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; Daniel Georgiev

doi:10.1371/journal.pone.0314992

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. HensleyKristen 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

Research output: Contribution to journal › Article › peer-review

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.

Original language	English (US)
Article number	e0314992
Journal	PloS one
Volume	19
Issue number	12 December
DOIs	https://doi.org/10.1371/journal.pone.0314992
State	Published - Dec 2024

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Fikar, P., Alvarez, L., Berne, L., Cienciala, M., Kan, C., Kasl, H., Luo, M., Novackova, Z., Ordonez, S., Sramkova, Z., Holubova, M., Lysak, D., Avery, L., Caro, A. A., Crowder, R. N., Diaz-Martinez, L. A., Donley, D. W., Giorno, R. R., Guttilla Reed, I. K., ... Georgiev, D. (2024). Enhancing reproducibility in single cell research with biocytometry: An inter-laboratory study. PloS one, 19(12 December), Article e0314992. https://doi.org/10.1371/journal.pone.0314992

@article{56c31dd10d4147b6b2910dafb88f1eda,

title = "Enhancing reproducibility in single cell research with biocytometry: An inter-laboratory study",

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.",

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

note = "Publisher Copyright: Copyright: {\textcopyright} 2024 Fikar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.",

year = "2024",

month = dec,

doi = "10.1371/journal.pone.0314992",

language = "English (US)",

volume = "19",

journal = "PloS one",

issn = "1932-6203",

publisher = "Public Library of Science",

number = "12 December",

}

Fikar, P, Alvarez, L, Berne, L, Cienciala, M, Kan, C, Kasl, H, Luo, M, Novackova, Z, Ordonez, S, Sramkova, Z, Holubova, M, Lysak, D, Avery, L, Caro, AA, Crowder, RN, Diaz-Martinez, LA, Donley, DW, Giorno, RR, Guttilla Reed, IK, Hensley, LL, Johnson, KC, Kim, AY, Kim, P, LaGier, AJ, Newman, JJ, Padilla-Crespo, E, Reyna, NS, Tsotakos, N, Al-Saadi, NN, Appleton, T, Arosemena-Pickett, A, Bell, BA, Bing, G, Bishop, B, Forde, C, Foster, MJ, Gray, K, Hasley, BL, Johnson, K, Jones, DJ, LaShall, AC, McGuire, K, McNaughton, N, Morgan, AM, Norris, L, Ossman, LA, Rivera-Torres, PA, Robison, ME, Thibodaux, K, Valmond, L & Georgiev, D 2024, 'Enhancing reproducibility in single cell research with biocytometry: An inter-laboratory study', PloS one, vol. 19, no. 12 December, e0314992. https://doi.org/10.1371/journal.pone.0314992

TY - JOUR

T1 - Enhancing reproducibility in single cell research with biocytometry

T2 - An inter-laboratory study

AU - Fikar, Pavel

AU - Alvarez, Laura

AU - Berne, Laura

AU - Cienciala, Martin

AU - Kan, Christopher

AU - Kasl, Hynek

AU - Luo, Mona

AU - Novackova, Zuzana

AU - Ordonez, Sheyla

AU - Sramkova, Zuzana

AU - Holubova, Monika

AU - Lysak, Daniel

AU - Avery, Lyndsay

AU - Caro, Andres A.

AU - Crowder, Roslyn N.

AU - Diaz-Martinez, Laura A.

AU - Donley, David W.

AU - Giorno, Rebecca R.

AU - Guttilla Reed, Irene K.

AU - Hensley, Lori L.

AU - Johnson, Kristen C.

AU - Kim, Audrey Y.

AU - Kim, Paul

AU - LaGier, Adriana J.

AU - Newman, Jamie J.

AU - Padilla-Crespo, Elizabeth

AU - Reyna, Nathan S.

AU - Tsotakos, Nikolaos

AU - Al-Saadi, Noha N.

AU - Appleton, Tayler

AU - Arosemena-Pickett, Ana

AU - Bell, Braden A.

AU - Bing, Grace

AU - Bishop, Bre

AU - Forde, Christa

AU - Foster, Michael J.

AU - Gray, Kassidy

AU - Hasley, Bennett L.

AU - Johnson, Kennedy

AU - Jones, Destiny J.

AU - LaShall, Allison C.

AU - McGuire, Kennedy

AU - McNaughton, Naomi

AU - Morgan, Angelina M.

AU - Norris, Lucas

AU - Ossman, Landon A.

AU - Rivera-Torres, Paollette A.

AU - Robison, Madeline E.

AU - Thibodaux, Kathryn

AU - Valmond, Lescia

AU - Georgiev, Daniel

N1 - Publisher Copyright: Copyright: © 2024 Fikar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

PY - 2024/12

Y1 - 2024/12

N2 - 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.

AB - 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.

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UR - http://www.scopus.com/inward/citedby.url?scp=85211971166&partnerID=8YFLogxK

U2 - 10.1371/journal.pone.0314992

DO - 10.1371/journal.pone.0314992

M3 - Article

C2 - 39652549

AN - SCOPUS:85211971166

SN - 1932-6203

VL - 19

JO - PloS one

JF - PloS one

IS - 12 December

M1 - e0314992

ER -

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

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