Climatic oscillations shape the phylogeographical structure of Atlantic Forest fire-eye antbirds (Aves: Thamnophilidae)

In the present study, mitochondrial (mt)DNA sequence data were used to examine the genetic structure of fire-eye antbirds (genus Pyriglena) along the Atlantic Forest and the predictions derived from the river hypothesis and from a Last Glacial Maximum Pleistocene refuge paleomodel were compared to explain the patterns of genetic variation observed in these populations. A total of 266 individuals from 45 populations were sampled over a latitudinal transect and a number of phylogeographical and population genetics analytical approaches were employed to address these questions. The pattern of mtDNA variation observed in fire-eye antbirds provides little support for the view that populations were isolated by the modern course of major Atlantic Forest rivers. Instead, the data provide stronger support for the predictions of the refuge model. These results add to the mounting evidence that climatic oscillations appear to have played a substantial role in shaping the phylogeographical structure and possibly the diversification of many taxa in this region. However, the results also illustrate the potential for more complex climatic history and historical changes in the geographical distribution of Atlantic Forest than envisioned by the refuge model. (c) 2012 The Linnean Society of London, Biological Journal of the Linnean Society, 2012, 105, 900824.

Effect of human TGF-beta on the gene expression profile of Schistosoma mansoni adult worms

Schistosoma mansoni is responsible for schistosomiasis, a parasitic disease that affects 200 million people worldwide. Molecular mechanisms of host-parasite interaction are complex and involve a crosstalk between host signals and parasite receptors. TGF-beta signaling pathway has been shown to play an important role in S. mansoni development and embryogenesis. In particular human (h) TGF-beta has been shown to bind to a S. mansoni receptor, transduce a signal that regulates the expression of a schistosome target gene. Here we describe 381 parasite genes whose expression levels are affected by in vitro treatment with hTGF-beta. Among these differentially expressed genes we highlight genes related to morphology, development and cell cycle that could be players of cytokine effects on the parasite. We confirm by qPCR the expression changes detected with microarrays for 5 out of 7 selected genes. We also highlight a set of non-coding RNAs transcribed from the same loci of protein-coding genes that are differentially expressed upon hTCF-beta treatment. These datasets offer potential targets to be explored in order to understand the molecular mechanisms behind the possible role of hTGF-beta effects on parasite biology. (C) 2012 Elsevier B.V. All rights reserved.

Gene expression down-regulation in CD90+ prostate tumor-associated stromal cells involves potential organ-specific genes

Abstract Background The prostate stroma is a key mediator of epithelial differentiation and development, and potentially plays a role in the initiation and progression of prostate cancer. The tumor-associated stroma is marked by increased expression of CD90/THY1. Isolation and characterization of these stromal cells could provide valuable insight into the biology of the tumor microenvironment. Methods Prostate CD90+ stromal fibromuscular cells from tumor specimens were isolated by cell-sorting and analyzed by DNA microarray. Dataset analysis was used to compare gene expression between histologically normal and tumor-associated stromal cells. For comparison, stromal cells were also isolated and analyzed from the urinary bladder. Results The tumor-associated stromal cells were found to have decreased expression of genes involved in smooth muscle differentiation, and those detected in prostate but not bladder. Other differential expression between the stromal cell types included that of the CXC-chemokine genes. Conclusion CD90+ prostate tumor-associated stromal cells differed from their normal counterpart in expression of multiple genes, some of which are potentially involved in organ development.

Modeling gene expression regulatory networks with the sparse vector autoregressive model

Abstract Background To understand the molecular mechanisms underlying important biological processes, a detailed description of the gene products networks involved is required. In order to define and understand such molecular networks, some statistical methods are proposed in the literature to estimate gene regulatory networks from time-series microarray data. However, several problems still need to be overcome. Firstly, information flow need to be inferred, in addition to the correlation between genes. Secondly, we usually try to identify large networks from a large number of genes (parameters) originating from a smaller number of microarray experiments (samples). Due to this situation, which is rather frequent in Bioinformatics, it is difficult to perform statistical tests using methods that model large gene-gene networks. In addition, most of the models are based on dimension reduction using clustering techniques, therefore, the resulting network is not a gene-gene network but a module-module network. Here, we present the Sparse Vector Autoregressive model as a solution to these problems. Results We have applied the Sparse Vector Autoregressive model to estimate gene regulatory networks based on gene expression profiles obtained from time-series microarray experiments. Through extensive simulations, by applying the SVAR method to artificial regulatory networks, we show that SVAR can infer true positive edges even under conditions in which the number of samples is smaller than the number of genes. Moreover, it is possible to control for false positives, a significant advantage when compared to other methods described in the literature, which are based on ranks or score functions. By applying SVAR to actual HeLa cell cycle gene expression data, we were able to identify well known transcription factor targets. Conclusion The proposed SVAR method is able to model gene regulatory networks in frequent situations in which the number of samples is lower than the number of genes, making it possible to naturally infer partial Granger causalities without any a priori information. In addition, we present a statistical test to control the false discovery rate, which was not previously possible using other gene regulatory network models.

Transcriptional effects of 1,25 dihydroxyvitamin D3 physiological and supra-physiological concentrations in breast cancer organotypic culture

Background Vitamin D transcriptional effects were linked to tumor growth control, however, the hormone targets were determined in cell cultures exposed to supra physiological concentrations of 1,25(OH)2D3 (50-100nM). Our aim was to evaluate the transcriptional effects of 1,25(OH)2D3 in a more physiological model of breast cancer, consisting of fresh tumor slices exposed to 1,25(OH)2D3 at concentrations that can be attained in vivo. Methods Tumor samples from post-menopausal breast cancer patients were sliced and cultured for 24 hours with or without 1,25(OH)2D3 0.5nM or 100nM. Gene expression was analyzed by microarray (SAM paired analysis, FDR≤0.1) or RT-qPCR (p≤0.05, Friedman/Wilcoxon test). Expression of candidate genes was then evaluated in mammary epithelial/breast cancer lineages and cancer associated fibroblasts (CAFs), exposed or not to 1,25(OH)2D3 0.5nM, using RT-qPCR, western blot or immunocytochemistry. Results 1,25(OH)2D3 0.5nM or 100nM effects were evaluated in five tumor samples by microarray and seven and 136 genes, respectively, were up-regulated. There was an enrichment of genes containing transcription factor binding sites for the vitamin D receptor (VDR) in samples exposed to 1,25(OH)2D3 near physiological concentration. Genes up-modulated by both 1,25(OH)2D3 concentrations were CYP24A1, DPP4, CA2, EFTUD1, TKTL1, KCNK3. Expression of candidate genes was subsequently evaluated in another 16 samples by RT-qPCR and up-regulation of CYP24A1, DPP4 and CA2 by 1,25(OH)2D3 was confirmed. To evaluate whether the transcripitonal targets of 1,25(OH)2D3 0.5nM were restricted to the epithelial or stromal compartments, gene expression was examined in HB4A, C5.4, SKBR3, MDA-MB231, MCF-7 lineages and CAFs, using RT-qPCR. In epithelial cells, there was a clear induction of CYP24A1, CA2, CD14 and IL1RL1. In fibroblasts, in addition to CYP24A1 induction, there was a trend towards up-regulation of CA2, IL1RL1, and DPP4. A higher protein expression of CD14 in epithelial cells and CA2 and DPP4 in CAFs exposed to 1,25(OH)2D3 0.5nM was detected. Conclusions In breast cancer specimens a short period of 1,25(OH)2D3 exposure at near physiological concentration modestly activates the hormone transcriptional pathway. Induction of CYP24A1, CA2, DPP4, IL1RL1 expression appears to reflect 1,25(OH)2D3 effects in epithelial as well as stromal cells, however, induction of CD14 expression is likely restricted to the epithelial compartment.

Multiple testing in spatial epidemiology: a Bayesian approach

In this work we aim to propose a new approach for preliminary epidemiological studies on Standardized Mortality Ratios (SMR) collected in many spatial regions. A preliminary study on SMRs aims to formulate hypotheses to be investigated via individual epidemiological studies that avoid bias carried on by aggregated analyses. Starting from collecting disease counts and calculating expected disease counts by means of reference population disease rates, in each area an SMR is derived as the MLE under the Poisson assumption on each observation. Such estimators have high standard errors in small areas, i.e. where the expected count is low either because of the low population underlying the area or the rarity of the disease under study. Disease mapping models and other techniques for screening disease rates among the map aiming to detect anomalies and possible high-risk areas have been proposed in literature according to the classic and the Bayesian paradigm. Our proposal is approaching this issue by a decision-oriented method, which focus on multiple testing control, without however leaving the preliminary study perspective that an analysis on SMR indicators is asked to. We implement the control of the FDR, a quantity largely used to address multiple comparisons problems in the eld of microarray data analysis but which is not usually employed in disease mapping. Controlling the FDR means providing an estimate of the FDR for a set of rejected null hypotheses. The small areas issue arises diculties in applying traditional methods for FDR estimation, that are usually based only on the p-values knowledge (Benjamini and Hochberg, 1995; Storey, 2003). Tests evaluated by a traditional p-value provide weak power in small areas, where the expected number of disease cases is small. Moreover tests cannot be assumed as independent when spatial correlation between SMRs is expected, neither they are identical distributed when population underlying the map is heterogeneous. The Bayesian paradigm oers a way to overcome the inappropriateness of p-values based methods. Another peculiarity of the present work is to propose a hierarchical full Bayesian model for FDR estimation in testing many null hypothesis of absence of risk.We will use concepts of Bayesian models for disease mapping, referring in particular to the Besag York and Mollié model (1991) often used in practice for its exible prior assumption on the risks distribution across regions. The borrowing of strength between prior and likelihood typical of a hierarchical Bayesian model takes the advantage of evaluating a singular test (i.e. a test in a singular area) by means of all observations in the map under study, rather than just by means of the singular observation. This allows to improve the power test in small areas and addressing more appropriately the spatial correlation issue that suggests that relative risks are closer in spatially contiguous regions. The proposed model aims to estimate the FDR by means of the MCMC estimated posterior probabilities b i's of the null hypothesis (absence of risk) for each area. An estimate of the expected FDR conditional on data (\FDR) can be calculated in any set of b i's relative to areas declared at high-risk (where thenull hypothesis is rejected) by averaging the b i's themselves. The\FDR can be used to provide an easy decision rule for selecting high-risk areas, i.e. selecting as many as possible areas such that the\FDR is non-lower than a prexed value; we call them\FDR based decision (or selection) rules. The sensitivity and specicity of such rule depend on the accuracy of the FDR estimate, the over-estimation of FDR causing a loss of power and the under-estimation of FDR producing a loss of specicity. Moreover, our model has the interesting feature of still being able to provide an estimate of relative risk values as in the Besag York and Mollié model (1991). A simulation study to evaluate the model performance in FDR estimation accuracy, sensitivity and specificity of the decision rule, and goodness of estimation of relative risks, was set up. We chose a real map from which we generated several spatial scenarios whose counts of disease vary according to the spatial correlation degree, the size areas, the number of areas where the null hypothesis is true and the risk level in the latter areas. In summarizing simulation results we will always consider the FDR estimation in sets constituted by all b i's selected lower than a threshold t. We will show graphs of the\FDR and the true FDR (known by simulation) plotted against a threshold t to assess the FDR estimation. Varying the threshold we can learn which FDR values can be accurately estimated by the practitioner willing to apply the model (by the closeness between\FDR and true FDR). By plotting the calculated sensitivity and specicity (both known by simulation) vs the\FDR we can check the sensitivity and specicity of the corresponding\FDR based decision rules. For investigating the over-smoothing level of relative risk estimates we will compare box-plots of such estimates in high-risk areas (known by simulation), obtained by both our model and the classic Besag York Mollié model. All the summary tools are worked out for all simulated scenarios (in total 54 scenarios). Results show that FDR is well estimated (in the worst case we get an overestimation, hence a conservative FDR control) in small areas, low risk levels and spatially correlated risks scenarios, that are our primary aims. In such scenarios we have good estimates of the FDR for all values less or equal than 0.10. The sensitivity of\FDR based decision rules is generally low but specicity is high. In such scenario the use of\FDR = 0:05 or\FDR = 0:10 based selection rule can be suggested. In cases where the number of true alternative hypotheses (number of true high-risk areas) is small, also FDR = 0:15 values are well estimated, and \FDR = 0:15 based decision rules gains power maintaining an high specicity. On the other hand, in non-small areas and non-small risk level scenarios the FDR is under-estimated unless for very small values of it (much lower than 0.05); this resulting in a loss of specicity of a\FDR = 0:05 based decision rule. In such scenario\FDR = 0:05 or, even worse,\FDR = 0:1 based decision rules cannot be suggested because the true FDR is actually much higher. As regards the relative risk estimation, our model achieves almost the same results of the classic Besag York Molliè model. For this reason, our model is interesting for its ability to perform both the estimation of relative risk values and the FDR control, except for non-small areas and large risk level scenarios. A case of study is nally presented to show how the method can be used in epidemiology.

Analisi del profilo tossicologico e cancerogeno di contaminanti ambientali e identificazione dei rischi per la salute umana correlati all'esposizione

L’attenta analisi della letteratura scientifica su argomenti riguardanti i contaminanti ambientali oggetto di studio (i policlorodifenili) ha permesso di raccogliere dati utili riguardanti le proprietà di queste molecole, la loro diffusione e la loro pericolosità. Oggetto della ricerca è stato lo studio in vitro del potenziale citotossico e trasformante dei PCB, utilizzando come riferimento una miscela commerciale di PCB, l’Aroclor 1260, e di un MIX di 18 congeneri ricostituito in laboratorio. Il lavoro è proseguito con la valutazione degli effetti di queste miscele e di due congeneri singoli (PCB 118 e PCB 153) su linee cellulari diverse in test di vitalità a breve termine. L’utilizzo di test specifici ha poi permesso la valutazione di un possibile potenziale estrogenico. Una volta ottenuto un quadro generale sui possibili effetti delle miscele grazie ai risultati dei test funzionali, è stata valutata la modulazione, da parte delle molecole e/o di miscele delle stesse, dell’espressione di geni coinvolti nella risposta ad estrogeni o a composti diossino simili, andando ad effettuare un’analisi di tipo molecolare con Real-Time PCR (RT-PCR) e analizzando nello specifico marcatori di pathway dell’Aryl Hydrocarbon Receptor (AhR) o dell’Estrogen Receptor (ER). In ultima analisi al fine di verificare l’applicabilità di biomarkers di espressione a situazioni di contaminazioni reali, ci si è focalizzati su campioni estratti da matrici ambientali, ed in particolare linee cellulari di interesse sono state esposte a estratti di sedimenti provenienti da siti inquinati. L’approccio scelto è stato di tipo molecolare, con lo scopo di individuare pathway da valutare in un secondo momento in test funzionali specifici. L’attività di ricerca si è avvalsa della tecnica del DNA-microarray per valutare la modulazione dell’espressione genica in risposta all’esposizione a contaminanti ambientali. In questo modo è possibile definire i profili di espressione genica che sottendono a risposte biologiche complesse nell’intento di individuare biomarcatori in grado di predire il rischio per l’uomo, e di consentire la stima di una relazione diretta tra esposizione ed effetti possibili.

LrhA als Regulator der Flagellen, Motilität, Chemotaxis und Typ 1 Fimbrien in Escherichia coli

Das lrhA-Gen von E. coli kodiert für einen Transkriptionsregulator der LysR-Familie. Die Funktion von LrhA war ungeklärt und sollte durch Vergleich der Gesamt-mRNA aus einem E. coli-Wildtyp und einer isogenen lrhA-Mutante mit Hilfe von Genomanalysen untersucht werden. In der lrhA-Mutante war der mRNA-Gehalt vieler Gene um den Faktor 3 bis 80 erhöht. Es handelt sich um Flagellen-, Motilitäts- und Chemotaxisgene, bzw. um Gene der Typ 1 Fimbrien. Diese Ergebnisse wurden in Expressionsmessungen bestätigt. LrhA war in der Lage an den Promotor von flhDC zu binden, aber nicht an die Promotoren der übrigen Gene für Motilität und Chemotaxis. FlhDC kodiert für den übergeordneten Regulator FlhD2C2 der Fagellensynthese.LrhA war außerdem in der Lage an die Promotoren der Gene für Typ 1 Fimbrien fimA und fimE zu binden. Typ 1 Fimbrien stellen in E. coli Virulenzfaktoren dar. Eine Regulation weiterer Virulenzfaktoren durch LrhA konnte in DNA-Pathoarrays ausgeschlossen werden.LrhA ist damit ein wichtiger Transkriptionsregulator, der die Expression der Gene für Flagellen, Motilität, Chemotaxis und Typ 1 Fimbrien reguliert. FlhDC, fimA und fimE stellen dabei direkte Zielgene von LrhA dar. Außerdem konnte eine positive Autoregulation von LrhA nachgewiesen werden.

Ruolo di interleuchina-33 sull'espressione di geni profibrotici e sull'ipertrofia dei miofibroblasti nella fibrosi intestinale

Background: Intestinal fibrosis is a serious complication of IBD, with more than a third of Crohn’s disease (CD) patients developing a fibrostenosing phenotype with formation of strictures that will require surgical intervention. Remarkably, SAMP1/YitFc (SAMP) mice, a spontaneous model of CD, develop gut fibrosis; similar to IBD patients, the pathophysiology of SAMP fibrosis is unknown. IL-33 is a member of the IL-1 cytokine family and increased expression is associated with IBD. Emerging evidence suggests its potential role in liver and cutaneous fibrosis, as well as myofibroblast-associated colonic ulcerations . Aim: The aim of this study was to evaluate the role of IL-33 as a potential mediator of profibrotic events leading to intestinal fibrosis and possible stricture formation. Methods: A detailed histologic time course study, with collagen-specific Masson trichrome staining and IHC for ST2 (IL-33 receptor), was performed on SAMP and control AKR (parental strain) mice. qRT-PCR was done on full-thickness ilea for the profibrogenic genes, collagen (coll)-1, coll-3, connective tissue growth factor (CTGF) and insulin-like growth factor 1 (IGF-1). Exogenous IL-33 (33 μg/kg, i.p.) or vehicle was administered daily for 7d to SAMP and AKR mice (N=6/exp group), and ileal tissues evaluated as above. Finally, microarray analysis was performed on full-thickness ilea from SAMP and AKR mice, and IL-33 stimulated subepithelial myofibroblasts (SEMFs). Results: SAMP mice displayed ileal skip lesions with randomly distributed strictures, preceded by typical pre-stricture dilations of the ileum. Ileal wall was visibly thickened with hypertrophy of the serosa, muscularis mucosa, muscularis propria, within which intense collagen deposition was observed, and inflammatory infiltrates in segments showing strictures. Interestingly, intense ST2 staining was present within the inflamed lamina propria of SAMP, notably localized to SEMFs. Fibrosis was first observed at 20 wks, and reached its peak by 50 wks of age. mRNA expression of coll-1 (4.74±0.69-fold; P=0.001), coll-3 (4.92±1.05-fold; P=0.01), IGF1 (12.9±3.45; P=0.006), and CTGF (3.29±0.69; P=0.004) was dramatically elevated in SAMP vs. AKR ilea. IL-33 treatment of AKR mice induced a marked increase in muscle fiber/myofibroblast cellularity and hypertrophy of the muscularis propria (4.13±0.74-fold; P<0.0001), and mRNA expression of coll-1 (5.16±0.89-fold; P=0.0009), coll-3 (1.97±0.14-fold; P=0.01), IGF-1 (9.32±2.27-fold; P=0.004), and CTGF (1.43±0.31-fold; P=0.006) vs. vehicle controls. Microarray data from SAMP ilea and IL-33-treated SEMFs confirmed these trends, displaying a global increase in profibrogenic gene expression. Conclusion: These data suggest an important role for IL-33 in intestinal fibrosis, and may represent a potential target for the treatment of IBD-associated fibrosis and stricture formation.

Muster und Prozesse in einer Microcebus-Hybridzone in Südostmadagaskar

Im Rahmen dieser Doktorarbeit wurde in zwei Schwerpunktanalysen mit eine Teil- und Gesamtdatensatz die Untersuchung der Hybridisierung zwischen den beiden Microcebus-Arten M. murinus und M. griseorufus im Ökoton Südostmadagaskars umfangreich und vertieft untersucht. Für die genetischen Analysen wurden die maternal vererbte mitochondriale Hypervariable Region I (HVR 1) und neun nukleäre biparental vererbte Mikrosatellitenmarker eingesetzt. Als weiterer Datensatz wurden morphometrische Daten verwendet. Für die erste Schwerpunktanalyse wurde ein bereits vorhandener Teildatensatz (Hapke 2005 & Gligor 2006) mit Daten von insgesamt 162 Individuen aus neun Populationen der Dornbuschzone, der Übergangswaldzone und des Küstenwaldgebietes eingesetzt. In der zweiten Schwerpunktanalyse wurde eine umfangreiche Untersuchung der Microcebus griseoruus-M. murinus- Hybridzone vorgenommen. Für diese detaillierte Charakterisierung der Hybridzone wurde eine ausgedehnte und fein auflösende Probennahme in einem als Kernzone definierten Bereich, der die gesamte Übergangswaldzone und die dazu benachbarten Dornbuschgebiete umfasste, durchgeführt. Die morphometrischen und genetischen Daten der neu beprobten Individuen dieser Kernzone wurden mit den Daten des Teildatensatzes und weiteren Daten aus Küstenwaldpopulationen (Hapke 2005) zu einem Gesamtdatensatz zusammengefasst. Die Integration des Teildatensatzes in den Gesamtdatensatz erforderte umfassende und zeitintensive Labor- und Analysearbeiten, die im Rahmen dieser Doktorarbeit durchgeführt wurden. Der Gesamtdatensatz umfasste insgesamt 569 Individuen der Gattung Microcebus aus 29 Untersuchungsstandorten. Die mit beiden Datensätzen durchgeführte Analyse morphometrischer Daten zeigte deutlich, dass die Mehrzahl der Individuen aus der Übergangswaldzone einen intermediären Morphotyp aufweist. Durch die mit den Daten des Teildatensatzes durchgeführten Bayes’schen Clusteranalysen und Assignment-Tests, das vornehmlich in den Populationen der Übergangszone beobachtete signifikante Kopplungsungleichgewicht und Heterozygotendefizit, die festgestellte Verteilung der mitochondrialen Haplotypen und das kontrastierende Muster zwischen nukleären Mikrosatellitengenotypen und mitochondrialen Haplotypen in den Übergangswaldpopulationen konnte erstmals das Vorkommen einer Hybridzone zwischen Microcebus-Arten wissenschaftlich fundiert festgestellt werden. Die Ergebnisse dieser Schwerpunktanalyse wurden in der Fachzeitschrift Molecular Ecology publiziert (Gligor et al. 2009). Die in der ersten Schwerpunktanalyse festgestellte Hybridzone konnte durch die zweite Schwerpunktanalyse mit den genetischen und morphometrischen Daten des Gesamtdatensatzes nicht nur bestätigt werden, sondern auch auf die gesamte Übergangswaldzone erweitert werden. Ferner wurden starke Hinweise auf eine Hybridisierung beider Microcebus-Arten an einigen Dornbuschstandorten der Kernzone gefunden. Durch die große Datenmenge des Gesamtdatensatzes, vor allem aus der Kernzone des Untersuchungsgebietes, war es möglich eine fundierte Charakterisierung der Microcebus griseoruus-M. murinus- Hybridzone durchzuführen. Die Übereinstimmung der Hybridzone mit dem beobachteten Vegetationsmosaik zusammen mit den Ergebnissen der PCA, der PCoA und der Bayes’schen Clusteranalyse sprechen für das Modell der „Mosaik Hybridzone“, während die Einzelbetrachtung der mosaikartig verteilten intermediären Übergangswälder eine hohe Abundanz der Hybride aufzeigte und somit eher das „Bounded Hybrid Superiority model“ unterstützt. Der gewählte geographische Beprobungsmaßstab könnte somit einen Einfluss auf die beobachtete Struktur einer Hybridzone haben. Eines der markantesten Muster in der Hybridzone ist das stark kontrastierende cyto-nukleäre Muster. Der seit ca. 3000 Jahren fortschreitende Klimawandel in Südmadagaskar und die damit verbundene Expansion des Verbreitungsgebietes der Art Microcebus griseorufus nach Osten, das in dieser Arbeit festgestellte „male-biased dispersal“ bei M. griseorufus und der Einfluss exogener Selektion sprechen stark für eine massive asymmetrische nukleäre Genintrogression von M. griseorufus-Allelen in M. murinus-Populationen, verbunden mit einer potentiellen Verdrängung der Art M. murinus aus der Übergangswaldzone. In den jeweiligen Kerngebieten Dornbusch und Küstenwald bleibt jedoch die Diskretheit beider Arten gewahrt.

Meta-analyses qualify metzincins and related genes as acute rejection markers in renal transplant patients

Definition of acute renal allograft rejection (AR) markers remains clinically relevant. Features of T-cell-mediated AR are tubulointerstitial and vascular inflammation associated with excessive extracellular matrix (ECM) remodeling, regulated by metzincins, including matrix metalloproteases (MMP). Our study focused on expression of metzincins (METS), and metzincins and related genes (MARGS) in renal allograft biopsies using four independent microarray data sets. Our own cases included normal histology (N, n = 20), borderline changes (BL, n = 4), AR (n = 10) and AR + IF/TA (n = 7). MARGS enriched in all data sets were further examined on mRNA and/or protein level in additional patients. METS and MARGS differentiated AR from BL, AR + IF/TA and N in a principal component analysis. Their expression changes correlated to Banff t- and i-scores. Two AR classifiers, based on METS (including MMP7, TIMP1), or on MARGS were established in our own and validated in the three additional data sets. Thirteen MARGS were significantly enriched in AR patients of all data sets comprising MMP7, -9, TIMP1, -2, thrombospondin2 (THBS2) and fibrillin1. RT-PCR using microdissected glomeruli/tubuli confirmed MMP7, -9 and THBS2 microarray results; immunohistochemistry showed augmentation of MMP2, -9 and TIMP1 in AR. TIMP1 and THBS2 were enriched in AR patient serum. Therefore, differentially expressed METS and MARGS especially TIMP1, MMP7/-9 represent potential molecular AR markers.

A subset of metzincins and related genes constitutes a marker of human solid organ fibrosis

Metzincins and functionally related genes play important roles in extracellular matrix remodeling both in healthy and fibrotic conditions. We recently presented a transcriptomic classifier consisting of 19 metzincins and related genes (MARGS) discriminating biopsies from renal transplant patients with or without interstitial fibrosis/tubular atrophy (IF/TA) by virtue of gene expression measurement (Roedder et al., Am J Transplant 9:517-526, 2009). Here we demonstrate that the same algorithm has diagnostic value in non-transplant solid organ fibrosis. We used publically available microarray datasets of 325 human heart, liver, lung, kidney cortex, and pancreas microarray samples (265 with fibrosis, 60 healthy controls). Expression of nine commonly differentially expressed genes was confirmed by TaqMan low-density arrays (Applied Biosystems, USA) in 50 independent archival tissue specimens with matched histological diagnoses to microarray patients. In separate and in combined, integrated microarray data analyses of five datasets with 325 samples, the previously published MARGS classifier for renal post-transplant IF/TA had a mean AUC of 87% and 82%, respectively. These data demonstrate that the MARGS gene panel classifier not only discriminates IF/TA from normal renal transplant tissue, but also classifies solid organ fibrotic conditions of human pancreas, liver, heart, kidney, and lung tissue samples with high specificity and accuracy, suggesting that the MARGS classifier is a cross-platform, cross-organ classifier of fibrotic conditions of different etiologies when compared to normal tissue.

Bone morphogenetic protein-7 is a MYC target with prosurvival functions in childhood medulloblastoma

Medulloblastoma (MB) is the most common malignant brain tumor in children. It is known that overexpression and/or amplification of the MYC oncogene is associated with poor clinical outcome, but the molecular mechanisms and the MYC downstream effectors in MB remain still elusive. Besides contributing to elucidate how progression of MB takes place, most importantly, the identification of novel MYC-target genes will suggest novel candidates for targeted therapy in MB. A group of 209 MYC-responsive genes was obtained from a complementary DNA microarray analysis of a MB-derived cell line, following MYC overexpression and silencing. Among the MYC-responsive genes, we identified the members of the bone morphogenetic protein (BMP) signaling pathway, which have a crucial role during the development of the cerebellum. In particular, the gene BMP7 was identified as a direct target of MYC. A positive correlation between MYC and BMP7 expression was documented by analyzing two distinct sets of primary MB samples. Functional studies in vitro using a small-molecule inhibitor of the BMP/SMAD signaling pathway reproduced the effect of the small interfering RNA-mediated silencing of BMP7. Both approaches led to a block of proliferation in a panel of MB cells and to inhibition of SMAD phosphorylation. Altogether, our findings indicate that high MYC levels drive BMP7 overexpression, promoting cell survival in MB cells. This observation suggests the potential relevance of targeting the BMP/SMAD pathway as a novel therapeutic approach for the treatment of childhood MB.

Chitinase expression in parotid glands of non-obese diabetic mice

OBJECTIVE: This investigation was a basal study that used a mouse model of xerostomia to identify protein biomarkers of xerostomia in saliva. We identified genes expressed differently in parotid glands from non-obese diabetic mice with diabetes and those from control mice; subsequently, we investigated expression of the proteins encoded by these genes in parotid glands and saliva. MATERIALS AND METHODS: DNA microarray and real-time PCR analyses were performed to detect differences between NOD/ShiJcl and C57BL/6JJcl (control) female mice in gene expression from parotid glands or parotid acinar cells. Subsequently, protein expression was assessed using immunoblotting and immunohistochemistry. Similarly, enzyme activity in saliva was assessed using zymography. RESULTS: Based on gene expression analyses, Chia expression was higher in diabetic mice than non-diabetic mice and control mice; similarly, expression of chitinase, the protein encoded by Chia, was higher in diabetic mice. Saliva from NOD/ShiJcl mice had more chitinase than saliva from control mice. CONCLUSIONS: Chitinase was highly expressed in parotid acinar cells from diabetic mice compared with non-diabetic and control mice. Increased chitinase expression and enzyme activity may characterize the autoimmune diabetes in mice; however, further investigation is required to assess its use as a biomarker of xerostomia in humans.

An integrated nano-scale approach to profile miRNAs in limited clinical samples

Profiling miRNA expression in cells that directly contribute to human disease pathogenesis is likely to aid the discovery of novel drug targets and biomarkers. However, tissue heterogeneity and the limited amount of human diseased tissue available for research purposes present fundamental difficulties that often constrain the scope and potential of such studies. We established a flow cytometry-based method for isolating pure populations of pathogenic T cells from bronchial biopsy samples of asthma patients, and optimized a high-throughput nano-scale qRT-PCR method capable of accurately measuring 96 miRNAs in as little as 100 cells. Comparison of circulating and airway T cells from healthy and asthmatic subjects revealed asthma-associated and tissue-specific miRNA expression patterns. These results establish the feasibility and utility of investigating miRNA expression in small populations of cells involved in asthma pathogenesis, and set a precedent for application of our nano-scale approach in other human diseases. The microarray data from this study (Figure 7) has been submitted to the NCBI Gene Expression Omnibus (GEO; http://ncbi.nlm.nih.gov/geo) under accession no. GSE31030.