PERT: A Method for Expression Deconvolution of Human Blood Samples from Varied Microenvironmental and Developmental Conditions

The cellular composition of heterogeneous samples can be predicted using an expression deconvolution algorithm to decompose their gene expression profiles based on pre-defined, reference gene expression profiles of the constituent populations in these samples. However, the expression profiles of the actual constituent populations are often perturbed from those of the reference profiles due to gene expression changes in cells associated with microenvironmental or developmental effects. Existing deconvolution algorithms do not account for these changes and give incorrect results when benchmarked against those measured by well-established flow cytometry, even after batch correction was applied. We introduce PERT, a new probabilistic expression deconvolution method that detects and accounts for a shared, multiplicative perturbation in the reference profiles when performing expression deconvolution. We applied PERT and three other state-of-the-art expression deconvolution methods to predict cell frequencies within heterogeneous human blood samples that were collected under several conditions (uncultured mono-nucleated and lineage-depleted cells, and culture-derived lineage-depleted cells). Only PERT's predicted proportions of the constituent populations matched those assigned by flow cytometry. Genes associated with cell cycle processes were highly enriched among those with the largest predicted expression changes between the cultured and uncultured conditions. We anticipate that PERT will be widely applicable to expression deconvolution strategies that use profiles from reference populations that vary from the corresponding constituent populations in cellular state but not cellular phenotypic identity

Differential Dynamics of Transposable Elements during Long-Term Diploidization of Nicotiana Section Repandae (Solanaceae) Allopolyploid Genomes

PubMed ID: 23185607This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Directed -in vitro- evolution of Precambrian and extant Rubiscos

Rubisco is an ancient, catalytically conserved yet slow enzyme, which plays a central role in the biosphere’s carbon cycle. The design of Rubiscos to increase agricultural productivity has hitherto relied on the use of in vivo selection systems, precluding the exploration of biochemical traits that are not wired to cell survival. We present a directed -in vitro- evolution platform that extracts the enzyme from its biological context to provide a new avenue for Rubisco engineering. Precambrian and extant form II Rubiscos were subjected to an ensemble of directed evolution strategies aimed at improving thermostability. The most recent ancestor of proteobacteria -dating back 2.4 billion years- was uniquely tolerant to mutagenic loading. Adaptive evolution, focused evolution and genetic drift revealed a panel of thermostable mutants, some deviating from the characteristic trade-offs in CO2-fixing speed and specificity. Our findings provide a novel approach for identifying Rubisco variants with improved catalytic evolution potential.This work was supported by the REPSOL Research contracts Rubolution (RC020401120018), Rubolution 2.0 (RC 020401140042), the CSIC project PIE-201780E043 and the Australian Research Council grant CE140100015

Blood Signature of Pre-Heart Failure: A Microarrays Study

International audienceBACKGROUND: The preclinical stage of systolic heart failure (HF), known as asymptomatic left ventricular dysfunction (ALVD), is diagnosed only by echocardiography, frequent in the general population and leads to a high risk of developing severe HF. Large scale screening for ALVD is a difficult task and represents a major unmet clinical challenge that requires the determination of ALVD biomarkers. METHODOLOGY/PRINCIPAL FINDINGS: 294 individuals were screened by echocardiography. We identified 9 ALVD cases out of 128 subjects with cardiovascular risk factors. White blood cell gene expression profiling was performed using pangenomic microarrays. Data were analyzed using principal component analysis (PCA) and Significant Analysis of Microarrays (SAM). To build an ALVD classifier model, we used the nearest centroid classification method (NCCM) with the ClaNC software package. Classification performance was determined using the leave-one-out cross-validation method. Blood transcriptome analysis provided a specific molecular signature for ALVD which defined a model based on 7 genes capable of discriminating ALVD cases. Analysis of an ALVD patients validation group demonstrated that these genes are accurate diagnostic predictors for ALVD with 87% accuracy and 100% precision. Furthermore, Receiver Operating Characteristic curves of expression levels confirmed that 6 out of 7 genes discriminate for left ventricular dysfunction classification. CONCLUSIONS/SIGNIFICANCE: These targets could serve to enhance the ability to efficiently detect ALVD by general care practitioners to facilitate preemptive initiation of medical treatment preventing the development of HF

Effects of aging and type 2 diabetes on resting and post occlusive hyperemia of the forearm; the impact of rosiglitazone

BACKGROUND: Both Diabetes and ageing are associated with reduced vascular endothelial function. The exact relationship between the 2 and any improvements from the insulin sensitizer rosiglitazone have not been explored. METHODS: Thirty controls and sixteen subjects with type 2 diabetes participated in a series of experiments to examine the interrelationships between age, diabetes and endothelial cell function. In subjects with diabetes, the insulin sensitizer rosiglitazone (RSG), a drug also known to improve vascular function, was administered for 3 months to see how it altered these relationships. Resting forearm flows (RF) and blood flows after 4 min of vascular occlusion (PF) were measured as an index of endothelial cell function. RESULTS: RF, measured by venous occlusion plethysmography, was negatively correlated to both age and diabetes. Administration of RSG for 3 months was associated with an increase in the blood flow response to venous occlusion so that it was not significantly different than that of age matched controls. Total PF in control subjects, compared to subjects with diabetes, averaged 56.58 +/- 12.57 and 13.6 +/- 8.01 cc/100 cc tissue per min respectively, and were significantly different (p < 0.01). After 3 months on RSG, differences between PF in the two groups were no longer evident. CONCLUSION: These studies suggest a different mechanism causing a reduction in vascular reactivity with aging and diabetes

Investigation of Variation in Gene Expression Profiling of Human Blood by Extended Principle Component Analysis

BACKGROUND: Human peripheral blood is a promising material for biomedical research. However, various kinds of biological and technological factors result in a large degree of variation in blood gene expression profiles. METHODOLOGY/PRINCIPAL FINDINGS: Human peripheral blood samples were drawn from healthy volunteers and analysed using the Human Genome U133Plus2 Microarray. We applied a novel approach using the Principle Component Analysis and Eigen-R(2) methods to dissect the overall variation of blood gene expression profiles with respect to the interested biological and technological factors. The results indicated that the predominating sources of the variation could be traced to the individual heterogeneity of the relative proportions of different blood cell types (leukocyte subsets and erythrocytes). The physiological factors like age, gender and BMI were demonstrated to be associated with 5.3% to 9.2% of the total variation in the blood gene expression profiles. We investigated the gene expression profiles of samples from the same donors but with different levels of RNA quality. Although the proportion of variation associated to the RNA Integrity Number was mild (2.1%), the significant impact of RNA quality on the expression of individual genes was observed. CONCLUSIONS: By characterizing the major sources of variation in blood gene expression profiles, such variability can be minimized by modifications to study designs. Increasing sample size, balancing confounding factors between study groups, using rigorous selection criteria for sample quality, and well controlled experimental processes will significantly improve the accuracy and reproducibility of blood transcriptome study

Directing the evolution of Rubisco and Rubisco activase: first impressions of a new tool for photosynthesis research

During the last decade the practice of laboratory-directed protein evolution has become firmly established as a versatile tool in biochemical research by enabling molecular evolution toward desirable phenotypes or detection of novel structure–function interactions. Applications of this technique in the field of photosynthesis research are still in their infancy, but recently first steps have been reported in the directed evolution of the CO2-fixing enzyme Rubisco and its helper protein Rubisco activase. Here we summarize directed protein evolution strategies and review the progressive advances that have been made to develop and apply suitable selection systems for screening mutant forms of these enzymes that improve the fitness of the host organism. The goal of increasing photosynthetic efficiency of plants by improving the kinetics of Rubisco has been a long-term goal scoring modest successes. We discuss how directed evolution methodologies may one day be able to circumvent the problems encountered during this venture

Early detection of breast cancer based on gene-expression patterns in peripheral blood cells

INTRODUCTION: Existing methods to detect breast cancer in asymptomatic patients have limitations, and there is a need to develop more accurate and convenient methods. In this study, we investigated whether early detection of breast cancer is possible by analyzing gene-expression patterns in peripheral blood cells. METHODS: Using macroarrays and nearest-shrunken-centroid method, we analyzed the expression pattern of 1,368 genes in peripheral blood cells of 24 women with breast cancer and 32 women with no signs of this disease. The results were validated using a standard leave-one-out cross-validation approach. RESULTS: We identified a set of 37 genes that correctly predicted the diagnostic class in at least 82% of the samples. The majority of these genes had a decreased expression in samples from breast cancer patients, and predominantly encoded proteins implicated in ribosome production and translation control. In contrast, the expression of some defense-related genes was increased in samples from breast cancer patients. CONCLUSION: The results show that a blood-based gene-expression test can be developed to detect breast cancer early in asymptomatic patients. Additional studies with a large sample size, from women both with and without the disease, are warranted to confirm or refute this finding