In Flow Cytometry, Image Is Everything

Goda, Keisuke; Filby, Andrew; Nitta, Nao

doi:10.1002/cyto.a.23778

Cited by 11 publications

(6 citation statements)

References 27 publications

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“…Once coupled with cell sorting, FCM can be successfully applied to isolate cyanobacteria from mixed phytoplankton samples. The recent emergence of advanced microfluidics, the availability of sophisticated digital image processing techniques, the advent of various optical imaging modalities, and image-guided cell sorting extend the capabilities of FCM from the measurements of one-dimensional signal intensities to multidimensional information-rich images, which can be used to analyze the spatial architecture of single cells in flow in addition to the analysis of the volume samples [125]. However, the presence of autofluorescence in cyanobacterial cells limits the use of staining cells with synthetic fluorochromes due to signal overlap.…”

Section: Flow Cytometrymentioning

confidence: 99%

Studying Cyanobacteria by Means of Fluorescence Methods: A Review

Grigoryeva¹

2020

Fluorescence Methods for Investigation of Living Cells and Microorganisms

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Self-fluorescence is a powerful tool for investigation of living photosynthetic microorganisms. Since the physiological state of such microorganisms is closely related to the operation and activity of photosynthetic system; thus, any variations in spectroscopic properties of their self-fluorescence indicate the changes in their physiological state. Cyanobacteria (or blue green alga) are one of the most widespread photosynthetic organisms in nature, and the ecological aspect in their investigation is quite valuable. On the other hand, thousands of strains belonging to different cyanobacterial species are cultivated in biolaboratories all over the world for different biotechnological applications such as biofuel cells, food production, pharmaceuticals, and fertilizers. Thus, the novel noninvasive methods of their investigation are quite important for on-line monitoring of cyanobacterial cultures. In this chapter, several fluorescence techniques are presented for investigation of living cyanobacterial cells and cultures.

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Section: Flow Cytometrymentioning

confidence: 99%

Studying Cyanobacteria by Means of Fluorescence Methods: A Review

Grigoryeva¹

2020

Fluorescence Methods for Investigation of Living Cells and Microorganisms

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“…Imaging flow cytometry (IFC) (11, 12) potentially offers a powerful alternative for cell cycle analysis, since it combines the high-throughput and quantitative analysis of flow cytometry with the visual and spatial information of microscopy by capturing images in brightfield, darkfield and fluorescence modes for every cell analysed. Further, the application of masks to identify areas of interest allows many morphological parameters, including length, width, perimeter, area, aspect ratio (AR) and circularity to be measured or calculated automatically.…”

Section: Introductionmentioning

confidence: 99%

Analysis of theLeishmania mexicanapromastigote cell cycle using imaging flow cytometry provides new insights into cell cycle flexibility and events of short duration

Howell

Omwenga

Jimenez

et al. 2023

Preprint

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PromastigoteLeishmania mexicanahave a complex cell division cycle characterised by the ordered replication of several single-copy organelles, a prolonged S phase and very rapid G2 and cytokinesis phases, accompanied by cell cycle stage-associated morphological changes. Here we exploit these morphological changes to develop a high-throughput and semi-automated imaging flow cytometry (IFC) pipeline to analyse the cell cycle ofL. mexicanain live cells. Firstly, we demonstrate that, unlike several other DNA stains, Vybrant™ DyeCycle™ Orange (DCO) is non-toxic and enables quantitative DNA imaging in liveL. mexicanapromastigotes. Secondly, by tagging the orphan spindle kinesin, KINF, with mNeonGreen, we describe KINF’s cell cycle-dependent expression and localisation. Then, by combining manual gating of DCO DNA intensity profiles with automated masking and morphological measurements of parasite images, visual determination of the number of flagella per cell, and automated masking and analysis of mNG:KINF fluorescence, we provide a newly detailed description ofL. mexicanapromastigote cell cycle events that, for the first time, includes the durations of individual G2, mitosis and post-mitosis phases. By applying IFC in this way, we were able, in minutes, to capture tens of thousands of high quality brightfield and fluorescent images of liveL. mexicanacells in solution, and to acquire quantitative data across multiple parameters for every image captured. Our custom-developed masking and gating scheme, allowed us to identify elusive G2 cells, show that cytokinesis commences during early mitosis and continues after mitosis is complete, and identify newly divided cells that were within the first 12 minutes of the new cell cycle. Our new pipeline offers many advantages over traditional methods of cell cycle analysis such as fluorescence microscopy and flow cytometry and paves the way for novel high-throughput analysis ofLeishmaniacell division.

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“…Imaging flow cytometer (IFC) combines the imaging capability of microscope and high cell analysis throughout of flow cytometer. Thus IFC can acquire high resolution cell images at a throughput of hundreds cells to 10000 cells per second [4,5]. On the other hand, for each single cell, normally several image channels are acquired, which provides rich information that benefits cell analysis.…”

Section: Introductionmentioning

confidence: 99%

Deep Learning based Cell Classification in Imaging Flow Cytometer

Chen

Xin

et al. 2021

ASP Trans. Pattern Recognit. Intell. Syst.

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Deep learning is an idea technique for image classification. Imaging flow cytometer enables high throughput cell image acquisition and some have integrated with real-time cell sorting. The combination of deep learning and imaging flow cytometer has changed the landscape of high throughput cell analysis research. In this review, we focus on deep learning technologies applied in imaging flow cytometer for cell classification and real-time cell sorting. This article describes some recent research, challenges and future trend in this area.

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In Flow Cytometry, Image Is Everything

Cited by 11 publications

References 27 publications

Studying Cyanobacteria by Means of Fluorescence Methods: A Review

Studying Cyanobacteria by Means of Fluorescence Methods: A Review

Analysis of theLeishmania mexicanapromastigote cell cycle using imaging flow cytometry provides new insights into cell cycle flexibility and events of short duration

Deep Learning based Cell Classification in Imaging Flow Cytometer

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