12,015 research outputs found

    Pollution-induced community tolerance in freshwater biofilms – from molecular mechanisms to loss of community functions

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    Exposure to herbicides poses a threat to aquatic biofilms by affecting their community structure, physiology and function. These changes render biofilms to become more tolerant, but on the downside community tolerance has ecologic costs. A concept that addresses induced community tolerance to a pollutant (PICT) was introduced by Blanck and Wängberg (1988). The basic principle of the concept is that microbial communities undergo pollution-induced succession when exposed to a pollutant over a long period of time, which changes communities structurally and functionally and enhancing tolerance to the pollutant exposure. However, the mechanisms of tolerance and the ecologic consequences were hardly studied up to date. This thesis addresses the structural and functional changes in biofilm communities and applies modern molecular methods to unravel molecular tolerance mechanisms. Two different freshwater biofilm communities were cultivated for a period of five weeks, with one of the communities being contaminated with 4 μg L-1 diuron. Subsequently, the communities were characterized for structural and functional differences, especially focusing on their crucial role of photosynthesis. The community structure of the autotrophs was assessed using HPLC-based pigment analysis and their functional alterations were investigated using Imaging-PAM fluorometry to study photosynthesis and community oxygen profiling to determine net primary production. Then, the molecular fingerprints of the communities were measured with meta-transcriptomics (RNA-Seq) and GC-based community metabolomics approaches and analyzed with respect to changes in their molecular functions. The communities were acute exposed to diuron for one hour in a dose-response design, to reveal a potential PICT and uncover related adaptation to diuron exposure. The combination of apical and molecular methods in a dose-response design enabled the linkage of functional effects of diuron exposure and underlying molecular mechanisms based on a sensitivity analysis. Chronic exposure to diuron impaired freshwater biofilms in their biomass accrual. The contaminated communities particularly lost autotrophic biomass, reflected by the decrease in specific chlorophyll a content. This loss was associated with a change in the molecular fingerprint of the communities, which substantiates structural and physiological changes. The decline in autotrophic biomass could be due to a primary loss of sensitive autotrophic organisms caused by the selection of better adapted species in the course of chronic exposure. Related to this hypothesis, an increase in diuron tolerance has been detected in the contaminated communities and molecular mechanisms facilitating tolerance have been found. It was shown that genes of the photosystem, reductive-pentose phosphate cycle and arginine metabolism were differentially expressed among the communities and that an increased amount of potential antioxidant degradation products was found in the contaminated communities. This led to the hypothesis that contaminated communities may have adapted to oxidative stress, making them less sensitive to diuron exposure. Moreover, the photosynthetic light harvesting complex was altered and the photoprotective xanthophyll cycle was increased in the contaminated communities. Despite these adaptation strategies, the loss of autotrophic biomass has been shown to impair primary production. This impairment persisted even under repeated short-term exposure, so that the tolerance mechanisms cannot safeguard primary production as a key function in aquatic systems.:1. The effect of chemicals on organisms and their functions .............................. 1 1.1 Welcome to the anthropocene .......................................................................... 1 1.2 From cellular stress responses to ecosystem resilience ................................... 3 1.2.1 The individual pursuit for homeostasis ....................................................... 3 1.2.2 Stability from diversity ................................................................................. 5 1.3 Community ecotoxicology - a step forward in monitoring the effects of chemical pollution? ................................................................................................................. 6 1.4 Functional ecotoxicological assessment of microbial communities ................... 9 1.5 Molecular tools – the key to a mechanistic understanding of stressor effects from a functional perspective in microbial communities? ...................................... 12 2. Aims and Hypothesis ......................................................................................... 14 2.1 Research question .......................................................................................... 14 2.2 Hypothesis and outline .................................................................................... 15 2.3 Experimental approach & concept .................................................................. 16 2.3.1 Aquatic freshwater biofilms as model community ..................................... 16 2.3.2 Diuron as model herbicide ........................................................................ 17 2.3.3 Experimental design ................................................................................. 18 3. Structural and physiological changes in microbial communities after chronic exposure - PICT and altered functional capacity ................................................. 21 3.1 Introduction ..................................................................................................... 21 3.2 Methods .......................................................................................................... 23 3.2.1 Biofilm cultivation ...................................................................................... 23 3.2.2 Dry weight and autotrophic index ............................................................. 23 3.2.4 Pigment analysis of periphyton ................................................................. 23 3.2.4.1 In-vivo pigment analysis for community characterization ....................... 24 3.2.4.2 In-vivo pigment analysis based on Imaging-PAM fluorometry ............... 24 3.2.4.3 In-vivo pigment fluorescence for tolerance detection ............................. 26 3.2.4.4 Ex-vivo pigment analysis by high-pressure liquid-chromatography ....... 27 3.2.5 Community oxygen metabolism measurements ....................................... 28 3.3 Results and discussion ................................................................................... 29 3.3.1 Comparison of the structural community parameters ............................... 29 3.3.2 Photosynthetic activity and primary production of the communities after selection phase ................................................................................................. 33 3.3.3 Acquisition of photosynthetic tolerance .................................................... 34 3.3.4 Primary production at exposure conditions ............................................... 36 3.3.5 Tolerance detection in primary production ................................................ 37 3.4 Summary and Conclusion ........................................................................... 40 4. Community gene expression analysis by meta-transcriptomics ................... 41 4.1 Introduction to meta-transcriptomics ............................................................... 41 4.2. Methods ......................................................................................................... 43 4.2.1 Sampling and RNA extraction................................................................... 43 4.2.2 RNA sequencing analysis ......................................................................... 44 4.2.3 Data assembly and processing................................................................. 45 4.2.4 Prioritization of contigs and annotation ..................................................... 47 4.2.5 Sensitivity analysis of biological processes .............................................. 48 4.3 Results and discussion ................................................................................... 48 4.3.1 Characterization of the meta-transcriptomic fingerprints .......................... 49 4.3.2 Insights into community stress response mechanisms using trend analysis (DRomic’s) ......................................................................................................... 51 4.3.3 Response pattern in the isoform PS genes .............................................. 63 4.5 Summary and conclusion ................................................................................ 65 5. Community metabolome analysis ..................................................................... 66 5.1 Introduction to community metabolomics ........................................................ 66 5.2 Methods .......................................................................................................... 68 5.2.1 Sampling, metabolite extraction and derivatisation................................... 68 5.2.2 GC-TOF-MS analysis ............................................................................... 69 5.2.3 Data processing and statistical analysis ................................................... 69 5.3 Results and discussion ................................................................................... 70 5.3.1 Characterization of the metabolic fingerprints .......................................... 70 5.3.2 Difference in the metabolic fingerprints .................................................... 71 5.3.3 Differential metabolic responses of the communities to short-term exposure of diuron ............................................................................................................ 73 5.4 Summary and conclusion ................................................................................ 78 6. Synthesis ............................................................................................................. 79 6.1 Approaches and challenges for linking molecular data to functional measurements ...................................................................................................... 79 6.2 Methods .......................................................................................................... 83 6.2.1 Summary on the data ............................................................................... 83 6.2.2 Aggregation of molecular data to index values (TELI and MELI) .............. 83 6.2.3 Functional annotation of contigs and metabolites using KEGG ................ 83 6.3 Results and discussion ................................................................................... 85 6.3.1 Results of aggregation techniques ........................................................... 85 6.3.2 Sensitivity analysis of the different molecular approaches and endpoints 86 6.3.3 Mechanistic view of the molecular stress responses based on KEGG functions ............................................................................................................ 89 6.4 Consolidation of the results – holistic interpretation and discussion ............... 93 6.4.1 Adaptation to chronic diuron exposure - from molecular changes to community effects.............................................................................................. 93 6.4.2 Assessment of the ecological costs of Pollution-induced community tolerance based on primary production ............................................................. 94 6.5 Outlook ............................................................................................................ 9

    Machine Learning Research Trends in Africa: A 30 Years Overview with Bibliometric Analysis Review

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    In this paper, a critical bibliometric analysis study is conducted, coupled with an extensive literature survey on recent developments and associated applications in machine learning research with a perspective on Africa. The presented bibliometric analysis study consists of 2761 machine learning-related documents, of which 98% were articles with at least 482 citations published in 903 journals during the past 30 years. Furthermore, the collated documents were retrieved from the Science Citation Index EXPANDED, comprising research publications from 54 African countries between 1993 and 2021. The bibliometric study shows the visualization of the current landscape and future trends in machine learning research and its application to facilitate future collaborative research and knowledge exchange among authors from different research institutions scattered across the African continent

    Mathematical models to evaluate the impact of increasing serotype coverage in pneumococcal conjugate vaccines

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    Of over 100 serotypes of Streptococcus pneumoniae, only 7 were included in the first pneumo- coccal conjugate vaccine (PCV). While PCV reduced the disease incidence, in part because of a herd immunity effect, a replacement effect was observed whereby disease was increasingly caused by serotypes not included in the vaccine. Dynamic transmission models can account for these effects to describe post-vaccination scenarios, whereas economic evaluations can enable decision-makers to compare vaccines of increasing valency for implementation. This thesis has four aims. First, to explore the limitations and assumptions of published pneu- mococcal models and the implications for future vaccine formulation and policy. Second, to conduct a trend analysis assembling all the available evidence for serotype replacement in Europe, North America and Australia to characterise invasive pneumococcal disease (IPD) caused by vaccine-type (VT) and non-vaccine-types (NVT) serotypes. The motivation behind this is to assess the patterns of relative abundance in IPD cases pre- and post-vaccination, to examine country-level differences in relation to the vaccines employed over time since introduction, and to assess the growth of the replacement serotypes in comparison with the serotypes targeted by the vaccine. The third aim is to use a Bayesian framework to estimate serotype-specific invasiveness, i.e. the rate of invasive disease given carriage. This is useful for dynamic transmission modelling, as transmission is through carriage but a majority of serotype-specific pneumococcal data lies in active disease surveillance. This is also helpful to address whether serotype replacement reflects serotypes that are more invasive or whether serotypes in a specific location are equally more invasive than in other locations. Finally, the last aim of this thesis is to estimate the epidemiological and economic impact of increas- ing serotype coverage in PCVs using a dynamic transmission model. Together, the results highlight that though there are key parameter uncertainties that merit further exploration, divergence in serotype replacement and inconsistencies in invasiveness on a country-level may make a universal PCV suboptimal.Open Acces

    Investigation of microparticle behavior in Newtonian, viscoelastic, and shear-thickening flows in straight microchannels

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    Sorting and separation of small substances such as cells, microorganisms, and micro- and nano-particles from a heterogeneous mixture is a common sample preparation step in many areas of biology, biotechnology, and medicine. Portability and inexpensive design of microfluidic-based sorting systems have benefited many of these biomedical applications. Accordingly, we have investigated microparticle hydrodynamics in fluids with various rheological behaviors (i.e., Newtonian, shear-thinning viscoelastic and shear-thickening non-Newtonian) flowing in straight microchannels. Numerical models were developed to simulate particles trajectories in Newtonian water and shear-thinning polyethylene oxide (PEO) solutions. The validated models were then used to perform numerical parametric studies and non-dimensional analysis on the Newtonian inertia-magnetic and shear-thinning elasto-inertal focusing regimes. Finally, the straight microfluidic device that was tested for Newtonian water and shear-thinning viscoelastic PEO solution, were adopted to experimentally study microparticle behavior in SiO2/Water shear-thickening nanofluid

    Towards a non-equilibrium thermodynamic theory of ecosystem assembly and development

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    Non-equilibrium thermodynamics has had a significant historic influence on the development of theoretical ecology, even informing the very concept of an ecosystem. Much of this influence has manifested as proposed extremal principles. These principles hold that systems will tend to maximise certain thermodynamic quantities, subject to the other constraints they operate under. A particularly notable extremal principle is the maximum entropy production principle (MaxEPP); that systems maximise their rate of entropy production. However, these principles are not robustly based in physical theory, and suffer from treating complex ecosystems in an extremely coarse manner. To address this gap, this thesis derives a limited but physically justified extremal principle, as well as carrying out a detailed investigation of the impact of non-equilibrium thermodynamic constraints on the assembly of microbial communities. The extremal principle we obtain pertains to the switching between states in simple bistable systems, with switching paths that generate more entropy being favoured. Our detailed investigation into microbial communities involved developing a novel thermodynamic microbial community model, using which we found the rate of ecosystem development to be set by the availability of free-energy. Further investigation was carried out using this model, demonstrating the way that trade-offs emerging from fundamental thermodynamic constraints impact the dynamics of assembling microbial communities. Taken together our results demonstrate that theory can be developed from non-equilibrium thermodynamics, that is both ecologically relevant and physically well grounded. We find that broad extremal principles are unlikely to be obtained, absent significant advances in the field of stochastic thermodynamics, limiting their applicability to ecology. However, we find that detailed consideration of the non-equilibrium thermodynamic mechanisms that impact microbial communities can broaden our understanding of their assembly and functioning.Open Acces

    Omics measures of ageing and disease susceptibility

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    While genomics has been a major field of study for decades due to relatively inexpensive genotyping arrays, the recent advancement of technology has also allowed the measure and study of various “omics”. There are now numerous methods and platforms available that allow high throughput and high dimensional quantification of many types of biological molecules. Traditional genomics and transcriptomics are now joined by proteomics, metabolomics, glycomics, lipidomics and epigenomics. I was lucky to have access to a unique resource in the Orkney Complex Disease Study (ORCADES), a cohort of individuals from the Orkney Islands that are extremely deeply annotated. Approximately 1000 individuals in ORCADES have genomics, proteomics, lipidomics, glycomics, metabolomics, epigenomics, clinical risk factors and disease phenotypes, as well as body composition measurements from whole body scans. In addition to these cross-sectional omics and health related measures, these individuals also have linked electronic health records (EHR) available, allowing the assessment of the effect of these omics measures on incident disease over a ~10-year follow up period. In this thesis I use this phenotype rich resource to investigate the relationship between multiple types of omics measures and both ageing and health outcomes. First, I used the ORCADES data to construct measures of biological age (BA). The idea that there is an underlying rate at which the body deteriorates with age that varies between individuals of the same chronological age, this biological age, would be more indicative of health status, functional capacity and risk of age-related diseases than chronological age. Previous models estimating BA (ageing clocks) have predominantly been built using a single type of omics assay and comparison between different omics ageing clocks has been limited. I performed the most exhaustive comparison of different omics ageing clocks yet, with eleven clocks spanning nine different omics assays. I show that different omics clocks overlap in the information they provide about age, that some omics clocks track more generalised ageing while others track specific disease risk factors and that omics ageing clocks are prognostic of incident disease over and above chronological age. Second, I assessed whether individually or in multivariable models, omics measures are associated with health-related risk factors or prognostic of incident disease over 10 years post-assessment. I show that 2,686 single omics biomarkers are associated with 10 risk factors and 44 subsequent incident diseases. I also show that models built using multiple biomarkers from whole body scans, metabolomics, proteomics and clinical risk factors are prognostic of subsequent diabetes mellitus and that clinical risk factors are prognostic of incident hypertensive disorders, obesity, ischaemic heart disease and Framingham risk score. Third, I investigated the genetic architecture of a subset of the proteomics measures available in ORCADES, specifically 184 cardiovascular-related proteins. Combining genome-wide association (GWAS) summary statistics from ORCADES and 17 other cohorts from the SCALLOP Consortium, giving a maximum sample size of 26,494 individuals, I performed 184 genome-wide association meta-analyses (GWAMAs) on the levels of these proteins circulating in plasma. I discovered 592 independent significant loci associated with the levels of at least one protein. I found that between 8-37% of these significant loci colocalise with known expression quantitative trait loci (eQTL). I also find evidence of causal associations between 11 plasma protein levels and disease susceptibility using Mendelian randomisation, highlighting potential candidate drug targets

    Contemporary, decadal, and millennial-scale permafrost- and vegetation dynamics and carbon release in an alpine region of Jotunheimen, Norway

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    Climatic warming in northern alpine regions facilitates the thawing of permafrost, the associated release of soil carbon into the atmosphere, and the altitudinal shifts in vegetation patterns. Here, a multi-disciplinary approach is adopted to investigate the response of an alpine permafrost landscape (Jotunheimen, Norway, with focus on Galdhøpiggen) to climatic changes over long- to medium timescales. First, a gas analyser is used to explore how ecosystem respiration is affected by ecosystem (soil and vegetation) and geomorphological (cryogenic disturbance) factors during the peak growing season. A palaeoecological record is then analysed to infer the past dynamics of the alpine tree lines and the lower limit of permafrost on Galdhøpiggen over the millennial- and centennial scales. Finally, remotely sensed satellite imagery is combined with observed air temperatures to create a model that provides an estimation of land surface temperatures over the past six decades. The model is then used to predict surface ‘greenness’ over the same period. Palynological evidence from Galdhøpiggen indicates that the altitudinal limits of alpine tree lines have shifted by hundreds of metres in response to climatic changes over the millennial scale. Since 1957, the model predictions indicate substantial increases in land surface temperatures and growing season surface ‘greenness’ (i.e., vegetation abundance) in Jotunheimen, but the change has not been spatially uniform. The highest increases were recorded over the low- and mid-alpine heaths above the tree line (1050-1500 m a.s.l.), which was attributed to increased shrub cover. This trend could facilitate carbon release from the ground, as peak growing season ecosystem respiration was found to be most strongly controlled by soil microclimate and plant growth forms. The likely future scenario in response to warming in Jotunheimen will be continued permafrost degradation, with higher altitudes (≥1500 m a.s.l.) experiencing decreased cryoturbation, increased shrub encroachment and higher surface CO2 emissions
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