Methods in molecular biology
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Gene Editing in Human Induced Pluripotent Stem Cells Using Doxycycline-Inducible CRISPR-Cas9 System.
Induced pluripotent stem cells (iPSCs) generated from patients are a valuable tool for disease modelling, drug screening, and studying the functions of cell/tissue-specific genes. However, for this research, isogenic iPSC lines are important for comparison of phenotypes in the wild type and mutant differentiated cells generated from the iPSCs. The advent of gene editing technologies to correct or generate mutations helps in the generation of isogenic iPSC lines with the same genetic background. ⋯ An iPSC line with drug inducible Cas9 expression from the Adeno-Associated Virus Integration Site 1 (AAVS1) safe harbor locus offers a controllable expression of Cas9 with robust gene editing. Here, we describe a stepwise protocol for the generation and characterization of such an iPSC line (AAVS1-PDi-Cas9 iPSC) with a doxycycline (dox)-inducible Cas9 expression cassette from the AAVS1 safe harbor site and efficient editing of target genes with lentiviral vectors expressing gRNAs. This approach with a tunable Cas9 expression that allows investigating gene functions in iPSCs or in the differentiated cells can serve as a versatile tool in disease modelling studies.
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Duchenne muscular dystrophy (DMD) is a devastating X-linked muscle disorder affecting many children. The disease is caused by the lack of dystrophin production and characterized by muscle wasting. The most common causes of death are respiratory failure and heart failure. ⋯ Here, we present methodologies to systemically inject PMOs into humanized DMD model mice and determine levels of dystrophin restoration via Western blotting. Using a tris-acetate gradient SDS gel and semi-dry transfer with three buffers, including the Concentrated Anode Buffer, Anode Buffer, and Cathode Buffer, less than 1% normal levels of dystrophin expression are easily detectable. This method is fast, easy, and sensitive enough for the detection of dystrophin from both cultured muscle cells and muscle biopsy samples.
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The intention-to-treat analysis is the gold standard for evaluating the efficacy in a randomized controlled trial. However, when non-adherence to randomized treatments is high the actual treatment effect may be underestimated. ⋯ These analyses may include censoring at the time of co-interventions associated with stopping treatment, lag censoring which allows an additional period after discontinuation of study treatment to account for residual treatment effects, inverse probability of censoring weights (IPCW), accelerated failure time models, and contamination adjusted intent-to-treat analysis. These methods are particularly useful in assessing the "prescribed efficacy" of the study treatment, which can aid clinical decision-making .
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With rapid advances in experimental instruments and protocols, imaging and sequencing data are being generated at an unprecedented rate contributing significantly to the current and coming big biomedical data. Meanwhile, unprecedented advances in computational infrastructure and analysis algorithms are realizing image-based digital diagnosis not only in radiology and cardiology but also oncology and other diseases. Machine learning methods, especially deep learning techniques, are already and broadly implemented in diverse technological and industrial sectors, but their applications in healthcare are just starting. ⋯ Moreover, the applications of genomics data are realizing the potential for personalized medicine, making diagnosis, treatment, monitoring, and prognosis more accurate. In this chapter, we discuss machine learning methods readily available for digital pathology applications, new prospects of integrating spatial genomics data on tissues with tissue morphology, and frontier approaches to combining genomics data with pathological imaging data. We present perspectives on how artificial intelligence can be synergized with molecular genomics and imaging to make breakthroughs in biomedical and translational research for computer-aided applications.
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The recently discovered clustered regularly interspaced short palindromic repeats (CRISPR)-Cpf1 system, now reclassified as Cas12a, is a DNA-editing platform analogous to the widely used CRISPR-Cas9 system. The Cas12a system exhibits several distinct features over the CRISPR-Cas9 system, such as increased specificity and a smaller gene size to encode the nuclease and the matching CRISPR guide RNA (crRNA), which could mitigate off-target and delivery problems, respectively, described for the Cas9 system. However, the Cas12a system exhibits reduced gene editing efficiency compared to Cas9. ⋯ To optimize the CRISPR-Cas12a system, we describe the inclusion of a self-cleaving ribozyme in the vector design to facilitate accurate 3'-end processing of the crRNA transcript to produce precise molecules. This optimized design enhanced not only the gene editing efficiency, but also the activity of the catalytically inactive Cas12a-based CRISPR gene activation platform. We thus generated an improved CRISPR-Cas12a system for more efficient gene editing and gene regulation purposes.