scholarly journals Real-time fluorescence and deformability cytometry — flow cytometry goes mechanics

2017 ◽  
Author(s):  
Philipp Rosendahl ◽  
Katarzyna Plak ◽  
Angela Jacobi ◽  
Martin Kraeter ◽  
Nicole Toepfner ◽  
...  

AbstractCell mechanical characterization has recently approached the throughput of conventional flow cytometers. However, this very sensitive, label-free approach still lacks the specificity of molecular markers. Here we combine real-time 1D-imaging fluorescence and deformability cytometry (RT-FDC) to merge the two worlds in one instrument — opening many new research avenues. We demonstrate its utility using sub-cellular fluorescence localization to identify mitotic cells and test for their mechanical changes in an RNAi screen.

Author(s):  
Maik Herbig ◽  
Martin Kräter ◽  
Katarzyna Plak ◽  
Paul Müller ◽  
Jochen Guck ◽  
...  

2019 ◽  
Author(s):  
Ahmad Ahsan Nawaz ◽  
Marta Urbanska ◽  
Maik Herbig ◽  
Martin Nötzel ◽  
Martin Kräter ◽  
...  

The identification and separation of specific cells from heterogeneous populations is an essential prerequisite for further analysis or use. Conventional passive and active separation approaches rely on fluorescent or magnetic tags introduced to the cells of interest through molecular markers. Such labeling is time- and cost-intensive, can alter cellular properties, and might be incompatible with subsequent use, for example, in transplantation. Alternative label-free approaches utilizing morphological or mechanical features are attractive, but lack molecular specificity. Here we combine image-based real-time fluorescence and deformability cytometry (RT-FDC) with downstream cell sorting using standing surface acoustic waves (SSAW). We demonstrate basic sorting capabilities of the device by separating cell mimics and blood cell types based on fluorescence as well as deformability and other image parameters. The identification of blood sub-populations is enhanced by flow alignment and deformation of cells in the microfluidic channel constriction. In addition, the classification of blood cells using established fluorescence-based markers provides hundreds of thousands of labeled cell images used to train a deep neural network. The trained algorithm, with latency optimized to below 1 ms, is then used to identify and sort unlabeled blood cells at rates of 100 cells/sec. This approach transfers molecular specificity into label-free sorting and opens up new possibilities for basic biological research and clinical therapeutic applications.


PLoS ONE ◽  
2016 ◽  
Vol 11 (5) ◽  
pp. e0156269 ◽  
Author(s):  
Mazen A. Juratli ◽  
Yulian A. Menyaev ◽  
Mustafa Sarimollaoglu ◽  
Eric R. Siegel ◽  
Dmitry A. Nedosekin ◽  
...  
Keyword(s):  

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Chengzhong Cai ◽  
Dmitry A. Nedosekin ◽  
Yulian A. Menyaev ◽  
Mustafa Sarimollaoglu ◽  
Mikhail A. Proskurnin ◽  
...  

Control of sickle cell disease (SCD) stage and treatment efficiency are still time-consuming which makes well-timed prevention of SCD crisis difficult. We show here thatin vivophotoacoustic (PA) flow cytometry (PAFC) has a potential for real-time monitoring of circulating sickled cells in mouse model.In vivodata were verified byin vitroPAFC and photothermal (PT) and PA spectral imaging of sickle red blood cells (sRBCs) expressing SCD-associated hemoglobin (HbS) compared to normal red blood cells (nRBCs). We discovered that PT and PA signal amplitudes from sRBCs in linear mode were 2–4-fold lower than those from nRBCs. PT and PA imaging revealed more profound spatial hemoglobin heterogeneity in sRBCs than in nRBCs, which can be associated with the presence of HbS clusters with high local absorption. This hypothesis was confirmed in nonlinear mode through nanobubble formation around overheated HbS clusters accompanied by spatially selective signal amplification. More profound differences in absorption of sRBCs than in nRBCs led to notable increase in PA signal fluctuation (fluctuation PAFC mode) as an indicator of SCD. The obtained data suggest that noninvasive label-free fluctuation PAFC has a potential for real-time enumeration of sRBCs bothin vitroandin vivo.


Lab on a Chip ◽  
2021 ◽  
Author(s):  
Yongxiang Feng ◽  
Zhen Cheng ◽  
Huichao Chai ◽  
Weihua He ◽  
Liang Huang ◽  
...  

Single-cell impedance flow cytometry (IFC) is emerging as a label-free and non-invasive method for characterizing the electrical properties and revealing the sample heterogeneity. At present, most IFC works utilized phenomenological...


Lab on a Chip ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 2306-2316 ◽  
Author(s):  
Konstanze Aurich ◽  
Bob Fregin ◽  
Raghavendra Palankar ◽  
Jan Wesche ◽  
Oliver Hartwich ◽  
...  

Real-time deformability cytometry is a unique tool for quality assessment of therapeutic blood cells utilizing their mechanical properties.


2020 ◽  
Author(s):  
Hossein Tavassoli ◽  
Prunella Rorimpandey ◽  
Young Chan Kang ◽  
Michael Carnell ◽  
Chris Brownlee ◽  
...  

AbstractTo advance our understanding of cardiomyocyte identity and function, we need appropriate tools to isolate pure primary cardiomyocytes. We have developed a label-free method to purify viable cardiomyocytes from mouse neonatal hearts using a simple inertial microfluidics biochip. Cardiomyocytes were sorted from neonatal hearts and isolated to >90% purity and their physico-mechanical properties were evaluated using real time deformability cytometry. Purified cardiomyocytes were viable and retained their identity and function as depicted by expression of cardiac specific markers and contractility. Furthermore, we showed that cardiomyocytes have a distinct physico-mechanical phenotype that could be used as an intrinsic biophysical marker to distinguish these cells from other cell types within the heart. Taken together, this cardiomyocyte isolation and phenotyping method could serve as a valuable tool to progress our understanding of cardiomyocyte identity and function, which will ultimately benefit many diagnostic development and cardiac treatment studies.


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