longitudinal sampling

纵向采样
  • 文章类型: Journal Article
    尽管哮喘患者和健康受试者之间存在不同的鼻咽微生物组(NPM)分布,关于NPM动力学及其与儿童哮喘加重(AE)的关系知之甚少。我们通过在2017年9月至12月的6个时间点(间隔2至4周)纵向收集来自33名学龄期哮喘儿童的135个蜂拥鼻咽拭子(FNPS),调查了NPM变化。根据受试者在随访期间是否经历任何恶化,将受试者分为AE组和稳定哮喘(AS)组。来自9名非哮喘儿童的一次性FNPS作为对照。使用16SrRNA基因测序分析微生物区系谱。所有144个NPM被分为六个微生物组(MPG),每个都以莫拉氏菌为主,棒状杆菌1号,多毛颗粒,葡萄球菌,链球菌,或者厌氧菌.恶化样品中NPM的微生物多样性和组成与基线样品和健康对照样品均不同。通过MPG过渡分析显示,莫拉氏菌和以Dolosigranulum为主的NPM表现出很高的时间稳定性。随着时间的推移,NPM多样性下降,而微生物组成保持相似。莫拉氏菌的相对丰度增加,而棒状杆菌1,厌氧菌,假单胞菌纵向减少。然而,这些时间模式在AE组和AS组之间没有差异,表明短期动态模式不足以预测AE的发生。哮喘NPM在AE期间经历了莫拉氏菌扩张,并在AE解决后表现出高微生物组弹性(恢复潜力)。涉及甲烷的微生物途径,酮体,AE期间维生素B3代谢增强,主要由莫拉氏菌引起。重要性哮喘患者NPM动态变化的证据仍然有限。这里,我们认为,偏离健康状况的哮喘NPM在受到干扰后仍表现出弹性。我们的数据从纵向角度暗示,莫拉氏菌的增加与AE的发生密切相关。AE期间功能失调(失衡)的发现为鼻咽莫拉氏菌扩张与AE风险增加之间的已知关联提供了合理的解释。这项工作作为未来长期前瞻性研究的基础,利用多组学方法阐明NPM和儿科AE之间的时间关联。
    Despite distinct nasopharyngeal microbiome (NPM) profiles between asthmatics and healthy subjects, little is known about the NPM dynamics and its relation to childhood asthma exacerbation (AE). We investigated NPM changes by longitudinally collecting 135 flocked nasopharyngeal swabs (FNPSs) from 33 school-age asthmatic children at six time points (2 to 4-week intervals) from September to December 2017 in Hong Kong. Subjects were categorized into AE and stable asthma (AS) groups according to whether they experienced any exacerbation during follow-up. One-off FNPSs from nine nonasthmatic children were included as controls. Microbiota profiles were analyzed using 16S rRNA gene sequencing. All 144 NPMs were classified into six microbiome profile groups (MPGs), each dominated by Moraxella, Corynebacterium 1, Dolosigranulum, Staphylococcus, Streptococcus, or Anoxybacillus. The microbial diversity and compositions of NPM in exacerbation samples were different from both baseline samples and those from healthy controls. Moraxella and Dolosigranulum-dominated NPM exhibited high temporal stability revealed by MPG transition analysis. NPM diversity decreased whereas microbial composition remained similar over time. The relative abundances of Moraxella increased while Corynebacterium 1, Anoxybacillus, and Pseudomonas decreased longitudinally. However, these temporal patterns did not differ between AE and AS groups, suggesting that short-term dynamic patterns were not sufficient to predict AE occurrence. Asthmatic NPM underwent Moraxella expansion during AE and presented a high microbiome resilience (recovery potential) after AE resolution. Microbial pathways involved in methane, ketone bodies, and vitamin B3 metabolisms were enhanced during AE and primarily contributed by Moraxella. IMPORTANCE Evidence on the dynamic changes of NPM in asthmatic patients remains limited. Here, we present that asthmatic NPMs deviating from a healthy status still showed resilience after disturbance. Our data imply from a longitudinal perspective that Moraxella increase is closely related to AE occurrence. The finding of functional dysbiosis (imbalance) during AE offers a plausible explanation for the known association between nasopharyngeal Moraxella expansion and increased AE risk. This work serves as a basis for future long-term prospective studies leveraging multiomics approaches to elucidate the temporal association between NPM and pediatric AE.
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  • 文章类型: Journal Article
    癌症是由基因组中的遗传或表观遗传改变推动的进化过程。了解在肿瘤进展的不同阶段起作用的进化动力学可能会为早期发现提供有效的策略。诊断,和癌症的治疗。然而,我们对肿瘤随时间演变的动力学的理解非常有限,因为通常不可能反复对患者肿瘤进行取样.体外3D类器官培养技术的最新进展为开发更现实的人类癌症模型开辟了新的途径,该模型模拟了人类肿瘤中的许多体内生物学特征。这里,我们综述了癌症基因组进化研究的最新进展和挑战,以及使用肿瘤类器官研究癌症进化的优势。我们建议建立基于患者来源的类器官的连续通道和纵向采样的实验进化模型,以研究随时间的克隆动力学和进化模式。发展群体遗传理论和计算模型并将其整合到肿瘤类器官的时程基因组数据中,将有助于查明癌症进化动力学背后的关键细胞机制。从而为高度动态性和异质性肿瘤的治疗策略提供了新的见解。
    Cancer is an evolutionary process fueled by genetic or epigenetic alterations in the genome. Understanding the evolutionary dynamics that are operative at different stages of tumor progression might inform effective strategies in early detection, diagnosis, and treatment of cancer. However, our understanding on the dynamics of tumor evolution through time is very limited since it is usually impossible to sample patient tumors repeatedly. The recent advances in in vitro 3D organoid culture technologies have opened new avenues for the development of more realistic human cancer models that mimic many in vivo biological characteristics in human tumors. Here, we review recent progresses and challenges in cancer genomic evolution studies and advantages of using tumor organoids to study cancer evolution. We propose to establish an experimental evolution model based on continuous passages of patient-derived organoids and longitudinal sampling to study clonal dynamics and evolutionary patterns over time. Development and integration of population genetic theories and computational models into time-course genomic data in tumor organoids will help to pinpoint the key cellular mechanisms underlying cancer evolutionary dynamics, thus providing novel insights on therapeutic strategies for highly dynamic and heterogeneous tumors.
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