Bioinformatics integration of microbiome and metabolomics data in the translational context : doctoral dissertation

Deutsch, Leon (avtor), Stres, Blaž (mentor)

Human metabolism was studied in three different projects focusing on different levels of inactivity. Urine, liquor and serum metabolomics were used to assess the impact of nusinersen treatment in patients with spinal muscular atrophy. Urine samples were contrasted with samples from matching healthy cohort. In the PreTerm project, metabolomics (fecal and urine) and fecal microbial metagenomics were used to assess the differences between preterm and full-term born adults. In the X-Adapt project, urinary metabolomics was used to evaluate the 10-day training regime and the differences between trained and untrained individuals. In all projects, classification models based on different data sets were developed as a proof of principle and to foster their use in future studies or possibly in medical diagnostics. In addition, two workflows (GUMPP and MAGO tool) and a method to study physicochemical parameters (minimum pressure of piercing strength) were developed to study the microbiome and its environment, respectively. The final work resulted in the creation of the first Slovenian urine 1H-NMR database, which consists of 1200 urine metabolomes from different projects (PlanHab, Spinal Muscular Atrophy, X-Adapt, PreTerm, Healthy males and females) measured by 1H-NMR, outlining the baseline for future extensions. The entire database can be used to build machine-learning models for classification between different diseases or levels of physical activity at a national level.

• Jezik: Angleški jezik
• Ključne besede: bioinformatics, metabolomics, metagenomcis, physical inactivity, data integration, systems biology, microbiome, urine, nuclear magnetic spectrometry
• Vrsta gradiva: Doktorsko delo/naloga
• Tipologija: 2.08 - Doktorska disertacija
• Organizacija: BF - Biotehniška fakulteta
• Leto izida: 2022
• PID: 20.500.12556/RUL-142851
• COBISS.SI-ID: 132071939
• Datum objave v RUL: 30.11.2022

DEUTSCH, Leon, 2022, Bioinformatics integration of microbiome and metabolomics data in the translational context : doctoral dissertation [na spletu]. Doktorska disertacija. [Dostopano 11 april 2025]. Pridobljeno s: https://repozitorij.uni-lj.si/IzpisGradiva.php?lang=slv&id=142851

Sekundarni jezik

• Jezik: Slovenski jezik
• Naslov: Bioinformacijska integracija mikrobiomskih in metabolomskih podatkov v translacijskem kontekstu : doktorska disertacija

Izvleček

V okviru večih projektov smo preučevali metabolome preiskovancev z različnimi stopnjami neaktivnosti. Za oceno učinka zdravljenja z zdravilom nusinersen pri bolnikih s spinalno mišično atrofijo smo uporabili metabolomiko urina, likvorja in seruma. Dodatne vzorce urina smo primerjali s tistimi iz zdrave kontrolne skupine. V projektu PreTerm smo s kombinacijo metabolomike fecesa in urina ter z metagenomiko fekalnega mikrobioma raziskovali razlike med predčasno in pravočasno rojenimi odraslimi. V projektu X-Adapt smo z metabolomiko urina ocenili učinke 10-dnevnega režima treninga in razlik med treniranimi in netreniranimi posamezniki. V vseh projektih smo na zbranih podatkih razvili modele za razvrščanje skupin z namenom razvoja analitskih poti ter prikaza možnostjo uporabe teh modelov v prihodnjih študijah ali morda v medicinski diagnostiki. Poleg tega sta bila razvita dva cevovoda (orodje GUMPP in MAGO) ter metoda za preučevanje fizikalno-kemijskih parametrov (minimalna prebodna sila) za preučevanje mikrobioma in njegovega okolja. Končni rezultat analize je bila izdelava prve slovenske metabolomske baze podatkov 1H-NMR urina, ki jo sestavlja 1200 metabolomov urina iz različnih projektov (PlanHab, Spinalna mišična atrofija, X-Adapt, PreTerm, Zdravi moški in ženske), merjenih z 1H-NMR, ki predstavljajo osnovo za prihodnje razširitve iz novih projektov. Celotno bazo podatkov je mogoče uporabiti za gradnjo modelov strojnega učenja za razvrščanje med različnimi boleznimi ali stopnjami telesne aktivnosti na nacionalni ravni.

• Ključne besede: bioinformatika, metabolomika, metagenomika, fizikalna inaktivnost, integracija podatkov, sistemska biologija, mikrobiom, urin, jedrska magnetna resonanca