Stripping flow cytometry: How many detectors do we need for bacterial identification?. Issue 12 (22nd November 2017)
- Record Type:
- Journal Article
- Title:
- Stripping flow cytometry: How many detectors do we need for bacterial identification?. Issue 12 (22nd November 2017)
- Main Title:
- Stripping flow cytometry: How many detectors do we need for bacterial identification?
- Authors:
- Rubbens, Peter
Props, Ruben
Garcia‐Timermans, Cristina
Boon, Nico
Waegeman, Willem - Abstract:
- Abstract: Multicolor approaches are challenging for microbial flow cytometry; as flow cytometers are mainly developed for biomedical applications, modern instruments contain more detectors than needed. Some of these additional fluorescence detectors measure biological information due to spectral overlap, yet the extent to which this information is relevant for the identification of bacterial populations is ambiguous. In this paper we characterize the usefulness of these additional detectors. We propose a data‐driven detector selection method to select the smallest subset of detectors that will optimally discriminate between bacterial populations. Using a detector elimination strategy, we show that one or more detectors can be removed without loss of resolving power. A number of additional detectors are included in the final subset, which help to improve the identification of bacterial populations. Experimental data were retrieved from two types of modern cytometers with different configurations. The method reveals a clear ordering of detector importances, which depends on the instrument from which the data were retrieved. In addition, we were able to pinpoint unexpected behavior of SYBR Green I in the red spectrum. As the field of microbial flow cytometry is maturing, these results motivate the construction of a different kind of cytometric instruments for microbiologists, for which the number of detectors is reduced, but tailored toward the characteristics of microbialAbstract: Multicolor approaches are challenging for microbial flow cytometry; as flow cytometers are mainly developed for biomedical applications, modern instruments contain more detectors than needed. Some of these additional fluorescence detectors measure biological information due to spectral overlap, yet the extent to which this information is relevant for the identification of bacterial populations is ambiguous. In this paper we characterize the usefulness of these additional detectors. We propose a data‐driven detector selection method to select the smallest subset of detectors that will optimally discriminate between bacterial populations. Using a detector elimination strategy, we show that one or more detectors can be removed without loss of resolving power. A number of additional detectors are included in the final subset, which help to improve the identification of bacterial populations. Experimental data were retrieved from two types of modern cytometers with different configurations. The method reveals a clear ordering of detector importances, which depends on the instrument from which the data were retrieved. In addition, we were able to pinpoint unexpected behavior of SYBR Green I in the red spectrum. As the field of microbial flow cytometry is maturing, these results motivate the construction of a different kind of cytometric instruments for microbiologists, for which the number of detectors is reduced, but tailored toward the characteristics of microbial experiments. © 2017 International Society for Advancement of Cytometry … (more)
- Is Part Of:
- Cytometry. Volume 91:Issue 12(2017)
- Journal:
- Cytometry
- Issue:
- Volume 91:Issue 12(2017)
- Issue Display:
- Volume 91, Issue 12 (2017)
- Year:
- 2017
- Volume:
- 91
- Issue:
- 12
- Issue Sort Value:
- 2017-0091-0012-0000
- Page Start:
- 1184
- Page End:
- 1191
- Publication Date:
- 2017-11-22
- Subjects:
- automated identification of bacterial populations -- bacterial communities -- detector elimination -- flow cytometry -- microbiology -- single‐cell analysis -- synthetic microbiology -- variable selection
Flow cytometry -- Periodicals
Imaging systems in biology -- Periodicals
Imaging systems in medicine -- Periodicals
Diagnostic imaging -- Periodicals
571.605 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1552-4930 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/cyto.a.23284 ↗
- Languages:
- English
- ISSNs:
- 1552-4922
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3506.855100
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 5549.xml