Search bioRxiv⌕ Search

Biology subjects

Yao, R.

Publications and source records attributed to Yao, R..

At least 37 records · Page 2Linked to original sources

Mmp17-deficient mice exhibit heightened goblet cell effector expression in the colon and increased resistance to chronic Trichuris muris infection

Intestinal epithelial homeostasis is maintained by intrinsic and extrinsic signals. The extrinsic signals include those provided by mesenchymal cell populations that surround intestinal crypts and is further facilitated by the extracellular matrix (ECM), which is modulated by proteases such as matrix metalloproteinases (MMPs). Extrinsic signals ensure an appropriate balance between intestinal epithelial proliferation and differentiation. This study explores the role of MMP17, which is expressed by mesenchymal cells, in intestinal homeostasis and during immunity to infection. Mice lacking MMP17 expressed high levels of goblet-cell associated genes, such as CLCA1 and RELM-{beta}, which are normally associated with immune responses to infection. Nevertheless, Mmp17 KO mice did not have altered resistance during a bacterial Citrobacter rodentium infection. However, when challenged with a low dose of the helminth Trichuris muris, Mmp17 KO mice had increased resistance, without a clear role for an altered immune response during infection. Mechanistically, we did not find changes in traditional modulators of goblet cell effectors such as the NOTCH pathway or specific cytokines. Instead, we found elevated BMP signaling in Mmp17 KO mouse large intestinal crypts that we propose to alter the goblet cell maturation state. Together, our data suggests that MMP17 extrinsically alters the goblet cell maturation state via a BMP signaling axis, which is sufficient to alter clearance in a helminth infection model.

immunology↗

Targeted photodynamic neutralization of SARS-CoV-2 mediated by singlet oxygen

The SARS-CoV-2 virus has been on a rampage for more than two years. Vaccines in combination with neutralizing antibodies (NAbs) against SARS-CoV-2 carry great hope in the treatment and final elimination of COVID-19. However, the relentless emergence of variants of concern (VOC), including the most recent Omicron variants, presses for novel measures to counter these variants that often show immune evasion. Hereby we developed a targeted photodynamic approach to neutralize SARS-CoV-2 by engineering a genetically encoded photosensitizer (SOPP3) to a diverse list of antibodies targeting the WT spike protein, including human antibodies isolated from a 2003 SARS patient, potent monomeric and multimeric nanobodies targeting RBD, and non-neutralizing antibodies (non-NAbs) targeting the more conserved NTD region. As confirmed by pseudovirus neutralization assay, this targeted photodynamic approach significantly increased the efficacy of these antibodies, especially that of non-NAbs, against not only the WT but also the Delta strain and the heavily immune escape Omicron strain (BA.1). Subsequent measurement of infrared phosphorescence at 1270 nm confirmed the generation of singlet oxygen (1O2) in the photodynamic process. Mass spectroscopy assay uncovered amino acids in the spike protein targeted by 1O2. Impressively, Y145 and H146 form an oxidization "hotspot", which overlaps with the antigenic "supersite" in NTD. Taken together, our study established a targeted photodynamic approach against the SARS-CoV-2 virus and provided mechanistic insights into the photodynamic modification of protein molecules mediated by 1O2.

bioengineering↗

Age-associated sleep-wake patterns are altered with Prdm13 signaling in the dorsomedial hypothalamus and dietary restriction in mice

Old animals display significant alterations in sleep-wake patterns such as increases in sleep fragmentation and sleep propensity. Here we demonstrated that dorsomedial hypothalamus-specific PR-domain containing protein 13-knockout (DMH-Prdm13-KO) mice recapitulated age-associated sleep alterations such as sleep fragmentation and increased sleep attempts during sleep deprivation (SD). These phenotypes were further exacerbated during aging, with increased adiposity and decreased physical activity, resulting in shortened lifespan. Dietary restriction (DR), a well-known anti-aging intervention in diverse organisms, ameliorated age-associated sleep alterations, whereas these effects of DR were abrogated in DMH-Prdm13-KO mice. Moreover, overexpression of Prdm13 in the DMH ameliorated sleep fragmentation and excessive sleepiness during SD in old mice. Therefore, maintaining Prdm13 signaling in the DMH might play an important role to control sleep-wake patterns during aging.

physiology↗

Toxicity of microplastics and plastic additive co-exposure in liver Disse organoids from healthy donors and patient-derived induced pluripotent stem cells

The ubiquitous microplastics (MPs) and plastic additives in the environment usually form complexes, enter human blood circulation, and increase the risk of steatohepatitis. The liver Disse space plays a vital role in corresponding hepatic pathological processes. However, due to the limited understanding of the regulatory cues in multilineage maturation, the generation of large-scale Disse-like organoids (DOs) mirroring the comprehensive toxicity responses of MPs is challenging. Here, using human-induced pluripotent stem cells (hiPSCs), we biofabricated healthy donors and patient-derived DOs containing hepatocytes, endothelial cells, and hepatic stellate cells, resembling the features of Disse space. These organoids revealed that polystyrene MPs preferentially entered endothelial cells and then dispersed throughout the organoids, similar to reported studies in zebrafish. Co-exposure to MPs and tetrabromobisphenol A (TBBPA), a common plastic additive, showed enhanced accumulation of contamination in the organoids. We also biofabricated alcoholic liver disease (ALD) patient-derived DOs representing the specific disease transcriptional profiles. We found that co-exposure to MPs and TBBPA at environmental-related dosages significantly elevated the pathological transcriptional expression and biochemical profiles in patient-derived DOs but not in healthy organoids, suggesting that both hereditary factors and pollutants contribute to susceptibility to environmental toxicants. This study exemplified the value of biofabricated hiPSC-derived organoids in environmental toxicology and offered a powerful strategy for personalized toxicology evaluation.

bioengineering↗

Human iPSC-derived neuron of 16p11.2 deletion reveals haplotype-specific expression of MAPK3 and its contribution to variable NDD phenotypes

Recurrent proximal 16p11.2 deletion (16p11.2del) is risk factor of diverse neurodevelopmental disorders (NDDs) with variable penetrance. Although previous human induced pluripotent stem cell (hiPSC) models of 16p11.2del confirmed disrupted neuron development, it is not known which gene(s) at this interval are mainly responsible for the abnormal cellular phenotypes and how the NDD penetrance is regulated. After haplotype phasing of 16p11.2 region, we generated hiPSCs for two 16p11.2del families with distinct residual haplotypes and variable NDD phenotypes. We also differentiated the hiPSCs to cortical neural cells and demonstrated MAPK3 as a driver signal of 16p11.2 region contributing to the dysfunctions in multiple pathways related to neuron development, which leads to altered morphological or electrophysiological properties in neuron cells. Furthermore, residual haplotype-specific MAPK3 expression was identified in 16p11.2del neuron cells, associating MAPK3 down-expression with the minor allele of the residual haplotype. Ten SNPs of the residual haplotype are mapped as enhancer SNPs (enSNPs) of MAPK3, eight enSNPs were functionally validated by luciferase assays, implying enSNPs contribute to residual haplotype-specific MAPK3 expression via cis-regulation. Finally, the analyses of three different patient cohorts showed that the residual haplotype of 16p11.2del is associated with variable NDD phenotypes.

genetics↗

Broad-spectrum mono- and combinational drug therapies for global viral pandemic preparedness

Broadly effective antiviral therapies must be developed to be ready for clinical trials, which should begin soon after the emergence of new life-threatening viruses. Here, we pave the way towards this goal by analyzing conserved druggable virus-host interactions, mechanisms of action and immunomodulatory properties of broad-spectrum antivirals (BSAs), routes of BSA delivery, and BSA interactions with other antivirals. Based on the analysis we developed scoring systems, which allowed us to predict novel BSAs and BSA-containing drug combinations (BCCs). Thus, we have developed a new strategy to broaden the spectrum of BSA indications and predict novel mono-and combinational therapies that can help better prepare for imminent future viral outbreaks. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/476444v2_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@7fee8dorg.highwire.dtl.DTLVardef@1069131org.highwire.dtl.DTLVardef@2632bforg.highwire.dtl.DTLVardef@1cdcbf0_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

pcnaDeep: A Fast and Robust Single-Cell Tracking Method Using Deep-Learning Mediated Cell Cycle Profiling

MotivationComputational methods that track single-cells and quantify fluorescent biosensors in time-lapse microscopy images have revolutionised our approach in studying the molecular control of cellular decisions. One barrier that limits the adoption of single-cell analysis in biomedical research is the lack of efficient methods to robustly track single-cells over cell division events. ResultsHere, we developed an application that automatically tracks and assigns mother-daughter relationships of single-cells. By incorporating cell cycle information from a well-established fluorescent cell cycle reporter, we associate mitosis relationships enabling high fidelity long-term single-cell tracking. This was achieved by integrating a deep-learning based fluorescent PCNA signal instance segmentation module with a cell tracking and cell cycle resolving pipeline. The application offers a user-friendly interface and extensible APIs for customized cell cycle analysis and manual correction for various imaging configurations. Availability and ImplementationpcnaDeep is an open-source Python application under the Apache 2.0 licence. The source code, documentation and tutorials are available at https://github.com/chan-labsite/PCNAdeep. Supplementary InformationSupplementary data are available online.

bioinformatics↗

Active components of commonly prescribed medicines affect influenza A virus-host cell interaction: a pilot study

BackgroundEvery year, millions of people are hospitalized, and thousands die from influenza A virus (FLUAV) infection. Most cases of hospitalizations and death occur among elderly. Many of these elderly patients are reliant on medical treatment of underlying chronic diseases, such as arthritis, diabetes, and hypertension. We hypothesized that the commonly prescribed medicines for treatment of underlying chronic diseases can affect host responses to FLUAV infection, and thus contribute to morbidity and mortality associated with influenza. Therefore, the aim of this study was to examine whether commonly prescribed medicines could affect host responses to virus infection in vitro. MethodsWe first identified 45 active compounds of commonly prescribed medicines. Then we constructed a drug-target interaction network and identified potential implication of these interactions for FLUAV-host cell interplay. Finally, we tested the effect of 45 drugs on viability, transcription and metabolism of mock- and FLUAV-infected human retinal pigment epithelial (RPE) cells. ResultsIn silico drug-target interaction analysis revealed that many drugs, such as atorvastatin, candesartan, and hydroxocobalam, could target and modulate FLUAV-host cell interaction. In vitro experiments showed that these and other compounds at non-cytotoxic concentrations differently affected transcription and metabolism of mock- and FLUAV-infected cells. ConclusionMany commonly prescribed drugs modulate FLUAV-host cell interactions in silico and in vitro and, therefore, could affect their interplay in vivo, thus, contributing to morbidity and mortality of patients with influenza virus infections.

pharmacology and toxicology↗

Placenta DNA methylation at ZNF300 is associated with fetal sex and placental morphology

Fetal sex-specific differences in placental morphology and physiology have been associated with sexually dimorphic health outcomes. However, the molecular mechanisms underlying these sex differences are not well understood. We performed whole genome bisulfite sequencing in 133 placenta samples and discovered a significant difference in DNA methylation (DNAm) at the ZNF300 gene locus between male and female offspring and replicated this result in 6 independent datasets. Additionally, the sex-specific pattern appears to be placenta-specific, is robust to a wide range of gestational ages and adverse health outcomes and is present in sorted placenta villous cytotrophoblast cells. Integration of DNAm, genetic, and placental morphology data from the same individuals revealed ZNF300 methylation is also associated with placenta area, perimeter, and max diameter, genetic variants on chromosomes 5 and X, and may mediate the effects of genetic variation on placental area.

genomics↗

Synergistic interferon alpha-based drug combinations inhibit SARS-CoV-2 and other viral infections in vitro

There is an urgent need for new antivirals with powerful therapeutic potential and tolerable side effects. In the present study, we found that recombinant human interferon-alpha (IFNa) triggers intrinsic and extrinsic cellular antiviral responses, as well as reduces replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in vitro. Although IFNa alone was insufficient to completely abolish SARS-CoV-2 replication, combinations of IFNa with remdesivir or other antiviral agents (EIDD-2801, camostat, cycloheximide, or convalescent serum) showed strong synergy and effectively inhibited SARS-CoV-2 infection in human lung epithelial Calu-3 cells. Furthermore, we showed that the IFNa-remdesivir combination suppressed virus replication in human lung organoids, and that its single prophylactic dose attenuated SARS-CoV-2 infection in lungs of Syrian hamsters. Transcriptome and metabolomic analyses showed that the combination of IFNa-remdesivir suppressed virus-mediated changes in infected cells, although it affected the homeostasis of uninfected cells. We also demonstrated synergistic antiviral activity of IFNa2a-based combinations against other virus infections in vitro. Altogether, our results indicate that IFNa2a-based combination therapies can achieve higher efficacy while requiring lower dosage compared to monotherapies, making them attractive targets for further pre-clinical and clinical development.

microbiology↗

Identification of novel antiviral drug combinations in vitro and tracking their development

Combination therapies have become a standard for the treatment for HIV and HCV infections. They are advantageous over monotherapies due to better efficacy and reduced toxicity, as well as the ability to prevent the development of resistant viral strains and to treat viral co-infections. Here, we identify several new synergistic combinations against emerging and re-emerging viral infections in vitro. We observed synergistic activity of nelfinavir with investigational drug EIDD-2801 and convalescent serum against SARS-CoV-2 infection in human lung epithelial Calu-3 cells. We also demonstrated synergistic activity of vemurafenib combination with emetine, homoharringtonine, gemcitabine, or obatoclax against echovirus 1 infection in human lung epithelial A549 cells. We also found that combinations of sofosbuvir with brequinar and niclosamide were synergistic against HCV infection in hepatocyte derived Huh-7.5 cells, whereas combinations of monensin with lamivudine and tenofovir were synergistic against HIV-1 infection in human cervical TZM-bl cells. Finally, we present an online resource that summarizes novel and known antiviral drug combinations and their developmental status. Overall, the development of combinational therapies could have a global impact improving the preparedness and protection of the general population from emerging and re-emerging viral threats.

microbiology↗

Antiviral options against SARS-CoV-2 infection

As of June 2020, the number of people infected with severe acute respiratory coronavirus 2 (SARS-CoV-2) continues to skyrocket, with more than 6,5 million cases worldwide. Both the World Health Organization (WHO) and United Nations (UN) has highlighted the need for better control of SARS-CoV-2 infections. However, developing novel virus-specific vaccines, monoclonal antibodies and antiviral drugs against SARS-CoV-2 can be time-consuming and costly. Convalescent sera and safe-in-man broad-spectrum antivirals (BSAAs) are readily available treatment options. Here we developed a neutralization assay using SARS-CoV-2 strain and Vero-E6 cells. We identified most potent sera from recovered patients for treatment of SARS-CoV-2-infected patients. We also screened 136 safe-in-man broad-spectrum antivirals against SARS-CoV-2 infection in Vero-E6 cells and identified nelfinavir, salinomycin, amodiaquine, obatoclax, emetine and homoharringtonine. We found that combinations of virus-directed nelfinavir along with host-directed amodiaquine exhibited the highest synergy. Finally, we developed a website to disseminate the knowledge on available and emerging treatments of COVID-19.

microbiology↗

Cellbow: a robust customizable cell segmentation program

Time-lapse live cell imaging of a growing cell population is routine in many biological investigations. A major challenge in imaging analysis is accurate segmentation, a process to define the boundaries of cells based on raw image data. Current segmentation methods relying on single boundary features have problems in robustness when dealing with inhomogeneous foci which invariably happens in cell population imaging. Here, we demonstrated that combined with multi-layer training set strategy, a neural-network-based algorithm Cellbow can achieve accurate and robust segmentation of cells in broad and general settings. It can also facilitate long-term tracking of cell growth and division. Furthermore, Cellbow is customizable and generalizable. It is broadly applicable to segmenting fluorescent images of diverse cell types with no further training needed. For bright-field images, only a small set of sample images of the specific cell type from the user may be needed for training. To facilitate the application of Cellbow, we provide a website on which one can online test the software, as well as an ImageJ plugin for the user to visualize the performance before software installation.

systems biology↗

Accelerating Monte Carlo modeling of structured-light based diffuse optical imaging via "photon sharing"

The increasing use of spatially-modulated imaging and single-pixel detection techniques demands computationally efficient methods for light transport modeling. Herein, we report an easy-to-implement yet significantly more efficient Monte Carlo (MC) method for simultaneously simulating spatially modulated illumination and detection patterns accurately in 3-D complex domains. We have implemented this accelerated algorithm, named "photon sharing", in our open-source MC simulators, reporting 13.6x and 5.5x speedups in mesh- and voxel-based MC benchmarks, respectively. In addition, the proposed algorithm is readily used for accelerating the solving of inverse problems in spatially-modulated imaging systems by building Jaco-bians of all illumination-detection pattern pairs concurrently, resulting in a 12.4-fold speed improvement. https://doi.org/10.1101/2020.02.16.951590

biophysics↗

Deep Learning Enhanced Hyperspectral Fluorescence Lifetime Imaging

Acquiring dense high-dimensional optical data in biological applications remains a challenge due to the very low levels of light typically encountered. Single pixel imaging methodologies enable improved detection efficiency in such conditions but are still limited by relatively slow acquisition times. Here, we propose a Deep Learning framework, NetFLICS-CR, which enables fast hyperspectral lifetime imaging for in vivo applications at enhanced resolution, acquisition and processing speeds, without the need of experimental training datasets. NetFLICS-CR reconstructs intensity and lifetime images at 128x128 pixels over 16 spectral channels while reducing the current acquisition times from [~]2.5 hours at 50% compression to [~]3 minutes at 99% compression when using a single-pixel Hyperspectral Macroscopic Fluorescence Lifetime Imaging (HMFLI) system. The potential of the technique is demonstrated in silico, in vitro and in vivo through the monitoring of receptor-ligand interactions in mice liver and bladder and further imaging of intracellular drug delivery of the clinical drug Trastuzumab in live animals bearing HER2-positive breast tumor xenografts.

biophysics↗

Quality of Whole Genome Sequencing from Blood versus Saliva Derived DNA in Cardiac Patients

Whole-genome sequencing (WGS) is becoming an increasingly important tool for detecting genomic variation. Blood derived DNA is the current standard for WGS for research or clinical purposes. We compared the level of microbial contamination, sequencing coverage, as well as yield and concordance of single-nucleotide polymorphism (SNP) and copy number variant (CNV) calls in WGS from paired blood and saliva samples from 5 pediatric heart disease patients. We found that although saliva samples contained a higher proportion of sequence reads that map to the human oral microbiome, these reads were readily excluded by mapping the reads to the human reference genome. Sequencing coverage was low only in 1 of 5 saliva samples. Over 95% SNPs (including rare SNPs) but <80% CNVs called in blood genomes were detected in paired saliva genomes. These findings suggest that most good quality saliva samples can serve as an alternative to blood samples for detection of sequence variants from WGS in cardiovascular disease patients.

genomics↗

Ultra-fast fit-free analysis of complex fluorescence lifetime imaging via deep learning

Fluorescence lifetime imaging (FLI) provides unique quantitative information in biomedical and molecular biology studies, but relies on complex data fitting techniques to derive the quantities of interest. Herein, we propose a novel fit-free approach in FLI image formation that is based on Deep Learning (DL) to quantify complex fluorescence decays simultaneously over a whole image and at ultra-fast speeds. Our deep neural network (DNN), named FLI-Net, is designed and model-based trained to provide all lifetime-based parameters that are typically employed in the field. We demonstrate the accuracy and generalizability of FLI-Net by performing quantitative microscopic and preclinical experimental lifetime-based studies across the visible and NIR spectra, as well as across the two main data acquisition technologies. Our results demonstrate that FLI-Net is well suited to quantify complex fluorescence lifetimes, accurately, in real time in cells and intact animals without any parameter settings. Hence, it paves the way to reproducible and quantitative lifetime studies at unprecedented speeds, for improved dissemination and impact of FLI in many important biomedical applications, especially in clinical settings.

bioengineering↗

Pre-implantation genetic diagnosis for a family with Usher syndrome through targeted sequencing and haplotype analysis

ObjectiveOur objective was to investigate the applicability of targeted capture massively parallel sequencing in developing personalized pre-implantation genetic diagnosis (PGD) assay.\n\nMethodsOne couple at risk of transmitting Usher Syndrome to their offspring was recruited to this study. The genomics DNA (gDNA) was extracted from the peripheral blood and underwent in vitro fertilization (IVF)-PGD. Prenatal molecular diagnosis was performed in the 20th week of gestation and the chromosomal anomaly was analyzed.\n\nResultsCustomized capture probe targeted at USH2A gene and 350kb flanking region were designed for PGD. Eleven blastocysts were biopsied and amplified by using multiple displacement amplification (MDA) and capture sequencing. A HMM-based haplotype analysis was performed to deduce embryos genotype by using SNPs identified in each sample. Four embryos were diagnosed as free of fathers rare mutation, two were transferred and one achieved a successful pregnancy. The fetal genotype was confirmed by Sanger sequencing of fetal genomic DNA obtained by amniocentesis. The PGD and prenatal diagnosis results were further confirmed by the molecular diagnosis of the babys genomic DNA sample. The auditory test showed that the hearing was normal.\n\nConclusionTargeted capture massively parallel sequencing (MPS) is an effective and convenient strategy to develop customized PGD assay.\n\nKey pointsGenetic counseling session was conducted with a family having Usher patient who was molecularly diagnosed, and a healthy baby was born with the help of successful PGD assay. This is of vast importance in management plans since it is the first report of PGD in Usher syndrome based on targeted capture MPS.

genetics↗