Biology subjects

Qin, P.

Publications and source records attributed to Qin, P..

30 records · Page 2Linked to original sources

bioRxiv2022

Detection of Frog virus 3 via the system integrating RPA-CRISPR/Cas12a-SPM with deep learning

Frog virus 3 (FV3, genera Ranavirus, family Iridoviridae), a double-stranded DNA virus, results in irreparable damage to biodiversity and significant economic losses to aquaculture. Although the existing FV3 detection methods are of high sensitivity and specificity, the complex procedure and requirement of expensive instruments limit their practical implantation. Herein, we develop a fast, easy-to-implement, highly sensitive, and point-of-care (POC) detection system for FV3. Combining recombinase polymerase amplification (RPA) and CRISPR/Cas12a, we achieve a limit of detection (LoD) of 100 aM (60.2 copies/L) by optimizing RPA primers and CRISPR RNAs (crRNAs). For POC detection, we build a smartphone microscopy (SPM) and achieve an LoD of 10 aM within 40 minutes. Four positive animal-derived samples with a quantitation cycle (Cq) value of quantitative PCR (qPCR) in the range of 13 to 32 are detectable by the proposed system. In addition, we deploy deep learning models for binary classification (positive or negative samples) and multiclass classification (different concentrations of FV3 and negative samples), achieving 100% and 98.75% accuracy, respectively. Without temperature regulation and expensive equipment, RPA-CRISPR/Cas12a combined with a smartphone readout and artificial intelligence (AI) assisted classification shows great potential for FV3 detection. This integrated system holds great promise for POC detection of aquatic DNA pathogens. HighlightsO_LIAn integrated DNA detection system is developed by combining RPA, CRISPR/Cas12a, smartphone microscopy, and deep learning. C_LIO_LIThe LoD of frog virus 3 is 10 aM within 40 min. C_LIO_LIThe detection system shows good performance on animal-derived samples. C_LI

molecular biology↗

bioRxiv2022

Decoding Subject's Own Name in the Primary Auditory Cortex

Current studies have shown that perception of subjects own name (SON) involves multiple multimodal brain regions, while activities in unimodal sensory regions (i.e., primary auditory cortex) and their interaction with multimodal regions during the self-processing remain unclear. To answer this, we combined multivariate pattern analysis and dynamic causal modelling analysis to explore the regional activation pattern and inter-region effective connection during the perception of SON. We found that SON and other names could be decoded from the activation pattern in the primary auditory cortex. In addition, we found an excitatory effect of SON on connections from the anterior insula/inferior frontal gyrus to the primary auditory cortex, and to the temporal parietal junction. Our findings extended the current knowledge of self-processing by showing that primary auditory cortex could discriminate SON from other names. Furthermore, our findings highlighted the importance of influence of the insula on the primary auditory cortex during self-processing.

neuroscience↗

bioRxiv2022

Longitudinal structural change of gray matter before and after hemispherotomy

BackgroundHemispherotomy is an effective surgery developed to treat refractory epilepsy caused by diffuse unihemispheric pathologies. Post-surgery neuroplastic mechanisms supporting behavioral recovery after left and right hemispherotomy as well as their difference remain largely unclear. MethodsIn a large cohort of 57 pediatric patients who underwent hemispherotomy, voxel-wise GMV in unaffected regions (contralesional cerebrum and bilateral cerebellum) and behavioral abilities were assessed before and after surgery. Using linear mixed models, we evaluated changes in GMV and behavioral scores, and how GMV changes correlated with improvements in behavioral scores. In addition, three machine learning regression algorithms were applied to assess whether preoperative GMV can predict postoperative behavior. ResultsIn the two patient groups (29 left hemispherotomy patients, age of surgery mean {+/-} standard deviation = 3.5 {+/-} 2.5; 28 right hemispherotomy patients, age of surgery 4.6 {+/-} 2.5), widespread increases in the postoperative GMV in the contralateral cerebrum and ipsilateral cerebellum but decreases in the postoperative GMV in the contralateral cerebellum were consistently observed. Importantly, the decrease in GMV in the contralateral cerebellum was significantly correlated with improvement in behavioral scores in right but not left hemispherotomy patients. Moreover, the preoperative GMV around the most longitudinally changed locations significantly predicted postoperative behavioral scores in left but not right hemispherotomy patients. ConclusionsOur findings indicate an important role for the contralateral cerebellum in the recovery after right hemispherotomy, and postoperative behavioral scores can be predicted with preoperative GMV features. What is already known on this topicThe contralesional cerebrum plays a key role in the recovery after hemispherotomy. What this study addsDespite suffering from gray matter atrophy, GMV decrease in contralesional cerebellum is associated with improvement in behavioral score in patients after hemispherotomy. How this study might affect research, practice or policyThese results provide novel insight into the prominence of the contralateral cerebellum in the recovery after hemispherotomy and highlight the clinical role of presurgery GMV in the prediction of postsurgery behavior.

neuroscience↗

bioRxiv2021

Amplification-free detection of viral RNA by super resolution imaging-based CRISPR/Cas13a System

RNA detection is crucial for biological research and clinical diagnosis. The current methods include both direct and amplification-based RNA detection. These methods require complicated procedures, suffering from low sensitivity, slow turnaround, and amplification bias. The CRISPR/Cas13a system is a direct RNA detection method via target RNA induced collateral cleavage activity. However, to detect low concentration RNA with CRISPR/Cas13a, target amplification is always required. Herein, we optimize the components of the CRISPR/Cas13a assay to enhance the sensitivity of viral RNA detection which improve the detection limit from 1 pM up to 100 fM. In addition, the integration of CRISPR/Cas13a biosensing and single molecule super resolution imaging is a novel strategy for direct and amplification-free RNA detection. After surface modification, fluorescent RNA reporters are immobilized on the glass coverslip surface and fluorescent signals are captured by total internal reflection fluorescence microscopy (TIRFM), shifting the measurement from spectroscopy to imaging. We quantify the fluorescence signal intensity before and after collateral cleavage of the CRISPR system when viral RNA is present and achieve a detection limit of 10 fM. Therefore, we provide a novel TIRFM-based system to visualize the CRISPR trans-cleavage for direct and robust RNA detection.

bioengineering↗

bioRxiv2021

The cortical hubs related to recovery of consciousness

Background and ObjectivesThe neural mechanism that enables the recovery of consciousness in patients with unresponsive wakefulness syndrome (UWS) remains unclear. The aim of the current study is to characterize the cortical hub regions related to the recovery of consciousness in patients with UWS. MethodsVoxel-wise degree centrality analysis was adopted to identify the cortical hubs related to the recovery of consciousness, for which a total of 27 UWS patients were used, including 13 patients who emerged from UWS (UWS-E), and 14 patients who remained in UWS (UWS-R) at least three months after the experiment performance. Furthermore, other recoverable unconscious states including three independent deep sleep datasets (n = 12, 9, 9 respectively) and three independent anesthesia datasets (n = 27, 14, 6 respectively) were adopted as validation groups. Spatial similarity of the hub characteristic with the validation groups between the UWS-E and UWS-R was compared using the dice coefficient. Finally, with the cortical regions persistently shown as hubs across UWS-E and validation states, functional connectivity analysis was further performed to explore the connectivity patterns underlying the recovery of consciousness. ResultsFour cortical hubs were identified with significantly higher degree centrality for UWS-E than UWS-R, including the anterior precuneus, left inferior parietal lobule, left inferior frontal gyrus, and left middle frontal gyrus, of which the degree centrality value also positively correlated with the patients Glasgow Outcome Scale (GOS) score. Furthermore, the anterior precuneus was found to show significantly higher similarity of hub characteristics as well as functional connectivity pattern between UWS-E and validation groups, compared with UWS-R. DiscussionThe results suggest that the recovery of consciousness may be relevant to the integrity of cortical hubs, especially the anterior precuneus. The identified cortical hub regions could serve as potential targets for noninvasive stimulation aimed at promoting the patients consciousness recovery.

neuroscience↗

bioRxiv2021

DeepHBV: A deep learning model to predict hepatitis B virus (HBV) integration sites.

Hepatitis B virus (HBV) is one of the main causes for viral hepatitis and liver cancer. Previous studies showed HBV can integrate into host genome and further promote malignant transformation. In this study, we developed an attention-based deep learning model DeepHBV to predict HBV integration sites by learning local genomic features automatically. We trained and tested DeepHBV using the HBV integration sites data from dsVIS database. Initially, DeepHBV showed AUROC of 0.6363 and AUPR of 0.5471 on the dataset. Adding repeat peaks and TCGA Pan Cancer peaks can significantly improve the model performance, with an AUROC of 0.8378 and 0.9430 and an AUPR of 0.7535 and 0.9310, respectively. On independent validation dataset of HBV integration sites from VISDB, DeepHBV with HBV integration sequences plus TCGA Pan Cancer (AUROC of 0.7603 and AUPR of 0.6189) performed better than HBV integration sequences plus repeat peaks (AUROC of 0.6657 and AUPR of 0.5737). Next, we found the transcriptional factor binding sites (TFBS) were significantly enriched near genomic positions that were paid attention to by convolution neural network. The binding sites of AR-halfsite, Arnt, Atf1, bHLHE40, bHLHE41, BMAL1, CLOCK, c-Myc, COUP-TFII, E2A, EBF1, Erra and Foxo3 were highlighted by DeepHBV attention mechanism in both dsVIS dataset and VISDB dataset, revealing the HBV integration preference. In summary, DeepHBV is a robust and explainable deep learning model not only for the prediction of HBV integration sites but also for further mechanism study of HBV induced cancer. Author summaryHepatitis B virus (HBV) is one of the main causes for viral hepatitis and liver cancer. Previous studies showed HBV can integrate into host genome and further promote malignant transformation. In this study, we developed an attention-based deep learning model DeepHBV to predict HBV integration sites by learning local genomic features automatically. The performance of DeepHBV model significantly improves after adding genomic features, with an AUROC of 0.9430 and an AUPR of 0.9310. Furthermore, we enriched the transcriptional factor binding sites of proteins by convolution neural network. In summary, DeepHBV is a robust and explainable deep learning model not only for the prediction of HBV integration sites but also for the further study of HBV integration mechanism.

bioinformatics↗

bioRxiv2020

In-House Forecasting of Crop Latitude Adaptation through a Daylength-sensing-based Environment Adaptation Simulator (DEAS)

Global climate change necessitates the accelerated breeding of new crop varieties that can sustain yields in new environments. As a proxy for environmental adaptation, the selection of crops that can adapt to different latitudes is an appealing strategy. However, such selection currently involves a lengthy procedure that severely restricts the rapid breeding of varieties. Here, we aimed to combine molecular technologies with an in-house streamlined screening method to facilitate rapid selection for latitude adaptation. We established the Daylength-sensing-based Environment Adaptation Simulator (DEAS) to measure crop latitude adaptation via the transcriptional dynamics of florigen genes at different latitudes. We used different statistical approaches to demonstrate that DEAS predicts the florigen expression profiles in rice with high accuracy. Furthermore, we demonstrated the potential for application of DEAS in different crops. Incorporating DEAS into the breeding programs of conventional and underutilized crops could help meet the future needs for crop adaptation and promote sustainable agriculture.

plant biology↗

bioRxiv2020

Higher-order sensorimotor circuit of the brain' global network supports human consciousness

The neural correlates of consciousness, defined as the minimum neuronal mechanisms sufficient for any conscious percept, are usually subject to different interpretations depending on whether one uses measures of local or global brain activities. We argue that the local regions may support consciousness by serving as hubs within the brains global network. We adopt a unique functional magnetic resonance imaging resting state dataset that encompasses various conscious states, including non-rapid eye movement (NREM)-sleep, rapid eye movement (REM)-sleep, anesthesia, and brain injury patients. Using a graph-theoretical measure for detecting local hubs within the brains global network, we identify various higher-order sensory and motor regions as hubs with significantly reduced degree centrality during unconsciousness. Additionally, these regions form a sensorimotor circuit which correlates with levels of consciousness. Our findings suggest that integration of higher-order sensorimotor function may be a key mechanism of consciousness. This opens novel perspectives for therapeutic modulation of unconsciousness.

neuroscience↗

bioRxiv2020

Integrated Micropillar Polydimethylsiloxane Accurate CRISPR Detection (IMPACT) System for Rapid Viral DNA Sensing

A fully Integrated Micropillar Polydimethylsiloxane Accurate CRISPR Detection (IMPACT) system is developed for viral DNA detection. This powerful system is patterned with high-aspect ratio micropillars to enhance reporter probe binding. After surface modification and probe immobilization, CRISPR Cas12a/crRNA complex is injected into the fully enclosed system. With the presence of double-stranded DNA target, the CRISPR enzyme is activated and non-specifically cleaves the ssDNA reporters initially immobilized on the micropillars. This collateral cleavage releases fluorescence dyes into the assay, and the intensity is linearly proportional to the target DNA concentration ranging from 0.1 to 10 nM. Importantly, this system does not rely on traditional dye-quencher labeled probe thus eliminating the fluorescence background presented in the assay. Furthermore, our one-step detection protocol is performed at isothermal conditions (37{degrees}C) without using complicated and time-consuming off-chip probe hybridization and denaturation. This miniaturized and fully packed IMPACT chip demonstrates rapid, sensitive, and simple nucleic acid detection and is an ideal candidate for the next generation molecular diagnostic platform for point-of-care (POC) applications, responding to emerging and deadly pathogen outbreaks.

bioengineering↗

bioRxiv2020

Integrated decoding hematopoiesis and leukemogenesis at single-cell resolution and its clinical implication

Integrated analyses of hematopoiesis and leukemogenesis could provide new biological and clinical insights1,2. Here we constructed a comprehensive cell atlas using [~]100,000 single cell transcriptomes of bone marrow mononuclear cells and its subsets from 5 healthy samples and 13 leukemia samples. Trajectory analysis showed hematopoietic stem cells continuously differentiated through tree-like structure into 7 lineages. Although our single cell analyses showed the major cellular heterogeneity were inter-patients, there were distinct leukemia cell subpopulations within patient. We developed counterpart composite index (CCI) for projecting leukemia cell subpopulation into reference hematopoietic cells, to identify their healthy counterparts that could predict leukemia subtype and clinical outcome. Interestingly, we found the trajectories of leukemogenesis were similar to that of their healthy counterparts, indicating lineage relationship of leukemia cell subpopulations. Single cell analyses of leukemia patient at diagnosis, refractory, remission and relapse vividly presented dynamics of cell population and the underlying genes. Single cell transcriptomic variants analyses showed the relapsed leukemia cells, whose healthy counterparts were closer to the root of hematopoietic tree, were derived from an early minor leukemia cell population. This study not only increased our understanding of hematopoiesis and leukemogenesis, but also provided an approach for leukemia classification and clinical outcome prediction.

genomics↗

bioRxiv2020

Rice NIN-LIKE PROTEIN 4 is a master regulator of nitrogen use efficiency

Nitrogen (N) is one of the key essential macronutrients that affects rice growth and yield. Inorganic N fertilizers are excessively used to boost yield and generate serious collateral environmental pollution. Therefore, improving crop N use efficiency (NUE) is highly desirable and has been a major endeavor in crop improvement. However, only a few regulators have been identified that can be used to improve NUE in rice to date. Here we show that the NIN-like protein OsNLP4 significantly improves the rice NUE and yield. Field trials consistently showed that loss-of-OsNLP4 dramatically reduced yield and NUE compared with wild type under different N regimes. In contrast, the OsNLP4 overexpression lines remarkably increased yield by 30% and NUE by 47% under moderate N level compared with wild type. Transcriptomic analyses revealed that OsNLP4 orchestrates the expression of a majority of known N uptake, assimilation and signaling genes by directly binding to the nitrate-responsive cis-element in their promoters to regulate their expression. Moreover, overexpression of OsNLP4 can recover the phenotype of Arabidopsis nlp7 mutant and enhance its biomass. Our results demonstrate that OsNLP4 is a master regulator of NUE in rice and sheds light on crop NUE improvement.

plant biology↗

bioRxiv2019

High-throughput and all-solution phase African Swine Fever Virus (ASFV) detection using CRISPR-Cas12a and fluorescence based point-of-care system

Here we report the development of a high throughput, all-solution phase, and isothermal detection system to detect African Swine Fever Virus (ASFV). CRISPR-Cas12a programmed with a CRISPR RNA (crRNA) is used to detect ASFV target DNA. Upon ASFV DNA binding, the Cas12a/crRNA/ASFV DNA complex becomes activated and degrades a fluorescent single stranded DNA (ssDNA) reporter present in the assay. We combine this powerful CRISPR-Cas assay with fluorescence-based point-of-care (POC) system we developed for rapid and accurate virus detection. Without nucleic acid amplification, a detection limit of 1 pM is achieved within 2 hrs. In addition, the ternary Cas12a/crRNA/ASFV DNA complex is highly stable at physiological temperature and continues to cleave the ssDNA reporter even after 24 hrs of incubation, resulting in an improvement of the detection limit to 100 fM. We show that this system is very specific and can differentiate nucleic acid targets with closely matched sequences. The high sensitivity and selectivity of our system enables the detection of ASFV in femtomolar range. Importantly, this system features a disposable cartridge and a sensitive custom designed fluorometer, enabling compact, multiplexing, and simple ASFV detection, intended for low resource settings.

bioengineering↗