Computational Molecular Biology 2024, Vol.14, No.1, 36-44 http://bioscipublisher.com/index.php/cmb 39 (Bhavsar et al., 2010). By comparing the proteomes of bacteria grown under laboratory conditions to those during in vivo infection, researchers can gain significant insights into bacterial pathogenesis. Proteomic technologies have been used to identify and characterize bacterial genes expressed specifically in vivo, which is crucial for understanding the molecular boundaries of microbial pathogenesis and for the development of targeted therapies and vaccines (Cash, 2011). In the context of rice bacterial pathogens, proteomics has been applied to clarify the interaction between rice and microbes, including bacteria. This research is essential for plant pathology and has led to discussions on the proteomic analysis of interactions between rice and various microbes, such as fungi, bacteria, and viruses. The identification of specific proteomic signatures in these interactions can help in understanding the complex dynamics between rice and bacterial pathogens. Table 1 Different quantitative proteomic approaches with the associated advantages and disadvantages (Source: Pérez-Llarena and Bou, 2016) Proteomic tools Advantage Disadvantage GEL-BASED METHODS 2DE (1) Simple (2)Robust (3) Suitabie for MS analysis (1) Involves large amount of sample (2) Low throughput (3) Poor recovery ol hydrophobic proteins (4) High inter-gel vaiabilitl 2-DIGE (1) Multiplexing (2) Better quantitation (3) Minimal gel to gell variation (1) Expensive Cy dyes (2) Poor recovery of hydrophobic proteins (3) Difiulty in separating low molecular weigh compounds GEL-FREE METHODS SILAC (1) High throughput (2)Robust (3) Sensitive and simple (1) Only suitable for tissue culture models (2) Costly reagents (3) Not ppliable to tissue sample ICAT (1) Selectvely isolates peptide (2) Compatible with any amount o protein (3) Complexity of the peptide mixture is reduced (1) Cannot identify proteins with less than eight cysteines (2) Large ICAT label (>500 Da) (3) Post-translational modificationo information is frequently lost iTRAQ (1) Applicable to versatle samples (2) Multiplexing (3) Better quantitation (1) Involves high amount o sample (2) Incomplete labeling (3) Expensive reagents ICPL (1) High-throughput quantitative proteome profing on a global scale (2) Able to detect post-translational modifications and protein isoforms (3) Applicable to protein samples such as tissue extracts or body fluids (1) lsotopic effect of deuterated tags interferes with retention time of the peptides labeled during LC Label-free (1) Involves less amount of sample (2) Higher proteome coverage (3) Awoids labeling (1) High throughput instrumentation (2) Not suitable for low abundant proteins (3) Incomplete digestion may introduce eror (4) Multiplexed analysis not possible in one experiment SRM (1) Highly sensitive, quantilatively accurate and highly reproducible (2) Protein detection is relativly rapid and straightforward (3) Enables detection of non abundant (> 10 ng/m) proteins (4) Quantification of post -ranslationai modfications (1) Limiled broad scale appcalion because of dfiully in generating high-quality SRM assay (2) Sensitivty is not comparable to immunological assays (3) Detection and quantification of non abundant proteins (i., ~10 ng/ml or less)
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