Designing broad-spectrum anti-HIV-1 gRNAs to target patient-derived variants

Dampier, Will; Sullivan, Neil T.; Chung, Ching‐Hu; Mell, Joshua Chang; Nonnemacher, Michael R.; Wigdahl, Brian

doi:10.1038/s41598-017-12612-z

Cited by 32 publications

(44 citation statements)

References 37 publications

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“…Pathogens, like the human immunodeficiency virus type 1 (HIV‐1), almost always succeed in causing disease by disabling immune cells, evading the immune system, and acquiring mutations that provide resistance to antiviral drugs. [ 11–14 ] Control of pathogens that have such mechanisms to evade the host immune system necessitates a pharmacological intervention to prevent the disease. Therefore, each pathogen may present a unique set of challenges to the immune system that must be specifically addressed.…”

Section: Infection and Immunitymentioning

confidence: 99%

Nonthermal plasma as part of a novel strategy for vaccination

Mohamed

Esposito

Kutzler

et al. 2020

Plasma Processes & Polymers

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Vaccination has been one of the most effective health intervention mechanisms to reduce morbidity and mortality associated with infectious diseases. Vaccines stimulate the body's protective immune responses through controlled exposure to modified versions of pathogens that establish immunological memory. However, only a few diseases have effective vaccines. The biological effects of nonthermal plasma on cells suggest that plasma could play an important role in improving efficacy of existing vaccines and overcoming some of the limitations and challenges with current vaccination strategies. This review summarizes the opportunities for nonthermal plasma for immunization and therapeutic purposes.

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Section: Infection and Immunitymentioning

confidence: 99%

Nonthermal plasma as part of a novel strategy for vaccination

Mohamed

Esposito

Kutzler

et al. 2020

Plasma Processes & Polymers

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“…Populations of mixed HIV-1 LTR-containing plasmids were subjected to an in vitro cutting assay, as described above, in an effort to explore the most appropriate way of predicting SpCas9 effectiveness against a mixed population of DNA fragments. This mirrors the biological situation found in HIV-1-infected individuals who often contain a swarm of related, yet genetically distinct, integrated viral genomes (Dampier et al, 2017). The script below describes how to compare the predictions of three popular methods with experimentally determined cutting profiles.…”

Section: Taskmentioning

confidence: 82%

“…This will be an invaluable tool for fields editing highly mutable genomes and meta-genomes of mixed populations. In the case of HIV-1, recent research has shown that inter-patient variability presents a barrier to effective targeting (Dampier et al, 2017;Roychoudhury et al, 2018). However, utilizing this tool it was possible to exploit the promiscuity of SpCas9 to construct a set spacers capable of targeting the wide range of known mutations (Dampier et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

CRSeek: a Python module for facilitating complicated CRISPR design strategies

Dampier

Chung

Sullivan

et al. 2018

Preprint

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With the popularization of the CRISPR-Cas gene editing system there has been an explosion of new techniques made possible by this versatile technology. However, the computational field has lagged behind with a current lack of computational tools for developing complicated CRISPR-Cas gene editing strategies. We present crseek, a Python package that provides a consistent application programming interface (API) for multiple cleavage prediction algorithms. Four popular cleavage prediction algorithms were implemented and further adapted to work on draft-quality genomes. Furthermore, since crseek mirrors the popular scikit-learn API, the package can be easily integrated as an upstream processing module for facilitating further CRISPR-Cas machine learning research.The package is fully integrated with the biopython package facilitating simple import, export, and manipulation of sequences before and after gene editing. This manuscript presents four common gene editing tasks that would be difficult with current tools but are easily performed with the crseek package. We believe this package will help bioinformaticians rapidly design complex CRISPR-Cas gene editing strategies and will be a useful addition to the field. With the popularization of the CRISPR-Cas gene editing system there has been an explosion of new techniques made possible by this versatile technology. However, the computational field has lagged behind with a current lack of computational tools for developing complicated CRISPR-Cas gene editing strategies. We present crseek, a Python package that provides a consistent application programming interface (API) for multiple cleavage prediction algorithms. Four popular cleavage prediction algorithms were implemented and further adapted to work on draft-quality genomes. Furthermore, since crseek mirrors the popular scikit-learn API, the package can be easily integrated as an upstream processing module for facilitating further CRISPR-Cas machine learning research. The package is fully integrated with the biopython package facilitating simple import, export, and manipulation of sequences before and after gene editing. This manuscript presents four common gene editing tasks that would be difficult with current tools but are easily performed with the crseek package. We believe this package will help bioinformaticians rapidly design complex CRISPR-Cas gene editing strategies and will be a useful addition to the field.

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“…The integrated HIV-1 copy in this cell line is located in the second intron of SEC16A (chromosome 9, position 136468579), providing a useful cell line for studying HIV-1 latency (3). In order to use J-Lat 10.6 for anti-HIV-1 gene editing and design strategies using the clustered regularly interspaced short palindromic repeats (CRISPR) system, it is necessary to have the full proviral DNA sequence (4)(5)(6)(7)(8)(9)(10)(11). However, the full-length sequence of integrated HIV/R7/E Ϫ /GFP has not been reported.…”

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confidence: 99%