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Microbial rhodopsins are omnipresent on Earth, however the vast majority of them remain uncharacterized. Here we describe a new rhodopsin clade from cold-adapted organisms and cold environments, such as glaciers, denoted as CryoRhodopsins (CryoRs). Our data suggest that CryoRs have photosensory activity. A distinguishing feature of the clade is the presence of a buried arginine residue close to the cytoplasmic face of its members. Combining single-particle cryo-electron microscopy and X-ray crystallography with the rhodopsin activation by light, we demonstrate that the arginine stabilizes a strongly blue-shifted intermediate of an extremely slow CryoRhodopsin photocycle. Together with extensive spectroscopic characterization, our investigations on CryoR1 and CryoR2 proteins reveal mechanisms of photoswitching in the newly identified clade and demonstrate principles of the adaptation of these rhodopsins to low temperatures.
Microbial rhodopsins are omnipresent on Earth, however the vast majority of them remain uncharacterized. Here we describe a new rhodopsin group from cold-adapted organisms and cold environments, such as glaciers, denoted as CryoRhodopsins (CryoRs). Our data suggest that CryoRs have dual functionality switching between inward transmembrane proton translocation and photosensory activity, both of which can be modulated with UV light. CryoR1 exhibits two subpopulations in the ground state, which upon light activation lead to transient photocurrents of opposing polarities. A distinguishing feature of the group is the presence of a buried arginine residue close to the cytoplasmic face of its members. Combining single-particle cryo-electron microscopy and X-ray crystallography with the rhodopsin activation by lit, we demonstrate that the arginine stabilizes a UV-absorbing intermediate of an extremely slow CryoRhodopsin photocycle. Together with extensive spectroscopic characterization, our investigations on CryoR1 and CryoR2 proteins reveal mechanisms of photoswitching in the newly identified group and demonstrate principles of the adaptation of these rhodopsins to low temperatures.Microbial rhodopsins are omnipresent on Earth, however the vast majority of them remain uncharacterized. Here we describe a new rhodopsin group from cold-adapted organisms and cold environments, such as glaciers, denoted as CryoRhodopsins (CryoRs). Our data suggest that CryoRs have dual functionality switching between inward transmembrane proton translocation and photosensory activity, both of which can be modulated with UV light. CryoR1 exhibits two subpopulations in the ground state, which upon light activation lead to transient photocurrents of opposing polarities. A distinguishing feature of the group is the presence of a buried arginine residue close to the cytoplasmic face of its members. Combining single-particle cryo-electron microscopy and X-ray crystallography with the rhodopsin activation by light, we demonstrate that the arginine stabilizes a UV-absorbing intermediate of an extremely slow CryoRhodopsin photocycle. Together with extensive spectroscopic characterization, our investigations on CryoR1 and CryoR2 proteins reveal mechanisms of photoswitching in the newly identified group and demonstrate principles of the adaptation of these rhodopsins to low temperatures.
Methods using environmental DNA to explore and analyze biodiversity from previously unexplored habitats and ecosystems have become increasingly popular in recent years. This is particularly due to the potential reduction in necessary taxonomic expertise, the opportunity to assess microorganismal communities, and decreased time investments required to cover large spatial extents. In forests, the surface of tree bark is an important habitat for epiphytic diversity. Because of the large surface area rich in micro-niches, the seasonal stability of the substrate, and the longevity of trees, tree bark surfaces provide an ideal habitat for many species. Yet, we lack a comprehensive understanding of their communities and the environmental drivers behind the community assembly. These missing links hinder the exploration of the forest microbiome as a whole and limits our understanding of functions of a large forest habitat and its connections to other forest microbiomes. With a holistic eDNA metabarcoding approach, encompassing samples of three major taxonomic groups (e.g. bacteria, fungi, and green algae), as well as simultaneous collections from multiple forest habitats we can contribute to closing these gaps and increase our knowledge of the forest microbiome.
My dissertation is set within the framework of the Biodiversity Exploratories and was conducted in four parts: I. the establishment of an eDNA metabarcoding workflow to reveal the local diversity of the bark surface microbiome; II. the upscaling of the method to large geographic and environmental gradients to uncover the drivers of the microbiome; III. the integration of soil and bark samples to investigate compositional differences in two important forest habitats; IV. the evaluation of eDNA metabarcoding as a tool for biodiversity assessments of lichen diversity in forests.
In the first part, I developed a simple, cost-effective and fast sampling strategy to acquire eDNA samples from the bark of trees in forest ecosystems. Using readily available medical-specimen-collection swabs I sampled bark surfaces of individual trees in Central German forests and used metabarcoding to amplify marker genes of green algae, fungi and bacteria. From the sequencing reads I calculated the first diversity estimates of the major organismal groups of bark surface microbiomes from Central European forests. Overall the methodology produced reliable results, allowing for an expanded sampling in the second part.
In the second part of the dissertation, I expanded the sampling based on the results of part one. I collected bark surface samples from the three regions of the Biodiversity Exploratories covering large spatial and environmental gradients representative for Central European forests. The collection included composite samples from 150 plots and over 750 trees. Utilizing measurements of climatic and forest structure variables provided by the Biodiversity Exploratories, as well as my own community data, I identified the biotic and abiotic drivers behind alpha and beta diversity of the bark surface microbiome.
In the third part, I studied the differences between the bark surface as an unexplored and the soil as an example of a well characterized forest microbiome. Using only the fungal part of the large sampling campaign and soil samples obtained from the same plots at the same time, I assessed the commonalities and differences of the micro-communities of these distinct forest niches. Furthermore, I included two coniferous and one deciduous tree species to examine, if the effect of tree species, previously shown for soil microbiomes, also holds true for the bark surface.
In the last part of my dissertation, I used eDNA in a more applied way as a tool in biodiversity assessments of lichenized fungi. I compared the results from eDNA metabarcoding to an expert floristic mapping conducted in the same plots in 2007/2008. I assigned functional guilds to the fungal taxa obtained in the large sampling campaign and used a subset that was assigned as lichenized fungi.
In conclusion, I showed that eDNA metabarcoding is a valuable tool to reveal the unknown diversity of microorganisms in forest ecosystems. In particular, my results advance our understanding of the bark surface microbiome, an underexplored habitat within forests. The tightly linked interactions of the three major microbial groups underline that studies need to take holistic approaches across multiple taxonomic groups to deepen our understanding of processes governing the assembly of microbiomes. Results from my dissertation may serve as a foundation to inform hypotheses addressing the functions of forest microbiomes. The massive diversity data collected may also contribute to closing the gap in our understanding of macro-organisms and micro-organisms with respect to diversity distributions and patterns of richness, and serve as a baseline for predictions of biodiversity responses under future anthropogenic change.
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.
IHMCIF: an extension of the PDBx/mmCIF data standard for integrative structure determination methods
(2024)
IHMCIF (github.com/ihmwg/IHMCIF) is a data information framework that supports archiving and disseminating macromolecular structures determined by integrative or hybrid modeling (IHM), and making them Findable, Accessible, Interoperable, and Reusable (FAIR). IHMCIF is an extension of the Protein Data Bank Exchange/macromolecular Crystallographic Information Framework (PDBx/mmCIF) that serves as the framework for the Protein Data Bank (PDB) to archive experimentally determined atomic structures of biological macromolecules and their complexes with one another and small molecule ligands (e.g., enzyme cofactors and drugs). IHMCIF serves as the foundational data standard for the PDB-Dev prototype system, developed for archiving and disseminating integrative structures. It utilizes a flexible data representation to describe integrative structures that span multiple spatiotemporal scales and structural states with definitions for restraints from a variety of experimental methods contributing to integrative structural biology. The IHMCIF extension was created with the benefit of considerable community input and recommendations gathered by the Worldwide Protein Data Bank (wwPDB) Task Force for Integrative or Hybrid Methods (wwpdb.org/task/hybrid). Herein, we describe the development of IHMCIF to support evolving methodologies and ongoing advancements in integrative structural biology. Ultimately, IHMCIF will facilitate the unification of PDB-Dev data and tools with the PDB archive so that integrative structures can be archived and disseminated through PDB.
The spike protein of SARS-CoV-2 is a highly flexible membrane receptor that triggers the translocation of the virus into cells by attaching to the human receptors. Like other type I membrane receptors, this protein has several extracellular domains connected by flexible hinges. The presence of these hinges results in high flexibility, which consequently results in challenges in defining the conformation of the protein. Here, We developed a new method to define the conformational space based on a few variables inspired by the robotic field’s methods to determine a robotic arm’s forward kinematics. Using newly performed atomistic molecular dynamics (MD) simulations and publicly available data, we found that the Denavit-Hartenberg (DH) parameters can reliably show the changes in the local conformation. Furthermore, the rotational and translational components of the homogenous transformation matrix constructed based on the DH parameters can identify the changes in the global conformation of the spike and also differentiate between the conformation with a similar position of the spike head, which other types of parameters, such as spherical coordinates, fail to distinguish between such conformations. Finally, the new method will be beneficial for looking at the conformational heterogeneity in all other type I membrane receptors.
Highlights
• Sampling the large conformational space of disordered proteins requires extensive molecular dynamics (MD) simulations.
• Fragment assembly complements MD simulations to produce extensive ensembles of disordered proteins with atomic detail.
• Hierarchical chain growth (HCG) ensembles capture key experimental descriptors “out of the box”.
• HCG has revealed local structural characteristics associated with protein dysfunction in neurodegeneration.
Abstract
Disordered proteins and nucleic acids play key roles in cellular function and disease. Here, we review recent advances in the computational exploration of the conformational dynamics of flexible biomolecules. While atomistic molecular dynamics (MD) simulation has seen a lot of improvement in recent years, large-scale computing resources and careful validation are required to simulate full-length disordered biopolymers in solution. As a computationally efficient alternative, hierarchical chain growth (HCG) combines pre-sampled chain fragments in a statistically reproducible manner into ensembles of full-length atomically detailed biomolecular structures. Experimental data can be integrated during and after chain assembly. Applications to the neurodegeneration-linked proteins α-synuclein, tau, and TDP-43, including as condensate, illustrate the use of HCG. We conclude by highlighting the emerging connections to AI-based structural modeling including AlphaFold2.
From hunting and foraging to clearing land for agriculture, humans modify forest biodiversity, landscapes, and climate. Forests constantly undergo disturbance–recovery dynamics and understanding them is a major objective of ecologists and conservationists. Chronosequences are a useful tool for understanding global restoration efforts. They represent a space-for-time substitution approach suited for the quantification of the resistance of ecosystem properties to withstand disturbance and the resilience of these properties until reaching pre-disturbance levels. Here we introduce a newly established chronosequence with 62 plots (50 ⍰ 50 m) in active cacao plantations and pastures, early and late regeneration, and mature old-growth forests, across a 200 km2 area in the extremely wet Chocó rainforest. Our chronosequence covers by far the largest total area of plots compared to others in the Neotropics. Plots ranged from 159–615 masl in a forested landscape with 74 ± 2.8 % forest cover within a 1-km radius including substantial old-growth forest cover. Land-use legacy and regeneration time were not confounded by elevation. We tested how six forest structure variables (maximum tree height and DBH, basal area, number of stems, vertical vegetation heterogeneity, and light availability), aboveground biomass (AGB), and rarefied tree species richness change along our chronosequence. Forest structure variables, AGB, and tree species richness increased with regeneration time and are predicted to reach similar levels to those in old-growth forests after ca. 30–116, 202, and 108 yrs, respectively. Compared to previous work in the Neotropics, old-growth forests in Canandé accumulate high AGB that takes one of the largest time spans reported until total recovery. Our chronosequence comprises one of the largest tree species pools, covers the largest total area of regenerating and old-growth forests, and has higher forest cover than other Neotropical chronosequences. Hence, our chronosequence can be used to determine the time for recovery and stability (resistance and resilience) of different taxa and ecosystem functions, including species interaction networks. This integrative effort will ultimately help to understand how one of the most diverse forests on the planet recovers from large-scale disturbances.
Pin1 is a peptidyl-prolyl cis/trans isomerase (PPIase) essential for cell cycle regulation. Pin1-catalyzed peptidyl-prolyl isomerization provides a key conformational switch to activate phosphorylation sites with the common phospho-Ser/Thr-Pro sequence motif. This motif is ubiquitously exploited in cellular response to a variety of signals. Pin1 is able to bind phospho-Ser/Thr-Pro-containing sequences at two different sites that compete for the same substrate. One binding site is located within the N-terminal WW domain, which is essential for protein targeting and localization. The other binding site is located in the C-terminal catalytic domain, which is structural homologous to the FK506-binding protein (FKBP) class of PPIases. A flexible linker of 12 residues connects the WW and catalytic domain. To characterize the structure and dynamics of full-length Pin1 in solution, high resolution NMR methods have been used to map the nature of interactions between the two domains of Pin1. In addition, the influence of target peptides on domain interactions has been investigated. The studies reveal a dynamic picture of the domain interactions. 15N spin relaxation data, differential chemical shift mapping, and residual dipolar coupling data indicate that Pin1 can either behave as two independent domains connected by the flexible linker or as a single intact domain with some amount of hinge bending motion depending on the sequence of the bound peptide. The functional importance of the modulation of relative domain flexibility in light of the multitude of interaction partners of Pin1 is discussed.
Inhibition of the soluble epoxide hydrolase (sEH) has beneficial effects on vascular inflammation and hypertension indicating that the enzyme may be a promising target for drug development. As the enzymatic core of the hydrolase domain of the human sEH contains two tyrosine residues (Tyr383 and Tyr466) that are theoretically crucial for enzymatic activity, we addressed the hypothesis that the activity of the sEH may be affected by nitrosative stress. Epoxide hydrolase activity was detected in human and murine endothelial cells as well in HEK293 cells and could be inhibited by either authentic peroxynitrite (ONOO−) or the ONOO− generator 3-morpholino-sydnonimine (SIN-1). Protection of the enzymatic core with 1-adamantyl-3-cyclohexylurea in vitro decreased sensitivity to SIN-1. Both ONOO− and SIN-1 elicited the tyrosine nitration of the sEH protein and mass spectrometry analysis of tryptic fragments revealed nitration on several tyrosine residues including Tyr383 and Tyr466. Mutation of the latter residues to phenylalanine was sufficient to abrogate epoxide hydrolase activity. In vivo, streptozotocin-induced diabetes resulted in the tyrosine nitration of the sEH in murine lungs and a significant decrease in its activity. Taken together, these data indicate that the activity of the sEH can be regulated by the tyrosine nitration of the protein. Moreover, nitrosative stress would be expected to potentiate the physiological actions of arachidonic acid epoxides by preventing their metabolism to the corresponding diols.