KR20160131137A - Detecting sensor for breathing results of cell, system of estimating cell population size, and system of distinguishing cell - Google Patents

Detecting sensor for breathing results of cell, system of estimating cell population size, and system of distinguishing cell Download PDF

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KR20160131137A
KR20160131137A KR1020150062873A KR20150062873A KR20160131137A KR 20160131137 A KR20160131137 A KR 20160131137A KR 1020150062873 A KR1020150062873 A KR 1020150062873A KR 20150062873 A KR20150062873 A KR 20150062873A KR 20160131137 A KR20160131137 A KR 20160131137A
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cell
color
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respiration
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오진우
김춘태
이소영
김규정
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부산대학교 산학협력단
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Abstract

In a sensor for detecting respiration by-products of a cell, a cell population estimation system, and a cell identification system, a sensor for detecting respiration by-products of a cell is characterized in that when the M13 bacteriophages are arranged on a base substrate in a spatially spiral manner, Change.

Description

TECHNICAL FIELD [0001] The present invention relates to a sensor for detecting respiration by-products of a cell, a cell population estimation system, and a cell identification system. BACKGROUND OF THE INVENTION 1. Field of the Invention [0002]

The present invention relates to a sensor for detecting respiration by-products of cells, a cell population estimation system, and a cell identification system, and more particularly, to a sensor for detecting respiration by-products of virus- .

Sensors that use color change are widely used in the real world such as pH measurement paper, pregnancy tester, and litmus paper. Such a sensor reacts with a target material to change its color, and it has an advantage that it can be intuitively identified, confirmed, and analyzed through the naked eye.

As a sensor using a change in color, a technique using metal nanoparticles and organic compounds is continuously being developed. In the case of metal nanoparticles, decomposition by organic matter is less and color change is apparent. However, it is difficult to carry and analysis of color change But there is a disadvantage that separate analysis equipment is required. It is difficult to design or synthesize an organic compound as a structure to be used as a sensor.

Recently, the use of titania and silica photonic crystal structures has been proposed to analyze the color change depending on the unique substance emitted over the storage period of the food, thereby suggesting applicability as a sensor (Geoffrey A. Ozin, Photonic Nose Sensor Platform for Water and Food Quality Control (2011)). However, the inorganic - based photonic crystal structure must be accompanied by high - temperature and high - pressure processes, and the problem of angle dependent color, which is a disadvantage of the photonic crystal structure, is difficult to quantify in the color change measurement.

One object of the present invention is a sensor for the detection of respiration byproducts of cells which quantitatively exhibits a color change.

Another object of the present invention is to provide a cell population estimation system using the sensor.

It is still another object of the present invention to provide a cell identification system capable of discriminating the type of a cell.

A sensor for detecting respiration byproducts of cells for an object of the present invention is characterized in that the M13 bacteriophages are arranged on a base substrate in a spatially spiral manner and the color changes when exposed to respiration by-products of the cells.

In one embodiment, the thickness of the bundles formed by the M13 bacteriophages in each of at least two regions of the base substrate may be different.

In one embodiment, a sensor for detecting respiration byproducts of a cell may change color by reacting with carbon dioxide in the respiration byproduct of the cell.

Another object of the present invention is to provide a cell population estimating system comprising a sensing unit including a M13 bacteriophage forming a spatially spiral nanofiber structure and having a sensor that changes color by respiration by-products of the cell, An optical data acquiring unit that acquires optical data when the sensor indicates a color change; and a determination unit that is connected to the optical data acquiring unit and compares the optical data with storage data for a color change per cell population, .

In one embodiment, the stored data of the determination unit is a color change amount per cell population based on the intrinsic color of the sensor, and the determination unit performs a step of calculating a color change amount based on the optical data, The change amount can be compared with the stored data to estimate the number of cells.

In one embodiment, the amount of color change may be a change in the intensity of the red, green, and blue light of the changed color based on the intrinsic color of the sensor.

In one embodiment, the amount of color change can be calculated by linear discriminant analysis.

Another object of the present invention is to provide a cell identification system comprising a sensing unit including a M13 bacteriophage forming a spimed helix nanofiber structure and having a color change by a respiration by-product of the cell, An optical data acquiring unit that acquires optical data when the sensor indicates a color change, and a storage unit that is connected to the optical data acquiring unit and compares the optical data with storage data of a color change of each cell type to identify the type of unknown cell And a judgment unit.

In one embodiment, the sensor is a human cancer cell line (HEK293), lung cancer cell (NCI-H1299), liver cancer cell (SK-Hep-1), cervical cancer cell (HeLa) And can exhibit color change by reacting.

In one embodiment, the storage data of the determination unit is a color variation amount per cell type based on the intrinsic color of the sensor, and the determination unit performs a step of calculating a color variation amount based on the optical data, May be compared with the stored data to identify the type of unknown cell.

In one embodiment, the amount of color change may be a change in the intensity of the red, green, and blue light of the changed color based on the intrinsic color of the sensor.

In one embodiment, the amount of color change can be calculated by linear discriminant analysis.

According to the sensor, the cell population estimation system, and the cell identification system for detecting respiration byproducts of a cell of the present invention, the sensor for detecting respiration by-products of a cell reacts with respiration by-products of cells to change color and change color.

In addition, the number of cells can be estimated on the basis of changes in the color of the virus-based sensor and the amount of color change due to respiration byproducts generated during cell proliferation. In this case, since the color change amount of the sensor does not appear to be a substantial parameter, the confidence in the estimation of the cell population can be secured.

Furthermore, the kind of unknown cell can be identified based on the color change and the color change amount that are different depending on the kind of cell, and it can be confirmed which cell exists.

1 is a view for explaining a sensor for detecting respiration byproducts of cells according to the present invention.
2 is a graph showing the amount of color change of the sensor according to the concentration of carbon dioxide.
3 is a graph showing the amount of change in color of the sensor during the growth of E. coli.
FIGS. 4 and 5 are graphs showing the amount of color change of the sensor according to the number of lung cancer cells.
FIGS. 6 and 7 are graphs showing the amount of color change of the sensor according to the cell type.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. The present invention is capable of various modifications and various forms, and specific embodiments are illustrated in the drawings and described in detail in the text. It is to be understood, however, that the invention is not intended to be limited to the particular forms disclosed, but on the contrary, is intended to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention. Like reference numerals are used for like elements in describing each drawing.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The singular expressions include plural expressions unless the context clearly dictates otherwise. In the present application, the term "comprises" or "having ", etc. is intended to specify that there is a feature, step, operation, element, part or combination thereof described in the specification, , &Quot; an ", " an ", " an "

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the contextual meaning of the related art and are to be interpreted as either ideal or overly formal in the sense of the present application Do not.

Sensor for detecting respiration by-products of cells

The M13 bacteriophage contained in the sensor for detecting respiration by-products of cells according to the present invention is tubular nanoparticles having a diameter of about 6.6 nm and a length of about 880 nm. Since the M13 bacteriophage is a protein particle that is expressed through a certain gene, the size and distribution of the bacteriophage are constant, that is, almost all of the M13 bacteriophages have the same size and shape. The M13 bacteriophage contains about 2700 pairs of proteins (protein VIII, hereinafter referred to as pVIII) and four to five pairs of proteins (pIII, pVI, pVII, pIX) at both ends.

1 is a view for explaining a sensor for detecting respiration byproducts of cells according to the present invention.

Referring to FIG. 1, in the sensor for detecting respiration by-products of cells, a plurality of M13 bacteriophages described above form a spimed helical nanofiber structure. That is, a plurality of M13 bacteriophages are arranged in a smectic structure, and the bundles formed by these M13 bacteriophages form a spiral spiral nanofiber structure by being pulled in one direction in a helical manner. In Fig. 1, one M13 bacteriophage is denoted by a reference numeral "VNP ", and a sensor for detecting respiration by-products of a cell may be implemented in a form showing different colors for each region such as a reference numeral" 100 ". Alternatively, the sensor for detecting respiration byproducts of a cell can be implemented in a single form.

As shown in FIG. 1, the thicknesses of the smectic spiral nanofiber bundles in at least two regions of the sensor for detecting respiration by-products of cells are different from each other, so that the color-change sensor includes regions exhibiting different colors. The thickness of the spiral nanofiber bundle can be determined by controlling the pulling rate, the concentration of the solution, and the like in the process of manufacturing the sensor for detecting respiration by-products of cells.

When the sensor for detecting the respiration by-products of the cell is exposed to the respiration by-products of the cell, the length of the wavelength reflecting the incident light is changed by changing the arrangement of the bundles of the M13 bacteriophage constituting the sensor for detecting respiration by- . As a result, the color visible to the naked eye is changed to function as a color change sensor. That is, the presence of the respiration by-products can be intuitively confirmed by only the color change of the sensor for detecting the respiration by-products of the cell, and it is possible to confirm the presence of carbon dioxide particularly in the respiration by-products.

In addition, the sensor for detecting respiration by-products of cells can detect the concentration of carbon dioxide according to the amount of color change. That is, depending on the concentration of carbon dioxide, the color change amount of the sensor for detecting carbon dioxide is different, and the concentration of carbon dioxide can be estimated on the basis of the color change amount.

2 is a graph showing the amount of color change of the sensor according to the concentration of carbon dioxide.

More specifically, FIG. 2 is a color change diagram in which the color change amount of each of the three regions is represented by the color of each of the three regions in a state in which the sensor is divided into three regions and is not exposed to carbon dioxide. 2, 2%, 3%, 4% and 5%, respectively, indicate the concentration of carbon dioxide. Based on the left figure (Contro) And the amount of color change at the concentration of each carbon dioxide is converted into color.

2, as the concentration of carbon dioxide applied to the sensor for detecting respiration by-products according to the present invention increases from 1% to 2%, 3%, 4% and 5% (from left to right) The chroma of the color represented by each of the colors increases. That is, the color change amount when exposed to carbon dioxide of 5% is larger than the color change amount when it is exposed to 1% of carbon dioxide. Since such a color change amount is substantially unaffected by other factors and appears almost without a variable, it has high reliability with respect to a color change amount.

When data of a sensor for detecting carbon dioxide, which has undergone color change by exposure to carbon dioxide having an unknown concentration, is provided to a detection system storing such data, the concentration of carbon dioxide can be estimated by comparing the stored data with corresponding data. The reliability of estimating the concentration of carbon dioxide is also high.

In FIG. 2, the concentration difference of carbon dioxide is set to 1% unit. However, it is possible to acquire color change data for each carbon dioxide concentration by setting the concentration difference to 0.5% unit or less, The estimated reliability of the unknown concentration can be further improved as compared with the amount of color change caused by carbon dioxide having the concentration of < RTI ID = 0.0 >

Cell population estimation system

The cell population estimation system according to the present invention includes a sensor that changes color, and estimates the cell population by cell proliferation based on the color change amount of the sensor. Since the sensor for changing the color of the cell population estimation system of the present invention is substantially the same as the sensor 100 for detecting the respiration by-products of the cell described with reference to FIG. 1, redundant detailed description will be omitted.

The sensors included in the cell population estimation system vary in the amount of color change depending on the amount of respiration by-products emitted during the cell proliferation process. That is, as the cell population increases, the amount of respiratory byproduct increases, and as the amount of respiration byproduct increases, the amount of color change also increases.

In one embodiment, the cell population estimation system includes a sensing unit including the sensor 100 described in FIG. 1, an optical image acquisition unit connected to the sensing unit, and a determination unit connected to the optical image acquisition unit.

The sensing unit may be exposed to respiration by-products of the cell. That is, the sample part where cell proliferation may occur and the sensing part are connected, and the color of the sensor 100 of the sensing part may be changed by receiving respiration by-products of the cells from the sample part.

The optical image acquiring unit may include a camera as a part that generates an optical image of the sensor 100 in which a color change has occurred. It is possible to generate a plurality of optical images according to the passage of time, that is, the cell proliferation time.

The determining unit receives the optical image from the optical image acquiring unit, analyzes the optical image, and compares the optical image with stored data already stored for the cell number to estimate the cell number.

In one embodiment, the stored data may be an optical image that represents a changed color of the sensor 100. At this time, the determination unit has already stored a plurality of optical images according to the number of cells, and the determination unit can estimate the number of cells by comparing the optical image received from the optical image obtaining unit with the stored image.

In one embodiment, the stored data may be a change in intensity (ΔRGB) of red light, green light, and blue light of the optical image per cell population based on the intrinsic color of the sensor 100. At this time, the intrinsic color of the sensor 100 means a state in which the sensor 100 is not exposed to respiration by-products of the cell, that is, the original color of the sensor 100. The judging unit already has the ΔRGB data of the optical image for each cell population as the storage data, converts it into the ΔRGB data of the optical image received from the optical image acquiring unit, and compares the ΔRGB data with the ΔRGB data of the optical image received from the optical image acquiring unit.

3 is a graph showing the amount of change in color of the sensor during the growth of E. coli.

Referring to FIG. 3, as shown in (a), the OD 600 (optical density 600) increases with the proliferation time of the actual E. coli, which means that the E. coli population increases. At this time, the sensor 100 reacts with respiration by-products discharged in the proliferation process to exhibit a color change, and the color change amount can be expressed as? RGB as shown in (b). (b), the? RGB also changes with the lapse of the proliferation time.

In the case of the sensor 100 partitioned into three regions,? RGB in each region appears in a different manner. Based on this, the population of E. coli can be estimated.

FIGS. 4 and 5 are graphs showing the amount of color change of the sensor according to the number of lung cancer cells.

FIG. 4 shows the color change amount by ΔRGB according to the number of individuals. When the number of lung cancer cells is 10 4 , 10 5 , 10 6, and 10 7 , the amount of color change is different for each sensor, Showing the amount of change.

In FIG. 5, (a) shows a color change amount as a color image, (b) shows a ΔRGB bar graph, and (c) shows a color change amount according to the cell population as a linear graph. (A), (b), and (c). The quantification result can be used to estimate the number of lung cancer cells in the proliferation process.

Cell Identification System

The cell identification system according to the present invention includes a sensor whose color changes, and can identify the type of unknown cell based on the color change amount of the sensor. The color-changing sensor of the cell identification system of the present invention is substantially the same as the sensor 100 for detecting the respiration by-products of the cells described in FIG. 1, and therefore detailed description thereof will be omitted.

Depending on the type of the cell, the respiration byproduct is different, and thus the color change of the sensor 100 included in the cell identification system is different. That is, the amount of color change of the sensor 100 varies depending on the respiration by-products discharged from the cells. Based on this, it is possible to identify what kinds of cells are unknown cells.

The cell identification system includes a sensing unit, an optical image acquiring unit, and a determination unit. Each of the sensing unit and the optical image acquiring unit is substantially the same as the sensing unit and the optical image acquiring unit of the cell population estimation system described above. Therefore, redundant detailed description will be omitted.

The determination unit of the cell identification system receives the optical image from the optical image acquiring unit, analyzes the optical image, and compares the color change with respect to the color change of respiration by-product per cell to compare the stored data with the stored data to identify the type of unknown cell .

In one embodiment, the stored data may be an optical image that represents a changed color of the sensor 100. At this time, the judging unit has already stored optical images representing color changes due to per-cell respiration by-products, and the judging unit compares the optical image received from the optical image obtaining unit with the stored image to identify the type of unknown cell have.

In one embodiment, the stored data may be a change in intensity (ΔRGB) of the red light, green light, and blue light of the optical image indicative of color change due to per-cell respiration by-products based on the intrinsic color of the sensor 100. That is, since the determination unit already has the storage data as described above, it can convert the .DELTA.RGB data of the optical image received from the optical image acquiring unit, and compare them to identify the type of unknown cell.

In one embodiment, the stored data may be color data based on color changes due to per-cell respiration by-products. For example, the color data may be data quantified in color based on? RGB data derived through optical data. At this time, the judging unit further converts the ΔRGB data of unknown cells into color data, and discriminates the kind of unknown cells by comparing the color data of respiration byproducts with the color data of unknown cells.

In one embodiment, the stored data may be linear discriminant analysis (LDA) data based on color changes by cell-specific respiration byproducts. For example, the LDA data may be data quantified based on the ΔRGB data. At this time, the judging unit further performs the step of converting the optical data by the respiration byproduct of the unknown cell into the LDA data, and by comparing the LDA data by the respiration by-product of the cell and the LDA data of the unknown cell, have.

FIGS. 6 and 7 are graphs showing the amount of color change of the sensor according to the cell type.

6, respiration by-products of human normal kidney cells (HEK293) and lung cancer cells (NCI-H1299), liver cancer cells (SK-Hep-1), cervical cancer cells (HeLa) The amount of color change of the sensor 100 is different. That is, the amount of color change of the sensor 100 due to respiration by-products of unknown cells can be calculated by? RGB and compared with the stored data to identify the type of unknown cell.

Referring to FIG. 7, the color change of the sensor 100 according to the type of the cell, that is, the stored data stored in the determination unit may be the .DELTA.RGB bar graph or color data as shown in FIG. Also, the stored data may be LDA data such as (c).

According to the above description, the number of cell populations can be estimated through the characteristic that the color changes and the color change amount is different by reacting with the respiration byproduct of the cell of the sensor for detecting respiration by-products of cells, Cells can be identified.

It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit or scope of the present invention as defined by the following claims. It can be understood that it is possible.

Claims (12)

On the base substrate, M13 bacteriophages are arranged in a spimed helix,
When the cells are exposed to breathing byproducts,
Sensors for the detection of respiration byproducts of cells.
The method according to claim 1,
Wherein the thickness of the bundles formed by the M13 bacteriophages in each of at least two regions of the base substrate are different from each other.
Sensors for the detection of respiration byproducts of cells.
The method according to claim 1,
Characterized by reacting with carbon dioxide in the respiration by-products of the cell to change color.
Sensors for the detection of respiration byproducts of cells.
A sensing unit including M13 bacteriophages forming a spatially spiral nanofiber structure and having a sensor whose color changes by the respiration byproduct of the cell;
An optical data acquiring unit connected to the sensing unit and acquiring optical data when the sensor indicates a color change; And
And a determination unit connected to the optical data acquiring unit and comparing the optical data with stored data for color variation according to the number of cells,
Cell population estimation system.
5. The method of claim 4,
Wherein the storage data of the determination unit is a color variation amount by cell number based on the intrinsic color of the sensor,
Wherein the determination unit performs a step of calculating a color change amount based on the optical data,
And comparing the color change amount derived from the optical data with the stored data to estimate the number of cell populations.
Cell population estimation system.
6. The method of claim 5,
The color change amount
Green light, and blue light based on the intrinsic color of the sensor.
Cell population estimation system.
6. The method of claim 5,
The color change amount
Characterized in that it is calculated by linear discriminant analysis.
Cell population estimation system.
A sensing unit including M13 bacteriophages forming a spatially spiral nanofiber structure and having a sensor whose color changes by the respiration byproduct of the cell;
An optical data acquiring unit connected to the sensing unit and acquiring optical data when the sensor indicates a color change; And
And a determination unit, connected to the optical data acquisition unit, for comparing the optical data with stored data for color change by cell type to identify the type of unknown cell,
Cell identification system.
9. The method of claim 8,
The sensor reacts with human normal kidney cells (HEK293), lung cancer cells (NCI-H1299), liver cancer cells (SK-Hep-1), cervical cancer cells (HeLa) and colon cancer cells (HCT 116) ≪ / RTI >
Cell identification system.
9. The method of claim 8,
Wherein the stored data of the determination unit is a color variation amount for each cell type based on the intrinsic color of the sensor,
Wherein the determination unit performs a step of calculating a color change amount based on the optical data,
And comparing the color change amount derived from the optical data with the stored data to identify the type of unknown cell.
Cell identification system.
11. The method of claim 10,
The color change amount
Green light, and blue light based on the intrinsic color of the sensor.
Cell identification system.
11. The method of claim 10,
The color change amount
Characterized in that it is calculated by linear discriminant analysis.
Cell identification system.
KR1020150062873A 2015-05-06 2015-05-06 Detecting sensor for breathing results of cell, system of estimating cell population size, and system of distinguishing cell KR101764001B1 (en)

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2024053903A1 (en) * 2022-09-07 2024-03-14 주식회사 젠라이프 Electronic nose sensor for diagnosing lung cancer, and electronic nose system for diagnosing lung cancer using same

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