Treatment of human airway epithelial Calu-3cells with a peptide-nucleic acid (PNA) targeting the microRNA miR-101-3p is associated with increased expression of the cystic fibrosis Transmembrane Conductance Regulator (CFTR) gene

Enrica Fabbri, Anna Tamanini, Tiziana Jakova, Jessica Gasparello, Alex Manicardi, Roberto Corradini, Alessia Finotti, Monica Borgatti, Ilaria Lampronti, Silvia Munari, Maria Cristina Dechecchi, Giulio Cabrini, Roberto Gambari

ABSTRACT

Since the identification of microRNAs (miRNAs) involved in the regulation of Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) gene, miRNAs known to downregulate the expression of the CFTR and associated proteins have been investigated as potential therapeutic targets. Here we show that miR-101-3p, targeting the 3’-UTR sequence of the CFTR mRNA, can be selectively inhibited by a peptide nucleic acid (PNA) carrying a full complementary sequence. With respect to clinical relevance of microRNA targeting, it is expected that reduction of concentration of miRNAs (the anti-miRNA approach) could be associated with increasing amounts of target mRNAs. Consistently to this hypothesis, we report that PNA-mediated inhibition of miR-101-3p was accompanied by CFTR up-regulation. Next Generation Sequencing (NGS) was performed in order to verify the effects of the anti-miR-101-3p PNA on the Calu-3 miRNome. Upon inhibition of miR-101-3p we observed a fold change (FC) expression <2 of the majority of miRNAs (403/479, 84.13%), whereas we identified a list of dysregulated miRNAs, suggesting that specific miRNA inhibition (in our case miR-101-3p) might be accompanied by alteration of expression of other miRNAs, some of them known to be involved in Cystic Fibrosis (CF), such as miR-155-5p and miR-125b-5p.

Key words: Peptide nucleic acids; cystic fibrosis; microRNAs; miR-101-3p; miRNA targeting; delivery; CFTR.

1. Introduction

Among the several regulatory networks controlling gene expression, those regulated by non-coding RNAs appear to be of great interest and involve possible novel molecular targets for therapeutic interventions. Among non-coding RNAs, microRNAs (miRNAs) (exhibiting a length comprised between 19 to 25 nucleotides) are key players. They interact with mRNAs by recognizing the 3’-UTR region at the level of the RNA-induced silencing complex (RISC), causing translational repression or mRNA degradation [1,2]. Depending on these mechanisms of action, miRNAs regulate complex biological functions, such as differentiation, cell cycle and apoptosis [3,4].
Cystic Fibrosis (CF) is the most common life-threatening rare disease among Caucasians, occurring in approximately one in 3,000–4,000 live birth and caused by genetic defects of the CF Transmembrane Conductance Regulator (CFTR) gene [5]. In the field of translational research on CF, miRNA-based regulation of the expression of the CFTR gene and of CFTR-regulators has been recently demonstrated [6-15] (Table I). In this respect, miR-101-3p is one of the validated microRNAs controlling CFTR gene expression [7,11-13]. For instance, Hassan et al. reported that miR-101-3p regulates the expression of the CFTR in the lung [7]. When a miR-101-3p precursor was transfected to human airway epithelial cells, it directly targeted the 3'-UTR of the CFTR mRNA and suppressed the expression of the CFTR protein. Interestingly, miR-101-3p is also deeply involved in CFTR regulation in lung samples from patients with severe chronic obstructive pulmonary disease (COPD), where this microRNA is overexpressed when compared to control patients [7]. This leads to a suppression and/or down-regulation of CFTR. Interestingly, Megiorni et al. found a synergism between miR-101-3p and miR-494 in post-transcriptional regulation of the CFTR gene [13]. The effect on CFTR was supported by the finding that both miR-101 and miR-494 mimics significantly inhibited the expression of a reporter construct containing the 3'-UTR of CFTR in luciferase assays. Moreover, a miR-101/miR-494 combination was able to markedly suppress CFTR activity, to an extent higher than that found in the case of treatments with single miRNAs [13]. According to this report, aberrant expression and function of miRNAs might explain the wide phenotypic variability observed among CF patients. This opens new avenues in the field of precision medicine in CF, i.e. the targeting of overexpressed miRNAs, providing that a careful analysis of their expression pattern is performed. This is particularly important in CFTR gene regulation, since CFTR mRNA is potential target of several microRNAs, including miR-433-3p, miR-509-3p, miR-335-5p, mir-132-3p, miR-101-3p, miR144-3p, miR-494-3p, miR-223-3p, miR-145-5p (see Table I) [14,15]. Furthermore, microRNAs have been suggested to negatively regulate the expression of several genes coding proteins stabilizing CFTR on the apical membrane of bronchial epithelial cells [16-19]. For instance, the Na(+)/H(+) Exchange Regulatory Factors 1 (NHERF1) [16] and 2 (NHERF2) [17] interact with the cytoskeleton via ezrin [18,19], suggesting that they may help in anchoring CFTR to the cytoskeleton at the apical membrane. In addition to miRNAs binding to the 3’-UTR of CFTR mRNA, Table I shows examples of miRNAs regulating NHERF1, NHERF2 and ezrin mRNAs [14,15]. Finally, in addition to miRNAs targeting CFTR and CFTR regulators, the expression of other miRNAs is altered in CF (see Table II for a partial list) [7-13, 20-33].
In the field of therapeutic molecules targeting microRNAs, Peptide Nucleic Acids (PNAs) have been described as DNA analogues exhibiting several properties of great interest in translational research [34-40]. Despite a radical structural change with respect to DNA and RNA, as they incorporate a backbone constituted of N-(2-aminoethyl)glycine units that replaces the natural ribose/phosphate polymer, PNAs are capable of an efficient sequence-specific hybridization with complementary DNA and RNA, generating WatsonCrick double helices [34-36]. In addition, they are able to participate in triple helix structures with double stranded DNA and to perform strand invasion [37]. Accordingly, PNAs have been extensively used for in vitro and in vivo pharmacologically-mediated alteration of gene expression [35,38-40]. For instance, PNA and PNA-based analogues have been proposed as antisense molecules targeting mRNAs, artificial promoters, triplehelix forming molecules targeting eukaryotic gene sequences, decoy molecules targeting transcription factors [39,40]. Recently, PNAs have been demonstrated to be a very efficient tool to alter the biological functions of microRNAs. This has been firmly demonstrated in studies conducted both in vitro and in vivo [41-48].
Concerning PNA-based targeting of miRNAs involved in the post-transcriptional regulation of the expression of CFTR, we recently reported that a PNA directed against miR-145-5p inhibits biological functions of this miRNA and up-regulates CFTR expression [49]. This finding was confirmed by another research group in CF tissues [50]. This is relevant, considering the increasing interest in RNA-targeting therapies for CF [51-55].
The objective of this paper is to verify whether down-regulation of miR-101-3p by a PNA molecules could alter/modulate CFTR expression. Specific down-regulation of miR101-3p was achieved with a PNA carrying a R8 poly-arginine motif to facilitate its uptake inside target cells. We then verified whether this was associated with increased expression of CFTR.

2. Results

2.1. Presence of miR-101-3p binding sites within the CFTR 3’-UTR mRNA sequences

Fig. 1A shows the location of the miR-101-3p binding site within the CFTR 3’-UTR mRNA sequence, obtained by performing the analysis employing RNAhybrid, a tool for finding the minimum free energy hybridization of a short sequence RNA to the best fitting The the 3’-UTR of the CFTR mRNA.

2.2. PNAs targeting miR-101-3p

The PNAs utilized in this study (Fig. 1C) were designed according to our standardized protocols [56] based on the following criteria: (a) a short 18-base-pairs length allowing efficient synthesis also on large scale; (b) lack of self-complementarity, both in antiparallel and parallel orientation; (c) minimal length of complementary sequences in mRNAs, as evaluated by BLAST search within the full transcriptome; (d) when possible, targeting the “seed region”, which is an essential element for miRNA function. A carrier octarginine R8 peptide was conjugated at the N-terminus of the PNA chain to increase the delivery efficiency, that allows the uptake of R8-PNA in about 100% of the cells, as elsewhere published [44,46]; this conjugation is easily realized during PNA solid-phase synthesis using the same reagents and solvents.
Concerning efficiency and specificity of PNA-miRNA interactions, we like to underline that (a) only PNAs with strong self-complementarity could fail to bind their target mRNAs, and (b) the efficiency of binding of PNAs with target RNAs is so high that they are even able to disrupt RNA secondary structures. Therefore, rather than efficiency of PNA/RNA interaction, we focused on sequence-specificity.
To this aim, a control PNA (R8-PNA-a101-MUT) was obtained by scrambling the position of 4 nucleobases, thus leaving the same base composition of the two PNAs. Mutated sequences were also analyzed using BLAST search to assess possible interactions with undesired mRNAs. As reported in Fig. 1C (showing the sequences of PNA selected in the present study) R8-PNA-a101-5p displays a fully complementary sequence with the miR-101-3p, while the R8-PNA-a101-MUT contains four scrambled changes, that are known to suppress the hybridization, as shown by circular dichroism and analysis of melting temperatures [57], by arrested RT-qPCR [58] and by SPR-based biospecific interaction analysis (BIA) [59]. As reported in several manuscripts, like PNAs and PNA-DNA chimeras, these R8-PNA-based molecules are resistant to degradation not only in cellular systems in vitro, but also in several biological fluids analyzed in vivo [6063].

2.3. R8-PNA-a101 inhibits miR-101-3p

In the experiment depicted in Fig.2A, human airway epithelial Calu-3 cells [64] were cultured for 72 hours in the presence of increasing amounts of R8-PNA-a101 (0.5, 1, 2 and 4 µM). The cells were then harvested, RNA isolated and RT-qPCR performed using primers amplifying miR-101-3p. The results obtained indicate an inhibitory effect on miR101-3p specific hybridization when 2 and 4 µM concentrations have been utilized (Fig.2A). Starting from this piece of information, 4 µM concentration was chosen and its inhibitory activity on miR-101-3p demonstrated to be statistically significant in four independent treatments of Calu-3 cells for 72 hours (Fig.2B). These experiments support the concept that treatment of Calu-3 cells with the R8-PNA-a101 leads to miR-101-3p inhibition.
In order to verify sequence-specificity of this effect the scrambled mutant R8-PNAa101-MUT was employed (see Fig.1C for sequence and comparison with the R8-PNAa101). When Calu-3 cells were treated with the R8-PNA-a101 and the R8-PNA-a101-MUT molecules (both administered for 72 hours at 4 µM concentration), a clear-cut result was obtained and depicted in Figure 2C. While treatment of Calu-3 cells with R8-PNA-a101 leads to a sharp inhibition of miR-101-3p RT-qPCR signals (black box), as also reported in Fig.2B, the mutant R8-PNA-a101-MUT displayed no inhibitory effects (gray box).
A further representative experiment confirming sequence-specificity of the effects is reported in Supplementary Figure S1. The RT-qPCR signals for other miRNAs expressed in Calu-3 cells (i.e. miR-335-5p) were unchanged following 72 hours treatment with 4 µM R8-PNA-a101, supporting the conclusion that the effect of R8-PNA-a101 is fairly specific.
Conversely, preferential inhibition of miR-335-5p was obtained following treatments of Calu-3 cells with a PNA targeting miR-335-5p (R8-PNA-a335, 4 µM). Altogether, the experiments shown in Fig.2C and supplementary Fig.S1 support the conclusion that the effects of R8-PNA-a101 on miR-101-3p are sequence-specific.

2.4. Effects of the R8-PNA-a101 on CFTR mRNA and protein

When Calu-3 cells were cultured in the presence of 4 µM R8-PNA-a101 for 72 hours, a clear effect was observed on CFTR gene expression, after RNA and protein isolation, following analysis using RT-qPCR and Western Blotting approaches. In fact, CFTR gene expression was found to be sharply increased (Figure 3, A-C) when analysis was performed using RT-qPCR (Figure 2A) and Western blotting (Figure 3, B and C). Figure 3A shows the increase of CFTR mRNA content when Calu-3 cells were treated with the R8-PNA-a101 (but not with R8-PNA-a 101-MUT). The Western blotting experiments (Figure 2, B and C) indicate that the R8-PNA-a101 is efficient in causing an increase of CFTR protein, in agreement with the RT-qPCR data shown in panel A of the same Figure.
We previously observed that PNAs against miR-145 and miR-494 were able to increase CFTR protein expression by 1.5-2 folds with respect to the constitutive levels [49]. In this respect, the R8-PNA-a101 seems definitely more potent than R8-PNA-a145 and other PNAs targeting microRNAs miR-433, miR-494 and miR-509, being the induced CFTR/βactin ratio 3-fold higher than the constitutive expression (Figure 3D). The results reported in Figure S2 (Supplementary data) demonstrate that the PNA tested in these experiments did not exhibit antiproliferative effects and did not reduce the extent of viable Calu-3 cells. Concerning the effect on apoptosis, the PNA retained only a limited pro-apoptotic activity when compared to the validated pro-apoptotic compound Stattic (Selective STAT3 inhibitor).

2.5. R8-PNA-a101 treated Calu-3 cells: miRNome profile studied by next-generation sequencing (NGS)

Despite the fact that treatment of Calu-3 with R8-PNA-a101 leads to a sharp inhibition of miR-101-3p (Figure 2, A and B) and a lower effect on other miRNAs (i.e. miR335, see Figure S1), we were interested in verifying the effects of PNA treatment on the overall miRNome, in order to obtain information on the specificity of the effects of the treatment. To this aim RNA extracted from Calu-3 cells, either untreated or treated with the R8-PNA-a101 for 48 hours was analyzed by NGS, using the Illumina NextSeq500 platform and NextSeq® 500/550 High Output Kit v2 (see the Materials and methods section). By the small RNA-Seq approach thousands of small RNA and miRNA sequences can be analyzed with unprecedented sensitivity and dynamic range. In particular, differential expression of all small RNAs in any sample can be measured and variations can be characterized without prior sequence or secondary structure information.

3. Discussion

Since the identification of the (miRNAs) involved in the regulation of CFTR gene [611], miRNAs known to down-regulate the expression of the CFTR and associated proteins have been investigated as potential therapeutic targets. For instance, PNA-mediated inhibition of miR-145-5p (which down-regulates CFTR) leads to CFTR increase in the Calu-3 model system [49].
The results here described show that miR-101-3p, targeting the 3’-UTR sequence of the CFTR mRNA [7,11,13] can be selectively inhibited by a PNA carrying a full complementary sequence. With respect to clinical relevance of microRNA targeting, it is expected that decreased availability of miRNAs (anti-miRNA approach) is associated with an accumulation of target mRNAs and/or increase of the encoded protein; conversely, increased expression of miRNAs (miRNA mimicking/replacement strategy) is expected to decrease the expression of the target mRNAs [49]. In this context Peptide Nucleic Acids [34] represent molecules with antimiRNA activity [44-49]. Our data sustain this concept, demonstrating up-regulation of CFTR following PNA-mediated inhibition of miR-101-3p (Figure 3).
While the results here presented are a strong proof-of-principle that PNA-based targeting miRNAs regulating CFTR might lead to CFTR up-regulation, several
considerations should be discussed. First of all, as for other mRNAs, CFTR is regulated by several miRNAs [14,15]. Therefore, targeting other miRNAs might lead to even more efficient up-regulation of CFTR. Second, possible combined effects of PNAs targeting different miRNAs involved in CFTR regulation should be in the future considered in order to obtain the highest level of CFTR induction. Third, our observations should be confirmed in CF cellular model systems.
Another important conclusion derived from the results here presented is that the miRNome is to some extend affected by the treatment of target cells with anti-miRNA PNAs. Despite the fact that the majority of miRNA (more than 84%) display low FC values after R8-PNA-a101 treatment of Calu-3 cells (FC < 2), the results depicted in Figure 4 show that some miRNAs are up-regulated and some miRNAs are down-regulated
following this treatment. Interestingly, most of the PNA-dysregulated miRNAs are different when different PNAs are employed. For instance, when we compare the list of miRNAs displaying FC>3 in cells treated with R8-PNA-a101 (Figure 4) and R8-PNA-a145 [67], only 6 miRNAs were found in common, while the majority (24 for R8-PNA-a101 and 18 for R8PNA-a145) were found specifically dysregulated for each PNA-based treatment. This finding supports the concept of a sequence-selectivity of the PNA-treatments targeting specific microRNAs. This is extensively discussed in the companion paper by Gasparello et al. [68].
While the miRNAs specifically modulated by the R8-PNA-a101 are only a large minority of the overall Calu-3 expressed miRNAs detectable by the NGS approach, our data sustains the concept that selective miRNA inhibition (in our case inhibition of miR101-3p) might be accompanied by co-inhibition of other miRNAs (for instance miR-155-5p and miR-125b-5p). This might be of great interest in using one PNA molecule affecting different miRNAs, either directly (miR-101-3p) or indirectly (miR-155-5p and miR-125b-5p, see Figure 5). This modulation deserves further studies, since all these miRNAs are involved in Cystic Fibrosis.
While the mechanism of action of miR-101-3p on miR-155-5p and miR-125b-5p expression remains to be elucidated, we would like to comment that miR-miR-155-3p is responsible for hyperactivating IL-8, thereby promoting CF inflammation [25]. Therefore, PNA-mediated targeting of miR-101-3p in Calu-3 cells is expected to lead, in addition to up-regulation of CFTR (Figure 3) down-regulation of IL-8, possibly combining two activities of great interest in CF therapy, i.e. CFTR modulation and anti-inflammatory effects. Considering the effect of the R8-PNA-a101 on miR-155-5p and miR-125b-5p, two additional mechanisms can be hypothesized (summarized in Figure 6): (a) an upregulation of NHERF2, mediated by the decrease of miR-155-5p and miR-125b-5p [14,15] and (b) an up-regulation of TCF4 [65] (caused by a decrease of miR-155-5p), which, in addition to CFTR up-regulation [66], is a potent repressor of another CFTR-regulating miRNA, miR-145 [69]. In this specific case, down regulation of miR-145 might lead to increased expression of CFTR as recently published by our research group, using a PNA targeting miR-145 [49] (see Figure 6).
Despite the fact that the hypothesis depicted in Figure 6 should be experimentally validated in each presented step, this study is the proof-of-principle that miRNA targeting might increase CFTR expression. In this regulatory network the participation of miRNAs/transcription factors interactions appears to be of great interest and impact, deserving further studies.
With respect to a possible miRNA-based therapeutic option in CF, our results are of interest for the personalized therapy of CF, which is characterized by more than 300 CFTR disease-causing mutations (www.genet.sickkids.on.ca/cftr/) [70]. In consideration of the different mutations of the CFTR gene, targeting miR-101-3p could be useful for type IV (less function), V (less protein) and VI (less stable protein) CFTR defect. For CFTR defects such as type I (no protein), II (no traffic), III (no function) miR-101-3p targeting may be however considered in combination with other therapeutic protocols based on the use of CFTR correctors [70-73].

4. Material and Methods

Synthesis and Characterization of PNAs. The synthesis and characterization of anti-miR-101 PNAs were similar to those previously reported by Brognara et al. [46]. The synthesis was performed utilizing a standard Fmoc-based automated peptide synthesizer (Syro I, MultiSynTech GmbH, Witten, Germany), using a ChemMatrix-RinkAmide resin loaded with Fmoc-Gly-OH (0.2 mmol/g) as first monomer and commercially available monomers (Link Technologies, Bellshill, UK) with HBTU/DIPEA coupling. Efficient cleavage from the solid support was obtained with 10% m-cresol in trifluoroacetic acid, followed by precipitation and washings with diethyl ether. Purification was performed by HPLC using a Phenomenex Jupiter RPC1, (250- 4.6mm, 1.7μm) column. Gradient: 100% A for 5 minutes, then from 0% to 50% B in 30 minutes at 0.25 mL/min flow (A: water + 0.1% trifluoroacetic acid; B: acetonitrile + 0.1% trifluoroacetic acid). After purification the PNAs identity and purity were confirmed by UPLC/ESI-MS, (Waters Acquity ultra performance LC HO6UPS-823M, with Waters SQ detector equipped with Waters UPLC BEH C18, 50×2.1 mm, 1.7 µm) at 35°C. A flow rate of 0.25 ml/min was used with the following solvent systems: (A): 0.2% FA in H2O and (B): 0.2% FA in MeCN (FA = formic acid). The column was flushed for 0.9 min with solvent A, then a gradient from 0 to 50% B in 5.7 min was used.
The concentration of the PNA was calculated using UV-absorbance at 260 nm assuming an additive contribution of nucleobases. The syntheses and characterizations of R8-PNA-a145, R8-PNA-a509, R8-PNA-a494, R8-PNA-a433 were reported elsewhere [49]. The UPLC-ESI/MS analysis of R8-PNA-a101 and R8-PNA-a101-MUT, and the characterization of R8-PNA-a335 are reported in Supplementary data (Fig.S4 and Fig.S5, respectively).
R8-PNA-a101: sequence H-R8-AGTTATCACAGTACTGTA-Gly-NH2 UPLC/ESI-MS Rt= 2.67 min, calculated MW: 6200.34 g/mol; m/z found (calculated): 1241.0 (1241.07) [MH5]5+, 1034.4 (1034.39) [MH6]6+, 886.8 (886.73) [MH7]7+, 776.0 (776.04) [MH8]8+, 690.0 (689.93) [MH9]9+, 621.0 (621.03) [MH10]10+. R8-PNA-a101-MUT: sequence H-R8-AGTAATCTCAGGACTTTA-Gly-NH2 (mutations underlined); UPLC/ESI-MS Rt= 2.76 min, calculated MW: 6200.34 g/mol; m/z found (calculated): 1240.89 (1241.07) [MH5]5+, 1034.24 (1034.39) [MH6]6+, 886.73 (886.73) [MH7]7+, 775.88 (776.04) [MH8]8+, 689.94 (689.93) [MH9]9+, 621.02 (621.03) [MH10]10+.
Culture Conditions. Calu-3 cells [55] were cultured in humidified atmosphere of 5% CO2/air in DMEM/F12 medium (Gibco, Grand Island, US) supplemented with 10% fetal bovine serum (Biowest, Nauillè, Francia), 100 units/ml penicillin and 100 mg/mL streptomycin (Lonza, Verviers, Belgio) and 1% NEEA (100X) (Non-Essential Amino Acids Solution; Gibco). To determine the effect on proliferation, cell growth was monitored by determining the cell number/ml using a Z2 Coulter Counter (Coulter Electronics, Hialeah, FL, USA).
RNA Extraction. Calu-3 cells were trypsinized and collected by centrifugation at 1,500 rpm for 10 minutes at 4°C. The cellular pellets were washed twice with PBS and lysed with the Tri-Reagent (Sigma Aldrich, St. Louis, Missouri, USA). RNA extraction was conducted following the manufacturer’s instructions and the isolated RNA was washed once with cold 75% ethanol. After this washing step, the RNA was dried and dissolved in nuclease free pure water and considered ready for the use.
Quantitative Analyses of miRNAs. For miRNA quantification using real-time RTqPCR reagents, the primers and probes (Assay name:hsa-miR-335-5p, TM:000546; Assay name:hsa-miR-101-3p, TM:002253; Assay name:hsa-miR-125b-5p, TM:000449; Assay name:hsa-miR-155-5p, TM:002623) were obtained from Applied Biosystems. The TaqMan MicroRNA Reverse Transcription Kit (Applied Biosystems, Foster City, CA, USA) was employed for Reverse transcriptase (RT) reactions; real-time PCR was performed according to the manufacturer’s protocols. Each assay was performed using 300 ng sample and all the RT-PCR reactions were performed using the CFX96 Touch Real-Time PCR Detection System (BioRad, Hercules, CA, USA). The U6 snRNA reference (TM:001973) was employed to normalize all RNA samples, as previously reported [44,46,49].
Analysis of CFTR expression: RT-qPCR. Gene expression analysis was performed by RT-qPCR. 300 ng of the total RNA was reverse transcribed by using random hexamers. Quantitative real-time PCR (qPCR) assays were carried out using gene-specific double fluorescently labeled probes. Primers and probes used to assay CFTR (Assay ID: Hs00357011_m1) gene expression were purchased from Applied Biosystems (Applied Biosystems, Foster City, CA, USA). The relative expression was calculated using the comparative cycle threshold method and, as reference genes, the human RPL13A (Assay ID: Hs03043885_g1) [49].
Analysis of CFTR expression: Western blotting. Cell pellets were lysed as reported by Fabbri et al. [49]. For CFTR analysis 20 µg of total protein was heated in Laemmli buffer (Bio-Rad Laboratories, Hercules, California, USA) and loaded onto a 3 to 8% Tris-acetate gel (Bio-Rad Laboratories, Hercules, California, USA). The gel was transferred to PVDF membrane by using Trans Blot Turbo (Bio-Rad Laboratories, Hercules, California, USA). For CFTR detection and quantification, the mouse monoclonal antibody, clone 596, against NBD2 domain of CFTR (University of North Carolina, Cystic Fibrosis Center, Chapel Hill, NC) was employed at a dilution of 1:2500. After washes, membranes were incubated with horseradish peroxidase-coupled anti-mouse immunoglobulin (R&D System, Minneapolis, MN, USA) at room temperature for 1 hour and after washes the signal was developed by enhanced chemiluminescence (LumiGlo Reagent and Peroxide, Cell Signaling). After membranes stripping, β-Actin monoclonal antibody (Sigma-Aldrich, St. Louis, Mo, USA) was used as a standard internal control [7476].
Next Generation Sequencing (RNA-Seq). NGS experiments were performed at the Laboratory for Technologies of Advanced Therapies (LTTA) of Ferrara University.
SmallRNA libraries were prepared from total RNA using TruSeq® Small RNA Library PrepKit v2 (Illumina, RS-200-0012/24/36/48), according to manufacturer’s indications. Briefly, 35 ng of purified RNA were linked to RNA 3’ and 5’ adapters, converted in cDNA and amplified using Illumina primers containing unique indexes for each sample. Libraries were quantified through Agilent Bioanalyzer, using High Sensitivity DNA kit (Agilent, 50674626); after size-selection and ethanol precipitation, the library pool was quantified through Agilent Bioanalyzer and High Sensitivity DNA kit, denatured and diluted to 1.8 pM and sequenced using Illumina NextSeq500 platform and NextSeq® 500/550 High Output Kit v2 (75 cycles) (Illumina, FC-404-2005). Raw base-call data generated from the Illumina NextSeq 500 system have been demultiplexed and converted to FASTQ format. After quality check, evaluated using FastQC tool (https://www.bioinformatics. babraham.ac.uk/projects/fastqc/), adapters sequences have been trimmed by Cutadapt (http://cutadapt.readthedocs.io/en/stable/index.html). In this step also sequences shorter than 10 nucleotides have been removed. Reads mapping has been performed using the STAR algorithm (https://www.ncbi.nlm.nih.gov/pubmed/23104886), and the reference genome was composed of human microRNAs sequences from the miRbase 22 (http://www.mirbase.org/). Count of raw mapped reads has been performed using the htseq-count script from the HTSeq tools (http://www-huber.embl.de/
HTSeq/doc/overview.html); raw counts have been normalized using DESeq2 bioconductor package (http://bioconductor.org/packages/release/bioc/html/DESeq2.html). The employed softwares use the Benjamini–Hochberg method to control the False Discovery Rate (FDR). The optimal read depth to analyse the miRNA transcriptome was determined at 10 million reads per sample. Differentially expressed miRNAs were employed for Cluster Analysis of samples using the Manhattan correlation as a measure of similarity [68].
Statistical Analysis. In order to detect significance of the observed effects, results have been expressed as mean ± standard deviation (S.D.) and comparison among groups was made by using analysis of variances (ANOVA) with Dunnett’s test for comparison with a single control. Statistical significance was defined as significant (*, p < 0.05) and highly significant (**, p < 0.01).

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