An engineered CRISPR-Cas12a variant and DNA-RNA hybrid guides enable robust and rapid COVID-19 testing

Extensive testing is essential to break the transmission of SARS-CoV-2, which causes the ongoing COVID-19 pandemic. Here, we present a CRISPR-based diagnostic assay that is robust to viral genome mutations and temperature, produces results fast, can be applied directly on nasopharyngeal (NP) specimens without RNA purification, and incorporates a human internal control within the same reaction. Specifically, we show that the use of an engineered AsCas12a enzyme enables detection of wildtype and mutated SARS-CoV-2 and allows us to perform the detection step with loop-mediated isothermal amplification (LAMP) at 60-65 °C. We also find that the use of hybrid DNA-RNA guides increases the rate of reaction, enabling our test to be completed within 30 minutes. Utilizing clinical samples from 72 patients with COVID-19 infection and 57 healthy individuals, we demonstrate that our test exhibits a specificity and positive predictive value of 100% with a sensitivity of 50 and 1000 copies per reaction (or 2 and 40 copies per microliter) for purified RNA samples and unpurified NP specimens respectively.

Coarse-grained nucleic acid–protein model for hybrid nanotechnology

A coarse-grained model for analysis and design of hybrid DNA-protein nanoscale structures.

Baculovirus-vectored precision delivery of large DNA cargoes in human genomes

Precise gene editing and genome engineering by CRISPR technology requires simultaneous delivery of multiple DNA-encoded components into living cells rapidly exceeding the cargo capacity of currently utilized viral vector systems. Here we exploit the unmatched heterologous DNA cargo capacity of baculovirus to resolve this bottleneck. We implement hybrid DNA techniques (MultiMate) for rapid and error-free assembly of currently up to 25 functional DNA modules in a single baculoviral vector enabling CRISPR-based genome engineering. Utilizing homology-independent targeted integration (HITI), we achieve up to 30% correct genome interventions in human cells, including precision docking of large DNA payloads in the ACTB locus. We demonstrate baculovirus-vectored delivery of prime-editing toolkits for seamless DNA search-and-replace interventions achieving, with a single vector, highly efficient cleavage-free trinucleotide insertion in the HEK3 locus without any detectable indels. Our approach thus unlocks a wide range of editing and engineering applications in human cell genomes.

Hybrid DNA Chaos Based Steganography on ECG Signal for Secured Data Communication

One of the principal issues in data sharing is security. Data being transferred on the internet is prone to severe attacks. Securing data is kind of digital privacy measures that are implemented to prevent the data to be hacked by unauthorized person while sharing the information over the communication network. Data may be of any form like image, signal or text. Encrypting the data before being transmitted is one step taken to promote security which is the well-known process of cryptography. Steganography deals with hiding the message in any unknown format. Combination of these methods turns to be more secure. A hybrid DNA hyper chaotic based algorithm with lifting wavelet technology to secure ECG signal is proposed here. The wavelet technique that decomposes the image into four bands namely LL, LH, HH, HL. To remove the redundancies the coefficients are utilised in the encoder process. The data hiding is implemented by selective embedding process is introduced in this method by determine host signal samples. The encrypted data then is hidden inside image using DNA method logically. When one knows and tries to get the hidden data they require the secret key to do so and any mistake in that leads to distortion of the signal which results in loss of data. This method is found to be secure and the simulation is done using MATLAB. A GUI is developed to choose the required ECG signal and other operations to embed the data and find the original signal after retrieval.