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Metagenomics

Overview of attention for book
Cover of 'Metagenomics'

Table of Contents

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    Book Overview
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    Chapter 1 Construction of Small-Insert and Large-Insert Metagenomic Libraries
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    Chapter 2 Extraction of Total DNA and RNA from Marine Filter Samples and Generation of a Universal cDNA as Universal Template for Marker Gene Studies
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    Chapter 3 Functional Metagenomics as a Tool to Tap into Natural Diversity of Valuable Biotechnological Compounds
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    Chapter 4 Functional and Sequence-Specific Screening Protocols for the Detection of Novel Antimicrobial Resistance Genes in Metagenomic DNA
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    Chapter 5 Identification of PKS Gene Clusters from Metagenomic Libraries Using a Next-Generation Sequencing Approach
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    Chapter 6 Activity-Based Screening of Metagenomic Fosmid Libraries for Hydrogen-Uptake Enzymes
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    Chapter 7 Functional Metagenomics Approach for the Discovery of Novel Genes Encoding Phosphatase Activity
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    Chapter 8 Isolation of Genes Encoding Carbon Metabolism Pathways from Complex Microbial Communities
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    Chapter 9 Screening Metagenomes for Algae Cell Wall Carbohydrates Degrading Hydrolases in Enrichment Cultures
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    Chapter 10 The PET-Degrading Potential of Global Metagenomes: From In Silico Mining to Active Enzymes
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    Chapter 11 High-Throughput Screening for Thermostable Polyester Hydrolases
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    Chapter 12 Metagenomic Screening of a Novel PET Esterase via In Vitro Expression System
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    Chapter 13 Assigning Functions of Unknown Enzymes by High-Throughput Enzyme Characterization
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    Chapter 14 Isolation of a Host-Confined Phage Metagenome Allows the Detection of Phages Both Capable and Incapable of Plaque Formation
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    Chapter 15 CRISPR-Cas9 Shaped Viral Metagenomes Associated with Bacillus subtilis
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    Chapter 16 Cloning and Expression of Metagenomic DNA in Streptomyces lividans and Its Subsequent Fermentation for Optimized Production
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    Chapter 17 DNA-, RNA-, and Protein-Based Stable-Isotope Probing for High-Throughput Biomarker Analysis of Active Microorganisms.
Attention for Chapter 17: DNA-, RNA-, and Protein-Based Stable-Isotope Probing for High-Throughput Biomarker Analysis of Active Microorganisms.
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Chapter title
DNA-, RNA-, and Protein-Based Stable-Isotope Probing for High-Throughput Biomarker Analysis of Active Microorganisms.
Chapter number 17
Book title
Metagenomics
Published in
Methods in molecular biology, January 2023
DOI 10.1007/978-1-0716-2795-2_17
Pubmed ID
Book ISBNs
978-1-07-162794-5, 978-1-07-162795-2
Authors

Jameson, Eleanor, Taubert, Martin, Angel, Roey, Coyotzi, Sara, Chen, Yin, Eyice, Özge, Schäfer, Hendrik, Murrell, J Colin, Neufeld, Josh D, Dumont, Marc G, Murrell, J. Colin, Neufeld, Josh D., Dumont, Marc G.

Abstract

Stable-isotope probing (SIP) enables researchers to target active populations within complex microbial communities, which is achieved by providing growth substrates enriched in heavy isotopes, usually in the form of 13C, 18O, or 15N. After growth on the substrate and subsequent extraction of microbial biomarkers, typically nucleic acids or proteins, the SIP technique is used for the recovery and analysis of isotope-labelled biomarkers from active microbial populations. In the years following the initial development of DNA- and RNA-based SIP, it was common practice to characterize labelled populations by targeted gene analysis. Such approaches usually involved fingerprint-based analyses or sequencing clone libraries containing 16S rRNA genes or functional marker gene amplicons. Although molecular fingerprinting remains a valuable approach for rapid confirmation of isotope labelling, recent advances in sequencing technology mean that it is possible to obtain affordable and comprehensive amplicon profiles, or even metagenomes and metatranscriptomes from SIP experiments. Not only can the abundance of microbial groups be inferred from metagenomes, but researchers can bin, assemble, and explore individual genomes to build hypotheses about the metabolic capabilities of labelled microorganisms. Analysis of labelled mRNA is a more recent advance that can provide independent metatranscriptome-based analysis of active microorganisms. The power of metatranscriptomics is that mRNA abundance often correlates closely with the corresponding activity of encoded enzymes, thus providing insight into microbial metabolism at the time of sampling. Together, these advances have improved the sensitivity of SIP methods and allowed using labelled substrates at environmentally relevant concentrations. Particularly as methods improve and costs continue to drop, we expect that the integration of SIP with multiple omics-based methods will become prevalent components of microbial ecology studies, leading to further breakthroughs in our understanding of novel microbial populations and elucidation of the metabolic function of complex microbial communities. In this chapter, we provide protocols for obtaining labelled DNA, RNA, and proteins that can be used for downstream omics-based analyses.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 20%
Researcher 2 20%
Student > Ph. D. Student 1 10%
Student > Doctoral Student 1 10%
Professor > Associate Professor 1 10%
Other 0 0%
Unknown 3 30%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 20%
Engineering 2 20%
Immunology and Microbiology 2 20%
Biochemistry, Genetics and Molecular Biology 1 10%
Environmental Science 1 10%
Other 0 0%
Unknown 2 20%
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 28 October 2022.
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#15,473,755
of 22,994,508 outputs
Outputs from Methods in molecular biology
#5,381
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Outputs of similar age
#160,989
of 312,302 outputs
Outputs of similar age from Methods in molecular biology
#84
of 224 outputs
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So far Altmetric has tracked 13,151 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 44th percentile – i.e., 44% of its peers scored the same or lower than it.
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