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Flow cytometry is an immunophenotyping technique whereby sing cell suspensions are stained for either cell surface markers or intracellular proteins by fluorescently-labelled antibodies and analyzed with a flow cytometer, where fluorescently-labelled molecules are excited by the laser to emit light at varying wavelengths, which is then detected by the instrument. There are several key criteria which are required to be kept in mind while designing a flow experiment- 1. Antibody titration (optimal dilution of antibodies should be calculated in order to avoid over- or under- saturated signals for proper detection of surface and intracellular markers), 2. Precision (3 or more replicates of the sample should be used per experiment), 3. Specificity (proper isotype controls should be included in the experiment), 4. Day-to-day variability (experiments should be repeated 3 or more times to ensure consistency and avoid variability due to flow cytometer settings), 5. Antibody interaction (Fluorescence minus one or FMO should be used, which is the comparison of signals from panel minus one antibody vs. the full panel), and 6. Antibody stability (fluorescently-labelled antibodies should be stored at 4C).

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As autophagy is a multi-step process which includes not just the formation of autophagosomes, but most importantly, flux through the entire system, including the degradation upon fusion with lysosomes, which makes it quite challenging for detection. There are several methods for detection in mammalian cells, including immunoblotting analysis of LC3 and p62 and detection of autophagosome formation/maturation by fluorescence microscopy, Currently, there is no single “gold standard” for determining the autophagic activity that is applicable in every experimental context, hence it is recommended to go for the combined use of multiple methods to accurately assess the autophagic activity in any given biological setting.

Protein expression refers to the techniques in which a protein of interest is synthesized, modified or regulated in cells. The blueprints for proteins are stored in DNA which is then transcribed to produce messenger RNA (mRNA). mRNA is then translated into protein. In prokaryotes, this process of mRNA translation occurs simultaneously with mRNA transcription. In eukaryotes, these two processes occur at separate times and in separate cellular regions (transcription in nucleus and translation in the cytoplasm). Recombinant protein expression utilizes cellular machinery to generate proteins, instead of chemical synthesis of proteins as it is very complex. Proteins produced from such DNA templates are called recombinant proteins and DNA templates are simple to construct. Recombinant protein expression involves transfecting cells with a DNA vector that contains the template. The cultured cells can then transcribe and translate the desired protein. The cells can be lysed to extract the expressed protein for subsequent purification. Both prokaryotic and eukaryotic protein expression systems are widely used. The selection of the system depends on the type of protein, the requirements for functional activity and the desired yield. These expression systems include mammalian, insect, yeast, bacterial, algal and cell-free. Each of these has pros and cons. Mammalian expression systems can be used for transient or stable expression, with ultra high-yield protein expression. However, high yields are only possible in suspension cultures and more demanding culture conditions. Insect cultures are the same as mammalian, except that they can be used as both static and suspension cultures. These cultures also have demanding culture conditions and may also be time-consuming. Yeast cultures can produce eukaryotic proteins and are scalable, with minimum culture requirements. Yeast cultures may require growth culture optimization. Bacterial cultures are simple, scalable and low cost, but these may require protein-specific optimization and are not suitable for all mammalian proteins. Algal cultures are optimized for robust selection and expression, but these are less developed than other host platforms. Cell-free systems are open, free of any unnatural compounds, fast and simple. This system is, however, not optimal for scaling up.

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