Innate responses following infection with enteric microbes

肠道微生物感染后的先天反应

基本信息

批准号：
10177672
负责人：
Soumita Das
金额：
$ 35.45万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN DIEGO
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-09-01 至 2023-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10177672
关键词：
2019-nCoV Abdominal Pain Address Affect Aftercare Anatomy Animals Artificial Intelligence Autopsy Biological Assay COVID-19 COVID-19 pandemic Cell model Cells China Chronic Disease Collaborations Colon Communities Consumption Cytokine Gene DNA Damage Data Data Set Diabetes Mellitus Diarrhea Disease Drug Screening Drug usage Duodenum Emergency Situation Enteral Enzyme-Linked Immunosorbent Assay Esophagus Feces Formalin Functional disorder Gastrointestinal tract structure Gene Expression Profile Genes Goals Healthcare Systems Human IL8 gene Immune response Immunohistochemistry Infection Inflammatory Inflammatory Bowel Diseases Interleukin-15 Interleukin-6 Intestines Knowledge Literature Lower Gastrointestinal Tract Lung Machine Learning Microbe Modeling Morbidity - disease rate Natural Immunity Nature Nausea Neutral Amino Acid Transport Systems Nomenclature Nutrient Nutritional Oral Organ Organoids Pathogenicity Pathology Pathway interactions Patients Pattern Pharmaceutical Preparations Pneumonia Probiotics Process Prodrugs Publishing Quantitative Reverse Transcriptase PCR RNA Rectum Reporting Research Route Sampling Severe Acute Respiratory Syndrome Severities Severity of illness Signal Transduction Small Intestines Specimen Stomach Supportive care Symptoms Testing Therapeutic Therapeutic Effect Time VIP gene Viral Virus Diseases Work base biobank biosafety level 3 facility cohort combat complex data coronavirus disease cytokine cytokine release syndrome dietary supplements drug candidate drug discovery gastrointestinal gastrointestinal infection gastrointestinal symptom genetic signature gut microbiota ileum intestinal epithelium microbial monolayer mortality pandemic disease prebiotics predictive modeling response therapeutic target tool transcriptome sequencing transcriptomics translational impact transmission process viral RNA virtual

项目摘要

ABSTRACT As the rapidly unfolding COVID-19 pandemic claims its victims around the world, it has also inspired the scientific community to come up with solutions to meet an urgent and unmet need —i.e., ameliorate the severity of Covid- 19 and reduce mortality. Two obstacles make that task difficult—First, the pathophysiology of Covid-19 remains a mystery; the emerging reports generally agree that the disease has a very slow onset and that those who succumb typically mount a ‘cytokine storm’, i.e., an overzealous immune response. However, despite being implicated as a culprit behind the observed mortality and morbidity in COVID-19, we know virtually nothing about what constitutes (nature, extent) or contributes to (cell or origin) such an overzealous response. A significant number of patients have GI symptoms. The treatment goals in COVID-19 have been formulated largely as a ‘trial and error’-approach; this is reflected in the mixed results of the trials that have concluded. Second, the process of drug discovery is comprised of time-consuming steps; to avoid delays, we need to define the nature of the fatal cellular response before deciding how to model it in animals or matching therapeutics to curb it. Our preliminary work has helped us define the aberrant host cellular response in COVID-19. We used machine learning tools that can look beyond interindividual variability to extract underlying gene expression patterns within complex data across multiple cohorts of viral pandemics, including COVID-19. The resultant pattern, i.e., signature, was subsequently exploited as a predictive model to navigate COVID-19 for GI symptoms. Surprisingly, the 166-gene signature was conserved in all viral pandemics, including COVID-19, inspiring the nomenclature-- (ViP)-signature. The ViP signature identified and predicted the disease severity of SARS-CoV2-infected patients. We hypothesized that the ViP signature provides a quantitative and qualitative framework for titrating the cellular response in viral pandemics and could serve as a powerful unbiased tool in our armamentarium to vet candidate drugs rapidly. In this proposal, our predicted model, experimental datasets and the information from published literature will be used to screen drugs/nutritional components/probiotics in the GI organoid derived monolayers in a semi-HTP format. We will experimentally validate the effect of the therapeutics predicted in ViP gene signature of the host. The following two aims will provide a translational impact on the COVID-19 emergency. Aim 1: Identify the gastro-intestinal pathogenic pathways during COVID-19. Aim 2: Determine the impact of drugs, nutrients and supplements in gut-in-a-dish model of COVID-19. Impact: This proposal will identify the gastro-intestinal pathways (in healthy and patients with chronic diseases) involved in the GI symptoms of COVID 19 and provide new treatment options in COVID-19.

抽象的随着迅速发展的Covid-19大流行声称其在世界范围内违反了它的侵犯，它也启发了科学社区提出解决方案以满足紧急和未满足的需求 - 即改善COVID的严重性 19并降低死亡率。两个障碍使这项任务变得困难 - 首先，Covid-19的病理生理学仍然存在一个神秘的新兴报告通常同意，这种疾病的发病很慢，那些疾病的人屈服通常会施加“细胞因子风暴”，即过度狂热的免疫响应。但是，多皮是我们几乎一无所知。构成（自然，范围）或有助于（细胞或起源）如此狂热的反应的原因。重要的患者人数有胃肠道症状。 COVID-19的治疗目标已被制定为“试验” 和错误的诉讼；这反映在已经得出的试验的混合结果中。其次，过程药物发现的含量包括耗时的步骤；为避免延误，我们需要定义在决定如何在动物中建模或匹配治疗以遏制它之前，致命的细胞反应。我们的初步工作帮助我们定义了Covid-19中异常的宿主细胞反应。我们使用了可以超越个体可变性以提取基础基因表达的机器学习工具包括COVID-19的多个病毒大流行同类群体中复杂数据中的模式。结果随后将模式（即签名）作为预测模型进行了探索症状。令人惊讶的是，166个基因的签名在所有病毒大流行中都保存了，包括COVID-19，启发命名法 - （VIP） - 签名。 VIP签名确定并预测了 SARS-COV2感染的患者。我们假设VIP签名提供了定量和定性的滴定病毒大流行中细胞反应的框架，可以用作强大的无偏见工具我们对审查候选药物的武术迅速。在此提案中，我们预测的模型，实验数据集并且已发表文献的信息将用于筛查药物/营养成分/益生菌 GI类器官以半HTP格式衍生的单层。我们将通过实验验证宿主的VIP基因特征预测的治疗。以下两个目标将提供翻译的影响在COVID-19紧急情况下。 AIM 1：确定Covid-19期间的胃肠道致病途径。 AIM 2：确定药物，养分和补充剂的影响，在肠道模型中，19009。影响：该提案将确定胃肠道途径（在健康和慢性疾病患者中）参与Covid 19的GI症状，并在Covid-19中提供新的治疗选择。

项目成果

期刊论文数量（34）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Boolean implication analysis unveils candidate universal relationships in microbiome data.

DOI：
10.1186/s12859-020-03941-4
发表时间：
2021-02-05
期刊：
BMC bioinformatics
影响因子：
3
作者：
Vo D;Singh SC;Safa S;Sahoo D
通讯作者：
Sahoo D

Inflammatory phenotype modulation in the respiratory tract and systemic circulation of e-cigarette users: a pilot study.

电子烟使用者呼吸道和体循环的炎症表型调节：一项试点研究。

DOI：
10.1152/ajplung.00363.2021
发表时间：
2021
期刊：
American journal of physiology. Lung cellular and molecular physiology
影响因子：
0
作者：
Sayed,IbrahimM;Masso-Silva,JorgeA;Mittal,Ankita;Patel,Arjun;Lin,Erica;Moshensky,Alex;Shin,John;Bojanowski,ChristineM;Das,Soumita;Akuthota,Praveen;CrottyAlexander,LauraE
通讯作者：
CrottyAlexander,LauraE

Regulation of Rac1 and Reactive Oxygen Species Production in Response to Infection of Gastrointestinal Epithelia.

DOI：
10.1371/journal.ppat.1005382
发表时间：
2016-01
期刊：
PLoS pathogens
影响因子：
6.7
作者：
den Hartog G;Chattopadhyay R;Ablack A;Hall EH;Butcher LD;Bhattacharyya A;Eckmann L;Harris PR;Das S;Ernst PB;Crowe SE
通讯作者：
Crowe SE

Isolation of RNA from the Murine Colonic Tissue and qRT-PCR for Inflammatory Cytokines.