目的 探究16S rDNA不同区间对药品生产环境常见细菌的种水平鉴定能力。方法 计算德国细菌古菌分类学数据库(List of Prokaryotic names with Standing in Nomenclature,LPSN)收录的所有模式菌株序列以及洁净室中常见分离细菌对应的模式...目的 探究16S rDNA不同区间对药品生产环境常见细菌的种水平鉴定能力。方法 计算德国细菌古菌分类学数据库(List of Prokaryotic names with Standing in Nomenclature,LPSN)收录的所有模式菌株序列以及洁净室中常见分离细菌对应的模式菌株在16S rDNA不同区间香农熵,分析16S rDNA不同区间的物种水平鉴定能力;对所有LPSN收录的模式菌株进行相似度差值的比较,同时收集403个具有代表性的药品生产环境分离菌株样品,进行16S rDNA测序后完成相似度差值的比较,基于相似度差值探究16S rDNA不同区间的鉴定结果区分度;考虑到不同区间对不同种属可能存在区分能力的差异,对各区间测序区分度不显著的物种进行了相关性分析。结果 16S rDNA的27F~533R区间相比其他区间(533F~1100R区间、1100F~1492R区间)具有最高的种间分辨率,同时该区间的鉴定结果中,第一顺位与第二顺位的序列相似度差值最大,扩展比对区间对提升物种间的区分度没有显著效果。结论 优先应用16S rDNA的27F~533R区间开展细菌的种水平鉴定是高效、可靠的做法。展开更多
Objectives:Pancreatic cancer(PC)is characterized by poor prognosis due to its limited treatment choices and delayed detection.S100A14 has been implicated in tumor progression,yet its regulatory hierarchy and functiona...Objectives:Pancreatic cancer(PC)is characterized by poor prognosis due to its limited treatment choices and delayed detection.S100A14 has been implicated in tumor progression,yet its regulatory hierarchy and functional interplay in PC remain unclear.This study aimed to define the role of S100A14 in PC progression.Methods:Integrated bioinformatic analyses of TCGA-PAAD and GSE22780 datasets identified candidate hub genes.Prognostic relevance was assessed via Kaplan-Meier and ROC analyses.Functional experiments were performed in PANC-1 and BxPC-3 cells,including qRT-PCR,CCK-8 assay,Western blotting,Transwell assay,and apoptosis assay.Co-immunoprecipitation(Co-IP)was used to verify S100A14-S100A16 interaction.CHX chase and dual-luciferase assays were employed to assess protein stability and transcriptional activity.Results:S100A14 was markedly upregulated in PC tissues and cell lines and identified as a key prognostic gene.Silencing S100A14 suppressed EMT,proliferation,invasion,and migration,while reversing S100A16-mediated p53 inhibition and enhancing apoptosis.Mechanistically,Co-IP assay confirmed the protein interaction between S100A14 and S100A16;S100A14 stabilized S100A16 protein through post-translational modification without transcriptional regulation;the S100A14/S100A16 axis reduced p53 protein stability and inhibited its transcriptional activity as well as the downstream p21 expression.Critically,knockdown of S100A14 abrogated the pro-metastatic phenotype of cancer cells.Conclusion:This study identifies S100A14 promotes PC progression by stabilizing S100A16 and suppressing the tumor-suppressive p53/p21 pathway;knockdown of S100A14 can reverse the above effects,restore p53 function,and enhance cancer cell apoptosis.Targeting the S100A14/S100A16/p53 regulatory axis could represent a promising therapeutic approach for PC.展开更多
Wu et al recently applied multi-region 16S rRNA sequencing to characterize the gastric cancer microbiome,demonstrating improved taxonomic resolution and detection sensitivity over conventional single-region approaches...Wu et al recently applied multi-region 16S rRNA sequencing to characterize the gastric cancer microbiome,demonstrating improved taxonomic resolution and detection sensitivity over conventional single-region approaches.While the study represents a valuable methodological step forward,it remains limited by singlecenter design,lack of quantitative calibration,and insufficient control for contamination and inter-laboratory variability.This editorial critically appraises these methodological gaps and emphasizes that future efforts must focus on harmonized,consensus-driven workflows to ensure reproducibility and clinical reliability.The translational potential of multi-region 16S lies in moving from descriptive microbial profiling to actionable clinical integration,particularly for recurrence prediction,treatment-response monitoring,and perioperative complication risk assessment.By addressing these methodological,economic,and ethical challenges,the field can advance toward evidence-based and clinically deployable microbiome-guided precision oncology.展开更多
文摘目的研究芎麻汤有效成分对偏头痛大鼠肠道微生物的影响。方法120只大鼠进行硬脑膜置管手术后,观察大鼠宏观体征,选取生活状态较好的90只大鼠于12 d内6次注射炎症汤刺激硬脑膜建立偏头痛模型,随机设置为9组,每组10只:模型组、降钙素基因相关肽(CGRP)抑制剂组、氟桂利嗪阳性组、芎麻汤有效成分组(芎麻汤正丁醇提取物低、高剂量组、芎麻汤乙酸乙酯提取物低、高剂量组、芎麻汤正丁醇+乙酸乙酯提取物低、高剂量组);另设置空白组10只,以上述相同建模方法注射0.9%氯化钠溶液。模型建立后,空白组与模型组灌胃纯水,CGRP抑制剂组大鼠经尾静脉给药,每周1次,共5次;余组灌胃相应药物,每天1次,共4周(28 d)。给药末期,通过大鼠糖水偏爱度检测、悬尾测试、新物体识别测试、水迷宫测试进行行为学评估;腹主动脉采血、ELISA法检测大鼠外周血CGRP、NO含量;取肠道内容物,16S r DNA高通量测序技术分析大鼠肠道微生物变化。结果与空白组相比,模型组大鼠表现出显著的抑郁样行为改变及认知障碍,同时血清中CGRP、NO含量明显升高(P<0.05)。肠道菌群分析显示菌群结构发生明显变化,在门水平,厚壁菌门(Firmicutes)、放线菌门(Actinobacteriota)、Unclassified和弯曲杆菌门(Campylobacterota)群落丰度明显降低(P<0.01,P<0.05),拟杆菌门(Bacteroidota)、疣微菌门(Verrucomicrobiota)、髌骨细菌门(Patescibacteria)和蓝藻细菌门(Cyanobacteria)群落丰度明显升高(P<0.01,P<0.05);在属水平,Muribaculaceae_unclassified、乳酸杆菌(Lactobacillus)群落丰度明显降低(P<0.05),瘤胃球菌(Ruminococcus)、Clostridia_UCG-014_unclassified、阿克曼菌(Akkermansia)、Firmicutes_unclassified和Monoglobus群落丰度明显升高(P<0.01,P<0.05)。与模型组相比,氟桂利嗪阳性组、CGRP抑制剂组、芎麻汤有效成分组均不同程度地明显改善偏头痛大鼠出现的抑郁样行为改变及认知障碍;均明显降低血清中CGRP、NO含量。芎麻汤有效成分组能够不同程度调节大鼠肠道微生物的多样性,α多样性分析提示其能提高大鼠肠道菌群多样性和丰富度(P<0.01,P<0.05),β多样性分析提示芎麻汤有效成分组大鼠的肠道微生物群落结构与空白组接近,且其肠道菌群结构在门、属水平上均观察到了与模型组相反的趋势。结论芎麻汤有效成分可能通过调节偏头痛大鼠肠道微生物防治偏头痛。
基金supported by the Yunnan Province Liu Liang Expert Workstation(No.202305AF150148)Famous Doctor Projects of Yunnan Province(No.XDYC-MY-2022-0032)+1 种基金Yunnan Health Training Project of High Level Talents(No.L-2024029)Innovation Team Special Program of Yunnan(No.202505AS350004).
文摘Objectives:Pancreatic cancer(PC)is characterized by poor prognosis due to its limited treatment choices and delayed detection.S100A14 has been implicated in tumor progression,yet its regulatory hierarchy and functional interplay in PC remain unclear.This study aimed to define the role of S100A14 in PC progression.Methods:Integrated bioinformatic analyses of TCGA-PAAD and GSE22780 datasets identified candidate hub genes.Prognostic relevance was assessed via Kaplan-Meier and ROC analyses.Functional experiments were performed in PANC-1 and BxPC-3 cells,including qRT-PCR,CCK-8 assay,Western blotting,Transwell assay,and apoptosis assay.Co-immunoprecipitation(Co-IP)was used to verify S100A14-S100A16 interaction.CHX chase and dual-luciferase assays were employed to assess protein stability and transcriptional activity.Results:S100A14 was markedly upregulated in PC tissues and cell lines and identified as a key prognostic gene.Silencing S100A14 suppressed EMT,proliferation,invasion,and migration,while reversing S100A16-mediated p53 inhibition and enhancing apoptosis.Mechanistically,Co-IP assay confirmed the protein interaction between S100A14 and S100A16;S100A14 stabilized S100A16 protein through post-translational modification without transcriptional regulation;the S100A14/S100A16 axis reduced p53 protein stability and inhibited its transcriptional activity as well as the downstream p21 expression.Critically,knockdown of S100A14 abrogated the pro-metastatic phenotype of cancer cells.Conclusion:This study identifies S100A14 promotes PC progression by stabilizing S100A16 and suppressing the tumor-suppressive p53/p21 pathway;knockdown of S100A14 can reverse the above effects,restore p53 function,and enhance cancer cell apoptosis.Targeting the S100A14/S100A16/p53 regulatory axis could represent a promising therapeutic approach for PC.
文摘Wu et al recently applied multi-region 16S rRNA sequencing to characterize the gastric cancer microbiome,demonstrating improved taxonomic resolution and detection sensitivity over conventional single-region approaches.While the study represents a valuable methodological step forward,it remains limited by singlecenter design,lack of quantitative calibration,and insufficient control for contamination and inter-laboratory variability.This editorial critically appraises these methodological gaps and emphasizes that future efforts must focus on harmonized,consensus-driven workflows to ensure reproducibility and clinical reliability.The translational potential of multi-region 16S lies in moving from descriptive microbial profiling to actionable clinical integration,particularly for recurrence prediction,treatment-response monitoring,and perioperative complication risk assessment.By addressing these methodological,economic,and ethical challenges,the field can advance toward evidence-based and clinically deployable microbiome-guided precision oncology.
