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. Author manuscript; available in PMC: 2021 Nov 26.
Published in final edited form as: Biochem Biophys Res Commun. 2020 Sep 9;533(1):9–16. doi: 10.1016/j.bbrc.2020.08.104

Optimizing Delivery for Efficient Cardiac Reprogramming

Martin H Kang 1, Jiabiao Hu 1, Richard E Pratt 1, Conrad P Hodgkinson 1, Aravind Asokan 1, Victor J Dzau 1,*
PMCID: PMC8339574  NIHMSID: NIHMS1726988  PMID: 32917363

Abstract

Following heart injury, cardiomyocytes, are lost and are not regenerated. In their place, fibroblasts invade the dead tissue where they generate a scar, which reduces cardiac function. We and others have demonstrated that combinations of specific miRNAs (miR combo) or transcription factors (GMT), delivered by individual lenti-/retro-viruses in vivo, can convert fibroblasts into cardiomyocytes and improve cardiac function. However, the effects are relatively modest due to the low efficiency of delivery of miR combo or GMT. We hypothesized that efficiency would be improved by optimizing delivery. In the first instance, we developed a multicistronic system to express all four miRNAs of miR combo from a single construct. The order of each miRNA in the multicistronic construct gave rise to different levels of miRNA expression. A combination that resulted in equivalent expression levels of each of the four miRNAs of miR combo showed the highest reprogramming efficiency. Further efficiency can be achieved by directly targeting fibroblasts. Screening of several AAV serotypes indicated that AAV1 displayed tropism towards cardiac fibroblasts. Combining multicistronic expression with AAV1 delivery robustly reprogrammed cardiac fibroblasts into cardiomyocytes in vivo.

Keywords: miRNAs, cardiac reprogramming, cardiomyocytes, stoichiometry

Introduction

Injury to the human heart results in an irreversible loss of cardiomyocytes. In their place, fibroblasts fill the dead tissue and through various processes form a scar [1,2]. The loss of cardiomyocytes and replacement by scar impair heart function and eventually lead to cardiac failure[2]. It has been shown that converting cardiac fibroblasts within the scar tissue into cardiomyocytes by administration of combinations of specific transcription factors or miRNAs improves heart function[3,4]. However, the effects are relatively modest due to the relatively low rate of conversion related to the low efficiency and lack of optimization of delivery of the combined reprogramming factors.

Currently, there are two demonstrated methods for converting scar fibroblasts into cardiomyocytes in vivo. The Srivastava and Olsen laboratories focused their approach on transcription factors implicated in cardiac development. Screening combinations of these cardiac development transcription factors identified that the combination of Gata4 (G), Mef2C (M), and Tbx5 (T) induced fibroblast conversion to cardiomyocytes[5,6]. In contrast to the transcription factor approach, we screened combinations of miRNAs that are highly expressed in cardiac muscle. Through this screening approach we found that a combination of four miRNAs (miR-1, miR-133, miR-208, and miR-499), which we call miR combo, induced fibroblast conversion into mature cardiomyocytes in vitro and in vivo [7–9]. Currently both GMT and miR combo are delivered in vivo via pooled lenti-/retro-viruses, each expressing one individual reprogramming factor[8,10,11]. This approach leads to widely different expression ratios between each reprogramming factor in every transduced fibroblast. Moreover, lenti- and retro-viruses are promiscuous and will infect any cell that is undergoing proliferation. The inability to control reprogramming factor stoichiometry and cellular targeting may explain the relatively low conversion rate observed in vivo.

The reprogramming of somatic cells is widely acknowledged as an anemic process as demonstrated by the 0.05% efficiency in reprogramming fibroblasts to induced pluripotent cells [12]. Balanced expression of factors is crucial and improved reprogramming efficiency is dependent on their relative ratios and optimal stoichiometry [13]. Direct reprogramming of fibroblasts into cardiomyocytes by transcription factors was improved following their administration using a precise dosage and stoichiometry [14]. By delivering a single transgene containing all reprogramming factors, a multicistronic system resulted in the precise relative expression of factors that resulted in improved reprogramming efficiency.

In vivo cardiac reprogramming by miR combo has been demonstrated using 4 individual lentiviral vectors delivering the individual miRNAs of miR combo [7–9]. The advantages of lentiviral vectors are their efficient transduction of many cell types, and rapid, long-term transgene expression following transduction [15]. Their limitations are integration of the transgene into the host genome resulting in possible insertional mutagenesis, and the immunogenicity associated with the lentiviral vector envelope [15]. Adeno-associated viruses (AAVs) have recently emerged as one of the most promising vectors used in cardiac gene therapy due to their lack of insertion and existence as episomes, the absence of immunogenicity compared to other viral vectors, and tropism for certain tissues with the capsid serotypes 1, 6, and 9 demonstrating the greatest potential for transducing cardiac cells [16]. Although the genome capacity of AAV is limited to ~5kb, their small size means most miRNA genes and clusters can be accommodated. Because the AAV genome is single-stranded, the conversion to double-stranded DNA for transcription can delay transgene expression. This is mitigated by using self-complementary sequences which package an inverted complementary sequence that folds into double-stranded DNA before transcription [17].

The objective of this study was to develop a delivery system that ensured fibroblasts were efficiently targeted and expressed all four constituent miRNAs of miR combo. To ensure expression of all four constituent miRNAs we developed a multicistronic system. The order of each miRNA in the multicistronic construct gave rise to different levels of miRNA expression. The combination that resulted in equivalent expression levels of each of the four miRNAs of miR combo demonstrated the highest reprogramming efficiency. Furthermore, to enhance cell selectively we measured the ability of various AAV serotypes to specifically target fibroblasts. We found that one serotype, AAV1, displayed fibroblast tropism. Combining AAV1 with multicistronic miR combo led to robust and efficient conversion of fibroblasts into cardiomyocytes in vivo.

Materials and Methods

Generation of multicistronic miR combo:

The endogenous multicistronic miR17-92 (NCBI database (NT_009952.14) was used as a scaffold to generate the multicistronic miR combo constructs. The multicistronic miR combo constructs were generated from the miR-17-92 cassette according to Yang et al [18]. Lower stems and loops (~11 bp) of the endogenous miRNAs, as well as all intervening sequences and 5’flanking (91bp) and 3’flanking (18bp), were all maintained. Sequences of the endogenous pre-miRNAs are shown below; sequences in italics were replaced with the miRNAs of miR combo:

miR-17

5’GUCAGAAUAAUGUCAAAGUGCUUACAGUGCAGGUAGUGAUGUGUGCAUCUACUGCAGUGAGGGCACUUGUAGCAUUAUGCUGAC3’

miR-18a

5’UGCGUGCUUUUUGUUCUAAGGUGCAUCUAGUGCAGAUAGUGAAGUAGACUAGCAUCUACUGCCCUAAGUGCUCCUUCUGGCAUAAGAAGUUAUGUC3’

miR-19a

5’GCAGCCCUCUGUUAGUUUUGCAUAGUUGCACUACAAGAAGAAUGUAGUUGUGCAAAUCUAUGCAAAACUGAUGGUGGCCUGC3’

miR-20a

5’GUGUGAUGUGACAGCUUCUGUAGCACUAAAGUGCUUAUAGUGCAGGUAGUGUGUAGCCAUCUACUGCAUUACGAGCACUUAAAGUACUGCCAGCUGUAGAACUCCAG3’

miR-19b

5’CACUGGUCUAUGGUUAGUUUUGCAGGUUUGCAUCCAGCUGUAUAAUAUUCUGCUGUGCAAAUCCAUGCAAAACUGACUGUGGUGGUG3’

Sequences employed for the constituent miRNAs of miR combo were:

miR-1: 5’UGGAAUGUAAAGAAGUAUGUAU3’

miR-133: 5’UUUGGUCCCCUUCAACCAGCUG3’

miR-208: 5’AUAAGACGAGCAAAAAGCUUGU3’

miR-499: 5’UUAAGACUUGCAGUGAUGUUU3’

All constructs were generated by GenScript and were supplied on the pcDNA3.1 plasmid vector backbone.

Transient transfection with miRNAs:

Mouse (C57BL/6) neonatal cardiac fibroblasts were isolated from 2 day old mouse neonates according to the method outlined in Jayawardena et al [19]. Following isolation fibroblasts were cultured in growth media containing DMEM (ATCC, Catalogue number 30-2002) supplemented with 15%v/v FBS (Thermo Scientific Hyclone Fetal bovine serum, Catalogue number SH30071.03, Lot number AXK49952) and 1%v/v penicillin/streptomycin (Gibco, Catalogue number 15140-122, 100units Penicillin, 100ug/ml Streptomycin). Fibroblasts were passaged once the cells had reached 70-80% confluence using 0.05% w/v trypsin (Gibco, Catalogue number 25300-054). Freshly isolated fibroblasts were labelled as Passage 0. Experiments were conducted with cells at passage 2. For all experiments, cells were seeded at 5000 cells/cm2 in growth media. After 24 hours, the cells were transfected with transfection reagent alone (Dharmafect-I, ThermoScientific), with transfection reagent plus non-targeting microRNAs (negmiR), or with transfection reagent plus our previously reported combination of cardiac reprogramming microRNAs[7] (miR combo, miR-1, miR-133, miR-208, miR-499).

Transient transfection with plasmid-DNA:

For transfection, neonatal cardiac fibroblasts were seeded one day prior to transfection at 22,500 cells per well of a 12-well plate. On the day of transfection, 0.5μg of each plasmid containing the multicistronic miR combo construct was diluted in Plus reagent (1.5μl, ThermoFisher) and serum-free DMEM (total volume 50μl). In a separate reaction, LTX reagent (1.5μl, ThermoFisher) was diluted in serum-free DMEM (48.5μl). After five minutes at room temperature, the reactions were combined, mixed and left for a further twenty minutes at room temperature. The complexes were added to cells and complete media added to total volume of 550μl per well. One day after transfection, complexes were removed and the cells cultured in growth media for the duration of the experiment.

Generation of self-complementary adeno-associated virus (scAAV):

scAAV was generated by sub-cloning the CMV promoter, miR combo No 1, and the BGH polyadenylation sequence from the pcDNA3.1 plasmid into the MCS of the tr1TR2-Basic (+) plasmid (Addgene). Viral particles were generated by Vector Biolabs.

Quantitative PCR:

miRNA: miRNAs were isolated with a MirVana Isolation kit (ThermoFisher) according to the manufacturer’s protocol. Expression of the miRNAs was determined in a standard qPCR reaction involving FAM conjugated specific primers (ThermoFisher) and TaqMan Gene Expression Master Mix. Briefly, miR combo expression levels were measured by absolute quantification using the Standard Curve Method. Reverse transcription products (cDNA) from miR precursor mimics to miR-1, miR-133, miR-208, and miR-499 (Ambion) were serially diluted and qPCR was performed to generate standard curves to correct for differences in primer efficiencies. Assay ID numbers for the primers employed: miR-1 477820_mir; miR-133 rno480920_mir; miR-208 477819_mir; miR-499 rno481402_mir. RNA: Total RNA was extracted using Quick-RNA MiniPrep Kit according to the manufacturer’s instructions (Zymo Research). Total RNA (50ng-100ng) was converted to cDNA using a high capacity cDNA reverse transcription kit (Applied Biosystems). cDNA was used in a standard qPCR reaction involving FAM conjugated gene specific primers (ThermoFisher) and TaqMan Gene Expression Master Mix (ThermoFisher). Primers were acquired from ThermoFisher and the assay ID numbers are: Mef2C Mm01340842_m1; Myh6 Mm00440359_m1.

Mice, Myocardial Infarction and Virus Injection:

Adult male fibroblast-specific protein 1 Cre-tandem dimer Tomato (tdTomato) mice were subjected to permanent ligation of the left anterior descending coronary artery AAV (AAV2/1) containing version 1 (GenScript) of the multicistronic miR combo (1011 viral particles) were injected at 2 sites 2 mm below the site of ligation. An AAV (AAV2/1) containing a non-targeting miRNA was used as a control.

Immunocytochemistry:

Hearts were removed and fixed in formalin. After sectioning, sections were stained with antibodies for cardiac troponin-T (Abcam) and tdTomato (Abcam). Confocal images were captured using an LSM 510 Meta DuoScan microscope (Zeiss) and processed using LSM 5 software, version 4.2.

Statistics:

All experiments are biological repeats. Data with two groups was analyzed by Students T-test. Data with more than two groups was analyzed by Anova with Bonferroni post-hoc tests.

Results & Discussion

The objective of this study was to generate a single delivery system for efficient reprogramming of cardiac fibroblasts into cardiomyocytes in vivo.

Current in vivo reprogramming strategies utilize independent vectors; with each vector carrying a single reprogramming factor. This is inefficient as it is impossible to ensure that each reprogramming factor can enter the cell. Moreover, it is impossible to control the relative amount of each reprogramming factor in each cell. Consequently, to ensure that each cell expressed all of the reprogramming factors at a defined stoichiometry we developed multicistronic expression system. With respect to cardiac reprogramming factors, we focused on our combination of four miRNAs (miR-1, miR-133, miR-208 and miR-499), also known as miR combo, which has been demonstrated to reprogram fibroblasts into functional mature cardiomyocytes. Within vertebrate genomes, miRNA genes tend to be clustered together with clusters transcribed as a single primary transcript which is then cleaved into the mature functional miRNAs[20]. These endogenous clusters offer a relatively straightforward template to develop a synthetic multicistronic miRNA construct. We utilized the miR-17-92 cluster which produces 7 miRNAs as a primary transcript[21,22] (Figure 1A). This cluster has been utilized previously to deliver miRNAs that target the Hepatitis C virus[18]. Importantly, the ordering and placement of the miRNAs in this cluster affected their expression levels. The mature miRNA sequences of miR-17-92 were replaced with those of the constituents of miR combo, keeping the pre-miRNA and linking sequences of the miR-17-92 backbone intact to ensure expression of our miRNAs (Figure 1B). The miR-92a-1 site was deleted entirely as expression of this miRNA is weak[21]. To determine if position/stoichiometry of the miRNAs affected expression and reprogramming we generated four multicistronic miR combo constructs and evaluated their effects in cultured neonatal cardiac fibroblasts (Figure 1C). Each individual miRNA of miR combo was placed in positions 2 and 5 of the original miR-17-92 multicistronic as it has been demonstrated that these positions give rise to highest miRNA expression of the endogenous miRNAs[18]. Each configuration strongly affected the relative expression levels of the four miRNAs in miR combo. Version number 1, miR-499:miR-1:miR-208:miR-133:miR-1 gave rise to roughly equivalent levels of expression for each miRNA (Figure 2A). In contrast, other combinations were more selective. Version 2 (miR-499:miR-133:miR-208:miR-133) strongly induced miR-133 and miR-208 expression only (Figure 2A). Similarly, version 4 (miR-208:miR-499:miR-133:miR-1:miR-499) only induced miR-499 (Figure 2A). Version 3 (miR-499:miR-208:miR-133:miR-1:miR-499) was unable to induce the expression of any miRNA (Figure 2A).

Figure 1. Generation of a multicistronic miR combo.

Figure 1.

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(A) The endogenous miR-17-92 multicistronic. Pre-miRNAs (grey boxes) and mature miRNAs (black boxes) are shown. (B) Generation of the multicistronic miR combo: The sequences for the mature endogenous miRNAs were replaced with the mature miRNA sequences of the constituent miRNAs of miR combo. As indicated in the figure, lower stems and loops of the endogenous miRNAs as well as the spacing between the endogenous miRNAs were maintained. The region occupied by miR-92a-1 was not used and was removed. (C) Versions of the multicistronic miR combo used in this study.

Figure 2. miRNA stoichiometry influences reprogramming efficiency.

Figure 2.

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(A) Neonatal cardiac fibroblasts were transiently transfected with a plasmid containing one of the four versions of the multicistronic miR combo. After 3 days, miRNA expression was analyzed by qPCR. Expression of each miRNA is shown relative to expression levels in fibroblasts transfected with a construct containing five identical copies of a non-targeting miRNA. (B) Cultured neonatal cardiac fibroblasts were transiently transfected with the four versions of the multicistronic miR combo in vitro. Following transfection, expression levels of the cardiac commitment marker Mef2C (day 3 post-transfection) and the mature cardiomyocyte marker aMHC (day 14 post-transfection) were measured by qPCR. Expression is shown relative to expression levels in fibroblasts transfected with a construct containing five identical copies of a non-targeting miRNA. N=3.

We then measured the effects of miRNA stoichiometry on reprogramming efficiency. As shown in Figure 2B, the positions of the miRNAs within the multicistronic affected the magnitude of reprogramming in vitro. Neonatal cardiac fibroblasts were transfected with the 4 different versions of miR combo or the non-targeting miRNA construct as a control. After 3 days, RNA was extracted and assayed for cardiac gene expression by qPCR. We found that version 1 of miR combo significantly induced the expression of Mef2C and α-MHC (Figure 2A). In contrast, neither version 2, version 3 nor version 4 were able to induce reprogramming (Figure 2B).

Current strategies to deliver reprogramming factors into the heart utilize lenti- and retro-viruses. However, these viruses are not selective; targeting any dividing cell. Efficient cardiac reprogramming requires that reprogramming factors are delivered solely into cardiac fibroblasts. AAVs are an ideal type of agent for cell specificity as various AAV serotypes. Consequently, we examined if an AAV serotype existed that would exhibit selectivity towards cardiac fibroblasts. To that end, neonatal cardiac fibroblasts were screened in vitro with AAV-GFPs of serotypes 1, 2, 5, 6, 9 and rh10. GFP expression was only observed with fibroblasts infected with the AAV2/1 serotype (Figure 3A) with a transduction efficiency of 35%. The analysis was repeated with neonatal cardiomyocytes, AAV1 serotype transduction was much lower (~10%) than that observed in the fibroblasts (Figure 3B). We then injected AAV-GFP serotype 1 into non-injured hearts to examine its ability to transduce fibroblasts in vivo. Three weeks later, hearts were removed and the expression of GFP and S100A4 (fibroblast marker) was detected by confocal immunofluorescence. The results demonstrated that in vivo, AAV1 transduced fibroblasts with high efficiency (Figure 3C).

Figure 3. AAV1 demonstrates fibroblast tropism.

Figure 3.

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(A) Cardiac fibroblasts were incubated with an AAV GFP reporter at a wide range of genome copies (GC) per cell. AAV1, 2, 5, 6, 9, and rh10 capsids were used. Imaging and FACS was performed 8 days following infection. Images 160,000 GC/cell. FACS AAV1 10,000 and 160,000 GC/cell shown. (B) Comparison of the number of cardiac fibroblasts and cardiomyocytes expressing the GFP transgene following incubation with 160,000 genome copies per cell using the indicated capsids. GFP+ cells were counted by FACS 8 days following infection. (C) AAV1-GFP was injected into mouse hearts. Three weeks following injection heart sections were immunostained for GFP and the fibroblast marker S100A4. N=3. Representative images are shown.

Following these experiments we wanted to determine if our optimized system for delivery of reprogramming factors into cardiac fibroblasts in vivo, efficiently reprogrammed fibroblasts into cardiomyocytes. The multicistronic miR combo was packaged into the AAV1 and injected into the mouse heart immediately following myocardial infarction. Fibroblast lineage tracing was then employed to track fibroblast conversion into cardiomyocytes. As demonstrated in Figure 4, delivery of the multicistronic miR combo was efficient in converting fibroblasts into cardiomyocytes in vivo (Figure 4).

Figure 4. A multicistronic miR combo reprograms fibroblasts into cardiomyocytes in vivo.

Figure 4.

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Fibroblast-specific protein 1-Cre/tandem dimer Tomato (tdTomato) mice were subjected to either a sham operation or myocardial infarction (MI). Immediately after MI, a control AAV or a single AAV virus containing version 1 of the multicistronic miR combo was injected into the heart. An AAV containing a non-targeting miRNA (negmiR) was used as a control. Eight weeks after injury the entire peri-infarct region was visualized by serial sectioning through the heart tissue. Sections were probed for tdTomato and cardiac troponin-T. For all panels, scale bar, 100 μm, n=3, P values indicated.

It is commonly thought that low reprogramming efficiency is due to reprogramming barriers. Indeed cell-cycle inhibitors; epigenetic regulators; Wnt/b-catenin pathway components; as well as the failure to activate innate immunity pathways have all been cited as barriers to reprogramming. In contrast, reprogramming factor stoichiometry has received far less attention. This is an important area of research as current methods of reprogramming factor delivery in vivo utilize pools of viruses each expressing one individual reprogramming factor leading to varying relative levels of each reprogramming factor in each transduced cell. The limited stoichiometric analysis conducted to date suggests that reprogramming factor stoichiometry is an under-appreciated barrier to reprogramming. Stoichiometric analysis of the OKSM factors for reprogramming to iPS has demonstrated that high Oct4 expression versus modest Klf4 expression is optimal [23,24]. Moreover, high Mef2C expression compared to Gata4 and Tbx5 expression increases the efficiency of GMT based fibroblast conversion into cardiomyocytes [14]. Our study indicates that stoichiometry also influences miRNA based reprogramming outcomes. In our hands, equivalent expression levels of the four miRNAs in miR combo were necessary for reprogramming fibroblasts into cardiomyocytes. Disordered miRNA expression, where the expression of a single miRNA dominated, was associated with poor reprogramming efficiency.

In conclusion, we provide further evidence that optimizing reprogramming factor stoichiometry is necessary for efficient cellular reprogramming.

Sources of Funding:

Research conducted in these studies was supported by the NIH.

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