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Manual Analysis of Mass Spectrometry Data


An identification process of protein that is accurate is required to be able to produce quantitative proteomics; this process is mostly carried out by searching automated softwares, they track the sequence of the database which contains mass spectra tandem of peptides, if these peptides do not have enough data, the software will most likely give results of peptide specifications that are not accurate. This makes manual analysis a more suitable alternative while inspecting the spectra mass. Though the disadvantages with the method are that it is time-consuming and that an experienced analyst is required to be able to make accurate results it does give an assurance that the results are accurate (Chen 2005, 1)

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Results from software are not always accurate and manual knowledge is required to be able to verify the peptide identifications, hence manual analysis of mass spectrometry data becomes vital at this point. For instance, a study done in the Department of Biochemistry and Molecular Biology at Colorado state university, whereby they used multiple protocols to make phosphopeptides rich, involving intense filtration during the flow of the work, was applied to analyze the samples that were obtained. the enriched phosphopeptides were from cultured renal that had been extracted from a rat’s proximal tubule (Nicholas 2011, 1)., applying three protocols that are mostly used and also a method that is dual, this method puts together separated immobile metal affinity chromatography and also TiO(2) which is titanium double oxide chromatography which is also referred to as dual IMAC or in short as(DIMAC) (Colleen 2005, 1). Phosphopeptides that were achieved from the four strategies of enrichment were put through an analysis process, by using liquid chromatography- multiple strata of mass spectrometry neutral-loss scanning, putting into use an ion trap that is of linear mass spectrometer. At first, the results from mass spectrometry (2) and mass spectrometry (3) spectra were put under an analysis by using the software peptide prophet and also making use of the search engine database thresholds which produced a false discovery rate (FDR) of less than 1.5 percent when it was put in search against a database that was reversed. Only 40 percent of the potential phosphopeptides brought positive similar results to a manual validation that was carried out, hence the combined analytical methods resulted in 110 affirmatively identified phosphopeptides (Colleen 2005, 1). Applying less rigorous initial filtering baselines, including a hundred and eleven (111) novel phosphorylation sites, were affirmed. Hence the conventional manner of data filtering in a range of widely agreed FDRs was not adequate to carry out analysis of phosphopeptides spectra that are of low resolution. Regarding this fact it is clear that having knowledge of manual analysis of mass spectrometry data is essential in order to correctly be able to use automated mass spectrometric database search programs. We can see that the combined streamline of front-ended enrichment approach and intense manual validation of spectra did allow for affirmative phosphopeptides identifications which were obtained from a sample that is complex using a low-resolution mass spectrometer ion trap (Chen 2005, 1).


Using automated mass spectrometric database searching programs has its disadvantages due to the amount of data required to come up with accurate results it is important to look at some disadvantages associated with the use of automated mass spectrometric database searching programs (Colleen 2005, 1).

The science associated with life research has increased its focus on a systematic way of identifying and quantifying proteins that are expressed in a cell so that a comprehensive, characterized total protein at the cell level can be achieved. More focus has been put on the study of the property of the proteins that include state of modification, s protein to protein interaction, and also where the protein is located within the cell. Present technologies used for the study of proteomics are founded on the basis of various separation technologies which are then followed by the process of identifying the proteins that are separated by the use of mass spectrometry (Nicholas 2011, 1). Currently high-resolution separation technique, which is commonly used is a two-dimension (2D) gel of electrophoresis which can give proteins that are in their state obtained from samples that are complex in nature. Mass spectrometry and sequential database searching are used to identify the spots of the protein that are in the gel. Both are assisted by a matrix laser desorption or ionization period of flight mass spectrometry and also ionization electrospray of mass spectrometry is widely used for protein, there is an identification process that is of a large scale, this is done by peptide mass mapping, in this case the proteolyptic peptide mass is put into a matching process comparing them with resulting calculations from database of the proteins. For the reason of its simplicity and also the relatively high throughput of the sample, it is commonly matrix-assisted laser desorption spectrometry which is commonly applied as a method of screening. Throughput of more than a hundred separated gel from protein sample has been witnessed within a day. The short fail of these techniques is that false or else ambiguous identification of protein can occur, with gel spots that are not resolved; there are also gel interferences, modifications of proteins and mutation points of proteins. More limitations of this approach are the incapability to provide accurate analysis quantitation and transitional modifications sites. With this limitation it is important that one understands manual analysis of mass spectrometry data, it is essential to correctly use automated mass spectrometric database searching programs (Goldstrohm 2011, 1)

Significant numbers of human genome and other kinds of genomes have been put into sequences, at a level of expression of each gene in the protein, they are put into a monitoring position by use of numerous technologies in DNA chips; researchers have turned into distribution profile analysis of thousands of proteins that have been encoded by these Genomes, also known proteomes. Mass spectrometry has gained popularity as the method by which researchers use it to obtain this daunting task. Mass spectrometry-based proteomics brings into combination ionization of peptide and technologies of fragmentation together with available databases for gene sequences to be able to identify the content of the protein from complex samples in biology, for instance an entire cell. In the process of Mass spectrometry analysis which was performed by a Spectrometry Group under the leadership of Damarys.L at the Curie institute, saw hundreds of fragmented peptide spectra are produced and put through an interpretation process, making use of a software known as MASCOT(Chen 2005, 1). With this it is possible for a single spectrum to be interpreted up to ten peptide sequences that are compatible with numerous proteins (Goldstrohm 2011, 1).

Regardless of the process described above manual validation was used to achieve accurate interpretations by the Mass spectrometry specialist (Nicholas 2011, 1). Manual process of validation for Mass spectrometry identification of peptide is a crucial evaluation procedure, this calls for experts to know how to apply because of the presence of a large number of genome endeavors, the process of manual validating is an irreversible process, analyst must have this knowledge to be able to use automated mass spectrometric database search programs. A major challenge in the identification of peptides from mixtures that are complex by use of shotgun proteomics is the capacity of the programs used for searching, to accurately be able to give peptide sequences by use of fragmented spectra of Mass spectrometry. Manual validation is critical for assessing the identification of borderline (Nicholas 2011, 1). Manual validation is important in a case like that of Label-free shotgun genomics, in particular where it has been a challenge in high requirement for computational ability to carry out activities like, detection of feature and alignment resulting from the complexity of genomics systems. A lot of software has been developed in the past years to aid this procedure but it has not yet been clarified to the users of this software if this software does obtain information from raw data in the right way and whether this data is in its completeness (Colleen 2005, 1).

While not denying that analysis for Mass spectrometry of phosphorylation has become more powerful over the past ten years and has also been used in various systems that are biological, a major challenge facing the community dealing with issues of phosphoproteomics and also the proteomics sector is the accuracy and quality of data that is generated in large scale. For instance, when protein is to be identified in a sample, the solution does require numerous peptides per protein which removes the possibility of identifying a single peptide based on a single assignment (Goldstrohm 2011, 1). This has a risk of increasing false positives within the given data set. Incidentally most of the data of phosphoproteomics does fall in the latter description, as site phosphorylation which will mostly be represented by a tryptic peptide that is single in form. It does give accurate results using protocols of manual of validating to assure that accurate peptide and also site of phosphorylation assignment for individual Mass spectrometry spectra (Chen 2005, 1).

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These facts do make it clear that technology as far biotechnology is concerned has improved tremendously but it does remain clear that the success of these software tools do require enough data and also data that is accurate so that results achieved can be credible, there is a tendency for a lot of professions to abandon the conventional methods of attaining certain required results, while in most cases the convectional methods have become obsolete due to the efficiency brought about by advancing technology, it seems not to be the case as far as mass- spectrometry analysis is concerned. Emerging experts in the field should find it important to know manual validation of peptide sequence and also tyrosine phosphorylation peptide mass-spectrometer (Colleen 2005, 1). Understanding manual analysis of mass spectrometry data is essential to correctly use automated mass spectrometric database searching programs for experts because, it is evident that results acquired from software tools cannot be entirely accredited 100% accuracy and hence expertise without the knowledge of manual analysis of mass spectrometry is most likely to result to giving inaccurate results, of which can be detrimental to research hence dire consequences.

Avoiding emerging technology as far as analysis of mass spectrometry data is concerned is not the way forward but having an understanding of manual analysis of mass spectrometry data is essential to correctly use automated mass spectrometric database searching programs this way it remains true that the results form analysis can be presented confidently


Chen, Y. 2005, “Integrated approach for manual evaluation of peptides identified by searching protein sequence databases with tandem mass spectra,”, Web.

Colleen, K, 2005, Characterization of a Fully Automated Nanoelectrospray system with Mass spectromic Detection for Proteomic Analysis. Newyork: Advion Biosciences,Inc.

Goldstrohm, D. 2011, “Importance of manual validation for the identification of phosphopetides using a linear ion trap mass spectrometer”, Web.

Nicholas, M. 2011, “Manual validation of peptide sequence and sites of tyrosine phosphorylation from MS/MS spectra”, Web.

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