Analyzing the miRNA regulatory landscape of OGT identifies evolutionarily conserved upregulation.

Analyzing the miRNA regulatory landscape of OGT identifies evolutionarily conserved upregulation | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Analyzing the miRNA regulatory landscape of OGT identifies evolutionarily conserved upregulation Zainab Ali Syeda , Faezeh Jame-Chenarboo , Hoi-Hei Ng , Chu Thu , Helia Dehghan Harati , Dawn Macdonald , View ORCID Profile Lara K. Mahal doi: https://doi.org/10.1101/2025.08.21.671361 Zainab Ali Syeda 1 Department of Chemistry, University of Alberta , Edmonton, Alberta, Canada T6G 2G2 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Faezeh Jame-Chenarboo 1 Department of Chemistry, University of Alberta , Edmonton, Alberta, Canada T6G 2G2 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Hoi-Hei Ng 1 Department of Chemistry, University of Alberta , Edmonton, Alberta, Canada T6G 2G2 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Chu Thu 1 Department of Chemistry, University of Alberta , Edmonton, Alberta, Canada T6G 2G2 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Helia Dehghan Harati 1 Department of Chemistry, University of Alberta , Edmonton, Alberta, Canada T6G 2G2 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Dawn Macdonald 1 Department of Chemistry, University of Alberta , Edmonton, Alberta, Canada T6G 2G2 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Lara K. Mahal 1 Department of Chemistry, University of Alberta , Edmonton, Alberta, Canada T6G 2G2 Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Lara K. Mahal For correspondence: lkmahal{at}ualberta.ca Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract O-GlcNAc transferase (OGT) is the key enzyme involved in post-translationally modifying cytoplasmic and nuclear proteins with O-GlcNAc. Maintenance of cellular O-GlcNAcylation levels is critical to cell health and requires precise transcriptional and post-transcriptional control. Herein we examine the miRNA regulation of OGT by the human miRNAome using our high-throughput miRFluR assay. We found >200 miRNA regulators of OGT, including 17 down- and 15 upregulatory miRNAs previously identified in CLIP datasets. We validated the impact of select miRNA on OGT and O-GlcNAc levels using both miRNA mimics and inhibitors that reduce endogenous miRNA levels. We focused our studies on two miRNA families, the downregulatory let-7 family and the upregulatory miR-148/152 family. For the let-7 family, we found that only let-7a-3p and let-7g-3p strongly downregulated OGT. Downregulation required two seed-dependent binding sites. Evolutionary analysis found that the more recent of the two sites emerged in placental mammals. A similar conservation pattern was observed for the site of regulation by the miR-148/152 family, which was previously identified in CLIP datasets. All three miRNA in this family upregulated OGT. Phylogenetic analysis revealed that this upregulatory site has been conserved for the past 98.7 million years. The emergence of these regulatory sites correlates with that of disease states that both OGT and the miRNA are known to impact. Overall, our results provide important insights into OGT, miRNA regulation and conservation through evolution. Introduction O-GlcNAc, in which N- acetylglucosamine modifies serines or threonines, is a nucleocytoplasmic modification that is crucial for cell cycle signaling, stress response and metabolic sensing ( 1 ). Levels of O-GlcNAc are controlled by O-GlcNAc transferase (OGT) ( 2 , 3 ), which puts on the modification, and O-GlcNAcase (OGA)( 4 – 10 ), which removes it ( Fig. 1 )( 10 – 13 ). Perturbations in O-GlcNAc have been observed in neurodegenerative disorders such as Alzheimer’s and Parkinson’s disease, Type 2 diabetes and cardiovascular disorders ( 14 – 16 ). This dynamic modification requires tight regulation of both OGT and OGA enzymes and UDP-GlcNAc levels. Download figure Open in new tab Figure 1. Scheme for O-GlcNAcylation. O-GlcNAc transferase (OGT) transfers N- acetyl-D-glucosamine (GlcNAc, blue square) onto serines or threonines on proteins. The enzyme O-GlcNAcase (OGA) is responsible for the removal of this modification, making it reversible. UDP-GlcNAc: uridine diphosphate N -acetyl-D-glucosamine. OGT is a highly conserved gene across a number of eukaryotes, from C. elegans to humans ( 17 – 19 ). Conservation of this enzyme suggests that O-GlcNAc plays an ancient and fundamental role in cells. OGT is essential for embryogenesis and for the viability of dividing cells ( 20 , 21 ). Alternative splicing produces three OGT isoforms: nucleocytoplasmic OGT (ncOGT), mitochondrial OGT (mOGT), and short OGT (sOGT), which differ in location and transcript length but share the same 3’ untranslated region (UTR), the primary site of miRNA regulatory interactions. miRNAs are endogenous non-coding RNAs (∼22 nucleotides in length) that fine tune protein expression. Canonically, they are thought to work by inhibiting translation or causing degradation of messenger RNA (mRNA) ( 22 – 24 ) through complementation of 6-7 nucleotides between mRNA and the seed-region of the miRNA. It has become clear that miRNA regulation is bidirectional, with the same miRNA inhibiting the expression of one protein, while enhancing that of another ( 25 , 26 ). First identified in 2007 by Vasudevan and Steitz, upregulation by miRNA has recently been shown to be a common occurrence ( 27 – 31 ). Upregulation requires Argonaute 2 (AGO2), yet is inhibited or unaffected by the presence of trinucleotide repeating-containing adaptor 6A (TNRC6A, aka GW182), a critical part of downregulatory AGO2 complexes ( 27 , 31 , 32 ). In contrast to downregulation, increasing evidence has shown upregulation often utilizes non-canonical (non-seed) binding between the miRNA and mRNA. At present, seven miRNA have been identified as downregulators of OGT ( 33 – 39 ), however it is unknown whether miRNA upregulate OGT as this has not been examined. Herein, we did a comprehensive analysis of miRNA regulation of OGT via its 3’UTR using our high-throughput assay, miRFluR ( 25 , 27 , 28 , 40 ). We identified ∼200 regulators of OGT, and found a bidirectional role for miRNA in tuning OGT expression. We focused on two miRNA families that regulate OGT, the let-7 family, members of which downregulated OGT, and the miR-148/152 family, which upregulates OGT protein expression. Identification of the miRNA binding sites of these two families enabled us to examine evolutionary conservation. We found that for these miRNA families, sites emerged with the introduction of placental mammals, showing conservation of both up- and downregulatory miRNA binding sites in OGT for >98 million years. Overall, our work sheds light on the post-transcriptional regulation of this crucial enzyme. Results High-throughput miRFluR analysis of OGT identifies both up- and down-regulatory miRNA O-GlcNAc transferase (OGT) is one of the most highly regulated proteins in the cell, with documented regulation at the transcriptional, post-transcriptional and post-translational levels ( 41 – 43 ). Levels of this enzyme are tuned by external environmental conditions, including stress, and are sensitive to metabolic perturbations which alter O-GlcNAc levels ( 44 – 46 ). Post-transcriptional regulation by miRNA has been observed and to date, a handful of miRNA regulators have been studied ( 34 – 39 , 47 , 48 ). To provide a more comprehensive view, we utilized our high-throughput miRFluR assay to test the human miRNAome for OGT regulators ( 27 , 49 ). This assay utilizes a genetically encoded ratiometric sensor (pFmiR) containing the fluorescent protein Cerulean upstream of the 3’-untranslated region (3’UTR) of the gene of interest and mCherry as an internal control ( Fig. 2A ). Co-transfection into HEK-293T cells of the plasmid and a library of miRNA allows interrogation of the miRNAome. Ratiometric analysis of Cerulean/mCherry fluorescence indicates the extent of miR:target regulation. Download figure Open in new tab Figure 2. High throughput analysis of OGT 3’UTR using miRFluR assay. (A) Scheme of miRFluR assay. The pFmiR-OGT 3’UTR sensor is co-transfected with the human miRNA library in HEK -293T cells. The ratio of Cerulean to mCherry is normalized to non-targeting control (NTC) and can identify downregulatory (down-miR, red), neutral, or up-regulatory (up-miR, blue) miRNA. (B) Pie chart of miRNA hits (yellow, 8.6 %) for OGT 3’UTR. (C) Representation of up-miRs (blue, 68 %) versus down-miRs (red, 32 %) among miRNAs hits. (D) Scatter plot of Z-score versus fold-change (log2) for QCed miRFluR data. miRNAs in the 90 % confidence interval are colored (down-miRs: red, up-miRs: blue) and those selected for further validation are labeled. To study the miRNA regulation of OGT, we cloned the 3’UTR of OGT into our pFmiR plasmid ( Figs.S1-S2 ). Although OGT has multiple isoforms, all share a single conserved 3’UTR (2147 nucleotides (nt)). We co-transfected pFmiR-OGT plasmid with the human miRNA mimic library (Dharmacon, v. 21) into HEK-293T cells. The library was displayed in 384-well plates (24 total) with 3-replicates for each miRNA mimic. After 48 hours (h), we analyzed the fluorescence of the cells and calculated the Cerulean:mCherry ratio. We normalized the data to a non-targeting control (NTC) present in each plate. After quality control (QC), our dataset contained 2214 miRNAs ( Dataset S1, see Methods ). Of the seven miRNA previously shown to downregulate OGT, one was QCed out (miR-424-5p) ( 33 ), one showed no change (miR-485-5p)( 34 ) and five showed downregulation of at least 30% in our assay (miRs-7-5p, -24-3p, -101-5p, -483-3p, -501-3p) ( 35 – 39 ). After z-scoring our data, we noted that three of the five downregulators were outside of the 95% confidence interval, thus we set the 90% confidence interval as the delineation for our hit list. We found that 8.5 % of miRNA passing QC were in this interval (183 total hits, Fig. 2B-D , Table S1 ). This is significantly higher than what is observed in our other miRFluR data sets (3-6%) and is consistent with predictions of OGT being one of the most highly regulated genes by miRNA ( 25 , 27 , 49 , 50 ). We found a higher number of upregulatory ( Fig. 2C , up-miRs, 68%, 124 miRs) than downregulatory (down-miRs, 32%, 59 miRs) miRNAs targeting OGT. We compared our miRNA hitlist with data generated through cross-linked immunoprecipitation (CLIP) of AGO complexes using starBase v.2., a comprehensive CLIP database ( 51 , 52 ). In CLIP, mRNA footprinting is combined with miRNA profiling from the IP and miRNA prediction algorithms are used to determine binding sites ( 53 ). We found that 17 down-miRs and 15 up-miRs from our hitlist were identified in AGO complexes with the OGT 3’UTR ( Dataset S2 ), including 3 of the known down-miRs. This data confirms the ability of our miRFluR assay to identify miRNA regulation of OGT. miRNAs regulate OGT expression bidirectionally in cancer cell lines To validate our miRFluR results, we chose a set of miRNA (5 down-miRs, 6 up-miRs) from throughout the confidence interval and added miR-7-5p as a positive control ( 37 , 54 ). We tested down-miRs: let-7a-2-3p, miR-7-5p , -15b, -556, -421, -34c-3p and up-miRs: miR-302b-3p , -148a-3p , -20a-3p, -151b-3p, -512-3p, -520c-3p (miRNAs observed in CLIP datasets are underlined, Dataset S2 ) . We transfected mimics or NTC into A549, a common lung adenocarcinoma cell line, and analyzed OGT levels by Western blot analysis at 72 h post-transfection ( Fig. 3 , Fig. S3, Table S2 ). Of the six down-miRs tested, only two impacted OGT levels in this cell line (let-7a-2-3p and our positive control, miR-7-5p, Fig. 3A-B , Fig. S3A-B ). In contrast, we observed clear upregulation for all of the up-miRs, although statistical significance was only reached for miR-148a-3p. Download figure Open in new tab Figure 3. Validation of miRNA regulators of OGT. (A) Representative Western blot analysis for OGT. A549 cells were treated with 50 nM of either non-targeting control (NTC) or miRNA mimics (down-miRs (red): -let-7a-2-3p, miR-7-5p, -15b, -556, -421,-34c-3p. up-miRs (blue): miR-302b-3p, -148a-3p, -20a-3p, -151b-3p, -512-3p and -520c-3p) for 72 h prior to lysis and analysis. (B) Quantification of Western blot data for n=4 biological replicates as in (A). (C) Representative Western blot analysis for OGT on Caco-2 cells treated with a subset of miRNA as in (A). (D) Quantification of Western blot data for Caco-2 (n=5 replicates). For all quantification, Western blot samples were normalized first to total protein (Ponceau) and then to the normalized NTC. Individual replicates are indicated as discrete points. Error bars represent standard deviations. Statistical analysis was done using both the one-sample t -test and paired t -test. Highest significance from either test is shown. * p < 0.05, ** < 0.01 . p -values for both the tests are reported in Table S2 . We revalidated the impact of a subset of the miRNA on OGT levels in the colorectal adenocarcinoma line Caco-2 ( Fig. 3C-D , Fig. S3C-D ; down-miRs: let-7a-2-3p, miR-7-5p; up-miRs: miR-20a-3p, -148a-3p, -302b-3p). In line with other studies, cell dependent effects were observed ( 48 , 55 – 58 ). While let-7a-2-3p significantly downregulated OGT expression, the known down regulator miR-7-5p, which has an AGO2 binding site, had no impact in this cell line ( Dataset S2 ). We again observed upregulation by all three up-miRs tested, although in Caco-2, only miR-20a-3p and -302b-3p were statistically significant. Overall, the validation data was in line with our miRFluR analysis. Inhibition of endogenous miRNA impacts OGT levels To confirm that our miRNA mimics accurately represent the activity of endogenous miRNA, we utilized antimiRs (miRNA hairpin inhibitors) ( Fig. 4 , Table S2 ). These inhibitors bind to endogenous miRNA in AGO2 complexes, resulting in enhancement of protein levels for anti-down-miRs and repression of protein expression for anti-up-miRs. For the inhibitors to function, the miRNAs must be expressed. In A549, only miR-7-5p and -148a-3p were expressed at moderate levels, therefore we focused on these miRNAs. Although we failed to see statistically significant changes with either anti-miR, we observed a clear decrease of OGT expression (∼50%) with the anti up-miR-148a-3p and a slight increase with the anti-down-miR-7-5p ( Fig. 4A-B , Fig. S4A-B ). We then focused on Caco-2. This cell line has very high expression of miR-148a-3p, moderate expression of miR-7-5p, low expression of miRs-302b-3p, and -20a-3p, and no detectable let-7a-2-3p.( 59 ) In line with this expression data, only inhibition of miR-148a-3p showed a strong and statistically significant response, with a loss of OGT expression ( Fig. 4C-D , Fig. S4C-D ). The anti-miR for the known miRNA downregulator of OGT, miR-7-5p, did not show any impact in Caco-2. Overall, our results provide strong evidence that endogenous miR-148a-3p upregulates OGT protein expression. Download figure Open in new tab Figure 4. Inhibition of endogenous miRNAs impact OGT levels. (A, C) Representative Western blot analysis for OGT in A549 (A) or Caco-2 (C). Cells were transfected with 50 nM of either anti-miR non-targeting control (NTC, grey) or anti-miRs (anti-down-miRs (red): let-7a-3p, -miR-7-5p. anti-up-miRs (blue): -20a-3p, -148a-3p, -302b-3p). (B, D) Quantification of Western blot analysis for OGT in A549 (B, n=4) or Caco-2 cells (D, n=5). Graph shows average data of replicates. For all quantification, Western blot samples were normalized first to total protein (Ponceau) and then to the normalized NTC. Individual replicates are indicated as discrete points. Error bars represent standard deviations. Statistical analysis was done using both the one-sample t-test and paired t-test. Highest significance from either test is shown. * p < 0.05. p -values for both the tests are reported in Table S2 . miRNA regulate O-GlcNAcylation levels through OGT To assess the functional consequence of miRNA mediated OGT regulation, we investigated the impact of miRNA on the resultant O-GlcNAcylation levels. O-GlcNAc is controlled by both OGT and OGA levels. Thus, we tested the impact of a subset of miRNA mimics (down-miRs: let-7a-2-3p, miR-7-5p; up-miRs: miR-20a-3p, -148a-3p, -302b-3p) and NTC on OGT, OGA and O-GlcNAc in A549 cells using the same lysate for all three Westerns ( Fig. 5 , Fig. S5, Table S2 ). In this coupled dataset, we observed the expected down- and up-regulation of OGT in line with our previous data, although here the down-miR let-7a-2-3p, and the up-miRs miR-20a-3p and -302b-3p were statistically significant ( Fig. 5A-B , Fig. S5A-B ). In examining the impact of miRNA mimics on OGA, we noted that the NTC had an inhibitory effect on OGA expression when compared to untreated lysate ( Fig. 5C-D , Fig. S5C-D ). In contrast, NTC did not impact OGT levels ( Fig. S4G-H ). The NTC used is a microRNA from C. elegans which has been shown to impact the expression of other proteins ( 25 , 27 , 40 ). Hence, we decided to use untreated cell lysate as the control in determining mimic effects on OGA protein levels. In general, we observed no changes in OGA expression with the tested miRNAs, although miR-7-5p did cause a slight decrease (∼20%) in OGA expression that was not statistical ( Fig. 5C-D , Fig. S5C-D ). In line with the OGT data, we observed clear decreases in O-GlcNAc levels with the down-miRs and clear increase with the up-miRs, although only let-7a-2-3p (down-miR) and miR-148a-3p (up-miR) were statistically significant ( Fig. 5E-F , Fig. S5E-F ). Download figure Open in new tab Figure 5. miRNAs regulate O-GlcNAc levels through OGT without impacting OGA. (A, C, E). Representative Western blot data for OGT (A), OGA (C) and O-GlcNAc (E) in A549 cells treated as in Figure 3 . miRNA mimics: NTC (grey), down-miRs (red): let-7a-2-3p, miR-7-5p, up-miRs (blue): miR-302b-3p, -148a-3p, -20a-3p. (B, D, F) Quantification of Western blot analysis for OGT (B, n=4), OGA (D, n=3) and O-GlcNAc (F, n=4). Bar charts represent average data. For OGT and O-GlcNAc, Western blot samples were normalized first to total protein (Ponceau) and then to the normalized NTC. For OGA, untreated lysate was used for normalization in lieu of NTC. Individual replicates are indicated as discrete points. Error bars represent standard deviations. Statistical analysis was done using both the one-sample t-test and paired t-test. Highest significance from either test is shown. *p < 0.05, ** < 0.01. p -values for both the tests are reported in Table S2 . We also analyzed the lysates for A549 treated with anti-miR-7-5p and anti-148a-3p shown in Fig. 4A-B to determine the impact of endogenous miRNA on O-GlcNAc levels. We observed a significant loss of O-GlcNAc expression (∼50% decrease, Fig. 6 , Fig. S6, Table S2 ) upon treatment with anti-up-miR-148a-3p. In contrast, the anti-down-miR-7-5p did not show changes. This is consistent with the stronger impact of up-miR-148a-3p on OGT protein levels. Overall, our results support miRNA regulation of O-GlcNAc levels through OGT. Download figure Open in new tab Figure 6. Endogenous miRNAs regulate O-GlcNAc levels. (A) Representative Western blot analysis for O-GlcNAc in the A549 cells from Figure 4A . (B) Quantification of Western blot analysis for O-GlcNAc. Bar charts represent average data (n=4). Western blot samples were normalized first to total protein (Ponceau) and then to the normalized NTC. Individual replicates are indicated as discrete points. Error bars represent standard deviations. Statistical analysis was done using both the one-sample t-test and paired t-test. Highest significance from either test is shown. *p < 0.05. p -values for both the tests are reported in Table S2 . Downregulation of OGT by the let-7 family is dependent on seed sequence conservation The let-7 family was one of the earliest and largest families of miRNA to be discovered and is conserved from invertebrates to humans ( 60 ). In C. elegans , let-7 controls the timing of terminal differentiation and is important in development ( 61 , 62 ). Like OGT, the let-7 family has a well documented role in the cell cycle, with high let-7 leading to cell cycle exit through targeting of multiple cell cycle genes.( 63 , 64 ) ( 65 ) In humans, there are 10 members of the let-7 family, with similar seed sequences ( Fig. 7 ) ( 66 , 67 ). With this is mind, we evaluated the impact of 8 members of the let-7 family on OGT expression by Western blot analysis (let-7a-2-3p, -7g-3p, -7c-3p, -7a-3p, -7b-3p, - 7d-3p, -7e-3p, -7f-1-3p, -7f-2-3p, and -7i-3p, Fig.7A -B, Fig. S7, Table S2 ). We observed strong downregulation of OGT expression by let-7a-2-3p and -7g-3p (∼80%), consistent with the conserved seed site between the two ( Fig. 7C ). Significant downregulation of OGT was also observed in cells treated with let-7e-3p, -7f-1-3p and -7i-3p (∼34-43%), but not other members of the family. Download figure Open in new tab Figure 7. let-7 family members downregulate OGT expression. (A) Representative Western blot analysis for OGT in A549 cells treated with NTC, (grey) or let-7 family members (let-7a-2-3p, -7b-3p, -7c-3p, -7d-3p, -7e-3p, -7f-1-3p, -7f-2-3p, -7g-3p and -7i-3p) as before. (B) Quantification of Western blot analysis for OGT. Bar graphs represent average data from n=5 biological replicates. Data for let-7a-2-3p and -7g-3p are solid red for emphasis. Western blot samples were normalized first to total protein (Ponceau) and then to the normalized NTC. Individual replicates are indicated as discrete points. Error bars represent standard deviations. Statistical analysis was done using both the one-sample t-test and paired t-test. Highest significance from either test is shown. (C) Alignment of let-7 family members in order of seed similarity to let-7a-2-3p. The seed region is shown in grey box and differences between miRs are outlined in red. (D) Small scale analysis of miRFluR assay for let-7 family. HEK-293T cells were co-transfected with pFmiR-OGT sensor and either NTC or select let-7 family members as indicated. Average signal (n=3 biological replicates) from miRFluR assay normalized over NTC is shown and individual replicates are indicated as discrete points. Error bars represent standard deviations. Statistics was done using paired t-test. * p < 0.05, ** < 0.01, *** < 0.001 . All p -values are reported in Table S2. Since let-7 family members share similar seed sequences, we aligned them in order of conservation of their seed region ( Fig. 7C ). As previously mentioned, let-7a-2-3p and -7g-3p have identical seeds and both show strong downregulation of OGT in both Western and using our miRFluR sensor ( Fig. 7D , note: let-7g-3p was QCed out of the initial dataset). In contrast, changing a single base pair in the seed, as seen in let-7c-3p, abrogated the impact on OGT expression, and much of the signal in our miRFluR assay. Although let-7e-3p, -7f-1-3p and -7i-3p showed some downregulation of OGT, no change was observed in our miRFluR assay, arguing that their impact is either indirect or through binding to the 5’UTR or coding region. Overall, our results are consistent with the importance of the seed region for let-7 family regulation of OGT via the 3’UTR and the impact that even a single nucleotide change can have. To identify sites of let-7a-2-3p regulation in the 3’-UTR, we surveyed Targetscan, which relies on seed pairing ( 22 ). Two binding sites were identified for let-7a-2-3p/-7g-3p ( Fig. 8A-D ), neither of which were observed in CLIP data. We made three mutant sensors to test the predicted sites (MUT-A for site +1757- 1779 bp, MUT- B for site +2866- 2886 bp and MUT A + B for both the sites together) mutating the sites to the sequence of let- 7g-3p. We analyzed miRNA regulation in the wildtype and mutant pFmiR-OGT sensors with let-7a-2-3p or -7g-3p mimics in HEK-293T cells, comparing them to NTC ( Fig. 8E , Table S2 ). Mutating either site relieved some of the repression from let-7a-2-3p or -7g- 3p. However, mutating both sites showed a more profound effect, almost completely abrogating the repressive effects of the miRNAs. The multiple sites might help to explain the strong repression observed from these miRNA on OGT expression in cells ( Figs. 3 , 7 ). Download figure Open in new tab Figure 8. Validation of let-7a/g site on OGT 3’UTR. (A-D) Alignment of let-7a-2-3p and -7g-3p with their predicted OGT-3’ UTR sites and their corresponding mutants are shown. Mutated nucleotides (orange) and wobble base pairs (pink) are indicated. The miRNA seed sequence outlined in grey box and underlined. (E) Bar graph shows average data for HEK-293T cells transfected with let-7a-2-3p (pink) or -7g-3p (orange) with WT (wildtype) or MUT (Mutant-A, Mutant-B and Mutant A+B) miRFluR sensors. For each sensor, data was normalized over NTC in that sensor. The experiment was performed in biological triplicates. Paired t- test was used to calculate statistical significance ( Table S2 ). * p < 0.05, ** < 0.01, *** < 0.001 . miR-148a/152 family upregulates OGT expression and is evolutionary conserved The upregulatory miRNA miR-148a-3p belongs to the miR-148/152 family of miRNA which emerged in vertebrates ( 68 ) and consists of miR-148a-3p, -148b-3p and - 152-3p ( Fig. 9A ) ( 63 , 69 ). These miRNA, which differ from one another by only 2-3 bases, are known to be involved in cancer and immune regulation ( 63 , 70 ). All three of these miRNA were hits in our miRFluR assay ( Fig. 2D ) and were observed in CLIP datasets ( 51 , 52 ). Therefore, we tested whether they impacted OGT protein expression in A549 cells. In line with our previous observations for miR-148a-3p, both miR-148b-3p and -152-3p significantly upregulated OGT (∼2-fold, Fig. 9B-C , Fig. S8, Table S2 ). Download figure Open in new tab Figure 9. The miR-148/152 family upregulates OGT expression. (A) Sequence alignment of miR-148/152 family. Conserved nucleotides are shown in blue. (B) Representative Western blot analysis for OGT in A549 treated with NTC (grey) or miR-148/152 family members (blue) as before. (C) Quantification of Western blot analysis for OGT. Bar graphs represent average data from n=4 biological replicates. Western blot samples were normalized first to total protein (Ponceau) and then to the normalized NTC. Individual replicates are indicated as discrete points. Error bars represent standard deviations. Statistical analysis was done using both the one-sample t-test and paired t-test. Highest significance from either test is shown. (D) Sequence alignment of miR-148a-3p, -148b-3p and -152-3p with predicted OGT-3’ UTR sites and their corresponding mutants. Mutated nucleotides (orange) and wobble base pairs (pink) are indicated. Grey box indicates main binding region. (E) Bar graph of data for HEK-293T cells transfected with miR-148a-3p (dark blue), -148b-3p (medium blue) or -152-3p (light blue) with WT (wildtype) or MUT (Mutant) miRFluR sensors. For each sensor, data was normalized over NTC in that sensor. The experiment was performed in biological triplicates. Paired t- test was used to calculate statistical significance ( Table S2 ). * p < 0.05 We next sought to determine binding sites for the miR-148/152 family. CLIP analysis identified two AGO2 binding sites for these miRNA, one canonical and one non-canonical ( Table S6 ). RNAhybrid analysis identified the non-canonical site as the strongest predicted binding site for the miR-148/152 family ( 71 ). This site was also the strongest site identified with the miRanda algorithm ( 72 ). We mutated all interacting base pairs in the site corresponding to the non-canonical site (chrX:71575261-71575284[+]) to the sequence for miR-148a-3p ( Fig. 9D ). We next tested the wildtype and mutant sensors with miR-148a-3p, -148b-3p and -152-3p and NTC mimics in HEK-293T cells ( Fig. 9D-E ). In all three cases, we observed a significant loss of upregulation in the mutant sensor, confirming this as the correct miRNA binding site. Conservation of binding sites is often a hallmark of their biological importance, thus we analyzed whether the miR-148a/152 binding site was conserved in vertebrate evolution. Phylogenetic analysis of ∼80 species from fish to human found that the site appears to have emerged later in evolution, more specifically in placental mammals ( Table S7 ). A more granular analysis of 10 mammalian species found that the site has been conserved for at least 98.7 million years, as it was not seen in the 3’UTR of elephant OGT but is in armadillo ( Fig. 10 ). Overall, our data provides compelling evidence for direct upregulation of OGT by the miR-148a/152 family and sets the stage for further exploration of the emergence of upregulation as a function of miRNA. Download figure Open in new tab Figure 10: Evolutionary conservation of the miR-148/152 site in OGT 3’UTR. Inset shows miR-148a:AGO2 complex identified in CLIP studies (see Table S6 ). Phylogenetic tree of miR-148a-3p binding site in OGT 3’UTR through evolution. The site sequence for different species is mentioned with miRNA binding site represented in purple; non-conserved bases are represented in red. Mya: Million years ago; sp.: species. Phylogenetic tree generated from OneZoom ( www.onezoom.org ) and used with permission ( 99 ). Discussion O-GlcNAc transferase (OGT) is a dynamic regulatory hub that responds to a variety of cellular signals ( 44 , 73 , 74 ). Control over OGT levels, and the resultant levels of O-GlcNAc, requires a high degree of transcriptional and post-transcriptional regulation of the enzyme, including by miRNA ( 34 – 39 , 47 , 48 , 75 – 78 ). Although traditionally thought to downregulate, it has become clear that the impact of miRNA is bidirectional and that upregulation of protein expression is a common occurrence ( 25 , 27 , 79 ). Herein we identify ∼200 miRNA regulators of OGT, including 59 down-miRs and 124 up-miRs using our high-throughput miRFluR assay ( 25 , 27 , 28 , 79 ) ( Fig. 2 , Table S1, Dataset S1 ). Of note, our hitlist included 5 known down-miRs and AGO2 binding sites for 32 of our hits (17 down-miRs, 15 up-miRs) were previously identified by CLIP data ( Dataset S2 ). In our validation experiments using both miRNA mimics and inhibitors of endogenous miRNA, we found that down-miRs had more context dependent effects on OGT levels than up- miRs. Cell line variability was observed even for miR-7-5p, a known regulator. This is in line with the cell line dependency observed for other miRNA regulatory interactions ( Fig. 3 ) ( 25 , 27 , 56 , 79 ). Overall, our work showcases the bidirectionality of miRNA’s impact on OGT. The regulation of O-GlcNAc is complex, responding to OGT and OGA levels as well as changes in the hexosamine biosynthetic pathway, thus it was unclear whether miRNA that regulated OGT would have a direct impact on O-GlcNAc levels ( 13 ),( 44 ),( 11 ). There is strong evidence that the levels of OGA and OGT can be coupled ( 80 – 82 ). In this work, we found that the miRNA impacting OGT, did not impact OGA and yet directly effected O-GlcNAc levels in line with the effects on OGT ( Fig. 5 ). However, we only tested a subset of the miRNA from our hitlist, thus it is possible that other miRNA may co-regulate the two genes. Analysis of this will require mapping of the miRNA regulation of OGA, a subject of future work. OGT is a highly conserved gene ( 17 – 19 ). One third of miRNA families are highly conserved across species ( 83 ), with 60% of miRNA loci conserved between humans and mice ( 84 ). The let-7 family, several members of which inhibited OGT in our assay, is one of the earliest miRNA families to emerge in evolution. Both let-7a-2-3p and let-7g-3p inhibited OGT expression through seed-dependent binding ( Figs. 7 & 8 ). Strong regulation by these miRNA required two canonical binding sites, one at chromosomal position chrX: 70,793,730 (1771 site) and the other at position chrX: 70,794,824 (2878 site) within the human 3’UTR for OGT. Analysis of their conservation found that the 1771 site emerged in placental mammals, with evidence for it in elephants, but not in opossum ( Table S4 ). The 2878 site, however, is far more recent, with evidence for it in primates, but not other mammals ( Table S5 ). Tight regulation of OGT expression required both binding sites ( Figs. 7 & 8 ). This binding interaction may be related to the roles of both OGT and let-7 in human health, most notably type 2 diabetes which emerged in primates and thus is an evolutionarily recent disease ( 85 ). Both, OGT and let-7a are known to play key roles in the metabolic pathways underlying diabetes. However, the precise role of OGT and O-GlcNAc in formation of type-II diabetes is still unclear ( 86 , 87 ). Deletion of OGT in islet β-cells causes severe hyperglycemia, glucose intolerance and severe diabetes in mice ( 14 ) and O-GlcNAc positively regulates the secretion of insulin ( 88 , 89 ). O-GlcNAc levels are closely tied to glucose levels and may also play a role in downstream damage from diabetes ( 86 , 87 ) ( 90 , 91 ). The let-7 family, including let-7a/g is known to regulate multiple proteins underlying glucose metabolism, including the insulin receptor ( 92 ). Knockdown of let-7 improved insulin resistance in obese mice ( 93 ). Although the importance of let-7a/g regulation of OGT in glucose metabolism is not known, the evolutionary appearance of the site and the regulatory roles of both the miRNA and the gene are intriguing. Unlike the let-7 family, the miR-148/152 family emerged later in evolution, first appearing in jawless fish ( 94 ). All three members of the miR-148/152 family (miR-148a-3p, -148b-3p and -152-3p) upregulated OGT expression. Unlike the let-7a/g-3p sites, the miR-148/152 binding site validated by mutational analysis was identified in CLIP pulldowns of AGO2 ( Table S6, Dataset S2 ). The site was non-canonical and emerged in placental mammals, with evidence of it in armadillo but not in elephants ( Fig. 10 , Table S7 ). In line with the emergence of this site, evidence suggests that the miR-148/152 family is involved in regulation of placental development during pregnancy ( 95 ). These miRNA are upregulated in pre-eclampsia, which is predominantly characterized by hypertension.( 96 ) In a recent paper, both OGT and O-GlcNAc were shown to be upregulated in the placentas of women with hypertensive pregnancies ( 97 ). Taken together, our data provides important insights into OGT, miRNA regulation and the potential evolution of disease mechanisms through dysregulation of both up- and downregulatory miRNA interactions. Experimental Procedures Cloning OGT 3’ UTR (ENST00000373719.3) was amplified from cDNA (HEK-293T cell line) using Q5 High-Fidelity DNA Polymerase (Catalog # M0492L, New England Biolabs (NEB)) according to the PCR conditions provided by NEB, using the primers shown in Table S3 . NheI and BamHI restriction sites were used for cloning the OGT 3’ UTR downstream from Cerulean in the pFmiR-empty backbone( 28 ) using the standard NEB ligation protocol. The cloned sequence was verified by Sanger Sequencing (Molecular Biology Services Unit, University of Alberta). NucleoBond Xtra Maxi EF (Ref. 740424.50, Macherey-Nagel) was used for large scale endotoxin free DNA preparation of the verified plasmid-pFmiR-OGT. The plasmid map for pFmiR-OGT and its corresponding 3’ UTR can be found in Figs. S1 & S2 . Cell lines All cell lines (HEK-293T, A549 and Caco-2) were purchased from the American Type Culture Collection (ATCC) and cultured in suggested media (HEK-293T in DMEM-Dulbecco’s Modified Eagle medium (DMEM) supplemented with 10% Fetal Bovine Serum (FBS); A549 in FK-12 medium supplemented with 10% FBS and Caco-2 in DMEM supplemented with 20% FBS) under standard conditions (5% CO2 at 37°C). All the cells were used below passage 20. miRFluR High-throughput assay The Human miRIDIAN miRNA mimic library version 21.0 (Dharmacon, v. 21) was resuspended in ultrapure nuclease-free water (REF. #: 10977-015, Invitrogen) and aliquoted into black 384-well Flat Clear Bottom Black TC-treated Microplates (Product Number: 3764, Corning). Each miRNA was aliquoted in triplicate (2 pmol/well) together with six wells of Non-Targeting Control (NTC, CN-001000-01, Horizon Discovery). 25ng of pFmiR-OGT sensors (wild-type and mutant) diluted in 5µL of Opti-MEM (Gibco) was added per well. 0.1µL of Lipofectamine 2000 Transfection Reagent (Catalog# 11668500, Invitrogen) in 5µL of Opti-MEM (pre-incubated at room temperature for 5 min) was added per well. The plates were then spun down at 300rpm for 30 seconds using Centrifuge 5430 (Eppendorf). The plates with the solutions were incubated at room temperature for 20 min (minutes). 25µL of HEK-293T (4 x 10 5 cells/mL prepared in phenol red free DMEM supplemented with 10% FBS, 10-25µL/10mL penicillin-streptomycin) was added per well after the 20 minute incubation. Plates were then incubated in incubator under standard conditions for 48 h. The fluorescence signals of Cerulean (Excitation: 433nm; Emission: 475nm) and mCherry (Excitation: 587nm; Emission: 610nm) were measured using the Synergy H1 microplate reader (BioTek) with the Gen5 software (version 3.08.01) at 48 h. The assay was done in duplicate. Data analysis of High-Throughput miRFluR assay The ratio of fluorescence signal from Cerulean and mCherry (Cer/mCh) for each well in individual plate was calculated. For each miRNA, the values of the ratios were averaged across wells and the standard deviation (S.D.) calculated. The % error of measurement (100 x S.D./mean), % error) was calculated for each miRNA. Plates where the mean % error was >15% were removed. We also removed miRNA with >15% error. As we ran the assay in duplicate, we averaged the values for miRNA that passed QC in both datasets and included any miRNA that passed QC in either dataset. Post QC, this resulted in 2215 miRNAs of the 2601 miRNAs screened. The mean Cer/mCh ratio for individual miRNA was normalised to the mean Cer/mCh ratio for the NTC within the same plate and S.D. were used to propagate the error. The z-score (±1.65), corresponding to a two -tailed p -value of 0.05, was used as a threshold for significance. Post-analysis we identified 183 miRNA hits for OGT within 90% confidence interval (see Fig. 2B-D , Table S2 and Dataset S1). Western blots Western blot analysis was conducted for OGT in two cell lines: A549 and Caco-2. 3 x 10 5 target cells were seeded in six-well plates and cultured for at least 24 h in their respective media. For miRNA mimic transfection, 50nM mimic (Dharamcon, Horizon Discovery), 5µl lipofectamine 2000 (Life technologies) in 250µl OptiMEM (Gibco) were used to make lipid droplets and spread drop by drop on the cells (without changing media). The media was changed to standard media 16 h post-transfection. The cells were harvested 72 h after transfection by placing the dishes on ice. Cells were then washed with ice cold Hanks buffered salt solution (HBSS, Gibco); RIPA lysis buffer (89900, Thermo Scientific) supplemented with protease inhibitor (HALT Proteinase and Phosphatase inhibitor cocktail Cat.78446, Thermofisher) was used for cell lysis. Lysed cells were incubated on ice for 20 min, followed by centrifugation at 14,000 rpm for 15 min at 4 °C and keeping the supernatant. Protein concentration of the supernatant was determined using Bio-Rad Protein Assay (Bio-Rad Laboratories, Inc., USA), 20 μg of protein was run on 10% gels (SDS-PAGE) for OGT and 8% for O-GlcNAc using standard conditions. Proteins were then transferred to iBlot2 Transfer Stacks (nitrocellulose, Invitrogen, catalog number: IB23002) using the iBlot2 transfer device (Invitrogen, standard protocol-P0). Transferred membranes were incubated with Ponceau S solution (Boston BioProducts, catalog #ST-180) for 5 min and the whole blot was imaged using protein gel mode (Azure 600, Azure Biosystems Inc.). Ponceau staining was removed by washing the membrane with TBS buffer. Blots were blocked using 5% non-fat dry milk in TBST buffer (TBS buffer supplemented with 0.1% Tween 20) for 1 hour at 60 rpm on shaker (LSE platform rocker, Corning) at room temperature. Blots were further subjected either OGT-O linked N acetylglucosamine transferase primary antibody (α-OGT, Abcam, AB96718-1:1000 in 5% BSA in TBST), O-GlcNAC-O linked N acetylglucosamine RL2 primary antibody (α-OGlcNAc, Abcam, AB2739 1:1000 in 5% BSA in TBST) or OGA-O linked glucosaminase primary antibody (α-OGA, Thermo, 61425, 1:1000 in 5% BSA in TBST), overnight at 4°C. Note, the OGT and OGA antibody was validated using siOGT and siOGA, respectively (Horizon Discovery, Figs. S3E-F & S5G-H ). After an overnight incubation, the blots were washed 5X for 2 min each with 0.1% TBST buffer on a reciprocating shaker. Membranes were incubated with the appropriate secondary antibody, goat anti-mouse IgG-HRP (α-OGlcNAc, Jackson laboratory) or anti-rabbit IgG-HRP (α-OGT, α-OGA, 1:10,000, Jackson laboratory), for 1 hour with shaking (60 rpm) at room temperature. Membranes were then washed 3 x with 0.1% TBST buffer and were developed using Clarity and Clarity Max Western ECL substrate according to the manufacturer’s protocol (Bio-Rad). Membranes were imaged using chemiluminescent mode (Azure 600, Azure Biosystems Inc.). Data analysis of Western blot Western blots were quantified using ImageJ software (ImageJ 1.54g, Java 1.8.0_345).( 98 ) For each lane, signal was normalized to the Ponceau for that lane. For each blot the Ponceau normalized signal for miRNA mimics was divided by the NTC to give the normalized signal shown in all graphs. We tested for statistical significance using two different statistical tests: the one-sample t -test against NTC=1 and the paired t -test comparing Ponceau normalized NTC to miR for each blot ( Table S2 ). Transient transfection, endogenous miRNA activity validation miRIDIAN microRNA hairpin inhibitors anti-miRs: (-let7a-2-3p, -miR-7-5p, -20a-3p, -148a-3p, -302b-3p) and miRIDIAN microRNA hairpin inhibitor negative control (α-NTC, cat.#: IN-001005-01) were purchased from Dharmacon (Horizon Discovery, Cambridge, UK). The selected anti-miRs for OGT protein were tested in A549 and Caco-2 cell line. Cells were seeded and incubated as previously described. Cells were transfected with anti-miR (50 nM, using Lipofectamine™ 2000 transfection reagent in OptiMEM following the manufacturer’s instructions (Life Technologies)). After 16 h, media was changed to standard culture media. Cells were lysed 72 h post-transfection and analyzed for OGT protein levels as described in Western blot analysis. All analysis was done in at least biological triplicate. Site Directed Mutagenesis The OGT 3’ UTR and the miRNA (let-7a-2-3p, -7g-3p and miR-148a-3p) sequences were uploaded and analyzed by RNAhybrid( 71 ) or Targetscan.( 22 ) The prediction with the least energy and the second least energy (optional) were identified in the OGT 3’UTR sequence as targets for the mutagenesis in pFmiR-sensors. Based on the prediction, primers were designed using the NEBChanger tool (version v2.5.1, New England Biolabs (NEB)) ( Table S3 ), and were ordered from Integrated DNA Technologies (IDT). The pmiR-OGT 3’ sensor was mutated using Q5 site-Directed Mutagenesis Kit (Catalog # E0554S, NEB). Plasmid isolated from the colonies of the mutagenesis (Catalog # KTS1015, Truin Science) were screened by Sanger sequencing at Molecular Biology Facility (MBSU, University of Alberta) and confirmed by whole plasmid sequencing (Plasmidsaurus). Endotoxin free maxiprep samples of the confirmed mutants were prepared with the NucleoBond Xtra Maxi EF (Ref. 740424.50, Macherey-Nagel), which were used in the miRFluR High-throughput Assay for RNA:miRNA site confirmation. A minimum of 4 wells were transfected per sensor and the analysis was done in 3 independent experiments. Data availability The authors declare that all data can be found in this document and its supporting files. Supporting Information This article contains supporting information: Figs. S1-S8 Tables S1-S7 Datasets S1-S2 (separate Excel files) Author contributions Conceptualization: Z.A.S., L.K.M.; Methodology: Z.A.S., F.J.C., C.T., L.K.M.; Investigation: Z.A.S., H.N; Validation: Z.A.S., H.N.; Formal Analysis: Z.A.S., H.N., L.K.M.; Visualization: Z.A.S., H.N., L.K.M.; Writing-Original Draft: Z.A.S., L.K.M; Supervision: L.K.M. Funding and additional information Funding for L.K.M. comes from the Canada Excellence Research Chairs Program (CERC in Glycomics). Figs. 1 and 2 were made using BioRender. Conflict of Interest The authors declare no competing interests. Abbreviations The abbreviations used are as follows: OGT: O-GlcNAc transferase; OGA: O-GlcNAcase; AGO2: Argonaute 2; 3’UTR: 3’-untranslated regions; mRNA: messenger ribonucleic acid; microRNA, miRNA, miR: micro ribonucleic acid; siRNA: small interfering RNA; NTP: non-targeting control pool; NTC: non-targeting control, down-miR: downregulatory miRNA; up-miR: upregulatory miRNA; WT: wildtype; MUT: mutant; SDS-PAGE: sodium dodecyl sulfate polyacrylamide gel electrophoresis; PCR: polymerase chain reaction. Acknowledgements We thank Dr. Dawn Macdonald and Helia Dehghan Harati for providing comments on this manuscript. Funder Information Declared Canada Excellence Research Chairs, https://ror.org/02tvrwm90 , CERC in Glycomics References 1. ↵ Bond , M. R. , and Hanover , J. A . 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