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In Arabidopsis thaliana, the stem cell niche (SCN) within the root apical meristem (RAM) is maintained by an intricate regulatory network that ensures optimal growth and high developmental plasticity. Yet, many aspects of this regulatory network of stem cell quiescence and replenishment are still not fully understood. Here, we investigate the interplay of the key transcription factors (TFs) BRASSINOSTEROID AT VASCULAR AND ORGANIZING CENTRE (BRAVO), PLETHORA 3 (PLT3) and WUSCHEL-RELATED HOMEOBOX 5 (WOX5) involved in SCN maintenance. Phenotypical analysis of mutants involving these TFs uncover their combinatorial regulation of cell fates and divisions in the SCN. Moreover, interaction studies employing fluorescence resonance energy transfer fluorescence lifetime imaging microscopy (FRET-FLIM) in combination with novel analysis methods, allowed us to quantify protein-protein interaction (PPI) affinities as well as higher-order complex formation of these TFs. We integrated our experimental results into a computational model, suggesting that cell type specific profiles of protein complexes and characteristic complex formation, that is also dependent on prion-like domains in PLT3, contribute to the intricate regulation of the SCN. We propose that these unique protein complex ‘signatures’ could serve as a read-out for cell specificity thereby adding another layer to the sophisticated regulatory network that balances stem cell maintenance and replenishment in the Arabidopsis root.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions, using signals from nanopore direct RNA sequencing. CHEUI processes observed and expected signals with convolutional neural networks to achieve high single-molecule accuracy and outperform other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A 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.
Tree-related microhabitats (TreMs) describe the microhabitats that a tree can provide for a multitude of other taxonomic groups and have been proposed as an important indicator for forest biodiversity (Asbeck et al., 2021). So far, the focus of TreM studies has been on temperate forests, although many trees in the tropics harbour exceptionally high numbers of TreMs. In this study, TreMs in the lowland tropical forests of the Choco (Ecuador) and in the mountain tropical forests of Mount Kilimanjaro (Tanzania) were surveyed. Our results extend the existing typology of TreMs of Larrieu et al. (2018) to include tropical forests and enabled a comparison of the relative recordings and diversity of TreMs between tropical and temperate forests. A new TreM form, Root formations, and three new TreM groups, concavities build by fruits or leaves, dendrotelms, and root formations, were established. In total, 15 new TreM types in five different TreM groups were specified. The relative recordings of most TreMs were similar between tropical and temperate forests. However, ivy and lianas, and ferns were more common in the lowland rainforest than in temperate forests, and bark microsoil, limb breakage, and foliose and fruticose lichens in tropical montane forest than in lowland rainforest. Mountain tropical forests hosted the highest diversity for common and dominant TreM types, and lowland tropical forest the highest diversity for rare TreMs. Our extended typology of tree-related microhabitats can support studies of forest-dwelling biodiversity in tropical forests. Specifically, given the ongoing threat to tropical forests, TreMs can serve as an additional tool allowing rapid assessments of biodiversity in these hyperdiverse ecosystems.
EF-P and its paralog EfpL (YeiP) differentially control translation of proline containing sequences
(2024)
Polyproline sequences (XPPX) stall ribosomes, thus being deleterious for all living organisms. In bacteria, translation elongation factor P (EF-P) plays a crucial role in overcoming such arrests. 12% of eubacteria possess an EF-P paralog – YeiP (EfpL) of unknown function. Here, we functionally and structurally characterize EfpL from Escherichia coli and demonstrate its yet unrecognized role in the translational stress response. Through ribosome profiling, we analyzed the EfpL arrest motif spectrum and discovered additional stalls beyond the canonical XPPX motifs at single-proline sequences (XPX), that both EF-P and EfpL can resolve. Notably, the two factors can also induce pauses. We further report that, contrary to the housekeeping EF-P, EfpL can sense the metabolic state of the cell, via lysine acylation. Together, our work uncovers a new player in ribosome rescue at proline-containing sequences, and provides evidence that co-occurrence of EF-P and EfpL is an evolutionary driver for higher bacterial growth rates.
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.
Abstract
Natural plant populations often harbour substantial heritable variation in DNA methylation. However, a thorough understanding of the genetic and environmental drivers of this epigenetic variation requires large-scale and high-resolution data, which currently exist only for a few model species. Here, we studied 207 lines of the annual weed Thlaspi arvense (field pennycress), collected across a large latitudinal gradient in Europe and propagated in a common environment. By screening for variation in DNA sequence and DNA methylation using whole-genome (bisulfite) sequencing, we found significant epigenetic population structure across Europe. Average levels of DNA methylation were strongly context-dependent, with highest DNA methylation in CG context, particularly in transposable elements and in intergenic regions. Residual DNA methylation variation within all contexts was associated with genetic variants, which often co-localized with annotated methylation machinery genes but also with new candidates. Variation in DNA methylation was also significantly associated with climate of origin, with methylation levels being higher in warmer regions and lower in more variable climates. Finally, we used variance decomposition to assess genetic versus environmental associations with differentially methylation regions (DMRs). We found that while genetic variation was generally the strongest predictor of DMRs, the strength of environmental associations increased from CG to CHG and CHH, with climate-of-origin as the strongest predictor in about one third of the CHH DMRs. In summary, our data show that natural epigenetic variation in Thlaspi arvense is significantly associated with both DNA sequence and environment of origin, and that the relative importance of the two factors strongly depends on the sequence context of DNA methylation. T. arvense is an emerging biofuel and winter cover crop; our results may hence be relevant for breeding efforts and agricultural practices in the context of rapidly changing environmental conditions.
Author Summary: Variation within species is an important level of biodiversity, and it is key for future adaptation. Besides variation in DNA sequence, plants also harbour heritable variation in DNA methylation, and we want to understand the evolutionary significance of this epigenetic variation, in particular how much of it is under genetic control, and how much is associated with the environment. We addressed these questions in a high-resolution molecular analysis of 207 lines of the common plant field pennycress (Thlaspi arvense), which we collected across Europe, propagated under standardized conditions, and sequenced for their genetic and epigenetic variation. We found large geographic variation in DNA methylation, associated with both DNA sequence and climate of origin. Genetic variation was generally the stronger predictor of DNA methylation variation, but the strength of environmental association varied between different sequence contexts. Climate-of-origin was the strongest predictor in about one third of the differentially methylated regions in the CHH context, which suggests that epigenetic variation may play a role in the short-term climate adaptation of pennycress. As pennycress is currently being domesticated as a new biofuel and winter cover crop, our results may be relevant also for agriculture, particularly in changing environments.
RNA-binding proteins (RBPs) control every RNA metabolic process by multiple protein-RNA and protein-protein interactions. Their roles have largely been analyzed by crude mutations, which abrogate multiple functions at once and likely impact the structural integrity of the large messenger ribonucleoprotein particle (mRNP) assemblies, these proteins often function in. Using UV-induced RNA-protein crosslinking and subsequent mass spectrometric analysis, we first identified more than 100 in vivo RNA crosslinks in 16 nuclear mRNP components in S. cerevisiae. For functional analysis, we chose Npl3, for which we determined crosslinks in its two RNA recognition motifs (RRM) and in the flexible linker region connecting the two. Using NMR and structural analyses, we show that both RRM domains and the linker uniquely contribute to RNA recognition. Interestingly, mutations in these regions cause different phenotypes, indicating distinct functions of the different RNA-binding domains of Npl3. Notably, the npl3-Linker mutation strongly impairs recruitment of several mRNP components to chromatin and incorporation of further mRNP components into nuclear mRNPs, establishing a function of Npl3 in nuclear mRNP assembly. Taken together, we determined the specific function of the RNA-binding activity of the nuclear mRNP component Npl3, an approach that can be applied to many RBPs in any RNA metabolic process.
Zinc finger (ZnF) domains appear in a pool of structural contexts and despite their small size achieve varying target specificities, covering single-stranded and double-stranded DNA and RNA as well as proteins. Combined with other RNA-binding domains, ZnFs enhance affinity and specificity of RNA-binding proteins (RBPs). The ZnF-containing immunoregulatory RBP Roquin initiates mRNA decay, thereby controlling the adaptive immune system. Its unique ROQ domain shape-specifically recognizes stem-looped cis-elements in mRNA 3’-untranslated regions (UTR). The N-terminus of Roquin contains a RING domain for protein-protein interactions and a ZnF, which was suggested to play an essential role in RNA decay by Roquin. The ZnF domain boundaries, its RNA motif preference and its interplay with the ROQ domain have remained elusive, also driven by the lack of high-resolution data of the challenging protein. We provide the solution structure of the Roquin-1 ZnF and use an RBNS-NMR pipeline to show that the ZnF recognizes AU-rich elements (ARE). We systematically refine the contributions of adenines in a poly(U)-background to specific complex formation. With the simultaneous binding of ROQ and ZnF to a natural target transcript of Roquin, our study for the first time suggests how Roquin integrates RNA shape and sequence specificity through the ROQ-ZnF tandem.
RBFOX1 is a highly pleiotropic gene that contributes to several psychiatric and neurodevelopmental disorders. Both rare and common variants in RBFOX1 have been associated with several psychiatric conditions, but the mechanisms underlying the pleiotropic effects of RBFOX1 are not yet understood. Here we found that, in zebrafish, rbfox1 is expressed in spinal cord, mid- and hindbrain during developmental stages. In adults, expression is restricted to specific areas of the brain, including telencephalic and diencephalic regions with an important role in receiving and processing sensory information and in directing behaviour. To investigate the effect of rbfox1 deficiency on behaviour, we used rbfox1sa15940, a rbfox1 loss-of-function line. We found that rbfox1sa15940 mutants present hyperactivity, thigmotaxis, decreased freezing behaviour and altered social behaviour. We repeated these behavioural tests in a second rbfox1 loss-of-function line with a different genetic background, rbfox1del19, and found that rbfox1 deficiency affects behaviour similarly in this line, although there were some differences. rbfox1del19 mutants present similar thigmotaxis, but stronger alterations in social behaviour and lower levels of hyperactivity than rbfox1sa15940 fish. Taken together, these results suggest that rbfox1 deficiency leads to multiple behavioural changes in zebrafish that might be modulated by environmental, epigenetic and genetic background effects, and that resemble phenotypic alterations present in Rbfox1-deficient mice and in patients with different psychiatric conditions. Our study thus highlights the evolutionary conservation of rbfox1 function in behaviour and paves the way to further investigate the mechanisms underlying rbfox1 pleiotropy on the onset of neurodevelopmental and psychiatric disorders.
RBFOX1 is a highly pleiotropic gene that contributes to several psychiatric and neurodevelopmental disorders. Both rare and common variants in RBFOX1 have been associated with several psychiatric conditions, but the mechanisms underlying the pleiotropic effects of RBFOX1 are not yet understood. Here we found that, in zebrafish, rbfox1 is expressed in spinal cord, mid- and hindbrain during developmental stages. In adults, expression is restricted to specific areas of the brain, including telencephalic and diencephalic regions with an important role in receiving and processing sensory information and in directing behaviour. To investigate the effect of rbfox1 deficiency on behaviour, we used rbfox1sa15940, a rbfox1 loss-of-function line. We found that rbfox1sa15940 mutants present hyperactivity, thigmotaxis, decreased freezing behaviour and altered social behaviour. We repeated these behavioural tests in a second rbfox1 loss-of-function line with a different genetic background, rbfox1del19, and found that rbfox1 deficiency affects behaviour similarly in this line, although there were some differences. rbfox1del19 mutants present similar thigmotaxis, but stronger alterations in social behaviour and lower levels of hyperactivity than rbfox1sa15940 fish. Taken together, these results suggest that rbfox1 deficiency leads to multiple behavioural changes in zebrafish that might be modulated by environmental, epigenetic and genetic background effects, and that resemble phenotypic alterations present in Rbfox1-deficient mice and in patients with different psychiatric conditions. Our study thus highlights the evolutionary conservation of rbfox1 function in behaviour and paves the way to further investigate the mechanisms underlying rbfox1 pleiotropy on the onset of neurodevelopmental and psychiatric disorders.
The production of bulk chemicals mostly depends on exhausting petroleum sources and leads to emission of greenhouse gases. Within the last decades the urgent need for alternative sources has increased and the development of bio-based processes received new attention. To avoid the competition between the use of sugars as food or fuel, other feedstocks with high availability and low cost are needed, which brought acetogenic bacteria into focus. This group of anaerobic organisms uses mixtures of CO2, CO and H2 for the production of mostly acetate and ethanol. Also methanol, a cheap and abundant bulk chemical produced from methane, is a suitable substrate for acetogenic bacteria. In methylotrophic acetogens the methyl group is transferred to the Wood-Ljungdahl pathway, a pathway to reduce CO2 to acetate via a series of C1-intermediates bound to tetrahydrofolic acid. Here we describe the biochemistry and bioenergetics of methanol conversion in the biotechnologically interesting group of anaerobic, acetogenic bacteria. Further, the bioenergetics of biochemical production from methanol is discussed.
Hydrogen is a promising fuel in a carbon-neutral economy, and many efforts are currently undertaken to produce hydrogen. One of the challenges is to store and transport the highly explosive gas in a safe and easy way. One option that is intensively analyzed by chemists and biologists is the conversion of hydrogen and CO2 to formic acid, the liquid organic hydrogen carrier. Here, we demonstrate for the first time that a bio-based system, using Acetobacterium woodii as the biocatalyst, allows multiple cycles of bi-directional hydrogenation of CO2 to formic acid in one bioreactor. The process was kept running over 2 weeks producing and oxidizing 330 mM formic acid in total. Unwanted side-product formation of acetic acid was prevented through metabolic engineering of the organism. The demonstrated process design can be considered as a future “bio-battery” for the reversible storage of electrons in the form of H2 in formic acid, a versatile compound.
The establishment and maintenance of protected areas(PAs) is viewed as a key action in delivering post-2020 biodiversity targets. PAs often need to meet a multitude of objectives, ranging from biodiversity protection to ecosystem service provision and climate change mitigation. As available land and conservation funding are limited, optimizing resources by selecting the most beneficial PAs is vital. Here we present a decision support tool that enables a flexible approach to PA selection on a global scale, allowing different conservation objectives to be weighted and prioritized according to user-specified preferences. We apply the tool across 1347 terrestrial PAs and highlight frequent trade-offs among different objectives, e.g., between biodiversity protection and ecosystem integrity. These results indicate that decision makers must usually decide among conflicting objectives. To assist this our decision support tool provides an explicitly value-based approach that can help resolve such conflicts by considering divergent societal and political demands and values.
The establishment and maintenance of protected areas (PAs) is viewed as a key action in delivering post-2020 biodiversity targets. PAs often need to meet multiple objectives, ranging from biodiversity protection to ecosystem service provision and climate change mitigation, but available land and conservation funding is limited. Therefore, optimizing resources by selecting the most beneficial PAs is vital. Here, we advocate for a flexible and transparent approach to selecting protected areas based on multiple objectives, and illustrate this with a decision support tool on a global scale. The tool allows weighting and prioritization of different conservation objectives according to user-specified preferences, as well as real-time comparison of the selected areas that result from such different priorities. We apply the tool across 1347 terrestrial PAs and highlight frequent trade-offs among different objectives, e.g., between species protection and ecosystem integrity. Outputs indicate that decision makers frequently face trade-offs among conflicting objectives. Nevertheless, we show that transparent decision-support tools can reveal synergies and trade-offs associated with PA selection, thereby helping to illuminate and resolve land-use conflicts embedded in divergent societal and political demands and values.