Biology subjects

Teng, Y.

Publications and source records attributed to Teng, Y..

26 records · Page 2Linked to original sources

bioRxiv2020

Distinct hydrogenotrophic bacteria are stimulated by elevated H2 levels in upland and wetland soils

BackgroundMolecular hydrogen (H2) is a major energy source supporting bacterial growth and persistence in soil ecosystems. While recent studies have uncovered mediators of atmospheric H2 consumption, far less is understood about how soil microbial communities respond to elevated H2 levels produced through natural or anthropogenic processes. Here we performed microcosm experiments to resolve how microbial community composition, capabilities, and activities change in upland (meadow, fluvo-aquic soil) and wetland (rice paddy, anthrosols soil) soils following H2 supplementation (at mixing doses from 0.5 to 50,000 ppmv). ResultsGenome-resolved metagenomic profiling revealed that these soils harbored diverse bacteria capable of using H2 as an electron donor for aerobic respiration (46 of the 196 MAGs from eight phyla) and carbon fixation (15 MAGs from three phyla). H2 stimulated the growth of several of these putative hydrogenotrophs in a dose-dependent manner, though the lineages stimulated differed between the soils; whereas actinobacterial lineages encoding group 2a [NiFe]-hydrogenases grew most in the upland soils (i.e. Mycobacteriaceae, Pseudonocardiaceae), proteobacterial lineages harboring group 1d [NiFe]-hydrogenases were most enriched in wetland soils (i.e. Burkholderiaceae). Hydrogen supplementation also influenced the abundance of various other genes associated with biogeochemical cycling and bioremediation pathways to varying extents between soils. Reflecting this, we observed an enrichment of a hydrogenotrophic Noviherbaspirillum MAG capable of biphenyl hydroxylation in the wetland soils and verified that H2 supplementation enhanced polychlorinated biphenyl (PCB) degradation in these soils, but not the upland soils. ConclusionsOur findings suggest that soils harbour different hydrogenotrophic bacteria that rapidly grow following H2 exposure. In turn, this adds to growing evidence of a large and robust soil H2 sink capable of counteracting growing anthropogenic emissions.

bioinformatics↗

bioRxiv2020

Time-resolved expression analysis comparing two selective retinal cell ablation paradigms in zebrafish reveals shared and cell-specific regenerative regulatory networks.

Retinal Muller glia (MG) can act as stem-like cells to generate new neurons in both zebrafish and mice. In zebrafish, retinal regeneration is innate and robust, resulting in the replacement of lost neurons and restoration of visual function. In mice, exogenous stimulation of MG is required to reveal a dormant and, to date, limited regenerative capacity. Zebrafish studies have been key in revealing factors that promote regenerative responses in the mammalian eye. Increased understanding of how the regenerative potential of MG is regulated in zebrafish may therefore aid efforts to promote retinal repair therapeutically. Developmental signaling pathways are known to coordinate regeneration following widespread retinal cell loss. In contrast, less is known about how regeneration is regulated in the context of retinal degenerative disease, i.e., following the loss of specific retinal cell types. To address this knowledge gap, we compared transcriptomic responses underlying regeneration following targeted loss of rod photoreceptors or bipolar cells. In total, 2,531 differentially expressed genes (DEGs) were identified, with the majority being paradigm specific, including during early MG activation phases, suggesting the nature of the injury/cell loss informs the regenerative process from initiation onward. For example, early modulation of Notch signaling was implicated in the rod but not bipolar cell ablation paradigm and components of JAK/STAT signaling were implicated in both paradigms. To examine candidate gene roles in rod cell regeneration, including several immune-related factors, CRISPR/Cas9 was used to create G0 mutant larvae (i.e., "crispants"). Rod cell regeneration was inhibited in stat3 crispants, while mutating stat5a/b, c7b and txn accelerated rod regeneration kinetics. These data support emerging evidence that discrete responses follow from selective retinal cell loss and that the immune system plays a key role in regulating "fate-biased" regenerative processes. Author SummaryBlinding diseases are linked to the loss of specific types of neurons in the retina. In humans, this eventually leads to loss of sight. In zebrafish, however, lost retinal neurons are regenerated resulting in restored vision. Our lab has developed zebrafish models that induce the loss of disease-relevant retinal neurons, thereby allowing us to study how individual cell types are regenerated. Here, to better understand how these processes are regulated, we compared gene expression changes occurring during loss and regeneration of two different retinal cell types, rod photoreceptors and bipolar interneurons. The majority of gene changes were specific to each cell type studied, providing strong evidence that genetic programs underlying stem cell activation vary depending on the cell type lost. We also found that the immune system was implicated as a regulator of regeneration in both models, but that individual immune-related genes were more strongly associated with one of the two models. Furthermore, disrupting multiple genes involved in immune system signaling led to enhanced rod regeneration. We hope that a better understanding of how retinal cell regeneration is regulated in zebrafish will aid efforts to develop regenerative therapeutics designed to restore sight to patients who have lost their vision.

neuroscience↗

bioRxiv2020

Rapid adaptation of SARS-CoV-2 in BALB/c mice: Novel mouse model for vaccine efficacy

Coronavirus disease 2019 (COVID-19) threatens global public health and economy. In order to develop safe and effective vaccines, suitable animal models must be established. Here we report the rapid adaption of SARS-CoV-2 in BALB/c mice, based on which a convenient, economical and effective animal model was developed. Specifically, we found that mouse-adapted SARS-CoV-2 at passage 6 (MACSp6) efficiently infected both aged and young wild-type BALB/c mice, resulting in moderate pneumonia as well as inflammatory responses. The elevated infectivity of MACSp6 in mice could be attributed to the substitution of a key residue (N501Y) in the receptorbinding domain (RBD). Using this novel animal model, we further evaluated the in vivo protective efficacy of an RBD-based SARS-CoV-2 subunit vaccine, which elicited highly potent neutralizing antibodies and conferred full protection against SARS-CoV-2 MACSp6 challenge. This novel mouse model is convenient and effective in evaluating the in vivo protective efficacy of SARS-CoV-2 vaccine. SummaryThis study describes a unique mouse model for SARS-CoV-2 infection and confirms protective efficacy of a SARS-CoV-2 RBD subunit vaccine.

microbiology↗

bioRxiv2019

A novel machine learning based approach for iPS progenitor cell identification

Identification of induced pluripotent stem (iPS) progenitor cells, the iPS forming cells in early stage of reprogramming, could provide valuable information for studying the origin and underlying mechanism of iPS cells. However, it is very difficult to identify experimentally since there are no biomarkers known for early progenitor cells, and only about 6 days after reprogramming initiation, iPS cells can be experimentally determined via fluorescent probes. What is more, the ratio of progenitor cells during early reprograming period is below 5%, which is too low to capture experimentally in the early stage.\n\nIn this paper, we propose a novel computational approach for the identification of iPS progenitor cells based on machine learning and microscopic image analysis. Firstly, we record the reprogramming process using a live cell imaging system after 48 hours of infection with retroviruses expressing Oct4, Sox2 and Klf4, later iPS progenitor cells and normal murine embryonic fibroblasts (MEFs) within 3 to 5 days after infection are labeled by retrospectively tracing the time-lapse microscopic image. We then calculate 11 types of cell morphological and motion features such as area, speed, etc., and select best time windows for modeling and perform feature selection. Finally, a prediction model using XGBoost is built based on the selected six types of features and best time windows. Our model allows several missing values/frames in the sample datasets, thus it is applicable to a wide range of scenarios.\n\nCross-validation, holdout validation and independent test experiments showed that the minimum precision is above 52%, that is, the ratio of predicted progenitor cells within 3 to 5 days after viral infection is above 52%. The results also confirmed that the morphology and motion pattern of iPS progenitor cells is different from that of normal MEFs, which helps with the machine learning methods for iPS progenitor cell identification.\n\nAuthor SummaryIdentification of induced pluripotent stem (iPS) progenitor cells could provide valuable information for studying the origin and underlying mechanism of iPS cells. However, it is very difficult to identify experimentally since there are no biomarkers known for early progenitor cells, and only after about 6 days of induction, iPS cells can be experimentally determined via fluorescent probes. What is more, the percentage of the progenitor cells during the early induction period is below 5%, too low to capture experimentally in early stage. In this work, we proposed an approach for the identification of iPS progenitor cells, the iPS forming cells, based on machine learning and microscopic image analysis. The aim is to help biologists to enrich iPS progenitor cells during the early stage of induction, which allows experimentalists to select iPS progenitor cells with much higher probability, and furthermore to study the biomarkers which trigger the reprogramming process.

bioinformatics↗

bioRxiv2019

An updated analysis of opioids increasing the risk of fractures

ObjectiveTo assess the relationship between opioid therapy for chronic noncancer pain and fracture risk by a meta-analysis of cohort studies and case-control studies.\n\nMethodsThe included cohort studies and case-control studies were identified by searching the PubMed and EMBASE databases from their inception until May 24, 2019. The outcome of interest was a fracture. This information was independently screened by two authors. When the heterogeneity among studies was significant, a random effects model was used to determine the overall combined risk estimate.\n\nResultsIn total, 12 cohort studies and 6 case-control studies were included. We used the Newcastle-Ottawa Scale (NOS) to evaluate the quality of the included literature, and 14 of the studies were considered high-quality studies. The overall relative risk of opioid therapy and fractures was 1.78 (95% confidence interval (CI) 1.53 - 2.07). Subgroup analyses revealed sources of heterogeneity, sensitivity analysis was stable, and no publication bias was observed.\n\nConclusionsThe meta-analysis showed that the use of opioids significantly increased the risk of fracture.

pharmacology and toxicology↗

bioRxiv2018

Nucleosome remodelling at origins of Global Genome-Nucleotide Excision Repair occurs at the boundaries of higher-order chromatin structure

Repair of UV-induced DNA damage requires chromatin remodeling. How repair is initiated in chromatin remains largely unknown. We recently demonstrated that Global Genome Nucleotide Excision Repair (GG-NER) in chromatin is organized into domains around open reading frames. Here, we identify these domains, and by examining DNA damage-induced changes in the linear structure of nucleosomes, we demonstrate how chromatin remodeling is initiated during repair. In undamaged cells, we show that the GG-NER complex occupies chromatin at nucleosome free regions of specific gene promoters. This establishes the nucleosome structure at these genomic locations, which we refer to as GG-NER complex binding sites (GCBSs). We demonstrate that these sites are frequently located at genomic boundaries that delineate chromasomally interacting domains (CIDs). These boundaries define domains of higher-order nucleosome-nucleosome interaction. We show that efficient repair of DNA damage in chromatin is initiated following disruption of H2A.Z-containing nucleosomes adjacent to GCBSs by the GG-NER complex.

genomics↗

bioRxiv2018

A novel GATA-binding protein 4 gene variation associated with familial atrial septal defect

Atrial septal defect (ASD) is the most common congenital heart defect. Part of ASD exhibits familial predisposition, but the genetic mechanism remains largely unknown. In the current study, we use multiple methods to identify and confirm the gene associated with a familial ASD. Chromosomal microarray analyses, whole exome sequencing, Sanger sequencing, multiple bioinformatics programs, in silico protein structure modeling and molecular dynamics simulation were performed to predict the pathogenic of the variant gene. Dual-Luciferase reporter gene assay was performed to evaluate the influence of downstream target gene of the target variation. A novel, heterozygous, missense variant GATA-binding protein 4 (GATA4):c.958C>T, p.R320W was identified. An autosomal dominant inheritance pattern with incomplete penetrance was observed in the family. Multiple prediction indicate the variant in GATA4 to be deleterious. Molecular dynamics simulation further revealed that the variation of p.R320W could prevent the zinc finger of GATA4 from interacting with the DNA. Dual-Luciferase reporter assay demonstrated a significant decrease in transcriptional activity (0.90{+/-}0.099 vs 1.50{+/-}0.079, p = 0.001) of the variant GATA4 compared with the wild type. We believe the novel variation of GATA4 (c.958C>T, p.R320W) with a pattern of incomplete inheritance that may be highly associated with this familial ASD. The finding enriched our knowledge of variations that may associated with ASD.

genetics↗

bioRxiv2017

Epidemic Potential for Human Infection with Influenza A (H7N9) Virus in China through Web Search Behaviors: A Data-Driven Study

Since the beginning of September 2016, a steep upsurge of the human cases of avian influenza A (H7N9) virus has been reported in China, which are alarming public concern for the pandemic potential of the H7N9 virus. In this study, we collected the data from H7N9 epidemics and H7N9-related Baidu Search Index (BSI) in China between September 2013 and June 2017. And we observed a strong correlation between the numbers of Influenza A (H7N9) cases and H7N9-related BSI in Guangdong province and Shanghai municipality (p<0.001). Autoregressive integrated moving average (ARIMA) models were constructed for the dynamic estimation of seasonal H7N9 outbreaks in 2016-2017 and the online search data acted as an external regressor with the historical H7N9 epidemic data in the forecasting model to improve the quality of predictions. Predictions by the models closely matched the actual numbers of reported cases during current H7N9 epidemic season. Especially, the estimated numbers of reported cases sharply increased to reach 49.88 (95% CI: 0-194.05) in Guangdong and 9.05 (95% CI: 0-37.43) in Shanghai from December 2016 to June 2017. Moreover, this accessible and flexible dynamic forecast model could be used in the monitoring of H7N9 virus to provide advanced warning of future emerging infection diseases.\n\nAuthor summaryAs the availability and popularity of the internet has greatly increased in recent years, an increasing number of cyber users, including patients and their family members, search online for health information on personal computers (PCs) and mobile phones (MPs) before seeking medical attention, making it possible to investigate the influenza prevalence by monitoring changes in frequencies of uses of particular search terms. In this study, we collected the data from H7N9 epidemics and H7N9-related Baidu Search Index (BSI) in China between September 2013 and June 2017. And then, we showed a strong correlation between the numbers of Influenza A (H7N9) cases and H7N9-related BSI in Guangdong province and Shanghai municipality (p<0.001). Furthermore, we reconstructed an improved dynamic forecasting method for outbreaks of H7N9 influenza using Autoregressive integrated moving average (ARIMA) models to predict future patterns of H7N9 transmission and the online search data acted as an external regressor with the historical H7N9 epidemic data in the forecasting model to improve the quality of predictions. Our results suggest that data from the Baidu search engine, combed with data from a traditional disease surveillance system, may be considered for early detection of H7N9 influenza outbreaks in mainland China.

epidemiology↗