Biology subjects

Wong, T.

Publications and source records attributed to Wong, T..

23 records · Page 2Linked to original sources

bioRxiv2021

High-throughput, label-free and slide-free histological imaging by computational microscopy and unsupervised learning

Rapid and high-resolution histological imaging with minimal tissue preparation has long been a challenging and yet captivating medical pursue. Here, we propose a promising and transformative histological imaging method, termed computational high-throughput autofluorescence microscopy by pattern illumination (CHAMP). With the assistance of computational microscopy, CHAMP enables high-throughput and label-free imaging of thick and unprocessed tissues with large surface irregularity at an acquisition speed of 10 mm2/10 seconds with 1.1-{micro}m lateral resolution. Moreover, the CHAMP image can be transformed into a virtually stained histological image (Deep-CHAMP) through unsupervised learning within 15 seconds, where significant cellular features are quantitatively extracted with high accuracy. The versatility of CHAMP is experimentally demonstrated using mouse brain/kidney tissues prepared with various clinical protocols, which enables a rapid and accurate intraoperative/postoperative pathological examination without tissue processing or staining, demonstrating its great potential as an assistive imaging platform for surgeons and pathologists to provide optimal adjuvant treatment.

bioengineering↗

bioRxiv2021

Differentiation of cortical brain organoids and optic nerve-like structures from retinal confluent cultures of pluripotent stem cells

Advances in the study of neurological conditions have been possible due to induced pluripotent stem cell technologies and the generation of neural cell types and organoids. Numerous studies have described the generation of neural ectoderm-derived retinal and brain structures from pluripotent stem cells. However, the field is still troubled by technical challenges, including high culture costs and organoid-to-organoid variability. Here, we describe a simple and economical protocol that reproducibly gives rise to the neural retina and cortical brain regions from confluent cultures of stem cells. The spontaneously generated cortical organoids were isolated and cultured in suspension conditions for maturation and are transcriptionally comparable to organoids generated by other methods and to human foetal cortex. Furthermore, these organoids show spontaneous functional network activity with proteomic analysis and electron microscopy demonstrating the presence of synaptic components and maturity. The generation of retinal and brain organoids in close proximity also enabled their mutual isolation. Further culture of this complex organoid system demonstrated the formation of optic nerve-like structures connecting retinal and brain organoids, which might facilitate the investigation of the mechanisms of neurological diseases of the eye and brain.

neuroscience↗

bioRxiv2020

AMPlify: attentive deep learning model for discovery of novel antimicrobial peptides effective against WHO priority pathogens

Antibiotic resistance is a growing global health concern prompting researchers to seek alternatives to conventional antibiotics. Antimicrobial peptides (AMPs) are emerging therapeutic agents with promising utility in this domain and using in silico methods to discover novel AMPs is a strategy that is gaining interest. Such methods can filter through large volumes of candidate sequences and reduce lab screening costs. Here we introduce AMPlify, an attentive deep learning model for AMP prediction, and demonstrate its utility in prioritizing peptide sequences derived from the Rana [Lithobates] catesbeiana (bullfrog) genome. We tested the bioactivity of our predicted peptides against a panel of bacterial species, including representatives from the World Health Organizations "priority pathogens" list. Four of our novel AMPs were active against multiple species of bacteria, including a multi-drug resistant isolate of carbapenemase-producing Escherichia coli, demonstrating the utility of tools like AMPlify in our fight against antibiotic resistance.

bioinformatics↗

bioRxiv2018

Chiral DNA sequences as commutable reference standards for clinical genomics

Chirality is a geometric property describing any object that is inequivalent to a mirror image of itself. Due to its 5-3 directionality, a DNA sequence is distinct from a mirrored sequence arranged in reverse nucleotide order, and is therefore chiral. A given sequence and its opposing chiral partner sequence share many properties, such as nucleotide composition and sequence entropy. Here we demonstrate that chiral DNA sequence pairs also perform equivalently during molecular and bioinformatic techniques that underpin modern genetic analysis, including PCR amplification, hybridization, whole-genome, target-enriched and nanopore sequencing, sequence alignment and variant detection. Given these shared properties, synthetic DNA sequences that directly mirror clinically relevant and/or analytically challenging regions of the human genome are ideal reference standards for clinical genomics. We show how the addition of chiral DNA standards to patient tumor samples can prevent false-positive and false-negative mutation detection and, thereby, improve diagnosis. Accordingly, we propose that chiral DNA standards can fulfill the unmet need for commutable internal reference standards in precision medicine.

genomics↗

bioRxiv2017

Development Of RNAseq Methodologies To Profile The In Vivo Transcriptome Of Bordetella pertussis During Murine Lung Infection

Bordetella pertussis is an obligate human respiratory pathogen that causes the disease whooping cough. A whole cell vaccine (DTP) was developed in the 1940s and was subsequently replaced in the 1990s with a protein-based subunit acellular vaccine (DTaP; tdap). Today, we are observing a resurgence of whooping cough due to evolution of the pathogen and waning vaccine immunity. The use of vaccines decreased the need for basic research on this pathogen. As a result, numerous questions on the basic pathogenesis of B. pertussis remain to be answered. Microarrays and more recently, RNA sequencing (RNAseq), have allowed the field to describe the in vitro gene expression profiles of the pathogen growing in both virulent and avirulent phases; however, no published studies have described an in vivo transcriptome of the pathogen. To address this need, we have designed and evaluated workflows to characterize the in vivo transcriptome of B. pertussis during infection of the murine lung. During our initial studies, we observed that only 0.014% of the ~100 million 2x50bp illumina reads corresponded to the pathogen, which is insufficient for analysis. Therefore, we developed a simple protocol to filter the bacteria out of the tissue homogenates and separate bacterial cells from the host tissue. RNA is then prepared, quantified, and the B. pertussis to host RNA ratio is determined. Here, we present the protocol and discuss the uses and next directions for which this RNAseq workflow can be applied. With this strategy we plan to fully characterize the B. pertussis transcriptome when the pathogen is infecting the murine lung in order to identify expressed genes that encode potential new vaccine antigens that will facilitate the development of the next generation of pertussis vaccines.

microbiology↗