In flow cytometry, scattered light is commonly measured in two scattering directions: (1) forward (i.e., 0-angle) scattering (FSC); and (2) side scattering (SSC), also known as 90-angle scattering. The angle refers to the angle between the direction of laser beam irradiation and the axial direction of the photomultiplier tube, which collects the scattered light signal. Generally speaking, the intensity of forward angle scattered light is related to the size of the cell, for the same kind of cell population with the increase of the cell cross-sectional area and increase; for the spherical living cells by experiments show that in the range of small stereo angle basically and cross-sectional area size into a linear relationship; for the shape of the complex with the orientation of the cell may be very different, especially need to pay attention to. Measurements of side-scattered light are mainly used to obtain information about the nature of particles in the internal fine structure of cells. Although side-scattered light is also related to the shape and size of the cell, it is more sensitive to the refractive index of the cell membrane, cytoplasm, and nuclear membrane, and can also give a sensitive reflection of the larger particles in the cytoplasm.
In practical use, the instrument first measures the light scattering signal. When light scattering analysis is used in conjunction with a fluorescent probe, stained and unstained cells in a sample can be identified. The most effective use of light scattering measurements is to identify certain subpopulations from non-homogeneous populations.
The fluorescence signal consists of two main components: (1) spontaneous fluorescence, i.e., fluorescence molecules inside the cell that are not fluorescently stained emit fluorescence after irradiation; (2) characteristic fluorescence, i.e., fluorescence emitted by the fluorescent dyes on the cell stained by irradiation of the fluorescent dyes, whose fluorescence is weaker in intensity and at a wavelength different from the irradiated laser light. Autofluorescence signals are noisy signals, which in most cases interfere with the resolution and measurement of specific fluorescence signals. In measurements such as immunocytochemistry, it is critical to improve the signal-to-noise ratio for fluorescent antibodies with low binding levels. In general, the higher the amount of autofluorescent molecules (e.g., riboflavin, cytochromes, etc.) in the cellular component, the stronger the autofluorescence; the higher the ratio of dead/living cells in the cultured cell, the stronger the autofluorescence; and the higher the proportion of bright cells in the cell sample, the stronger the autofluorescence.
The main measures to reduce the interference of autofluorescence and improve the signal-to-noise ratio are: ① try to use brighter fluorescent dyes; ② choose the appropriate laser and filter optical system; ③ use electronic compensation circuit to compensate for the background contribution of autofluorescence.
Sample sorting principle flow cytometer sorting function is completed by the cell sorter. The general process is: the liquid column from the nozzle is divided into a series of small droplets, according to a selected parameter by the logic circuit to determine whether it will be sorted, and then by the charging circuit to select the cell droplet charging, charged droplets carrying cells through the electrostatic field and deflection, falling into the collector; other liquids are treated as a waste liquid pumped off, some types of instruments also have to use the capture tube to carry out the sorting.
Small stable droplets are formed by piezoelectric crystals on the flow chamber that vibrate under the action of an electrical signal of several tens of KHz, forcing the liquid stream to break uniformly. The general droplet spacing is about hundreds of μm. The experimental empirical formula f=v/4.5d gives the frequency of the oscillating signal that forms the stable droplets. Where v is the velocity of the liquid stream and d is the diameter of the orifice. It can be seen that using different orifice diameters and changing the liquid flow velocity may change the sorting effect. The cell-containing droplets sorted in the electrostatic field is deflected by the charging circuit and deflection plate **** with the completion. The charging voltage is generally selected as +150V, or -150V; the potential difference between the deflector plates is several thousand volts. Charging circuit in the charging pulse generator is controlled by the logic circuit, so from the parameter determination by the logic selection and then to the pulse charging requires a delay time, generally tens of ms. Accurate determination of the delay time is the key to determine the quality of sorting, the instrument is mostly used in the digital circuit of the shift register to generate the delay. According to the specific requirements can be adjusted appropriately.
(50) data processing principle: FCM data processing mainly includes the display and analysis of data, as to how to interpret the results given by the instrument with the specific problem to be solved.
①Data display: the data display mode of FCM includes single-parameter histogram, two-dimensional point map, two-dimensional contour map, pseudo three-dimensional map and list mode.
Histogram is the most used form of graphic display for one-dimensional data, which can be used for both qualitative and quantitative analysis, and is similar to the curve given by general X-Y plane tracing instrument. Depending on the type of amplifier chosen, the coordinates can be linear or logarithmic scales, expressed in "channels", which are essentially the intensity of the fluorescent or scattered light measured. The coordinates generally represent the relative number of cells. Figure 10-2 gives the form of a histogram. The fact that only one parameter can be shown in relation to the cells is its limitation.
The two-dimensional dot plot is able to show the relationship between two independent parameters and the relative number of cells. The coordinates and the coordinates are the two independent parameters related to the cells, and each point on the plane indicates the presence of cells that also have the corresponding coordinate values. Two one-dimensional histograms can be obtained from a two-dimensional point map, but the information content of the two-dimensional point map is greater than that of the two one-dimensional histograms due to the phenomenon of merging. The so-called merging means that multiple cells with the same two-dimensional coordinates are represented as a single point on the map, which makes it difficult to show the fine structure of the cell where the points are densely packed.
Two-dimensional point map two-dimensional contour map is similar to the map contour representation. It is a display method set up to overcome the shortcomings of the two-dimensional point map. Each successive curve on the contour map has the same relative or absolute number of cells, i.e. "contour". The higher the level of the curve, the greater the number of cells represented. Generally the levels represent equal intervals between cell numbers, so that denser contours indicate a greater rate of change, and sparser contours indicate a balanced change. Figure 10-4 gives the style of a two-dimensional contour map.
The pseudo three-dimensional map is a visual intuitive representation of the two-dimensional contour map using computer technology. It will be the original two-dimensional map of the hidden coordinates - the number of cells at the same time, but the parameters of the dimensional map can be rotated, tilted and other operations, in order to multi-directional observation of the "peaks" and "valleys" of the structure and details, which undoubtedly helps to analyze the data. This is certainly helpful in analyzing the data.
The Pseudo-3D ListMode is actually just a computerized way of storing multi-parameter data files, where more than three parameters are displayed using multiple histograms, 2D charts, and pseudo-3D charts. ListMode can be used in the special technology, open the window or cursor to call out the relevant parts and then change the number of dimensions for display. For example, "one to two" is a two-dimensional map on a one-dimensional map; "two to one" is a one-dimensional map from a two-dimensional map. Figure 10-6 gives a schematic of the histogram of the corresponding window from a two-dimensional map contour plot.
Figure 10-6 from the two-dimensional map of the window to call out the histogram schematic Above briefly introduced several forms of data display, in the actual application, according to the need to choose to match, in order to understand and obtain as much useful information.
②Data analysis: data analysis methods can be divided into two categories: parametric and non-parametric methods. Parametric methods are mostly used when the biological system being detected can be modeled with some kind of mathematical modeling technique. Mathematical model can be an equation or system of equations, the parameters of the equation to generate the information needed from the measured data. For example, in determining the DNA content of rat sperm, a sharp waveform distribution of cell frequencies can be obtained. If a normal distribution function is used to describe these data, the parameters are the area, mean and standard deviation. Data fitting of the equations, on the other hand, is usually done using the least squares method. Non-parametric analysis, on the other hand, makes no assumptions about the shape of the distribution obtained from the measurements, i.e., set-free parametric analysis is used. The analysis procedure can be as simple as visualizing the frequency distribution, or as complex as comparing two or more histograms channel by channel.
Point-by-point tracing (either by hand, or with a tracer or computer system) is an important means of data analysis commonly used by everyone. We can often use it to understand the characteristics of the data, to look for those unanticipated idiosyncratic signs, to choose a model for statistical analysis, to show the final results, etc.. In fact, data should never be analyzed numerically without first analyzing it visually. From this point of view, nonparametric analysis is the basis of parametric analysis.
Lane-by-lane comparisons are more work, but it is easy to find significant differences with the intuitive method, especially in the control and test groups. Considering the reliability of FCM, it is important to note that for each group of measurements, there should be a control group, which can be a blank control group, a negative control group, or a zero-moment control group, etc., and the specific settings should be based on the overall experimental requirements. A lane-by-lane comparison of control and test groups can often reduce many unnecessary errors and misinterpretations. Incidentally, it is often appropriate to normalize the total number of cells in the curves for comparison, or even to subtract the two curves lane by lane to obtain a "poor result curve".
Because data analysis is often so closely related to the interpretation of results, i.e., to the biological context, the specific analytical methods and principles will be described later with examples.