We would like to thank Nick Russell and Brandon McKethan of Bio-Rad for their helpful discussions during the development of this method.

Quantification of Viral Vectors in Tears Using ddPCR for Bioshedding Studies

<ol>
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European Medicines Agency Available from: <a target="_blank" href="https://www.ema.europa.eu/en/documents/scientific-guideline/guideline-quality-non-clinical-clinical-aspects-gene-therapy-medicinal-products_en.pdf">https://www.ema.europa.eu/en/documents/scientific-guideline/guideline-quality-non-clinical-clinical-aspects-gene-therapy-medicinal-products_en.pdf</a> (2018)</li><li>Kaur, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=white+paper+on+recent+issues+in+bioanalysis:+mass+spec+of+proteins,+extracellular+vesicles,+CRISPR,+chiral+assays,+oligos;+nanomedicines+bioanalysis;+ICH+M10+section+7.1;+non-liquid+&amp;+rare+matrices;+regulatory+inputs+(part+1A+-+recommendations+on+endogenous+compounds,+small+molecules,+complex+methods,+regulated+mass+spec+of+large+molecules,+small+molecule,+PoC+&amp;+part+1B+-+regulatory+agencies'+inputs+on+bioanalysis,+biomarkers,+immunogenicity,+gene+&amp;+cell+therapy+and+vaccine).">white paper on recent issues in bioanalysis: mass spec of proteins, extracellular vesicles, CRISPR, chiral assays, oligos; nanomedicines bioanalysis; ICH M10 section 7.1; non-liquid &amp; rare matrices; regulatory inputs (part 1A - recommendations on endogenous compounds, small molecules, complex methods, regulated mass spec of large molecules, small molecule, PoC &amp; part 1B - regulatory agencies' inputs on bioanalysis, biomarkers, immunogenicity, gene &amp; cell therapy and vaccine).</a> Bioanalysis. 14 (9), 505-580 (2022).</li><li>Hays, A., Islam, R., Matys, K., Williams, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Best+practices+in+qPCR+and+qPCR+validation+in+regulated+bio+analytical+laboratories.">Best practices in qPCR and qPCR validation in regulated bio analytical laboratories.</a> The AAPS Journal. 24 (2), 36 (2022).</li><li>Ma, H., Bell, K. N., Loker, R. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=qPCR+and+qRT-PCR+analysis:+Regulatory+points+to+consider+when+conducting+biodistribution+and+vector+shedding+studies.">qPCR and qRT-PCR analysis: Regulatory points to consider when conducting biodistribution and vector shedding studies.</a> Molecular Therapy. Methods &amp; Clinical Development. 17 (20), 152-168 (2020).</li><li>Wissel, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Recommendations+on+qPCR/ddPCR+assay+validation+by+GCC.">Recommendations on qPCR/ddPCR assay validation by GCC.</a> Bioanalysis. 14 (12), 853-863 (2022).</li><li>Expectations for biodistribution (BD) assessments for gene therapy (GT) products. International Pharmaceutical Regulators Programme Available from: <a target="_blank" href="https://admin.iprp.global/sites/default/files/2018-09/IPRP_GTWG_ReflectionPaper_BD_Final_2018_0713.pdf">https://admin.iprp.global/sites/default/files/2018-09/IPRP_GTWG_ReflectionPaper_BD_Final_2018_0713.pdf</a> (2018)</li><li>Pinheiro, L., Emslie, K. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Basic+concepts+and+validation+of+digital+PCR+measurements.">Basic concepts and validation of digital PCR measurements.</a> Methods in Molecular Biology. 1768, 11-24 (2018).</li><li>Tzonev, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fundamentals+of+counting+statistics+in+digital+PCR:+I+measured+two+target+copies-what+does+it+mean.">Fundamentals of counting statistics in digital PCR: I measured two target copies-what does it mean.</a> Methods in Molecular Biology. 1768, 25-43 (2018).</li><li>Prantner, A., Marr, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome+concentration,+characterization,+and+integrity+analysis+of+recombinant+adeno-associated+viral+vectors+using+droplet+digital+PCR.">Genome concentration, characterization, and integrity analysis of recombinant adeno-associated viral vectors using droplet digital PCR.</a> PLoS One. 18, 0280242 (2023).</li><li>Primer-BLAST. 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Bio-Rad Available from: <a target="_blank" href="https://www.bio-rad.com/webroot/we/pdf/lsr/literature/Bulletin_6407.pdf">https://www.bio-rad.com/webroot/we/pdf/lsr/literature/Bulletin_6407.pdf</a> (2023)</li><li>Qian, P. L., Sauzade, M., Brouzes, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=dPCR:+A+technology+review.">dPCR: A technology review.</a> Sensors. 18 (4), 1271 (2018).</li><li>Basu, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Digital+assays+part+I:+portioning+statistics+and+digital+PCR.">Digital assays part I: portioning statistics and digital PCR.</a> SLAS Technology. 22 (4), 369-386 (2017).</li><li>Sanmiguel, J., Gao, G., Vandeberghe, L. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+and+digital+droplet-based+AAV+genome+titration.">Quantitative and digital droplet-based AAV genome titration.</a> Methods in Molecular Biology. 1950, 51-83 (2019).</li><li>Bachhuber, F., Huss, A., Senel, M., Tumani, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Diagnostic+biomarkers+in+tear+fluid:+from+sampling+to+preanalytical+processing.">Diagnostic biomarkers in tear fluid: from sampling to preanalytical processing.</a> Scientific Reports. 11, 10064 (2021).</li><li>Martinez-Fernandez de la Camara, C., McClements, M. E., MacLaren, R. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Accurate+quantification+of+AAV+vector+genomes+by+quantitative+PCR.">Accurate quantification of AAV vector genomes by quantitative PCR.</a> Genes. 12 (4), 601 (2021).</li><li>Ai, J., Ibraheim, R., Tai, P. W. L., Gao, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+scalable+and+accurate+method+for+quantifying+vector+genomes+of+recombinant+adeno-associated+viruses+in+crude+lysate.">A scalable and accurate method for quantifying vector genomes of recombinant adeno-associated viruses in crude lysate.</a> Human Gene TherapyMethods. 28 (3), 139-147 (2017).</li><li>Dobnik, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Accurate+quantification+and+characterization+of+adeno-associated+viral+vectors.">Accurate quantification and characterization of adeno-associated viral vectors.</a> Frontiers in Microbiology. 10, 1570 (2019).</li><li>Bennett, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Thermal+stability+as+a+determinant+of+AAV+serotype+identity.">Thermal stability as a determinant of AAV serotype identity.</a> Molecular Therapy Methods and Clinical Development. 6, 171-182 (2017).</li></ol>

All authors are employees of KCAS Bioanalytical and Biomarker Services, a contract research organization providing comprehensive Good Laboratory Practices/Good Clinical Practices compliant development services from early discovery support through product registration, including supporting AAV-based assays, as described in this protocol. KCAS funded this project and publication of this protocol. While there are no current FDA guidelines for the design and validation of the experiments presented in this paper, the experts and thought leaders developing such studies at KCAS have adopted this approach as the baseline approach. Additional criteria and parameters are discussed on a project-by-project basis and may be included based on the intended use.

There are several steps of the ddPCR protocol that are critical to proper performance of the assay. The first critical step is the design and optimization of the primers and probe. In general, the use of hydrolysis probe-based chemistry over dye-based chemistry (e.g., SYBR Green) in a preclinical or clinical setting is recommended due to their superior specificity. Additionally, the choice of amplification target is a critical one. Typically, the transgene of interest of the vector is targeted. However, in earlier preclinical stages or in vectors where it may not be possible to distinguish vector transgene versus genomic DNA, it may be appropriate to use standardized vector targets. For example, one could target the inverted terminal repeat region, promoter, poly-A tail, or the inter-segment junctions between these vector components. The choice of target will vary based on vector design. Traditional qPCR primer and probe design strategies and software are typically appropriate for ddPCR. Design parameters that are expected to yield a consistent annealing temperature (for example, 60&#176;C) should be selected to reduce the amount of optimization required. It has also been recommended to design, order, and evaluate at least three different sets for each target. One should then select the set that shows the greatest specificity (no amplification in the negative control well or in a matrix of related target DNA) and sensitivity (i.e., limit of detection)20.
If it is advantageous to be able to transition the assay between qPCR and ddPCR, it is recommended to optimize the assay conditions using qPCR first, and to identify conditions for the selected set that result in amplification efficiencies of 90%-110% with an R2&#160;&#8805; 0.98. However, ddPCR as an endpoint method is typically less sensitive than qPCR due to variances in amplification efficiencies. At a minimum, it is recommended to run a thermal temperature gradient in the annealing/extension step to cover temperatures above and below the expected annealing temperatures and to evaluate the rain and fluorescent amplitude separation between the negative and positive droplet clusters as a function of temperature. If the workspace allows, it is recommended to have individual dedicated workstations for master mix preparation, template addition, and amplification. Where possible, these should physically be segregated by a unidirectional workflow with built-in engineering controls, such as controlled access and differential air pressures, to reduce the risk for cross contamination and false positives. If this is not possible, extreme caution must be taken to prevent cross contamination.
There are two steps in this protocol that may appear unusual to those who are more accustomed to qPCR assay development. The first is the inclusion of a restriction enzyme in the PCR master mix. During ddPCR amplification, each droplet is thermocycled to endpoint. In a properly optimized assay, this results in two populations of droplets, one set displaying a consistently high level of fluorescent signals-the positives-and another consistently displaying a low level of fluorescent signal-the negatives. If PCR interference occurs, it may desynchronize the initiation of PCR amplification, resulting in the droplet not reaching an amplification plateau, and thus inconsistent fluorescent endpoints. In this case, the droplets will be distributed between the negatives and positives, resulting in a phenomenon called ddPCR rain. This can result in inaccurate quantification of the target and inconsistently and subjectively applied thresholds. Our recommendation to set the threshold slightly above the signal of the NTC, which should minimize the effects of rain in the final quantification as all droplets are still considered positive, even if not fully cycled to endpoint. AAVs have a highly complex secondary structure that, depending on the amplification target, may reduce accessibility to the primers and probes, resulting in PCR interference and thus rain. The inclusion of the restriction enzyme in the master mix cleaves this secondary structure to increase access by the primers and probes, reducing the rain, which may thereby improve the accuracy of the assay. The effects of the inclusion of a restriction enzyme in the ddPCR reaction have been described previously25,32. Any restriction enzyme can be used, so long as it is confirmed to not cut within the target amplification region. No predigestion steps or alternative buffer compositions are required.
The second unusual step is the preparation of the tear sample containing AAV. In this protocol, a 1:10 (or greater) ratio of tears was utilized and subsequently the sample was heated. Typically, when tears are collected via a capillary tube, which is a widely utilized collection method, on average approximately 10.0 &#181;L can be collected33. The dilution helps to address the limited sample volume and provide enough material for duplicate well testing. While this does reduce the theoretical limit of detection, the robust sensitivity of ddPCR should still result in the detection of all but an extremely few number of vector particles. This approach additionally creates a &#34;backup&#34; well if one were to unexpectedly fail. In this case, or in cases of insufficient sample volume to run two wells, the Poisson error could be used to assess precision. Furthermore, in cases where the concentration is below the limit of detection, it creates an opportunity to merge well data to determine a concentration. It is necessary to liberate the AAV vectors from the viral capsids for ddPCR detection. Some methods for the quantification of AAV have included a proteinase K digestion step to remove the viral capsid34,35,36. All naturally occurring AAV serotypes have melting temperatures at or below approximately 90 &#176;C, with most falling below 80 &#176;C; therefore, this appears to be an unnecessary inclusion37. Heating alone appears to be sufficient to release vector DNA.
Furthermore, ddPCR is generally less susceptible to PCR inhibitors that may be present in a sample that may affect a qPCR assay. If a specific DNA isolation step is included, this would also require specific validation, which is avoided in this protocol. Samples are diluted prior to heating due to the kinetics of diffusion of the vector genomes in a liquid. During the heating and subsequent cooling process, the positive and negative sense strands of the single-stranded DNA genome can anneal together to produce a double-stranded intermediate if the concentrations are sufficiently high. Dilution prior to heating reduces the concentrations and makes it mathematically unlikely that enough double-stranded intermediates form to have an adverse effect on the accuracy of quantification. It should be noted that the synthetic DNA fragments or linearized plasmids used as quality controls must not undergo this heating step. As these are double-stranded, heating would result in conversion to single-stranded intermediates. Following independent partitioning of these single-stranded QCs into droplets, this would be expected to result in a twofold increase in QC concentration relative to the nominal concentration. Alternatively, if QCs are to be heated to standardize the method, this must be factored into the reconstitution and assignment of a nominal concentration.
Finally, with regards to sample preparation, many protocols also recommend the inclusion of a DNase treatment step to remove any unencapsidated vector DNA. This step is critical in cases where it is not desired to quantify free DNA associated with the vector preparation (such as during quantification for dosage purposes). However, in the context of biodistribution and bioshedding studies, one typically desires to know where any vector DNA has traveled, regardless of if it is encapsidated or not. Therefore, it is suggested to typically not perform a DNase treatment step during such studies. If it is determined to be necessary to include a DNase step, this step should be prior to dilutions and heating.
In this paper, data representative of the approach to assessment of the dynamic range, sensitivity, accuracy, and precision of the method within the context of a fit-for-purpose, good laboratory practice compliant validation are presented. The current lack of guidance on this topic leaves validating laboratories to determine target assay criteria for themselves, in line with current industry thinking. Different groups have posed both higher and lower target criteria than used in this study19,20,21,22,23,24,25. The target assay criteria, until more rigidly defined, should be selected prior to validation based on the intended clinical applications of the method. Depending on the downstream decisions to be made on the basis of the data, higher levels of accuracy and precision may be needed. Conversely, a simple positive versus negative result may be sufficient.
The approach also addressed recommendations for the assessment of specificity and a matrix effect. A pool of tears collected from untreated individuals failed to produce a positive result in this assay, whereas the target could be detected when the vector was spiked into the tears at a high and low concentration within the recommended recovery rates. Ideally, matrix containing endogenous vector (e.g., collected following treatment with viral vector) would also be included in these assessments. However, it is unlikely that such samples will be available for use in a validation. To increase the robustness of the validation, multiple pools of tears, or tears collected from a variety of individuals, could be assessed to determine if a patient-specific matrix effect occurs. Finally, it is recommended to evaluate the stability. In workflows where DNA extraction occurs out of the biological matrix, it may be necessary to evaluate the stability of both the sample and the extracted DNA. In this workflow, the sample is tested directly in the assay without the need for DNA extraction. Therefore, in consideration of the evaluation of the stability for this method, one must evaluate the stability of the tear samples. Typically, benchtop, refrigerator, freeze/thaw, and long-term stability assessments are recommended. These were not performed as part of this study, but the methods developed here can be used in this assessment, following manipulations to the input samples.
Overall, this method has been demonstrated to be a robust, repeatable, and validatable assay to detect AAV-based vectors in tear samples. It may serve as a platform to be adapted to specific vectors to support clinical trials and provides a basis for validation of an assay consistent with good laboratory practices.

Gene therapy definitions vary, but generally induce an intentional and often expected permanent alternation of a specific DNA sequence of the cellular genome to modify or manipulate the expression of a gene or to alter the biological properties of a living cell for a clinical purpose1,2. Viral vectors are increasingly being used as vehicles for gene therapy due to their efficiency of transduction, with one report suggesting that over 70% of current gene therapy clinical trials utilize viral vectors3. Interest in viral vectors for gene therapy has been gaining steadily. The Quarter 4 2022 Quarterly Data Report on the Gene, Cell, and RNA therapy landscape from the American Society of Gene and Cell Therapy reported that in 2022, the gene, cell, and RNA therapy pipeline from preclinical to pre-registration grew by 7%, bringing the total number of therapies in development to 3,726, of which 2,053 (55%) were gene therapies4. The United States Food and Drug Administration (USA FDA) currently has approved 27 cell and gene therapies for clinical use in humans, five of which specifically utilize viral vectors5.
Adeno-associated viruses (AAVs) have gained specific interest as vehicles for gene therapy. A recent meta-analysis revealed that there have been approximately 136 clinical trials investigating the use of AAVs in the past two decades6. Additionally, three of the five USA FDA approved gene therapies are AAV based. This is due to their highly editable nature, broad host range that can be tuned based on the use of specific naturally occurring or artificially engineered vectors, low pathogenicity and toxicity in humans, and generally low immunogenicity7,8. AAVs have also been successfully used to treat ocular diseases in an approved clinical setting. Voretigene neparvovec-rzyl is an AAV2-based therapy that was approved by the USA FDA in 2017 and by the European Medicines Agency (EMA) in 2018 to treat biallelic RPE65 mutation-associated retinal dystrophy9.
With increasing interest in the development of AAV-based therapies comes the need for regulatory guidance on assays. Accurate detection and quantification of any viral vector is an integral part of the discovery, manufacturing, and preclinical/clinical testing phases of product development. The USA FDA has begun to issue some guidance for gene therapies, including on the chemistry, manufacturing, and control for human gene therapy investigational new drug applications10, long-term follow-up after administration of gene therapy11, replication-competent retrovirus testing12, and recommendations for microbial vectors used in gene therapies13. The EMA has also released a series of guidelines concerning the development of gene therapy products that generally align with the FDA recommendations, though some differences do exist14. It is important to note that while these guidance do not establish legally enforceable responsibilities, except where specific regulations are referenced, they provide clarity on the current thinking from regulatory agencies on the topic and their expectations for assays required for drug filings and regulatory approval.
The FDA specifically recommends that studies should be conducted to assess the distribution, persistence, and clearance of a vector from the site of administration to target ocular and non-ocular tissues, intraocular fluids, and blood15. These take the form of biodistribution and shedding studies. Biodistribution studies evaluate exposure by investigating how a product is spread throughout a patient&#39;s body from the site of administration. Shedding specifically evaluates the release of the product from the patient into the environment and raises the possibility of transmission of the vector to untreated individuals16. The FDA makes recommendations for the design of biodistribution and shedding studies with respect to the frequency of sample collection, duration of sample collection, types of samples collected, and storage conditions.
Additionally, the FDA recommends the use of quantitative polymerase chain reaction (qPCR, or real-time PCR) for the quantitative detection of vector genomes due to its ease of performance, high-throughput format, rapid turnaround times, and assay sensitivity. However, there is a relative lack of recommendations for the design and performance assessment of molecular methods compared to those which exist for small and large molecules. Many of the guidelines for such studies are difficult to apply to molecular methods due to the unique and complex design of both the products and the assays themselves, raising questions as to the appropriateness of the available platforms for the recommended assessments and appropriate methods for assay validation. To date, the FDA has not required formal validation of PCR-based assays, though the EMA has imposed this requirement17. In light of this void, different groups and workshops have issued white papers and recommendations that manufacturers and contract research organizations have sought to follow18,19,20,21,22,23,24,25. Most of these recommendations are written specifically with qPCR assays in mind, with suggestions or alterations for emerging platforms, such as droplet digital PCR (ddPCR), included only as deemed relevant. More recent recommendations have focused on considerations for ddPCR assays, but have largely focused on their applications to vector genome quantification in a manufacturing setting rather than in the complex biological matrices encountered in bioshedding studies.
Depending on clinical application and goals, ddPCR may be preferred over qPCR in support of biodistribution and shedding studies due to ddPCR&#39;s increased sensitivity and ability to handle matrix interference compared to qPCR. Furthermore, due to the partitioning of samples into approximately 20,000 droplets, accurate quantification of the copy number can be achieved without the use of a standard curve using Poisson statistics, simplifying the method development and validation. The goal of this protocol is to describe a standardized approach for the development and validation of a ddPCR-based method for the detection of AAV vectors in tears collected from the ocular surface in support of clinical bioshedding studies.

<table><tbody><tr><td>AAV-eGFP Vector</td><td>Charles River Laboratories</td><td>RS-AAV2-FL</td><td>Lot AAV2-0720-FL, used as a proof of principle vector</td></tr><tr><td>AutoDG Droplet Digital PCR system</td><td>Bio-Rad</td><td>QX200</td><td>Alternative ddPCR system may be used following manufacturer&amp;rsquo;s protocol.</td></tr><tr><td>AutoDG Oil for Probes</td><td>Bio-Rad</td><td>1864110</td><td>Or use material compatible with ddPCR system.</td></tr><tr><td>ddPCR Buffer Control for Probes</td><td>Bio-Rad</td><td>1863052</td><td>Or use material compatible with ddPCR system and PCR chemistry.</td></tr><tr><td>ddPCR Droplet Reader Oil</td><td>Bio-Rad</td><td>1863004</td><td>Or use material compatible with ddPCR system.</td></tr><tr><td>ddPCR Piercable Foil Seals</td><td>Bio-Rad</td><td>1814040</td><td>Or use material compatible with ddPCR system.</td></tr><tr><td>ddPCR Plates 96-Well, Semi-Skirted</td><td>Bio-Rad</td><td>12001925</td><td>Or use material compatible with ddPCR system.</td></tr><tr><td>ddPCR Supermix for Probes (no dUTP)</td><td>Bio-Rad</td><td>1863023, 1863024, or 1863025</td><td>Use master mix compatible with primers/probes and ddPCR system.</td></tr><tr><td>DG32 AutoDG Cartidges</td><td>Bio-Rad</td><td>1864108</td><td>Or use material compatible with ddPCR system.</td></tr><tr><td>Droplet Reader</td><td>Bio-Rad</td><td>QX200</td><td>Alternative ddPCR system may be used following manufacturer&amp;rsquo;s protocol.</td></tr><tr><td>GeneAmp PCR Buffer</td><td>Applied Biosystems</td><td>N8080129</td><td>N/A</td></tr><tr><td>Nuclease-Free Water</td><td>Ambion</td><td>AM9906</td><td>N/A</td></tr><tr><td>PCR Plate Sealer</td><td>Bio-Rad</td><td>PX1</td><td>Or use material compatible with ddPCR system.</td></tr><tr><td>Pipet Tips for AutoDG</td><td>Bio-Rad</td><td>1864120</td><td>Or use material compatible with ddPCR system.</td></tr><tr><td>Pluronic F-68 Non-ionic Surfactant</td><td>Gibco</td><td>24040</td><td>N/A</td></tr><tr><td>Primer and Hydrolysis Probes</td><td>Various</td><td>Various</td><td>Design based on target sequence using general approaches for primer/probe design. Select fluorphores and quenchers compatible with ddPCR system.</td></tr><tr><td>Restriction Enzyme</td><td>Various</td><td>Various</td><td>Varies with target amplification sequence. Use restriction enzyme that does not cut in the amplified sequence</td></tr><tr><td>Sheared salmon sperm DNA</td><td>ThermoFisher</td><td>AM9680</td><td>N/A</td></tr><tr><td>Synthetic DNA gene fragment or linearized plasmid</td><td>Various</td><td>Various</td><td>Design a synthetic DNA fragment containing the target amplification region for use as a quality control</td></tr><tr><td>TE Buffer</td><td>Teknova</td><td>T0224</td><td>Ensure prepared or purchases nuclease free. 10 mM Tris-HCl, 1.0 mM EDTA, pH=8.0</td></tr><tr><td>Touch Thermal Cycler</td><td>Bio-Rad</td><td>C1000</td><td>Or use material compatible with ddPCR system.</td></tr></tbody></table>

a validatable droplet digital polymerase chain reaction assay for the detection of adeno-associated viral vectors in bioshedding studies of tears

The use of viral vectors to treat genetic diseases has increased substantially in recent years, with over 2,000 studies registered to date. Adeno-associated viral (AAV) vectors have found particular success in the treatment of eye related diseases, as exemplified by the approval of voretigene neparvovec-rzyl. To bring new therapies to market, regulatory agencies typically request qualified or validated bioshedding studies to evaluate release of the vector into the environment. However, no official guidelines for the development of molecular based assays to support such shedding studies have been released by the United States Food and Drug Administration, leaving developers to determine best practices for themselves. The purpose of this protocol is to present a validatable protocol for the detection of AAV vectors in human tears by droplet digital polymerase chain reaction (ddPCR) in support of clinical bioshedding studies. This manuscript discusses current industry approaches to molecular assay validation and demonstrates that the method exceeds the target assay acceptance criteria currently proposed in white papers. Finally, steps critical in the performance of any ddPCR assay, regardless of application, are discussed.

For demonstrative purposes, an assay designed to detect a commercially available, enhanced green fluorescent protein (eGFP)-expressing AAV2 vector, with a synthetic double-stranded DNA fragment containing eGFP as a quality control, was developed. Currently, there is ongoing debate as to whether the vector itself or a synthetic DNA fragment or linearized plasmid is most appropriate for use as the QC. Generally, a synthetic DNA fragment or linearized plasmid may be used if equivalency to the vector is demonstrated in method development (data not shown). Primers and probes were designed and optimized to detect the eGFP transgene. Refer to Supplementary Table S1 for the sequences used in this work. The concentration of the QC fragment stock was empirically determined using ddPCR. All assays were performed using the concentrations and PCR conditions given as examples in the protocol section.
For qPCR assays, it is recommended to evaluate the linearity, sensitivity, dynamic range, accuracy, and precision of the standard curve. Since ddPCR does not rely on a standard curve for target quantification, these recommendations must be modified. Instead, QCs consisting of synthetic double-stranded DNA fragments diluted to various concentrations to span the expected quantifiable range of a ddPCR reaction based on the Poisson statistical modeling were utilized29,30,31,32 to define the dynamic range and sensitivity and to evaluate accuracy and precision. The choice of QC concentrations was based primarily on the expected ratio of positive to total droplets within a well at a given concentration. Mathematically, ddPCR is theoretically most accurate when approximately 80% of the partitions positively amplify. As the positive to total droplet ratio increases above 0.8, the accuracy decreases due to saturation of the partitions, with quantification not being possible once 100% of the droplets are positive. On the low end, theoretically, as little as one positive droplet may be detected and quantified, though the accuracy is poorer and the assay is subject to low-level false positives. Typically, at least three droplets must be positive for a result to be calculated with 95% confidence, which is the threshold to calculate a concentration we used here.
A series of five different QC concentrations was prepared, with the target copy number/&#181;L PCR reaction volumes calculated expected to yield positive to total droplet ratios spanning the quantifiable range of ddPCR, as shown in Table 5. These were used to evaluate the accuracy and precision of the assay. In the assessment here, the upper and lower limits of quantification were not pushed to the theoretical maximum possible in ddPCR. Accurate quantification may be possible at higher and lower levels than demonstrated here. The range should be developed in alignment with the downstream applications of this method.
A total of three independently prepared dilution series of these QCs were prepared in sample dilution buffer for each batch to evaluate the intra-assay accuracy and precision. Duplicate wells of each QC dilution were included. To simulate an actual validation protocol, a total of six accuracy and precision batches were performed by multiple analysts over multiple days. The results from these six batches were analyzed to define the intra-assay and inter-assay accuracy and precision of the method and to define the dynamic range of the assay.
Intra-assay performance was assessed for each batch at each QC level. We expected that all QC and NTC wells would have at least 10,000 droplets. This was met in 216 out of 216 wells tested across all six batches, with an average droplet count of 19,748 droplets/well (Table 6). Next, the inter-well %CV of each set of duplicate wells of each QC was expected to be &#8804;25.0%, except for the upper and lower limit QC, where &#8804;30.0% was expected. This was met in sets of 90 out of 90 wells tested across all six batches for the QCs, with an average inter-well %CV of 3.9% across all the QC levels (Table 7). All QCs yielded mean positive to total droplet ratios within the expected ranges outlined above (Table 6).
Within each batch, the intra-assay mean and standard deviation were calculated for each of the independently prepared dilution series points, and these were used to calculate an intra-assay mean for each concentration in each assay. This was used to assess the accuracy and precision of the assay (Table 8). Precision refers to the variability in the data from replicates of the same homogenous sample under normal assay conditions and is evaluated by calculating the %CV of the multiple included aliquots. We expected that the three aliquots tested within each batch would yield an intra-assay %CV &#8804;25.0%, except for the upper and lower limit QC where &#8804;30.0% was expected. This was met for all five QC levels in each of the 60 batches (30 out of 30 total performances). Generally, greater intra-assay precision than the target criteria could be achieved, with a mean intra-assay %CV of 7.7% across all QC levels. Accuracy refers to the closeness of agreement between the experimentally determined value and the nominal value. This is evaluated by calculating the percent relative error (%RE, or %Bias) between the calculated concentrations of each QC and their theoretically expected nominal concentrations. It was expected that the intra-assay mean of the three aliquots would be &#177;25.0% RE of the nominal concentration, except for the upper and lower limit QC where &#177;30.0% was expected. This was met for all five QC levels in each of the 60 batches (30 out of 30 total performances). Generally, greater intra-assay accuracy than our target could be achieved, with a mean absolute intra-assay %RE of 4.2% across all QC levels. In all performances of the NTC (30 total), no positive droplets were detectable.
Inter-assay accuracy and precision were also calculated using the intra-assay mean of each QC level within each batch. The inter-assay precision was expected to be &#8804;25.0% CV, except for the upper and lower limit QC where &#8804;30.0% was expected. Likewise, for inter-assay accuracy, &#177;25.0% RE was expected, except for the upper and lower limit QC where &#177;30.0% was expected. A significantly greater inter-assay accuracy and precision than these targets were observed (Table 9), with an inter-assay precision ranging from 4.0% to 8.5% and an inter-assay absolute accuracy ranging from 1.0% to 3.2%. Collectively, these results demonstrate that this method can achieve sufficient intra- and inter-assay accuracy and precision well within current industry targets. A dynamic range of this assay of 2,500-2.5 copies per &#181;L of PCR reaction can be defined based on these results, with an overall assay sensitivity of 2.5 copies per &#181;L of PCR reaction. As previously mentioned, it may be possible to validate wider dynamic ranges.
Next, it was necessary to evaluate assay accuracy and precision within the target matrix - in this case, tears. Typically, assays are validated prior to the initiation of clinical studies, meaning that tears collected from vector-treated patients are unlikely to be available for validation purposes. This can be artificially created by spiking the target AAV vector into tears collected from volunteer donors to create matrix-spiked QCs. Pooled human tears were collected by a third party (BioIVT). For proof of principle, an eGFP-expressing AAV2 vector acquired from a commercial source was utilized. The concentration of the AAV2 vector stock was empirically determined using ddPCR, without the use of a DNA isolation step, as described in this protocol. In each run, the AAV2 was independently spiked into the three tear aliquots at a high (expected 1.41 x 103 copies/&#181;L PCR reaction) and low (28.2 copies/&#181;L PCR reaction) level. Unspiked aliquots were included as a control to demonstrate the specificity of the method.
Intra-assay performance was assessed for each batch at each spike level. It was expected that all tear samples would have at least 10,000 droplets. This was met in 108 out of 108 wells tested across all six batches, with a mean total droplet number of 20,208 droplets/well (Table 10). Next, the inter-well %CV of each set of duplicate wells of each QC was expected to be &#8804;25.0% for the high and low spike levels. This was met in 36 out of 36 sets of wells tested across all six batches for the QCs, with a mean inter-well %CV of 3.2% (Table 11).
Within each batch, the intra-assay mean and standard deviation were calculated for each of the independently prepared tear spikes, and these were used to calculate an intra-assay mean for each concentration in each assay. This was used to assess the accuracy and precision of the assay in matrix (Table 12). We expected the intra-assay %CV to be &#8804;25.0% and high and low spike levels. This was met in six out of six batches for each level. Generally, greater intra-assay precision in matrix than the target could be achieved, with a mean intra-assay %CV of 3.7% at the high level and 12.2% at the low level (overall 8.0%). It was also expected the intra-assay %RE would be &#177;25.0% at both spike levels. This was met in six out of six batches for each level. Likewise, it was generally found that greater intra-assay accuracy in matrix than the target could be achieved, with a mean intra-assay absolute %RE of 8.1% at the low level and 11.3% at the high level (overall 9.7%). For the unspiked control, no eGFP signal was detectable in any of the aliquots (Table 12), demonstrating the specificity of the method in the human tear matrix.
Inter-assay accuracy and precision in tear matrix were also calculated using the intra-assay mean of each spike level within each batch. It was expected that the inter-assay precision would be &#8804;25.0% CV, and for inter-assay accuracy, we expected &#177;25.0% RE. A significantly greater inter-assay accuracy and precision than these targets were observed (Table 13), with an inter-assay precision of 5.5% at the high level and 7.1% at the low level, and with absolute inter-assay accuracy of 11.3% at the high level and 8.1% at the low level. Collectively, these results demonstrate the accuracy, precision, and specificity of the method in tear matrix.
Table 5: Quality controls used to define the dynamic range of the assay. Abbreviations: ULQC = upper limit quality control; HQC = high quality control; MQC = medium quality control; LQC = low quality control; LLQC = lower limit quality control; NTC = no template control. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65495/Longacre Table 5.xlsx" target="_blank">Please click here to download this Table.</a>
Table 6: Total droplet counts and positive to total droplet ratios of synthetic double-stranded DNA quality control and NTC. Abbreviations: ULQC = upper limit quality control; HQC = high quality control; MQC = medium quality control; LQC = low quality control; LLQC = lower limit quality control; NTC = no template control. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65495/Longacre Table 6.xlsx" target="_blank">Please click here to download this Table.</a>
Table 7: QC inter-well statistics (copy targets/&#181;L PCR reaction). Abbreviations: ULQC = upper limit quality control; HQC = high quality control; MQC = medium quality control; LQC = low quality control; LLQC = lower limit quality control; NTC = no template control. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65495/Longacre Table 7.xlsx" target="_blank">Please click here to download this Table.</a>
Table 8: Intra-assay accuracy and precision of QCs (copy targets/&#181;L PCR reaction). Abbreviations: ULQC = upper limit quality control; HQC = high quality control; MQC = medium quality control; LQC = low quality control; LLQC = lower limit quality control; NTC = no template control. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65495/Longacre Table 8.xlsx" target="_blank">Please click here to download this Table.</a>
Table 9: Inter-assay accuracy and precision of QCs (copy targets/&#181;L PCR reaction). Abbreviations: ULQC = upper limit quality control; HQC = high quality control; MQC = medium quality control; LQC = low quality control; LLQC = lower limit quality control; NTC = no template control. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65495/65495_Longacre Table 9.xlsx" target="_blank">Please click here to download this Table.</a>
Table 10: Total droplet counts of tear samples. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65495/Longacre Table 10.xlsx" target="_blank">Please click here to download this Table.</a>
Table 11: Tear sample inter-well statistics (copy targets/&#181;L PCR reaction). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65495/Longacre Table 11.xlsx" target="_blank">Please click here to download this Table.</a>
Table 12: Intra-assay accuracy and precision of tear samples (copy targets/&#181;L PCR reaction). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65495/Longacre Table 12.zip" target="_blank">Please click here to download this Table.</a>
Table 13: Inter-assay accuracy and precision of tear samples (copy targets/&#181;L PCR reaction). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65495/65495_Longacre Table 13.xlsx" target="_blank">Please click here to download this Table.</a>
Supplementary Table S1: Sequences of primer, probes, and synthetic double-stranded DNA quality control utilized in this study. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65495/65495_Longacre Supp. Table 1.xlsx" target="_blank">Please click here to download this Table.</a>

Watch this Scientific Journal Video about Addressing Regulatory Gaps in Molecular Studies by Quantifying Viral Vectors in Complex Matrices at JoVE.com

Author Spotlight: Addressing Regulatory Gaps in Molecular Studies by Quantifying Viral Vectors in Complex Matrices 

Here, we present a protocol for the development and validation of good laboratory practices in the compliant detection of adeno-associated viral vectors in human tears by droplet digital polymerase chain reaction in support of clinical development of gene therapy vectors.

A Validatable Droplet Digital Polymerase Chain Reaction Assay for the Detection of Adeno-Associated Viral Vectors in Bioshedding Studies of Tears

The use of viral vectors to treat genetic diseases has increased substantially in recent years, with over 2,000 studies registered to date. ...

a-validatable-droplet-digital-polymerase-chain-reaction-assay-for

Nanyang Technological University

Research

JoVE Journal

Biology

1.8K Views.  KCAS Bioanalytical and Biomarker Services. Here, we present a protocol for the development and validation of good laboratory practices in the compliant detection of adeno-associated viral vectors in human tears by droplet digital polymerase chain reaction in support of clinical development of gene therapy vectors. 

Video: Author Spotlight: Addressing Regulatory Gaps in Molecular Studies by Quantifying Viral Vectors in Complex Matrices 

Mutagenesis and Functional Analysis of Ion Channels Heterologously Expressed in Mammalian Cells

We will demonstrate how to study the functional effects of introducing a point mutation in an ion channel. We study G protein-gated inwardly rectifying potassium (referred to as GIRK) channels, which are important for regulating the excitability of neurons. There are four different mammalian GIRK channel subunits (GIRK1-GIRK4) - we focus on GIRK2 because it forms a homotetramer. Stimulation of different types of G protein-coupled receptors (GPCRs), such as the muscarinic receptor (M2R), leads to activation of GIRK channels. Alcohol also directly activates GIRK channels. We will show how to mutate one amino acid by specifically changing one or more nucleotides in the cDNA for the GIRK channel. This mutated cDNA sequence will be amplified in bacteria, purified, and the presence of the point mutation will be confirmed by DNA sequencing. The cDNAs for the mutated and wild-type GIRK channels will be transfected into human embryonic kidney HEK293T cells cultured in vitro. Lastly, whole-cell patch-clamp electrophysiology will be used to study the macroscopic potassium currents through the ectopically expressed wild-type or mutated GIRK channels. In this experiment, we will examine the effect of a L257W mutation in GIRK2 channels on M2R-dependent and alcohol-dependent activation.

We will demonstrate how to study the effect of a single point mutation on the function of an ion channel.

We will demonstrate how to study the functional effects of introducing a point mutation in an ion channel. We study G protein-gated inwardly rectifying ...

Polymerase Chain Reaction: Basic Protocol Plus Troubleshooting and Optimization Strategies

In the biological sciences there have been technological advances that catapult the discipline into golden ages of discovery. For example, the field of microbiology was transformed with the advent of Anton van Leeuwenhoek&#39;s microscope, which allowed scientists to visualize prokaryotes for the first time. The development of the polymerase chain reaction (PCR) is one of those innovations that changed the course of molecular science with its impact spanning countless subdisciplines in biology. The theoretical process was outlined by Keppe and coworkers in 1971; however, it was another 14 years until the complete PCR procedure was described and experimentally applied by Kary Mullis while at Cetus Corporation in 1985. Automation and refinement of this technique progressed with the introduction of a thermal stable DNA polymerase from the bacterium Thermus aquaticus, consequently the name Taq DNA polymerase.
PCR is a powerful amplification technique that can generate an ample supply of a specific segment of DNA (i.e., an amplicon) from only a small amount of starting material (i.e., DNA template or target sequence). While straightforward and generally trouble-free, there are pitfalls that complicate the reaction producing spurious results. When PCR fails it can lead to many non-specific DNA products of varying sizes that appear as a ladder or smear of bands on agarose gels. Sometimes no products form at all. Another potential problem occurs when mutations are unintentionally introduced in the amplicons, resulting in a heterogeneous population of PCR products. PCR failures can become frustrating unless patience and careful troubleshooting are employed to sort out and solve the problem(s). This protocol outlines the basic principles of PCR, provides a methodology that will result in amplification of most target sequences, and presents strategies for optimizing a reaction. By following this PCR guide, students should be able to: 
 
&#9679; Set up reactions and thermal cycling conditions for a conventional PCR experiment 
&#9679; Understand the function of various reaction components and their overall effect on a PCR experiment 
&#9679; Design and optimize a PCR experiment for any DNA template 
&#9679; Troubleshoot failed PCR experiments

PCR has emerged as a common technique in many molecular biology laboratories. Provided here is a quick guide to several conventional PCR protocols. Because each reaction is a unique experiment, optimal conditions required to generate a product vary. Understanding the variables in a reaction will greatly enhance troubleshooting efficiency, thereby increasing the chance to obtain the desired result.

In the biological sciences there have been technological advances that catapult the discipline into golden ages of discovery. For example, the field of ...

Detection of Viral RNA by Fluorescence in situ Hybridization (FISH)

Viruses that infect cells elicit specific changes to normal cell functions which serve to divert energy and resources for viral replication. Many aspects of host cell function are commandeered by viruses, usually by the expression of viral gene products that recruit host cell proteins and machineries. Moreover, viruses engineer specific membrane organelles or tag on to mobile vesicles and motor proteins to target regions of the cell (during de novo infection, viruses co-opt molecular motor proteins to target the nucleus; later, during virus assembly, they will hijack cellular machineries that will help in the assembly of viruses). Less is understood on how viruses, in particular those with RNA genomes, coordinate the intracellular trafficking of both protein and RNA components and how they achieve assembly of infectious particles at specific loci in the cell. The study of RNA localization began in earlier work. Developing lower eukaryotic embryos and neuronal cells provided important biological information, and also underscored the importance of RNA localization in the programming of gene expression cascades. The study in other organisms and cell systems has yielded similar important information. Viruses are obligate parasites and must utilise their host cells to replicate. Thus, it is critical to understand how RNA viruses direct their RNA genomes from the nucleus, through the nuclear pore, through the cytoplasm and on to one of its final destinations, into progeny virus particles 1.
FISH serves as a useful tool to identify changes in steady-state localization of viral RNA. When combined with immunofluorescence (IF) analysis 22, FISH/IF co-analyses will provide information on the co-localization of proteins with the viral RNA3. This analysis therefore provides a good starting point to test for RNA-protein interactions by other biochemical or biophysical tests 4,5, since co-localization by itself is not enough evidence to be certain of an interaction. In studying viral RNA localization using a method like this, abundant information has been gained on both viral and cellular RNA trafficking events 6. For instance, HIV-1 produces RNA in the nucleus of infected cells but the RNA is only translated in the cytoplasm. When one key viral protein is missing (Rev) 7, FISH of the viral RNA has revealed that the block to viral replication is due to the retention of the HIV-1 genomic RNA in the nucleus 8. 
Here, we present the method for visual analysis of viral genomic RNA in situ. The method makes use of a labelled RNA probe. This probe is designed to be complementary to the viral genomic RNA. During the in vitro synthesis of the antisense RNA probe, the ribonucleotide that is modified with digoxigenin (DIG) is included in an in vitro transcription reaction. Once the probe has hybridized to the target mRNA in cells, subsequent antibody labelling steps (Figure 1) will reveal the localization of the mRNA as well as proteins of interest when performing FISH/IF.

Detection of Viral RNA by Fluorescence in situ Hybridization FISH

A fluorescence in situ hybridization (FISH) method was developed to visually detect viral genomic RNA using fluorescence microscopy. A probe is made with specificity to the viral RNA that can then be identified using a combination of hybridization and immunofluorescence techniques. This technique offers the advantage of identifying the localization of the viral RNA or DNA at steady-state, providing information on the control of intracellular virus trafficking events.

Viruses  that infect cells elicit specific changes to normal cell functions which serve  to divert energy and resources for viral replication. Many ...

Standardized Protocol for Viral Genome Quantification Using Digital Droplet PCR

Quantification of Adeno-Associated Viral Genomes in Purified Vector Samples by Digital Droplet Polymerase Chain Reaction

Adeno-associated virus (AAV) is a non-pathogenic virus used as a delivery vehicle to transfer therapeutic genes into patients. Accurate quantification of AAV genome copy number in vector preparations is essential for bioprocess optimization and dosage calculation in both preclinical and clinical studies of AAV-based gene therapy products. Currently, a consensus protocol for AAV viral genome titration is lacking. Here, we present a digital droplet PCR (dd_PCR) protocol for the quantification of viral genomes in purified vector samples. Samples are treated with DNase I to eliminate unpackaged contaminant DNA. DNase-treated samples are then mixed with an appropriate primer-probe set (designed according to the target AAV genome) and PCR reagents, and then loaded into a droplet generator. The prepared droplets are transferred into a PCR plate, where PCR amplification is performed and analyzed. The viral genome titer is calculated based on the concentration (copies/&#181;L), accounting for sample dilutions. A successful measurement shows a clear separation of the positive and negative droplet clouds, has at least 10,000 accepted droplets, shows a value between 10 copies/&#181;L and 10,000 copies/&#181;L, and has a coefficient of variation (CV) between repeats lower than 20%. Reliable viral genome titration will aid in the development of safe and effective AAV-based gene therapy products.

Author Spotlight: Optimizing Digital Droplet PCR Method for Accurate Adeno-Associated Viral Genome Quantification

Precise quantification of adeno-associated virus (AAV) vector genome copies is critical, but a standardized protocol has yet to be established. This protocol describes a validated method for preparing purified AAV samples and conducting digital droplet polymerase chain reaction (dd_PCR) to reliably quantify the viral genome titer.

Adeno-associated virus (AAV) is a non-pathogenic virus used as a delivery vehicle to transfer therapeutic genes into patients. Accurate quantification of ...

Bioengineering

Digital Droplet PCR Method for the Quantification of AAV Transduction Efficiency in Murine Retina

Many retinal cell biology laboratories now routinely use Adeno-associated viruses (AAVs) for gene editing and regulatory applications. The efficiency of AAV transduction is usually critical, which affects the overall experimental outcomes. One of the main determinants for transduction efficiency is the serotype or variant of the AAV vector. Currently, various artificial AAV serotypes and variants are available with different affinities to host cell surface receptors. For retinal gene therapy, this results in varying degrees of transduction efficiencies for different retinal cell types. In addition, the injection route and the quality of AAV production may also affect the retinal AAV transduction efficiencies. Therefore, it is essential to compare the efficiency of different variants, batches, and methodologies. The digital droplet PCR (dd-PCR) method quantifies the nucleic acids with high precision and allows performing absolute quantification of a given target without any standard or a reference. Using dd-PCR, it is also feasible to assess the transduction efficiencies of AAVs by absolute quantification of AAV genome copy numbers within an injected retina. Here, we provide a straightforward method to quantify the transduction rate of AAVs in retinal cells using dd-PCR. With minor modifications, this methodology can also be the basis for the copy number quantification of mitochondrial DNA as well as assessing the efficiency of base editing, critical for several retinal diseases and gene therapy applications.

This protocol presents how to quantify AAV transduction efficiency in mouse retina using digital droplet PCR (dd-PCR) together with small scale AAV production, intravitreal injection, retinal imaging, and retinal genomic DNA isolation.

Many retinal cell biology laboratories now routinely use Adeno-associated viruses (AAVs) for gene editing and regulatory applications. The efficiency of ...

Neuroscience

Development of a Quantitative Recombinase Polymerase Amplification Assay with an Internal Positive Control

It was recently demonstrated that recombinase polymerase amplification (RPA), an isothermal amplification platform for pathogen detection, may be used to quantify DNA sample concentration using a standard curve. In this manuscript, a detailed protocol for developing and implementing a real-time quantitative recombinase polymerase amplification assay (qRPA assay) is provided. Using HIV-1 DNA quantification as an example, the assembly of real-time RPA reactions, the design of an internal positive control (IPC) sequence, and co-amplification of the IPC and target of interest are all described. Instructions and data processing scripts for the construction of a standard curve using data from multiple experiments are provided, which may be used to predict the concentration of unknown samples or assess the performance of the assay. Finally, an alternative method for collecting real-time fluorescence data with a microscope and a stage heater as a step towards developing a point-of-care qRPA assay is described. The protocol and scripts provided may be used for the development of a qRPA assay for any DNA target of interest.

Provided is a protocol for developing a real-time recombinase polymerase amplification assay to quantify initial concentration of DNA samples using either a thermal cycler or a microscope and stage heater. Also described is the development of an internal positive control. Scripts are provided for processing raw real-time fluorescence data.

It was recently demonstrated that recombinase polymerase amplification (RPA), an isothermal amplification platform for pathogen detection, may be used to ...

Employing Digital Droplet PCR to Detect BRAF V600E Mutations in Formalin-fixed Paraffin-embedded Reference Standard Cell Lines

ddPCR is a highly sensitive PCR method that utilizes a water-oil emulsion system. Using a droplet generator, an extracted nucleic acid sample is partitioned into ~20,000 nano-sized, water-in-oil droplets, and PCR amplification occurs in individual droplets. The ddPCR approach is in identifying sequence mutations, copy number alterations, and select structural rearrangements involving targeted genes. Here, we demonstrate the use of ddPCR as a powerful technique for precisely quantitating rare BRAF V600E mutations in FFPE reference standard cell lines, which is helpful in identifying individuals with cancer. In conclusion, ddPCR technique offers the potential to precisely profile the specific rare mutations in different genes in various types of FFPE samples.

The goal of this video is to demonstrate how to perform&#160;automated DNA extraction from formalin-fixed paraffin-embedded (FFPE) reference standard cell lines and digital droplet PCR&#160;(ddPCR) analysis to detect rare mutations in a clinical setting. Detecting mutations in FFPE samples demonstrates the clinical utility of ddPCR in FFPE samples.

ddPCR is a highly sensitive PCR method that utilizes a water-oil emulsion system. Using a droplet generator, an extracted nucleic acid sample is ...

A Quantitative Dot Blot Assay for AAV Titration and Its Use for Functional Assessment of the Adeno-associated Virus Assembly-activating Proteins

While adeno-associated virus (AAV) is widely accepted as an attractive vector for gene therapy, it also serves as a model virus for understanding virus biology. In the latter respect, the recent discovery of a non-structural AAV protein, termed assembly-activating protein (AAP), has shed new light on the processes involved in assembly of the viral capsid VP proteins into a capsid. Although many AAV serotypes require AAP for assembly, we have recently reported that AAV4, 5, and 11 are exceptions to this rule. Furthermore, we demonstrated that AAPs and assembled capsids of different serotypes localize to different subcellular compartments. This unexpected heterogeneity in the biological properties and functional roles of AAPs among different AAV serotypes underscores the importance of studies on AAPs derived from diverse serotypes. This manuscript details a straightforward dot blot assay for AAV quantitation and its application to assess AAP dependency and serotype specificity in capsid assembly. To demonstrate the utility of this dot blot assay, we set out to characterize capsid assembly and AAP dependency of Snake AAV, a previously uncharacterized reptile AAV, as well as AAV5 and AAV9, which have previously been shown to be AAP-independent and AAP-dependent serotypes, respectively. The assay revealed that Snake AAV capsid assembly requires Snake AAP and cannot be promoted by AAPs from AAV5 and AAV9. The assay also showed that, unlike many of the common serotype AAPs that promote heterologous capsid assembly by cross-complementation, Snake AAP does not promote assembly of AAV9 capsids. In addition, we show that the choice of nuclease significantly affects the readout of the dot blot assay, and thus, choosing an optimal enzyme is critical for successful assessment of AAV titers.

This manuscript details a straightforward dot blot assay for quantitation of adeno-associated virus (AAV) titers and its application to study the role of assembly-activating proteins (AAPs), a novel class of non-structural viral proteins found in all AAV serotypes, in promoting the assembly of capsids derived from cognate and heterologous AAV serotypes.

While adeno-associated virus (AAV) is widely accepted as an attractive vector for gene therapy, it also serves as a model virus for understanding virus ...

Quantitative Proteomics Workflow using Multiple Reaction Monitoring Based Detection of Proteins from Human Brain Tissue

The proteomic analysis of the human brain tissue over the last decade has greatly enhanced our understanding of the brain. However, brain related disorders continue to be a major contributor of deaths around the world, necessitating the need for even greater understanding of their pathobiology. Traditional antibody-based techniques like western blotting or immunohistochemistry suffer from being low-throughput besides being labor-intensive and qualitative or semi-quantitative. Even conventional mass spectrometry-based shotgun approaches fail to provide conclusive evidence to support a certain hypothesis. Targeted proteomics approaches are largely hypothesis driven and differ from the conventional shotgun proteomics approaches that have been long in use. Multiple reaction monitoring is one such targeted approach that requires the use of a special mass spectrometer called the tandem quadrupole mass spectrometer or triple quadrupole mass spectrometer. In the current study, we have systematically highlighted the major steps involved in performing a successful tandem quadrupole mass spectrometry-based proteomics workflow using human brain tissue with an aim to introduce this workflow to a broader research community.

The protocol aims to introduce the use of a triple quadrupole mass spectrometer for Multiple Reaction Monitoring (MRM) of proteins from clinical samples. We have provided a systematic workflow starting from sample preparation to data analysis for clinical samples with all the necessary precautions to be taken.

The proteomic analysis of the human brain tissue over the last decade has greatly enhanced our understanding of the brain. However, brain related ...

Two-Step Reverse Transcription Droplet Digital PCR Protocols for SARS-CoV-2 Detection and Quantification

Diagnosis of the ongoing SARS-CoV-2 pandemic is a priority for all countries across the globe. Currently, reverse transcription quantitative PCR (RT-qPCR) is the gold standard for SARS-CoV-2 diagnosis as no permanent solution is available. However effective this technique may be, research has emerged showing its limitations in detection and diagnosis especially when it comes to low abundant targets. In contrast, droplet digital PCR (ddPCR), a recent emerging technology with superior advantages over qPCR, has been shown to overcome the challenges of RT-qPCR in diagnosis of SARS-CoV-2 from low abundant target samples. Prospectively, in this article, the capabilities of RT-ddPCR are further expanded by showing steps on how to develop simplex, duplex, triplex probe mix, and quadruplex assays using a two-color detection system. Using primers and probes targeting specific sites of the SARS-CoV-2 genome (N, ORF1ab, RPP30, and RBD2), the development of these assays is shown to be possible. Additionally, step by step detailed protocols, notes, and suggestions on how to improve the assays workflow and analyze data are provided. Adapting this workflow in future works will ensure that the maximum number of targets can be sensitively detected in a small sample significantly improving on cost and sample throughput.

This work summarizes steps on developing different assays for SARS-CoV-2 detection using a two color ddPCR system. The steps are elaborate and notes have been included on how to improve the assays and experiment performance. These assays may be used for multiple SARS-CoV-2 RT-ddPCR applications.

Diagnosis of the ongoing SARS-CoV-2 pandemic is a priority for all countries across the globe. Currently, reverse transcription quantitative PCR (RT-qPCR) ...