Browsing by Subject "metagenomiikka"
Now showing items 1-9 of 9
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(2019)In recent decades, ancient DNA recovered from old and degraded samples, such as bones and fossils, has presented novel prospects in the fields of genetics, archaeology and anthropology. In Finland, ancient DNA research is constrained by the poor preservation of bones: they are quickly degraded by acidic soils, limiting the age of DNA that can be recovered from physical remains. However, some soil components can bind DNA and thus protect the molecules from degradation. Ancient DNA from soils and sediments has previously been used to reconstruct paleoenvironments, to study ancient parasites and diet and to demonstrate the presence of a species at a given site, even when there are no visible fossils present. In this pilot study, I explored the potential of archaeological sediments as an alternative source of ancient human DNA. I collected sediment samples from five Finnish Neolithic Stone Age (6,000–4,000 years ago) settlement sites, located in woodland. In addition, I analysed a lakebed sample from a submerged Mesolithic (10,000–7,000 years ago) settlement site, and a soil sample from an Iron Age burial with bones present to compare DNA yields between the two materials. Soil samples were converted into Illumina sequencing libraries and enriched for human mtDNA. I analysed the sequencing data with a customised metagenomics-based bioinformatic analysis workflow. I also tested program performance with simulated data. The results suggested that human DNA preservation in Finnish archaeological sediments may be poor or very localised. I detected small amounts of human mtDNA in three Stone Age woodland settlement sites and a submerged Mesolithic settlement site. One Stone Age sample exhibited terminal damage patterns suggestive of DNA decay, but the time of deposition is difficult to estimate. Interestingly, no human DNA was recovered from the Iron Age burial soil, suggesting that body decomposition may not serve as a significant source of sedimentary ancient DNA. Additional complications may arise from the high inhibitor content of the soil and the abundance of microbial and other non-human DNA present in environmental samples. In the future, a more refined sampling approach, such as targeting microscopic bone fragments, could be a strategy worth trialling.
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(2020)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.
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(2020)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.
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(2021)The spread of antibiotic resistance is a global health threat. Hospitals are a potential source of antibiotic-resistant bacteria and antibiotic resistance genes (ARGs), which may disseminate into the environment via wastewater. Hospital water environments, such as sink traps and shower drains, are known to harbor antibiotic-resistant bacteria, which might spread from the drains to the patients causing nosocomial infections that are hard to treat because of the limited number of treatments available. However, the current understanding of antibiotic resistance in the drains of residences, and how it relates to the situation in hospitals is limited. The aim of this study was to compare the microbial communities and ARGs in the water environments of homes and hospitals. The sink traps and shower drains of three hospital rooms and eighteen homes were sampled for metagenomic sequencing, and bioinformatic tools were used to detect the microbial taxa and ARGs in the metagenomes. The resistomes of hospital environments were distinct from those of homes and exhibited a higher diversity of ARGs. On the other hand, the microbial communities of homes and hospital rooms could not be clearly distinguished, although there were some differences in the abundances of certain taxa. The abundance of ARGs was higher in the hospital shower drains than in the corresponding samples in homes, but there was no statistical difference in the abundance of ARGs between the sink traps of homes and the hospital. Although the study had limitations, such as the low number of hospital samples, it indicates that the water environments of hospitals have a resistome that is distinct from that of homes and highlights the role of hospital sink traps and shower drains as potential hotspots of antibiotic resistance.
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(2021)The spread of antibiotic resistance is a global health threat. Hospitals are a potential source of antibiotic-resistant bacteria and antibiotic resistance genes (ARGs), which may disseminate into the environment via wastewater. Hospital water environments, such as sink traps and shower drains, are known to harbor antibiotic-resistant bacteria, which might spread from the drains to the patients causing nosocomial infections that are hard to treat because of the limited number of treatments available. However, the current understanding of antibiotic resistance in the drains of residences, and how it relates to the situation in hospitals is limited. The aim of this study was to compare the microbial communities and ARGs in the water environments of homes and hospitals. The sink traps and shower drains of three hospital rooms and eighteen homes were sampled for metagenomic sequencing, and bioinformatic tools were used to detect the microbial taxa and ARGs in the metagenomes. The resistomes of hospital environments were distinct from those of homes and exhibited a higher diversity of ARGs. On the other hand, the microbial communities of homes and hospital rooms could not be clearly distinguished, although there were some differences in the abundances of certain taxa. The abundance of ARGs was higher in the hospital shower drains than in the corresponding samples in homes, but there was no statistical difference in the abundance of ARGs between the sink traps of homes and the hospital. Although the study had limitations, such as the low number of hospital samples, it indicates that the water environments of hospitals have a resistome that is distinct from that of homes and highlights the role of hospital sink traps and shower drains as potential hotspots of antibiotic resistance.
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(2020)BACKGROUND: Diet has a major influence on the human gut microbiome, which has been linked to health and disease. However, epidemiological studies on the association of a healthy diet with the gut microbiome utilizing a whole-diet approach are still scant. OBJECTIVES: To assess associations between healthy food choices and human gut microbiome composition, and to determine the strength of association with the functional potential of the microbiome. DESIGN: The study sample consisted of 4,930 participants in the FINRISK 2002 study. Food intake was assessed using a food propensity questionnaire. Intake of food items recommended to be part of a healthy diet in the Nordic Nutrition Recommendations were transformed into a healthy food choices (HFC) score. Microbial diversity (alpha diversity) and compositional differences (beta diversity) and their associations with the HFC score and its components were assessed using linear regression and permutational multivariate analysis of variance (PERMANOVA). Associations between specific taxa and HFC were analyzed using multivariate associations with linear models (MaAsLin). Functional associations were derived from KEGG orthologies (KO) with linear regression models. RESULTS: Both microbial alpha (p = 1.90x10-4) and beta diversity (p ≤ 0.001) associated with HFC score. For alpha diversity, the strongest associations were observed for fiber-rich breads, poultry, fruits, and low-fat cheeses. For beta diversity, most prominent associations were observed for vegetables followed by berries and fruits. Genera with fiber-degrading and short-chain fatty acids (SCFA) producing capacity were positively associated with the HFC score. HFC associated positively with KO-based functions such as vitamin biosynthesis and SCFA metabolism, and inversely with fatty acid biosynthesis and the sulfur relay system. CONCLUSIONS: These results from a large and representative population-based survey confirm and extend findings of other smaller-scale studies that plant and fiber-rich dietary choices are associated with a more diverse and compositionally distinct microbiome, and with a greater potential to produce SCFAs.
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(2020)BACKGROUND: Diet has a major influence on the human gut microbiome, which has been linked to health and disease. However, epidemiological studies on the association of a healthy diet with the gut microbiome utilizing a whole-diet approach are still scant. OBJECTIVES: To assess associations between healthy food choices and human gut microbiome composition, and to determine the strength of association with the functional potential of the microbiome. DESIGN: The study sample consisted of 4,930 participants in the FINRISK 2002 study. Food intake was assessed using a food propensity questionnaire. Intake of food items recommended to be part of a healthy diet in the Nordic Nutrition Recommendations were transformed into a healthy food choices (HFC) score. Microbial diversity (alpha diversity) and compositional differences (beta diversity) and their associations with the HFC score and its components were assessed using linear regression and permutational multivariate analysis of variance (PERMANOVA). Associations between specific taxa and HFC were analyzed using multivariate associations with linear models (MaAsLin). Functional associations were derived from KEGG orthologies (KO) with linear regression models. RESULTS: Both microbial alpha (p = 1.90x10-4) and beta diversity (p ≤ 0.001) associated with HFC score. For alpha diversity, the strongest associations were observed for fiber-rich breads, poultry, fruits, and low-fat cheeses. For beta diversity, most prominent associations were observed for vegetables followed by berries and fruits. Genera with fiber-degrading and short-chain fatty acids (SCFA) producing capacity were positively associated with the HFC score. HFC associated positively with KO-based functions such as vitamin biosynthesis and SCFA metabolism, and inversely with fatty acid biosynthesis and the sulfur relay system. CONCLUSIONS: These results from a large and representative population-based survey confirm and extend findings of other smaller-scale studies that plant and fiber-rich dietary choices are associated with a more diverse and compositionally distinct microbiome, and with a greater potential to produce SCFAs.
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(2020)Global warming caused by the warming effect of greenhouse gases (GHGs) induces permafrost thaw, which could alter Arctic ecosystems from prominent carbon sinks to potential sources of GHG emissions when polar microorganisms become metabolically more active and have access to carbon compounds that were previously largely unavailable. Polar microbes can have significant contributions to the growing emissions of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) and therefore, studies on their metabolism are important. The aim of my study was to investigate polar microbial community composition and diversity as well as functional potential that was related to GHG-cycling in a subarctic environment with genome-resolved metagenomics. Soil cores were collected at the Rásttigáisá fell that is located in Northern Norway. After DNA extraction, ten mineral soil samples were sequenced. Metagenome-assembled genomes (MAGs) were reconstructed using either the combination of human-guided binning and automatic binning or human-guided binning only. Taxonomy was assigned to the MAGs and the functional potential of the MAGs was determined. I recovered dozens of good-quality MAGs. Notably, the MAGs from the mostly unknown phyla Dormibacterota (formerly candidate phylum AD3) and Eremiobacterota (formerly candidate phylum WPS-2) were reconstructed. There were MAGs from the following bacterial phyla as well: Acidobacteriota, Actinobacteriota, Chloroflexota, Gemmatimonadota, Proteobacteria and Verrucomicrobiota. In addition to the bacterial MAGs, MAGs from the group of ammonia-oxidizing archaea were recovered. Most of the MAGs belonged to poorly studied phylogenetic groups and consequently, novel functional potential was discovered in many groups of microorganisms. The following metabolic pathways were observed: CO2 fixation via the Calvin cycle and possibly via a modified version of 3-hydroxypropionate/4-hydroxybutyrate cycle; carbon monoxide oxidation to CO2; CH4 oxidation and subsequent carbon assimilation via serine pathway; urea, ammonia and nitrite oxidation; incomplete denitrification as well as dissimilatory nitrate reduction to ammonium. My study demonstrates how genome-resolved metagenomics provides a valuable overview of the microbial community and its functional potential.
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(2019)Kissoilla esiintyy monia ruoansulatuskanavan viruksia. Taudinaiheuttajasta riippuen osa tartunnoista voivat olla täysin oireettomia, mutta myös kuolemaan johtavia tartuntoja esiintyy. Ihmiselle tautiriskin voi aiheuttaa esimerkiksi kissojen rotavirukset. Uuden sukupolven sekvensointimenetelmiä (Next-generation sequencing, NGS) käyttämällä voidaan sekvensoida viruksen koko perimä eli genomi nopeasti yhdellä kerralla. NGS:ää käytettäessä sekvensointi voidaan tehdä ilman ennakkotietoja ja täten löytää myös aiemmin tuntemattomia viruksia. Suomalaisten kissojen virusten esiintyvyydestä ei ole aikaisemmin tehty kattavia tutkimuksia. Työn tavoitteena oli tutkia, mitä viruksia löytyy terveiden ja ripuloivien kissojen ulosteista Suomessa. Tutkimuksessa analysoitiin yhteensä 15 kpl kissojen ulostenäytteitä, joista yhdeksän oli eläinsuojeluyhdistyksen kissaa ja kuusi lemmikkikissaa. Kahdeksalla kissalla oli esiintynyt ruoansulatuskanavan oireita. Työhön kuului nukleiinihappojen eristys kissojen ulosteista. Esikäsittelyn avulla pyrittiin poistamaan ulosteesta bakteerit, jonka jälkeen näytteistä tehtiin kirjasto, joka sekvensoitiin Illumina Miseq-laitteistolla. Data analysoitiin bioinformatiikan avulla, johon kuului muun muassa huonolaatuisten sekvenssien poisto ja yhdistelmäsekvenssien eli contigien koostaminen lyhyistä sekvensseistä. Contigit käännettiin aminohapposekvenssiksi, joille etsittiin vastaavaa sekvenssiä geenipankista. Löydettyjen virusten nimet perustuivat geenipankkisekvenssien nimiin. Näytteistä löydettiin yhteensä kuusi virusta, joista kaksi esiintyi samalla kissalla. Yhdestä näytteestä löydettiin täysi vastaavuus kissan panleukopenia virukseen (FPV). Kissa oli saanut yhden rokotuksen ennen näytteiden keräämistä eikä kissalla ollut minkäänlaisia oireita. Löydetty virus ei ollut täysin identtinen rokotekantojen virusten kanssa, mutta ero ei ollut suuri. Taustalla voi olla luonnollinen tartunta tai esimerkiksi heikentyneen immuunivasteen aiheuttama rokotekannan pitkäaikainen replikoituminen. Yhdestä näytteestä löydettiin circovirukseen vastaavaa sekvenssiä ja lisäksi tunnistamaton virus, jonka sekvenssi vastasi myös circovirusta. Circovirusten tiedetään aiheuttavan ruoansulatuskanavaoireita, mutta kissoilta ei ole aiemmin todettu tartuntoja. Löydetty virus voi olla aiemmin tunnistamaton kissojen oma circovirus, mutta lisätutkimuksia tulisi tehdä asian varmentamiseksi. Viruksen yhteys ripuliin on myös epäselvä. Muut löydetyt virukset olivat todennäköisesti peräisin ruoasta tai esimerkiksi RNA-eristyskolumnista. Ulosteista löytyneiden virusten määrä oli pieni eikä suuria johtopäätöksiä pystytä tekemään näytteiden vähäisen lukumäärän vuoksi. Kuitenkin ulkomailla tehdyissä ulosteen viromia selvittävissä tutkimuksissa vastaavilla kissamäärillä on löydetty huomattavasti enemmän viruksia kuin tässä tutkimuksessa. Tulevaisuudessa suuremmalla kissamäärällä tehty tutkimus vertaillen eroavaisuuksia maantieteellisesti sekä sisä- ja ulkokissojen välillä, antaisi luotettavampaa dataa Suomen tilanteesta. NGS:n käyttäminen ulosteen viromin selvittämiseksi vaikuttaisi olevan käyttökelpoinen tutkimusmenetelmä.
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