Biology subjects

Nguyen, H.

Publications and source records attributed to Nguyen, H..

At least 73 records · Page 4Linked to original sources

bioRxiv2024

Navigating directed evolution efficiently: optimizing selection conditions and selection output analysis

Directed evolution is a powerful tool that can bypass gaps in our understanding of the sequence-function relationship of proteins and still isolate variants with desired activities, properties, and substrate specificities. The rise of directed evolution platforms for polymerase engineering has accelerated the isolation of xenobiotic nucleic acids (XNAs) synthetases and reverse transcriptases (RTs) capable of processing a wide array of unnatural XNAs which have numerous therapeutic and biotechnological applications. Still, the current generation of XNA polymerases functions with significantly lower efficiency than the natural counterparts and retains a significant level of DNA polymerase activity which limits their in vivo applications. Although directed evolution approaches are continuously being developed and implemented to improve XNA polymerase engineering, the field lacks an in-depth analysis of the effect of selection parameters, library construction biases and sampling biases. Focusing on the directed evolution pipeline for DNA and XNA polymerase engineering, this work sets out a method for understanding the impact of selection conditions on selection success and efficiency. We also explore the influence of selection conditions on fidelity at the population and individual mutant level. Additionally, we explore the sequencing coverage requirements in directed evolution experiments, which differ from genome assembly and other -omics approaches. This analysis allowed us to identify the sequencing coverage threshold for the accurate and precise identification of significantly enriched mutants. Overall, this study introduces a robust methodology for optimizing selection protocols, which effectively streamlines selection processes by employing small libraries and cost-effective NGS sequencing. It provides valuable insights into critical considerations, thereby enhancing the overall effectiveness and efficiency of directed evolution strategies applicable to enzymes other than the ones considered here.

synthetic biology↗

bioRxiv2024

Predictive biomarkers of breast ductal carcinoma in situ may underestimate the risk of recurrence due to de novo ipsilateral breast carcinoma development

Development of ipsilateral breast carcinoma following diagnosis of breast ductal carcinoma in situ (DCIS) has been assumed to represent recurrence of the primary tumour. However, this may not be the case and it is important to know how often recurrences are new tumours. Ipsilateral primary-recurrence pairs (n=78) were sequenced to test their clonal relatedness. Shared genetic events were identified from whole exome sequencing (n=54 pairs) using haplotype-specific copy number and phylogenetic analysis. The remaining pairs were sequenced by a targeted panel or low-coverage whole genome sequencing. We included 32 non-recurrent DCIS to compare recurrent and non-recurrent disease. We found that 7% of DCIS recurrences were non-clonal by whole exome sequencing, indicative of a new breast carcinoma. Lower resolution methods detected a higher non-clonality rate (29%). Comparing primary DCIS with their recurrences found that evolution of DCIS to invasive disease was associated with increased ploidy and copy number events. TP53 mutations were enriched in DCIS with clonal recurrence compared with non-recurrent DCIS. Our results verify that de novo "recurrent tumours" of independent origin occur in patients who may be at high risk.

cancer biology↗

bioRxiv2024

Worldwide study of the taste of bitter medicines and their modifiers

The bitter taste of medicines hinders patient compliance, but not everyone experiences these difficulties because people worldwide differ in their bitterness perception. To better understand how people from diverse ancestries perceive medicines and taste modifiers, 338 adults, European and recent US and Canada immigrants from Asia, South Asia, and Africa, rated the bitterness intensity of taste solutions on a 100-point generalized visual analog scale and provided a saliva sample for genotyping. The taste solutions were five medicines, tenofovir alafenamide (TAF), moxifloxacin, praziquantel, amodiaquine, and propylthiouracil (PROP), and four other solutions, TAF mixed with sucralose (sweet, reduces bitterness) or 6-methylflavone (tasteless, reduces bitterness), sucralose alone, and sodium chloride alone. Bitterness ratings differed by ancestry for two of the five drugs (amodiaquine and PROP) and for TAF mixed with sucralose. Genetic analysis showed that people with variants in one bitter receptor variant gene (TAS2R38) reported PROP was more bitter than did those with a different variant (p= 7.6e-19) and that people with either an RIMS2 or a THSD4 genotype found sucralose more bitter than did others (p=2.6e-8, p=7.9e-11, resp.). Our findings may help guide the formulation of bad- tasting medicines to meet the needs of those most sensitive to them.

physiology↗

bioRxiv2024

Deep learning-based detection of murine congenital heart defects from μCT scans

Congenital heart defects (CHD) result in high morbidity and mortality rates, but their origins are poorly understood. Mouse models of heart morphogenesis are required to study the pathological mechanisms of heart development compared to normal. In mouse fetuses, CHD can be observed and detected in 3D images obtained by thoracic micro-computed tomography (CT). However, diagnosis of CHD from CT scans is a time-consuming process that requires the experience of senior experts. An automated alternative would thus save time, empower less experienced investigators and could broaden analysis to larger numbers of samples. Here, we describe and validate an approach based on deep learning to automatically segment the heart and screen normal from malformed hearts in mouse CT scans. In an initial cohort, we collected 139 CT scans from thorax and abdomen of control and mutant perinatal mice. We trained a self-configurating neural network (nnU-Net) to segment hearts from body CT scans and validated its performance on expert segmentations, achieving a Dice coefficient of 96%. To identify malformed hearts, we developed and trained a 3D convolutional neural network (CNN) that uses segmented CT scans as inputs. Despite the relatively small training data size, our diagnosis model achieved a sensitivity, specificity (for a 0.5 threshold), and area under the curve (AUC) of 92%, 96%, and 97% respectively, as determined by 5-fold cross-validation. As further validation, we analyzed two additional cohorts that were collected after the model was trained: a prospective cohort, using the same experimental protocol as the initial cohort, and containing a subset of its genotypes, and a divergent cohort in which mice were subjected to a different treatment for heart arrest (cardioplegia) and that contained a new mouse line. Performance on the prospective cohort was excellent, with a sensitivity of 92%, a specificity of 100%, and an AUC of 100%. Performance on the divergent cohort was moderate (sensitivity: 69%, specificity: 80% and AUC: 81%), but was much improved when the model was finetuned on (a subset of) the cohort (sensitivity: 79%, specificity: 88% and AUC: 91%). These results showcase our models robustness and adaptability to technical and biological differences in the data, highlighting its usefulness for practical applications. In order to facilitate the adoption, adaptation and further improvement of these methods, we built a user-friendly Napari plugin (available at napari-hub.org/plugins/mousechd-napari) that allows users without programming skills to utilize the segmentation and diagnosis models and re-train the latter on their own data and resources. The plugin also highlights the cardiac regions used for the diagnosis. Our automatic and retrainable pipeline, which can be employed in high-throughput genetic screening, will accelerate diagnosis of heart anomalies in mice and facilitate studies of the mechanisms of CHD.

developmental biology↗

bioRxiv2024

BET inhibitors as a therapeutic intervention in gastrointestinal gene signature-positive castration-resistant prostate cancer.

A subgroup of castration-resistant prostate cancer (CRPC) aberrantly expresses a gastrointestinal (GI) transcriptome governed by two GI-lineage-restricted transcription factors, HNF1A and HNF4G. In this study, we found that expression of GI transcriptome in CRPC correlates with adverse clinical outcomes to androgen receptor signaling inhibitor treatment and shorter overall survival. Bromo- and extra-terminal domain inhibitors (BETi) downregulated HNF1A, HNF4G, and the GI transcriptome in multiple CRPC models, including cell lines, patient-derived organoids, and patient-derived xenografts, while AR and the androgen-dependent transcriptome were largely spared. Accordingly, BETi selectively inhibited growth of GI transcriptome-positive preclinical models of prostate cancer. Mechanistically, BETi inhibited BRD4 binding at enhancers globally, including both AR and HNF4G bound enhancers while gene expression was selectively perturbed. Restoration of HNF4G expression in the presence of BETi rescued target gene expression without rescuing BRD4 binding. This suggests that inhibition of master transcription factors expression underlies the selective transcriptional effects of BETi. SIGNIFICANCEGI transcriptome expression in CRPC is regulated by the HNF1A-HNF4G-BRD4 axis and correlates with worse clinical outcomes. Accordingly, BET inhibitors significantly reduce tumor cell growth in multiple GI-transcriptome-positive preclinical models of CRPC. Our studies point that expression of GI transcriptome could serve as a predictive biomarker to BETi therapy response.

cancer biology↗

bioRxiv2024

Correlation measures in metagenomic data: the blessing of dimensionality

Microbiome analysis has revolutionized our understanding of various biological processes, spanning human health, epidemiology (including antimicrobial resistance and horizontal gene transfer), as well as environmental and agricultural studies. At the heart of microbiome analysis lies the characterization of microbial communities through the quantification of microbial taxa and their dynamics. In the study of bacterial abundances, it is becoming more relevant to consider their relationship, to embed these data in the framework of network theory, allowing characterization of features like node relevance, pathway and community structure. In this study, we address the primary biases encountered in reconstructing networks through correlation measures, particularly in light of the compositional nature of the data, within-sample diversity, and the presence of a high number of unobserved species. These factors can lead to inaccurate correlation estimates. To tackle these challenges, we employ simulated data to demonstrate how many of these issues can be mitigated by applying typical transformations designed for compositional data. These transformations enable the use of straightforward measures like Pearsons correlation to correctly identify positive and negative relationships among relative abundances, especially in high-dimensional data, without having any need for further corrections. However, some challenges persist, such as addressing data sparsity, as neglecting this aspect can result in an underestimation of negative correlations.

systems biology↗

bioRxiv2024

Epigenetic Control of Adaptive or Homeostatic Splicing of Alternative Exons and Prolactin Gene Expression During Interval-Training Activities of Pituitary Cells

Interval-training activities induce adaptive cellular changes without altering their fundamental identity, but the precise underlying molecular mechanisms are not fully understood. In this study, we demonstrate that interval-training depolarization (ITD) of pituitary cells triggers distinct adaptive or homeostatic splicing responses of alternative exons. This occurs while preserving the steady-state expression of the Prolactin and other hormone genes. The nature of these splicing responses depends on the exons DNA methylation status, the methyl-C-binding protein MeCP2 and its associated CA-rich motif-binding hnRNP L. Interestingly, the steady expression of the Prolactin gene is also reliant on MeCP2, whose disruption during ITD leads to exacerbated overexpression and multi-exon aberrant splicing of the hormone gene transcripts, similar to the observed hyperprolactinemia or activity-dependent aberrant splicing in Rett Syndrome. Therefore, depending on how many times cells are stimulated, exons may exhibit different splicing responses to cell activities. During the ITD, epigenetic control is crucial for both adaptive or homeostatic splicing and the steady expression of the Prolactin hormone gene. Disruption in this regulation may have significant implications for the development of progressive diseases.

cell biology↗

bioRxiv2024

CRM1 regulates androgen receptor stability and impacts DNA repair pathways in prostate cancer, independent of the androgen receptor.

Among the known nuclear exportins, CRM1 is the most studied prototype. Dysregulation of CRM1 occurs in many cancers, hence, understanding the role of CRM1 in cancer can help in developing synergistic therapeutics. The study investigates how CRM1 affects prostate cancer growth and survival. It examines the role of CRM1 in regulating androgen receptor (AR) and DNA repair in prostate cancer. Our findings reveal that CRM1 influences AR mRNA and protein stability, leading to a loss of AR protein upon CRM1 inhibition. Furthermore, it highlights the involvement of HSP90 alpha, a known AR chaperone, in the CRM1-dependent regulation of AR protein stability. The combination of CRM1 inhibition with an HSP90 inhibitor demonstrates potent effects on decreasing prostate cancer cell growth and survival. The study further explores the influence of CRM1 on DNA repair proteins and proposes a strategy of combining CRM1 inhibitors with DNA repair pathway inhibitors to decrease prostate cancer growth. Overall, the findings suggest that CRM1 plays a crucial role in prostate cancer growth, and a combination of inhibitors targeting CRM1 and DNA repair pathways could be a promising therapeutic strategy.

cancer biology↗

bioRxiv2024

REL2 overexpression in the Anopheles gambiae midgut causes major transcriptional changes but fails to induce an immune response

The NF-{kappa}B-like transcription factor, REL2, is a key player in the mosquito Immunodeficiency (Imd) pathway and holds promise for controlling malaria parasite infections in genetically modified Anopheles gambiae mosquitoes. We engineered transgenic mosquitoes overexpressing REL2 from within the bloodmeal-inducible zinc carboxypeptidase A1 (CP) host gene in the adult posterior midgut. Our results confirmed elevated REL2 expression in the posterior midgut following a bloodmeal, with the corresponding protein localized within epithelial cell nuclei. While this induced overexpression triggered substantial transcriptional changes, accompanied by notable fitness costs, the resultant reduction in Plasmodium falciparum infection was modest. An in-depth analysis of regulatory regions of differentially regulated genes allowed us to identify direct REL2 target genes and revealed signatures indicative of potential transcriptional repressors. To account for potential impacts of host gene modification, we also created a CP knockout line that caused marginal effects on mosquito fitness. These findings shed light on the observed absence of transcriptional activation and, in some cases, induced repression of antimicrobial peptides (AMPs) presumed to be under Imd pathway control. In conclusion, our study suggests that elevated REL2 expression in the posterior midgut may induce the upregulation of negative immune regulators, facilitating control over an otherwise unrestrained immune response, and that concurrent transcriptional derepression may be needed to effectively induce the mosquito immune response. This work contributes valuable insights into the intricate regulation of midgut immunity in malaria vector mosquitoes.

immunology↗

bioRxiv2024

Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease

To understand dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune and clinical markers of microbiomes from four body sites in 86 participants over six years. We found that microbiome stability and individuality are body-site-specific and heavily influenced by the host. The stool and oral microbiome were more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. Also, we identified individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlated across body sites, suggesting systemic coordination influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals showed altered microbial stability and associations between microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease. Study HighlightsO_LIThe stability of the human microbiome varies among individuals and body sites. C_LIO_LIHighly individualized microbial genera are more stable over time. C_LIO_LIAt each of the four body sites, systematic interactions between the environment, the host and bacteria can be detected. C_LIO_LIIndividuals with insulin resistance have lower microbiome stability, a more diversified skin microbiome, and significantly altered host-microbiome interactions. C_LI

microbiology↗

bioRxiv2024

Biochemical characterization of the Escherichia coli surfaceome: A focus on type I fimbriae and flagella.

The Escherichia coli surfaceome consists mainly of the large surface organelles expressed by the organism to navigate and interact with the surrounding environment. The current study focuses on type I fimbriae and flagella. These large polymeric surface organelles are composed of hundreds to thousands of subunits, with their large size often preventing them from being studied in their native form. Recent studies are accumulating which demonstrate the glycosylation of surface proteins or virulence factors in pathogens, including E. coli. Using biochemical and glycobiological techniques, including biotin-hydrazide labelling of glycans and chemical and glycosidase treatments, we demonstrate i) the presence of a well-defined and chemically resistant FimA oligomer in several strains of pathogenic and non-pathogenic E. coli, ii) the major subunit of type I fimbriae, FimA, in pathogenic and laboratory strains is recognized by concanavalin A, iii) standard methods to remove N-glycans (PNGase F) or a broad-specificity mannosidase fail to remove the glycan structure, despite the treatments resulting in altered migration in SDS-PAGE, iv) PNGase F treatment results in a novel 32 kDa band recognized by anti-FliC antiserum. While the exact identity of the glycan(s) and their site of attachment currently elude detection by conventional glycomics/glycoproteomics, the current findings highlight a potential additional layer of complexity of the surface (glyco)proteome of the commensal or adhesive and invasive E. coli strains studied.

microbiology↗

bioRxiv2024

Invasion of glioma cells through confined space requires membrane tension regulation and mechano-electrical coupling via Plexin-B2

Glioblastoma (GBM) is a malignant brain tumor with uncontrolled invasive growth. Here, we demonstrate how GBM cells usurp guidance receptor Plexin-B2 to gain biomechanical plasticity for polarized migration through confined space. Using live-cell imaging to track GBM cells negotiating microchannels, we reveal active endocytosis at cell front and filamentous actin assembly at rear to propel GBM cells through constrictions. These two processes are interconnected and governed by Plexin-B2 that orchestrates cortical actin and membrane tension, shown by biomechanical assays. Molecular dynamics simulations predict that balanced membrane and actin tension are required for optimal migratory velocity and consistency. Furthermore, Plexin-B2 mechanosensitive function requires a bendable extracellular ring structure and affects membrane internalization, permeability, phospholipid composition, as well as inner membrane surface charge. Together, our studies unveil a key element of membrane tension and mechanoelectrical coupling via Plexin-B2 that enables GBM cells to adapt to physical constraints and achieve polarized confined migration.

cancer biology↗

bioRxiv2023

Benchmarking AlphaSC: A Leap in Single-Cell Data Processing

AO_SCPLOWBSTRACTC_SCPLOWWe benchmarked AlphaSC, BioTurings GPU-accelerated single-cell analytics package, against other popular tools including Scanpy, Seurat, and RAPIDS. The results demonstrate that AlphaSC operates thousands of times faster than Seurat and Scanpy. Additionally, it surpasses RAPIDS, another GPU-accelerated package from NVIDIA, by an order of magnitude in terms of speed while also consuming considerably less RAM and GPU memory. Importantly, this significant increase in AlphaSCs performance does not compromise its quality. 1

bioinformatics↗

bioRxiv2023

Pyruvate Oxidation Sustains B Cell Antigen-Specific Activation to Exacerbate MASH

B cells play a crucial role in the pathogenesis of metabolic dysfunction-associated steatohepatitis (MASH), a severe form of steatotic liver disease that if persistent can lead to cirrhosis, liver failure, and cancer. Chronic inflammation and fibrosis are key features of MASH that determine disease progression and outcomes. Recent advances have revealed that pathogenic B cell-derived cytokines and antibodies promote the development of MASH. However, the mechanisms through which B cells promote fibrosis and the metabolic adaptations underlying their pathogenic responses remain unclear. Here, we report that a subset of mature B cells with heightened cytokine responses accumulate in the liver and promote inflammation in MASH. To meet the increased energetic demand of effector responses, B cells increase their ATP production via oxidative phosphorylation (OXPHOS) fueled by pyruvate oxidation in a B cell receptor (BCR)-specific manner. Blocking pyruvate oxidation completely abrogated the inflammatory capacity of MASH B cells. Accordingly, the restriction of the BCR led to MASH attenuation, including reductions in steatosis, hepatic inflammation, and fibrosis. Mechanistically, BCR restriction decreased B cell maturation, activation, and effector responses in the liver, accompanied by decreased T cell- and macrophage-mediated inflammation. Notably, attenuated liver fibrosis in BCR-restricted mice was associated with lower IgG production and decreased expression of Fc-gamma receptors on hepatic stellate cells. Together, these findings indicate a key role for B cell antigen-specific responses in promoting steatosis, inflammation, and fibrosis during MASH.

physiology↗

bioRxiv2023

IC-VAE: A Novel Deep Learning Framework for Interpreting Multiplexed Tissue Imaging Data.

AO_SCPLOWBSTRACTC_SCPLOWInterpreting protein expression in multiplexed tissue imaging data presents a significant challenge due to the high dimensionality of the resulting images, the variety of intracellular structures, cell shapes resulting from 2-D tissue sectioning, and the presence of technological noise and imaging artifacts. Here, we introduce the Information-Controlled Variational Autoencoder (IC-VAE), a deep generative model designed to tackle this challenge. The contribution of IC-VAE to the VAE framework is the ability to control the shared information among latent subspaces. We use IC-VAE to factorize each cells image into its true protein expression, various cellular components, and background noise, while controlling the shared information among some of these components. Compared with other normalization methods, this approach leads to superior results in downstream analysis, such as analyzing the expression of biomarkers, classification for cell types, or visualizing cell clusters using t-SNE/UMAP techniques.

bioinformatics↗

bioRxiv2023

Small-molecule binding and sensing with a designed protein family

Despite transformative advances in protein design with deep learning, the design of small-molecule-binding proteins and sensors for arbitrary ligands remains a grand challenge. Here we combine deep learning and physics-based methods to generate a family of proteins with diverse and designable pocket geometries, which we employ to computationally design binders for six chemically and structurally distinct small-molecule targets. Biophysical characterization of the designed binders revealed nanomolar to low micromolar binding affinities and atomic-level design accuracy. The bound ligands are exposed at one edge of the binding pocket, enabling the de novo design of chemically induced dimerization (CID) systems; we take advantage of this to create a biosensor with nanomolar sensitivity for cortisol. Our approach provides a general method to design proteins that bind and sense small molecules for a wide range of analytical, environmental, and biomedical applications.

biochemistry↗

bioRxiv2023

Direct measures of liking and intensity of taste, smell, and chemesthetic stimuli are similar between young people reporting they did or did not have COVID-19

The recovery period from post-COVID-19 smell and taste dysfunctions varies substantially, lasting from a few days to over a year. We aimed to assess the impact of COVID-19 on post-COVID-19 chemosensory sensitivity in a group of young convalescents of eastern/central European ancestry. We measured subjects smell and taste capabilities with a standard testing kit, Monell Flavor Quiz (MFQ), and collected surveys on COVID-19 history. During testing, subjects rated liking and intensity of six odor samples (galaxolide, guaiacol, beta-ionone, trimethylamine, phenylethyl alcohol, 2-ethyl fenchol) and six taste samples (sucralose, sodium chloride, citric acid, phenylthiocarbamide, menthol, capsaicin) on a scale from 1 (dislike extremely, or no intensity) to 9 (like extremely, or extremely intense). There was no statistical difference in intensity ratings or liking of any sample between subjects who reported a history of COVID-19 (n = 34) and those reporting no history (n = 40), independent of presence/absence or severity of smell/taste impairments (P > 0.05). Additionally, neither vaccination status (full vaccination or no vaccination) nor time from the COVID-19 onset (2-27 months) correlated with liking or intensity. These results suggest that most young adults who had COVID-19 recovered their sense of smell and taste.

physiology↗

bioRxiv2023

Competition between stacking and divalent cation mediated electrostatic interactions determines the conformations of short DNA sequences

Interactions between divalent cations (Mg2+ and Ca2+) and highly charged single stranded DNA (ssDNA) and double stranded DNA (dsDNA), as well as stacking interactions, are important in a variety of problems, including nucleosome stability and phase separation in nucleic acids. Quantitative techniques accounting for ion-DNA interactions are needed to obtain insights into these and related problems. Towards this end, we created a computational model that explicitly takes into account monovalent and divalent ions, within the framework of the sequence-dependent coarse-grained Three Interaction Site (TIS) model for DNA. Molecular simulations of the rigid 24 base-pair (bp) dsDNA and flexible ssDNA sequences, dT30 and dA30, in a buffer containing Na+ and Cl-, with varying amounts of the divalent cations, are used to show that the calculated excess number of ions around the dsDNA and ssDNA agree quantitatively with ion-counting experiments. Using an ensemble of all-atom structures generated from coarse-grained simulations, we calculated the Small Angle X-ray Scattering (SAXS) profiles, which are also in excellent agreement with experiments. Strikingly, recapitulation of all the experimental findings was achieved without adjusting any of the parameters in the energy function to fit the data. At a molecular level, we find that Mg2+ and Ca2+ sense the differences between the major and minor grooves in dsDNA even though they are masked in ion-counting and SAXS experiments. The smaller Mg2+ binds predominantly to the minor grooves and phosphate groups whereas Ca2+ binds specifically only to the minor groove. The dA30 conformations are dominated by stacking interactions, resulting in structures with considerable helical order. In contrast, the near cancellation of the favorable stacking and unfavorable electrostatic interactions leads to dT30 populating an ensemble of heterogeneous conformations.

biophysics↗