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PathogenTrack and Yeskit:tools for identifying intracellular pathogens from single-cell RNA-sequencing datasets as illustrated by application to COVID-19

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Frontiers of Medicine 2022年第2期16卷 251-262页

作者： Wei Zhang Xiaoguang Xu Ziyu Fu Jian Chen Saijuan Chen yun tan Shanghai Institute of Hematology State Key Laboratory of Medical GenomicsNational Research Center for Translational Medicine at ShanghaiRuijin Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghai 200025China School of Life Sciences and Biotechnology Shanghai Jiao Tong UniversityShanghai 200240China Department of Thoracic Surgery Shanghai Pulmonary HospitalTongji University School of MedicineShanghai 200433China

Pathogenic microbes can induce cellular dysfunction,immune response,and cause infectious disease and other diseases including cancers.However,the cellular distributions of pathogens and their impact on host cells remain rarely explored due to the limited methods.Taking advantage of single-cell RNA-sequencing(scRNA-seq)analysis,we can assess the transcriptomic features at the single-cell level.Still,the tools used to interpret pathogens(such as viruses,bacteria,and fungi)at the single-cell level remain to be explored.Here,we introduced PathogenTrack,a python-based computational pipeline that uses unmapped scRNA-seq data to identify intracellular pathogens at the single-cell level.In addition,we established an R package named Yeskit to import,integrate,analyze,and interpret pathogen abundance and transcriptomic features in host cells.Robustness of these tools has been tested on various real and simulated scRNA-seq datasets.PathogenTrack is competitive to the state-of-the-art tools such as Viral-Track,and the first tools for identifying bacteria at the single-cell level.Using the raw data of bronchoalveolar lavage fluid samples(BALF)from COVID-19 patients in the SRA database,we found the SARS-CoV-2 virus exists in multiple cell types including epithelial cells and macrophages.SARS-CoV-2-positive neutrophils showed increased expression of genes related to type I interferon pathway and antigen presenting module.Additionally,we observed the Haemophilus parahaemolyticus in some macrophage and epithelial cells,indicating a co-infection of the bacterium in some severe cases of COVID-19.The PathogenTrack pipeline and the Yeskit package are publicly available at GitHub.

关键词： scRNA-seq intracellular pathogen microbe COVID-19 SARS-CoV-2

Distinct gene expression pattern of RUNX1 mutations coordinated by target repression and promoter hypermethylation in acute myeloid leukemia

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Frontiers of Medicine 2022年第4期16卷 627-636页

作者： Jingming Li Wen Jin yun tan Beichen Wang Xiaoling Wang Ming Zhao Kankan Wang Shanghai Institute of Hematology State Key Laboratory of Medical GenomicsNational Research Center for Translational Medicine at ShanghaiRuijin Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghai 200025China CNRS-LIA Hematology and Cancer Sino-French Research Center for Life Sciences and GenomicsRuijin Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghai 200025China

Runt-related transcription factor 1(RUNX1)is an essential regulator of normal hematopoiesis.Its dysfunction,caused by either fusions or mutations,is frequently reported in acute myeloid leukemia(AML).However,RUNX1 mutations have been largely under-explored compared with RUNX1 fusions mainly due to their elusive genetic characteristics.Here,based on 1741 patients with AML,we report a unique expression pattern associated with RUNX1 mutations in AML.This expression pattern was coordinated by target repression and promoter hypermethylation.We first reanalyzed a joint AML cohort that consisted of three public cohorts and found that RUNX1 mutations were mainly distributed in the Runt domain and almost mutually exclusive with NPM1 mutations.Then,based on RNA-seq data from The Cancer Genome Atlas AML cohort,we developed a 300-gene signature that significantly distinguished the patients with RUNX1 mutations from those with other AML subtypes.Furthermore,we explored the mechanisms underlying this signature from the transcriptional and epigenetic levels.Using chromatin immunoprecipitation sequencing data,we found that RUNX1 target genes tended to be repressed in patients with RUNX1 mutations.Through the integration of DNA methylation array data,we illustrated that hypermethylation on the promoter regions of RUNX1-regulated genes also contributed to dysregulation in RUNX1-mutated AML.This study revealed the distinct gene expression pattern of RUNX1 mutations and the underlying mechanisms in AML development.

关键词： RUNX1 gene mutation acute myeloid leukemia transcriptional repression DNA methylation

Coverless Video Steganography Based on Frame Sequence Perceptual Distance Mapping

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Computers, Materials & Continua 2022年第10期73卷 1571-1583页

作者： Runze Li Jiaohua Qin yun tan Neal N.Xiong College of Computer Science and Information Technology Central South University of Forestry&TechnologyChangsha410004China Department of Mathematics and Computer Science Northeastern State UniversityTahlequah74464OKUSA

Most existing coverless video steganography algorithms use a particular video frame for information hiding.These methods do not reflect the unique sequential features of video carriers that are different from image and have poor robustness.We propose a coverless video steganography method based on frame sequence perceptual distance mapping.In this method,we introduce Learned Perceptual Image Patch Similarity(LPIPS)to quantify the similarity between consecutive video frames to obtain the sequential features of the video.Then we establish the relationship map between features and the hash sequence for information hiding.In addition,the MongoDB database is used to store the mapping relationship and speed up the index matching speed in the information hiding process.Experimental results show that the proposed method exhibits outstanding robustness under various noise attacks.Compared with the existing methods,the robustness to Gaussian noise and speckle noise is improved by more than 40%,and the algorithm has better practicability and feasibility.

关键词： Coverless steganography frame sequence perception distance

Aortic Dissection Diagnosis Based on Sequence Information and Deep Learning

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Computers, Materials & Continua 2022年第11期73卷 2757-2771页

作者： Haikuo Peng yun tan Hao tang Ling tan Xuyu Xiang Yongjun Wang Neal N.Xiong Central South University of Forestry and Technology Changsha410004China The Second Xiangya Hospital of Central South University Changsha410011China Department of Mathematics and Computer Science Northeastern State UniversityTahlequah74464USA

Aortic dissection(AD)is one of the most serious diseases with high mortality,and its diagnosis mainly depends on computed tomography(CT)results.Most existing automatic diagnosis methods of AD are only suitable for AD recognition,which usually require preselection of CT images and cannot be further classified to different types.In this work,we constructed a dataset of 105 cases with a total of 49021 slices,including 31043 slices expertlevel annotation and proposed a two-stage AD diagnosis structure based on sequence information and deep learning.The proposed region of interest(RoI)extraction algorithm based on sequence information(RESI)can realize high-precision for RoI identification in the first stage.Then DenseNet-121 is applied for further diagnosis.Specially,the proposed method can judge the type of AD without preselection of CT images.The experimental results show that the accuracy of Stanford typing classification of AD is 89.19%,and the accuracy at the slice-level reaches 97.41%,which outperform the state-ofart methods.It can provide important decision-making information for the determination of further surgical treatment plan for patients.

关键词： Aortic dissection deep learning sequence information RoI

Integrated analysis of gut microbiome and host immune responses in COVID-19

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Frontiers of Medicine 2022年第2期16卷 263-275页

作者： Xiaoguang Xu Wei Zhang Mingquan Guo Chenlu Xiao Ziyu Fu Shuting Yu Lu Jiang Shengyue Wang yun Ling Feng Liu yun tan Saijuan Chen Shanghai Institute of Hematology State Key Laboratory of Medical GenomicsNational Research Center for Translational Medicine at ShanghaiRuijin Hospital Affiliated to Shanghai Jiao Tong University School ofMedicineShanghai 200025China Schoolof Life Sciences and Biotechnology Shanghai Jiao Tong UniversityShanghai 200240China Shanghai Public Health Clinical Center Shanghai 201508China Department of Laboratory Medicine Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghai 200025China

Emerging evidence indicates that the gut microbiome contributes to the host immune response to infectious diseases.Here,to explore the role of the gut microbiome in the host immune responses in COVID-19,we conducted shotgun metagenomic sequencing and immune profiling of 14 severe/critical and 24 mild/moderate COVID-19 cases as well as 31 healthy control samples.We found that the diversity of the gut microbiome was reduced in severe/critical COVID-19 cases compared to mild/moderate ones.We identified the abundance of some gut microbes altered post-SARS-CoV-2 infection and related to disease severity,such as Enterococcus faecium,Coprococcus comes,Roseburia intestinalis,Akkermansia ntuciniphila,Bacteroides cellulosilyticus and Blautia obeum.We further analyzed the correlation between the abundance of gut microbes and host responses,and obtained a correlation map between clinical features of COVID-19 and 16 severity-related gut microbe,including Coprococcus comes that was positively correlated with CD3^(+)/CD4^(+)/CD8^(+)lymphocyte counts.In addition,an integrative analysis of gut microbiome and the transcriptome of peripheral blood mononuclear cells(PBMCs)showed that genes related to viral transcription and apoptosis were up-regulated in Coprococcus comes low samples.Moreover,a number of metabolic pathways in gut microbes were also found to be differentially enriched in severe/critical or mild/moderate COVID-19 cases,including the superpathways of polyamine biosynthesis II and sulfur oxidation that were suppressed in severe/critical COVID-19.Together,our study highlighted a potential regulatory role of severity related gut microbes in the immune response of host.

关键词： COVID-19 SARS-COV-2 gut microbiome immune response

Criss-Cross Attentional Siamese Networks for Object Tracking

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Computers, Materials & Continua 2022年第11期73卷 2931-2946页

作者： Zhangdong Wang Jiaohua Qin Xuyu Xiang yun tan Neal N.Xiong College of Computer Science and Information Technology Central South University of Forestry&TechnologyChangsha410004China Department of Mathematics and Computer Science Northeastern State UniversityTahlequah74464OKUSA

Visual object tracking is a hot topic in recent years.In the meanwhile,Siamese networks have attracted extensive attention in this field because of its balanced precision and speed.However,most of the Siamese network methods can only distinguish foreground from the non-semantic background.The fine-tuning and retraining of fully-convolutional Siamese networks for object tracking(SiamFC)can achieve higher precision under interferences,but the tracking accuracy is still not ideal,especially in the environment with more target interferences,dim light,and shadows.In this paper,we propose crisscross attentional Siamese networks for object tracking(SiamCC).To solve the imbalance between foreground and non-semantic background,we use the feature enhancement module of criss-cross attention to greatly improve the accuracy of video object tracking in dim light and shadow environments.Experimental results show that the maximum running speed of SiamCC in the object tracking benchmark dataset is 90 frames/second.In terms of detection accuracy,the accuracy of shadow sequences is greatly improved,especially the accuracy score of sequence HUMAN8 is improved from 0.09 to 0.89 compared with the original SiamFC,and the success rate score is improved from 0.07 to 0.55.

关键词： Criss-cross attention object-tracking siamese-network

Primary assessment of the diversity of Omicron sublineages and the epidemiologic features of autumn/winter 2022 COVID-19 wave in Chinese mainland

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Frontiers of Medicine 2023年第4期17卷 758-767页

作者： Gang Lu yun Ling Minghao Jiang yun tan Dong Wei Lu Jiang Shuting Yu Fangying Jiang Shuai Wang Yao Dai Jinzeng Wang Geng Wu Xinxin Zhang Guoyu Meng Shengyue Wang Feng Liu Xiaohong Fan Saijuan Chen Shanghai Institute of Hematology National Research Center for Translational MedicineState Key Laboratory of Medical GenomicsRuijin Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghai 200025China Shanghai Public Health Clinical Center Fudan UniversityShanghai 200083China Department of Infectious Diseases Research Laboratory of Clinical VirologyNational Research Center for Translational MedicineRuijin Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghai 200025China State Key Laboratory of Microbial Metabolism School of Life Sciences and BiotechnologyThe Joint International Research Laboratory of Metabolic and Developmental SciencesShanghai Jiao Tong UniversityShanghai 200240China

With the recent ongoing autumn/winter 2022 COVID-19 wave and the adjustment of public health control measures,there have been widespread SARS-CoV-2 infections in Chinese mainland.Here we have analyzed 369 viral genomes from recently diagnosed COVID-19 patients in Shanghai,identifying a large number of sublineages of the SARS-CoV-2 Omicron family.Phylogenetic analysis,coupled with contact history tracing,revealed simultaneous community transmission of two Omicron sublineages dominating the infections in some areas of China(BA.5.2 mainly in Guangzhou and Shanghai,and BF.7 mainly in Beijing)and two highly infectious sublineages recently imported from abroad(XBB and BQ.1).Publicly available data from August 31 to November 29,2022 indicated an overall severe/critical case rate of 0.035%nationwide,while analysis of 5706 symptomatic patients treated at the Shanghai Public Health Center between September 1 and December 26,2022 showed that 20 cases(0.35%)without comorbidities progressed into severe/critical conditions and 153 cases(2.68%)with COVID-19-exacerbated comorbidities progressed into severe/critical conditions.These observations shall alert healthcare providers to place more resources for the treatment of severe/critical cases.Furthermore,mathematical modeling predicts this autumn/winter wave might pass through major cities in China by the end of the year,whereas some middle and western provinces and rural areas would be hit by the upcoming infection wave in mid-to-late January 2023,and the duration and magnitude of upcoming outbreak could be dramatically enhanced by the extensive travels during the Spring Festival(January 21,2023).Altogether,these preliminary data highlight the needs to allocate resources to early diagnosis and effective treatment of severe cases and the protection of vulnerable population,especially in the rural areas,to ensure the country’s smooth exit from the ongoing pandemic and accelerate socio-economic recovery.

关键词： SARS-CoV-2 COVID-19 Omicron genomic epidemiology

Predictive values of plasma TNFαand IL-8 for intracranial hemorrhage in patients with acute promyelocytic leukemia

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Frontiers of Medicine 2022年第6期16卷 909-918页

作者： Fangyi Dong Li Chen Chaoxian Zhao Xiaoyang Li yun tan Huan Song Wen Jin Hongming Zhu yunxiang Zhang Kai Xue Junmin Li Kankan Wang Shanghai Institute of Hematology State Key Laboratory of Medical GenomicsNational Research Center for Translational Medicine at ShanghaiRuijin Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghai200025China CNRS-LIA Hematology and Cancer Sino-French Research Center for Life Sciences and GenomicsRuijin Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghai200025China

In patients with acute promyelocytic leukemia(APL),intracranial hemorrhage(ICH),if not identified promptly,could be fatal.It is the leading cause of failure of induction and early death.Thus,biomarkers that could promptly predict severe complications are critical.Here,cytokine differences between patients with APL with and without ICH were investigated to develop predictive models for this complication.The initial cytokine profiling using plasma samples from 39 patients and 18 healthy donors found a series of cytokines that were remarkedly different between patients with APL and healthy controls.The APL patients were subsequently divided into high and low white blood cell count groups.Results showed that tumor necrosis factor a and interleukin 8(IL-8)were vital in distinguishing patients with APL who did or did not develop ICH.In addition,verification in 81 patients with APL demonstrated that the two cytokines were positively correlated with the cumulative incidence of ICH.Finally,in-vitro and in-vivo experimental evidence were provided to show that IL-8 influenced the migration of APL-derived NB4 cells and impaired the blood-brain barrier in PML/RARαpositive blast-transplanted FVB/NJ mice.These assessments may facilitate the early warning of ICH and reduce future mortality levels in APL.

关键词： acute promyelocytic leukemia intracranial hemorrhage cytokines biomarker

Prediction of treatment response to antipsychotic drugs for precision medicine approach to schizophrenia:randomized trials and multiomics analysis

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Military Medical Research 2024年第1期11卷 19-33页

作者： Liang-Kun Guo Yi Su Yu-Ya-Nan Zhang Hao Yu Zhe Lu Wen-Qiang Li Yong-Feng Yang Xiao Xiao Hao Yan Tian-Lan Lu Jun Li yun-Dan Liao Zhe-Wei Kang Li-Fang Wang Yue Li Ming Li Bing Liu Hai-Liang Huang Lu-Xian Lv Yin Yao yun-Long tan Gerome Breen Ian Everall Hong-Xing Wang Zhuo Huang Dai Zhang Wei-Hua Yue Institute of Mental Health Peking University Sixth HospitalBeijing 100191China National Clinical Research Center for Mental Disorders Peking University Sixth HospitalBeijing 100191China NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder(2018RU006) Chinese Academy of Medical SciencesBeijing 100191China Peking University Huilongguan Clinical Medical School Beijing Huilongguan HospitalBeijing 100096China Department of Psychiatry Jining Medical UniversityJining 272067ShandongChina Henan Key Lab of Biological Psychiatry the Second Affiliated Hospital of Xinxiang Medical UniversityXinxiang 435001HenanChina Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and yunnan Province Kunming Institute of ZoologyChinese Academy of SciencesKunming 650223China Institute of Psychiatry Psychology and NeuroscienceKing’s College LondonLondon WC2R 2LSUK State Key Laboratory of Cognitive Neuroscience and Learning Beijing Normal UniversityBeijing 100875China Analytic and Translational Genetics Unit Massachusetts General HospitalBostonMA 02114USA Stanley Center for Psychiatric Research the Broad Institute of MIT and HarvardCambridgeMA 02141USA Department of Medicine Harvard Medical SchoolBostonMA 02115USA Department of Biostatistics and Computational Biology School of Life SciencesFudan UniversityShanghai 200438China Department of Neurology Xuanwu HospitalCapital Medical UniversityBeijing 100053China State Key Laboratory of Natural and Biomimetic Drugs Key Laboratory for Neuroscience for Ministry of EducationSchool of Pharmaceutical SciencesPeking University Health Science CenterBeijing 100191China PKU-IDG/McGovern Institute for Brain Research Peking UniversityBeijing 100871China Chinese Institute for Brain Research Beijing 102206China

Background:Choosing the appropriate antipsychotic drug(APD)treatment for patients with schizophrenia(SCZ)can be challenging,as the treatment response to APD is highly variable and difficult to predict due to the lack of effective biomarkers.Previous studies have indicated the association between treatment response and genetic and epigenetic factors,but no effective biomarkers have been identified.Hence,further research is imperative to enhance precision medicine in SCZ treatment.Methods:Participants with SCZ were recruited from two randomized trials.The discovery cohort was recruited from the CAPOC trial(n=2307)involved 6 weeks of treatment and equally randomized the participants to the Olanzapine,Risperidone,Quetiapine,Aripiprazole,Ziprasidone,and Haloperidol/Perphenazine(subsequently equally assigned to one or the other)groups.The external validation cohort was recruited from the CAPEC trial(n=1379),which involved 8 weeks of treatment and equally randomized the participants to the Olanzapine,Risperidone,and Aripiprazole groups.Additionally,healthy controls(n=275)from the local community were utilized as a genetic/epigenetic reference.The genetic and epigenetic(DNA methylation)risks of SCZ were assessed using the polygenic risk score(PRS)and polymethylation score,respectively.The study also examined the genetic-epigenetic interactions with treatment response through differential methylation analysis,methylation quantitative trait loci,colocalization,and promoteranchored chromatin interaction.Machine learning was used to develop a prediction model for treatment response,which was evaluated for accuracy and clinical benefit using the area under curve(AUC)for classification,R^(2) for regression,and decision curve analysis.Results:Six risk genes for SCZ(LINC01795,DDHD2,SBNO1,KCNG2,SEMA7A,and RUFY1)involved in cortical morphology were identified as having a genetic-epigenetic interaction associated with treatment response.The developed and externally validated prediction model,which incorporated clinical information,

关键词： Schizophrenia Antipsychotic drug Treatment response Prediction model Genetics Epigenetics