MicroRNAs (miRs) are small RNA molecules which target many mRNA transcripts, leading to their post-transcriptional silencing (Bartel, 2009). Many mRNAs can be silenced by multiple miRs and miRs often target more than one mRNA participating in a particular biological function (Bartel, 2009). Together, this suggests that the miR networks affecting specific mRNA transcripts may provide useful information on the biological roles in which these transcripts are involved. Cholinesterases are involved in many biological functions (Massoulie, 2002). However, miR-132 is the only miR so far that has been experimentally validated as targeting AChE, with consequences on inflammatory responses (Shaked et al., 2009). To delineate additional miRs which might regulate cholinesterase functions, we explored the 3′-untranslated regions (3′-UTR) of human cholinesterase transcripts (acetyl- and butyrylcholinesterase, AChE, BChE; Soreq and Seidman, 2001).

Given that several of the proteins involved in a specific function are often repressed by the same miR (Girardot et al., 2010), changes in a particular miR might down-regulate the entire process. Hence, we surmised that those functions that are shared by cholinesterases and the other targets of the cholinesterase-complementary miRs would be more susceptible for being affected by miR control than other processes. That concept is schematically presented as a workflow in Figure 1.

MicroRNA candidates were identified on each of the 3′-UTR sequences of AChE and BChE, which are 235, 1030, and 478 nucleotides long for BChE, the major “synaptic” AChE-S variant and the stress-inducible AChE-R variant, respectively (Figure 2A). We used the PicTar¹, miRanda², miRbase³, and microCosm⁴ algorithms to identify these transcript-specific miRs. All predictions ensured a threshold P-value < 0.05, and analysis specifications allowed both evolutionarily conserved and non-conserved miRs, which enabled us to include primate-targeting miRs as well.

Validation of miR-target interactions generally involved a 3′UTR luciferase assay. In some cases, it was complemented by protein blots, real-time RT-qPCR, microarrays, transgenic technology, β-galactosidase, or GFP-tagged targets. See, for example the Shaked et al. (2009) report for several of the latter technologies used to explore the miR-132 target AChE, and (Hansen et al., 2010) for the “classical” 3′-UTR and transgenic approaches, in exploring p250GAP which is also a miR-132 target.

To search for gene ontology (GO) categories which are also relevant for the other mRNA targets of cholinesterase-related miRs, we used the DAVID functional annotation clustering tool⁵. For each of the miRs identified as targeting one of the cholinesterases we searched for other experimentally validated targets; and we then used the lists of the other validated targets as gene lists for the DAVID search. Each list was normalized to the entire human genome, which served as a background.

We identified 116, 81, and 47 miRs (24, 8, and 20 miRs/100 nucleotides) that are complementary to the 3′-UTR domains of the BChE, AChE-R, and AChE-S transcripts, respectively. Of these, 6 miRs target both BChE and AChE-R whereas 11 miRs are common to both AChE-R and AChE-S, but BChE and AChE-S do not share any miR (Figure 2B). Positions of the identified miRs are presented in Figure 2C, with miR-132 targeting a similar seed domain localized at the very 3′-end of the 3′-UTR in both the AChE-S and AChE-R transcripts. Of the cholinesterase-targeting miRs, seven had multiple binding sites to the target AChE-S, nine to AChE-R, and seven to the BChE transcript, suggesting that they have a higher prospect for being functional (John et al., 2004). Compatible with the different conceptual principles on which each of the algorithms employed is based, only 8.6, 17, and 13.7% (7/81), (8/47), (16/116) of the miRs identified as targeting AChE-R, AChE-S, and BChE, respectively, were predicted by more than one of the algorithms. For AChE-R, these are hsa-miR-28-5p, −423-3p, −484, −483-5p, −663, −582-3p, −380*. For AChE-S, hsa-miR-194, −939, −658, −608,-615-5p, −423-5p −920, and let-7f-2* and for BChE, hsa-miR-203, −218, −221, −222, −181a, −181b, −181c, −181d, −494, −200b, −200c, −576-3p, −16-2*, −625, −195*, −889.

These cholinesterase-targeting miRs and their other validated non-cholinesterase targets are listed in Tables 1– 3 with the corresponding functions attributed to these other targets. The relevant citations appear in Tables A1– A4 in Appendix. Of note, numerous cholinesterase-targeting miRs have no experimentally validated targets at this time, yet others have more than one validated target and associate with more than one biological function. Examples include miR-124 which targets both the AChE-S and IQGAP1-(Furuta et al., 2010), a GTPase activating protein which promotes neurite outgrowth (Table 1). Additionally miR-152 and miR-148a, which target AChE-R, also target the calmodulin regulating kinase CaMKIIα (Liu et al., 2010; Table 2). Lastly, the BChE-targeting cluster of miRs-222 and −221 also target the neuronal early immediate protein c-fos (Ichimura et al., 2010; Table 3).

We focused our survey on those functions of those miRs for which experimental validation is available. Table 4 presents these miRs which are shared for AChE-R and AChE-S or AChE-R and BChE and some of their additional targets, highlighting the multitude of miR targets with predicted regulatory functions (e.g., the chromatin modulator zinc finger proteins ZEB1 and ZEB2 targeted by miR-200b, miR-200c, and miR-429 that are also directed to both AChE-R and AChE-S; Gregory et al., 2008). Likewise, the AChE-S-targeted miR-132 (Shaked et al., 2009; Soreq and Wolf, 2011) also targets the GTPase regulator p250GAP involved in neurite extension (Vo et al., 2005; Hansen et al., 2010; Table 4).

The process-regulation hypothesis of miR function predicts the existence of biological functions in which both cholinesterases, and those other targets which share miRs with cholinesterases, would be involved. To challenge this hypothesis, we first identified the GO categories in which AChE and BChE are involved, and found 24 and 11 biological processes for these two proteins, respectively. Twenty-three, 13, and 18 enriched biological processes emerged as shared processes for the other validated targets of AChE-R, AChE-S, and BChE-targeting miRs, respectively (P-value threshold < 0.05).

Out of over 20 ontology categories attributed to AChE, only two are shared with the categories attributed to the other validated targets of the cholinesterase-targeting miRs. These are: Response to wounding (GO: 0009611; 68 transcripts) and Neuron development (GO: 0048666), and specifically its AChE-relevant child terms Regulation of axonogenesis (GO: 0050770; 78 transcripts) and regulation of dendrite morphogenesis (GO: 0048814; 27 transcripts). Surprisingly, all 10 miRs that regulate Response to wounding and Neuron development selectively target the normally rare, stress-responsive AChE-R transcript, (miR-186, −125b, −200c, −199a-5p, −199b-5p, −125a, −214, −7, −663, −31, and −148a) whereas only three of these miRs also target the prevalent AChE-S mRNA (miR-194, −24, and −132). For BChE, we found only one shared category out of 11 relevant ontology groups: Response to glucocorticoid stimulus (GO: 0051384; 119 transcripts), and no overlap with the AChE-relevant categories (Figures 3A,B).

Using a variety of available algorithms, we found a plethora of cholinesterase-targeted miRs. Some of these were already validated as functionally capable of silencing other mRNA transcripts. A study of the functionally relevant biological processes in which these other targets are involved revealed a highly focused overlap with only few of the biological processes in which cholinesterases participate. Given that miRs regulate targets which share biological processes, cholinesterases appear to be primarily subject to miR regulation when involved in neuronal development, response to wounding, and glucocorticoid stimulus; and specific cholinergic processes are regulated by miRs targeting both AChE and other targets participating in the same biological process.

Several limitations should be considered in the context of this study. First, the currently available search algorithms for miR candidates appear to differ substantially, which casts a shadow on the veracity of such identification. Second, research bias has focused much of the efforts in the miR field toward cancer research, whereas neuroscience-focused miRs were relatively neglected. Therefore, we might have overlooked important miRs simply because they have not yet been validated experimentally. This being said, that many of the biological functions in which cholinesterases are involved show no relevant cholinesterase-targeting miR sequences suggests other modes of regulation of cholinesterase levels for most of these functions [e.g., transcriptional (Hill and Treisman, 1995), epigenetic (Allshire and Karpen, 2008), or post-translational processes (Fukushima et al., 2009)]. Alternatively, or in addition, miRs might exist which control these functions, but have no role in cancer biology and are therefore not yet characterized. MiR regulation of cholinesterase functions will therefore need to be re-inspected in the near future.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.