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Synthetically designed alternative photorespiratory pathways increase the biomass of tobacco and rice plants. Likewise, some in planta–tested synthetic carbon-concentrating cycles (CCCs) hold promise to increase plant biomass while diminishing atmospheric carbon dioxide burden. Taking these individual contributions into account, we hypothesize that the integration of bypasses and CCCs will further increase plant productivity. To test this in silico, we reconstructed a metabolic model by integrating photorespiration and photosynthesis with the synthetically designed alternative pathway 3 (AP3) enzymes and transporters. We calculated fluxes of the native plant system and those of AP3 combined with the inhibition of the glycolate/glycerate transporter by using the YANAsquare package. The activity values corresponding to each enzyme in photosynthesis, photorespiration, and for synthetically designed alternative pathways were estimated. Next, we modeled the effect of the crotonyl-CoA/ethylmalonyl-CoA/hydroxybutyryl-CoA cycle (CETCH), which is a set of natural and synthetically designed enzymes that fix CO₂ manifold more than the native Calvin–Benson–Bassham (CBB) cycle. We compared estimated fluxes across various pathways in the native model and under an introduced CETCH cycle. Moreover, we combined CETCH and AP3-w/plgg1RNAi, and calculated the fluxes. We anticipate higher carbon dioxide–harvesting potential in plants with an AP3 bypass and CETCH–AP3 combination. We discuss the in vivo implementation of these strategies for the improvement of C3 plants and in natural high carbon harvesters.
Background: Hemostasis is a critical and active function of the blood mediated by platelets. Therefore, the prevention of pathological platelet aggregation is of great importance as well as of pharmaceutical and medical interest. Endogenous platelet inhibition is predominantly based on cyclic nucleotides (cAMP, cGMP) elevation and subsequent cyclic nucleotide-dependent protein kinase (PKA, PKG) activation. In turn, platelet phosphodiesterases (PDEs) and protein phosphatases counterbalance their activity. This main inhibitory pathway in human platelets is crucial for countervailing unwanted platelet activation. Consequently, the regulators of cyclic nucleotide signaling are of particular interest to pharmacology and therapeutics of atherothrombosis. Modeling of pharmacodynamics allows understanding this intricate signaling and supports the precise description of these pivotal targets for pharmacological modulation. Results: We modeled dynamically concentration-dependent responses of pathway effectors (inhibitors, activators, drug combinations) to cyclic nucleotide signaling as well as to downstream signaling events and verified resulting model predictions by experimental data. Experiments with various cAMP affecting compounds including antiplatelet drugs and their combinations revealed a high fidelity, fine-tuned cAMP signaling in platelets without crosstalk to the cGMP pathway. The model and the data provide evidence for two independent feedback loops: PKA, which is activated by elevated cAMP levels in the platelet, subsequently inhibits adenylyl cyclase (AC) but as well activates PDE3. By multi-experiment fitting, we established a comprehensive dynamic model with one predictive, optimized and validated set of parameters. Different pharmacological conditions (inhibition, activation, drug combinations, permanent and transient perturbations) are successfully tested and simulated, including statistical validation and sensitivity analysis. Downstream cyclic nucleotide signaling events target different phosphorylation sites for cAMP- and cGMP-dependent protein kinases (PKA, PKG) in the vasodilator-stimulated phosphoprotein (VASP). VASP phosphorylation as well as cAMP levels resulting from different drug strengths and combined stimulants were quantitatively modeled. These predictions were again experimentally validated. High sensitivity of the signaling pathway at low concentrations is involved in a fine-tuned balance as well as stable activation of this inhibitory cyclic nucleotide pathway. Conclusions: On the basis of experimental data, literature mining and database screening we established a dynamic in silico model of cyclic nucleotide signaling and probed its signaling sensitivity. Thoroughly validated, it successfully predicts drug combination effects on platelet function, including synergism, antagonism and regulatory loops.
Modulating key dynamics of plant growth and development, the effects of the plant hormone cytokinin on animal cells gained much attention recently. Most previous studies on cytokinin effects on mammalian cells have been conducted with elevated cytokinin concentration (in the μM range). However, to examine physiologically relevant dose effects of cytokinins on animal cells, we systematically analyzed the impact of kinetin in cultured cells at low and high concentrations (1nM-10μM) and examined cytotoxic and genotoxic conditions. We furthermore measured the intrinsic antioxidant activity of kinetin in a cell-free system using the Ferric Reducing Antioxidant Power assay and in cells using the dihydroethidium staining method. Monitoring viability, we looked at kinetin effects in mammalian cells such as HL60 cells, HaCaT human keratinocyte cells, NRK rat epithelial kidney cells and human peripheral lymphocytes. Kinetin manifests no antioxidant activity in the cell free system and high doses of kinetin (500 nM and higher) reduce cell viability and mediate DNA damage in vitro. In contrast, low doses (concentrations up to 100 nM) of kinetin confer protection in cells against oxidative stress. Moreover, our results show that pretreatment of the cells with kinetin significantly reduces 4-nitroquinoline 1-oxide mediated reactive oxygen species production. Also, pretreatment with kinetin retains cellular GSH levels when they are also treated with the GSH-depleting agent patulin. Our results explicitly show that low kinetin doses reduce apoptosis and protect cells from oxidative stress mediated cell death. Future studies on the interaction between cytokinins and human cellular pathway targets will be intriguing.
Cushing’s disease (CD) is a rare condition caused by adrenocorticotropic hormone (ACTH)-producing adenomas of the pituitary, which lead to hypercortisolism that is associated with high morbidity and mortality. Treatment options in case of persistent or recurrent disease are limited, but new insights into the pathogenesis of CD are raising hope for new therapeutic avenues. Here, we have performed a meta-analysis of the available sequencing data in CD to create a comprehensive picture of CD’s genetics. Our analyses clearly indicate that somatic mutations in the deubiquitinases are the key drivers in CD, namely USP8 (36.5%) and USP48 (13.3%). While in USP48 only Met415 is affected by mutations, in USP8 there are 26 different mutations described. However, these different mutations are clustering in the same hotspot region (affecting in 94.5% of cases Ser718 and Pro720). In contrast, pathogenic variants classically associated with tumorigenesis in genes like TP53 and BRAF are also present in CD but with low incidence (12.5% and 7%). Importantly, several of these mutations might have therapeutic potential as there are drugs already investigated in preclinical and clinical setting for other diseases. Furthermore, network and pathway analyses of all somatic mutations in CD suggest a rather unified picture hinting towards converging oncogenic pathways.
The ITS2 Database
(2012)
The internal transcribed spacer 2 (ITS2) has been used as a phylogenetic marker for more than two decades. As ITS2 research mainly focused on the very variable ITS2 sequence, it confined this marker to low-level phylogenetics only. However, the combination of the ITS2 sequence and its highly conserved secondary structure improves the phylogenetic resolution1 and allows phylogenetic inference at multiple taxonomic ranks, including species delimitation.
The ITS2 Database presents an exhaustive dataset of internal transcribed spacer 2 sequences from NCBI GenBank accurately reannotated. Following an annotation by profile Hidden Markov Models (HMMs), the secondary structure of each sequence is predicted. First, it is tested whether a minimum energy based fold (direct fold) results in a correct, four helix conformation. If this is not the case, the structure is predicted by homology modeling. In homology modeling, an already known secondary structure is transferred to another ITS2 sequence, whose secondary structure was not able to fold correctly in a direct fold.
The ITS2 Database is not only a database for storage and retrieval of ITS2 sequence-structures. It also provides several tools to process your own ITS2 sequences, including annotation, structural prediction, motif detection and BLAST search on the combined sequence-structure information. Moreover, it integrates trimmed versions of 4SALE and ProfDistS for multiple sequence-structure alignment calculation and Neighbor Joining tree reconstruction. Together they form a coherent analysis pipeline from an initial set of sequences to a phylogeny based on sequence and secondary structure.
In a nutshell, this workbench simplifies first phylogenetic analyses to only a few mouse-clicks, while additionally providing tools and data for comprehensive large-scale analyses.
The IronChip evaluation package: a package of perl modules for robust analysis of custom microarrays
(2010)
Background: Gene expression studies greatly contribute to our understanding of complex relationships in gene regulatory networks. However, the complexity of array design, production and manipulations are limiting factors, affecting data quality. The use of customized DNA microarrays improves overall data quality in many situations, however, only if for these specifically designed microarrays analysis tools are available. Results: The IronChip Evaluation Package (ICEP) is a collection of Perl utilities and an easy to use data evaluation pipeline for the analysis of microarray data with a focus on data quality of custom-designed microarrays. The package has been developed for the statistical and bioinformatical analysis of the custom cDNA microarray IronChip but can be easily adapted for other cDNA or oligonucleotide-based designed microarray platforms. ICEP uses decision tree-based algorithms to assign quality flags and performs robust analysis based on chip design properties regarding multiple repetitions, ratio cut-off, background and negative controls. Conclusions: ICEP is a stand-alone Windows application to obtain optimal data quality from custom-designed microarrays and is freely available here (see “Additional Files” section) and at: http://www.alice-dsl.net/evgeniy. vainshtein/ICEP/
The drug-minded protein interaction database (DrumPID) has been designed to provide fast, tailored information on drugs and their protein networks including indications, protein targets and side-targets. Starting queries include compound, target and protein interactions and organism-specific protein families. Furthermore, drug name, chemical structures and their SMILES notation, affected proteins (potential drug targets), organisms as well as diseases can be queried including various combinations and refinement of searches. Drugs and protein interactions are analyzed in detail with reference to protein structures and catalytic domains, related compound structures as well as potential targets in other organisms. DrumPID considers drug functionality, compound similarity, target structure, interactome analysis and organismic range for a compound, useful for drug development, predicting drug side-effects and structure–activity relationships.
New antimycotic drugs are challenging to find, as potential target proteins may have close human orthologs. We here focus on identifying metabolic targets that are critical for fungal growth and have minimal similarity to targets among human proteins. We compare and combine here: (I) direct metabolic network modeling using elementary mode analysis and flux estimates approximations using expression data, (II) targeting metabolic genes by transcriptome analysis of condition-specific highly expressed enzymes, and (III) analysis of enzyme structure, enzyme interconnectedness (“hubs”), and identification of pathogen-specific enzymes using orthology relations. We have identified 64 targets including metabolic enzymes involved in vitamin synthesis, lipid, and amino acid biosynthesis including 18 targets validated from the literature, two validated and five currently examined in own genetic experiments, and 38 further promising novel target proteins which are non-orthologous to human proteins, involved in metabolism and are highly ranked drug targets from these pipelines.
Synergy of chemo- and photodynamic therapies with C\(_{60}\) Fullerene-Doxorubicin nanocomplex
(2019)
A nanosized drug complex was explored to improve the efficiency of cancer chemotherapy, complementing it with nanodelivery and photodynamic therapy. For this, nanomolar amounts of a non-covalent nanocomplex of Doxorubicin (Dox) with carbon nanoparticle C\(_{60}\) fullerene (C\(_{60}\)) were applied in 1:1 and 2:1 molar ratio, exploiting C\(_{60}\) both as a drug-carrier and as a photosensitizer. The fluorescence microscopy analysis of human leukemic CCRF-CEM cells, in vitro cancer model, treated with nanocomplexes showed Dox’s nuclear and C\(_{60}\)'s extranuclear localization. It gave an opportunity to realize a double hit strategy against cancer cells based on Dox's antiproliferative activity and C\(_{60}\)'s photoinduced pro-oxidant activity. When cells were treated with 2:1 C\(_{60}\)-Dox and irradiated at 405 nm the high cytotoxicity of photo-irradiated C\(_{60}\)-Dox enabled a nanomolar concentration of Dox and C\(_{60}\) to efficiently kill cancer cells in vitro. The high pro-oxidant and pro-apoptotic efficiency decreased IC\(_{50}\) 16, 9 and 7 × 10\(^3\)-fold, if compared with the action of Dox, non-irradiated nanocomplex, and C\(_{60}\)'s photodynamic effect, correspondingly. Hereafter, a strong synergy of therapy arising from the combination of C\(_{60}\)-mediated Dox delivery and C\(_{60}\) photoexcitation was revealed. Our data indicate that a combination of chemo- and photodynamic therapies with C\(_{60}\)-Dox nanoformulation provides a promising synergetic approach for cancer treatment.
Intricate mechanisms discriminate between friends and foes in plants. Plant organs deploy overlapping and distinct protection strategies. Despite vulnerability to a plethora of pathogens, the growing tips of plants grow bacteria free. The shoot apical meristem (SAM) is among three stem cells niches, a self-renewable reservoir for the future organogenesis of leaf, stem, and flowers. How plants safeguard this high value growth target from infections was not known until now. Recent reports find the stem cell secreted 12-amino acid peptide CLV3p (CLAVATA3 peptide) is perceived by FLS2 (FLAGELLIN SENSING 2) receptor and activates the transcription of immunity and defense marker genes. No infection in the SAM of wild type plants and bacterial infection in clv3 and fls2 mutants illustrate this natural protection against infections. Cytokinins (CKs) are enriched in the SAM and regulate meristem activities by their involvement in stem cell signaling networks. Auxin mediates plant susceptibility to pathogen infections while CKs boost plant immunity. Here, in addition to the stem-cell-triggered immunity we also highlight a potential link between CK signaling and CLV3p mediated immune response in the SAM.
Serine/threonine kinase PknB and its corresponding phosphatase Stp are important regulators of many cell functions in the pathogen S. aureus. Genome-scale gene expression data of S. aureus strain NewHG (sigB\(^+\)) elucidated their effect on physiological functions. Moreover, metabolic modelling from these data inferred metabolic adaptations. We compared wild-type to deletion strains lacking pknB, stp or both. Ser/Thr phosphorylation of target proteins by PknB switched amino acid catabolism off and gluconeogenesis on to provide the cell with sufficient components. We revealed a significant impact of PknB and Stp on peptidoglycan, nucleotide and aromatic amino acid synthesis, as well as catabolism involving aspartate transaminase. Moreover, pyrimidine synthesis was dramatically impaired by stp deletion but only slightly by functional loss of PknB. In double knockouts, higher activity concerned genes involved in peptidoglycan, purine and aromatic amino acid synthesis from glucose but lower activity of pyrimidine synthesis from glucose compared to the wild type. A second transcriptome dataset from S. aureus NCTC 8325 (sigB\(^−\)) validated the predictions. For this metabolic adaptation, PknB was found to interact with CdaA and the yvcK/glmR regulon. The involved GlmR structure and the GlmS riboswitch were modelled. Furthermore, PknB phosphorylation lowered the expression of many virulence factors, and the study shed light on S. aureus infection processes.
In a nice assay published in Nature in 1993 the physicist Richard God III started from a human observer and made a number of witty conclusions about our future prospects giving estimates for the existence of the Berlin Wall, the human race and all the rest of the universe. In the same spirit, we derive implications for "the meaning of life, the universe and all the rest" from few principles. Adams´ absurd answer "42" tells the lesson "garbage in / garbage out" - or suggests that the question is non calculable. We show that experience of "meaning" and to decide fundamental questions which can not be decided by formal systems imply central properties of life: Ever higher levels of internal representation of the world and an escalating tendency to become more complex. An observer, "collecting observations" and three measures for complexity are examined. A theory on living systems is derived focussing on their internal representation of information. Living systems are more complex than Kolmogorov complexity ("life is NOT simple") and overcome decision limits (Gödel theorem) for formal systems as illustrated for cell cycle. Only a world with very fine tuned environments allows life. Such a world is itself rather complex and hence excessive large in its space of different states – a living observer has thus a high probability to reside in a complex and fine tuned universe.
Background
The knowledge of metabolic pathways and fluxes is important to understand the adaptation of organisms to their biotic and abiotic environment. The specific distribution of stable isotope labelled precursors into metabolic products can be taken as fingerprints of the metabolic events and dynamics through the metabolic networks. An open-source software is required that easily and rapidly calculates from mass spectra of labelled metabolites, derivatives and their fragments global isotope excess and isotopomer distribution.
Results
The open-source software “Least Square Mass Isotopomer Analyzer” (LS-MIDA) is presented that processes experimental mass spectrometry (MS) data on the basis of metabolite information such as the number of atoms in the compound, mass to charge ratio (m/e or m/z) values of the compounds and fragments under study, and the experimental relative MS intensities reflecting the enrichments of isotopomers in 13C- or 15 N-labelled compounds, in comparison to the natural abundances in the unlabelled molecules. The software uses Brauman’s least square method of linear regression. As a result, global isotope enrichments of the metabolite or fragment under study and the molar abundances of each isotopomer are obtained and displayed.
Conclusions
The new software provides an open-source platform that easily and rapidly converts experimental MS patterns of labelled metabolites into isotopomer enrichments that are the basis for subsequent observation-driven analysis of pathways and fluxes, as well as for model-driven metabolic flux calculations.
The signal modelling framework JimenaE simulates dynamically Boolean networks. In contrast to SQUAD, there is systematic and not just heuristic calculation of all system states. These specific features are not present in CellNetAnalyzer and BoolNet. JimenaE is an expert extension of Jimena, with new optimized code, network conversion into different formats, rapid convergence both for system state calculation as well as for all three network centralities. It allows higher accuracy in determining network states and allows to dissect networks and identification of network control type and amount for each protein with high accuracy. Biological examples demonstrate this: (i) High plasticity of mesenchymal stromal cells for differentiation into chondrocytes, osteoblasts and adipocytes and differentiation-specific network control focusses on wnt-, TGF-beta and PPAR-gamma signaling. JimenaE allows to study individual proteins, removal or adding interactions (or autocrine loops) and accurately quantifies effects as well as number of system states. (ii) Dynamical modelling of cell–cell interactions of plant Arapidopsis thaliana against Pseudomonas syringae DC3000: We analyze for the first time the pathogen perspective and its interaction with the host. We next provide a detailed analysis on how plant hormonal regulation stimulates specific proteins and who and which protein has which type and amount of network control including a detailed heatmap of the A.thaliana response distinguishing between two states of the immune response. (iii) In an immune response network of dendritic cells confronted with Aspergillus fumigatus, JimenaE calculates now accurately the specific values for centralities and protein-specific network control including chemokine and pattern recognition receptors.
Introduction
Pro-thrombotic events are one of the prevalent causes of intensive care unit (ICU) admissions among COVID-19 patients, although the signaling events in the stimulated platelets are still unclear.
Methods
We conducted a comparative analysis of platelet transcriptome data from healthy donors, ICU, and non-ICU COVID-19 patients to elucidate these mechanisms. To surpass previous analyses, we constructed models of involved networks and control cascades by integrating a global human signaling network with transcriptome data. We investigated the control of platelet hyperactivation and the specific proteins involved.
Results
Our study revealed that control of the platelet network in ICU patients is significantly higher than in non-ICU patients. Non-ICU patients require control over fewer proteins for managing platelet hyperactivity compared to ICU patients. Identification of indispensable proteins highlighted key subnetworks, that are targetable for system control in COVID-19-related platelet hyperactivity. We scrutinized FDA-approved drugs targeting indispensable proteins and identified fostamatinib as a potent candidate for preventing thrombosis in COVID-19 patients.
Discussion
Our findings shed light on how SARS-CoV-2 efficiently affects host platelets by targeting indispensable and critical proteins involved in the control of platelet activity. We evaluated several drugs for specific control of platelet hyperactivity in ICU patients suffering from platelet hyperactivation. The focus of our approach is repurposing existing drugs for optimal control over the signaling network responsible for platelet hyperactivity in COVID-19 patients. Our study offers specific pharmacological recommendations, with drug prioritization tailored to the distinct network states observed in each patient condition. Interactive networks and detailed results can be accessed at https://fostamatinib.bioinfo-wuerz.eu/.