Strategies to minimize false positives and interpret novel microdeletions based on maternal copy-number variants in 87,000 noninvasive prenatal screens.

BACKGROUND: Noninvasive prenatal screening (NIPS) of common aneuploidies using cell-free DNA from maternal plasma is part of routine prenatal care and is widely used in both high-risk and low-risk patient populations. High specificity is needed for clinically acceptable positive predictive values. Maternal copy-number variants (mCNVs) have been reported as a source of false-positive aneuploidy results that compromises specificity. METHODS: We surveyed the mCNV landscape in 87,255 patients undergoing NIPS. We evaluated both previously reported and novel algorithmic strategies for mitigating the effects of mCNVs on the screen's specificity. Further, we analyzed the frequency, length, and positional distribution of CNVs in our large dataset to investigate the curation of novel fetal microdeletions, which can be identified by NIPS but are challenging to interpret clinically. RESULTS: mCNVs are common, with 65% of expecting mothers harboring an autosomal CNV spanning more than 200 kb, underscoring the need for robust NIPS analysis strategies. By analyzing empirical and simulated data, we found that general, outlier-robust strategies reduce the rate of mCNV-caused false positives but not as appreciably as algorithms specifically designed to account for mCNVs. We demonstrate that large-scale tabulation of CNVs identified via routine NIPS could be clinically useful: together with the gene density of a putative microdeletion region, we show that the region's relative tolerance to duplications versus deletions may aid the interpretation of microdeletion pathogenicity. CONCLUSIONS: Our study thoroughly investigates a common source of NIPS false positives and demonstrates how to bypass its corrupting effects. Our findings offer insight into the interpretation of NIPS results and inform the design of NIPS algorithms suitable for use in screening in the general obstetric population.

High temporal resolution of glucosyltransferase dependent and independent effects of Clostridium difficile toxins across multiple cell types.

BACKGROUND: Clostridium difficile toxins A and B (TcdA and TcdB), considered to be essential for C. difficile infection, affect the morphology of several cell types with different potencies and timing. However, morphological changes over various time scales are poorly characterized. The toxins' glucosyltransferase domains are critical to their deleterious effects, and cell responses to glucosyltransferase-independent activities are incompletely understood. By tracking morphological changes of multiple cell types to C. difficile toxins with high temporal resolution, cellular responses to TcdA, TcdB, and a glucosyltransferase-deficient TcdB (gdTcdB) are elucidated. RESULTS: Human umbilical vein endothelial cells, J774 macrophage-like cells, and four epithelial cell lines (HCT8, T84, CHO, and immortalized mouse cecal epithelial cells) were treated with TcdA, TcdB, gdTcdB. Impedance across cell cultures was measured to track changes in cell morphology. Metrics from impedance data, developed to quantify rapid and long-lasting responses, produced standard curves with wide dynamic ranges that defined cell line sensitivities. Except for T84 cells, all cell lines were most sensitive to TcdB. J774 macrophages stretched and increased in size in response to TcdA and TcdB but not gdTcdB. High concentrations of TcdB and gdTcdB (>10 ng/ml) greatly reduced macrophage viability. In HCT8 cells, gdTcdB did not induce a rapid cytopathic effect, yet it delayed TcdA and TcdB's rapid effects. gdTcdB did not clearly delay TcdA or TcdB's toxin-induced effects on macrophages. CONCLUSIONS: Epithelial and endothelial cells have similar responses to toxins yet differ in timing and degree. Relative potencies of TcdA and TcdB in mouse epithelial cells in vitro do not correlate with potencies in vivo. TcdB requires glucosyltransferase activity to cause macrophages to spread, but cell death from high TcdB concentrations is glucosyltransferase-independent. Competition experiments with gdTcdB in epithelial cells confirm common TcdA and TcdB mechanisms, yet different responses of macrophages to TcdA and TcdB suggest different, additional mechanisms or targets in these cells. This first-time, precise quantification of the response of multiple cell lines to TcdA and TcdB provides a comparative framework for delineating the roles of different cell types and toxin-host interactions.

MicroRNAs induced in melanoma treated with combination targeted therapy of Temsirolimus and Bevacizumab.

BACKGROUND: Targeted therapies directed at commonly overexpressed pathways in melanoma have clinical activity in numerous trials. Little is known about how these therapies influence microRNA (miRNA) expression, particularly with combination regimens. Knowledge of miRNAs altered with treatment may contribute to understanding mechanisms of therapeutic effects, as well as mechanisms of tumor escape from therapy. We analyzed miRNA expression in metastatic melanoma tissue samples treated with a novel combination regimen of Temsirolimus and Bevacizumab. Given the preliminary clinical activity observed with this combination regimen, we hypothesized that we would see significant changes in miRNA expression with combination treatment. METHODS: Using microarray analysis we analyzed miRNA expression levels in melanoma samples from a Cancer Therapy Evaluation Program-sponsored phase II trial of combination Temsirolimus and Bevacizumab in advanced melanoma, which elicited clinical benefit in a subset of patients. Pre-treatment and post-treatment miRNA levels were compared using paired t-tests between sample groups (patients), using a p-value < 0.01 for significance. RESULTS: microRNA expression remained unchanged with Temsirolimus alone; however, expression of 15 microRNAs was significantly upregulated (1.4 to 2.5-fold) with combination treatment, compared to pre-treatment levels. Interestingly, twelve of these fifteen miRNAs possess tumor suppressor capabilities. We identified 15 putative oncogenes as potential targets of the 12 tumor suppressor miRNAs, based on published experimental evidence. For 15 of 25 miRNA-target mRNA pairings, changes in gene expression from pre-treatment to post-combination treatment samples were inversely correlated with changes in miRNA expression, supporting a functional effect of those miRNA changes. Clustering analyses based on selected miRNAs suggest preliminary signatures characteristic of clinical response to combination treatment and of tumor BRAF mutational status. CONCLUSIONS: To our knowledge, this is the first study analyzing miRNA expression in pre-treatment and post-treatment human metastatic melanoma tissue samples. This preliminary investigation suggests miRNAs that may be involved in the mechanism of action of combination Temsirolimus and Bevacizumab in metastatic melanoma, possibly through inhibition of oncogenic pathways, and provides the preliminary basis for further functional studies of these miRNAs.

In vivo physiological and transcriptional profiling reveals host responses to Clostridium difficile toxin A and toxin B.

Toxin A (TcdA) and toxin B (TcdB) of Clostridium difficile cause gross pathological changes (e.g., inflammation, secretion, and diarrhea) in the infected host, yet the molecular and cellular pathways leading to observed host responses are poorly understood. To address this gap, we evaluated the effects of single doses of TcdA and/or TcdB injected into the ceca of mice, and several endpoints were analyzed, including tissue pathology, neutrophil infiltration, epithelial-layer gene expression, chemokine levels, and blood cell counts, 2, 6, and 16 h after injection. In addition to confirming TcdA's gross pathological effects, we found that both TcdA and TcdB resulted in neutrophil infiltration. Bioinformatics analyses identified altered expression of genes associated with the metabolism of lipids, fatty acids, and detoxification; small GTPase activity; and immune function and inflammation. Further analysis revealed transient expression of several chemokines (e.g., Cxcl1 and Cxcl2). Antibody neutralization of CXCL1 and CXCL2 did not affect TcdA-induced local pathology or neutrophil infiltration, but it did decrease the peripheral blood neutrophil count. Additionally, low serum levels of CXCL1 and CXCL2 corresponded with greater survival. Although TcdA induced more pronounced transcriptional changes than TcdB and the upregulated chemokine expression was unique to TcdA, the overall transcriptional responses to TcdA and TcdB were strongly correlated, supporting differences primarily in timing and potency rather than differences in the type of intracellular host response. In addition, the transcriptional data revealed novel toxin effects (e.g., altered expression of GTPase-associated and metabolic genes) underlying observed physiological responses to C. difficile toxins.

A metabolic network approach for the identification and prioritization of antimicrobial drug targets.

For many infectious diseases, novel treatment options are needed in order to address problems with cost, toxicity and resistance to current drugs. Systems biology tools can be used to gain valuable insight into pathogenic processes and aid in expediting drug discovery. In the past decade, constraint-based modeling of genome-scale metabolic networks has become widely used. Focusing on pathogen metabolic networks, we review in silico strategies used to identify effective drug targets and highlight recent successes as well as limitations associated with such computational analyses. We further discuss how accounting for the host environment and even targeting the host may offer new therapeutic options. These systems-level approaches are beginning to provide novel avenues for drug targeting against infectious agents.

Systems analysis of the transcriptional response of human ileocecal epithelial cells to Clostridium difficile toxins and effects on cell cycle control.

BACKGROUND: Toxins A and B (TcdA and TcdB) are Clostridium difficile's principal virulence factors, yet the pathways by which they lead to inflammation and severe diarrhea remain unclear. Also, the relative role of either toxin during infection and the differences in their effects across cell lines is still poorly understood. To better understand their effects in a susceptible cell line, we analyzed the transciptome-wide gene expression response of human ileocecal epithelial cells (HCT-8) after 2, 6, and 24 hr of toxin exposure. RESULTS: We show that toxins elicit very similar changes in the gene expression of HCT-8 cells, with the TcdB response occurring sooner. The high similarity suggests differences between toxins are due to events beyond transcription of a single cell-type and that their relative potencies during infection may depend on differential effects across cell types within the intestine. We next performed an enrichment analysis to determine biological functions associated with changes in transcription. Differentially expressed genes were associated with response to external stimuli and apoptotic mechanisms and, at 24 hr, were predominately associated with cell-cycle control and DNA replication. To validate our systems approach, we subsequently verified a novel G1/S and known G2/M cell-cycle block and increased apoptosis as predicted from our enrichment analysis. CONCLUSIONS: This study shows a successful example of a workflow deriving novel biological insight from transcriptome-wide gene expression. Importantly, we do not find any significant difference between TcdA and TcdB besides potency or kinetics. The role of each toxin in the inhibition of cell growth and proliferation, an important function of cells in the intestinal epithelium, is characterized.

Structural and dynamic determinants of protein-peptide recognition.

Protein-peptide interactions play important roles in many cellular processes, including signal transduction, trafficking, and immune recognition. Protein conformational changes upon binding, an ill-defined peptide binding surface, and the large number of peptide degrees of freedom make the prediction of protein-peptide interactions particularly challenging. To address these challenges, we perform rapid molecular dynamics simulations in order to examine the energetic and dynamic aspects of protein-peptide binding. We find that, in most cases, we recapitulate the native binding sites and native-like poses of protein-peptide complexes. Inclusion of electrostatic interactions in simulations significantly improves the prediction accuracy. Our results also highlight the importance of protein conformational flexibility, especially side-chain movement, which allows the peptide to optimize its conformation. Our findings not only demonstrate the importance of sufficient sampling of the protein and peptide conformations, but also reveal the possible effects of electrostatics and conformational flexibility on peptide recognition.