Modeling of Urinary Microbiota Associated With Cystitis

Frontiers in Cellular and Infection Microbiology

Marina Ceprnja¹  Jasenka Skrlin²  Karmela Barisic³  Jurica Zucko⁴  Lucija Starcevic⁴  Antonio Starcevic⁴  Ema Svetlicic⁴  Damir Oros⁴  Ena Melvan⁵ 

[1] Biochemical Laboratory, Special Hospital Agram, Polyclinic Zagreb, Zagreb, Croatia;Department of Medical Biochemistry and Hematology, Faculty of Pharmacy and Biochemistry, Zagreb University, Zagreb, Croatia;Department for Clinical Microbiology and Hospital Infection, University Hospital Dubrava, Zagreb, Croatia;Department of Medical Biochemistry and Hematology, Faculty of Pharmacy and Biochemistry, Zagreb University, Zagreb, Croatia;Laboratory for Bioinformatics, Faculty of Food Technology and Biotechnology, Zagreb University, Zagreb, Croatia;Laboratory for Bioinformatics, Faculty of Food Technology and Biotechnology, Zagreb University, Zagreb, Croatia;Department of Biological Science, Faculty of Science, Macquarie University, Sydney, NSW, Australia;

关键词: urinary tract infection;    microbiome;    16S rRNA sequencing;    microbial interaction modeling;    antibiotics;    therapy duration;   

DOI  :  10.3389/fcimb.2021.643638

来源: Frontiers

【 摘 要 】

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 – Gammaproteobacteria, 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, Actinobacteria and Bacteroidia class, which appear to actively suppress pathogen overgrowth.

【 授权许可】

CC BY