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Toll-Like Receptors

Overview of attention for book
Cover of 'Toll-Like Receptors'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Toll-Like Receptors: Ligands, Cell-Based Models, and Readouts for Receptor Action
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    Chapter 2 Bioinformatic Analysis of Toll-Like Receptor Sequences and Structures.
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    Chapter 3 Toll-Like Receptor Interactions Measured by Microscopic and Flow Cytometric FRET
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    Chapter 4 Using Confocal Microscopy to Investigate Intracellular Trafficking of Toll-Like Receptors
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    Chapter 5 Assessing the Inhibitory Activity of Oligonucleotides on TLR7 Sensing.
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    Chapter 6 Methods for Delivering DNA to Intracellular Receptors
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    Chapter 7 Detection of Interaction Between Toll-Like Receptors and Other Transmembrane Proteins by Co-immunoprecipitation Assay
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    Chapter 8 Flow Cytometry-Based Bead-Binding Assay for Measuring Receptor Ligand Specificity
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    Chapter 9 Measuring Monomer-to-Filament Transition of MAVS as an In Vitro Activity Assay for RIG-I-Like Receptors
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    Chapter 10 Co-transcriptomic Analysis by RNA Sequencing to Simultaneously Measure Regulated Gene Expression in Host and Bacterial Pathogen
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    Chapter 11 Simple Methods to Investigate MicroRNA Induction in Response to Toll-Like Receptors.
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    Chapter 12 Determining the Function of Long Noncoding RNA in Innate Immunity.
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    Chapter 13 Analysis of Post-transcriptional Gene Regulation of Nod-Like Receptors via the 3'UTR.
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    Chapter 14 TLR Function in Murine CD4+ T Lymphocytes and Their Role in Inflammation
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    Chapter 15 Analysis by Flow Cytometry of B-Cell Activation and Antibody Responses Induced by Toll-Like Receptors.
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    Chapter 16 Toll-Like Receptor-Dependent Immune Complex Activation of B Cells and Dendritic Cells.
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    Chapter 17 Analysis of TLR-Induced Metabolic Changes in Dendritic Cells Using the Seahorse XF(e)96 Extracellular Flux Analyzer.
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    Chapter 18 Toll-Like Receptor Signalling and the Control of Intestinal Barrier Function
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    Chapter 19 Understanding the Role of Cellular Molecular Clocks in Controlling the Innate Immune Response.
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    Chapter 20 Methods to Investigate the Role of Toll-Like Receptors in Allergic Contact Dermatitis
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    Chapter 21 Allergens and Activation of the Toll-Like Receptor Response.
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    Chapter 22 Investigating the Role of Toll-Like Receptors in Models of Arthritis
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    Chapter 23 Delineating the Role of Toll-Like Receptors in the Neuro-inflammation Model EAE.
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    Chapter 24 The Use of MiRNA Antagonists in the Alleviation of Inflammatory Disorders.
  26. Altmetric Badge
    Chapter 25 Investigating the Role of Toll-Like Receptors in Mouse Models of Gastric Cancer
Attention for Chapter 10: Co-transcriptomic Analysis by RNA Sequencing to Simultaneously Measure Regulated Gene Expression in Host and Bacterial Pathogen
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Chapter title
Co-transcriptomic Analysis by RNA Sequencing to Simultaneously Measure Regulated Gene Expression in Host and Bacterial Pathogen
Chapter number 10
Book title
Toll-Like Receptors
Published in
Methods in molecular biology, January 2016
DOI 10.1007/978-1-4939-3335-8_10
Pubmed ID
Book ISBNs
978-1-4939-3333-4, 978-1-4939-3335-8
Authors

Ravasi, Timothy, Mavromatis, Charalampos, Bokil, Nilesh J., Schembri, Mark A., Sweet, Matthew J., Timothy Ravasi, Charalampos (Harris) Mavromatis, Nilesh J. Bokil, Mark A. Schembri, Matthew J. Sweet

Abstract

Intramacrophage pathogens subvert antimicrobial defence pathways using various mechanisms, including the targeting of host TLR-mediated transcriptional responses. Conversely, TLR-inducible host defence mechanisms subject intramacrophage pathogens to stress, thus altering pathogen gene expression programs. Important biological insights can thus be gained through the analysis of gene expression changes in both the host and the pathogen during an infection. Traditionally, research methods have involved the use of qPCR, microarrays and/or RNA sequencing to identify transcriptional changes in either the host or the pathogen. Here we describe the application of RNA sequencing using samples obtained from in vitro infection assays to simultaneously quantify both host and bacterial pathogen gene expression changes, as well as general approaches that can be undertaken to interpret the RNA sequencing data that is generated. These methods can be used to provide insights into host TLR-regulated transcriptional responses to microbial challenge, as well as pathogen subversion mechanisms against such responses.

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X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Luxembourg 1 6%
Unknown 17 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 44%
Student > Bachelor 3 17%
Lecturer 1 6%
Student > Doctoral Student 1 6%
Student > Master 1 6%
Other 1 6%
Unknown 3 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 28%
Agricultural and Biological Sciences 4 22%
Immunology and Microbiology 3 17%
Environmental Science 2 11%
Unknown 4 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 January 2016.
All research outputs
#17,782,514
of 22,840,638 outputs
Outputs from Methods in molecular biology
#7,242
of 13,127 outputs
Outputs of similar age
#267,679
of 393,571 outputs
Outputs of similar age from Methods in molecular biology
#752
of 1,470 outputs
Altmetric has tracked 22,840,638 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,127 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 39th percentile – i.e., 39% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 393,571 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,470 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.