Project description:The gut microbiota is susceptible to modulation by environmental stimuli and therefore can serve as a biological sensor. Recent evidence suggests that xenobiotics can disrupt the interaction between the microbiota and host. Here, we describe an approach that combines in vitro microbial incubation (isolated cecal contents from mice), flow cytometry, and mass spectrometry- and 1H nuclear magnetic resonance (NMR)-based metabolomics to evaluate xenobiotic-induced microbial toxicity. Tempol, a stabilized free radical scavenger known to remodel the microbial community structure and function in vivo, was studied to assess its direct effect on the gut microbiota. The microbiota was isolated from mouse cecum and was exposed to tempol for 4 h under strict anaerobic conditions. The flow cytometry data suggested that short-term tempol exposure to the microbiota is associated with disrupted membrane physiology as well as compromised metabolic activity. Mass spectrometry and NMR metabolomics revealed that tempol exposure significantly disrupted microbial metabolic activity, specifically indicated by changes in short-chain fatty acids, branched-chain amino acids, amino acids, nucleotides, glucose, and oligosaccharides. In addition, a mouse study with tempol (5 days gavage) showed similar microbial physiologic and metabolic changes, indicating that the in vitro approach reflected in vivo conditions. Our results, through evaluation of microbial viability, physiology, and metabolism and a comparison of in vitro and in vivo exposures with tempol, suggest that physiologic and metabolic phenotyping can provide unique insight into gut microbiota toxicity. IMPORTANCE The gut microbiota is modulated physiologically, compositionally, and metabolically by xenobiotics, potentially causing metabolic consequences to the host. We recently reported that tempol, a stabilized free radical nitroxide, can exert beneficial effects on the host through modulation of the microbiome community structure and function. Here, we investigated a multiplatform phenotyping approach that combines high-throughput global metabolomics with flow cytometry to evaluate the direct effect of tempol on the microbiota. This approach may be useful in deciphering how other xenobiotics directly influence the microbiota.
Project description:We have developed a multi-analyte fluid-phase protein array technology termed high-throughput immunophenotyping using transcription (HIT). This method employs a panel of monoclonal antibodies, each tagged with a unique oligonucleotide sequence that serves as a molecular barcode. After staining a sample, T7 polymerase amplifies the tags which are then hybridized to a DNA microarray for indirect measurement of each analyte. Here we screened 90 antibodies directed against a panel of cell surface markers as well as 4 isotype controls to compare resting human naive CD4+ T cells versus CD4+ T cells activated for 48 h with anti-CD3/anti-CD28 coated beads. Keywords: protein profiling, response to stimulus Two-condition experiment, activated versus resting cells. Biological replicates: 3 normal human donors, each donor served as an internal control. One replicate per array. One of the biological replicates was performed as a dye-swap to monitor dye-bias. We also performed a self-self comparison between activated cells from two different donors.
Project description:Plant phenotyping is essential in plant breeding and management. High-throughput data acquisition and automatic phenotypes extraction are common concerns in plant phenotyping. Despite the development of phenotyping platforms and the realization of high-throughput three-dimensional (3D) data acquisition in tall plants, such as maize, handling small-size plants with complex structural features remains a challenge. This study developed a miniaturized shoot phenotyping platform MVS-Pheno V2 focusing on low plant shoots. The platform is an improvement of MVS-Pheno V1 and was developed based on multi-view stereo 3D reconstruction. It has the following four components: Hardware, wireless communication and control, data acquisition system, and data processing system. The hardware sets the rotation on top of the platform, separating plants to be static while rotating. A novel local network was established to realize wireless communication and control; thus, preventing cable twining. The data processing system was developed to calibrate point clouds and extract phenotypes, including plant height, leaf area, projected area, shoot volume, and compactness. This study used three cultivars of wheat shoots at four growth stages to test the performance of the platform. The mean absolute percentage error of point cloud calibration was 0.585%. The squared correlation coefficient R 2 was 0.9991, 0.9949, and 0.9693 for plant height, leaf length, and leaf width, respectively. The root mean squared error (RMSE) was 0.6996, 0.4531, and 0.1174 cm for plant height, leaf length, and leaf width. The MVS-Pheno V2 platform provides an alternative solution for high-throughput phenotyping of low individual plants and is especially suitable for shoot architecture-related plant breeding and management studies.
Project description:Health effects of pesticides are not always accurately detected using the current battery of regulatory toxicity tests. We compared standard histopathology and serum biochemistry measures and multi-omics analyses in a subchronic toxicity test of a mixture of six pesticides frequently detected in foodstuffs (azoxystrobin, boscalid, chlorpyrifos, glyphosate, imidacloprid and thiabendazole) in Sprague-Dawley rats. Analysis of water and feed consumption, body weight, histopathology and serum biochemistry showed little effect. Contrastingly, serum and caecum metabolomics revealed that nicotinamide and tryptophan metabolism were affected, which suggested activation of an oxidative stress response. This was not reflected by gut microbial community composition changes evaluated by shotgun metagenomics. Transcriptomics of the liver showed that 257 genes had their expression changed. Gene functions affected included the regulation of response to steroid hormones and the activation of stress response pathways. Genome-wide DNA methylation analysis of the same liver samples showed that 4,255 CpG sites were differentially methylated. Overall, we demonstrated that in-depth molecular profiling in laboratory animals exposed to low concentrations of pesticides allows the detection of metabolic perturbations that would remain undetected by standard regulatory biochemical measures and which could thus improve the predictability of health risks from exposure to chemical pollutants.
Project description:This study introduces multi-zone visco-Node-Pore Sensing (mz-visco-NPS), an electronic-based microfluidic platform for single-cell viscoelastic phenotyping. mz-visco-NPS implements a series of sinusoidal-shaped contraction zones that periodically deform a cell at specific strain frequencies, leading to changes in resistance across the zones that correspond to the cell's frequency-dependent elastic G' and viscous G″ moduli. mz-visco-NPS is validated by measuring the viscoelastic changes of MCF-7 cells when their cytoskeleton is disrupted. mz-visco-NPS is also employed to measure the viscoelastic properties of human mammary epithelial cells across the entire continuum of epithelial transformation states, from average- and high-risk primary epithelial cells, to immortal non-malignant (MCF-10A), malignant (MCF-7), and metastatic (MDA-MB-231) cell lines. With a throughput of 600 cells per hour and demonstrated ease-of-use, mz-visco-NPS reveals a remarkable level of single-cell heterogeneity that would otherwise be masked by ensemble averaging.
Project description:Exposure to ionizing radiation has dramatically increased in modern society, raising serious health concerns. The molecular response to ionizing radiation, however, is still not completely understood. Here, we screened mouse serum for metabolic alterations following an acute exposure to ? radiation using a multiplatform mass-spectrometry-based strategy. A global, molecular profiling revealed that mouse serum undergoes a series of significant molecular alterations following radiation exposure. We identified and quantified bioactive metabolites belonging to key biochemical pathways and low-abundance, oxygenated, polyunsaturated fatty acids (PUFAs) in the two groups of animals. Exposure to ? radiation induced a significant increase in the serum levels of ether phosphatidylcholines (PCs) while decreasing the levels of diacyl PCs carrying PUFAs. In exposed mice, levels of pro-inflammatory, oxygenated metabolites of arachidonic acid increased, whereas levels of anti-inflammatory metabolites of omega-3 PUFAs decreased. Our results indicate a specific serum lipidomic biosignature that could be utilized as an indicator of radiation exposure and as novel target for therapeutic intervention. Monitoring such a molecular response to radiation exposure might have implications not only for radiation pathology but also for countermeasures and personalized medicine.
Project description:We have developed a multi-analyte fluid-phase protein array technology termed high-throughput immunophenotyping using transcription (HIT). This method employs a panel of monoclonal antibodies, each tagged with a unique oligonucleotide sequence that serves as a molecular barcode. After staining a sample, T7 polymerase amplifies the tags which are then hybridized to a DNA microarray for indirect measurement of each analyte. Here we screened 90 antibodies directed against a panel of cell surface markers as well as 4 isotype controls to compare resting human naive CD4+ T cells versus CD4+ T cells activated for 48 h with anti-CD3/anti-CD28 coated beads. Keywords: protein profiling, response to stimulus
Project description:Microbes are an integral component of the tumor microenvironment. However, determinants of microbial presence remain ill-defined. Here, using spatial-profiling technologies, we show that bacterial and immune cell heterogeneity are spatially coupled. Mouse models of pancreatic cancer recapitulate the immune-microbial spatial coupling seen in humans. Distinct intra-tumoral niches are defined by T cells, with T cell-enriched and T cell-poor regions displaying unique bacterial communities that are associated with immunologically active and quiescent phenotypes, respectively, but are independent of the gut microbiome. Depletion of intra-tumoral bacteria slows tumor growth in T cell-poor tumors and alters the phenotype and presence of myeloid and B cells in T cell-enriched tumors but does not affect T cell infiltration. In contrast, T cell depletion disrupts the immunological state of tumors and reduces intra-tumoral bacteria. Our results establish a coupling between microbes and T cells in cancer wherein spatially defined immune-microbial communities differentially influence tumor biology.
Project description:AimsThis study sought to assess the volatile organic compound (VOC) profiles of ampicillin-resistant and -susceptible Escherichia coli to evaluate whether VOC analysis may be utilized to identify resistant phenotypes.Methods and resultsAn E. coli BL21 (DE3) strain and its pET16b plasmid transformed ampicillin-resistant counterpart were cultured for 6 h in drug-free, low- and high-concentrations of ampicillin. Headspace analysis was undertaken using thermal desorption-gas chromatography-mass spectrometry. Results revealed distinct VOC profiles with ampicillin-resistant bacteria distinguishable from their susceptible counterparts using as few as six compounds. A minimum of 30 compounds (fold change >2, p ≤ 0.05) were differentially expressed between the strains across all set-ups. Furthermore, three compounds (indole, acetoin and 3-methyl-1-butanol) were observed to be significantly more abundant (fold change >2, p ≤ 0.05) in the resistant strain compared to the susceptible strain both in the presence and in the absence of drug stress.ConclusionsResults indicate that E. coli with acquired ampicillin resistance exhibit an altered VOC profile compared to their susceptible counterpart both in the presence and in the absence of antibiotic stress. This suggests that there are fundamental differences between the metabolisms of ampicillin-resistant and -susceptible E. coli which may be detected by means of VOC analysis.Significance and impact of the studyOur findings suggest that VOC profiles may be utilized to differentiate between resistant and susceptible bacteria using just six compounds. Consequently, the development of machine-learning models using VOC signatures shows considerable diagnostic applicability for the rapid and accurate detection of antimicrobial resistance.