193 research outputs found
External calibration with Drosophila whole-cell spike-ins delivers absolute mRNA fold changes from human RNA-Seq and qPCR data
No full textGene expression measurements are typically performed on a fixed-weight aliquot of RNA, which assumes that the total number of transcripts per cell stays nearly constant across all conditions. In cases where this assumption does not hold (e.g., when comparing cell types with different cell sizes) the expression data provide a distorted view of cellular events. Assuming constant numbers of total transcripts, increases in expression of some RNAs must be compensated for by decreases in expression of others. Therefore, we propose calibrating gene expression data to an external reference point, the number of cells in the sample, using whole-cell spike-ins. In a systematic dilution experiment, we mixed varying numbers of human cells with fixed numbers of Drosophila melanogaster cells and scaled the expression levels of the human genes relative to those of the Drosophila genes. This approach restored the original gene expression ratios generated by the dilutions. We then used Drosophila whole-cell spike-ins to uncover non-symmetric gene expression changes, in this case much larger numbers of induced than repressed genes, under perturbations of the human cell line P493-6. Drosophila whole-cell spike-ins are an experimentally and computationally easy and low-priced method to derive mRNA fold changes of absolute abundances from RNA sequencing (RNA-Seq) and quantitative real-time PCR (qPCR) data
Transcription in Mycoplasma pneumoniae: Analysis of the Promoters of the ackA and ldh genes
No full textThe nucleotide sequences that control transcription initiation and regulation in Mycoplasma pneumoniae are poorly understood. Moreover, only few regulatory events have been reported for M. pneumoniae. We have studied changes in the global protein synthesis pattern in M. pneumoniae in response to the presence of glycerol. The ackA and ldh genes, encoding acetate kinase and lactate dehydrogenase, respectively, were controlled in a carbon source-dependent manner. While the ackA gene was strongly expressed in the presence of glucose, transcription of ldh was induced by glycerol. The promoters of both genes were mapped by primer extension analysis. Molecular analysis of transcription regulatory mechanisms in M. pneumoniae has so far not been possible due to the lack of appropriate reporter systems that can be used to study the activity of promoter fragments and their mutant derivatives in vivo. Recently, a reporter system has been developed which allows cloning of promoter fragments in front of a promoterless lacZ gene and inserting this construct into the genome of M. pneumoniae. To study the requirements of M. pneumoniae RNA polymerase for promoter recognition, a series of fusions of deletion and mutant variants of the ldh promoter was constructed and analyzed in vivo. While mutations affecting the -10 region strongly interfered with gene expression, the -35 region seems to be of minor importance in M. pneumoniae. (c) 2007 Elsevier Ltd. All rights reserved
Synergy of interleukin 10 and toll-like receptor 9 signalling in B cell proliferation: Implications for lymphoma pathogenesis
No full textA network of autocrine and paracrine signals defines B cell homeostasis and is thought to be involved in transformation processes. Investigating interactions of these microenvironmental factors and their relation to proto-oncogenes as c-Myc (MYC) is fundamental to understand the biology of B cell lymphoma. Therefore, B cells with conditional MYC expression were stimulated with CD40L, insulin-like growth factor 1, alpha-IgM, Interleukin-10 (IL10) and CpG alone or in combination. The impact of forty different interventions on cell proliferation was investigated in MYC deprived cells and calculated by linear regression. Combination of CpG and IL10 led to a strong synergistic activation of cell proliferation (S-phase/doubling of total cell number) comparable to cells with high MYC expression. A synergistic up-regulation of CDK4, CDK6 and CCND3 expression by IL10 and CpG treatment was causal for this proliferative effect as shown by qRT-PCR analysis and inhibition of the CDK4/6 complex by PD0332991. Furthermore, treatment of stimulated MYC deprived cells with MLN120b, ACHP, Pyridone 6 or Ruxolitinib showed that IL10/CpG induced proliferation and CDK4 expression were JAK/STAT3 and IKK/NF-jB dependent. This was further supported by STAT3 and p65/RELA knockdown experiments, showing strongest effects on cell proliferation and CDK4 expression after double knockdown. Additionally, chromatin immunoprecipitation revealed a dual binding of STAT3 and p65 to the proximal promotor of CDK4 after IL10/CpG treatment. Therefore, the observed synergism of IL10R and TLR9 signalling was able to induce proliferation in a comparable way as aberrant MYC and might play a role in B cell homeostasis or transformation
Modeling cross-hybridization on phylogenetic DNA microarrays increases the detection power of closely related species
No full textEngelmann JA, Rahmann S, Wolf M, et al. Modeling cross-hybridization on phylogenetic DNA microarrays increases the detection power of closely related species. Molecular Ecology Resources. 2009;9(1):83-93
Einblicke in die Funktion von NWMN_0364/Pvr von Staphylococcus aureus, zeigen ein Virulenz-regulierendes Protein
No full textThe lifestyle of Staphylococcus aureus leads to skin infections, pneumonia, endocarditis, especially in immunocompromised patients. In addition, the ability of S. aureus to form biofilms and the increasing occurrence of antibiotic-resistant variants causes serious problems not only in hospitals. In order to understand more about the virulence behaviour of S. aureus, proteins of unknown function offer new possibilities. In this study, the function of the previously hypothetical protein NWMN_0364 was analyzed. At the beginning there was only evidence that indicated a cell wall or virulence function. Using an infection assay, it could be shown that an S. aureus strain with a deletion mutation of the NWMN_0364 gene had a significantly reduced virulence. In order to find the reason for this reduced virulence, extracellular proteins were examined with a proteomic approach. This revealed that many virulence factors that are regulated by the SaeRS virulence regulation system were reduced in the deletion mutant. In addition, SaeP, the negative regulator of SaeRS, was less abundant in the mutant. This possible connection of NWMN_0364 with SaeRS was verified by transcription analyses, which showed that the transcripts of the sae operon and the virulence factors were reduced in the mutant. Interestingly, a co-immunoprecipitation experiment in vivo revealed evidence of an interaction between NWMN_0364 and SaeP. To confirm this interaction, recombinant proteins from SaeP and NWMN_0364 were used, which showed an interaction in vitro. Using cross-linking experiments, NWMN_0364 showed that it binds to SaeP mainly with the C-terminal PepSY domain. Taken together, a hypothesis of the function of NWMN_0364 was created based on the experimental results of this study. NWMN_0364 is important for virulence activation through binding to SaeP and thus activation of the SaeRS system. Based on these findings, the protein NWMN_0364 was renamed “PepSY containing, virulence regulating protein” (Pvr).Der Lebensstil von Staphylococcus aureus führt insbesondere bei immungeschwächten Patienten zu Hautinfektionen, Pneumonien, Endokarditis. Zudem verursacht die Fähigkeit von S. aureus Biofilme zu bilden und das zunehmende Vorkommen antibiotikaresistenter Varianten schwerwiegende Probleme nicht nur in Krankenhäusern. Um mehr über das Virulenzverhalten von S. aureus zu verstehen bieten Proteine unbekannter Funktion neue Möglichkeiten. In dieser Arbeit wurde die Funktion des bisher hypothetischen Proteins NWMN_0364 analysiert. Es gab zu Beginn nur Hinweise, die auf eine Zellwand oder Virulenzfunktion hinwiesen. Mit Hilfe eines Infektionsassays konnte gezeigt werden, dass ein S. aureus Stamm mit einer Deletionsmutation des NWMN_0364 Gens eine deutlich verringerte Virulenz aufwies. Um den Grund für die verringerte Virulenz zu finden, wurden extrazelluläre Proteine? mit einem proteomischen Ansatz untersucht. Dieses ergab, dass viele Virulenzfaktoren, die durch das Virulenzregulationssystem SaeRS reguliert werden, in der Deletionsmutante reduziert waren. Darüber hinaus war SaeP, der negative Regulator von SaeRS, weniger abundant in der Mutante. Diese mögliche Verbindung von NWMN_0364 mit SaeRS wurde durch Transkriptionsanalysen verifiziert, welche zeigten, dass auch die Transkripte des sae Operons als auch der Virulenzfaktoren in der Mutante verringert waren. Interessanterweise ergab ein Co-Immunpräzipitationsexperiment in vivo Hinweise auf eine Interaktion zwischen NWMN_0364 und SaeP. Um diese Interaktion zu bestätigen, wurden rekombinante Proteine ??von SaeP und NWMN_0364 verwendet, die in vitro eine Interaktion zeigten. Unter Verwendung von Cross-linkingexperimenten zeigte NWMN_0364, dass es hauptsächlich mit der C-terminale PepSY-Domäne an SaeP bindet. Zusammengenommen wurde eine Hypothese der Funktion von NWMN_0364 basierend auf den experimentellen Ergebnissen dieser Studie erstellt. NWMN_0364 ist wichtig für die Virulenzaktivierung durch Bindung an SaeP und damit Aktivierung des SaeRS-Systems. Basierend auf diesen Befunden wurde das Protein NWMN_0364 in „PepSY containing, virulence regulating protein“ (Pvr) umbenannt
FastqPuri: high-performance preprocessing of RNA-seq data
No full textPérez-Rubioet al. BMC Bioinformatics (2019) 20:226 https://doi.org/10.1186/s12859-019-2799-0SOFTWAREOpen AccessFastqPuri: high-performancepreprocessing of RNA-seq dataPaula Pérez-Rubio1, Claudio Lottaz1and Julia C. Engelmann2*AbstractBackground:RNA sequencing (RNA-seq) has become the standard means of analyzing gene and transcriptexpression in high-throughput. While previously sequence alignment was a time demanding step, fast alignmentmethods and even more so transcript counting methods which avoid mapping and quantify gene and transcriptexpression by evaluating whether a read is compatible with a transcript, have led to significant speed-ups in dataanalysis. Now, the most time demanding step in the analysis of RNA-seq data is preprocessing the raw sequence data,such as running quality control and adapter, contamination and quality filtering before transcript or genequantification. To do so, many researchers chain different tools, but a comprehensive, flexible and fast software thatcovers all preprocessing steps is currently missing.Results:We here presentFastqPuri, a light-weight and highly efficient preprocessing tool for fastq data.FastqPuriprovides sequence quality reports on the sample and dataset level with new plots which facilitate decision making forsubsequent quality filtering. Moreover,FastqPuriefficiently removes adapter sequences and sequences frombiological contamination from the data. It accepts both single- and paired-end data in uncompressed or compressedfastq files.FastqPurican be run stand-alone and is suitable to be run within pipelines. We benchmarkedFastqPuriagainst existing tools and found thatFastqPuriis superior in terms of speed, memory usage, versatility andcomprehensiveness.Conclusions:FastqPuriis a new tool which covers all aspects of short read sequence data preprocessing. It wasdesigned for RNA-seq data to meet the needs for fast preprocessing of fastq data to allow transcript and genecounting, but it is suitable to process any short read sequencing data of which high sequence quality is needed, suchas for genome assembly or SNV (single nucleotide variant) detection.FastqPuriis most flexible in filtering undesiredbiological sequences by offering two approaches to optimize speed and memory usage dependent on the total sizeof the potential contaminating sequences.FastqPuriis available athttps://github.com/jengelmann/FastqPuri.Itisimplemented in C and R and licensed under GPL v3
Gene expression can be predicted from miRNA expression with high accuracy.
No full text<p>A) Gene expression values. B) Gene expression values predicted from miRNA expression. C) Correlation of gene expression values. D) Correlation of predicted gene expression values. Besides the gene expression structure, the correlation structure is well-preserved. Predictions are from unconstrained gene models. In subfigures A and B, samples are in rows and genes are in columns. Expression values were centered and scaled and color-coded with blue representing low and yellow high expression values. The subfigures C and D show the gene-by-gene correlation structure of the genes displayed in subfigures A and B. Here, yellow indicates high correlation and red indicates anti-correlation of genes. The order of genes and samples is the same for all subfigures.</p
Gene expression of genes for which miR-19b-1 serves as one of the predictors.
No full text<p>A) Gene expression values. B) Gene expression predicted from miR-19b-1 only. C) Gene expression predicted from all predictors of the gene models. Gene expression can only be predicted if all predictors of the direct target and the residual model are used. If only miR-19b-1 is allowed as a predictor in the LARS model, the prediction is poor. In all subfigures, samples are in rows and genes in columns. Expression and predicted expression values were centered and scaled and color-coded with blue representing low and yellow high expression values. The order of genes and samples is the same for all sub-figures.</p
Interaction network of miR-19b-1.
No full text<p>Interactions of miR-19b-1 with genes with functions in ‘DNA recombination’ (orange), ‘DNA repair’ (pink), ‘programmed cell death’ (green), all three categories (yellow), in ‘DNA recombination’ and ‘DNA repair’ (purple) and in ‘DNA recombination’ and ‘programmed cell death’ (red). miR-19b-1 is located in the center of the network, around it are genes for which miR-19b-1 is one of the predictors from the negative restricted models (NRM) and the third layer consists of miRNAs for which the genes from the second layer are predictors (unconstrained models). Genes from direct target NRM models (miR-19b-1 is predicted to target the gene by at least two miRNA target prediction algorithms) are represented by rectangular nodes. Genes from residual models have ellipsoid nodes. TFPT: TCF3 (E2A) fusion partner (in childhood Leukemia) [HGNC:13630]; POLR2E: polymerase (RNA) II (DNA directed) polypeptide E, 25 kDa [HGNC:9192]; MDK: midkine (neurite growth-promoting factor 2) [HGNC:6972]; PSMA2: proteasome (prosome, macropain) subunit, alpha type, 2 [HGNC:9531]; SWAP70: SWAP switching B-cell complex 70 kDa subunit [HGNC:17070]; PLK2: polo-like kinase 2 [HGNC:19699]; CTGF: connective tissue growth factor [HGNC:2500]; UBE2B: ubiquitin-conjugating enzyme E2B [HGNC:12473]; NGFRAP1:nerve growth factor receptor (TNFRSF16) associated protein 1 [HGNC:13388]; TPX2: TPX2, microtubule-associated, homolog (Xenopus laevis) [HGNC:1249]; PRKCD: protein kinase C, delta [HGNC:9399]; RUVBL1: RuvB-like 1 (E. coli) [HGNC:10474]; AGRN: agrin [HGNC:329]; NR3C1: nuclear receptor subfamily 3, group C, member 1 (glucocorticoid receptor) [HGNC:7978]; HUWE1: HECT, UBA and WWE domain containing 1, E3 ubiquitin protein ligase [HGNC:30892]; RRAGA: Ras-related GTP binding A [HGNC:16963]; USP1: ubiquitin specific peptidase 1 [HGNC:12607]; RPS6KA3: ribosomal protein S6 kinase, 90 kDa, polypeptide 3 [HGNC:10432]; DUSP1: dual specificity phosphatase 1 [HGNC:3064]; PHLDA3: pleckstrin homology-like domain, family A, member 3 [HGNC:8934].</p
A least angle regression model for the prediction of canonical and non-canonical miRNA-mRNA interactions
No full textmicroRNAs (miRNAs) are short non-coding RNAs with regulatory functions in various biological processes including cell differentiation, development and oncogenic transformation. They can bind to mRNA transcripts of protein-coding genes and repress their translation or lead to mRNA degradation. Conversely, the transcription of miRNAs is regulated by proteins including transcription factors, co-factors, and messenger molecules in signaling pathways, yielding a bidirectional regulatory network of gene and miRNA expression. We describe here a least angle regression approach for uncovering the functional interplay of gene and miRNA regulation based on paired gene and miRNA expression profiles. First, we show that gene expression profiles can indeed be reconstructed from the expression profiles of miRNAs predicted to be regulating the specific gene. Second, we propose a two-step model where in the first step, sequence information is used to constrain the possible set of regulating miRNAs and in the second step, this constraint is relaxed to find regulating miRNAs that do not rely on perfect seed binding. Finally, a bidirectional network comprised of miRNAs regulating genes and genes regulating miRNAs is built from our previous regulatory predictions. After applying the method to a human cancer cell line data set, an analysis of the underlying network reveals miRNAs known to be associated with cancer when dysregulated are predictors of genes with functions in apoptosis. Among the predicted and newly identified targets that lack a classical miRNA seed binding site of a specific oncomir, miR-19b-1, we found an over-representation of genes with functions in apoptosis, which is in accordance with the previous finding that this miRNA is the key oncogenic factor in the mir-17-92 cluster. In addition, we found genes involved in DNA recombination and repair that underline its importance in maintaining the integrity of the cell
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