Proteome, interpretation techniques

In the previous section we have given an overview of approaches and tools for assisted interpretation of MS spectra of glycans. It is obvious that unlike for proteomics, currently no widely available and accepted solution exists for the rapid identification of glycans. Here, we describe in more detail three approaches to assisted interpretation and their implementation in more detail. In the opinion of the authors, these three techniques have the promise to become widely adopted. Two of the techniques, embodied in Glyco-PeakFinder and GlycoWorkbench, are... 

It is important to note that RNA may not always correlate with the expression of encoded proteins. Use of proteomic techniques increasingly serves to resolve discrepancies between mRNA levels and expressed proteins. However, proteomics of integral membrane proteins still remains a challenge moreover, comparing mRNA levels in similar tissues from different subjects is likely to provide an indication of protein levels. Any polymorphism that affects protein structure and function could also lead to false interpretations if the array fails to measure the functional polymorphism. 

Both genomics and proteomics approaches generate extensive data86. It will be important to develop methods, or to apply methods developed by others, to interpret and categorize this information in a useful manner. In order to achieve the best information from any technique or method, full and meaningful analysis will be critical. 

There have been signihcant advances to harvest the power of the mass spectrometry-based analysis technique. The ability to perform real-time scanning experiments with real-hme automated dynamic feedback has become an essenhal component of qualitahve analysis, such as biotransformahon or proteomics applicahons. Most commercial mass spectrometry software packages provide the ability to perform data-dependent scanning procedures. Metabolic prohling and proteomics generate large quanhties of data that must be quickly and efficiently interpreted and hltered such that the data can be quickly reported in a way that will support rapid decisions. 

Increasing reproducibility of available separation techniques and sensitivity and affordability of mass spectrometers, as well as the desire and need to automate the identification process, have caused peptide mass fingerprinting and MS/MS sequencing to gain importance and to become the method of choice for many proteomics laboratories. Several tools are available to assist users in the interpretation of mass spectrometry data. Peptldent (http //www.expasy.org/tools/peptident.html) on the ExPASy server follows the concept of the other tools from the ExPASy proteomics suite, in that it takes into account annotation available in the SWISS-PROT/TrEMBL database, in particular as post-translational modifications and processing are concerned. The user can paste peptide masses (monoisotopic or average) into the Peptldent form, but peptide mass data can also be uploaded from a file on the user s local computer. Supported file formats are .pkm ... 

An important factor in the progress of bioinformatics has been the constant increase in computer speed and memory capacity of desktop computers and the increasing sophistication of data processing techniques. The computation power of common personal computers has increased within 12 years approximately 100-fold in processor speed, 250-fold in RAM memory space and 500-fold or more in hard disk space, while the price has nearly halved. This enables acquisition, transformation, visuahsation and interpretation of large amounts of data at a fraction of the cost compared to 12 years ago. Presently, bioanalytical databases are also growing quickly in size and many databases are directly accessible via the Internet One of the first chemical databases to be placed on the Internet was the Brookha-ven protein data bank, which contains very valuable three-dimensional structural data of proteins. The primary resource for proteomics is the ExPASy (Expert Protein Analysis System) database, which is dedicated to the analysis of protein sequences and structures and contains a rapidly growing index of 2D-gel electrophoresis maps. Some primary biomolecular database resources compiled from spectroscopic data are given in Tab. 14.1. 

Bottom-up proteomics methods still need refinement of protocols, and improvements in the standardization and availability of bioinformatics tools for comprehensive data analysis on a routine basis. Although recent innovations in mass spec-trometric instramentation have aeeelerated the speed and sensitivity of proteome analysis (Hebert et al. 2014), further improvements can be obtained by emphasizing the optimization, simplification, and automation of sample preparation, for example, through single-tube proteomics approaches integrating all steps from cell lysis to peptide fractionation (Hughes et al. 2014 Fan et al. 2014), peptide separation techniques, and bioinformatics tools for fast, automated data interpretation for strain-level identification of cultivable bacteria and comprehensive characterization of each isolated microbial strain in the near future. 

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