Evidence map›Paper›PMID 38468277›Full record

ArticleArthritis research & therapy2024

Streamlined, single-step non-viral CRISPR-Cas9 knockout strategy enhances gene editing efficiency in primary human chondrocyte populations.

Simone Ponta, Angela Bonato, Philipp Neidenbach, Valentino F Bruhin, Alexis Laurent, Lee Ann Applegate, Marcy Zenobi-Wong, Goncalo Barreto

Open access · goldAbstract read
In one paragraph

Article in Arthritis research & therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.6field-weighted citation impact, top 17% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 7 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 2 countries.

Simone Ponta *Department of Health Sciences and Technology, ETH Zürich, Zurich, 8093, Switzerland.
Angela Bonato *Department of Health Sciences and Technology, ETH Zürich, Zurich, 8093, Switzerland.
Philipp NeidenbachSchulthess Clinic, Department of Lower Extremity Orthopaedics, Musculoskeletal Centre, Zurich, 8008, Switzerland.
Valentino F BruhinSchulthess Clinic, Department of Lower Extremity Orthopaedics, Musculoskeletal Centre, Zurich, 8008, Switzerland.
Alexis LaurentRegenerative Therapy Unit, Plastic, Reconstructive & Hand Surgery Service, Lausanne University Hospital, University of Lausanne, Epalinges, 1066, Switzerland.
Lee Ann ApplegateRegenerative Therapy Unit, Plastic, Reconstructive & Hand Surgery Service, Lausanne University Hospital, University of Lausanne, Epalinges, 1066, Switzerland.
Marcy Zenobi-WongDepartment of Health Sciences and Technology, ETH Zürich, Zurich, 8093, Switzerland.
Goncalo BarretoClinicum, Faculty of Medicine, University of Helsinki and Helsinki University Hospital, Helsinki, 00014, Finland. goncalo.barreto@helsinki.fi.
ETH Zurich · CHSchulthess-Klinik · CHUniversity of Lausanne · CHInvalidisäätiö · FI

Funding

Suomen Kulttuurirahasto 00220103
6 · The paper itself

Abstract

backgroundCRISPR-Cas9-based genome engineering represents a powerful therapeutic tool for cartilage tissue engineering and for understanding molecular pathways driving cartilage diseases. However, primary chondrocytes are difficult to transfect and rapidly dedifferentiate during monolayer (2D) cell culture, making the lengthy expansion of a single-cell-derived edited clonal population not feasible. For this reason, functional genetics studies focused on cartilage and rheumatic diseases have long been carried out in cellular models that poorly recapitulate the native molecular properties of human cartilaginous tissue (e.g., cell lines, induced pluripotent stem cells). Here, we set out to develop a non-viral CRISPR-Cas9, bulk-gene editing method suitable for chondrocyte populations from different cartilaginous sources.

methodsWe screened electroporation and lipid nanoparticles for ribonucleoprotein (RNP) delivery in primary polydactyly chondrocytes, and optimized RNP reagents assembly. We knocked out RELA (also known as p65), a subunit of the nuclear factor kappa B (NF-κB), in polydactyly chondrocytes and further characterized knockout (KO) cells with RT-qPCR and Western Blot. We tested RELA KO in chondrocytes from diverse cartilaginous sources and characterized their phenotype with RT-qPCR. We examined the chondrogenic potential of wild-type (WT) and KO cell pellets in presence and absence of interleukin-1β (IL-1β).

resultsWe established electroporation as the optimal transfection technique for chondrocytes enhancing transfection and editing efficiency, while preserving high cell viability. We knocked out RELA with an unprecedented efficiency of ~90%, confirming lower inflammatory pathways activation upon IL-1β stimulation compared to unedited cells. Our protocol could be easily transferred to primary human chondrocytes harvested from osteoarthritis (OA) patients, human FE002 chondroprogenitor cells, bovine chondrocytes, and a human chondrocyte cell line, achieving comparable mean RELA KO editing levels using the same protocol. All KO pellets from primary human chondrocytes retained chondrogenic ability equivalent to WT cells, and additionally displayed enhanced matrix retention under inflamed conditions.

conclusionsWe showcased the applicability of our bulk gene editing method to develop effective autologous and allogeneic off-the-shelf gene therapies strategies and to enable functional genetics studies in human chondrocytes to unravel molecular mechanisms of cartilage diseases.

Indexed as

Cartilage DiseasesPolydactylyAnimalsCattleChondrocytesCRISPR-Cas SystemsGene EditingHumansInterleukin-1betaInterleukin-1betaCRISPR-Cas9Gene editingNF-κBPrimary chondrocytesRELA

Identifiers

PMID38468277
PMCPMC10926593
OpenAlexW4392658362

What OpenQuestion holds

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.