Plasmodium falciparum CRK4 directs continuous rounds of DNA replication during schizogony.

: Plasmodium parasites, the causative agents of malaria, have evolved a unique cell division cycle in the clinically relevant asexual blood stage of infection(1). DNA replication commences approximately halfway through the intracellular development following invasion and parasite growth. The schizont stage is associated with multiple rounds of DNA replication and nuclear division without cytokinesis, resulting in a multinucleated cell. Nuclei divide asynchronously through schizogony, with only the final round of DNA replication and segregation being synchronous and coordinated with daughter cell assembly(2,3). However, the control mechanisms for this divergent mode of replication are unknown. Here, we show that the Plasmodium-specific kinase PfCRK4 is a key cell-cycle regulator that orchestrates multiple rounds of DNA replication throughout schizogony in Plasmodium falciparum. PfCRK4 depletion led to a complete block in nuclear division and profoundly inhibited DNA replication. Quantitative phosphoproteomic profiling identified a set of PfCRK4-regulated phosphoproteins with greatest functional similarity to CDK2 substrates, particularly proteins involved in the origin of replication firing. PfCRK4 was required for initial and subsequent rounds of DNA replication during schizogony and, in addition, was essential for development in the mosquito vector. Our results identified an essential S-phase promoting factor of the unconventional P. falciparum cell cycle. PfCRK4 is required for both a prolonged period of the intraerythrocytic stage of Plasmodium infection, as well as for transmission, revealing a broad window for PfCRK4-targeted chemotherapeutics.<br/

Quantitative Proteomic and Interaction Network Analysis of Cisplatin Resistance in HeLa Cells

Cisplatin along with other platinum based drugs are some of the most widely used chemotherapeutic agents. However drug resistance is a major problem for the successful chemotherapeutic treatment of cancer. Current evidence suggests that drug resistance is a multifactorial problem due to changes in the expression levels and activity of a wide number of proteins. A majority of the studies to date have quantified mRNA levels between drug resistant and drug sensitive cell lines. Unfortunately mRNA levels do not always correlate with protein expression levels due to post-transcriptional changes in protein abundance. Therefore global quantitative proteomics screens are needed to identify the protein targets that are differentially expressed in drug resistant cell lines. Here we employ a quantitative proteomics technique using stable isotope labeling with amino acids in cell culture (SILAC) coupled with mass spectrometry to quantify changes in protein levels between cisplatin resistant (HeLa/CDDP) and sensitive HeLa cells in an unbiased fashion. A total of 856 proteins were identified and quantified, with 374 displaying significantly altered expression levels between the cell lines. Expression level data was then integrated with a network of protein-protein interactions, and biological pathways to obtain a systems level view of proteome changes which occur with cisplatin resistance. Several of these proteins have been previously implicated in resistance towards platinum-based and other drugs, while many represent new potential markers or therapeutic targets

The Comprehensive Native Interactome of a Fully Functional Tagged Prion Protein

The enumeration of the interaction partners of the cellular prion protein, PrPC, may help clarifying its elusive molecular function. Here we added a carboxy proximal myc epitope tag to PrPC. When expressed in transgenic mice, PrPmyc carried a GPI anchor, was targeted to lipid rafts, and was glycosylated similarly to PrPC. PrPmyc antagonized the toxicity of truncated PrP, restored prion infectibility of PrPC-deficient mice, and was physically incorporated into PrPSc aggregates, indicating that it possessed all functional characteristics of genuine PrPC. We then immunopurified myc epitope-containing protein complexes from PrPmyc transgenic mouse brains. Gentle differential elution with epitope-mimetic decapeptides, or a scrambled version thereof, yielded 96 specifically released proteins. Quantitative mass spectrometry with isotope-coded tags identified seven proteins which co-eluted equimolarly with PrPC and may represent component of a multiprotein complex. Selected PrPC interactors were validated using independent methods. Several of these proteins appear to exert functions in axomyelinic maintenance

Estrogen Receptor Alpha Is Expressed in Mesenteric Mesothelial Cells and Is Internalized in Caveolae upon Freund's Adjuvant Treatment

Transformation of epithelial cells into connective tissue cells (epithelial-mesenchymal transition, EMT) is a complex mechanism involved in tumor metastasis, and in normal embryogenesis, while type II EMT is mainly associated with inflammatory events and tissue regenaration. In this study we examined type II EMT at the ultrastructural and molecular level during the inflammatory process induced by Freund's adjuvant treatment in rat mesenteric mesothelial cells. We found that upon the inflammatory stimulus mesothelial cells lost contact with the basal lamina and with each other, and were transformed into spindle-shaped cells. These morphological changes were accompanied by release of interleukins IL-1alpha, -1beta and IL-6 and by secretion of transforming growth factor beta (TGF-beta) into the peritoneal cavity. Mesothelial cells also expressed estrogen receptor alpha (ER-alpha) as shown by immunolabeling at the light and electron microscopical levels, as well as by quantitative RT-PCR. The mRNA level of ER-alpha showed an inverse correlation with the secretion of TGF-beta. At the cellular and subcellular levels ER-alpha was colocalized with the coat protein caveolin-1 and was found in the plasma membrane of mesothelial cells, in caveolae close to multivesicular bodies (MVBs) or in the membrane of these organelles, suggesting that ER-alpha is internalized via caveola-mediated endocytosis during inflammation. We found asymmetric, thickened, electron dense areas on the limiting membrane of MVBs (MVB plaques) indicating that these sites may serve as platforms for collecting and organizing regulatory proteins. Our morphological observations and biochemical data can contribute to form a potential model whereby ER-alpha and its caveola-mediated endocytosis might play role in TGF-beta induced type II EMT in vivo

Systems Biology of the qa Gene Cluster in Neurospora crassa

An ensemble of genetic networks that describe how the model fungal system, Neurospora crassa, utilizes quinic acid (QA) as a sole carbon source has been identified previously. A genetic network for QA metabolism involves the genes, qa-1F and qa-1S, that encode a transcriptional activator and repressor, respectively and structural genes, qa-2, qa-3, qa-4, qa-x, and qa-y. By a series of 4 separate and independent, model-guided, microarray experiments a total of 50 genes are identified as QA-responsive and hypothesized to be under QA-1F control and/or the control of a second QA-responsive transcription factor (NCU03643) both in the fungal binuclear Zn(II)2Cys6 cluster family. QA-1F regulation is not sufficient to explain the quantitative variation in expression profiles of the 50 QA-responsive genes. QA-responsive genes include genes with products in 8 mutually connected metabolic pathways with 7 of them one step removed from the tricarboxylic (TCA) Cycle and with 7 of them one step removed from glycolysis: (1) starch and sucrose metabolism; (2) glycolysis/glucanogenesis; (3) TCA Cycle; (4) butanoate metabolism; (5) pyruvate metabolism; (6) aromatic amino acid and QA metabolism; (7) valine, leucine, and isoleucine degradation; and (8) transport of sugars and amino acids. Gene products both in aromatic amino acid and QA metabolism and transport show an immediate response to shift to QA, while genes with products in the remaining 7 metabolic modules generally show a delayed response to shift to QA. The additional QA-responsive cutinase transcription factor-1β (NCU03643) is found to have a delayed response to shift to QA. The series of microarray experiments are used to expand the previously identified genetic network describing the qa gene cluster to include all 50 QA-responsive genes including the second transcription factor (NCU03643). These studies illustrate new methodologies from systems biology to guide model-driven discoveries about a core metabolic network involving carbon and amino acid metabolism in N. crassa

Evaluating genetic markers and neurobiochemical analytes for fluoxetine response using a panel of mouse inbred strains

RationaleIdentification of biomarkers that establish diagnosis or treatment response is critical to the advancement of research and management of patients with depression.ObjectiveOur goal was to identify biomarkers that can potentially assess fluoxetine response and risk to poor treatment outcome.MethodsWe measured behavior, gene expression, and the levels of 36 neurobiochemical analytes across a panel of genetically diverse mouse inbred lines after chronic treatment with water or fluoxetine.ResultsGlyoxylase 1 (GLO1) and guanine nucleotide-binding protein 1 (GNB1) mostly account for baseline anxiety-like and depressive-like behavior, indicating a common biological link between depression and anxiety. Fluoxetine-induced biochemical alterations discriminated positive responders, while baseline neurobiochemical differences differentiated negative responders (p < 0.006). Results show that glial fibrillary acidic protein, S100 beta protein, GLO1, and histone deacetylase 5 contributed most to fluoxetine response. These proteins are linked within a cellular growth/proliferation pathway, suggesting the involvement of cellular genesis in fluoxetine response. Furthermore, a candidate genetic locus that associates with baseline depressive-like behavior contains a gene that encodes for cellular proliferation/adhesion molecule (Cadm1), supporting a genetic basis for the role of neuro/gliogenesis in depression.ConclusionWe provided a comprehensive analysis of behavioral, neurobiochemical, and transcriptome data across 30 mouse inbred strains that has not been accomplished before. We identified biomarkers that influence fluoxetine response, which, altogether, implicate the importance of cellular genesis in fluoxetine treatment. More broadly, this approach can be used to assess a wide range of drug response phenotypes that are challenging to address in human samples.Electronic supplementary materialThe online version of this article (doi:10.1007/s00213-011-2574-z) contains supplementary material, which is available to authorized users

Studying protein–protein affinity and immobilized ligand–protein affinity interactions using MS-based methods

This review discusses the most important current methods employing mass spectrometry (MS) analysis for the study of protein affinity interactions. The methods are discussed in depth with particular reference to MS-based approaches for analyzing protein–protein and protein–immobilized ligand interactions, analyzed either directly or indirectly. First, we introduce MS methods for the study of intact protein complexes in the gas phase. Next, pull-down methods for affinity-based analysis of protein–protein and protein–immobilized ligand interactions are discussed. Presently, this field of research is often called interactomics or interaction proteomics. A slightly different approach that will be discussed, chemical proteomics, allows one to analyze selectivity profiles of ligands for multiple drug targets and off-targets. Additionally, of particular interest is the use of surface plasmon resonance technologies coupled with MS for the study of protein interactions. The review addresses the principle of each of the methods with a focus on recent developments and the applicability to lead compound generation in drug discovery as well as the elucidation of protein interactions involved in cellular processes. The review focuses on the analysis of bioaffinity interactions of proteins with other proteins and with ligands, where the proteins are considered as the bioactives analyzed by MS