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      Species-Specific Endotoxin Stimulus Determines Toll-Like Receptor 4- and Caspase 11-Mediated Pathway Activation Characteristics

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          ABSTRACT

          The innate immune system is the body’s first line of defense against pathogens and its protection against infectious diseases. On the surface of host myeloid cells, Toll-like receptor 4 (TLR4) senses lipopolysaccharide (LPS), the major outer membrane component of Gram-negative bacteria. Intracellularly, LPS is recognized by caspase 11 through the noncanonical inflammasome to induce pyroptosis—an inflammatory form of lytic cell death. While TLR4-mediated signaling perturbations result in secretion of cytokines and chemokines that help clear infection and facilitate adaptive immunity, caspase 11-mediated pyroptosis leads to the release of damage-associated molecular patterns and inflammatory mediators. Although the core signaling events and many associated proteins in the TLR4 signaling pathway are known, the complex signaling events and protein networks within the noncanonical inflammasome pathway remain obscure. Moreover, there is mounting evidence for pathogen-specific innate immune tuning. We characterized the major LPS structures from two different pathogens, modeled their binding to the surface receptors, systematically examined macrophage inflammatory responses to these LPS molecules, and surveyed the temporal differences in global protein secretion resulting from TLR4 and caspase 11 activation in macrophages using mass spectrometry (MS)-based quantitative proteomics. This integrated strategy, spanning functional activity assays, top-down structural elucidation of endotoxins, and secretome analysis of stimulated macrophages, allowed us to identify crucial differences in TLR4- and caspase 11-mediated protein secretion in response to two Gram-negative bacterial endotoxins.

          IMPORTANCE Macrophages and monocytes are innate immune cells playing an important role in orchestrating the initial innate immune response to bacterial infection and the tissue damage. This response is facilitated by specific receptors on the cell surface and intracellularly. One of the bacterial molecules recognized is a Gram-negative bacteria cell wall component, lipopolysaccharide (LPS). The structure of LPS differs between different species. We have characterized the innate immune responses to the LPS molecules from two bacteria, Escherichia coli and Bordetella pertussis, administered either extracellularly or intracellularly, whose structures we first determined. We observed marked differences in the temporal dynamics and amounts of proteins secreted by the innate immune cells stimulated by any of these molecules and routes. This suggests that there is specificity in the first line of response to different Gram-negative bacteria that can be explored to tailor specific therapeutic interventions.

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          The PRIDE database and related tools and resources in 2019: improving support for quantification data

          Abstract The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.uk/pride/) is the world’s largest data repository of mass spectrometry-based proteomics data, and is one of the founding members of the global ProteomeXchange (PX) consortium. In this manuscript, we summarize the developments in PRIDE resources and related tools since the previous update manuscript was published in Nucleic Acids Research in 2016. In the last 3 years, public data sharing through PRIDE (as part of PX) has definitely become the norm in the field. In parallel, data re-use of public proteomics data has increased enormously, with multiple applications. We first describe the new architecture of PRIDE Archive, the archival component of PRIDE. PRIDE Archive and the related data submission framework have been further developed to support the increase in submitted data volumes and additional data types. A new scalable and fault tolerant storage backend, Application Programming Interface and web interface have been implemented, as a part of an ongoing process. Additionally, we emphasize the improved support for quantitative proteomics data through the mzTab format. At last, we outline key statistics on the current data contents and volume of downloads, and how PRIDE data are starting to be disseminated to added-value resources including Ensembl, UniProt and Expression Atlas.
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            MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.

            Efficient analysis of very large amounts of raw data for peptide identification and protein quantification is a principal challenge in mass spectrometry (MS)-based proteomics. Here we describe MaxQuant, an integrated suite of algorithms specifically developed for high-resolution, quantitative MS data. Using correlation analysis and graph theory, MaxQuant detects peaks, isotope clusters and stable amino acid isotope-labeled (SILAC) peptide pairs as three-dimensional objects in m/z, elution time and signal intensity space. By integrating multiple mass measurements and correcting for linear and nonlinear mass offsets, we achieve mass accuracy in the p.p.b. range, a sixfold increase over standard techniques. We increase the proportion of identified fragmentation spectra to 73% for SILAC peptide pairs via unambiguous assignment of isotope and missed-cleavage state and individual mass precision. MaxQuant automatically quantifies several hundred thousand peptides per SILAC-proteome experiment and allows statistically robust identification and quantification of >4,000 proteins in mammalian cell lysates.
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              The Perseus computational platform for comprehensive analysis of (prote)omics data.

              A main bottleneck in proteomics is the downstream biological analysis of highly multivariate quantitative protein abundance data generated using mass-spectrometry-based analysis. We developed the Perseus software platform (http://www.perseus-framework.org) to support biological and biomedical researchers in interpreting protein quantification, interaction and post-translational modification data. Perseus contains a comprehensive portfolio of statistical tools for high-dimensional omics data analysis covering normalization, pattern recognition, time-series analysis, cross-omics comparisons and multiple-hypothesis testing. A machine learning module supports the classification and validation of patient groups for diagnosis and prognosis, and it also detects predictive protein signatures. Central to Perseus is a user-friendly, interactive workflow environment that provides complete documentation of computational methods used in a publication. All activities in Perseus are realized as plugins, and users can extend the software by programming their own, which can be shared through a plugin store. We anticipate that Perseus's arsenal of algorithms and its intuitive usability will empower interdisciplinary analysis of complex large data sets.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                mSystems
                mSystems
                msystems
                mSystems
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                2379-5077
                3 August 2021
                Jul-Aug 2021
                3 August 2021
                : 6
                : 4
                Affiliations
                [a ] Signaling Systems Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA
                [b ] Functional Cellular Networks Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA
                [c ] School of Medicine, University of Maryland, Baltimore, Maryland, USA
                [d ] Computer-Aided Drug Design Center, Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, Baltimore, Maryland, USA
                [e ] Department of Microbial Pathogenesis, School of Dentistry, University of Maryland, Baltimore, Maryland, USA
                Princeton University
                Author notes
                [*]

                Present address: Mohd M. Khan, Deloitte Consulting LLP, Arlington, Virginia, USA; Benjamin L. Oyler, Tissue Analysis Core, Immunology Laboratory, Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Gaithersburg, Maryland, USA, and University of Victoria, Genome British Columbia Proteomics Centre, Victoria, British Columbia, Canada; David R. Goodlett, Department of Biochemistry and Microbiology, University of Victoria, Victoria, British Columbia, Canada, and University of Gdańsk, International Centre for Cancer Vaccine Science, Gdańsk, Poland.

                Orna Ernst and Mohd M. Khan contributed equally. Author order was determined alphabetically.

                Citation Ernst O, Khan MM, Oyler BL, Yoon SH, Sun J, Lin F-Y, Manes NP, MacKerell AD, Jr, Fraser IDC, Ernst RK, Goodlett DR, Nita-Lazar A. 2021. Species-specific endotoxin stimulus determines Toll-like receptor 4- and caspase 11-mediated pathway activation characteristics. mSystems 6:e00306-21. https://doi.org/10.1128/mSystems.00306-21.

                Article
                mSystems00306-21
                10.1128/mSystems.00306-21
                8407122
                34342534
                c2ab287b-957b-48da-9b3a-0da5fe493dab

                This is a work of the U.S. Government and is not subject to copyright protection in the United States. Foreign copyrights may apply.

                Page count
                supplementary-material: 10, Figures: 7, Tables: 2, Equations: 0, References: 79, Pages: 19, Words: 12994
                Product
                Funding
                Funded by: International Research Agenda's Program for the Foundation of Polish Science;
                Award ID: MAB/2017/03
                Award Recipient :
                Funded by: American Association of Pharmaceutical Scientists (AAPS), FundRef https://doi.org/10.13039/100005296;
                Award Recipient :
                Funded by: Division of Intramural Research, National Institute of Allergy and Infectious Diseases (DIR, NIAID), FundRef https://doi.org/10.13039/100006492;
                Award Recipient : Award Recipient : Award Recipient : Award Recipient : Award Recipient : Award Recipient :
                Funded by: Genome Canada (Génome Canada), FundRef https://doi.org/10.13039/100008762;
                Award ID: 264PRO
                Award Recipient :
                Funded by: HHS | NIH | National Institute of Allergy and Infectious Diseases (NIAID), FundRef https://doi.org/10.13039/100000060;
                Award ID: 1R01AI123820-01
                Award Recipient : Award Recipient : Award Recipient : Award Recipient : Award Recipient : Award Recipient :
                Categories
                Research Article
                Custom metadata
                July/August 2021

                infection,lipopolysaccharide,toll-like receptors,caspase 11,site identification by ligand competitive saturation,silcs,caspases,cytokines,host response,host-pathogen interactions,inflammasome,innate immunity,macrophages,proteomics,secretome

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