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Clean water is fundamental to human health and ecosystem integrity. However, water quality deteriorates due to novel anthropogenic pollutants present at microgram per liter concentrations in urban water cycles (termed micropollutants). Wastewater treatment plants (WWTP) have been identified as major point sources for aquatic (micro-)pollutants. Chemical and ecotoxicological analyses have shown that conventional biological WWTPs do not fully remove micropollutants and associated toxicities, which is often because of mobile, polar and/or recalcitrant compounds and transformation products (TPs). To minimize possible environmental risks, advanced wastewater treatment (AWWT) technologies could be a promising mitigation measure. Multiple processes are therefore being developed and evaluated such as ozonation and ozonation followed by granulated activated carbon (GAC) or biological filtration. Assessing the performance of these combined AWWTs was the focus the TransRisk project. Within this project, this thesis accomplished four major goals.
Firstly, the preparation of (waste)water samples was optimised for in vitro bioassays. Acidification, filtration and solid phase extraction (SPE) were tested for their impact on environmentally relevant in vitro endocrine activities, mutagenicity, genotoxicity and cytotoxicity. Significantly different outcomes of these assays were detected comparing neutral and acidified samples. Sample filtration had a lesser impact, but in some cases retention of particle-bound compounds could have caused significant toxicity losses. Out of three SPE sorbents the Telos C18/ENV at sample pH 2.5 extracted highest toxicity, some undetected in aqueous samples. These results indicate that sample preparation needs to be optimised for specific sample matrices and bioassays to avoid false-positive or -negative detects in effect-based analyses.
Secondly, the above listed in vitro toxicities were monitored in a protected region for drinking water production in South-West Germany (2012-2015). Out of 30 sampling sites surface water and groundwater were the least polluted. Nonetheless, a few groundwater samples induced high anti-estrogenic activity that prompted further monitoring. The latter included a waterworks in which no toxicity was detected. Hospital wastewater also had elevated in vitro toxicities and hospitals are, thus, relevant intervention points for source control. The biological WWTPs were effective in removing most of the detected toxicity, and the selected bioassays proved to be pertinent tools for water quality assessment and prioritisation of pollution hotspots.
Thirdly, the in vivo bioassay ISO10872 based on Caenorhabditis elegans (C. elegans) was adapted for this thesis. Using this model, a median effect concentration (EC50) for reproductive toxicity of the polycyclic aromatic hydrocarbon β-naphthoflavone (β- NF) of 114 µg/L was computed which is slightly lower than reported in the scientific literature. β-NF induced cyp-35A3::GFP (a biomarker in transgenic animals) in a time and concentration dependent manner (≤ 21.3–24 fold above controls). β-NF spiked wastewater samples supported earlier hypotheses on particle-bound pollutants. Reproductive toxicity (96 h) and cyp-35A3 induction (24 h) of biologically treated and/or ozonated wastewater extracts and growth promoting effects of GAC/biologically filtered ozonated wastewater extracts were observed. This suggested the presence of residual bioactive/toxic chemicals not included in the targeted chemical analysis. It also highlighted the importance of integrating multiple (apical and molecular) endpoints in wastewater assessments.
Fourthly, five in vitro and the adapted C. elegans bioassay were integrated into a wastewater quality evaluation (developed within TransRisk). Out of the five AWWT options, ozonation (at 1 g O3,applied/g DOC, HRT ~ 18 min) combined with nonaerated GAC filtration was rated most effective for toxicity removal. All five AWWTs largely removed estrogenic and (anti-)androgenic activities, but not anti-estrogenic activity and mutagenicity, which even increased during ozonation. This has been observed in related studies and points towards toxic TPs. These results also emphasized the need for implementing an effective post-treatment for ozonation. The results from a parallel in vivo study with Lumbriculus variegatus and Potamopyrgus antipodarum conducted on site at the WWTP (using flow through systems) were in accordance with the C. elegans results. In this context, it is suggested to further implement C. elegans as sensitive, feasible and ecologically relevant model.
In conclusion, this thesis shows how optimised sample preparation, long-term (in vitro) environmental monitoring, sensitive and ecologically relevant (in vivo) bioassays as well as innovative evaluation concepts, are pivotal in improving the removal of micropollutants and their toxicities with AWWTs. Future research should further develop and evaluate measures at sewer systems, conventional biological, tertiary and other advanced treatment technologies, as well as sociopolitical strategies (e.g., source control or natural conservation) and restoration projects. The effect-based tools optimised in this thesis will support assessing their success.
Bacterial biosynthetic assembly lines, such as non-ribosomal peptide synthetases (NRPS) and polyketide synthases, are often subject of synthetic biology – because they produce a variety of natural products invaluable for modern pharmacotherapy. Acquiring the ability to engineer these biosynthetic assembly lines allows the production of artificial non-ribosomal peptides (NRP), polyketides, and hybrids thereof with new or improved properties. However, traditional bioengineering approaches have suffered for decades from their very limited applicability and, unlike combinatorial chemistry, are stigmatized as inefficient because they cannot be linked to the high-throughput screening platforms of the pharmaceutical industry. Although combinatorial chemistry can generate new molecules cheaper, faster, and in greater numbers than traditional natural product discovery and bioengineering approaches, it does not meet current medical needs because it covers only a limited biologically relevant chemical space. Hence, methods for high-throughput generation of new natural product-like compound libraries could provide a new avenue towards the identification of new lead compounds. To this end, prior to this work, we introduced an artificial synthetic NRPS type, referred to as type S NRPS, to provide a first-of-its-kind bicombinatorial approach to parallelized high-throughput NRP library generation. However, a bottleneck of these first two generations of type S NRPS was a significant drop in production yields. To address this issue, we applied an iterative optimization process that enabled titer increases of up to 55-fold compared to the non-optimized equivalents, restoring them to wild-type levels and beyond.
Neuronale Repräsentation intrinsischer cochleärer Signale im Colliculus inferior der Wüstenrennmaus
(2008)
Die vorliegende Arbeit untersucht die neuronale Repräsentation von cochleären Verzerrungsprodukten im auditorischen Mittelhirn der Wüstenrennmaus. Die hohe Sensitivität und die gute Frequenzauflösung des Hörorgans der Säugetiere basiert auf einer aktiven mechanischen Verstärkung der schallinduzierten Basilarmembranschwingung im Innenohr. Die äußeren Haarsinneszellen, die während des Transduktionsprozesses zyklisch ihre Länge ändern und dabei zusätzliche Schwingungsenergie in das System zurückführen, sind der zugrunde liegende Motor des aktiven cochleären Verstärkers. Die stark nichtlinearen Eigenschaften dieses Verstärkers führen allerdings bei gleichzeitiger Verstärkung mehrerer Frequenzkomponenten zur Generierung von Kombinationsschwingungen, welche im Ursprungssignal nicht vorhanden sind. Wird das Ohr beispielsweise durch zwei Töne mit den Frequenzen f1 und f2 stimuliert (f1<f2), so entstehen verschiedene Kombinationsschwingungen, deren prominenteste das quadratische (f2-f1) und das cubische (2 f1-f2) Verzerrungsprodukt sind. Diese Verzerrungen des Ursprungssignals breiten sich von ihrem Entstehungsort im Innenohr, dem Überlappungsbereich der Stimuluswanderwellen, im Flüssigkeitsraum der Cochlea aus und werden über das Mittelohr in den Gehörgang übertragen. Im Gehörgang sind sie mit Hilfe eines sensitiven Mikrophons als otoakustische Emissionen (DPOAE - distortion product otoacoustic emissions) messbar. Zusätzlich bilden sie an ihrem Resonanzort auf der Basilarmembran, vergleichbar mit einem externen Stimuluston gleicher Frequenz, eine eigene Wanderwelle aus und aktivieren den Transduktionsprozess. Die neuronalen Korrelate der cochleären Verzerrungsprodukte sind auf verschiedenen Stationen der Hörbahn messbar und cochleäre Verzerrungsprodukte können als separate Töne wahrgenommen werden. In der vorliegenden Arbeit wurden die neuronalen Korrelate und otoakustischen Emissionen von cochleären Verzerrungsprodukten erstmals simultan bestimmt. Durch den direkten Vergleich der neuronalen Aktivität mit der peripheren Emissionsmessung sollen eventuelle zentralnervöse Veränderungen der Repräsentation der cochleären Verzerrungsprodukte untersucht werden. Dazu wurde die elektrische Aktivität von 91 Neuronen des Colliculus inferior der Wüstenrennmaus während der Stimulation durch zwei hochfrequente Stimulustöne gemessen. Die Frequenzen der Stimulustöne waren so gewählt, dass die Frequenz eines, durch sie evozierten Verzerrungsproduktes, mit der charakteristischen Frequenz des jeweiligen Neurons übereinstimmte. In 95 % aller Messungen konnte eine robuste neuronale Aktivität während Zweitonstimulation gemessen werden, die sich auf die Stimulation durch ein spezifisches cochleäres Verzerrungsprodukt zurückführen lässt. Bei einem Teil der Versuche wurden die Verzerrungsprodukte durch direkte intracochleäre Auslöschung mit einem dritten Tonstimulus eindeutig als Quelle der neuronalen Aktivität bestätigt. Für Verzerrungsproduktfrequenzen oberhalb 1,3 kHz lassen sich die Antworten der Neurone im schwellennahen Bereich gut mit den simultan im Gehörgang bestimmten DPOAE-Pegeln erklären, was einen engen Zusammenhang zwischen intracochleärem Verzerrungsproduktpegel und DPOAE-Pegel nahe legt. Bei höheren Stimuluspegeln konnten die maximalen neuronalen Antworten auf den intracochleären Verzerrungsproduktstimulus signifikant von der Einzeltonantwort abweichen, wobei sowohl eine Erhöhung als auch eine Reduktion der Maximalantwort möglich war. Ein inhibitorischer bzw. verstärkender Einfluss der Stimulustöne auf die neuronale Verzerrungsproduktantwort wird als mögliche Ursache der Unterschiede diskutiert. Für Verzerrungsproduktfrequenzen unterhalb 1,3 kHz wurde ein deutlicher Unterschied zwischen dem intracochleären Verzerrungsproduktpegel und dem im Gehörgang gemessenen Emissionspegel deutlich. Ein Teil der getesteten tieffrequenten Neurone antwortete während Zweitonstimulation bereits für Stimuluspegel, die unterhalb der Reintonschwelle des Neurons lagen. Eine frequenzspezifische Verschlechterung der Mittelohrübertragungsleistung bei tiefen Frequenzen wird als mögliche Ursache für die unterschwelligen Antworten der Neurone diskutiert. Die Ergebnisse der vorliegenden Arbeit zeigen, dass cochleäre Verzerrungsprodukte einen substanziellen Anteil an der neuronalen Repräsentation von komplexen Stimuli haben können. Im Besonderen machen die vorgestellten Daten deutlich, dass die neuronalen Repräsentation der Grundfrequenz eines komplexen Klangs wesentlich von cochleären Verzerrungsprodukten beeinflusst sein kann. Dies bedeutet, dass bereits im Innenohr Tonhöheninformation extrahiert werden kann und damit die Relevanz in der Literatur diskutierter neuronaler Mechanismen zur Berechnung von Tonhöhe relativiert wird.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions, using signals from nanopore direct RNA sequencing. CHEUI processes observed and expected signals with convolutional neural networks to achieve high single-molecule accuracy and outperform other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A significant roadblock hindering progress in epitranscriptomics is the identification of more than one modification in individual transcript molecules. We address this with CHEUI (CH3 (methylation) Estimation Using Ionic current). CHEUI predicts N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual molecules from the same sample, the stoichiometry at transcript reference sites, and differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals to achieve high single-molecule, transcript-site, and stoichiometry accuracies in multiple tests using synthetic RNA standards and cell line data. CHEUI’s capability to identify two modification types in the same sample reveals a co-occurrence of m6A and m5C in individual mRNAs in cell line and tissue transcriptomes. CHEUI provides new avenues to discover and study the function of the epitranscriptome.