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Prediction of Protein Complexes in Trypanosoma brucei by Protein Correlation Profiling Mass Spectrometry and Machine Learning.

ABSTRACT: A disproportionate number of predicted proteins from the genome sequence of the protozoan parasite Trypanosoma brucei, an important human and animal pathogen, are hypothetical proteins of unknown function. This paper describes a protein correlation profiling mass spectrometry approach, using two size exclusion and one ion exchange chromatography systems, to derive sets of predicted protein complexes in this organism by hierarchical clustering and machine learning methods. These hypothesis-generating proteomic data are provided in an open access online data visualization environment (http://134.36.66.166:8083/complex_explorer). The data can be searched conveniently via a user friendly, custom graphical interface. We provide examples of both potential new subunits of known protein complexes and of novel trypanosome complexes of suggested function, contributing to improving the functional annotation of the trypanosome proteome. Data are available via ProteomeXchange with identifier PXD005968.

SUBMITTER: Crozier TWM

PROVIDER: S-EPMC5724185 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Prediction of Protein Complexes in <i>Trypanosoma brucei</i> by Protein Correlation Profiling Mass Spectrometry and Machine Learning.

Crozier Thomas W M TWM Tinti Michele M Larance Mark M Lamond Angus I AI Ferguson Michael A J MAJ

Molecular & cellular proteomics : MCP 20171017 12

A disproportionate number of predicted proteins from the genome sequence of the protozoan parasite <i>Trypanosoma brucei</i>, an important human and animal pathogen, are hypothetical proteins of unknown function. This paper describes a protein correlation profiling mass spectrometry approach, using two size exclusion and one ion exchange chromatography systems, to derive sets of predicted protein complexes in this organism by hierarchical clustering and machine learning methods. These hypothesis ...[more]

PMID: 29042480

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Project description:?-D-glucosyl-5-hydroxymethyluracil (base J) is a hyper-modified nucleobase found in the nuclear DNA of kinetoplastid parasites. With replacement of a fraction of thymine in DNA, J is localized primarily in telomeric regions of all organisms carrying this modified base. The biosynthesis of J occurs in two putative steps: first, a specific thymine in DNA is recognized and converted into 5-hydroxymethyluracil (5-HmU) by J-binding proteins (JBP1 and JBP2); a glucosyl transferase (GT) subsequently glucosylates the 5-HmU to yield J. Although several recent studies revealed the roles of internal J in regulating transcription in kinetoplastids, functions of telomeric J and proteins involved in J synthesis remain elusive. Assessing the functions of base J and understanding fully its biosynthesis necessitate the measurement of its level in cells and organisms. In this study, we reported a reversed-phase HPLC coupled with tandem mass spectrometry (LC-MS/MS) method, together with the use of a surrogate internal standard (?-D-glucosyl-5-hydroxymethyl-2'-deoxycytidine, 5-gHmdC), for the accurate detection of ?-D-glucosyl-5-hydroxymethyl-2'-deoxyuridine (dJ) in Trypanosoma brucei DNA. For comparison, we also measured the level of the precursor for dJ synthesis [i.e. 5-hydroxymethyl-2'-deoxyuridine (5-HmdU)]. We found that base J was not detectable in the JBP-null cells whereas it replaced approximately 0.5% thymine in wild-type cells, which was accompanied with a markedly decreased level of 5-HmdU in JBP1/JBP2-null strain relative to the wild-type strain. These results provided direct evidence supporting that JBP proteins play an important role in oxidizing thymidine to form 5-HmdU, which facilitated the generation of dJ. This is the first report about the application of LC-MS/MS for the quantification of base J. The analytical method built a solid foundation for dissecting the molecular mechanisms of J biosynthesis and assessing the biological functions of base J in the future.?

Dataset Information

Prediction of Protein Complexes in Trypanosoma brucei by Protein Correlation Profiling Mass Spectrometry and Machine Learning.

Publications

Prediction of Protein Complexes in <i>Trypanosoma brucei</i> by Protein Correlation Profiling Mass Spectrometry and Machine Learning.

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