Literature DB >> 30178307

Insights into archaeal chaperone machinery: a network-based approach.

Shikha Rani1, Ankush Sharma2,3, Manisha Goel4.   

Abstract

Molecular chaperones are a diverse group of proteins that ensure proteome integrity by helping the proteins fold correctly and maintain their native state, thus preventing their misfolding and subsequent aggregation. The chaperone machinery of archaeal organisms has been thought to closely resemble that found in humans, at least in terms of constituent players. Very few studies have been ventured into system-level analysis of chaperones and their functioning in archaeal cells. In this study, we attempted such an analysis of chaperone-assisted protein folding in archaeal organisms through network approach using Picrophilus torridus as model system. The study revealed that DnaK protein of Hsp70 system acts as hub in protein-protein interaction network. However, DnaK protein was present only in a subset of archaeal organisms and absent from many archaea, especially members of Crenarchaeota phylum. Therefore, a similar network was created for another archaeal organism, Sulfolobus solfataricus, a member of Crenarchaeota. The chaperone network of S. solfataricus suggested that thermosomes played an integral part of hub proteins in archaeal organisms, where DnaK was absent. We further compared the chaperone network of archaea with that found in eukaryotic systems, by creating a similar network for Homo sapiens. In the human chaperone network, the UBC protein, a part of ubiquitination system, was the most important module, and interestingly, this system is known to be absent in archaeal organisms. Comprehensive comparison of these networks leads to several interesting conclusions regarding similarities and differences within archaeal chaperone machinery in comparison to humans.

Entities:  

Keywords:  Archaea; Chaperones; Networks; Protein folding; Protein-protein interactions

Mesh:

Substances:

Year:  2018        PMID: 30178307      PMCID: PMC6237683          DOI: 10.1007/s12192-018-0933-y

Source DB:  PubMed          Journal:  Cell Stress Chaperones        ISSN: 1355-8145            Impact factor:   3.667


  65 in total

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Authors:  Karthik Raman
Journal:  Autom Exp       Date:  2010-02-15

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Authors:  Akira Ideno; Tadashi Maruyama
Journal:  Gene       Date:  2002-06-12       Impact factor: 3.688

4.  A travel guide to Cytoscape plugins.

Authors:  Rintaro Saito; Michael E Smoot; Keiichiro Ono; Johannes Ruscheinski; Peng-Liang Wang; Samad Lotia; Alexander R Pico; Gary D Bader; Trey Ideker
Journal:  Nat Methods       Date:  2012-11-06       Impact factor: 28.547

5.  The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible.

Authors:  Damian Szklarczyk; John H Morris; Helen Cook; Michael Kuhn; Stefan Wyder; Milan Simonovic; Alberto Santos; Nadezhda T Doncheva; Alexander Roth; Peer Bork; Lars J Jensen; Christian von Mering
Journal:  Nucleic Acids Res       Date:  2016-10-18       Impact factor: 16.971

6.  PID: the Pathway Interaction Database.

Authors:  Carl F Schaefer; Kira Anthony; Shiva Krupa; Jeffrey Buchoff; Matthew Day; Timo Hannay; Kenneth H Buetow
Journal:  Nucleic Acids Res       Date:  2008-10-02       Impact factor: 16.971

7.  The importance of bottlenecks in protein networks: correlation with gene essentiality and expression dynamics.

Authors:  Haiyuan Yu; Philip M Kim; Emmett Sprecher; Valery Trifonov; Mark Gerstein
Journal:  PLoS Comput Biol       Date:  2007-02-14       Impact factor: 4.475

8.  Systems analysis of chaperone networks in the malarial parasite Plasmodium falciparum.

Authors:  Soundara Raghavan Pavithra; Ranjit Kumar; Utpal Tatu
Journal:  PLoS Comput Biol       Date:  2007-09       Impact factor: 4.475

9.  Characterization of the MCM homohexamer from the thermoacidophilic euryarchaeon Picrophilus torridus.

Authors:  Kasturi Goswami; Jasmine Arora; Swati Saha
Journal:  Sci Rep       Date:  2015-03-12       Impact factor: 4.379

Review 10.  Protein-protein interaction detection: methods and analysis.

Authors:  V Srinivasa Rao; K Srinivas; G N Sujini; G N Sunand Kumar
Journal:  Int J Proteomics       Date:  2014-02-17
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