Bioengineering
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In Situ Microscopy for Real-time Determination of Single-cell Morphology in Bioprocesses
Chapters
Summary December 5th, 2019
A photo-optical in situ microscopy device was developed to monitor the size of single cells directly in the cell suspension. The real-time measurement is conducted by coupling the photo-optical sterilizable probe to an automated image analysis. Morphological changes appear with dependence on the growth state and cultivation conditions.
Transcript
This method can help answer key questions of population heterogeneity through the morphological assessment of the cells. In situ microscopy allows study cultivation conditions, process yields, and product quality. The main advantage of this technique is an in situ measurement, which provides real-time data without sampling or bringing risk of contamination.
In situ microscopy coupled to automated image recognition can provide additional information about cellular structures, shape, and cell agglomeration beyond size. It's also possible to measure cell concentrations. The method has proven to be a reliable tool.
No alternative method provides the same information in such a short time and low effort for sample preparation. The method has been adapted to various bioprocesses and microorganisms, SEG filamentous fungi, micro-allergy, and yeast. The probe is used in conjunction with a computer.
The hardware consists of a single rod probe with a high-resolution CCD camera. Cells that pass through an adjustable measurement gap are imaged by the camera. Light enters the gap opposite the camera, meaning illumination is by transmission.
Set the hardware parameters using cell concentrations that span the expected range. Begin making preparations for offline measurements. Use a thickness gauge to adjust the measurement gap.
Then turn the probe screw nut to set the measurement gap to five or 10 times the maximum expected cell diameter. At the computer, open the probe controller software. In the software, select the desired probe and go to section actions.
Then press Connect. Next, go to the Probe Control tab and open it. Start video streaming by pressing the play button.
Fix the probe to a tripod and perform the following steps for each measurement. Work with the probe and spray ethanol in the measurement gap. Carefully wipe any dust or dirt away with optical paper.
At the computer, use live view to check that the glass of the sensor is free of particles. Next, place a dry optical paper in the measurement gap for focusing. Turn the binding screw to move the focus manually.
Stop focusing when single fibers of the paper in the measurement gap are clearly seen. Now, get a tube filled with culture broth. Dip the microscope in the broth, so the gap is fully covered with cell suspension.
Use the binding screws to fine-tune the focus on the cells. Once this focusing is done, do not change it again during the experiment. Return to the software for the experiment.
Go to the Triggering menu. Under the Triggering menu, set the frame rate. One hertz is recommended for offline measurements.
From there, go to the Frames Per Trigger field and set it as necessary for good statistics. Here, about 200. Also, go to the General menu.
There, select the directory in which the images will be saved. Begin image acquisition with the Start Image Trigger Acquisition button. Gently move the tube to induce flow in the measurement gap.
Use the images from the first run of the experiment as a training set. Have the open source software Fiji ready and drop the images from the experiment into its window. When done, select Analyze, followed by Tools, then ROI Manager.
Next, choose a selection tool. In the image, decide on a particle to annotate that is in focus. Draw a circle around it with the selection tool.
Press Add to add the annotation to the ROI Manager. Next, select a brush tool and choose an appropriate pixel size. Use the brush tool to refine the selection.
Continue marking all objects of interest in the same way on about 15 images. Save the annotated files and use them as a training set. When the recognition algorithm is trained and ready, use it to visualize results.
In the Results Analyzer, go to File, followed by Import File. There, select the desired results file. Continue by pressing the Create Chart button.
Select Distribution Chart. This will display the morphological distribution of the culture. Return to Create Chart to select Sensitivity Plot.
The information displayed can help determine how many cells must be analyzed to obtain the desired accuracy. Perform online measurements after completing offline measurements. For online measurements, connect the probe directly to a bioreactor.
Once connected, properly sterilize the assembly. Select Monitoring in the dashboard. There is a play button to start image acquisition and a stop button to end it.
Press the play button. At the bioreactor, begin inoculation of the culture. The camera will capture video of the cells and automatically identify them for analysis.
The monitoring provides online data of cell sizes and shapes of different cell morphologies during the entire fermentation. The real-time results can be formatted in various ways and also be exported for further analysis. This plot of cumulative distributions of S.Cerevisiae cell diameter is created from data analyzed using this technique.
It demonstrates the automatic cell recognition is able to distinguish budding and non-budding cells. The solid curve is the distribution during a cultivation at three hours. The dotted curve is the distribution of the same cultivation at seven hours.
The dashed curve represents data collected at 13 hours. The annotation procedure is time-consuming, but it is the key for achieving the desired accuracy for the cell identification. With this procedure, if the measurement times are shorter than the process dynamics, the real-time measurement is able to be used for process control.
This technique paves the way for using the measurement of population heterogeneity as a process parameter for microbial cultivations from the early process development steps to production scale.
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