Literature DB >> 26660201

Mitochondria and the non-genetic origins of cell-to-cell variability: More is different.

Raúl Guantes1, Juan Díaz-Colunga2, Francisco J Iborra2.   

Abstract

Gene expression activity is heterogeneous in a population of isogenic cells. Identifying the molecular basis of this variability will improve our understanding of phenomena like tumor resistance to drugs, virus infection, or cell fate choice. The complexity of the molecular steps and machines involved in transcription and translation could introduce sources of randomness at many levels, but a common constraint to most of these processes is its energy dependence. In eukaryotic cells, most of this energy is provided by mitochondria. A clonal population of cells may show a large variability in the number and functionality of mitochondria. Here, we discuss how differences in the mitochondrial content of each cell contribute to heterogeneity in gene products. Changes in the amount of mitochondria can also entail drastic alterations of a cell's gene expression program, which ultimately leads to phenotypic diversity. Also watch the Video Abstract.
© 2015 WILEY Periodicals, Inc.

Entities:  

Keywords:  alternative splicing; gene expression noise; non-genetic variability; transcription

Mesh:

Substances:

Year:  2015        PMID: 26660201     DOI: 10.1002/bies.201500082

Source DB:  PubMed          Journal:  Bioessays        ISSN: 0265-9247            Impact factor:   4.345


  8 in total

1.  The contribution of Saccharomyces cerevisiae replicative age to the variations in the levels of Trx2p, Pdr5p, Can1p and Idh isoforms.

Authors:  Aglaia V Azbarova; Kseniia V Galkina; Maxim I Sorokin; Fedor F Severin; Dmitry A Knorre
Journal:  Sci Rep       Date:  2017-10-16       Impact factor: 4.379

Review 2.  Mitophagy plays a central role in mitochondrial ageing.

Authors:  Alan Diot; Karl Morten; Joanna Poulton
Journal:  Mamm Genome       Date:  2016-06-28       Impact factor: 2.957

3.  Cell population heterogeneity driven by stochastic partition and growth optimality.

Authors:  Jorge Fernandez-de-Cossio-Diaz; Roberto Mulet; Alexei Vazquez
Journal:  Sci Rep       Date:  2019-06-28       Impact factor: 4.379

4.  Single cell functional genomics reveals the importance of mitochondria in cell-to-cell phenotypic variation.

Authors:  Ben Lehner; Lucas B Carey; Riddhiman Dhar; Alsu M Missarova
Journal:  Elife       Date:  2019-01-14       Impact factor: 8.140

Review 5.  Liver Microphysiological Systems for Predicting and Evaluating Drug Effects.

Authors:  Alexandre J S Ribeiro; Xinning Yang; Vikram Patel; Rajnikanth Madabushi; David G Strauss
Journal:  Clin Pharmacol Ther       Date:  2019-06-04       Impact factor: 6.875

Review 6.  Microbial metabolic noise.

Authors:  Andreas E Vasdekis; Abhyudai Singh
Journal:  WIREs Mech Dis       Date:  2020-11-23

7.  Mitochondrial levels determine variability in cell death by modulating apoptotic gene expression.

Authors:  Silvia Márquez-Jurado; Juan Díaz-Colunga; Ricardo Pires das Neves; Antonio Martinez-Lorente; Fernando Almazán; Raúl Guantes; Francisco J Iborra
Journal:  Nat Commun       Date:  2018-01-26       Impact factor: 14.919

Review 8.  Order Through Disorder: The Characteristic Variability of Systems.

Authors:  Yaron Ilan
Journal:  Front Cell Dev Biol       Date:  2020-03-20
  8 in total

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