{"doi":"10.1002/smtd.202500295","title":"Analyzing DNA Origami Nanostructure Assembly by Dynamic Light Scattering and Nanoparticle Tracking Analysis","abstract":"The field of nucleic acid self-assembly has advanced significantly, enabling the creation of multi-dimensional nanostructures with precise sizes and shapes. These nanostructures hold great potential for various applications, including biocatalysis, smart materials, molecular diagnosis, and therapeutics. Here, dynamic light scattering (DLS) and nanoparticle tracking analysis (NTA) are employed to investigate DNA origami nanostructures, focusing on size distribution and particle concentration. Compared to DLS, NTA provided higher resolution in size measurement with a smaller full-width at half-maximum (FWHM), making it particularly suitable for characterizing DNA nanostructure. To enhance sensitivity, a fluorescent NTA method is developed by incorporating an intercalation dye to amplify the fluorescence signals of DNA origami. This method is validated by analyzing various DNA origami structures, ranging from 1 and 2D flexible structures to 3D compact shapes, and evaluating structural assembly yields. Additionally, NTA is used to analyze dynamic DNA nanocages that undergo conformational switches among linear, square, and pyramid shapes in response to the addition of trigger strands. Quantitative size distribution data is crucial not only for production quality control but also for providing mechanistic insights into the various applications of DNA nanomaterials.","journal":"Small Methods","year":2025,"id":519741,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":6,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.949,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1388706,"name":"Xu Chang","orcid":"0000-0001-9590-9329","position":1,"is_corresponding":false},{"id":1245375,"name":"Alireza Ebrahimimojarad","orcid":null,"position":2,"is_corresponding":false},{"id":1388707,"name":"Akshay Shah","orcid":"0000-0002-1869-2231","position":3,"is_corresponding":false},{"id":925600,"name":"Fei Zhang","orcid":"0000-0002-3177-7547","position":4,"is_corresponding":false},{"id":923570,"name":"Jinglin Fu","orcid":"0000-0002-0814-0089","position":5,"is_corresponding":false},{"id":1244906,"name":"Qiaochu Zhang","orcid":"0000-0003-3554-9215","position":0,"is_corresponding":true}],"reference_count":53,"raw_metadata":null,"created_at":"2026-07-19T02:49:23.618703Z","pmid":"40536202","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}