@article { ISI:000349848800001,
	title = {Mathematical modeling of combinatorial regulation suggests that apparent positive regulation of targets by miRNA could be an artifact resulting from competition for mRNA},
	journal = {RNA-A Publication of the RNA Society},
	volume = {21},
	number = {3},
	year = {2015},
	month = {MAR},
	pages = {307-319},
	publisher = {COLD SPRING HARBOR LAB PRESS, PUBLICATIONS DEPT},
	address = {1 BUNGTOWN RD, COLD SPRING HARBOR, NY 11724 USA},
	abstract = {<p>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.</p>},
	keywords = {combinatorial binding, mathematical model, miRNA, post-transcriptional regulation},
	issn = {1355-8382},
	doi = {10.1261/rna.046862.114},
	author = {Nyayanit, Dimpal and Gadgil, Chetan J.}
}
@article {47810,
	title = {Mathematical model of the multi-amino acid multi-transporter system predicts uptake flux in CHO cells},
	journal = {Journal of Biotechnology},
	volume = {344},
	year = {2022},
	month = {JAN},
	pages = {40-49},
	type = {Article},
	abstract = {Supply and uptake of amino acids is of great importance to mammalian cell culture processes. Mammalian cells such as Chinese hamster ovary (CHO) cells express several amino acid (AA) transporters including uniporters and exchangers. Each transporter transports multiple AAs, making prediction of the effect of changed medium composition or transporter levels on individual AA transport rate challenging. A general kinetic model for such combinatorial amino acid transport, and a simplified analytical expression for the uptake rate as a function of amino acid concentrations and transporter levels is presented. From this general model, a CHO cell-specific AA transport model, to our knowledge the first such network model for any cell type, is constructed. The model is validated by its prediction of reported uptake flux and dependencies from experiments that were not used in model construction or parameter estimation. The model defines theoretical conditions for synergistic/repressive effect on the uptake rates of other AAs upon external addition of one AA. The ability of the CHO-specific model to predict amino acid interdependencies experimentally observed in other mammalian cell types suggests its robustness. This model will help formulate testable hypotheses of the effect of process changes on AA initial uptake, and serve as the AA transport component of kinetic models for cellular metabolism.},
	keywords = {Amino acid transport, CHO cell, Exchanger, mathematical model, Multiple transporters},
	issn = {0168-1656},
	doi = {10.1016/j.jbiotec.2021.12.003},
	author = {Sreejan, Ashley and Gadgil, Mugdha and Gadgil, Chetan J.}
}
