Ramona Schmid

MetaSim—A Sequencing Simulator for Genomics and Metagenomics

Background The new research field of metagenomics is providing exciting insights into various, previously unclassified ecological systems. Next-generation sequencing technologies are producing a rapid increase of environmental data in public databases. There is great need for specialized software solutions and statistical methods for dealing with complex metagenome data sets. Methodology/Principal Findings To facilitate the development and improvement of metagenomic tools and the planning of metagenomic projects, we introduce a sequencing simulator called MetaSim. Our software can be used to generate collections of synthetic reads that reflect the diverse taxonomical composition of typical metagenome data sets. Based on a database of given genomes, the program allows the user to design a metagenome by specifying the number of genomes present at different levels of the NCBI taxonomy, and then to collect reads from the metagenome using a simulation of a number of different sequencing technologies. A population sampler optionally produces evolved sequences based on source genomes and a given evolutionary tree. Conclusions/Significance MetaSim allows the user to simulate individual read datasets that can be used as standardized test scenarios for planning sequencing projects or for benchmarking metagenomic software.

Comparison of normalization methods for Illumina BeadChip HumanHT-12 v3

BackgroundNormalization of microarrays is a standard practice to account for and minimize effects which are not due to the controlled factors in an experiment. There is an overwhelming number of different methods that can be applied, none of which is ideally suited for all experimental designs. Thus, it is important to identify a normalization method appropriate for the experimental setup under consideration that is neither too negligent nor too stringent. Major aim is to derive optimal results from the underlying experiment. Comparisons of different normalization methods have already been conducted, none of which, to our knowledge, comparing more than a handful of methods.ResultsIn the present study, 25 different ways of pre-processing Illumina Sentrix BeadChip array data are compared. Among others, methods provided by the BeadStudio software are taken into account. Looking at different statistical measures, we point out the ideal versus the actual observations. Additionally, we compare qRT-PCR measurements of transcripts from different ranges of expression intensities to the respective normalized values of the microarray data. Taking together all different kinds of measures, the ideal method for our dataset is identified.ConclusionsPre-processing of microarray gene expression experiments has been shown to influence further downstream analysis to a great extent and thus has to be carefully chosen based on the design of the experiment. This study provides a recommendation for deciding which normalization method is best suited for a particular experimental setup.

Phenocopy - a strategy to qualify chemical compounds during hit-to-lead and/or lead optimization

A phenocopy is defined as an environmentally induced phenotype of one individual which is identical to the genotype-determined phenotype of another individual. The phenocopy phenomenon has been translated to the drug discovery process as phenotypes produced by the treatment of biological systems with new chemical entities (NCE) may resemble environmentally induced phenotypic modifications. Various new chemical entities exerting inhibition of the kinase activity of Transforming Growth Factor β Receptor I (TGF-βR1) were qualified by high-throughput RNA expression profiling. This chemical genomics approach resulted in a precise time-dependent insight to the TGF-β biology and allowed furthermore a comprehensive analysis of each NCEs off-target effects. The evaluation of off-target effects by the phenocopy approach allows a more accurate and integrated view on optimized compounds, supplementing classical biological evaluation parameters such as potency and selectivity. It has therefore the potential to become a novel method for ranking compounds during various drug discovery phases.

Urinary Exosomal miRNA Signature in Type II Diabetic Nephropathy Patients.

MicroRNAs (miRNAs) are short non-coding RNA species which are important post-transcriptional regulators of gene expression and play an important role in the pathogenesis of diabetic nephropathy. miRNAs are present in urine in a remarkably stable form packaged in extracellular vesicles, predominantly exosomes. In the present study, urinary exosomal miRNA profiling was conducted in urinary exosomes obtained from 8 healthy controls (C), 8 patients with type II diabetes (T2D) and 8 patients with type II diabetic nephropathy (DN) using Agilent´s miRNA microarrays. In total, the expression of 16 miRNA species was deregulated (>2-fold) in DN patients compared to healthy donors and T2D patients: the expression of 14 miRNAs (miR-320c, miR-6068, miR-1234-5p, miR-6133, miR-4270, miR-4739, miR-371b-5p, miR-638, miR-572, miR-1227-5p, miR-6126, miR-1915-5p, miR-4778-5p and miR-2861) was up-regulated whereas the expression of 2 miRNAs (miR-30d-5p and miR-30e-5p) was down-regulated. Most of the deregulated miRNAs are involved in progression of renal diseases. Deregulation of urinary exosomal miRNAs occurred in micro-albuminuric DN patients but not in normo-albuminuric DN patients. We used qRT-PCR based analysis of the most strongly up-regulated miRNAs in urinary exosomes from DN patients, miRNAs miR-320c and miR-6068. The correlation of miRNA expression and micro-albuminuria levels could be replicated in a confirmation cohort. In conclusion, urinary exosomal miRNA content is altered in type II diabetic patients with DN. Deregulated miR-320c, which might have an impact on the TGF-β-signaling pathway via targeting thrombospondin 1 (TSP-1) shows promise as a novel candidate marker for disease progression in type II DN that should be evaluated in future studies.

A comparison of RNA-seq and exon arrays for whole genome transcription profiling of the L5 spinal nerve transection model of neuropathic pain in the rat

BackgroundThe past decade has seen an abundance of transcriptional profiling studies of preclinical models of persistent pain, predominantly employing microarray technology. In this study we directly compare exon microarrays to RNA-seq and investigate the ability of both platforms to detect differentially expressed genes following nerve injury using the L5 spinal nerve transection model of neuropathic pain. We also investigate the effects of increasing RNA-seq sequencing depth. Finally we take advantage of the “agnostic” approach of RNA-seq to discover areas of expression outside of annotated exons that show marked changes in expression following nerve injury.ResultsRNA-seq and microarrays largely agree in terms of the genes called as differentially expressed. However, RNA-seq is able to interrogate a much larger proportion of the genome. It can also detect a greater number of differentially expressed genes than microarrays, across a wider range of fold changes and is able to assign a larger range of expression values to the genes it measures. The number of differentially expressed genes detected increases with sequencing depth. RNA-seq also allows the discovery of a number of genes displaying unusual and interesting patterns of non-exonic expression following nerve injury, an effect that cannot be detected using microarrays.ConclusionWe recommend the use of RNA-seq for future high-throughput transcriptomic experiments in pain studies. RNA-seq allowed the identification of a larger number of putative candidate pain genes than microarrays and can also detect a wider range of expression values in a neuropathic pain model. In addition, RNA-seq can interrogate the whole genome regardless of prior annotations, being able to detect transcription from areas of the genome not currently annotated as exons. Some of these areas are differentially expressed following nerve injury, and may represent novel genes or isoforms. We also recommend the use of a high sequencing depth in order to detect differential expression for genes with low levels of expression.

Genome-wide transcriptional profiling of skin and dorsal root ganglia after ultraviolet-B-induced inflammation.

Ultraviolet-B (UVB)-induced inflammation produces a dose-dependent mechanical and thermal hyperalgesia in both humans and rats, most likely via inflammatory mediators acting at the site of injury. Previous work has shown that the gene expression of cytokines and chemokines is positively correlated between species and that these factors can contribute to UVB-induced pain. In order to investigate other potential pain mediators in this model we used RNA-seq to perform genome-wide transcriptional profiling in both human and rat skin at the peak of hyperalgesia. In addition we have also measured transcriptional changes in the L4 and L5 DRG of the rat model. Our data show that UVB irradiation produces a large number of transcriptional changes in the skin: 2186 and 3888 genes are significantly dysregulated in human and rat skin, respectively. The most highly up-regulated genes in human skin feature those encoding cytokines (IL6 and IL24), chemokines (CCL3, CCL20, CXCL1, CXCL2, CXCL3 and CXCL5), the prostanoid synthesising enzyme COX-2 and members of the keratin gene family. Overall there was a strong positive and significant correlation in gene expression between the human and rat (R = 0.8022). In contrast to the skin, only 39 genes were significantly dysregulated in the rat L4 and L5 DRGs, the majority of which had small fold change values. Amongst the most up-regulated genes in DRG were REG3B, CCL2 and VGF. Overall, our data shows that numerous genes were up-regulated in UVB irradiated skin at the peak of hyperalgesia in both human and rats. Many of the top up-regulated genes were cytokines and chemokines, highlighting again their potential as pain mediators. However many other genes were also up-regulated and might play a role in UVB-induced hyperalgesia. In addition, the strong gene expression correlation between species re-emphasises the value of the UVB model as translational tool to study inflammatory pain.

Leucine-Rich Repeat Kinase 2 Modulates Retinoic Acid-Induced Neuronal Differentiation of Murine Embryonic Stem Cells

Background Dominant mutations in the leucine-rich repeat kinase 2 (LRRK2) gene are the most prevalent cause of Parkinsons disease, however, little is known about the biological function of LRRK2 protein. LRRK2 is expressed in neural precursor cells suggesting a role in neurodevelopment. Methodology/Principal Findings In the present study, differential gene expression profiling revealed a faster silencing of pluripotency-associated genes, like Nanog, Oct4, and Lin28, during retinoic acid-induced neuronal differentiation of LRRK2-deficient mouse embryonic stem cells compared to wildtype cultures. By contrast, expression of neurotransmitter receptors and neurotransmitter release was increased in LRRK2+/− cultures indicating that LRRK2 promotes neuronal differentiation. Consistently, the number of neural progenitor cells was higher in the hippocampal dentate gyrus of adult LRRK2-deficient mice. Alterations in phosphorylation of the putative LRRK2 substrates, translation initiation factor 4E binding protein 1 and moesin, do not appear to be involved in altered differentiation, rather there is indirect evidence that a regulatory signaling network comprising retinoic acid receptors, let-7 miRNA and downstream target genes/mRNAs may be affected in LRRK2-deficient stem cells in culture. Conclusion/Significance Parkinsons disease-linked LRRK2 mutations that associated with enhanced kinase activity may affect retinoic acid receptor signaling during neurodevelopment and/or neuronal maintenance as has been shown in other mouse models of chronic neurodegenerative diseases.

Characterization of Micro-RNA Changes during the Progression of Type 2 Diabetes in Zucker Diabetic Fatty Rats

The aim of the present pilot study was the identification of micro-RNA changes over time during the development and progression of type 2 diabetes (T2D) in Zucker diabetic fatty rats (ZDF rats). T2D is a complex metabolic disorder that is characterized, inter alia, by progressive failure of pancreatic β cells to produce insulin, but also by functional or morphological modifications of others organ, such as liver, adipose tissue and the cardiovascular system. Micro-RNAs are a novel class of biomarkers that have the potential to represent biomarkers of disease progression. In this study, the onset and progression of diabetes was followed in ZDF rats from six weeks until 17 weeks of age. After an initial phase of hyperinsulinemia, the animals developed T2D and lost the capacity to produce sufficient insulin. Circulating miRNAs were measured from plasma samples at four time points: pre-diabetes (six weeks of age), hyperinsulinemia (eight weeks), β cell failure (11 weeks) and late-stage diabetes (17 weeks) using TaqMan miRNA arrays. Bioinformatic analysis revealed distinct changes of circulating miRNAs over time. Several miRNAs were found to be increased over the course of the disease progression, such as miR-122, miR-133, miR-210 and miR-375. The most significantly decreased miRNAs were miR-140, miR-151-3p, miR-185, miR-203, miR-434-3p and miR-450a. Some of the miRNAs have also been identified in type 2 diabetic patients recently and, therefore, may have the potential to be useful biomarkers for the disease progression of T2D and/or the treatment response for anti-diabetic medications.

Clonal Evolutionary Analysis during HER2 Blockade in HER2-Positive Inflammatory Breast Cancer: A Phase II Open-Label Clinical Trial of Afatinib +/- Vinorelbine

Background Inflammatory breast cancer (IBC) is a rare, aggressive form of breast cancer associated with HER2 amplification, with high risk of metastasis and an estimated median survival of 2.9 y. We performed an open-label, single-arm phase II clinical trial (ClinicalTrials.gov NCT01325428) to investigate the efficacy and safety of afatinib, an irreversible ErbB family inhibitor, alone and in combination with vinorelbine in patients with HER2-positive IBC. This trial included prospectively planned exome analysis before and after afatinib monotherapy. Methods and Findings HER2-positive IBC patients received afatinib 40 mg daily until progression, and thereafter afatinib 40 mg daily and intravenous vinorelbine 25 mg/m2 weekly. The primary endpoint was clinical benefit; secondary endpoints were objective response (OR), duration of OR, and progression-free survival (PFS). Of 26 patients treated with afatinib monotherapy, clinical benefit was achieved in 9 patients (35%), 0 of 7 trastuzumab-treated patients and 9 of 19 trastuzumab-naïve patients. Following disease progression, 10 patients received afatinib plus vinorelbine, and clinical benefit was achieved in 2 of 4 trastuzumab-treated and 0 of 6 trastuzumab-naïve patients. All patients had treatment-related adverse events (AEs). Whole-exome sequencing of tumour biopsies taken before treatment and following disease progression on afatinib monotherapy was performed to assess the mutational landscape of IBC and evolutionary trajectories during therapy. Compared to a cohort of The Cancer Genome Atlas (TCGA) patients with HER2-positive non-IBC, HER2-positive IBC patients had significantly higher mutational and neoantigenic burden, more frequent gain-of-function TP53 mutations and a recurrent 11q13.5 amplification overlapping PAK1. Planned exploratory analysis revealed that trastuzumab-naïve patients with tumours harbouring somatic activation of PI3K/Akt signalling had significantly shorter PFS compared to those without (p = 0.03). High genomic concordance between biopsies taken before and following afatinib resistance was observed with stable clonal structures in non-responding tumours, and evidence of branched evolution in 8 of 9 tumours analysed. Recruitment to the trial was terminated early following the LUX-Breast 1 trial, which showed that afatinib combined with vinorelbine had similar PFS and OR rates to trastuzumab plus vinorelbine but shorter overall survival (OS), and was less tolerable. The main limitations of this study are that the results should be interpreted with caution given the relatively small patient cohort and the potential for tumour sampling bias between pre- and post-treatment tumour biopsies. Conclusions Afatinib, with or without vinorelbine, showed activity in trastuzumab-naïve HER2-positive IBC patients in a planned subgroup analysis. HER2-positive IBC is characterized by frequent TP53 gain-of-function mutations and a high mutational burden. The high mutational load associated with HER2-positive IBC suggests a potential role for checkpoint inhibitor therapy in this disease. Trial Registration ClinicalTrials.gov NCT01325428

Modeling Pulmonary Disease Pathways Using Recombinant Adeno-Associated Virus 6.2

Viral vectors have been applied successfully to generate disease-related animal models and to functionally characterize target genes in vivo. However, broader application is still limited by complex vector production, biosafety requirements, and vector-mediated immunogenic responses, possibly interfering with disease-relevant pathways. Here, we describe adeno-associated virus (AAV) variant 6.2 as an ideal vector for lung delivery in mice, overcoming most of the aforementioned limitations. In a proof-of-concept study using AAV6.2 vectors expressing IL-13 and transforming growth factor-β1 (TGF-β1), we were able to induce hallmarks of severe asthma and pulmonary fibrosis, respectively. Phenotypic characterization and deep sequencing analysis of the AAV-IL-13 asthma model revealed a characteristic disease signature. Furthermore, suitability of the model for compound testing was also demonstrated by pharmacological intervention studies using an anti-IL-13 antibody and dexamethasone. Similarly, the AAV-TGF-β1 fibrosis model showed several disease-like pathophenotypes monitored by micro-computed tomography imaging and lung function measurement. Most importantly, analyses using stuffer control vectors demonstrated that in contrast to a common adenovirus-5 vector, AAV6.2 vectors did not induce any measurable inflammation and therefore carry a lower risk of altering relevant readouts. In conclusion, we propose AAV6.2 as an ideal vector system for the functional characterization of target genes in the context of pulmonary diseases in mice.