Multimodal regulation of encystation in Giardia duodenalis revealed by deep proteomics.

Cyst formation in the parasitic protist Giardia duodenalis is critical to its transmission. Existing proteomic data quantifies only 17% of coding genes transcribed during encystation and does not cover the complete process from trophozoite to mature cyst. Using high-resolution mass spectrometry, we have quantified proteomic changes across encystation and compared this with published transcriptomic data. We reproducibly identified 3863 (64.5% of Giardia proteins) and quantified 3382 proteins (56.5% of Giardia proteins) over standard trophozoite growth (TY), during low-bile encystation priming (LB), 16 h into encystation (EC), and at cyst maturation (C). This work provides the first known expanded observation of encystation at the proteomic level and triples the coverage of previous encystation proteomes. One-third (1169 proteins) of the quantified proteome is differentially expressed in the mature cyst relative to the trophozoite, including proteasomal machinery, metabolic pathways, and secretory proteins. Changes in lipid metabolism indicated a shift in lipid species dependency during encystation. Consistent with this, we identified the first, putative lipid transporters in this species, representing the steroidogenic acute regulatory protein-related lipid transfer (StARkin), oxysterol binding protein related protein (ORP/Osh) and glycosphingolipid transfer protein (GLTP) families, and follow their differential expression over cyst formation. Lastly, we undertook correlation analyses of the transcriptome and proteome of trophozoites and cysts, and found evidence of post-transcriptional regulation of key protein classes (RNA binding proteins) and stage-specific genes (encystation markers) implicating translation-repression in encystation. We provide the most extensive proteomic analysis of encystation in Giardia to date and the first known exploration across its complete duration. This work identifies encystation as highly coordinated, involving major changes in proteostasis, metabolism and membrane dynamics, and indicates a potential role for post-transcriptional regulation, mediated through RNA-binding proteins. Together our work provides a valuable resource for Giardia research and the development of transmission-blocking anti-giardials.

Eukaryote-Conserved Methylarginine Is Absent in Diplomonads and Functionally Compensated in Giardia.

Methylation is a common posttranslational modification of arginine and lysine in eukaryotic proteins. Methylproteomes are best characterized for higher eukaryotes, where they are functionally expanded and evolved complex regulation. However, this is not the case for protist species evolved from the earliest eukaryotic lineages. Here, we integrated bioinformatic, proteomic, and drug-screening data sets to comprehensively explore the methylproteome of Giardia duodenalis-a deeply branching parasitic protist. We demonstrate that Giardia and related diplomonads lack arginine-methyltransferases and have remodeled conserved RGG/RG motifs targeted by these enzymes. We also provide experimental evidence for methylarginine absence in proteomes of Giardia but readily detect methyllysine. We bioinformatically infer 11 lysine-methyltransferases in Giardia, including highly diverged Su(var)3-9, Enhancer-of-zeste and Trithorax proteins with reduced domain architectures, and novel annotations demonstrating conserved methyllysine regulation of eukaryotic elongation factor 1 alpha. Using mass spectrometry, we identify more than 200 methyllysine sites in Giardia, including in species-specific gene families involved in cytoskeletal regulation, enriched in coiled-coil features. Finally, we use known methylation inhibitors to show that methylation plays key roles in replication and cyst formation in this parasite. This study highlights reduced methylation enzymes, sites, and functions early in eukaryote evolution, including absent methylarginine networks in the Diplomonadida. These results challenge the view that arginine methylation is eukaryote conserved and demonstrate that functional compensation of methylarginine was possible preceding expansion and diversification of these key networks in higher eukaryotes.

Effect of STAT3 inhibitor in chronic myeloid leukemia associated signaling pathway: a mathematical modeling, simulation and systems biology study.

Chronic myeloid leukemia (CML) is a hematopoietic stem-cell disorder which proliferates due to abnormal growth of basophil cells. Several proangiogenic molecules have been reported to be associated in CML progression, including the hepatocyte growth factor (HGF). However, detail mechanism about the cellular distribution and function of HGF in CML is yet to be revealed. The proliferation of hematopoietic cells are regulated by some of the growth factors like interleukin 3 (IL-3), IL-6, erythropoietin, thrombopoietin, etc. In this study IL-6 pathways have been taken into consideration which induces JAK/STAT and MAPK pathways to decipher the CML progression stages. An attempt has been made to model these pathways with the help of ordinary differential equations (ODEs) and estimating unknown parameters through fminsearch optimization algorithm. Some of the specific component like STAT3, of the pathway has been analyzed in detail and their role in CML progression has been elucidated. The roles of STAT3 inhibitors into the treatment of CML have been thoroughly studied and optimum concentration of the inhibitors have been predicted.

Parameters Involved in Autophosphorylation in Chronic Myeloid Leukemia: a Systems Biology Approach.

BACKGROUND: Chronic myeloid leukemia (CML) is a stem cell disorder characterized by the fusion of two oncogenes namely BCR and ABL with their aberrant expression. Autophosphorylation of BCR-ABL oncogenes results in proliferation of CML. The study deals with estimation of rate constant involved in each step of the cellular autophosphorylation process, which are consequently playing important roles in the proliferation of cancerous cells. MATERIALS AND METHODS: A mathematical model was proposed for autophosphorylation of BCR-ABL oncogenes utilizing ordinary differential equations to enumerate the rate of change of each responsible system component. The major difficulty to model this process is the lack of experimental data, which are needed to estimate unknown model parameters. Initial concentration data of each substrate and product for BCR-ABL systems were collected from the reported literature. All parameters were optimized through time interval simulation using the fminsearch algorithm. RESULTS: The rate of change versus time was estimated to indicate the role of each state variable that are crucial for the systems. The time wise change in concentration of substrate shows the convergence of each parameter in autophosphorylation process. CONCLUSIONS: The role of each constituent parameter and their relative time dependent variations in autophosphorylation process could be inferred.