Medical Immunology: Fifth Edition, Revised And Expanded
Book file PDF easily for everyone and every device.
You can download and read online Medical Immunology: Fifth Edition, Revised And Expanded file PDF Book only if you are registered here.
And also you can download or read online all Book PDF file that related with Medical Immunology: Fifth Edition, Revised And Expanded book.
Happy reading Medical Immunology: Fifth Edition, Revised And Expanded Bookeveryone.
Download file Free Book PDF Medical Immunology: Fifth Edition, Revised And Expanded at Complete PDF Library.
This Book have some digital formats such us :paperbook, ebook, kindle, epub, fb2 and another formats.
Here is The CompletePDF Book Library.
It's free to register here to get Book file PDF Medical Immunology: Fifth Edition, Revised And Expanded Pocket Guide.
Photomultiplier tubes PMTs meet these requirements and are therefore employed in almost all flow cytometers. PMTs are vacuum tubes containing a photocathode, electron focusing electrodes, and a series of dynodes for electron multiplication. The photocathode converts photons to photoelectrons which are then multiplied by a series of dynodes driven by a high voltage Fig. In many applications, PMTs are increasingly being replaced, e. Amplifiers in a flow cytometer can be grouped as pre and main amplifiers. All amplifiers in a cytometer are analogue hardware devices which must be very well designed for optimal signal to noise ratios SNRs.
In modern cytometers, the conversion of the continuous analog voltage signal into discrete digital values is done by ADCs which are defined by their sampling frequency and sample resolution. The required dynamic detection range DNR of a flow cytometer can be defined as the intensity range of stained and unstained cells, for example. In practice, the effective number of bits of an ADC is, due to noise and distortion of the circuit, some decibels below the theoretical value e.
This limits the dynamic range to less than 4 decades and, more importantly, shrinks the resolution of dim signals. In the digital domain the signals are processed by filters, baseline restorer, pulse height, pulse width algorithms, and trigger see Section I. The resulting signal consists of an unwanted DC part due to laser scatter light and electronic noise among others and a specific AC part. The baseline restorer attempts to keep the baseline at zero. In practise however, baseline restoring is not perfect and can lead to negative values on the histogram axis or introduce a slight distortion of low signals and therefore to a increased CV of dim signals.
Taken together, the analogue and digital components of a flow cytometer in combination with the baseline and pulse shaping algorithms need to be well adjusted in order to maximize SNR and DNR. Since the invention of the first prototype of a Fluorescence Activated Cell Sorter in at Stanford University, the technology has become a powerful tool to analyze and sort individual cells based on their functional status. Moreover, flow cytometry provides a robust statistic of thousands of individual cells and can detect rare events at a frequency below 10 —4 cells. In a typical cytometer, the sensitivity decreases with increasing flow rate due to the increasing diameter of the cell stream within the flow cell.
Typically these markers are fluorescently tagged antibodies, molecular sensors, as well as genetically encoded reporters. In practice, this high number of parameters is not achievable because at the moment the range of appropriate fluorescent dyes is limited. Technical limitations regarding the maximum number of detectable markers are also given by the overlap of the emission spectra of the different fluorescent tags, since each fluorescence detection channel is correlated to a biological marker.
To overcome this, fluorescent tags became available which have different excitation wavelengths. Currently, up to seven lasers with emission wavelengths from to nm are used in order to achieve a high flexibility in the choice of the fluorescent tags. Furthermore, tunable lasers are used for special applications like fluorescent life time measurements FLIMs. Flow cytometers use either photomultipliers PMTs or avalanche diodes to convert the emitted or scattered light into amplified electrical pulses which are processed by appropriate electronics to extract information like pulse height, area, length, and time.
The electronics of the cytometer consist basically of a preamp circuit, baseline restoration circuit, and an analog to digital converter ADC. All components together must have a low noise level i. Within this instrument, the emitted fluorescence light is divided by a wavelength division multiplexer WDM through a series of band pass filters and integrated optics, onto an array of avalanche diodes which enables a high sensitivity in the detection of e.
Avalanche diodes or PMTs itself are light detectors which are unsuitable for wavelength detection, hence the fluorescent light needs to be filtered by optical filters and mirrors. These filters must be carefully chosen because a multiparameter experiment, i. Conventional flow cytometers circumvent this problem by compensation see Section III. Following this, the data are analyzed in a multivariate fashion in combination with a hierarchical gating strategy see Section VI.
It is essential to adapt the combination of fluorescent tags to the given optical, laser, and electronic setup of the instrument to minimize spillover, increase Q, and lower B signals. For instance, by choosing the right concentration of a certain reagent see Section IV. This can help to increase the separation the distance between the means between a blank and a fluorescent population which is a function of Q and B. Thus, it requires the characterization of Q and B of the used instrument.
Mostly polystyrene particles beads are used for this purpose in combination with software based protocols implemented in the instruments e. Scale calibration is an especially useful approach to measure absolute values e. Beside beads, scale calibration can also be achieved by using LED light pulses. Furthermore, by using this tool, instruments can be compared within or between labs regarding their Q and B values.
Up to this point, analytical cytometers have been described but cells can, in addition, be sorted based on specific marker expression for downstream analysis molecular biology, sequencing, etc. After excitation A in Fig. Gratings are susceptible for polarized light. As polarization occurs frequently in flow cytometry 22 , the total efficiency of a grating may be reduced. In fact, prisms are better suited for spectral light dispersion because they have a better light transmission and are also stable for polarized light.
Unfortunately, the dispersion of a prism is not linear with regard to the wavelength, which makes it difficult to use linear detector arrays such as multianode PMTs On the other hand, this in combination with high spectral resolution allows the spectral detection of Raman scattering which is a characteristic spectrum of molecular vibrations, much narrower than fluorescence spectra. This allows the application of new biological markers, such as surface enhanced Raman scattering tags or near infrared fluorescent dyes 24 , More recently, Robinson et al.
- Original Research ARTICLE!
- John von Neumann: Selected Letters.
This spectrograph was implemented in the optical pathway of a conventional flow cytometer and was able to take spectra of single cells and microspheres as well as to discriminate free versus bound propidium iodide. The first commercially available spectral flow cytometer, the SP, was developed by Sony Moreover, the instrument is equipped with 3 lasers , , and nm , which allows for full spectral detection of the resulting emission spectra.
The measured spectra from single cells are subsequently unmixed by using reference spectra of all used dyes and the autofluorescence spectrum. Least Square Fitting algorithms are used to calculate the most accurate fit for all reference spectra, leading to an accurate determination of which dyes are present on each cell and at which intensity. Using this method, a complete fluorescence emission is used instead of only a small portion of emitted light entering a dedicated detector through a specific set of mirrors and optical filters. This is a major advantage over conventional flow cytometry, in which light that is lost outside of the optical filters also contaminates other channels with unwanted light which has to be corrected by a subtractive method see Section III.
Since dyes frequently used in flow cytometry have rather broad emission spectra and large spectral overlaps, spectral unmixing can help mitigate this problem. Moreover, control of reagents especially tandem dyes is paramount with the increased need for standardization. Given that spectral flow cytometry shows full spectrum unbiased data, quality control is more or less integrated.
In this fashion, spectral flow cytometers are designed to measure the biological information across multiple detection channels, where the optical configuration can be fixed for all experiments, giving the added benefit of instrument stability, sensitivity 33 , and easier standardization across instruments, aided by the lack of individual PMTs and individual optical filters and mirrors. Imaging flow cytometers combine conventional flow cytometry with the additional benefit of imaging each individual cell.
By utilizing the speed and phenotyping ability of flow cytometry with the imagery of microscopy, it allows a broad range of applications to be studied that would be impossible using either technique alone. Each generation has become faster with higher resolution, and the addition of a benchtop model has made imaging flow cytometry more accessible to researchers. Both capture 12 images of each cell, of which 10 can be fluorescent. The high throughput cell imaging of these instruments allows cellular functions, which are often only otherwise measurable by microscopy, to be investigated.
It is very time consuming and user biased to analyze large number of cells by microscopy, and near impossible for rare cell types. An antibody panel appropriate for the biological question should be chosen and selection of the fluorochrome conjugates should take into account the expression level of the molecules while avoiding excessive compensation. Web based software can aid in the panel design, such as BD fluorescence spectrum viewer and Biolegend fluorescence spectra analyzer.
Since the laser powers frequently differ from conventional flow cytometers, even antibodies, which provide optimal cell detection in conventional flow cytometry require titration. The imaging component helps to determine the appropriate concentration and ensures that the protein is detected in the expected cell compartment.
As for conventional flow cytometry, correct controls positive and negative need to be included, i. Positive experimental controls are also vital to assist in the generation of the best analysis strategy. After acquisition, the machines return unused sample, and this could be useful when setting up a new assay allowing direct comparison of imaging flow cytometer data to an established technique i. Therefore, when performing titration experiments, it is important to test antibodies from the same panel at the same laser power. This prevents saturation of bright stains when they are used in combination with dim stains.
Data quality is enhanced when the brightness levels of all probes excited off a single laser are balanced within one log scale of fluorescence intensity. Due to long acquisition times and the lack of temperature control of the machines, fixation of cells is recommended for further information see Section IV.
File sizes which are generated after acquisition can be very large, for example MB for a 10 event file. To investigate rare cell populations several s of cells may need to be acquired. Here it would be beneficial to collect data only from the cells of interest. Thus, the file size becomes manageable and the analysis is sped up, as it needs to be remembered that the software is slow when handling large data files. FCS files and the associated images, in.
The FCS files alone can also be exported into other data analysis software for flow cytometry, but would only provide information about fluorescence intensity and not imaging. Analysis of a new experiment can be very time consuming, but once optimized, for example the optimal mask and feature have been determined, it can be quickly applied to future experiments. IDEAS has many features to aid new users with analysis, as well as user defined features for advanced users. The first step is compensation.
IDEAS guides the user through the process automatically, selecting what it considers as positive events for each channel. This can be inaccurate, and therefore it is important to check that the correct population has been selected by clicking on the values in the compensation matrix and if necessary adjusting the gating in the compensation graphs. These guide the user step by step through the analysis. If no analysis wizard exists, the feature finder wizard is a useful tool to determine the best feature to use.
Once an analysis method has been developed, samples can be batch analysed. One should be aware that each sample might require a different gating. A treatment or activation may change the properties of the cell e. Therefore, the analysis should be checked ensuring the gating is still valid for each treatment and adjust if necessary. Following analysis, a statistics report can be then generated of the parameters of interest.
The brightness and contrast can be manipulated for each channel and any background staining removed. Importantly, changing the way the images are viewed does not alter the raw data or analysis. However, slow running and long complicated analysis should be taken into consideration when opting for this technique over conventional flow cytometry. The mass cytometer combines a cell introduction system with a mass spectrometer consisting of three basic components: the ion source, the ion analyzer, and the ion detector.
Essential parts and steps of the measurement are summarized in Fig. Using argon as a carrier gas, the nebulizer creates an aerosol that is guided into the ion source. The ion source of the CyTOF instrument is an inductively coupled argon plasma. At a plasma temperature of approx. Thus, each cell generates an ion cloud that expands by diffusion and enters the vacuum. Ions are accelerated by an electric field of a known strength, resulting in ions receiving the same energy. Since the ions all have the same charge, the ions can be separated by their mass difference.
The velocity of lighter ions is higher and they reach the detector first, followed by heavier and slower ions, in the sequence of increasing ion mass. The ion cloud of a given cell is measured in small portions, termed pushes. Since the CyTOF technology focuses on metal isotopes with high atomic mass, only the segment of the spectrum corresponding to atomic masses higher than 80 Da is taken in consideration.
Typically, a single ion cloud is captured by approximately 10—40 spectra. An electron multiplier is used for ion detection and consists of a series of dynodes maintained at increasing potentials, resulting in serial amplification of the original signal. The spectra are then analyzed by two successive integration steps, to obtain information about the amount of metal associated with each ion cloud corresponding to a single event.
The first integration is an area under curve calculated over an around 19—26 nanosecond interval according to the region of a given mass spectrum and represents the intensity of the peak for a given isotope. The region used for the first integration is determined during the instrument setup procedure termed mass calibration, using a tuning solution. The second integration summarizes consecutive positive peaks corresponding to a single cell event.
Finally, the integrated signal intensities obtained for one cell in the different mass channels are converted into flow cytometry standard FCS 3. Thus, mass cytometric data can be viewed and analyzed manually using standard flow cytometry software packages. An important point to consider is that data analyses of a given study more and more often employ several algorithms organized in an analysis pipeline, very similar to an experimental procedure that needs to be described and annotated in appropriate detail At present, Fluidigm Corp.
Similar data can be generated using an alternative approach i. However, it is advisable to have the instrument maintained and managed by an expert operator. While the advantages of mass cytometry are striking for various applications, it should be noted that due to the destruction of the cells in the argon plasma, CyTOF instruments cannot recover the original cell sample for subsequent experiments. Instrument sensitivity, cell throughput and recovery should be taken in consideration when planning a study involving mass cytometry.
The variability in sensitivity for the detection of different reporters is lower in mass cytometry compared with that in flow cytometry. In theory, sensitivity could be improved by hardware design, allowing for the detection of more of the injected target ions, and by the use of probes that carry more metal per specific probe, such as heavy metal nanoparticles 64 - Mass cytometers need to be set up and tuned daily procedure detailed in The experimental workflow for preparing mass cytometry assays is typically very similar to that for conventional flow cytometry, except for the strict requirement of cell fixation and their resuspension in water prior to acquisition on the CyTOF instrument.
Briefly, cells are subjected to cell surface staining and optional dead cell label incubation, fixed, usually using formaldehyde , permeabilized, stained for intracellular antigens and DNA content, and finally resuspended in water optionally supplemented with normalization beads for injection into the mass cytometer.
Mass cytometers do not measure the light scatter parameters usually employed in flow cytometry for detection of cell events and separation of cell aggregates. In mass cytometry, cells are solely detected by the metal associated with them. A typical gating strategy is provided in Fig. The design of mass cytometry panels is generally easier as compared to flow cytometric panels of similar marker capacity, since signal spillover and sensitivity differences are comparably minor issues However, the mere number of parameters and the implementation of quality control for antibodies 74 both make panel design a significant effort.
Panel design includes optimizing the pairing of specific probes with unique heavy metal isotopes considering instrument sensitivity for that particular isotope mass, target antigen abundance, and additionally potential signal spillover. A careful panel design, an optimally tuned instrument and highly pure reagents, however, can minimize these spillovers to very low levels that are orders of magnitude lower than fluorescent spectral overlaps.
However, the sole fact that, in mass cytometry, typical panels include approximately 40 antibodies renders the routine and consistent realization of these controls quite complicated, and often unfeasible. Isotope controls require the use of an antibody with a matching isotype and the same amount of metal per antibody as the reagent that is to be controlled, and are presently not commercially available. However, both strategies deliver only limited control information. Here, the expression of a given marker is evaluated in the same sample on different cell populations, or by comparing samples from untreated versus treated conditions.
Counterstaining for multiple cell lineage markers in antibody conjugate evaluation experiments enables the identification of reference cell populations serving as positive and negative controls for a given antibody conjugate in the multitude of populations identifiable by a 40 parameter panel. Therefore, sample banking and assay automation are actively pursued research areas in the mass cytometry field.
Mass cytometry is a new hybrid technology employing principles of flow cytometry and mass spectrometry. There is great diversity amongst biological cells. Studying the function of different cell types and subsets often requires the isolation of many cells of a specific population with a high degree of purity or the isolation of single cells for a better understanding of the heterogeneity of cells within a subset.
Parallel cell sorting also called bulk cell sorting is useful when either simple physical parameters, e. In particular, magnetic cell sorting techniques see Section II. As detailed in Sections II. With some methods more than 10 11 cells can be processed in less than 1 h. Serial cell sorting technologies use rapid measurements at the single cell level.
This allows the isolation of even very rare cells from complicated mixtures. Serial cell sorting discerns cell subsets by staining with combinations of fluorescently labeled antibodies. Analytical methods for rapid electrostatic serial cell sorting have been refined to use multiple lasers and more than 18 optical parameters derived from the reaction of cells with fluorescently labelled affinity reagents providing diverse excitation and emission signatures to define very specific subsets with many applications in immunology see Section II.
The combination of many serial cell sorters in a microfluidic chip promises very high sorting rates see Section II. Present serial cell sorters process cells at rates from a few cells per hour to 10 5 cells per second depending on the diverse range of applications being done and the specific cell sorter configuration being used.
Parallel sorting uses parameters like cell size, density, magnetic, or electrical properties. Affinity binding reagents e. General considerations : Bulk cell sorting from a cell mixture can be done by many methods, each one having different advantages and challenges. The main variable parameters to be considered are specificity, yield, purity, viability, functionality.
Moreover, speed, cost, and consumables for equipment must be also taken into account Fig. The importance of the different functional parameters will depend on the specific experimental goals, e. Instrumentation features depend on the specific needs and the experience of the user s. Figure 10 illustrates the various parameters needed in deciding on a sorting strategy or method. Not always can all parameters be set at optimal levels simultaneously.
First, because it reduces time of the cell sort, and second because it helps to improve gating quality by eliminating potential fluorescence overlap between stained and unstained cells Fig. An overview of cell sorting technologies and applications can be found in Keeping track of cell numbers, viability, and analyzing the sorted cells before, during and after any separation is good routine in order to determine cell yield and cell purity, and to detect any unreasonable cell losses or damages.
To quantitatively evaluate sorting performance, several calculations can be performed. The purity, i. This provides a helpful metric when optimizing a sorting technology. Another approach for the evaluation of bulk sorting performance is described in 84 , where it only uses fractions of cells in the original and positive fraction and does not need information about the yield of the positive wanted population.
At lower yields there are small differences between the two metrics. Table 1 provides an example showing that final purity values alone are not a good measure for sorting performance rows 4 and 5 in Table 1 , even though it may be the important measure for biological activity. Physical properties of cells can be changed by the reaction with specially tagged affinity reagents like antibody conjugates with magnetic particles.
In this way specific subsets can be isolated with bulk sorting methods. This technique uses the force of magnetism to sort out cells according to specific cell surface markers. Several commercial systems are available, which use either inorganic superparamagnetic or ferromagnetic materials embedded in polystyrene beads or in a matrix such as dextran, or coated with graphene Beads in sizes from tens of nanometers up to several times the size of a typical mammalian cell are available for bulk cell sorting. Nanometer sized beads require high field strength and field gradients, generally achieved in columns or microfluidic channels with optimized ferromagnetic structures.
Unwanted cells are poured off or eluted. In negative selection strategies, all unwanted cells are labeled, leaving the wanted ones untouched for downstream applications or a second round of selection by another surface marker. Several bead or affinity reagent chemistries allow the detachment from the cells if needed. The bulk sorting method hinges on the quality of the antibodies used, and the density of the surface markers on the cells. Cells with a low density surface marker expression may be more difficult to sort. Bulk sorting with beads, especially with large beads, cannot distinguish between high and low expression of a given antigen on the cells.
Selection of a good antibody is crucial for successful sorting, as is the concentration of beads in the labeling step. Nowadays, many kits for sorting a range of cell types in various species are commercially available. Note : the sort quality must always be analyzed to detect possible cell losses and impurities. Specificity is achieved by the antibodies and, again, the quality of the antibodies is important.
As beads vary in size, several cell subsets can be sorted out of a mixture by using different sized beads for different antibodies. A potential advantage is that the size of the beads may prevent phagocytic uptake. Beads can be detached by a special buffer, and sequential sorting is possible. Temperature and duration for binding must be considered in the context of phagocytosis, decreasing possibility of unspecific binding, capping, or efficient binding kinetics. Cells, organelles, parasites etc. Efficient removal of dead cells from a mixture is possible as well note of caution: this procedure is stressful for the living cells.
When separating blood, the upper fraction contains both lymphocytes and other mononuclear cells. They thus are not based on a polysaccharide net Pitfalls : Density for similar cells between species can differ, e. Centrifugation must be done at room temperature and without brakes. Loss of cells and recontamination when harvesting them from the gradient surface is possible. Cell activation can be an issue, e. Manufacturers: gelifesciences.
A second density separation medium is Percoll, made from colloidal nanosized silica particles coated with polyvinylpyrrolidone Cells of differing densities collect at the different interfaces and can be taken off. Size differences of cells of interest, e. The pore size enables larger cells to be retained on the membrane and smaller cells to pass through. However classical filter membranes do not have homogeneous and precisely controlled pore sizes, so the resolving power of this separation is limited and, due to the material of the filter, the recovery of white blood cells may be inefficient.
Another separation method based on cell size that targets red blood cells and platelets specifically uses microfibrated silicon chips. These feature homogeneously etched slots of a certain size designed to let erythrocytes pass through under a certain pressure whilst retaining leukocytes on the surface of the chip. The leukocytes can then be recovered by elution. Early evaluation of this technology has demonstrated Pitfalls : Throughput of the filters is limited by surface area and overload may result in reduced purity and recovery of leukocytes.
So far the commercial devices can only handle up to 2 mL of whole blood which is sufficient for some cell analysis assays but not enough for blood transplantation and cell therapy applications. The recovery of leukocytes is sensitive to the pressure applied—pushing with higher pressure and higher flow rate may result in decreased recovery. A method of bulk sorting currently under development is based on cell size.
There are several publications reporting a microfluidic device that separates particles and cells with high resolution 97 and is able to not only fractionate whole blood components by their sizes 98 but to also isolate CTCsfrom whole blood Recent work describes improvements for the routine use of the technology Multiple sections of an obstacle matrix with varying gap sizes can be built in one device so that multiple sized particles can be isolated because each sized particle will follow its own determined path flowing through the device.
In theory, there should be no throughput limitation of the technology as it is a continuous flow system; however, some surface treatment of the device may be needed to avoid cell adhesion. Particles exposed to an acoustic field are known to move in response to an applied acoustic radiation force. Numerous researchers have investigated the effect of acoustic waves on cells and particles in aqueous solution. Thus, acoustic focusing can be used to separate and position particles based on size, density, and deformability.
The ultrasonic standing wave is generated by a piezoelectric transducer and resonance vibration of the microfluidic device made in silicon or glass. The acoustic pressure pushes leukocytes to the pressure node located at the center of the channel and leaves platelets at the side stream going to a waste outlet. Size is a dominant parameter for acoustic cell sorting but not the only parameter as shown in the equation above. For example, separation of leukocytes from erythrocytes in whole blood is not easily done on an acoustic device as erythrocytes, though having a smaller diameter, move to the acoustic energy node along with leukocytes as the erythrocytes have a higher density.
Pitfalls : The cell moving trajectory in the flow channel is determined by both the acoustic pressure and the shear pressure so the flow rate and channel configuration need to be well controlled otherwise the separation efficiency will suffer. No commercial product is available yet. Enucleated erythrocytes are more susceptible to hypotonic shock than nucleated cells. Several other cell lysis solutions are available commercially as well , The methods described in Sections II.
These older methods are not discussed here, but they are summarized in Successful flow cytometry cell sorting often requires that more attention be paid to sample preparation than is typically done when preparing samples for analysis only. When sorting, the often challenging objective is to not only separate some sample fraction in a timely manner such that the sorted output is a pure viable fraction, but also that the sorted cells be functionally capable, that they expand well in culture or perhaps be competent to perform in some other subsequent assay e.
How to best achieve good sample behavior and maximize performance? HEPES buffered bicarbonate media has been reported to be light sensitive , and it is generally a good idea to protect any sample for flow cytometry cell sorting from light. If there is any doubt, a few simple pilot experiments designed to determine the best preparation method for the specific cells in question is often a very good investment toward successful sorting.
Similarly, isolating cells from any primary tissue for flow cytometry cell sorting can be very challenging, care should be taken to ensure the chosen protocol is optimized and tested to not only provide the intended cells e. The highest quality reagents should be used, especially when using proteolytic enzymes such as collagenase, pronase, dispase, or trypsin since small amounts of contaminants can have serious undesirable effects resulting in poor sample performance.
Adding unbuffered bicarbonate media to the collection tube and sorting on top of it runs the risk of high pH conditions causing undesirable salts to form while the phosphate and bicarbonate buffers mix with the cells present, thereby reducing cell viability. Once prepared, the sample should have a final cell concentration that allows the desired event rate to be achieved with only a modest differential pressure on the sample.
Increasing the sample rate significantly by simply forcing more through the system is not recommended. The sample should be filtered just prior to being loaded onto the sorter to help ensure no clumps are present and further disperse any weakly adhered cells. This is a very common scenario with many cell preparations, especially adherent and primary cells, and often the sorter performance is blamed for what is a behavior intrinsic to the sample.
Sorters certainly cannot read the operator's mind and will attempt to do exactly what they are set up to do so, if a positive selection from the sorter suffers from disappointing purity, one simple performance check is enough to sort a completely negative cell fraction for comparison. In many flow systems, doublets tend to align with the doublet figure's major axis in line with the partially developed laminar flow and the pulse width becomes a very useful parameter to help distinguish singlets from doublets.
Matching nozzle size to particle size is key, and the general rule of thumb is that the nozzle should be 4 to 5 times that of the particles for bulk sorting and 5 to 6 times that of the particles for plate deposition where accuracy is more critical. Electrostatic cell sorters tend to perform very well with monodisperse samples and struggle with poorly dispersed ones so, as with many other applications, sample preparation can be the limiting or enabling step. Recently, microfluidic devices have entered the arena of flow cytometry and, in particular, cell sorting devices - As these devices also utilize sequential sorting and similar fluorescence detection technologies to identify the cells of interest, best practices for microfluidic devices have a lot in common with those applicable to droplet sorters.
This is especially true for considerations regarding sample preparation, such as choosing the right marker panel or appropriate buffer selection as discussed in the previous section Section II. While sequential sorting technologies have a lot in common, there are also some major differences and knowing and understanding these differences is key to successful application. One of the biggest differences is that droplet sorters are typically operated in resonance , whereas many microfluidic sorters are operated purely on demand , , Even though the enabling principles vary, the sorting effect is mainly generated by displacing a certain volume , The expected purity can be calculated as follows:.
With this, the expected purity P can be calculated to be. In this case, the yield calculation is simply the likelihood of having a single cell within the displaced volume:. In order to give a practical example, these two figures are here calculated for a virtual sorting device assuming that the microfluidic sorter: has a sample flow rate of 4 mL per hour and does not require a sheath to be operated.
This translates to a flow of 1. Since in this example 0. Thus the expected purity in a yield sort would be. Similarly the expected yield in a purity sort would be. This opens up the opportunity to utilize a sequential sorting strategy, where a fast yield sort is followed by a purity sort. As seen in Fig. The target cell frequency was determined to be 0. With a target frequency of 0. The results are shown in Fig. Since microchip sorting devices are particularly powerful in sorting cells gently due to the absence of high shear forces or electrostatic charges, they are ideally suited to follow such a sequential sorting approach.
The rarer the target cell population or the higher the total cell count, the more advantageous this method becomes. In flow cytometry, fluorescence spillover i. Correctly compensating for spillover is critical to accurately identify populations in multicolor flow experiments. Mastering fluorescence spillover is much like chess, the rules are simple, but becoming a skilled practitioner can take some effort. Here the basic concepts of fluorescence spillover are reviewed and some simple principles to follow in order to maximize data quality are provided, while debunking some of the myths that surround this field.
For further information on this subject readers are referred to the following references - This includes recommendations for ways to document compensation of complex panels.
Fluorescence spillover is the amount of signal, measured in median fluorescence intensity MdFI , that a fluorochrome emits in a secondary detector specific for a different fluorochrome Fig. This is equivalent to a background in that detector. In Fig. With a few exceptions, the mathematical calculation of SOVs is the same for all cytometers and flow cytometry software packages. Most errors in calculating SOVs are due to the use of inappropriate compensation controls.
A compensation control should consist of a positively stained population and a negative or unstained population. The positive and negative populations do not need to be run in the same tube. Cytometer and software protocols will specify what combinations can be used. While these can be very powerful, they are based on automated gating algorithms in which the software identifies the positive and negative populations.
These gates may not always be appropriate. It is recommended that for new controls the user confirm that the software is providing correct gates and results. More specifically, the fluorochrome should be identical not similar. This principle is especially critical for tandem reagents e.
The autofluoresence of the positive and negative populations must be equivalent. The spillover calculation assumes that any difference in the MdFI of the spillover detector e. Y in Fig. If the autofluoresence differs, then part of the MdFI in the spillover detector will be due to the difference in autofluoresence and not the fluorochrome itself.
An example is shown in Table 3. This also applies to cell types. Cell lines and lymphocytes should not be used for the same control. If a stained cell line is used as a positive control, the same unstained cell line should be used as a negative control. It is similar with cell subsets, for example if lymphocytes are analysed, lymphocytes, and not monocytes, should be used as both the positive and negative control. Some software programs allow a universal negative population e. Myth : the SOV depends upon the type and autofluoresence of the cells you are analyzing. The SOV is only a function of the fluorochrome.
When correctly measured, the SOV is independent of the cell type s in the biological sample. The actual SOV is not a function of the brightness of the positive population but is the same all across the dynamic range. A truly correct SOV will provide correct compensation whether it is derived from a bright or dim positive population Fig. When calculating a slope, the most accurate measurement i. SOV is obtained when the two data points obtained are apart as far as possible.
Myth : For spillover to be correct it is required that the compensation control positive population needs to be as bright as your sample. Therefore as noted in the title, it is good practice to have the positive control population as bright as possible, preferably close to your sample MdFI static or activated.
However, for spillover to be correct, it is NOT required that the compensation control positive population needs to be as bright as your sample. In some cases, the positive population of compensation beads may not be as bright as your sample. This does not mean it is not a valid compensation control. In general, if the positive population is approximately equivalent to CD4, you will get good results.
There is one major caveat to this statement. For all measurements, it is critical that the positive population is in the linear range of the detector. Outside of this range, the corrected data will be inaccurate. Most cytometer manufacturers provide linearity information for their instruments. Again this is to ensure the accuracy of the measurements, especially for low SOVs.
Each of these controls has advantages and disadvantages. That is beads positive and negative can be used to compensate Fluorochrome A, and cells positive and negative to compensate Fluorochrome B. The key is to follow the second principle and not mix and match different control types within the same single color fluorescent control.
The advantage of using stained cells is that these controls most closely replicate what is happening in the assay tube. The disadvantage is that you may have to use precious biological material. This may therefore require the use of even more of the biological sample at the outset. The advantage of beads is that no biological material is required and they are easy to prepare and use. Following the manufacturer's protocols, for many fluorochromes, beads provide sufficiently accurate SOVs. The disadvantage is that these beads are a surrogate for cells and may not in all cases provide a perfect match to cells.
This can result in discernible and reproducible differences in the SOVs obtained from the exact same reagent measured on beads versus cells. Where different SOVs are obtained, the cells must be considered the biologically relevant gold standard. However, when used for 10—18 color instruments, differences in SOVs can be seen in all of these beads when comparing the SOVs obtained with the beads to the SOVs obtained with the gold standard of cells.
These differences can vary from manufacturer to manufacturer. Compensation beads are a powerful tool for making the process of determining SOVs fast and easy and should be used where appropriate. However, it is important to use them with reasonable caution. For example, if you are using a new fluorochrome or a new lot of a tandem, run a quick test staining both cells and beads; calculate the SOVs from both.
Recommended for you
If the SOVs are effectively equivalent then you can be comfortable using the beads as controls for all future assays. However, if there are significant differences, you may need to use cells as your controls or try a different bead. Finally, in such a test you may want to treat the cells and beads as you would in your assay, e. This is really a question that cannot be definitively answered. There is great deal of misunderstanding regarding what SOVs actually mean in terms of a multicolor flow cytometer and the experiments run on them.
- Medical Immunology: Fifth Edition, Revised And Expanded.
- Encyclopedia of Physical Science and Technology - Biochemistry.
- Related Articles.
First and foremost, SOVs are empirically determined mathematical values which are used by flow cytometry software to correct for the background due to fluorescence. While these values are related to fluorescence spillover, they ARE NOT direct absolute measurements of the fluorescence spillover of one fluorochrome into another detector. SOVs are based upon median fluorescence measurements which are gain i.
PMT voltage dependent. However, the actual spillover of fluorescence from one detector into another is unchanged. Using the right compensation controls under the right conditions will maximize the accuracy of your spillover values. Still, no matter which controls are used it is likely that there will be some error in some of the SOV measurements you make. This brings up the final question of what SOV accuracy is good enough to provide you quality data. Any error in the final data is directly proportional to both the error in the SOV measurement and the brightness MdFI of the population being analyzed.
This is demonstrated in Fig. The situation in the assay shown in the bottom panels is quite different. Identical errors i. Maintaining flow cytometric instruments is an important step in ensuring a constant quality level of measurement. The signals generated by flow cytometric instruments are dependent on many factors i. A prerequisite is thereby a deeper knowledge of the performance of the respective system, making it necessary to define the original status once and track it over time. This can be done at different levels and is dependent on the type of instrument analyzer, cell sorter , the instrumental layout number of lasers, high throughput system and the type of measurement one wants to conduct on such an instrument e.
Due to the high diversity of available flow cytometers on the market, there is no common routine of conducting maintenance and also the time frames and maintenance intervals may vary from instrument to instrument. While most of the manufacturers offer service contracts for their systems, the user can do several things to prevent potential damage and maintain or restore the instrument's original level of performance. Be aware that for some steps during maintenance e. Why is tracking of instrument performance so important?
One reason is that the data generated by flow cytometers have no absolute unit numbers but are relative. They are strictly dependent on the context of and the conditions during data acquisition. Maintaining a flow cytometer means being able to retrieve information about the actual status of an instrument and compare it to the original ideal situation.
If the performance check fails one needs to know how to bring it back to the original level if possible. The following section describes several options for how to check the performance of a flow cytometric instrument and what can be done as a preventive procedure summarized in Table 4. Maintenance starts with cleaning the instrument. These parts can be cleaned with unsoiled pressurized air e. How often these types of preventive maintenance have to be performed strictly depends on the environmental conditions and are sometimes included in maintenance contracts of the vendors.
The combination of software and the use of standardized beads make it possible to retrieve critical parameters in one run. After installation through a service engineer or exchange of components e. All the introduced values are summarized in Table 5 with a very brief explanation and cannot be discussed further here but are described in much greater detail elsewhere - The software module reports every observed change compared to the baseline and has some more features, which are not described here. Besides the target channels, the shape and width of the peaks are also of importance and can indicate for instance a laser misalignment.
As shown in Fig. As noted earlier, there are several additional parameters, which can be tracked e. The fluidic system of most flow cytometers is assembled with parts that need to be maintained on a regular basis. One has to ensure that the fluidic lines and filters are free of air bubbles. The more lasers a machine has, the less tolerant the system is against air bubbles or unstable compressed air supply. Sheath or saline filters therefore have to be vented on a daily basis and replaced every 6 months the most commonly suggested time interval by manufacturers.
In machines without an extra sheath supply e. Sheath tanks, especially when they are pressurized, have to be refilled and checked for leakiness on a frequent basis. Ball seals have to be replaced before they lose integrity. The consequences are similar to those described above for entrapped air bubbles.
This goes in line with cleaning the sample injection port SIP and the sample tubing see Table 4. Distilled or deionized water is ideal for washing out the cleaning solution. This is to ensure that even if the SIP or tubing were to dry out, no salt crystal formation, which could subsequently cause clogging, would occur. Sticky or clumpy cells, which are either not properly filtered or used at too high a cell concentration, could block the orifice of an instrument. In some mostly pump driven instruments e. In other cases e. In machines where one can easily access and remove the SIP, sonication in clean water of the tubing is also an option e.
Guava EasyCyte. As a last resort, the usage of thin wires to clean the SIP, working like a sweeper is cleaning a chimney, can be recommended.
(PDF) Immunology & Serology in Laboratory Medicine | Shafinewaz RPh - bonyledewydy.gq
If an optional High Throughput Sytem or Carousel Module is available, the washing steps become even more important and fluidic parts and tubing should be changed as recommended by the vendor. These dyes are often stained in excess to ensure a good staining profile. Due to their planar structure, they are sticky and can also adhere to the tubing. Running a bleaching solution e. This will damage the tubing and sealing and ends up in leakiness of the system. Some flow cytometers e. A prerequisite for accurate cell counting is again an air bubble and particle free filtered sheath fluid and intact sample tubings.
Mechanical stress makes it necessary to replace the tubing at constant intervals e. This will impair and slow down the performance of the entire system at a certain time point. Although most flow cytometers on the market are very robust and reliable, there are still many things that need to be controlled.
Table 4 summarizes many common steps to consider during instrument maintenance.
As already mentioned, it depends on the instrument and environmental setup, as to which steps have to be done in which frequency, and the focus might vary from lab to lab. Therefore, this is an overview and a suggestion of procedures, which should help to get the best results out of your flow data. For antibodies the desired way of binding is the specific binding of the antibody, i. It is of critical importance to exclude the latter two to be able to reliably quantify antigen expression by immunofluorescence.
Antibodies, the most widely used staining reagents in flow cytometry, can bind a cell in many different manners. Hyperlinks and signposting to other chapters are available, and the references are linked by PMIDs to the original article. The fifth edition was published in The book provides insights into the use of epidemiological approaches and principles related to the occurrence, prevention, surveillance, etiology, and control of health conditions and diseases in defined populations, and demonstrates the practical uses of epidemiology in evaluating health services and policy implementation.
The digital version enhances both readability and portability, as well as leveraging its potential as an educational resource. This book is ideal for students requiring grounding in the principles and practice of epidemiology, but is equally a fantastic reference for professionals involved in the teaching of epidemiology in various settings and for those needing to confirm their understanding of essential information. The first five editions of this book were authored by the late Professor Leon Gordis. Elements of this edition have been sensitively expanded, updated, and revised by two new authors David Celentano and Moyses Szklo , both of whom were trained in public health at Johns Hopkins under the guidance of Professor Gordis during the earlier parts of their careers, with valuable contributions from several notable epidemiologists.
The overall length remains almost the same pages versus in the fifth edition. Although the answers to the review questions are provided at the back of the book, they do not detail how to work them out. Much of these changes reflect the reorganization of the section to emphasize a hierarchy of evidence-based practice, discussing study designs ranging from case reports and case series the lowest level of evidence all the way up to the randomized controlled trial considered the gold standard of study designs.
It is noteworthy that chapter 16 on genetic epidemiology has been given an overhaul. It is written with more concision two pages shorter than the fifth edition , and the sequencing of information has been changed, bringing discussions around complex diseases and seminal findings from twin, adoption, and migrant studies before the application of genetic markers and precision medicine. Visit Store.