Raman flow cytometry using time-delay integration
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (Arcadia Science)
Abstract
Raman flow cytometry offers chemically sensitive, label-free measurement of cells and particles; however, the technique suffers from low cell throughput due to the weak Raman signal. Here, we demonstrate the use of time-delay integration (TDI) to achieve Raman flow cytometry combined with dual-sided line illumination. The use of line illumination from both sides of the cell flow capillary kept the cell stream in the detection area by balancing optical force from the illumination lines. The TDI allowed the accumulation of Raman signals from flowing cells without sacrificing the spectrum readout rate. With the developed system, we achieved Raman flow cytometry at throughputs of 32 and 78 events per second for cell and particle detection, respectively. We applied the technique for analyzing biological cells and successfully detected lipid uptake in HepG2 cells and degranulation in bone-marrow-derived murine mast cells. Our TDI Raman flow cytometry approach improves the throughput of Raman-spectroscopy-based cell analysis and extends its applicability to a wider range of biomedical research.
Article activity feed
-
To counteract this, we retroreflected the illumination line as shown in Figure 1C & D, such that the flowing sample was illuminated (pushed) from both sides.
Instead of adding the second beam to counteract the force of the light sheet, is it possible to add a 3D sheath flow that pushes cells toward the bottom of the channel? This paper explains this concept https://doi.org/10.1063/5.0033291
-
-
We flowed cells through a square quartz capil-lary (outer width and height 600 µm, channel width andheight 240 µm)
Given the high light intensity and the duration of the exposure of each cell, do you have a sense of whether the spectrum generated when the cell first enters the light beam differs from the spectrum at the end? You might be able to find this by removing the temporal integration and averaging the spectra of different cells across the integration window.
-
As an application demonstration, we analyzed the lipid con-tent of the human HepG2 hepatocyte cell line followingtreatment with 0.2 mM free fatty acid (FFA). Cells werecultured under two conditions. These consisted of a controlsample, and a sample with FFA in the growth media usingbovine serum albumin (BSA) as a carrier. More than 1800events for each condition were analyzed by our flow cytom-eter, with the average spectrum from each condition shownin Figure 4A. An increased lipid signal at 2862 cm-1 can beobserved in the FFA sample. To distinguish this fatty acidaccumulation at the single event level, we applied principalcomponent analysis-linear discriminant analysis (PCA-LDA). PCA was first applied and the first principal compo-nents (PCs) contributing 95% were selected. Then we traineda linear discrimination analysis (LDA) model on …
As an application demonstration, we analyzed the lipid con-tent of the human HepG2 hepatocyte cell line followingtreatment with 0.2 mM free fatty acid (FFA). Cells werecultured under two conditions. These consisted of a controlsample, and a sample with FFA in the growth media usingbovine serum albumin (BSA) as a carrier. More than 1800events for each condition were analyzed by our flow cytom-eter, with the average spectrum from each condition shownin Figure 4A. An increased lipid signal at 2862 cm-1 can beobserved in the FFA sample. To distinguish this fatty acidaccumulation at the single event level, we applied principalcomponent analysis-linear discriminant analysis (PCA-LDA). PCA was first applied and the first principal compo-nents (PCs) contributing 95% were selected. Then we traineda linear discrimination analysis (LDA) model on the datasets reconstructed by the selected PCs. 5/6 of the data wasused as a randomly selected training set and model accuracywas validated against the remaining 1/6 of data, yielding aclassification accuracy of 89%. We show the plot of LDAscores in Figure 4B. We next used our flow cytometer to dis-tinguish granulated and degranulated murine mast cells.Mast cells are granulocytes which play a role in inflamma-tory immune system by releasing histamines from intracel-lular storage granules in response to pathogens, parasites, orallergens. Averaged spectra from all events for granulatedand degranulated samples are shown in Figure 4C. PCA-LDA classification distinguished the samples with an accu-racy of 81%. We show the LDA scores in Figure 4D
Given the high photon flux in the exposure cuvette, do you know how much light damage is occurring? Have you tried to culture the cells after cytometry? Are they viable? If not, do you know whether this impacts the spectra generated by these cells?
-
hat shaped the beam into a light sheet
What was the length of the light sheet? I am curious about how the time integrated signal might be impacted by the size of the cells and how long they spend in the light sheet.
-
We designed the image magnification at the CCD camera to be low (4.8 to 9.6 times) so that signal from a relatively large volume within the sample could be integrated in a single CCD pixel
With the objectives used, what area does a CCD pixel cover? Is this cellular level resolution for the HepG2 cells (diameter ~20µm) and could cellular resolution for smaller cells, e.g. E. coli (diameter ~2µm) also be achieved?
-
acoustic focusing from an attached pi-ezoelectric transducer to confine cell motion to the center ofthe capillary
a citation describing acoustic focusing may be useful. is it known how well the particles are confined using this technique?
-
Conclusion
very impressive technology!
-
-865, nac Image Tech-nology
i may have missed it but what is the CMOS camera used for in the study?
-
depending laser out-put
typo: depending on laser output
-
0.26 – 3.2 mW/μm
this seems like a large amount of power, is it possible to theoretically determine the temperature increase that this light could induce in a transiting object?
-
