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      Proximity-Dependent Biotinylation and Identification of Flagellar Proteins in Trypanosoma cruzi

      research-article
      a , b , a ,
      mSphere
      American Society for Microbiology
      Trypanosoma cruzi, TurboID, amastigote, flagellum, proteomics, proximity labeling

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          ABSTRACT

          The flagellated kinetoplastid protozoan and causative agent of human Chagas disease, Trypanosoma cruzi, inhabits both invertebrate and mammalian hosts over the course of its complex life cycle. In these disparate environments, T. cruzi uses its single flagellum to propel motile life stages and, in some instances, to establish intimate contact with the host. Beyond its role in motility, the functional capabilities of the T. cruzi flagellum have not been defined. Moreover, the lack of proteomic information for this organelle, in any parasite life stage, has limited functional investigation. In this study, we employed a proximity-dependent biotinylation approach based on the differential targeting of the biotin ligase TurboID to the flagellum or cytosol in replicative stages of T. cruzi to identify proteins that are enriched in the flagellum by mass spectrometry. Proteomic analysis of the resulting biotinylated protein fractions yielded 218 candidate flagellar proteins in T. cruzi epimastigotes (insect stage) and 99 proteins in intracellular amastigotes (mammalian stage). Forty of these enriched flagellar proteins were common to both parasite life stages and included orthologs of known flagellar proteins in other trypanosomatid species, proteins specific to the T. cruzi lineage and hypothetical proteins. With the validation of flagellar localization for several of the identified candidates, our results demonstrate that TurboID-based proximity proteomics is an effective tool for probing subcellular compartments in T. cruzi. The proteomic data sets generated in this work offer a valuable resource to facilitate functional investigation of the understudied T. cruzi flagellum.

          IMPORTANCE Trypanosoma cruzi is a protozoan parasite that causes Chagas disease, which causes substantial morbidity and mortality in South and Central America. Throughout its life cycle, T. cruzi interacts with insect and mammalian hosts via its single flagellum, establishing intimate contact with host membranes. Currently, few flagellar proteins have been identified in T. cruzi that could provide insight into the mechanisms involved in mediating physical and biochemical interactions with the host. Here, we set out to identify flagellar proteins in the main replicative stages of T. cruzi using a proximity-labeling approach coupled with mass spectrometry. The >200 candidate flagellar proteins identified represent the first large-scale identification of candidate flagellar proteins in T. cruzi with preliminary validation. These data offer new avenues to investigate the biology of T. cruzi-host interactions, a promising area for development of new strategies aimed at the control of this pathogen.

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          Most cited references65

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          Fiji: an open-source platform for biological-image analysis.

          Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
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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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              Andromeda: a peptide search engine integrated into the MaxQuant environment.

              A key step in mass spectrometry (MS)-based proteomics is the identification of peptides in sequence databases by their fragmentation spectra. Here we describe Andromeda, a novel peptide search engine using a probabilistic scoring model. On proteome data, Andromeda performs as well as Mascot, a widely used commercial search engine, as judged by sensitivity and specificity analysis based on target decoy searches. Furthermore, it can handle data with arbitrarily high fragment mass accuracy, is able to assign and score complex patterns of post-translational modifications, such as highly phosphorylated peptides, and accommodates extremely large databases. The algorithms of Andromeda are provided. Andromeda can function independently or as an integrated search engine of the widely used MaxQuant computational proteomics platform and both are freely available at www.maxquant.org. The combination enables analysis of large data sets in a simple analysis workflow on a desktop computer. For searching individual spectra Andromeda is also accessible via a web server. We demonstrate the flexibility of the system by implementing the capability to identify cofragmented peptides, significantly improving the total number of identified peptides.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                mSphere
                mSphere
                msphere
                mSphere
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                2379-5042
                5 April 2023
                May-Jun 2023
                5 April 2023
                : 8
                : 3
                : e00088-23
                Affiliations
                [a ] Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA
                [b ] Harvard Chan Advanced Multi-omics Platform, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA
                University at Buffalo
                Author notes

                The authors declare no conflict of interest.

                Author information
                https://orcid.org/0000-0003-4268-2006
                https://orcid.org/0000-0002-3642-7247
                Article
                00088-23 msphere.00088-23
                10.1128/msphere.00088-23
                10286712
                37017578
                5c420a5a-8086-4281-ae47-c2de82862683
                Copyright © 2023 Won et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 15 February 2023
                : 21 March 2023
                Page count
                supplementary-material: 7, Figures: 4, Tables: 1, Equations: 0, References: 65, Pages: 14, Words: 10352
                Funding
                Funded by: HHS | NIH | National Institute of Allergy and Infectious Diseases (NIAID), FundRef https://doi.org/10.13039/100000060;
                Award ID: R21AI135520
                Award Recipient :
                Funded by: HHS | NIH | National Institute of Allergy and Infectious Diseases (NIAID), FundRef https://doi.org/10.13039/100000060;
                Award ID: 5T32AI049928
                Award Recipient :
                Categories
                Research Article
                molecular-and-cellular-biology, Molecular and Cellular Biology
                Custom metadata
                May/June 2023

                trypanosoma cruzi,turboid,amastigote,flagellum,proteomics,proximity labeling

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