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Institute
- Institut für Biochemie und Biologie (26)
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- Institut für Physik und Astronomie (21)
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- Hasso-Plattner-Institut für Digital Engineering GmbH (17)
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- Department Sport- und Gesundheitswissenschaften (7)
- Department Psychologie (6)
- Institut für Ernährungswissenschaft (6)
With the recent growth of sensors, cloud computing handles the data processing of many applications. Processing some of this data on the cloud raises, however, many concerns regarding, e.g., privacy, latency, or single points of failure. Alternatively, thanks to the development of embedded systems, smart wireless devices can share their computation capacity, creating a local wireless cloud for in-network processing. In this context, the processing of an application is divided into smaller jobs so that a device can run one or more jobs.
The contribution of this thesis to this scenario is divided into three parts. In part one, I focus on wireless aspects, such as power control and interference management, for deciding which jobs to run on which node and how to route data between nodes. Hence, I formulate optimization problems and develop heuristic and meta-heuristic algorithms to allocate wireless and computation resources. Additionally, to deal with multiple applications competing for these resources, I develop a reinforcement learning (RL) admission controller to decide which application should be admitted. Next, I look into acoustic applications to improve wireless throughput by using microphone clock synchronization to synchronize wireless transmissions.
In the second part, I jointly work with colleagues from the acoustic processing field to optimize both network and application (i.e., acoustic) qualities. My contribution focuses on the network part, where I study the relation between acoustic and network qualities when selecting a subset of microphones for collecting audio data or selecting a subset of optional jobs for processing these data; too many microphones or too many jobs can lessen quality by unnecessary delays. Hence, I develop RL solutions to select the subset of microphones under network constraints when the speaker is moving while still providing good acoustic quality. Furthermore, I show that autonomous vehicles carrying microphones improve the acoustic qualities of different applications. Accordingly, I develop RL solutions (single and multi-agent ones) for controlling these vehicles.
In the third part, I close the gap between theory and practice. I describe the features of my open-source framework used as a proof of concept for wireless in-network processing. Next, I demonstrate how to run some algorithms developed by colleagues from acoustic processing using my framework. I also use the framework for studying in-network delays (wireless and processing) using different distributions of jobs and network topologies.
This thesis explores the variation in coreference patterns across language modes (i.e., spoken and written) and text genres. The significance of research on variation in language use has been emphasized in a number of linguistic studies. For instance, Biber and Conrad [2009] state that “register/genre variation is a fundamental aspect of human language” and “Given the ubiquity of register/genre variation, an understanding of how linguistic features are used in patterned ways across text varieties is of central importance for both the description of particular languages and the development of cross-linguistic theories of language use.”[p.23]
We examine the variation across genres with the primary goal of contributing to the body of knowledge on the description of language use in English. On the computational side, we believe that incorporating linguistic knowledge into learning-based systems can boost the performance of automatic natural language processing systems, particularly for non-standard texts. Therefore, in addition to their descriptive value, the linguistic findings we provide in this study may prove to be helpful for improving the performance of automatic coreference resolution, which is essential for a good text understanding and beneficial for several downstream NLP applications, including machine translation and text summarization.
In particular, we study a genre of texts that is formed of conversational interactions on the well-known social media platform Twitter. Two factors motivate us: First, Twitter conversations are realized in written form but resemble spoken communication [Scheffler, 2017], and therefore they form an atypical genre for the written mode. Second, while Twitter texts are a complicated genre for automatic coreference resolution, due to their widespread use in the digital sphere, at the same time they are highly relevant for applications that seek to extract information or sentiments from users’ messages. Thus, we are interested in discovering more about the linguistic and computational aspects of coreference in Twitter conversations. We first created a corpus of such conversations for this purpose and annotated it for coreference. We are interested in not only the coreference patterns but the overall discourse behavior of Twitter conversations. To address this, in addition to the coreference relations, we also annotated the coherence relations on the corpus we compiled. The corpus is available online in a newly developed form that allows for separating the tweets from their annotations.
This study consists of three empirical analyses where we independently apply corpus-based, psycholinguistic and computational approaches for the investigation of variation in coreference patterns in a complementary manner. (1) We first make a descriptive analysis of variation across genres through a corpus-based study. We investigate the linguistic aspects of nominal coreference in Twitter conversations and we determine how this genre relates to other text genres in spoken and written modes. In addition to the variation across genres, studying the differences in spoken-written modes is also in focus of linguistic research since from Woolbert [1922]. (2) In order to investigate whether the language mode alone has any effect on coreference patterns, we carry out a crowdsourced experiment and analyze the patterns in the same genre for both spoken and written modes. (3) Finally, we explore the potentials of domain adaptation of automatic coreference resolution (ACR) for the conversational Twitter data. In order to answer the question of how the genre of Twitter conversations relates to other genres in spoken and written modes with respect to coreference patterns, we employ a state-of-the-art neural ACR model [Lee et al., 2018] to examine whether ACR on Twitter conversations will benefit from mode-based separation in out-of-domain training data.
Insight by de—sign
(2023)
The calculus of design is a diagrammatic approach towards the relationship between design and insight. The thesis I am evolving is that insights are not discovered, gained, explored, revealed, or mined, but are operatively de—signed. The de in design neglects the contingency of the space towards the sign. The — is the drawing of a distinction within the operation. Space collapses through the negativity of the sign; the command draws a distinction that neglects the space for the form's sake. The operation to de—sign is counterintuitively not the creation of signs, but their removal, the exclusion of possible sign propositions of space. De—sign is thus an act of exclusion; the possibilities of space are crossed into form.
Planets outside our solar system, so-called "exoplanets", can be detected with different methods, and currently more than 5000 exoplanets have been confirmed, according to NASA Exoplanet Archive. One major highlight of the studies on exoplanets in the past twenty years is the characterization of their atmospheres usingtransmission spectroscopy as the exoplanet transits. However, this characterization is a challenging process and sometimes there are reported discrepancies in the literature regarding the atmosphere of the same exoplanet. One potential reason for the observed atmospheric inconsistencies is called impact parameter degeneracy, and it is highly driven by the limb darkening effect of the host star. A brief introductionto those topics in presented in chapter 1, while the motivation and objectives of thiswork are described in chapter 2.The first goal is to clarify the origin of the transmission spectrum, which is anindicator of an exoplanet’s atmosphere; whether it is real or influenced by the impactparameter degeneracy. A second goal is to determine whether photometry from space using the Transiting Exoplanet Survey Satellite (TESS), could improve on the major parameters, which are responsible for the aforementioned degeneracy, of known exoplanetary systems. Three individual projects were conducted in order toaddress those goals. The three manuscripts are presented, in short, in the manuscriptoverview in chapter 3.More specifically, in chapter 4, the first manuscript is presented, which is an ex-tended investigation on the impact parameter degeneracy and its application onsynthetic transmission spectra. Evidently, the limb darkening of the host star isan important driver for this effect. It keeps the degeneracy persisting through different groups of exoplanets, based on the uncertainty of their impact parameter and on the type of their host star. The second goal, was addressed in the second and third manuscripts (chapter 5 and chapter 6 respectively). Using observationsfrom the TESS mission, two samples of exoplanets were studied; 10 transiting inflated hot-Jupiters and 43 transiting grazing systems. Potentially, the refinement or confirmation of their major system parameters’ measurements can assist in solving current or future discrepancies regarding their atmospheric characterization.In chapter 7 the conclusions of this work are discussed, while in chapter 8 itis proposed how TESS’s measurements can be able to discern between erroneousinterpretations of transmission spectra, especially on systems where the impact parameter degeneracy is likely not applicable.
The electrical resistivity tomography (ERT) method is widely used to investigate geological, geotechnical, and hydrogeological problems in inland and aquatic environments (i.e., lakes, rivers, and seas). The objective of the ERT method is to obtain reliable resistivity models of the subsurface that can be interpreted in terms of the subsurface structure and petrophysical properties. The reliability of the resulting resistivity models depends not only on the quality of the acquired data, but also on the employed inversion strategy. Inversion of ERT data results in multiple solutions that explain the measured data equally well. Typical inversion approaches rely on different deterministic (local) strategies that consider different smoothing and damping strategies to stabilize the inversion. However, such strategies suffer from the trade-off of smearing possible sharp subsurface interfaces separating layers with resistivity contrasts of up to several orders of magnitude. When prior information (e.g., from outcrops, boreholes, or other geophysical surveys) suggests sharp resistivity variations, it might be advantageous to adapt the parameterization and inversion strategies to obtain more stable and geologically reliable model solutions. Adaptations to traditional local inversions, for example, by using different structural and/or geostatistical constraints, may help to retrieve sharper model solutions. In addition, layer-based model parameterization in combination with local or global inversion approaches can be used to obtain models with sharp boundaries.
In this thesis, I study three typical layered near-surface environments in which prior information is used to adapt 2D inversion strategies to favor layered model solutions. In cooperation with the coauthors of Chapters 2-4, I consider two general strategies. Our first approach uses a layer-based model parameterization and a well-established global inversion strategy to generate ensembles of model solutions and assess uncertainties related to the non-uniqueness of the inverse problem. We apply this method to invert ERT data sets collected in an inland coastal area of northern France (Chapter~2) and offshore of two Arctic regions (Chapter~3). Our second approach consists of using geostatistical regularizations with different correlation lengths. We apply this strategy to a more complex subsurface scenario on a local intermountain alluvial fan in southwestern Germany (Chapter~4). Overall, our inversion approaches allow us to obtain resistivity models that agree with the general geological understanding of the studied field sites. These strategies are rather general and can be applied to various geological environments where a layered subsurface structure is expected. The flexibility of our strategies allows adaptations to invert other kinds of geophysical data sets such as seismic refraction or electromagnetic induction methods, and could be considered for joint inversion approaches.
Background: Physical fitness is a key aspect of children’s ability to perform activities of daily living, engage in leisure activities, and is associated with important health characteristics. As such, it shows multi-directional associations with weight status as well as executive functions, and varies according to a variety of moderating factors, such as the child’s gender, age, geographical location, and socioeconomic conditions and context. The assessment and monitoring of children’s physical fitness has gained attention in recent decades, as has the question of how to promote physical fitness through the implementation of a variety of programs and interventions. However, these programs and interventions rarely focus on children with deficits in their physical fitness. Due to their deficits, these children are at the highest risk of suffering health impairments compared to their more average fit peers. In efforts to promote physical fitness, schools could offer promising and viable approaches to interventions, as they provide access to large youth populations while providing useful infrastructure. Evidence suggests that school-based physical fitness interventions, particularly those that include supplementary physical education, are useful for promoting and improving physical fitness in children with normal fitness. However, there is little evidence on whether these interventions have similar or even greater effects on children with deficits in their physical fitness. Furthermore, the question arises whether these measures help to sustainably improve the development/trajectories of physical fitness in these children.
The present thesis aims to elucidate the following four objectives: (1) to evaluate the effects of a 14 week intervention with 2 x 45 minutes per week additional remedial physical education on physical fitness and executive function in children with deficits in their physical fitness; (2) to assess moderating effects of body height and body mass on physical fitness components in children with physical fitness deficits; (3) to assess moderating effects of age and skeletal growth on physical fitness in children with physical fitness deficits; and (4) to analyse moderating effects of different physical fitness components on executive function in children with physical fitness deficits.
Methods: Using physical fitness data from the EMOTIKON study, 76 third graders with physical fitness deficits were identified in 11 schools in Brandenburg state that met the requirements for implementing a remedial physical education intervention (i.e., employing specially trained physical education teachers). The fitness intervention was implemented in a cross-over design and schools were randomly assigned to either an intervention-control or control-intervention group. The remedial physical education intervention consisted of a 14 week, 2 x 45 minutes per week remedial physical education curriculum supplemented by a physical exercise homework program. Assessments were conducted at the beginning and end of each intervention and control period, and further assessments were conducted at the beginning and end of each school year until the end of sixth grade. Physical fitness as the primary outcome was assessed using fitness tests implemented in the EMOTIKON study (i.e., lower body muscular strength (standing long jump), speed (20 m sprint), cardiorespiratory fitness (6 min run), agility (star run), upper body muscular strength (ball push test), and balance (one leg balance)). Executive functions as a secondary outcome were assessed using attention and psychomotor processing speed (digit symbol substitution test), mental flexibility and fine motor skills (trail making test), and inhibitory control (Simon task). Anthropometric measures such as body height, body mass, maturity offset, and body composition parameters, as well as socioeconomic information were recorded as potential moderators.
Results: (1) The evaluation of possible effects of the remedial physical education intervention on physical fitness and executive functions of children with deficits in their physical fitness did not reveal any detectable intervention-related improvements in physical fitness or executive functions. The implemented analysis strategies also showed moderating effects of body mass index (BMI) on performance in 6 min run, star run, and standing long jump, with children with a lower BMI performing better, moderating effects of proximity to Berlin on performance in the 6 min run and standing long jump, better performances being found in children living closer to Berlin, and overall gendered differences in executive function test performance, with boys performing better compared to girls. (2) Analysing moderating effects of body height and body mass on physical fitness performance, better overall physical fitness performance was found for taller children. For body mass, a negative effect was found on performance in the 6 min run (linear), standing long jump (linear), and 20 m sprint (quadratic), with better performance associated with lighter children, and a positive effect of body mass on performance in the ball push test, with heavier children performing better. In addition, the analysis revealed significant interactions between body height and body mass on performance in 6 min run and 20 m sprint, with higher body mass being associated with performance improvements in larger children, while higher body mass was associated with performance declines in smaller children. In addition, the analysis revealed overall age-related improvements in physical fitness and was able to show that children with better overall physical fitness also elicit greater age-related improvements. (3) In the analysis of moderating effects of age and maturity offset on physical fitness performances, two unrotated principal components of z-transformed age and maturity offset values were calculated (i.e., relative growth = (age + maturity offset)/2; growth delay = (age - maturity offset)) to avoid colinearity. Analysing these constructs revealed positive effects of relative growth on performances in star run, 20 m sprint, and standing long jump, with children of higher relative growth performing better. For growth delay, positive effects were found on performances in 6 min run and 20 m sprint, with children having larger growth delays showing better performances. Further, the model revealed gendered differences in 6 min run and 20 m sprint performances with girls performing better than boys. (4) Analysing the effects of physical fitness tests on executive function revealed a positive effect of star run and one leg balance performance and a negative effect of 6 min run performance on reaction speed in the Simon task. However, these effects were not detectable when individual differences were accounted for. Then these effects showed overall positive effects, with better performances being associated with faster reaction speeds. In addition, the analysis revealed a positive correlation between overall reaction speed and effects of the 6 min run, suggesting that children with greater effects of 6 min run had faster overall reaction speeds. Negative correlations were found between star run effects and age effects on Simon task reaction speed, meaning that children with larger star run effects had smaller age effects, and between 6 min run effects and star run effects on Simon task reaction speed, meaning that children with larger 6 min run effects tended to have smaller star run effects on Simon task reaction speed and vice versa.
Conclusions: (1) The lack of detectable intervention-related effects could have been caused by an insufficient intervention period, by the implementation of comprehensive and thus non- specific exercises, or by both. Accordingly, longer intervention periods and/or more specific exercises may have been more beneficial and could have led to detectable improvements in physical fitness and/or executive function. However, it remains unclear whether these interventions can benefit children with deficits in physical fitness, as it is possible that their deficits are not caused by a mere lack of exercise, but rather depend on the socioeconomic conditions of the children and their families and areas. Therefore, further research is needed to assess the moderation of physical fitness in children with physical fitness deficits and, in particular, the links between children’s environment and their physical fitness trajectories. (2) Findings from this work suggest that using BMI as a composite of body height and body mass may not be able to capture the variation associated with these parameters and their interactions. In particular, because of their multidirectional associations, further research would help elucidate how BMI and its subcomponents influence physical fitness and how they vary between children with and without physical fitness deficits. (3) The assessment of growth- related changes indicated negative effects associated with the growth spurt approaching age of peak height velocity, and furthermore showed significant differences in these effects between children. Thus, these effects and possible interindividual differences should be considered in the assessment of the development of physical fitness in children. (4) Furthermore, this work has shown that the associations between physical fitness and executive functions vary between children and may be moderated by children’s socioeconomic conditions and the structure of their daily activities. Further research is needed to explore these associations using approaches that account for individual variance.
Im Rahmen dieser Dissertation wurden die erstmaligen Totalsynthesen der Arylnaphthalen-Lignane Alashinol D, Vitexdoin C, Vitrofolal E, Noralashinol C1 und Ternifoliuslignan E vorgestellt. Der Schlüsselschritt der entwickelten Methode, basiert auf einer regioselektiven intramolekularen Photo-Dehydro-Diels-Alder (PDDA)-Reaktion, die mittels UV-Strahlung im Durchflussreaktor durchgeführt wurde. Bei der Synthese der PDDA-Vorläufer (Diarylsuberate) wurde eine Synthesestrategie nach dem Baukastenprinzip verfolgt. Diese ermöglicht die Darstellung asymmetrischer komplexer Systeme aus nur wenigen Grundbausteinen und die Totalsynthese einer Vielzahl an Lignanen. In systematischen Voruntersuchungen konnte zudem die klare Überlegenheit der intra- gegenüber der intermolekularen PDDA-Reaktion aufgezeigt werden. Dabei stellte sich eine Verknüpfung der beiden Arylpropiolester über einen Korksäurebügel, in para-Position, als besonders effizient heraus. Werden asymmetrisch substituierte Diarylsuberate, bei denen einer der endständigen Estersubstituenten durch eine Trimethylsilyl-Gruppe oder ein Wasserstoffatom ersetzt wurde, verwendet, durchlaufen diese Systeme eine regioselektive Cyclisierung und als Hauptprodukt werden Naphthalenophane mit einem Methylester in 3-Position erhalten. Mit Hilfe von umfangreichen Experimenten zur Funktionalisierung der 4-Position, konnte zudem gezeigt werden, dass die Substitution der nucleophilen Cycloallen-Intermediate, während der PDDA-Reaktion, generell durch die Zugabe von N-Halogen-Succinimiden möglich ist. In Anbetracht der geringen Ausbeuten haben diese intermolekularen Abfangreaktionen, jedoch keinen präparativen Nutzen für die Totalsynthesen von Lignanen. Mit dem Ziel die allgemeinen photochemischen Reaktionsbedingungen zu optimieren, wurde erstmalig die triplettsensibilisierte PDDA-Reaktion vorgestellt. Durch die Verwendung von Xanthon als Sensibilisator wurde der Einsatz von effizienteren UVA-Lichtquellen ermöglicht, wodurch die Gefahr einer Photozersetzung durch Überbestrahlung minimiert wurde. Im Vergleich zur direkten Anregung mit UVB-Strahlung, konnten die Ausbeuten mit indirekter Anregung durch einen Photokatalysator signifikant gesteigert werden. Die grundlegenden Erkenntnisse und die entwickelten Synthesestrategien dieser Arbeit, können dazu beitragen zukünftig die Erschließung neuer pharmakologisch interessanter Lignane voranzutreiben.
1 Bisher ist nur die semisynthetische Darstellung von Noralashinol C ausgehend von Hydroxymatairesinol literaturbekannt.
In the last two decades, process mining has developed from a niche
discipline to a significant research area with considerable impact on academia and industry. Process mining enables organisations to identify the running business processes from historical execution data. The first requirement of any process mining technique is an event log, an artifact that represents concrete business process executions in the form of sequence of events. These logs can be extracted from the organization's information systems and are used by process experts to retrieve deep insights from the organization's running processes. Considering the events pertaining to such logs, the process models can be automatically discovered and enhanced or annotated with performance-related information. Besides behavioral information, event logs contain domain specific data, albeit implicitly. However, such data are usually overlooked and, thus, not utilized to their full potential.
Within the process mining area, we address in this thesis the research gap of discovering, from event logs, the contextual information that cannot be captured by applying existing process mining techniques. Within this research gap, we identify four key problems and tackle them by looking at an event log from different angles. First, we address the problem of deriving an event log in the absence of a proper database access and domain knowledge. The second problem is related to the under-utilization of the implicit domain knowledge present in an event log that can increase the understandability of the discovered process model. Next, there is a lack of a holistic representation of the historical data manipulation at the process model level of abstraction. Last but not least, each process model presumes to be independent of other process models when discovered from an event log, thus, ignoring possible data dependencies between processes within an organization.
For each of the problems mentioned above, this thesis proposes a dedicated method. The first method provides a solution to extract an event log only from the transactions performed on the database that are stored in the form of redo logs. The second method deals with discovering the underlying data model that is implicitly embedded in the event log, thus, complementing the discovered process model with important domain knowledge information. The third method captures, on the process model level, how the data affects the running process instances. Lastly, the fourth method is about the discovery of the relations between business processes (i.e., how they exchange data) from a set of event logs and explicitly representing such complex interdependencies in a business process architecture.
All the methods introduced in this thesis are implemented as a prototype and their feasibility is proven by being applied on real-life event logs.
Recurrences in past climates
(2023)
Our ability to predict the state of a system relies on its tendency to recur to states it has visited before. Recurrence also pervades common intuitions about the systems we are most familiar with: daily routines, social rituals and the return of the seasons are just a few relatable examples. To this end, recurrence plots (RP) provide a systematic framework to quantify the recurrence of states. Despite their conceptual simplicity, they are a versatile tool in the study of observational data. The global climate is a complex system for which an understanding based on observational data is not only of academical relevance, but vital for the predurance of human societies within the planetary boundaries. Contextualizing current global climate change, however, requires observational data far beyond the instrumental period. The palaeoclimate record offers a valuable archive of proxy data but demands methodological approaches that adequately address its complexities. In this regard, the following dissertation aims at devising novel and further developing existing methods in the framework of recurrence analysis (RA). The proposed research questions focus on using RA to capture scale-dependent properties in nonlinear time series and tailoring recurrence quantification analysis (RQA) to characterize seasonal variability in palaeoclimate records (‘Palaeoseasonality’).
In the first part of this thesis, we focus on the methodological development of novel approaches in RA. The predictability of nonlinear (palaeo)climate time series is limited by abrupt transitions between regimes that exhibit entirely different dynamical complexity (e.g. crossing of ‘tipping points’). These possibly depend on characteristic time scales. RPs are well-established for detecting transitions and capture scale-dependencies, yet few approaches have combined both aspects. We apply existing concepts from the study of self-similar textures to RPs to detect abrupt transitions, considering the most relevant time scales. This combination of methods further results in the definition of a novel recurrence based nonlinear dependence measure. Quantifying lagged interactions between multiple variables is a common problem, especially in the characterization of high-dimensional complex systems. The proposed ‘recurrence flow’ measure of nonlinear dependence offers an elegant way to characterize such couplings. For spatially extended complex systems, the coupled dynamics of local variables result in the emergence of spatial patterns. These patterns tend to recur in time. Based on this observation, we propose a novel method that entails dynamically distinct regimes of atmospheric circulation based on their recurrent spatial patterns. Bridging the two parts of this dissertation, we next turn to methodological advances of RA for the study of Palaeoseasonality. Observational series of palaeoclimate ‘proxy’ records involve inherent limitations, such as irregular temporal sampling. We reveal biases in the RQA of time series with a non-stationary sampling rate and propose a correction scheme.
In the second part of this thesis, we proceed with applications in Palaeoseasonality. A review of common and promising time series analysis methods shows that numerous valuable tools exist, but their sound application requires adaptions to archive-specific limitations and consolidating transdisciplinary knowledge. Next, we study stalagmite proxy records from the Central Pacific as sensitive recorders of mid-Holocene El Niño-Southern Oscillation (ENSO) dynamics. The records’ remarkably high temporal resolution allows to draw links between ENSO and seasonal dynamics, quantified by RA. The final study presented here examines how seasonal predictability could play a role for the stability of agricultural societies. The Classic Maya underwent a period of sociopolitical disintegration that has been linked to drought events. Based on seasonally resolved stable isotope records from Yok Balum cave in Belize, we propose a measure of seasonal predictability. It unveils the potential role declining seasonal predictability could have played in destabilizing agricultural and sociopolitical systems of Classic Maya populations.
The methodological approaches and applications presented in this work reveal multiple exciting future research avenues, both for RA and the study of Palaeoseasonality.
Increasing demand for food, healthcare, and transportation arising from the growing world population is accompanied by and driving global warming challenges due to the rise of the atmospheric CO2 concentration. Industrialization for human needs has been increasingly releasing CO2 into the atmosphere for the last century or more. In recent years, the possibility of recycling CO2 to stabilize the atmospheric CO2 concentration and combat rising temperatures has gained attention. Thus, using CO2 as the feedstock to address future world demands is the ultimate solution while controlling the rapid climate change. Valorizing CO2 to produce activated and stable one-carbon feedstocks like formate and methanol and further upgrading them to industrial microbial processes to replace unsustainable feedstocks would be crucial for a future biobased circular economy. However, not all microbes can grow on formate as a feedstock, and those microbes that can grow are not well established for industrial processes.
S. cerevisiae is one of the industrially well-established microbes, and it is a significant contributor to bioprocess industries. However, it cannot grow on formate as a sole carbon and energy source. Thus, engineering S. cerevisiae to grow on formate could potentially pave the way to sustainable biomass and value-added chemicals production.
The Reductive Glycine Pathway (RGP), designed as the aerobic twin of the anaerobic Reductive Acetyl-CoA pathway, is an efficient formate and CO2 assimilation pathway. The RGP comprises of the glycine synthesis module (Mis1p, Gcv1p, Gcv2p, Gcv3p, and Lpd1p), the glycine to serine conversion module (Shmtp), the pyruvate synthesis module (Cha1p), and the energy supply module (Fdh1p). The RGP requires formate and elevated CO2 levels to operate the glycine synthesis module. In this study, I established the RGP in the yeast system using growth-coupled selection strategies to achieve formate and CO2-dependent biomass formation in aerobic conditions.
Firstly, I constructed serine biosensor strains by disrupting the native serine and glycine biosynthesis routes in the prototrophic S288c and FL100 yeast strains and insulated serine, glycine, and one-carbon metabolism from the central metabolic network. These strains cannot grow on glucose as the sole carbon source but require the supply of serine or glycine to complement the engineered auxotrophies. Using growth as a readout, I employed these strains as selection hosts to establish the RGP. Initially, to achieve this, I engineered different serine-hydroxymethyltransferases in the genome of serine biosensor strains for efficient glycine to serine conversion. Then, I implemented the glycine synthesis module of the RGP in these strains for the glycine and serine synthesis from formate and CO2. I successfully conducted Adaptive Laboratory Evolution (ALE) using these strains, which yielded a strain capable of glycine and serine biosynthesis from formate and CO2. Significant growth improvements from 0.0041 h-1 to 0.03695 h-1 were observed during ALE. To validate glycine and serine synthesis, I conducted carbon tracing experiments with 13C formate and 13CO2, confirming that more than 90% of glycine and serine biosynthesis in the evolved strains occurs via the RGP. Interestingly, labeling data also revealed that 10-15% of alanine was labelled, indicating pyruvate synthesis from the formate-derived serine using native serine deaminase (Cha1p) activity. Thus, RGP contributes to a small pyruvate pool which is converted to alanine without any selection pressure for pyruvate synthesis from formate. Hence, this data confirms the activity of all three modules of RGP even in the presence of glucose. Further, ALE in glucose limiting conditions did not improve pyruvate flux via the RGP.
Growth characterization of these strains showed that the best growth rates were achieved in formate concentrations between 25 mM to 300 mM. Optimum growth required 5% CO2, and dropped when the CO2 concentration was reduced from 5% to 2.5%.
Whole-genome sequencing of these evolved strains revealed mutations in genes that encode Gdh1p, Pet9p, and Idh1p. These enzymes might influence intracellular NADPH, ATP, and NADH levels, indicating adjustment to meet the energy demand of the RGP. I reverse-engineered the GDH1 truncation mutation on unevolved serine biosensor strains and reproduced formate dependent growth. To elucidate the effect of the GDH1 mutation on formate assimilation, I reintroduced this mutation in the S288c strain and conducted carbon-tracing experiments to compared formate assimilation between WT and ∆gdh1 mutant strains. Comparatively, enhanced formate assimilation was recorded in the ∆gdh1 mutant strain.
Although the 13C carbon tracing experiments confirmed the activity of all three modules of the RGP, the overall pyruvate flux via the RGP might be limited by the supply of reducing power. Hence, in a different approach, I overexpressed the formate dehydrogenase (Fdh1p) for energy supply and serine deaminase (Cha1p) for active pyruvate synthesis in the S288c parental strain and established growth on formate and serine without glucose in the medium. Further reengineering and evolution of this strain with a consistent energy, and formate-derived serine supply for pyruvate synthesis, is essential to achieve complete formatotrophic growth in the yeast system.