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Overview


Antibody-based Circulating Tumor Cells (CTCs) detection is the most convenient way to monitor cancer metastasis. However, the equipment for CTC detection is unaffordable for most regional hospitals. Therefore, we aim to develop an automatic CTC quantification device, namely CTC-FAST device, for CTC detection.

The CTC-FAST device is composed of three main systems: The first one is the fluid propulsion system for propelling CTCs for capture, labeling, and detection. The secondary one is the microfluidic technology for cell alignment. The final one is the fluorescence detection system for detecting the emitting light from fluorescence-labeled CTC after laser excitation. The operation of these systems is controlled by software we developed (software link).

Fluid Propulsion System


The goal of the fluid propulsion system is to build up the prototype for automatically processing CTC capture and labeling. Accordingly, this system should allow washing buffer and labeling reagent to flow in and out of the main chamber step by step. In addition, this prototype also allows us to manually measure the operating time of the whole automatic process, which is important in clinical application.

The whole process of the fluid Propulsion System in CTC-FAST device is as follows:

  1. PBS buffer stored in a container is pumped out to bring the sample into the main chamber, which contains the CTC-capture DNA tetrahedrons, by the peristaltic pump.
  2. The servo motor causes the main chamber to oscillate left and right, ensuring an even distribution of the sample.
  3. PBS buffer is introduced into the main chamber to wash out cells that are not bound.
  4. The CTC labeling reagent, fluorescent protein (mGL-4A-C7), is introduced into the main chamber by the peristaltic pump.
  5. PBS buffer is introduced into the main chamber to wash out unbound mGL.
  6. Zinc ions and ssDNAs are introduced into the main chamber to release the labeled CTC from the DNA tetrahedron by inducing trans-auto splicing.
  7. PBS buffer is introduced into the main chamber to flush out the labeled CTCs for detection.

Liquid container and flow controller:

The liquids applied in CTC detection include PBS buffer, mGL-4A-C7 protein, and ssDNA solutions. Taking the water line connection into consideration, we selected a syringe as the container in the prototype. To propel the liquid out of the container, we connected a peristaltic pump to each syringe.

Peristaltic pump (12V/5W)

▲ Peristaltic pump (12V/5W): to provide a constant force for fluid propulsion.

We used Arduino's I/O ports to control the liquid flow sequence of each container. Because the voltage output of Arduino is too weak for peristaltic pump activation, relays are connected to Arduino for amplification.

Arduino UNO R3

▲ Microprocessor System: Arduino UNO R3
The conventional Arduino microprocessor

12V Relay

▲ Power control switch: 12V Relay
A voltage-controlled initiator is employed to activate high-voltage circuits with the aid of Arduino's low-voltage source inputs.



Buffering tank:

After the liquid flows out from the container, a new issue arises. The buffer/reagent may flow back to contaminate other containers if they share the same pipeline. To avoid this possibility, we connected these three containers with the buffering tank and non-return valves, allowing gravity to prevent the countercurrent. Buffer chamber:

▲ Buffer chamber:
to prevent the countercurrent and cross contamination among buffers and reagents.

Non-return valve

▲ Non-return valve:
to prevent cross-contamination among buffers, reagents, and waste.



Selection of main chamber:

The main chamber is the place where CTC capture and labeling occurs. Between the capture and labeling steps is the washing step. To reduce the residue during each step, we designed the main chamber in a flat diamond shape to facilitate the smooth drainage of liquids.

The main chamber

▲ The main chamber:
The main chamber is a diamond shape to avoid the accumulation of sample cells at the corners of the chamber.



After the sample enters the main chamber, shaking or swinging is necessary to allow complete interaction between the sample and CTC-capture DNA tetrahedrons. To achieve this, we connected a servo motor to the main chamber to swing it.

MG-996 Servo motor

▲ MG-996 Servo motor
The servo motor is applied to precisely swing the main chamber with an angle of ± 6° by setting the time.

The driving power of the peristaltic pump is not accurate enough for the microfluidic system. Therefore, we selected a stepper motor and DM-542 driving controller for the microfluidic system to ensure the liquid flows steadily through the main channel and sheath channels of the microfluidic channel to produce the sheath fluid. We developed a tri-syringe push device.

stepper motor & DM-542 controller

▲ The production of sheath fluid: tri-syringe push device
Driving force: stepper motor & DM-542 controller



Finally, the production of sheath fluid in the microfluidic channel remained a significant challenge. The injected flow may seep from the faying surface if the adhesion is poor. To overcome this problem, we sealed the microfluidic channel by clamping two pieces of acrylic together with screws.

stabilizer

▲ The stabilizer of faying surface between tri-syringe push device and microfluidic system

We need three different voltages (5V/12V/18V) to drive the components in the CTC-FAST prototype. For voltages under 30V and 2A current, DC-DC transform modules are the best choice. We used the XL2006 boost module and LM2596 buck module to meet the voltage requirements of different components. At the same time, we used a transformer as the power source for all components with a 12V output.

Buck/Boost converter:

▲ Buck/Boost converter:
Boost: XL2006 DC-DC Boost Module; Buck: LM2596 DC-DC Buck Module

To build the CTC-FAST device,of course an experimental CTC FAST device, an extensive record of the amount or time of drained liquid is required because we still need to adjust some Calibrate parameters to get the best condition. Inspired by the 3D printer operating interface in the laboratory, we used a rotary encoder paired with an LCD screen as the operating system. The rotary encoder itself has both "rotate" and "press" hardware operation modes, which can be interpreted as "selection" and "confirmation." by the software.

Rotary encoder

▲ Control device: Rotary encoder
The display screen's forward, reverse, and push button functions enable the selection, confirmation, and modification of manipulation variables.

LCD1602

▲ Screen Display: LCD1602
The interface displays the presently controlled mode and every manipulation variable. The design draws inspiration from a laboratory 3D printer, which employs a rotary encoder and screen as its control system.



After setup of the rotary encoder and screen display, user feedback showed that it was not clear if they “did” confirm the action. Inspired by the beep sound in air conditioner remote controls, we add a buzzer to make a brief sound when the program reads the "confirmation" button of the rotary encoder. Together, users can rotate the encoder and use the LCD screen to conduct experiments and record the time required for each component to perform its tasks, determining the working time required for future automated product devices.

Buzzer

▲ Confirmation Key Alert: Buzzer
Buzzer provides users with tactile feedback of successful operation.



Finally, we built a user-friendly interface to control each system, which is also our first prototype of CTC-FAST.

Buzzer

▲ First experimental control interface Buzzer

Program


Since CTC-FAST is still in the developmental stage, our initial program design logic is specifically focused on "finding the various manipulation variables needed in each step", of the program operation flow as follows.

frame

As shown in the figure, the machinery we need to manipulate in the CTC-FAST device is basically divided into propulsion fluid and rocking.

In the propulsion stepping motor system, because the stepping motor can control the time required for each step forward, and can determine the amount of liquid to be discharged by controlling the number of steps, the variables we manipulate are
  1. the amount of liquid to be dispensed
  2. the amount of liquid to be discharged and the forward speed in mm/s.
We need to find out the fastest flow rate of liquid that the microfluidic channel can withstand.

When choosing the control method, we used a rotary encoder and LCD screen as a simple control system.
  1. Rotary encoder
    The program design uses the encoder to read the value of several steps of forward and backward rotation based on the different waveforms generated by the forward and backward rotation, and at the same time uses a push button as a confirmation button.

    code

  2. LCD screen
    Arduino will read the number of forward and reverse turns of the encoder, and then display different messages on the LCD screen according to the sequence. For example, when selecting the control mode, you can choose to drive the creeping motor or stepping motor, when manipulating the variables, you can use the encoder to rotate forward to increase the desired value, and when rotating backward, you can choose whether to return to the main page (mode selection page).
    Details of overall programming

Having identified the time, flow rate or volume of liquid in each section, the team will use this data as the basis for operating the instrument in a pre-set standardized mode. In addition, as this is an automated device, we hope that in the future the product can have automatic detection and adjustment functions, such as adding a three-axis gyroscope to the same plane as the main reaction chamber, or detecting the tilt angle of the main reaction chamber in real time and adjusting the level.

Microfluidic technology


To successfully count the number of CTCs in the sample, we apply microfluidic technology to align the cells for detection after CTC labeling. The microfluidic confinement effect is applied to precisely align CTCs in micron-scale tubes. Accordingly, we designed a trident-shaped microchannel, with the main flow channel at 150 microns and the other two channels at 300 microns.

trident-shaped-microchannel

Design:

The first step in starting to fabricate a microchannel is the design. We used drafting software to draw the design of the microchannel, taking into account the flow path of the fluid and the required functions.

Trident microchannel seal formula

▲ Trident microchannel seal formula


where d, D1, D2, D3 are the cell flow concentration widths, v1, v2 and v3 are the fluid inlet flow velocities, and 𑄺a, 𑄺1, 𑄺2 and 𑄺3 are the fluid densities of the injected fluid at the outlet and at the inlet microfluidic channel.

Calculation of tube diameter after microchannel sealing

▲ Calculation of tube diameter after microchannel sealing


Based on this formula, we designed a trident-shaped microchannel, with the main flow channel at 150 microns and the other two channels at 300 microns, constricted to 20 µm.

Making Shells:

The design of the trident microchannel is converted into a digital model by slicing software for printing shells through a light-curing 3D printer. The printed shells are solidified by UV-irradiation.

 UV irradiator

▲ UV irradiator

Trident Microchannel Design

▲ Trident Microchannel Design


Shell casting:

The mixture of ethylbenzene and PMS (10:1) is degassed by a vacuum machine and injected into a microchannel shell.

 Shell casting

Solidifying the microchannel:

The casting shell of the microchannel is baked at 85 C for 4 hours for solidification. The solidified microchannel is carefully removed from the shell.

 Solidifying the microchannel

Fixing the microchannel:

The removed microchannel was attached to a carrier slide and exposed to ozone for 60 min to ensure complete crosslinking between the microchannel and carrier slide.

Ozone Processing:

Combine the microchannel with the carrier slide and expose it to ozone for 60 minutes to ensure that the microfluidic channel is fully bonded to the carrier slide.

Ozone Machine

▲ Ozone Machine

 Microchannel

▲ Microchannel

The faying between the injection needle and the microchannel is affected by the thickness of the microchannel and the incision of the needle. To promote faying, we thickened the microchannel to 5 mm by increase the height around the microchannel shell

Height of microchannel shell

▲ Height of microchannel shell

Thickness of microchannel

▲ Thickness of microchannel


On the other hand, we adjusted the opening of the injection needle from a chamfer shape to a flat cut. We also adjusted the length of the needle to 5 mm to fit the thickness of the microchannel.

Length of needle

▲ Length of needle

Fluorescence Detection System


After the microchannel aligns the individual cells, we designed a fluorescence detection system to detect the mGL-labeled CTCs. The mGL protein labeling the CTCs could be stimulated by laser light at 488 nm wavelength and emits light at 513 nm for detection.

To achieve accurate targeting of a single CTC using laser light without any scattering or interference from non-fluorescent materials, a light processing technique incorporating scaling and filtering is utilized. Lenses with diverse focal lengths are adjusted to achieve the desired diameter, and filters are used to enable only specific wavelengths of light to pass through. This approach effectively minimizes errors by preventing detection of light from non-fluorescent materials by the photodiode.

Laser focus system, Fluorescence detection system

▲ Laser focus system, Fluorescence detection system

(All experiments are conducted in a dimly-lit room to minimize errors and facilitate highly accurate data collection.)

Parameter curves of opto-electronic diodes

The first step of building is to test the limitation of photodiodes, and to establish a reference of the photodiode's voltage output. To test the limitations of photodiode, we decreased the light intensity as below:
  • Polarizers are employed to regulate the luminosity of the emitted laser light
  • A piezoelectric tank is employed to enhance the energy dispersion of the transmitting light.
  • Multiple acrylic sheets are applied to decrease light intensity by refracting and reflecting.


Overview of equipment for detecting photodiode limitation

▲ Overview of equipment for detecting photodiode limitation

Polarizers & piezoelectric tank

▲ Polarizers & piezoelectric tank

Multiple acrylic sheets

▲ Multiple acrylic sheets


After setup, the decrease of light intensity was detected by optical power meter, showing that our setup could decrease the laser's intensity from a minimum of 5mW to the lowest detectable 10nW.

Next, we replaced the optical power meter with a photodiode, and recorded the measurement displayed on the triple meter. In theory, the voltage generated by the photodiode should increase with the intensity of light. To analyze the data, we selected three experiments closely aligned with the theoretical data out of the ten conducted and calculated their average.

The experimental data and graph of the relationship between light intensity and voltage.

▲ The experimental data and graph of the relationship between light intensity and voltage.


Amplified Signal

The voltage detection module was integrated with the photodiode, and Arduino was used to measure the voltage value. It was observed that surpassing a specific threshold was necessary in order to register a value that could be detected by Arduino. However, due to the limited brightness of the fluorescent material, it was unable to reach the required threshold. Consequently, amplification of the voltage generated by the photodiode was needed.

Initially, we used the commonly available LM358 amplifier. However, our attempt to amplify the photodiode using the inverting amplifier circuit did not yield the expected outcome as it failed to amplify the photodiode in the way we had anticipated.

Inverted Amplifier Circuit

▲ Inverted Amplifier Circuit

No discernible difference

▲ No discernible difference without (left) and with amplifier circuit (right)

After searching for related papers, we found that this result is due to LM3588 being a general-purpose amplifier, so its amplification precision is not enough to amplify small signals. Therefore, we changed to an instrumentation amplifier, AD620, and referred to the circuit diagram below for trial use. This time it successfully amplified the small signal generated by the photodiode.

Amplification Circuit of AD620

▲ Amplification Circuit of AD620

Voltage before ans after amplification

▲ Voltage before amplification was 0.0008V, after amplification, 0.392V, a 490-fold amplification



Before amplification, the voltage was 0.0008V and after amplification, it increased to 0.392V, resulting in a 490-fold amplification. Accordingly, we selected the AD620 amplifier module for subsequent detection.
Voltage Sensor

▲ Voltage Sensor

AD620 amplifier module

▲ AD620 amplifier module


Measurement of Fluorescent protein

After confirming the photodiode's parametric curve and the amplification circuit, we replaced the laser with stimulated mGL solution as a light source for measurement.

We placed the mGL solution in a quartz tube, and stimulated it by a 488 nm laser. The laser will pass through the visible window and stimulate the mGL in the quartz tube.

The laser beam pass through the quartz tube

▲ The laser beam pass through the quartz tube


To detect the light emitted by th stimulated mGL, we used a bandpass filter (500-525 nm) and adhered the photodiode next to the filter. We also printed a holder for filters and photodiodes by 3D printer. To prevent light leakage, we covered the outer surface with black electrical tape.

The holder of filter and photodiode

▲ The holder of filter and photodiode


Next, we obtained crude mGL protein solution from the wet lab, and serially diluted the protein solution into five concentrations: 1.83*10^-7 mg/ml, 9.14*10^-8 mg/ml, 1.83*10^-9 mg/ml, 9.14*10^-10 mg/ml, and 1.83*10^-11 mg/ml. The measurement result after laser stimulation shows that the voltage difference decreases as the protein concentration decreases.

Measurement data

▲ Measurement data and trend charts for various fluorescence concentrations with and without the laser turned on.


Mimicking CTC measurement

We then tried to test if we could measure the light emitted from the mGL-labeled CTCs. Since we were not allowed to collect clinical samples, we decided to mimic the mGL-labled CTCs. On average, each CTC carries 5.00E+5 FRα molecules (Hongyun Zheng, 2021). We assumed that all the FRα are recognized by mGL. That is to say, we could mimic one CTC if we put 5.00E+5 mGL molecules in the optical path. Accordingly, we estimated the concentration of mGL should be 4.15E-18~4.15E-17.

Calculation of concentration of CTC-mimic mGL solution

▲ Calculation of concentration of CTC-mimic mGL solution



After calculating mGL concentration corresponding to different numbers of labeled CTCs, we carried out relevant examinations.

Trend chart

▲ Trend chart for two consecutive measurements of fluorescent substances with 1 to 10 equivalent CTCs (with amplifier).



Unfortunately, the result indicated that the voltage difference is not proportional to the number of cells, and no distinguishable pattern can be discerned between the sets of data. It is possible that the concentration is undetectable, or there may be interference caused by noise.

To examine whether amplifier noise affects the result, we measured the voltage difference without the amplifier. The result still shows that the measurement value is not proportional to the number of cells. Therefore, we concluded that the photodiode we used may not be sensitive enough.

Results of fluorescent substance measurement without the amplifier.

▲ Results of fluorescent substance measurement without the amplifier.

The finished device


References


Hongyun zheng (Ed.). (n.d.). Detection of Folate Receptor‐positive Circulating Tumor Cells as a Biomarker for Diagnosis, Prognostication, and Therapeutic Monitoring in Breast Cancer. J Clin Lab Anal. 2022 Jan; 36(1): E24180.