Francisco J. Iborra
Group Leader
Fernando Almazán
Group Leader
Research summary
We would like to understand the fundamental question of the control of cell differentiation, how a cell moves from one genetic program to another. The difference between the cells of our body is the set of genes they express. Pathological situations tend to be associated with aberrant patterns of gene expression. Gene expression starts at the DNA, which can be modified to be silent.
Publications
Márquez-Jurado S, Díaz-Colunga J, Pires das Neves R, Martinez-Lorente A, Almazán F, Guantes R and J. Iborra F. Mitochondrial levels determine variability in cell death by modulating apoptotic gene expression. Nature Communications 2018; 9:389
Guantes R, Díaz-Colunga J, Iborra FJ. Mitochondria and the non-genetic origins of cell-to-cell variability: More is different. Bioessays, 2016 Jan;38(1):64-76. doi: 10.1002/bies.201500082
Almazán F, Marquez-Jurado S, Nogales A, Enjuanes L. Engineering infectious cDNAs of coronavirus as bacterial artificial chromosomes. Methods Mol Biol 2015; 1282:135-52
Marquez-Jurado S, Nogales A, Zuñiga S, Enjuanes L, Almazán F. Identification of a gamma interferon-activated inhibitor of translation-like RNA motif at the 3’ end of the transmissible gastroenteritis coronavirus genome modulating innate immune response. MBio 2015; 6: e00105-15
Guantes R, Rastrojo A, das Neves R, Lima A, Aguado B, Iborra F. Global variability in gene expression and alternative splicing is modulated by mitochondrial content. Genome Res 2015; 25: 633-644
Our lab is interested in the origin of the phenotypic variability between genetically identical individuals. The reason we pursue this endeavour is that non-genic variability is the basis of many pathophysiological processes such as cell differentiation, cellular responses to drugs, and even the execution of apoptotic programmes. Non-genetic phenotypic variability can be classified as intrinsic or extrinsic. Intrinsic variability, or intrinsic noise, is due to differences in the expression patterns of specific genes and depends on levels of the factors that control expression of such genes. Extrinsic variability (extrinsic noise) affects many genes within a single cell. We approach this question using a combination of experimental and computational techniques.
Our group demonstrated that one factor that contributes to extrinsic noise is the difference in the mitochondrial content in clonal cell populations. This is because the activity of RNA polymerase II is very sensitive to changes in cellular ATP, which is derived from mitochondria. To understand the implications of the heterogeneous distribution of mitochondria, we have modelled how differences in mitochondria between individual cells can be responsible for extrinsic noise in gene expression or noise in cell cycle length and cell differentiation.
We found that human umbilical cord haematopoietic stem cells have fewer mitochondria than those committed to differentiation programs (Romero-Moya, et al., 2013). Our aim is characterise how mitochondria influence gene expression and study how they contribute to disease. We have shown that variability in mitochondria content also affects mRNA content and affects mRNA species differently, as we hypothesised. One unexpected effect of this mitochondrial variability is the acute change in alternative splicing, which can be attributed to the effect of mitochondria on RNA pol II (Guantes et al., 2015).
