Selective Delivery to Cardiac Muscle Cells Using Cell-Specific Aptamers
Abstract
:1. Introduction
2. Results
2.1. In Vivo SELEX for Cardiomyocyte Selection
2.2. Enriched Aptamer Pool Selectivity for Cardiomyocytes
2.3. Sequencing Analysis of Aptamer Enrichment
2.4. Identification of Candidate Aptamer Clusters
2.5. Secondary NGS Analysis for Diversity Confirmation
2.6. 2′F-Py RNA Aptamer 10478 Shows Selective Localization in CMs
3. Discussion
4. Materials and Methods
4.1. Animals
4.2. Oligonucleotides
4.3. Aptamer Library Preparation
4.4. In Vivo SELEX
4.5. PCR Cycle Optimization
4.6. Next Generation Sequencing for Aptamer Enrichment
4.7. Bioinformatics Analysis of NGS Data
4.8. RT-qPCR Quantification
4.9. Immunocytochemistry
4.10. Tissue Harvesting and Preparation
4.11. Tissue Processing and (Immuno)Staining
4.12. Fluorescence Microscopy
4.13. Serum Stability Assay
4.14. Secondary Structure Prediction
4.15. Statistical Analysis
4.16. Terms and Definitions
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
UCID | Unique cluster identification number assigned to the NGS data, abbreviated UC# that allows the identification of the different clusters/families of sequences in the NGS data following SELEX. |
Clusters | Groups or families of biological sequences that share similarities in their primary sequence. Sequence-clustering algorithms attempt to group the sequences that are somewhat related and the most represented sequence serves as the seed sequence of the cluster. |
Unique sequences | Any sequence in the NGS data that presents with ≤50 read counts. |
Enriched sequences | Any sequence in the NGS data that presents with >50 read counts. |
Number of raw sequences | The total number of reads going off the sequencer and into data analysis. |
Read count | The number of reads/sequences going off the sequencer or that align to a reference sequence (e.g., to the seed sequence of a cluster). |
Read count fraction | This is the proportion of the sum of the read counts (sequences) in each class (enriched or unique) over the total number of reads in the dataset, per round. Total read in the dataset = 1. |
Bin fraction | Bin fraction denotes the proportion of each bin over the total population of reads on the dataset. Total reads = 1. The fraction of read counts was derived by binning the sequences with respect to the read counts of each across 6 bands (≤10, 11–100, 101–1000, 1001–5000, 5001–10,000, >10,000). |
Base fraction | Nucleotide (base) fractions per position, in a given round, were obtained by calculating the frequency of each base per position over the total number of reads. Total number of reads = 1. |
Reads per million (RPM) | The read counts per cluster were divided by the “per million” scaling factor. This normalizes for sequencing depth, giving the reads per million. The “per million” scaling factor is derived by counting the total reads in a sample (i.e., SELEX round) and then dividing that number by 1,000,000. |
Technical duplicate | Technical replicates are repeated measurements of the same sample that demonstrate the variability of the protocol. Technical replicates are important because they address the reproducibility of the assay or technique. In this study, a technical duplicate is used in RT-qPCR assay to ensure the validity of the method (i.e., the pipetting technique). It is the same cDNA pipetted into multiple wells, thus Ct values with little variability should be obtained. The mean value from these replicates is then used as a representative value for each biological sample in subsequent data analyses. |
Biological replicate | Biological replicates are parallel measurements of biologically distinct samples that capture random biological variation, which can be a subject of study or a source of noise itself. Biological replicates address how widely your experimental results can be generalized. Unless otherwise stated, three biologically distinct samples (n = 3) were used in each experiment (biological triplicate). |
Appendix B
SELEX Round | Ranking | UCID | Cluster ID | Cluster Counts | Top Seq Counts | SequenceID | Random Region Sequence |
---|---|---|---|---|---|---|---|
1 | 1 | UC145 | Cluster 144 | 396 | 345 | >2-345-2257.31_2 | AGGGTAAGCCTTTCCATCGGGTCGACTTCGGATTGCATCG |
2 | UC156 | Cluster 155 | 394 | 346 | >1-346-2263.85_1 | TGTGAGTGATTACGCTCTGTGCGTATGGGGACAGTTCCGC | |
3 | UC538 | Cluster 537 | 386 | 333 | >3-333-2178.79_3 | AAAGTCTACAGGTGAAAGGCGTCACCGCGAGGCGAGCGTT | |
4 | UC124 | Cluster 123 | 384 | 326 | >5-326-2132.99_5 | CGGTGCACTGGCATGCTGGACCGGAGGTCAGGACGGTCGG | |
5 | UC17 | Cluster 16 | 381 | 323 | >6-323-2113.36_6 | TGGCCCGCTACTCCGCGGTCTATACTAGTATTCCGTAACA | |
6 | UC45 | Cluster 44 | 378 | 323 | >6-323-2113.36_7 | ACTGTGTCGATCAGGTAAACGACACTTGCGGCCTGCTATA | |
7 | UC88 | Cluster 87 | 374 | 321 | >8-321-2100.28_8 | TACCCCATAATAGGCCTTGTAGGATCGTAGACGTTACGTC | |
8 | UC504 | Cluster 503 | 374 | 314 | >13-314-2054.48_13 | TACTTGACAACACTAGTGATAGCAGAATCGCGAGACCGCA | |
9 | UC400 | Cluster 399 | 371 | 327 | >4-327-2139.53_4 | GTGGACGAGCCGGGCATGGTCGAGTGTGAAGGGAGCCGCG | |
10 | UC605 | Cluster 604 | 370 | 321 | >8-321-2100.28_9 | CCGGCGACTCTCGCGAACAGCTTCCCATCCGCATTTGTGG | |
2 | 1 | UC3215 | Cluster 141 | 723 | 635 | >1-635-4884.31_1 | TGCCGCAGGGTGTGGATTGAATTGACGGTGAGACGCGCAC |
2 | UC7082 | Cluster 35 | 718 | 631 | >2-631-4853.55_2 | CGGTGGACGTGTAGCGGGAATCCGCGGCAAACACAGAGCT | |
3 | UC7117 | Cluster 75 | 717 | 615 | >5-615-4730.48_5 | GGCCCAACGTGGTTGGGGTCAACACGCGGGATTCGGGGTT | |
4 | UC7087 | Cluster 40 | 705 | 609 | >7-609-4684.33_7 | ATAGCGTCCGGCTAGGCTTTCTCGGTGCGCAGCGGAGACA | |
5 | UC7091 | Cluster 45 | 701 | 617 | >4-617-4745.86_4 | GCACTTGCAGCGCGGTGTACGCTAACGCCTGGGCCGGTGA | |
6 | UC7171 | Cluster 135 | 690 | 622 | >3-622-4784.32_3 | TCTGTGCACGGCATCCGCTTAGAGTGTCCGGTCGGACATC | |
7 | UC3458 | Cluster 269 | 689 | 610 | >6-610-4692.02_6 | AGGGCGGGTCGCGGGCCTGGTGATTGGACGGAGGCTGGCC | |
8 | UC7116 | Cluster 74 | 683 | 606 | >8-606-4661.25_8 | CGATGCCCTGTGGTCGGTCGCCCGGCAGGGCTGTGCAGTT | |
9 | UC7053 | Cluster 2 | 677 | 578 | >15-578-4445.88_15 | CGGTTCCGAGCGTTGGTGGAGGACGCGGGTAGGCGGACGT | |
10 | UC7189 | Cluster 155 | 677 | 585 | >11-585-4499.72_11 | TGAGCCTGCGCGCGGGGGGAGGCGGCGGAGGACCAGTAGT | |
3 | N/A—No back up sample for NGS analysis | ||||||
4 | 1 | UC10474 | Cluster 2 | 9235 | 8057 | >1-8057-43057.24_1 | CGACGGACAAGGCTCACCGTGGCCATGTGAGCTCGGGCGC |
2 | UC10476 | Cluster 5 | 9086 | 8034 | >2-8034-42934.33_2 | TGCGACGTGGGCGCGTCATGCTGCGCGGTGCTGTGCACGC | |
3 | UC1370 | Cluster 3 | 8256 | 7138 | >3-7138-38146.03_3 | ACGGGCGCCCGTGCATAAGGTGCGGCGGGCTGACGTGTCG | |
4 | UC10479 | Cluster 8 | 7072 | 5973 | >4-5973-31920.18_4 | CACGCGGCGGCCGTGAATGGTCACGGAGGCGAGCTGTGCC | |
5 | UC10478 | Cluster 7 | 5617 | 4911 | >5-4911-26244.77_5 | TGCAGGTGCATGTGGGATCACGCGCGGTTAGGTCGCCGCG | |
6 | UC10483 | Cluster 12 | 5143 | 4463 | >6-4463-23850.62_6 | TCACGGGCGTGGCGGGCGACGAGCCACGGAGCGGGGTTGC | |
7 | UC10984 | Cluster 547 | 4316 | 3932 | >7-3932-21012.92_7 | ATGTCACGAACGAGGGCGTGCTCGCGTGGTGCGGAGGCA | |
8 | UC10488 | Cluster 17 | 4190 | 3664 | >8-3664-19580.70_8 | GTGCGCCACAGGTGTTACGGTGGTGCATCCGTGGGCTGCG | |
9 | UC10481 | Cluster 10 | 3752 | 3309 | >9-3309-17683.56_9 | CGGAGCCACCGGCGCGTGGGTGCGGGTGCGGCCACCAGCA | |
10 | UC10487 | Cluster 16 | 3528 | 3109 | >10-3109-16614.74_10 | TGACGGCCCTGCAAGGAGGGCTAGGATGTCGCTGTTGCGC | |
5 | 1 | UC10478 | Cluster 4 | 10293 | 8302 | >1-8302-56908.23_1 | TGCAGGTGCATGTGGGATCACGCGCGGTTAGGTCGCCGCG |
2 | UC11601 | Cluster 5 | 9563 | 8251 | >2-8251-56558.64_2 | CGACGGACAAGGCTCACCGTGGCCATGTGAGCTCGGGCGC | |
3 | UC10476 | Cluster 9 | 7566 | 6655 | >3-6655-45618.44_3 | TGCGACGTGGGCGCGTCATGCTGCGCGGTGCTGTGCACGC | |
4 | UC1370 | Cluster 7 | 7499 | 6515 | >4-6515-44658.77_4 | ACGGGCGCCCGTGCATAAGGTGCGGCGGGCTGACGTGTCG | |
5 | UC10481 | Cluster 8 | 7128 | 6262 | >5-6262-42924.52_5 | CGGAGCCACCGGCGCGTGGGTGCGGGTGCGGCCACCAGCA | |
6 | UC10984 | Cluster 428 | 5679 | 5206 | >6-5206-35685.89_6 | ATGTCACGAACGAGGGCGTGCTCGCGTGGTGCGGAGGCA | |
7 | UC10479 | Cluster 10 | 3747 | 3314 | >7-3314-22716.68_7 | CACGCGGCGGCCGTGAATGGTCACGGAGGCGAGCTGTGCC | |
8 | UC16931 | Cluster 12 | 3223 | 2828 | >8-2828-19385.27_8 | TGGGGGCTCAGTGACGGCGCGTCGTCGTTGAGCAGCGGCA | |
9 | UC10484 | Cluster 11 | 3070 | 2545 | >9-2545-17445.37_9 | CGCGGCCCCGGTAGTGTGGCTGGAGGGGTTGTTGTCGACA | |
10 | UC10494 | Cluster 2 | 3057 | 2508 | >10-2508-17191.74_10 | CGTGGGACGGCCGGCGTAGGGTCGGCAGCGAGTGGCGCGC | |
6 | 1 | UC10478 | Cluster 3 | 10172 | 8763 | >1-8763-61923.64_1 | TGCAGGTGCATGTGGGATCACGCGCGGTTAGGTCGCCGCG |
2 | UC11601 | Cluster 4 | 7883 | 6702 | >2-6702-47359.61_2 | CGACGGACAAGGCTCACCGTGGCCATGTGAGCTCGGGCGC | |
3 | UC1370 | Cluster 1 | 7636 | 6472 | >3-6472-45734.31_3 | ACGGGCGCCCGTGCATAAGGTGCGGCGGGCTGACGTGTCG | |
4 | UC10984 | Cluster 311 | 6694 | 6016 | >4-6016-42512.00_4 | ATGTCACGAACGAGGGCGTGCTCGCGTGGTGCGGAGGCA | |
5 | UC10476 | Cluster 7 | 6010 | 5149 | >5-5149-36385.35_5 | TGCGACGTGGGCGCGTCATGCTGCGCGGTGCTGTGCACGC | |
6 | UC18725 | Cluster 10 | 5056 | 4306 | >6-4306-30428.30_6 | CGGAGCCACCGGCGCGTGGGTGCGGGTGCGGCCACCAGCA | |
7 | UC17023 | Cluster 8 | 4858 | 4173 | >8-4173-29488.46_8 | CACGCGGCGGCCGTGAATGGTCACGGAGGCGAGCTGTGCC | |
8 | UC18722 | Cluster 5 | 4856 | 4182 | >7-4182-29552.06_7 | TCACGGTGGGATGACTGAAGGTCTGGTGCGACCGGGGCGC | |
9 | UC10489 | Cluster 17 | 3427 | 2949 | >9-2949-20839.07_9 | GGCGCGCCAGTCGCTCCGAGGGAGGGTGCGACGGTGCGTC | |
10 | UC16938 | Cluster 15 | 2911 | 1953 | >12-1953-13800.85_12 | CACGGCAACTGTGAGGCAAAAACGCCTTTGGCCCGGCGCT | |
7 | 1 | UC10478 | Cluster 10 | 10716 | 9067 | >1-9067-52008.17_1 | TGCAGGTGCATGTGGGATCACGCGCGGTTAGGTCGCCGCG |
2 | UC10476 | Cluster 3 | 8321 | 6970 | >2-6970-39979.81_2 | TGCGACGTGGGCGCGTCATGCTGCGCGGTGCTGTGCACGC | |
3 | UC18725 | Cluster 8 | 7826 | 6729 | >4-6729-38597.44_4 | CGGAGCCACCGGCGCGTGGGTGCGGGTGCGGCCACCAGCA | |
4 | UC10984 | Cluster 263 | 7715 | 6915 | >3-6915-39664.33_3 | ATGTCACGAACGAGGGCGTGCTCGCGTGGTGCGGAGGCA | |
5 | UC11601 | Cluster 2 | 7300 | 6184 | >5-6184-35471.33_5 | CGACGGACAAGGCTCACCGTGGCCATGTGAGCTCGGGCGC | |
6 | UC1370 | Cluster 11 | 6511 | 5386 | >7-5386-30894.01_7 | ACGGGCGCCCGTGCATAAGGTGCGGCGGGCTGACGTGTCG | |
7 | UC18776 | Cluster 11 | 6511 | 5386 | >7-5386-30894.01_7 | ACGGGCGCCCGTGCATAAGGTGCGGCGGGCTGACGTGTCG | |
8 | UC16938 | Cluster 35 | 3812 | 2578 | >12-2578-14787.37_12 | CACGGCAACTGTGAGGCAAAAACGCCTTTGGCCCGGCGCT | |
9 | UC20614 | Cluster 5 | 3516 | 3017 | >10-3017-17305.46_10 | CTGCCGGCGGTTGGGCCCTGGGCGGGCCAGCGGATGTCGC | |
10 | UC16931 | Cluster 14 | 3437 | 2860 | >11-2860-16404.91_11 | TGGGGGCTCAGTGACGGCGCGTCGTCGTTGAGCAGCGGCA |
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Gender | Male |
Age | 8 weeks old |
Average yield | 5.53 × 105 ± 3.79 × 104 |
Average viability | 81.7 ± 7.64 |
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Philippou, S.; Mastroyiannopoulos, N.P.; Tomazou, M.; Oulas, A.; Ackers-Johnson, M.; Foo, R.S.; Spyrou, G.M.; Phylactou, L.A. Selective Delivery to Cardiac Muscle Cells Using Cell-Specific Aptamers. Pharmaceuticals 2023, 16, 1264. https://doi.org/10.3390/ph16091264
Philippou S, Mastroyiannopoulos NP, Tomazou M, Oulas A, Ackers-Johnson M, Foo RS, Spyrou GM, Phylactou LA. Selective Delivery to Cardiac Muscle Cells Using Cell-Specific Aptamers. Pharmaceuticals. 2023; 16(9):1264. https://doi.org/10.3390/ph16091264
Chicago/Turabian StylePhilippou, Styliana, Nikolaos P. Mastroyiannopoulos, Marios Tomazou, Anastasios Oulas, Matthew Ackers-Johnson, Roger S. Foo, George M. Spyrou, and Leonidas A. Phylactou. 2023. "Selective Delivery to Cardiac Muscle Cells Using Cell-Specific Aptamers" Pharmaceuticals 16, no. 9: 1264. https://doi.org/10.3390/ph16091264
APA StylePhilippou, S., Mastroyiannopoulos, N. P., Tomazou, M., Oulas, A., Ackers-Johnson, M., Foo, R. S., Spyrou, G. M., & Phylactou, L. A. (2023). Selective Delivery to Cardiac Muscle Cells Using Cell-Specific Aptamers. Pharmaceuticals, 16(9), 1264. https://doi.org/10.3390/ph16091264