Replacing concurrent controls with virtual control groups in rat toxicity studies.

Virtual control groups (VCGs) in nonclinical toxicity represent the concept of using appropriate historical control data for replacing concurrent control group animals. Historical control data collected from standardized studies can serve as base for constructing VCGs and legacy study reports can be used as a benchmark to evaluate the VCG performance. Replacing concurrent controls of legacy studies with VCGs should ideally reproduce the results of these studies. Based on three four-week rat oral toxicity legacy studies with varying degrees of toxicity findings we developed a concept to evaluate VCG performance on different levels: the ability of VCGs to (i) reproduce statistically significant deviations from the concurrent control, (ii) reproduce test substance-related effects, and (iii) reproduce the conclusion of the toxicity study in terms of threshold dose, target organs, toxicological biomarkers (clinical pathology) and reversibility. Although VCGs have shown a low to moderate ability to reproduce statistical results, the general study conclusions remained unchanged. Our results provide a first indication that carefully selected historical control data can be used to replace concurrent control without impairing the general study conclusion. Additionally, the developed procedures and workflows lay the foundation for the future validation of virtual controls for a use in regulatory toxicology.

A standardised frankincense extract reduces disease activity in relapsing-remitting multiple sclerosis (the SABA phase IIa trial).

OBJECTIVE: To investigate whether oral administration of a standardised frankincense extract (SFE) is safe and reduces disease activity in patients with relapsing-remitting multiple sclerosis (RRMS). METHODS: We performed an investigator-initiated, bicentric phase IIa, open-label, baseline-to-treatment pilot study with an oral SFE in patients with RRMS (NCT01450124). After a 4-month baseline observation phase, patients were treated for 8 months with an option to extend treatment for up to 36 months. The primary outcome measures were the number and volume of contrast-enhancing lesions (CEL) measured in MRI during the 4-month treatment period compared with the 4-month baseline period. Eighty patients were screened at two centres, 38 patients were included in the trial, 28 completed the 8-month treatment period and 18 of these participated in the extension period. RESULTS: The SFE significantly reduced the median number of monthly CELs from 1.00 (IQR 0.75-3.38) to 0.50 (IQR 0.00-1.13; difference -0.625, 95% CI -1.25 to -0.50; P<0.0001) at months 5-8. We observed significantly less brain atrophy as assessed by parenchymal brain volume change (P=0.0081). Adverse events were generally mild (57.7%) or moderate (38.6%) and comprised mainly gastrointestinal symptoms and minor infections. Mechanistic studies showed a significant increase in regulatory CD4+ T cell markers and a significant decrease in interleukin-17A-producing CD8+ T cells indicating a distinct mechanism of action of the study drug. INTERPRETATION: The oral SFE was safe, tolerated well and exhibited beneficial effects on RRMS disease activity warranting further investigation in a controlled phase IIb or III trial. CLINICAL TRIAL REGISTRATION: NCT01450124; Results.

BCL6--regulated by AhR/ARNT and wild-type MEF2B--drives expression of germinal center markers MYBL1 and LMO2.

Genetic heterogeneity is widespread in tumors, but poorly documented in cell lines. According to immunoglobulin hypermutation analysis, the diffuse large B-cell lymphoma cell line U-2932 comprises two subpopulations faithfully representing original tumor subclones. We set out to identify molecular causes underlying subclone-specific expression affecting 221 genes including surface markers and the germinal center oncogenes BCL6 and MYC. Genomic copy number variations explained 58/221 genes differentially expressed in the two U-2932 clones. Subclone-specific expression of the aryl-hydrocarbon receptor (AhR) and the resulting activity of the AhR/ARNT complex underlaid differential regulation of 11 genes including MEF2B. Knock-down and inhibitor experiments confirmed that AhR/ARNT regulates MEF2B, a key transcription factor for BCL6. AhR, MEF2B and BCL6 levels correlated not only in the U-2932 subclones but in the majority of 23 cell lines tested, indicting overexpression of AhR as a novel mechanism behind BCL6 diffuse large B-cell lymphoma. Enforced modulation of BCL6 affected 48/221 signature genes. Although BCL6 is known as a transcriptional repressor, 28 genes were up-regulated, including LMO2 and MYBL1 which, like BCL6, signify germinal center diffuse large B-cell lymphoma. Supporting the notion that BCL6 can induce gene expression, BCL6 and the majority of potential targets were co-regulated in a series of B-cell lines. In conclusion, genomic copy number aberrations, activation of AhR/ARNT, and overexpression of BCL6 are collectively responsible for differential expression of more than 100 genes in subclones of the U-2932 cell line. It is particularly interesting that BCL6 - regulated by AhR/ARNT and wild-type MEF2B - may drive expression of germinal center markers in diffuse large B-cell lymphoma.

opm: an R package for analysing OmniLog(R) phenotype microarray data.

SUMMARY: opm is an R package designed to analyse multidimensional OmniLog® phenotype microarray (PM) data. opm provides management, visualization and statistical analysis of PM data, including curve-parameter estimation and discretization, dedicated and customizable plots, metadata management, automated generation of textual and tabular reports, mapping of substrates to databases, batch conversion of files and export to phylogenetic software in the YAML markup language. AVAILABILITY: opm is distributed under the GPL through the Comprehensive R Archive Network (http://cran.r-project.org/package=opm) along with a comprehensive manual and a user-friendly tutorial. Further information may be found at http://www.dsmz.de/research/microorganisms/projects/. CONTACT: johannes.sikorski@dsmz.de.

The road to virtual control groups and the importance of proper body-weight selection.

Virtual control groups (VCGs) created from historical control data (HCD) can reduce the number of concurrent control group animals needed in regulatory toxicity studies by up to 25%. This study investigates the performance of VCGs on statistical outcomes of body weight development between treatment and control groups in legacy studies. The objective is to reproduce the statistical outcomes of 28-day sub-chronic studies (legacy studies) after replacing the concurrent control group with virtual ones. In rodent toxicity studies initial body weight is used as surrogate for the age of animals. For the assessment of VCG-sampling methods three different approaches are explored: (i) sampling VCGs from the entire HCD ignoring initial body weight information of the legacy study, (ii) sampling from HCD matching the legacy study's initial body weights, and (iii) sampling from HCD with assigned statistical weights derived from legacy study initial body weight information. It is shown that the ability to reproduce statistical outcomes by virtual controls is mainly determined by the congruence between the legacy study and the HCD weight distribution: regardless of the chosen approach, the ability to reproduce statistical outcomes was well for VCGs when the legacy study's initial-body-weight distribution was similar to the HCD's. When the initial body weight range of the legacy study was at the extreme ends of the HCD's distribution, the weighted-sampling approach was superior. This article highlights the importance of proper HCD-matching by the legacy study's initial body weight and discusses required conditions to accurately reproduce body weight development.

Animal control data from past studies performed in a standardized manner can be used to create virtual control groups (VCGs) to use in new studies instead of control animals. This approach can reduce the number of study animals by up to 25%. This study assesses the performance of VCGs selected by body weight in rat studies. The objective was to reproduce the original study results as closely as possible after replacing the original control group values with VCGs from a pool of historical control values. Several methods for selecting control animal data to create VCGs were compared. Among these, assigning statistical weights to the sampling pool yielded the best performance. Ideally the body weight distributions on day 1 of the study should be similar between the VCG and the original study animals. This article shows that proper selection VCGs can yield reliable study data with fewer animals.

Impacts of pr-10a overexpression at the molecular and the phenotypic level.

Biotechnological approaches using genetic modifications such as homologous gene overexpression can be used to decode gene functions under well-defined circumstances. However, only the recording of the resulting phenotypes allows inferences about the impact of the modification on the organisms' evolutionary, ecological or economic performance. We here compare a potato wild-type cell line with two genetically engineered cell cultures homologously overexpressing Pathogenesis Related Protein 10a (pr-10a). A detailed analysis of the relative gene-expression patterns of pr-10a and its regulators sebf and pti4 over time provides insights into the molecular response of heterotrophic cells to distinct osmotic and salt-stress conditions. Furthermore, this system serves as an exemplar for the tracing of respiration kinetics as a faster and more sensitive alternative to the laborious and time-consuming recording of growth curves. The utility and characteristics of the resulting data type and the requirements for its appropriate analysis are figured out. It is demonstrated how this novel type of phenotypic information together with the gene-expression-data provides valuable insights into the effect of genetic modifications on the behaviour of cells on both the molecular and the macroscopic level.

Impact of pr-10a overexpression on the cryopreservation success of Solanum tuberosum suspension cultures.

Although many genes are supposed to be a part of plant cell tolerance mechanisms against osmotic or salt stress, their influence on tolerance towards stress during cryopreservation procedures has rarely been investigated. For instance, the overexpression of the pathogenesis-related gene 10a (pr-10a) leads to improved osmotic tolerance in a transgenic cell culture of Solanum tuberosum cv. Désirée. In this study, a cryopreservation method, consisting of osmotic pretreatment, cryoprotection with DMSO and controlled-rate freezing, was used to characterize the relation between cryopreservation success and pr-10a expression in suspension cultures of S. tuberosum wild-type cells and cells overexpressing pathogenesis-related protein 10a (Pr-10a). By varying the sorbitol concentration, thus modifying the strength of the osmotic stress during the pretreatment phase, it can be shown that the wild type can successfully be cryopreserved only in a relatively narrow range of sorbitol concentrations, while the pr-10a overexpression leads to an enhanced cryopreservation success over the whole range of applied sorbitol concentrations. Together with transcription data we show that the pr-10a overexpression causes an enhanced osmotic tolerance, which in turn leads to enhanced cryopreservability, but also indicates a role of pr-10a in signal transduction. An increased cryopreservability of the transgenic cell line occurs for pretreatments longer than 24 h. Since both genotypes, characterized by distinct baseline levels of expression, exhibited similar patterns of expression induction, the induction of pr-10a appears to be a key step in the stress signal transduction of plant cells under osmotic stress.

Charcoal filter paper improves the viability of cryopreserved filamentous ectomycorrhizal and saprotrophic Basidiomycota and Ascomycota.

We assessed viability of 18 strains of filamentous ectomycorrhizal and saprotrophic basid-iomycetes and ascomycetes after cryopreservation with a novel technique based on charcoal filter paper strips (CFS). The results indicate that axenic fungal cultures grown on CFS recovered from freezing within a few days, even though none survived cryopreservation by the conventional straw method. Fungal growth on CFS was more vigorous, with morphological differentiations such as rhizomorphs and an increased amount of aerial mycelia compared to the unamended culture media. Accordingly CFS allows the cryopreservation of a wide range of rare and important ectomycorrhizal and saprotrophic fungi, which hitherto were difficult to revive from liquid nitrogen storage with the conventional and widely applied straw technique.

The Target Residence Time of Antihistamines Determines Their Antagonism of the G Protein-Coupled Histamine H1 Receptor.

The pharmacodynamics of drug-candidates is often optimized by metrics that describe target binding (Kd or Ki value) or target modulation (IC50). However, these metrics are determined at equilibrium conditions, and consequently information regarding the onset and offset of target engagement and modulation is lost. Drug-target residence time is a measure for the lifetime of the drug-target complex, which has recently been receiving considerable interest, as target residence time is shown to have prognostic value for the in vivo efficacy of several drugs. In this study, we have investigated the relation between the increased residence time of antihistamines at the histamine H1 receptor (H1R) and the duration of effective target-inhibition by these antagonists. Hela cells, endogenously expressing low levels of the H1R, were incubated with a series of antihistamines and dissociation was initiated by washing away the unbound antihistamines. Using a calcium-sensitive fluorescent dye and a label free, dynamic mass redistribution based assay, functional recovery of the H1R responsiveness was measured by stimulating the cells with histamine over time, and the recovery was quantified as the receptor recovery time. Using these assays, we determined that the receptor recovery time for a set of antihistamines differed more than 40-fold and was highly correlated to their H1R residence times, as determined with competitive radioligand binding experiments to the H1R in a cell homogenate. Thus, the receptor recovery time is proposed as a cell-based and physiologically relevant metric for the lead optimization of G protein-coupled receptor antagonists, like the H1R antagonists. Both, label-free or real-time, classical signaling assays allow an efficient and physiologically relevant determination of kinetic properties of drug molecules.

Light spectrum modifies the utilization pattern of energy sources in Pseudomonas sp. DR 5-09.

Despite the overruling impact of light in the phyllosphere, little is known regarding the influence of light spectra on non-phototrophic bacteria colonizing the leaf surface. We developed an in vitro method to study phenotypic profile responses of bacterial pure cultures to different bands of the visible light spectrum using monochromatic (blue: 460 nm; red: 660 nm) and polychromatic (white: 350-990 nm) LEDs, by modification and optimization of a protocol for the Phenotype MicroArray™ technique (Biolog Inc., CA, USA). The new protocol revealed high reproducibility of substrate utilization under all conditions tested. Challenging the non-phototrophic bacterium Pseudomonas sp. DR 5-09 with white, blue, and red light demonstrated that all light treatments affected the respiratory profile differently, with blue LED having the most decisive impact on substrate utilization by impairing respiration of 140 substrates. The respiratory activity was decreased on 23 and 42 substrates under red and white LEDs, respectively, while utilization of one, 16, and 20 substrates increased in the presence of red, blue, and white LEDs, respectively. Interestingly, on four substrates contrasting utilization patterns were found when the bacterium was exposed to different light spectra. Although non-phototrophic bacteria do not rely directly on light as an energy source, Pseudomonas sp. DR 5-09 changed its respiratory activity on various substrates differently when exposed to different lights. Thus, ability to sense and distinguish between different wavelengths even within the visible light spectrum must exist, and leads to differential regulation of substrate usage. With these results, we hypothesize that different light spectra might be a hitherto neglected key stimulus for changes in microbial lifestyle and habits of substrate usage by non-phototrophic phyllospheric microbiota, and thus might essentially stratify leaf microbiota composition and diversity.

MicroRNAs in the Host Response to Viral Infections of Veterinary Importance.

The discovery of small regulatory non-coding RNAs has been an exciting advance in the field of genomics. MicroRNAs (miRNAs) are endogenous RNA molecules, approximately 22 nucleotides in length, that regulate gene expression, mostly at the posttranscriptional level. MiRNA profiling technologies have made it possible to identify and quantify novel miRNAs and to study their regulation and potential roles in disease pathogenesis. Although miRNAs have been extensively investigated in viral infections of humans, their implications in viral diseases affecting animals of veterinary importance are much less understood. The number of annotated miRNAs in different animal species is growing continuously, and novel roles in regulating host-pathogen interactions are being discovered, for instance, miRNA-mediated augmentation of viral transcription and replication. In this review, we present an overview of synthesis and function of miRNAs and an update on the current state of research on host-encoded miRNAs in the genesis of viral infectious diseases in their natural animal host as well as in selected in vivo and in vitro laboratory models.

Transcriptomic Biomarkers for Tuberculosis: Evaluation of DOCK9. EPHA4, and NPC2 mRNA Expression in Peripheral Blood.

Lately, much effort has been made to find mRNA biomarkers for tuberculosis (TB) disease/infection with microarray-based approaches. In a pilot investigation, through RNA sequencing technology, we observed a prominent modulation of DOCK9, EPHA4, and NPC2 mRNA abundance in the blood of TB patients. To corroborate these findings, independent validations were performed in cohorts from different areas. Gene expression levels in blood were evaluated by quantitative real-time PCR (Brazil, n = 129) or reanalysis of public microarray data (UK: n = 96; South Africa: n = 51; Germany: n = 26; and UK/France: n = 63). In the Brazilian cohort, significant modulation of all target-genes was observed comparing TB vs. healthy recent close TB contacts (rCt). With a 92% specificity, NPC2 mRNA high expression (NPC2high) showed the highest sensitivity (85%, 95% CI 65%-96%; area under the ROC curve [AUROC] = 0.88), followed by EPHA4 (53%, 95% CI 33%-73%, AUROC = 0.73) and DOCK9 (19%, 95% CI 7%-40%; AUROC = 0.66). All the other reanalyzed cohorts corroborated the potential of NPC2high as a biomarker for TB (sensitivity: 82-100%; specificity: 94-97%). An NPC2high profile was also observed in 60% (29/48) of the tuberculin skin test positive rCt, and additional follow-up evaluation revealed changes in the expression levels of NPC2 during the different stages of Mycobacterium tuberculosis infection, suggesting that further studies are needed to evaluate modulation of this gene during latent TB and/or progression to active disease. Considering its high specificity, our data indicate, for the first time, that NPC2high might serve as an accurate single-gene biomarker for TB.

Making sense of big data in health research: Towards an EU action plan.

Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of "big data" for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health and healthcare for all Europeans.

Phenotypic profiling of Scedosporium aurantiacum, an opportunistic pathogen colonizing human lungs.

Genotyping studies of Australian Scedosporium isolates have revealed the strong prevalence of a recently described species: Scedosporium aurantiacum. In addition to occurring in the environment, this fungus is also known to colonise the respiratory tracts of cystic fibrosis (CF) patients. A high throughput Phenotype Microarray (PM) analysis using 94 assorted substrates (sugars, amino acids, hexose-acids and carboxylic acids) was carried out for four isolates exhibiting different levels of virulence, determined using a Galleria mellonella infection model. A significant difference was observed in the substrate utilisation patterns of strains displaying differential virulence. For example, certain sugars such as sucrose (saccharose) were utilised only by low virulence strains whereas some sugar derivatives such as D-turanose promoted respiration only in the more virulent strains. Strains with a higher level of virulence also displayed flexibility and metabolic adaptability at two different temperature conditions tested (28 and 37°C). Phenotype microarray data were integrated with the whole-genome sequence data of S. aurantiacum to reconstruct a pathway map for the metabolism of selected substrates to further elucidate differences between the strains.

Visualization and curve-parameter estimation strategies for efficient exploration of phenotype microarray kinetics.

BACKGROUND: The Phenotype MicroArray (OmniLog® PM) system is able to simultaneously capture a large number of phenotypes by recording an organism's respiration over time on distinct substrates. This technique targets the object of natural selection itself, the phenotype, whereas previously addressed '-omics' techniques merely study components that finally contribute to it. The recording of respiration over time, however, adds a longitudinal dimension to the data. To optimally exploit this information, it must be extracted from the shapes of the recorded curves and displayed in analogy to conventional growth curves. METHODOLOGY: The free software environment R was explored for both visualizing and fitting of PM respiration curves. Approaches using either a model fit (and commonly applied growth models) or a smoothing spline were evaluated. Their reliability in inferring curve parameters and confidence intervals was compared to the native OmniLog® PM analysis software. We consider the post-processing of the estimated parameters, the optimal classification of curve shapes and the detection of significant differences between them, as well as practically relevant questions such as detecting the impact of cultivation times and the minimum required number of experimental repeats. CONCLUSIONS: We provide a comprehensive framework for data visualization and parameter estimation according to user choices. A flexible graphical representation strategy for displaying the results is proposed, including 95% confidence intervals for the estimated parameters. The spline approach is less prone to irregular curve shapes than fitting any of the considered models or using the native PM software for calculating both point estimates and confidence intervals. These can serve as a starting point for the automated post-processing of PM data, providing much more information than the strict dichotomization into positive and negative reactions. Our results form the basis for a freely available R package for the analysis of PM data.