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Host-Pathogen Interactions

Overview of attention for book
Cover of 'Host-Pathogen Interactions'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Genetic Association Studies in Host–Pathogen Interaction Analysis
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    Chapter 2 Bacterial Genotyping Methods: From the Basics to Modern
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    Chapter 3 Real-Time Reverse Transcription PCR as a Tool to Study Virulence Gene Regulation in Bacterial Pathogens
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    Chapter 4 Usage of a Bioluminescence Reporter System to Image Promoter Activity During Host Infection
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    Chapter 5 lacZ Reporter System as a Tool to Study Virulence Gene Regulation in Bacterial Pathogens
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    Chapter 6 Western Blotting Against Tagged Virulence Determinants to Study Bacterial Pathogenicity
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    Chapter 7 Molecular Methods to Analyze the Effect of Proteins Expressed by Salmonella During Its Intracellular Stage
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    Chapter 8 Organoids as a Model to Study Infectious Disease
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    Chapter 9 Surface Proteome Biotinylation Combined with Bioinformatic Tools as a Strategy for Predicting Pathogen Interacting Proteins
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    Chapter 10 Systems Biology Modeling to Study Pathogen–Host Interactions
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    Chapter 11 Phage Therapy: Various Perspectives on How to Improve the Art
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    Chapter 12 Application of RNA-seq and Bioimaging Methods to Study Microbe–Microbe Interactions and Their Effects on Biofilm Formation and Gene Expression
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    Chapter 13 Serial Dilution-Based Growth Curves and Growth Curve Synchronization for High-Resolution Time Series of Bacterial Biofilm Growth
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    Chapter 14 Detection of Bacterial Quorum Sensing Molecules
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    Chapter 15 Generating Chromosome-Located Transcriptional Fusions to Fluorescent Proteins for Single-Cell Gene Expression Analysis in Pseudomonas syringae
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    Chapter 16 Introduction of Genetic Material in Ralstonia solanacearum Through Natural Transformation and Conjugation
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    Chapter 17 In Vitro and In Vivo Secretion/Translocation Assays to Identify Novel Ralstonia solanacearum Type 3 Effectors
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    Chapter 18 Plant Pathogenicity Phenotyping of Ralstonia solanacearum Strains
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    Chapter 19 Methods to Quantify Biotic-Induced Stress in Plants
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    Chapter 20 From Sample to Data: Preparing, Obtaining, and Analyzing Images of Plant-Pathogen Interactions Using Confocal Microscopy
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    Chapter 21 Screening of c-di-GMP-Regulated Exopolysaccharides in Host Interacting Bacteria
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    Chapter 22 Primary Characterization of Small RNAs in Symbiotic Nitrogen-Fixing Bacteria
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    Chapter 23 A New, Nondestructive, Split-Root System for Local and Systemic Plant Responses Studies with Soybean
  25. Altmetric Badge
    Chapter 24 Methods for the Characterization of Plant-Growth Promoting Rhizobacteria
Attention for Chapter 15: Generating Chromosome-Located Transcriptional Fusions to Fluorescent Proteins for Single-Cell Gene Expression Analysis in Pseudomonas syringae
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age and source (51st percentile)

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Chapter title
Generating Chromosome-Located Transcriptional Fusions to Fluorescent Proteins for Single-Cell Gene Expression Analysis in Pseudomonas syringae
Chapter number 15
Book title
Host-Pathogen Interactions
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7604-1_15
Pubmed ID
Book ISBNs
978-1-4939-7603-4, 978-1-4939-7604-1
Authors

José S. Rufián, Diego López-Márquez, Nieves López-Pagán, Murray Grant, Javier Ruiz-Albert, Carmen R. Beuzón

Abstract

The last decade has seen significant effort directed toward the role of phenotypic heterogeneity in bacterial adaptation. Phenotypic heterogeneity usually refers to phenotypic diversity that takes place through nongenetic means, independently of environmental induced variation. Recent findings are changing how microbiologists analyze bacterial behavior, with a shift from traditional assays averaging large populations to single-cell analysis focusing on bacterial individual behavior. Fluorescence-based methods are often used to analyze single-cell gene expression by flow cytometry, fluorescence microscopy and/or microfluidics. Moreover, fluorescence reporters can also be used to establish where and when are the genes of interest expressed. In this chapter, we use the model bacterial plant pathogen Pseudomonas syringae to illustrate a method to generate chromosome-located transcriptional gene fusions to fluorescent reporter genes, without affecting the function of the gene of interest.

Twitter Demographics

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

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 50%
Student > Bachelor 1 25%
Student > Ph. D. Student 1 25%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 75%
Biochemistry, Genetics and Molecular Biology 1 25%

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 31 December 2017.
All research outputs
#11,664,870
of 15,283,064 outputs
Outputs from Methods in molecular biology
#3,995
of 8,987 outputs
Outputs of similar age
#268,546
of 404,600 outputs
Outputs of similar age from Methods in molecular biology
#734
of 1,813 outputs
Altmetric has tracked 15,283,064 research outputs across all sources so far. This one is in the 20th percentile – i.e., 20% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,987 research outputs from this source. They receive a mean Attention Score of 2.6. This one is in the 48th percentile – i.e., 48% 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 404,600 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 1,813 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.