Adjusting Noise in the Genetic Toggle Switch through Stochastic Circuit Design

Hortsch, Sayuri K.; Kremling, Andreas

doi:10.1016/j.ifacol.2018.09.045

Cited by 3 publications

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…CV is a unitless parameter and has been used to compare cell-to-cell variability between mRNAs or protein levels resulting from the expression of different genes ( Foreman and Wollman 2020 ). On the other hand, FF has a dimension and has been used to measure how the observed data are dispersed from a Poisson distribution ( Thattai and Van Oudenaarden 2001 ; Hortsch and Kremling 2018 ). As we are comparing measurements relative to the same gene between 2 genotypes, we calculated the FFs for the rho mRNA counts reported in Figs.…”

Section: Resultsmentioning

confidence: 99%

miR-9a regulates levels of both rhomboid mRNA and protein in the early Drosophila melanogaster embryo

Gallicchio

Griffiths-Jones

Ronshaugen

2022

G3 Genes|Genomes|Genetics

View full text Add to dashboard Cite

MicroRNAs can have subtle and combinatorial effects on the levels of the targets and pathways they act on. Studying the consequences of a single microRNA knockout often proves difficult as many such knockouts exhibit phenotypes only under stress conditions. This has often led to the hypothesis that microRNAs buffer the effects of intrinsic and environmental stochasticity on gene expression. Observing and understanding this buffering effect entails quantitative analysis of microRNA and target expression in single cells. To this end, we have employed single molecule fluorescence in situ hybridization, immunofluorescence, and high-resolution confocal microscopy to investigate the effects of miR-9a loss on the expression of the serine-protease Rhomboid in Drosophila melanogaster early embryos. Our single-cell quantitative approach shows that spatially, the rhomboid mRNA pattern is identical in WT and miR-9a knockout embryos. However, we find that the number of mRNA molecules per cell is higher when miR-9a is absent, and the level and temporal accumulation of rhomboid protein shows a more dramatic increase in the miR-9a knockout. Specifically, we see accumulation of rhomboid protein in miR-9a mutants by stage 5, much earlier than in WT. The data therefore show that miR-9a functions in the regulation of rhomboid mRNA and protein levels. While further work is required to establish whether rhomboid is a direct target of miR-9 in Drosophila, our results further establish the miR-9 family microRNAs as conserved regulators of timing in neurogenic processes. This work shows the power of single-cell quantification as an experimental tool to study phenotypic consequences of microRNA mis-regulation.

show abstract

Section: Resultsmentioning

confidence: 99%

miR-9a regulates levels of both rhomboid mRNA and protein in the early Drosophila melanogaster embryo

Gallicchio

Griffiths-Jones

Ronshaugen

2022

G3 Genes|Genomes|Genetics

View full text Add to dashboard Cite

show abstract

“…CV is a unitless parameter, and has been used to compare cell-to-cell variability between mRNAs or protein levels resulting from the expression of different genes (Foreman and Wollman 2020). On the other hand, FF has a dimension, and has been used to measure how the observed data are dispersed from a Poisson distribution, which has FF equal to 1 (Thattai and Van Oudenaarden 2001; Hortsch and Kremling 2018). We therefore calculated the FFs for the rho mRNA and TS counts reported in Figure 2 and Figure 3 (see Figure 4).…”

Section: Resultsmentioning

confidence: 99%

miR-9aregulates levels of bothrhomboidmRNA and protein in the earlyDrosophila melanogasterembryo

Gallicchio

Griffiths‐Jones

Ronshaugen

2021

Preprint

View full text Add to dashboard Cite

MicroRNAs have subtle and combinatorial effects on the expression levels of their targets. Studying the consequences of a single microRNA knockout often proves difficult as many such knockouts exhibit phenotypes only under stress conditions. This has led to the hypothesis that microRNAs frequently act as buffers of noise in gene expression. Observing and understanding buffering effects requires quantitative analysis of microRNA and target expression in single cells. To this end, we have employed single molecule fluorescence in situ hybridization, immunofluorescence, and high-resolution confocal microscopy to investigate the effects of miR-9a loss on the expression of the serine-protease rhomboid in Drosophila melanogaster early embryos. Our single-cell quantitative approach shows that rhomboid mRNA exhibits the same spatial expression pattern in WT and miR-9a knockout embryos, although the number of mRNA molecules per cell is higher when miR-9a is absent. However, the level of rhomboid protein shows a much more dramatic increase in the miR-9a knockout. Specifically, we see accumulation of rhomboid protein in miR-9a mutants by stage 5, much earlier than in WT. The data therefore show that miR-9a functions in the regulation of rhomboid activity by both inducing mRNA degradation and inhibiting translation in the blastoderm embryo. Temporal regulation of neural proliferation and differentiation in vertebrates by miR-9 is well-established. We suggest that miR-9 family microRNAs are conserved regulators of timing in neurogenic processes. This work shows the power of single-cell quantification as an experimental tool to study phenotypic consequences of microRNA mis-regulation.

show abstract

Stochastic Models for Studying the Role of Cellular Noise and Heterogeneity

Hortsch

Kremling

2021

Systems Medicine

View full text Add to dashboard Cite

Adjusting Noise in the Genetic Toggle Switch through Stochastic Circuit Design

Cited by 3 publications

References 9 publications

miR-9a regulates levels of both rhomboid mRNA and protein in the early Drosophila melanogaster embryo

miR-9a regulates levels of both rhomboid mRNA and protein in the early Drosophila melanogaster embryo

miR-9aregulates levels of bothrhomboidmRNA and protein in the earlyDrosophila melanogasterembryo

Stochastic Models for Studying the Role of Cellular Noise and Heterogeneity

Contact Info

Product

Resources

About