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Biology subjects

Nguyen, M. K.

Publications and source records attributed to Nguyen, M. K..

4 recordsLinked to original sources

Robust fluorescent labeling and tracking of endogenous non-repetitive genomic loci

The spatial organization and dynamics of a genome are central to gene regulation. While a comprehensive understanding of chromatin organization in the human nucleus has been achieved using fixed-cell methods, measuring the dynamics of specific genomic regions over extended periods in individual living cells remains challenging. Here, we present a robust and fully genetically encoded system for fluorescent labeling and long-term tracking of any accessible non-repetitive genomic locus in live human cells using fluorogenic and replenishable nanobody array fusions of the Staphylococcus aureus dCas9, and compact polycistronic single guide (sg)RNAs. First, we characterize the selectivity and photostability of our probes, enabling genome-wide visualization of chromatin dynamics at locally repetitive elements. Next, through multiplexed expression of 8-10 sgRNAs from polycistronic cassettes, we demonstrate efficient and sustained labeling of non-repetitive loci, enabling high-fidelity tracking of gene-proximal regions at exceptional spatial and temporal resolution. Finally, by correlating chromatin mobility with transcriptional activity at multiple genes, we find that local chromatin dynamics at 20 Hz are gene-specific and not necessarily dependent on transcription. Our approach is versatile, minimally invasive, and scalable, enabling multiplexed imaging of regulatory element dynamics involved in gene control, with broad applicability across diverse biological systems and disease contexts.

biophysics↗

Oblique Line Scan Illumination Enables Expansive, Accurate and Sensitive Single Protein Measurements in Solution and in Living Cells

Single-molecule localization microscopy (SMLM) techniques, such as single-molecule tracking (SMT), enable in situ measurements in cells from which data-rich metrics can be extracted. SMT has been successfully applied to a variety of biological questions and model systems, aiming to unravel the spatiotemporal regulation of molecular mechanisms that govern protein function, downstream pathway effects, and cellular function. While powerful, SMLM often suffers from low throughput and illumination inhomogeneity, along with microscope and user-induced technical biases. Due to technical limitations in scaling SMLM techniques, a tradeoff between spatiotemporal resolution and throughput has been made historically, restricting broad application of these technologies. Here we address these limitations using Oblique Line Scan (OLS), a robust single-objective light-sheet based illumination and detection modality that achieves nanoscale spatial resolution and sub-millisecond temporal resolution across a 250 x 190 m field of view. We demonstrate OLS-enabled SMT on Halo-Tagged proteins in living cells capturing protein motion up to 14 m2 /s. By exploiting the adaptability of the acquisition frame rate and the improved rejection of out of focus light, we extend the utility of OLS beyond cellular compartments with in-solution SMT (isSMT) for single-molecule measurement of ligand-protein interactions and disruption of protein-protein interactions (PPI). We illustrate the versatility of OLS by showcasing two-color SMT, STORM, and single molecule fluorescence recovery after photobleaching (FRAP). OLS expands the range of SMLM applications and paves the way for robust, high-throughput single-molecule investigations of protein dynamics required for drug screening and systems biology studies, both in cells and in solution.

biophysics↗

ODNA: Identification of Organellar DNA by Machine Learning

MotivationIdentifying organellar DNA, such as mitochondrial or plastid sequences, inside a whole genome assembly, remains challenging and requires biological background knowledge. To address this, we developed ODNA based on genome annotation and machine learning to fulfill. ResultsODNA is a software that performs organellar DNA sequence classification of a genome assembly by machine learning based on a pre-defined genome annotation workflow. We trained our model with 829,769 DNA sequences from 405 genome assemblies and achieved very high predictive performance (e.g., MCC of 0.61) on independent validation data, thus outperforming existing approaches significantly. AvailabilityOur software ODNA is freely accessible as a web service at https://odna.mathematik.uni-marburg.de and can also be run in a docker container. The source code can be found at https://gitlab.com/mosga/odna and the processed data at Zenodo (DOI: 10.5281/zenodo.7506483).

bioinformatics↗

PRE-CLINICAL IMMUNE RESPONSE AND SAFETY EVALUATION OF THE PROTEIN SUBUNIT VACCINE NANOCOVAX FOR COVID-19

The Coronavirus disease-2019 (COVID-19) pandemic caused by the Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2), has become a dire global health concern. The development of vaccines with high immunogenicity and safety is crucial for control of the global COVID-19 pandemic and prevention of further illness and fatalities. Here, we report development of SARS-CoV-2 vaccine candidate, Nanocovax, based on recombinant protein production of the extracellular (soluble) portion of the S protein of SARS-CoV-2. The results showed that Nanocovax induced high levels of S protein-specific IgG, as well neutralizing antibody in three animal models including Balb/C mice, Syrian hamsters, and non-human primate (Macaca leonina). In addition, the viral challenge study using the hamster model showed that Nanocovax protected the upper respiratory tract from SARS-CoV-2 infection. No adverse effects were induced by Nanocovax in swiss mice (Musmusculus var. Albino), Rats (Rattus norvegicus), and New Zealand rabbits. These pre-clinical results indicated that Nanocovax is safe and effective.

immunology↗