Browsing by Subject "DeepARG"

The human gut is inhabited by gut microbiota, a complex and diverse ecological community of trillions of microbes that affect both the normal human physiology and countless disease states and susceptibilities. Understanding the composition, functions and the causes and effects of changes in the microbiota is invaluable for understanding diseases that are connected to the microbiota and developing better treatments to the diseases. The gut microbiota varies between individuals and keeps changing over time. Behind the variability are e.g. the person’s age, genetics, diet, environment, and especially diseases and the use of antibiotics. When antibiotic use disrupts the gut microbiota, the changes can persist for years. Antibiotic resistance tends to increase after the use of antibiotics. Since antibiotic resistance in bacterial pathogens is considered a major health threat, the characterization of the human gut resistome (the antibiotic resistance genes (ARGs) found in the gut microbiota) is of great medical interest. Next-generation sequencing techniques have enabled studying also those microbe species that cannot be cultured at the moment. Metagenomics provides information on all genetic material collected from a given environment and enables searching for any sequences of interest within it, e.g. ARG sequences. The development of Parkinson’s disease (PD) is suspected to begin in the enteric nervous system and spread from there toward the central nervous system. The use of antibiotics could be linked to PD through their effects on gut microbiota, and since these effects are modified by the gut resistome, the aim of this study was to find gene sequences coding antibiotic resistance in human gut metagenomics data originating from stool samples of PD patients and healthy controls, and to find out potential differences in the occurrence of antibiotic resistance genes in the gut microbes of the two study groups. DeepARG was the chosen method for searching antibiotic resistance gene sequences in the metagenomics data. The statistical data analyses, including alpha diversity, multivariate analyses, and differential abundance analysis, were performed with the R statistical programming language in RStudio. DeepARG found 840 different ARGs in 192 samples. The ARGs belonged to 29 different ARG classes. The alpha diversity analysis showed a small estimated difference between PD and control groups indicating a possible slightly higher ARG diversity in the PD group. Multivariate analysis did not give any strong suggestions of definite biologically meaningful differences between the study groups. 16 ARGs were deemed differentially abundant in the study groups. BepE, cmeA, cmlv, dfrE, mefC, msrB, opcM, oprM and RbpA seemed to have increased abundance, and arnC, BN537_02049, dfrK, mgrA, murA, tet35 and tetT were suggested to have decreased abundance in PD patients compared to the healthy controls. These ARGs do not appear interconnected in any other way except for some sharing antibiotic types to which they offer resistance, and some having similar resistance mechanisms. In the light of an ongoing, unpublished epidemiological study of the connection between PD and the use of antibiotics it would seem that only three ARGs (msrB, mefC and dfrE) might be somehow relevant in PD development, but their effects, if any, are most likely minor. Eight ARG classes were shown to have differential abundance between PD patients and healthy controls. Bacitracin, fosfomycin and polymyxin classes showed decrease and chloramphenicol, fosmidomycin, puromycin, rifampin and sulfonamide classes showed increase in abundance in PD compared to controls. The change in the abundance of a certain ARG could reflect change in the abundance of the bacteria carrying that resistance gene. If so, the follow-up questions would be how much change in the abundance of bacteria is due to the use of certain antibiotics and how much is caused by environmental factors. It also remains to be studied whether specific antibiotics associated with the ARGs that in this study showed differential abundance in PD patients and healthy controls might have an actual role in PD development. The results of this thesis study are later to be combined with and further studied alongside information coming from ongoing studies on antibiotics use in general population and in PD patients. While this study did not concentrate its efforts into finding novel ARGs, the metagenomics dataset could also in the future be applied for that purpose.