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Institute
How the brain evolved remains a mystery. The goal of this thesis is to understand the fundamental processes that are behind the evolutionary history of the brain. Amniotes appeared 320 million years ago with the transition from water to land. This early group bifurcated into sauropsids (reptiles and birds) and synapsids (mammals). Amniote brains evolved separately and display obvious structural and functional differences. Although those differences reflect brain diversification, all amniote brains share a common ancestor and their brains show multiple derived similarities: equivalent structures, networks, circuits and cell types have been preserved during millions of years. Finding these differences and similarities will help us understand brain historical evolution and function. Studying brain evolution can be approached from various levels, including brain structure, circuits, cell types, and genes. We propose a focus on cell types for a more comprehensive understanding of brain evolution. Neurons are the basic building blocks and the most diverse cell types in the brain. Their evolution reflects changes in the developmental processes that produce them, which in turn may shape the neural circuits they belong to. However, there is currently a lack of a unified criteria for studying the homology of connectivity and development between neurons. A neuron’s transcriptome is a molecular representation of its identity, connectivity, and developmental/evolutionary history. Hence the comparison of neuronal transcriptomes within and across species is a new and transformative development in the study of brain evolution. As an alternative, comparing neuronal transcriptomes across different species can provide insights into the evolution of the brain. We propose that comparing transcriptomes can be a way to fill this gap and unify these criteria. In previous studies, published in Science (Tosches et al., 2018) and Nature (Norimoto et al., 2020), we leveraged scRNAseq in reptiles to re-evaluate the origins and evolution of the mammalian cerebral cortex and claustrum. Motivated by the success of this approach, in this thesis we have now expanded single-cell profiling to the entire brain of a lizard species, the Australian dragon Pogona vitticeps, with a special focus in thalamus and prethalamus of. This approach allowed us to study the evolution of neuron types in amniotes. Therefore, we aimed to build a multilevel atlas of the lizard brain based on histology and transcriptomic and compare it to an equal mouse dataset (Zeisel et al., 2018).
Our atlas reveals a general structure that is consistent with that for other amniote brains, allowing us to make a direct comparison between lizard and mouse, despite their evolutionary divergence 320 million years ago. Through our analysis of the transcriptomes present in various neuron types, we have uncovered a core of conserved classes and discovered a fascinating dichotomy of new and conserved neuron types throughout the brain. This research challenges the traditional notion that certain brain regions are more conserved than others.
Our research also has uncovered the evolutionary history of the lizard thalamus and prethalamus by comparing them to homologous brain regions of the mouse. This pioneering research sheds new light on our understanding of the evolutionary history of the lizard brain. We propose a new classification of the lizard thalamic nuclei based on
transcriptomics. Our research revealed that the thalamic neuron types in lizards can be grouped into two large, conserved categories from the medial to lateral thalamus. These categories are encoded by a common set of effector genes, linking theories based on connectivity and molecular studies of these areas. In our data we have seen that there is a conservation of the medial-lateral transcriptomic axis in mouse and lizard, this conservation was most likely already present in the common ancestor. Although there is a shared medial-lateral axis, a deeper study of the thalamic cell types has allowed us to see the existence of a partial diversification of the thalamic population, specifically in the sensory-related lateral thalamus; in opposition, the medial thalamic nuclei neuron-types have been preserved.
On the other hand, the comparison with the mammalian prethalamus allowed us to confirm that the lizard ventromedial thalamic neuron types are homologous to mouse reticular thalamic neuron types (Díaz et al., 1994), even if they do not express the classical Reticular thalamic nucleus (RTn) marker PV/pvalb. We also discovered that there has been a simplification in the mammalian prethalamic neuron types in favor of an increase in the number of Interneurons (IN) types within their thalamus. We suggest that the loss of GABAergic neuronal types in the mammalian prethalamus is linked to the need for a more efficient control of the thalamo-pallial communication in mammals, while in lizards, where thalamo-pallial communication is probably simpler, the diversity prethalamus presents a higher diversity.
The prefrontal cortex (PFC) is considered the cognitive center of the mammalian brain. It is involved in a variety of cognitive functions such as decision making, working memory, goal-directed behavior, processing of emotions, flexible action selection, attention, and others (Fuster, 2015). In rodents, these functions are associated with the medial prefrontal cortex (mPFC). Experiments in mice and rats have shown that neurons in the mPFC are necessary for successful performance of many cognitive tasks. Moreover, measurements of neural activity in the mPFC show excitation or inhibition in different cells in relation to specific aspects of the tasks to be solved. To date, however, it is largely unknown whether prefrontal neurons are stably activated during the same behaviors within a task and whether similar aspects are represented by the same neurons in different tasks. In addition, it is unclear how specifically neurons are activated, for example, whether cells that are activated in response to reward are activated in a different task without reward in a different situation or remain inactive. To address these questions, we recorded the same neurons in the mPFC of mice over the course of several weeks while the animals performed various behaviors.
To do this, we expressed GCaMP6 in pyramidal neurons in the mPFC of mice. A small lens was implanted in the same location and a miniature microscope ("miniscope") was used to record neural activity. Later the extracted neurons got aligned based on their shape and position across multiple days and sessions. The mice performed five different behavioral tests while neural activity was measured: A spatial working memory test in a T-maze, exploration of the elevated plus maze (EPM), a novel object recognition (NO) test including free open field (OF) exploration, a social interaction (SI) test and discriminatory auditory fear conditioning (FC). Each task was repeated at least twice to check for stable task encoding across sessions. Behavioral performance and neural correlates to specific task events were similar to earlier studies across all tasks. We utilized generalized linear models (GLM) to determine which behavioral variables most strongly influence neural activity in the mPFC. The position of the mouse in the environment was found to explain most of the variance in neural activity, together with movement speed they were the strongest predictors of neural activity across all tasks. Reward time points in the working memory test, the conditioned stimulus after fear conditioning, or head direction in general were also strongly encoded in the mPFC.
Many of the recorded neurons showed a stable spatial activity profile across multiple sessions of the same task. Similarly, cells that coded for position in one task tended to code for position in other tasks. Not only did the same cells code for position across multiple tasks, but cells also coded for movement speed and head direction. This indicates that at least these general behavioral variables are each represented by the same neurons in the mPFC. Interestingly, the stability of position or speed coding did not depend on the time between two sessions, but only on whether it was within the same or across different tasks. Within the same task, stability was slightly higher than across different tasks.
To find out whether task-specific behavioral aspects were also stably encoded in the mPFC, difference scores as the difference in neural activity between two task aspects like left- and right-choice trials or exposed and enclosed locations were calculated. Many cells encoded these aspects stably across different sessions of each task. Both the left-right differences in the different phases of the working memory test, the open-closed-arm differences in the elevated plus maze, the different activity between center and corners in the open field, the social target-object differences in the social interaction test, and the differences between the two tones during fear conditioning were all stably encoded across the population of mPFC cells. Only the distinction between the novel and the familiar object during object recognition was not stably encoded, but also the preference for the novel object was not present in the second session of novel object exploration.
There was also an overlap in coding for different aspects within a task across multiple sessions. For example, cells stably encoded left-right differences in the T-maze between different sessions as a function of walking direction across different phases of working memory, an aspect that we could already show within one session (Vogel, Hahn et al., 2022). During fear conditioning, the same cells showed a discrimination between CS+ and CS- that also responded to the start of CS+.
Consistency in the neurons activity across different tasks was also found, but only between tasks with similar demands, the elevated plus-maze and free exploration of the open field. Cells that were more active in the open arms also showed more activity in the center of the open field and vice versa. This could be an indicator that the cells were coding for anxiety or exposure across those tasks, indicating that neurons in the mPFC also stably encode general task aspects independent of the specific environment. However, it remains unclear what exactly these neurons encode; in the case of a general fear signal, one would also expect activation during fear conditioning which could not be found.
Overall, we found that neurons in the mPFC of mice encoded multiple general behavioral variables across multiple tasks and task-specific variables were encoded stably within each of the tested tasks. However, we found little task-specific variables that were systematically encoded by the same neurons with the exception being the elevated plus-maze and open field exploration, two tasks with similar features.
Precise regulation of gene expression networks is required to develop and maintain a healthy organism before and after birth and throughout adulthood. Such networks are mostly comprised of regulatory proteins, but meanwhile many long non-coding transcripts (lncRNAs) are shown to participate in these regulatory processes. The functions and mechanisms of these lncRNAs vary greatly, however they are often associated with transcriptional regulation. Three lncRNAs, namely Sweetheart RNA (Swhtr), Fetal-lethal noncoding developmental regulatory RNA / Foxf1 adjacent non-Coding developmental regulatory RNA (Fendrr) and lncFsd2, were studied in this work to demonstrate the variety of cellular and biological processes that require lncRNA-mediated fine-tuning, in regard to the cardiopulmonary system.
Swhtr was found to be expressed exclusively in cardiomyocytes and became critical for regeneration after myocardial injury. Mice lacking Swhtr did not show issues under normal conditions, but failed to undergo compensatory hypertrophic remodeling after injury, leading to increased mortality. This effect was rescued by re-expressing Swhtr, demonstrating importance of the RNA. Genes dependent on Swhtr during cardiac stress were found to likely be regulated by NKX2-5 through physical interaction with Swhtr. Fendrr was found to be expressed in lung and interacted with target promoters through its RNA:dsDNA binding domain, the FendrrBox, which was partially required for Fendrr function. Fendrr, together with activated WNT signaling, regulated fibrosis related target genes via the FendrrBox in fibroblasts. LncFsd2, an ubiquitously expressed lncRNA, showed possible interaction with the striated muscle specific Fsd2, but its exact function and regulatory role remain unclear in muscle physiology. Immunoprecipitation and subcellular fractionation experiments suggest that lncFsd2 might be involved in nuclear retention of Fsd2 mRNA, thus fine-tuning FSD2 protein expression. These investigations have shed light on the roles of these lncRNAs in stress responses, fibrosis-related gene regulation, and localization processes, advancing our understanding of cardiovascular and pulmonary maintenance, reaction to injury, and diseases. The diverse and intricate roles of these three lncRNAs highlight how they influence various cellular processes and disease states, offering avenues for exploring lncRNA functions in different biological contexts.
Anthropogenic activities have a major impact on our planet and rapidly drive biodiversity loss in ecosystems at a global scale. Particularly over the last century, rising CO2 emissions significantly raised global temperatures and increased the intensity and frequency of droughts and heatwaves. Additionally, agricultural land use and fossil fuel combustion contribute to the continuous release of nitrogen (N) and phosphorus (P) into ecosystems worldwide through extensive fertilization and deposition from the atmosphere. It is important to understand how these rapid changes affect the evolution of plant populations and their adaptive potential. Adaptation by natural selection (i.e., adaptive evolution) within a few generations is an essential process as a response to rapid environmental changes. Rapid evolution of plant populations can be detected by using the so-called resurrection approach. Here, diaspores (i.e., seeds) from a population are collected before (ancestors) and after (descendants) a potential selection pressure (e.g., consecutive years of drought or changes in nutrient supply). Comparing phenotypes of ancestors and descendants in a common environment such as an outside garden, greenhouse, or climate chamber, may then reveal evolutionary changes. Ideally, plants are first grown in a common environment for an intermediate refresher generation to reduce parental and storage effects.
The aim of this thesis was to investigate the occurrence of adaptive evolution in natural plant populations in response to rapidly changing environments over the past three decades. I conducted three experiments using the resurrection approach to generate comprehensive data on the adaptive processes that acted on three plant populations from three different species over the last three decades. Furthermore, I filled knowledge gaps in plant evolutionary ecology and conceptually developed the resurrection approach further.
In Chapter I, I performed a novel approach by testing for adaptive evolution in natural plant populations using the resurrection approach in combination with in-situ transplantations. I cultivated seedlings from ancestors (23 – 26 years old) and contemporary descendants of three perennial species (Melica ciliata, Leontodon hispidus and Clinopodium vulgare) from calcareous grasslands in the greenhouse and In Chapter III, I assessed the reproducibility of phenotypic differences between genotypes among three different growth facilities (climate chamber, greenhouse, and outdoor garden). I also evaluated differences in phenotypic expression between plants grown after one vs. two intermediate generations (i.e., refresher generations). I performed this experiment within the framework of the resurrection approach and compared ancestors and descendants of the same population of Leontodon hispidus.
I observed very strong differences among plants growing in the different growth facilities. I found a significant interaction between the growth facility and the temporal origin (ancestors vs. descendants): descendants had significantly larger rosettes than ancestors only in the greenhouse and they flowered significantly later than ancestors exclusively in the climate chamber. I did not find significant differences between intermediate generations within the growth facilities. Overall, Chapter III shows that the use of a particular experimental system can dictate the presence and magnitude of phenotypic differences. This implies that absence of evidence is not evidence of absence when it comes to investigating genetically based trait differentiation among plant origins (in space or time). Experimental systems should be carefully designed to provide meaningful conditions, ideally mimicking the environmental conditions of the population’s origins. Finally, growing a second intermediate generation did not impact the genetic differences of ancestors and descendants within the environments, supporting the idea that only one intermediate generation may be sufficient to reduce detectable parental and storage effects.
The resurrection approach allows a better understanding of rapid plant adaptation, but some limitations deserve to be highlighted. I only studied one population per species, and Chapters II and III only focus on one population of L. hispidus, which is also hampering generalizations, as adaptive potential can vary greatly among populations of the same species. I only compared the ancestral genotypes to one descendant sample with a long time span in between (26 – 28 years), which makes it hard to pinpoint the selection agents that caused the genetic differentiation among the sampling years. Hence, closely monitoring biotic and abiotic factors of the studied populations between the ancestral and descendant sampling in future studies, would make identifying the responsible selection pressures more precise. I also recommend sampling multiple populations over consecutive years to improve the robustness of results and make generalizations more approachable.Furthermore, combining the resurrection approach with other methods such as in-situ transplantations will be valuable to offset the limitation that adaptations cannot be proven under artificial conditions (e.g., in the greenhouse).
The nucleus reuniens drives hippocampal goal‑directed trajectory sequences for route planning
(2023)
Goal-directed spatial navigation requires accurate estimates of one’s position and destination, as well as careful planning of a route between them to avoid known obstacles in the environment. Despite its general importance across species, the neural circuitry supporting the ability for route planning remains largely unclear. Previous studies described that place cells in the hippocampal CA1 encode the animal's next movement direction (Wood et al., 2000; Ito et al., 2015) and upcoming navigational routes (Pfeiffer & Foster, 2013). However, it has been shown that part of the CA1 activity representing the animal’s future behaviors is not necessarily generated in the hippocampus, but is derived from the medial prefrontal cortex (PFC) via the nucleus reuniens of the thalamus (RE) (Ito et al., 2015). Notably, the importance of the PFC in navigation has been demonstrated in several studies, including the recent finding of a goal map in the orbitofrontal cortex (Basu et al., 2021). Therefore, I hypothesized that information flow from the PFC to CA1 via the RE plays a key role in route planning.
To assess the animals' route planning ability, I designed a new navigation task in which a rat has to navigate to a fixed target location from various starting positions in an arena. Furthermore, by adding an L-shaped wall in the maze and removing all light sources in the experimental room, this task forced the animals to plan a wall-avoiding route without relying on direct sensory perceptions. I confirmed that rats could learn this task successfully, memorizing the wall location and taking a smooth wall-avoidance route. To test the role of the RE, I inactivated RE neurons by expressing the inhibitory opsin SwiChR++, which resulted in a significant deficit in the animal’s route planning ability, taking a longer non-smooth path to the destination. By contrast, this manipulation did not affect navigation performance when a straight goal-directed route was available, suggesting a specific role of the RE in route planning. I further found that DREADDs-mediated inactivation of neurons in the bilateral hippocampi resulted in a similar deficit in route planning ability, implying cooperation between the RE and the hippocampus.
I finally examined the activity of hippocampal CA1 neurons with and without RE inactivation. While neurons in the hippocampus exhibited brief trajectory sequences corresponding to the animal’s subsequent goal-directed journey, I found that this goal-directed bias of trajectory events was significantly reduced by RE inactivation, likely associated with route-planning deficits in these animals.
Altogether, this dissertation demonstrates the role of the RE from both behavioral and neural coding perspectives, identifying a pivotal circuit element supporting the animal’s route-planning ability.
Biotechnological processes offer better production conditions for a wide variety of goods of industrial interest. The production of aromatic compounds, for example, involves molecules of great value for cosmetic, plastic, agrochemical and pharmaceutic industries. However, the yield of such processes frequently prevents a proper implementtation that would allow the replacement of traditional production processes.
Numerous rational engineering approaches have been attempted to enhance metabolic pathways associated with desired products. Unfortunately, genetic modifications and heterologous pathway expression often lead to a higher metabolic burden on the producing organisms, ultimately leading to reduced production levels and fitness.
This project utilised adaptive laboratory evolution to better understand the development of synthetic cooperative consortia, using S. cerevisiae as a model organism. Specifically, a synthetic cooperative consortium was developed around the exchange of lysine and tyrosine, which was subjected to adaptive laboratory evolution aiming to induce mutations that would improve the system’s fitness either by enhanced production or upgraded stress resistance. Consequently, the mutant strains isolated after the evolution rounds were sequenced to identify relevant variations that could be related to the growth and production phenotypes observed.
The insights derived from this project are expected to contribute to further developing synthetic cooperative consortia with utilitarian purposes.
Hyperparasitic fungi on black mildews (Meliolales, Ascomycota) : hidden diversity in the tropics
(2023)
Meliolales (Sordariomycetes, Ascomycota) is a group of obligate plant parasitic microfungi mainly distributed in the tropics and subtropics. Meliolalean fungi are commonly known as “black mildews”, as they form black, superficial hyphae on the surface of vegetative and reproductive organs of vascular plants. They are considered biotrophic parasites, and the infections caused by black mildews can lead to a decrease in the photosynthetic activity of plants, as well as to an increase in the temperature and respiration rate of their leaves.
Meliolales are frequently parasitized by hyperparasitic fungi, i.e., parasitic fungi that have parasitic hosts. These hyperparasites are all Ascomycota and belong mainly to the Dothideomycetes and Sordariomycetes. Although hyperparasites represent a megadiverse group, species were only described by morphology until 1980, and the systematic position of more than 60 % of known species is still unclear. In addition, there are no DNA reference sequences available in public databases for any of the species of hyperparasites of Meliolales, and no ecological studies have been done up to now.
Before this study, no exact number of hyperparasitic fungi growing on colonies of black mildews existed. Here, we present a checklist including 189 species of fungi known to be hyperparasitic on Meliolales, but the number of existing species is likely to be even higher. The elaboration of this species checklist laid the foundations for this investigation, as it helped to understand the present state of knowledge of hyperparasitic fungi on Meliolales worldwide.
For the present study, fresh specimens of leaves infected with colonies of Meliolales and hyperparasites were opportunistically collected at 32 collection sites in Western Panama and Benin, West Africa, in 2020 and 2022, respectively. In total, 100 samples of plant specimens infected with black mildews were collected, of which 58 samples were parasitized by hyperparasitic fungi. 31 species and morphospecies of hyperparasitic fungi were identified. In addition, 35 historical specimens, including 12 type specimens, were examined for the present work.
DNA of hyperparasitic fungi was isolated directly from conidia, synnemata, apothecia, perithecia or pseudothecia of fresh and dried specimens. The main challenges faced by scientists in doing molecular studies of hyperparasitic fungi are related to the fact that the hyperparasitic fungi are intermingled with tissues of the meliolalean hosts and other organisms present in a given sample. This makes the isolation of DNA exclusively from the hyperparasite difficult. Moreover, hyperparasitic fungi on Meliolales are biotrophs and cannot be grown axenically. The hosts themselves are also biotrophic, further complicating DNA isolation from either partner. These factors have contributed to a lack of reference sequences in public databases. After more than 100 attempts, DNA of 20 specimens of hyperparasitic fungi, representing seven species, has been isolated in the context of the present investigation. Three partial nuclear gene regions were amplified and sequenced: nrLSU, nrSSU and nrITS. The datasets were assembled for phylogenetic analyses applying Maximum Likelihood (ML) and Bayesian inference (BI) methods. DNA sequences of hyperparasitic fungi on Meliolales were generated for the first time in the context of the present investigation.
Hyperparasitic fungi on Meliolales do not represent a single systematic group, but a polyphyletic ecological guild of fungi. Because of this huge diversity, only the systematics of species of perithecioid hyperparasites, as well as of the species of the genera Atractilina and Spiropes known to be hyperparasitic on black mildews was discussed in this thesis, as they represented the most common groups of fungi found in Benin and Panama. The results indicated, for example, the systematic position of Dimerosporiella cephalosporii and Paranectriella minuta in the Sordariomycetes and Dothideomycetes, respectively. In addition, the first record of a hyperparasitic fungus of black mildews in the Lecanoromycetes, namely Calloriopsis herpotricha, is reported here. The systematics of Atractilina parasitica and of some species of Spiropes is also discussed here.
In the context of the present investigation, four species new to science were described. They are presented with detailed descriptions, photos and scientific illustrations. Taxonomic studies of this thesis also generated seven new synonyms, nine new records for Benin, seven for Panama, one for Africa and two for mainland America, as well as the confirmation of one anamorph-teleomorph connection by molecular sequence data.
The ecology of hyperparasitic fungi on Meliolales is complex and far from being completely understood. The hypothesis of host specificity between hyperparasitic fungi, their meliolalean hosts and their plant hosts was tested for the first time, through a tritrophic network analysis. Results indicate that hyperparasites of Meliolales are generalists concerning genera of Meliolales, but apparently specialists at the level of order. In addition, hyperparasitic fungi tend to be found alongside their meliolalean hosts, suggesting a pantropical distribution.
Discrepancies between knockdown and knockout animal model phenotypes have long stood as a perplexing phenomenon. Several mechanisms explaining such observations have been proposed, namely the toxicity or the off-target effects of the knockdown reagents, as well as, in certain cases, genetic robustness – an organism's ability to maintain its phenotype despite genetic perturbations. In addition to these explanations, transcriptional adaptation (TA), a phenomenon defined as an event whereby a mutation in one gene leads to transcriptional upregulation or downregulation of another, adapting, gene or genes expression, has been recently proposed as an alternative explanation for the conflicting knockdown and knockout phenotype paradox.
Since its discovery in 2015, TA's precise mechanism remains a subject of ongoing research. Majority of evidence suggests that mutant mRNA degradation plays a central in TA. Epigenetic remodeling is also thought to play a role, as evidenced by an increase in active histone marks at the transcription start sites of the adapting genes. Whether mRNA degradation is indeed the key player in TA remains debated. Furthermore, it is still unknown how exactly TA develops, what adapting genes it targets, and whether genomic mutations that render mutant mRNA sensitive to degradation are required for TA to occur.
Throughout the experiments described in this Dissertation, I have designed an inducible TA system where TA can be triggered on demand and its effects on the cell’s transcriptome followed through time. I have demonstrated that degradation-prone transgenes, once induced and expressed, can be efficiently degraded, resulting in the protein loss-independent upregulation of adapting genes via TA. Adapting genes with higher degree of sequence similarity become upregulated faster than genes with lower degree of sequence similarity. Further functionality of this approach to study TA is limited by the leakiness of the inducible gene expression system; however, constitutively expressed degradation-prone transgenes were used to demonstrate TA in human cells.
In addition, I have developed an approach to target wild-type cytoplasmic mRNAs without altering the cell’s genome and reported a TA-like phenomenon, which manifested as adapting gene upregulation not relying on mutations in other genes. Cytoplasmic mRNA cleavage with CRISPR-Cas13d triggered a TA-like response in three different gene models: Actg1 knockdown, Ctnna1 knockdown, and Nckap1 knockdown. After comparing two different modes of triggering TA, CRISPR-Cas9 knockout versus CRISPR-Cas13d knockdown, I reported little overlap between the dysregulated genes and suggested that diverse mRNA degradation modes led to distinct TA responses. In addition, the transcriptional increase of Actg2 caused by CRISPR-Cas13d-mediated Actg1 mRNA cleavage did not require chromatin accessibility changes.
Experiments and genetic tools described in this dissertation investigated how TA develops from its earliest onset, how it affects the global transcriptome of the cell, as well as provided compelling evidence for an mRNA degradation-central TA mechanism. I have created tools to study both direct and indirect TA gene targets and unveiled important insights into the temporal dynamics of TA. Genes with higher sequence similarity were found to be upregulated more rapidly than those with lower similarity. Furthermore, it was revealed that the epigenetic properties of TA responses vary depending on the triggering mechanism. Cas13d-mediated degradation of wild-type mRNAs led to immediate transcriptional enhancement independent of epigenetic changes, which stood in contrast to previously measured alterations in chromatin accessibility in CRISPR-Cas9 mutants. This research has thus significantly advanced our knowledge of TA and provided valuable tools and findings that contribute to the broader understanding of gene expression regulation in response to mRNA degradation.
Trait-dependent effects of biotic and abiotic filters on plant regeneration in Southern Ecuador
(2024)
Tropical forests have always fascinated scientists due to their unique biodiversity. However, our understanding of ecological processes shaping the complexity of tropical rainforests is still relatively poor. Plant regeneration is one of the processes that remain understudied in the tropics although this is a key process defining the structure, diversity and assembly of tropical plant communities. In my dissertation, I combine experimental, observational and trait-based approaches to identify processes shaping the assembly of seedling communities and compare associations between environmental conditions and plant traits across plant life stages. By working along a steep environmental gradient in the tropical mountains of Southern Ecuador, I was able to investigate how processes of plant regeneration vary in response to biotic and abiotic factors in tropical montane forests.
My dissertation comprises three complementary chapters, each addressing an individual research question. First, I studied how trait composition in plant communities varies in relation to the broad- and local-scale environmental conditions and across the plant life cycle. I measured key traits reflecting different ecological strategies of plants that correspond to three stages of the plant life cycle (i.e., adult trees, seed rain and recruiting seedlings). I worked on 81 subplots along an elevational gradient covering a large climatic gradient at three different elevations (1000, 2000 and 3000 m a.s.l.). In addition, I measured soil and light conditions at the local spatial scale within each subplot. My findings show that the trait composition of leaves, seeds and seedlings changed similarly across the elevational gradient, but that the different life stages responded differently to the local gradients in soil nutrients and light availability. Consequently, my findings highlight that trait-environment associations in plant communities differ between large and small spatial scales and across plant life stages.
Second, I investigated how seed size affects seedling recruitment in natural forests and in pastures in relation to abiotic and biotic factors. I set up a seed sowing experiment in both habitat types and sowed over 8,000 seeds belonging to seven tree species differing in seed size. I found that large-seeded species had higher proportions of recruitment in the forests compared to small-seeded species. However, small-seeded species tended to recruit better in pastures compared to large-seeded species. I showed that high surface temperature was the main driver of differences in seedling recruitment between habitats, because it limited seedling recruitment of large-seeded species. The results from this experiment show that pasture restoration requires seed addition of large-seeded species and active protection of recruiting seedlings in order to mitigate harmful conditions associated with high temperatures in deforested areas.
Third, I examined the associations between seedling beta-diversity and different abiotic and biotic factors between and within elevations. I applied beta-diversity partitioning to obtain two components of beta-diversity: species turnover and species richness differences. I associated these components of beta-diversity with biotic pressures by herbivores and fungal pathogens and environmental heterogeneity in light and soil conditions. I found that species turnover in seedling communities was positively associated with the dissimilarity in biotic pressures within elevations and with environmental heterogeneity between elevations. Further, I found that species richness differences increased primarily with increasing environmental heterogeneity within elevations. My findings show that the associations between beta-diversity of seedling communities and abiotic and biotic factors are scale-dependent, most likely due to differences in species sorting in response to biotic pressures and species coexistence in response to environmental heterogeneity.
My dissertation reveals that studying processes of community assembly at different plant life stages and spatial scales can yield new insights into patterns and processes of plant regeneration in tropical forests. I investigated how community assembly processes are governed by abiotic and biotic filtering across and within elevations. I also experimentally explored how the process of seedling recruitment depends on seed size-dependent interactions, and verified how these effects are associated with abiotic and biotic filtering. Identifying such processes is crucial to inform predictive models of environmental change on plant regeneration and successful forest restoration. Further exploration of plant functional traits and their associations with local-scale environmental conditions could effectively support local conservation efforts needed to enhance forest cover in the future and halt the accelerating loss of biodiversity.
Influenza is a contagious respiratory disease caused by influenza A and influenza B viruses. The World Health Organisation (WHO) reports that annual influenza epidemics result in approximately 1 billion infections, 3 to 5 million severe cases, and 300 to 650 thousand deaths. Understanding hidden mechanisms that lead to optimal vaccine efficacy and improvement antiviral treatment strategies remain continuous and central tasks. First, regarding the immune response to vaccines and natural infections, the antibody response echoes the dynamics of diverse immune elements such as B-cells, and plasma cells. Also, responses reflect the processes for B-cells to gain and adapt affinity for the virus. Antibodies (Abs) that respond to the virus surface proteins, particularly to the hemagglutinin (HA), have been identified to protect against infection. The Abs responses binding to HA can be broadly protective as this protein is considerably accessible on the virion. When following sequential infections with similar influenza strains, i.e. two infections with different strains of a subtype, an enhanced breadth and magnitude of Abs response is developed, mainly after the second infection. The effect of being effective to new strains is called Abs cross-reaction.
On the other hand, as for antiviral treatment, the WHO currently approves the use of neuraminidase inhibitors (NIs) such as zanamivir and oseltamivir. Diverse research areas such as system biology, learning-based methods, control theory, and systems pharmacology have guided the development of modern treatment schemes. To do so, mathematical models are used to describe a wide range of phenomena such as viral pathogenesis, immune responses, and the drug's dynamics in the body. Drug dynamics are usually expressed in two phases, pharmacokinetics (PK) and pharmacodynamics (PD) - the PK/PD approach. These schemes leverage pre-clinical and clinical data through modeling and simulation of infection and drug effects at diverse levels. Under such a framework, control-based scheduling systems seek to tailor optimal antiviral treatment for infectious diseases. Thus, influenza treatment can be theoretically studied as a control-based optimization duty (about systems stability, bounded inputs, and optimality). Finally, towards real-world implementation, learning-based methods such as neural networks (NNs) can guide solving issues on the control-based performance. Using NNs as identifiers provide a setting to deal with infrequent measures and uncertain parameters for the control systems.
This thesis theoretically explores central mechanisms in influenza infection via modeling and control approaches. In the first project, we explore how and to what extent antibody-antigen affinity flexibility could guide the Abs cross-reaction in two sequential infections using a hypothetical family of antigens. The set of antigens generally represent strains of influenza, such as those of a subtype. Each antigen is composed of a variable and a conserved area, generically representing the structures of the HA, head, and stalk, respectively. We test diverse scenarios of affinity thresholds in the conserved and variable areas of the antigens. The Abs response reaches a high magnitude when using equivalent affinity thresholds in the conserved and variable areas during the first infection. However, improved cross-reaction is developed when slightly increasing the affinity threshold of the variable area for the second infection. Key mutations via affinity maturation is a feature that, together with affinity flexibility between infections, guides Abs cross-reaction in the model outcome. These results could correlate with studies pointing out that broad responses might be dependent on reaching specific mutations for getting affinity to a newly presented antigen while broadly reaching related antigens. The general platform may serve as a proof-of-concept for exploring fundamental mechanisms that favor the Abs cross-reaction.
In a second project, theoretical schemes are developed to combine impulsive and inverse optimal control strategies to address antiviral treatment scheduling. We present results regarding stability, passivity, bounded inputs, and optimality using impulsive action. The study is founded on mathematical models of the influenza virus (target-cell limited model) adjusted to data from clinical trials. In these studies, participants were experimentally infected with influenza H1N1 and treated with NIs. Results show that control-based strategies could tailor dosage and reduce the amount of medication by up to 44%. Also, control-based treatment reaches the efficacy (98%) of the current treatment recommendations by the WHO. Monte Carlo simulations (MCS) disclose the robustness of the proposed control-based techniques. Using MCS, we also explore the applicability to the individualized treatment of infectious diseases through virtual clinical trials. Furthermore, bounded control strategies are applied directly in drug dose estimation accounting for overdose prevention. Finally, due to the limitations of the available technology intended for clinical practice, we emphasize the necessity of developing system identifiers and observers for real-world applications.
In the third project, the problem of data scarcity and infrequent measures in the real world is handled by means of learning-based methods. System identification is derived using a Recurrent High Order Neural Network (RHONN) trained with the Extended Kalman filter (EKF). Lessons learned from impulsive control frameworks are taken to develop a neural inverse optimal impulsive control --neurocontrol. The treatment efficacy is tested for early (one day post-infection) and late (2 to 3 days post-infection) treatment initiation. The neurocontrol reaches an efficacy of up to 95% while saving almost 40% of the total drug in the early treatment. Robustness is tested via virtual clinical trials using MCS.
Lastly, taking all together, the schemes developed in this thesis for modeling the Abs cross-reaction and control-based treatment tailoring can be extended and adapted to explore similar phenomena in different respiratory pathogens, such as SARS-CoV-2.