Biology subjects

Cheung, Y. F.

Publications and source records attributed to Cheung, Y. F..

3 recordsLinked to original sources

bioRxiv2024

CIWARS: a web server for waterborne antibiotic resistance surveillance using longitudinal metagenomic data

The rise of antibiotic resistance (AR) is a major global health crisis, exacerbated by the overuse and misuse of antibiotics, leading to the rapid spread of antibiotic resistance genes (ARGs) in bacterial pathogens. This phenomenon poses significant threats to human and animal health, food security, and economic stability. Water bodies, particularly wastewater treatment plants (WWTPs), serve as critical reservoirs for ARGs, creating environments that favor the proliferation of resistant bacteria. Wastewater-based surveillance (WBS) has emerged as a cost-effective strategy for monitoring AR at the population level, providing real-time data to guide public health and policy decisions. Despite advancements in WBS, there are no comprehensive online analytical platforms for continuous environmental AR surveillance. This paper introduces CIWARS, a web server designed for AR analyses of longitudinal metagenomic data. CIWARS offers comprehensive ARG profiling, taxonomic annotation, and anomalous AR risk points detection. We demonstrate its capabilities through an interactive temporal data visualization, showcasing its potential for enhancing AR risk monitoring and guiding effective mitigation strategies. CIWARS is broadly applicable to longitudinal metagenomic data generated from any environment and aims to support global efforts in addressing the AR crisis by providing cyberinfrastructure for continuous AR surveillance. The web server is freely available at https://ciwars.cs.vt.edu/.

bioinformatics↗

bioRxiv2023

Kairos infers in situ horizontal gene transfer in longitudinally sampled microbiomes through microdiversity-aware sequence analysis

Horizontal gene transfer (HGT) occurring within microbiomes is linked to complex environmental and ecological dynamics that are challenging to replicate in controlled settings. Consequently, most extant studies of microbiome HGT are either simplistic experimental settings with tenuous relevance to real microbiomes or correlative studies that assume that HGT potential is a function of the relative abundance of mobile genetic elements (MGEs), the vehicles of HGT. Here we introduce Kairos as a bioinformatic tool deployed in nextflow for detecting HGT events "in situ," i.e., within a microbiome, through analysis of time-series metagenomic sequencing data. The in-situ framework proposed here leverages available metagenomic data from a longitudinally sampled microbiome to assess whether the chronological occurrence of potential donors, recipients, and putatively transferred regions could plausibly have arisen due to HGT over a range of defined time periods. The centerpiece of the Kairos workflow is a novel competitive read alignment method that enables discernment of even very similar genomic sequences, such as those produced by MGE-associated recombination. A key advantage of Kairos is its reliance on assemblies rather than metagenome assembled genomes (MAGs), which avoids systematic exclusion of accessory genes associated with the binning process. In an example test-case of real world data, use of assemblies directly produced a 264-fold increase in the number of antibiotic resistance genes included in the analysis of HGT compared to analysis of MAGs with MetaCHIP. Further, in silico evaluation of contig taxonomy was performed to assess the accuracy of classification for both chromosomally- and MGE-derived sequences, indicating a high degree of accuracy even for conjugative plasmids up to the level of class or order. Thus, Kairos enables the analysis of very recent HGT events, making it suitable for studying rapid prokaryotic adaptation in environmental systems without disturbing the ornate ecological dynamics associated with microbiomes. Current versions of the Kairos workflow are available here: https://github.com/clb21565/kairos.

bioinformatics↗

bioRxiv2023

APLNR marks a cardiac progenitor derived with human induced pluripotent stem cells

Cardiomyocytes can be readily derived from human induced pluripotent stem cell (hiPSC) lines, yet its efficacy varies across different batches of the same and different hiPSC lines. To unravel the inconsistencies of in vitro cardiac differentiation, we utilized single cell transcriptomics on hiPSCs undergoing cardiac differentiation and identified cardiac and extra-cardiac lineages throughout differentiation. We further identified APLNR as a surface marker for in vitro cardiac progenitors and immunomagnetically isolated them. Differentiation of isolated in vitro APLNR+ cardiac progenitors derived from multiple hiPSC lines resulted in predominantly cardiomyocytes accompanied with cardiac mesenchyme. Transcriptomic analysis of differentiating in vitro APLNR+ cardiac progenitors revealed transient expression of cardiac progenitor markers before further commitment into cardiomyocyte and cardiac mesenchyme. Analysis of in vivo human and mouse embryo single cell transcriptomic datasets have identified APLNR expression in early cardiac progenitors of multiple lineages. This platform enables generation of in vitro cardiac progenitors from multiple hiPSC lines without genetic manipulation, which has potential applications in studying cardiac development, disease modelling and cardiac regeneration.

cell biology↗