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Microbial Metagenomics, Metatranscriptomics, and Metaproteomics de Ed DeLong

Microbial Metagenomics, Metatranscriptomics, and Metaproteomics: Methods in Enzymology, cartea 531

Ed DeLong
en Limba Engleză Hardback – 15 noi 2013
This new volume of Methods in Enzymology continues the legacy of this premier serial with quality chapters authored by leaders in the field. This volume covers microbial metagenomics, metatranscriptomics, and metaproteomics, and includes chapters on such topics as in-solution FISH for single cell genome preparation, preparation of BAC libraries from marine microbial community DNA, and preparation of microbial community cDNA for metatranscriptomic analysis in marine plankton.


  • Continues the legacy of this premier serial with quality chapters authored by leaders in the field
  • Covers microbial metagenomics, metatranscriptomics, and metaproteomics
  • Contains chapters on such topics as in-solution fluorescence in situ hybridization (FISH) for single cell genome preparation, preparation of BAC libraries from marine microbial community DNA, and preparation of microbial community cDNA for metatranscriptomic analysis in marine plankton
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Specificații

ISBN-13: 9780124078635
ISBN-10: 012407863X
Pagini: 688
Ilustrații: colour illustrations, black & white tables, figures
Dimensiuni: 152 x 229 x 38 mm
Greutate: 1.26 kg
Editura: ELSEVIER SCIENCE
Seria Methods in Enzymology

Public țintă

Biochemists, biophysicists, molecular biologists, analytical chemists, and physiologists

Cuprins

SECTION I. PREPARATION AND GENOMIC ANALYSES OF SINGLE CELLS FROM NATURAL POPULATIONS
1. In-solution fluorescence in situ hybridization (FISH) for single cell genome preparation
2. Ribosomal RNA-­‐targeted magnetic cell separation for targeted metagenomic analysis
3. Genomic characterization of uncultivated symbiont populations using FACs and genome amplification.
4. Microfluidic Cell separation from complex microbial communities for single cell genome analysis
5. Assessing the abundance of active/damage cells and using cell sorting to determine their composition.
SECTION II. MICROBIAL COMMUNITY GENOMICS – SAMPLING, LIBRARY PREPARATION, AND SEQUENCING
6. Preparation of BAC libraries from marine microbial community DNA.
7. Preparation of fosmid libraries and functional metagenomic analysis of microbial community DNA
8. Preparation of metagenomic libraries from naturally occurring marine phage.
9. Preparation and metatranscriptomic analyses of host-­‐microbe systems.
10. Massively multiplexed ribosomal RNA tag sequencing on the Illumina Mi Seq platform
SECTION III. MICROBIAL COMMUNITY TRANSCRIPTOMICS -­‐ SAMPLING, SAMPLE PREPARATION, AND SEQUENCING
11. Preparation of microbial community cDNA for metatranscriptomic analysis in marine plankton.
12. Simultaneous extraction of metabolites, RNA, DNA, and proteins from the same sample
13. Utilization of quantitative internal standards for microbial community metatranscriptomics
14. Informatics workflows for phytoplankton metatranscriptomics
15. Sample processing and cDNA preparation for microbial metatranscriptomics in complex soil communities
SECTION IV. MICROBIAL COMMUNITY PROTETOMICS -­‐ SAMPLING, SAMPLE PREPARATION, AND SPECTRAL ANALYSIS AND INTERPRETATION.
16. Sample preparation and processing for planktonic microbial community protetomics.
17. Bioinformatic analysis of microbial metaproteomic datasets
18. Sample handling, mass spectrometry and spectra-­‐peptide matching for microbial metatproteomic analyses
SECTION V. MICROBIAL COMMUNITY "OMICS" – DATABASES, COMPUTATIONAL ANALYSES, COMPARATIVE ANALYSES, AND STATISTICS
19. Microbial community analysis using Megan
20. Microbial community analysis on the MG-­‐RAST platform.
21. Analysis/assembly of shotgun-re-sequenced genomes.
22. Computational methods for high-­‐throughput comparative analyses of natural microbial communities
23. Microbial community analysis using QIIME
24. Genome assembly from fosmid metagenomic library sequences
25. Qualitative and quantitative analyses of metagenomic datasets
26. Assembling full length rRNA genes from short read metagenomic sequence datasets using EMIRGE