Literature DB >> 27442864

A highly multiplexed and sensitive RNA-seq protocol for simultaneous analysis of host and pathogen transcriptomes.

Roi Avraham1, Nathan Haseley1, Amy Fan1, Zohar Bloom-Ackermann1, Jonathan Livny1,2, Deborah T Hung1,3,4,5.   

Abstract

The ability to simultaneously characterize the bacterial and host expression programs during infection would facilitate a comprehensive understanding of pathogen-host interactions. Although RNA sequencing (RNA-seq) has greatly advanced our ability to study the transcriptomes of prokaryotes and eukaryotes separately, limitations in existing protocols for the generation and analysis of RNA-seq data have hindered simultaneous profiling of host and bacterial pathogen transcripts from the same sample. Here we provide a detailed protocol for simultaneous analysis of host and bacterial transcripts by RNA-seq. Importantly, this protocol details the steps required for efficient host and bacteria lysis, barcoding of samples, technical advances in sample preparation for low-yield sample inputs and a computational pipeline for analysis of both mammalian and microbial reads from mixed host-pathogen RNA-seq data. Sample preparation takes 3 d from cultured cells to pooled libraries. Data analysis takes an additional day. Compared with previous methods, the protocol detailed here provides a sensitive, facile and generalizable approach that is suitable for large-scale studies and will enable the field to obtain in-depth analysis of host-pathogen interactions in infection models.

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Year:  2016        PMID: 27442864     DOI: 10.1038/nprot.2016.090

Source DB:  PubMed          Journal:  Nat Protoc        ISSN: 1750-2799            Impact factor:   13.491


  30 in total

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Journal:  Nucleic Acids Res       Date:  2000-01-01       Impact factor: 16.971

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Authors:  Ruslan Medzhitov
Journal:  Semin Immunol       Date:  2007-02       Impact factor: 11.130

3.  Normalization of RNA-seq data using factor analysis of control genes or samples.

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4.  Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.

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Journal:  Proc Natl Acad Sci U S A       Date:  2005-09-30       Impact factor: 11.205

5.  Pathogen Cell-to-Cell Variability Drives Heterogeneity in Host Immune Responses.

Authors:  Roi Avraham; Nathan Haseley; Douglas Brown; Cristina Penaranda; Humberto B Jijon; John J Trombetta; Rahul Satija; Alex K Shalek; Ramnik J Xavier; Aviv Regev; Deborah T Hung
Journal:  Cell       Date:  2015-09-03       Impact factor: 41.582

6.  An interferon-inducible neutrophil-driven blood transcriptional signature in human tuberculosis.

Authors:  Matthew P R Berry; Christine M Graham; Finlay W McNab; Zhaohui Xu; Susannah A A Bloch; Tolu Oni; Katalin A Wilkinson; Romain Banchereau; Jason Skinner; Robert J Wilkinson; Charles Quinn; Derek Blankenship; Ranju Dhawan; John J Cush; Asuncion Mejias; Octavio Ramilo; Onn M Kon; Virginia Pascual; Jacques Banchereau; Damien Chaussabel; Anne O'Garra
Journal:  Nature       Date:  2010-08-19       Impact factor: 49.962

7.  How deep is deep enough for RNA-Seq profiling of bacterial transcriptomes?

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Journal:  BMC Genomics       Date:  2012-12-27       Impact factor: 3.969

8.  An Interspecies Regulatory Network Inferred from Simultaneous RNA-seq of Candida albicans Invading Innate Immune Cells.

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10.  Simultaneous transcriptional profiling of bacteria and their host cells.

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Journal:  PLoS One       Date:  2013-12-04       Impact factor: 3.240

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  13 in total

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2.  Bioinformatic analysis of bacteria and host cell dual RNA-sequencing experiments.

Authors:  James W Marsh; Regan J Hayward; Amol C Shetty; Anup Mahurkar; Michael S Humphrys; Garry S A Myers
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3.  A Common Genetic Variation in Langerin (CD207) Compromises Cellular Uptake of Staphylococcus aureus.

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4.  Resolving the Microalgal Gene Landscape at the Strain Level: a Novel Hybrid Transcriptome of Emiliania huxleyi CCMP3266.

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5.  Collection and Processing of Lymph Nodes from Large Animals for RNA Analysis: Preparing for Lymph Node Transcriptomic Studies of Large Animal Species.

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Review 6.  Resolving host-pathogen interactions by dual RNA-seq.

Authors:  Alexander J Westermann; Lars Barquist; Jörg Vogel
Journal:  PLoS Pathog       Date:  2017-02-16       Impact factor: 6.823

7.  Metaproteomics reveals potential mechanisms by which dietary resistant starch supplementation attenuates chronic kidney disease progression in rats.

Authors:  Boris L Zybailov; Galina V Glazko; Yasir Rahmatallah; Dmitri S Andreyev; Taylor McElroy; Oleg Karaduta; Stephanie D Byrum; Lisa Orr; Alan J Tackett; Samuel G Mackintosh; Ricky D Edmondson; Dorothy A Kieffer; R J Martin; Sean H Adams; Nosratola D Vaziri; John M Arthur
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8.  Path-seq identifies an essential mycolate remodeling program for mycobacterial host adaptation.

Authors:  Eliza Jr Peterson; Rebeca Bailo; Alissa C Rothchild; Mario L Arrieta-Ortiz; Amardeep Kaur; Min Pan; Dat Mai; Abrar A Abidi; Charlotte Cooper; Alan Aderem; Apoorva Bhatt; Nitin S Baliga
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Review 9.  Clinical metagenomics.

Authors:  Charles Y Chiu; Steven A Miller
Journal:  Nat Rev Genet       Date:  2019-06       Impact factor: 53.242

Review 10.  Transcriptomic Studies of Malaria: a Paradigm for Investigation of Systemic Host-Pathogen Interactions.

Authors:  Hyun Jae Lee; Athina Georgiadou; Thomas D Otto; Michael Levin; Lachlan J Coin; David J Conway; Aubrey J Cunnington
Journal:  Microbiol Mol Biol Rev       Date:  2018-04-25       Impact factor: 11.056

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