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Biomedical subjects

Xinming Wang

Publications and source records attributed to Xinming Wang.

2 recordsLinked to original sources

Efficient and precise programmable DNA knock-in without double-strand breaks.

Programmable gene knock-in holds substantial promise for treating genetic diseases and advancing cell therapies. However, achieving precise and efficient kilobase-scale DNA fragment integration remains challenging1,2. Here we report CRISPR kilobase-scale nickase-targeting (KNIT) editing for efficient, precise and programmable kilobase-scale DNA insertion without double-strand DNA cleavage, which is enabled through the coupling of a Cas9 nickase with a DNA donor recruiting system. KNIT editing facilitates programmable integration of DNA fragments from 0.7 kb to more than 10 kb and is effective across genomic loci and cell types. It achieves up to 89% efficiency and markedly reduces unintended insertion-deletion mutation (indels) rates, translocations and off-target editing. The system supports repeated insertion editing and multiloci gene knock-in with minimal translocations. Its enhanced version, KNIT editor 2, further improves efficiency via a single transfection. Moreover, in mutant cells with a pathological mutation, KNIT editing restores normal gene expression by inserting a therapeutic gene into a safe harbour locus or its native locus. Notably, KNIT editing enables non-viral and programmable chimeric antigen receptor T cell (CAR-T cell) engineering without double-strand breaks and with clinically relevant efficiencies. Moreover, the engineered CAR-T cells exhibit effective antitumour activity in vitro and in mouse models. Therefore, by achieving programmable and site-specific kilobase-scale DNA insertions without double-strand breaks while reducing unintended outcomes, KNIT editing provides a versatile platform for advancing personalized medicine.

Animals

Proteomic Analysis of 442 Clinical Plasma Samples From Individuals With Symptom Records Revealed Subtypes of Convalescent Patients Who Had COVID-19.

After the coronavirus disease 2019 (COVID-19) pandemic, the postacute effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have gradually attracted attention. To precisely evaluate the health status of convalescent patients with COVID-19, we analyzed symptom and proteome data of 442 plasma samples from healthy controls, hospitalized patients, and convalescent patients 6 or 12 months after SARS-CoV-2 infection. Symptoms analysis revealed distinct relationships in convalescent patients. Results of plasma protein expression levels showed that C1QA, C1QB, C2, CFH, CFHR1, and F10, which regulate the complement system and coagulation, remained highly expressed even at the 12-month follow-up compared with their levels in healthy individuals. By combining symptom and proteome data, 442 plasma samples were categorized into three subtypes: S1 (metabolism-healthy), S2 (COVID-19 retention), and S3 (long COVID). We speculated that convalescent patients reporting hair loss could have a better health status than those experiencing headaches and dyspnea. Compared to other convalescent patients, those reporting sleep disorders, appetite decrease, and muscle weakness may need more attention because they were classified into the S2 subtype, which had the most samples from hospitalized patients with COVID-19. Subtyping convalescent patients with COVID-19 may enable personalized treatments tailored to individual needs. This study provides valuable plasma proteomic datasets for further studies associated with long COVID.

Humans