Project description:We quantify the effects of electrical stimulation on murine cells at the cellular and transcriptomic level using single cell RNA-sequencing. We characterize circulating cells and compare them to unstimulated circulating cells.
Project description:The aim of the study is to identify a pattern of chemoresistive sensors able to recognise the presence of a tumoral pathology from a health state through the analysis of Volatile Organic Compounds inside the specimen.
The chemoresistive nanostructured sensors are into an innovative patented device SCENT B1 which can analyse different specimens: blood samples, tissue biopsies, cell cultures.
In this study SCENT B1 wil be used to compare the measures of:
* tumoral and health tissues taken from different neoplasms after their surgical resection
* blood samples from healthy and tumor affected people
* pre and post- operative blood samples of tumor affected people
Project description:Metabolic sensors are microbial strains modified such that biomass formation correlates with the availability of specific target metabolites. These sensors are essential for bioengineering (e.g. in growth-coupled selection of synthetic pathways), but their design is often time-consuming and low-throughput. In contrast, in silico analysis can accelerate their development. We present a systematic workflow for designing, implementing, and testing versatile metabolic sensors using Escherichia coli as a model. Glyoxylate, a key metabolite in synthetic CO2 fixation and carbon-conserving pathways, served as the test molecule. Through iterative screening of a compact metabolic reconstruction, we identified non-trivial growth-coupled designs that resulted in six metabolic sensors with different glyoxylate-to-biomass ratios. These metabolic sensors had a linear correlation between biomass formation and glyoxylate concentration spanning three orders of magnitude and were further adapted for glycolate sensing. We demonstrate the utility of these sensors in pathway engineering (implementing a synthetic route for one-carbon assimilation via glyoxylate) and environmental applications (quantifying glycolate produced by photosynthetic microalgae). The versatility and ease of implementation of this workflow make it suitable for designing and building multiple metabolic sensors for diverse biotechnological applications.
Project description:HEK293T/17 cells were genetically edited by SMART editing to assess the effectiveness of SMART editing. There are 4 target genes: CXCR4, Lmnb1, Nrl and NRXN3. Cultured cells were first synchronized at the G2/M phase. Then, cells were transfected with Cas9 RNP along with SMART or traditional templates. After culture for two to three days, cells were harvested, and genomic DNA was extracted. The targeted loci were amplified by PCR and sequenced on an Illumina MiSeq.