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Engineering and Analyzing Multicellular Systems

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Cover of 'Engineering and Analyzing Multicellular Systems'

Table of Contents

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    Book Overview
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    Chapter 1 Recent progress in engineering human-associated microbiomes.
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    Chapter 2 Constructing synthetic microbial communities to explore the ecology and evolution of symbiosis.
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    Chapter 3 Combining engineering and evolution to create novel metabolic mutualisms between species.
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    Chapter 4 Design, construction, and characterization methodologies for synthetic microbial consortia.
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    Chapter 5 An Observation Method for Autonomous Signaling-Mediated Synthetic Diversification in Escherichia coli.
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    Chapter 6 Integration-Free Reprogramming of Human Somatic Cells to Induced Pluripotent Stem Cells (iPSCs) Without Viral Vectors, Recombinant DNA, and Genetic Modification.
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    Chapter 7 Transformation of Bacillus subtilis.
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    Chapter 8 Culturing anaerobes to use as a model system for studying the evolution of syntrophic mutualism.
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    Chapter 9 Therapeutic microbes for infectious disease.
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    Chapter 10 Quantitative measurement and analysis in a synthetic pattern formation multicellular system.
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    Chapter 11 Transcriptome Analysis of a Microbial Coculture in which the Cell Populations Are Separated by a Membrane.
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    Chapter 12 Identification of Mutations in Laboratory-Evolved Microbes from Next-Generation Sequencing Data Using breseq.
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    Chapter 13 3D-Fluorescence In Situ Hybridization of Intact, Anaerobic Biofilm.
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    Chapter 14 The characterization of living bacterial colonies using nanospray desorption electrospray ionization mass spectrometry.
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    Chapter 15 Modeling community population dynamics with the open-source language R.
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    Chapter 16 Simulating microbial community patterning using biocellion.
Attention for Chapter 8: Culturing anaerobes to use as a model system for studying the evolution of syntrophic mutualism.
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Chapter title
Culturing anaerobes to use as a model system for studying the evolution of syntrophic mutualism.
Chapter number 8
Book title
Engineering and Analyzing Multicellular Systems
Published in
Methods in molecular biology, April 2014
DOI 10.1007/978-1-4939-0554-6_8
Pubmed ID
24838882
Book ISBNs
978-1-4939-0553-9, 978-1-4939-0554-6
Authors

Lim S, Stolyar S, Hillesland K, Sujung Lim, Sergey Stolyar, Kristina Hillesland, Lim, Sujung, Stolyar, Sergey, Hillesland, Kristina

Editors

Lianhong Sun, Wenying Shou

Abstract

Our current understanding of the evolution of mutualisms is limited partly because there have been relatively few model systems for studying it in real time. A model mutualistic interaction between the bacterium D. vulgaris and the archaeaon M. maripaludis was developed to allow for rigorous tests of general hypotheses about the evolution and ecology of mutualisms. This model system also allows us to develop an evolutionary genetics perspective on an interaction that plays a key ecological role in many oxygen-free microbial communities. Here, we describe the techniques used to make anoxic media for propagating these species alone or in conditions that require their cooperation.

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X Demographics

The data shown below were collected from the profile of 1 X user 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 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 10%
Unknown 9 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 50%
Lecturer 1 10%
Other 1 10%
Professor > Associate Professor 1 10%
Student > Postgraduate 1 10%
Other 0 0%
Unknown 1 10%
Readers by discipline Count As %
Environmental Science 4 40%
Agricultural and Biological Sciences 3 30%
Psychology 1 10%
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 06 January 2015.
All research outputs
#20,248,338
of 22,776,824 outputs
Outputs from Methods in molecular biology
#9,866
of 13,092 outputs
Outputs of similar age
#192,548
of 226,178 outputs
Outputs of similar age from Methods in molecular biology
#97
of 149 outputs
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