scholarly journals In VitroGene Expression Dissected: Chemostat Surgery forMycobacterium tuberculosis

2002 ◽  
Vol 3 (4) ◽  
pp. 345-347 ◽  
Author(s):  
Brian W. James ◽  
Joanna Bacon ◽  
Tobias Hampshire ◽  
Kim Morley ◽  
Philip D. Marsh
Keyword(s):  
Gene Expression ◽  
Culture System ◽  
Time Course ◽  
Dna Microarrays ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Multiple Time ◽  
Unique Approach ◽  
Highly Correlated

A unique approach, combining defined and reproduciblein vitromodels with DNA microarrays, has been developed to study environmental modulation of mycobacterial gene expression. The gene expression profiles of samples ofMycobacterium tuberculosis, from independent chemostat cultures grown under defined and reproducible conditions, were found to be highly correlated. This approach is now being used to study the effect of relevant stimuli, such as limited oxygen availability, on mycobacterial gene expression. A modification of the chemostat culture system, enabling largevolume controlled batch culture, has been developed to study starvation survival. Cultures ofM. tuberculosishave been maintained under nutrient-starved conditions for extended periods, with106–107bacilli surviving in a culturable state after 100 days. The design of the culture system has made it possible to control the environment and collect multiple time-course samples to study patterns of gene expression. These studies demonstrate that it is possible to perform long-term studies and obtain reproducible expression data using controlled and definedin vitromodels.

scholarly journals Bayesian approach for predicting responses to therapy from high-dimensional time-course gene expression profiles

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Arika Fukushima ◽  
Masahiro Sugimoto ◽  
Satoru Hiwa ◽  
Tomoyuki Hiroyasu
Keyword(s):  
Gene Expression ◽  
Time Course ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Response To Therapy ◽  
Hcv Infection ◽  
Entire Treatment Period ◽  
Time Points ◽  
Time Course Data ◽  
Conventional Methods

Abstract Background Historical and updated information provided by time-course data collected during an entire treatment period proves to be more useful than information provided by single-point data. Accurate predictions made using time-course data on multiple biomarkers that indicate a patient’s response to therapy contribute positively to the decision-making process associated with designing effective treatment programs for various diseases. Therefore, the development of prediction methods incorporating time-course data on multiple markers is necessary. Results We proposed new methods that may be used for prediction and gene selection via time-course gene expression profiles. Our prediction method consolidated multiple probabilities calculated using gene expression profiles collected over a series of time points to predict therapy response. Using two data sets collected from patients with hepatitis C virus (HCV) infection and multiple sclerosis (MS), we performed numerical experiments that predicted response to therapy and evaluated their accuracies. Our methods were more accurate than conventional methods and successfully selected genes, the functions of which were associated with the pathology of HCV infection and MS. Conclusions The proposed method accurately predicted response to therapy using data at multiple time points. It showed higher accuracies at early time points compared to those of conventional methods. Furthermore, this method successfully selected genes that were directly associated with diseases.

scholarly journals Transcriptome analysis of gravitational effects on mouse skeletal muscles under microgravity and artificial 1 g onboard environment

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Risa Okada ◽  
Shin-ichiro Fujita ◽  
Riku Suzuki ◽  
Takuto Hayashi ◽  
Hirona Tsubouchi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Muscle Mass ◽  
Muscle Atrophy ◽  
Transcriptome Analysis ◽  
Fiber Type ◽  
Expression Profiles ◽  
Space Station ◽  
Gene Expression Profiles

AbstractSpaceflight causes a decrease in skeletal muscle mass and strength. We set two murine experimental groups in orbit for 35 days aboard the International Space Station, under artificial earth-gravity (artificial 1 g; AG) and microgravity (μg; MG), to investigate whether artificial 1 g exposure prevents muscle atrophy at the molecular level. Our main findings indicated that AG onboard environment prevented changes under microgravity in soleus muscle not only in muscle mass and fiber type composition but also in the alteration of gene expression profiles. In particular, transcriptome analysis suggested that AG condition could prevent the alterations of some atrophy-related genes. We further screened novel candidate genes to reveal the muscle atrophy mechanism from these gene expression profiles. We suggest the potential role of Cacng1 in the atrophy of myotubes using in vitro and in vivo gene transductions. This critical project may accelerate the elucidation of muscle atrophy mechanisms.

Gene expression profiles of homogentisate-treated Fah−/− Hpd−/−mice using DNA microarrays

2006 ◽  
Vol 89 (3) ◽  
pp. 203-209 ◽  
Author(s):  
Yasuhiko Tanaka ◽  
Kimitoshi Nakamura ◽  
Shirou Matsumoto ◽  
Yoshiko Kimoto ◽  
Akito Tanoue ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Microarrays ◽  
Expression Profiles ◽  
Gene Expression Profiles

Simulated microgravity using the Random Positioning Machine inhibits differentiation and alters gene expression profiles of 2T3 preosteoblasts

2005 ◽  
Vol 288 (6) ◽  
pp. C1211-C1221 ◽  
Author(s):  
Steven J. Pardo ◽  
Mamta J. Patel ◽  
Michelle C. Sykes ◽  
Manu O. Platt ◽  
Nolan L. Boyd ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alkaline Phosphatase ◽  
Bone Loss ◽  
Simulated Microgravity ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Underlying Mechanism ◽  
Bone Biology ◽  
Random Positioning Machine

Exposure to microgravity causes bone loss in humans, and the underlying mechanism is thought to be at least partially due to a decrease in bone formation by osteoblasts. In the present study, we examined the hypothesis that microgravity changes osteoblast gene expression profiles, resulting in bone loss. For this study, we developed an in vitro system that simulates microgravity using the Random Positioning Machine (RPM) to study the effects of microgravity on 2T3 preosteoblast cells grown in gas-permeable culture disks. Exposure of 2T3 cells to simulated microgravity using the RPM for up to 9 days significantly inhibited alkaline phosphatase activity, recapitulating a bone loss response that occurs in real microgravity conditions without altering cell proliferation and shape. Next, we performed DNA microarray analysis to determine the gene expression profile of 2T3 cells exposed to 3 days of simulated microgravity. Among 10,000 genes examined using the microarray, 88 were downregulated and 52 were upregulated significantly more than twofold using simulated microgravity compared with the static 1-g condition. We then verified the microarray data for some of the genes relevant in bone biology using real-time PCR assays and immunoblotting. We confirmed that microgravity downregulated levels of alkaline phosphatase, runt-related transcription factor 2, osteomodulin, and parathyroid hormone receptor 1 mRNA; upregulated cathepsin K mRNA; and did not significantly affect bone morphogenic protein 4 and cystatin C protein levels. The identification of gravisensitive genes provides useful insight that may lead to further hypotheses regarding their roles in not only microgravity-induced bone loss but also the general patient population with similar pathological conditions, such as osteoporosis.

Building Gene Networks by Analyzing Gene Expression Profiles

2019 ◽  
pp. 27-44
Author(s):  
Crescenzio Gallo
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Gene Networks ◽  
Dna Microarrays ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Expression Data ◽  
Gene Expressions ◽  
Over Time

The possible applications of modeling and simulation in the field of bioinformatics are very extensive, ranging from understanding basic metabolic paths to exploring genetic variability. Experimental results carried out with DNA microarrays allow researchers to measure expression levels for thousands of genes simultaneously, across different conditions and over time. A key step in the analysis of gene expression data is the detection of groups of genes that manifest similar expression patterns. In this chapter, the authors examine various methods for analyzing gene expression data, addressing the important topics of (1) selecting the most differentially expressed genes, (2) grouping them by means of their relationships, and (3) classifying samples based on gene expressions.

scholarly journals Prediction of Pharmacological and Xenobiotic Responses to Drugs Based on Time Course Gene Expression Profiles

PLoS ONE ◽  
2009 ◽  
Vol 4 (12) ◽  
pp. e8126 ◽  
Author(s):  
Tao Huang ◽  
WeiRen Cui ◽  
LeLe Hu ◽  
KaiYan Feng ◽  
Yi-Xue Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Time Course ◽  
Expression Profiles ◽  
Gene Expression Profiles

171 THE EFFECT OF TRICHOSTATIN A ON THE DEVELOPMENT AND THE GLOBAL GENE EXPRESSION PATTERNS IN MOUSE EMBRYOS DEVELOPING IN VITRO

2008 ◽  
Vol 20 (1) ◽  
pp. 165
Author(s):  
X. S. Cui ◽  
X. Y. Li ◽  
T. Kim ◽  
N.-H. Kim
Keyword(s):  
Gene Expression ◽  
Trichostatin A ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Mouse Embryos ◽  
Differentially Expressed ◽  
Gene Expression Patterns ◽  
Cell Stage

Trichostatin A (TSA) is an inhibitor of histone deacetylase and is able to alter gene expression patterns by interfering with the removal of acetyl groups from histones. The aim of this study was to determine the effect of TSA treatment on the development and gene expression patterns of mouse zygotes developing in vitro. The addition of 100 nm TSA to the culture medium did not affect the cleavage of mouse embryos (TSA treatment, 148/150 (99%) v. control, 107/107 (100%)); however, embryos that were treated with TSA arrested at the 2-cell stage (145/148, 98%). We estimated the number of nuclei in control and TSA-treated embryos by propidium iodide staining, taking into account the presence of any cells with two or more nuclei. At 62–63 h post-hCG stimulation, control zygotes had developed to the 4-cell stage and exhibited one nucleus in each blastomere, indicative of normal development. In contrast, we observed tetraploid nuclei in at least one blastomere in 20.8% (11/53) of the embryos that had been treated with TSA. At 28–29 h post-hCG stimulation (metaphase of the 1-cell stage), there was no difference in the mitotic index (as determined by analyzing the microtubule configuration) in the TSA group compared to the control group. At the 2-cell stage, however, we did not observe mitotic spindles and metaphase chromatin in embryos in the TSA treatment group compared to the controls. Interestingly, when embryos were cultured in TSA-free medium from 35 h post-hCG stimulation (S- or early G2-phase of the 2-cell stage) onward, almost all of them (47/50) developed to the blastocyst stage. In contrast, when embryos were cultured in TSA-free medium from 42 h post-hCG stimulation (middle G2-phase of the 2-cell stage) onward, they did not develop to the 4-cell stage. We used Illumina microarray technology to analyze the gene expression profiles in control and TSA-treated late 2-cell-stage embryos. Applied Biosystems Expression System software was used to extract assay signals and assay signal-to-noise ratio values from the microarray images. Our data showed that 897 genes were significantly (P < 0.05; 2-sample t-test) up- or down-regulated by TSA treatment compared to controls. Analysis using the PANTHER classification system (https://panther.appliedbiosystems.com) revealed that the 575 genes that were differentially expressed in the TSA group compared to the control were classified as being associated with putative biological processes or molecular function. Overall, in terms of putative biological processes, more nucleoside, nucleotide, and nucleic acid metabolism, protein metabolism and modification, signal transduction, developmental process, and cell cycle genes were differentially expressed between the TSA and control groups. In terms of putative molecular function, more nucleic acid-binding transcription factor and transferase genes were differentially expressed between the groups. The results collectively suggest that inhibition of histone acetylation in mouse embryos affects gene expression profiles at the time of zygotic genome activation, and this subsequently affects further development.

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