DataXflow: Synergizing data-driven modeling with best parameter fit and optimal control - An efficient data analysis for cancer research.

Building data-driven models is an effective strategy for information extraction from empirical data. Adapting model parameters specifically to data with a best fitting approach encodes the relevant information into a mathematical model. Subsequently, an optimal control framework extracts the most efficient targets to steer the model into desired changes via external stimuli. The DataXflow software framework integrates three software pipelines, D2D for model fitting, a framework solving optimal control problems including external stimuli and JimenaE providing graphical user interfaces to employ the other frameworks lowering the barriers for the need of programming skills, and simultaneously automating reoccurring modeling tasks. Such tasks include equation generation from a graph and script generation allowing also to approach systems with many agents, like complex gene regulatory networks. A desired state of the model is defined, and therapeutic interventions are modeled as external stimuli. The optimal control framework purposefully exploits the model-encoded information by providing those external stimuli that effect the desired changes most efficiently. The implementation of DataXflow is available under https://github.com/MarvelousHopefull/DataXflow. We showcase its application by detecting specific drug targets for a therapy of lung cancer from measurement data to lower proliferation and increase apoptosis. By an iterative modeling process refining the topology of the model, the regulatory network of the tumor is generated from the data. An application of the optimal control framework in our example reveals the inhibition of AURKA and the activation of CDH1 as the most efficient drug target combination. DataXflow paves the way to an agile interplay between data generation and its analysis potentially accelerating cancer research by an efficient drug target identification, even in complex networks.

Cat-E: A comprehensive web tool for exploring cancer targeting strategies.

Identifying potential cancer-associated genes and drug targets from omics data is challenging due to its diverse sources and analyses, requiring advanced skills and large amounts of time. To facilitate such analysis, we developed Cat-E (Cancer Target Explorer), a novel R/Shiny web tool designed for comprehensive analysis with evaluation according to cancer-related omics data. Cat-E is accessible at https://cat-e.bioinfo-wuerz.eu/. Cat-E compiles information on oncolytic viruses, cell lines, gene markers, and clinical studies by integrating molecular datasets from key databases such as OvirusTB, TCGA, DrugBANK, and PubChem. Users can use all datasets and upload their data to perform multiple analyses, such as differential gene expression analysis, metabolic pathway exploration, metabolic flux analysis, GO and KEGG enrichment analysis, survival analysis, immune signature analysis, single nucleotide variation analysis, dynamic analysis of gene expression changes and gene regulatory network changes, and protein structure prediction. Cancer target evaluation by Cat-E is demonstrated here on lung adenocarcinoma (LUAD) datasets. By offering a user-friendly interface and detailed user manual, Cat-E eliminates the need for advanced computational expertise, making it accessible to experimental biologists, undergraduate and graduate students, and oncology clinicians. It serves as a valuable tool for investigating genetic variations across diverse cancer types, facilitating the identification of novel diagnostic markers and potential therapeutic targets.

Calcineurin and mTOR inhibitors in kidney transplantation: integrative metamodeling on transplant survival and kidney function.

In our study, we examined the efficacy of mTOR (mammalian target of rapamycin) inhibitors, specifically rapamycin (Rap), compared to calcineurin inhibitors (CNIs) in kidney transplantation. By conducting a comprehensive search across reputable databases (EMBASE, Scopus, PubMed, Cochrane, and Crossref), we gathered data for a six-month post-transplantation period. Our analysis revealed that mTOR inhibitor administration resulted in improved glomerular filtration rate (GFR) and serum creatinine levels. However, it is important to note that the mTOR inhibitor group had a higher incidence of acute rejection after biopsy. Through molecular modeling, we observed that Rap exhibited a superior binding affinity for mTOR compared to CNIs' binding to calcineurin, probably contributing to the transplant rejection. Our meta-analysis supports the cautious use of an optimal mTOR inhibitor in conjunction with careful consideration of clinical features when minimizing CNIs early in the transplantation process. This is because mTOR inhibitors have complementary mechanisms of action, a low nephrotoxicity profile, and favorable outcomes in serum creatinine and GFR, which contribute to improved transplant survival.

PRO-Simat: Protein network simulation and design tool.

PRO-Simat is a simulation tool for analysing protein interaction networks, their dynamic change and pathway engineering. It provides GO enrichment, KEGG pathway analyses, and network visualisation from an integrated database of more than 8 million protein-protein interactions across 32 model organisms and the human proteome. We integrated dynamical network simulation using the Jimena framework, which quickly and efficiently simulates Boolean genetic regulatory networks. It enables simulation outputs with in-depth analysis of the type, strength, duration and pathway of the protein interactions on the website. Furthermore, the user can efficiently edit and analyse the effect of network modifications and engineering experiments. In case studies, applications of PRO-Simat are demonstrated: (i) understanding mutually exclusive differentiation pathways in Bacillus subtilis, (ii) making Vaccinia virus oncolytic by switching on its viral replication mainly in cancer cells and triggering cancer cell apoptosis and (iii) optogenetic control of nucleotide processing protein networks to operate DNA storage. Multilevel communication between components is critical for efficient network switching, as demonstrated by a general census on prokaryotic and eukaryotic networks and comparing design with synthetic networks using PRO-Simat. The tool is available at https://prosimat.heinzelab.de/ as a web-based query server.

Simplified urinary steroid profiling by LC-MS as diagnostic tool for malignancy in adrenocortical tumors.

OBJECTIVES: Preoperative identification of malignant adrenal tumors is challenging. 24-h urinary steroid profiling by LC-MS/MS and machine learning has demonstrated high diagnostic power, but the unavailability of bioinformatic models for public use has limited its routine application. We here aimed to increase usability with a novel classification model for the differentiation of adrenocortical adenoma (ACA) and adrenocortical carcinoma (ACC). METHODS: Eleven steroids (5-pregnenetriol, dehydroepiandrosterone, cortisone, cortisol, α-cortolone, tetrahydro-11-deoxycortisol, etiocholanolone, pregnenolone, pregnanetriol, pregnanediol, and 5-pregnenediol) were quantified by LC-MS/MS in 24-h urine samples from 352 patients with adrenal tumor (281 ACA, 71 ACC). Random forest modelling and decision tree algorithms were applied in training (n = 188) and test sets (n = 80) and independently validated in 84 patients with paired 24-h and spot urine. RESULTS: After examining different models, a decision tree using excretions of only 5-pregnenetriol and tetrahydro-11-deoxycortisol classified three groups with low, intermediate, and high risk for malignancy. 148/217 ACA were classified as being at low, 67 intermediate, and 2 high risk of malignancy. Conversely, none of the ACC demonstrated a low-risk profile leading to a negative predictive value of 100% for malignancy. In the independent validation cohort, the negative predictive value was again 100% in both 24-h urine and spot urine with a positive predictive value of 87.5% and 86.7%, respectively. CONCLUSIONS: This simplified LC-MS/MS-based classification model using 24-h-urine provided excellent results for exclusion of ACC and can help to avoid unnecessary surgeries. Analysis of spot urine led to similarly satisfactory results suggesting that cumbersome 24-h urine collection might be dispensable after future validation.

Nephroprotective potential of eugenol in a rat experimental model of chronic kidney injury; targeting NOX, TGF-ß, and Akt signaling.

Chronic kidney disease is a crucial health problem associated with high morbidity and mortality. Eugenol is a natural phenolic plant compound with various pharmacological activities including antioxidant and anti-inflammatory properties. This study was designed to evaluate the possible protective effect of different eugenol doses in an experimental model of chronic CCl4-induced renal damage and investigate various mechanisms that underlie this postulated effect. Eugenol treatment (100 mg/kg) ameliorated kidney damage induced by CCl4 and rectified the distorted kidney function parameters and renal histological structure. Additionally, eugenol at a dose of 100 mg/kg suppressed the upregulated oxidative stress, inflammation and apoptosis in CCl4-treated rats as evident by down regulations of NADPH oxidase (NOX2 and NOX4), proinflammatory markers (IL-6 and TNF-α) and proapoptotic markers (cyt c and caspase-3), respectively. Importantly, eugenol co-administration in rats challenged with CCl4 downregulated the renal protein expressions of both TGF-ß as well as pAkt compared with CCl4 group. In conclusion, eugenol showed a potent nephroprotective effect against CCl4-induced renal damage through its antioxidant, anti-inflammatory and anti-fibrotic activities.

In silico investigation of nonsynonymous single nucleotide polymorphisms in BCL2 apoptosis regulator gene to design novel protein-based drugs against cancer.

BCL2 apoptosis regulator gene encodes Bcl-2 pro-survival protein, which plays an important role to evade apoptosis in various cancers. Moreover, single nucleotide polymorphisms (SNPs) in the BCL2 gene can be nonsynonymous (nsSNPs), which might affect the protein stability and probably its function. Therefore, we implement cutting-edge computational techniques based on the Spherical Polar Fourier and Monte-Carlo algorithms to investigate the impact of these SNPs on the B cell lymphoma-2 (Bcl-2) stability and therapeutic potential of protein-based molecules to inhibit this protein. As a result, we identified two nsSNPs (Q118R and R129C) to be deleterious and highly conserved, having a negative effect on protein stability. Additionally, molecular docking and molecular dynamics simulations confirmed the decreased binding affinity of mutated Bcl-2 variants to bind three-helix bundle protein inhibitor as these mutations occurred in the protein-protein binding site. Overall, this computational approach investigating nsSNPs provides a useful basis for designing novel molecules to inhibit Bcl-2 pro-survival pathway in malignant cells.

Targeted metabolic profiling of urinary steroids with a focus on analytical accuracy and sample stability.

Introduction: Preoperative diagnostic workup of adrenal tumors is based on imaging and hormone analyses, but charged with uncertainties. Steroid profiling by liquid chromatography tandem mass spectrometry (LC-MS/MS) in 24-h urine has shown potential to discriminate benign and malignant adrenal tumors. Our aim was to develop and validate a specific and accurate LC-MS/MS method for the quantification of deconjugated urinary marker steroids, to evaluate their pre-analytical stability and to apply the method to clinical samples of patients with adrenal tumors. Methods: A method for the quantification of 11 deconjugated steroids (5-pregnenetriol, dehydroepiandrosterone, cortisone, cortisol, α-cortolone, tetrahydro-11-deoxycortisol, etiocholanolone, pregnenolone, pregnanetriol, pregnanediol, and 5-pregnenediol) in human urine was developed and validated based on international guidelines. Steroids were enzymatically deconjugated and extracted by solid phase extraction before LC-MS/MS quantification in positive electrospray ionization mode. Results: Excellent linearity with R2 > 0.99 and intra- and inter-day precisions of < 10.1 % were found. Relative matrix effects were between 96.4 % and 101.6 % and relative recovery was between 98.2 % and 115.0 %. Sufficient pre-freeze stability for all steroids in urine was found at 20-25 °C for seven days and at 4-6 °C for up to 28 days. Samples were stable during long-term storage at -20 °C and -80 °C for 6 months. Conclusions: A sensitive and robust LC-MS/MS method for the quantification of 11 urinary steroids was developed and validated according to international guidelines. Pre-analytical matrix stability was evaluated and the suitability of the method for the analysis of clinical samples and prospective validation studies was shown.

Optimization of synthetic molecular reporters for a mesenchymal glioblastoma transcriptional program by integer programing.

MOTIVATION: A recent approach to perform genetic tracing of complex biological problems involves the generation of synthetic deoxyribonucleic acid (DNA) probes that specifically mark cells with a phenotype of interest. These synthetic locus control regions (sLCRs), in turn, drive the expression of a reporter gene, such as fluorescent protein. To build functional and specific sLCRs, it is critical to accurately select multiple bona fide cis-regulatory elements from the target cell phenotype cistrome. This selection occurs by maximizing the number and diversity of transcription factors (TFs) within the sLCR, yet the size of the final sLCR should remain limited. RESULTS: In this work, we discuss how optimization, in particular integer programing, can be used to systematically address the construction of a specific sLCR and optimize pre-defined properties of the sLCR. Our presented instance of a linear optimization problem maximizes the activation potential of the sLCR such that its size is limited to a pre-defined length and a minimum number of all TFs deemed sufficiently characteristic for the phenotype of interest is covered. We generated an sLCR to trace the mesenchymal glioblastoma program in patients by solving our corresponding linear program with the software optimizer Gurobi. Considering the binding strength of transcription factor binding sites (TFBSs) with their TFs as a proxy for activation potential, the optimized sLCR scores similarly to an sLCR experimentally validated in vivo, and is smaller in size while having the same coverage of TFBSs. AVAILABILITY AND IMPLEMENTATION: We provide a Python implementation of the presented framework in the Supplementary Material with which an optimal selection of cis-regulatory elements can be calculated once the target set of TFs and their binding strength with their TFBSs is known. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A modular systems biological modelling framework studies cyclic nucleotide signaling in platelets.

BACKGROUND: The cyclic nucleotides cAMP and cGMP inhibit platelet activation. Different platelet signaling modules work together. We develop here a modelling framework to integrate different signaling modules and apply it to platelets. RESULTS: We introduce a novel standardized bilinear coupling mechanism allowing sub model debugging and standardization of coupling with optimal data driven modelling by methods from optimization. Besides cAMP signaling our model considers specific cGMP effects including external stimuli by drugs. Moreover, the output of the cGMP module serves as input for a modular model of VASP phosphorylation and for the activity of cAMP and cGMP pathways in platelets. Experimental data driven modeling allows us to design models with quantitative output. We use the condensed information about involved regulation and system responses for modeling drug effects and obtaining optimal experimental settings. Stepwise further validation of our model is given by direct experimental data. CONCLUSIONS: We present a general framework for model integration using modules and their stimulus responses. We demonstrate it by a multi-modular model for platelet signaling focusing on cGMP and VASP phosphorylation. Moreover, this allows to estimate drug action on any of the inhibitory cyclic nucleotide pathways (cGMP, cAMP) and is supported by experimental data.

EMT, Stemness, and Drug Resistance in Biological Context: A 3D Tumor Tissue/In Silico Platform for Analysis of Combinatorial Treatment in NSCLC with Aggressive KRAS-Biomarker Signatures.

Epithelial-to-mesenchymal transition (EMT) is discussed to be centrally involved in invasion, stemness, and drug resistance. Experimental models to evaluate this process in its biological complexity are limited. To shed light on EMT impact and test drug response more reliably, we use a lung tumor test system based on a decellularized intestinal matrix showing more in vivo-like proliferation levels and enhanced expression of clinical markers and carcinogenesis-related genes. In our models, we found evidence for a correlation of EMT with drug resistance in primary and secondary resistant cells harboring KRASG12C or EGFR mutations, which was simulated in silico based on an optimized signaling network topology. Notably, drug resistance did not correlate with EMT status in KRAS-mutated patient-derived xenograft (PDX) cell lines, and drug efficacy was not affected by EMT induction via TGF-ß. To investigate further determinants of drug response, we tested several drugs in combination with a KRASG12C inhibitor in KRASG12C mutant HCC44 models, which, besides EMT, display mutations in P53, LKB1, KEAP1, and high c-MYC expression. We identified an aurora-kinase A (AURKA) inhibitor as the most promising candidate. In our network, AURKA is a centrally linked hub to EMT, proliferation, apoptosis, LKB1, and c-MYC. This exemplifies our systemic analysis approach for clinical translation of biomarker signatures.

Toward Zero Variance in Proteomics Sample Preparation: Positive-Pressure FASP in 96-Well Format (PF96) Enables Highly Reproducible, Time- and Cost-Efficient Analysis of Sample Cohorts.

As novel liquid chromatography-mass spectrometry (LC-MS) technologies for proteomics offer a substantial increase in LC-MS runs per day, robust and reproducible sample preparation emerges as a new bottleneck for throughput. We introduce a novel strategy for positive-pressure 96-well filter-aided sample preparation (PF96) on a commercial positive-pressure solid-phase extraction device. PF96 allows for a five-fold increase in throughput in conjunction with extraordinary reproducibility with Pearson product-moment correlations on the protein level of r = 0.9993, as demonstrated for mouse heart tissue lysate in 40 technical replicates. The targeted quantification of 16 peptides in the presence of stable-isotope-labeled reference peptides confirms that PF96 variance is barely assessable against technical variation from nanoLC-MS instrumentation. We further demonstrate that protein loads of 36-60 µg result in optimal peptide recovery, but lower amounts ≥3 µg can also be processed reproducibly. In summary, the reproducibility, simplicity, and economy of time provide PF96 a promising future in biomedical and clinical research.

Antibody ligation of CEACAM1, CEACAM3, and CEACAM6, differentially enhance the cytokine release of human neutrophils in responses to Candida albicans.

Invasive candidiasis is a healthcare-associated fungal infection with a high mortality rate. Neutrophils, the first line of defense during fungal infections, express the immunoregulatory Candida albicans receptors CEACAM1, CEACAM3, and CEACAM6. We analyzed the effects of specific antibodies on C. albicans-induced neutrophil responses. CEACAM6 ligation by 1H7-4B and to some extent CEACAM1 ligation by B3-17, but not CEACAM3 ligation by 308/3-3, resulted in the immediate release of stored CXCL8 and altered transcriptional responses of the C. albicans-stimulated neutrophils. Integrated network analyses and dynamic simulations of signaling cascades predicted alterations in apoptosis and cytokine secretion. We verified that CEACAM6 ligation enhanced Candida-induced neutrophil apoptosis and increased long-term IL-1ß/IL-6 release in responses to C. albicans. CEACAM3 ligation, but not CEACAM1 ligation, increased the long-term release of pro-inflammatory IL-1ß/IL-6. Taken together, we demonstrated for the first time that ligation of CEACAM receptors differentially affects the regulation of C. albicans-induced immune functions in human neutrophils.

A translational study: Involvement of miR-21-5p in development and maintenance of neuropathic pain via immune-related targets CCL5 and YWHAE.

Neuropathic pain occurs in more than half of the patients suffering from peripheral neuropathies. We investigated the role of microRNA (miR)-21 in neuropathic pain using a murine-human translational approach. We applied the spared nerve injury (SNI) model at the sciatic nerve of mice and assessed the potential analgesic effect of perineurial miR-21-5p inhibitor application. Immune-related targets of miR-21-5p were determined by a qRT-PCR based cytokine and chemokine array. Bioinformatical analysis identified potential miR-21-5p targets interacting with CC-chemokine ligand (CCL)5. We validated CCL5 and tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein (YWHAE), an interaction partner of miR-21-5p and CCL5, by qRT-PCR in murine common peroneal and tibial nerves. Validated candidates were then investigated in white blood cell and sural nerve biopsy samples of patients with focal to generalized pain syndromes, i.e. small fiber neuropathy (SFN), polyneuropathy (PNP), and nerve lesion (NL). We showed that perineurial miR-21-5p inhibition reverses SNI-induced mechanical and heat hypersensitivity in mice and found a reduction of the SNI-induced increase of the pro-inflammatory mediators CCL5 (p < 0.01), CCL17 (p < 0.05), and IL-12ß (p < 0.05) in miR-21-5p inhibitor-treated mice. In silico analysis revealed several predicted and validated targets for miR-21-5p with CCL5 interaction. Among these, we found lower YWHAE gene expression in mice after SNI and perineurial injections of a scrambled oligonucleotide compared to naïve mice (p < 0.05), but this was not changed by miR-21-5p inhibition. Furthermore, miR-21-5p inhibition led to a further increase of the SNI-induced increase in TGFß (p < 0.01). Patient biomaterial revealed different systemic expression patterns of miR-21-5p, with higher expression in SFN and lower expression in NL. Further, we showed higher systemic expression of pro-inflammatory mediators in white blood cells of SFN patients compared to healthy controls. We have conducted a translational study comparing results from animal models to human patients with three different neuropathic pain syndromes. We identified CCL5 as a miR-21 dependent common player in the mouse SNI model and the human painful disease SFN.

Influence of breast cancer risk factors on proliferation and DNA damage in human breast glandular tissues: role of intracellular estrogen levels, oxidative stress and estrogen biotransformation.

Breast cancer etiology is associated with both proliferation and DNA damage induced by estrogens. Breast cancer risk factors (BCRF) such as body mass index (BMI), smoking, and intake of estrogen-active drugs were recently shown to influence intratissue estrogen levels. Thus, the aim of the present study was to investigate the influence of BCRF on estrogen-induced proliferation and DNA damage in 41 well-characterized breast glandular tissues derived from women without breast cancer. Influence of intramammary estrogen levels and BCRF on estrogen receptor (ESR) activation, ESR-related proliferation (indicated by levels of marker transcripts), oxidative stress (indicated by levels of GCLC transcript and oxidative derivatives of cholesterol), and levels of transcripts encoding enzymes involved in estrogen biotransformation was identified by multiple linear regression models. Metabolic fluxes to adducts of estrogens with DNA (E-DNA) were assessed by a metabolic network model (MNM) which was validated by comparison of calculated fluxes with data on methoxylated and glucuronidated estrogens determined by GC- and UHPLC-MS/MS. Intratissue estrogen levels significantly influenced ESR activation and fluxes to E-DNA within the MNM. Likewise, all BCRF directly and/or indirectly influenced ESR activation, proliferation, and key flux constraints influencing E-DNA (i.e., levels of estrogens, CYP1B1, SULT1A1, SULT1A2, and GSTP1). However, no unambiguous total effect of BCRF on proliferation became apparent. Furthermore, BMI was the only BCRF to indeed influence fluxes to E-DNA (via congruent adverse influence on levels of estrogens, CYP1B1 and SULT1A2).

An In Vitro and In Silico Study of the Enhanced Antiproliferative and Pro-Oxidant Potential of Olea europaea L. cv. Arbosana Leaf Extract via Elastic Nanovesicles (Spanlastics).

The olive tree is a venerable Mediterranean plant and often used in traditional medicine. The main aim of the present study was to evaluate the effect of Olea europaea L. cv. Arbosana leaf extract (OLE) and its encapsulation within a spanlastic dosage form on the improvement of its pro-oxidant and antiproliferative activity against HepG-2, MCF-7, and Caco-2 human cancer cell lines. The LC-HRESIMS-assisted metabolomic profile of OLE putatively annotated 20 major metabolites and showed considerable in vitro antiproliferative activity against HepG-2, MCF-7, and Caco-2 cell lines with IC50 values of 9.2 ± 0.8, 7.1 ± 0.9, and 6.5 ± 0.7 µg/mL, respectively. The encapsulation of OLE within a (spanlastic) nanocarrier system, using a spraying method and Span 40 and Tween 80 (4:1 molar ratio), was successfully carried out (size 41 ± 2.4 nm, zeta potential 13.6 ± 2.5, and EE 61.43 ± 2.03%). OLE showed enhanced thermal stability, and an improved in vitro antiproliferative effect against HepG-2, MCF-7, and Caco-2 (IC50 3.6 ± 0.2, 2.3 ± 0.1, and 1.8 ± 0.1 µg/mL, respectively) in comparison to the unprocessed extract. Both preparations were found to exhibit pro-oxidant potential inside the cancer cells, through the potential inhibitory activity of OLE against glutathione reductase and superoxide dismutase (IC50 1.18 ± 0.12 and 2.33 ± 0.19 µg/mL, respectively). These inhibitory activities were proposed via a comprehensive in silico study to be linked to the presence of certain compounds in OLE. Consequently, we assume that formulating such a herbal extract within a suitable nanocarrier would be a promising improvement of its therapeutic potential.

Topological Analysis of the Carbon-Concentrating CETCH Cycle and a Photorespiratory Bypass Reveals Boosted CO2-Sequestration by Plants.

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.

Rapid proliferation due to better metabolic adaptation results in full virulence of a filament-deficient Candida albicans strain.

The ability of the fungal pathogen Candida albicans to undergo a yeast-to-hypha transition is believed to be a key virulence factor, as filaments mediate tissue damage. Here, we show that virulence is not necessarily reduced in filament-deficient strains, and the results depend on the infection model used. We generate a filament-deficient strain by deletion or repression of EED1 (known to be required for maintenance of hyphal growth). Consistent with previous studies, the strain is attenuated in damaging epithelial cells and macrophages in vitro and in a mouse model of intraperitoneal infection. However, in a mouse model of systemic infection, the strain is as virulent as the wild type when mice are challenged with intermediate infectious doses, and even more virulent when using low infectious doses. Retained virulence is associated with rapid yeast proliferation, likely the result of metabolic adaptation and improved fitness, leading to high organ fungal loads. Analyses of cytokine responses in vitro and in vivo, as well as systemic infections in immunosuppressed mice, suggest that differences in immunopathology contribute to some extent to retained virulence of the filament-deficient mutant. Our findings challenge the long-standing hypothesis that hyphae are essential for pathogenesis of systemic candidiasis by C. albicans.

Design, Synthesis, and Anticancer Screening for Repurposed Pyrazolo[3,4-d]pyrimidine Derivatives on Four Mammalian Cancer Cell Lines.

The present study reports the synthesis of new purine bioisosteres comprising a pyrazolo[3,4-d]pyrimidine scaffold linked to mono-, di-, and trimethoxy benzylidene moieties through hydrazine linkages. First, in silico docking experiments of the synthesized compounds against Bax, Bcl-2, Caspase-3, Ki67, p21, and p53 were performed in a trial to rationalize the observed cytotoxic activity for the tested compounds. The anticancer activity of these compounds was evaluated in vitro against Caco-2, A549, HT1080, and Hela cell lines. Results revealed that two (5 and 7) of the three synthesized compounds (5, 6, and 7) showed high cytotoxic activity against all tested cell lines with IC50 values in the micro molar concentration. Our in vitro results show that there is no significant apoptotic effect for the treatment with the experimental compounds on the viability of cells against A549 cells. Ki67 expression was found to decrease significantly following the treatment of cells with the most promising candidate: drug 7. The overall results indicate that these pyrazolopyrimidine derivatives possess anticancer activity at varying doses. The suggested mechanism of action involves the inhibition of the proliferation of cancer cells.

RhoA/Cdc42 signaling drives cytoplasmic maturation but not endomitosis in megakaryocytes.

Megakaryocytes (MKs), the precursors of blood platelets, are large, polyploid cells residing mainly in the bone marrow. We have previously shown that balanced signaling of the Rho GTPases RhoA and Cdc42 is critical for correct MK localization at bone marrow sinusoids in vivo. Using conditional RhoA/Cdc42 double-knockout (DKO) mice, we reveal here that RhoA/Cdc42 signaling is dispensable for the process of polyploidization in MKs but essential for cytoplasmic MK maturation. Proplatelet formation is virtually abrogated in the absence of RhoA/Cdc42 and leads to severe macrothrombocytopenia in DKO animals. The MK maturation defect is associated with downregulation of myosin light chain 2 (MLC2) and ß1-tubulin, as well as an upregulation of LIM kinase 1 and cofilin-1 at both the mRNA and protein level and can be linked to impaired MKL1/SRF signaling. Our findings demonstrate that MK endomitosis and cytoplasmic maturation are separately regulated processes, and the latter is critically controlled by RhoA/Cdc42.