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      Protein markers for Candida albicans EVs include claudin-like Sur7 family proteins

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          ABSTRACT

          Background: Fungal extracellular vesicles (EVs) have been implicated in host-pathogen and pathogen-pathogen communication in some fungal diseases. In depth research into fungal EVs has been hindered by the lack of specific protein markers such as those found in mammalian EVs that have enabled sophisticated isolation and analysis techniques. Despite their role in fungal EV biogenesis, ESCRT proteins such as Vps23 (Tsg101) and Bro1 (ALIX) are not present as fungal EV cargo. Furthermore, tetraspanin homologs are yet to be identified in many fungi including the model yeast S. cerevisiae.

          Objective: We performed de novo identification of EV protein markers for the major human fungal pathogen Candida albicans with adherence to MISEV2018 guidelines.

          Materials and methods: EVs were isolated by differential ultracentrifugation from DAY286, ATCC90028 and ATCC10231 yeast cells, as well as DAY286 biofilms. Whole cell lysates (WCL) were also obtained from the EV-releasing cells. Label-free quantitative proteomics was performed to determine the set of proteins consistently enriched in EVs compared to WCL.

          Results: 47 proteins were consistently enriched in C. albicans EVs. We refined these to 22 putative C. albicans EV protein markers including the claudin-like Sur7 family (Pfam: PF06687) proteins Sur7 and Evp1 (orf19.6741). A complementary set of 62 EV depleted proteins was selected as potential negative markers.

          Conclusions: The marker proteins for C. albicans EVs identified in this study will be useful tools for studies on EV biogenesis and cargo loading in C. albicans and potentially other fungal species and will also assist in elucidating the role of EVs in C. albicans pathogenesis. Many of the proteins identified as putative markers are fungal specific proteins indicating that the pathways of EV biogenesis and cargo loading may be specific to fungi, and that assumptions made based on studies in mammalian cells could be misleading.

          Abbreviations: A1 – ATCC10231; A9 – ATCC90028; DAY B – DAY286 biofilm; DAY Y – DAY286 yeast; EV – extracellular vesicle; Evp1 – extracellular vesicle protein 1 (orf19.6741); GO – gene ontology; Log 2(FC) – log 2(fold change); MCC – membrane compartment of Can1; MDS – multidimensional scaling; MISEV – minimal information for studies of EVs; sEVs – small EVs; SP – signal peptide; TEMs – tetraspanin enriched microdomains; TM – transmembrane; VDM – vesicle-depleted medium; WCL – whole cell lysate

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          Most cited references72

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Exosome secretion: molecular mechanisms and roles in immune responses.

            Exosomes are small membrane vesicles, secreted by most cell types from multivesicular endosomes, and thought to play important roles in intercellular communications. Initially described in 1983, as specifically secreted by reticulocytes, exosomes became of interest for immunologists in 1996, when they were proposed to play a role in antigen presentation. More recently, the finding that exosomes carry genetic materials, mRNA and miRNA, has been a major breakthrough in the field, unveiling their capacity to vehicle genetic messages. It is now clear that not only immune cells but probably all cell types are able to secrete exosomes: their range of possible functions expands well beyond immunology to neurobiology, stem cell and tumor biology, and their use in clinical applications as biomarkers or as therapeutic tools is an extensive area of research. Despite intensive efforts to understand their functions, two issues remain to be solved in the future: (i) what are the physiological function(s) of exosomes in vivo and (ii) what are the relative contributions of exosomes and of other secreted membrane vesicles in these proposed functions? Here, we will focus on the current ideas on exosomes and immune responses, but also on their mechanisms of secretion and the use of this knowledge to elucidate the latter issue. © 2011 John Wiley & Sons A/S.
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              Robust hyperparameter estimation protects against hypervariable genes and improves power to detect differential expression

              One of the most common analysis tasks in genomic research is to identify genes that are differentially expressed (DE) between experimental conditions. Empirical Bayes (EB) statistical tests using moderated genewise variances have been very effective for this purpose, especially when the number of biological replicate samples is small. The EB procedures can however be heavily influenced by a small number of genes with very large or very small variances. This article improves the differential expression tests by robustifying the hyperparameter estimation procedure. The robust procedure has the effect of decreasing the informativeness of the prior distribution for outlier genes while increasing its informativeness for other genes. This effect has the double benefit of reducing the chance that hypervariable genes will be spuriously identified as DE while increasing statistical power for the main body of genes. The robust EB algorithm is fast and numerically stable. The procedure allows exact small-sample null distributions for the test statistics and reduces exactly to the original EB procedure when no outlier genes are present. Simulations show that the robustified tests have similar performance to the original tests in the absence of outlier genes but have greater power and robustness when outliers are present. The article includes case studies for which the robust method correctly identifies and downweights genes associated with hidden covariates and detects more genes likely to be scientifically relevant to the experimental conditions. The new procedure is implemented in the limma software package freely available from the Bioconductor repository.
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                Author and article information

                Journal
                J Extracell Vesicles
                J Extracell Vesicles
                ZJEV
                zjev20
                Journal of Extracellular Vesicles
                Taylor & Francis
                2001-3078
                2020
                16 April 2020
                : 9
                : 1
                : 1750810
                Affiliations
                [a ]Department of Biochemistry and Genetics, La Trobe Institute for Molecular Science. La Trobe University , Australia
                [b ]Department of Biochemistry, Cambridge Centre for Proteomics, Milner Therapeutics Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge , Cambridge, UK
                [c ]La Trobe Comprehensive Proteomics Platform, La Trobe Institute for Molecular Science. La Trobe University , Australia
                Author notes
                CONTACT Marilyn A Anderson m.anderson@ 123456latrobe.edu.au La Trobe Institute for Molecular Science, La Trobe University , 3086 Bundoora, Victoria, Australia
                [$]

                These authors contributed equally to this work

                Author information
                http://orcid.org/0000-0002-7151-5971
                http://orcid.org/0000-0003-4718-4233
                http://orcid.org/0000-0001-7521-0991
                http://orcid.org/0000-0002-3755-7502
                http://orcid.org/0000-0002-9717-7560
                http://orcid.org/0000-0002-8257-5128
                Article
                1750810
                10.1080/20013078.2020.1750810
                7178836
                32363014
                452c1b1a-3ce3-4edd-8d0a-a5c65dd0729e
                © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of The International Society for Extracellular Vesicles.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 18 July 2019
                : 24 March 2020
                : 27 March 2020
                Page count
                Figures: 8, Tables: 1, References: 120, Pages: 21
                Funding
                Funded by: Australian Research Council Discovery 10.13039/501100000923
                Award ID: DP160100309
                Funded by: Australian Research Council 10.13039/501100000923
                Award ID: DP160100309
                This work was supported by a grant awarded to MAA; Australian Research Council [DP160100309].
                Categories
                Research Article

                candida albicans,extracellular vesicles,proteomics,markers,pathogen,fungi

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