Articles de revues : « Phenotype Microarray »

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De, Supriyo, Yongqing Zhang, John R. Garner, S. Alex Wang et Kevin G. Becker. « Disease and phenotype gene set analysis of disease-based gene expression in mouse and human ». Physiological Genomics 42A, n^o 2 (octobre 2010) : 162–67. http://dx.doi.org/10.1152/physiolgenomics.00008.2010.

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The genetic contributions to common disease and complex disease phenotypes are pleiotropic, multifactorial, and combinatorial. Gene set analysis is a computational approach used in the analysis of microarray data to rapidly query gene combinations and multifactorial processes. Here we use novel gene sets based on population-based human genetic associations in common human disease or experimental genetic mouse models to analyze disease-related microarray studies. We developed a web-based analysis tool that uses these novel disease- and phenotype-related gene sets to analyze microarray-based gene expression data. These gene sets show disease and phenotype specificity in a species-specific and cross-species fashion. In this way, we integrate population-based common human disease genetics, mouse genetically determined phenotypes, and disease or phenotype structured ontologies, with gene expression studies relevant to human disease. This may aid in the translation of large-scale high-throughput datasets into the context of clinically relevant disease phenotypes.

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Xuan, Jianhua. « Cross phenotype normalization of microarray data ». Frontiers in Bioscience E2, n^o 1 (2010) : 171–86. http://dx.doi.org/10.2741/e80.

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Bochner, Barry, Vanessa Gomez, Michael Ziman, Shihui Yang et Steven D. Brown. « Phenotype MicroArray Profiling of Zymomonas mobilis ZM4 ». Applied Biochemistry and Biotechnology 161, n^o 1-8 (12 décembre 2009) : 116–23. http://dx.doi.org/10.1007/s12010-009-8842-2.

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von Eiff, Christof, Peter McNamara, Karsten Becker, Donna Bates, Xiang-He Lei, Michael Ziman, Barry R. Bochner, Georg Peters et Richard A. Proctor. « Phenotype Microarray Profiling of Staphylococcus aureus menD and hemB Mutants with the Small-Colony-Variant Phenotype ». Journal of Bacteriology 188, n^o 2 (15 janvier 2006) : 687–93. http://dx.doi.org/10.1128/jb.188.2.687-693.2006.

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ABSTRACT Standard biochemical tests have revealed that hemin and menadione auxotrophic Staphylococcus aureus small-colony variants (SCVs) exhibit multiple phenotypic changes. To provide a more complete analysis of the SCV phenotype, two genetically defined mutants with a stable SCV phenotype were comprehensively tested. These mutants, generated via mutations in menD or hemB that yielded menadione and hemin auxotrophs, were subjected to phenotype microarray (PM) analysis of over 1,500 phenotypes (including utilization of different carbon, nitrogen, phosphate, and sulfur sources; growth stimulation or inhibition by amino acids and other nutrients, osmolytes, and metabolic inhibitors; and susceptibility to antibiotics). Compared to parent strain COL, the hemB mutant was defective in utilization of a variety of carbon sources, including Krebs cycle intermediates and compounds that ultimately generate ATP via electron transport. The phenotype of the menD mutant was similar to that of the hemB mutant, but the defects in carbon metabolism were more pronounced than those seen with the hemB mutant. In both mutant strains, hexose phosphates and other carbohydrates that provide ATP in the absence of electron transport stimulated growth. Other phenotypes of SCV mutants, such as hypersensitivity to sodium selenite, sodium tellurite, and sodium nitrite, were also uncovered by the PM analysis. Key results of the PM analysis were confirmed in independent growth studies and by using Etest strips for susceptibility testing. PM technology is a new and efficient technology for assessing cellular phenotypes in S. aureus.

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Card, Roderick, Jiancheng Zhang, Priya Das, Charlotte Cook, Neil Woodford et Muna F. Anjum. « Evaluation of an Expanded Microarray for Detecting Antibiotic Resistance Genes in a Broad Range of Gram-Negative Bacterial Pathogens ». Antimicrobial Agents and Chemotherapy 57, n^o 1 (5 novembre 2012) : 458–65. http://dx.doi.org/10.1128/aac.01223-12.

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ABSTRACTA microarray capable of detecting genes for resistance to 75 clinically relevant antibiotics encompassing 19 different antimicrobial classes was tested on 132 Gram-negative bacteria. Microarray-positive results correlated >91% with antimicrobial resistance phenotypes, assessed using British Society for Antimicrobial Chemotherapy clinical breakpoints; the overall test specificity was >83%. Microarray-positive results without a corresponding resistance phenotype matched 94% with PCR results, indicating accurate detection of genes present in the respective bacteria by microarray when expression was low or absent and, hence, undetectable by susceptibility testing. The low sensitivity and negative predictive values of the microarray results for identifying resistance to some antimicrobial resistance classes are likely due to the limited number of resistance genes present on the current microarray for those antimicrobial agents or to mutation-based resistance mechanisms. With regular updates, this microarray can be used for clinical diagnostics to help accurate therapeutic options to be taken following infection with multiple-antibiotic-resistant Gram-negative bacteria and prevent treatment failure.

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Viti, Carlo, Enrico Tatti et Luciana Giovannetti. « Phenotype MicroArray analysis of cells : fulfilling the promise ». Research in Microbiology 167, n^o 9-10 (novembre 2016) : 707–9. http://dx.doi.org/10.1016/j.resmic.2016.08.003.

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TOHSATO, YUKAKO, TOMOYA BABA, YUSAKU MAZAKI, MASAHIRO ITO, BARRY L. WANNER et HIROTADA MORI. « ENVIRONMENTAL DEPENDENCY OF GENE KNOCKOUTS ON PHENOTYPE MICROARRAY ANALYSIS IN ESCHERICHIA COLI ». Journal of Bioinformatics and Computational Biology 08, supp01 (décembre 2010) : 83–99. http://dx.doi.org/10.1142/s021972001000521x.

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Systematic studies have revealed that single gene deletions often display little phenotypic effects under laboratory conditions and that in many cases gene dispensability depends on the experimental conditions. To elucidate the environmental dependency of genes, we analyzed the effects of gene deletions by Phenotype MicroArray™ (PM), a system for quantitative screening of thousands of phenotypes in a high-throughput manner. Here, we proposed a new statistical approach to minimize error inherent in measurements of low respiration rates and find which mutants showed significant phenotypic changes in comparison to the wild-type. We show analyzing results from comprehensive PM assays of 298 single-gene knockout mutants in the Keio collection and two additional mutants under 1,920 different conditions. We focused on isozymes of these genes as simple duplications and analyzed correlations between phenotype changes and protein expression levels. Our results revealed divergence of the environmental dependency of the gene among the knockout genes and have also given some insights into possibilities of alternative pathways and availabilities of information on protein synthesis patterns to classify or predict functions of target genes from systematic phenotype screening.

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Çebi, Alper Han, et Şule Altıner. « Application of Chromosome Microarray Analysis in the Investigation of Developmental Disabilities and Congenital Anomalies : Single Center Experience and Review of NRXN3 and NEDD4L Deletions ». Molecular Syndromology 11, n^o 4 (2020) : 197–206. http://dx.doi.org/10.1159/000509645.

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Chromosomal microarray analysis (CMA) is a first step test used for the diagnosis of patients with developmental delay, intellectual disability, autistic spectrum disorder, and multiple congenital anomalies. Its widespread usage has allowed genome-wide identification of copy number variations (CNVs). In our study, we performed a retrospective study on clinical and microarray data of 237 patients with developmental disabilities and/or multiple congenital anomalies and investigated the clinical utility of CMA. Phenotype-associated CNVs were detected in 15.18% of patients. Besides, we detected submicroscopic losses on 14q24.3q31.1 in a patient with speech delay and on 18q21.31q21.32 in twin patients with seizures. Deletions of <i>NRXN3</i> and <i>NEDD4L</i> were responsible for the phenotypes, respectively. This study showed that CMA is a powerful diagnostic tool in this patient group and expands the genotype-phenotype correlations on developmental disabilities.

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Gerstgrasser, Matthias, Sarah Nicholls, Michael Stout, Katherine Smart, Chris Powell, Theodore Kypraios et Dov Stekel. « A Bayesian approach to analyzing phenotype microarray data enables estimation of microbial growth parameters ». Journal of Bioinformatics and Computational Biology 14, n^o 03 (juin 2016) : 1650007. http://dx.doi.org/10.1142/s0219720016500074.

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Biolog phenotype microarrays (PMs) enable simultaneous, high throughput analysis of cell cultures in different environments. The output is high-density time-course data showing redox curves (approximating growth) for each experimental condition. The software provided with the Omnilog incubator/reader summarizes each time-course as a single datum, so most of the information is not used. However, the time courses can be extremely varied and often contain detailed qualitative (shape of curve) and quantitative (values of parameters) information. We present a novel, Bayesian approach to estimating parameters from Phenotype Microarray data, fitting growth models using Markov Chain Monte Carlo (MCMC) methods to enable high throughput estimation of important information, including length of lag phase, maximal “growth” rate and maximum output. We find that the Baranyi model for microbial growth is useful for fitting Biolog data. Moreover, we introduce a new growth model that allows for diauxic growth with a lag phase, which is particularly useful where Phenotype Microarrays have been applied to cells grown in complex mixtures of substrates, for example in industrial or biotechnological applications, such as worts in brewing. Our approach provides more useful information from Biolog data than existing, competing methods, and allows for valuable comparisons between data series and across different models.

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Holt, S., et E. Sweeney. « Using microarray to diagnose Noonan Syndrome and predict phenotype ». Archives of Disease in Childhood 97, Suppl 1 (mai 2012) : A15.3—A16. http://dx.doi.org/10.1136/archdischild-2012-301885.38.

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Ko, In Kap, Koichi Kato et Hiroo Iwata. « Antibody microarray for correlating cell phenotype with surface marker ». Biomaterials 26, n^o 6 (février 2005) : 687–96. http://dx.doi.org/10.1016/j.biomaterials.2004.03.014.

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Greetham, Darren. « Phenotype microarray technology and its application in industrial biotechnology ». Biotechnology Letters 36, n^o 6 (22 février 2014) : 1153–60. http://dx.doi.org/10.1007/s10529-014-1481-x.

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Seta, Karen A., et David E. Millhorn. « Functional genomics approach to hypoxia signaling ». Journal of Applied Physiology 96, n^o 2 (février 2004) : 765–73. http://dx.doi.org/10.1152/japplphysiol.00836.2003.

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Mammalian cells require a constant supply of oxygen to maintain energy balance, and sustained hypoxia can result in cell death. It is therefore not surprising that sophisticated adaptive mechanisms have evolved that enhance cell survival during hypoxia. During the past few years, there have been a growing number of reports on hypoxia-induced transcription of specific genes. In this review, we describe a unique experimental approach that utilizes focused cDNA libraries coupled to microarray analyses to identify hypoxia-responsive signal transduction pathways and genes that confer the hypoxia-tolerant phenotype. We have used the subtractive suppression hybridization (SSH) method to create a cDNA library enriched in hypoxia-regulated genes in oxygen-sensing pheochromocytoma cells and have used this library to create microarrays that allow us to examine hundreds of genes at a time. This library contains over 300 genes and expressed sequence tags upregulated by hypoxia, including tyrosine hydroxylase, vascular endothelial growth factor, and junB. Hypoxic regulation of these and other genes in the library has been confirmed by microarray, Northern blot, and real-time PCR analyses. Coupling focused SSH libraries with microarray analyses allows one to specifically study genes relevant to a phenotype of interest while reducing much of the biological noise associated with these types of studies. When used in conjunction with high-throughput, dye-based assays for cell survival and apoptosis, this approach offers a rapid method for discovering validated therapeutic targets for the treatment of cardiovascular disease, stroke, and tumors.

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Jung, Kyung-Mi, Jongbeom Park, Jueun Jang, Seok-Hwa Jung, Sang Han Lee et Soo Rin Kim. « Characterization of Cold-Tolerant Saccharomyces cerevisiae Cheongdo Using Phenotype Microarray ». Microorganisms 9, n^o 5 (30 avril 2021) : 982. http://dx.doi.org/10.3390/microorganisms9050982.

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The cold-tolerant yeast Saccharomyces cerevisiae is industrially useful for lager fermentation, high-quality wine, and frozen dough production. S. cerevisiae Cheongdo is a recent isolate from frozen peach samples which has a good fermentation performance at low temperatures and desirable flavor profiles. Here, phenotype microarray was used to investigate industrial potentials of S. cerevisiae Cheongdo using 192 carbon sources. Compared to commercial wine yeast S. cerevisiae EC1118, Cheongdo showed significantly different growth rates on 34 substrates. The principal component analysis of the results highlighted that the better growth of Cheongdo on galactose than on EC1118 was the most significant difference between the two strains. The intact GAL4 gene and the galactose fermentation performance at a low temperatures suggested that S. cerevisiae Cheongdo is a promising host for industrial fermentation rich in galactose, such as lactose and agarose.

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Abu Bakar, F., R. R. Hafidh et A. S. Abdulamir. « Phenotype microarray profiling of the antibacterial activity of red cabbage ». Functional Foods in Health and Disease 2, n^o 6 (14 juin 2012) : 212. http://dx.doi.org/10.31989/ffhd.v2i6.88.

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Background: Functional food can be a potent source of wide array of biocomonents with antimicrobial activity. We investigated the antibacterial activity of red cabbage (RC) extract on Gram negative and positive ATCC strains. Most intersting, we, for the first time, explored and analysed the complete phenotypic profile of RC-treated bacteria using Omnilog Phenotype Microarray.Results: This study revealed that the phenotype microarray (PM) screen was a valuable tool in the search for compounds and their antibacterial mechanisms that can inhibit bacterial growth by affecting certain metabolic pathways. It was shown that RC exerted remarkable antibacterial effect on S. aureus and E. coli bacteria, and PM showed a wide range phenotypic profile of the exerted RC antibacterial activity. RC targeted the peptide, carbon, nutriontional assembly, and sulfur metbolic pathways altogether. The peptidoglycan synthesis pathway was inferred to be targeted by RC extract at a metabolic point different from other available cell wall-targeting drugs; these could be hot targets for the discovery of new therapy for many problematic microbes.Conclusions: Taken together, the phenotype microarray for functional food and medicinal plants can be a very useful tool for profiling their antimicrobial activity. Moreover, extracts of functional food can exert antibacterial activity by hitting a wide range of metabolic pathways, at the same time leading to very difficult condition for bacteria to rapidly develop resistance. Therefore, using functional foods or medicinal plants as such, or as extracts, can be superior on mono-targeting antibiotics if the optimal concentrations and conditions of these functional foods were sought.Key words: red cabbage, bacteria, antibacterial, phenotype microarray, Omnilog, Biolog

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Dawoud, Turki M., Anita Khatiwara, Si Hong Park, Morgan L. Davis, Christopher A. Baker, Steven C. Ricke et Young Min Kwon. « Heat Survival and Phenotype Microarray Profiling of Salmonella Typhimurium Mutants ». Current Microbiology 74, n^o 2 (21 décembre 2016) : 257–67. http://dx.doi.org/10.1007/s00284-016-1170-1.

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Zhou, Lu, Xiang-He Lei, Barry R. Bochner et Barry L. Wanner. « Phenotype MicroArray Analysis of Escherichia coli K-12 Mutants with Deletions of All Two-Component Systems ». Journal of Bacteriology 185, n^o 16 (15 août 2003) : 4956–72. http://dx.doi.org/10.1128/jb.185.16.4956-4972.2003.

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ABSTRACT Two-component systems are the most common mechanism of transmembrane signal transduction in bacteria. A typical system consists of a histidine kinase and a partner response regulator. The histidine kinase senses an environmental signal, which it transmits to its partner response regulator via a series of autophosphorylation, phosphotransfer, and dephosphorylation reactions. Much work has been done on particular systems, including several systems with regulatory roles in cellular physiology, communication, development, and, in the case of bacterial pathogens, the expression of genes important for virulence. We used two methods to investigate two-component regulatory systems in Escherichia coli K-12. First, we systematically constructed mutants with deletions of all two-component systems by using a now-standard technique of gene disruption (K. A. Datsenko and B. L. Wanner, Proc. Natl. Acad. Sci. USA 97:6640-6645, 2000). We then analyzed these deletion mutants with a new technology called Phenotype MicroArrays, which permits assays of nearly 2,000 growth phenotypes simultaneously. In this study we tested 100 mutants, including mutants with individual deletions of all two-component systems and several related genes, including creBC-regulated genes (cbrA and cbrBC), phoBR-regulated genes (phoA, phoH, phnCDEFGHIJKLMNOP, psiE, and ugpBAECQ), csgD, luxS, and rpoS. The results of this battery of nearly 200,000 tests provided a wealth of new information concerning many of these systems. Of 37 different two-component mutants, 22 showed altered phenotypes. Many phenotypes were expected, and several new phenotypes were also revealed. The results are discussed in terms of the biological roles and other information concerning these systems, including DNA microarray data for a large number of the same mutants. Other mutational effects are also discussed.

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Cuadros, Marta, Sandeep S. Dave, Elaine S. Jaffe, Emiliano Honrado, Roger Milne, Javier Alves, Jose Rodríguez et al. « Identification of a Proliferation Signature Related to Survival in Nodal Peripheral T-Cell Lymphomas ». Journal of Clinical Oncology 25, n^o 22 (1 août 2007) : 3321–29. http://dx.doi.org/10.1200/jco.2006.09.4474.

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Purpose Nodal peripheral T-cell lymphomas (PTCLs) constitute a heterogeneous group of neoplasms, suggesting the existence of molecular differences contributing to their histologic and clinical variability. Initial expression profiling studies of T-cell lymphomas have been inconclusive in yielding clinically relevant insights. We applied DNA microarrays to gain insight into the molecular signatures associated with prognosis. Materials and Methods We analyzed the expression profiles of 35 nodal PTCLs (23 PTCLs unspecified and 12 angioimmunoblastic) using two different microarray platforms, the cDNA microarray developed at the Spanish National Cancer Centre and an oligonucleotide microarray. Results We identified five clusters of genes, the expression of which varied significantly among the samples. Genes in these clusters seemed to be functionally related to different cellular processes such as proliferation, inflammatory response, and T-cell or B-cell lineages. Regardless of the microarray platform used, overexpression of genes in the proliferation signature was associated significantly with shorter survival of patients. This proliferation signature included genes commonly associated with the cell cycle, such as CCNA, CCNB, TOP2A, and PCNA. Moreover the PTCL proliferation signature showed a statistically significant inverse correlation with clusters of the inflammatory response (P < .0001), as well as with the percentage of CD68+ cells. Conclusion Our findings indicate that proliferation could be an important factor in evaluating nodal PTCL outcome and may help to define a more aggressive phenotype.

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Ray, P. S., J. Wang, Y. Qu, M. Shin-Sim, J. Shamonki, B. Liu, D. S. Hoon, A. E. Giuliano et X. Cui. « Role of FOXC1 in regulation of basal-like/triple-negative breast cancer ». Journal of Clinical Oncology 27, n^o 15_suppl (20 mai 2009) : 11016. http://dx.doi.org/10.1200/jco.2009.27.15_suppl.11016.

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11016 Background: Class identification studies have proposed 3 prognostically relevant molecular subtypes of breast cancer: luminal, HER2 and basal-like. The latter is associated with poor prognosis but its molecular basis is not clear. We hypothesized a direct correlation between FOXC1 expression and basal-like breast cancer. Methods: Expression of FOXC1, CK5, CK14, EGFR, c-Kit, αB-crystallin, ITGB4 and FOXC2 in basal-like breast cancer was examined using publicly available microarray datasets. A molecular signature of 40 genes sharing co-ordinate up or down regulation with FOXC1 was identified on one microarray (49 patients) and validated on 5 other microarrays (1,232 patients). The clinical significance of FOXC1 gene expression and the FOXC1 gene signature was evaluated using censored survival data. FOXC1 protein expression was assessed by immunohistochemistry (IHC) of a 96-sample breast cancer tissue microarray. Normal breast epithelial, luminal and basal breast cancer cells transfected with FOXC1 vectors were evaluated for cell proliferation, migration and invasion. Results: FOXC1 was found to be consistently and exclusively upregulated in basal-like triple negative breast cancer and was associated with poor overall survival (p<0.0001). The FOXC1 gene signature accurately predicted the basal-like phenotype. IHC analysis of FOXC1 protein expression in human breast cancers confirmed its potential to be used as a clinical biomarker of basal-like breast cancer. Normal breast epithelial cells and luminal breast cancer cells with low or no FOXC1 expression underwent epithelial-to-mesenchymal transition and displayed increased cellular proliferation, migration, invasion, and expression of basal cell markers when FOXC1 was overexpressed. In contrast, knockdown of FOXC1 by shRNA in basal-like breast cancer cells conferred luminal phenotype. Breast cancer progression-linked signaling pathways like NF-κB and p38MAPK were significantly stimulated in basal-like breast cancer as well as by in vitro FOXC1 overexpression. Conclusions: FOXC1 is a dominant determinant of the basal-like phenotype of breast cancer. We propose FOXC1 to be the single best molecular marker of and a potential therapeutic target for basal-like / triple negative breast cancer. No significant financial relationships to disclose.

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Paschoalini, Rafael Bispo, Rozany Mucha Dufloth, Francisco Alves Moraes Neto et Fernando C. Schmitt. « Cytological Criteria for Predicting the Luminal Phenotype of Breast Carcinoma ». Acta Cytologica 60, n^o 5 (2016) : 406–12. http://dx.doi.org/10.1159/000448835.

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Background: Specific cytological criteria for the luminal phenotype of breast carcinoma, despite it being the most common and having a better prognosis as well as targeted therapies under study, remain to be established. Using fine-needle aspiration cytology (FNAC), we aimed to identify the luminal phenotype through the evaluation of cytological criteria recognized in routine practice. Methods: We correlated 169 FNACs of breast carcinomas with their tissue specimens, classified into phenotypes by immunohistochemistry (applying tissue microarray technology) as luminal A, luminal B, HER2 overexpression, and triple negative. All FNAC samples were blindly reviewed according to cellularity, cell cohesion, necrosis, nucleoli, and nuclear atypia. Fisher's exact test was used to test associations between the cytological criteria and phenotypes. Results: The following phenotypes were obtained - luminal A: 107 (63.3%), luminal B: 39 (23.1%), HER2 overexpression: 8 (4.7%), and triple negative: 15 (8.9%). The luminal phenotype showed mild/moderate cellularity (40.4%) (OR = 7.12, 95% CI: 1.61-31.52), inconspicuous, present nucleoli (55.5%) (OR = 8.31, 95% CI: 2.36-29.19), and mild/moderate nuclear atypia (44.5%) (OR = 8.42, 95% CI: 1.90-37.25). Conclusion: The criteria that might indicate the luminal phenotype of breast carcinoma in FNAC were mild/moderate cellularity, inconspicuous, present, and nonprominent nucleoli, and mild/moderate nuclear atypia.

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LEE, PHILIP R., JONATHAN E. COHEN, ELISABETTA A. TENDI, ROBERT FARRER, GEORGE H. DE VRIES, KEVIN G. BECKER et R. DOUGLAS FIELDS. « Transcriptional profiling in an MPNST-derived cell line and normal human Schwann cells ». Neuron Glia Biology 1, n^o 2 (mai 2004) : 135–47. http://dx.doi.org/10.1017/s1740925x04000274.

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cDNA microarrays were utilized to identify abnormally expressed genes in a malignant peripheral nerve sheath tumor (MPNST)-derived cell line, T265, by comparing the mRNA abundance profiles with that of normal human Schwann cells (nhSCs). The findings characterize the molecular phenotype of this important cell-line model of MPNSTs, and elucidate the contribution of Schwann cells in MPNSTs. In total, 4608 cDNA sequences were screened and hybridizations replicated on custom cDNA microarrays. In order to verify the microarray data, a large selection of differentially expressed mRNA transcripts were subjected to semi-quantitative reverse transcription PCR (LightCycler). Western blotting was performed to investigate a selection of genes and signal transduction pathways, as a further validation of the microarray data. The data generated from multiple microarray screens, semi-quantitative RT–PCR and Western blotting are in broad agreement. This study represents a comprehensive gene-expression analysis of an MPNST-derived cell line and the first comprehensive global mRNA profile of nhSCs in culture. This study has identified ∼900 genes that are expressed abnormally in the T265 cell line and detected many genes not previously reported to be expressed in nhSCs. The results provide crucial information on the T265 cells that is essential for investigation using this cell line in experimental studies in neurofibromatosis type I (NF1), and important information on normal human Schwann cells that is applicable to a wide range of studies on Schwann cells in cell culture.

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Magbanua, M. M., J. E. Lang, J. Scott, J. R. Crothers, S. Federman, C. Haqq et J. Park. « Gene expression profiling of circulating tumor cells from breast cancer patients ». Journal of Clinical Oncology 24, n^o 18_suppl (20 juin 2006) : 10769. http://dx.doi.org/10.1200/jco.2006.24.18_suppl.10769.

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10769 Background: Levels of circulating tumor cells (CTC) have prognostic and predictive significance in metastatic breast cancer. However, since CTCs are extremely rare, little is known about the actual phenotype of these cells. In order to characterize these cells, we performed cDNA microarray analyses of CTC isolated from peripheral blood (PB) of breast cancer patients. Methods: CTCs were directly isolated via immunomagnetic enrichment (IE) followed by fluorescence activated cell sorting (FACS). Total RNA was then subjected to two rounds of linear amplification and hybridized to cDNA microarrays (∼40,000 cDNAs). Validation studies used spiked BT474 cells. Clinical studies used PB (10–20 ml) from patients with metastatic breast cancer. Results: Rare spiked tumor cells (e.g., 320 cells in 10 mL PB) were efficiently recovered by IE/FACS (50% yield). Expression profiles of recovered cells, both by TaqMan of a 37 gene panel as well as by global gene expression analysis, matched that of BT474 cells in culture. In contrast, these profiles were clearly distinct from that of normal PB, ruling out significant contamination from blood elements. In clinical studies, IE/FACS isolated small numbers of CTCs (10–1000 cells). Expression profiles of CTCs were compared to that of normal blood, primary breast tumors, and normal epithelial samples. Unsupervised hierarchical clustering revealed that CTC profiles were readily distinguished from that of normal blood and normal epithelium; and further analysis revealed that CTC cluster with a subset of primary breast tumors, particularly the basal-like phenotype. Candidate genes associated with the CTC phenotype were also identified. Conclusions: We have developed and validated a method to isolate rare CTCs and profile them via cDNA microarray analysis. In addition, our gene expression analyses of CTC further provide evidence to the malignant nature of these cells. Further expression profiling of CTC may yield insights into their phenotype, pathophysiology and potential as biomarkers. [Table: see text]

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Biyani, Manish, Y. Hosoi, T. Ichiki et N. Nemoto. « 3P075 Genotype-phenotype linked Microarray Evolution Reactor : Construction and screening a new fluorescent protein from random-sequence space ». Seibutsu Butsuri 45, supplement (2005) : S222. http://dx.doi.org/10.2142/biophys.45.s222_3.

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Pecorelli, Alessandra, Guido Leoni, Franco Cervellati, Raffaella Canali, Cinzia Signorini, Silvia Leoncini, Alessio Cortelazzo et al. « Genes Related to Mitochondrial Functions, Protein Degradation, and Chromatin Folding Are Differentially Expressed in Lymphomonocytes of Rett Syndrome Patients ». Mediators of Inflammation 2013 (2013) : 1–18. http://dx.doi.org/10.1155/2013/137629.

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Rett syndrome (RTT) is mainly caused by mutations in the X-linked methyl-CpG binding protein (MeCP2) gene. By binding to methylated promoters on CpG islands, MeCP2 protein is able to modulate several genes and important cellular pathways. Therefore, mutations inMeCP2can seriously affect the cellular phenotype. Today, the pathways thatMeCP2mutations are able to affect in RTT are not clear yet. The aim of our study was to investigate the gene expression profiles in peripheral blood lymphomonocytes (PBMC) isolated from RTT patients to try to evidence new genes and new pathways that are involved in RTT pathophysiology. LIMMA (Linear Models for MicroArray) and SAM (Significance Analysis of Microarrays) analyses on microarray data from 12 RTT patients and 7 control subjects identified 482 genes modulated in RTT, of which 430 were upregulated and 52 were downregulated. Functional clustering of a total of 146 genes in RTT identified key biological pathways related to mitochondrial function and organization, cellular ubiquitination and proteosome degradation, RNA processing, and chromatin folding. Our microarray data reveal an overexpression of genes involved in ATP synthesis suggesting altered energy requirement that parallels with increased activities of protein degradation. In conclusion, these findings suggest that mitochondrial-ATP-proteasome functions are likely to be involved in RTT clinical features.

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Xiong, Jianghui, Juan Liu, Simon Rayner, Yinghui Li et Shanguang Chen. « Protein-Protein Interaction Reveals Synergistic Discrimination of Cancer Phenotype ». Cancer Informatics 9 (janvier 2010) : CIN.S3899. http://dx.doi.org/10.4137/cin.s3899.

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Cancer is a disease associated with the deregulation of multiple gene networks. Microarray data has permitted researchers to identify gene panel markers for diagnosis or prognosis of cancer but these are not sufficient to make specific mechanistic assertions about phenotype switches. We propose a strategy to identify putative mechanisms of cancer phenotypes by protein-protein interactions (PPI). We first extracted the logic status of a PPI via the relative expression of the corresponding gene pair. The joint association of a gene pair on a cancer phenotype was calculated by entropy minimization and assessed using a support vector machine. A typical predictor is “ If Src high-expression, and Cav-1 low-expression, then cancer.“ We achieved 90% accuracy on test data with a majority of predictions associated with the MAPK pathway, focal adhesion, apoptosis and cell cycle. Our results can aid in the development of phenotype discrimination biomarkers and identification of putative therapeutic interference targets for drug development.

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Guard-Bouldin, Jean, Cesar A. Morales, Jonathan G. Frye, Richard K. Gast et Michael Musgrove. « Detection of Salmonella enterica Subpopulations by Phenotype Microarray Antibiotic Resistance Patterns ». Applied and Environmental Microbiology 73, n^o 23 (26 octobre 2007) : 7753–56. http://dx.doi.org/10.1128/aem.01228-07.

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ABSTRACT Three strains of Salmonella enterica serotype Enteritidis were compared to Salmonella enterica serotype Heidelberg, Salmonella enterica serotype Newport, and Salmonella enterica serovar Typhimurium for growth in the presence of 240 antibiotics arranged within a commercial high-throughput phenotype microarray. The results show that antibiotic resistances were different for subpopulations of serotype Enteritidis separated only by genetic drift.

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Hand, Jennifer L., Cassandra K. Runke et Jennelle C. Hodge. « The phenotype spectrum of X-linked ichthyosis identified by chromosomal microarray ». Journal of the American Academy of Dermatology 72, n^o 4 (avril 2015) : 617–27. http://dx.doi.org/10.1016/j.jaad.2014.12.020.

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Vaas, L. A. I., J. Sikorski, B. Hofner, A. Fiebig, N. Buddruhs, H. P. Klenk et M. Goker. « opm : an R package for analysing OmniLog(R) phenotype microarray data ». Bioinformatics 29, n^o 14 (5 juin 2013) : 1823–24. http://dx.doi.org/10.1093/bioinformatics/btt291.

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LEE, Gyoung-Jae, Wan-Seon LEE, Ki-Seon JEON, Chan-Hwi UM, Yang-Suk KIM, Seung-Jun KIM, Chang-Hyeon LEE et al. « cDNA Microarray Gene Expression Analysis and Toxicological Phenotype for Anticancer Drug ». Journal of Veterinary Medical Science 66, n^o 11 (2004) : 1339–45. http://dx.doi.org/10.1292/jvms.66.1339.

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Kumar, Manu, Inyoung Kim, Yeon-Ki Kim, Jae Bok Heo, Mi Chung Suh et Hyun Uk Kim. « Strigolactone Signaling Genes Showing Differential Expression Patterns in Arabidopsis max Mutants ». Plants 8, n^o 9 (19 septembre 2019) : 352. http://dx.doi.org/10.3390/plants8090352.

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Strigolactone (SL) is a recently discovered class of phytohormone that inhibits shoot branching. The molecular mechanism underlying SL biosynthesis, perception, and signal transduction is vital to the plant branching phenotype. Some aspects of their biosynthesis, perception, and signaling include the role of four MORE AXILLARY GROWTH genes, MAX3, MAX4, MAX1, and MAX2. It is important to identify downstream genes that are involved in SL signaling. To achieve this, we studied the genomic aspects of the strigolactone biosynthesis pathway using microarray analysis of four max mutants. We identified SL signaling candidate genes that showed differential expression patterns in max mutants. More specifically, 1-AMINOCYCLOPROPANE-1-CARBOXYLATE SYNTHASE 4 (ACC4) and PROTEIN KINASE 3 (PKS3) displayed contrasting expression patterns, indicating a regulatory mechanism in SL signaling pathway to control different phenotypes apart from branching phenotype.

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Xie, Wanqin, Haiyan Zhou, Lin Zhou, Yun Gong, Jiwu Lin et Yong Chen. « Clinical features and genetic analysis of two Chinese families with X-linked ichthyosis ». Journal of International Medical Research 48, n^o 10 (octobre 2020) : 030006052096229. http://dx.doi.org/10.1177/0300060520962292.

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Objective Recessive X-linked ichthyosis (RXLI) caused by deficiency of the steroid sulfatase gene ( STS) has a reported prevalence of 1/2000 to 1/6000. The present study aimed to characterize the phenotypes and genotypes of two Chinese families with RXLI. Methods The patients were referred to the Family Planning Research Institute of Hunan Province for genetic counseling. Their skin phenotypes were photographed, and venous blood was drawn and used for chromosomal microarray analysis (CMA). Results The skin phenotype of the proband from the first family was characterized by generalized skin dryness and scaling, with noticeable dark brown, polygonal scales on his trunk and extensor surfaces of his extremities. The proband from the second family had an atypical phenotype showing mild skin dryness over his entire body, slight scaling on his abdomen, and small skin fissures on his arms and legs. No mental disability or developmental anomaly was noted in either proband. CMA revealed that both probands carried a 1.4-Mb deletion on chromosome Xp22.31 involving four Online Mendelian Inheritance in Man-listed genes including STS. Conclusions Our findings add knowledge to the genotype and phenotype spectrum of RXLI, which may be helpful in genetic counseling and prenatal diagnosis.

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Goldmann, Oliver, Maren von Köckritz-Blickwede, Claudia Höltje, Gursharan S. Chhatwal, Robert Geffers et Eva Medina. « Transcriptome Analysis of Murine Macrophages in Response to Infection with Streptococcus pyogenes Reveals an Unusual Activation Program ». Infection and Immunity 75, n^o 8 (25 mai 2007) : 4148–57. http://dx.doi.org/10.1128/iai.00181-07.

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ABSTRACT The complex response of murine macrophages to infection with Streptococcus pyogenes was investigated at the level of gene expression with a high-density oligomer microarray. More than 400 genes were identified as being differentially regulated. Many of the up-regulated genes encode molecules involved in the immune response and in inflammation, transcription, signaling, apoptosis, the cell cycle, electron transport, and cell adhesion. Of particular interest was the up-regulation of proinflammatory cytokines, typical of the classically activated macrophages (M1 phenotype), such as tumor necrosis factor alpha, interleukin 1 (IL-1), and IL-6, and as well as the up-regulation of anti-inflammatory mediators, such as IL-1 decoy receptor and IL-10, associated with alternative macrophage activation (M2 phenotype). Furthermore, the gene encoding inducible nitric oxide synthase (iNOS), an enzyme typically implicated in classical activation, was not induced in infected macrophages. Instead, the gene encoding arginase, a competitor for the iNOS substrate arginine involved in the alternative activation pathway, was up-regulated in S. pyogenes-infected cells. Thus, the microarray-based gene expression analysis demonstrated that S. pyogenes induces an atypical activation program in macrophages, with some but not all features of the classical or alternative activation phenotypes. The microarray data also suggested that the bactericidal activity of macrophages against S. pyogenes is mediated by phagocyte oxidase, as p47phox was up-regulated in infected cells. Indeed, the in vivo and in vitro killing of S. pyogenes was markedly diminished in the absence of functional phagocyte (p47 phox−/−) but not in the absence of iNOS (iNOS−/−). An understanding of how macrophages respond to S. pyogenes at the molecular level may facilitate the development of new therapeutic paradigms.

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Cariss, S. James L., Chrystala Constantinidou, Mala D. Patel, Yuiko Takebayashi, Jon L. Hobman, Charles W. Penn et Matthew B. Avison. « YieJ (CbrC) Mediates CreBC-Dependent Colicin E2 Tolerance in Escherichia coli ». Journal of Bacteriology 192, n^o 13 (23 avril 2010) : 3329–36. http://dx.doi.org/10.1128/jb.01352-09.

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ABSTRACT Colicin E2-tolerant (known as Cet2) Escherichia coli K-12 mutants overproduce an inner membrane protein, CreD, which is believed to cause the Cet2 phenotype. Here, we show that overproduction of CreD in a Cet2 strain results from hyperactivation of the CreBC two-component regulator, but CreD overproduction is not responsible for the Cet2 phenotype. Through microarray analysis and gene knockout and overexpression studies, we show that overexpression of another CreBC-regulated gene, yieJ (also known as cbrC), causes the Cet2 phenotype.

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Sabaouni, Imane, Brigitte Vannier, Ahmed Moussa et Azeddine Ibrahimi. « Microarray Integrated Analysis of a Gene Network for the CD36 Myocardial Phenotype ». Bioinformation 12, n^o 06 (30 août 2016) : 332–39. http://dx.doi.org/10.6026/97320630012332.

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Timmons, James A., et Carl Johan Sundberg. « Oligonucleotide microarray expression profiling : Human skeletal muscle phenotype and aerobic exercise training ». IUBMB Life 58, n^o 1 (1 janvier 2006) : 15–24. http://dx.doi.org/10.1080/15216540500507390.

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Ansari, Nadeem A., Riyue Bao, Calin Voichita et Sorin Draghici. « Detecting Phenotype-Specific Interactions between Biological Processes from Microarray Data and Annotations ». IEEE/ACM Transactions on Computational Biology and Bioinformatics 9, n^o 5 (septembre 2012) : 1399–409. http://dx.doi.org/10.1109/tcbb.2012.65.

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Sun, J. R., Y. S. Chiang, H. S. Shang, C. L. Perng, Y. S. Yang et T. S. Chiueh. « Phenotype microarray analysis of the AdeRS two-component system in Acinetobacter baumannii ». European Journal of Clinical Microbiology & ; Infectious Diseases 36, n^o 12 (24 juillet 2017) : 2343–53. http://dx.doi.org/10.1007/s10096-017-3066-9.

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Scolari, Luca M., Robert D. Hancock, Pete E. Hedley, Jenny Morris, Kay Smith et Julie Graham. « Combining QTL Mapping and Gene Expression Analysis to Elucidate the Genetic Control of ‘Crumbly’ Fruit in Red Raspberry (Rubus idaeus L.) ». Agronomy 11, n^o 4 (17 avril 2021) : 794. http://dx.doi.org/10.3390/agronomy11040794.

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‘Crumbly’ fruit is a developmental disorder in raspberry that results in malformed and unsaleable fruits. For the first time, we define two distinct crumbly phenotypes as part of this work. A consistent crumbly fruit phenotype affecting the majority of fruits every season, which we refer to as crumbly fruit disorder (CFD) and a second phenotype where symptoms vary across seasons as malformed fruit disorder (MFD). Here, segregation of crumbly fruit of the MFD phenotype was examined in a full-sib family and three QTL (Quantitative Trait Loci) were identified on a high density GbS (Genotype by Sequencing) linkage map. This included a new QTL and more accurate location of two previously identified QTLs. A microarray experiment using normal and crumbly fruit at three different developmental stages identified several genes that were differentially expressed between the crumbly and non-crumbly phenotypes within the three QTL. Analysis of gene function highlighted the importance of processes that compromise ovule fertilization as triggers of crumbly fruit. These candidate genes provided insights regarding the molecular mechanisms involved in the genetic control of crumbly fruit in red raspberry. This study will contribute to new breeding strategies and diagnostics through the selection of molecular markers associated with the crumbly trait.

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Peng, Yanxiong, Wenyuan Li et Ying Liu. « A Hybrid Approach for Biomarker Discovery from Microarray Gene Expression Data for Cancer Classification ». Cancer Informatics 2 (janvier 2006) : 117693510600200. http://dx.doi.org/10.1177/117693510600200024.

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Microarrays allow researchers to monitor the gene expression patterns for tens of thousands of genes across a wide range of cellular responses, phenotype and conditions. Selecting a small subset of discriminate genes from thousands of genes is important for accurate classification of diseases and phenotypes. Many methods have been proposed to find subsets of genes with maximum relevance and minimum redundancy, which can distinguish accurately between samples with different labels. To find the minimum subset of relevant genes is often referred as biomarker discovery. Two main approaches, filter and wrapper techniques, have been applied to biomarker discovery. In this paper, we conducted a comparative study of different biomarker discovery methods, including six filter methods and three wrapper methods. We then proposed a hybrid approach, FR-Wrapper, for biomarker discovery. The aim of this approach is to find an optimum balance between the precision of the biomarker discovery and the computation cost, by taking advantages of both filter method's efficiency and wrapper method's high accuracy. Our hybrid approach applies Fisher's ratio, a simple method easy to understand and implement, to filter out most of the irrelevant genes, then a wrapper method is employed to reduce the redundancy. The performance of FR-Wrapper approach is evaluated over four widely used microarray datasets. Analysis of experimental results reveals that the hybrid approach can achieve the goal of maximum relevance with minimum redundancy.

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De Majumdar, Shyamasree, Mark Veleba, Sarah Finn, Séamus Fanning et Thamarai Schneiders. « Elucidating the Regulon of Multidrug Resistance Regulator RarA in Klebsiella pneumoniae ». Antimicrobial Agents and Chemotherapy 57, n^o 4 (14 janvier 2013) : 1603–9. http://dx.doi.org/10.1128/aac.01998-12.

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ABSTRACTRarA is an AraC-type regulator inKlebsiella pneumoniae, which, when overexpressed, confers a low-level multidrug-resistant (MDR) phenotype linked to the upregulation of both theacrABandoqxABefflux genes. IncreasedrarAexpression has also been shown to be integral in the development of tigecycline resistance in the absence oframAinK. pneumoniae. Given its phenotypic role in MDR, microarray analyses were performed to determine the RarA regulon. Transcriptome analysis was undertaken using strains Ecl8ΔrarA/pACrarA-2 (rarA-expressing construct) and Ecl8ΔrarA/pACYC184 (vector-only control) using bespoke microarray slides consisting of probes derived from the genomic sequences ofK. pneumoniaeMGH 78578 (NC_009648.1) and Kp342 (NC_011283.1). Our results show thatrarAoverexpression resulted in the differential expression of 66 genes (42 upregulated and 24 downregulated). Under the COG (clusters of orthologous groups) functional classification, the majority of affected genes belonged to the category of cell envelope biogenesis and posttranslational modification, along with genes encoding the previously uncharacterized transport proteins (e.g., KPN_03141,sdaCB, andleuE) and the porin OmpF. However, genes associated with energy production and conversion and amino acid transport/metabolism (e.g.,nuoA,narJ, andproWX) were found to be downregulated. Biolog phenotype analyses demonstrated thatrarAoverexpression confers enhanced growth of the overexpresser in the presence of several antibiotic classes (i.e., beta-lactams and fluoroquinolones), the antifungal/antiprotozoal compound clioquinol, disinfectants (8-hydroxyquinoline), protein synthesis inhibitors (i.e., minocycline and puromycin), membrane biogenesis agents (polymyxin B and amitriptyline), DNA synthesis (furaltadone), and the cytokinesis inhibitor (sanguinarine). Both our transcriptome and phenotypic microarray data support and extend the role of RarA in the MDR phenotype ofK. pneumoniae.

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Morales, Cesar A., Steffen Porwollik, Jonathan G. Frye, Hailu Kinde, Michael McClelland et Jean Guard-Bouldin. « Correlation of Phenotype with the Genotype of Egg-Contaminating Salmonella enterica Serovar Enteritidis ». Applied and Environmental Microbiology 71, n^o 8 (août 2005) : 4388–99. http://dx.doi.org/10.1128/aem.71.8.4388-4399.2005.

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ABSTRACT The genotype of Salmonella enterica serovar Enteritidis was correlated with the phenotype using DNA-DNA microarray hybridization, ribotyping, and Phenotype MicroArray analysis to compare three strains that differed in colony morphology and phage type. No DNA hybridization differences were found between two phage type 13A (PT13A) strains that varied in biofilm formation; however, the ribotype patterns were different. Both PT13A strains had DNA sequences similar to that of bacteriophage Fels2, whereas the PT4 genome to which they were compared, as well as a PT4 field isolate, had a DNA sequence with some similarity to the bacteriophage ST64b sequence. Phenotype MicroArray analysis indicated that the two PT13A strains and the PT4 field isolate had similar respiratory activity profiles at 37°C. However, the wild-type S. enterica serovar Enteritidis PT13A strain grew significantly better in 20% more of the 1,920 conditions tested when it was assayed at 25°C than the biofilm-forming PT13A strain grew. Statistical analysis of the respiratory activity suggested that S. enterica serovar Enteritidis PT4 had a temperature-influenced dimorphic metabolism which at 25°C somewhat resembled the profile of the biofilm-forming PT13A strain and that at 37°C the metabolism was nearly identical to that of the wild-type PT13A strain. Although it is possible that lysogenic bacteriophage alter the balance of phage types on a farm either by lytic competition or by altering the metabolic processes of the host cell in subtle ways, the different physiologies of the S. enterica serovar Enteritidis strains correlated most closely with minor, rather than major, genomic changes. These results strongly suggest that the pandemic of egg-associated human salmonellosis that came into prominence in the 1980s is primarily an example of bacterial adaptive radiation that affects the safety of the food supply.

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Dinu, Irina, Qi Liu, John D. Potter, Adeniyi J. Adewale, Gian S. Jhangri, Thomas Mueller, Gunilla Einecke, Konrad Famulsky, Philip Halloran et Yutaka Yasui. « A Biological Evaluation of Six Gene Set Analysis Methods for Identification of Differentially Expressed Pathways in Microarray Data ». Cancer Informatics 6 (janvier 2008) : CIN.S867. http://dx.doi.org/10.4137/cin.s867.

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Gene-set analysis of microarray data evaluates biological pathways, or gene sets, for their differential expression by a phenotype of interest. In contrast to the analysis of individual genes, gene-set analysis utilizes existing biological knowledge of genes and their pathways in assessing differential expression. This paper evaluates the biological performance of five gene-set analysis methods testing “self-contained null hypotheses” via subject sampling, along with the most popular gene-set analysis method, Gene Set Enrichment Analysis (GSEA). We use three real microarray analyses in which differentially expressed gene sets are predictable biologically from the phenotype. Two types of gene sets are considered for this empirical evaluation: one type contains “truly positive” sets that should be identified as differentially expressed; and the other type contains “truly negative” sets that should not be identified as differentially expressed. Our evaluation suggests advantages of SAM-GS, Global, and ANCOVA Global methods over GSEA and the other two methods.

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Espirito Santo, Layla Damasceno, Lília Maria Azevedo Moreira et Mariluce Riegel. « Cri-Du-Chat Syndrome : Clinical Profile and Chromosomal Microarray Analysis in Six Patients ». BioMed Research International 2016 (2016) : 1–9. http://dx.doi.org/10.1155/2016/5467083.

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Cri-du-chat syndrome is a chromosomal disorder caused by a deletion of the short arm of chromosome 5. The disease severity, levels of intellectual and developmental delay, and patient prognosis have been related to the size and position of the deletion. Aiming to establish genotype-phenotype correlations, we applied array-CGH to evaluate six patients carrying cytogenetically detected deletions of the short arm of chromosome 5 who were followed at a genetics community service. The patients’ cytogenetic and clinical profiles were reevaluated. A database review was performed to predict additional genes and regulatory elements responsible for the characteristic phenotypic and behavioral traits of this disorder. Array-CGH analysis allowed for delineation of the terminal deletions, which ranged in size from approximately 11.2 Mb to 28.6 Mb, with breakpoints from 5p15.2 to 5p13. An additional dup(8)(p23) (3.5 Mb), considered to be a benign copy number variation, was also observed in one patient. The correlation coefficient value(ρ=0.13)calculated indicated the presence of a weak relationship between developmental delay and deletion size. Genetic background, family history, epigenetic factors, quantitative trait locus polymorphisms, and environmental factors may also affect patient phenotype and must be taken into account in genotype-phenotype correlations.

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Carvalho, Luiz Joaquim Castelo Branco, Eduardo Alano Vieira, Josefino de Freitas Fialho et Claudia Regina Batista de Souza. « A genomic assisted breeding program for cassava to improve nutritional quality and industrial traits of storage root ». Crop Breeding and Applied Biotechnology 11, n^o 4 (décembre 2011) : 289–96. http://dx.doi.org/10.1590/s1984-70332011000400001.

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Cassava is cultivated for two ends proposals: "sweet cassava" as fresh consumes and "industry cassava" as source of starch and farina. Landraces were used to discover "spontaneous mutations" and to develop evolutionary and breeding perspective of gene function. Genomic and Proteomic resources were obtained. Gene expression by RNA blot and Microarray analysis were performed to identify differentially expressed genes. A new sugary cassava was identified to be related to missing expression of BEI and a nonsense mutation in GBSSI gene leading to amylose free starch. A pink phenotype showed no expression of CasLYB gene, and a yellow phenotype a down regulation of CasHYb. Proteomic analysis of carotenoid-protein complex together with gene expression analysis of CAP4 revealed a heteroduplex double strand cDNA associated with high carotenoid content. GBSSI gene sequencing identified 22 haplotypes and large nucleotide diversity. Segregating populations by crossing differential biochemical phenotypes and parents adapted to Cerrado's Region were obtained.

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ZHANG, YUANYUAN, SHUDONG WANG, MEIXI YANG, DASHUN XU et DAZHI MENG. « A NEW METHOD OF DETERMINING THRESHOLD OF GENE NETWORK BASED ON PHENOTYPES ». Journal of Biological Systems 19, n^o 04 (décembre 2011) : 607–16. http://dx.doi.org/10.1142/s0218339011004068.

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With the rapid growth of microarray data, it has become a hot topic to reveal complex behaviors and functions of life system by studying the relationships among genes. In the process of reverse network modeling, the relationships with less relevance are generally not considered by determining a threshold when the relationships among genes are mined. However, there are no effective methods to determine the threshold up to now. It is worthwhile to note that the phenotypes of genetic diseases are generally regarded as external representation of the functions of genes. Therefore, two types of phenotype networks are constructed from gene and disease views, respectively, and through comparing these two types of phenotype networks, the threshold of gene network corresponding to a certain disease can be determined when their similarity reaches to maximum. Because the gene network is determined based on the relationships among phenotypes and phenotypes are external representation of the functions of genes, it is considered that relationships in the gene network may show functional relationships among genes in biological system. In this work, the thresholds 0.47 and 0.48 of gene network are determined based on Parkinson disease phenotypes. Furthermore, the validity of these thresholds is verified by the specificity and susceptibility of phenotype networks. Also, through comparing the structural parameters of gene networks for normal and disease stage at different thresholds, significant difference between the two gene networks at threshold 0.47 or 0.48 is found. The significant difference of structural parameters further verifies the efficiency of this method.

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Biondi, Emanuele G., Enrico Tatti, Diego Comparini, Elisa Giuntini, Stefano Mocali, Luciana Giovannetti, Marco Bazzicalupo, Alessio Mengoni et Carlo Viti. « Metabolic Capacity of Sinorhizobium (Ensifer) meliloti Strains as Determined by Phenotype MicroArray Analysis ». Applied and Environmental Microbiology 75, n^o 16 (26 juin 2009) : 5396–404. http://dx.doi.org/10.1128/aem.00196-09.

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ABSTRACT Sinorhizobium meliloti is a soil bacterium that fixes atmospheric nitrogen in plant roots. The high genetic diversity of its natural populations has been the subject of extensive analysis. Recent genomic studies of several isolates revealed a high content of variable genes, suggesting a correspondingly large phenotypic differentiation among strains of S. meliloti. Here, using the Phenotype MicroArray (PM) system, hundreds of different growth conditions were tested in order to compare the metabolic capabilities of the laboratory reference strain Rm1021 with those of four natural S. meliloti isolates previously analyzed by comparative genomic hybridization (CGH). The results of PM analysis showed that most phenotypic differences involved carbon source utilization and tolerance to osmolytes and pH, while fewer differences were scored for nitrogen, phosphorus, and sulfur source utilization. Only the variability of the tested strain in tolerance to sodium nitrite and ammonium sulfate of pH 8 was hypothesized to be associated with the genetic polymorphisms detected by CGH analysis. Colony and cell morphologies and the ability to nodulate Medicago truncatula plants were also compared, revealing further phenotypic diversity. Overall, our results suggest that the study of functional (phenotypic) variability of S. meliloti populations is an important and complementary step in the investigation of genetic polymorphism of rhizobia and may help to elucidate rhizobial evolutionary dynamics, including adaptation to diverse environments.

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Vaas, Lea A. I., Johannes Sikorski, Victoria Michael, Markus Göker et Hans-Peter Klenk. « Visualization and Curve-Parameter Estimation Strategies for Efficient Exploration of Phenotype Microarray Kinetics ». PLoS ONE 7, n^o 4 (20 avril 2012) : e34846. http://dx.doi.org/10.1371/journal.pone.0034846.

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Huestis, Diana L., et Jeremy L. Marshall. « From Gene Expression to Phenotype in Insects : Non-microarray Approaches for Transcriptome Analysis ». BioScience 59, n^o 5 (mai 2009) : 373–84. http://dx.doi.org/10.1525/bio.2009.59.5.5.

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Irby, Rosalyn B., Renae L. Malek, Greg Bloom, Jennifer Tsai, Noah Letwin, Bryan C. Frank, Kathleen Verratti, Timothy J. Yeatman et Norman H. Lee. « Iterative Microarray and RNA Interference–Based Interrogation of the Src-Induced Invasive Phenotype ». Cancer Research 65, n^o 5 (1 mars 2005) : 1814–21. http://dx.doi.org/10.1158/0008-5472.can-04-3609.

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Yamasaki, Seiji, Takuma Fujioka, Katsuhiko Hayashi, Suguru Yamasaki, Mitsuko Hayashi-Nishino et Kunihiko Nishino. « Phenotype microarray analysis of the drug efflux systems in Salmonella enterica serovar Typhimurium ». Journal of Infection and Chemotherapy 22, n^o 11 (novembre 2016) : 780–84. http://dx.doi.org/10.1016/j.jiac.2016.03.015.

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