Identification of urine microorganisms by genomic and proteomic analysis

U identifikaciji bakterija koji su najčešći uzročnici infekcija mokraćnoga sustava najčešće se koriste klasične medicinsko-mikrobiološke metode. Glavni nedostatak tih metoda je njihova dugotrajnost. Upravo iz toga razloga kontinuirano se istražuju mogućnosti bržih i učinkovitijih postupaka za određivanje broja i vrste mikroorganizama. U ovom doktorskom radu istraživane su mogućnosti upotrebe masene spektrometrije (MS) i sekvenciranja gena za 16S rRNA u svrhu identifikacije bakterija iz mokraće. Za identifikaciju mikroorganizama izoliranih iz mokraće ispitanika sa simptomima cistitisa, kao kontrola koristila se klasična mikrobiološka dijagnostika nakon koje se na istim uzorcima provodila analiza mikrobioma i metaproteoma. Analiza mikrobioma obuhvaćala je identifikaciju gena za 16S rRNA, dok se analizom metaproteoma provedenoga na MALDI-TOF MS/MS (engl. matrix assisted laser desorption ionization-time of flight tandem mass spectrometry) pokušala postići rezolucija na nivou soja. Cilj ovoga rada bio je dizajnirati i ispitati metodu MS-a za izravnu, brzu i pouzdanu identifikaciju mikroorganizama u uzorcima mokraće ispitanika kod kojih je klasičnim mikrobiološkim metodama dokazana prisutnost mikroorganizama >105 CFU/ml te je usporediti s rezultatima dobivenim genomskom analizom mikroorganizama mokraće. Također, cilj rada bio je pratiti promjene sastava mokraćne mikrobiote izazvane cistitisom i dinamiku njihove promjene uslijed antibiotske terapije. Istraživanje je obuhvatilo analizu ukupno 396 uzoraka mokraće prikupljenih u KB Dubrava. Osim toga, analizirano je dodatnih osam uzoraka mokraće istoga ispitanika koji je bio na antimikrobnoj terapiji s ciljem praćenja promjena u mokraćnoj mikrobioti, te 40 uzoraka kultura četiri najčešća uropatogena. Rezultati ovoga istraživanja pokazali su da se koristeći masenu spektroskopiju mogu identificirati bakterije u monomikrobnim kulturama na razini roda. Međutim, ukoliko se radi o polimikrobnim kulturama MS ne daje pouzdane rezultate identifikacije. Sekvenciranjem gena za 16S rRNA postignuta je taksonomska kategorizacija uropatogena do razine roda (44 %) i obitelji (56 %), dok identifikacija na razini vrste nije postignuta. Također, utvrđeno je da antibiotska terapija ima snažan utjecaj na dinamiku promjena sastava mokraćne mikrobiote, te da je trajanje terapije iznimno važan terapijski parametar, kao i početni izbor lijeka.The bacteria that are the most prevalent causes of urinary tract infections are typically identified using standard microbiological procedures. The biggest downside of these approaches is that they take a long time to complete. As a result, researchers are always looking for new ways to determine the quantity and kind of microorganisms faster and more efficiently. The possibility of utilizing mass spectrometry (MS) and sequencing of 16S rRNA genes to detect bacteria from urine were studied in this doctoral thesis. Classical microbiological tests were utilized to identify bacteria isolated from the urine of patients with cystitis symptoms, after which microbiomes and metaproteom were analyzed. Microbiome investigation included identifying genes for 16S rRNA, while MALDI-TOF MS/MS (matrix aided laser desorption ionization-time of flight tandem mass spectrometry) analysis of the metaproteome tried to acquire strain-level resolution. The aim of the study was to design and test an MS method for direct, rapid, and reliable identification of microorganisms in urine samples of patients whose presence of microorganisms > 105 CFU / ml was confirmed by traditional microbiological methods, and to compare the results with those of genomic analysis of urine microorganisms. Also, the aim of the study was to monitor changes in the composition of the urinary microbiota caused by cystitis and the dynamics of their change due to antibiotic therapy. The research included the analysis of a total of 396 urine samples collected through four phases in KB Dubrava. In addition, 40 culture samples from the four most frequent uropathogens were studied, as well as 8 urine samples from the same person who had been on antibiotic therapy to monitor changes in the urinary microbiota. The findings of this study revealed that mass spectroscopy can be used to identify bacteria in monomicrobial cultures at the genus level. Mass spectroscopy, on the other hand, does not yield good identification results in polymicrobial cultures. The 16S rRNA gene provided taxonomic categorization of uropathogens down to the genus (44 %) and family (56 %) levels, but not species level identification. It was discovered that monitoring the urine microbiota during antibiotic therapy has a substantial influence on the dynamics of changes in its composition, and that the duration of therapy, as well as the initial drug choice, is an extremely essential therapeutic parameter