Name: characterization and functional prediction of bacteria in ovarian tissues
Uploaded: 2021-10-23T13:00:00
Description: Watch this Scientific Journal Video about Characterization and Functional Prediction of Bacteria in Ovarian Tissues at JoVE.com

本课题由中国西安交通大学第一附属医院临床研究奖（XJTU1AF-2018-017，XJTU1AF-CRF-2019-002），陕西省科技厅自然科学重大基础研究项目（2018JM7073， 2017ZDJC-11），陕西省科技厅重点研发项目（2017ZDXM-SF-068，2019QYPY-138），陕西省合作技术创新项目（2）017XT-026，2018XT-002），西安社会发展指导计划医学研究项目（2017117SF/YX011-3）。资助者在研究设计、数据收集和分析、决定出版或准备手稿方面没有作用。
我们感谢西安交通大学第一附属医院妇科的同事们为采集样本所做的贡献。

本研究获西安交通大学第一附属医院医疗机构伦理委员会批准（第1号）XJTUIAF2018LSK-139）。所有登记的患者都获得了知情同意。
1. 进入癌症组和对照组的标准
<ol><li>对于癌症组，登记主要被诊断为卵巢癌的患者，腹腔切除术后，通过病理学发现，他们证明患有血清卵巢癌。</li>
	<li>对于对照组，登记主要被诊断为子宫肌瘤或子宫腺造血的患者，而不出现任何卵巢?...

<ol>
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卵巢癌对女性生育能力有显著影响。大多数卵巢癌患者在晚期被诊断出来，5年生存率低于30%18。腹部固体内脏（包括肝脏、胰腺和脾脏）中的细菌确认已经发表。上部女性生殖道中细菌的存在是因为子宫颈没有封闭2，3，4，5。然而，卵巢，这是腹部固体内脏，是否...

最近，越来越多的文章发表，证明细菌在腹部固体内脏的存在，如肾脏，脾脏，肝脏和卵巢1，2。盖勒等人在胰腺肿瘤中发现了细菌，这些细菌对化疗药物2的宝石素具有抗药性。曼弗雷多·维埃拉等人的结论是，肠球菌胆汁可移植到淋巴结、肝脏和脾脏，可以驱动自身免疫3。
由于子宫颈起到防御作用，对含有子宫、输卵管和卵巢的女性上部生殖道中的细菌的研究很少。然而，近年来已经建立了一些新的理论。由于粘液4，5的变化，细菌在月经周期内可能进入子宫腔。此外，泽沃马诺拉基斯等人证实，子宫与输卵管一起，是由卵巢内分泌系统控制的内分泌泵，这种排列使细菌能够进入子宫内膜、输卵管和卵巢6。
由于细菌检测方法的发展，上生殖道不再是一个谜了。Verstraelen等人使用条形码配对端测序方法，通过瞄准16SRNA基因7的V1-2超变区域来发现子宫细菌。方等人对子宫内息肉患者采用条形码测序，揭示了宫内细菌的多样性。此外，通过使用16SRNA基因，迈尔斯等人和陈等人分别在接受过萨平果卵巢切除术和子宫切除术的妇女的生殖器系统中发现了细菌。
近年来，肿瘤组织中的细菌越来越受到重视。班纳吉等人发现，卵巢癌患者之间的微生物群特征不同，对照10。氧纳龙西比里库姆与肿瘤阶段有关，甲基苯丙胺血管瘤可用于诊断卵巢癌11。除卵巢癌外，胃、肺、前列腺、乳腺癌、子宫颈癌和子宫内膜癌等其他癌症也与12、13、14、15、16、17、18等细菌有关。Poore等人提出了一种新的基于微生物的肿瘤诊断，预见到早期癌症筛查19。在这个协议中，我们通过比较这两种组织中细菌的组成和功能，调查了癌性卵巢组织和正常卵巢组织之间的差异。
进行了免疫造血染色和16S rRNA基因测序，以确认卵巢中是否存在细菌。研究了卵巢细菌在癌性和非癌性卵巢组织中的差异和预测功能。结果表明卵巢组织中存在细菌。 氧纳龙西比里库姆 和 梅萨诺萨尔西纳真空素 分别与卵巢癌的阶段和诊断有关。比较了两组存在46种明显不同的KEGG通路。

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>2200 TapeStation Software</td>
			<td>Agilgent 
			United States</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>AmpliSeq for Illumina Library Prep, Indexes, and Accessories</td>
			<td>Illumina</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Image-pro plus 7</td>
			<td>Media Cybernetics</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Leica ASP 300S</td>
			<td>Leica Biosystems Division of Leica Microsystems</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Leica EG 1150</td>
			<td>Leica Biosystems Division of Leica Microsystems</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Leica RM2235</td>
			<td>Leica Biosystems Division of Leica Microsystems</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>LPS Core monoclonal antibody, clone WN1 222-5</td>
			<td>Hycult Biotech</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Mag-Bind RxnPure Plus magnetic beads</td>
			<td>Omega Biotek</td>
			<td>M1386-00</td>
			<td></td>
		</tr>
		<tr>
			<td>Mag-Bind Universal Pathogen 96 Kit</td>
			<td>Omega Biotek</td>
			<td>M4029-01</td>
			<td></td>
		</tr>
		<tr>
			<td>MiSeq</td>
			<td>Illumina</td>
			<td>SY-410-1003</td>
			<td></td>
		</tr>
		<tr>
			<td>Silva database</td>
			<td>Max Planck Institute for Marine Microbiology and Jacobs University</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>the QuantiFluor dsDNA System</td>
			<td>Promega</td>
			<td>E2670</td>
			<td></td>
		</tr>
		<tr>
			<td>Trimmomatic</td>
			<td>Bj&#246;rn Usadel</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>ZytoChem Plus (HRP) Anti-Rabbit (DAB) Kit</td>
			<td>Zytomed Systems</td>
			<td>HRP008DAB-RB</td>
			<td></td>
		</tr>
	</tbody>
</table>

characterization and functional prediction of bacteria in ovarian tissues

由于细菌检测的进步，"无菌"女性上生殖道理论一直遭到越来越多的反对。然而，卵巢是否含有细菌尚未得到证实。在此，引入了检测卵巢组织细菌的实验。我们选择了癌症组的卵巢癌患者和对照组的非癌患者。16S rRNA基因测序用于区分卵巢组织中的细菌与癌症和对照组。此外，我们使用虫基和PICRUSt预测了所识别细菌的功能组成。这种方法也可以用于其他内脏和组织，因为许多器官已被证明含有细菌近年来。内脏和组织中细菌的存在可能有助于科学家评估癌变和正常组织，并可能有助于癌症的治疗。

病人 共有16名合格的患者参与了这项研究。对照组包括10名诊断为良性子宫肿瘤的妇女（其中3名患者被诊断为子宫肌瘤，7名患者被诊断为子宫腺瘤）。同时，癌症组包括6名诊断为血清卵巢癌的妇女（其中2名患者被诊断为II期，2名被诊断为III期）。以下特征表明对照组和癌症组的患者之间没有差异：年龄、更年期状况、均等、高血压史和糖尿病史（表1）。
<p class="jo...

Watch this Scientific Journal Video about Characterization and Functional Prediction of Bacteria in Ovarian Tissues at JoVE.com

Characterization and Functional Prediction of Bacteria in Ovarian Tissues

为了发现和区分原位癌和非癌卵巢组织的细菌，进行了免疫造血染色和16S核糖核化核糖核素（16S rRNA基因）测序。通过利用"未观测状态"（PICRUST）重建对社区的虫基和邻苯二甲酸酯遗传学调查来预测细菌的组成和功能差异。

卵巢组织细菌的特征和功能预测

The theory of a "sterile" female upper reproductive tract has been encountering increasing opposition due to advancements in bacterial detection. However, ...

该协议旨在发现卵巢组织中的细菌并预测其功能。免疫造血化学染色和16S rRNA测序，用于发现和区分原位癌和非癌卵巢组织的细菌。通过重建未观察到的日子，通过对社区的BOP和细胞遗传调查来预测细菌的补偿和功能差异。我们的协议旨在从卵巢组织中提取细菌。它也可用于发现任何种类的肿瘤中的细菌。我们协议的主要优点是它简单方便，几乎每个实验室都能实现。获得结果也很快。在协议中的练习中，重要的是排除任何细菌异位肿瘤组织。因此，本协议中的所有程序都需要无菌。在手术过程中，用一对新的无菌钳将卵巢分离成大约一厘米厚的组织样本。在整个过程中避免触摸任何其他内容。分离后，将样品取出到无菌管中，放入液氮中进行传输。将样品保存在零下80摄氏度。用正式组织修复组织，然后用石蜡嵌入组织。此协议可以在此处暂停。组织可以保存在室温下以进行更长的保存。为了进一步操作，将样品切成五微米序列部分。然后，干燥样品。对样品进行脱石蜡和补液。要检索抗原，需要在EDTA缓冲区进行10分钟的微波处理。将样品浸入含有0.3%氢气的PBS中。过氧化20分钟，以阻止内源性过氧化酶活动。在 LPS 核心执行抗体 EMA，浓度为 1 超过 300。并在摄氏四度下维持一晚。为了发现细菌，使用 DAP 基板套件来检测 HRP 的存在。根据制造商的说明，使用 HRP 聚合物、抗兔抗体。使用表浓缩器让抗体完全结合。使用 PBS 消除未组合的抗体。按照制造商的说明进行化学染色，然后将样品冲洗到水下。对样品脱水。通过签名来套取样品。并根据制造商的协议使用成像 Pro Plus 准备库作为示例输入。练习引物模式，该模式由基因特异性序列和 Illumina 适配器悬空核苷酸序列组成。为了放大rRNA基因序列中细菌16sV4区域的出生率，使用放大PCR放大DNA样本输入的模板。使用 Mag-Bind RxNPure 加磁珠从 PCR 产品中去除反应组合。第二次执行指数化 PCR 放大。使用安捷伦 2200 磁带站检查库。使用量子流 dsDNA 系统对库进行量化。v3 标准流细胞具有 600 个周期，可产生大约 100，000 个配对端。2 倍 300 基 3.图书馆是去规范化、集中化和排序的。每个样品的原始速率根据修剪的测序质量进行过滤。应同时删除引物和适配器序列。序列读取与对和质量低于25应缩短。通过软件包 QIIME 分析 16s rRNA。收集序列以形成具有相似性截止值的 OTUs，对于 OTUs，应在每个样本中计算相对丰度。使用 Bayesian 分类器，该分类器在 RDP 培训集中对所有序列进行排序。在给定的 OTU 中，将具有序列主要一致性的分类分配给 OTU。OTUs 基于样本组信息与席尔瓦数据库对齐。执行字母多样性和基于 UniFrac 的主要坐标分析。要预测相关说明细菌的特征，请使用 BugBase。预测 PICRUST 的元基因组的功能组成。使用监控数据和包含参考基因组的数据库，在 STAMP 软件的帮助下分析每个组之间的不同功能。使用一个统计软件来计算结果。统计意义的指示应设定为 p 小于 0.05。通过学生的 t 测试计算混淆因素（包括年龄和均等值）。通过Chi-square测试计算更年期状况、高血压史和糖尿病。通过曼-惠特尼 U 测试计算卵巢细菌分类数。16名患者参加了这项研究。BugBase 用于对预测的元信息进行实践分析。使用抗菌LPS抗体的卵巢的潜在病原体和免疫造血术。这个数字显示了癌症和对照组的细菌丰富性和多样性。通过 16S rRNA 测序显示。这些数字是观察到的物种指数。超1指数、ACE指数、香农指数、均匀指数、辛普森指数。卵巢样本中植物的相对丰度和12种最丰富的细菌物种如图所示。图A、B、C和D表示对照组患者卵巢和卵巢癌组中面板的相对丰度。对照患者卵巢和卵巢癌组12种最丰富的细菌的相对丰度。这是最常见的，使用PCoA和相对丰度的氧纳龙西比里库姆和梅萨诺萨尔西纳真空。图 A 显示了使用 PCOA 聚类的最常见值。PC1 和 PC2 绘制在 x 和 y 轴上。红块等于卵巢癌组的样本。蓝色圆等于对照组中的示例。卵巢癌组的样本可以从对照组的其他样本中分离出来。图 B 显示了使用 PCOA 聚类的最常见。PC1 和 PC2 绘制在 x 和 y 轴上。红色块等于卵巢癌组的样本。蓝色固体圆等于子宫肌瘤患者的样本。蓝色空心圆等于子宫腺瘤患者的样本。图 C 显示了氧纳龙西比里库姆的相对丰度。图 D 是梅萨诺萨尔西娜真空。这个数字是预测的元基因组学的BugBase分析。癌症组卵巢的潜在致病性和氧化抗压表型强于对照组。通过PICRUSt分析，这个数字与癌症和对照组之间的KEGG路径空间有显著差异。当我们得到我们的样品，一对新的无菌钳子是需要的。注意样品的潜在污染。这种细菌的异地肿瘤组织可能会极大地影响解决。首选将控制组设置为每个步骤。为了减少潜在污染的影响。

Research

JoVE Journal

Cancer Research

Enrichment and Characterization of the Tumor Immune and Non-immune Microenvironments in Established Subcutaneous Murine Tumors

肿瘤免疫和非免疫微环境在小鼠皮下肿瘤中的富集与鉴定

The tumor immune microenvironment (TIME) has recently been recognized as a critical mediator of treatment response in solid tumors, especially for ...

科研

癌症研究

Digital Analysis of Immunostaining of ZW10 Interacting Protein in Human Lung Tissues

人肺组织中ZW10相互作用蛋白免疫染色的数字化分析

The purpose of this study is to introduce a methodology of the immunostaining of human lung tissues, followed by whole-slide digital scanning and image ...

Preparation of Mitochondria from Ovarian Cancer Tissues and Control Ovarian Tissues for Quantitative Proteomics Analysis

卵巢癌组织线粒体的制备与控制卵巢组织进行定量蛋白质组学分析

Ovarian cancer is a common gynecologic cancer with high mortality but unclear molecular mechanism. Most ovarian cancers are diagnosed in the advanced ...

Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer

生物信息学方法与实验验证的集成，了解诺奇信号在卵巢癌中的作用

Notch signaling is a highly conserved regulatory pathway involved in many cellular processes. Dysregulation of this signaling pathway often leads to ...

Circulating Tumor Cell Lines: an Innovative Tool for Fundamental and Translational Research

循环肿瘤细胞系：基础和转化研究的创新工具

Metastasis is a leading cause of cancer death. Despite improvements in treatment strategies, metastatic cancer has a poor prognosis. We thus face an ...

Generation and Culturing of High-Grade Serous Ovarian Cancer Patient-Derived Organoids

高级别浆液性卵巢癌患者来源类器官的生成和培养

Organoids are 3D dynamic tumor models that can be grown successfully from patient-derived ovarian tumor tissue, ascites, or pleural fluid and aid in the ...

Quantifying Replication Stress in Ovarian Cancer Cells Using Single-Stranded DNA Immunofluorescence

使用单链DNA免疫荧光量化卵巢癌细胞中的复制应激

Replication stress is a hallmark of several ovarian cancers. Replication stress can emerge from multiple sources, including double-strand breaks, ...

Visualizing DNA Damage Repair Proteins in Patient-Derived Ovarian Cancer Organoids via Immunofluorescence Assays

Visualizing DNA Damage Repair Proteins in Patient-Derived Ovarian Cancer Organoids via Immunofluorescence Assays

通过免疫荧光测定 可视化 患者来源的卵巢癌类器官中的 DNA 损伤修复蛋白

Immunofluorescence is one of the most widely used techniques to visualize target antigens with high sensitivity and specificity, allowing for the accurate ...

Ovarian Cancer Patient-Derived Organoid Models for Pre-Clinical Drug Testing

Ovarian cancer is a fatal gynecologic cancer and the fifth leading cause of cancer death among women in the United States. Developing new drug treatments ...