Ines Heiland

Role of Sirtuins in Lifespan Regulation is Linked to Methylation of Nicotinamide

Sirtuins, a family of histone deacetylases, have a fiercely debated role in regulating lifespan. In contrast with recent observations, here we find that overexpression of sir-2.1, the ortholog of mammalian SirT1, does extend Caenorhabditis elegans lifespan. Sirtuins mandatorily convert NAD(+) into nicotinamide (NAM). We here find that NAM and its metabolite, 1-methylnicotinamide (MNA), extend C. elegans lifespan, even in the absence of sir-2.1. We identify a previously unknown C. elegans nicotinamide-N-methyltransferase, encoded by a gene now named anmt-1, to generate MNA from NAM. Disruption and overexpression of anmt-1 have opposing effects on lifespan independent of sirtuins, with loss of anmt-1 fully inhibiting sir-2.1-mediated lifespan extension. MNA serves as a substrate for a newly identified aldehyde oxidase, GAD-3, to generate hydrogen peroxide, which acts as a mitohormetic reactive oxygen species signal to promote C. elegans longevity. Taken together, sirtuin-mediated lifespan extension depends on methylation of NAM, providing an unexpected mechanistic role for sirtuins beyond histone deacetylation.

Model of Tryptophan Metabolism, Readily Scalable Using Tissue-specific Gene Expression Data

Background: Changes in tryptophan metabolism are associated with various diseases. Results: A comprehensive model of human tryptophan metabolism was constructed and verified with existing experimental data. Conclusion: The subtle balance of tryptophan derivatives required for proper brain function is sensitive to alterations in peripheral tissues. Significance: The model is applicable as a diagnostic tool to study disease related changes in tryptophan metabolism. Tryptophan is utilized in various metabolic routes including protein synthesis, serotonin, and melatonin synthesis and the kynurenine pathway. Perturbations in these pathways have been associated with neurodegenerative diseases and cancer. Here we present a comprehensive kinetic model of the complex network of human tryptophan metabolism based upon existing kinetic data for all enzymatic conversions and transporters. By integrating tissue-specific expression data, modeling tryptophan metabolism in liver and brain returned intermediate metabolite concentrations in the physiological range. Sensitivity and metabolic control analyses identified expected key enzymes to govern fluxes in the branches of the network. Combining tissue-specific models revealed a considerable impact of the kynurenine pathway in liver on the concentrations of neuroactive derivatives in the brain. Moreover, using expression data from a cancer study predicted metabolite changes that resembled the experimental observations. We conclude that the combination of the kinetic model with expression data represents a powerful diagnostic tool to predict alterations in tryptophan metabolism. The model is readily scalable to include more tissues, thereby enabling assessment of organismal tryptophan metabolism in health and disease.

Dynamics of NAD-metabolism: everything but constant.

NAD, as well as its phosphorylated form, NADP, are best known as electron carriers and co-substrates of various redox reactions. As such they participate in approximately one quarter of all reactions listed in the reaction database KEGG. In metabolic pathway analysis, the total amount of NAD is usually assumed to be constant. That means that changes in the redox state might be considered, but concentration changes of the NAD moiety are usually neglected. However, a growing number of NAD-consuming reactions have been identified, showing that this assumption does not hold true in general. NAD-consuming reactions are common characteristics of NAD(+)-dependent signalling pathways and include mono- and poly-ADP-ribosylation of proteins, NAD(+)-dependent deacetylation by sirtuins and the formation of messenger molecules such as cyclic ADP-ribose (cADPR) and nicotinic acid (NA)-ADP (NAADP). NAD-consuming reactions are thus involved in major signalling and gene regulation pathways such as DNA-repair or regulation of enzymes central in metabolism. All known NAD(+)-dependent signalling processes include the release of nicotinamide (Nam). Thus cellular NAD pools need to be constantly replenished, mostly by recycling Nam to NAD(+). This process is, among others, regulated by the circadian clock, causing complex dynamic changes in NAD concentration. As disturbances in NAD homoeostasis are associated with a large number of diseases ranging from cancer to diabetes, it is important to better understand the dynamics of NAD metabolism to develop efficient pharmacological invention strategies to target this pathway.

Effect of substrate competition in kinetic models of metabolic networks.

Substrate competition can be found in many types of biological processes, ranging from gene expression to signal transduction and metabolic pathways. Although several experimental and in silico studies have shown the impact of substrate competition on these processes, it is still often neglected, especially in modelling approaches. Using toy models that exemplify different metabolic pathway scenarios, we show that substrate competition can influence the dynamics and the steady state concentrations of a metabolic pathway. We have additionally derived rate laws for substrate competition in reversible reactions and summarise existing rate laws for substrate competition in irreversible reactions.

Suppression of indoleamine-2,3-dioxygenase 1 expression by promoter hypermethylation in ER-positive breast cancer

ABSTRACT Kynurenine formation by tryptophan-catabolic indoleamine-2,3-dioxygenase 1 (IDO1) plays a key role in tumor immune evasion and inhibition of IDO1 is efficacious in preclinical models of breast cancer. As the response of breast cancer to immune checkpoint inhibitors may be limited, a better understanding of the expression of additional targetable immunomodulatory pathways is of importance. We therefore investigated the regulation of IDO1 expression in different breast cancer subtypes. We identified estrogen receptor α (ER) as a negative regulator of IDO1 expression. Serum kynurenine levels as well as tumoral IDO1 expression were lower in patients with ER-positive than ER-negative tumors and an inverse relationship between IDO1 and estrogen receptor mRNA was observed across 14 breast cancer data sets. Analysis of whole genome bisulfite sequencing, 450k, MassARRAY and pyrosequencing data revealed that the IDO1 promoter is hypermethylated in ER-positive compared with ER-negative breast cancer. Reduced induction of IDO1 was also observed in human ER-positive breast cancer cell lines. IDO1 induction was enhanced upon DNA demethylation in ER-positive but not in ER-negative cells and methylation of an IDO1 promoter construct reduced IDO1 expression, suggesting that enhanced methylation of the IDO1 promoter suppresses IDO1 in ER-positive breast cancer. The association of ER overexpression with epigenetic downregulation of IDO1 appears to be a particular feature of breast cancer as IDO1 was not suppressed by IDO1 promoter hypermethylation in the presence of high ER expression in cervical or endometrial cancer.

Improving the accuracy of expression data analysis in time course experiments using resampling

BackgroundAs time series experiments in higher eukaryotes usually obtain data from different individuals collected at the different time points, a time series sample itself is not equivalent to a true biological replicate but is, rather, a combination of several biological replicates. The analysis of expression data derived from a time series sample is therefore often performed with a low number of replicates due to budget limitations or limitations in sample availability. In addition, most algorithms developed to identify specific patterns in time series dataset do not consider biological variation in samples collected at the same conditions.ResultsUsing artificial time course datasets, we show that resampling considerably improves the accuracy of transcripts identified as rhythmic. In particular, the number of false positives can be greatly reduced while at the same time the number of true positives can be maintained in the range of other methods currently used to determine rhythmically expressed genes.ConclusionsThe resampling approach described here therefore increases the accuracy of time series expression data analysis and furthermore emphasizes the importance of biological replicates in identifying oscillating genes. Resampling can be used for any time series expression dataset as long as the samples are acquired from independent individuals at each time point.

Upregulation of tryptophanyl-tRNA synthethase adapts human cancer cells to nutritional stress caused by tryptophan degradation

ABSTRACT Tryptophan (Trp) metabolism is an important target in immuno-oncology as it represents a powerful immunosuppressive mechanism hijacked by tumors for protection against immune destruction. However, it remains unclear how tumor cells can proliferate while degrading the essential amino acid Trp. Trp is incorporated into proteins after it is attached to its tRNA by tryptophanyl-tRNA synthestases. As the tryptophanyl-tRNA synthestases compete for Trp with the Trp-catabolizing enzymes, the balance between these enzymes will determine whether Trp is used for protein synthesis or is degraded. In human cancers expression of the Trp-degrading enzymes indoleamine-2,3-dioxygenase-1 (IDO1) and tryptophan-2,3-dioxygenase (TDO2) was positively associated with the expression of the tryptophanyl-tRNA synthestase WARS. One mechanism underlying the association between IDO1 and WARS identified in this study is their joint induction by IFNγ released from tumor-infiltrating T cells. Moreover, we show here that IDO1- and TDO2-mediated Trp deprivation upregulates WARS expression by activating the general control non-derepressible-2 (GCN2) kinase, leading to phosphorylation of the eukaryotic translation initiation factor 2α (eIF2α) and induction of activating transcription factor 4 (ATF4). Trp deprivation induced cytoplasmic WARS expression but did not increase nuclear or extracellular WARS levels. GCN2 protected the cells against the effects of Trp starvation and enabled them to quickly make use of Trp for proliferation once it was replenished. Computational modeling of Trp metabolism revealed that Trp deficiency shifted Trp flux towards WARS and protein synthesis. Our data therefore suggest that the upregulation of WARS via IFNγ and/or GCN2-peIF2α-ATF4 signaling protects Trp-degrading cancer cells from excessive intracellular Trp depletion.

Human long intrinsically disordered protein regions are frequent targets of positive selection

Intrinsically disordered regions occur frequently in proteins and are characterized by a lack of a well-defined three-dimensional structure. Although these regions do not show a higher order of structural organization, they are known to be functionally important. Disordered regions are rapidly evolving, largely attributed to relaxed purifying selection and an increased role of genetic drift. It has also been suggested that positive selection might contribute to their rapid diversification. However, for our own species, it is currently unknown whether positive selection has played a role during the evolution of these protein regions. Here, we address this question by investigating the evolutionary pattern of more than 6600 human proteins with intrinsically disordered regions and their ordered counterparts. Our comparative approach with data from more than 90 mammalian genomes uses a priori knowledge of disordered protein regions, and we show that this increases the power to detect positive selection by an order of magnitude. We can confirm that human intrinsically disordered regions evolve more rapidly, not only within humans but also across the entire mammalian phylogeny. They have, however, experienced substantial evolutionary constraint, hinting at their fundamental functional importance. We find compelling evidence that disordered protein regions are frequent targets of positive selection and estimate that the relative rate of adaptive substitutions differs fourfold between disordered and ordered protein regions in humans. Our results suggest that disordered protein regions are important targets of genetic innovation and that the contribution of positive selection in these regions is more pronounced than in other protein parts.

SBMLmod: a Python-based web application and web service for efficient data integration and model simulation

BackgroundSystems Biology Markup Language (SBML) is the standard model representation and description language in systems biology. Enriching and analysing systems biology models by integrating the multitude of available data, increases the predictive power of these models. This may be a daunting task, which commonly requires bioinformatic competence and scripting.ResultsWe present SBMLmod, a Python-based web application and service, that automates integration of high throughput data into SBML models. Subsequent steady state analysis is readily accessible via the web service COPASIWS. We illustrate the utility of SBMLmod by integrating gene expression data from different healthy tissues as well as from a cancer dataset into a previously published model of mammalian tryptophan metabolism.ConclusionSBMLmod is a user-friendly platform for model modification and simulation. The web application is available at http://sbmlmod.uit.no, whereas the WSDL definition file for the web service is accessible via http://sbmlmod.uit.no/SBMLmod.wsdl. Furthermore, the entire package can be downloaded from https://github.com/MolecularBioinformatics/sbml-mod-ws. We envision that SBMLmod will make automated model modification and simulation available to a broader research community.