult balance between host defense and inflammatory disease. In this review, we discuss innate immunity in the context of the systems biology concepts, emergence, robustness, and modularity, and we describe emerging technologies we are applying in our systems-level analyses. These technologies include genomics, proteomics, computational analysis, forward genetics screens, and analyses that link human genetic polymorphisms to disease resistance.