Computational Characterization of Exogenous MicroRNAs That Can Be Transferred into Human Circulation

¹Department of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, NE, USA
²Department of Nutrition and Health Sciences, University of Nebraska-Lincoln, Lincoln, NE, USA

MicroRNAs have been long considered synthesized endogenously until very recent discoveries showing that human can absorb dietary microRNAs from animal and plant origins while the mechanism remains unknown. Compelling evidences of microRNAs from rice, milk, and honeysuckle transported to human blood and tissues have created high volume of interest in the fundamental questions that which and how exogenous microRNAs can get integrated into human circulation and possibly exert functions in humans. Here we present an integrated genomics and computational analysis to study the transportable features of microRNAs. Specially, we analyzed all publicly available microRNAs, a total of 34,612 from 194 species, with 1,102 features derived from the microRNA sequence and structure. Through in-depth bioinformatics analysis, 8 groups of discriminative features have been used to characterize human circulating microRNAs and infer the likelihood that a microRNA will get transferred into human circulation. For example, 345 dietary microRNAs have been predicted as highly transportable candidates where 117 of them have identical sequences with their homologs in human and 73 are known to be associated with exosomes. Through a milk feeding experiment, we have validated 9 cow-milk microRNAs in human plasma using microRNA-sequencing analysis, including the top ranked microRNAs such as bta-miR-487b, miR-181b, and miR-421. The implications in health-related processes have been illustrated in the functional analysis. This work demonstrates the data-driven computational analysis is highly promising to study novel molecular characteristics of transportable microRNAs while bypassing the complex mechanistic details.

[Supplementary Methods and Materials]
[Source code]
[microRNA feature data]
[microRNA ranking list]