Biology subjects

Nguyen, S. H.

Publications and source records attributed to Nguyen, S. H..

7 recordsLinked to original sources

bioRxiv2025

To the homeRNAmax: Developing an Improved Blood Self-Collection and Stabilization Platform for Remote Transcriptomic Studies

Shifting human subjects research from research sites to participants homes removes barriers to participation, including transportation and scheduling difficulties. Previously, we developed homeRNA, a kit for immediate stabilization of RNA in self-collected blood using a custom-engineered tube containing RNA stabilizer fluid. The stabilized RNA is extracted and used for downstream gene expression analysis. Here, we introduce homeRNAmax, which improves our original design by interfacing with a commercially available blood collection tube (BD Microtainer), allowing homeRNAmax to be used with any blood collection method that uses this tube and doubling the possible sample volume that can be collected and stabilized compared to the original homeRNA. Through a pilot study (n=19 participants), we show that homeRNAmax (with the Tasso+ blood collection device) produces RNA samples of sufficient quality (mean RIN=7.8) and yield (mean yield=1.93 g) for downstream analysis and can reach participants across the United States, who generally (n=17/19) found the homeRNAmax kit easy to use. A key aspect of the homeRNA and homeRNAmax platforms is a fluidic feature that prevents the RNA stabilizer from spilling, however our previous work had not yet fully characterized the mechanism of this feature. Here, we developed a theoretical model of the spill-resistant feature. In brief, fluid in the tube is suspended due to a balance of pressures; an increase in air volume within the tube reduces the air pressure above the fluid, creating a small vacuum, and preventing fluid leakage. Overall, we show that homeRNAmax is a user-friendly, effective tool for remote blood RNA stabilization.

bioengineering↗

bioRxiv2024

Suspended Tissue Open Microfluidic Patterning (STOMP)

Free-standing tissue structures tethered between pillars are powerful mechanobiology tools for studying cell contraction. To model interfaces ubiquitous in natural tissues and upgrade existing single-region suspended constructs, we developed Suspended Tissue Open Microfluidic Patterning (STOMP), a method to create multi-regional suspended tissues. STOMP uses open microfluidics and capillary pinning to pattern subregions within free-standing tissues, facilitating the study of complex tissue interfaces, such as diseased-healthy boundaries (e.g., fibrotic-healthy) and tissue-type interfaces (e.g., bone-ligament). We observed altered contractile dynamics in fibrotic-healthy engineered heart tissues compared to single-region tissues and differing contractility in bone-ligament enthesis constructs compared to single-tissue periodontal ligament models. STOMP is a versatile platform - surface tension-driven patterning removes material requirements common with other patterning methods (e.g., shear-thinning, photopolymerizable) allowing tissue generation in multiple geometries with native extracellular matrices and advanced 4D materials. STOMP combines the contractile functionality of suspended tissues with precise patterning, enabling dynamic and spatially controlled studies.

bioengineering↗

bioRxiv2024

AMRomics: a scalable workflow to analyze large microbial genome collection

Whole genome analysis for microbial genomics is critical to studying and monitoring antimicrobial resistance strains. The exponential growth of microbial sequencing data necessitates a fast and scalable computational pipeline to generate the desired outputs in a timely and cost-effective manner. Recent methods have been implemented to integrate individual genomes into large collections of specific bacterial populations and are widely employed for systematic genomic surveillance. However, they do not scale well when the population expands and turnaround time remains the main issue for this type of analysis. Here, we introduce AMRomics, a minimalized microbial genomics pipeline that can work efficiently with big datasets. We use different bacterial data collections to compare AMRomics against competitive tools and show that our pipeline can generate similar results of interest but with better performance. The software is open source and is publicly available at https://github.com/amromics/amromics under an MIT license.

bioinformatics↗

bioRxiv2023

Pasa: Leverage population pangenome graph to scaffold prokaryote genome assemblies.

Whole genome sequencing has increasingly become the essential method for studying the genetic mechanisms of antimicrobial resistance and for surveillance of drug-resistant bacterial pathogens. The majority of bacterial genomes sequenced to date have been sequenced with Illumina sequencing technology, owing to its high-throughput, excellent sequence accuracy, and low cost. However, because of the short-read nature of the technology, these assemblies are fragmented into large numbers of contigs, hindering the obtaining of full information of the genome. We develop Pasa, a graph-based algorithm that utilizes the pangenome graph and the assembly graph information to improve scaffolding quality. By leveraging the population information of the bacteria species, Pasa is able to utilize the linkage information of the gene families of the species to resolve the contig graph of the assembly. We show that our method outperforms the current state of the art in terms of accuracy, and at the same time, is computationally efficient to be applied to a large number of existing draft assemblies.

bioinformatics↗

bioRxiv2021

HiC-TE: a computational pipeline for Hi-C data analysis shows a possible role of repeat family interactions in the genome 3D organization

The role of repetitive DNA in the 3D organization of the interphase nucleus in plant cells is a subject of intensive study. High-throughput chromosome conformation capture (Hi-C) is a sequencing-based method detecting the proximity of DNA segments in nuclei. We combined Hi-C data, plant reference genome data and tools for the characterization of genomic repeats to build a Nextflow pipeline identifying and quantifying the contacts of specific repeats revealing the preferential homotypic interactions of ribosomal DNA, DNA transposons and some LTR retrotransposon families. We provide a novel way to analyze the organization of repetitive elements in the 3D nucleus.

bioinformatics↗

bioRxiv2019

Analysis of polyclonal vector integration sites using Nanopore sequencing as a scalable, cost-effective platform

Vector integration site analysis can be important in the follow-up of patients who received gene-modified cells, but current platforms based on next-generation sequencing are expensive and relatively inaccessible. We analyzed polyclonal T cells transduced by a gammaretroviral vector, SFG.iCasp9.2A.{Delta}CD19, from a clinical trial. Following restriction enzyme digestion, the unknown flanking genomic sequences were amplified by inverse polymerase chain reaction (PCR) or cassette ligation PCR. Nanopore sequencing could identify thousands of unique integration sites within polyclonal samples, with cassette ligation PCR showing less bias. The assay is scalable and requires minimum capital, which together enable cost-effective and timely analysis.

genomics↗

bioRxiv2017

Real-Time Demultiplexing Nanopore Barcoded Sequencing Data With npBarcode

MotivationThe recently introduced barcoding protocol to Oxford Nanopore sequencing has increased the versatility of the technology. Several bioinformatic tools have been developed to demultiplex the barcoded reads, but none of them support the streaming analysis. This limits the use of pooled sequencing in real-time applications, which is one of the main advantages of the technology.\n\nResultsWe introduced npBarcode, an open source and cross platform tool for barcode demultiplex in streaming fashion. npBarcode can be seamlessly integrated into a streaming analysis pipeline. The tool also provides a friendly graphical user interface through npReader, allowing the real-time visual monitoring of the sequencing progress of barcoded samples. We show that npBarcode achieves comparable accuracies to the other alternatives.\n\nAvailabilitynpBarcode is bundled in Japsa - a Java tools kit for genome analysis, and is freely available at https://github.com/hsnguyen/npBarcode.

bioinformatics↗