Enhancing reproducibility in single cell research with biocytometry: An inter-laboratory study

Fikar, Pavel; Alvarez, Laura; Berne, Laura; Cienciala, Martin; Kan, Christopher; Kasl, Hynek; Luo, Mona; Novackova, Zuzana; Ordonez, Sheyla; Sramkova, Zuzana; Holubova, Monika; Lysak, Daniel; Avery, Lyndsay; Caro, Andres A; Crowder, Roslyn N; Diaz-Martinez, Laura A; Donley, David W; Giorno, Rebecca R; Reed, Irene K Guttilla; Hensley, Lori L; Johnson, Kristen C; Kim, Audrey Y; Kim, Paul; LaGier, Adriana J; Newman, Jamie J; Padilla-Crespo, Elizabeth; Reyna, Nathan S; Tsotakos, Nikolaos; Al-Saadi, Noha N; Appleton, Tayler; Arosemena-Pickett, Ana; Bell, Braden A; Bing, Grace; Bishop, Bre; Forde, Christa; Foster, Michael J; Gray, Kassidy; Hasley, Bennett L; Johnson, Kennedy; Jones, Destiny J; LaShall, Allison C; McGuire, Kennedy; McNaughton, Naomi; Morgan, Angelina M; Norris, Lucas; Ossman, Landon A; Rivera-Torres, Paollette A; Robison, Madeline E; Thibodaux, Kathryn; Valmond, Lescia; Georgiev, Daniel

Enhancing reproducibility in single cell research with biocytometry: An inter-laboratory study

Pavel Fikar, Laura Alvarez, Laura Berne, Martin Cienciala, Christopher Kan, Hynek Kasl, Mona Luo, Zuzana Novackova, Sheyla Ordonez, Zuzana Sramkova, Monika Holubova, Daniel Lysak, Lyndsay Avery, Andres A Caro, Roslyn N Crowder, Laura A Diaz-Martinez, David W Donley, Rebecca R Giorno, Irene K Guttilla Reed, Lori L Hensley, Kristen C Johnson, Audrey Y Kim, Paul Kim, Adriana J LaGier, Jamie J Newman, Elizabeth Padilla-Crespo, Nathan S Reyna, Nikolaos Tsotakos, Noha N Al-Saadi, Tayler Appleton, Ana Arosemena-Pickett, Braden A Bell, Grace Bing, Bre Bishop, Christa Forde, Michael J Foster, Kassidy Gray, Bennett L Hasley, Kennedy Johnson, Destiny J Jones, Allison C LaShall, Kennedy McGuire, Naomi McNaughton, Angelina M Morgan, Lucas Norris, Landon A Ossman, Paollette A Rivera-Torres, Madeline E Robison, Kathryn Thibodaux, Lescia Valmond and Daniel Georgiev

PLOS ONE, 2024, vol. 19, issue 12, 1-20

Abstract: Biomedicine today is experiencing a shift towards decentralized data collection, which promises enhanced reproducibility and collaboration across diverse laboratory environments. This inter-laboratory study evaluates the performance of biocytometry, a method utilizing engineered bioparticles for enumerating cells based on their surface antigen patterns. In centralized and aggregated inter-lab studies, biocytometry demonstrated significant statistical power in discriminating numbers of target cells at varying concentrations as low as 1 cell per 100,000 background cells. User skill levels varied from expert to beginner capturing a range of proficiencies. Measurement was performed in a decentralized environment without any instrument cross-calibration or advanced user training outside of a basic instruction manual. The results affirm biocytometry to be a viable solution for immunophenotyping applications demanding sensitivity as well as scalability and reproducibility and paves the way for decentralized analysis of rare cells in heterogeneous samples.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0314992

DOI: 10.1371/journal.pone.0314992

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