Two genes on A/J chromosome 18 are associated with susceptibility to Staphylococcus aureus infection by combined microarray and QTL analyses.

Although it has recently been shown that A/J mice are highly susceptible to Staphylococcus aureus sepsis as compared to C57BL/6J, the specific genes responsible for this differential phenotype are unknown. Using chromosome substitution strains (CSS), we found that loci on chromosomes 8, 11, and 18 influence susceptibility to S. aureus sepsis in A/J mice. We then used two candidate gene selection strategies to identify genes on these three chromosomes associated with S. aureus susceptibility, and targeted genes identified by both gene selection strategies. First, we used whole genome transcription profiling to identify 191 (56 on chr. 8, 100 on chr. 11, and 35 on chr. 18) genes on our three chromosomes of interest that are differentially expressed between S. aureus-infected A/J and C57BL/6J. Second, we identified two significant quantitative trait loci (QTL) for survival post-infection on chr. 18 using N(2) backcross mice (F(1) [C18A]xC57BL/6J). Ten genes on chr. 18 (March3, Cep120, Chmp1b, Dcp2, Dtwd2, Isoc1, Lman1, Spire1, Tnfaip8, and Seh1l) mapped to the two significant QTL regions and were also identified by the expression array selection strategy. Using real-time PCR, 6 of these 10 genes (Chmp1b, Dtwd2, Isoc1, Lman1, Tnfaip8, and Seh1l) showed significantly different expression levels between S. aureus-infected A/J and C57BL/6J. For two (Tnfaip8 and Seh1l) of these 6 genes, siRNA-mediated knockdown of gene expression in S. aureus-challenged RAW264.7 macrophages induced significant changes in the cytokine response (IL-1 beta and GM-CSF) compared to negative controls. These cytokine response changes were consistent with those seen in S. aureus-challenged peritoneal macrophages from CSS 18 mice (which contain A/J chromosome 18 but are otherwise C57BL/6J), but not C57BL/6J mice. These findings suggest that two genes, Tnfaip8 and Seh1l, may contribute to susceptibility to S. aureus in A/J mice, and represent promising candidates for human genetic susceptibility studies.

Alterations in cardiac adrenergic signaling and calcium cycling differentially affect the progression of cardiomyopathy.

The medical treatment of chronic heart failure has undergone a dramatic transition in the past decade. Short-term approaches for altering hemodynamics have given way to long-term, reparative strategies, including beta-adrenergic receptor (betaAR) blockade. This was once viewed as counterintuitive, because acute administration causes myocardial depression. Cardiac myocytes from failing hearts show changes in betaAR signaling and excitation-contraction coupling that can impair cardiac contractility, but the role of these abnormalities in the progression of heart failure is controversial. We therefore tested the impact of different manipulations that increase contractility on the progression of cardiac dysfunction in a mouse model of hypertrophic cardiomyopathy. High-level overexpression of the beta(2)AR caused rapidly progressive cardiac failure in this model. In contrast, phospholamban ablation prevented systolic dysfunction and exercise intolerance, but not hypertrophy, in hypertrophic cardiomyopathy mice. Cardiac expression of a peptide inhibitor of the betaAR kinase 1 not only prevented systolic dysfunction and exercise intolerance but also decreased cardiac remodeling and hypertrophic gene expression. These three manipulations of cardiac contractility had distinct effects on disease progression, suggesting that selective modulation of particular aspects of betaAR signaling or excitation-contraction coupling can provide therapeutic benefit.

Association of a peripheral blood metabolic profile with coronary artery disease and risk of subsequent cardiovascular events.

BACKGROUND: Molecular tools may provide insight into cardiovascular risk. We assessed whether metabolites discriminate coronary artery disease (CAD) and predict risk of cardiovascular events. METHODS AND RESULTS: We performed mass-spectrometry-based profiling of 69 metabolites in subjects from the CATHGEN biorepository. To evaluate discriminative capabilities of metabolites for CAD, 2 groups were profiled: 174 CAD cases and 174 sex/race-matched controls ("initial"), and 140 CAD cases and 140 controls ("replication"). To evaluate the capability of metabolites to predict cardiovascular events, cases were combined ("event" group); of these, 74 experienced death/myocardial infarction during follow-up. A third independent group was profiled ("event-replication" group; n=63 cases with cardiovascular events, 66 controls). Analysis included principal-components analysis, linear regression, and Cox proportional hazards. Two principal components analysis-derived factors were associated with CAD: 1 comprising branched-chain amino acid metabolites (factor 4, initial P=0.002, replication P=0.01), and 1 comprising urea cycle metabolites (factor 9, initial P=0.0004, replication P=0.01). In multivariable regression, these factors were independently associated with CAD in initial (factor 4, odds ratio [OR], 1.36; 95% CI, 1.06 to 1.74; P=0.02; factor 9, OR, 0.67; 95% CI, 0.52 to 0.87; P=0.003) and replication (factor 4, OR, 1.43; 95% CI, 1.07 to 1.91; P=0.02; factor 9, OR, 0.66; 95% CI, 0.48 to 0.91; P=0.01) groups. A factor composed of dicarboxylacylcarnitines predicted death/myocardial infarction (event group hazard ratio 2.17; 95% CI, 1.23 to 3.84; P=0.007) and was associated with cardiovascular events in the event-replication group (OR, 1.52; 95% CI, 1.08 to 2.14; P=0.01). CONCLUSIONS: Metabolite profiles are associated with CAD and subsequent cardiovascular events.

Portable, Fiber-Based, Diffuse Reflection Spectroscopy (DRS) Systems for Estimating Tissue Optical Properties.

Steady-state diffuse reflection spectroscopy is a well-studied optical technique that can provide a noninvasive and quantitative method for characterizing the absorption and scattering properties of biological tissues. Here, we compare three fiber-based diffuse reflection spectroscopy systems that were assembled to create a light-weight, portable, and robust optical spectrometer that could be easily translated for repeated and reliable use in mobile settings. The three systems were built using a broadband light source and a compact, commercially available spectrograph. We tested two different light sources and two spectrographs (manufactured by two different vendors). The assembled systems were characterized by their signal-to-noise ratios, the source-intensity drifts, and detector linearity. We quantified the performance of these instruments in extracting optical properties from diffuse reflectance spectra in tissue-mimicking liquid phantoms with well-controlled optical absorption and scattering coefficients. We show that all assembled systems were able to extract the optical absorption and scattering properties with errors less than 10%, while providing greater than ten-fold decrease in footprint and cost (relative to a previously well-characterized and widely used commercial system). Finally, we demonstrate the use of these small systems to measure optical biomarkers in vivo in a small-animal model cancer therapy study. We show that optical measurements from the simple portable system provide estimates of tumor oxygen saturation similar to those detected using the commercial system in murine tumor models of head and neck cancer.

WNT3 is a biomarker capable of predicting the definitive endoderm differentiation potential of hESCs.

Generation of functional cells from human pluripotent stem cells (PSCs) through in vitro differentiation is a promising approach for drug screening and cell therapy. However, the observed large and unavoidable variation in the differentiation potential of different human embryonic stem cell (hESC)/induced PSC (iPSC) lines makes the selection of an appropriate cell line for the differentiation of a particular cell lineage difficult. Here, we report identification of WNT3 as a biomarker capable of predicting definitive endoderm (DE) differentiation potential of hESCs. We show that the mRNA level of WNT3 in hESCs correlates with their DE differentiation efficiency. In addition, manipulations of hESCs through WNT3 knockdown or overexpression can respectively inhibit or promote DE differentiation in a WNT3 level-dependent manner. Finally, analysis of several hESC lines based on their WNT3 expression levels allowed accurate prediction of their DE differentiation potential. Collectively, our study supports the notion that WNT3 can serve as a biomarker for predicting DE differentiation potential of hESCs.

Molecular characterization of chordoma xenografts generated from a novel primary chordoma cell source and two chordoma cell lines.

OBJECT: Chordoma cells can generate solid-like tumors in xenograft models that express some molecular characteristics of the parent tumor, including positivity for brachyury and cytokeratins. However, there is a dearth of molecular markers that relate to chordoma tumor growth, as well as the cell lines needed to advance treatment. The objective in this study was to isolate a novel primary chordoma cell source and analyze the characteristics of tumor growth in a mouse xenograft model for comparison with the established U-CH1 and U-CH2b cell lines. METHODS: Primary cells from a sacral chordoma, called "DVC-4," were cultured alongside U-CH1 and U-CH2b cells for more than 20 passages and characterized for expression of CD24 and brachyury. While brachyury is believed essential for driving tumor formation, CD24 is associated with healthy nucleus pulposus cells. Each cell type was subcutaneously implanted in NOD/SCID/IL2Rγ(null) mice. The percentage of solid tumors formed, time to maximum tumor size, and immunostaining scores for CD24 and brachyury (intensity scores of 0-3, heterogeneity scores of 0-1) were reported and evaluated to test differences across groups. RESULTS: The DVC-4 cells retained chordoma-like morphology in culture and exhibited CD24 and brachyury expression profiles in vitro that were similar to those for U-CH1 and U-CH2b. Both U-CH1 and DVC-4 cells grew tumors at rates that were faster than those for U-CH2b cells. Gross tumor developed at nearly every site (95%) injected with U-CH1 and at most sites (75%) injected with DVC-4. In contrast, U-CH2b cells produced grossly visible tumors in less than 50% of injected sites. Brachyury staining was similar among tumors derived from all 3 cell types and was intensely positive (scores of 2-3) in a majority of tissue sections. In contrast, differences in the pattern and intensity of staining for CD24 were noted among the 3 types of cell-derived tumors (p < 0.05, chi-square test), with evidence of intense and uniform staining in a majority of U-CH1 tumor sections (score of 3) and more than half of the DVC-4 tumor sections (scores of 2-3). In contrast, a majority of sections from U-CH2b cells stained modestly for CD24 (scores of 1-2) with a predominantly heterogeneous staining pattern. CONCLUSIONS: This is the first report on xenografts generated from U-CH2b cells in which a low tumorigenicity was discovered despite evidence of chordoma-like characteristics in vitro. For tumors derived from a primary chordoma cell and U-CH1 cell line, similarly intense staining for CD24 was observed, which may correspond to their similar potential to grow tumors. In contrast, U-CH2b tumors stained less intensely for CD24. These results emphasize that many markers, including CD24, may be useful in distinguishing among chordoma cell types and their tumorigenicity in vivo.

An active learning approach for rapid characterization of endothelial cells in human tumors.

Currently, no available pathological or molecular measures of tumor angiogenesis predict response to antiangiogenic therapies used in clinical practice. Recognizing that tumor endothelial cells (EC) and EC activation and survival signaling are the direct targets of these therapies, we sought to develop an automated platform for quantifying activity of critical signaling pathways and other biological events in EC of patient tumors by histopathology. Computer image analysis of EC in highly heterogeneous human tumors by a statistical classifier trained using examples selected by human experts performed poorly due to subjectivity and selection bias. We hypothesized that the analysis can be optimized by a more active process to aid experts in identifying informative training examples. To test this hypothesis, we incorporated a novel active learning (AL) algorithm into FARSIGHT image analysis software that aids the expert by seeking out informative examples for the operator to label. The resulting FARSIGHT-AL system identified EC with specificity and sensitivity consistently greater than 0.9 and outperformed traditional supervised classification algorithms. The system modeled individual operator preferences and generated reproducible results. Using the results of EC classification, we also quantified proliferation (Ki67) and activity in important signal transduction pathways (MAP kinase, STAT3) in immunostained human clear cell renal cell carcinoma and other tumors. FARSIGHT-AL enables characterization of EC in conventionally preserved human tumors in a more automated process suitable for testing and validating in clinical trials. The results of our study support a unique opportunity for quantifying angiogenesis in a manner that can now be tested for its ability to identify novel predictive and response biomarkers.

Temporal dynamics of host molecular responses differentiate symptomatic and asymptomatic influenza a infection.

Exposure to influenza viruses is necessary, but not sufficient, for healthy human hosts to develop symptomatic illness. The host response is an important determinant of disease progression. In order to delineate host molecular responses that differentiate symptomatic and asymptomatic Influenza A infection, we inoculated 17 healthy adults with live influenza (H3N2/Wisconsin) and examined changes in host peripheral blood gene expression at 16 timepoints over 132 hours. Here we present distinct transcriptional dynamics of host responses unique to asymptomatic and symptomatic infections. We show that symptomatic hosts invoke, simultaneously, multiple pattern recognition receptors-mediated antiviral and inflammatory responses that may relate to virus-induced oxidative stress. In contrast, asymptomatic subjects tightly regulate these responses and exhibit elevated expression of genes that function in antioxidant responses and cell-mediated responses. We reveal an ab initio molecular signature that strongly correlates to symptomatic clinical disease and biomarkers whose expression patterns best discriminate early from late phases of infection. Our results establish a temporal pattern of host molecular responses that differentiates symptomatic from asymptomatic infections and reveals an asymptomatic host-unique non-passive response signature, suggesting novel putative molecular targets for both prognostic assessment and ameliorative therapeutic intervention in seasonal and pandemic influenza.