Biology subjects

Yao, Y.

Publications and source records attributed to Yao, Y..

At least 163 records · Page 9Linked to original sources

bioRxiv2022

Data Driven Control of Vagus Nerve Stimulation for the Cardiac System

1Vagus nerve stimulation is an emerging therapy that seeks to offset pathological conditions by electrically stimulating the vagus nerve through cuff electrodes, where an electrical pulse is defined by several parameters such as pulse amplitude, pulse width, and pulse frequency. This electroceutical therapy has been approved for epilepsy, and treatment resistant depression. Currently, vagus nerve stimulation is under investigation for the treatment of heart failure, heart arrhythmia, hypertension, and gastric motility disorders. Through several clinical trials that sought to assess vagus nerve stimulation for the treatment of heart failure, stimulation parameters were determined heuristically and the results were left inconclusive, which has led to the suggestion of using a closed-loop approach to optimize the stimulation parameters. A recent investigation has demonstrated highly specific control of cardiac physiology by selectively activating different fibers in the vagus nerve. When multiple locations and multiple stimulation parameters are considered for optimization, the design of closed-loop control becomes considerably more challenging. To address this challenge, we investigated a data-driven control scheme for both modeling and controlling the rat cardiac system. Using an existing in silico physiological model of a rat heart to generate synthetic input-output data, we trained a long short-term memory network (LSTM) to map the effect of stimulation on the heart rate and the blood pressure. The trained LSTM was utilized in a model predictive control framework to optimize the vagus nerve stimulation parameters for set point tracking of the heart rate and the blood pressure in closed-loop simulations. Additionally, we altered the underlying in silico physiological model to consider intra-patient variability, and diseased dynamics from increased sympathetic tone in designing closed-loop VNS strategies. Throughout the different simulation scenarios, we leveraged the design of the controller to demonstrate alternative clinical objectives. Our results show the controller can optimize stimulation parameters to achieve set-point tracking with nominal offset while remaining computationally efficient. Furthermore, we show a controller formulation that compensates for mismatch due to intra-patient variabilty, and diseased dynamics. This study demonstrates the first application and a proof-of-concept for using a purely data-driven approach for the optimization of vagus nerve stimulation parameters in closed-loop control of the cardiac system.

bioengineering↗

bioRxiv2022

Primary cilia loss promotes reactivation of morphogenesis and cyst-fission through a deregulated TGFβ-ECM-Integrin axis in polycystic liver disease.

Pathological liver cysts are an important comorbidity in multiple diseases and syndromes(1, 2) driven by dysfunction of the primary cilium (PC), a complex sensory organelle that protrudes from the apical surface of biliary epithelial cells (BECs)(3, 4). The essential nature of PC in liver development(5, 6) makes understanding the molecular role of this organelle in the structural maintenance of the adult bile duct challenging. Here, we show that PC loss deletion of Wdr35 in adult mouse BECs is sufficient to cause bile duct expansion, driving cyst formation through the de novo production of a fibronectin-rich pro-cystic microenvironment. This newly formed niche promotes both cell-autonomous changes in cell shape and duct-level mechanical rearrangements that converge to drive cyst-fission, a novel process whereby single, large cysts undergo morphological splitting. This process gives rise to many, smaller polycystic progeny and can be halted by pharmacological inhibition of a specific pro-cystic integrin receptor.

cell biology↗

bioRxiv2022

Limitations of principal components in quantitative genetic association models for human studies

Principal Component Analysis (PCA) and the Linear Mixed-effects Model (LMM), sometimes in combination, are the most common genetic association models. Previous PCA-LMM comparisons give mixed results, unclear guidance, and have several limitations, including not varying the number of principal components (PCs), simulating simple population structures, and inconsistent use of real data and power evaluations. We evaluate PCA and LMM both varying number of PCs in realistic genotype and complex trait simulations including admixed families, subpopulation trees, and real multiethnic human datasets with simulated traits. We find that LMM without PCs usually performs best, with the largest effects in family simulations and real human datasets and traits without environment effects. Poor PCA performance on human datasets is driven by large numbers of distant relatives more than the smaller number of closer relatives. While PCA was known to fail on family data, we report strong effects of family relatedness in genetically diverse human datasets, not avoided by pruning close relatives. Environment effects driven by geography and ethnicity are better modeled with LMM including those labels instead of PCs. This work better characterizes the severe limitations of PCA compared to LMM in modeling the complex relatedness structures of multiethnic human data for association studies.

genetics↗

bioRxiv2022

Establishment of an efficient transformation and CRISPR/Cas9-mediated gene editing system in Chinese local planting cassava (Manihot esculenta Crantz) cultivar SC8

Cassava starch is a widely used raw material for industrial production. South Chinese cassava cultivar 8 (Manihot esculenta Crantz cv. SC8) is one of the main locally planted cultivars. In this study, an efficient transformation system for cassava SC8 mediated with Agrobacterium strain LBA4404 was presented for the first time, in which the factors of Agrobacterium strain cell infection (density OD600 = 0.65), 250 {micro}M acetosyringone induction, and agro-cultivation with wet friable embryogenic callus (FEC) for 3 days in dark conditions were found to increase the transformation efficiency through the binary vector pCAMBIA1304 harboring GUS- and GFP-fused genes driven by the CaMV35S promoter. Based on the optimized transformation protocol, approximately 120-140 independent transgenic lines per mL settled FEC cell volume (SCV) by gene transformation in approximately five months, and 45.83% homozygous mono-allelic mutations of the MePDS gene with a YAO promoter-driven CRISPR/Cas9 system were generated. This study will open a more functional avenue for the genetic improvement of cassava SC8.

molecular biology↗

bioRxiv2022

Engineering bacterial blight-resistant plants through CRISPR/Cas9-targeted editing of the MeSWEET10a promoter in cassava

Cassava starch is a widely used raw materials for industrial production. However, cassava bacterial blight (CBB) caused by Xanthomonas axonopodis pv. manihotis (Xam) results in severe yield losses and is the most destructive bacterial disease in all worldwide cassava planting regions. This study showed that editing of the promoter in the disease-susceptibility gene MeSWEET10a of SC8 cassava confers resistance to CBB. All mutated cassava lines had normal morphological and yield-related traits as the wild type. The results lay a research foundation for breeding cassava resistant to bacterial blight. HighlightsMeSWEET10a gene in SC8 cultivar is hijacked by TALE20 from Xam11 strain. Editing of the MeSWEET10a promoter in SC8 cultivar confers resistance to CBB. All the mutated cassava lines had similar yield-related traits compared to wild-type.

plant biology↗

bioRxiv2022

Combined single-cell RNA-seq profiling and enhancer editing reveals critical spatiotemporal controls over thalamic nuclei formation in the murine embryo

The thalamus is the principal information hub of the vertebrate brain, with essential roles in sensory and motor information processing, attention, and memory. The molecular mechanisms regulating the formation of thalamic nuclei are unclear. We apply longitudinal single-cell RNA-sequencing, regional abrogation of Sonic-hedgehog (Shh), and spatial profiling of gene expression to map the developmental trajectories of thalamic progenitors, intermediate progenitors, and post-mitotic neurons as they coalesce into distinct thalamic nuclei. These data reveal that the complex architecture of the thalamus is established early during embryonic brain development through the coordinated action of four cell differentiation lineages derived from Shh-dependent and independent progenitors. We systematically characterize the gene expression programs that define these lineages across time and demonstrate how their disruption upon Shh depletion causes pronounced locomotor impairment resembling infantile Parkinsons disease. These results reveal key principles of thalamic development and provide mechanistic insights into neurodevelopmental disorders resulting from thalamic dysfunction.

neuroscience↗

bioRxiv2022

Sensitization of Chrysosplenetin against Artemisinin Resistant Plasmodium berghei K173 via Blocking Host ABC Transporters Potentially Mediated by NF-κBB p52 or PXR/CAR Signaling Pathway

This study investigated if artemisinin-chrysosplenetin combination (ART-CHR) improved ART antimalarial efficacy against resistant Plasmodium berghei K173 via depressing host ABC transporter and potential molecular mechanism. Parasitaemia% and inhibition% were calculated and gene/protein expressions of ABC transporters or PXR/CAR/NF-{kappa}B p52 were detected by Western-blot and RT-qPCR. In vitro transcription of PXR/CAR was studied by dual-luciferase reporter assay. Our data indicated that ART-CHR improved ART efficacy against resistant parasites. P-gp inhibitor verapamil and CHR showed a stronger effect in killing resistant parasites while vehicle and Bcrp inhibitor novobiocin did not. ART activated intestinal ABCB1/ABCG2 and CHR inhibited them. ART decreased Bcrp protein whereas CHR increased it. ART ascended ABCC1/ABCC4/ABCC5 mRNA but ART-CHR descended them. CHR as well as rifampin (RIF) or 5-fluorouracil (5-FU) increased transcription levels of PXR/CAR while showed a versatile regulation on in vivo hepatic and enternal PXR/CAR in Mdr1a+/+ (WT) or Mdr1a-/- (KO) mice infected with sensitive or resistant parasites. Oppositely, hepatic and enteric N-{kappa}B p52 mRNA was conformably decreased in WT but increased in KO-resistant mice. NF-{kappa}B pathway should potentially involved in the mechanism of CHR on inhibiting ABC transporters and ART resistance while PXR/CAR play a more complicated role in this mechanism.

molecular biology↗

bioRxiv2021

BioThings SDK: a toolkit for building high-performance data APIs in biomedical research

SummaryTo meet the increased need of making biomedical resources more accessible and reusable, Web APIs or web services have become a common way to disseminate knowledge sources. The BioThings APIs are a collection of high-performance, scalable, annotation as a service APIs that automate the integration of biological annotations from disparate data sources. This collection of APIs currently includes MyGene.info, MyVariant.info, and MyChem.info for integrating annotations on genes, variants, and chemical compounds, respectively. These APIs are used by both individual researchers and application developers to simplify the process of annotation retrieval and identifier mapping. Here, we describe the BioThings Software Development Kit (SDK), a generalizable and reusable toolkit for integrating data from multiple disparate data sources and creating high-performance APIs. This toolkit allows users to easily create their own BioThings APIs for any data type of interest to them, as well as keep APIs up-to-date with their underlying data sources. Availability and implementationThe BioThings SDK is built in Python and released via PyPI (https://pypi.org/project/biothings/). Its source code is hosted at its github repository (https://github.com/biothings/biothings.api).

bioinformatics↗

bioRxiv2021

OpenMonkeyChallenge: Dataset and Benchmark Challenges for Pose Tracking of Non-human Primates

The ability to automatically track non-human primates as they move through the world is important for several subfields in biology and biomedicine. Inspired by the recent success of computer vision models enabled by benchmark challenges (e.g., object detection), we propose a new benchmark challenge called OpenMonkeyChallenge that facilitates collective community efforts through an annual competition to build generalizable non- human primate pose tracking models. To host the benchmark challenge, we provide a new public dataset consisting of 111,529 annotated (17 body landmarks) photographs of non-human primates in naturalistic contexts obtained from various sources including the internet, three National Primate Research Centers, and the Minnesota Zoo. Such annotated datasets will be used for the training and testing datasets to develop generalizable models with standardized evaluation metrics. We demonstrate the effectiveness of our dataset quantitatively by comparing it with existing datasets based on seven state-of-the-art pose tracking models.

animal behavior and cognition↗

bioRxiv2021

Spermidine dampens inflammation by directly inhibiting Th17 cytokine production through a PRDX1 associated antioxidant pathway

The activation of IL-17 signaling has been linked to the pathogenesis of many chronic, inflammatory lung diseases including Cystic Fibrosis (CF). Through unbiased single-cell RNAseq screening, we found that IL-17+ T cells highly express Srm and Smox, which encode two key enzymes for spermidine synthesis. Spermidine has been shown to reduce inflammation by regulating macrophage activation and balancing Th17/Treg differentiation, but its direct effects on Th17 cytokine production has not been carefully investigated. Here, using already differentiated Th17 cells from cultured mouse splenocytes, we found that exogenous spermidine directly inhibits IL-1{beta}/IL-23 induced IL-17 production. Blockade of endogenous spermidine synthesis enhanced IL-17 production above native levels, further supporting that spermidine is a direct regulator of cytokine secretion independent of differentiation. In vivo, spermidine alleviates lung inflammation in both PA infection and LPS induced acute lung injury models. Further RNA-seq analysis suggests spermidine suppression of Th17 cytokine production is mediated through its PRDX1 dependent antioxidant activity. Our data establishes that spermidine is a direct regulator of Type-17 T cell cytokine production and has potent anti-inflammatory effects against lung inflammation.

immunology↗

bioRxiv2021

Conserved T-cell epitopes predicted by bioinformatics in SARS-COV-2 variants

BackgroundFinding conservative T cell epitopes in the proteome of numerous variants of SARS-COV-2 is required to develop T cell activating SARS-COV-2 capable of inducing T cell responses against SARS-COV-2 variants. MethodsA computational workflow was performed to find HLA restricted CD8+ and CD4+ T cell epitopes among conserved amino acid sequences across the proteome of 474727 SARS-CoV-2 strains. ResultsA batch of covserved regions in the amino acid sequences were found in the proteome of the SARS-COV-2 strains. 2852 and 847 peptides were predicted to have high binding affinity to distint HLA class I and class II molecules. Among them, 1456 and 484 peptides are antigenic. 392 and 111 of the antigenic peptides were found in the conseved amino acid sequences. Among the antigenic-conserved peptides, 6 CD8+ T cell epitopes and 7 CD4+ T cell epitopes were identifed. The T cell epitopes could be presented to T cells by high-affinity HLA molecules which are encoded by the HLA alleles with high population coverage. ConclusionsThe T cell epitopes are conservative, antigenic and HLA presentable, and could be constructed into SARS-COV-2 vaccines for inducing protective T cell immunity against SARS-COV-2 and their variants.

immunology↗

bioRxiv2021

RPnet: A Reverse Projection Based Neural Network for Coarse-graining Metastable Conformational States for Protein Dynamics

Markov State Model (MSM) is a powerful tool for modeling the long timescale dynamics based on numerous short molecular dynamics (MD) simulation trajectories, which makes it a useful tool for elucidating the conformational changes of biological macromolecules. By partitioning the phase space into discretized states and estimate the probabilities of inter-state transitions based on short MD trajectories, one can construct a kinetic network model that could be used to extrapolate long time kinetics if the Markovian condition is met. However, meeting the Markovian condition often requires hundreds or even thousands of states (microstates), which greatly hinders the comprehension of conformational dynamics of complex biomolecules. Kinetic lumping algorithms can coarse grain numerous microstates into a handful of metastable states (macrostates), which would greatly facilitate the elucidation of biological mechanisms. In this work, we have developed a reverse projection based neural network (RPnet) method to lump microstates into macrostates, by making use of a physics-based loss function based on the projection operator framework of conformational dynamics. By recognizing that microstate and macrostate transition modes can be related through a projection process, we have developed a reverse projection scheme to directly compare the microstate and macrostate dynamics. Based on this reverse projection scheme, we designed a loss function that allows effectively assess the quality of a given kinetic lumping. We then make use of a neural network to efficiently minimize this loss function to obtain an optimized set of macrostates. We have demonstrated the power of our RPnet in analyzing the dynamics of a numerical 2D potential, alanine dipeptide, and the clamp opening of an RNA polymerase. In all these systems, we have illustrated that our method could yield comparable or better results than competing methods in terms of state partitioning and reproduction of slow dynamics. We expect that our RPnet holds promise in analyzing conformational dynamics of biological macromolecules.

biophysics↗

bioRxiv2021

Oxidative phosphorylation safeguards pluripotency via UDP-N-acetylglucosamine

The roles of mitochondrial respiration in pluripotency remain largely unknown. We show here that mouse ESC mitochondria possess superior respiration capacity compared to somatic cell mitochondria, and oxidative phosphorylation (OXPHOS) generates the majority of cellular ATP in ESCs. Inhibition of OXPHOS results in extensive pluripotency and metabolic gene expression reprogram, leading to disruption of self-renewal and pluripotency. Metabolomics profiling identifies UDP-N-acetylglucosamine (UDP-GlcNAc) as one of the most significantly decreased metabolites in response to OXPHOS inhibition. The loss of ESC identity induced by OXPHOS inhibition can be ameliorated by directly adding GlcNAc both in vitro and in vivo. This work demonstrates that mitochondrial respiration, but not glycolysis, produces the majority of ATP in ESCs, and uncovers a novel mechanism whereby mitochondrial respiration is coupled with the hexosamine biosynthesis pathway to generate UDP-GlcNAc for ESC identity maintenance. SIGNIFICANCEOxidative phosphorylation (OXPHOS) and glycolysis are the two major pathways for generating ATP in mammalian cells. It is widely assumed that somatic cells utilize OXPHOS, whereas embryonic stem cells (ESCs) utilize glycolysis with low mitochondrial respiration rates even under aerobic conditions. However, the relative contribution of OXPHOS and glycolysis to ATP generation in ESCs, and the role of mitochondrial respiration in regulating ESC identity, have remained unclear. In this study, Cao et al demonstrate that mouse ESC mitochondria have a significantly higher respiration capacity than somatic cell mitochondria. Oxidative phosphorylation produces the majority of cellular ATP in mESCs and is coupled with the hexosamine biosynthesis pathway to generate UDP-GlcNAc for pluripotency maintenance. These findings define the function and mechanism of OXPHOS in regulating pluripotency, and challenge the traditional concept that mESCs rely on glycolysis over OXPHOS for their major supply of energy. HIGHLIGHTSO_LIESC mitochondria have a significantly higher respiration capability than somatic cell mitochondria C_LIO_LIOXPHOS, but not glycolysis, produces the majority of cellular ATP in ESCs C_LIO_LIOXPHOS inhibition induces a decrease in O-GlcNAcylation and the expression of pluripotency genes in blastocysts that can be partially rescued by adding GlcNAc C_LIO_LIOXPHOS is coupled with the hexosamine biosynthesis pathway for UDP-GlcNAc biosynthesis to maintain ESC identity C_LI

cell biology↗

bioRxiv2021

Characterizing collaborative transcription regulation with a graph-based deep learning approach

Human epigenome and transcription activities have been characterized by a number of sequence-based deep learning approaches which only utilize the DNA sequences. However, transcription factors interact with each other, and their collaborative regulatory activities go beyond the linear DNA sequence. Therefore leveraging the informative 3D chromatin organization to investigate the collaborations among transcription factors is critical. We developed ECHO, a graph-based neural network, to predict chromatin features and characterize the collaboration among them by incorporating 3D chromatin organization from 200-bp high-resolution Micro-C contact maps. ECHO predicts 2, 583 chromatin features with significantly higher average AUROC and AUPR than the best sequence-based model. We observed that chromatin contacts of different distances affected different types of chromatin features prediction in diverse ways, suggesting complex and divergent collaborative regulatory mechanisms. Moreover, ECHO was interpretable via gradient-based attribution methods. The attributions on chromatin contacts identify important contacts relevant to chromatin features. The attributions on DNA sequences identify TF binding motifs and TF collaborative binding. Furthermore, combining the attributions on contacts and sequences reveals important sequence patterns in the neighborhood which are relevant to target sequences chromatin feature prediction. The attribution results that reveal TF collaboration activities are provided on a website https://echo.dcmb.med.umich.edu/echo/.

bioinformatics↗

bioRxiv2021

An Efficient Method to Quantify Structural Distributions in Heterogeneous cryo-EM Datasets

Cryogenic Electron Microscopy (cryo-EM) preserves the ensemble of protein conformations in solution and thus provide a promising way to characterize conformational changes underlying protein functions. However, it remains challenging for existing software to elucidate distributions of multiple conformations from a heterogeneous cryo-EM dataset. We developed a new algorithm: Linear Combinations of Template Conformations (LCTC) to obtain distributions of multiple conformations from cryo-EM datasets. LCTC assigns 2D images to the template 3D structures obtained by Multi-body Re-finement of RELION via a novel two-stage matching algorithm. Specifically, an initial rapid assignment of experimental 2D images to template 2D images was applied based on auto-correlation functions of image contours that can efficiently remove the majority of irrelevant 2D images. This is followed by pixel-pixel matching of images with fewer number of 2D images, which can accurately assign the 2D images to the template images. We validate the LCTC method by demonstrating that it can accurately reproduce the distributions of 3 Thermus aquaticus (Taq) RNA polymerase (RNAP) structures with different degrees of clamp opening from a simulated cryo-EM dataset, in which the correct distributions are known. For this dataset, we also show that LCTC greatly outperforms clustering-based Manifold Embedding and Maximum Likelihood-based Multi-body Re-finement algorithms in terms of reproducing the structural distributions. Lastly, we also successfully applied LCTC to reveal the populations of various clamp-opening conformations from an experimental Escherichia coli RNAP cryo-EM dataset. Source code is available at https://github.com/ghl1995/LCTC.

biophysics↗

bioRxiv2021

Single-dose AAV-based vaccine induces a high level of neutralizing antibodies and provides long-term protection against SARS-CoV-2 in rhesus macaques

Coronavirus disease 2019 (COVID-19), which is triggered by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, continues to threaten global public health. Developing a vaccine that only requires single immunization but provides long-term protection for the prevention and control of COVID-19 is important. Here, we developed an adeno-associated virus (AAV)-based vaccine expressing a stable receptor-binding domain (SRBD) protein. The vaccine requires only a single shot but provides effective neutralizing antibodies (NAbs) over 598 days in rhesus macaques (Macaca mulatta). Importantly, our results showed that the NAbs were kept in high level and long lasting against authentic wild-type SARS-CoV-2, Beta, Delta and Omicron variants using plaque reduction neutralization test. Of note, although we detected pre-existing AAV2/9 antibodies before immunization, the vaccine still induced high and effective NAbs against COVID-19 in rhesus macaques. AAV-SRBD immune serum also efficiently inhibited the binding of ACE2 with RBD in the SARS-CoV-2 B.1.1.7 (Alpha), B.1.351 (Beta), P.1/P.2 (Gamma), B.1.617.2 (Delta), B.1.617.1/3(Kappa), and C.37 (Lambda) variants. Thus, these data suggest that the vaccine has great potential to prevent the spread of SARS-CoV-2.

immunology↗

bioRxiv2021

The SCP4-STK35/PDIK1L complex is a dual phospho-catalytic signaling dependency in acute myeloid leukemia

Acute myeloid leukemia (AML) cells rely on phospho-signaling pathways to gain unlimited proliferation potential. Here, we used domain-focused CRISPR screening to identify the nuclear phosphatase SCP4 as a dependency in AML, yet this enzyme is dispensable in normal hematopoietic progenitor cells. Using CRISPR exon scanning and gene complementation assays, we show that the catalytic function of SCP4 is essential in AML. Through mass spectrometry analysis of affinity-purified complexes, we identify the kinase paralogs STK35 and PDIK1L as binding partners and substrates of the SCP4 phosphatase domain. We show that STK35 and PDIK1L function catalytically and redundantly in the same pathway as SCP4 to maintain AML proliferation and to support amino acid biosynthesis and transport. We provide evidence that SCP4 regulates STK35/PDIK1L through two distinct mechanisms: catalytic removal of inhibitory phosphorylation and by promoting kinase stability. Our findings reveal a phosphatase-kinase signaling complex that supports the pathogenesis of AML.

cancer biology↗

bioRxiv2021

Rapid Electronic Diagnostics of Ebola Virus with Synthetic Nanobody-Conjugated Gold Nanoparticles

Successful control of emerging infectious diseases requires accelerated development of fast, affordable, and accessible assays to be widely implemented at a high frequency. Here we present a generalizable assay platform, nanobody-functionalized nanoparticles for rapid, electronic detection (Nano2RED), demonstrated in the detection of Ebola and COVID-19 antigens. To efficiently generate high-quality affinity reagents, synthetic nanobody co-binders and mono-binders with high affinity, specificity, and stability were selected by phage display screening of a vastly diverse, rationally randomized combinatorial library, bacterially expressed and site-specifically conjugated to gold nanoparticles (AuNPs) as multivalent in-solution sensors. Without requiring fluorescent labelling, washing, or enzymatic amplification, these AuNPs reliably transduce antigen binding signals upon mixing into physical AuNP aggregation and sedimentation processes, displaying antigen-dependent optical extinction readily detectable by spectrometry or simple electronic circuitry. With nanobodies against an Ebola virus secreted glycoprotein (sGP) and a SARS-CoV-2 spike protein receptor binding domain (RBD) as targets, Nano2RED showed a high sensitivity (limit of detection of [~]10 pg/mL for sGP and [~]40 pg/mL for RBD in diluted human serum), a high specificity, and a large dynamic range ([~]7 logs). Unlike conventional assays where slow mass transport for surface binding limits the assay time, Nano2RED features fast antigen diffusion at micrometer scale, and can be accelerated to deliver results within a few minutes. The rapid detection, low material cost (estimated < $0.01 per test), inexpensive and portable readout system (< $5 and < 100 cm3), and digital data output, make Nano2RED particularly suitable for screening of patient samples with simplified operation and accelerated data transmission. Our method is widely applicable for prototyping diagnostic assays for other antigens from new emerging viruses.

bioengineering↗