Structural Biochemistry/Counting proteins using fluorescence microscopy

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Introduction[edit | edit source]

Two method of counting protein molecules have been used widely: stepwise photobleaching and ratio comparison to fluorescent standards.

Fluorescence takes place when light is given off from the fluorophore after light is absorbed, and GFP is able to fluorescence without enzymatic modification or a cofactor, which allows a single gene to be expressed in detectable emission in any organism. Counting the number of protein molecules in live cells allows researchers to determine the stoichiometry of functional protein complexes and to seek models of cellular structures. Since genome-wide studies may not recognize information about low-abundance proteins or local protein concentrations, single-molecule techniques, if successful, would be able to solve this problem.

Stepwise photobleaching[edit | edit source]

Stepwise photobleaching is one of the fluorescence microscopy method for counting protein molecules, which “relies on the irreversible and stochastic loss of fluorescence from repeated exposure of fluorescent proteins (FPs) to a light source.” The sample would be continuously exposed to excitation light at low intensity to allow the sample to be “slowly bleached until its emission intensity reaches background level.” The number of florescent molecules present in the structure determines the suitable light intensity and exposure time. The missed bleaching events need to be minimized because it would show a step approximately twice the size of other steps. The bleaching method is only useful for low protein numbers as the probability of missed events increases exponentially with the number of molecules in a structure. “Das et al. estimated that a maximum of 15 bleaching steps can be directly detected without mathematical extrapolation, although they detected no more than seven steps in their experiments.” The maximum number of molecules that can be counted by photobleaching can be increased to approximately 30 molecules using mathematical aids. A background correction is needed to eliminate fluorescence from diffused proteins and calibrate the starting intensity. During photobleaching, regions of interest (ROIs) should be selected to avoid confusing multiple structures. It is also essential to filter the data to reveal the discrete drops as the raw data are noisy. For example, Chung-Kennedy filter is the most commonly used filter for quantification of the bacterial replisome. “It calculates the mean and standard deviation in two consecutive sets within the data from one photobleaching ROI, and reports the mean of the set with the lower standard deviation.” The number of averaged data points in the data set should be big enough to reduce the noise but small enough to make sure that few steps are missed.

Quantification by ratio comparison to fluorescent standards[edit | edit source]

This method involves the measurement of ratio of the fluorescence intensities of a protein sample to a standard. It uses a series of images of cells that express either the protein sample or the standard, with had obtained fluorescent properties by fusion with an FP. “If the standard can be distinguished from the protein of interest, it is desirable to include cells that express the standard and experimental fusion proteins on the same slide to ensure comparable illumination. If the standard is not distinguishable, images can be taken consecutively or another marker can be imaged separately to distinguish the control cells distant to eliminate Forster resonance energy transfer.” This method is advantageous in the way that a relatively larger number of protein molecules can be counted. Corrections need to be made to achieve more accurate measurements. For example, the uneven illumination in the microscope system needs to be corrected if the whole field is used. Also, if sample molecules are at different depths relative to the coverslip, calibrations on the effect of depth on intensity should be done using fluorescent beads. Different exposure times can be used to control the signal to noise ration and avoid saturation. Excitation intensity should be kept constant to avoid nonlinear changes to photon counts due to blinking molecules. “The background should be taken from a concentric area unles there are overlapping neighbouring signals or an inhomogenous cytoplasmic intensity.” It is important to use a trustworthy standard for this method. When proteins of different sizes or same structure proteins with very different intensities are compared, the sum of intensity of multiple z sections should be used. Additional verification using methods such as genomic DNA sequencing should be used to ensure accuracy of number measured. The number of molecules of each protein and their relative stoichiometries can be obtained using the ratio method at one or many time points.

Important considerations in counting proteins[edit | edit source]

Genetically encoded FPs should be used in order to generate a 1:1 stoichiometry with the protein sample, which may affect the maturation efficiency or proportion of unfolded FPs.

Properties of FPs[edit | edit source]

The best available FPs should be used by researchers to maximize the signal-to-noise ratio, especially for less abundant proteins. The folding and maturation efficiency, brightness, and photostability of the FPs that are going to be used in the fusions should be taken into consideration before constructing fusion proteins. Research conduced in the budding yeast Saccharomyces cerevisiae and the folded YFP in E. coli suggest that YFP maturation and folding efficiency are not major issues for counting proteins, in particular for proteins with low turnover rates.

Functionality of fluorescent fusion proteins[edit | edit source]

It is advantages to use yeast, because fluorescent fusion protein can replace native protein using homologous recombination, which allows the functionality of the fusion protein to be determined. The functionalities for some proteins could be improved by using a flexible linker between the FP and protein sample. The fact that endogenous genes cannot be replaced with tagged version, alternative methods of protein counting need to be used. The local actin abundance in actin patches can be quantified by making corrections after immunoblotting. However, this method is only possible given the assumption that tagged and untagged actins are utilized with similar efficiency in actin patches. Engel et al uses stepwise photobleaching method in a mutant background to count exogenous tagged proteins in exogenous tagged proteins in green algae Chlamydomonas reinhardtii flagella. Since the endogenous genes do not localize, the ratio of tagged and untagged protein assumptions do not need to hold. The recent development of ‘genome editing’ techniques has allowed endogenous genes to be tagged in any model organism in which “the zinc finger nuclease or transcription activator-like effector nuclease genes can be introduced.”

In vivo versus in vitro standards and quenching[edit | edit source]

The environment in which the number of proteins is measured is important. Early studies employed in vitro standards, where the effect of background on fluorescence intensity is unknown. This meant that immunoblotting or internal standards were needed to calibrate the fluorescence intensity inside the cell. Experiments were done recently to suggest that in vitro YFP/GFP is comparable to YFP/GFP in bacteria or yeast. Also, fluorescence quenching could take place if FPs were packed into very tight structures. The effects of quenching on counting proteins should be examined individually depending on the specific structures of interest. Fluorescence lifetime imaging with the aid of specialized equipment and analysis can be used to measure quenching due to environmental changes.

Validation of protein quantification by complementary approaches[edit | edit source]

Cellular concentrations should be authorized by a cell sorting device called the flow cytometry or fluorescence correlation spectroscopy fro a higher resolution. It is also important to ensure that protein concentrations from fluorescence microscopy are consistent with quantitative immunoblotting. In any protein counting experiment, suitable fluorescent protein genes, suitable standards and controls for environmental changes or the possibility of quenching will ensure appropriate interpretations of the data, which can then be confirmed with complementary experiments.

Future of counting proteins using fluorescence microscopy[edit | edit source]

Super-resolution microscopy techniques can produce high-resolution images of intracellular structures, which pinpoint exact locations of individual fluorescent molecules. For such techniques, it is most important to simplify the analysis of high-density images of FPs and minimize errors due to blinking or photobleach failure. Single-molecule techniques are now more commonly used due to the inability to observe stochastic events in average population behaviours. The advantage of using such techniques is that molecules can be counted directly without using collective images, or even determine different protein complexes that are within a diffraction limited area. Super-resolution imagining could lead to the quantification of higher numbers of proteins.

Conclusion[edit | edit source]

Counting proteins molecules in a cell is essential in determining structural models and protein function. In vitro, protein numbers help determine the reaction rate and also give more of an understanding to multiproteins. The two methods introduced are stepwise photobleaching and ratio comparison to a given standard. This maybe used in any laboratory with a fluorescence microscope to isolate a particular protein. Of course, there are many advantages and disadvantages in every method including this one. The properties of FPs is of high significance to both methods. There are other methods that will help validate the quantity of proteins such as electron microscopy. Fluorescence microscopy has help determine exact numbers of proteins and also their binding ranges.

Source: Coffman VC, Wu JQ. Trends Biochem Sci. 2012 Sep 1.