In vivo and ex vivo regulation of bacterial virulence gene expression

Bacteria are remarkably adaptable organisms that are able to survive and multiply in diverse and sometimes hostile environments. Adaptability is determined by the complement of genetic information available to an organism and by the mechanisms that control gene expression. In general, gene products conferring a growth or survival advantage in a particular situation are expressed, while unnecessary or deleterious functions are not. Expression of virulence gene products that allow pathogenic bacteria to multiply on and within host cells and tissues are no exception to this rule. Being of little or no use to the bacterium except during specific stages of the infectious cycle, these accessory factors are nearly always subject to tight and coordinate regulation. As a result of recent advances, we are beginning to appreciate the complexities of the interactions between bacteria and their hosts. The ability to probe virulence gene regulation in vivo has broadened our perspectives on pathogenesis.     

Gene expression signatures and ex vivo drug sensitivity profiles in children with acute lymphoblastic leukemia

Introduction  

Causes of treatment failure in acute lymphoblastic leukemia (ALL) are still poorly understood. Microarray technology gives new possibilities for the analysis of the biology of leukemias. We hypothesize that drug sensitivity in pediatric ALL is driven by specific molecular mechanisms that correlate with gene expression profiles assessed by microarray analysis.     

Web-based interrogation of gene expression signatures using EXALT

Background  

Widespread use of high-throughput techniques such as microarrays to monitor gene expression levels has resulted in an explosive growth of data sets in public domains. Integration and exploration of these complex and heterogeneous data have become a major challenge.     

Caspase inhibition supports proper gene expression in ex vivo mouse limb cultures

We standardized conditions for ex vivo mouse limb culture to study cartilage maturation and joint formation. We compared 12.5 d.p.c. mouse forelimbs that were cultured either mounted or freely rotating for up to 72 h. Limb outgrowth progressed ex vivo at a variable rate as compared to its development in vivo, spanning approximately 48 h. Although cartilage maturation and joint formation developed grossly normal, aberrant expression of skeletal marker genes was seen. Interestingly, no regression of the interdigital webs took place in mounted cultures, in contrast to limited webbing under freely rotating conditions. Caspase inhibition, by addition of zVAD-fmk to the culture medium of freely rotating limbs, supported proper gene expression associated with skeletal development, and prevented interdigital web regression. Taken together, a freely rotating ex vivo culture for mouse limb outgrowth that is combined with caspase inhibition provides a good model to study cartilage maturation and joint formation.     

In vivo skin dose measurement using MOSkin detectors in tangential breast radiotherapy

The purpose of this study is to measure patient skin dose in tangential breast radiotherapy. Treatment planning dose calculation algorithm such as Pencil Beam Convolution (PBC) and in vivo dosimetry techniques such as radiochromic film can be used to accurately monitor radiation doses at tissue depths, but they are inaccurate for skin dose measurement. A MOSFET-based (MOSkin) detector was used to measure skin dose in this study. Tangential breast radiotherapies (“bolus” and “no bolus”) were simulated on an anthropomorphic phantom and the skin doses were measured. Skin doses were also measured in 13 patients undergoing each of the techniques. In the patient study, the EBT2 measurements and PBC calculation tended to over-estimate the skin dose compared with the MOSkin detector (p < 0.05) in the “no bolus radiotherapy”. No significant differences were observed in the “bolus radiotherapy” (p > 0.05). The results from patients were similar to that of the phantom study. This shows that the EBT2 measurement and PBC calculation, while able to predict accurate doses at tissue depths, are inaccurate in predicting doses at build-up regions. The clinical application of the MOSkin detectors showed that the average total skin doses received by patients were 1662 ± 129 cGy (medial) and 1893 ± 199 cGy (lateral) during “no bolus radiotherapy”. The average total skin doses were 4030 ± 72 cGy (medial) and 4004 ± 91 cGy (lateral) for “bolus radiotherapy”. In some cases, patient skin doses were shown to exceed the dose toxicity level for skin erythema. Hence, a suitable device for in vivo dosimetry is necessary to accurately determine skin dose.     

New algorithms for multi-class cancer diagnosis using tumor gene expression signatures

MOTIVATION: The increasing use of DNA microarray-based tumor gene expression profiles for cancer diagnosis requires mathematical methods with high accuracy for solving clustering, feature selection and classification problems of gene expression data. RESULTS: New algorithms are developed for solving clustering, feature selection and classification problems of gene expression data. The clustering algorithm is based on optimization techniques and allows the calculation of clusters step-by-step. This approach allows us to find as many clusters as a data set contains with respect to some tolerance. Feature selection is crucial for a gene expression database. Our feature selection algorithm is based on calculating overlaps of different genes. The database used, contains over 16 000 genes and this number is considerably reduced by feature selection. We propose a classification algorithm where each tissue sample is considered as the center of a cluster which is a ball. The results of numerical experiments confirm that the classification algorithm in combination with the feature selection algorithm perform slightly better than the published results for multi-class classifiers based on support vector machines for this data set. AVAILABILITY: Available on request from the authors.     

Prediction of treatment response using gene expression profiles

This paper concerns prediction of clinical outcome from gene expression profiles using work in a different area, nonlinear system identification. In particular, the approach can predict long-term treatment response from data of a landmark article by Golub et al. (Golub, T. R.; Slonim, D. K.; Tamayo, P.; Huard, C.; Gaasenbeek, M.; Mesirov, J. P. et al. Science 1999, 286, 531-537) that has not previously been achieved with these data. The present paper shows that, for these data, gene expression profiles taken at time of diagnosis of acute myeloid leukemia contain information predictive of eventual response to chemotherapy. This was not evident in previous work; indeed, the Golub et al. article did not find a set of genes strongly correlated with clinical outcome. However, the present approach can accurately predict outcome class of gene expression profiles even when the genes do not have large differences in expression levels between the classes.     

Altered dose response to beta-agonists in SERCA1a-expressing hearts ex vivo and in vivo

In this study we evaluated the contractile characteristics of sarco(endo)plasmic reticulum Ca(2+)-ATPase (SERCA)1a-expressing hearts ex vivo and in vivo and in particular their response to beta-adrenergic stimulation. Analysis of isolated, work-performing hearts revealed that transgenic (TG) hearts develop much higher maximal rates of contraction and relaxation than wild-type (WT) hearts. Addition of isoproterenol only moderately increased the maximal rate of relaxation (+20%) but did not increase contractility or decrease relaxation time in TG hearts. Perfusion with varied buffer Ca(2+) concentrations indicated an altered dose response to Ca(2+). In vivo TG hearts displayed fairly higher maximal rates of contraction (+ 25%) but unchanged relaxation parameters and a blunted but significant response to dobutamine. Our study also shows that the phospholamban (PLB) level was decreased (-40%) and its phosphorylation status modified in TG hearts. This study clearly demonstrates that increases in SERCA protein level alter the beta-adrenergic response and affect the phosphorylation of PLB. Interestingly, the overall cardiac function in the live animal is only slightly enhanced, suggesting that (neuro)hormonal regulations may play an important role in controlling in vivo heart function.     

体外实时动态监测水动力注射分泌型荧光素酶基因的表达

为了建立体外实时动态监测转导基因的体内表达,本研究选择分泌型的荧光素酶基因Gluc作为报告基因,对其体内外表达特性和检测方法进行了研究。首先构建了Gluc表达质粒pAAV2neo-Gluc。将pAAV2neo-Gluc转染体外培养的Huh7、HepG2细胞后,细胞培养上清和细胞裂解液中分别检测到Gluc的活性,而上清比细胞中的含量高约100倍。表明表达的Gluc以分泌形式为主。用水动力法经小鼠尾静脉注射pAAV2neo-Gluc质粒,活体成像表明Gluc在小鼠体内呈全身分布,而注射了萤火虫荧光素酶质粒pAAV2neo-Fluc的对照小鼠则主要在肝脏显像。将剂量分别为0.1、1、10、50μg每只的pAAV2neo-GlucDNA用水动力法尾静脉注射小鼠,不同时间点连续尾静脉采血测定其中的Gluc酶活性,观察其Gluc体内表达和分泌的动态变化。结果显示,各剂量组的Gluc表达变化规律高度一致:注射后2h即可检测到Gluc表达,10h后达到高峰,之后逐渐下降;Gluc的表达水平与注射质粒DNA的量呈正相关;为了进一步观察Gluc检测的灵敏性,本研究又比较了注射更低的质粒剂量(包括0.001、0.01和0.1μg每...     

Adenoviral gene transfer of eNOS: high-level expression in ex vivo expanded marrow stromal cells

Endothelial nitric oxide synthase (eNOS) is an attractive target for cardiovascular gene therapy. Marrow stromal cells (MSCs), also known as mesenchymal stem cells, hold great promise for use in adult stem cell-based cell and gene therapy. To determine the feasibility of adenoviral-mediated eNOS gene transfer into ex vivo expanded MSCs, rat MSCs (rMSCs) were isolated, expanded ex vivo, and transduced with Ad5RSVeNOS, an adenoviral vector containing the eNOS gene under the control of the Rous sarcoma virus promoter. The presence of eNOS protein in Ad5RSVeNOS-transduced rMSCs was confirmed by immunohistochemical and Western blot analysis. Transduction efficiency was dose dependent, and eNOS transgene expression in rMSCs persisted for =" BORDER="0">21 days in culture. The rMSCs retained multipotential differentiation capability after adenoviral-mediated eNOS gene transfer. Furthermore, intracavernosal injection of Ad5RSVeNOS-transduced rMSCs increased the expression of eNOS in the corpus cavernosum, and stem cells were identified within corporal sinusoids. These findings demonstrate that replication-deficient recombinant adenovirus can be used to engineer ex vivo expanded rMSCs and that high-level eNOS transgene expression can be achieved, pointing out the clinical potential of using this novel adult stem cell-based gene therapy method for the treatment of cardiovascular diseases. adenoviral vector; nitric oxide; gene expression; differentiation; gene therapy     

Revealing signaling pathway deregulation by using gene expression signatures and regulatory motif analysis

Gene expression signatures consisting of tens to hundreds of genes have been found to be informative for different biological states. Recently, many computational methods have been proposed for biological interpretation of such signatures. However, there is a lack of methods for identifying cell signaling pathways whose deregulation results in an observed expression signature. We present a strategy for identifying such signaling pathways and evaluate the strategy using six human and mouse gene expression signatures.     

Graph-based identification of cancer signaling pathways from published gene expression signatures using PubLiME

Gene expression technology has become a routine application in many laboratories and has provided large amounts of gene expression signatures that have been identified in a variety of cancer types. Interpretation of gene expression signatures would profit from the availability of a procedure capable of assigning differentially regulated genes or entire gene signatures to defined cancer signaling pathways. Here we describe a graph-based approach that identifies cancer signaling pathways from published gene expression signatures. Published gene expression signatures are collected in a database (PubLiME: Published Lists of Microarray Experiments) enabled for cross-platform gene annotation. Significant co-occurrence modules composed of up to 10 genes in different gene expression signatures are identified. Significantly co-occurring genes are linked by an edge in an undirected graph. Edge-betweenness and k-clique clustering combined with graph modularity as a quality measure are used to identify communities in the resulting graph. The identified communities consist of cell cycle, apoptosis, phosphorylation cascade, extra cellular matrix, interferon and immune response regulators as well as communities of unknown function. The genes constituting different communities are characterized by common genomic features and strongly enriched cis-regulatory modules in their upstream regulatory regions that are consistent with pathway assignment of those genes.     

Prediction of regulatory elements in mammalian genomes using chromatin signatures

Background  

Recent genomic scale survey of epigenetic states in the mammalian genomes has shown that promoters and enhancers are correlated with distinct chromatin signatures, providing a pragmatic way for systematic mapping of these regulatory elements in the genome. With rapid accumulation of chromatin modification profiles in the genome of various organisms and cell types, this chromatin based approach promises to uncover many new regulatory elements, but computational methods to effectively extract information from these datasets are still limited.     

Lentiviral and MLV based retroviral vectors for ex vivo and in vivo gene transfer

Retroviral vectors have become an important tool for gene transfer in vitro and in vivo. Classical Moloney murine leukemia virus (MLV) based retroviral vectors have been used for over 20 years to transfer genes into dividing cells. Cell lines for production of retroviral vectors have become commonly available and modifications in retroviral vector design and use of envelope proteins have made the production of high titer, helper-free, infectious virus stocks relatively easy. More recently, lentiviral vectors, another class of retroviruses, have been modified for in vitro and in vivo gene transfer. The ability of lentiviral vectors to transduce non-dividing cells has made them especially attractive for in vivo gene transfer into differentiated, non-dividing tissues. Several improvements in helper plasmids and vectors have made lentivirus a safe vector system for ex vivo and in vivo gene transfer. This review will briefly summarize the background of these vector systems and provide some common protocols available for the preparation of MLV based retroviral vectors and HIV-1 based lentiviral vectors.     

Strategy for encoding and comparison of gene expression signatures

EXALT (EXpression signature AnaLysis Tool) is a computational system enabling comparisons of microarray data across experimental platforms and different laboratories . An essential feature of EXALT is a database holding thousands of gene expression signatures extracted from the Gene Expression Omnibus, and encoded in a searchable format. This novel approach to performing global comparisons of shared microarray data may have enormous value when coupled directly with a shared data repository.     

A densely interconnected genome-wide network of microRNAs and oncogenic pathways revealed using gene expression signatures

MicroRNAs (miRNAs) are important components of cellular signaling pathways, acting either as pathway regulators or pathway targets. Currently, only a limited number of miRNAs have been functionally linked to specific signaling pathways. Here, we explored if gene expression signatures could be used to represent miRNA activities and integrated with genomic signatures of oncogenic pathway activity to identify connections between miRNAs and oncogenic pathways on a high-throughput, genome-wide scale. Mapping >300 gene expression signatures to >700 primary tumor profiles, we constructed a genome-wide miRNA-pathway network predicting the associations of 276 human miRNAs to 26 oncogenic pathways. The miRNA-pathway network confirmed a host of previously reported miRNA/pathway associations and uncovered several novel associations that were subsequently experimentally validated. Globally, the miRNA-pathway network demonstrates a small-world, but not scale-free, organization characterized by multiple distinct, tightly knit modules each exhibiting a high density of connections. However, unlike genetic or metabolic networks typified by only a few highly connected nodes ("hubs"), most nodes in the miRNA-pathway network are highly connected. Sequence-based computational analysis confirmed that highly-interconnected miRNAs are likely to be regulated by common pathways to target similar sets of downstream genes, suggesting a pervasive and high level of functional redundancy among coexpressed miRNAs. We conclude that gene expression signatures can be used as surrogates of miRNA activity. Our strategy facilitates the task of discovering novel miRNA-pathway connections, since gene expression data for multiple normal and disease conditions are abundantly available.