Discovery of novel tumor suppressor p53 response elements using information theory

Whole-genome functional characterization of RE1 silencers using a modified massively parallel reporter assay

Both upregulation and downregulation by cis-regulatory elements help modulate precise gene expression. However, our understanding of repressive elements is far more limited than activating elements. To address this gap, we characterized RE1, a group of transcriptional silencers bound by REST, at genome-wide scale using a modified massively parallel reporter assay (MPRAduo). MPRAduo empirically defined a minimal binding strength of REST (REST motif-intrinsic value [m-value]), above which cofactors colocalize and silence transcription. We identified 1,500 human variants that alter RE1 silencing and found that their effect sizes are predictable when they overlap with REST-binding sites above the m-value. Additionally, we demonstrate that non-canonical REST-binding motifs exhibit silencer function only if they precisely align half sites with specific spacer lengths. Our results show mechanistic insights into RE1, which allow us to predict its activity and effect of variants on RE1, providing a paradigm for performing genome-wide functional characterization of transcription-factor-binding sites.

ROS and pentose phosphate pathway: mathematical modelling of the metabolic regulation in response to xenobiotic-induced oxidative stress and the proposed Impact of the gluconate shunt

Elevated intracellular levels of reactive oxygen species (ROS), e.g. resulting from exposure to xenobiotics, can cause severe damages. Antioxidant defence mechanisms, which involve regulation of enzyme activities, protect cells to a certain extent. Nevertheless, continuous or increased exposure can overwhelm this system resulting in an adverse cellular state. To simulate exposure scenarios and to investigate the transition to an adverse cellular state, a mathematical model for the dynamics of ROS in response to xenobiotic-induced oxidative stress has been developed. It is based on exposure experiments of human urothelial cells (RT4) to the nitrated polycyclic aromatic hydrocarbon 3-nitrobenzanthrone (3-NBA), a component of diesel engine exhaust, and takes into account the following metabolic pathways of the antioxidant defence system: glutathione redox cycle scavenging directly ROS, the pentose phosphate pathway and the gluconate shunt as NADPH supplier and the beginning of glycolysis. In addition, ROS generation due to the bioactivation of 3-NBA has been implemented. The regulation of enzyme activities plays an important role in the presented mathematical model. The in silico model consists of ordinary differential equations on the basis of enzyme kinetics and mass action for the metabolism of 3-NBA. Parameters are either estimated from performed in vitro experiments via least-squares fitting or obtained from the literature. The results underline the importance of the pentose phosphate pathway to cope with oxidative stress and suggest an important role of the gluconate shunt during low-dose exposure.

LC-MS/MS-based targeted proteomics quantitatively detects the interaction between p53 and MDM2 in breast cancer

In breast cancer, p53 could be functionally compromised by interaction with several proteins. Among those proteins, MDM2 serves as a pivotal negative regulator and counteracts p53 activation. Thus, the ability to quantitatively and accurately monitor the changes in level of p53-MDM2 interaction with disease state can enable an improved understanding of this protein-protein interaction (PPI), provide a better insight into cancer development and allow the emergence of advanced treatments. However, rare studies have evaluated the quantitative extent of PPI including p53-MDM2 interaction so far. In this study, a LC-MS/MS-based targeted proteomics assay was developed and coupled with co-immunoprecipitation (Co-IP) for the quantification of p53-MDM2 complex. A p53 antibody with the epitope residing at 156-214 residues achieved the greatest IP efficiency. 321KPLDGEYFTLQIR333 (p53) and 327ENWLPEDK334 (MDM2) were selected as surrogate peptides in the targeted analysis. Stable isotope-labeled synthetic peptides were used as internal standards. An LOQ (limit of quantification) of 2ng/mL was obtained. Then, the assay was applied to quantitatively detect total p53, total MDM2 and p53-MDM2 in breast cells and tissue samples. Western blotting was performed for a comparison. Finally, a quantitative time-course analysis in MCF-7 cells with the treatment of nutlin-3 as a PPI inhibitor was also monitored.

BIOLOGICAL SIGNIFICANCE

Proteins do not function as single entities but rather as a team player that has to communicate. Protein-protein interaction (PPI), normally by means of non-covalent contact among binary or large protein complex, is essential for many cellular processes including cancer progression. Thus, the ability to quantitatively and accurately monitor the changes in level of PPI with disease state can enable an improved understanding of PPI, provide a better insight into cancer development and allow the emergence of advanced treatments. However, rare studies have evaluated the quantitative extent of PPI so far. The major issue of current available approaches is the trade-off between sensitivity and specificity. Thus, techniques with the ability to quantify PPIs with both high sensitivity (low false-negative rate) and high specificity (low false-positive rate) are eagerly desired. Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based targeted proteomics has shown its potential to study biomolecules because of its high sensitivity, high selectivity and wide dynamic range. In this study, we made an effort to develop a LC-MS/MS-based targeted proteomics assay for the quantitative detection of p53-MDM2 interaction in breast cells and tissue samples.

Acidosis induces reprogramming of cellular metabolism to mitigate oxidative stress

Background

A variety of oncogenic and environmental factors alter tumor metabolism to serve the distinct cellular biosynthetic and bioenergetic needs present during oncogenesis. Extracellular acidosis is a common microenvironmental stress in solid tumors, but little is known about its metabolic influence, particularly when present in the absence of hypoxia. In order to characterize the extent of tumor cell metabolic adaptations to acidosis, we employed stable isotope tracers to examine how acidosis impacts glucose, glutamine, and palmitate metabolism in breast cancer cells exposed to extracellular acidosis.

Results

Acidosis increased both glutaminolysis and fatty acid β-oxidation, which contribute metabolic intermediates to drive the tricarboxylic acid cycle (TCA cycle) and ATP generation. Acidosis also led to a decoupling of glutaminolysis and novel glutathione (GSH) synthesis by repressing GCLC/GCLM expression. We further found that acidosis redirects glucose away from lactate production and towards the oxidative branch of the pentose phosphate pathway (PPP). These changes all serve to increase nicotinamide adenine dinucleotide phosphate (NADPH) production and counter the increase in reactive oxygen species (ROS) present under acidosis. The reduced novel GSH synthesis under acidosis may explain the increased demand for NADPH to recycle existing pools of GSH. Interestingly, acidosis also disconnected novel ribose synthesis from the oxidative PPP, seemingly to reroute PPP metabolites to the TCA cycle. Finally, we found that acidosis activates p53, which contributes to both the enhanced PPP and increased glutaminolysis, at least in part, through the induction of G6PD and GLS2 genes.

Conclusions

Acidosis alters the cellular metabolism of several major metabolites, which induces a significant degree of metabolic inflexibility. Cells exposed to acidosis largely rely upon mitochondrial metabolism for energy generation to the extent that metabolic intermediates are redirected away from several other critical metabolic processes, including ribose and glutathione synthesis. These alterations lead to both a decrease in cellular proliferation and increased sensitivity to ROS. Collectively, these data reveal a role for p53 in cellular metabolic reprogramming under acidosis, in order to permit increased bioenergetic capacity and ROS neutralization. Understanding the metabolic adaptations that cancer cells make under acidosis may present opportunities to generate anti-tumor therapeutic agents that are more tumor-specific.

DeGNServer: deciphering genome-scale gene networks through high performance reverse engineering analysis

Analysis of genome-scale gene networks (GNs) using large-scale gene expression data provides unprecedented opportunities to uncover gene interactions and regulatory networks involved in various biological processes and developmental programs, leading to accelerated discovery of novel knowledge of various biological processes, pathways and systems. The widely used context likelihood of relatedness (CLR) method based on the mutual information (MI) for scoring the similarity of gene pairs is one of the accurate methods currently available for inferring GNs. However, the MI-based reverse engineering method can achieve satisfactory performance only when sample size exceeds one hundred. This in turn limits their applications for GN construction from expression data set with small sample size. We developed a high performance web server, DeGNServer, to reverse engineering and decipher genome-scale networks. It extended the CLR method by integration of different correlation methods that are suitable for analyzing data sets ranging from moderate to large scale such as expression profiles with tens to hundreds of microarray hybridizations, and implemented all analysis algorithms using parallel computing techniques to infer gene-gene association at extraordinary speed. In addition, we integrated the SNBuilder and GeNa algorithms for subnetwork extraction and functional module discovery. DeGNServer is publicly and freely available online.

The next generation of transcription factor binding site prediction

Finding where transcription factors (TFs) bind to the DNA is of key importance to decipher gene regulation at a transcriptional level. Classically, computational prediction of TF binding sites (TFBSs) is based on basic position weight matrices (PWMs) which quantitatively score binding motifs based on the observed nucleotide patterns in a set of TFBSs for the corresponding TF. Such models make the strong assumption that each nucleotide participates independently in the corresponding DNA-protein interaction and do not account for flexible length motifs. We introduce transcription factor flexible models (TFFMs) to represent TF binding properties. Based on hidden Markov models, TFFMs are flexible, and can model both position interdependence within TFBSs and variable length motifs within a single dedicated framework. The availability of thousands of experimentally validated DNA-TF interaction sequences from ChIP-seq allows for the generation of models that perform as well as PWMs for stereotypical TFs and can improve performance for TFs with flexible binding characteristics. We present a new graphical representation of the motifs that convey properties of position interdependence. TFFMs have been assessed on ChIP-seq data sets coming from the ENCODE project, revealing that they can perform better than both PWMs and the dinucleotide weight matrix extension in discriminating ChIP-seq from background sequences. Under the assumption that ChIP-seq signal values are correlated with the affinity of the TF-DNA binding, we find that TFFM scores correlate with ChIP-seq peak signals. Moreover, using available TF-DNA affinity measurements for the Max TF, we demonstrate that TFFMs constructed from ChIP-seq data correlate with published experimentally measured DNA-binding affinities. Finally, TFFMs allow for the straightforward computation of an integrated TF occupancy score across a sequence. These results demonstrate the capacity of TFFMs to accurately model DNA-protein interactions, while providing a single unified framework suitable for the next generation of TFBS prediction.

The role of D-GADD45 in oxidative, thermal and genotoxic stress resistance

There is a relationship between various cellular stress factors and aging. In earlier studies, we demonstrated that overexpression of the D-GADD45 gene increases the life span of Drosophila melanogaster. In this study, we investigate the relationship between D-GADD45 activity and resistance to oxidative, genotoxic and thermal stresses as well as starvation. In most cases, flies with constitutive and conditional D-GADD45 overexpression in the nervous system were more stress-resistant than ones without overexpression. At the same time, most of the studied stress factors increased D-GADD45 expression in the wild-type strain. The lifespan-extending effect of D-GADD45 overexpression was also retained after exposure to chronic and acute gamma-irradiation, with doses of 40 сGy and 30 Gy, respectively. However, knocking out D-GADD45 resulted in a significant reduction in lifespan, lack of radiation hormesis and radioadaptive response. A dramatic decrease in the spontaneous level of D-GADD45 expression was observed in the nervous system as age progressed, which may be one of the causes of the age-related deterioration of organismal stress resistance. Thus, D-GADD45 expression is activated by most of the studied stress factors, and D-GADD45 overexpression resulted in an increase of stress resistance.

The Regulation of Aging and Longevity: A New and Complex Role of p53

p53 plays a critical role in tumor suppression. As a transcription factor, in response to stress signals, p53 regulates its target genes and initiates stress responses, including cell cycle arrest, apoptosis, and/or senescence, to exert its function in tumor suppression. Emerging evidence has suggested that p53 is also an important but complex player in the regulation of aging and longevity in worms, flies, mice, and humans. Whereas p53 accelerates the aging process and shortens life span in some contexts, p53 can also extend life span in some other contexts. Thus, p53 appears to regulate aging and longevity in a context-dependent manner. Here, the authors review some recent advances in the study of the role of p53 in the regulation of aging and longevity in both invertebrate and vertebrate models. Furthermore, they discuss the potential mechanisms by which p53 regulates aging and longevity, including the p53 regulation of insulin/TOR signaling, stem/progenitor cells, and reactive oxygen species.

Gene-specific transcription activation via long-range allosteric shape-shifting

How is specificity transmitted over long distances at the molecular level? REs (regulatory elements) are often far from transcription start sites. In the present review we discuss possible mechanisms to explain how information from specific REs is conveyed to the basal transcription machinery through TFs (transcription factors) and the Mediator complex. We hypothesize that this occurs through allosteric pathways: binding of a TF to a RE results in changes in the AD (activation domain) of the TF, which binds to Mediator and alters the distribution of the Mediator conformations, thereby affecting transcription initiation/activation. We argue that Mediator is formed by highly disordered proteins with large densely packed interfaces that make efficient long-range signal propagation possible. We suggest two possible general mechanisms for Mediator action: one in which Mediator influences PIC (pre-initiation complex) assembly and transcription initiation, and another in which Mediator exerts its effect on the already assembled but stalled transcription complex. We summarize (i) relevant information from the literature about Mediator composition, organization and structure; (ii) Mediator interaction partners and their effect on Mediator conformation, function and correlation to the RNA Pol II (polymerase II) CTD (C-terminal domain) phosphorylation; and (iii) propose that different allosteric signal propagation pathways in Mediator relate to PIC assembly and polymerase activation of the stalled transcription complex. The emerging picture provides for the first time a mechanistic view of allosteric signalling from the RE sequence to transcription activation, and an insight into how gene specificity and signal transmission can take place in transcription initiation.

Redox control and interplay between p53 isoforms: roles in the regulation of basal p53 levels, cell fate, and senescence

The p53 tumor suppressor protein has achieved stardom in molecular oncology owing to frequent inactivation in a large range of cancers. Known as a factor activated by multiple forms of stress and causing a broad suppressive response to DNA damage, its regulation and functions in basal (non-stress) conditions has received relatively little attention. We summarize recent findings highlighting roles of p53 in physiological processes such as stem cell maintenance, development, aging and senescence, and regulation of basal oxidative cell metabolism. We suggest that these properties are regulated through two integrated biochemical systems: the redox-sensing capacity of the p53 protein (due to its structural features and its regulation by redox factors such as thioredoxin, metallothioneins, or the redox-repair enzyme APE1/ref-1), and the expression of p53 as multiple isoforms with antagonist effects. We propose that interactions between p53 and its isoforms Δ40p53 or Δ133p53 play critical roles in intracellular signaling by reactive oxygen species. We also discuss evidence that p53 controls energy production by repressing glycolysis and enhancing mitochondrial oxidative metabolism. Together, these mechanisms suggest that p53 acts not only as a "guardian of the genome" against DNA damage but also as a finely-tuned regulator of redox-dependent physiological processes.

Mitochondrial liaisons of p53

Mitochondria play a central role in cell survival and cell death. While producing the bulk of intracellular ATP, mitochondrial respiration represents the most prominent source of harmful reactive oxygen species. Mitochondria participate in many anabolic pathways, including cholesterol and nucleotide biosynthesis, yet also control multiple biochemical cascades that contribute to the programmed demise of cells. The tumor suppressor protein p53 is best known for its ability to orchestrate a transcriptional response to stress that can have multiple outcomes, including cell cycle arrest and cell death. p53-mediated tumor suppression, however, also involves transcription-independent mechanisms. Cytoplasmic p53 can physically interact with members of the BCL-2 protein family, thereby promoting mitochondrial membrane permeabilization. Moreover, extranuclear p53 can suppress autophagy, a major prosurvival mechanism that is activated in response to multiple stress conditions. Thirty years have passed since its discovery, and p53 has been ascribed with an ever-increasing number of functions. For instance, p53 has turned out to influence the cell's redox status, by transactivating either anti- or pro-oxidant factors, and to regulate the metabolic switch between glycolysis and aerobic respiration. In this review, we will analyze the mechanisms by which p53 affects the balance between the vital and lethal functions of mitochondria.

p53 Protects lung cancer cells against metabolic stress

The preferential use of aerobic glycolysis for energy production by cancer cells, a phenomenon known as the 'Warburg effect', is well recognized and is being considered for therapeutic applications. However, whether inhibition of glycolysis will be effective in all types of cancer is unclear. The current study shows that a glycolytic inhibitor, 2-deoxy-D-glucose (2DG), exhibits the cytotoxic effect on non-small cell lung cancer in a p53-dependent manner. 2DG significantly inhibits ATP production in p53-deficient lung cancer cells (H358) but not in p53-wt cells (A549). In contrast to p53-wt cells, p53-defective cells are unable to compensate for their need of energy via oxidative phosphorylation (OXPHOS) when glycolysis is inhibited. In the presence of p53, increased ROS from OXPHOS increases the expression of p53 target genes known to modulate metabolism, including synthesis of cytochrome c oxidase 2 (SCO2) and TP53-induced glycolysis and apoptosis regulator (TIGAR). Importantly, 2DG selectively induces the expression of the antioxidant enzymes manganese superoxide dismutase (MnSOD) and glutathione peroxidase 1 (GPx1) in a p53-dependent manner. The results demonstrate that the killing of cancer cells by the inhibitor of glycolysis is more efficient in cancer cells without functional p53 and that p53 protects against metabolic stress by up-regulation of oxidative phosphorylation and modulation of antioxidants.

Discovery and preclinical validation of salivary transcriptomic and proteomic biomarkers for the non-invasive detection of breast cancer

Background

A sensitive assay to identify biomarkers using non-invasively collected clinical specimens is ideal for breast cancer detection. While there are other studies showing disease biomarkers in saliva for breast cancer, our study tests the hypothesis that there are breast cancer discriminatory biomarkers in saliva using de novo discovery and validation approaches. This is the first study of this kind and no other study has engaged a de novo biomarker discovery approach in saliva for breast cancer detection. In this study, a case-control discovery and independent preclinical validations were conducted to evaluate the performance and translational utilities of salivary transcriptomic and proteomic biomarkers for breast cancer detection.

Methodology/Principal Findings

Salivary transcriptomes and proteomes of 10 breast cancer patients and 10 matched controls were profiled using Affymetrix HG-U133-Plus-2.0 Array and two-dimensional difference gel electrophoresis (2D-DIGE), respectively. Preclinical validations were performed to evaluate the discovered biomarkers in an independent sample cohort of 30 breast cancer patients and 63 controls using RT-qPCR (transcriptomic biomarkers) and quantitative protein immunoblot (proteomic biomarkers). Transcriptomic and proteomic profiling revealed significant variations in salivary molecular biomarkers between breast cancer patients and matched controls. Eight mRNA biomarkers and one protein biomarker, which were not affected by the confounding factors, were pre-validated, yielding an accuracy of 92% (83% sensitive, 97% specific) on the preclinical validation sample set.

Conclusions

Our findings support that transcriptomic and proteomic signatures in saliva can serve as biomarkers for the non-invasive detection of breast cancer. The salivary biomarkers possess discriminatory power for the detection of breast cancer, with high specificity and sensitivity, which paves the way for prediction model validation study followed by pivotal clinical validation.

A brief review of molecular information theory

The idea that we could build molecular communications systems can be advanced by investigating how actual molecules from living organisms function. Information theory provides tools for such an investigation. This review describes how we can compute the average information in the DNA binding sites of any genetic control protein and how this can be extended to analyze its individual sites. A formula equivalent to Claude Shannon's channel capacity can be applied to molecular systems and used to compute the efficiency of protein binding. This efficiency is often 70% and a brief explanation for that is given. The results imply that biological systems have evolved to function at channel capacity, which means that we should be able to build molecular communications that are just as robust as our macroscopic ones.

70% efficiency of bistate molecular machines explained by information theory, high dimensional geometry and evolutionary convergence

The relationship between information and energy is key to understanding biological systems. We can display the information in DNA sequences specifically bound by proteins by using sequence logos, and we can measure the corresponding binding energy. These can be compared by noting that one of the forms of the second law of thermodynamics defines the minimum energy dissipation required to gain one bit of information. Under the isothermal conditions that molecular machines function this is Emin = Kb T ln 2 joules per bit (kB is Boltzmann's constant and T is the absolute temperature). Then an efficiency of binding can be computed by dividing the information in a logo by the free energy of binding after it has been converted to bits. The isothermal efficiencies of not only genetic control systems, but also visual pigments are near 70%. From information and coding theory, the theoretical efficiency limit for bistate molecular machines is ln 2=0.6931. Evolutionary convergence to maximum efficiency is limited by the constraint that molecular states must be distinct from each other. The result indicates that natural molecular machines operate close to their information processing maximum (the channel capacity), and implies that nanotechnology can attain this goal.

Mechanisms of transcription factor selectivity

The initiation of transcription is regulated by transcription factors (TFs) binding to DNA response elements (REs). How do TFs recognize specific binding sites among the many similar ones available in the genome? Recent research has illustrated that even a single nucleotide substitution can alter the selective binding of TFs to coregulators, that prior binding events can lead to selective DNA binding, and that selectivity is influenced by the availability of binding sites in the genome. Here, we combine structural insights with recent genomics screens to address the problem of TF-DNA interaction specificity. The emerging picture of selective binding site sequence recognition and TF activation involves three major factors: the cellular network, protein and DNA as dynamic conformational ensembles and the tight packing of multiple TFs and coregulators on stretches of regulatory DNA. The classification of TF recognition mechanisms based on these factors impacts our understanding of how transcription initiation is regulated.

Data Compression Concepts and Algorithms and their Applications to Bioinformatics

Data compression at its base is concerned with how information is organized in data. Understanding this organization can lead to efficient ways of representing the information and hence data compression. In this paper we review the ways in which ideas and approaches fundamental to the theory and practice of data compression have been used in the area of bioinformatics. We look at how basic theoretical ideas from data compression, such as the notions of entropy, mutual information, and complexity have been used for analyzing biological sequences in order to discover hidden patterns, infer phylogenetic relationships between organisms and study viral populations. Finally, we look at how inferred grammars for biological sequences have been used to uncover structure in biological sequences.

p53 and metabolism

Although metabolic alterations have been observed in cancer for almost a century, only recently have the mechanisms underlying these changes been identified and the importance of metabolic transformation realized. p53 has been shown to respond to metabolic changes and to influence metabolic pathways through several mechanisms. The contributions of these activities to tumour suppression are complex and potentially rather surprising: some reflect the function of basal p53 levels that do not require overt activation and others might even promote, rather than inhibit, tumour progression.

Cooperativity dominates the genomic organization of p53-response elements: a mechanistic view

p53-response elements (p53-REs) are organized as two repeats of a palindromic DNA segment spaced by 0 to 20 base pairs (bp). Several experiments indicate that in the vast majority of the human p53-REs there are no spacers between the two repeats; those with spacers, particularly with sizes beyond two nucleotides, are rare. This raises the question of what it indicates about the factors determining the p53-RE genomic organization. Clearly, given the double helical DNA conformation, the orientation of two p53 core domain dimers with respect to each other will vary depending on the spacer size: a small spacer of 0 to 2 bps will lead to the closest p53 dimer-dimer orientation; a 10-bp spacer will locate the p53 dimers on the same DNA face but necessitate DNA looping; while a 5-bp spacer will position the p53 dimers on opposite DNA faces. Here, via conformational analysis we show that when there are 0-2 bp spacers, p53-DNA binding is cooperative; however, cooperativity is greatly diminished when there are spacers with sizes beyond 2 bp. Cooperative binding is broadly recognized to be crucial for biological processes, including transcriptional regulation. Our results clearly indicate that cooperativity of the p53-DNA association dominates the genomic organization of the p53-REs, raising questions of the structural organization and functional roles of p53-REs with larger spacers. We further propose that a dynamic landscape scenario of p53 and p53-REs can better explain the selectivity of the degenerate p53-REs. Our conclusions bear on the evolutionary preference of the p53-RE organization and as such, are expected to have broad implications to other multimeric transcription factor response element organization.

Homeostatic functions of the p53 tumor suppressor: regulation of energy metabolism and antioxidant defense

The p53 tumor suppressor plays pivotal role in the organism by supervising strict compliance of individual cells to needs of the whole organisms. It has been widely accepted that p53 acts in response to stresses and abnormalities in cell physiology by mobilizing the repair processes or by removing the diseased cells through initiating the cell death programs. Recent studies, however, indicate that even under normal physiological conditions certain activities of p53 participate in homeostatic regulation of metabolic processes and that these activities are important for prevention of cancer. These novel functions of p53 help to align metabolic processes with the proliferation and energy status, to maintain optimal mode of glucose metabolism and to boost the energy efficient mitochondrial respiration in response to ATP deficiency. Additional activities of p53 in non-stressed cells tune up the antioxidant defense mechanisms reducing the probability of mutations caused by DNA oxidation under conditions of daily stresses. The deficiency in the p53-mediated regulation of glycolysis and mitochondrial respiration greatly accounts for the deficient respiration of the predominance of aerobic glycolysis in cancer cells (the Warburg effect), while the deficiency in the p53-modulated antioxidant defense mechanisms contributes to mutagenesis and additionally boosts the carcinogenesis process.