Rubisco small subunit, chlorophyll a/b-binding protein and sucrose : fructan-6-fructosyl transferase gene expression and sugar status in single barley leaf cells in situ. Cell type specificity and induction by light

Chungui Lu, Olga A. Koroleva, John F. Farrar, Joe Gallagher, Chris J. Pollock, and A. Deri Tomos (2002). Rubisco small subunit, chlorophyll a/b-binding protein and sucrose : fructan-6-fructosyl transferase gene expression and sugar status in single barley leaf cells in situ. Cell type specificity and induction by light. Plant Physiology, 130 (3) pp.1335-1348 Sponsorship: BBSRC RAE2008

Ex vivo culture of patient tissue and examination of gene delivery

Gene therapy has emerged as a realistic prospect for the treatment of cancer due to its potential for selective tumour cell targeting. The greatest challenge gene delivery vectors face is the ability to safely and efficiently deliver genes into target cells. The overall objectives of this thesis are to evaluate the efficacy of various gene delivery methods in a clinically relevant tumour model and to also investigate potential strategies for tumour selective delivery. We began with the development of a tumour slice model system using patient waste tissue. This model involves the use of fresh human tumour tissue, cut into thin slices and maintained ex vivo and is universally applicable to gene delivery methods, using a real-time luminescence detection method to assess gene delivery. The nature of the ex vivo culture system permitted examination of specific physiological variables, the influence of intratumoural factors and tissue specific effects on vector expression. Adenoviral vectors under the control of the human CXCR4 promoter demonstrated a 'tumour on' and 'normal off' expression profile when compared with the ubiquitously active CMV promoter when tested in patient tumour tissue. In addition, we developed an ex vivo system of changing oxygenation using the hypoxia inducer, cobalt, to mimic the transient hypoxic conditions found in solid tumours. We found that Adenoviral transgene expression was robust in the cycling hypoxic conditions relevant to solid tumours and re-oxygenation of chronically hypoxic tissue enhanced transgene expression. Finally, we demonstrated an AAV-based tumour targeting strategy using a tumour-selective promoter allowing for the efficient targeting of AAV vectors to cancer cells and the sparing of normal tissue in both murine metastatic liver tumours models and patient tissue. The thesis highlights the importance of indepth preclinical assessment of novel therapeutics and may serve as a platform for further testing of novel gene delivery approaches.

Modeling the evolution of regulatory elements by simultaneous detection and alignment with phylogenetic pair HMMs.

The computational detection of regulatory elements in DNA is a difficult but important problem impacting our progress in understanding the complex nature of eukaryotic gene regulation. Attempts to utilize cross-species conservation for this task have been hampered both by evolutionary changes of functional sites and poor performance of general-purpose alignment programs when applied to non-coding sequence. We describe a new and flexible framework for modeling binding site evolution in multiple related genomes, based on phylogenetic pair hidden Markov models which explicitly model the gain and loss of binding sites along a phylogeny. We demonstrate the value of this framework for both the alignment of regulatory regions and the inference of precise binding-site locations within those regions. As the underlying formalism is a stochastic, generative model, it can also be used to simulate the evolution of regulatory elements. Our implementation is scalable in terms of numbers of species and sequence lengths and can produce alignments and binding-site predictions with accuracy rivaling or exceeding current systems that specialize in only alignment or only binding-site prediction. We demonstrate the validity and power of various model components on extensive simulations of realistic sequence data and apply a specific model to study Drosophila enhancers in as many as ten related genomes and in the presence of gain and loss of binding sites. Different models and modeling assumptions can be easily specified, thus providing an invaluable tool for the exploration of biological hypotheses that can drive improvements in our understanding of the mechanisms and evolution of gene regulation.

Gene expression signatures of radiation response are specific, durable and accurate in mice and humans.

BACKGROUND: Previous work has demonstrated the potential for peripheral blood (PB) gene expression profiling for the detection of disease or environmental exposures. METHODS AND FINDINGS: We have sought to determine the impact of several variables on the PB gene expression profile of an environmental exposure, ionizing radiation, and to determine the specificity of the PB signature of radiation versus other genotoxic stresses. Neither genotype differences nor the time of PB sampling caused any lessening of the accuracy of PB signatures to predict radiation exposure, but sex difference did influence the accuracy of the prediction of radiation exposure at the lowest level (50 cGy). A PB signature of sepsis was also generated and both the PB signature of radiation and the PB signature of sepsis were found to be 100% specific at distinguishing irradiated from septic animals. We also identified human PB signatures of radiation exposure and chemotherapy treatment which distinguished irradiated patients and chemotherapy-treated individuals within a heterogeneous population with accuracies of 90% and 81%, respectively. CONCLUSIONS: We conclude that PB gene expression profiles can be identified in mice and humans that are accurate in predicting medical conditions, are specific to each condition and remain highly accurate over time.

Comparison of pattern detection methods in microarray time series of the segmentation clock.

While genome-wide gene expression data are generated at an increasing rate, the repertoire of approaches for pattern discovery in these data is still limited. Identifying subtle patterns of interest in large amounts of data (tens of thousands of profiles) associated with a certain level of noise remains a challenge. A microarray time series was recently generated to study the transcriptional program of the mouse segmentation clock, a biological oscillator associated with the periodic formation of the segments of the body axis. A method related to Fourier analysis, the Lomb-Scargle periodogram, was used to detect periodic profiles in the dataset, leading to the identification of a novel set of cyclic genes associated with the segmentation clock. Here, we applied to the same microarray time series dataset four distinct mathematical methods to identify significant patterns in gene expression profiles. These methods are called: Phase consistency, Address reduction, Cyclohedron test and Stable persistence, and are based on different conceptual frameworks that are either hypothesis- or data-driven. Some of the methods, unlike Fourier transforms, are not dependent on the assumption of periodicity of the pattern of interest. Remarkably, these methods identified blindly the expression profiles of known cyclic genes as the most significant patterns in the dataset. Many candidate genes predicted by more than one approach appeared to be true positive cyclic genes and will be of particular interest for future research. In addition, these methods predicted novel candidate cyclic genes that were consistent with previous biological knowledge and experimental validation in mouse embryos. Our results demonstrate the utility of these novel pattern detection strategies, notably for detection of periodic profiles, and suggest that combining several distinct mathematical approaches to analyze microarray datasets is a valuable strategy for identifying genes that exhibit novel, interesting transcriptional patterns.

A host transcriptional signature for presymptomatic detection of infection in humans exposed to influenza H1N1 or H3N2.

There is great potential for host-based gene expression analysis to impact the early diagnosis of infectious diseases. In particular, the influenza pandemic of 2009 highlighted the challenges and limitations of traditional pathogen-based testing for suspected upper respiratory viral infection. We inoculated human volunteers with either influenza A (A/Brisbane/59/2007 (H1N1) or A/Wisconsin/67/2005 (H3N2)), and assayed the peripheral blood transcriptome every 8 hours for 7 days. Of 41 inoculated volunteers, 18 (44%) developed symptomatic infection. Using unbiased sparse latent factor regression analysis, we generated a gene signature (or factor) for symptomatic influenza capable of detecting 94% of infected cases. This gene signature is detectable as early as 29 hours post-exposure and achieves maximal accuracy on average 43 hours (p = 0.003, H1N1) and 38 hours (p-value = 0.005, H3N2) before peak clinical symptoms. In order to test the relevance of these findings in naturally acquired disease, a composite influenza A signature built from these challenge studies was applied to Emergency Department patients where it discriminates between swine-origin influenza A/H1N1 (2009) infected and non-infected individuals with 92% accuracy. The host genomic response to Influenza infection is robust and may provide the means for detection before typical clinical symptoms are apparent.

Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies.

BACKGROUND: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. RESULTS: Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. CONCLUSIONS: Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data.

Radioactive in situ hybridization for detecting diverse gene expression patterns in tissue.

Knowing the timing, level, cellular localization, and cell type that a gene is expressed in contributes to our understanding of the function of the gene. Each of these features can be accomplished with in situ hybridization to mRNAs within cells. Here we present a radioactive in situ hybridization method modified from Clayton et al. (1988)(1) that has been working successfully in our lab for many years, especially for adult vertebrate brains(2-5). The long complementary RNA (cRNA) probes to the target sequence allows for detection of low abundance transcripts(6,7). Incorporation of radioactive nucleotides into the cRNA probes allows for further detection sensitivity of low abundance transcripts and quantitative analyses, either by light sensitive x-ray film or emulsion coated over the tissue. These detection methods provide a long-term record of target gene expression. Compared with non-radioactive probe methods, such as DIG-labeling, the radioactive probe hybridization method does not require multiple amplification steps using HRP-antibodies and/or TSA kit to detect low abundance transcripts. Therefore, this method provides a linear relation between signal intensity and targeted mRNA amounts for quantitative analysis. It allows processing 100-200 slides simultaneously. It works well for different developmental stages of embryos. Most developmental studies of gene expression use whole embryos and non-radioactive approaches(8,9), in part because embryonic tissue is more fragile than adult tissue, with less cohesion between cells, making it difficult to see boundaries between cell populations with tissue sections. In contrast, our radioactive approach, due to the larger range of sensitivity, is able to obtain higher contrast in resolution of gene expression between tissue regions, making it easier to see boundaries between populations. Using this method, researchers could reveal the possible significance of a newly identified gene, and further predict the function of the gene of interest.

Development of a Novel c-MET-Based CTC Detection Platform.

UNLABELLED: Amplification of the MET oncogene is associated with poor prognosis, metastatic dissemination, and drug resistance in many malignancies. We developed a method to capture and characterize circulating tumor cells (CTC) expressing c-MET using a ferromagnetic antibody. Immunofluorescence was used to characterize cells for c-MET, DAPI, and pan-CK, excluding CD45(+) leukocytes. The assay was validated using appropriate cell line controls spiked into peripheral blood collected from healthy volunteers (HV). In addition, peripheral blood was analyzed from patients with metastatic gastric, pancreatic, colorectal, bladder, renal, or prostate cancers. CTCs captured by c-MET were enumerated, and DNA FISH for MET amplification was performed. The approach was highly sensitive (80%) for MET-amplified cells, sensitive (40%-80%) for c-MET-overexpressed cells, and specific (100%) for both c-MET-negative cells and in 20 HVs. Of 52 patients with metastatic carcinomas tested, c-MET CTCs were captured in replicate samples from 3 patients [gastric, colorectal, and renal cell carcinoma (RCC)] with 6% prevalence. CTC FISH demonstrated that MET amplification in both gastric and colorectal cancer patients and trisomy 7 with gain of MET gene copies in the RCC patient. The c-MET CTC assay is a rapid, noninvasive, sensitive, and specific method for detecting MET-amplified tumor cells. CTCs with MET amplification can be detected in patients with gastric, colorectal, and renal cancers. IMPLICATIONS: This study developed a novel c-MET CTC assay for detecting c-MET CTCs in patients with MET amplification and warrants further investigation to determine its clinical applicability. Mol Cancer Res; 14(6); 539-47. ©2016 AACR.

Validation of the detection of Alexandrium species using specific RNA probes tested in a microarray format: Calibration of signal using variability of RNA content with environmental conditions.

The dinoflagellate genus Alexandrium contains several toxin producing species and strains, which can cause major economic losses to the shell fish industry. It is therefore important to be able to detect these toxin producers and also distinguish toxic strains from some of the morphologically identical non-toxic strains. To facilitate this DNA probes to be used in a microarray format were designed in silico or developed from existing published probes. These probes targeted either the 18S or 28S ribosomal ribonucleic acid (rRNA) gene in Alexandrium tamarense Group I, Group III and Group IV, Alexandrium ostenfeldii and Alexandrium minutum. Three strains of A. tamarense Group I, A. tamarense Group III, A. minutum and two strains of A. ostenfeldii were grown at optimal conditions and transferred into new environmental conditions changing either the light intensity, salinity, temperature or nutrient concentrations, to check if any of these environmental conditions induced changes in the cellular ribonucleic acid (RNA) concentration or growth rate. The aim of this experiment was the calibration of several species-specific probes for the quantification of the toxic Alexandrium strains. Growth rates were highly variable but only elevated or lowered salinity significantly lowered growth rate for A. tamarense Group I and Group III; differences in RNA content were not significant for the majority of the treatments. Only light intensity seemed to affect significantly the RNA content in A. tamarense Group I and Group III, but this was still within the same range as for the other treatments meaning that a back calibration from RNA to cell numbers was possible. The designed probes allow the production of quantitative information for Alexandrium species for the microarray chip.

Significantly improved PCR-based clonality testing in B-cell malignancies by use of multiple immunoglobulin gene targets: Report of the BIOMED-2 Concerted Action BHM4-CT98-3936.

Polymerase chain reaction (PCR) assessment of clonal immunoglobulin (Ig) and T-cell receptor (TCR) gene rearrangements is an important diagnostic tool in mature B-cell neoplasms. However, lack of standardized PCR protocols resulting in a high level of false negativity has hampered comparability of data in previous clonality studies. In order to address these problems, 22 European laboratories investigated the Ig/TCR rearrangement patterns as well as t(14;18) and t(11;14) translocations of 369 B-cell malignancies belonging to five WHO-defined entities using the standardized BIOMED-2 multiplex PCR tubes accompanied by international pathology panel review. B-cell clonality was detected by combined use of the IGH and IGK multiplex PCR assays in all 260 definitive cases of B-cell chronic lymphocytic leukemia (n¼56), mantle cell lymphoma (n¼54), marginal zone lymphoma (n¼41) and follicular lymphoma (n¼109). Two of 109 cases of diffuse large B-cell lymphoma showed no detectable clonal marker. The use of these techniques to assign cell lineage should be treated with caution as additional clonal TCR gene rearrangements were frequently detected in all disease categories. Our study indicates that the BIOMED-2 multiplex PCR assays provide a powerful strategy for clonality assessment in B-cell malignancies resulting in high Ig clonality detection rates particularly when IGH and IGK strategies are combined.

Development and clinical validation of a loop-mediated isothermal amplification (LAMP) method for the rapid detection of Neisseria meningitidis

Loop-mediated isothermal amplification (LAMP) is an innovative technique that allows the rapid detection of target nucleic acid sequences under isothermal conditions without the need for complex instrumentation. The development, optimization, and clinical validation of a LAMP assay targeting the ctrA gene for the rapid detection of capsular Neisseria meningitidis were described. Highly specific detection of capsular N. meningitidis type strains and clinical isolates was demonstrated, with no cross-reactivity with other Neisseria spp. or with a comprehensive panel of other common human pathogens. The lower limit of detection was 6 ctrA gene copies detectable in 48 min, with positive reactions readily identifiable visually via a simple color change. Higher copy numbers could be detected in as little as 16 min. When applied to a total of 394 clinical specimens, the LAMP assay in comparison to a conventional TaqMan® based real-time polymerase chain reaction system demonstrated a sensitivity of 100% and a specificity of 98.9% with a ? coefficient of 0.942. The LAMP method represents a rapid, sensitive, and highly specific technique for the detection of N. meningitidis and has the potential to be used as a point-of-care molecular test and in resource-poor settings.

Detection of epidermal growth factor receptor variations by partially denaturing HPLC

Background: Epidermal growth factor receptor gene (EGFR) variants may be useful markers for identifying responders to gefitinib and erlotinib, small-molecule tyrosine kinase inhibitors of EGFR; therefore, sensitive and cost-effective assays are needed to detect EGFR variants in routine clinical samples. We have developed a partially denaturing HPLC (pDHPLC) assay that is superior to direct sequencing with respect to detection limits, costs, and time requirements.

Tailored Microarray Platform for the Detection of Marine Toxins

Currently, there are no fast in vitro broad spectrum screening bioassays for the detection of marine toxins. The aim of this study was to develop such an assay. In gene expression profiling experiments 17 marker genes were provisionally selected that were differentially regulated in human intestinal Caco-2 cells upon exposure to the lipophilic shellfish poisons azaspiracid-1 (AZA1) or dinophysis toxin-1 (DTX1). These 17 genes together with two control genes were the basis for the design of a tailored microarray platform for the detection of these marine toxins and potentially others. Five out of the 17 selected marker genes on this dedicated DNA microarray gave dear signals, whereby the resulting fingerprints could be used to detect these toxins. CEACAM1, DDIT4, and TUBB3 were up-regulated by both AZA1 and DTX1, TRIB3 was up-regulated by AZA1 only, and OSR2 by DTX1 only. Analysis by singleplex qRT-PCR revealed the up- and down-regulation of the selected RGS16 and NPPB marker genes by DTX1, that were not envisioned by the new developed dedicated array. The qRT-PCR targeting the DDIT4, RSG16 and NPPB genes thus already resulted in a specific pattern for AZA1 and DTX1 indicating that for this specific case qRT-PCR might a be more suitable approach than a dedicated array.

Validation and application of reporter gene assays for the determination of estrogenic and androgenic endocrine disruptor activity in sport supplements.

Previously developed estrogen and androgen mammalian reporter gene assays (RGAs) were assessed for their potential use as a quantitative screening method in the detection of estrogenic and androgenic endocrine disruptors (EDs) in sport supplements. The validation of both RGAs coupled with dispersive solid phase extraction (dSPE) was performed in accordance with European Commission Decision EC/2002/6579 for biological screening methods. Decision limits (CCa) and detection capabilities (CCß) were established for both the estrogen and androgen RGAs. All samples were compliant with CCa and CCß in both bioassays. Recovery rates were 96 % for 17ß-estradiol and 115 % for dihydrotestosterone as obtained in their corresponding RGA. Both estrogens and androgens were stable in samples for more than 3 weeks, when stored at -20 °C. Specificity, good repeatability (coefficients of variation (CV), 12–25 %), reproducibility and robustness of both bioassays were also observed. Four different ED modes of action were determined for estrogens and androgens in 53 sport supplements, using the validated RGAs. This study revealed that 89 % of the investigated sport supplements contained estrogenic EDs and 51 % contained androgenic compounds. In conclusion, both bioassays are suitable for sport supplement screening of estrogenic and androgenic EDs.