Biology subjects

Moon, S.

Publications and source records attributed to Moon, S..

36 records · Page 2Linked to original sources

bioRxiv2023

Structural basis of aggregate binding by the AAA+ disaggregase ClpG

Severe heat stress causes massive loss of essential proteins by aggregation necessitating a cellular activity that rescues aggregated proteins. This activity is executed by ATP-dependent, ring-forming, hexameric AAA+ disaggregases. Little is known about the recognition principles of stress-induced protein aggregates. How can disaggregases specifically target aggregated proteins while avoiding binding to soluble non-native proteins? Here, we determined by NMR spectroscopy the core structure of the aggregate targeting N1 domain of the bacterial AAA+ disaggregase ClpG, which confers extreme heat resistance to bacteria. N1 harbors a Zn2+-coordination site that is crucial for structural integrity and disaggregase functionality. Conserved hydrophobic N1 residues located on a {beta}-strand were found crucial for aggregate targeting and disaggregation activity. Mixing experiments with N1-truncated AAA+ hexamers revealed that a minimal number of four N1 domains must be present in a AAA+ ring for high disaggregation activity. We suggest that multiple N1 domains increase substrate affinity through avidity effects. These findings define the recognition principle of a protein aggregate by a disaggregase, involving simultaneous contacts with multiple hydrophobic substrate patches located in close vicinity on an aggregate surface. This binding mode ensures selectivity for aggregated proteins while sparing soluble, non-native protein structures from disaggregase activity.

biochemistry↗

bioRxiv2023

Automated cell annotation in multi-cell images using an improved CRF_ID algorithm

Cell identification is an important yet difficult process in data analysis of biological images. Previously, we developed an automated cell identification method called CRF_ID and demonstrated its high performance in C. elegans whole-brain images (Chaudhary et al, 2021). However, because the method was optimized for whole-brain imaging, comparable performance could not be guaranteed for application in commonly used C. elegans multi-cell images that display a subpopulation of cells. Here, we present an advance CRF_ID 2.0 that expands the generalizability of the method to multi-cell imaging beyond whole-brain imaging. To illustrate the application of the advance, we show the characterization of CRF_ID 2.0 in multi-cell imaging and cell-specific gene expression analysis in C. elegans. This work demonstrates that high accuracy automated cell annotation in multi-cell imaging can expedite cell identification and reduce its subjectivity in C. elegans and potentially other biological images of various origins.

bioengineering↗

bioRxiv2023

Identification of Therapeutic Leads from Ficus hispida Fruit Phytochemicals against Prostate Cancer Using Pharmacoinformatic and Molecular Dynamics Simulation Approach

Prostate cancer is one of the leading causes of death and the most common cancer type in men. In this study, potential leads from the phytochemicals of Ficus hispida fruit were screened using in silico tools against androgen receptor (AR), a known target for prostate cancer. PASS online and ADMET tools were used to screen specific phytochemicals that are relevant to prostate cancer treatment and have drug-like properties. Of 13, a total of 10 phytochemicals passed PASS online and ADMET screening. Next, a total of three phytochemicals, including nodakenetin (CID: 26305), isowigtheone hydrate (CID: 66728267), and 7-hydroxycoumarin (CID: 5281426) were selected based on their docking scores (-9.946 to -7.653 kcal/mol) and relevance to selective bioactivity. The MD simulation further confirmed the binding stability of these three phytochemicals with their target AR protein and determined that the main amino acid residues mainly responsible for this stability including RMSD, RMSF, and post simulation binding free energies. These findings suggest that these three phytochemicals of Ficus hispida fruit can further be developed as prospective therapeutics against prostate cancer.

bioinformatics↗

bioRxiv2023

Comparative analysis of gonadal hormone receptor expression in the house mouse, meadow vole, and prairie vole brain

The socially monogamous prairie vole (Microtus ochrogaster) and promiscuous meadow vole (Microtus pennsylvanicus) are closely related, but only prairie voles display long-lasting pair bonds, biparental care, and selective aggression towards unfamiliar individuals after pair bonding. These social behaviors in mammals are largely mediated by steroid hormone signaling in the social behavior network (SBN) of the brain. Hormone receptors are reproducible markers of sex differences that can provide more information than anatomy alone, and can even be at odds with anatomical dimorphisms. We reasoned that behaviors associated with social monogamy in prairie voles may emerge in part from unique expression patterns of steroid hormone receptors in this species, and that these expression patterns would be more similar across males and females in prairie than in meadow voles or the laboratory mouse. To obtain insight into steroid hormone signaling in the developing prairie vole brain, we assessed expression of estrogen receptor alpha (Esr1), estrogen receptor beta (Esr2), and androgen receptor (Ar) within the SBN, using in situ hybridization at postnatal day 14 in mice, meadow, and prairie voles. We found species-specific patterns of hormone receptor expression in the hippocampus and ventromedial hypothalamus, as well as species differences in the sex bias of these markers in the principal nucleus of the bed nucleus of the stria terminalis. These findings suggest the observed differences in gonadal hormone receptor expression may underlie species differences in the display of social behaviors.

neuroscience↗

bioRxiv2023

An expanded GCaMP reporter toolkit for functional imaging in C. elegans

In living organisms, changes in calcium flux are integral to many different cellular functions and are especially critical for the activity of neurons and myocytes. Genetically encoded calcium indicators (GECIs) have been popular tools for reporting changes in calcium levels in vivo. In particular, GCaMP, derived from GFP, are the most widely used GECIs and have become an invaluable toolkit for neurophysiological studies. Recently, new variants of GCaMP, which offer a greater variety of temporal dynamics and improved brightness, have been developed. However, these variants are not readily available to the Caenorhabditis elegans research community. This work reports a set of GCaMP6 and jGCaMP7 reporters optimized for C. elegans studies. Our toolkit provides reporters with improved dynamic range, varied kinetics, and targeted subcellular localizations. Besides optimized routine uses, this set of reporters are also well-suited for studies requiring fast imaging speeds and low magnification or low-cost platforms.

neuroscience↗

bioRxiv2022

An international scholastic network to generate LexA enhancer-trap lines for Drosophila

Conditional gene regulation in Drosophila through binary expression systems like the LexA-LexAop system provides a superb tool for investigating gene and tissue function. To increase the availability of defined LexA enhancer trap insertions, we present molecular, genetic and tissue expression studies of 301 novel Stan-X LexA enhancer traps derived from mobilization of the index SX4 line. This includes insertions into distinct loci on the X, II and III chromosomes that were not previously associated with enhancer traps or targeted LexA constructs, an insertion into ptc, and eleven insertions into natural transposons. A subset of enhancer traps was expressed in CNS neurons known to produce and secrete insulin, an essential regulator of growth, development and metabolism. Fly lines described here were generated and characterized through studies by students and teachers in an international network of genetics classes at public, independent high schools, and universities serving a diversity of students, including those underrepresented in science. Thus, a unique partnership between secondary schools and university-based programs has produced and characterized novel resources in Drosophila, establishing instructional paradigms devoted to unscripted experimental science.

genetics↗

bioRxiv2022

Fast, Efficient, and Accurate Neuro-Imaging Denoising via Deep Learning

Volumetric functional imaging is widely used for recording neuron activities in vivo, but there exist tradeoffs between the quality of the extracted calcium traces, imaging speed, and laser power. While deep-learning methods have recently been applied to denoise images, their applications to downstream analyses, such as recovering high-SNR calcium traces, have been limited. Further, these methods require temporally-linked pre-registered data with ultrafast rates. Here, we demonstrate supervised deep-denoising methods to circumvent these tradeoffs for several applications, including whole-brain imaging, large field-of-view imaging in freely moving animals, and recovering complex neurite structures in C. elegans. Our framework has 30x smaller memory footprint, and is fast in training and inference (50-70ms); it is highly accurate and generalizable, and further, only small, non-temporally-sequential, independently-acquired training datasets ([~]500 images) are needed. We envision that the framework will enable faster and long-term imaging experiments necessary to study neuronal mechanisms of many behaviors.

neuroscience↗

bioRxiv2022

Engineered bacterial swarm patterns as spatial records of environmental inputs

A diverse array of bacteria species naturally self-organize into durable macroscale patterns on solid surfaces via swarming motility--a highly coordinated, rapid movement of bacteria powered by flagella1-5. Engineering swarming behaviors is an untapped opportunity to increase the scale and robustness of coordinated synthetic microbial systems. Here we engineer Proteus mirabilis, which natively forms centimeter-scale bullseye patterns on solid agar through swarming, to "write" external inputs into a visible spatial record. Specifically, we engineer tunable expression of swarming-related genes that accordingly modify pattern features, and develop quantitative approaches to decode input conditions. Next, we develop a two-input system that modulates two swarming-related genes simultaneously, and show the resulting patterns can be interpreted using a deep learning classification model. Lastly, we show a growing colony can record dynamic environmental changes, which can be decoded from endpoint images using a segmentation model. This work creates an approach for building a macroscale bacterial recorder and expands the framework for engineering emergent microbial behaviors.

synthetic biology↗

bioRxiv2022

A deep learning pipeline for segmentation of Proteus mirabilis colony patterns

The motility mechanisms of microorganisms are critical virulence factors, enabling their spread and survival during infection. Motility is frequently characterized by qualitative analysis of macroscopic colonies, yet the standard quantification method has mainly been limited to manual measurement. Recent studies have applied deep learning for classification and segmentation of specific microbial species in microscopic images, but less work has focused on macroscopic colony analysis. Here, we advance computational tools for analyzing colonies of Proteus mirabilis, a bacterium that produces a macroscopic bullseye-like pattern via periodic swarming, a process implicated in its virulence. We present a dual-task pipeline for segmenting (1) the macroscopic colony including faint outer swarm rings, and (2) internal ring boundaries, unique features of oscillatory swarming. Our convolutional neural network for patch-based colony segmentation and U-Net with a VGG-11 encoder for ring boundary segmentation achieved test Dice scores of 93.28% and 83.24%, respectively. The predicted masks at times improved on the ground truths from our automated annotation algorithms. We demonstrate how application of our pipeline to a typical swarming assay enables ease of colony analysis and precise measurements of more complex pattern features than those which have been historically quantified.

microbiology↗

bioRxiv2021

In vitro efficacy of Artemisia extracts against SARS-CoV-2

Traditional medicines based on herbal extracts have been proposed as affordable treatments for patients suffering from coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Teas and drinks containing extracts of Artemisia annua and Artemisia afra have been widely used in Africa in efforts to prevent and fight COVID-19 infections. We sought to study the ability of different A. annua and A. afra extracts and the Covid-Organics drink produced in Madagascar to inhibit SARS-CoV-2 and feline coronavirus (FCoV) replication in vitro. Several extracts as well as Covid-Organics inhibit SARS-CoV-2 and FCoV replication at concentrations that did not affect cell viability. It remains unclear whether peak plasma concentrations in humans can reach levels needed to inhibit viral replication following consumption of teas or Covid-Organics. Clinical studies are required to evaluate the utility of these drinks for COVID-19 prevention or treatment in patients.

pharmacology and toxicology↗

bioRxiv2021

Measurements of acoustic radiation force of ultrahigh frequency ultrasonic transducers using model-based approach

Even though ultrahigh frequency ultrasonic transducers over 60 MHz have been used for single cell level manipulation such as intracellular delivery, acoustic tweezers, and stimulation to investigate cell phenotype and cell mechanics, no techniques have been available to measure actual acoustic radiation force (ARF) applied to target cells. Therefore, we have developed an approach to measure ARF of ultrahigh frequency ultrasonic transducers using theoretical model of the dynamics of a solid sphere in a gelatin phantom. To estimate ARF at the focus of 130 MHz transducer, we matched measured maximum displacements of a solid sphere with theoretical calculations. We selected appropriate ranges of input voltages and pulse durations for single cell applications and estimated ARF were in the range of tens of pN to nN. FRET live cell imaging was demonstrated to visualize calcium transport between cells after a target single cell was stimulated by the developed ultrasonic transducer.

bioengineering↗

bioRxiv2020

Dismantling and rebuilding the trisulfide cofactor demonstrates its essential role in human sulfide quinone oxidoreductase

Sulfide quinone oxidoreductase (SQR) catalyzes the first step in sulfide clearance, coupling H2S oxidation to coenzyme Q reduction. Recent structures of human SQR revealed a sulfur atom bridging the SQR active site cysteines in a trisulfide configuration. Here, we assessed the importance of this cofactor using kinetic, crystallographic and computational modeling approaches. Cyanolysis of SQR proceeds via formation of an intense charge transfer complex that subsequently decays to eliminate thiocyanate. Cyanolysis leads to reversible loss of SQR activity, which is restored in the presence of sulfide. We captured a crystallographic intermediate in SQR that provides clues as to how the oxidized state of the cysteines is preserved. Computational modeling and MD simulations revealed an ~105-fold rate enhancement for nucleophilic addition of sulfide into the trisulfide versus a disulfide cofactor. The cysteine trisulfide in SQR is thus critical for activity and provides a significant catalytic advantage over a cysteine disulfide.

biochemistry↗

bioRxiv2020

Focused ultrasound stimulates ER localized mechanosensitive PANNEXIN-1 to mediate intracellular calcium release in invasive cancer cells

Focused ultrasound (FUS) is a rapidly developing stimulus technology with the potential to uncover novel mechanosensory dependent cellular processes. Since it is noninvasive, it holds great promise for future therapeutic applications in patients used either alone or as a complement to boost existing treatments. For example, FUS stimulation causes invasive but not noninvasive cancer cell lines to exhibit marked activation of calcium signaling pathways. Here, we identify the membrane channel PANNEXIN1 (PANX1) as a mediator for activation of calcium signaling in invasive cancer cells. Knockdown of PANX1 decreases calcium signaling in invasive cells, while PANX1 overexpression enhances calcium elevations in non-invasive cancer cells. We demonstrate that FUS may directly stimulate mechanosensory PANX1 localized in endoplasmic reticulum to evoke calcium release from internal stores. This process does not depend on mechanosensory stimulus transduction through an intact cytoskeleton and does not depend on plasma membrane localized PANX1. Plasma membrane localized PANX1 however plays a different role in mediating the spread of intercellular calcium waves via ATP release. Additionally, we show that FUS stimulation evokes cytokine/chemokine release from invasive cancer cells, suggesting that FUS could be an important new adjuvant treatment to improve cancer immunotherapy.

cell biology↗

bioRxiv2020

A CTGF-YAP regulatory pathway is essential for angiogenesis and barriergenesis in the retina

Connective tissue growth factor (CTGF) or CCN2 is a matricellular protein essential for normal embryonic development and tissue repair. CTGF exhibits cell- and context-dependent activities, but the CTGF function in vascular development and permeability barrier is not known. Here we show that endothelial cells (ECs) are one of the major cellular sources of CTGF in the developing and adult retinal vasculature. Mice lacking CTGF expression either globally or specifically in ECs exhibit impaired vascular cell growth and morphogenesis, and blood barrier breakdown. The global molecular signature of CTGF includes cytoskeletal and extracellular matrix protein, growth factor, and transcriptional co-regulator genes such as yes-associated protein (YAP). YAP, itself a transcriptional activator of the CTGF gene, mediates several CTGF-controlled angiogenic and barriergenic transcriptional programs. Re-expression of YAP rescues, at least partially, angiogenesis and barriergenesis in CTGF mutant mouse retinas. Thus, the CTGF-YAP angiomodulatory pathway is critical for vascular development and barrier function.

developmental biology↗

bioRxiv2019

A metal artifact reduction method for small field of view CT imaging.

To reduce metal artifacts, several sinogram inpainting-based metal artifact reduction (MAR) methods have been proposed where projection data within the metal trace region of the sinogram are treated as missing and subsequently estimated. However, these methods generally assume data truncation does not occur and all metal objects reside inside the field-of-view (FOV). For small FOV imaging, these assumptions are violated, and thus existing inpainting-based MAR methods would not be effective. In this paper, we propose a new MAR method to reduce metal artifacts effectively in the presence of data truncation. The main idea behind the proposed method is the synthesis of a sinogram, which is treated as the originally measured sinogram. First, an initial reconstruction step is performed to remove truncation artifacts. The next step consists of a forward projection of the small FOV image, replacing the original sinogram with the synthesized sinogram. The final step is the application of sinogram inpainting based MAR methods using the synthesized sinogram. Verification of the proposed method was performed for three situations: extended cardiac-torso (XCAT) simulation, clinical data, and experimental data. The proposed method was applied with linear MAR (LMAR) and normalized MAR (NMAR), and the performance of the proposed method was compared with that of the previous method. For quantitative evaluation, normalized mean squared error (NMSE) and structure similarity (SSIM) were used. The results show the effectiveness of the proposed method to reduce residual metal artifacts, which are present in the results obtained with the previous method. The evaluation results using NMSE and SSIM also indicate that the proposed method is more effective than the previous method.

bioengineering↗

bioRxiv2019

Identification of type 2 diabetes loci in 433,540 East Asian individuals

Meta-analyses of genome-wide association studies (GWAS) have identified >240 loci associated with type 2 diabetes (T2D), however most loci have been identified in analyses of European-ancestry individuals. To examine T2D risk in East Asian individuals, we meta-analyzed GWAS data in 77,418 cases and 356,122 controls. In the main analysis, we identified 298 distinct association signals at 178 loci, and across T2D association models with and without consideration of body mass index and sex, we identified 56 loci newly implicated in T2D predisposition. Common variants associated with T2D in both East Asian and European populations exhibited strongly correlated effect sizes. New associations include signals in/near GDAP1, PTF1A, SIX3, ALDH2, a microRNA cluster, and genes that affect muscle and adipose differentiation. At another locus, eQTLs at two overlapping T2D signals act through two genes, NKX6-3 and ANK1, in different tissues. Association studies in diverse populations identify additional loci and elucidate disease genes, biology, and pathways.\n\nType 2 diabetes (T2D) is a common metabolic disease primarily caused by insufficient insulin production and/or secretion by the pancreatic {beta} cells and insulin resistance in peripheral tissues1. Most genetic loci associated with T2D have been identified in populations of European (EUR) ancestry, including a recent meta-analysis of genome-wide association studies (GWAS) of nearly 900,000 individuals of European ancestry that identified >240 loci influencing the risk of T2D2. Differences in allele frequency between ancestries affect the power to detect associations within a population, particularly among variants rare or monomorphic in one population but more frequent in another3,4. Although smaller than studies in European populations, a recent T2D meta-analysis in almost 200,000 Japanese individuals identified 28 additional loci4. The relative contributions of different pathways to the pathophysiology of T2D may also differ between ancestry groups. For example, in East Asian (EAS) populations, T2D prevalence is greater than in European populations among people of similar body mass index (BMI) or waist circumference5. We performed the largest meta-analysis of East Asian individuals to identify new genetic associations and provide insight into T2D pathogenesis.

genetics↗

bioRxiv2019

Graphene-enabled, spatially controlled electroporation of adherent cells for live-cell super-resolution microscopy

The incorporation of exogenous molecules into live cells is essential for both biological research and therapeutic applications. In particular, for the emerging field of super-resolution microscopy of live mammalian cells, reliable fluorescent labeling of intracellular targets remains a challenge. Here, utilizing the unique mechanical, electrical, and optical properties of graphene, a single layer of bonded carbon atoms, we report a facile approach that enables both high-throughput delivery of fluorescent probes into adherent live cells and in situ super-resolution microscopy on the same device. [~]90% delivery efficiencies are achieved for free dyes and dye-tagged affinity probes, short peptides, and whole antibodies, thus enabling high-quality super-resolution microscopy. Moreover, we demonstrate excellent spatiotemporal controls, which, in combination with the ready patternablity of graphene, allow for the spatially selective delivery of two different probes for cells at different locations on the same substrate. We thus open up a new pathway to the microscopic manipulation and visualization of live cells.

bioengineering↗

bioRxiv2018

Information-rich localization microscopy through machine learning

While current single-molecule localization microscopy (SMLM) methods often rely on the target-specific alteration of the point spread function (PSF) to encode the multidimensional contents of single fluorophores, we argue that the details of the PSF in an unmodified microscope already contain rich, multidimensional information. We introduce a data-driven approach in which artificial neural networks (ANNs) are trained to make a direct link between an experimental PSF image and its underlying parameters. To demonstrate this concept in real systems, we decipher in fixed cells both the colors and the axial positions of single molecules in regular SMLM data.

biophysics↗