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1. Guidelines for the use of flow cytometry and cell sorting in immunological studies (third edition)

Author

Cossarizza, A, Chang, H, Radbruch, A, Abrignani, S, Addo, R, Akdis, M, Andra, I, Andreata, F, Annunziato, F, Arranz, E, Bacher, P, Bari, S, Barnaba, V, Barros-Martins, J, Baumjohann, D, Beccaria, C, Bernardo, D, Boardman, D, Borger, J, Bottcher, C, Brockmann, L, Burns, M, Busch, D, Cameron, G, Cammarata, I, Cassotta, A, Chang, Y, Chirdo, F, Christakou, E, Cicin-Sain, L, Cook, L, Corbett, A, Cornelis, R, Cosmi, L, Davey, M, De Biasi, S, De Simone, G, del Zotto, G, Delacher, M, Di Rosa, F, Santo, J, Diefenbach, A, Dong, J, Dorner, T, Dress, R, Dutertre, C, Eckle, S, Eede, P, Evrard, M, Falk, C, Feuerer, M, Fillatreau, S, Fiz-Lopez, A, Follo, M, Foulds, G, Frobel, J, Gagliani, N, Galletti, G, Gangaev, A, Garbi, N, Garrote, J, Geginat, J, Gherardin, N, Gibellini, L, Ginhoux, F, Godfrey, D, Gruarin, P, Haftmann, C, Hansmann, L, Harpur, C, Hayday, A, Heine, G, Hernandez, D, Herrmann, M, Hoelsken, O, Huang, Q, Huber, S, Huber, J, Huehn, J, Hundemer, M, Hwang, W, Iannacone, M, Ivison, S, Jack, H, Jani, P, Keller, B, Kessler, N, Ketelaars, S, Knop, L, Knopf, J, Koay, H, Kobow, K, Kriegsmann, K, Kristyanto, H, Krueger, A, Kuehne, J, Kunze-Schumacher, H, Kvistborg, P, Kwok, I, Latorre, D, Lenz, D, Levings, M, Lino, A, Liotta, F, Long, H, Lugli, E, Macdonald, K, Maggi, L, Maini, M, Mair, F, Manta, C, Manz, R, Mashreghi, M, Mazzoni, A, Mccluskey, J, Mei, H, Melchers, F, Melzer, S, Mielenz, D, Monin, L, Moretta, L, Multhoff, G, Munoz, L, Munoz-Ruiz, M, Muscate, F, Natalini, A, Neumann, K, Ng, L, Niedobitek, A, Niemz, J, Almeida, L, Notarbartolo, S, Ostendorf, L, Pallett, L, Patel, A, Percin, G, Peruzzi, G, Pinti, M, Pockley, A, Pracht, K, Prinz, I, Pujol-Autonell, I, Pulvirenti, N, Quatrini, L, Quinn, K, Radbruch, H, Rhys, H, Rodrigo, M, Romagnani, C, Saggau, C, Sakaguchi, S, Sallusto, F, Sanderink, L, Sandrock, I, Schauer, C, Scheffold, A, Scherer, H, Schiemann, M, Schildberg, F, Schober, K, Schoen, J, Schuh, W, Schuler, T, Schulz, A, Schulz, S, Schulze, J, Simonetti, S, Singh, J, Sitnik, K, Stark, R, Starossom, S, Stehle, C, Szelinski, F, Tan, L, Tarnok, A, Tornack, J, Tree, T, van Beek, J, van de Veen, W, van Gisbergen, K, Vasco, C, Verheyden, N, von Borstel, A, Ward-Hartstonge, K, Warnatz, K, Waskow, C, Wiedemann, A, Wilharm, A, Wing, J, Wirz, O, Wittner, J, Yang, J, Cossarizza A., Chang H. -D., Radbruch A., Abrignani S., Addo R., Akdis M., Andra I., Andreata F., Annunziato F., Arranz E., Bacher P., Bari S., Barnaba V., Barros-Martins J., Baumjohann D., Beccaria C. G., Bernardo D., Boardman D. A., Borger J., Bottcher C., Brockmann L., Burns M., Busch D. H., Cameron G., Cammarata I., Cassotta A., Chang Y., Chirdo F. G., Christakou E., Cicin-Sain L., Cook L., Corbett A. J., Cornelis R., Cosmi L., Davey M. S., De Biasi S., De Simone G., del Zotto G., Delacher M., Di Rosa F., Santo J. D., Diefenbach A., Dong J., Dorner T., Dress R. J., Dutertre C. -A., Eckle S. B. G., Eede P., Evrard M., Falk C. S., Feuerer M., Fillatreau S., Fiz-Lopez A., Follo M., Foulds G. A., Frobel J., Gagliani N., Galletti G., Gangaev A., Garbi N., Garrote J. A., Geginat J., Gherardin N. A., Gibellini L., Ginhoux F., Godfrey D. I., Gruarin P., Haftmann C., Hansmann L., Harpur C. M., Hayday A. C., Heine G., Hernandez D. C., Herrmann M., Hoelsken O., Huang Q., Huber S., Huber J. E., Huehn J., Hundemer M., Hwang W. Y. K., Iannacone M., Ivison S. M., Jack H. -M., Jani P. K., Keller B., Kessler N., Ketelaars S., Knop L., Knopf J., Koay H. -F., Kobow K., Kriegsmann K., Kristyanto H., Krueger A., Kuehne J. F., Kunze-Schumacher H., Kvistborg P., Kwok I., Latorre D., Lenz D., Levings M. K., Lino A. C., Liotta F., Long H. M., Lugli E., MacDonald K. N., Maggi L., Maini M. K., Mair F., Manta C., Manz R. A., Mashreghi M. -F., Mazzoni A., McCluskey J., Mei H. E., Melchers F., Melzer S., Mielenz D., Monin L., Moretta L., Multhoff G., Munoz L. E., Munoz-Ruiz M., Muscate F., Natalini A., Neumann K., Ng L. G., Niedobitek A., Niemz J., Almeida L. N., Notarbartolo S., Ostendorf L., Pallett L. J., Patel A. A., Percin G. I., Peruzzi G., Pinti M., Pockley A. G., Pracht K., Prinz I., Pujol-Autonell I., Pulvirenti N., Quatrini L., Quinn K. M., Radbruch H., Rhys H., Rodrigo M. B., Romagnani C., Saggau C., Sakaguchi S., Sallusto F., Sanderink L., Sandrock I., Schauer C., Scheffold A., Scherer H. U., Schiemann M., Schildberg F. A., Schober K., Schoen J., Schuh W., Schuler T., Schulz A. R., Schulz S., Schulze J., Simonetti S., Singh J., Sitnik K. M., Stark R., Starossom S., Stehle C., Szelinski F., Tan L., Tarnok A., Tornack J., Tree T. I. M., van Beek J. J. P., van de Veen W., van Gisbergen K., Vasco C., Verheyden N. A., von Borstel A., Ward-Hartstonge K. A., Warnatz K., Waskow C., Wiedemann A., Wilharm A., Wing J., Wirz O., Wittner J., Yang J. H. M., Yang J., Cossarizza, A, Chang, H, Radbruch, A, Abrignani, S, Addo, R, Akdis, M, Andra, I, Andreata, F, Annunziato, F, Arranz, E, Bacher, P, Bari, S, Barnaba, V, Barros-Martins, J, Baumjohann, D, Beccaria, C, Bernardo, D, Boardman, D, Borger, J, Bottcher, C, Brockmann, L, Burns, M, Busch, D, Cameron, G, Cammarata, I, Cassotta, A, Chang, Y, Chirdo, F, Christakou, E, Cicin-Sain, L, Cook, L, Corbett, A, Cornelis, R, Cosmi, L, Davey, M, De Biasi, S, De Simone, G, del Zotto, G, Delacher, M, Di Rosa, F, Santo, J, Diefenbach, A, Dong, J, Dorner, T, Dress, R, Dutertre, C, Eckle, S, Eede, P, Evrard, M, Falk, C, Feuerer, M, Fillatreau, S, Fiz-Lopez, A, Follo, M, Foulds, G, Frobel, J, Gagliani, N, Galletti, G, Gangaev, A, Garbi, N, Garrote, J, Geginat, J, Gherardin, N, Gibellini, L, Ginhoux, F, Godfrey, D, Gruarin, P, Haftmann, C, Hansmann, L, Harpur, C, Hayday, A, Heine, G, Hernandez, D, Herrmann, M, Hoelsken, O, Huang, Q, Huber, S, Huber, J, Huehn, J, Hundemer, M, Hwang, W, Iannacone, M, Ivison, S, Jack, H, Jani, P, Keller, B, Kessler, N, Ketelaars, S, Knop, L, Knopf, J, Koay, H, Kobow, K, Kriegsmann, K, Kristyanto, H, Krueger, A, Kuehne, J, Kunze-Schumacher, H, Kvistborg, P, Kwok, I, Latorre, D, Lenz, D, Levings, M, Lino, A, Liotta, F, Long, H, Lugli, E, Macdonald, K, Maggi, L, Maini, M, Mair, F, Manta, C, Manz, R, Mashreghi, M, Mazzoni, A, Mccluskey, J, Mei, H, Melchers, F, Melzer, S, Mielenz, D, Monin, L, Moretta, L, Multhoff, G, Munoz, L, Munoz-Ruiz, M, Muscate, F, Natalini, A, Neumann, K, Ng, L, Niedobitek, A, Niemz, J, Almeida, L, Notarbartolo, S, Ostendorf, L, Pallett, L, Patel, A, Percin, G, Peruzzi, G, Pinti, M, Pockley, A, Pracht, K, Prinz, I, Pujol-Autonell, I, Pulvirenti, N, Quatrini, L, Quinn, K, Radbruch, H, Rhys, H, Rodrigo, M, Romagnani, C, Saggau, C, Sakaguchi, S, Sallusto, F, Sanderink, L, Sandrock, I, Schauer, C, Scheffold, A, Scherer, H, Schiemann, M, Schildberg, F, Schober, K, Schoen, J, Schuh, W, Schuler, T, Schulz, A, Schulz, S, Schulze, J, Simonetti, S, Singh, J, Sitnik, K, Stark, R, Starossom, S, Stehle, C, Szelinski, F, Tan, L, Tarnok, A, Tornack, J, Tree, T, van Beek, J, van de Veen, W, van Gisbergen, K, Vasco, C, Verheyden, N, von Borstel, A, Ward-Hartstonge, K, Warnatz, K, Waskow, C, Wiedemann, A, Wilharm, A, Wing, J, Wirz, O, Wittner, J, Yang, J, Cossarizza A., Chang H. -D., Radbruch A., Abrignani S., Addo R., Akdis M., Andra I., Andreata F., Annunziato F., Arranz E., Bacher P., Bari S., Barnaba V., Barros-Martins J., Baumjohann D., Beccaria C. G., Bernardo D., Boardman D. A., Borger J., Bottcher C., Brockmann L., Burns M., Busch D. H., Cameron G., Cammarata I., Cassotta A., Chang Y., Chirdo F. G., Christakou E., Cicin-Sain L., Cook L., Corbett A. J., Cornelis R., Cosmi L., Davey M. S., De Biasi S., De Simone G., del Zotto G., Delacher M., Di Rosa F., Santo J. D., Diefenbach A., Dong J., Dorner T., Dress R. J., Dutertre C. -A., Eckle S. B. G., Eede P., Evrard M., Falk C. S., Feuerer M., Fillatreau S., Fiz-Lopez A., Follo M., Foulds G. A., Frobel J., Gagliani N., Galletti G., Gangaev A., Garbi N., Garrote J. A., Geginat J., Gherardin N. A., Gibellini L., Ginhoux F., Godfrey D. I., Gruarin P., Haftmann C., Hansmann L., Harpur C. M., Hayday A. C., Heine G., Hernandez D. C., Herrmann M., Hoelsken O., Huang Q., Huber S., Huber J. E., Huehn J., Hundemer M., Hwang W. Y. K., Iannacone M., Ivison S. M., Jack H. -M., Jani P. K., Keller B., Kessler N., Ketelaars S., Knop L., Knopf J., Koay H. -F., Kobow K., Kriegsmann K., Kristyanto H., Krueger A., Kuehne J. F., Kunze-Schumacher H., Kvistborg P., Kwok I., Latorre D., Lenz D., Levings M. K., Lino A. C., Liotta F., Long H. M., Lugli E., MacDonald K. N., Maggi L., Maini M. K., Mair F., Manta C., Manz R. A., Mashreghi M. -F., Mazzoni A., McCluskey J., Mei H. E., Melchers F., Melzer S., Mielenz D., Monin L., Moretta L., Multhoff G., Munoz L. E., Munoz-Ruiz M., Muscate F., Natalini A., Neumann K., Ng L. G., Niedobitek A., Niemz J., Almeida L. N., Notarbartolo S., Ostendorf L., Pallett L. J., Patel A. A., Percin G. I., Peruzzi G., Pinti M., Pockley A. G., Pracht K., Prinz I., Pujol-Autonell I., Pulvirenti N., Quatrini L., Quinn K. M., Radbruch H., Rhys H., Rodrigo M. B., Romagnani C., Saggau C., Sakaguchi S., Sallusto F., Sanderink L., Sandrock I., Schauer C., Scheffold A., Scherer H. U., Schiemann M., Schildberg F. A., Schober K., Schoen J., Schuh W., Schuler T., Schulz A. R., Schulz S., Schulze J., Simonetti S., Singh J., Sitnik K. M., Stark R., Starossom S., Stehle C., Szelinski F., Tan L., Tarnok A., Tornack J., Tree T. I. M., van Beek J. J. P., van de Veen W., van Gisbergen K., Vasco C., Verheyden N. A., von Borstel A., Ward-Hartstonge K. A., Warnatz K., Waskow C., Wiedemann A., Wilharm A., Wing J., Wirz O., Wittner J., Yang J. H. M., and Yang J.

Abstract

The third edition of Flow Cytometry Guidelines provides the key aspects to consider when performing flow cytometry experiments and includes comprehensive sections describing phenotypes and functional assays of all major human and murine immune cell subsets. Notably, the Guidelines contain helpful tables highlighting phenotypes and key differences between human and murine cells. Another useful feature of this edition is the flow cytometry analysis of clinical samples with examples of flow cytometry applications in the context of autoimmune diseases, cancers as well as acute and chronic infectious diseases. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid. All sections are written and peer-reviewed by leading flow cytometry experts and immunologists, making this edition an essential and state-of-the-art handbook for basic and clinical researchers.

Published
2021

5. Guidelines for the use of flow cytometry and cell sorting in immunological studies (third edition)

Author

Andrea Cossarizza, Hyun‐Dong Chang, Andreas Radbruch, Sergio Abrignani, Richard Addo, Mübeccel Akdis, Immanuel Andrä, Francesco Andreata, Francesco Annunziato, Eduardo Arranz, Petra Bacher, Sudipto Bari, Vincenzo Barnaba, Joana Barros‐Martins, Dirk Baumjohann, Cristian G. Beccaria, David Bernardo, Dominic A. Boardman, Jessica Borger, Chotima Böttcher, Leonie Brockmann, Marie Burns, Dirk H. Busch, Garth Cameron, Ilenia Cammarata, Antonino Cassotta, Yinshui Chang, Fernando Gabriel Chirdo, Eleni Christakou, Luka Čičin‐Šain, Laura Cook, Alexandra J. Corbett, Rebecca Cornelis, Lorenzo Cosmi, Martin S. Davey, Sara De Biasi, Gabriele De Simone, Genny del Zotto, Michael Delacher, Francesca Di Rosa, James Di Santo, Andreas Diefenbach, Jun Dong, Thomas Dörner, Regine J. Dress, Charles‐Antoine Dutertre, Sidonia B. G. Eckle, Pascale Eede, Maximilien Evrard, Christine S. Falk, Markus Feuerer, Simon Fillatreau, Aida Fiz‐Lopez, Marie Follo, Gemma A. Foulds, Julia Fröbel, Nicola Gagliani, Giovanni Galletti, Anastasia Gangaev, Natalio Garbi, José Antonio Garrote, Jens Geginat, Nicholas A. Gherardin, Lara Gibellini, Florent Ginhoux, Dale I. Godfrey, Paola Gruarin, Claudia Haftmann, Leo Hansmann, Christopher M. Harpur, Adrian C. Hayday, Guido Heine, Daniela Carolina Hernández, Martin Herrmann, Oliver Hoelsken, Qing Huang, Samuel Huber, Johanna E. Huber, Jochen Huehn, Michael Hundemer, William Y. K. Hwang, Matteo Iannacone, Sabine M. Ivison, Hans‐Martin Jäck, Peter K. Jani, Baerbel Keller, Nina Kessler, Steven Ketelaars, Laura Knop, Jasmin Knopf, Hui‐Fern Koay, Katja Kobow, Katharina Kriegsmann, H. Kristyanto, Andreas Krueger, Jenny F. Kuehne, Heike Kunze‐Schumacher, Pia Kvistborg, Immanuel Kwok, Daniela Latorre, Daniel Lenz, Megan K. Levings, Andreia C. Lino, Francesco Liotta, Heather M. Long, Enrico Lugli, Katherine N. MacDonald, Laura Maggi, Mala K. Maini, Florian Mair, Calin Manta, Rudolf Armin Manz, Mir‐Farzin Mashreghi, Alessio Mazzoni, James McCluskey, Henrik E. Mei, Fritz Melchers, Susanne Melzer, Dirk Mielenz, Leticia Monin, Lorenzo Moretta, Gabriele Multhoff, Luis Enrique Muñoz, Miguel Muñoz‐Ruiz, Franziska Muscate, Ambra Natalini, Katrin Neumann, Lai Guan Ng, Antonia Niedobitek, Jana Niemz, Larissa Nogueira Almeida, Samuele Notarbartolo, Lennard Ostendorf, Laura J. Pallett, Amit A. Patel, Gulce Itir Percin, Giovanna Peruzzi, Marcello Pinti, A. Graham Pockley, Katharina Pracht, Immo Prinz, Irma Pujol‐Autonell, Nadia Pulvirenti, Linda Quatrini, Kylie M. Quinn, Helena Radbruch, Hefin Rhys, Maria B. Rodrigo, Chiara Romagnani, Carina Saggau, Shimon Sakaguchi, Federica Sallusto, Lieke Sanderink, Inga Sandrock, Christine Schauer, Alexander Scheffold, Hans U. Scherer, Matthias Schiemann, Frank A. Schildberg, Kilian Schober, Janina Schoen, Wolfgang Schuh, Thomas Schüler, Axel R. Schulz, Sebastian Schulz, Julia Schulze, Sonia Simonetti, Jeeshan Singh, Katarzyna M. Sitnik, Regina Stark, Sarah Starossom, Christina Stehle, Franziska Szelinski, Leonard Tan, Attila Tarnok, Julia Tornack, Timothy I. M. Tree, Jasper J. P. van Beek, Willem van de Veen, Klaas van Gisbergen, Chiara Vasco, Nikita A. Verheyden, Anouk von Borstel, Kirsten A. Ward‐Hartstonge, Klaus Warnatz, Claudia Waskow, Annika Wiedemann, Anneke Wilharm, James Wing, Oliver Wirz, Jens Wittner, Jennie H. M. Yang, Juhao Yang, Rolf M. Schwiete Foundation, Associazione Italiana per la Ricerca sul Cancro, German Research Foundation, National Institutes of Health (US), European Commission, AII - Inflammatory diseases, Cossarizza, A, Chang, H, Radbruch, A, Abrignani, S, Addo, R, Akdis, M, Andra, I, Andreata, F, Annunziato, F, Arranz, E, Bacher, P, Bari, S, Barnaba, V, Barros-Martins, J, Baumjohann, D, Beccaria, C, Bernardo, D, Boardman, D, Borger, J, Bottcher, C, Brockmann, L, Burns, M, Busch, D, Cameron, G, Cammarata, I, Cassotta, A, Chang, Y, Chirdo, F, Christakou, E, Cicin-Sain, L, Cook, L, Corbett, A, Cornelis, R, Cosmi, L, Davey, M, De Biasi, S, De Simone, G, del Zotto, G, Delacher, M, Di Rosa, F, Santo, J, Diefenbach, A, Dong, J, Dorner, T, Dress, R, Dutertre, C, Eckle, S, Eede, P, Evrard, M, Falk, C, Feuerer, M, Fillatreau, S, Fiz-Lopez, A, Follo, M, Foulds, G, Frobel, J, Gagliani, N, Galletti, G, Gangaev, A, Garbi, N, Garrote, J, Geginat, J, Gherardin, N, Gibellini, L, Ginhoux, F, Godfrey, D, Gruarin, P, Haftmann, C, Hansmann, L, Harpur, C, Hayday, A, Heine, G, Hernandez, D, Herrmann, M, Hoelsken, O, Huang, Q, Huber, S, Huber, J, Huehn, J, Hundemer, M, Hwang, W, Iannacone, M, Ivison, S, Jack, H, Jani, P, Keller, B, Kessler, N, Ketelaars, S, Knop, L, Knopf, J, Koay, H, Kobow, K, Kriegsmann, K, Kristyanto, H, Krueger, A, Kuehne, J, Kunze-Schumacher, H, Kvistborg, P, Kwok, I, Latorre, D, Lenz, D, Levings, M, Lino, A, Liotta, F, Long, H, Lugli, E, Macdonald, K, Maggi, L, Maini, M, Mair, F, Manta, C, Manz, R, Mashreghi, M, Mazzoni, A, Mccluskey, J, Mei, H, Melchers, F, Melzer, S, Mielenz, D, Monin, L, Moretta, L, Multhoff, G, Munoz, L, Munoz-Ruiz, M, Muscate, F, Natalini, A, Neumann, K, Ng, L, Niedobitek, A, Niemz, J, Almeida, L, Notarbartolo, S, Ostendorf, L, Pallett, L, Patel, A, Percin, G, Peruzzi, G, Pinti, M, Pockley, A, Pracht, K, Prinz, I, Pujol-Autonell, I, Pulvirenti, N, Quatrini, L, Quinn, K, Radbruch, H, Rhys, H, Rodrigo, M, Romagnani, C, Saggau, C, Sakaguchi, S, Sallusto, F, Sanderink, L, Sandrock, I, Schauer, C, Scheffold, A, Scherer, H, Schiemann, M, Schildberg, F, Schober, K, Schoen, J, Schuh, W, Schuler, T, Schulz, A, Schulz, S, Schulze, J, Simonetti, S, Singh, J, Sitnik, K, Stark, R, Starossom, S, Stehle, C, Szelinski, F, Tan, L, Tarnok, A, Tornack, J, Tree, T, van Beek, J, van de Veen, W, van Gisbergen, K, Vasco, C, Verheyden, N, von Borstel, A, Ward-Hartstonge, K, Warnatz, K, Waskow, C, Wiedemann, A, Wilharm, A, Wing, J, Wirz, O, Wittner, J, Yang, J, Publica, Cossarizza, A., Chang, H. -D., Radbruch, A., Abrignani, S., Addo, R., Akdis, M., Andra, I., Andreata, F., Annunziato, F., Arranz, E., Bacher, P., Bari, S., Barnaba, V., Barros-Martins, J., Baumjohann, D., Beccaria, C. G., Bernardo, D., Boardman, D. A., Borger, J., Bottcher, C., Brockmann, L., Burns, M., Busch, D. H., Cameron, G., Cammarata, I., Cassotta, A., Chang, Y., Chirdo, F. G., Christakou, E., Cicin-Sain, L., Cook, L., Corbett, A. J., Cornelis, R., Cosmi, L., Davey, M. S., De Biasi, S., De Simone, G., del Zotto, G., Delacher, M., Di Rosa, F., Santo, J. D., Diefenbach, A., Dong, J., Dorner, T., Dress, R. J., Dutertre, C. -A., Eckle, S. B. G., Eede, P., Evrard, M., Falk, C. S., Feuerer, M., Fillatreau, S., Fiz-Lopez, A., Follo, M., Foulds, G. A., Frobel, J., Gagliani, N., Galletti, G., Gangaev, A., Garbi, N., Garrote, J. A., Geginat, J., Gherardin, N. A., Gibellini, L., Ginhoux, F., Godfrey, D. I., Gruarin, P., Haftmann, C., Hansmann, L., Harpur, C. M., Hayday, A. C., Heine, G., Hernandez, D. C., Herrmann, M., Hoelsken, O., Huang, Q., Huber, S., Huber, J. E., Huehn, J., Hundemer, M., Hwang, W. Y. K., Iannacone, M., Ivison, S. M., Jack, H. -M., Jani, P. K., Keller, B., Kessler, N., Ketelaars, S., Knop, L., Knopf, J., Koay, H. -F., Kobow, K., Kriegsmann, K., Kristyanto, H., Krueger, A., Kuehne, J. F., Kunze-Schumacher, H., Kvistborg, P., Kwok, I., Latorre, D., Lenz, D., Levings, M. K., Lino, A. C., Liotta, F., Long, H. M., Lugli, E., Macdonald, K. N., Maggi, L., Maini, M. K., Mair, F., Manta, C., Manz, R. A., Mashreghi, M. -F., Mazzoni, A., Mccluskey, J., Mei, H. E., Melchers, F., Melzer, S., Mielenz, D., Monin, L., Moretta, L., Multhoff, G., Munoz, L. E., Munoz-Ruiz, M., Muscate, F., Natalini, A., Neumann, K., Ng, L. G., Niedobitek, A., Niemz, J., Almeida, L. N., Notarbartolo, S., Ostendorf, L., Pallett, L. J., Patel, A. A., Percin, G. I., Peruzzi, G., Pinti, M., Pockley, A. G., Pracht, K., Prinz, I., Pujol-Autonell, I., Pulvirenti, N., Quatrini, L., Quinn, K. M., Radbruch, H., Rhys, H., Rodrigo, M. B., Romagnani, C., Saggau, C., Sakaguchi, S., Sallusto, F., Sanderink, L., Sandrock, I., Schauer, C., Scheffold, A., Scherer, H. U., Schiemann, M., Schildberg, F. A., Schober, K., Schoen, J., Schuh, W., Schuler, T., Schulz, A. R., Schulz, S., Schulze, J., Simonetti, S., Singh, J., Sitnik, K. M., Stark, R., Starossom, S., Stehle, C., Szelinski, F., Tan, L., Tarnok, A., Tornack, J., Tree, T. I. M., van Beek, J. J. P., van de Veen, W., van Gisbergen, K., Vasco, C., Verheyden, N. A., von Borstel, A., Ward-Hartstonge, K. A., Warnatz, K., Waskow, C., Wiedemann, A., Wilharm, A., Wing, J., Wirz, O., Wittner, J., Yang, J. H. M., and Yang, J.

Subjects
Immunology, citometry, Flow Cytometry, Infections, ddc, Autoimmune Diseases, Animals, Chronic Disease, Humans, Mice, Neoplasms, Practice Guidelines as Topic, Immunology and Allergy, ddc:610, Function and Dysfunction of the Nervous System, guideline
Abstract

© 2021 The Authors., The third edition of Flow Cytometry Guidelines provides the key aspects to consider when performing flow cytometry experiments and includes comprehensive sections describing phenotypes and functional assays of all major human and murine immune cell subsets. Notably, the Guidelines contain helpful tables highlighting phenotypes and key differences between human and murine cells. Another useful feature of this edition is the flow cytometry analysis of clinical samples with examples of flow cytometry applications in the context of autoimmune diseases, cancers as well as acute and chronic infectious diseases. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid. All sections are written and peer-reviewed by leading flow cytometry experts and immunologists, making this edition an essential and state-of-the-art handbook for basic and clinical researchers., Hyun-Dong Chang is supported by the Dr. Rolf M. Schwiete Foundation. Susanne Melzer and Attila Tarnok thank De Novo Software for providing FCS Express. Enrico Lugli is supported by a grant from the Associazione Italiana per la Ricerca sul Cancro (AIRC IG20676). Gabriele De Simone and Giovanni Galletti were supported by Fellowships from the Fondazione Italiana per la Ricerca sul Cancro-Associazione Italiana per la Ricerca sul Cancro (FIRC-AIRC). Jun Dong is supported by Deutsche Forschungsgemeinschft (DFG, German Research Foundation) Projektnummer 389687267 and Chinesisch-Deutsches Zentrum für Wissenschaftsförderung [Sino-German Center for Research Promotion (SGC)] grant C-0072. Nicola Gagliani, Samuel Huber and Franziska Muscate are supported by DFG fundings: SFB841,GA 2441/3-1, HU 1714/10-1. The tetramer APC-conjugated H-2K (d) HIV-1 gag197-205 AMQMLKETI used in TDS assay for mouse blood T cells was obtained through the NIH Tetramer Facility. Larissa Nogueira Almeida was supported by DFG research grant MA 2273/14-1. Supported by the following grants: AIRC 5X1000 2018 id. 21147 (Lorenzo Moretta); AIRC IG 2017 id. 19920 (Lorenzo Moretta); RC-2020 OPBG (Lorenzo Moretta); AIRC and European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 800924 (Linda Quatrini). Dirk Baumjohann was supported by Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Emmy Noether Programme BA 5132/1-2 (252623821) and Germany's Excellence Strategy EXC2151 (390873048).

Published
2021

6. The age-related decline of helicase function-how G-quadruplex structures promote genome instability.

Author

Frobel J and Hänsel-Hertsch R

Abstract

The intricate mechanisms underlying transcription-dependent genome instability involve G-quadruplexes (G4) and R-loops. This perspective elucidates the potential link between these structures and genome instability in aging. The co-occurrence of G4 DNA and RNA-DNA hybrid structures (G-loop) underscores a complex interplay in genome regulation and instability. Here, we hypothesize that the age-related decline of sirtuin function leads to an increase in acetylated helicases that bind to G4 DNA and RNA-DNA hybrid structures, but are less efficient in resolving them. We propose that acetylated, less active, helicases induce persistent G-loop structures, promoting transcription-dependent genome instability in aging., (© 2024 The Author(s). FEBS Letters published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.)

Published
2024
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7. Hematopoietic differentiation persists in human iPSCs defective in de novo DNA methylation.

Author

Cypris O, Franzen J, Frobel J, Glück P, Kuo CC, Schmitz S, Nüchtern S, Zenke M, and Wagner W

Subjects
Animals, Cell Differentiation genetics, DNA (Cytosine-5-)-Methyltransferases genetics, DNA (Cytosine-5-)-Methyltransferases metabolism, DNA Methylation, DNA Methyltransferase 3A, Epigenesis, Genetic, Humans, Mice, Induced Pluripotent Stem Cells metabolism, Induced Pluripotent Stem Cells pathology, Leukemia, Myeloid, Acute
Abstract

Background: DNA methylation is involved in the epigenetic regulation of gene expression during developmental processes and is primarily established by the DNA methyltransferase 3A (DNMT3A) and 3B (DNMT3B). DNMT3A is one of the most frequently mutated genes in clonal hematopoiesis and leukemia, indicating that it plays a crucial role for hematopoietic differentiation. However, the functional relevance of Dnmt3a for hematopoietic differentiation and hematological malignancies has mostly been analyzed in mice, with the specific role for human hematopoiesis remaining elusive. In this study, we therefore investigated if DNMT3A is essential for hematopoietic differentiation of human induced pluripotent stem cells (iPSCs)., Results: We generated iPSC lines with knockout of either exon 2, 19, or 23 and analyzed the impact of different DNMT3A exon knockouts on directed differentiation toward mesenchymal and hematopoietic lineages. Exon 19 -/- and 23 -/- lines displayed an almost entire absence of de novo DNA methylation during mesenchymal and hematopoietic differentiation. Yet, differentiation efficiency was only slightly reduced in exon 19 -/- and rather increased in exon 23 -/- lines, while there was no significant impact on gene expression in hematopoietic progenitors (iHPCs). Notably, DNMT3A -/- iHPCs recapitulate some DNA methylation patterns of acute myeloid leukemia (AML) with DNMT3A mutations. Furthermore, multicolor genetic barcoding revealed growth advantage of exon 23 -/- iHPCs in a syngeneic competitive differentiation assay., Conclusions: Our results demonstrate that iPSCs with homozygous knockout of different exons of DNMT3A remain capable of mesenchymal and hematopoietic differentiation-and exon 23 -/- iHPCs even gained growth advantage-despite loss of almost the entire de novo DNA methylation. Partial recapitulation of DNA methylation patterns of AML with DNMT3A mutations by our DNMT3A knockout iHPCs indicates that our model system can help to elucidate mechanisms of clonal hematopoiesis., (© 2022. The Author(s).)

Published
2022
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8. Tracking of epigenetic changes during hematopoietic differentiation of induced pluripotent stem cells.

Author

Cypris O, Frobel J, Rai S, Franzen J, Sontag S, Goetzke R, Szymanski de Toledo MA, Zenke M, and Wagner W

Subjects
Cell Differentiation, Cell Proliferation, Cells, Cultured, Coculture Techniques, Epigenesis, Genetic, Hematopoietic Stem Cells chemistry, Humans, Induced Pluripotent Stem Cells chemistry, Mesenchymal Stem Cells cytology, DNA Methylation, Hematopoietic Stem Cells cytology, Induced Pluripotent Stem Cells cytology, Leukocyte Common Antigens genetics
Abstract

Background: Differentiation of induced pluripotent stem cells (iPSCs) toward hematopoietic progenitor cells (HPCs) raises high hopes for disease modeling, drug screening, and cellular therapy. Various differentiation protocols have been established to generate iPSC-derived HPCs (iHPCs) that resemble their primary counterparts in morphology and immunophenotype, whereas a systematic epigenetic comparison was yet elusive., Results: In this study, we compared genome-wide DNA methylation (DNAm) patterns of iHPCs with various different hematopoietic subsets. After 20 days of in vitro differentiation, cells revealed typical hematopoietic morphology, CD45 expression, and colony-forming unit (CFU) potential. DNAm changes were particularly observed in genes that are associated with hematopoietic differentiation. On the other hand, the epigenetic profiles of iHPCs remained overall distinct from natural HPCs. Furthermore, we analyzed if additional co-culture for 2 weeks with syngenic primary mesenchymal stromal cells (MSCs) or iPSC-derived MSCs (iMSCs) further supports epigenetic maturation toward the hematopoietic lineage. Proliferation of iHPCs and maintenance of CFU potential was enhanced upon co-culture. However, DNAm profiles support the notion that additional culture expansion with stromal support did not increase epigenetic maturation of iHPCs toward natural HPCs., Conclusion: Differentiation of iPSCs toward the hematopoietic lineage remains epigenetically incomplete. These results substantiate the need to elaborate advanced differentiation regimen while DNAm profiles provide a suitable measure to track this process.

Published
2019
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9. Variants of DNMT3A cause transcript-specific DNA methylation patterns and affect hematopoiesis.

Author

Božić T, Frobel J, Raic A, Ticconi F, Kuo CC, Heilmann-Heimbach S, Goecke TW, Zenke M, Jost E, Costa IG, and Wagner W

Abstract

De novo DNA methyltransferase 3A (DNMT3A) plays pivotal roles in hematopoietic differentiation. In this study, we followed the hypothesis that alternative splicing of DNMT3A has characteristic epigenetic and functional sequels. Specific DNMT3A transcripts were either down-regulated or overexpressed in human hematopoietic stem and progenitor cells, and this resulted in complementary and transcript-specific DNA methylation and gene expression changes. Functional analysis indicated that, particularly, transcript 2 (coding for DNMT3A2) activates proliferation and induces loss of a primitive immunophenotype, whereas transcript 4 interferes with colony formation of the erythroid lineage. Notably, in acute myeloid leukemia expression of transcript 2 correlates with its in vitro DNA methylation and gene expression signatures and is associated with overall survival, indicating that DNMT3A variants also affect malignancies. Our results demonstrate that specific DNMT3A variants have a distinct epigenetic and functional impact. Particularly, DNMT3A2 triggers hematopoietic differentiation and the corresponding signatures are reflected in acute myeloid leukemia., Competing Interests: RWTH Aachen Medical School has applied for a patent on the DNMT3A epimutation. W Wagner is involved in Cygenia GmbH that can provide service for epigenetic diagnostics. Apart from this, the authors do not have a conflict of interest to declare.

Published
2018
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10. Epigenetic aging of human hematopoietic cells is not accelerated upon transplantation into mice.

Author

Frobel J, Rahmig S, Franzen J, Waskow C, and Wagner W

Subjects
Animals, Cell Differentiation, Cells, Cultured, Cellular Senescence, Epigenesis, Genetic, Hematopoiesis, Hematopoietic Stem Cell Transplantation, Hematopoietic Stem Cells chemistry, Humans, Mice, DNA Methylation, Genome-Wide Association Study methods, Hematopoietic Stem Cells cytology
Abstract

Background: Transplantation of human hematopoietic stem cells into immunodeficient mice provides a powerful in vivo model system to gain functional insights into hematopoietic differentiation. So far, it remains unclear if epigenetic changes of normal human hematopoiesis are recapitulated upon engraftment into such "humanized mice." Mice have a much shorter life expectancy than men, and therefore, we hypothesized that the xenogeneic environment might greatly accelerate the epigenetic clock., Results: We demonstrate that genome-wide DNA methylation patterns of normal human hematopoietic development are indeed recapitulated upon engraftment in mice-particularly those of normal early B cell progenitor cells. Furthermore, we tested three epigenetic aging signatures, and none of them indicated that the murine environment accelerated age-associated DNA methylation changes., Conclusions: Epigenetic changes of human hematopoietic development are recapitulated in the murine transplantation model, whereas epigenetic aging is not accelerated by the faster aging environment and seems to occur in the cell intrinsically., Competing Interests: All human samples were used in accordance with the guidelines approved by the Ethics Committee of the Dresden University of Technology. Animal experiments were performed in accordance with German animal welfare legislation and approved by the relevant authorities (Landesdirektion Dresden, Referat 24).WW is a cofounder of Cygenia GmbH that can provide service for Epigenetic-Aging-Signatures (www.cygenia.com). Apart from that, the authors declare that they have no competing interests.Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Published
2018
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11. Leukocyte Counts Based on DNA Methylation at Individual Cytosines.

Author

Frobel J, Božić T, Lenz M, Uciechowski P, Han Y, Herwartz R, Strathmann K, Isfort S, Panse J, Esser A, Birkhofer C, Gerstenmaier U, Kraus T, Rink L, Koschmieder S, and Wagner W

Subjects
Blood Preservation methods, Carrier Proteins genetics, CpG Islands, Humans, Leukocytes physiology, Lymphocyte Subsets, Lymphoma blood, Lymphoma genetics, Proto-Oncogene Proteins c-fyn genetics, Reproducibility of Results, Cytosine metabolism, DNA Methylation, Leukocyte Count methods
Abstract

Background: White blood cell counts are routinely measured with automated hematology analyzers, by flow cytometry, or by manual counting. Here, we introduce an alternative approach based on DNA methylation (DNAm) at individual CG dinucleotides (CpGs)., Methods: We identified candidate CpGs that were nonmethylated in specific leukocyte subsets. DNAm levels (ranging from 0% to 100%) were analyzed by pyrosequencing and implemented into deconvolution algorithms to determine the relative composition of leukocytes. For absolute quantification of cell numbers, samples were supplemented with a nonmethylated reference DNA., Results: Conventional blood counts correlated with DNAm at individual CpGs for granulocytes ( r = -0.91), lymphocytes ( r = -0.91), monocytes ( r = -0.74), natural killer (NK) cells ( r = -0.30), T cells ( r = -0.73), CD4+ T cells ( r = -0.41), CD8+ T cells ( r = -0.88), and B cells ( r = -0.66). Combination of these DNAm measurements into the "Epi-Blood-Count" provided similar precision as conventional methods in various independent validation sets. The method was also applicable to blood samples that were stored at 4 °C for 7 days or at -20 °C for 3 months. Furthermore, absolute cell numbers could be determined in frozen blood samples upon addition of a reference DNA, and the results correlated with measurements of automated analyzers in fresh aliquots ( r = 0.84)., Conclusions: White blood cell counts can be reliably determined by site-specific DNAm analysis. This approach is applicable to very small blood volumes and frozen samples, and it allows for more standardized and cost-effective analysis in clinical application., (© 2017 American Association for Clinical Chemistry.)

Published
2018
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12. Epigenetic quality check - how good are your mesenchymal stromal cells?

Author

Wagner W, Frobel J, and Goetzke R

Subjects
Clinical Trials as Topic methods, Clinical Trials as Topic standards, Gene Expression Regulation, Humans, Quality Control, Reproducibility of Results, Tissue Engineering methods, Tissue Engineering standards, Epigenesis, Genetic physiology, Mesenchymal Stem Cell Transplantation standards, Mesenchymal Stem Cells metabolism
Published
2016
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13. iPSC-derived mesenchymal stromal cells are less supportive than primary MSCs for co-culture of hematopoietic progenitor cells.

Author

Vasko T, Frobel J, Lubberich R, Goecke TW, and Wagner W

Subjects
AC133 Antigen, Antigens, CD genetics, Antigens, CD metabolism, Antigens, CD34 metabolism, Cadherins genetics, Cadherins metabolism, Cell Communication, Cells, Cultured, Coculture Techniques, Flow Cytometry, Gene Expression Profiling, Glycoproteins metabolism, Hematopoietic Stem Cells metabolism, Humans, Immunophenotyping, Induced Pluripotent Stem Cells metabolism, Laminin genetics, Laminin metabolism, Mesenchymal Stem Cells metabolism, Peptides metabolism, Vascular Cell Adhesion Molecule-1 genetics, Vascular Cell Adhesion Molecule-1 metabolism, Cell Culture Techniques methods, Cell Differentiation, Hematopoietic Stem Cells cytology, Induced Pluripotent Stem Cells cytology, Mesenchymal Stem Cells cytology
Abstract

In vitro culture of hematopoietic stem and progenitor cells (HPCs) is supported by a suitable cellular microenvironment, such as mesenchymal stromal cells (MSCs)-but MSCs are heterogeneous and poorly defined. In this study, we analyzed whether MSCs derived from induced pluripotent stem cells (iPS-MSCs) provide a suitable cellular feeder layer too. iPS-MSCs clearly supported proliferation of HPCs, maintenance of a primitive immunophenotype (CD34(+), CD133(+), CD38(-)), and colony-forming unit (CFU) potential of CD34(+) HPCs. However, particularly long-term culture-initiating cell (LTC-IC) frequency was lower with iPS-MSCs as compared to primary MSCs. Relevant genes for cell-cell interaction were overall expressed at similar level in MSCs and iPS-MSCs, whereas VCAM1 was less expressed in the latter. In conclusion, our iPS-MSCs support in vitro culture of HPCs; however, under the current differentiation and culture conditions, they are less suitable than primary MSCs from bone marrow.

Published
2016
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14. Epigenetic Classification of Human Mesenchymal Stromal Cells.

Author

de Almeida DC, Ferreira MR, Franzen J, Weidner CI, Frobel J, Zenke M, Costa IG, and Wagner W

Subjects
Adipose Tissue cytology, Bone Marrow Cells cytology, Clone Cells, CpG Islands genetics, DNA Methylation genetics, Fibroblasts metabolism, Humans, Induced Pluripotent Stem Cells cytology, Mesenchymal Stem Cells cytology, Epigenesis, Genetic, Mesenchymal Stem Cells classification, Mesenchymal Stem Cells metabolism
Abstract

Standardization of mesenchymal stromal cells (MSCs) is hampered by the lack of a precise definition for these cell preparations; for example, there are no molecular markers to discern MSCs and fibroblasts. In this study, we followed the hypothesis that specific DNA methylation (DNAm) patterns can assist classification of MSCs. We utilized 190 DNAm profiles to address the impact of tissue of origin, donor age, replicative senescence, and serum supplements on the epigenetic makeup. Based on this, we elaborated a simple epigenetic signature based on two CpG sites to classify MSCs and fibroblasts, referred to as the Epi-MSC-Score. Another two-CpG signature can distinguish between MSCs from bone marrow and adipose tissue, referred to as the Epi-Tissue-Score. These assays were validated by site-specific pyrosequencing analysis in 34 primary cell preparations. Furthermore, even individual subclones of MSCs were correctly classified by our epigenetic signatures. In summary, we propose an alternative concept to use DNAm patterns for molecular definition of cell preparations, and our epigenetic scores facilitate robust and cost-effective quality control of MSC cultures., (Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.)

Published
2016
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16. DNA-methylation in C1R is a prognostic biomarker for acute myeloid leukemia.

Author

Božić T, Lin Q, Frobel J, Wilop S, Hoffmann M, Müller-Tidow C, Brümmendorf TH, Jost E, and Wagner W

Abstract

Background: Epigenetic aberrations play a central role in the pathophysiology of acute myeloid leukemia (AML). It has been shown that molecular signatures based on DNA-methylation (DNAm) patterns can be used for classification of the disease. In this study, we followed the hypothesis that DNAm at a single CpG site might support risk stratification in AML., Findings: Using DNAm profiles of 194 patients from The Cancer Genome Atlas (TCGA), we identified a CpG site in complement component 1 subcomponent R (C1R) as best suited biomarker: patients with higher methylation at this CpG site (>27 % DNAm) reveal significantly longer overall survival (53 versus 11 months; P < 0.0001). This finding was validated in an independent set of 62 DNAm profiles of cytogenetically normal AML patients (P = 0.009) and with a region-specific pyrosequencing assay in 84 AML samples (P = 0.012). DNAm of C1R correlated with genomic DNAm and gene expression patterns, whereas there was only moderate association with gene expression levels of C1R. These results indicate that DNAm of C1R is a biomarker reflecting chromatin reorganization rather than being of pathophysiological relevance per se. Notably, DNAm of C1R was associated with occurrence of specific genomic mutations that are traditionally used for risk stratification in AML. Furthermore, DNAm of C1R correlates also with overall survival in several other types of cancer, but the prognostic relevance was less pronounced than in AML., Conclusions: Analysis of DNAm at C1R provides a simple, robust, and cost-effective biomarker to further complement risk assessment in AML.

Published
2015
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17. Epigenetic rejuvenation of mesenchymal stromal cells derived from induced pluripotent stem cells.

Author

Frobel J, Hemeda H, Lenz M, Abagnale G, Joussen S, Denecke B, Sarić T, Zenke M, and Wagner W

Subjects
Cell Differentiation, Cells, Cultured, DNA Methylation, Humans, Induced Pluripotent Stem Cells cytology, Mesenchymal Stem Cells cytology, Transcriptome, Epigenesis, Genetic, Induced Pluripotent Stem Cells metabolism, Mesenchymal Stem Cells metabolism
Abstract

Standardization of mesenchymal stromal cells (MSCs) remains a major obstacle in regenerative medicine. Starting material and culture expansion affect cell preparations and render comparison between studies difficult. In contrast, induced pluripotent stem cells (iPSCs) assimilate toward a ground state and may therefore give rise to more standardized cell preparations. We reprogrammed MSCs into iPSCs, which were subsequently redifferentiated toward MSCs. These iPS-MSCs revealed similar morphology, immunophenotype, in vitro differentiation potential, and gene expression profiles as primary MSCs. However, iPS-MSCs were impaired in suppressing T cell proliferation. DNA methylation (DNAm) profiles of iPSCs maintained donor-specific characteristics, whereas tissue-specific, senescence-associated, and age-related DNAm patterns were erased during reprogramming. iPS-MSCs reacquired senescence-associated DNAm during culture expansion, but they remained rejuvenated with regard to age-related DNAm. Overall, iPS-MSCs are similar to MSCs, but they reveal incomplete reacquisition of immunomodulatory function and MSC-specific DNAm patterns-particularly of DNAm patterns associated with tissue type and aging., (Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.)

Published
2014
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