Introduction

The multi-channel fluorescence and luminescence detection system has practical significance in drug screening, medical diagnosis, high-throughput sequencing, biological action research, ecology research, practical quality inspection and other fields, because it can increase the speed of batch analysis by several times to tens of times. However, existing fluorescence and luminescence measure devices mostly use imagemultiplier tube as detector, which can only measure the light intensity in a small localized area and can’t measure samples with multiple channels at the same time. To address these problems and make fluorescence detection equipment available to every lab, we designed, built, tested, and open-sourced LviSense, a bioluminescence detector based on a high-sensitivity camera. (See Fig 1) LviSense can sensitively and reliably detect concentration of fluorescent protein as well as the oxidation process of D-Luciferin.

Fig 1. LviSense final product

Structure overview

The main components of LviSense are linear laser module, filter, CMOS digital camera, image processing software, matte black shell, temperature control module. The shell of the device is built with acrylic sheet, and the shell is sprayed with matte black paint to reduce the influence of environmental stray light. The lower part is designed with pull-out structure to facilitate the replacement of samples. LviSense adopts reflex light path structure. The solution emits emission light on the excitation light path. A CMOS digital camera collects images filtered by a filter to remove background light. The images are converted into fluorescence intensity data by ImageView (An image processing software) in the computer. As long as we replace the excitation light source and filter, and adjust the parameters of the camera, the fluorescent substances with different excitation wavelengths can be detected. Of course, LviSense can detect luminescent substances. With a PID temperature control module, LviSense maintains the enzymatic reaction at a specific temperature.

Fig 2. Components of LviSense; A) ImageView; B) CMOS Digital Camera; C) Reflex Light Path Structure

Device budget

Image digitization

Images must be converted to digital form before they can be analyzed by computers. Each pixel has two properties: position and gray level. The position of a pixel is determined by its two coordinates, which are also called rows and columns. The integer value representing the brightness value of a pixel is called gray scale. After all the pixels have been sampled and quantified, the image can be represented as an integer matrix, which can be used as the object of computer image processing.

Fig 3. Image Digitizing

After digitizing an image with a width of M pixels and a height of N pixels, the matrix is as follows: 

Where g(i,j) represents the gray level of position (i,j). For gray images, g(i,j) varies between 0 and 2^N-1 according to the bit depth value N of the camera. Since we use a color camera, the formula for converting color image to gray image is 

In fluorescence analysis with gray images, we meet the need for quantitative detection by obtaining the brightness value of each sample on the image. According to the principle of image digitization, each fluorescent spot on a image is composed of thousands of pixels, and the gray average value of the pixels is used to characterize the brightness value of the spot. 

Temperature control module

Main controller

Our main controller uses Arduino UNO (providing consistent 5V output) and the corresponding circuit expansion board. 

Fig 4. Arduino UNO

Temperature sensor and temperature acquisition circuit

Based on the characteristics of fast response time and wide range of temperature measurement, we choose NTC3950 as temperature sensitive element. The task of the temperature acquisition circuit is to convert the resistance change of NTC into a recognizable signal input into the main controller. We have designed the corresponding circuit: TL431CSF is used to provide stable voltage, and the voltage signal is amplified by single power operational amplifier LM321LV, and 16-bit AD converter ADS1115 with IIC interface is used to communicate with the main controller to complete the signal transmission. 

Fig 5. Design of Temperature Acquisition Circuit

By preprocessing the temperature-resistance comparison table of NTC3950, the relationship between temperature and collected voltage can be established by binary search algorithm and linear Interpolation. The temperature-voltage conversion curve is shown in Fig 6. In addition, we use mercury thermometer to calibrate the temperature sensor, so that the error between temperature sensor of LviSense and mercury thermometer is within 0.5^oC. 

Fig 6. Temperature-Voltage Conversion Curve

Peltier and related driver circuit

The thermoelectric effect is the basic principle of Peltier's work. Since the output current of I/O port of MCU is 0-40mA, it cannot directly drive Peltiers. Two BTS7960 chips form H-bridge drive circuit to drive them. By adjusting the direction of current and the duty cycle of PWM wave input to INH, the degree of heating or cooling can be controlled. 

Fig 7. Peltier and Driver Circuit; A) Peltier; B) Internal Structure of BTS7960; C) Design of Driver Circuit

Fan and thermal conductive materials

In the refrigeration of Peltiel, it is necessary to cool the non-working surface of Peltiel to improve the effect of refrigeration, so we use thermal silicone to connect the non-working surface with the heat sink and use fans to help the heat sink cool down quickly.

PID control

The accuracy and stability of temperature control have great influence on the experimental results. Proportional, integral and differential control, referred to as PID control, has the advantages of simple structure, good robustness and easy implementation. When the PID controller works, the proportion, integral and differential of the error signal constitute the control quantity by linear combination, which is applied to the controlled object, and its control law is

Fig 8. PID Block Diagram

In the main controller, the above equation needs to be discretized and the coefficients unified to get the discrete PID control algorithm. The discrete PID expression at k sampling time is:

According to the actual control performance requirements, we determine the relevant parameters of the PID controller after adjustment.

Arduino code

As the code for main controller, it needs to complete the following functions:
1)Communicate with the temperature acquisition circuit to obtain the real-time temperature value
2)Communicate with the upper computer, receive the upper computer set parameters
3)Control the working condition of Peltier by PID control, and adjust temperature
4)Control the operation of the fan and laser module

Fig 9. Partial Code of Arduino

Verify the performance of temperature control module

To evaluate the performance of temperature control module, we input a constant temperature value, and then input the parameters in the temperature cycle (95 ° C for 10s, 55 ° C for 15s, and 72 ° C for 60s), then record the temperature changes and draw a curve. The curve shows that the temperature control module has good heat preservation effect and small overshot.

Fig 10. Temperature-Time Curve; A) Constant Temperature Input; B) Temperature Cycle Input

System block diagram and physical image

By assembling all parts above, we have completed temperature control module and LviSense. (The open source material is available on this page )

Fig 11. LviSense; A) System Block Diagram; B) Temperature Control Module

Detection of fluorescent proteins

The fluorescent protein selected in the wet lab is mRFP1, which is a monomic red fluorescent protein. The excitation spectrum and emission spectrum of mRFP1 are shown in Fig 12. The excitation wavelength (λex) of mRFP1 is 584nm, and the emission wavelength (λem) is 607nm.

Fig 12. Spectrogram of mRFP1

Excitation light source

By installing a Powell Lens in front of the laser point source, the laser beam can be transformed into a straight line with uniform optical density. It is equipped with universal support for fixing and adjusting the orientation of the laser module. According to the spectrogram of mRFP1, we selected 20mW 532nm laser module. Too much power is likely to cause imagebleaching of fluorescent molecules and high background noise, and too little power generates less fluorescent imagens, which cannot reach the sensitivity of detection. The luminescence wavelength of the laser module was detected by fluorescence spectroimagemeter. The spectrum shows that the laser module has good monochromatism. 

Fig 13. Excitation Light Source; A) Linear Laser Module; B) spectrum of Laser Module

Filter

Because the light signal collected by the camera lens includes not only fluorescence emitted by samples, but also the reflection and scattering from the light source. Filter can alleviate the effect of background light and improve SNR of the system. For mRFP1, We used a 580nm longwave pass filter. (580 nm, T = 50%; 585-1100 nm, T ≈ 91%)

Fig 14. longwave pass filter and its spectrum

Light source intensity distribution and light source correction

Six 200μL centrifuge tubes were added with 200μL mRFP1 solution of the same concentration, and were excited by the linear laser light source to investigate whether the linear laser intensity received by each centrifuge tube was different. The shooting parameters of CMOS digital camera were set (exposure time =10ms; Av = 1.4).

According to the image and fluorescence intensity curve of mRFP1 solution in the following figure, the light intensity on the hole of each sample is different, so the light source intensity needs to be normalized during actual measurement.

Fig 15. Fluorescence Intensity Curve of mRFP1

The correction coefficient is defined as

Where, F_max and F_i are the maximum fluorescence intensity detected and the fluorescence intensity detected by the ith centrifuge tube, respectively.

The corrected fluorescence intensity F_Ri of the ith centrifuge tube is

The mean values and relative standard deviations of light source correction coefficients measured with different concentrations of mRFP1(0ng/ ml-500ng /mL) are shown in the following form.

Stability

The fluorescence intensity of a group of 200μL mRFP1 solution with a concentration of 330ng/mL was detected in 10 repetitions, and we got relatively stable results after correction.

Fig 16. Fluorescence Intensity(corrected)

Linearity and detection limit

Linearity is the basis of mRFP1 detection, and standard curves were derived by configuring and detecting a series of standard concentrations of mRFP1 protein. By comparing the gray scale with the standard curve, the corresponding concentration of mRFP1 solution can be obtained. When the concentration of mRFP1 solution was in the range of 10ng/ml-500ng/mL, the fluorescence intensity showed a strong linear relationship with the concentration of mRFP1.

Fig 17. mRFP1 Concentration Standard Curve

Thermal stability of luciferase

D-luciferin is a common substrate of Luciferase, which is widely used in the whole biotechnology field. The mechanism of action is that D-luciferin is oxidized and luminescent in the presence of ATP and luciferase.

We can explore the thermal stability of luciferase in the presence of a temperature control module with excellent heat preservation effect, which will help us determine the optimum temperature for luciferase reaction. We established luminescence system (5μL luciferase, 195μL buffer containing 25mM Tris-HCl (pH=8.0), 10mM MgSO4, 0.15mM D-Luciferin and 25mM ATP). The reaction process was imageed at 15^oC, 20^oC, 25^oC, 30^oC, 35^oC, and 40^oC.

The luciferase has the highest activity at 20^oC and is almost completely inactivated at 40^oC. (See Fig 18)

Fig 18. Reaction Process Curve at Different Temperature

Characterization of LRE

Principle

Oxyluciferin, which is the product of the luciferase reaction, has a strong inhibitory effect on the luciferase in a manner competitive with luciferin.

Luciferin-regenerating enzyme (LRE) plays an important role in the recycling of oxyluciferin into luciferin, improving the luminescent signal of firefly luciferase. In the presence of LRE and D-cysteine, the luminescence time of the system can be prolonged.

The reaction can be explained by the following two-step reaction:

(1) Transformation of oxyluciferin to 2-cyano-6-hydroxybenzothiazole

(2) Condensation of 2-cyano-6-hydroxybenzothiazole with D-cysteine to yield luciferin.

Fig 19. Luciferin recycling

Experimental procedure

Induced expression of His tagged luciferase and luciferase regenerating enzyme
(1)Add BL21 single colonies with plasmids pet28a-luciferase (expressing luciferase) and plasmids pet28a-LRE (expressing luciferase regenerating enzyme) to 10mL LB medium containing appropriate amount of antibiotics and culture overnight.
(2)1:100 transfer to 100mL LB medium containing appropriate antibiotics, continue culturing until OD₆₀₀≈0.6
(3)Add IPTG to final concentration of 1mM, and continue culturing at 25^oC for 10 hours
(4)Collect the precipitate by centrifugation at 8000g for 5min at 4^oC

Purification of His tag protein under non-denaturing conditions
(1)Add non-denaturing lysate at a ratio of 5ml per gram of precipitate, and add the appropriate amount of protease inhibitor to the lysate.
(2)Lyse bacteria by ultrasound on ice, and each ultrasound treatment was performed for 10s，with a 10s interval, for a total of 30 mins.
(3)Collect supernatant by centrifugation at 10000g for 30min at 4^oC.
(4)4:1 mix the supernatant and 50% gel, and shake it slowly at 4^oC for 60min on a side swing shaker.
(5)Load the mixture into an empty column tube, and open the bottom lid of the purification column to allow fluid to flow through the column.
(6)Wash the column 5 times, add 1 column volume of non-denaturing detergent each time, and collect the detergent.
(7)Elute target protein 5 times by adding 1 column volume of non-denaturing eluate each time, and add each eluant to a different centrifuge tube to obtain His tag protein samples.

Functional validation of luciferase regenerating enzyme

Establish luminescence system

To test the function of LRE catalyzing the regeneration of luciferin, 5μL purified LRE and 5μL purified luciferase were added in triplicate to the reaction mixture containing 0.15mM D-luciferin, 2mM ATP, 10 mM MgSO4 and 5mM D-cysteine in 25mM Tris-HCl (pH=8.0). The total volume of the reaction system was 200μL. For the control group, 5μL LRE was replaced with 5μL 25mM Tris-HCl (pH=8.0) 

The optimum temperature of luciferase oxidation reaction was input to the temperature control module at 20^oC, and the parameters of the camera were set (exposure time =6s, Av=1.4, brightness gain =200%). As shown in the gray scale-time curve, luciferase regenerating enzyme had a good inhibitory effect on the attenuation of luminescence intensity. The luminescence intensity can be maintained stable in the subsequent stages of the reaction.

Fig 20. Characterization of LRE

Future application

LviSense has great function scalability by changing the module conveniently on the drawer (pull-out structure) and switching among different programs. For instance, by replacing the temperature control module with a UV transmission excitation module or a simple black plate, LviSense can be used as gel imager and chemiluminescence imager, respectively. In preliminary temperature performance validation, it responded well to temperature periodic inputs. After further optimizing the performance of the temperature control module, we can use the device for quantitative real-time PCR (QPCR) assay.