Biology subjects

Ho, C. H.

Publications and source records attributed to Ho, C. H..

3 recordsLinked to original sources

bioRxiv2024

ASPYRE-Lung: Validation of a simple, fast, robust and novel method for multi-variant genomic analysis of actionable NSCLC variants in tissue

Genomic variant testing of tumors is a critical gateway for patients to access the full potential of personalized oncology therapeutics. Current methods such as next-generation sequencing are costly and challenging to interpret, while PCR assays are limited in the number of variants they can cover. We developed ASPYRE(R) (Allele-Specific PYrophosphorolysis REaction) technology to address the urgent need for rapid, accessible and affordable diagnostics informing actionable genomic target variants of a given cancer. The targeted ASPYRE-Lung panel for non-small cell carcinoma covers 114 variants in 11 genes (ALK, BRAF, EGFR, ERBB2, KRAS, RET, ROS1, MET & NTRK1/2/3) to robustly inform clinical management. The assay detects single nucleotide variants, insertions, deletions, and gene fusions from tissue-derived DNA and RNA simultaneously. We tested the limit of detection, specificity, analytical accuracy and analytical precision of ASPYRE-Lung using FFPE lung tissue samples from patients with non-small cell lung carcinoma, variant-negative FFPE tissue from healthy donors, and FFPE-based contrived samples with controllable variant allele fractions. The sensitivity of ASPYRE-Lung was determined to be [≤] 3% variant allele fraction for single nucleotide variants and insertions or deletions, 100 copies for fusions, and 200 copies for MET exon 14 skipping. The specificity was 100% with no false positive results. The analytical accuracy test yielded no discordant calls between ASPYRE-Lung and expected results for clinical samples (via orthogonal testing) or contrived samples, and results were replicable across operators, reagent lots, runs, and real-time PCR instruments with a high degree of precision. The technology is simple and fast, requiring only four reagent transfer steps using standard laboratory equipment (PCR and qPCR instruments) with analysis via a cloud-based analysis algorithm. The ASPYRE-Lung assay has the potential to be transformative in facilitating access to rapid, actionable molecular profiling of tissue for patients with non-small cell carcinoma.

cancer biology↗

bioRxiv2021

A gap-filling algorithm for prediction of metabolic interactions in microbial communities

The study of microbial communities and their interactions has attracted the interest of the scientific community, because of their potential for applications in biotechnology, ecology and medicine. The complexity of interspecies interactions, which are key for the macroscopic behavior of microbial communities, cannot be studied easily experimentally. For this reason, the modeling of microbial communities has begun to leverage the knowledge of established constraint-based methods, which have long been used for studying and analyzing the microbial metabolism of individual species based on genome-scale metabolic reconstructions of microorganisms. A main problem of genome-scale metabolic reconstructions is that they usually contain metabolic gaps due to genome misannotations and unknown enzyme functions. This problem is traditionally solved by using gap-filling algorithms that add biochemical reactions from external databases to the metabolic reconstruction, in order to restore model growth. However, gap-filling algorithms could evolve by taking into account metabolic interactions among species that coexist in microbial communities. In this work, a gap-filling method that resolves metabolic gaps at the community level was developed. The efficacy of the algorithm was tested by analyzing its ability to resolve metabolic gaps on a synthetic community of auxotrophic Escherichia coli strains. Subsequently, the algorithm was applied to resolve metabolic gaps and predict metabolic interactions in a community of Bifidobacterium adolescentis and Faecalibacterium prausnitzii, two species present in the human gut microbiota, and in an experimentally studied community of Dehalobacter and Bacteroidales species of the ACT-3 community. The community gap-filling method can facilitate the improvement of metabolic models and the identification of metabolic interactions that are difficult to identify experimentally in microbial communities. Author summaryMicrobes compose the most abundant form of life on our planet and they are almost never found in isolation, as they live in close association with one another and with other organisms. The metabolic capacity of individual microbial species dictates their ways of interaction with other species as well as with their environment. The metabolic interactions among microorganisms have been recognised as the driving force for the emergence of the properties of microbial communities. For this reason, understanding the effect of microbial metabolism on interspecies metabolic interactions is detrimental for the study of microbial communities. This study can be benefited by metabolic modeling and the insights offered by constraint-based methods which have been developed for interrogating metabolic models. In this paper, we present an algorithm that predicts cooperative and competitive metabolic interactions between species, while it resolves metabolic gaps in their metabolic models in a computationally efficient way. We use our community gap-filling algorithm to study microbial communities with interesting environmental and health-related applications.

systems biology↗

bioRxiv2021

An exon junction complex-independent function of Barentsz in neuromuscular synapse growth

The exon junction complex controls the translation, degradation and localization of spliced mRNAs, and three of its four core subunits also play a role in splicing. Here we show that the fourth subunit, Barentsz, has distinct biological functions within and separate from the exon junction complex in neuromuscular development. Barentsz controls the distribution of mitochondria in larval muscles, a function that also depends on other subunits of the exon junction complex and that is not rescued by a transgene in which residues required for binding to the core subunit eIF4AIII are mutated. In contrast, interactions with the exon junction complex are not required for Barentsz to promote the growth of neuromuscular synapses. We found that the Activin ligand Dawdle shows reduced expression in barentsz mutants and acts downstream of Barentsz to control synapse growth. Both barentsz and dawdle are required in motor neurons, muscles and glia for normal synapse growth, and exogenous Dawdle can rescue synapse growth in the absence of barentsz. These results identify a biological function for Barentsz that is independent of the exon junction complex.

developmental biology↗