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      Dual RNA-seq of Orientia tsutsugamushi informs on host-pathogen interactions for this neglected intracellular human pathogen

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          Abstract

          Studying emerging or neglected pathogens is often challenging due to insufficient information and absence of genetic tools. Dual RNA-seq provides insights into host-pathogen interactions, and is particularly informative for intracellular organisms. Here we apply dual RNA-seq to Orientia tsutsugamushi (Ot), an obligate intracellular bacterium that causes the vector-borne human disease scrub typhus. Half the Ot genome is composed of repetitive DNA, and there is minimal collinearity in gene order between strains. Integrating RNA-seq, comparative genomics, proteomics, and machine learning to study the transcriptional architecture of Ot, we find evidence for wide-spread post-transcriptional antisense regulation. Comparing the host response to two clinical isolates, we identify distinct immune response networks for each strain, leading to predictions of relative virulence that are validated in a mouse infection model. Thus, dual RNA-seq can provide insight into the biology and host-pathogen interactions of a poorly characterized and genetically intractable organism such as Ot.

          Abstract

          Studying emerging pathogens is often challenging due to the lack of information. Here the authors show that dual RNA-seq, profiling the host and pathogen transcriptome simultaneously, helps uncovering the biology of Orientia tsutsugamushi, a major cause of febrile illness in South-East Asia, and its interaction with the host.

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          Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

          The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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            edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

            Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au
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              Cutadapt removes adapter sequences from high-throughput sequencing reads

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                Author and article information

                Contributors
                lars.barquist@helmholtz-hiri.de
                js2522@njms.rutgers.edu
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                3 July 2020
                3 July 2020
                2020
                : 11
                : 3363
                Affiliations
                [1 ]GRID grid.498164.6, Helmholtz Institute for RNA-based Infection Research (HIRI), Helmholtz Centre for Infection Research (HZI), ; Würzburg, Germany
                [2 ]ISNI 0000 0004 5936 4917, GRID grid.501272.3, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, ; Bangkok, Thailand
                [3 ]ISNI 0000 0001 1958 8658, GRID grid.8379.5, Institute for Molecular Infection Biology (IMIB), University of Würzburg, ; Würzburg, Germany
                [4 ]ISNI 0000 0004 1936 8796, GRID grid.430387.b, Rutgers, the State Univeristy of New Jersey, ; New Jersey, NJ USA
                [5 ]ISNI 0000 0004 0620 9243, GRID grid.418812.6, Functional Proteomics Laboratory, Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), ; Singapore, Singapore
                [6 ]ISNI 0000 0004 0620 9243, GRID grid.418812.6, SingMass - National Mass Spectrometry Laboratory, Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), ; Singapore, Singapore
                [7 ]ISNI 0000 0004 0419 1772, GRID grid.413910.e, Armed Forces Research Institute of Medical Sciences, ; Bangkok, Thailand
                [8 ]ISNI 0000 0004 1936 8796, GRID grid.430387.b, Public Health Research Institute, Rutgers University, ; New Jersey, NJ USA
                [9 ]ISNI 0000 0001 1958 8658, GRID grid.8379.5, Faculty of Medicine, University of Würzburg, ; Würzburg, Germany
                [10 ]ISNI 0000 0004 1936 8948, GRID grid.4991.5, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, ; Oxford, UK
                Author information
                http://orcid.org/0000-0003-1014-4609
                http://orcid.org/0000-0002-7020-1129
                http://orcid.org/0000-0002-8054-6673
                http://orcid.org/0000-0002-2455-2526
                http://orcid.org/0000-0003-2220-1404
                http://orcid.org/0000-0003-4732-2667
                http://orcid.org/0000-0001-5802-4580
                Article
                17094
                10.1038/s41467-020-17094-8
                7335160
                32620750
                7f990b8a-e3ad-458f-a397-85e307a596e5
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 1 November 2019
                : 11 June 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100000288, Royal Society;
                Award ID: DH140154
                Award Recipient :
                Funded by: University of Oxford Medical Sciences Division Medical Research Fund
                Categories
                Article
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                © The Author(s) 2020

                Uncategorized
                rna sequencing,antimicrobial responses,bacterial host response,cellular microbiology

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