Ceprnja Marina, Oros Damir, Melvan Ena, Svetlicic Ema, Skrlin Jasenka, Barisic Karmela, Starcevic Lucija, Zucko Jurica, Starcevic Antonio
Biochemical Laboratory, Special Hospital Agram, Polyclinic Zagreb, Zagreb, Croatia.
Department of Medical Biochemistry and Hematology, Faculty of Pharmacy and Biochemistry, Zagreb University, Zagreb, Croatia.
Front Cell Infect Microbiol. 2021 Mar 16;11:643638. doi: 10.3389/fcimb.2021.643638. eCollection 2021.
A decade ago, when the Human Microbiome Project was starting, urinary tract (UT) was not included because the bladder and urine were considered to be sterile. Today, we are presented with evidence that healthy UT possesses native microbiota and any major event disrupting its "equilibrium" can impact the host also. This dysbiosis often leads to cystitis symptoms, which is the most frequent lower UT complaint, especially among women. Cystitis is one of the most common causes of antimicrobial drugs prescriptions in primary and secondary care and an important contributor to the problem of antimicrobial resistance. Despite this fact, we still have trouble distinguishing whether the primary cause of majority of cystitis cases is a single pathogen overgrowth, or a systemic disorder affecting entire UT microbiota. There are relatively few studies monitoring changes and dynamics of UT microbiota in cystitis patients, making this field of research still an unknown. In this study variations to the UT microbiota of cystitis patients were identified and microbial dynamics has been modeled. The microbial genetic profile of urine samples from 28 patients was analyzed by 16S rDNA Illumina sequencing and bioinformatics analysis. One patient with bacterial cystitis symptoms was prescribed therapy based on national guideline recommendations on antibacterial treatment of urinary tract infections (UTI) and UT microbiota change was monitored by 16S rDNA sequencing on 24 h basis during the entire therapy duration. The results of sequencing implied that a particular class of bacteria is associated with majority of cystitis cases in this study. The contributing role of this class of bacteria - , was further predicted by generalized Lotka-Volterra modeling (gLVM). Longitudinal microbiota insight obtained from a single patient under prescribed antimicrobial therapy revealed rapid and extensive changes in microbial composition and emphasized the need for current guidelines revision in regards to therapy duration. Models based on gLVM indicated protective role of two taxonomic classes of bacteria, and class, which appear to actively suppress pathogen overgrowth.
十年前，当人类微生物组计划启动时，尿路（UT）并未被纳入其中，因为膀胱和尿液被认为是无菌的。如今，我们有证据表明健康的尿路拥有原生微生物群，任何破坏其“平衡”的重大事件也会影响宿主。这种生态失调通常会导致膀胱炎症状，这是下尿路最常见的病症，尤其是在女性中。膀胱炎是初级和二级护理中抗菌药物处方的最常见原因之一，也是抗菌药物耐药性问题的一个重要因素。尽管如此，我们仍然难以区分大多数膀胱炎病例的主要原因是单一病原体过度生长，还是影响整个尿路微生物群的系统性疾病。监测膀胱炎患者尿路微生物群变化和动态的研究相对较少，使得这个研究领域仍然未知。在这项研究中，确定了膀胱炎患者尿路微生物群的变化，并对微生物动态进行了建模。通过16S rDNA Illumina测序和生物信息学分析，分析了28名患者尿液样本的微生物基因谱。一名有细菌性膀胱炎症状的患者根据国家关于尿路感染（UTI）抗菌治疗的指南建议接受治疗，并在整个治疗期间通过16S rDNA测序每24小时监测一次尿路微生物群的变化。测序结果表明，在这项研究中，某一类细菌与大多数膀胱炎病例有关。通过广义洛特卡-沃尔泰拉模型（gLVM）进一步预测了这类细菌的作用。从一名接受规定抗菌治疗的患者身上获得的纵向微生物群见解揭示了微生物组成的快速和广泛变化，并强调了当前关于治疗持续时间的指南需要修订。基于gLVM的模型表明，两类细菌，即 和 类，具有保护作用，它们似乎能积极抑制病原体过度生长。
