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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.
In high light, the antenna system in oxygenic photosynthetic organisms switches to a photoprotective mode, dissipating excess energy in a process called non-photochemical quenching (NPQ). Diatoms exhibit very efficient NPQ, accompanied by a xanthophyll cycle in which diadinoxanthin is de-epoxidized into diatoxanthin. Diatoms accumulate pigments from this cycle in high light, and exhibit faster and more pronounced NPQ. The mechanisms underlying NPQ in diatoms remain unclear, but it can be mimicked by aggregation of their isolated light-harvesting complexes, FCP (fucoxanthin chlorophyll-a/c protein). We assess this model system by resonance Raman measurements of two peripheral FCPs, trimeric FCPa and nonameric FCPb, isolated from high- and low-light-adapted cells (LL, HL). Quenching is associated with a reorganisation of these proteins, affecting the conformation of their bound carotenoids, and in a manner which is highly dependent on the protein considered. FCPa from LL diatoms exhibits significant changes in diadinoxanthin structure, together with a smaller conformational change of at least one fucoxanthin. For these LL-FCPa, quenching is associated with consecutive events, displaying distinct spectral signatures, and its amplitude correlates with the planarity of the diadinoxanthin structure. HL-FCPa aggregation is associated with a change in planarity of a 515-nm-absorbing fucoxanthin, and, to a lesser extent, of diadinoxanthin. Finally, in FCPb, a blue-absorbing fucoxanthin is primarily affected. FCPs thus possess a plastic structure, undergoing several conformational changes upon aggregation, dependent upon their precise composition and structure. NPQ in diatoms may therefore arise from a combination of structural changes, dependent on the environment the cells are adapted to.
Highlights
• Seed size mediates seedling recruitment in tropical forests and pastures.
• Large-seeded species recruited better than small-seeded species in the forest.
• Recruitment of large-seeded species in pastures was limited by surface temperature.
• Large-seeded species should be protected against drought in regenerating pastures.
Abstract
Seedling recruitment is a key process of plant regeneration that often depends on plant functional traits, such as seed size. To optimize forest restoration efforts, we need to better understand how seedling recruitment of different seed sizes varies along environmental gradients with strong variation in abiotic and biotic factors. To understand these interacting effects, we conducted a sowing experiment with different-sized seeds in forests and pastures in the tropical mountains of southern Ecuador. We quantified seedling recruitment in relation to temperature, soil moisture and biotic pressures. We sowed seeds of five tree species of varying seed size at three elevations (1000, 2000 and 3000 m a.s.l.) in primary forest and pastures. We tested (1) how habitat type influences the recruitment of seedlings belonging to three small- and two large-seeded species, and (2) how abiotic and biotic factors limit seedling recruitment of species with different seed sizes. We found that seedlings of the two large-seeded species recruited better than seedlings of the three small-seeded species, but only in the forest habitat. Seedling recruitment of large seeds was primarily limited by high surface temperature, which explains lower recruitment of large seeds in pastures compared to forests. Our study shows that seed size can be a key trait mediating variability in seedling recruitment in tropical ecosystems. We conclude that restoration measures should aim to mitigate extreme temperatures in tropical pastures to aid the natural regeneration of large-seeded tree species.
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.
Determining the structure and mechanisms of all individual functional modules of cells at high molecular detail has often been seen as equal to understanding how cells work. Recent technical advances have led to a flush of high-resolution structures of various macromolecular machines, but despite this wealth of detailed information, our understanding of cellular function remains incomplete. Here, we discuss present-day limitations of structural biology and highlight novel technologies that may enable us to analyze molecular functions directly inside cells. We predict that the progression toward structural cell biology will involve a shift toward conceptualizing a 4D virtual reality of cells using digital twins. These will capture cellular segments in a highly enriched molecular detail, include dynamic changes, and facilitate simulations of molecular processes, leading to novel and experimentally testable predictions. Transferring biological questions into algorithms that learn from the existing wealth of data and explore novel solutions may ultimately unveil how cells work.
Highlights
• Three ecological groups were identified based on distributional patterns.
• Old assessments were confirmed with the latest occurrence data.
• For each group, we derived different population trends in times of global change.
• Global change elevates importance of vector-borne diseases.
• Our results serve as base for effective Simuliidae monitoring.
Abstract
The black fly genus Simulium includes medically and ecologically important species, characterized by a wide variation of ecological niches largely determining their distributional patterns. In a rapidly changing environment, species-specific niche characteristics determine whether a species benefits or not. With aquatic egg, larval and pupal stages followed by a terrestrial adult phase, their spatial arrangements depend upon the interplay of aquatic conditions and climatic-landscape parameters in the terrestrial realm. The aim of this study was to enhance the understanding of the distributional patterns among Simulium species and their ecological drivers. In an ecological niche modelling approach, we focused on 12 common black fly species with different ecological requirements. Our modelling was based on available distribution data along with five stream variables describing the climatic, land-cover, and topographic conditions of river catchments. The modelled freshwater habitat suitability was spatially interpolated to derive an estimate of the adult black flies' probability of occurrence. Based on similarities in the spatial patterns of modelled habitat suitability we were able to identify three biogeographical groups, which allows us to confirm old assessments with current occurrence data: (A) montane species, (B) broad range species and (C) lowland species. The five veterinary and human medical relevant species Simulium equinum, S. erythrocephalum, S. lineatum, S. ornatum and S. reptans are mainly classified in the lowland species group. In the course of climatic changes, it is expected that biocoenosis will slightly shift towards upstream regions, so that the lowland group will presumably emerge as the winner. This is mainly explained by wider ecological niches, including a higher temperature tolerance and tolerance to various pollutants. In conclusion, these findings have significant implications for human and animal health. As exposure to relevant Simulium species increases, it becomes imperative to remain vigilant, particularly in investigating the potential transmission of pathogens.