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Related Concept Videos

Cooperative Allosteric Transitions01:58

Cooperative Allosteric Transitions

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Cooperative allosteric transitions can occur in multimeric proteins, where each subunit of the protein has its own ligand-binding site. When a ligand binds to any of these subunits, it triggers a conformational change that affects the binding sites in the other subunits; this can change the affinity of the other sites for their respective ligands. The ability of the protein to change the shape of its binding site is attributed to the presence of a mix of flexible and stable segments in the...
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Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

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Transcriptional regulators bind to specific cis-regulatory sequences in the DNA to regulate gene transcription. These cis-regulatory sequences are very short, usually less than ten nucleotide pairs in length. The short length means that there is a high probability of the exact same sequence randomly occurring throughout the genome.  Since regulators can also bind to groups of similar sequences, this further increases the chances of random binding. Transcriptional regulators form...
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Cooperative Binding of Transcription Regulators02:13

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Protein Networks02:26

Protein Networks

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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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NetCooperate: a network-based tool for inferring host-microbe and microbe-microbe cooperation.

Roie Levy1, Rogan Carr2, Anat Kreimer3,4

  • 1Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA. roie@uw.edu.

BMC Bioinformatics
|May 19, 2015
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Summary
This summary is machine-generated.

NetCooperate predicts host-microbe and microbe-microbe cooperation using metabolic network analysis. This tool quantifies interactions, revealing ecological and evolutionary insights into community assembly.

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Area of Science:

  • Microbiology
  • Systems Biology
  • Bioinformatics

Background:

  • Host-microbe and microbe-microbe interactions are crucial for understanding species impact and community assembly.
  • Metabolic network organization reflects these interactions, enabling prediction via graph theory.
  • Reverse ecology uses network topology to infer ecological and evolutionary processes.

Purpose of the Study:

  • To introduce NetCooperate, a tool for assessing host-microbe and microbe-microbe cooperative potential.
  • To implement and provide access to key interaction metrics derived from metabolic networks.

Main Methods:

  • NetCooperate analyzes pairs of metabolic networks.
  • It calculates the Biosynthetic Support Score (BSS) and Metabolic Complementarity Index (MCI).
  • The tool identifies potential syntrophic metabolic compounds.

Main Results:

  • NetCooperate quantifies the nutritional support a host provides to a microbe (BSS).
  • It measures niche complementarity between microbial pairs (MCI).
  • The software returns interaction metrics and lists of shared metabolic compounds.

Conclusions:

  • The BSS and MCI offer valuable insights into metabolic interactions.
  • NetCooperate provides a scalable method for analyzing these interactions from network topology.
  • It is available as a web tool and open-source Python module.