Bioinformatics analysis of various aspects in immunology
Date
2024-04-10
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Abstract
Bioinformaatika on interdistsiplinaarne valdkond, mis on segu nii bioloogiast, statistikast kui ka arvutiteadusest. Antud doktoritöös kasutasime bioinformaatilist analüüsi vastamaks mitmesugustele immunoloogilistele küsimustele.
Üks töösse kaasatud artiklitest keskendus erinevate T-raku alatüüpide kirjeldamisele. T-rakud on adaptiivse immuunsüsteemi rakud, mis on olulised nii patogeenide eemaldamisel kui ka immunoloogilise mälu kujunemisel. Meil oli täpsemalt fookuses CD8+ TEMRA rakud, mida on varasemalt seostatud mitmesuguste haigustega. Oma töös kirjeldasime antud rakutüübi seoseid muuhulgas DNA metülatsiooniga, mis on raku fenotüübi kujunemiseks oluline keemiline modifikatsioon. Oma töös identifitseerisime sellised DNA positsioonid, mille metülatsiooni põhjal saime luua CD8+ TEMRA rakkude taset ennustava mudeli, mis võiks olla kasulik inimese tervisliku seisundi hindamisel.
Ka teises doktoritöösse kaasatud uuringus keskendusime T-rakkudele, kuid sel korral keskendusime DNA metülatsiooni võrdlemisele konventsionaalsete ja immuunvastust supresseerivate regulatoorsete T-rakkude vahel. Me leidsime tuhandeid positsioone DNA-s, mille puhul olid need rakutüübid erinevad metüleeritud, kuid lisaks sellele leidsime ka erinevuse Graves’i tõve riskilookuses. Kuigi me ei suutnud välja selgitada, kuidas antud regioon võiks osaleda Graves’i haiguse väljakujunemisel, siiski loodame, et meie töö inspireerib teisi välja selgitama, kas antud regioonil on mõju regulatoorsete T-rakkude fenotüübile.
Kolmandas artiklis uurisime T-raku arengus olulisi tüümuse säsi epiteelrakke. Meie analüüs vihjas, et antud rakutüüp differentseerub sarnaselt keratinotsüütidega ning selle hilisemad staadiumid võiksid olla olulised tüümuses normaalse põletikulise keskkonna loomisel, mis on T-rakkude arengu jaoks oluline.
Kahes viimases töösse kaasatud artiklis andsime oma panuse COVID-19 uurimisse. Meie analüüs näitas, et iseäranis just raske COVID-19 kulg on seotud apoptootiliste signaaliradadega. Lisaks leidsime, et isegi asümptomaatilistel inimestel võib SARS-CoV-2 infektsioon kaasa tuua pikaajalise põletikuliste valkude taseme tõusu.
Bioinformatics is an interdisciplinary field that combines computer science, statistics, and biology to study biological systems. In this thesis, we used bioinformatics analysis to answer several immunological questions. In one of our studies, we focused on characterizing different T cell subpopulations, which are immune cells that play a critical role in adaptive immunity. We specifically looked at CD8+ TEMRA cells, a population that has been associated with age-related health problems. By examining their DNA methylation patterns, which is a chemical modification essential for defining a cell's phenotype, we identified specific methylated positions in DNA that could predict TEMRA cell levels. This model could be useful for monitoring age-associated immune dysfunction. In the second study, we compared DNA methylation patterns between conventional T cells and immune response-suppressing regulatory T cells. We observed vast differences in thousands of positions and identified differential methylation in a known risk locus for Graves’ disease. Although we could not determine the exact role of this locus in the disease, our work provides a foundation for future investigations to explore if this genetic locus affects regulatory T cells’ phenotype and predisposes individuals to the development of Graves’ disease. In the third study we focused on medullary thymic epithelial cells, a key cell type involved in T cell development. Our analysis revealed how these cells differentiate similarly to keratinocytes, which are cells that make up the skin's outer layer. We found that the late stages of medullary thymic epithelial cell differentiation contribute to a tonic inflammatory state in the thymus that is relevant for T cell development. Lastly, we contributed to COVID-19 research by analyzing longitudinally obtained samples from COVID-19 patients with different clinical manifestations. Our findings showed that the disease is associated with apoptotic pathways, particularly in severe cases. Apoptosis is a form of programmed cell death that occurs when cells are damaged or infected. We also found evidence of a long-term inflammation among asymptomatic individuals, which could have implications for long COVID.
Bioinformatics is an interdisciplinary field that combines computer science, statistics, and biology to study biological systems. In this thesis, we used bioinformatics analysis to answer several immunological questions. In one of our studies, we focused on characterizing different T cell subpopulations, which are immune cells that play a critical role in adaptive immunity. We specifically looked at CD8+ TEMRA cells, a population that has been associated with age-related health problems. By examining their DNA methylation patterns, which is a chemical modification essential for defining a cell's phenotype, we identified specific methylated positions in DNA that could predict TEMRA cell levels. This model could be useful for monitoring age-associated immune dysfunction. In the second study, we compared DNA methylation patterns between conventional T cells and immune response-suppressing regulatory T cells. We observed vast differences in thousands of positions and identified differential methylation in a known risk locus for Graves’ disease. Although we could not determine the exact role of this locus in the disease, our work provides a foundation for future investigations to explore if this genetic locus affects regulatory T cells’ phenotype and predisposes individuals to the development of Graves’ disease. In the third study we focused on medullary thymic epithelial cells, a key cell type involved in T cell development. Our analysis revealed how these cells differentiate similarly to keratinocytes, which are cells that make up the skin's outer layer. We found that the late stages of medullary thymic epithelial cell differentiation contribute to a tonic inflammatory state in the thymus that is relevant for T cell development. Lastly, we contributed to COVID-19 research by analyzing longitudinally obtained samples from COVID-19 patients with different clinical manifestations. Our findings showed that the disease is associated with apoptotic pathways, particularly in severe cases. Apoptosis is a form of programmed cell death that occurs when cells are damaged or infected. We also found evidence of a long-term inflammation among asymptomatic individuals, which could have implications for long COVID.
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Keywords
immunoloogia