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1.
Sci Rep. 2018 Aug 13;8(1):12064. doi: 10.1038/s41598-018-30500-y.

The Gpr1-regulated Sur7 family protein Sfp2 is required for hyphal growth and cell wall stability in the mycoparasite Trichoderma atroviride.

Author information

1
Institute of Microbiology, University of Innsbruck, Innsbruck, Austria.
2
Institute of Food Technology, University of Natural Resources and Life Sciences (BOKU), Vienna, Austria.
3
Institute of Chemical, Environmental & Bioscience Engineering, TU Wien, Vienna, Austria.
4
MIPS - Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, Munich, Germany.
5
Functional Genomics and Bioinformatics, Sopron University, Sopron, Hungary.
6
Chair of Bioinformatics, Boku University Vienna, Vienna, Austria.
7
Institute of Microbiology, University of Innsbruck, Innsbruck, Austria. Susanne.zeilinger@uibk.ac.at.
8
Institute of Chemical, Environmental & Bioscience Engineering, TU Wien, Vienna, Austria. Susanne.zeilinger@uibk.ac.at.

Abstract

Mycoparasites, e.g. fungi feeding on other fungi, are prominent within the genus Trichoderma and represent a promising alternative to chemical fungicides for plant disease control. We previously showed that the seven-transmembrane receptor Gpr1 regulates mycelial growth and asexual development and governs mycoparasitism-related processes in Trichoderma atroviride. We now describe the identification of genes being targeted by Gpr1 under mycoparasitic conditions. The identified gene set includes a candidate, sfp2, encoding a protein of the fungal-specific Sur7 superfamily, whose upregulation in T. atroviride upon interaction with a fungal prey is dependent on Gpr1. Sur7 family proteins are typical residents of membrane microdomains such as the membrane compartment of Can1 (MCC)/eisosome in yeast. We found that GFP-labeled Gpr1 and Sfp2 proteins show partly overlapping localization patterns in T. atroviride hyphae, which may point to shared functions and potential interaction during signal perception and endocytosis. Deletion of sfp2 caused heavily altered colony morphology, defects in polarized growth, cell wall integrity and endocytosis, and significantly reduced mycoparasitic activity, whereas sfp2 overexpression enhanced full overgrowth and killing of the prey. Transcriptional activation of a chitinase specific for hyphal growth and network formation and strong downregulation of chitin synthase-encoding genes were observed in Δsfp2. Taken together, these findings imply crucial functions of Sfp2 in hyphal morphogenesis of T. atroviride and its interaction with prey fungi.

2.
Dis Model Mech. 2018 Jul 6;11(7). pii: dmm033092. doi: 10.1242/dmm.033092.

Fetal articular cartilage regeneration versus adult fibrocartilaginous repair: secretome proteomics unravels molecular mechanisms in an ovine model.

Author information

1
VETERM, University Equine Hospital, University of Veterinary Medicine Vienna, Vienna 1210, Austria.
2
Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Vienna 1090, Austria.
3
Histology & Embryology, Department of Pathobiology, University of Veterinary Medicine Vienna, Vienna 1210, Austria.
4
Department of Biotechnology, Boku University Vienna, Vienna 1180, Austria.
5
Institute of Bioinformatics, Johannes Kepler University, Linz 4040, Austria.
6
Department of Companion Animals and Horses, University of Veterinary Medicine Vienna, Vienna 1210, Austria.
7
Teaching and Research Farm Kremesberg, Clinical Unit for Herd Health Management in Ruminants, Department for Farm Animals and Veterinary Public Health, University of Veterinary Medicine Vienna, Vienna 1210, Austria.
8
VETERM, University Equine Hospital, University of Veterinary Medicine Vienna, Vienna 1210, Austria florien.jenner@vetmeduni.ac.at.

Abstract

Osteoarthritis (OA), a degenerative joint disease characterized by progressive cartilage degeneration, is one of the leading causes of disability worldwide owing to the limited regenerative capacity of adult articular cartilage. Currently, there are no disease-modifying pharmacological or surgical therapies for OA. Fetal mammals, in contrast to adults, are capable of regenerating injured cartilage in the first two trimesters of gestation. A deeper understanding of the properties intrinsic to the response of fetal tissue to injury would allow us to modulate the way in which adult tissue responds to injury. In this study, we employed secretome proteomics to compare fetal and adult protein regulation in response to cartilage injury using an ovine cartilage defect model. The most relevant events comprised proteins associated with the immune response and inflammation, proteins specific for cartilage tissue and cartilage development, and proteins involved in cell growth and proliferation. Alarmins S100A8, S100A9 and S100A12 and coiled-coil domain containing 88A (CCDC88A), which are associated with inflammatory processes, were found to be significantly upregulated following injury in adult, but not in fetal animals. By contrast, cartilage-specific proteins like proteoglycan 4 were upregulated in response to injury only in fetal sheep postinjury. Our results demonstrate the power and relevance of the ovine fetal cartilage regeneration model presented here for the first time. The identification of previously unrecognized modulatory proteins that plausibly affect the healing process holds great promise for potential therapeutic interventions.

KEYWORDS:

Articular cartilage; Fetus; Osteoarthritis; Proteome; Regeneration

Conflict of interest statement

Competing interestsThe authors declare no competing or financial interests.

3.
J Biotechnol. 2017 Sep 10;257:13-21. doi: 10.1016/j.jbiotec.2017.03.012. Epub 2017 Mar 14.

Transcriptomic changes in CHO cells after adaptation to suspension growth in protein-free medium analysed by a species-specific microarray.

Author information

1
Department of Biotechnology, BOKU University, Vienna, Austria.
2
Austrian Centre of Industrial Biotechnology, Austria.
3
Department of Biotechnology, BOKU University, Vienna, Austria. Electronic address: david.kreil@boku.ac.at.
4
Department of Biotechnology, BOKU University, Vienna, Austria; Austrian Centre of Industrial Biotechnology, Austria. Electronic address: nicole.borth@boku.ac.at.

Abstract

Chinese Hamster Ovary (CHO) cells are the preferred cell line for production of biopharmaceuticals. These cells are capable to grow without serum supplementation, but drastic changes in their phenotype occur during adaptation to protein-free growth, which typically include the change to a suspension phenotype with reduced growth rate. A possible approach to understand this transformation, with the intention to counteract the reduction in growth by targeted supplementation of protein-free media, is gene expression profiling. The increasing availability of genome-scale data for CHO now facilitates quests for a better understanding of metabolic pathways and gene networks. So far, systematic large-scale expression profiling in CHO cells by microarray was limited due to lack of publicly available array designs and limitations of alternative approaches. Based on the recent release of CHO and Chinese Hamster genome sequences, including an annotated RefSeq genome, we have constructed a publicly available microarray design for effective genome-scale expression profiling. The design employed microarray probes optimized for uniformity, sensitivity, and specificity, with probe properties computed using the latest thermodynamic models. We validated the platform in an analysis of gene expression changes in response to serum-free adaptation. The observed effects on the lipid metabolism as well as on nucleotide synthesis were used to successfully select media supplements that were able to increase growth rate.

KEYWORDS:

CHO; Chinese Hamster Ovary; Gene ontology; KEGG; Microarray; Probe design; Serum deprivation; Specificity; Transcriptome

PMID:
28302587
DOI:
10.1016/j.jbiotec.2017.03.012
[Indexed for MEDLINE]
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4.
Biol Direct. 2016 Dec 20;11(1):66.

Sensitivity, specificity, and reproducibility of RNA-Seq differential expression calls.

Author information

1
APART Fellow, Austrian Academy of Science, Vienna, Austria. pawel.labaj@boku.ac.at.
2
Chair of Bioinformatics Research Group, Boku University, Vienna, Austria. pawel.labaj@boku.ac.at.
3
Chair of Bioinformatics Research Group, Boku University, Vienna, Austria.

Abstract

BACKGROUND:

The MAQC/SEQC consortium has recently compiled a key benchmark that can serve for testing the latest developments in analysis tools for microarray and RNA-seq expression profiling. Such objective benchmarks are required for basic and applied research, and can be critical for clinical and regulatory outcomes. Going beyond the first comparisons presented in the original SEQC study, we here present extended benchmarks including effect strengths typical of common experiments.

RESULTS:

With artefacts removed by factor analysis and additional filters, for genome scale surveys, the reproducibility of differential expression calls typically exceed 80% for all tool combinations examined. This directly reflects the robustness of results and reproducibility across different studies. Similar improvements are observed for the top ranked candidates with the strongest relative expression change, although here some tools clearly perform better than others, with typical reproducibility ranging from 60 to 93%.

CONCLUSIONS:

In our benchmark of alternative tools for RNA-seq data analysis we demonstrated the benefits that can be gained by analysing results in the context of other experiments employing a reference standard sample. This allowed the computational identification and removal of hidden confounders, for instance, by factor analysis. In itself, this already substantially improved the empirical False Discovery Rate (eFDR) without changing the overall landscape of sensitivity. Further filtering of false positives, however, is required to obtain acceptable eFDR levels. Appropriate filters noticeably improved agreement of differentially expressed genes both across sites and between alternative differential expression analysis pipelines.

REVIEWERS:

An extended abstract of this research paper was selected for the CAMDA Satellite Meeting to ISMB 2015 by the CAMDA Programme Committee. The full research paper then underwent one round of Open Peer Review under a responsible CAMDA Programme Committee member, Lan Hu, PhD (Bio-Rad Laboratories, Digital Biology Center-Cambridge). Open Peer Review was provided by Charlotte Soneson, PhD (University of Zürich) and Michał Okoniewski, PhD (ETH Zürich). The Reviewer Comments section shows the full reviews and author responses.

KEYWORDS:

Differential expression calling; RNA-seq; Reproducibility; Sensitivity; Specificity

PMID:
27993156
PMCID:
PMC5168849
DOI:
10.1186/s13062-016-0169-7
[Indexed for MEDLINE]
Free PMC Article
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5.
J Proteome Res. 2016 May 6;15(5):1487-96. doi: 10.1021/acs.jproteome.5b01067. Epub 2016 Mar 25.

MALDI TOF/TOF-Based Approach for the Identification of d- Amino Acids in Biologically Active Peptides and Proteins.

Author information

1
Centre for Physiology and Pharmacology, Medical University of Vienna , Schwarzspanierstraße 17, A-1090 Vienna, Austria.
2
School of Biomedical Sciences, The University of Queensland , Brisbane, QLD, 4072 Australia.
3
Institute of Biological Chemistry, Department of Chemistry, University of Vienna , Währinger Straße 38, A-1090 Vienna, Austria.
4
Chair of Bioinformatics, University of Natural Resources and Life Sciences , Muthgasse 18, A-1190 Vienna, Austria.

Abstract

Several biologically active peptides contain a d- amino acid in a well-defined position, which is position 2 in all peptide epimers isolated to date from vertebrates and also some from invertebrates. The detection of such D- residues by standard analytical techniques is challenging. In tandem mass spectrometric (MS) analysis, although fragment masses are the same for all stereoisomers, peak intensities are known to depend on chirality. Here, we observe that the effect of a d- amino acid in the second N-terminal position on the fragmentation pattern in matrix assisted laser desorption time-of-flight spectrometry (MALDI-TOF/TOF MS) strongly depends on the peptide sequence. Stereosensitive fragmentation (SF) is correlated to a neighborhood effect, but the d- residue also exerts an overall effect influencing distant bonds. In a fingerprint analysis, multiple peaks can thus serve to identify the chirality of a sample in short time and potentially high throughput. Problematic variations between individual spots could be successfully suppressed by cospotting deuterated analogues of the epimers. By identifying the [d-Leu2] isomer of the predicted peptide GH-2 (gene derived bombininH) in skin secretions of the toad Bombina orientalis, we demonstrated the analytical power of SF-MALDI-TOF/TOF measurements. In conclusion, SF-MALDI-TOF/TOF MS combines high sensitivity, versatility, and the ability to complement other methods.

KEYWORDS:

chirality; d- amino acid containing peptide; isotope label; peptidomics; post-translational modification; proteomics

PMID:
26985971
PMCID:
PMC4861975
DOI:
10.1021/acs.jproteome.5b01067
[Indexed for MEDLINE]
Free PMC Article
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6.
Biotechnol J. 2015 Oct;10(10):1625-38. doi: 10.1002/biot.201400857. Epub 2015 Sep 23.

Microarray profiling of preselected CHO host cell subclones identifies gene expression patterns associated with increased production capacity.

Author information

1
Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria.
2
ACIB GmbH, Graz, Austria.
3
RNA Biology Group, Institute for Genomics and Bioinformatics, Graz University of Technology, Graz, Austria.
4
Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria. nicole.borth@boku.ac.at.
5
ACIB GmbH, Graz, Austria. nicole.borth@boku.ac.at.

Abstract

Over the last three decades, product yields from CHO cells have increased dramatically, yet specific productivity (qP) remains a limiting factor. In a previous study, using repeated cell-sorting, we have established different host cell subclones that show superior transient qP over their respective parental cell lines (CHO-K1, CHO-S). The transcriptome of the resulting six cell lines in different biological states (untransfected, mock transfected, plasmid transfected) was first explored by hierarchical clustering and indicated that gene activity associated with increased qP did not stem from a certain cellular state but seemed to be inherent for a high qP host line. We then performed a novel gene regression analysis identifying drivers for an increase in qP. Genes significantly implicated were first systematically tested for enrichment of GO terms using a Bayesian approach incorporating the hierarchical structure of the GO term tree. Results indicated that specific cellular components such as nucleus, ER, and Golgi are relevant for cellular productivity. This was complemented by targeted GSA that tested functionally homogeneous, manually curated subsets of KEGG pathways known to be involved in transcription, translation, and protein processing. Significantly implicated pathways included mRNA surveillance, proteasome, protein processing in the ER and SNARE interactions in vesicular transport.

KEYWORDS:

Chinese hamster ovary (CHO) productivity; Gene set analysis; Host cell lines; Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways; Microarray profiling

PMID:
26315449
DOI:
10.1002/biot.201400857
[Indexed for MEDLINE]
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7.
Biol Direct. 2015 Aug 19;10:43. doi: 10.1186/s13062-015-0071-8.

Experiences with workflows for automating data-intensive bioinformatics.

Author information

1
Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, SE-75124, Uppsala, P.O. Box 591, Sweden. ola.spjuth@farmbio.uu.se.
2
SLU-Global Bioinformatics Centre, Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden. Erik.Bongcam@slu.se.
3
Science for Life Laboratory, Karolinska Institutet, SE-17121, Stockholm, P.O. Box 1031, Sweden. guillermo.carrasco@scilifelab.se.
4
Division of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, 6020, Austria. lukas.forer@i-med.ac.at.
5
Science for Life Laboratory, Karolinska Institutet, SE-17121, Stockholm, P.O. Box 1031, Sweden. mario.giovacchini@scilifelab.se.
6
Science for Life Laboratory, Karolinska Institutet, SE-17121, Stockholm, P.O. Box 1031, Sweden. brainstorm@nopcode.org.
7
CSC - IT Center for Science Ltd., FI-02101, Espoo, P.O. Box 405, Finland. aleksi.kallio@csc.fi.
8
CSC - IT Center for Science Ltd., FI-02101, Espoo, P.O. Box 405, Finland. eija.korpelainen@csc.fi.
9
Chair of Bioinformatics Research Group, Boku University, Vienna, Austria. maciej.kandula@boku.ac.at.
10
Faculty of Mathematics and Informatics, Sofia University, Sofia, Bulgaria. wfxp@milko.3mhz.net.
11
Chair of Bioinformatics Research Group, Boku University, Vienna, Austria. david.kreil@boku.ac.at.
12
Faculty of Mathematics and Informatics, Sofia University, Sofia, Bulgaria. okulev@fmi.uni-sofia.bg.
13
Chair of Bioinformatics Research Group, Boku University, Vienna, Austria. pawel.labaj@boku.ac.at.
14
Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, SE-75124, Uppsala, P.O. Box 591, Sweden. samuel.lampa@it.uu.se.
15
CRS4 Polaris, Pula, Italy. luca.pireddu@crs4.it.
16
Division of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, 6020, Austria. sebastian.schoenherr@i-med.ac.at.
17
Department of Information Technology, Uppsala University, SE-75105, Uppsala, P.O. Box 337, Sweden. alexey.siretskiy@it.uu.se.
18
AgroBioInstitute and Joint Genomic Centre, Sofia, Bulgaria. jim6329@gmail.com.

Abstract

High-throughput technologies, such as next-generation sequencing, have turned molecular biology into a data-intensive discipline, requiring bioinformaticians to use high-performance computing resources and carry out data management and analysis tasks on large scale. Workflow systems can be useful to simplify construction of analysis pipelines that automate tasks, support reproducibility and provide measures for fault-tolerance. However, workflow systems can incur significant development and administration overhead so bioinformatics pipelines are often still built without them. We present the experiences with workflows and workflow systems within the bioinformatics community participating in a series of hackathons and workshops of the EU COST action SeqAhead. The organizations are working on similar problems, but we have addressed them with different strategies and solutions. This fragmentation of efforts is inefficient and leads to redundant and incompatible solutions. Based on our experiences we define a set of recommendations for future systems to enable efficient yet simple bioinformatics workflow construction and execution.

PMID:
26282399
PMCID:
PMC4539931
DOI:
10.1186/s13062-015-0071-8
[Indexed for MEDLINE]
Free PMC Article
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8.
Invest Ophthalmol Vis Sci. 2015 Aug;56(9):5246-55. doi: 10.1167/iovs.14-15114.

Polarization-Sensitive Optical Coherence Tomography and Conventional Retinal Imaging Strategies in Assessing Foveal Integrity in Geographic Atrophy.

Author information

1
Department of Ophthalmology Medical University of Vienna, Vienna, Austria.
2
Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria.
3
Chair of Bioinformatics Research Group, Department of Biotechnology, BOKU University Vienna, Austria.

Abstract

PURPOSE:

To compare current imaging methods with respect to their ability to detect the condition of the fovea in patients with geographic atrophy (GA).

METHODS:

The retinas of 176 eyes with GA were imaged using two spectral-domain optical coherence tomography (SD-OCT) systems, Cirrus HD-OCT and Spectralis HRA+OCT, and fundus autofluorescence (FAF) and infrared imaging (IR) was used in the scanning laser ophthalmoscope (SLO) mode. Polarization-sensitive OCT (PS-OCT), which selectively visualizes the RPE in addition to SD-OCT features, was used to image 95 eyes. Geographic atrophy lesions were categorized as fovea spared, involved, or not quantifiable (grades 0, 1, and 2). Morphologic gradings were subsequently correlated with best-corrected visual acuity (BCVA) measurements to independently identify the corresponding functional condition of the fovea. Cohen's κ statistics with a bootstrap method was applied to compare retinal imaging methods.

RESULTS:

In PS-OCT, 84% of eyes with BCVA greater than or equal to 20/40 were detected, whereas in conventional retinal imaging the rate ranged from 27% in FAF to 45% in the SD-OCT segment. Cohen's κ statistics revealed significant differences between the gradings of PS-OCT and conventional imaging with κ = 0.488 and a global Hotelling's T2 statistic of 17.9 with a P value of P = 0.003. Statistical tests revealed no statistically significant differences between the conventional retinal imaging modalities.

CONCLUSIONS:

Polarization-sensitive OCT can better allow correct grading of the fovea in relation to BCVA and identify foveal sparing than other imaging modalities. The differences in imaging precision should be considered in diagnostic and therapeutic evaluations.

PMID:
26244300
DOI:
10.1167/iovs.14-15114
[Indexed for MEDLINE]
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9.
Plant Sci. 2015 May;234:38-49. doi: 10.1016/j.plantsci.2015.02.002. Epub 2015 Feb 16.

Phylloxera (Daktulosphaira vitifoliae Fitch) alters the carbohydrate metabolism in root galls to allowing the compatible interaction with grapevine (Vitis ssp.) roots.

Author information

1
Division of Viticulture and Pomology, Department of Crop Sciences, University of Natural Resources and Life Sciences, Konrad Lorenz Str. 24, 3430 Tulln, Austria.
2
Division of Plant Protection, Department of Crop Sciences, University of Natural Resources and Life Sciences, Konrad Lorenz Str. 24, 3430 Tulln, Austria.
3
Department of Botany, Warsaw University of Life Sciences (SGGW), Nowoursynowska 159, 02-787 Warsaw, Poland.
4
Department of Chemistry, Division of Chemistry of Renewable Resources, University of Natural Resources and Life Sciences, Konrad Lorenz Str. 24, 3430 Tulln, Austria.
5
Department of Biotechnology, University of Natural Resources and Life Sciences, Muthgasse 18, 1190 Vienna, Austria.
6
Department of Biotechnology, University of Natural Resources and Life Sciences, Muthgasse 18, 1190 Vienna, Austria; Life Sciences, University of Warwick, Coventry CV4 7AL, UK.
7
Division of Viticulture and Pomology, Department of Crop Sciences, University of Natural Resources and Life Sciences, Konrad Lorenz Str. 24, 3430 Tulln, Austria. Electronic address: astrid.forneck@boku.ac.at.

Abstract

Gall forming phylloxera may compete for nutrients with meristematic tissues and develop heterotrophic structures that act as carbon sinks. In this work, we studied the underlying starch metabolism, sink-source translocation of soluble sugars towards and within root galls. We demonstrated that nodosities store carbohydrates by starch accumulation and monitored the expression of genes involved in the starch metabolic. Thereby we proved that the nodosity is symplastically connected to the source tissues through its development and that the starch metabolism is significantly affected to synthesize and degrade starch within the gall. Genes required for starch biosynthesis and degradation are up-regulated. Among the carbohydrate transporters the expression of a glucose-6-phosphate translocater, one sucrose transporter and two SWEET proteins were increases, whereas hexose transporters, tonoplast monosaccharide transporter and Erd6-like sugar transporters were decreased. We found general evidence for plant response to osmotic stress in the nodosity as previously suggested for gall induction processes. We conclude that nodosities are heterogenous plant organs that accumulate starch to serve as temporary storage structure that is gradually withdrawn by phylloxera. Phylloxera transcriptionally reprograms gall tissues beyond primary metabolism and included downstream secondary processes, including response to osmotic stress.

KEYWORDS:

Carbohydrate; Grapevine; Plant sink; Primary metabolism; Root gall

PMID:
25804808
PMCID:
PMC4388344
DOI:
10.1016/j.plantsci.2015.02.002
[Indexed for MEDLINE]
Free PMC Article
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10.
Nat Commun. 2014 Sep 25;5:5125. doi: 10.1038/ncomms6125.

Assessing technical performance in differential gene expression experiments with external spike-in RNA control ratio mixtures.

Author information

1
1] National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, Maryland 20899, USA [2] Department of Bioengineering, Stanford University, 443 Via Ortega, Stanford, California 94305, USA.
2
National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, Maryland 20899, USA.
3
Interdisciplinary Centre for Bioinformatics, University of Leipzig, Härtelstrasse 16-18, 04107 Leipzig, Germany.
4
Institute of Bioinformatics, Johannes Kepler University, Altenberger Str. 69, 4040 Linz, Austria.
5
Computational Genomics Program, Principe Felipe Research Center, Avd Eduardo Primo Yúfera 3, 46012 Valencia, Spain.
6
1] Computational Genomics Program, Principe Felipe Research Center, Avd Eduardo Primo Yúfera 3, 46012 Valencia, Spain [2] CIBER de Enfermedades Raras (CIBERER) and Functional Genomics Node, INB., Valencia, Spain.
7
ecSeq Bioinformatics, Brandvorwerkstrasse 43, 04275 Leipzig, Germany.
8
National Center for Toxicological Research, Food and Drug Administration, 3900 NCTR Road, Jefferson, Arkansas 72079, USA.
9
Genomics Core Facility, Feinberg School of Medicine, Northwestern University, Tarry building 2-757, 300 E. Superior St. Chicago, Illinois 60611, USA.
10
1] Chair of Bioinformatics, Boku University Vienna, Muthgasse 18, Vienna 1190, Austria [2] University of Warwick, Coventry CV4 7AL, UK.
11
Chair of Bioinformatics, Boku University Vienna, Muthgasse 18, Vienna 1190, Austria.
12
Department of Physiology and Biophysics, Institute for Computational Biomedicine, Weill Cornell Medical College, 1305 York Avenue, Room Y13-04, Box 140, New York, New York 10021, USA.
13
1] Division of Bioinformatics, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3052, Australia [2] Department of Medical Biology, The University of Melbourne, Parkville, Victoria 3010, Australia.
14
Nationwide Children's Hospital, Columbus, Ohio 43205, USA.
15
1] CIBER de Enfermedades Raras (CIBERER) and Functional Genomics Node, INB., Valencia, Spain [2] Medical Genome Project, Genomics and Bioinformatics Platform of Andalusia, c/ Albert Einstein s/n, 41092 Sevilla, Spain.
16
Thermo Fisher Scientific, Research &Development, 2170 Woodward Street, Austin, Texas 78744, USA.
17
State Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology, Schools of Life Sciences and Pharmacy, Fudan University, Shanghai 201203, China.
18
1] Division of Bioinformatics, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3052, Australia [2] Department of Computing and Information Systems, The University of Melbourne, Parkville, Victoria 3010, Australia.
19
1] Division of Bioinformatics, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3052, Australia [2] Department of Mathematics and Statistics, The University of Melbourne, Parkville, Victoria 3010, Australia.
20
Division of Microbiology and Molecular Genetics, Center for Genomics, School of Medicine, Loma Linda University, Loma Linda, California 92350, USA.
21
Research Informatics, Eli Lilly and Company, Lilly Corporate Center, Indianapolis, Indiana 46285, USA.
22
Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, 1000 N Oak Avenue, Marshfield, Wisconsin 54449, USA.

Abstract

There is a critical need for standard approaches to assess, report and compare the technical performance of genome-scale differential gene expression experiments. Here we assess technical performance with a proposed standard 'dashboard' of metrics derived from analysis of external spike-in RNA control ratio mixtures. These control ratio mixtures with defined abundance ratios enable assessment of diagnostic performance of differentially expressed transcript lists, limit of detection of ratio (LODR) estimates and expression ratio variability and measurement bias. The performance metrics suite is applicable to analysis of a typical experiment, and here we also apply these metrics to evaluate technical performance among laboratories. An interlaboratory study using identical samples shared among 12 laboratories with three different measurement processes demonstrates generally consistent diagnostic power across 11 laboratories. Ratio measurement variability and bias are also comparable among laboratories for the same measurement process. We observe different biases for measurement processes using different mRNA-enrichment protocols.

PMID:
25254650
DOI:
10.1038/ncomms6125
[Indexed for MEDLINE]
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11.
Nat Biotechnol. 2014 Sep;32(9):926-32. doi: 10.1038/nbt.3001. Epub 2014 Aug 24.

The concordance between RNA-seq and microarray data depends on chemical treatment and transcript abundance.

Author information

1
1] Center for Genomics and Division of Microbiology &Molecular Genetics, School of Medicine, Loma Linda University, Loma Linda, California, USA. [2].
2
1] Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, Arkansas, USA. [2].
3
1] Microarray and Genome Informatics Group, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA. [2] Biostatistics Branch, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA. [3].
4
National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA.
5
Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, Arkansas, USA.
6
The Office of Scientific Coordination, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, Arkansas, USA.
7
Functional Genomics Core, Department of Molecular Medicine, Beckman Research Institute, City of Hope, Duarte, California, USA.
8
Chair of Bioinformatics Research Group, Boku University Vienna, Vienna, Austria.
9
1] Chair of Bioinformatics Research Group, Boku University Vienna, Vienna, Austria. [2] University of Warwick, Coventry, UK.
10
CMINDS Research Center, Department of Electrical and Computer Engineering, Francis College of Engineering, University of Massachusetts, Lowell, Massachusetts, USA.
11
Department of Toxicogenomics, Maastricht University, Maastricht, the Netherlands.
12
Australian Genome Research Facility Ltd., The Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia.
13
AbbVie, Inc., North Chicago, Illinois, USA.
14
Research Informatics and Statistics, Eli Lilly and Company, Lilly Corporate Center, Indianapolis, Indiana, USA.
15
Thomson Reuters, IP &Science, Carlsbad, California, USA.
16
Vavilov Institute of General Genetics, Russian Academy of Science, Moscow, Russia.
17
Fondazione Bruno Kessler, Trento, Italy.
18
1] Fondazione Bruno Kessler, Trento, Italy. [2] Computational Biology Department, Research and Innovation Centre, Fondazione Edmund Mach (FEM), San Michele all'Adige, Italy.
19
Bioinformatics core, Department of Pathology, University of North Dakota, Grand Forks, North Dakota, USA.
20
1] Microarray and Genome Informatics Group, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA. [2] Kelly Government Solutions, Inc., Durham, North Carolina, USA.
21
Biomolecular Screening Branch, Division of the National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA.
22
SRA International, Durham, North Carolina, USA.
23
Division of Systems Biology, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, Arkansas, USA.
24
Department of Internal Medicine and Biochemistry, Rush University Medical Center, Chicago, Illinois, USA.
25
1] Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, Arkansas, USA. [2] State Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology, Schools of Life Sciences and Pharmacy, Fudan University, Shanghai, China (L.S.'s primary affiliation).
26
Laboratory of Toxicology and Pharmacology, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA.

Abstract

The concordance of RNA-sequencing (RNA-seq) with microarrays for genome-wide analysis of differential gene expression has not been rigorously assessed using a range of chemical treatment conditions. Here we use a comprehensive study design to generate Illumina RNA-seq and Affymetrix microarray data from the same liver samples of rats exposed in triplicate to varying degrees of perturbation by 27 chemicals representing multiple modes of action (MOAs). The cross-platform concordance in terms of differentially expressed genes (DEGs) or enriched pathways is linearly correlated with treatment effect size (R(2)0.8). Furthermore, the concordance is also affected by transcript abundance and biological complexity of the MOA. RNA-seq outperforms microarray (93% versus 75%) in DEG verification as assessed by quantitative PCR, with the gain mainly due to its improved accuracy for low-abundance transcripts. Nonetheless, classifiers to predict MOAs perform similarly when developed using data from either platform. Therefore, the endpoint studied and its biological complexity, transcript abundance and the genomic application are important factors in transcriptomic research and for clinical and regulatory decision making.

PMID:
25150839
PMCID:
PMC4243706
DOI:
10.1038/nbt.3001
[Indexed for MEDLINE]
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12.
Nat Biotechnol. 2014 Sep;32(9):903-14. doi: 10.1038/nbt.2957. Epub 2014 Aug 24.

A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium.

Collaborators (162)

Su Z, Łabaj PP, Li S, Thierry-Mieg J, Thierry-Mieg D, Shi W, Wang C, Schroth GP, Setterquist RA, Thompson JF, Jones WD, Xiao W, Xu W, Jensen RV, Kelly R, Xu J, Conesa A, Furlanello C, Gao H, Hong H, Jafari N, Letovsky S, Liao Y, Lu F, Oakeley EJ, Peng Z, Praul CA, Santoyo-Lopez J, Scherer A, Shi T, Smyth GK, Staedtler F, Sykacek P, Tan XX, Thompson EA, Vandesompele J, Wang MD, Wang J, Wolfinger RD, Zavadil J, Auerbach SS, Bao W, Binder H, Blomquist T, Brilliant MH, Bushel PR, Cai W, Catalano JG, Chang CW, Chen T, Chen G, Chen R, Chierici M, Chu TM, Clevert DA, Deng Y, Derti A, Devanarayan V, Dong Z, Dopazo J, Du T, Fang H, Fang Y, Fasold M, Fernandez A, Fischer M, Furió-Tari P, Fuscoe JC, Caimet F, Gaj S, Gandara J, Gao H, Ge W, Gondo Y, Gong B, Gong M, Gong Z, Green B, Guo C, Guo L, Guo LW, Hadfield J, Hellemans J, Hochreiter S, Jia M, Jian M, Johnson CD, Kay S, Kleinjans J, Lababidi S, Levy S, Li QZ, Li L, Li L, Li P, Li Y, Li H, Li J, Li S, Lin SM, López FJ, Lu X, Luo H, Ma X, Meehan J, Megherbi DB, Mei N, Mu B, Ning B, Pandey A, Pérez-Florido J, Perkins RG, Peters R, Phan JH, Pirooznia M, Qian F, Qing T, Rainbow L, Rocca-Serra P, Sambourg L, Sansone SA, Schwartz S, Shah R, Shen J, Smith TM, Stegle O, Stralis-Pavese N, Stupka E, Suzuki Y, Szkotnicki LT, Tinning M, Tu B, van Delft J, Vela-Boza A, Venturini E, Walker SJ, Wan L, Wang W, Wang J, Wang J, Wieben ED, Willey JC, Wu PY, Xuan J, Yang Y, Ye Z, Yin Y, Yu Y, Yuan YC, Zhang J, Zhang KK, Zhang W, Zhang W, Zhang Y, Zhao C, Zheng Y, Zhou Y, Zumbo P, Tong W, Kreil DP, Mason CE, Shi L.

Abstract

We present primary results from the Sequencing Quality Control (SEQC) project, coordinated by the US Food and Drug Administration. Examining Illumina HiSeq, Life Technologies SOLiD and Roche 454 platforms at multiple laboratory sites using reference RNA samples with built-in controls, we assess RNA sequencing (RNA-seq) performance for junction discovery and differential expression profiling and compare it to microarray and quantitative PCR (qPCR) data using complementary metrics. At all sequencing depths, we discover unannotated exon-exon junctions, with >80% validated by qPCR. We find that measurements of relative expression are accurate and reproducible across sites and platforms if specific filters are used. In contrast, RNA-seq and microarrays do not provide accurate absolute measurements, and gene-specific biases are observed for all examined platforms, including qPCR. Measurement performance depends on the platform and data analysis pipeline, and variation is large for transcript-level profiling. The complete SEQC data sets, comprising >100 billion reads (10Tb), provide unique resources for evaluating RNA-seq analyses for clinical and regulatory settings.

PMID:
25150838
PMCID:
PMC4321899
DOI:
10.1038/nbt.2957
[Indexed for MEDLINE]
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13.
Nat Biotechnol. 2014 Sep;32(9):888-95. doi: 10.1038/nbt.3000. Epub 2014 Aug 24.

Detecting and correcting systematic variation in large-scale RNA sequencing data.

Author information

1
1] Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, USA. [2] The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, New York, USA. [3].
2
1] Chair of Bioinformatics Research Group, Boku University Vienna, Vienna, Austria. [2].
3
Chair of Bioinformatics Research Group, Boku University Vienna, Vienna, Austria.
4
Department of Bioinformatics, WEHI, Melbourne, Australia.
5
State Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology, Schools of Life Sciences and Pharmacy, Fudan University, Shanghai, China.
6
School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.
7
Center for Genomics and Division of Microbiology &Molecular Genetics, School of Medicine, Loma Linda University, Loma Linda, California, USA.
8
National Center for Biotechnology Information (NCBI), Bethesda, Maryland, USA.
9
1] Chair of Bioinformatics Research Group, Boku University Vienna, Vienna, Austria. [2] University of Warwick, Coventry, UK.
10
1] Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, USA. [2] The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, New York, USA. [3] The Feil Family Brain and Mind Research Institute, New York, New York, USA.

Abstract

High-throughput RNA sequencing (RNA-seq) enables comprehensive scans of entire transcriptomes, but best practices for analyzing RNA-seq data have not been fully defined, particularly for data collected with multiple sequencing platforms or at multiple sites. Here we used standardized RNA samples with built-in controls to examine sources of error in large-scale RNA-seq studies and their impact on the detection of differentially expressed genes (DEGs). Analysis of variations in guanine-cytosine content, gene coverage, sequencing error rate and insert size allowed identification of decreased reproducibility across sites. Moreover, commonly used methods for normalization (cqn, EDASeq, RUV2, sva, PEER) varied in their ability to remove these systematic biases, depending on sample complexity and initial data quality. Normalization methods that combine data from genes across sites are strongly recommended to identify and remove site-specific effects and can substantially improve RNA-seq studies.

PMID:
25150837
PMCID:
PMC4160374
DOI:
10.1038/nbt.3000
[Indexed for MEDLINE]
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14.
PLoS One. 2014 Jul 17;9(7):e102360. doi: 10.1371/journal.pone.0102360. eCollection 2014.

The beet cyst nematode Heterodera schachtii modulates the expression of WRKY transcription factors in syncytia to favour its development in Arabidopsis roots.

Author information

1
Division of Plant Protection, Department of Crop Sciences, University of Natural Resources and Life Sciences, Vienna, Austria; Department of Plant Pathology, Centre of Agricultural Biochemistry and Biotechnology (CABB), University of Agriculture, Faisalabad, Pakistan.
2
Division of Plant Protection, Department of Crop Sciences, University of Natural Resources and Life Sciences, Vienna, Austria.
3
Chair of Bioinformatics, Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria; School of Life Sciences, University of Warwick, Coventry, United Kingdom.

Abstract

Cyst nematodes invade the roots of their host plants as second stage juveniles and induce a syncytium which is the only source of nutrients throughout their life. A recent transcriptome analysis of syncytia induced by the beet cyst nematode Heterodera schachtii in Arabidopsis roots has shown that thousands of genes are up-regulated or down-regulated in syncytia as compared to root segments from uninfected plants. Among the down-regulated genes are many which code for WRKY transcription factors. Arabidopsis contains 66 WRKY genes with 59 represented by the ATH1 GeneChip. Of these, 28 were significantly down-regulated and 6 up-regulated in syncytia as compared to control root segments. We have studied here the down-regulated genes WRKY6, WRKY11, WRKY17 and WRKY33 in detail. We confirmed the down-regulation in syncytia with promoter::GUS lines. Using various overexpression lines and mutants it was shown that the down-regulation of these WRKY genes is important for nematode development, probably through interfering with plant defense reactions. In case of WRKY33, this might involve the production of the phytoalexin camalexin.

PMID:
25033038
PMCID:
PMC4102525
DOI:
10.1371/journal.pone.0102360
[Indexed for MEDLINE]
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15.
Am J Ophthalmol. 2014 Sep;158(3):557-66.e1. doi: 10.1016/j.ajo.2014.05.026. Epub 2014 May 28.

A longitudinal comparison of spectral-domain optical coherence tomography and fundus autofluorescence in geographic atrophy.

Author information

1
Vienna Reading Center, Department of Ophthalmology, Medical University of Vienna, Vienna, Austria; Department of Ophthalmology, Medical University of Vienna, Vienna, Austria.
2
Vienna Reading Center, Department of Ophthalmology, Medical University of Vienna, Vienna, Austria; Department of Ophthalmology, Medical University of Vienna, Vienna, Austria. Electronic address: ramzi.sayegh@meduniwien.ac.at.
3
Vienna Reading Center, Department of Ophthalmology, Medical University of Vienna, Vienna, Austria.
4
Department of Ophthalmology, Medical University of Vienna, Vienna, Austria.
5
Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria; School of Life Sciences, University of Warwick, Coventry, UK.

Abstract

PURPOSE:

To identify reliable criteria based on spectral-domain optical coherence tomography (SD OCT) to monitor disease progression in geographic atrophy attributable to age-related macular degeneration (AMD) compared with lesion size determination based on fundus autofluorescence (FAF).

DESIGN:

Prospective longitudinal observational study.

METHODS:

setting: Institutional. study population: A total of 48 eyes in 24 patients with geographic atrophy. observation procedures: Eyes with geographic atrophy were included and examined at baseline and at months 3, 6, 9, and 12. At each study visit best-corrected visual acuity (BCVA), FAF, and SD OCT imaging were performed. FAF images were analyzed using the region overlay device. Planimetric measurements in SD OCT, including alterations or loss of outer retinal layers and the RPE, as well as choroidal signal enhancement, were performed with the OCT Toolkit. main outcome measures: Areas of interest in patients with geographic atrophy measured from baseline to month 12 by SD OCT compared with the area of atrophy measured by FAF.

RESULTS:

Geographic atrophy lesion size increased from 8.88 mm² to 11.22 mm² based on quantitative FAF evaluation. Linear regression analysis demonstrated that results similar to FAF planimetry for determining lesion progression can be obtained by measuring the areas of outer plexiform layer thinning (adjusted R(2) = 0.93), external limiting membrane loss (adjusted R(2) = 0.89), or choroidal signal enhancement (R(2) = 0.93) by SD OCT.

CONCLUSIONS:

SD OCT allows morphologic markers of disease progression to be identified in geographic atrophy and may improve understanding of the pathophysiology of atrophic AMD.

PMID:
24879944
DOI:
10.1016/j.ajo.2014.05.026
[Indexed for MEDLINE]
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16.
Br J Ophthalmol. 2014 Aug;98(8):1050-5. doi: 10.1136/bjophthalmol-2014-305195. Epub 2014 Apr 7.

A systematic correlation of morphology and function using spectral domain optical coherence tomography and microperimetry in patients with geographic atrophy.

Author information

1
Vienna Reading Center, Department of Ophthalmology, Medical University of Vienna, Vienna, Austria Department of Ophthalmology, Medical University of Vienna, Vienna, Austria.
2
Department of Ophthalmology, Medical University of Vienna, Vienna, Austria.
3
Vienna Reading Center, Department of Ophthalmology, Medical University of Vienna, Vienna, Austria.
4
Chair of Bioinformatics, Department of Biotechnology, Boku University Vienna, Austria & School of Life Sciences, University of Warwick, Vienna, UK.

Abstract

AIMS:

This study has been designed to describe the functional impact of distinct pathologies within the retinal layers in patients with geographic atrophy (GA) by means of a point-to-point correlation between optical coherence tomography (OCT) and microperimetry.

METHODS:

Retinal morphology and function of 23 patients suffering from GA of the retinal pigment epithelium (RPE) have been investigated using the Spectralis OCT (Heidelberg Engineering) and the MP1 microperimeter (Nidek Technologies). The point-to-point overlay of morphology and function has been done using proprietary software, allowing OCT image grading to define distinct alterations of the neurosensory retina, the RPE and the choroid. By overlaying the retinal sensitivity map on the OCT data set, retinal layer alterations could be evaluated regarding their impact on visual function.

RESULTS:

A total of 1005 stimulation points in the lesion area in 2107 spectral domain OCT B-scans were graded in 43 eyes of 23 patients (mean best corrected visual acuity=20/70). Retinal sensitivity decreases with an increasing number of morphological alterations graded (p<10(-13)). Alterations of the RPE and the external limiting membrane (p<0.02) were associated with absolute scotomas. Furthermore, the loss of the external limiting membrane as the largest area of morphological alteration among our patients with GA (mean area=5.65 mm(2)), had a significant impact (p<10(-4)) on sensitivity (-1.3 dB).

CONCLUSIONS:

Mapping retinal sensitivity to distinct retinal pathologies revealed outer retinal layers, in addition to the RPE, as significant for sensitivity loss. Therefore in GA the RPE loss and the alteration of outer retinal layers should be analysed, which could also provide insight into lesion progression.

KEYWORDS:

Imaging; Retina

[Indexed for MEDLINE]
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17.
J Gerontol A Biol Sci Med Sci. 2015 Mar;70(3):273-81. doi: 10.1093/gerona/glu030. Epub 2014 Mar 22.

WNT signaling suppression in the senescent human thymus.

Author information

1
Laboratorio InmunoBiología Molecular, Hospital General Universitario Gregorio Marañón Madrid, Spain; Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain. Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Spain. Laboratory of Immunovirology, Clinic Unit of Infectious Diseases, Microbiology and Preventive Medicine. Institute of Biomedicine of Seville, IBiS, Virgen del Rocío University Hospital/CSIC/University of Seville, Spain. s.ferrandomartinez@gmail.com.
2
Laboratory of Immunovirology, Clinic Unit of Infectious Diseases, Microbiology and Preventive Medicine. Institute of Biomedicine of Seville, IBiS, Virgen del Rocío University Hospital/CSIC/University of Seville, Spain.
3
Department of Immunology and Medicine, Sloan Kettering Institute, New York City, USA.
4
Department of Biotechnology, VIBT-BOKU, University of Natural Resources and Applied Life Sciences, Vienna, Austria.
5
Chair of Bioinformatics, BOKU University Vienna, Austria and Life Sciences, University of Warwick, UK.
6
Laboratorio InmunoBiología Molecular, Hospital General Universitario Gregorio Marañón Madrid, Spain; Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain. Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Spain.

Abstract

Human thymus is completely developed in late fetal stages and its function peaks in newborns. After the first year of life, the thymus undergoes a progressive atrophy that dramatically decreases de novo T-lymphocyte maturation. Hormonal signaling and changes in the microRNA expression network are identified as underlying causes of human thymus involution. However, specific pathways involved in the age-related loss of thymic function remain unknown. In this study, we analyzed differential gene-expression profile and microRNA expression in elderly (70 years old) and young (less than 10 months old and 11 years old) human thymic samples. Our data have shown that WNT pathway deregulation through the overexpression of different inhibitors by the nonadipocytic component of the human thymus stimulates the age-related involution. These results are of particular interest because interference of WNT signaling has been demonstrated in both animal models and in vitro studies, with the three major hallmarks of thymic involution: (i) epithelial structure disruption, (ii) adipogenic process, and (iii) thymocyte development arrest. Thus, our results suggest that secreted inhibitors of the WNT pathway could be explored as a novel therapeutical target in the reversal of the age-related thymic involution.

KEYWORDS:

Aging.; Human thymus; Thymus involution; WNT pathway

PMID:
24657825
PMCID:
PMC4351388
DOI:
10.1093/gerona/glu030
[Indexed for MEDLINE]
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18.
Gut. 2014 Oct;63(10):1566-77. doi: 10.1136/gutjnl-2012-303786. Epub 2014 Jan 16.

Bacterial protein signals are associated with Crohn's disease.

Author information

1
UMR1319 Micalis, INRA, Jouy-en-Josas, France.
2
Chair of Bioinformatics, Boku University Vienna, Vienna, Austria Department of Life Sciences, University of Warwick, Warwickshire, UK.
3
UMR1313 GABI, Iso Cell Express (ICE), INRA, Jouy-en-Josas, France.
4
Plate-forme d'Analyse Protéomique de Paris Sud-Ouest (PAPPSO), INRA, Gif-sur-Yvette, France.
5
Laboratoire de Spectrométrie de Masse BioOrganique (LSMBO), IPHC, Université de Strasbourg, Strasbourg, France.
6
Chair of Bioinformatics, Boku University Vienna, Vienna, Austria.
7
UMR1319 Micalis, INRA, Jouy-en-Josas, France Gastroenterology and Nutrition Unit, Hôpital Saint-Antoine, AP-HP, Paris, France.
8
UR1077, Mathématique Informatique et Génome (MIG), INRA, Jouy-en-Josas, France.
9
UR341, Mathématiques et Informatique Appliquées (MIA), INRA, Jouy-en-Josas, France.
10
Gastroenterology and Nutrition Unit, Hôpital Saint-Antoine, AP-HP, Paris, France.

Abstract

OBJECTIVE:

No Crohn's disease (CD) molecular maker has advanced to clinical use, and independent lines of evidence support a central role of the gut microbial community in CD. Here we explore the feasibility of extracting bacterial protein signals relevant to CD, by interrogating myriads of intestinal bacterial proteomes from a small number of patients and healthy controls.

DESIGN:

We first developed and validated a workflow-including extraction of microbial communities, two-dimensional difference gel electrophoresis (2D-DIGE), and LC-MS/MS-to discover protein signals from CD-associated gut microbial communities. Then we used selected reaction monitoring (SRM) to confirm a set of candidates. In parallel, we used 16S rRNA gene sequencing for an integrated analysis of gut ecosystem structure and functions.

RESULTS:

Our 2D-DIGE-based discovery approach revealed an imbalance of intestinal bacterial functions in CD. Many proteins, largely derived from Bacteroides species, were over-represented, while under-represented proteins were mostly from Firmicutes and some Prevotella members. Most overabundant proteins could be confirmed using SRM. They correspond to functions allowing opportunistic pathogens to colonise the mucus layers, breach the host barriers and invade the mucosae, which could still be aggravated by decreased host-derived pancreatic zymogen granule membrane protein GP2 in CD patients. Moreover, although the abundance of most protein groups reflected that of related bacterial populations, we found a specific independent regulation of bacteria-derived cell envelope proteins.

CONCLUSIONS:

This study provides the first evidence that quantifiable bacterial protein signals are associated with CD, which can have a profound impact on future molecular diagnosis.

KEYWORDS:

Crohn's Disease; Enteric Bacterial Microflora; Inflammatory Bowel Disease

PMID:
24436141
PMCID:
PMC4173658
DOI:
10.1136/gutjnl-2012-303786
[Indexed for MEDLINE]
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19.
Sci Data. 2014 Aug 26;1:140020. doi: 10.1038/sdata.2014.20. eCollection 2014.

Cross-platform ultradeep transcriptomic profiling of human reference RNA samples by RNA-Seq.

Author information

1
Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, Food and Drug Administration , Jefferson, Arkansas 72079, USA.
2
National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health , Bethesda, Maryland 20814, USA.
3
Chair of Bioinformatics Research Group, Boku University Vienna , Vienna, Austria ; University of Warwick , Coventry CV4 7AL, UK.
4
Department of Physiology and Biophysics and the Institute for Computational Biomedicine, Weill Cornell Medical College , New York, New York 10021, USA.
5
Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, Food and Drug Administration , Jefferson, Arkansas 72079, USA ; State Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology, Schools of Life Sciences and Pharmacy, Fudan University , Shanghai 201203, China.

Abstract

Whole-transcriptome sequencing ('RNA-Seq') has been drastically changing the scale and scope of genomic research. In order to fully understand the power and limitations of this technology, the US Food and Drug Administration (FDA) launched the third phase of the MicroArray Quality Control (MAQC-III) project, also known as the SEquencing Quality Control (SEQC) project. Using two well-established human reference RNA samples from the first phase of the MAQC project, three sequencing platforms were tested across more than ten sites with built-in truths including spike-in of external RNA controls (ERCC), titration data and qPCR verification. The SEQC project generated over 30 billion sequence reads representing the largest RNA-Seq data ever generated by a single project on individual RNA samples. This extraordinarily ultradeep transcriptomic data set and the known truths built into the study design provide many opportunities for further research and development to advance the improvement and application of RNA-Seq.

PMID:
25977777
PMCID:
PMC4322577
DOI:
10.1038/sdata.2014.20
[Indexed for MEDLINE]
Free PMC Article
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20.
Biotechnol Adv. 2013 Dec;31(8):1501-13. doi: 10.1016/j.biotechadv.2013.07.007. Epub 2013 Aug 2.

CHO microRNA engineering is growing up: recent successes and future challenges.

Author information

1
Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria.

Abstract

microRNAs with their ability to regulate complex pathways that control cellular behavior and phenotype have been proposed as potential targets for cell engineering in the context of optimization of biopharmaceutical production cell lines, specifically of Chinese Hamster Ovary cells. However, until recently, research was limited by a lack of genomic sequence information on this industrially important cell line. With the publication of the genomic sequence and other relevant data sets for CHO cells since 2011, the doors have been opened for an improved understanding of CHO cell physiology and for the development of the necessary tools for novel engineering strategies. In the present review we discuss both knowledge on the regulatory mechanisms of microRNAs obtained from other biological models and proof of concepts already performed on CHO cells, thus providing an outlook of potential applications of microRNA engineering in production cell lines.

KEYWORDS:

Bioprocess relevant properties; Chinese Hamster Ovary cells; MicroRNA engineering

PMID:
23916872
PMCID:
PMC3854872
DOI:
10.1016/j.biotechadv.2013.07.007
[Indexed for MEDLINE]
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