scholarly journals scAAVengr, a transcriptome-based pipeline for quantitative ranking of engineered AAVs with single-cell resolution

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Bilge E Öztürk ◽  
Molly E Johnson ◽  
Michael Kleyman ◽  
Serhan Turunç ◽  
Jing He ◽  
...  
Keyword(s):  
Single Cell ◽  
Genetic Research ◽  
Cell Types ◽  
Infection Rates ◽  
Adeno Associated Virus ◽  
Systemic Injection ◽  
Gene Therapies ◽  
Naturally Occurring ◽  
Large Animals ◽  
Therapy Center

Background:Adeno-associated virus (AAV)-mediated gene therapies are rapidly advancing to the clinic, and AAV engineering has resulted in vectors with increased ability to deliver therapeutic genes. Although the choice of vector is critical, quantitative comparison of AAVs, especially in large animals, remains challenging. Methods:Here, we developed an efficient single-cell AAV engineering pipeline (scAAVengr) to simultaneously quantify and rank efficiency of competing AAV vectors across all cell types in the same animal. Results:To demonstrate proof-of-concept for the scAAVengr workflow, we quantified - with cell-type resolution - the abilities of naturally occurring and newly engineered AAVs to mediate gene expression in primate retina following intravitreal injection. A top performing variant identified using this pipeline, K912, was used to deliver SaCas9 and edit the rhodopsin gene in macaque retina, resulting in editing efficiency similar to infection rates detected by the scAAVengr workflow. scAAVengr was then used to identify top-performing AAV variants in mouse brain, heart and liver following systemic injection. Conclusions:These results validate scAAVengr as a powerful method for development of AAV vectors. Funding:This work was supported by funding from the Ford Foundation, NEI/NIH, Research to Prevent Blindness, Foundation Fighting Blindness, UPMC Immune Transplant and Therapy Center, and the Van Sloun fund for canine genetic research.

scholarly journals scAAVengr: Single-cell transcriptome-based quantification of engineered AAVs in non-human primate retina

2020 ◽  
Author(s):  
Bilge E. Öztürk ◽  
Molly E. Johnson ◽  
Michael Kleyman ◽  
Serhan Turunç ◽  
Jing He ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Cell Types ◽  
Adeno Associated Virus ◽  
Gene Therapies ◽  
Naturally Occurring ◽  
Cell Transcriptome ◽  
Large Animals ◽  
Single Cell Transcriptome ◽  
Human Primate

AbstractAdeno-associated virus (AAV)-mediated gene therapies are rapidly advancing to the clinic, and AAV engineering has resulted in vectors with increased ability to deliver therapeutic genes. Although the choice of vector is critical, quantitative comparison of AAVs, especially in large animals, remains challenging. Here, we developed an efficient single-cell AAV engineering pipeline (scAAVengr) to quantify efficiency of AAV-mediated gene expression across all cell types. scAAVengr allows for definitive, head-to-head comparison of vectors in the same animal. To demonstrate proof-of-concept for the scAAVengr workflow, we quantified – with cell-type resolution – the abilities of naturally occurring and newly engineered AAVs to mediate gene expression in primate retina following intravitreal injection. A top performing variant, K912, was used to deliver SaCas9 and edit the rhodopsin gene in macaque retina, resulting in editing efficiency similar to infection rates detected by the scAAVengr workflow. These results validate scAAVengr as a powerful method for development of AAV vectors.

scholarly journals Quantitative single-cell transcriptome-based ranking of engineered AAVs in human retinal explants

2021 ◽  
Author(s):  
Zhouhuan Xi ◽  
Bilge E. Ozturk ◽  
Molly E. Johnson ◽  
Leah C. Byrne
Keyword(s):  
Single Cell ◽  
Viral Vector ◽  
Cell Types ◽  
Adeno Associated Virus ◽  
Altered Expression ◽  
Gene Therapies ◽  
Retinal Tissue ◽  
Retinal Explants ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

Gene therapy is a rapidly developing field, and adeno-associated virus (AAV) is a leading viral vector candidate for therapeutic gene delivery. Newly engineered AAVs with improved abilities are now entering the clinic. It has proven challenging, however, to predict the translational potential of gene therapies developed in animal models, due to cross-species differences. Human retinal explants are the only available model of fully developed human retinal tissue, and are thus important for the validation of candidate AAV vectors. In this study, we evaluated 18 wildtype and engineered AAV capsids in human retinal explants using a recently developed single-cell RNA-Seq AAV engineering pipeline (scAAVengr). Human retinal explants retained the same major cell types as fresh retina, with similar expression of cell-specific markers, except for a cone population with altered expression of cone-specific genes. The efficiency and tropism of AAVs in human explants were quantified, with single-cell resolution. The top performing serotypes, K91, K912, and 7m8, were further validated in non-human primate and human retinal explants. Together, this study provides detailed information about the transcriptome profiles of retinal explants, and quantifies the infectivity of leading AAV serotypes in human retina, accelerating the translation of retinal gene therapies to the clinic.

scholarly journals Adenine Base Editing in vivo with a Single Adeno-Associated Virus Vector

2021 ◽  
Author(s):  
Han Zhang ◽  
Nathan Bamidele ◽  
Pengpeng Liu ◽  
Ogooluwa Ojelabi ◽  
Xin D. Gao ◽  
...  
Keyword(s):  
Genetic Diseases ◽  
Cell Types ◽  
Vector System ◽  
Adeno Associated Virus ◽  
Base Editing ◽  
Guide Rna ◽  
Gene Therapies ◽  
Compact Size ◽  
Adenine Base

Base editors (BEs) have opened new avenues for the treatment of genetic diseases. However, advances in delivery approaches are needed to enable disease targeting of a broad range of tissues and cell types. Adeno-associated virus (AAV) vectors remain one of the most promising delivery vehicles for gene therapies. Currently, most BE/guide combinations and their promoters exceed the packaging limit (~5 kb) of AAVs. Dual-AAV delivery strategies often require high viral doses that impose safety concerns. In this study, we engineered an adenine base editor using a compact Cas9 from Neisseria meningitidis (Nme2Cas9). Compared to the well-characterized Streptococcus pyogenes Cas9-containing ABEs, Nme2-ABE possesses a distinct PAM (N4CC) and editing window, exhibits fewer off-target effects, and can efficiently install therapeutically relevant mutations in both human and mouse genomes. Importantly, we showed that in vivo delivery of Nme2-ABE and its guide RNA by a single-AAV vector can revert the disease mutation and phenotype in an adult mouse model of tyrosinemia. We anticipate that Nme2-ABE, by virtue of its compact size and broad targeting range, will enable a range of therapeutic applications with improved safety and efficacy due in part to packaging in a single-vector system.

scholarly journals Development of a Bispecific Antibody-Based Platform for Retargeting of Capsid Modified AAV Vectors

2021 ◽  
Vol 22 (15) ◽  
pp. 8355
Author(s):  
Juliane Kuklik ◽  
Stefan Michelfelder ◽  
Felix Schiele ◽  
Sebastian Kreuz ◽  
Thorsten Lamla ◽  
...  
Keyword(s):  
Bispecific Antibody ◽  
Tumor Stroma ◽  
Cell Types ◽  
Limiting Factor ◽  
Adeno Associated Virus ◽  
Gene Therapies ◽  
Programmed Death ◽  
Distinct Disease ◽  
Activated Fibroblasts ◽  
Surface Loops

A major limiting factor for systemically delivered gene therapies is the lack of novel tissue specific AAV (Adeno-associated virus) derived vectors. Bispecific antibodies can be used to redirect AAVs to specific target receptors. Here, we demonstrate that the insertion of a short linear epitope “2E3” derived from human proprotein-convertase subtilisin/kexin type 9 (PCSK9) into different surface loops of the VP capsid proteins can be used for AAV de-targeting from its natural receptor(s), combined with a bispecific antibody-mediated retargeting. We chose to target a set of distinct disease relevant membrane proteins—fibroblast activation protein (FAP), which is upregulated on activated fibroblasts within the tumor stroma and in fibrotic tissues, as well as programmed death-ligand 1 (PD-L1), which is strongly upregulated in many cancers. Upon incubation with a bispecific antibody recognizing the 2E3 epitope and FAP or PD-L1, the bispecific antibody/rAAV complex was able to selectively transduce receptor positive cells. In summary, we developed a novel, rationally designed vector retargeting platform that can target AAVs to a new set of cellular receptors in a modular fashion. This versatile platform may serve as a valuable tool to investigate the role of disease relevant cell types and basis for novel gene therapy approaches.

scholarly journals Transduction of gluconeogenic enzymes prolongs cone photoreceptor survival and function in models of retinitis pigmentosa

2019 ◽  
Author(s):  
Yashodhan Chinchore ◽  
Tedi Begaj ◽  
Christelle Guillermeir ◽  
Matthew L. Steinhauser ◽  
Claudio Punzo ◽  
...  
Keyword(s):  
Retinitis Pigmentosa ◽  
Genetic Defect ◽  
Metabolic Stress ◽  
Cell Types ◽  
Adeno Associated Virus ◽  
Gene Therapies ◽  
Degenerative Disorders ◽  
Medical Need ◽  
Hereditary Nature ◽  
And Function

AbstractThe hereditary nature of many retinal degenerative disorders makes them potentially amenable to corrective gene therapies. Numerous clinical trials are ongoing with the goal to rectify the genetic defect in the afflicted cell types. However, the personalized nature of these approaches excludes many patients for whom the underlying mutation is not mapped, or the number of affected individuals is too few to develop a commercially viable therapy (vide infra). Thus, a therapy that can delay visual impairment irrespective of the underlying genetic etiology can satisfy this unmet medical need. Here, we demonstrate the utility of such an approach in retinitis pigmentosa (RP) by promoting survival of cone photoreceptors by targeting metabolic stress. These cells are not primarily affected by the inherited mutation, but their non-autonomous demise leads to a decline in daylight vision, greatly reducing the quality of life. We designed adeno-associated virus (AAV) vectors that promote gluconeogenesis- a pathway found in the liver which produces glucose in response to hypoglycemia. Retinal transduction with these vectors resulted in improved cone survival and delayed a decline in visual acuity in three different RP mouse models. Because this approach extended visual function independent of the primary mutation, therapies emanating from this approach could be used as a treatment option for a genetically heterogenous cohort of patients.

Prioritization of cell types responsive to biological perturbations in single-cell data with Augur

2021 ◽  
Author(s):  
Jordan W. Squair ◽  
Michael A. Skinnider ◽  
Matthieu Gautier ◽  
Leonard J. Foster ◽  
Grégoire Courtine
Keyword(s):  
Single Cell ◽  
Cell Types ◽  
Cell Data

scholarly journals Identifying cell types from single-cell data based on similarities and dissimilarities between cells

2021 ◽  
Vol 22 (S3) ◽  
Author(s):  
Yuanyuan Li ◽  
Ping Luo ◽  
Yi Lu ◽  
Fang-Xiang Wu
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Spectral Clustering ◽  
Incidence Matrix ◽  
Expression Patterns ◽  
Cell Types ◽  
Clustering Method ◽  
Different Types ◽  
Cell Data ◽  
Spectral Clustering Method

Abstract Background With the development of the technology of single-cell sequence, revealing homogeneity and heterogeneity between cells has become a new area of computational systems biology research. However, the clustering of cell types becomes more complex with the mutual penetration between different types of cells and the instability of gene expression. One way of overcoming this problem is to group similar, related single cells together by the means of various clustering analysis methods. Although some methods such as spectral clustering can do well in the identification of cell types, they only consider the similarities between cells and ignore the influence of dissimilarities on clustering results. This methodology may limit the performance of most of the conventional clustering algorithms for the identification of clusters, it needs to develop special methods for high-dimensional sparse categorical data. Results Inspired by the phenomenon that same type cells have similar gene expression patterns, but different types of cells evoke dissimilar gene expression patterns, we improve the existing spectral clustering method for clustering single-cell data that is based on both similarities and dissimilarities between cells. The method first measures the similarity/dissimilarity among cells, then constructs the incidence matrix by fusing similarity matrix with dissimilarity matrix, and, finally, uses the eigenvalues of the incidence matrix to perform dimensionality reduction and employs the K-means algorithm in the low dimensional space to achieve clustering. The proposed improved spectral clustering method is compared with the conventional spectral clustering method in recognizing cell types on several real single-cell RNA-seq datasets. Conclusions In summary, we show that adding intercellular dissimilarity can effectively improve accuracy and achieve robustness and that improved spectral clustering method outperforms the traditional spectral clustering method in grouping cells.

scholarly journals Adult tissue-resident stem cells—fact or fiction?

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Deepa Bhartiya
Keyword(s):  
Stem Cells ◽  
Single Cell ◽  
Adult Stem Cells ◽  
Cell Types ◽  
Specific Cell ◽  
Tissue Specific ◽  
Cardiac Tissues ◽  
Adult Tissues ◽  
Resident Stem Cells ◽  
Abundant Cytoplasm

AbstractLife-long tissue homeostasis of adult tissues is supposedly maintained by the resident stem cells. These stem cells are quiescent in nature and rarely divide to self-renew and give rise to tissue-specific “progenitors” (lineage-restricted and tissue-committed) which divide rapidly and differentiate into tissue-specific cell types. However, it has proved difficult to isolate these quiescent stem cells as a physical entity. Recent single-cell RNAseq studies on several adult tissues including ovary, prostate, and cardiac tissues have not been able to detect stem cells. Thus, it has been postulated that adult cells dedifferentiate to stem-like state to ensure regeneration and can be defined as cells capable to replace lost cells through mitosis. This idea challenges basic paradigm of development biology regarding plasticity that a cell enters point of no return once it initiates differentiation. The underlying reason for this dilemma is that we are putting stem cells and somatic cells together while processing for various studies. Stem cells and adult mature cell types are distinct entities; stem cells are quiescent, small in size, and with minimal organelles whereas the mature cells are metabolically active and have multiple organelles lying in abundant cytoplasm. As a result, they do not pellet down together when centrifuged at 100–350g. At this speed, mature cells get collected but stem cells remain buoyant and can be pelleted by centrifuging at 1000g. Thus, inability to detect stem cells in recently published single-cell RNAseq studies is because the stem cells were unknowingly discarded while processing and were never subjected to RNAseq. This needs to be kept in mind before proposing to redefine adult stem cells.

scholarly journals Optimizing expression quantitative trait locus mapping workflows for single-cell studies

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Anna S. E. Cuomo ◽  
Giordano Alvari ◽  
Christina B. Azodi ◽  
Davis J. McCarthy ◽  
Marc Jan Bonder ◽  
...  
Keyword(s):  
Gene Expression ◽  
Quantitative Trait Locus ◽  
Single Cell ◽  
Quantitative Trait ◽  
Cell Types ◽  
Expression Quantitative Trait Locus ◽  
Eqtl Mapping ◽  
Trait Locus ◽  
The Impact

Abstract Background Single-cell RNA sequencing (scRNA-seq) has enabled the unbiased, high-throughput quantification of gene expression specific to cell types and states. With the cost of scRNA-seq decreasing and techniques for sample multiplexing improving, population-scale scRNA-seq, and thus single-cell expression quantitative trait locus (sc-eQTL) mapping, is increasingly feasible. Mapping of sc-eQTL provides additional resolution to study the regulatory role of common genetic variants on gene expression across a plethora of cell types and states and promises to improve our understanding of genetic regulation across tissues in both health and disease. Results While previously established methods for bulk eQTL mapping can, in principle, be applied to sc-eQTL mapping, there are a number of open questions about how best to process scRNA-seq data and adapt bulk methods to optimize sc-eQTL mapping. Here, we evaluate the role of different normalization and aggregation strategies, covariate adjustment techniques, and multiple testing correction methods to establish best practice guidelines. We use both real and simulated datasets across single-cell technologies to systematically assess the impact of these different statistical approaches. Conclusion We provide recommendations for future single-cell eQTL studies that can yield up to twice as many eQTL discoveries as default approaches ported from bulk studies.

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