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Polysome profiling of the malaria parasite Plasmodium falciparum.

ABSTRACT: In the malaria parasite Plasmodium falciparum, global studies of translational regulation have been hampered by the inability to isolate malaria polysomes. We describe here a novel method for polysome profiling in P. falciparum, a powerful approach which allows both a global view of translation and the measurement of ribosomal loading and density for specific mRNAs. Simultaneous lysis of infected erythrocytes and parasites releases stable, intact malaria polysomes, which are then purified by centrifugation through a sucrose cushion. The polysomes are resuspended, separated by velocity sedimentation and then fractionated, yielding a characteristic polysome profile reflecting the global level of translational activity in the parasite. RNA isolated from specific fractions can be used to determine the density of ribosomes loaded onto a particular transcript of interest, and is free of host ribosome contamination. Thus, our approach opens translational regulation in malaria to genome-wide analysis.

SUBMITTER: Lacsina JR

PROVIDER: S-EPMC3135974 | biostudies-literature | 2011 Sep

REPOSITORIES: biostudies-literature

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Polysome profiling of the malaria parasite Plasmodium falciparum.

Lacsina Joshua R JR LaMonte Gregory G Nicchitta Christopher V CV Chi Jen-Tsan JT

Molecular and biochemical parasitology 20110513 1

In the malaria parasite Plasmodium falciparum, global studies of translational regulation have been hampered by the inability to isolate malaria polysomes. We describe here a novel method for polysome profiling in P. falciparum, a powerful approach which allows both a global view of translation and the measurement of ribosomal loading and density for specific mRNAs. Simultaneous lysis of infected erythrocytes and parasites releases stable, intact malaria polysomes, which are then purified by cen ...[more]

PMID: 21605599

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Project description:MudPIT analysis of Plasmodium polysomes. TCA precipitated pellet from Plasmodium falciparum polysomes (~50ug) was solubilized in TRIS-HCl pH8.5 and Urea; reduced and alkylated. The protein suspension was digested overnight using Endoproteinase Lys-C followed by a second overnight digestion at 37°C using Trypsin. Formic acid (5% final) was added to stop the reactions. Sample was loaded on split-triple-phase fused-silica micro-capillary column and placed in-line with linear Velos pro ion-trap mass spectrometer (Thermo Scientific), coupled with quaternary Agilent 1260 series HPLC. Fully automated 10-step chromatography run (for a total of 20 hours) was carried out on the sample. Each full MS scan (400-1600 m/z) was followed by ten data-dependent MS/MS scans. The number of the micro scans was set to 1 both for MS and MS/MS. The dynamic exclusion settings used were as follows: repeat count 2; repeat duration 30s; exclusion list size 500 and exclusion duration 90 sec, the minimum signal threshold was set to 500. The MS/MS dataset was searched using SEQUEST (v.27; rev. 9) against a database of 72358 sequences, consisting of 5487 P. falciparum non-redundant proteins (downloaded from PlasmoDB on 2012-07-12), 30536 H. sapiens non-redundant proteins (downloaded from NCBI on 2012-08-27), 177 usual contaminants (such as human keratins, IgGs, and proteolytic enzymes), and, to estimate false discovery rates, 36179 randomized amino acid sequences derived from each non-redundant protein entry. To account for alkylation by CAM, 57 Da were added statically to cysteine residues and to account for the oxidation of methionine residues to methionine sulfoxide (that can occur as an artifact during sample processing) 16Da were added as a differential modification to methionine residue. Peptide/spectrum matches were sorted, selected using DTASelect/CONTRAST (v 1.9). Proteins had to be detected by 1 peptide with 2 independent spectra, leading to FDRs at the protein and spectral levels of 2.89% and 0.26%, respectively.

Project description:Studies of the Plasmodium falciparum transcriptome have shown that the tightly controlled progression of the parasite through the intra-erythrocytic developmental cycle (IDC) is accompanied by a continuous gene expression cascade in which most expressed genes exhibit a single transcriptional peak. Because the biochemical and cellular functions of most genes are mediated by the encoded proteins, understanding the relationship between mRNA and protein levels is crucial for inferring biological activity from transcriptional gene expression data. Although studies on other organisms show that <50% of protein abundance variation may be attributable to corresponding mRNA levels, the situation in Plasmodium is further complicated by the dynamic nature of the cyclic gene expression cascade. In this study, we simultaneously determined mRNA and protein abundance profiles for P. falciparum parasites during the IDC at 2-hour resolution based on oligonucleotide microarrays and two-dimensional differential gel electrophoresis protein gels. We find that most proteins are represented by more than one isoform, presumably because of post-translational modifications. Like transcripts, most proteins exhibit cyclic abundance profiles with one peak during the IDC, whereas the presence of functionally related proteins is highly correlated. In contrast, the abundance of most parasite proteins peaks significantly later (median 11 h) than the corresponding transcripts and often decreases slowly in the second half of the IDC. Computational modeling indicates that the considerable and varied incongruence between transcript and protein abundance may largely be caused by the dynamics of translation and protein degradation. Furthermore, we present cyclic abundance profiles also for parasite-associated human proteins and confirm the presence of five human proteins with a potential role in antioxidant defense within the parasites. Together, our data provide fundamental insights into transcript-protein relationships in P. falciparum that are important for the correct interpretation of transcriptional data and that may facilitate the improvement and development of malaria diagnostics and drug therapy.

Project description:BackgroundMalaria continues to be one of the most severe global infectious diseases, responsible for 1-2 million deaths yearly. The rapid evolution and spread of drug resistance in parasites has led to an urgent need for the development of novel antimalarial targets. Proteases are a group of enzymes that play essential roles in parasite growth and invasion. The possibility of designing specific inhibitors for proteases makes them promising drug targets. Previously, combining a comparative genomics approach and a machine learning approach, we identified the complement of proteases (degradome) in the malaria parasite Plasmodium falciparum and its sibling species 123, providing a catalog of targets for functional characterization and rational inhibitor design. Network analysis represents another route to revealing the role of proteins in the biology of parasites and we use this approach here to expand our understanding of the systems involving the proteases of P. falciparum.ResultsWe investigated the roles of proteases in the parasite life cycle by constructing a network using protein-protein association data from the STRING database 4, and analyzing these data, in conjunction with the data from protein-protein interaction assays using the yeast 2-hybrid (Y2H) system 5, blood stage microarray experiments 678, proteomics 9101112, literature text mining, and sequence homology analysis. Seventy-seven (77) out of 124 predicted proteases were associated with at least one other protein, constituting 2,431 protein-protein interactions (PPIs). These proteases appear to play diverse roles in metabolism, cell cycle regulation, invasion and infection. Their degrees of connectivity (i.e., connections to other proteins), range from one to 143. The largest protease-associated sub-network is the ubiquitin-proteasome system which is crucial for protein recycling and stress response. Proteases are also implicated in heat shock response, signal peptide processing, cell cycle progression, transcriptional regulation, and signal transduction networks.ConclusionsOur network analysis of proteases from P. falciparum uses a so-called guilt-by-association approach to extract sets of proteins from the proteome that are candidates for further study. Novel protease targets and previously unrecognized members of the protease-associated sub-systems provide new insights into the mechanisms underlying parasitism, pathogenesis and virulence.

Dataset Information

Polysome profiling of the malaria parasite Plasmodium falciparum.

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Polysome profiling of the malaria parasite Plasmodium falciparum.

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