A simple method for extracting phycocyanin from Arthrospira (Spirulina) platensis by autolysis.

Phycocyanin (PC) is a natural blue pigment that has great commercial value in food and pharmaceutical industry. Arthrospira (Spirulina) platensis is a photosynthetic spiral-shaped cyanobacterium containing a rich PC pigment. Autolysis is the enzymatic digestion of cells by the action of its own enzymes.

In vivo gene correction with targeted sequence substitution through microhomology-mediated end joining.

Genome editing technology using programmable nucleases has rapidly evolved in recent years. The primary mechanism to achieve precise integration of a transgene is mainly based on homology-directed repair (HDR). However, an HDR-based genome-editing approach is less efficient than non-homologous end-joining (NHEJ).

Deep learning improves prediction of CRISPR-Cpf1 guide RNA activity.

We present two algorithms to predict the activity of AsCpf1 guide RNAs. Indel frequencies for 15,000 target sequences were used in a deep-learning framework based on a convolutional neural network to train Seq-deepCpf1. We then incorporated chromatin accessibility information to create the better-performing DeepCpf1 algorithm for cell lines for which such information is available and show that both algorithms outperform previous machine learning algorithms on our own and published data sets.

In vivo high-throughput profiling of CRISPR-Cpf1 activity.

CRISPR from Prevotella and Francisella 1 (Cpf1) is an effector endonuclease of the class 2 CRISPR-Cas (clustered regularly interspaced short palindromic repeats-CRISPR-associated proteins) gene editing system. We developed a method for evaluating Cpf1 activity, based on target sequence composition in mammalian cells, in a high-throughput manner. A library of >11,000 target sequence and guide RNA pairs was delivered into human cells using lentiviral vectors.