Selection of control genes for quantitative RT-PCR based on microarray data

CVID enteropathy is characterized by exceeding low mucosal IgA levels and interferon-driven inflammation possibly related to the presence of a pathobiont

Common variable immunodeficiency (CVID), the most common symptomatic primary antibody deficiency, is accompanied in some patients by a duodenal inflammation and malabsorption syndrome known as CVID enteropathy (E-CVID).The goal of this study was to investigate the immunological abnormalities in CVID patients that lead to enteropathy as well as the contribution of intestinal microbiota to this process.We found that, in contrast to noE-CVID patients (without enteropathy), E-CVID patients have exceedingly low levels of IgA in duodenal tissues. In addition, using transkingdom network analysis of the duodenal microbiome, we identified Acinetobacter baumannii as a candidate pathobiont in E-CVID. Finally, we found that E-CVID patients exhibit a pronounced activation of immune genes and down-regulation of epithelial lipid metabolism genes. We conclude that in the virtual absence of mucosal IgA, pathobionts such as A. baumannii, may induce inflammation that re-directs intestinal molecular pathways from lipid metabolism to immune processes responsible for enteropathy.

Global transcriptional responses of Acidithiobacillus ferrooxidans Wenelen under different sulfide minerals

In order to provide new information about the adaptation of Acidithiobacillus ferrooxidans during the bioleaching process, the current analysis presents the first report of the global transcriptional response of the native copper mine strain Wenelen (DSM 16786) oxidized under different sulfide minerals. Microarrays were used to measure the response of At. ferrooxidans Wenelen to shifts from iron supplemented liquid cultures (reference state) to the addition of solid substrates enriched in pyrite or chalcopyrite. Genes encoding for energy metabolism showed a similar transcriptional profile for the two sulfide minerals. Interestingly, four operons related to sulfur metabolism were over-expressed during growth on a reduced sulfur source. Genes associated with metal tolerance (RND and ATPases type P) were up-regulated in the presence of pyrite or chalcopyrite. These results suggest that At. ferrooxidans Wenelen presents an efficient transcriptional system developed to respond to environmental conditions, namely the ability to withstand high copper concentrations.

Reverse enGENEering of Regulatory Networks from Big Data: A Roadmap for Biologists

Omics technologies enable unbiased investigation of biological systems through massively parallel sequence acquisition or molecular measurements, bringing the life sciences into the era of Big Data. A central challenge posed by such omics datasets is how to transform these data into biological knowledge, for example, how to use these data to answer questions such as: Which functional pathways are involved in cell differentiation? Which genes should we target to stop cancer? Network analysis is a powerful and general approach to solve this problem consisting of two fundamental stages, network reconstruction, and network interrogation. Here we provide an overview of network analysis including a step-by-step guide on how to perform and use this approach to investigate a biological question. In this guide, we also include the software packages that we and others employ for each of the steps of a network analysis workflow.

Identification of stable reference genes in differentiating human pluripotent stem cells

Reference genes, often referred to as housekeeping genes (HKGs), are frequently used to normalize gene expression data based on the assumption that they are expressed at a constant level in the cells. However, several studies have shown that there may be a large variability in the gene expression levels of HKGs in various cell types. In a previous study, employing human embryonic stem cells (hESCs) subjected to spontaneous differentiation, we observed that the expression of commonly used HKG varied to a degree that rendered them inappropriate to use as reference genes under those experimental settings. Here we present a substantially extended study of the HKG signature in human pluripotent stem cells (hPSC), including nine global gene expression datasets from both hESC and human induced pluripotent stem cells, obtained during directed differentiation toward endoderm-, mesoderm-, and ectoderm derivatives. Sets of stably expressed genes were compiled, and a handful of genes (e.g., EID2, ZNF324B, CAPN10, and RABEP2) were identified as generally applicable reference genes in hPSCs across all cell lines and experimental conditions. The stability in gene expression profiles was confirmed by reverse transcription quantitative PCR analysis. Taken together, the current results suggest that differentiating hPSCs have a distinct HKG signature, which in some aspects is different from somatic cell types, and underscore the necessity to validate the stability of reference genes under the actual experimental setup used. In addition, the novel putative HKGs identified in this study can preferentially be used for normalization of gene expression data obtained from differentiating hPSCs.

Transcriptional profiling of C. elegans DAF-19 uncovers a ciliary base-associated protein and a CDK/CCRK/LF2p-related kinase required for intraflagellar transport

Cilia are ubiquitous cell surface projections that mediate various sensory- and motility-based processes and are implicated in a growing number of multi-organ genetic disorders termed ciliopathies. To identify new components required for cilium biogenesis and function, we sought to further define and validate the transcriptional targets of DAF-19, the ciliogenic C. elegans RFX transcription factor. Transcriptional profiling of daf-19 mutants (which do not form cilia) and wild-type animals was performed using embryos staged to when the cell types developing cilia in the worm, the ciliated sensory neurons (CSNs), still differentiate. Comparisons between the two populations revealed 881 differentially regulated genes with greater than a 1.5-fold increase or decrease in expression. A subset of these was confirmed by quantitative RT-PCR. Transgenic worms expressing transcriptional GFP fusions revealed CSN-specific expression patterns for 11 of 14 candidate genes. We show that two uncharacterized candidate genes, termed dyf-17 and dyf-18 because their corresponding mutants display dye-filling (Dyf) defects, are important for ciliogenesis. DYF-17 localizes at the base of cilia and is specifically required for building the distal segment of sensory cilia. DYF-18 is an evolutionarily conserved CDK7/CCRK/LF2p-related serine/threonine kinase that is necessary for the proper function of intraflagellar transport, a process critical for cilium biogenesis. Together, our microarray study identifies targets of the evolutionarily conserved RFX transcription factor, DAF-19, providing a rich dataset from which to uncover-in addition to DYF-17 and DYF-18-cellular components important for cilium formation and function.

Identification of reference genes across physiological states for qRT-PCR through microarray meta-analysis

Background

The accuracy of quantitative real-time PCR (qRT-PCR) is highly dependent on reliable reference gene(s). Some housekeeping genes which are commonly used for normalization are widely recognized as inappropriate in many experimental conditions. This study aimed to identify reference genes for clinical studies through microarray meta-analysis of human clinical samples.

Methodology/Principal Findings

After uniform data preprocessing and data quality control, 4,804 Affymetrix HU-133A arrays performed by clinical samples were classified into four physiological states with 13 organ/tissue types. We identified a list of reference genes for each organ/tissue types which exhibited stable expression across physiological states. Furthermore, 102 genes identified as reference gene candidates in multiple organ/tissue types were selected for further analysis. These genes have been frequently identified as housekeeping genes in previous studies, and approximately 71% of them fall into Gene Expression (GO:0010467) category in Gene Ontology.

Conclusions/Significance

Based on microarray meta-analysis of human clinical sample arrays, we identified sets of reference gene candidates for various organ/tissue types and then examined the functions of these genes. Additionally, we found that many of the reference genes are functionally related to transcription, RNA processing and translation. According to our results, researchers could select single or multiple reference gene(s) for normalization of qRT-PCR in clinical studies.

Determination of reference genes for circadian studies in different tissues and mouse strains

BACKGROUND

Circadian rhythms have a profound effect on human health. Their disruption can lead to serious pathologies, such as cancer and obesity. Gene expression studies in these pathologies are often studied in different mouse strains by quantitative real time polymerase chain reaction (qPCR). Selection of reference genes is a crucial step of qPCR experiments. Recent studies show that reference gene stability can vary between species and tissues, but none has taken circadian experiments into consideration.

RESULTS

In the present study the expression of ten candidate reference genes (Actb, Eif2a, Gapdh, Hmbs, Hprt1, Ppib, Rn18s, Rplp0, Tbcc and Utp6c) was measured in 131 liver and 97 adrenal gland samples taken from three mouse strains (C57BL/6JOlaHsd, 129Pas plus C57BL/6J and Crem KO on 129Pas plus C57BL/6J background) every 4 h in a 24 h period. Expression stability was evaluated by geNorm and NormFinder programs. Differences in ranking of the most stable reference genes were observed both between individual mouse strains as well as between tissues within each mouse strain. We show that selection of reference gene (Actb) that is often used for analyses in individual mouse strains leads to errors if used for normalization when different mouse strains are compared. We identified alternative reference genes that are stable in these comparisons.

CONCLUSIONS

Genetic background and circadian time influence the expression stability of reference genes. Differences between mouse strains and tissues should be taken into consideration to avoid false interpretations. We show that the use of a single reference gene can lead to false biological conclusions. This manuscript provides a useful reference point for researchers that search for stable reference genes in the field of circadian biology.

CD38 regulation in activated astrocytes: implications for neuroinflammation and HIV-1 brain infection

Reactive astrogliosis is a key pathological aspect of neuroinflammatory disorders including human immunodeficiency virus type 1 (HIV-1)-associated neurological disease. On the basis of previous data that showedastrocytes activated with interleukin (IL)-1beta induce neuronal injury, we analyzed global gene changes in IL-1beta-activated human astrocytes by gene microarray. Among the up-regulated genes, CD38, a 45-kDa type II single chain transmembrane glycoprotein, was a top candidate, with a 17.24-fold change that was validated by real-time polymerase chain reaction. Key functions of CD38 include enzymatic activities and involvement in adhesion and cell signaling. Importantly, CD38(+)CD8(+) T-cell expression is a clinical correlate for progression of HIV-1 infection and biological marker for immune activation. Thus, CD38 expression in HIV-1 and/or IL-1beta-stimulated human astrocytes and human brain tissues was analyzed. IL-1beta and HIV-1 activation of astrocytes enhanced CD38 mRNA levels. Both CD38 immunoreactivity and adenosine 5'-diphosphate (ADP)-ribosyl cyclase activity were up-regulated in IL-1beta-activated astrocytes. CD38 knockdown using specific siRNAs significantly reduced astrocyte proinflammatory cytokine and chemokine production. However, CD38 mRNA levels were unchanged in IL-1beta knockdown conditions, suggesting that IL-1beta autocrine loop is not implicated in this process. Quantitative immunohistochemical analysis of HIV-seropositive without encephalitis and HIV-1 encephalitis brain tissues showed significant up-regulation of CD38, which colocalized with glial fibrillary acidic protein-positive cells in areas of inflammation. These results suggest an important role of CD38 in the regulation of astrocyte dysfunction during the neuroinflammatory processes involved in neurodegenerative/neuroinflammatory disorders such as HIV-1 encephalitis.

Identification of novel reference genes using multiplatform expression data and their validation for quantitative gene expression analysis

Normalization of mRNA levels using endogenous reference genes (ERGs) is critical for an accurate comparison of gene expression between different samples. Despite the popularity of traditional ERGs (tERGs) such as GAPDH and ACTB, their expression variability in different tissues or disease status has been reported. Here, we first selected candidate housekeeping genes (HKGs) using human gene expression data from different platforms including EST, SAGE, and microarray, and 13 novel ERGs (nERGs) (ARL8B, CTBP1, CUL1, DIMT1L, FBXW2, GPBP1, LUC7L2, OAZ1, PAPOLA, SPG21, TRIM27, UBQLN1, ZNF207) were further identified from these HKGs. The mean coefficient variation (CV) values of nERGs were significantly lower than those of tERGs and the expression level of most nERGs was relatively lower than high expressing tERGs in all dataset. The higher expression stability and lower expression levels of most nERGs were validated in 108 human samples including formalin-fixed paraffin-embedded (FFPE) tissues, frozen tissues and cell lines, through quantitative real-time RT-PCR (qRT-PCR). Furthermore, the optimal number of nERGs required for accurate normalization was as few as two, while four genes were required when using tERGs in FFPE tissues. Most nERGs identified in this study should be better reference genes than tERGs, based on their higher expression stability and fewer numbers needed for normalization when multiple ERGs are required.

High levels of granzyme B expression in invasive cervical carcinoma correlates to poor response to treatment

The present study assessed, in cervical carcinoma, expression levels of seven immune response genes and sought correlation to response to treatment. The expression levels of CD28, CTLA4, ICOS, ICOSL, CD80 and CD86 and granzyme B genes were assessed by real-time RT-PCR in pre-treatment tumor fragments. During the six-month follow-up after treatment, 8 patients presented tumor and 10 survived free of tumor. The only gene whose expression levels were higher in patients with poor outcome (p = 0.03) was granzyme B. Further evaluation, in adequately powered prospective studies is warranted to confirm the data and to translate this observation to the clinical setting.

Optimizing human post-mortem brain tissue gene expression profiling in Parkinson's disease and other neurodegenerative disorders: from target "fishing" to translational breakthroughs

Insights on the etiopathogenesis of common neurodegenerative disorders such as Parkinson's disease (PD) and Alzheimer's disease (AD) have been largely based on the discovery of gene mutations in genetically determined forms. Although these discoveries have been helpful in elucidating the basic molecular pathogenesis of familial forms, they represent a small fraction of cases, leaving the large majority classified as idiopathic. In the postgenomic era, brain tissue gene expression profiling has allowed relative quantitative assessment of thousands of genes simultaneously from one tissue sample, providing clues for novel candidate genes and processes implicated in neurodegenerative disorders. Some remain critical of "fishing expedition" science, but gene expression profiling is a discovery-based procedure well suited for the study of largely idiopathic and multifactorial diseases. However, the technology is still under development, and many methodological and biological aspects contribute to the heterogeneous results obtained from gene expression profiling. In this Review, we discuss the advantages and limitations of this technology in simple terms and identify the key variables that influence/limit gene expression profiling-derived translational breakthroughs in neurodegenerative diseases.

Differentiating human embryonic stem cells express a unique housekeeping gene signature

Housekeeping genes (HKGs) are involved in basic functions needed for the sustenance of the cell and are assumed to be constitutively expressed at a constant level. Based on these features, HKGs are frequently used for normalization of gene expression data. In the present study, we used the CodeLink Gene Expression Bioarray system to interrogate changes in gene expression occurring during differentiation of human ESCs (hESCs). Notably, in the three hESC lines used for the study, we observed that the RNA levels of 56 frequently used HKGs varied to a degree that rendered them inappropriate as reference genes. Therefore, we defined a novel set of HKGs specifically for hESCs. Here we present a comprehensive list of 292 genes that are stably expressed (coefficient of variation <20%) in differentiating hESCs. These genes were further grouped into high-, medium-, and low-expressed genes. The expression patterns of these novel HKGs show very little overlap with results obtained from somatic cells and tissues. We further explored the stability of this novel set of HKGs in independent, publicly available gene expression data from hESCs and observed substantial similarities with our results. Gene expression was confirmed by real-time quantitative polymerase chain reaction analysis. Taken together, these results suggest that differentiating hESCs have a unique HKG signature and underscore the necessity to validate the expression profiles of putative HKGs. In addition, this novel set of HKGs can preferentially be used as controls in gene expression analyses of differentiating hESCs.

Novel insights into lung transplant rejection by microarray analysis

Gene expression microarrays can estimate the prevalence of mRNA for thousands of genes in a small sample of cells or tissue. Organ transplant researchers are increasingly using microarrays to identify specific patterns of gene expression that predict and characterize acute and chronic rejection, and to improve our understanding of the mechanisms underlying organ allograft dysfunction. We used microarrays to assess gene expression in bronchoalveolar lavage cell samples from lung transplant recipients with and without acute rejection on simultaneous lung biopsies. These studies showed increased expression during acute rejection of genes involved in inflammation, apoptosis, and T-cell activation and proliferation. We also studied gene expression during the evolution of airway obliteration in a murine heterotopic tracheal transplant model of chronic rejection. These studies demonstrated specific patterns of gene expression at defined time points after transplantation in allografts, whereas gene expression in isografts reverted back to that of native tracheas within 2 wk after transplantation. These studies demonstrate the potential power of microarrays to identify biomarkers of acute and chronic lung rejection. The application of new genetic, genomic, and proteomic technologies is in its infancy, and the microarray-based studies described here are clearly only the beginning of their application to lung transplantation. The massive amount of data generated per tissue or cell sample has spawned an outpouring of invention in the bioinformatics field, which is developing methodologies to turn data into meaningful and reproducible clinical and mechanistic inferences.

Molecular profiling improves diagnoses of rejection and infection in transplanted organs

The monitoring of transplanted hearts is currently based on histological evaluation of endomyocardial biopsies, a method that is fairly insensitive and that does not always accurately discriminate between rejection and infection in the heart. Accurate diagnosis of rejection and infection is absolutely crucial, however, as the respective treatments are completely different. Using microarrays, we analyzed gene expression in 76 cardiac biopsies from 40 heart recipients undergoing rejection, no rejection, or Trypanosoma cruzi infection. We found a set of genes whose expression patterns were typical of acute rejection, and another set of genes that discriminated between rejection and T cruzi infection. These sets revealed acute rejection episodes up to 2 weeks earlier, and trypanosome infection up to 2 months earlier than did histological evaluation. When applied to raw data from other institutions, the 2 sets of predictive genes were also able to accurately pinpoint acute rejection of lung and kidney transplants, as well as bacterial infections in kidneys. In addition to their usefulness as diagnostic tools, the data suggest that there are similarities in the biology of the processes involved in rejection of different grafts and also in the tissue responses to pathogens as diverse as bacteria and protozoa.