Effect of RNA quality on transcript intensity levels in microarray analysis of human post-mortem brain tissues

<p>Abstract</p> <p>Background</p> <p>Large-scale gene expression analysis of post-mortem brain tissue offers unique opportunities for investigating genetic mechanisms of psychiatric and neurodegenerative disorders. On the other hand microarray data analysis associated with these studies is a challenging task. In this publication we address the issue of low RNA quality data and corresponding data analysis strategies.</p> <p>Results</p> <p>A detailed analysis of effects of post chip RNA quality on the measured abundance of transcripts is presented. Overall Affymetrix GeneChip data (HG-U133_AB and HG-U133_Plus_2.0) derived from ten different brain regions was investigated. Post chip RNA quality being assessed by 5'/3' ratio of housekeeping genes was found to introduce a well pronounced systematic noise into the measured transcript expression levels. According to this study RNA quality effects have: 1) a "random" component which is introduced by the technology and 2) a systematic component which depends on the features of the transcripts and probes. Random components mainly account for numerous negative correlations of low-abundant transcripts. These negative correlations are not reproducible and are mainly introduced by an increased relative level of noise. Three major contributors to the systematic noise component were identified: the first is the probe set distribution, the second is the length of mRNA species, and the third is the stability of mRNA species. Positive correlations reflect the 5'-end to 3'-end direction of mRNA degradation whereas negative correlations result from the compensatory increase in stable and 3'-end probed transcripts. Systematic components affect the expressed transcripts by introducing irrelevant gene correlations and can strongly influence the results of the main experiment. A linear model correcting the effect of RNA quality on measured intensities was introduced.</p> <p>In addition the contribution of a number of pre-mortem and post-mortem attributes to the overall detected RNA quality effect was investigated. Brain pH, duration of agonal stage, post-mortem interval before sampling and donor's age of death within considered limits were found to have no significant contribution.</p> <p>Conclusion</p> <p>Basic conclusions for data analysis in expression profiling study are as follows: 1) testing for RNA quality dependency should be included in the preprocessing of the data; 2) investigating inter-gene correlation without regard to RNA quality effects could be misleading; 3) data normalization procedures relying on housekeeping genes either do not influence the correlation structure (if 3'-end intensities are used) or increase it for negatively correlated transcripts (if 5'-end or median intensities are included in normalization procedure); 4) sample sets should be matched with regard to RNA quality; 5) RMA preprocessing is more sensitive to RNA quality effect, than MAS 5.0.</p

Characterization of Toll-like receptors in primary lung epithelial cells: strong impact of the TLR3 ligand poly(I:C) on the regulation of Toll-like receptors, adaptor proteins and inflammatory response

BACKGROUND: Bacterial and viral exacerbations play a crucial role in a variety of lung diseases including COPD or asthma. Since the lung epithelium is a major source of various inflammatory mediators that affect the immune response, we analyzed the inflammatory reaction of primary lung epithelial cells to different microbial molecules that are recognized by Toll-like receptors (TLR). METHODS: The effects of TLR ligands on primary small airway epithelial cells were analyzed in detail with respect to cytokine, chemokine and matrix metalloproteinase secretion. In addition, the regulation of the expression of TLRs and their adaptor proteins in small airway epithelial cells was investigated. RESULTS: Our data demonstrate that poly(I:C), a synthetic analog of viral dsRNA, mediated the strongest proinflammatory effects among the tested ligands, including an increased secretion of IL-6, IL-8, TNF-α, GM-CSF, GRO-α, TARC, MCP-1, MIP-3α, RANTES, IFN-β, IP-10 and ITAC as well as an increased release of MMP-1, MMP-8, MMP-9, MMP-10 and MMP-13. Furthermore, our data show that poly(I:C) as well as type-1 and type-2 cytokines have a pronounced effect on the expression of TLRs and molecules involved in TLR signaling in small airway epithelial cells. Poly(I:C) induced an elevated expression of TLR1, TLR2 and TLR3 and increased the gene expression of the general TLR adaptor MyD88 and IRAK-2. Simultaneously, poly(I:C) decreased the expression of TLR5, TLR6 and TOLLIP. CONCLUSION: Poly(I:C), an analog of viral dsRNA and a TLR3 ligand, triggers a strong inflammatory response in small airway epithelial cells that is likely to contribute to viral exacerbations of pulmonary diseases like asthma or COPD. The pronounced effects of poly(I:C) on the expression of Toll-like receptors and molecules involved in TLR signaling is assumed to influence the immune response of the lung epithelium to viral and bacterial infections. Likewise, the regulation of TLR expression by type-1 and type-2 cytokines is important considering the impact of exogenous and endogenous TLR ligands on Th1 or Th2 driven pulmonary inflammations like COPD or asthma, respectively

Genetic effects on molecular network states explain complex traits

The complexity of many cellular and organismal traits results from the integration of genetic and environmental factors via molecular networks. Network structure and effect propagation are best understood at the level of functional modules, but so far, no concept has been established to include the global network state. Here, we show when and how genetic perturbations lead to molecular changes that are confined to small parts of a network versus when they lead to modulation of network states. Integrating multi-omics profiling of genetically heterogeneous budding and fission yeast strains with an array of cellular traits identified a central state transition of the yeast molecular network that is related to PKA and TOR (PT) signaling. Genetic variants affecting this PT state globally shifted the molecular network along a single-dimensional axis, thereby modulating processes including energy and amino acid metabolism, transcription, translation, cell cycle control, and cellular stress response. We propose that genetic effects can propagate through large parts of molecular networks because of the functional requirement to centrally coordinate the activity of fundamental cellular processes

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 NCE's 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

Into the unknown: expression profiling without genome sequence information in CHO by next generation sequencing

The arrival of next-generation sequencing (NGS) technologies has led to novel opportunities for expression profiling and genome analysis by utilizing vast amounts of short read sequence data. Here, we demonstrate that expression profiling in organisms lacking any genome or transcriptome sequence information is feasible by combining Illumina’s mRNA-seq technology with a novel bioinformatics pipeline that integrates assembled and annotated Chinese hamster ovary (CHO) sequences with information derived from related organisms. We applied this pipeline to the analysis of CHO cells which were chosen as a model system owing to its relevance in the production of therapeutic proteins. Specifically, we analysed CHO cells undergoing butyrate treatment which is known to affect cell cycle regulation and to increase the specific productivity of recombinant proteins. By this means, we identified sequences for >13 000 CHO genes which added sequence information of ∼5000 novel genes to the CHO model. More than 6000 transcript sequences are predicted to be complete, as they covered >95% of the corresponding mouse orthologs. Detailed analysis of selected biological functions such as DNA replication and cell cycle control, demonstrated the potential of NGS expression profiling in organisms without extended genome sequence to improve both data quantity and quality

Next-generation insights into regulatory T cells: expression profiling and FoxP3 occupancy in Human

Regulatory T-cells (Treg) play an essential role in the negative regulation of immune answers by developing an attenuated cytokine response that allows suppressing proliferation and effector function of T-cells (CD4+ Th). The transcription factor FoxP3 is responsible for the regulation of many genes involved in the Treg gene signature. Its ablation leads to severe immune deficiencies in human and mice. Recent developments in sequencing technologies have revolutionized the possibilities to gain insights into transcription factor binding by ChiP-seq and into transcriptome analysis by mRNA-seq. We combine FoxP3 ChiP-seq and mRNA-seq in order to understand the transcriptional differences between primary human CD4+ T helper and regulatory T-cells, as well as to study the role of FoxP3 in generating those differences. We show, that mRNA-seq allows analyzing the transcriptomal landscape of T-cells including the expression of specific splice variants at much greater depth than previous approaches, whereas 50% of transcriptional regulation events have not been described before by using diverse array technologies. We discovered splicing patterns like the expression of a kinase-dead isoform of IRAK1 upon T-cell activation. The immunoproteasome is up-regulated in both Treg and CD4+ Th cells upon activation, whereas the ‘standard’ proteasome is up-regulated in Tregs only upon activation

Next-generation insights into regulatory T cells: expression profiling and FoxP3 occupancy in Human

Regulatory T-cells (Treg) play an essential role in the negative regulation of immune answers by developing an attenuated cytokine response that allows suppressing proliferation and effector function of T-cells (CD4+ Th). The transcription factor FoxP3 is responsible for the regulation of many genes involved in the Treg gene signature. Its ablation leads to severe immune deficiencies in human and mice. Recent developments in sequencing technologies have revolutionized the possibilities to gain insights into transcription factor binding by ChiP-seq and into transcriptome analysis by mRNA-seq. We combine FoxP3 ChiP-seq and mRNA-seq in order to understand the transcriptional differences between primary human CD4+ T helper and regulatory T-cells, as well as to study the role of FoxP3 in generating those differences. We show, that mRNA-seq allows analyzing the transcriptomal landscape of T-cells including the expression of specific splice variants at much greater depth than previous approaches, whereas 50% of transcriptional regulation events have not been described before by using diverse array technologies. We discovered splicing patterns like the expression of a kinase-dead isoform of IRAK1 upon T-cell activation. The immunoproteasome is up-regulated in both Treg and CD4+ Th cells upon activation, whereas the ‘standard’ proteasome is up-regulated in Tregs only upon activation

Polychaete families in sediment samples from the Antarctic Peninsula and the Weddell Sea: data from multicorer and box corer samples from stations of POLARSTERN cruises PS81, PS96, and PS118

This dataset provides abundance data for polychaete families determined from sediment samples collected around the Antarctic Peninsula (PS 81, seven stations, 22 Jan - 18 Mar 2013), in the southeastern Weddell Sea (PS 96, six stations, 06 Dec 2015 - 14 Feb 2016) and the northwestern Weddell Sea (PS 118, three stations, 09 Feb - 10 Apr 2019). During the three expeditions a minimum of three samples (cores) were collected at each station with a MUC10 multicorer or a giant box corer (in this case subsampled with MUC10 core liners). Sediment cores from station 037, 048 (PS 96) and 006, 008, 038 (PS 118) were sliced into depth layers 0-1 cm, 1-2 cm, 2-3 cm, 3-4 cm, 4-5 cm, 5 cm-bottom. Sediment cores from station 241 (PS 81) and 017, 026, 061, 072 (PS 96) were sliced into depth layers 0-2 cm, 2-5 cm, 5 cm-bottom. For the remaining six stations from PS 81 the whole core was used (unsliced). Sediment samples were preserved in 4%-borax-buffered formaldehyde solution prior to sieving and counting (detailed methods in Weith et al. 2023, Säring et al. 2022). Stacked sieves with a mesh size of 500 µm and 1000 µm were used for samples from PS 96, PS 118 and station 241 from PS 81. Samples of the remaining six stations from PS 81 were sieved over a 500-µm sieve. Abundance for each polychaete family is presented per depth layer (note different slice volumes) as counts (note different core diameters) and as ind./m². Data from different sieve size fractions are available upon request. Polychaete communities included individuals from 34 families. The polychaete abundance data are part of a larger ecological study on meio- and macrofauna communities and their relation to environmental conditions and remineralisation at the sediment-water interface (see "Supplement to", "Related to" and "Further details" below). Sediment cores from which polychaete abundance data are deposited here were also used for microcosm incubations: Untreated incubations (Benthic Ecosystem Functioning Experiment BEFEx) and incubations with and without microalgae addition (Algae Feeding Experiment AFEx). Cores from BEFEx and AFEx without algae are labeled with NT (not treated), cores from AFEx with algae are labeled as T (treated)

Experimental Characterization of an Adaptive Supersonic Micro Turbine for Waste Heat Recovery Applications

Micro turbines (el) are commercially used as expansion machines in waste heat recovery (WHR) systems such as organic Rankine cycles (ORCs). These highly loaded turbines are generally designed for a specific parameter set, and their isentropic expansion efficiency significantly deteriorates when the mass flow rate of the WHR system deviates from the design point. However, in numerous industry processes that are potentially interesting for the implementation of a WHR process, the temperature, mass flow rate or both can fluctuate significantly, resulting in fluctuations in the WHR system as well. In such circumstances, the inlet pressure of the ORC turbine, and therefore the reversible cycle efficiency must be significantly reduced during these fluctuations. In this context, the authors developed an adaptive supersonic micro turbine for WHR applications. The variable geometry of the turbine nozzles enables an adjustment of the swallowing capacity in respect of the available mass flow rate in order to keep the upper cycle pressure constant. In this paper, an experimental test series of a WHR ORC test rig equipped with the developed adaptive supersonic micro turbine is analysed. The adaptive turbine is characterized concerning its off-design performance and the results are compared to a reference turbine with fixed geometry. To create a fair data basis for this comparison, a digital twin of the plant based on experimental data was built. In addition to the characterization of the turbine itself, the influence of the improved pressure ratio on the energy conversion chain of the entire ORC is analysed