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

Author

Listed:
  • 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
  • Daniel Georgiev

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.

Suggested Citation

  • 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 , 2024. "Enhancing reproducibility in single cell research with biocytometry: An inter-laboratory study," PLOS ONE, Public Library of Science, vol. 19(12), pages 1-20, December.
    • Handle: RePEc:plo:pone00:0314992
    DOI: 10.1371/journal.pone.0314992
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    References listed on IDEAS

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    1. C. Glenn Begley & Lee M. Ellis, 2012. "Raise standards for preclinical cancer research," Nature, Nature, vol. 483(7391), pages 531-533, March.
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