Journal articles: 'Phenotype Microarry'

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Wang, Mengyu, Jingfang Ju, Stein Saeboe-Larssen, Svein-Ole Mikalsen, Elena Olsen, Jahn M. Nesland, Oystein Fodstad, Gunhild Maelandsmo, and Gunnar Kvalheim. "Characterization of a Bone Marrow Derived Mesenchymal Cell Line from Nude Rat Assembling Tumor Stem/Progenitor Cell Properties In Vitro and In Vivo." Blood 108, no. 11 (November 16, 2006): 4256. http://dx.doi.org/10.1182/blood.v108.11.4256.4256.

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Abstract Here we report the in vitro and in vivo properties of a spontaneously transformed nude rat mesenchymal stem cells (rTMSCs) following culture passages 23. When this cell line was compared with early passages of mesenchymal cells (rMSCs) from the same animal, no apparent differences could be seen with regard to the phenotype and Gap junctions’ connexin 43. However, the telomerase activity in rTMSCs is lower than in the rMSCs. Karyotyping of rTMSC gave a trisome 6 phenotype. Microarry analysis of rTMSC shows over expression of the transforming growth factor family including TGF-beta and BMp6. Both rMSC and rTMSC had equal capability to differentiate into adipocytic and “neural like” linage. In contrast rTMSC was unable to differentiate into bone and only this cell line form spheroids in cultures. Subcutaneously injection of rTMSC in doses down to 2x 104 into nude/nude mice formed tumor in all animals tested. Examination of the tumor assembles morphology like an immature sarcoma. When 100–200 SP + cells were administered to the animals, tumor could also be formed. After intravenous injections and direct injections into left heart ventricle all animals developed metastasis in the lung; abdominal cavity; bone and skin. The rTMSC has been stabled marked with reporter gene GFP and Leucipherase. Currently the proliferation and migration capacity of the linage-differentiated rTMSC is studied in vivo by imaging and these results will be presented. We conclude that our normal and transformed rMSCs could be potential useful for further biological studies on mesenchymal cells both in vitro and in vivo.

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De, Supriyo, Yongqing Zhang, John R. Garner, S. Alex Wang, and Kevin G. Becker. "Disease and phenotype gene set analysis of disease-based gene expression in mouse and human." Physiological Genomics 42A, no. 2 (October 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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Ameen, Sirwan Muhsin Muhammed Ameen. "High throughput Phenotypic Microarray profiling of Mycobacterium abscessus." Journal of Zankoy Sulaimani - Part A 20, no. 2 (June 20, 2018): 9–20. http://dx.doi.org/10.17656/jzs.10720.

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von Eiff, Christof, Peter McNamara, Karsten Becker, Donna Bates, Xiang-He Lei, Michael Ziman, Barry R. Bochner, Georg Peters, and Richard A. Proctor. "Phenotype Microarray Profiling of Staphylococcus aureus menD and hemB Mutants with the Small-Colony-Variant Phenotype." Journal of Bacteriology 188, no. 2 (January 15, 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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Bochner, B. R. "Phenotype MicroArrays for High-Throughput Phenotypic Testing and Assay of Gene Function." Genome Research 11, no. 7 (July 1, 2001): 1246–55. http://dx.doi.org/10.1101/gr.186501.

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Card, Roderick, Jiancheng Zhang, Priya Das, Charlotte Cook, Neil Woodford, and 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, no. 1 (November 5, 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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Paschoalini, Rafael Bispo, Rozany Mucha Dufloth, Francisco Alves Moraes Neto, and Fernando C. Schmitt. "Cytological Criteria for Predicting the Luminal Phenotype of Breast Carcinoma." Acta Cytologica 60, no. 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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Çebi, Alper Han, and 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, no. 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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Biyani, Manish, Y. Hosoi, T. Ichiki, and 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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Zhou, Lu, Xiang-He Lei, Barry R. Bochner, and Barry L. Wanner. "Phenotype MicroArray Analysis of Escherichia coli K-12 Mutants with Deletions of All Two-Component Systems." Journal of Bacteriology 185, no. 16 (August 15, 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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Xuan, Jianhua. "Cross phenotype normalization of microarray data." Frontiers in Bioscience E2, no. 1 (2010): 171–86. http://dx.doi.org/10.2741/e80.

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TOHSATO, YUKAKO, TOMOYA BABA, YUSAKU MAZAKI, MASAHIRO ITO, BARRY L. WANNER, and HIROTADA MORI. "ENVIRONMENTAL DEPENDENCY OF GENE KNOCKOUTS ON PHENOTYPE MICROARRAY ANALYSIS IN ESCHERICHIA COLI." Journal of Bioinformatics and Computational Biology 08, supp01 (December 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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Gerstgrasser, Matthias, Sarah Nicholls, Michael Stout, Katherine Smart, Chris Powell, Theodore Kypraios, and Dov Stekel. "A Bayesian approach to analyzing phenotype microarray data enables estimation of microbial growth parameters." Journal of Bioinformatics and Computational Biology 14, no. 03 (June 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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LEE, PHILIP R., JONATHAN E. COHEN, ELISABETTA A. TENDI, ROBERT FARRER, GEORGE H. DE VRIES, KEVIN G. BECKER, and R. DOUGLAS FIELDS. "Transcriptional profiling in an MPNST-derived cell line and normal human Schwann cells." Neuron Glia Biology 1, no. 2 (May 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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Xie, Wanqin, Haiyan Zhou, Lin Zhou, Yun Gong, Jiwu Lin, and Yong Chen. "Clinical features and genetic analysis of two Chinese families with X-linked ichthyosis." Journal of International Medical Research 48, no. 10 (October 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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Seta, Karen A., and David E. Millhorn. "Functional genomics approach to hypoxia signaling." Journal of Applied Physiology 96, no. 2 (February 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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Bochner, Barry, Vanessa Gomez, Michael Ziman, Shihui Yang, and Steven D. Brown. "Phenotype MicroArray Profiling of Zymomonas mobilis ZM4." Applied Biochemistry and Biotechnology 161, no. 1-8 (December 12, 2009): 116–23. http://dx.doi.org/10.1007/s12010-009-8842-2.

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Bhattacharya, Soumyaroop, and Thomas J. Mariani. "Array of hope: expression profiling identifies disease biomarkers and mechanism." Biochemical Society Transactions 37, no. 4 (July 22, 2009): 855–62. http://dx.doi.org/10.1042/bst0370855.

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High-throughput, genome-wide analytical technologies are now commonly used in all fields of medical research. The most commonly applied of these technologies, gene expression microarrays, have been shown to be both accurate and precise when properly implemented. For over a decade, microarrays have provided novel insight into many complex human diseases. Microarray-based discovery can be classified into three components, biomarker detection, disease (sub)classification and identification of causal mechanism, in order of accomplishment. Within the respiratory system, the application of microarrays has achieved significant success in all components, particularly with respect to lung cancer. Numerous studies over the last half-decade have applied this technology to the characterization of non-malignant respiratory diseases, animal models of respiratory disease and normal developmental processes. Studies of obstructive lung diseases by many groups, including our own, have yielded not only disease biomarkers, but also some novel putative pathogenic mechanisms. We have successfully used an integrative genomics approach, combining microarray analysis with human genetics, to identify susceptibility genes for COPD (chronic obstructive pulmonary disease). Interestingly, we find that the assessment of quantitative phenotypic variables enhances gene discovery. Our studies contribute to the identification of obstructive lung disease biomarkers, provide data associated with disease phenotypes and support the use of an integrated approach to move beyond marker identification to mechanism discovery.

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Kwon, Yong-Jun, Jin Heo, Hi Kim, Jin Kim, Michel Liuzzi, and Veronica Soloveva. "Phenotypic MicroRNA Microarrays." Microarrays 2, no. 2 (April 3, 2013): 63–80. http://dx.doi.org/10.3390/microarrays2020063.

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ZHANG, YUANYUAN, SHUDONG WANG, MEIXI YANG, DASHUN XU, and DAZHI MENG. "A NEW METHOD OF DETERMINING THRESHOLD OF GENE NETWORK BASED ON PHENOTYPES." Journal of Biological Systems 19, no. 04 (December 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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Scolari, Luca M., Robert D. Hancock, Pete E. Hedley, Jenny Morris, Kay Smith, and 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, no. 4 (April 17, 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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Kumar, Manu, Inyoung Kim, Yeon-Ki Kim, Jae Bok Heo, Mi Chung Suh, and Hyun Uk Kim. "Strigolactone Signaling Genes Showing Differential Expression Patterns in Arabidopsis max Mutants." Plants 8, no. 9 (September 19, 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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Xiong, Jianghui, Juan Liu, Simon Rayner, Yinghui Li, and Shanguang Chen. "Protein-Protein Interaction Reveals Synergistic Discrimination of Cancer Phenotype." Cancer Informatics 9 (January 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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Tart, Anne H., Matthew C. Wolfgang, and Daniel J. Wozniak. "The Alternative Sigma Factor AlgT Represses Pseudomonas aeruginosa Flagellum Biosynthesis by Inhibiting Expression of fleQ." Journal of Bacteriology 187, no. 23 (December 1, 2005): 7955–62. http://dx.doi.org/10.1128/jb.187.23.7955-7962.2005.

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ABSTRACT Pseudomonas aeruginosa poses a serious risk in individuals suffering from cystic fibrosis (CF). Strains colonizing the CF lung are generally motile but frequently convert to a nonmotile phenotype as the disease progresses. In many cases, this is coordinately regulated with the overproduction of the exopolysaccharide alginate. Both the expression of alginate (mucoidy) and the loss of flagellum synthesis may provide the bacterium with a selective advantage in the CF lung. Previously published data showed that the regulation of alginate production and flagellum biosynthesis in the CF isolate FRD1 is inversely controlled by the alternative sigma factor AlgT. In this study, we observed that in CF isolates, the mucoid and the nonmotile phenotypes occur predominantly together. Using microarrays, we compared the transcriptomes of isogenic AlgT+ and AlgT− P. aeruginosa and discovered that AlgT significantly downregulated the majority of flagellar genes. A pronounced inhibitory effect was observed in several genes essential for proper flagellum expression, including fleQ, which encodes an essential flagellar regulator. The microarray data were confirmed by reverse transcriptase PCR analysis and promoter fusion assays in isogenic AlgT+ and AlgT− strains. Transmission electron microscopy, motility assays, and Western blots showed that ectopic expression of FleQ in mucoid, nonmotile CF isolates restored flagellum biosynthesis and motility. Together, these data show that AlgT mediates the negative control of flagellum expression by inhibiting the expression of the flagellar regulator fleQ.

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Peng, Yanxiong, Wenyuan Li, and Ying Liu. "A Hybrid Approach for Biomarker Discovery from Microarray Gene Expression Data for Cancer Classification." Cancer Informatics 2 (January 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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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, no. 22 (August 1, 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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Schüller, Christoph, Yasmine M. Mamnun, Mehdi Mollapour, Gerd Krapf, Michael Schuster, Bettina E. Bauer, Peter W. Piper, and Karl Kuchler. "Global Phenotypic Analysis and Transcriptional Profiling Defines the Weak Acid Stress Response Regulon inSaccharomyces cerevisiae." Molecular Biology of the Cell 15, no. 2 (February 2004): 706–20. http://dx.doi.org/10.1091/mbc.e03-05-0322.

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Weak organic acids such as sorbate are potent fungistatic agents used in food preservation, but their intracellular targets are poorly understood. We thus searched for potential target genes and signaling components in the yeast genome using contemporary genome-wide functional assays as well as DNA microarray profiling. Phenotypic screening of the EUROSCARF collection revealed the existence of numerous sorbate-sensitive strains. Sorbate hypersensitivity was detected in mutants of the shikimate biosynthesis pathway, strains lacking the PDR12 efflux pump or WAR1, a transcription factor mediating stress induction of PDR12. Using DNA microarrays, we also analyzed the genome-wide response to acute sorbate stress, allowing for the identification of more than 100 genes rapidly induced by weak acid stress. Moreover, a novel War1p- and Msn2p/4p-independent regulon that includes HSP30 was identified. Although induction of the majority of sorbate-induced genes required Msn2p/4p, weak acid tolerance was unaffected by a lack of Msn2p/4p. Ectopic expression of PDR12 from the GAL1-10 promoter fully restored sorbate resistance in a strain lacking War1p, demonstrating that PDR12 is the major target of War1p under sorbic acid stress. Interestingly, comparison of microarray data with results from the phenotypic screening revealed that PDR12 remained as the only gene, which is both stress inducible and required for weak acid resistance. Our results suggest that combining functional assays with transcriptome profiling allows for the identification of key components in large datasets such as those generated by global microarray analysis.

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Magbanua, M. M., J. E. Lang, J. Scott, J. R. Crothers, S. Federman, C. Haqq, and J. Park. "Gene expression profiling of circulating tumor cells from breast cancer patients." Journal of Clinical Oncology 24, no. 18_suppl (June 20, 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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Khatri, Bhagwati, Mark Fielder, Gareth Jones, William Newell, Manal Abu-Oun, and Paul R. Wheeler. "High Throughput Phenotypic Analysis of Mycobacterium tuberculosis and Mycobacterium bovis Strains' Metabolism Using Biolog Phenotype Microarrays." PLoS ONE 8, no. 1 (January 10, 2013): e52673. http://dx.doi.org/10.1371/journal.pone.0052673.

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Viti, Carlo, Enrico Tatti, and Luciana Giovannetti. "Phenotype MicroArray analysis of cells: fulfilling the promise." Research in Microbiology 167, no. 9-10 (November 2016): 707–9. http://dx.doi.org/10.1016/j.resmic.2016.08.003.

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Ray, P. S., J. Wang, Y. Qu, M. Shin-Sim, J. Shamonki, B. Liu, D. S. Hoon, A. E. Giuliano, and X. Cui. "Role of FOXC1 in regulation of basal-like/triple-negative breast cancer." Journal of Clinical Oncology 27, no. 15_suppl (May 20, 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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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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Liao, Ben-Yang, and Meng-Pin Weng. "Unraveling the association between mRNA expressions and mutant phenotypes in a genome-wide assessment of mice." Proceedings of the National Academy of Sciences 112, no. 15 (March 30, 2015): 4707–12. http://dx.doi.org/10.1073/pnas.1415046112.

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High-throughput gene expression profiling has revealed substantial leaky and extraneous transcription of eukaryotic genes, challenging the perceptions that transcription is strictly regulated and that changes in transcription have phenotypic consequences. To assess the functional implications of mRNA transcription directly, we analyzed mRNA expression data derived from microarrays, RNA-sequencing, and in situ hybridization, together with phenotype data of mouse mutants as a proxy of gene function at the tissue level. The results indicated that despite the presence of widespread ectopic transcription, mRNA expression and mutant phenotypes of mammalian genes or tissues remain associated. The expression-phenotype association at the gene level was particularly strong for tissue-specific genes, and the association could be underestimated due to data insufficiency and incomprehensive phenotyping of mouse mutants; the strength of expression-phenotype association at the tissue level depended on tissue functions. Mutations on genes expressed at higher levels or expressed at earlier embryonic stages more often result in abnormal phenotypes in the tissues where they are expressed. The mRNA expression profiles that have stronger associations with their phenotype profiles tend to be more evolutionarily conserved, indicating that the evolution of transcriptome and the evolution of phenome are coupled. Therefore, mutations resulting in phenotypic aberrations in expressed tissues are more likely to occur in highly transcribed genes, tissue-specific genes, genes expressed during early embryonic stages, or genes with evolutionarily conserved mRNA expression profiles.

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Ball, S. L., S. J. Cockell, J. A. Wilson, D. A. Mann, and A. J. Fisher. "Microarray analysis of primary epithelial and fibroblast cells in chronic rhinosinusitis without nasal polyps." Rhinology journal 58, no. 6 (December 1, 2020): 581–87. http://dx.doi.org/10.4193/rhin19.319.

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Background: Chronic rhinosinusitis is an inflammatory condition with an as yet unknown pathophysiology. We aimed to detect clusters of differentially regulated genes in the epithelial and fibroblast cells of patients with Chronic Rhinosinusitis without nasal polyposis (CRSsNP) and healthy controls. Methodology: Carefully phenotyped CRSsNP and healthy control participants were recruited. Primary cultures of isolated epithelial and fibroblast cells were established. Whole transcriptome analysis of the cells was performed using microarrays and replicated with quantitative RT-PCR and immunohistochemistry. Results: Fibroblast cells from CRSsNP patients showed a significant upregulation (more than 2x) of the transcription factor NFE2L3 when compared to healthy controls by microarray with multiple hypothesis testing correction, qRT-PCR and immunohistochemistry. Conclusions: Here we have utilized microarray analysis to search for differentially expressed genes in isolated patient derived epithelial and fibroblast cells. The transcription factor NFE2L3 has been shown to be upregulated in fibroblast cells consistent with increasing evidence that fibroblasts play a key role in tissue specific inflammation within the paranasal sinuses.

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Pantazatos, Spiro P., Jianrong Li, Paul Pavlidis, and Yves A. Lussier. "Integration of Neuroimaging and Microarray Datasets through Mapping and Model-Theoretic semantic Decomposition of Unstructured phenotypes." Cancer Informatics 8 (January 2009): CIN.S1046. http://dx.doi.org/10.4137/cin.s1046.

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An approach towards heterogeneous neuroscience dataset integration is proposed that uses Natural Language Processing (NLP) and a knowledge-based phenotype organizer system (PhenOS) to link ontology-anchored terms to underlying data from each database, and then maps these terms based on a computable model of disease (SNOMED CT®). The approach was implemented using sample datasets from fMRIDC, GEO, The Whole Brain Atlas and Neuronames, and allowed for complex queries such as “List all disorders with a finding site of brain region X, and then find the semantically related references in all participating databases based on the ontological model of the disease or its anatomical and morphological attributes”. Precision of the NLP-derived coding of the unstructured phenotypes in each dataset was 88% (n = 50), and precision of the semantic mapping between these terms across datasets was 98% (n = 100). To our knowledge, this is the first example of the use of both semantic decomposition of disease relationships and hierarchical information found in ontologies to integrate heterogeneous phenotypes across clinical and molecular datasets.

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Zhang, Simin, Jingjing Wang, Yan Pei, Jijing Han, Xiaowei Xiong, Yani Yan, Juan Zhang, et al. "Diagnostic Value of Chromosomal Microarray Analysis for Fetal Congenital Heart Defects with Different Cardiac Phenotypes and Extracardiac Abnormalities." Diagnostics 13, no. 8 (April 20, 2023): 1493. http://dx.doi.org/10.3390/diagnostics13081493.

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(1) Background: The objective of this study was to investigate the diagnostic value of chromosomal microarray analysis (CMA) for congenital heart defects (CHDs) with different cardiac phenotypes and extracardiac abnormalities (ECAs) and to explore the pathogenic genetic factors of CHDs. (2) Methods: We collected fetuses diagnosed with CHDs by echocardiography at our hospital from January 2012 to December 2021. We analyzed the CMA results of 427 fetuses with CHDs. We then categorized the CHD into different groups according to two dimensions: different cardiac phenotypes and whether it was combined with ECAs. The correlation between the numerical chromosomal abnormalities (NCAs) and copy number variations (CNVs) with CHDs was analyzed. Statistical analyses, including Chi-square tests and t-tests, were performed on the data using IBM SPSS and GraphPad Prism. (3) Results: In general, CHDs with ECAs increased the detection rate for CA, especially the conotruncal defects. CHD combined with the thoracic and abdominal walls and skeletal, thymic and multiple ECAs, were more likely to exhibit CA. Among the CHD phenotypes, VSD and AVSD were associated with NCA, while DORV may be associated with NCA. The cardiac phenotypes associated with pCNVs were IAA (type A and B), RAA, TAPVC, CoA and TOF. In addition, IAA, B, RAA, PS, CoA and TOF were also associated with 22q11.2DS. The length distribution of the CNV was not significantly different between each CHD phenotype. We detected twelve CNV syndromes, of which six syndromes may be related to CHDs. The pregnancy outcome in this study suggests that termination of pregnancy with fetal VSD and vascular abnormality is more dependent on genetic diagnosis, whereas the outcome in other phenotypes of CHDs may be associated with other additional factors. (4) Conclusions: CMA examination for CHDs is still necessary. We should identify the existence of fetal ECAs and specific cardiac phenotypes, which are helpful for genetic counseling and prenatal diagnosis.

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Suzuki, Hiroaki, Tadakazu Hisamatsu, Makoto Naganuma, Hirotoshi Ebinuma, Nobuhiro Nakamoto, Kiyoto Mori, Mina Kitazume, Katsuyoshi Shimamura, Sayako Chiba, and Takanori Kanai. "Glycolysis regulates macrophage differentiation into IL-10 producing phenotype (INM6P.342)." Journal of Immunology 194, no. 1_Supplement (May 1, 2015): 193.16. http://dx.doi.org/10.4049/jimmunol.194.supp.193.16.

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Abstract There are a lot of reports indicating that cellular metabolic state or some metabolites regulate the phenotype of immune cells. In case of macrophages (Mφ), it is believed that regulatory and inflammatory Mφ shifts ATP production to each oxidative phosphorylation and glycolysis, respectively. However, it is not clear how metabolic pathway affects Mφ in the acquisition of their specific phenotypes. In this report, we tried to reveal how glycolysis affects Mφ during the acquisition of IL-10 producing phenotype. We used in vitro differentiated human monocyte derived Mφ cultured in the presence of M-CSF or M-CSF plus IFNγ as IL-10 producing-Mφ (M-Mφ) or inflammatory Mφ (Mγ-Mφ), respectively. M-Mφ showed regulatory Mφ-like phenotypes and produced more IL-10 when it was stimulated with LPS compared to Mγ-Mφ. Interestingly, M-Mφ differentiated with glycolysis inhibitors (2-deoxy-D-glucose or DCA) produced significantly lower amount of IL-10 and lager amount of IL-6 compared to M-Mφ differentiated without glycolysis inhibitors. Glycolysis inhibited M-Mφ reduced the expression of regulatory Mφ marker genes (MRC1 and CCL22) and exhibited distinct pattern of cell surface antigens (CD163, CD206, CD209 and HLA-DR) compared to M-Mφ. DNA microarray analysis revealed that inhibition of glycolysis affects gene expression profiles during Mφ differentiation. Our finding suggests that glycolysis plays key roles in the course of differentiation of Mφ into IL-10 producing phenotype.

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Makbul, Cihan, Vladimir Khayenko, Hans Michael Maric, and Bettina Böttcher. "Conformational Plasticity of Hepatitis B Core Protein Spikes Promotes Peptide Binding Independent of the Secretion Phenotype." Microorganisms 9, no. 5 (April 29, 2021): 956. http://dx.doi.org/10.3390/microorganisms9050956.

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Hepatitis B virus is a major human pathogen, which forms enveloped virus particles. During viral maturation, membrane-bound hepatitis B surface proteins package hepatitis B core protein capsids. This process is intercepted by certain peptides with an “LLGRMKG” motif that binds to the capsids at the tips of dimeric spikes. With microcalorimetry, electron cryo microscopy and peptide microarray-based screens, we have characterized the structural and thermodynamic properties of peptide binding to hepatitis B core protein capsids with different secretion phenotypes. The peptide “GSLLGRMKGA” binds weakly to hepatitis B core protein capsids and mutant capsids with a premature (F97L) or low-secretion phenotype (L60V and P5T). With electron cryo microscopy, we provide novel structures for L60V and P5T and demonstrate that binding occurs at the tips of the spikes at the dimer interface, splaying the helices apart independent of the secretion phenotype. Peptide array screening identifies “SLLGRM” as the core binding motif. This shortened motif binds only to one of the two spikes in the asymmetric unit of the capsid and induces a much smaller conformational change. Altogether, these comprehensive studies suggest that the tips of the spikes act as an autonomous binding platform that is unaffected by mutations that affect secretion phenotypes.

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Folaron, Margaret, Mihai Merzianu, Umamaheswar Duvvuri, Robert L. Ferris, and Mukund Seshadri. "Profiling the Stromal and Vascular Heterogeneity in Patient-derived Xenograft Models of Head and Neck Cancer: Impact on Therapeutic Response." Cancers 11, no. 7 (July 6, 2019): 951. http://dx.doi.org/10.3390/cancers11070951.

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Head and neck squamous cell carcinomas (HNSCC) represent a group of epithelial neoplasms that exhibit considerable heterogeneity in clinical behavior. Here, we examined the stromal and vascular heterogeneity in a panel of patient-derived xenograft (PDX) models of HNSCC and the impact on therapeutic response. Tumor sections from established tumors were stained for p16 (surrogate for human papillomavirus (HPV) infection), stromal (Masson’s trichrome) and vascular (CD31) markers. All PDX models retained the HPV/p16 status of the original patient tumor. Immunohistochemical evaluation revealed the presence of multiple vessel phenotypes (tumor, stromal or mixed) in the PDX panel. Vascular phenotypes identified in the PDX models were validated in a tissue microarray of human HNSCC. Treatment with a microtubule targeted vascular disrupting agent (VDA) resulted in a heterogeneous antivascular and antitumor response in PDX models. The PDX with the tumor vessel phenotype that exhibited higher CD31+ vessel counts and leaky vasculature on magnetic resonance imaging (MRI) was sensitive to VDA treatment while the PDX with the stromal vessel phenotype was resistant to therapy. Collectively, our results demonstrate the phenotypic and functional vascular heterogeneity in HNSCC and highlight the impact of this heterogeneity on response to antivascular therapy in PDX models of HNSCC.

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Goldmann, Oliver, Maren von Köckritz-Blickwede, Claudia Höltje, Gursharan S. Chhatwal, Robert Geffers, and Eva Medina. "Transcriptome Analysis of Murine Macrophages in Response to Infection with Streptococcus pyogenes Reveals an Unusual Activation Program." Infection and Immunity 75, no. 8 (May 25, 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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MacGlashan, Donald. "Development of mRNA signatures tools to detect in vivo basophil phenotypes: IL-3 signatures (57.5)." Journal of Immunology 188, no. 1_Supplement (May 1, 2012): 57.5. http://dx.doi.org/10.4049/jimmunol.188.supp.57.5.

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Abstract There are several well-recognized phenotypes of peripheral blood basophils (e.g., non-releasers) but the underlying bases for the phenotypes are not explained. IL-3 has many effects on basophil maturation and function and is known to induce considerable changes in basophil phenotype. Purified human basophils were cultured with or without IL-3 for 24 hours and the microarray expression profile, relative to pre-culture, analyzed for transcripts that acted in a reciprocal fashion depending on the condition. A 51- gene transcript set was identified that was composed 34 transcripts that increased with IL-3 and decreased without IL-3 and a further 17 transcripts that did the reverse. The changes were stable in time, with 3-day cultures generating a concordant signature. The inverted nature of the response to ±IL-3 suggested that the normal circulating basophil is in a sensitive balanced state of IL-3 exposure. For example, it could detect the early generation of IL-3 that follows IgE-mediated stimulation of basophils. When this signature tool was applied to freshly isolated basophils, it was observed that the signature was stable in time for the same subjects’ basophils. But when comparing the non-releaser and releaser phenotypes, the signature was consistent with a low-level deficiency in exposure to IL-3 or an IL-3-like cytokine in the “non-releaser phenotype. These studies identified an IL-3 signature to probe changes in basophils occurring in vivo.

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Carvalho, Luiz Joaquim Castelo Branco, Eduardo Alano Vieira, Josefino de Freitas Fialho, and 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, no. 4 (December 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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Holt, S., and E. Sweeney. "Using microarray to diagnose Noonan Syndrome and predict phenotype." Archives of Disease in Childhood 97, Suppl 1 (May 2012): A15.3—A16. http://dx.doi.org/10.1136/archdischild-2012-301885.38.

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Ko, In Kap, Koichi Kato, and Hiroo Iwata. "Antibody microarray for correlating cell phenotype with surface marker." Biomaterials 26, no. 6 (February 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, no. 6 (February 22, 2014): 1153–60. http://dx.doi.org/10.1007/s10529-014-1481-x.

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Wang, Hancheng, Yanfei Huang, Jin Wang, Maosheng Wang, Haiqian Xia, and Hongxue Lu. "Phenotypic Fingerprints of Ralstonia solanacearum Biovar 3 Strains from Tobacco and Tomato in China Assessed by Phenotype MicroArray Analysis." Plant Pathology Journal 14, no. 1 (December 15, 2015): 38–43. http://dx.doi.org/10.3923/ppj.2015.38.43.

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Singh, Shiva M., Julie Treadwell, Morgan L. Kleiber, Michelle Harrison, and Raihan K. Uddin. "Analysis of behavior using genetical genomics in mice as a model: from alcohol preferences to gene expression differences." Genome 50, no. 10 (October 2007): 877–97. http://dx.doi.org/10.1139/g06-118.

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Most familial behavioral phenotypes result from the complex interaction of multiple genes. Studies of such phenotypes involving human subjects are often inconclusive owing to complexity of causation and experimental limitations. Studies of animal models argue for the use of established genetic strains as a powerful tool for genetic dissection of behavioral disorders and have led to the identification of rare genes and genetic mechanisms implicated in such phenotypes. We have used microarrays to study global gene expression in adult brains of four genetic strains of mice (C57BL/6J, DBA/2J, A/J, and BALB/c). Our results demonstrate that different strains show expression differences for a number of genes in the brain, and that closely related strains have similar patterns of gene expression as compared with distantly related strains. In addition, among the 24 000 genes and ESTs on the microarray, 77 showed at least a 1.5-fold increase in the brains of C57BL/6J mice as compared with those of DBA/2J mice. These genes fall into such functional categories as gene regulation, metabolism, cell signaling, neurotransmitter transport, and DNA/RNA binding. The importance of these findings as a novel genetic resource and their use and application in the genetic analysis of complex behavioral phenotypes, susceptibilities, and responses to drugs and chemicals are discussed.

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Pačínková, Anna, and Vlad Popovici. "Cross-platform Data Analysis Reveals a Generic Gene Expression Signature for Microsatellite Instability in Colorectal Cancer." BioMed Research International 2019 (March 17, 2019): 1–9. http://dx.doi.org/10.1155/2019/6763596.

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The dysfunction of the DNA mismatch repair system results in microsatellite instability (MSI). MSI plays a central role in the development of multiple human cancers. In colon cancer, despite being associated with resistance to 5-fluorouracil treatment, MSI is a favourable prognostic marker. In gastric and endometrial cancers, its prognostic value is not so well established. Nevertheless, recognising the MSI tumours may be important for predicting the therapeutic effect of immune checkpoint inhibitors. Several gene expression signatures were trained on microarray data sets to understand the regulatory mechanisms underlying microsatellite instability in colorectal cancer. A wealth of expression data already exists in the form of microarray data sets. However, the RNA-seq has become a routine for transcriptome analysis. A new MSI gene expression signature presented here is the first to be valid across two different platforms, microarrays and RNA-seq. In the case of colon cancer, its estimated performance was (i) AUC = 0.94, 95% CI = (0.90 – 0.97) on RNA-seq and (ii) AUC = 0.95, 95% CI = (0.92 – 0.97) on microarray. The 25-gene expression signature was also validated in two independent microarray colon cancer data sets. Despite being derived from colorectal cancer, the signature maintained good performance on RNA-seq and microarray gastric cancer data sets (AUC = 0.90, 95% CI = (0.85 – 0.94) and AUC = 0.83, 95% CI = (0.69 – 0.97), respectively). Furthermore, this classifier retained high concordance even when classifying RNA-seq endometrial cancers (AUC = 0.71, 95% CI = (0.62 – 0.81). These results indicate that the new signature was able to remove the platform-specific differences while preserving the underlying biological differences between MSI/MSS phenotypes in colon cancer samples.

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JIA, ZHENYU, and SHIZHONG XU. "Clustering expressed genes on the basis of their association with a quantitative phenotype." Genetical Research 86, no. 3 (November 25, 2005): 193–207. http://dx.doi.org/10.1017/s0016672305007822.

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Cluster analyses of gene expression data are usually conducted based on their associations with the phenotype of a particular disease. Many disease traits have a clearly defined binary phenotype (presence or absence), so that genes can be clustered based on the differences of expression levels between the two contrasting phenotypic groups. For example, cluster analysis based on binary phenotype has been successfully used in tumour research. Some complex diseases have phenotypes that vary in a continuous manner and the method developed for a binary trait is not immediately applicable to a continuous trait. However, understanding the role of gene expression in these complex traits is of fundamental importance. Therefore, it is necessary to develop a new statistical method to cluster expressed genes based on their association with a quantitative trait phenotype. We developed a model-based clustering method to classify genes based on their association with a continuous phenotype. We used a linear model to describe the relationship between gene expression and the phenotypic value. The model effects of the linear model (linear regression coefficients) represent the strength of the association. We assumed that the model effects of each gene follow a mixture of several multivariate Gaussian distributions. Parameter estimation and cluster assignment were accomplished via an Expectation-Maximization (EM) algorithm. The method was verified by analysing two simulated datasets, and further demonstrated using real data generated in a microarray experiment for the study of gene expression associated with Alzheimer's disease.

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Clemmer, Katy M., Gwen M. Sturgill, Alexander Veenstra, and Philip N. Rather. "Functional Characterization of Escherichia coli GlpG and Additional Rhomboid Proteins Using an aarA Mutant of Providencia stuartii." Journal of Bacteriology 188, no. 9 (May 1, 2006): 3415–19. http://dx.doi.org/10.1128/jb.188.9.3415-3419.2006.

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ABSTRACT The Providencia stuartii AarA protein is a member of the rhomboid family of intramembrane serine proteases and required for the production of an extracellular signaling molecule that regulates cellular functions including peptidoglycan acetylation, methionine transport, and cysteine biosynthesis. Additional aarA-dependent phenotypes include (i) loss of an extracellular yellow pigment, (ii) inability to grow on MacConkey agar, and (iii) abnormal cell division. Since these phenotypes are easily assayed, the P. stuartii aarA mutant serves as a useful host system to investigate rhomboid function. The Escherichia coli GlpG protein was shown to be functionally similar to AarA and rescued the above aarA-dependent phenotypes in P. stuartii. GlpG proteins containing single alanine substitutions at the highly conserved catalytic triad of asparagine (N154A), serine (S201A), or histidine (H254A) residues were nonfunctional. The P. stuartii aarA mutant was also used as a biosensor to demonstrate that proteins from a variety of diverse sources exhibited rhomboid activity. In an effort to further investigate the role of a rhomboid protein in cell physiology, a glpG mutant of E. coli was constructed. In phenotype microarray experiments, the glpG mutant exhibited a slight increase in resistance to the β-lactam antibiotic cefotaxime.

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Journal articles on the topic 'Phenotype Microarry'

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