基于全基因组测序的耐碳青霉烯类抗生素鲍曼不动杆菌耐药基因、毒力因子及同源性分析

摘要：目的 通过应用全基因组测序(whole genome sequencing, WGS)技术分析某三级医疗机构耐碳青霉烯类抗生素鲍曼不 动杆菌(carbapenem-resistant Acinetobacter baumannii, CRAB)的耐药基因、毒力因子及同源性。方法 收集该院2020年1月至3月 重症监护病房(Intensive care unit, ICU)、神经外科分离的11株医院感染CRAB菌株，通过二代测序平台进行全基因组测序, 应用 基因组流行病学中心(Center for genomic epidemiology, CGE)ResFinder 4. 0软件分析其耐药基因型，并应用MORPHEUS在线制作 热图，应用毒力因子数据库(virulence factors of pathogenic bacteria, VFDB)VFanalyzer软件筛选毒力因子，应用MLST软件检测菌 株的ST型，应用Kaptive软件检测荚膜型，应用CSI Phylogeny 1. 4软件及FigTree v1. 4. 4软件构建最大似然树(maximum likelihood tree, MLT)以分析其同源性。结果 11株CRAB对亚胺培南、美罗培南、头孢菌素、环丙沙星均呈现耐药，而对阿米卡星、左氧 氟沙星耐药的菌株株数较少。11株CRAB共检测出18种耐药基因，11株同时携带碳青霉烯酶耐药基因blaOXA-23和blaOXA-66，β-内酰 胺酶耐药基因以blaTEM-1D和blaADC-25为主，大部分菌株携带多种外排泵相关耐药基因及抗菌药物修饰酶耐药基因。11株CRAB均携 带多种毒力因子，包括外膜孔蛋白、脂多糖、生物膜、外排泵、磷脂酶和效应蛋白等，如OmpA、Lps、Csu、Pga、Ade、Plc、 Bas、Bau、Ent、Hem、Aba、Bfm、Pbp和Kat等。11株CRAB均为ST2-K22型，同源性分析结果显示C组内同源性关系相近，存 在院内传播的可能。结论 该院CRAB的耐药性、毒力特征复杂多样，同源性分析显示该院存在1种优势克隆株，该克隆株有医 院内传播的风险。     

凉血通瘀方干预高血压大鼠急性脑出血模型对脑组织中差异miRNA表达的影响＊

目的 研究凉血通瘀方对高血压大鼠急性脑出血模型脑组织miRNA表达的影响，对差异表达的miRNA靶基因进行分析，探索凉血通瘀方可能的药效机制。方法 将自发性高血压大鼠随机分成对照组（B）和实验组（C）。适应性饲养一周后，C组灌胃凉血通瘀方，B组灌胃等体积生理盐水，连续5天，每天1次。构建脑出血模型后收集脑组织，借助全转录组测序技术获得miRNA表达量，与miRBase数据库比对获取已知miRNA，使用miRDeep2预测新miRNA。差异分析软件为DESeq2，筛选阈值为|log₂FC| ≥1 并且P <0.05。对显著差异表达的miRNA进行靶基因预测，对靶基因进行GO功能、KEGG通路富集和PPI网络分析。结果 实验组和对照组对比，共发现21个显著差异表达的miRNA，上调有9个，下调有12个，共预测得到1243个有统计学意义的靶基因。GO富集分析发现，生物过程中突触囊泡分泌的调节、神经递质分泌的调节和神经递质运输的调节占前三位，神经元投射终点、全膜、质膜区域和细胞投射则是主要的细胞成分。分子功能分别为小GTPase绑定、底物特异性跨膜转运蛋白活性和离子跨膜转运体活性。通路分析结果显示，靶基因在癌证通路、pI3K-Akt信号通路、人类乳头瘤病毒感染、神经活性配体-受体相互作用和MAPK通路等分布广泛。采用STRING网站和Cytoscape软件，根据MCC算法筛选出ADRA2C、CASR、CCL28、CCR1、DRD2、GNAT3、GRM2、DYNC1LI1、GABBR1、GNAI1等核心靶基因。结论 凉血通瘀方对脑出血急性期鼠脑组织内miRNA的表达有重要影响；显著差异表达miRNAs可能通过靶向核心基因调控凉血通瘀方干预急性脑出血的病理过程及预后。     

Communicating regulatory high-throughput sequencing data using BioCompute Objects

This project demonstrates the use of the IEEE 2791–2020 Standard (BioCompute Objects [BCO]) to enable the complete and concise communication of results from next generation sequencing (NGS) analysis. One arm of a clinical trial was replicated using synthetically generated data made to resemble real biological data and then two independent analyses were performed. The first simulated a pharmaceutical regulatory submission to the US Food and Drug Administration (FDA) including analysis of results and a BCO. The second simulated an FDA review that included an independent analysis of the submitted data. Of the 118 simulated patient samples generated, 117 (99.15%) were in agreement in the two analyses. This process exemplifies how a template BCO (tBCO), including a verification kit, facilitates transparency and reproducibility, thereby reinforcing confidence in the regulatory submission process.     

Differences in Evidentiary Requirements Between European Medicines Agency and European Health Technology Assessment of Oncology Drugs—Can Alignment Be Enhanced?

ObjectivesNational health technology assessments (HTAs) across Europe show differences in evidentiary requirements from assessments by the European Medicines Agency (EMA), affecting time to patient access for drugs after marketing authorization. This article analyzes the differences between EMA and HTA bodies’ evidentiary requirements for oncology drugs and provides recommendations on potential further alignment to minimize and optimally manage the remaining differences.MethodsInterviews were performed with representatives and drug assessment experts from EMA and HTA bodies to identify evidentiary requirements for several subdomains and collect recommendations for potentially more efficiently addressing differences. A comparative analysis of acceptability of the evidence by EMA and the HTA bodies and for potential further alignment between both authorities was conducted.ResultsAcceptability of available evidence was higher for EMA than HTA bodies. HTA bodies and EMA were aligned on evidentiary requirements in most cases. The subdomains showing notable differences concerned the acceptance of limitation of the target population and extrapolation of target populations, progression-free survival and (other) surrogate endpoints as outcomes, cross-over designs, short trial duration, and clinical relevance of the effect size. Recommendations for reducing or optimally managing differences included joint early dialogues, joint relative effectiveness assessments, and the use of managed entry agreements.ConclusionsDifferences between assessments of EMA and HTA bodies were identified in important areas of evidentiary requirements. Increased alignment between EMA and HTA bodies is suggested and recommendations for realization are discussed.     

RNA sequencing steps toward the first line

• DNA is the sequence that codes for proteins.
• Messenger RNA is transcribed from the DNA sequence of genes and translated into protein.
• It can be difficult to predict how a change in the DNA sequence will affect messenger RNA and protein quantity and quality.
• DNA translocation changes can cause the joining of sequences from two different genes or different parts of the same gene.
• DNA sequencing is often used clinically to predict how DNA changes might affect proteins.
• Alternatively, RNA sequencing can be used as a more direct measure of the effect of DNA changes on the protein products.
• This sequencing is important for identifying changes in cancer that may indicate response to targeted therapy, prognosis, or diagnosis.