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Antibiotic Resistance Protocols

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Cover of 'Antibiotic Resistance Protocols'

Table of Contents

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    Book Overview
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    Chapter 1 Methods for Measuring the Production of Quorum Sensing Signal Molecules
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    Chapter 2 Construction and Use of Staphylococcus aureus Strains to Study Within-Host Infection Dynamics
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    Chapter 3 Method for Detecting and Studying Genome-Wide Mutations in Single Living Cells in Real Time
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    Chapter 4 Detecting Phenotypically Resistant Mycobacterium tuberculosis Using Wavelength Modulated Raman Spectroscopy
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    Chapter 5 A Flow Cytometry Method for Assessing M. tuberculosis Responses to Antibiotics
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    Chapter 6 Application of Continuous Culture for Assessing Antibiotic Activity Against Mycobacterium tuberculosis
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    Chapter 7 Real-Time Digital Bright Field Technology for Rapid Antibiotic Susceptibility Testing
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    Chapter 8 Enhanced Methodologies for Detecting Phenotypic Resistance in Mycobacteria
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    Chapter 9 Methods to Determine Mutational Trajectories After Experimental Evolution of Antibiotic Resistance
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    Chapter 10 Selection of ESBL-Producing E. coli in a Mouse Intestinal Colonization Model
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    Chapter 11 Transcriptional Profiling Mycobacterium tuberculosis from Patient Sputa
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    Chapter 12 Direct in Gel Genomic Detection of Antibiotic Resistance Genes in S1 Pulsed Field Electrophoresis Gels
  14. Altmetric Badge
    Chapter 13 Using RT qPCR for Quantifying Mycobacteria marinum from In Vitro and In Vivo Samples
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    Chapter 14 Use of Larval Zebrafish Model to Study Within-Host Infection Dynamics
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    Chapter 15 A Method to Evaluate Persistent Mycobacterium tuberculosis In Vitro and in the Cornell Mouse Model of Tuberculosis
Attention for Chapter 13: Using RT qPCR for Quantifying Mycobacteria marinum from In Vitro and In Vivo Samples
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Chapter title
Using RT qPCR for Quantifying Mycobacteria marinum from In Vitro and In Vivo Samples
Chapter number 13
Book title
Antibiotic Resistance Protocols
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7638-6_13
Pubmed ID
Book ISBNs
978-1-4939-7636-2, 978-1-4939-7638-6
Authors

Han Xaio, Stephen H. Gillespie

Abstract

Mycobacterium marinum, the causative agent of fish tuberculosis, is rarely a human pathogen causing a chronic skin infection. It is now wildely used as a model system in animal models, especially in zebra fish model, to study the pathology of tuberculosis and as a means of screening new anti-tuberculosis agent. To facilitate such research, quantifying the viable count of M. marinum bacteria is a crucial step. The main approach used currently is still by counting the number of colony forming units (cfu), a method that has been in place for almost 100 years. Though this method well established, understood and relatively easy to perform, it is time-consuming and labor-intensive. The result can be compromised by failure to grow effectively and the relationship between count and actual numbers is confused by clumping of the bacteria where a single colony is made from multiple organisms. More importantly, this method is not able to detect live but not cultivable bacteria, and there is increasing evidence that mycobacteria readily enter a "dormant" state which confounds the relationship between bacterial number in the host and the number detected in a cfu assay. DNA based PCR methods detect both living and dead organisms but here we describe a method, which utilizes species specific Taq-Man assay and RT-qPCR technology for quantifying the viable M. marinum bacterial load by detecting 16S ribosomal RNA (16S rRNA).

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 19%
Student > Master 4 15%
Student > Bachelor 4 15%
Unspecified 2 7%
Other 2 7%
Other 6 22%
Unknown 4 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 22%
Immunology and Microbiology 4 15%
Biochemistry, Genetics and Molecular Biology 3 11%
Unspecified 2 7%
Chemistry 2 7%
Other 5 19%
Unknown 5 19%
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 13 January 2018.
All research outputs
#20,458,307
of 23,015,156 outputs
Outputs from Methods in molecular biology
#9,945
of 13,165 outputs
Outputs of similar age
#378,187
of 442,344 outputs
Outputs of similar age from Methods in molecular biology
#1,193
of 1,498 outputs
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So far Altmetric has tracked 13,165 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 1,498 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.