Piotr Zielenkiewicz

Epigenetic Reactivation of Tumor Suppressor Genes by a Novel Small-Molecule Inhibitor of Human DNA Methyltransferases

DNA methylation regulates gene expression in normal and malignant cells. The possibility to reactivate epigenetically silenced genes has generated considerable interest in the development of DNA methyltransferase inhibitors. Here, we provide a detailed characterization of RG108, a novel small molecule that effectively blocked DNA methyltransferases in vitro and did not cause covalent enzyme trapping in human cell lines. Incubation of cells with low micromolar concentrations of the compound resulted in significant demethylation of genomic DNA without any detectable toxicity. Intriguingly, RG108 caused demethylation and reactivation of tumor suppressor genes, but it did not affect the methylation of centromeric satellite sequences. These results establish RG108 as a DNA methyltransferase inhibitor with fundamentally novel characteristics that will be particularly useful for the experimental modulation of epigenetic gene regulation.

The effect of transcription and translation initiation frequencies on the stochastic fluctuations in prokaryotic gene expression.

The kinetics of prokaryotic gene expression has been modelled by the Monte Carlo computer simulation algorithm of Gillespie, which allowed the study of random fluctuations in the number of protein molecules during gene expression. The model, when applied to the simulation of LacZ gene expression, is in good agreement with experimental data. The influence of the frequencies of transcription and translation initiation on random fluctuations in gene expression has been studied in a number of simulations in which promoter and ribosome binding site effectiveness has been changed in the range of values reported for various prokaryotic genes. We show that the genes expressed from strong promoters produce the protein evenly, with a rate that does not vary significantly among cells. The genes with very weak promoters express the protein in “bursts” occurring at random time intervals. Therefore, if the low level of gene expression results from the low frequency of transcription initiation, huge fluctuations arise. In contrast, the protein can be produced with a low and uniform rate if the gene has a strong promoter and a slow rate of ribosome binding (a weak ribosome binding site). The implications of these findings for the expression of regulatory proteins are discussed.

Influence of macromolecular crowding on protein-protein association rates--a Brownian dynamics study.

The high total concentration of macromolecules, often referred to as macromolecular crowding, is one of the characteristic features of living cells. Macromolecular crowding influences interactions between many types of macromolecules, with consequent effects on, among others, the rates of reactions occurring in the cell. Simulations to study the influence of crowding on macromolecular association rate were performed using a modified Brownian dynamics protocol. The calculated values of the time-dependent self-diffusion coefficients in different crowding conditions are in a very good agreement with those obtained by other authors. Simulations of the complex formation between the monoclonal antibody HyHEL-5 and its antigen hen egg lysozyme, both represented at atomic level detail, show that the calculated association rates strongly depend on the volume excluded by crowding. The rate obtained for the highest concentration of crowding particles is greater than twofold higher than the rate for proteins without crowding.

A Comprehensive, Quantitative, and Genome-Wide Model of Translation

Translation is still poorly characterised at the level of individual proteins and its role in regulation of gene expression has been constantly underestimated. To better understand the process of protein synthesis we developed a comprehensive and quantitative model of translation, characterising protein synthesis separately for individual genes. The main advantage of the model is that basing it on only a few datasets and general assumptions allows the calculation of many important translational parameters, which are extremely difficult to measure experimentally. In the model, each gene is attributed with a set of translational parameters, namely the absolute number of transcripts, ribosome density, mean codon translation time, total transcript translation time, total time required for translation initiation and elongation, translation initiation rate, mean mRNA lifetime, and absolute number of proteins produced by gene transcripts. Most parameters were calculated based on only one experimental dataset of genome-wide ribosome profiling. The model was implemented in Saccharomyces cerevisiae, and its results were compared with available data, yielding reasonably good correlations. The calculated coefficients were used to perform a global analysis of translation in yeast, revealing some interesting aspects of the process. We have shown that two commonly used measures of translation efficiency – ribosome density and number of protein molecules produced – are affected by two distinct factors. High values of both measures are caused, i.a., by very short times of translation initiation, however, the origins of initiation time reduction are completely different in both cases. The model is universal and can be applied to any organism, if the necessary input data are available. The model allows us to better integrate transcriptomic and proteomic data. A few other possibilities of the model utilisation are discussed concerning the example of the yeast system.

Establishment and functional validation of a structural homology model for human DNA methyltransferase 1

Changes in DNA methylation patterns play an important role in tumorigenesis. The DNA methyltransferase 1 (DNMT1) protein represents a major DNA methyltransferase activity in human cells and is therefore a prominent target for experimental cancer therapies. However, there are only few available inhibitors and their high toxicity and low specificity have so far precluded their broad use in chemotherapy. Based on the strong conservation of catalytic DNA methyltransferase domains we have used a homology modeling approach to determine the three-dimensional structure of the DNMT1 catalytic domain. Our results suggest an overall structural conservation with other DNA methyltransferases but also indicate local conformational differences. To prove the validity of our model we used it as a template to design a novel derivative of the known DNA methyltransferase inhibitor 5-azacytidine. The resulting compound (N4-fluoroacetyl-5-azacytidine) functioned as an efficient inhibitor of DNA methylation in human tumor cell lines and also provides novel opportunities for pharmacological applications.

Discovery of novel potent ΔF508-CFTR correctors that target the nucleotide binding domain

The deletion of Phe508 (ΔF508) in the first nucleotide binding domain (NBD1) of CFTR is the most common mutation associated with cystic fibrosis. The ΔF508‐CFTR mutant is recognized as improperly folded and targeted for proteasomal degradation. Based on molecular dynamics simulation results, we hypothesized that interaction between ΔF508‐NBD1 and housekeeping proteins prevents ΔF508‐CFTR delivery to the plasma membrane. Based on this assumption we applied structure‐based virtual screening to identify new low‐molecular‐weight compounds that should bind to ΔF508‐NBD1 and act as protein–protein interaction inhibitors. Using different functional assays for CFTR activity, we demonstrated that in silico‐selected compounds induced functional expression of ΔF508‐CFTR in transfected HeLa cells, human bronchial CF cells in primary culture, and in the nasal epithelium of homozygous ΔF508‐CFTR mice. The proposed compounds disrupt keratin8‐ΔF508‐CFTR interaction in ΔF508‐CFTR HeLa cells. Structural analysis of ΔF508‐NBD1 in the presence of these compounds suggests their binding to NBD1. We conclude that our strategy leads to the discovery of new compounds that are among the most potent correctors of ΔF508‐CFTR trafficking defect known to date.

Models of protein crystal growth.

The growth of large and well ordered protein crystals remains the major obstacle in protein structure determination by means of X-ray crystallography. One of the reasons is that the physico-chemical aspect of protein crystallization process is not understood. This article reviews efforts towards formulation of models that could become theoretical frameworks for the interpretation of voluminous experimental data collected on protein crystal growth. Special attention is devoted to microscopic models that recognize the role of the shape of protein molecules in crystal formation.

In Silico Identification of Plant miRNAs in Mammalian Breast Milk Exosomes - A Small Step Forward?

MicroRNAs (miRNAs) are a class of small RNA molecules that regulate gene expression by inhibiting the protein translation or targeting the mRNA cleavage. They play many important roles in living organism cells; however, the knowledge on miRNAs functions has become more extensive upon their identification in biological fluids and recent reports on plant-origin miRNAs abundance in human plasma and serum. Considering these findings, we performed a rigorous bioinformatics analysis of publicly available, raw data from high-throughput sequencing studies on miRNAs composition in human and porcine breast milk exosomes to identify the fraction of food-derived miRNAs. Several processing and filtering steps were applied to increase the accuracy, and to avoid false positives. Through aforementioned analysis, 35 and 17 miRNA species, belonging to 25 and 11 MIR families, were identified, respectively. In the human samples the highest abundance levels yielded the ath-miR166a, pab-miR951, ptc-miR472a and bdi-miR168, while in the porcine breast milk exosomes, the zma-miR168a, zma-miR156a and ath-miR166a have been identified in the largest amounts. The consensus prediction and annotation of potential human targets for select plant miRNAs suggest that the aforementioned molecules may interact with mRNAs coding several transcription factors, protein receptors, transporters and immune-related proteins, thus potentially influencing human organism. Taken together, the presented analysis shows proof of abundant plant miRNAs in mammal breast milk exosomes, pointing at the same time to the new possibilities arising from this discovery.

Nicotiana tabacum Osmotic Stress-activated Kinase Is Regulated by Phosphorylation on Ser-154 and Ser-158 in the Kinase Activation Loop

NtOSAK (Nicotiana tabacum osmotic stress-activated protein kinase), a member of the SnRK2 subfamily, is activated rapidly in response to hyperosmotic stress. Our previous results as well as data presented by others indicate that phosphorylation is involved in activation of SnRK2 kinases. Here, we have mapped the regulatory phosphorylation sites of NtOSAK by mass spectrometry with collision-induced peptide fragmentation. We show that active NtOSAK, isolated from NaCl-treated tobacco BY-2 cells, is phosphorylated on Ser-154 and Ser-158 in the kinase activation loop. Prediction of the NtOSAK three-dimensional structure indicates that phosphorylation of Ser-154 and Ser-158 triggers changes in enzyme conformation resulting in its activation. The involvement of Ser-154 and Ser-158 phosphorylation in regulation of NtOSAK activity was confirmed by site-directed mutagenesis of NtOSAK expressed in bacteria and in maize protoplasts. Our data reveal that phosphorylation of Ser-158 is essential for NtOSAK activation, whereas phosphorylation of Ser-154 most probably facilitates Ser-158 phosphorylation. The time course of NtOSAK phosphorylation on Ser-154 and Ser-158 in BY-2 cells subjected to osmotic stress correlates with NtOSAK activity, indicating that NtOSAK is regulated by reversible phosphorylation of these residues in vivo. Importantly, Ser-154 and Ser-158 are conserved in all SnRK2 subfamily members, suggesting that phosphorylation at these sites may be a general mechanism for SnRK2 activation.

A Specialized Histone H1 Variant Is Required for Adaptive Responses to Complex Abiotic Stress and Related DNA Methylation in Arabidopsis

Stress-inducible linker histone variant is required for adaptive response of Arabidopsis to complex environmental stress. Linker (H1) histones play critical roles in chromatin compaction in higher eukaryotes. They are also the most variable of the histones, with numerous nonallelic variants cooccurring in the same cell. Plants contain a distinct subclass of minor H1 variants that are induced by drought and abscisic acid and have been implicated in mediating adaptive responses to stress. However, how these variants facilitate adaptation remains poorly understood. Here, we show that the single Arabidopsis (Arabidopsis thaliana) stress-inducible variant H1.3 occurs in plants in two separate and most likely autonomous pools: a constitutive guard cell-specific pool and a facultative environmentally controlled pool localized in other tissues. Physiological and transcriptomic analyses of h1.3 null mutants demonstrate that H1.3 is required for both proper stomatal functioning under normal growth conditions and adaptive developmental responses to combined light and water deficiency. Using fluorescence recovery after photobleaching analysis, we show that H1.3 has superfast chromatin dynamics, and in contrast to the main Arabidopsis H1 variants H1.1 and H1.2, it has no stable bound fraction. The results of global occupancy studies demonstrate that, while H1.3 has the same overall binding properties as the main H1 variants, including predominant heterochromatin localization, it differs from them in its preferences for chromatin regions with epigenetic signatures of active and repressed transcription. We also show that H1.3 is required for a substantial part of DNA methylation associated with environmental stress, suggesting that the likely mechanism underlying H1.3 function may be the facilitation of chromatin accessibility by direct competition with the main H1 variants.