Biology subjects

Nguyen, T.

Publications and source records attributed to Nguyen, T..

At least 109 records · Page 6Linked to original sources

bioRxiv2024

Select autosomal dominant DFNA11 deafness mutations activate Myo7A in epithelial cells

Myosin-7A (Myo7A) is a motor protein crucial for the organization and function of stereocilia, specialized actin-rich protrusions on the surface of inner ear hair cells that mediate hearing. Mutations in Myo7A cause several forms of genetic hearing loss, including autosomal dominant DFNA11 deafness. Despite its importance, the structural elements of Myo7A that control its motor activity within cells are not well understood. In this study, we used cultured kidney epithelial cells to screen for mutations that activate the motor-dependent targeting of Myo7A to the tips of apical microvilli on these cells. Our findings reveal that Myo7A is regulated by specific IQ motifs within its lever arm, and that this regulation can function at least partially independent of its tail sequence. Importantly, we demonstrate that many of the DFNA11 deafness mutations reported in patients activate Myo7A targeting, providing a potential explanation for the autosomal dominant genetics of this form of deafness.

cell biology↗

bioRxiv2024

53BP1 deficiency leads to hyperrecombination using break-induced replication (BIR)

Break-induced replication (BIR) is mutagenic, and thus its use requires tight regulation, yet the underlying mechanisms remain elusive. Here we uncover an important role of 53BP1 in suppressing BIR after end resection at double strand breaks (DSBs), distinct from its end protection activity, providing insight into the mechanisms governing BIR regulation and DSB repair pathway selection. We demonstrate that loss of 53BP1 induces BIR-like hyperrecombination, in a manner dependent on Pol-primase-mediated end fill-in DNA synthesis on single-stranded DNA (ssDNA) overhangs at DSBs, leading to PCNA ubiquitination and PIF1 recruitment to activate BIR. On broken replication forks, where BIR is required for repairing single-ended DSBs (seDSBs), SMARCAD1 displaces 53BP1 to facilitate the localization of ubiquitinated PCNA and PIF1 to DSBs for BIR activation. Hyper BIR associated with 53BP1 deficiency manifests template switching and large deletions, underscoring another aspect of 53BP1 in suppressing genome instability. The synthetic lethal interaction between the 53BP1 and BIR pathways provides opportunities for targeted cancer treatment.

molecular biology↗

bioRxiv2024

A cell and transcriptome atlas of the human arterial vasculature

Contiguous arterial segments show different propensities for different vascular pathologies, yet mechanisms explaining these fundamental differences remain unknown. We sought to build a transcriptomic, cellular, and spatial atlas of human arterial cells across multiple different arterial segments to understand these underlying differences. Analysis of multiple isogenic arterial segments from healthy donors reveals a significant stereotyped pattern of cell type-specific segmental heterogeneity in healthy arteries. Combining single cell analysis with spatial transcriptomic data reveals cellular heterogeneity not captured by commonly used cell-type marker genes. Determinants of arterial transcriptomic identities are predominantly encoded in fibroblasts and smooth muscle cells (SMC), and their differentially expressed genes are particularly enriched for different vascular disease-associated genetic risk- loci and risk-genes. Adventitial fibroblast-specific heterogeneity in gene expression coincides with a disproportionally large number of vascular disease genetic signals, suggesting a previously unrecognized role for this cell type in disease risk. Adult arterial cells from different segments cluster not by anatomical proximity, but by embryonic origin. Global regulon analysis of disease related segment-specific gene expression program in fibroblast and SMC enriches for binding sites of transcription factors that are developmental master regulators whose expression persists into adulthood, suggesting an important functional role of the same developmental master regulators in adult gene expression and disease. Lastly, non-coding transcriptomes across arterial cells contain extensive variation in lncRNAs expressed in cell type- and segment-specific patterns, rivaling heterogeneity in protein coding transcriptomes. Differentially expressed LncRNA demonstrate enrichment for non-coding genetic signals for vascular diseases, suggesting a potential global role of segmental specific LncRNAs in regulating inherited human vascular disease risk.

cell biology↗

bioRxiv2024

Biophysical Simulation Enables Multi-Scale Segmentation and Atlas Mapping for Top-Down Spatial Omics of the Nervous System

Spatial omics (SO) has produced high-definition mapping of subcellular molecules (like transcripts or proteins) within tissue samples. Mapping transcripts to anatomical regions requires segmentation, but even segmenting nuclei remains challenging for tissues like nerve cross sections, let alone for larger regions such as within the spinal cord. Neural networks could address this but need extensive human annotations--a bottleneck. We present SiDoLa-NS (Simulate, Dont Label - Nervous System), an image-driven (top-down) approach to SO analysis in the nervous system. We utilize biophysical properties of tissue architectures to design synthetic images mimicking tissue samples. With these in silico samples, we train supervised instance segmentation convolutional neural networks (CNNs) for nucleus segmentation, achieving precision and F1-scores > 0.95. We take this a step further with generalizable CNNs that can identify macroscopic tissue structures in the mouse brain (mAP50 = 0.869), spinal cord (mAP50 = 0.96), and pig sciatic nerve (mAP50 = 0.995). Short SummaryThe SiDoLa-NS micro-, meso-, and macro-scale models are generalizable, supervised CNNs for neuronal segmentation in cell to tissue-level contexts. SiDoLa-NS is novel in its combination of three core ideas: it is top-down (image first), trained solely on synthetic images, and it is multi-scale. The tool is validated on brain, spinal cord, and sciatic nerve for advanced segmentation tasks.

neuroscience↗

bioRxiv2024

Nomination of a novel plasma protein biomarker panel capable of classifying Alzheimer's disease dementia with high accuracy in an African American cohort

IntroductionAfrican Americans (AA) are widely underrepresented in plasma biomarker studies for Alzheimers disease (AD) and current diagnostic biomarker candidates do not reflect the heterogeneity of AD. MethodsUntargeted proteome measurements were obtained using the SomaScan 7k platform to identify novel plasma biomarkers for AD in a cohort of AA clinically diagnosed as AD dementia (n=183) or cognitively unimpaired (CU, n=145). Machine learning approaches were implemented to identify the set of plasma proteins that yields the best classification accuracy. ResultsA plasma protein panel achieved an area under the curve (AUC) of 0.91 to classify AD dementia vs CU. The reproducibility of this finding was observed in the ANMerge plasma and AMP-AD Diversity brain datasets (AUC=0.83; AUC=0.94). DiscussionThis study demonstrates the potential of biomarker discovery through untargeted plasma proteomics and machine learning approaches. Our findings also highlight the potential importance of the matrisome and cerebrovascular dysfunction in AD pathophysiology.

neuroscience↗

bioRxiv2024

Transformer Graph Variational Autoencoder for Generative Molecular Design

In the field of drug discovery, the generation of new molecules with desirable properties remains a critical challenge. Traditional methods often rely on SMILES (Simplified Molecular Input Line Entry System) representations for molecular input data, which can limit the diversity and novelty of generated molecules. To address this, we present the Transformer Graph Variational Autoencoder (TGVAE), an innovative AI model that employs molecular graphs as input data, thus captures the complex structural relationships within molecules more effectively than string models. To enhance molecular generation capabilities, TGVAE combines a Transformer, Graph Neural Network (GNN), and Variational Autoencoder (VAE). Additionally, we address common issues like over-smoothing in training GNNs and posterior collapse in VAE to ensure robust training and improve the generation of chemically valid and diverse molecular structures. Our results demonstrate that TGVAE outperforms existing approaches, generating a larger collection of diverse molecules and discovering structures that were previously unexplored. This advancement not only brings more possibilities for drug discovery but also sets a new level for the use of AI in molecular generation.

biophysics↗

bioRxiv2024

Goal-directed action preparation in humans entails a mixture of corticospinal neural computations

The seemingly effortless ability of humans to transition from thinking about actions to initiating them relies on sculpting corticospinal output from primary motor cortex. This study tested whether canonical additive and multiplicative neural computations, well-described in sensory systems, generalize to the corticospinal pathway during human action preparation. We used non-invasive brain stimulation to measure corticospinal input-output across varying action preparation contexts during instructed-delay finger response tasks. Goal-directed action preparation was marked by increased multiplicative gain of corticospinal projections to task-relevant muscles and additive suppression of corticospinal projections to non-selected and task-irrelevant muscles. Individuals who modulated corticospinal gain to a greater extent were faster to initiate prepared responses. Our findings provide physiological evidence of combined additive suppression and gain modulation in the human motor system. We propose these computations support action preparation by enhancing the contrast between selected motor representations and surrounding background activity to facilitate response selection and execution. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/602530v4_figa1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@9f2444org.highwire.dtl.DTLVardef@5f6eforg.highwire.dtl.DTLVardef@196f41corg.highwire.dtl.DTLVardef@1746035_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOC_FLOATNO Goal-directed action preparation shapes corticospinal output across selected, nonselected, and task-irrelevant motor representations. This study examined whether additive and multiplicative neural computations, common in sensory systems, occur within the corticospinal pathway during action preparation. We probed corticospinal input-output during the performance of various instructed-delay response tasks by applying a range of transcranial magnetic stimulation (TMS) intensities (input) over the primary motor cortex and measuring the resultant motor-evoked potentials (output) from the hand. We found that goal-directed action preparation increases corticospinal gain multiplicatively in task-relevant motor representations while additively suppressing nonselected and irrelevant representations. Greater gain modulation predicted faster responses, highlighting how these computations can enhance signal-to-noise (SNR) to enable efficient action selection and execution in the human motor system. C_FIG Key pointsO_LINeural computations determine what information is transmitted through brain circuits. C_LIO_LIWe investigated whether the motor system uses computations similar to those observed in sensory systems by noninvasively stimulating the corticospinal pathway in humans during goal-directed action preparation. C_LIO_LIWe discovered physiological evidence that corticospinal projections to behaviorally relevant muscles exhibit nonlinear gain computations, while projections to behaviorally irrelevant muscles exhibit linear suppression. C_LIO_LIOur findings suggest that certain computational principles generalize to the human motor system and serve to enhance the contrast between relevant and background neural activity. C_LIO_LIThese results indicate that neural computations during goal-directed action preparation may support motor control by increasing signal-to-noise within the corticospinal pathway. C_LI

neuroscience↗

bioRxiv2024

Smooth muscle expression of RNA editing enzyme ADAR1 controls vascular integrity and progression of atherosclerosis

Mapping the genomic architecture of complex disease has been predicated on the understanding that genetic variants influence disease risk through modifying gene expression. However, recent discoveries have revealed that a significant burden of disease heritability in common autoinflammatory disorders and coronary artery disease (CAD) is mediated through genetic variation modifying post-transcriptional modification of RNA through adenosine-to-inosine (A-to-I) RNA editing. This common RNA modification is catalyzed by ADAR enzymes, where ADAR1 edits specific immunogenic double stranded RNA (dsRNA) to prevent activation of the double strand RNA (dsRNA) sensor MDA5 (IFIH1) and stimulation of an interferon stimulated gene (ISG) response. Multiple lines of human genetic data indicate impaired RNA editing and increased dsRNA sensing by MDA5 to be an important mechanism of CAD risk. Here, we provide a crucial link between observations in human genetics and mechanistic cell biology leading to progression of CAD. Through analysis of human atherosclerotic plaque and culture of human coronary artery vascular smooth muscle cells (SMCs) we implicate the SMC to have a distinct requirement for RNA editing, and that MDA5 activation regulates SMC phenotypic modulation. Through generation of a conditional SMC specific Adar1 deletion mouse model on a pro-atherosclerosis background with additional constitutive deletion of MDA5 (Ifih1), and with incorporation of single cell RNA sequencing cellular profiling, we further show that Adar1 controls SMC phenotypic state by regulating Mda5 activation, is required to maintain vascular integrity, and controls progression of atherosclerosis and vascular calcification. Finally, we further corroborate our findings in a large human carotid endarterectomy dataset (Athero-Express) where we show that ISG activation is strongly associated with decreased plaque stability, increased SMC phenotypic modulation, and increased plaque calcification. Through this work, we describe a fundamental mechanism of CAD, where cell type and context specific RNA editing and sensing of dsRNA mediates disease progression, bridging our understanding of human genetics and disease causality. One Sentence SummarySmooth muscle expression of RNA editing enzyme ADAR1 regulates activation of double strand RNA sensor MDA5 in novel mechanism of atherosclerosis.

genomics↗

bioRxiv2024

Atypical contribution of caspase-3 to melanoma cancer cell motility by regulation of coronin 1B activity

Recent studies have unveiled unexpected connections between cell death and cell motility. While traditionally recognized for their pro-apoptotic roles, caspases have emerged as regulators of physiological processes beyond cell death, including cellular differentiation and motility. In some particularly aggressive cancers like melanoma, caspase-3, a prominent executioner caspase, is unexpectedly and inexplicably highly expressed. Here, we describe a novel non-apoptotic role for caspase-3 in melanoma cell motility. Through comprehensive molecular and cellular analyses, we demonstrate that caspase-3 is constitutively associated with the cytoskeleton and crucially regulates melanoma cell migration and invasion in vitro and in vivo. Mechanistically, caspase-3 interacts with and modulates the activity of coronin 1B, a key regulator of actin polymerization, thereby promoting melanoma cell motility, independently of its apoptotic protease function. Furthermore, we identify specificity protein 1 (SP1) as a transcriptional regulator of CASP3 expression, and show that its inhibition reduces caspase-3 expression and impairs melanoma cell migration. Overall, this study provides insights into the multifaceted roles of caspase-3 in cancer progression, highlighting its relevance as a novel target for anti-metastatic therapies.

cancer biology↗

bioRxiv2024

Cathartocytosis: How Cells Jettison Unwanted Material as They Reprogram

Injury can cause differentiated cells to undergo massive reprogramming to become proliferative to repair tissue via a cellular program called paligenosis. Gastric digestive-enzyme-secreting chief cells use paligenosis to reprogram into progenitor-like Spasmolytic-Polypeptide Expressing Metaplasia (SPEM) cells. Stage 1 of paligenosis is the downscaling of mature cell architecture via a process involving lysosomes. Here, we noticed that sulfated glycoproteins were not only digested during paligenosis but also excreted into the gland lumen. Various genetic and pharmacological approaches showed that endoplasmic reticulum membranes and secretory granule cargo were also excreted and that the process proceeded in parallel with, but was mechanistically independent of autophagy. 3-dimensional light and electron-microscopy demonstrated that excretion occurred via unique, complex, multi-chambered invaginations of the apical plasma membrane. As this lysosome-independent cell cleansing process does not seem to have been priorly described, we termed it "cathartocytosis". Cathartocytosis allows a cell to rapidly eject excess material without waiting for autophagic and lysosomal digestion. We speculate the ejection of sulfated glycoproteins would aid in downscaling and might also help bind and flush pathogens away from tissue.

cell biology↗

bioRxiv2024

Dynamin-1 is a potential mediator in Cancer-Related Cognitive Impairment

Dynamin-1 (DNM1) consolidates memory through synaptic transmission and modulation and has been explored as a therapeutic target in Alzheimers disease. Through a two-prong approach, this study examined its role in cancer-related cognitive impairment (CRCI) pathogenesis using human and animal models. The human study recruited newly diagnosed, chemotherapy-naive adolescent and young adult cancer and non-cancer controls to complete a cognitive instrument (FACT-Cog) and blood draws for up to three time points. Concurrently, a syngeneic young-adult WT (C57BL/6 female) mouse model of breast cancer was developed to study DNM1 expression in the brain. Samples from eighty-six participants with 30 adolescent and young adult (AYA) cancer and 56 non-cancer participants were analyzed. DNM1 levels were significantly lower among cancer participants compared to non-cancer prior to treatment. While receiving cancer treatment, cognitively impaired patients were found with a significant downregulation of DNM1, but not among those without impairment. In murine breast cancer-bearing mice receiving chemotherapy, we consistently found a significant decline in DNM1 immunoreactivity in the hippocampal CA1 and CA3 subregions. Observed in both human and animal studies, the downregulation of DNM1 is linked with the onset of CRCI. Future research should explore the potential of DNM1 in CRCI pathogenesis and therapeutics development.

pathology↗

bioRxiv2024

Protein structure, a genetic encoding for glycosylation

Unlike DNA, RNA, and protein biosynthesis, dogma describes glycosylation as primarily determined by intrinsic cellular limitations, such as glycosyltransferase expression and precursor availability. However, this cannot explain the commonly-observed differences between glycans on the same protein. By examining site-specific glycosylation on diverse human proteins, we detected associations between protein structure and glycan structure, broadly generalizable to human-expressed glycoproteins. Through structural analysis of site-specific glycosylation data, we found protein-sequence and structural features consistently correlated with specific glycan features. To quantify these relationships, we present a new amino acid substitution matrix describing "glycoimpact", i.e., the association of primary protein structure and glycosylation. High-glycoimpact amino acids co-evolve with glycosites, and glycoimpact is high when estimates of amino acid conservation and variant pathogenicity diverge. We report thousands of disease variants near glycosites with high-glycoimpact, including several with known links to aberrant glycosylation (e.g., Oculocutaneous Albinism, Jakob-Creutzfeldt disease, Gerstmann-Straussler-Scheinker, and Gauchers Disease). Finally, glycoimpact quantification is validated by studying oligomannose-complex glycan ratios on HIV ENV, differential sialylation on IgG3 Fc, differential glycosylation on SARS-CoV-2 Spike, and fucose-modulated function of a tuberculosis monoclonal antibody. Finally, to test the causality of protein-glycan associations, we created 5 glycoimpact-designed novel Rituximab variants, 4 of which substantially changed glycoprofiles as predicted. In all, we report that site-specific glycan biosynthesis is influenced by underlying protein structure, enabling glycan structure prediction and genetic sequence-guided glycoengineering.

genetics↗

bioRxiv2024

Adapting C4 photosynthesis to atmospheric change and increasing productivity by elevating Rubisco content in Sorghum and Sugarcane

Meta-analyses and theory show that with rising atmospheric [CO2], Rubisco has become the greatest limitation to light-saturated leaf CO2 assimilation rates (Asat) in C4 crops. So would transgenically increasing Rubisco increase Asat and result in increased productivity in the field? Here, we successfully overexpressed the Rubisco small subunit (RbcS) with Rubisco accumulation factor 1 (Raf1) in both sorghum and sugarcane, resulting in significant increases in Rubisco content of 13-25% and up to 90% respectively. Asat increased 12-15% and Rubisco enzyme activity [~]40% in three independent transgenic events of both species. Sorghum plants also showed increased speeds of photosynthetic induction and decreased bundle sheath leakiness. These improvements translated into average increases of 15.5% in biomass in field-grown sorghum and a 37-81% increase in greenhouse-grown sugarcane. This suggests a potential opportunity to achieve substantial increases in productivity of this key economically important clade of C4 crops, future proofing their value under global atmospheric change. Significance StatementThe world is projected to need a 60% increase in food supply by 2050 (UN), and this must be achieved under conditions of global change without expanding onto yet more land. C4 crops, while few in number, account for a large proportion of agricultural productivity. We reason that rising atmospheric [CO2] has very recently made Rubisco, the enzyme used for all carbon fixation in plants, the greatest limitation to light saturated photosynthesis in C4 crops. We demonstrate that transgenically increasing Rubisco content in sorghum and sugarcane, increases their photosynthetic efficiency and productivity, including in a field trial of sorghum. This shows a means to sustainably increase the productivity of this key group of crops.

plant biology↗

bioRxiv2024

Large- Scale Deep Proteomic Analysis in Alzheimer's Disease Brain Regions Across Race and Ethnicity

AbstractO_ST_ABSIntroductionC_ST_ABSAlzheimers disease (AD) is the most prevalent neurodegenerative disease, yet our comprehension predominantly relies on studies within the non-Hispanic White (NHW) population. Here we aimed to provide comprehensive insights into the proteomic landscape of AD across diverse racial and ethnic groups. MethodsDorsolateral prefrontal cortex (DLPFC) and superior temporal gyrus (STG) brain tissues were donated from multiple centers (Mayo Clinic, Emory University, Rush University, Mt. Sinai School of Medicine) and were harmonized through neuropathological evaluation, specifically adhering to the Braak staging and CERAD criteria. Among 1105 DLPFC tissue samples (998 unique individuals), 333 were from African American donors, 223 from Latino Americans, 529 from NHW donors, and the rest were from a mixed or unknown racial background. Among 280 STG tissue samples (244 unique individuals), 86 were African American, 76 Latino American, 116 NHW and the rest were mixed or unknown ethnicity. All tissues were uniformly homogenized and analyzed by tandem mass tag mass spectrometry (TMT-MS). ResultsAs a Quality control (QC) measure, proteins with more than 50% missing values were removed and iterative principal component analysis was conducted to remove outliers within brain regions. After QC, 9,180 and 9,734 proteins remained in the DLPC and STG proteome, respectively, of which approximately 9,000 proteins were shared between regions. Protein levels of microtubule-associated protein tau (MAPT) and amyloid-precursor protein (APP) demonstrated AD-related elevations in DLPFC tissues with a strong association with CERAD and Braak across racial groups. APOE4 protein levels in brain were highly concordant with APOE genotype of the individuals. DiscussionThis comprehensive region resolved large-scale proteomic dataset provides a resource for the understanding of ethnoracial-specific protein differences in AD brain.

neuroscience↗

bioRxiv2024

Characterization of age-associated inflammasome activation reveals tissue specific differences in transcriptional and post-translational inflammatory responses

Aging is associated with systemic chronic, low-grade inflammation, termed inflammaging. This pattern of inflammation is multifactorial and is driven by numerous inflammatory pathways, including the inflammasome. However, most studies to date have examined changes in the transcriptomes that are associated with aging and inflammaging, despite the fact that inflammasome activation is driven by a series of post-translational activation steps, culminating in the cleavage and activation of caspase-1. Here, we utilized transgenic mice expressing a caspase-1 biosensor to examine age-associated inflammasome activation in various organs and tissues to define these post-translational manifestations of inflammaging. Consistent with other studies, we observe increased inflammation, including inflammasome activation, in tissues. However, we note that the degree of inflammasome activation is not uniformly correlated with transcriptional changes commonly used as a surrogate for inflammasome activation in tissues. Furthermore, we used a skull thinning technique to monitor central nervous system inflammasome activation in vivo in aged mice and found that neuroinflammation is significantly amplified in aged mice in response to endotoxin challenge. Together, these data reveal that inflammaging is associated with both transcriptional and post-translational inflammatory pathways that are not uniform between tissues and establish new methodologies for measuring age-associated inflammasome activation in vivo and ex vivo.

immunology↗

bioRxiv2024

Robust self-supervised denoising of voltage imaging data using CellMincer

Voltage imaging enables high-throughput investigation of neuronal activity, yet its utility is often constrained by a low signal-to-noise ratio (SNR). Conventional denoising algorithms, such as those based on matrix factorization, impose limiting assumptions about the noise process and the spatiotemporal structure of the signal. While deep learning based denoising techniques offer greater adaptability, existing approaches fail to fully exploit the fast temporal dynamics and unique short- and long-range dependencies within voltage imaging datasets. Here, we introduce CellMincer, a novel self-supervised deep learning method designed specifically for denoising voltage imaging datasets. CellMincer operates on the principle of masking and predicting sparse sets of pixels across short temporal windows and conditions the denoiser on precomputed spatiotemporal auto-correlations to effectively model long-range dependencies without the need for large temporal denoising contexts. We develop and utilize a physics-based simulation framework to generate realistic datasets for rigorous hyperparameter optimization and ablation studies, highlighting the key role of conditioning the denoiser on precomputed spatiotemporal auto-correlations to achieve 3-fold further reduction in noise. Comprehensive benchmarking on both simulated and real voltage imaging datasets, including those with paired patch-clamp electrophysiology (EP) as ground truth, demonstrates CellMincers state-of-the-art performance. It achieves substantial noise reduction across the entire frequency spectrum, enhanced detection of subthreshold events, and superior cross-correlation with ground-truth EP recordings. Finally, we demonstrate how CellMincers addition to a typical voltage imaging data analysis workflow improves neuronal segmentation, peak detection, and ultimately leads to significantly enhanced separation of functional phenotypes.

neuroscience↗

bioRxiv2024

CDC42 Inhibitors Alter Patterns of Vessel Arborization in Skin and Tumors in vivo

Tumors that arise in the epidermis must develop a vascular supply to grow beyond a millimeter in depth. This process requires CDC42 GTPases such as CDC42, RhoJ and RhoQ. Despite this dependence on angiogenesis for growth, melanoma tumors are minimally responsive to current anti-angiogenesis agents, highlighting the need for more effective drugs in this class. Here we integrate antibody infusion, optical tissue clearing, multiphoton imaging, and three-dimensional semi-automated tracing to develop a quantitative approach to measure changes in vascular architecture in skin and skin tumors. This new approach uncovered differences in vessel arborization in the skin of RhoJ KO mice as compared to wild-type mice. Furthermore, novel small molecules that inhibit CDC42 GTPases inhibited both tumor growth and vessel branching within tumors to a similar degree as Braf inhibitors, which are commonly used to treat melanoma. In contrast to Braf inhibitors, however, which only affected tumor vasculature, CDC42 inhibitors affected vascularization in both tumor and normal skin without apparent toxicity to endothelial or stromal cells. These novel CDC42 inhibitors similarly blocked vessel branching in human cell-based micro-physiological models of normal and tumor vessels. RNA sequencing revealed reduced expression of multiple angiogenesis-related genes in drug-treated skin. Taken together, these studies identify a new class of pharmacologic agents that inhibit vessel branching in both normal skin and tumors with potential utility for treating skin cancer and skin diseases characterized by pathologic angiogenesis.

cancer biology↗

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↗