Biology subjects

Stoll, S.

Publications and source records attributed to Stoll, S..

14 recordsLinked to original sources

bioRxiv2025

Towards a multi-metric assessment of river restoration ecological outcomes across projects and contexts

The assessment of the ecological outcomes of river restoration projects remains a complex undertaking due to the high variability of responses observed. This variability is dependent on a number of factors, including the location of the site under study, the indicators and taxa utilised in the analysis. In this study, a multi-metric and multi-contextual approach was applied to analyse 62 river restoration projects located in France, Germany and the Netherlands. This methodological approach facilitated the characterisation of the responses exhibited by macroinvertebrate communities in response to restoration initiatives, and the subsequent identification of the environmental contexts and the categories of restoration measures that exerted influence on these responses. Utilising log-response ratios based on both taxonomic and functional ecological metrics, a k-means clustering analysis was performed. This analysis yielded two distinct groups of sites: the first exhibiting predominantly positive responses to restoration, and the second demonstrating neutral or marginally negative responses. Positive responses have been shown to be associated with ambitious restoration projects, which are characterised by measures targeting regional-scale processes. These measures include the implementation of projects designed to improve river longitudinal continuity in degraded catchment areas, where the density of obstacles and the intensity of agricultural use are particularly high. Conversely, restoration initiatives targeting local-scale issues within more natural contexts or at high altitude exhibited minimal to no ecological response. This study emphasises the significance of an integrated approach that incorporates various facets (taxonomic and functional) of biodiversity, along with a meticulous examination of the environmental context and project construction, to enhance the evaluation of the ecological benefits of river restoration. The findings of this study may also be applicable in the context of fieldwork, providing practitioners with a framework to inform the design of restoration projects.

ecology↗

bioRxiv2025

Modeling 2D Spatio-Tactile Population Receptive Fields of the Fingertip in Human Primary Somatosensory Cortex

Tactile fingertip sensations are critical for everyday life. Accordingly, tactile fingertip maps have been extensively studied in human primary somatosensory cortex. However, the fine-grained functional architecture of these maps remains largely unknown. To uncover this architecture, we sought to estimate 2D spatio-tactile population receptive fields (pRFs) of the tip of the index finger in human Brodmann area 3b (BA3b). Using functional magnetic resonance imaging at 7T and submillimeter resolution along with prospective motion correction, we recorded brain responses whilst participants sensed a row of vibrotactile pins sweeping along cardinal axes over a portion of the fingertip. To estimate pRF position and size, we initially fit a 2D Gaussian pRF model to the data, which, however, produced largely implausible pRF estimates. Simulations indicated that this likely occurred because the size of pRFs in BA3b surpasses the portion of the fingertip we stimulated, resulting in an incomplete mapping of pRFs. To address this issue, we constrained the fitting procedure and refined the 2D Gaussian pRF model by keeping pRF size constant. Our results for pRF position then revealed that the ulnar-to-radial axis spanning the fingertip maps onto a superior-to-inferior axis in BA3b. Both the putatively large pRF size (relative to the mapping area) and the pRF position gradient we uncover here appear compatible with receptive field properties quantified in monkeys. Our study provides the first comprehensive investigation into the fine-grained functional architecture of human fingertip maps and brings us one step closer to a thorough understanding thereof.

neuroscience↗

bioRxiv2024

Design of facilitated dissociation enables control over cytokine signaling duration

Protein design has focused primarily on the design of ground states, ensuring they are sufficiently low energy to be highly populated1. Designing the kinetics and dynamics of a system requires, in addition, the design of excited states that are traversed in transitions from one low-lying state to another2,3. This is a challenging task as such states must be sufficiently strained to be poorly populated, but not so strained that they are not populated at all, and because protein design methods have generally focused on creating near-ideal structures4-7. Here we describe a general approach for designing systems which use an induced-fit power stroke8 to generate a structurally frustrated9 and strained excited state, allosterically driving protein complex dissociation. X-ray crystallography, double electron-electron resonance spectroscopy, and kinetic binding measurements demonstrate that incorporating excited states enables design of effector-induced increases in dissociation rates as high as 6000-fold. We highlight the power of this approach by designing cytokine mimics which can be dissociated within seconds from their receptors.

biochemistry↗

bioRxiv2023

Long-distance tmFRET using bipyridyl- and phenanthroline-based ligands

With the great progress on determining protein structures over the last decade comes a renewed appreciation that structures must be combined with dynamics and energetics to understand function. Fluorescence spectroscopy, specifically Forster resonance energy transfer (FRET), provides a great window into dynamics and energetics due to its application at physiological temperatures and ability to measure dynamics on the [a]ngstrom scale. We have recently advanced transition metal FRET (tmFRET) to study allosteric regulation of maltose binding protein and have reported measurements of maltose- dependent distance changes with an accuracy of [~]1.5 [A]. When paired with the noncanonical amino acid Acd as a donor, our previous tmFRET acceptors were useful over a working distance of 10 [A] to 20 [A]. Here, we use cysteine-reactive bipyridyl and phenanthroline compounds as chelators for Fe2+ and Ru2+ to produce novel tmFRET acceptors to expand the working distance to as long as 50 [A], while preserving our ability to resolve even small maltose-dependent changes in distance. We compare our measured FRET efficiencies to predictions based on models using rotameric ensembles of the donors and acceptors to demonstrate that steady-state measurements of tmFRET with our new probes have unprecedented ability to measure conformational rearrangements under physiological conditions. STATEMENT OF SIGNIFICANCEIn this work, we expand the working distance of transition metal ion Forster Resonance Energy Transfer (tmFRET) to allow the measurement of donor-acceptor distances from 10 [A] to 50 [A]. We develop new cysteine-reactive bipyridyl- and phenanthroline-based ligands for Cu2+, Fe2+, and Ru2+ and examine their ability to resolve small ligand-dependent distance changes in maltose binding protein. We extend these studies using pulsed electron paramagnetic resonance spectroscopy to demonstrate the high accuracy of tmFRET for studying protein allostery.

biophysics↗

bioRxiv2023

Measuring conformational equilibria in allosteric proteins with time-resolved tmFRET

Proteins are the workhorses of biology, orchestrating a myriad of cellular functions through intricate conformational changes. Protein allostery, the phenomenon where binding of ligands or environmental changes induce conformational rearrangements in the protein, is fundamental to these processes. We have previously shown that transition metal Forster resonance energy transfer (tmFRET) can be used to interrogate the conformational rearrangements associated with protein allostery and have recently introduced novel FRET acceptors utilizing metal-bipyridyl derivatives to measure long (>20 [A]) intramolecular distances in proteins. Here, we combine our tmFRET system with fluorescence lifetime measurements to measure the distances, conformational heterogeneity, and energetics of maltose binding protein (MBP), a model allosteric protein. Time-resolved tmFRET captures near-instantaneous snapshots of distance distributions, offering insights into protein dynamics. We show that time-resolved tmFRET can accurately determine distance distributions and conformational heterogeneity of proteins. Our results demonstrate the sensitivity of time-resolved tmFRET in detecting subtle conformational or energetic changes in protein conformations, which are crucial for understanding allostery. In addition, we extend the use of metal-bipyridyl compounds, showing Cu(phen)2+ can serve as a spin label for pulse dipolar electron paramagnetic resonance (EPR) spectroscopy, a method which also reveals distance distributions and conformational heterogeneity. The EPR studies both establish Cu(phen)2+ as a useful spin label for pulse dipolar EPR and validate our time-resolved tmFRET measurements. Our approach offers a versatile tool for deciphering conformational landscapes and understanding the regulatory mechanisms governing biological processes. STATEMENT OF SIGNIFICANCEResponsible for the regulation of virtually all biological processes, allosteric proteins are fundamental to all life. To understand the mechanisms for their vital functions, we must determine the structure and energetics of these proteins under physiological conditions. In this work, we have developed a fluorescence method that allows for the simultaneous measurement of protein structure and energetics under physiological conditions. These studies pave the way for future advances in physiology and medicine.

biophysics↗

bioRxiv2023

Vocal-visual combinations in wild chimpanzees

Human communication is strikingly multi-modal, relying on vocal utterances combined with visual gestures, facial expressions and more. Recent efforts to describe multi-modal signal production in our ape relatives have shed important light on the evolutionary trajectory of this core hallmark of human language. However, whilst promising, a systematic quantification of primate signal production which filters out random combinations produced across modalities is currently lacking. Here, through recording the communicative behaviour of wild chimpanzees from the Kibale forest, Uganda we address this issue and generate the first repertoire of non-random combined vocal and visual components. Using collocation analysis, we identify more than 100 vocal-visual combinations which occur more frequently than expected by chance. We also probe how multi-modal production varies in the population, finding no differences between individuals as a function of age, sex or rank. The number of visual components exhibited alongside vocalizations was, however, associated with vocalization type and duration. We demonstrate that chimpanzees produce a vast array of combined vocal and visual components, exhibiting a hitherto underappreciated level of combinatorial complexity. We conclude that a multi-modal approach is crucial to accurately representing the communicative abilities of non-human primates.

animal behavior and cognition↗

bioRxiv2023

A novel approach to modeling side chain ensembles of the bifunctional spin label RX

We introduce a novel approach to modeling side chain ensembles of bifunctional spin labels. This approach utilizes rotamer libraries to generate side chain conformational ensembles. Because the bifunctional label is constrained by two attachment sites, the label is split into two monofunctional rotamers which are first attached to their respective sites, then rejoined by a local optimization in dihedral space. We validate this method against a set of previously published experimental data using the bifunctional spin label, RX. This method is relatively fast and can readily be used for both experimental analysis and protein modeling, providing significant advantages over modeling bifunctional labels with molecular dynamics simulations. Use of bifunctional labels for site directed spin labeling (SDSL) electron paramagnetic resonance (EPR) spectroscopy dramatically reduces label mobility, which can significantly improve resolution of small changes in protein backbone structure and dynamics. Coupling the use of bifunctional labels with side chain modeling methods allows for improved quantitative application of experimental SDSL EPR data to protein modeling. Statements and DeclarationsThe authors declare no competing interests.

biophysics↗

bioRxiv2023

Design of stimulus-responsive two-state hinge proteins

Proteins that switch between two structural states as a function of environmental stimuli are widespread in nature. These proteins structurally transduce biochemical information in a manner analogous to how transistors control information flow in computing devices. Engineering challenges ranging from biological computing devices to molecular motors require such two-state switches, but designing these is an unsolved problem as it requires sculpting an energy landscape with two low-energy but structurally distinct conformations that can be modulated by external inputs. Here we describe a general design approach for creating "hinge" proteins that populate one distinct state in the absence of ligand and a second designed state in the presence of ligand. X-ray crystallography, electron microscopy, and double electron-electron resonance spectroscopy demonstrate that despite the significant structural differences, the two states are designed with atomic level accuracy. The kinetics and thermodynamics of effector binding can be finely tuned by modulating the free energy differences between the two states; when this difference becomes sufficiently small, we obtain bistable proteins that populate both states in the absence of effector, but collapse to a single state upon effector addition. Like the transistor, these switches now enable the design of a wide array of molecular information processing systems.

biophysics↗

bioRxiv2023

Ultra-Fast Bioorthogonal Spin-Labeling and Distance Measurements in Mammalian Cells Using Small, Genetically Encoded Tetrazine Amino Acids

Studying protein structures and dynamics directly in the cellular environments in which they function is essential to fully understand the molecular mechanisms underlying cellular processes. Site-directed spin-labeling (SDSL)--in combination with double electron-electron resonance (DEER) spectroscopy--has emerged as a powerful technique for determining both the structural states and the conformational equilibria of biomacromolecules. In-cell DEER spectroscopy on proteins in mammalian cells has thus far not been possible due to the notable challenges of spin-labeling in live cells. In-cell SDSL requires exquisite biorthogonality, high labeling reaction rates and low background signal from unreacted residual spin label. While the bioorthogonal reaction must be highly specific and proceed under physiological conditions, many spin labels display time-dependent instability in the reducing cellular environment. Additionally, high concentrations of spin label can be toxic. Thus, an exceptionally fast bioorthogonal reaction is required that can allow for complete labeling with low concentrations of spin-label prior to loss of signal. Here we utilized genetic code expansion to site-specifically encode a novel family of small, tetrazine-bearing non-canonical amino acids (Tet-v4.0) at multiple sites in green fluorescent protein (GFP) and maltose binding protein (MBP) expressed both in E. coli and in human HEK293T cells. We achieved specific and quantitative spin-labeling of Tet-v4.0-containing proteins by developing a series of strained trans-cyclooctene (sTCO)-functionalized nitroxides--including a gem-diethyl-substituted nitroxide with enhanced stability in cells--with rate constants that can exceed 106 M-1 s-1. The remarkable speed of the Tet-v4.0/sTCO reaction allowed efficient spin-labeling of proteins in live HEK293T cells within minutes, requiring only sub-micromolar concentrations of sTCO-nitroxide added directly to the culture medium. DEER recorded from intact cells revealed distance distributions in good agreement with those measured from proteins purified and labeled in vitro. Furthermore, DEER was able to resolve the maltose-dependent conformational change of Tet-v4.0-incorporated and spin-labeled MBP in vitro and successfully discerned the conformational state of MBP within HEK293T cells. We anticipate the exceptional reaction rates of this system, combined with the relatively short and rigid side chains of the resulting spin labels, will enable structure/function studies of proteins directly in cells, without any requirements for protein purification. TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/525763v2_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1251523org.highwire.dtl.DTLVardef@18ee6ddorg.highwire.dtl.DTLVardef@d6d4b0org.highwire.dtl.DTLVardef@259a53_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2022

chiLife: An open-source Python package for in silico spin labeling and integrative protein modeling

Here we introduce chiLife, a Python package for site-directed spin label (SDSL) modeling for electron paramagnetic resonance (EPR) spectroscopy, in particular double electron-electron resonance (DEER). It is based on in silico attachment of rotamer ensemble representations of spin labels to protein structures. chiLife enables the development of custom protein analysis and modeling pipelines using SDSL EPR experimental data. It allows the user to add custom spin labels, scoring functions and spin label modeling methods. chiLife is designed with integration into third-party software in mind, to take advantage of the diverse and rapidly expanding set of molecular modeling tools available with a Python interface. This article describes the main design principles of chiLife and presents a series of examples. Author summaryThanks to modern modeling methods like AlphaFold2, RosettaFold, and ESMFold, high-resolution structural models of proteins are widely available. While these models offer insight into the structure and function of biomedically and technologically significant proteins, most of them are not experimentally validated. Furthermore, many proteins exhibit functionally important conformational flexibility that is not captured by these models. Site-directed spin labeling (SDSL) electron paramagnetic resonance (EPR) spectroscopy is a powerful tool for probing protein structure and conformational heterogeneity, making it ideal for validating, refining, and expanding protein models. To extract quantitative protein backbone information from experimental SDSL EPR data, accurate modeling methods are needed. For this purpose, we introduce chiLife, an open-source Python package for SDSL modeling designed to be extensible and integrable with other Python-based protein modeling packages. With chiLife, appropriate SDSL EPR experiments for protein model validation can be designed, and protein models can be refined using experimental SDSL EPR data as constraints.

biophysics↗

bioRxiv2021

From collocations to call-ocations: using linguistic methods to quantify animal call combinations

Emerging data in a range of non-human animal species have highlighted a latent ability to combine certain pre-existing calls together into larger structures. Currently, however, there exists no objective quantification of call combinations. This is problematic because animal calls can co-occur with one another simply through chance alone. One common approach applied in language sciences to identify recurrent word combinations is collocation analysis. Through comparing the co-occurrence of two words with how each word combines with other words within a corpus, collocation analysis can highlight above chance, two-word combinations. Here, we demonstrate how this approach can also be applied to non-human animal communication systems by implementing it on a pseudo dataset. We argue collocation analysis represents a promising tool for identifying non-random, communicatively relevant call combinations in animals.

animal behavior and cognition↗

bioRxiv2021

Climate, latitude, and land cover predict flying insect biomass across a German malaise trap network

O_LIAmong the many concerns for biodiversity in the Anthropocene, recent reports of flying insect loss are particularly alarming, given their importance as pollinators and as a food source for many predators. Few insect monitoring programs cover large spatial scales required to provide more generalizable estimates of insect responses to global change drivers. C_LIO_LIWe ask how climate and surrounding habitat affect flying insect biomass and day of peak biomass using data from the first year of a new standardized distributed monitoring network at 84 locations across Germany comprising spatial gradient of land-cover types from protected to urban areas. C_LIO_LIFlying insect biomass increased linearly with monthly temperature across Germany. However, the effect of temperature on flying insect biomass flipped to negative in the hot months of June and July when local temperatures most exceeded long-term averages. C_LIO_LILand-cover explained little variation in insect biomass, but biomass was lowest in forested sites. Grasslands, pastures and orchards harbored the highest insect biomass. The date of peak biomass was primarily driven by surrounding land-cover type, with grasslands especially having earlier insect biomass phenologies. C_LIO_LIStandardized, large-scale monitoring is pivotal to uncover underlying processes of insect decline and to develop climate-adapted strategies to promote insect diversity. In a temperate climate region, we find that the benefits of temperature on flying insect biomass diminish in a German summer at locations where temperatures most exceeded long-term averages. These results highlighting the importance of local adaptation in climate change-driven impacts on insect communities. C_LI

ecology↗

bioRxiv2020

Flaws in Data Binning for Population Receptive Field Analyses

Data binning involves grouping observations into bins and calculating bin-wise summary statistics. It can cope with overplotting and noise, making it a versatile tool for comparing many observations. However, data binning goes awry if the same observations are used for binning (selection) and contrasting (selective analysis). This creates circularity, biasing noise components and resulting in artifactual changes in the form of regression towards the mean. Importantly, these artifactual changes are a statistical necessity. Here, we use (null) simulations and empirical repeat data to expose this flaw in the scope of post hoc analyses of population receptive field data. In doing so, we reveal that the type of data analysis, data properties, and circular data cleaning are factors shaping the appearance of such artifactual changes. We furthermore highlight that circular data cleaning and circular sorting of change scores are selection practices that result in artifactual changes even without circular data binning. These pitfalls might have led to erroneous claims about changes in population receptive fields in previous work and can be mitigated by using independent data for selection purposes. Our evaluations highlight the urgency for us researchers to make the validation of analysis pipelines standard practice. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=116 SRC="FIGDIR/small/422942v3_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@11c0c73org.highwire.dtl.DTLVardef@7583d3org.highwire.dtl.DTLVardef@121cf6dorg.highwire.dtl.DTLVardef@b9340d_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LICircular data binning produces artifactual changes in the form of regression towards the mean C_LIO_LIAnalysis type, data properties, and circular data cleaning shape these artifactual changes C_LIO_LICircular data cleaning and sorting produce artifactual changes even without circular data binning C_LI

neuroscience↗

bioRxiv2019

Topographic Signatures of Global Object Perception in Human Visual Cortex

Our visual system readily groups dynamic fragmented input into global objects. How the brain represents such perceptual grouping remains however unclear. To address this question, we recorded brain responses using functional magnetic resonance imaging whilst observers perceived a dynamic bistable stimulus that could either be perceived globally (i.e., as a grouped and coherently moving shape) or locally (i.e., as ungrouped and incoherently moving elements). We further estimated population receptive fields and used these to back-project the brain activity during stimulus perception into visual space via a searchlight procedure. Global perception resulted in non-topographic suppression of responses in lower visual cortex accompanied by wide-spread enhancement in higher object-sensitive cortex. However, follow-up experiments indicated that higher object-sensitive cortex is suppressed if global perception lacks shape grouping, and that grouping-related suppression can be diffusely confined to stimulated sites once stimulus size is reduced. These results speak against a rigid between-area response amplitude code acting as a generic grouping mechanism and point to a within-area response amplitude code mediating the perception of figure and ground.

neuroscience↗