Mathematical modeling of combinatorial regulation suggests that apparent positive regulation of targets by miRNA could be an artifact resulting from competition for mRNA

Abstract

MicroRNAs bind to and regulate the abundance and activity of target messenger RNA through sequestration, enhanced degradation, and suppression of translation. Although miRNA have a predominantly negative effect on the target protein concentration, several reports have demonstrated a positive effect of miRNA, i.e., increase in target protein concentration on miRNA overexpression and decrease in target concentration on miRNA repression. miRNA-target pair-specific effects such as protection of mRNA degradation owing to miRNA binding can explain some of these effects. However, considering such pairs in isolation might be an oversimplification of the RNA biology, as it is known that one miRNA interacts with several targets, and conversely target mRNA are subject to regulation by several miRNAs. We formulate a mathematical model of this combinatorial regulation of targets by multiple miRNA. Through mathematical analysis and numerical simulations of this model, we show that miRNA that individually have a negative effect on their targets may exhibit an apparently positive net effect when the concentration of one miRNA is experimentally perturbed by repression/overexpression in such a multi-miRNA multitarget situation. We show that this apparent unexpected effect is due to competition and will not be observed when miRNA interact noncompetitively with the target mRNA. This result suggests that some of the observed unusual positive effects of miRNA may be due to the combinatorial complexity of the system rather than due to any inherently unusual positive effect of the miRNA on its target.

A causal mediation model of ischemia reperfusion injury in the retina

“…Therefore, this feedback loop confirms the mutually exclusive expression of mir-233 and NFI-A , thereby generating a bi-stable system (undifferentiated versus differentiated hematopoietic cells). A quite intriguing observation from Table 4 suggests that the opposite sign of ACME and ADE in class M TM loops reveals that the miRNAs and TFs are competing to regulate the target gene in opposite manners [ 70 – 71 ]. The factors that decide the winner are not known, but it is noticeable that more loops with competing miRNAs and TFs occur at 7d than at 24h.…”

Biological Pathway Specificity in the Cell—Does Molecular Diversity Matter?

“…In fact, increasing evidence is emerging that, for example, many cryptic RNA‐binding sites exist on proteins of all trades, including many metabolic housekeeping enzymes . Similarly, such dynamic equilibrium considerations are the essence of recent modeling efforts of the regulatory RNA silencing machinery, whereby each RNA target competes both for protein partners of the RNA‐induced silencing complex (RISC) and microRNAs (miRNAs; Figure ) . This competition can lead to some nonintuitive behaviors, such as that highly expressed miRNAs become sequestered and thus neutralized in terms of their regulatory power by targets that “sponge” them up, whereas competition between binding sites on different RNAs can lead to regulatory crosstalk and even apparent upregulation of targets (Figure B) .…”

“…[25][26][27] This competition can lead to some nonintuitive behaviors, such as that highly www.advancedsciencenews.com www.bioessays-journal.com expressed miRNAs become sequestered and thus neutralized in terms of their regulatory power by targets that "sponge" them up, whereas competition between binding sites on different RNAs can lead to regulatory crosstalk and even apparent upregulation of targets ( Figure 3B). [25,26] Importantly, the severity of these effects depends on both the affinities of all potential binding partners and the extent to which a specific component(s) of a given pathway becomes limiting in concentration, which the cell of course can control dynamically through gene regulation. Notably, evolution will fine-tune the affinity and gene expression level of each cellular component concomitantly, leading to highly complex networks of interactions where all content of the cell is interconnected and some components become particularly highly connected system hubs.…”

Exercise Training-Induced Changes in MicroRNAs: Beneficial Regulatory Effects in Hypertension, Type 2 Diabetes, and Obesity

“…Besides the role of individual variability, one of the many challenges involved in the study of miRNAs’ regulatory network is the ability of each single miRNA to regulate multiple targets, which adds complexity to the analysis and interpretation of the results [ 15 ]. It can be challenging to establish the biological significance of altered microRNA profiles in different settings, tissues, and compartments [ 16 , 17 ].…”