Tie, S. | bioRxiv Science

bioRxiv2024

Extraction-free colorimetric RT-LAMP for SARS-CoV-2 RNA detection from saliva

AimTo develop a rapid and easy diagnostic assay for detection of SARS-CoV-2 RNA presented in saliva samples. MethodThe color-based RT-LAMP was used to detect nucleocapsid (N) gene of SARS-CoV-2 without RNA extraction from saliva. ResultsRNA spiked saliva can be used directly for cDNA synthesis after heat inactivation of the saliva and diluted 2-fold with either water or PBS. For both PCR and LAMP, 20% of saliva did not have obvious effect on the reaction. Saliva did not interfere with RT-LAMP when the volume of saliva was less than 20% of the total volume. The sensitivity of the RT-LAMP reached to 1.034x10-5 ng/{micro}l (475 copies/l). The RT-LAMP assay was validated by testing 20 RNA spiked saliva samples. The assay specificity was similar to that of data without saliva. ConclusionsThe RT-LAMP colorimetric assay can be used as a screening method with the advantages of being rapid, easy to use than the qRT-PCR.

microbiology↗

bioRxiv2022

Illuminating protein space with a programmable generative model

Three billion years of evolution have produced a tremendous diversity of protein molecules, and yet the full potential of this molecular class is likely far greater. Accessing this potential has been challenging for computation and experiments because the space of possible protein molecules is much larger than the space of those likely to host function. Here we introduce Chroma, a generative model for proteins and protein complexes that can directly sample novel protein structures and sequences and that can be conditioned to steer the generative process towards desired properties and functions. To enable this, we introduce a diffusion process that respects the conformational statistics of polymer ensembles, an efficient neural architecture for molecular systems based on random graph neural networks that enables long-range reasoning with sub-quadratic scaling, equivariant layers for efficiently synthesizing 3D structures of proteins from predicted inter-residue geometries, and a general low-temperature sampling algorithm for diffusion models. We suggest that Chroma can effectively realize protein design as Bayesian inference under external constraints, which can involve symmetries, substructure, shape, semantics, and even natural language prompts. With this unified approach, we hope to accelerate the prospect of programming protein matter for human health, materials science, and synthetic biology.

bioinformatics↗