Extrachromosomal circular DNA (eccDNA) has been identified in a broad range of eukaryotes and have been shown to carry genes and regulatory sequences. Additionally, they can amplify within a cell by autonomous replication or reintegration into the genome, effectively influencing copy number in cells. This has significant implications for cancer, where oncogenes are frequently amplified on eccDNA. However, little is known about the exact molecular mechanisms governing eccDNA functionality. To this end, we constructed a fluorescent reporter at an eccDNA-prone locus of the yeast genome, CUP1. It is our hope that this reporter will contribute to a better understanding of eccDNA formation and amplification within a cell.
Protein and gene circuit level synthetic bioengineering can require years to develop a single target. Phage assisted continuous evolution (PACE) is a powerful new tool for rapidly engineering new genes and proteins, but the method requires an automated cell culture system, making it inaccessible to non industrial research programs. Complex protein functions, like specific binding, require similarly dynamic PACE selection that can be alternatively induced or suppressed, with heat labile chemicals like tetracycline. Selection conditions must be controlled continuously over days, with adjustments made every few minutes. To make PACE experiments accessible to the broader community, we designed dedicated cell culture hardware and integrated optogenetically controlled plasmids. The low cost and open source platform allows a user to conduct PACE with continuous monitoring and precise control of evolution using light.
In the past decade, numerous methods have been developed to analyze in-vivo calcium imaging data that involves complex techniques such as overlapping signals segregation and motion artifact correction. The hypothesis used to detect calcium signal is the spatiotemporal sparsity of calcium signal, and these methods are unable to identify the passive cells that are not actively firing during the time frame in the video. Statistics regarding the percentage of cells in each frame of view can be critical for the analysis of calcium imaging data for human induced pluripotent stem cells derived neurons and astrocytes.
The objective of this research is to develop a simple and efficient semi-automated pipeline for analysis of in-vitro calcium imaging data. The region of interest (ROI) based image segmentation is used to extract the data regarding intensity fluctuation caused by calcium concentration changes in each cell. It is achieved by using two approaches: basic image segmentation approach and a machine learning approach. The intensity data is evaluated using a custom-made MATLAB that generates statistical information and graphical representation of the number of spiking cells in each field of view, the number of spikes per cell and spike height.
An algebraic representation of the nucleotide bases is developed. This algebraic representation makes it possible to convert nucleotide sequences into algebraic sequences, apply mathematical ideas and convert results back into nucleotide terms. Using the algebra developed, a mapping is found from the naturally-occurring codons to an alternative set of codons which makes genes constructed from them mutation-tolerant, provided no more than one substitution mutation occurs per codon. The ideas discussed naturally extend to finding codons that can tolerate t arbitrarily chosen number of mutations per codon. Finally, random substitution events are simulated in both a wild-type green fluorescent protein (GFP) gene and its mutol variant and the amino acid sequence expressed from each post-mutation is compared with the amino acid sequence pre-mutation.
This work assumes the existence of synthetic protein-assembling entities that function like tRNAs but can read k nucleotides at a time, with k greater than or equal to 5. The realization of this assumption is presented as a challenge to the research community.