Biology subjects

HUANG, L.

Publications and source records attributed to HUANG, L..

3 recordsLinked to original sources

bioRxiv2024

Discovery and Engineering of a New BvCas12a Nuclease for Mammalian Genome Editing and Nucleic Acid Detection

Cas12a is an RNA-guided endonuclease that has emerged as a powerful gene-editing tool. We have identified a novel Cas protein, BvCas12a, from Butyricimonas virosa with a 5-TYTN protospacer adjacent motif (PAM). BvCas12a exhibits double-stranded DNA cleavage activity in vitro and genome editing activity in eukaryotic cells. Though the editing efficiency of BvCas12a is marginally lower than that of AsCas12a, the editing specificity of BvCas12a in eukaryotic cells is comparable or superior to that of AsCas12a. Moreover, BvCas12a exhibits substantial collateral activity and can detect HPV DNA effectively and accurately in conjunction with isothermal amplification, highlighting its potential in nucleic acid diagnostics. Furthermore, we have engineered BvCas12a to create two variants, BvCas12a-R (N549R, T606P) and BvCas12a-RVR (N549R, K555V, C559R, T606P). These variants recognize expanded 5-YYN and 5-YN PAM in vitro, respectively. Additionally, they exhibit higher editing activity than wild-type BvCas12a and recognize 5-YYN PAM in vivo at all sites detected. In conclusion, we have identified a novel BvCas12a protein with high specificity and engineered two variants with broader PAM compatibility and improved genome editing efficiency. These findings offer a potent gene editing tool for application in scientific research, gene therapy, and nucleic acid diagnostics.

genomics↗

bioRxiv2021

An awareness-dependent saliency map in the human visual system

The bottom-up contribution to the allocation of exogenous attention is a saliency map. However, how the saliency map is distributed when multiple salient stimuli are presented simultaneously and how this distribution interacts with awareness remain unclear. These questions were addressed here using visible and invisible stimuli that consisting of two salient foregrounds: the high one served as the target and the low one served as the distractor, which did or did not interfere the target saliency, indicating a gradient or winner-take-all manner, respectively. By combining psychophysics, fMRI, and effective connectivity analysis, we found that the saliency map was distributed as a gradient or winner-take-all manner with and without awareness, respectively. Crucially, we further revealed that the gradient manner was derived by feedback from pIPS, whereas the winner-take-all manner was constructed in V1. Together, our findings indicate an awareness-dependent saliency map and reconcile previous, seemingly contradictory findings on the saliency map.

neuroscience↗

bioRxiv2020

Augmenting Vascular Disease Diagnosis by Vasculature-awareUnsupervised Learning

Vascular diseases are among the leading causes of death and threaten human health worldwide. Imaging examination of vascular pathology with reduced invasiveness is challenging due to the intrinsic vasculature complexity and the non-uniform scattering from bio-tissues. Here, we report VasNet, a vasculature-aware unsupervised learning algorithm that augments pathovascular recognition from small sets of unlabeled fluorescence and digital subtraction angiography (DSA) images. The VasNet adopts the multi-scale fusion strategy with a domain adversarial neural network (DANN) loss function that induces biased pattern reconstruction, by strengthening the features relevant to the retinal vasculature reference while weakening the irrelevant features. VasNet delivers outputs of "Structure + X", where X refers to multi-dimensional features such as blood flows, the distinguishment of blood dilation and its suspicious counterparts, and the dependence of new pattern emergence on a disease progression, which may assist the discovery of novel diagnostics. Therefore, explainable imaging output from VasNet and other algorithm extensions hold the promise to revolutionize the practice of medical diagnosis, as it improves performance while reduces the cost on human expertise, equipment exquisite and time consumption.

bioengineering↗