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Epicardium-derived cells (EPDC) and atrial stromal cells (ASC) display cardio-regenerative potential, but the molecular details are still unexplored. Signals which induce activation, migration and differentiation of these cells are largely unknown. Here we have isolated rat ventricular EPDC and rat/human ASC and performed genetic and proteomic profiling. EPDC and ASC expressed epicardial/mesenchymal markers (WT-1, Tbx18, CD73,CD90, CD44, CD105), cardiac markers (Gata4, Tbx5, troponin T) and also contained phosphocreatine. We used cell surface biotinylation to isolate plasma membrane proteins of rEPDC and hASC, Nano-liquid chromatography with subsequent mass spectrometry and bioinformatics analysis identified 396 rat and 239 human plasma membrane proteins with 149 overlapping proteins. Functional GO-term analysis revealed several significantly enriched categories related to extracellular matrix (ECM), cell migration/differentiation, immunology or angiogenesis. We identified receptors for ephrin and growth factors (IGF, PDGF, EGF, anthrax toxin) known to be involved in cardiac repair and regeneration. Functional category enrichment identified clusters around integrins, PI3K/Akt-signaling and various cardiomyopathies. Our study indicates that EPDC and ASC have a similar molecular phenotype related to cardiac healing/regeneration. The cell surface proteome repository will help to further unravel the molecular details of their cardio-regenerative potential and their role in cardiac diseases.
A precise and rapid adjustment of fluxes through metabolic pathways is crucial for organisms to prevail in changing environmental conditions. Based on this reasoning, many guiding principles that govern the evolution of metabolic networks and their regulation have been uncovered. To this end, methods from dynamic optimization are ideally suited since they allow to uncover optimality principles behind the regulation of metabolic networks. We used dynamic optimization to investigate the influence of toxic intermediates in connection with the efficiency of enzymes on the regulation of a linear metabolic pathway. Our results predict that transcriptional regulation favors the control of highly efficient enzymes with less toxic upstream intermediates to reduce accumulation of toxic downstream intermediates. We show that the derived optimality principles hold by the analysis of the interplay between intermediate toxicity and pathway regulation in the metabolic pathways of over 5000 sequenced prokaryotes. Moreover, using the lipopolysaccharide biosynthesis in Escherichia coli as an example, we show how knowledge about the relation of regulation, kinetic efficiency and intermediate toxicity can be used to identify drug targets, which control endogenous toxic metabolites and prevent microbial growth. Beyond prokaryotes, we discuss the potential of our findings for the development of antifungal drugs.
Comparison of the central human and mouse platelet signaling cascade by systems biological analysis
(2020)
Background
Understanding the molecular mechanisms of platelet activation and aggregation is of high interest for basic and clinical hemostasis and thrombosis research. The central platelet protein interaction network is involved in major responses to exogenous factors. This is defined by systemsbiological pathway analysis as the central regulating signaling cascade of platelets (CC).
Results
The CC is systematically compared here between mouse and human and major differences were found. Genetic differences were analysed comparing orthologous human and mouse genes. We next analyzed different expression levels of mRNAs. Considering 4 mouse and 7 human high-quality proteome data sets, we identified then those major mRNA expression differences (81%) which were supported by proteome data. CC is conserved regarding genetic completeness, but we observed major differences in mRNA and protein levels between both species. Looking at central interactors, human PLCB2, MMP9, BDNF, ITPR3 and SLC25A6 (always Entrez notation) show absence in all murine datasets. CC interactors GNG12, PRKCE and ADCY9 occur only in mice. Looking at the common proteins, TLN1, CALM3, PRKCB, APP, SOD2 and TIMP1 are higher abundant in human, whereas RASGRP2, ITGB2, MYL9, EIF4EBP1, ADAM17, ARRB2, CD9 and ZYX are higher abundant in mouse. Pivotal kinase SRC shows different regulation on mRNA and protein level as well as ADP receptor P2RY12.
Conclusions
Our results highlight species-specific differences in platelet signaling and points of specific fine-tuning in human platelets as well as murine-specific signaling differences.
High attrition-rates entailed by drug testing in 2D cell culture and animal models stress the need for improved modeling of human tumor tissues. In previous studies our 3D models on a decellularized tissue matrix have shown better predictivity and higher chemoresistance. A single porcine intestine yields material for 150 3D models of breast, lung, colorectal cancer (CRC) or leukemia. The uniquely preserved structure of the basement membrane enables physiological anchorage of endothelial cells and epithelial-derived carcinoma cells. The matrix provides different niches for cell growth: on top as monolayer, in crypts as aggregates and within deeper layers. Dynamic culture in bioreactors enhances cell growth. Comparing gene expression between 2D and 3D cultures, we observed changes related to proliferation, apoptosis and stemness. For drug target predictions, we utilize tumor-specific sequencing data in our in silico model finding an additive effect of metformin and gefitinib treatment for lung cancer in silico, validated in vitro. To analyze mode-of-action, immune therapies such as trispecific T-cell engagers in leukemia, as well as toxicity on non-cancer cells, the model can be modularly enriched with human endothelial cells (hECs), immune cells and fibroblasts. Upon addition of hECs, transmigration of immune cells through the endothelial barrier can be investigated. In an allogenic CRC model we observe a lower basic apoptosis rate after applying PBMCs in 3D compared to 2D, which offers new options to mirror antigen-specific immunotherapies in vitro. In conclusion, we present modular human 3D tumor models with tissue-like features for preclinical testing to reduce animal experiments.
The opportunistic human pathogen Staphylococcus aureus causes serious infectious diseases that range from superficial skin and soft tissue infections to necrotizing pneumonia and sepsis. While classically regarded as an extracellular pathogen, S. aureus is able to invade and survive within human cells. Host cell exit is associated with cell death, tissue destruction, and the spread of infection. The exact molecular mechanism employed by S. aureus to escape the host cell is still unclear. In this study, we performed a genome-wide small hairpin RNA (shRNA) screen and identified the calcium signaling pathway as being involved in intracellular infection. S. aureus induced a massive cytosolic Ca\(^{2+}\) increase in epithelial host cells after invasion and intracellular replication of the pathogen. This was paralleled by a decrease in endoplasmic reticulum Ca\(^{2+}\) concentration. Additionally, calcium ions from the extracellular space contributed to the cytosolic Ca2+ increase. As a consequence, we observed that the cytoplasmic Ca\(^{2+}\) rise led to an increase in mitochondrial Ca\(^{2+}\) concentration, the activation of calpains and caspases, and eventually to cell lysis of S. aureus-infected cells. Our study therefore suggests that intracellular S. aureus disturbs the host cell Ca\(^{2+}\) homeostasis and induces cytoplasmic Ca\(^{2+}\) overload, which results in both apoptotic and necrotic cell death in parallel or succession.
IMPORTANCE Despite being regarded as an extracellular bacterium, the pathogen Staphylococcus aureus can invade and survive within human cells. The intracellular niche is considered a hideout from the host immune system and antibiotic treatment and allows bacterial proliferation. Subsequently, the intracellular bacterium induces host cell death, which may facilitate the spread of infection and tissue destruction. So far, host cell factors exploited by intracellular S. aureus to promote cell death are only poorly characterized. We performed a genome-wide screen and found the calcium signaling pathway to play a role in S. aureus invasion and cytotoxicity. The intracellular bacterium induces a cytoplasmic and mitochondrial Ca\(^{2+}\) overload, which results in host cell death. Thus, this study first showed how an intracellular bacterium perturbs the host cell Ca\(^{2+}\) homeostasis."
Metabolism and signaling of cytokinins was first established in plants, followed by cytokinin discoveries in all kingdoms of life. However, understanding of their role in mammalian cells is still scarce. Kinetin is a cytokinin that mitigates the effects of oxidative stress in mammalian cells. The effective concentrations of exogenously applied kinetin in invoking various cellular responses are not well standardized. Likewise, the metabolism of kinetin and its cellular targets within the mammalian cells are still not well studied. Applying vitality tests as well as comet assays under normal and hyper-oxidative states, our analysis suggests that kinetin concentrations of 500 nM and above cause cytotoxicity as well as genotoxicity in various cell types. However, concentrations below 100 nM do not cause any toxicity, rather in this range kinetin counteracts oxidative burst and cytotoxicity. We focus here on these effects. To get insights into the cellular targets of kinetin mediating these pro-survival functions and protective effects we applied structural and computational approaches on two previously testified targets for these effects. Our analysis deciphers vital residues in adenine phosphoribosyltransferase (APRT) and adenosine receptor (A2A-R) that facilitate the binding of kinetin to these two important human cellular proteins. We finally discuss how the therapeutic potential of kinetin against oxidative stress helps in various pathophysiological conditions.
The predicted 80 open reading frames (ORFs) of herpes simplex virus 1 (HSV-1) have been intensively studied for decades. Here, we unravel the complete viral transcriptome and translatome during lytic infection with base-pair resolution by computational integration of multi-omics data. We identify a total of 201 transcripts and 284 ORFs including all known and 46 novel large ORFs. This includes a so far unknown ORF in the locus deleted in the FDA-approved oncolytic virus Imlygic. Multiple transcript isoforms expressed from individual gene loci explain translation of the vast majority of ORFs as well as N-terminal extensions (NTEs) and truncations. We show that NTEs with non-canonical start codons govern the subcellular protein localization and packaging of key viral regulators and structural proteins. We extend the current nomenclature to include all viral gene products and provide a genome browser that visualizes all the obtained data from whole genome to single-nucleotide resolution. Here, using computational integration of multi-omics data, the authors provide a detailed transcriptome and translatome of herpes simplex virus 1 (HSV-1), including previously unidentified ORFs and N-terminal extensions. The study also provides a HSV-1 genome browser and should be a valuable resource for further research.
Apart from some model organisms, the interactome of most organisms is largely unidentified. High-throughput experimental techniques to determine protein-protein interactions (PPIs) are resource intensive and highly susceptible to noise. Computational methods of PPI determination can accelerate biological discovery by identifying the most promising interacting pairs of proteins and by assessing the reliability of identified PPIs. Here we present a first in-depth study describing a global view of the ant Camponotus floridanus interactome. Although several ant genomes have been sequenced in the last eight years, studies exploring and investigating PPIs in ants are lacking. Our study attempts to fill this gap and the presented interactome will also serve as a template for determining PPIs in other ants in future. Our C. floridanus interactome covers 51,866 non-redundant PPIs among 6,274 proteins, including 20,544 interactions supported by domain-domain interactions (DDIs), 13,640 interactions supported by DDIs and subcellular localization, and 10,834 high confidence interactions mediated by 3,289 proteins. These interactions involve and cover 30.6% of the entire C. floridanus proteome.
Background
Processing and analysis of DNA sequences obtained from next-generation sequencing (NGS) face some difficulties in terms of the correct prediction of DNA sequencing outcomes without the implementation of bioinformatics approaches. However, algorithms based on NGS perform inefficiently due to the generation of long DNA fragments, the difficulty of assembling them and the complexity of the used genomes. On the other hand, the Sanger DNA sequencing method is still considered to be the most reliable; it is a reliable choice for virtual modeling to build all possible consensus sequences from smaller DNA fragments.
Results
In silico and in vitro experiments were conducted: (1) to implement and test our novel sequencing algorithm, using the standard cloning vectors of different length and (2) to validate experimentally virtual shotgun sequencing using the PCR technique with the number of cycles from 1 to 9 for each reaction.
Conclusions
We applied a novel algorithm based on Sanger methodology to correctly predict and emphasize the performance of DNA sequencing techniques as well as in de novo DNA sequencing and its further application in synthetic biology. We demonstrate the statistical significance of our results.
We explore a cosmology where the Big Bang singularity is replaced by a condensation event of interacting strings. We study the transition from an uncontrolled, chaotic soup (“before”) to a clearly interacting “real world”. Cosmological inflation scenarios do not fit current observations and are avoided. Instead, long-range interactions inside this crystallization event limit growth and crystal symmetries ensure the same laws of nature and basic symmetries over our domain. Tiny mis-arrangements present nuclei of superclusters and galaxies and crystal structure leads to the arrangement of dark (halo regions) and normal matter (galaxy nuclei) so convenient for galaxy formation. Crystals come and go, allowing an evolutionary cosmology where entropic forces from the quantum soup “outside” of the crystal try to dissolve it. These would correspond to dark energy and leads to a big rip scenario in 70 Gy. Preference of crystals with optimal growth and most condensation nuclei for the next generation of crystals may select for multiple self-organizing processes within the crystal, explaining “fine-tuning” of the local “laws of nature” (the symmetry relations formed within the crystal, its “unit cell”) to be particular favorable for self-organizing processes including life or even conscious observers in our universe.
Independent of cosmology, a crystallization event may explain quantum-decoherence in general: The fact, that in our macroscopic everyday world we only see one reality. This contrasts strongly with the quantum world where you have coherence, a superposition of all quantum states. We suggest that a “real world” (so our everyday macroscopic world) happens only in our domain, i.e. inside a crystal. “Outside” of our domain and our observable universe there is the quantum soup of boiling quantum foam and superposition of all possibilities. In our crystallized world the vacuum no longer boils but is cooled down by the crystallization event and hence is 10**20 smaller, exactly as observed in our everyday world. As we live in a “solid” state, within a crystal, the different quanta which build our world have all their different states nicely separated. This theory postulates there are only n quanta and m states available for them (there is no Everett-like ever splitting multiverse after each decision). In the solid state we live in, there is decoherence, the states are nicely separated. The arrow of entropy for each edge of the crystal forms one fate, one worldline or clear development of a world, while the layers of the crystal are different system states.
Some mathematical leads from loop quantum gravity point to required interactions and potentials. A complete mathematical treatment of this unified theory is far too demanding currently. Interaction potentials for strings or membranes of any dimension allow a solid state of quanta, so allowing decoherence in our observed world are challenging to calculate. However, if we introduce here the heuristic that any type of physical interaction of strings corresponds just to a type of calculation, there is already since 1898 the Hurwitz theorem showing that then only 1D, 2D, 4D and 8D (octonions) allow complex or hypercomplex number calculations. No other hypercomplex numbers and hence dimensions or symmetries are possible to allow calculations without yielding divisions by zero. However, the richest solution allowed by the Hurwitz theorem, octonions, is actually the observed symmetry of our universe, E8.
C60 fullerene as an effective nanoplatform of alkaloid Berberine delivery into leukemic cells
(2019)
A herbal alkaloid Berberine (Ber), used for centuries in Ayurvedic, Chinese, Middle-Eastern, and native American folk medicines, is nowadays proved to function as a safe anticancer agent. Yet, its poor water solubility, stability, and bioavailability hinder clinical application. In this study, we have explored a nanosized carbon nanoparticle—C60 fullerene (C60)—for optimized Ber delivery into leukemic cells. Water dispersions of noncovalent C60-Ber nanocomplexes in the 1:2, 1:1, and 2:1 molar ratios were prepared. UV–Vis spectroscopy, dynamic light scattering (DLS), and atomic force microscopy (AFM) evidenced a complexation of the Ber cation with the negatively charged C60 molecule. The computer simulation showed that π-stacking dominates in Ber and C\(_{60}\) binding in an aqueous solution. Complexation with C\(_{60}\) was found to promote Ber intracellular uptake. By increasing C\(_{60}\) concentration, the C\(_{60}\)-Ber nanocomplexes exhibited higher antiproliferative potential towards CCRF-CEM cells, in accordance with the following order: free Ber < 1:2 < 1:1 < 2:1 (the most toxic). The activation of caspase 3/7 and accumulation in the sub-G1 phase of CCRF-CEM cells treated with C\(_{60}\)-Ber nanocomplexes evidenced apoptosis induction. Thus, this study indicates that the fast and easy noncovalent complexation of alkaloid Ber with C\(_{60}\) improved its in vitro efficiency against cancer cells.
Protein-protein interaction (PPI) studies are gaining momentum these days due to the plethora of various high-throughput experimental methods available for detecting PPIs. Proteins create complexes and networks by functioning in harmony with other proteins and here in silico network biology hold the promise to reveal new functionality of genes as it is very difficult and laborious to carry out experimental high-throughput genetic screens in living organisms. We demonstrate this approach by computationally screening C. elegans conserved homologs of already reported human tumor suppressor and aging associated genes. We select by this nhr-6, vab-3 and gst-23 as predicted longevity genes for RNAi screen. The RNAi results demonstrated the pro-longevity effect of these genes. Nuclear hormone receptor nhr-6 RNAi inhibition resulted in a C. elegans phenotype of 23.46% lifespan reduction. Moreover, we show that nhr-6 regulates oxidative stress resistance in worms and does not affect the feeding behavior of worms. These findings imply the potential of nhr-6 as a common therapeutic target for aging and cancer ailments, stressing the power of in silico PPI network analysis coupled with RNAi screens to describe gene function.
Aspergillus fumigatus is a saprophytic, cosmopolitan fungus that attacks patients with a weak immune system. A rational solution against fungal infection aims to manipulate fungal metabolism or to block enzymes essential for Aspergillus survival. Here we discuss and compare different bioinformatics approaches to analyze possible targeting strategies on fungal-unique pathways. For instance, phylogenetic analysis reveals fungal targets, while domain analysis allows us to spot minor differences in protein composition between the host and fungi. Moreover, protein networks between host and fungi can be systematically compared by looking at orthologs and exploiting information from host–pathogen interaction databases. Further data—such as knowledge of a three-dimensional structure, gene expression data, or information from calculated metabolic fluxes—refine the search and rapidly put a focus on the best targets for antimycotics. We analyzed several of the best targets for application to structure-based drug design. Finally, we discuss general advantages and limitations in identification of unique fungal pathways and protein targets when applying bioinformatics tools.
Virotherapy on the basis of oncolytic vaccinia virus (VACV) strains is a promising approach for cancer therapy. Recently, we showed that the oncolytic vaccinia virus GLV-1h68 has a therapeutic potential in treating human prostate and hepatocellular carcinomas in xenografted mice. In this study, we describe the use of dynamic boolean modeling for tumor growth prediction of vaccinia virus-injected human tumors. Antigen profiling data of vaccinia virus GLV-1h68-injected human xenografted mice were obtained, analyzed and used to calculate differences in the tumor growth signaling network by tumor type and gender. Our model combines networks for apoptosis, MAPK, p53, WNT, Hedgehog, the T-killer cell mediated cell death, Interferon and Interleukin signaling networks. The in silico findings conform very well with in vivo findings of tumor growth. Similar to a previously published analysis of vaccinia virus-injected canine tumors, we were able to confirm the suitability of our boolean modeling for prediction of human tumor growth after virus infection in the current study as well. In summary, these findings indicate that our boolean models could be a useful tool for testing of the efficacy of VACV-mediated cancer therapy already before its use in human patients.
Dendritic cells (DCs) are antigen presenting cells which serve as a passage between the innate and the acquired immunity. Aspergillosis is a major lethal condition in immunocompromised patients caused by the adaptable saprophytic fungus Aspergillus fumigatus. The healthy human immune system is capable to ward off A. fumigatus infections however immune-deficient patients are highly vulnerable to invasive aspergillosis. A. fumigatus can persist during infection due to its ability to survive the immune response of human DCs. Therefore, the study of the metabolism specific to the context of infection may allow us to gain insight into the adaptation strategies of both the pathogen and the immune cells. We established a metabolic model of A. fumigatus central metabolism during infection of DCs and calculated the metabolic pathway (elementary modes; EMs). Transcriptome data were used to identify pathways activated when A. fumigatus is challenged with DCs. In particular, amino acid metabolic pathways, alternative carbon metabolic pathways and stress regulating enzymes were found to be active. Metabolic flux modeling identified further active enzymes such as alcohol dehydrogenase, inositol oxygenase and GTP cyclohydrolase participating in different stress responses in A. fumigatus. These were further validated by qRT-PCR from RNA extracted under these different conditions. For DCs, we outlined the activation of metabolic pathways in response to the confrontation with A. fumigatus. We found the fatty acid metabolism plays a crucial role, along with other metabolic changes. The gene expression data and their analysis illuminate additional regulatory pathways activated in the DCs apart from interleukin regulation. In particular, Toll-like receptor signaling, NOD-like receptor signaling and RIG-I-like receptor signaling were active pathways. Moreover, we identified subnetworks and several novel key regulators such as UBC, EGFR, and CUL3 of DCs to be activated in response to A. fumigatus. In conclusion, we analyze the metabolic and regulatory responses of A. fumigatus and DCs when confronted with each other.
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.
Rational drug design of Axl tyrosine kinase type I inhibitors as promising candidates against cancer
(2020)
The high level of Axl tyrosine kinase expression in various cancer cell lines makes it an attractive target for the development of anti-cancer drugs. In this study, we carried out several sets of in silico screening for the ATP-competitive Axl kinase inhibitors based on different molecular docking protocols. The best drug-like candidates were identified, after parental structure modifications, by their highest affinity to the target protein. We found that our newly designed compound R5, a derivative of the R428 patented analog, is the most promising inhibitor of the Axl kinase according to the three molecular docking algorithms applied in the study. The molecular docking results are in agreement with the molecular dynamics simulations using the MM-PBSA/GBSA implicit solvation models, which confirm the high affinity of R5 toward the protein receptor. Additionally, the selectivity test against other kinases also reveals a high affinity of R5 toward ABL1 and Tyro3 kinases, emphasizing its promising potential for the treatment of malignant tumors.
Eugenol is a phytochemical present in different plant products, e.g., clove oil. Traditionally, it is used against a number of different disorders and it was suggested to have anticancer activity. In this study, the activity of eugenol was evaluated in a human cervical cancer (HeLa) cell line and cell proliferation was examined after treatment with various concentrations of eugenol and different treatment durations. Cytotoxicity was tested using lactate dehydrogenase (LDH) enzyme leakage. In order to assess eugenol’s potential to act synergistically with chemotherapy and radiotherapy, cell survival was calculated after eugenol treatment in combination with cisplatin and X-rays. To elucidate its mechanism of action, caspase-3 activity was analyzed and the expression of various genes and proteins was checked by RT-PCR and western blot analyses. Eugenol clearly decreased the proliferation rate and increased LDH release in a concentration- and time-dependent manner. It showed synergistic effects with cisplatin and X-rays. Eugenol increased caspase-3 activity and the expression of Bax, cytochrome c (Cyt-c), caspase-3, and caspase-9 and decreased the expression of B-cell lymphoma (Bcl)-2, cyclooxygenase-2 (Cox-2), and interleukin-1 beta (IL-1β) indicating that eugenol mainly induced cell death by apoptosis. In conclusion, eugenol showed antiproliferative and cytotoxic effects via apoptosis and also synergism with cisplatin and ionizing radiation in the human cervical cancer cell line.
To improve and focus preclinical testing, we combine tumor models based on a decellularized tissue matrix with bioinformatics to stratify tumors according to stage-specific mutations that are linked to central cancer pathways. We generated tissue models with BRAF-mutant colorectal cancer (CRC) cells (HROC24 and HROC87) and compared treatment responses to two-dimensional (2D) cultures and xenografts. As the BRAF inhibitor vemurafenib is—in contrast to melanoma—not effective in CRC, we combined it with the EGFR inhibitor gefitinib. In general, our 3D models showed higher chemoresistance and in contrast to 2D a more active HGFR after gefitinib and combination-therapy. In xenograft models murine HGF could not activate the human HGFR, stressing the importance of the human microenvironment. In order to stratify patient groups for targeted treatment options in CRC, an in silico topology with different stages including mutations and changes in common signaling pathways was developed. We applied the established topology for in silico simulations to predict new therapeutic options for BRAF-mutated CRC patients in advanced stages. Our in silico tool connects genome information with a deeper understanding of tumor engines in clinically relevant signaling networks which goes beyond the consideration of single drivers to improve CRC patient stratification.