Search bioRxiv⌕ Search

Biology subjects

Kuehn, S.

Publications and source records attributed to Kuehn, S..

At least 37 records · Page 2Linked to original sources

Functional phases encode the response of the soil microbiome to environmental change

The metabolic activity of soil microbiomes plays a central role in carbon and nitrogen cycling. Given the changing climate, it is important to understand how the metabolism of natural communities responds to environmental change. However, the ecological, spatial, and chemical complexity of soils makes understanding the mechanisms governing the response of these communities to perturbations challenging. Here, we overcome this complexity by using dynamic measurements of metabolism in microcosms and modeling to reveal regimes where a few key mechanisms govern the response of soils to environmental change. We sample soils along a natural pH gradient, construct >1500 microcosms to perturb the pH, and quantify the dynamics of respiratory nitrate utilization, a key process in the nitrogen cycle. Despite the complexity of the soil microbiome, a minimal mathematical model with two variables, the quantity of active biomass in the community and the availability of a growth-limiting nutrient, quantifies observed nitrate utilization dynamics across soils and pH perturbations. Across environmental perturbations, changes in these two variables give rise to three functional regimes each with qualitatively distinct dynamics of nitrate utilization over time: a regime where acidic perturbations induce cell death that limits metabolic activity, a nutrientlimiting regime where nitrate uptake is performed by dominant taxa that utilize nutrients released from the soil matrix, and a resurgent growth regime in basic conditions, where excess nutrients enable growth of initially rare taxa. The underlying mechanism of each regime is predicted by our interpretable model and tested via amendment experiments, nutrient measurements, and sequencing. Further, our data suggest that the long-term history of environmental variation in the wild influences the transitions between functional regimes. Therefore, quantitative measurements and a mathematical model reveal the existence of qualitative regimes that capture the mechanisms and dynamics of a community responding to environmental change.

ecology↗

SARS-CoV-2 methyltransferase nsp10-16 in complex with natural and drug-like purine analogs for guiding structure-based drug discovery

Non-structural protein 10 (nsp10) and non-structural protein 16 (nsp16) are part of the RNA synthesis complex, which is crucial for the replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Nsp16 exhibits 2-O-methyltransferase activity during viral messenger RNA capping and is active in a heterodimeric complex with enzymatically inactive nsp10. It has been shown that inactivation of the nsp10-16 protein complex interferes severely with viral replication, making it a highly promising drug target. As information on ligands binding to the nsp10-16 complex (nsp10-16) is still scarce, we screened the active site for potential binding of drug-like and fragment-like compounds using X-ray crystallography. The screened set of 234 compounds consists of derivatives of the natural substrate S-adenosyl methionine (SAM) and adenine derivatives, of which some have been described previously as methyltransferase inhibitors and nsp16 binders. A docking study guided the selection of many of these compounds. Here we report structures of binders to the SAM site of nsp10-16 and for two of them, toyocamycin and sangivamycin, we present additional crystal structures in the presence of a second substrate, Cap0-analog/Cap0-RNA. The identified hits were tested for binding to nsp10-16 in solution and antiviral activity in cell culture. Our data provide important structural information on various molecules that bind to the SAM substrate site which can be used as novel starting points for selective methyltransferase inhibitor designs.

biochemistry↗

Statistical design of a synthetic microbiome that clears a multi-drug resistant gut pathogen

Engineering functional microbiomes is challenging due to complex interactions between bacteria and their environments1-6. Using a set of 848 gut commensal strains and clearance of multi-drug resistant Klebsiella pneumoniae (Kp-MH258) as a target function, we engineered a functional 15-member synthetic microbiome--SynCom15--through a statistical approach agnostic to strain phenotype, mechanism of action, bacterial interactions, or composition of natural microbiomes. Our approach involved designing, building, and testing 96 metagenomically diverse consortia, learning a generative model using community strain presence/absence as input, and distilling model constraints through statistical inference. SynCom15 cleared Kp-MH258 across in vitro, ex vivo, and in vivo environments, matching the efficacy of a fecal microbiome transplant in a clinically relevant murine model of infection. The mechanism of suppression by SynCom15 was related to fatty acid production coupled with environmental acidification. SynCom15 also suppressed other pathogens--Clostridioides difficile, Escherichia coli, and other K. pneumoniae strains--but through different mechanisms. Sensitivity analysis revealed models trained on strain presence/absence captured the statistical structure of pathogen suppression, illustrating that community representation was key to our approach succeeding. Our framework, Constraint Distillation, could be a general and efficient strategy for building emergent complex systems, offering a path towards synthetic ecology more broadly.

synthetic biology↗

A precision microgel platform to direct vascular morphogenesis in vitro

The dynamic organization of tissue development is reciprocally controlled by localized gradients of morphogens emanating from distinct clusters of cells that act as signaling centers1. While microgels2,3 have shown promise to recapitulate this process in engineered tissue constructs, their capacity to tailor morphogen distribution in space and time remained limited4-7. Here, we introduce a library of sulfated glycosaminoglycan (sGAG)-based microgels that offer unprecedented control over morphogen affinity (GUIDe, Gel Units to Instruct Development), thus enabling precise formation of concentration gradients. Multiparametric adjustment of the microgel charge patterns resulting from sGAG ionization was key to programmable morphogen release. The potential of our microgel system to guide tissue morphogenesis is demonstrated through the local administration of VEGF gradients in a microgel-in-gel in vitro vasculogenesis model and in hiPSC-derived kidney organoid cultures. Our micromaterials-based methodology offers valuable new options to mimic and modulate morphogen signaling centers, thereby advancing tissue/organ development research.

bioengineering↗

Common types of microdebris affect the physiology of reef-building corals

Marine debris, particularly microdebris (< 1 mm) poses a potential threat to marine life, including reef-building corals. While previous research has mainly focused on the impact of single polymer microplastics, the effects of natural microdebris, composed of a mixture of materials, have not been explored. Therefore, this study aimed to assess the effects of different microdebris, originating from major sources of pollution, on reef-building corals. For this, we exposed two scleractinian coral species, Pocillopora verrucosa and Stylophora pistillata, known to frequently ingest microplastics, to four types of microdebris in an 8-week laboratory experiment: fragmented environmental plastic debris, artificial fibers from clothing, residues from the automobile sector consisting of tire wear, brake abrasion, and varnish flakes, a single polymer microplastic treatment consisting of polyethylene particles, and a microdebris-free control treatment. Specifically, we (I) compared the effects of the different microdebris on coral growth, necrosis, and photosynthesis, (II) investigated the difference between the microdebris mixtures and the exposure to the single polymer treatment, and (III) identified potential mechanisms causing species-specific effects by contrasting the feeding responses of the two coral species on microdebris and natural food. We show that the fibers and tire wear had the strongest effects on coral physiology, with P. verrucosa being more affected than S. pistillata. Both species showed increased volume growth in response to the microdebris treatments, accompanied by decreased calcification in P. verrucosa. Photosynthetic efficiency of the symbionts was enhanced in both species. The species-specific physiological responses might be attributed to feeding reactions, with P. verrucosa responding significantly more often to microdebris than S. pistillata. These findings highlight the effect of different microdebris on coral physiology and the need for future studies to use particle mixtures to better mimic naturally occurring microdebris and assess its effect on corals in more detail. HighlightsO_LIThe effects of major sources of microdebris pollution on coral physiology were compared. C_LIO_LIOverall, microdebris had only minor impacts on coral physiology. C_LIO_LIArtificial fibers and tire wear caused the strongest effect on coral physiology. C_LIO_LISingle polymer and complex microdebris caused similar, yet species-specific effects. C_LIO_LISpecies-specific effects might be due to different feeding behaviors. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/569976v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@1ba7ba8org.highwire.dtl.DTLVardef@c5795org.highwire.dtl.DTLVardef@4a10deorg.highwire.dtl.DTLVardef@9983e5_HPS_FORMAT_FIGEXP M_FIG C_FIG

physiology↗

Linking cognitive integrity to working memory dynamics in the aging human brain

Aging is accompanied by a decline of multiple cognitive capacities, including working memory: the ability to maintain information online for the flexible control of behavior. Working memory involves stimulus-selective neural activity, persisting after stimulus presentation in widely distributed cortical areas. Here, we unraveled the mechanisms of working memory in healthy older adults and patients with mild cognitive impairment (MCI), a condition associated with increased risk of developing dementia. We studied a sample of 19 older adults diagnosed with MCI and 20 older healthy controls using a combination of model-based behavioral psychophysics, neuropsychological assessment, and magnetoencephalographic (MEG) recordings of brain activity. Twenty-one younger healthy adults were studied with model-based behavioral psychophysics only. All subjects performed a visuo-spatial delayed-match-to-sample working memory task under systematic manipulation of the temporal delay and the spatial distance between successively presented sample and test stimuli. We developed a computational model of the latent dynamics underlying task behavior and fit this to individual behavior. In the model, working memory representations diffused over time, a threshold was applied to produce a match/non-match decision about sample and test locations, and occasional lapses produced random decisions. For the older participants, we related the individual model parameters to a summary measure of individual cognitive integrity obtained from a large neuropsychological test battery, as well as to cortical MEG activity during the delay interval of the working memory task. For all groups, task accuracy decreased with delay duration and sample-test distance. When sample/test distances were small, older adults exhibited larger false alarm rates than younger adults. The behavioral effects were well captured by the model, which explained the age-related differences in terms of a deterioration of the quality of working memory representations, rather than differences in task strategy (i.e., threshold parameter). Task accuracy as well as the parameters governing behavioral stochasticity (diffusion noise and lapse rate combined) were correlated with overall cognitive integrity in the MCI group, but not in the older healthy controls. Individual task accuracy and stochasticity parameters (diffusion noise and lapse rate) were also correlated with stimulus-selective cortical activity during the delay interval, as assessed by decoding of the MEG signals, corroborating their validity as markers of cortical working memory mechanisms. Our findings provide insight into the mechanistic basis of aging-related changes in working memory maintenance and reveal a link between individual working memory dynamics and cognitive integrity in MCI.

neuroscience↗

Statistical prediction of microbial metabolic traits from genomes

The metabolic activity of microbial communities is central to their role in biogeochemical cycles, human health, and biotechnology. Despite the abundance of sequencing data characterizing these consortia, it remains a serious challenge to predict microbial metabolic traits from sequencing data alone. Here we culture 96 bacterial isolates individually and assay their ability to grow on 10 distinct compounds as a sole carbon source. Using these data as well as two existing datasets, we show that statistical approaches can accurately predict bacterial carbon utilization traits from genomes. First, we show that classifiers trained on gene content can accurately predict bacterial carbon utilization phenotypes by encoding phylogenetic information. These models substantially outperform predictions made by constraint-based metabolic models automatically constructed from genomes. However, phylogeny-based predictions fail to predict traits for taxa that are phyloge-netically distant from any strains in the training set. To overcome this we train improved models on gene presence/absence to predict carbon utilization traits from gene content. We show that models that predict carbon utilization traits from gene presence/absence can generalize to taxa that are phylogenetically distant from the training set either by exploiting biochemical information for feature selection or by having sufficiently large datasets. In the latter case, we provide evidence that a statistical approach can identify putatively mechanistic genes involved in metabolic traits. Our study demonstrates the potential power for predicting microbial phenotypes from genotypes using statistical approaches.

ecology↗

Genomic patterns in the global soil microbiome emerge from microbial interactions

Microbial metabolism sustains life on Earth. Sequencing surveys of communities in hosts, oceans, and soils have revealed ubiquitous patterns linking the microbes present, the genes they possess, and local environmental conditions. One prominent explanation for these patterns is environmental filtering: local conditions select strains with particular traits. However, filtering assumes ecological interactions do not influence patterns, despite the fact that interactions can and do play an important role in structuring communities. Here, we demonstrate the insufficiency of the environmental filtering hypothesis for explaining global patterns in topsoil microbiomes. Using denitrification as a model system, we find that the abundances of two characteristic genotypes trade-off with pH; nar gene abundances increase while nap abundances decrease with declining pH. Contradicting the filtering hypothesis, we show that strains possessing the Nar genotype are enriched in low pH conditions but fail to grow alone. Instead, the dominance of Nar genotypes at low pH arises from an ecological interaction with Nap genotypes that alleviates nitrite toxicity. Our study provides a roadmap for dissecting how global associations between environmental variables and gene abundances arise from environmentally modulated community interactions.

ecology↗

Highly pathogenic avian influenza causes mass mortality in Sandwich tern (Thalasseus sandvicensis) breeding colonies across northwestern Europe

AO_SCPLOWBSTRACTC_SCPLOWIn 2022, highly pathogenic avian influenza (HPAI) A(H5N1) virus clade 2.3.4.4b became enzootic and caused mass mortality in Sandwich terns and other seabird species across northwestern Europe. We present data on characteristics of the spread of the virus between breeding colonies and the number of dead adult Sandwich terns recorded at breeding sites throughout northwestern Europe. Within two months after the first mortalities were reported, in total 20,531 adult Sandwich terns were found dead, which is >17% of the total northwestern European breeding population. Losses are likely higher, as we expect that many victims were not found (mortality rate might be up to 74% of the breeding population). Inside the colonies almost all chicks died. After the peak of the outbreak, in a colony established by late breeders, 25.7% of adults showed immunity against HPAI subtype H5. Removal of carcasses helped in reducing the spread of the disease and consequently total mortality. More research on the sources and modes of transmission, incubation times, effective containment and immunity is urgently needed to combat this major threat for colonial seabirds.

ecology↗

Learning the functional landscape of microbial communities

Microbial consortia exhibit complex functional properties in contexts ranging from soils to bioreactors to human hosts. Understanding how community composition determines emergent function is a major goal of microbial ecology. Here we address this challenge using the concept of community-function landscapes - analogs to fitness landscapes - that capture how changes in community composition alter collective function. Using datasets that represent a broad set of community functions, from production/degradation of specific compounds to biomass generation, we show that statistically-inferred landscapes quantitatively predict community functions from knowledge of strain presence or absence. Crucially, community-function landscapes allow prediction without explicit knowledge of abundance dynamics or interactions between species, and can be accurately trained using measurements from a small subset of all possible community compositions. The success of our approach arises from the fact that empirical community-function landscapes are typically not rugged, meaning that they largely lack high-order epistatic contributions that would be difficult to fit with limited data. Finally, we show this observation is generic across many ecological models, suggesting community-function landscapes can be applied broadly across many contexts. Our results open the door to the rational design of consortia without detailed knowledge of abundance dynamics or interactions.

ecology↗

Environmental modulators of algae-bacteria interactions at scale

Photosynthetic microbes associated with non-photosynthetic, heterotrophic, bacteria play a key role in the global primary production. Understanding these phototroph-heterotroph associations is therefore important, but remains challenging because they reside in chemically complex aquatic and terrestrial environments. We do not understand how the myriad of environmental parameters from nutrient availability to pH impact interactions between phototrophs and their heterotrophic partners. Here, we leverage a massively parallel droplet microfluidic platform that enables us to interrogate algae-bacteria interactions in >100,000 communities across [~]525 environmental conditions with varying pH, carbon availability and phosphorous availability. By developing a statistical framework to dissect interactions in this complex dataset, we reveal that dependance of algae-bacteria interactions on nutrient availability is strongly modulated by pH and buffering capacity. Furthermore, we show that the chemical identity of the available organic carbon source controls how pH, buffering capacity, and nutrient availability modulate algae-bacteria interactions. By leveraging a high-throughput platform, our study reveals the previously underappreciated role of pH in modulating phototroph-heterotroph interactions.

ecology↗

A Latent Clinical-anatomical Dimension Relating Metabolic Syndrome to Brain Morphology - Evidence from a Multivariate Imaging Analysis of 40,087 Individuals

The link between metabolic syndrome (MetS) and neurodegenerative as well cerebrovascular conditions holds substantial implications for brain health in at-risk populations. This study elucidates the complex relationship between MetS and brain health by conducting a comprehensive examination of cardiometabolic risk factors, cortical morphology, and cognitive function in 40,087 individuals. Multivariate, data-driven statistics identified a latent dimension linking more severe MetS to widespread brain morphological abnormalities, accounting for up to 71% of shared variance in the data. This dimension was replicable across sub-samples. In a mediation analysis we could demonstrate that MetS-related brain morphological abnormalities mediated the link between MetS severity and cognitive performance in multiple domains. Employing imaging transcriptomics and connectomics, our results also suggest that MetS-related morphological abnormalities are linked to the regional cellular composition and macroscopic brain network organization. By leveraging extensive, multi-domain data combined with a dimensional stratification approach, our analysis provides profound insights into the association of MetS and brain health. These findings can inform effective therapeutic and risk mitigation strategies aimed at maintaining brain integrity.

neuroscience↗

The integrity of dopaminergic and noradrenergic brain regions is associated with different aspects of late-life memory performance

Researchers have identified changes in dopaminergic neuromodulation as playing a key role in adult memory decline. Facilitated by technical advancements, recent research has also implicated noradrenergic neuromodulation in shaping late-life memory performance. However, it is not yet clear whether these two neuromodulators have distinct roles in age-related cognitive changes. Combining longitudinal high-resolution magnetic resonance imaging of the dopaminergic substantia nigra-ventral tegmental area (SN-VTA) and the noradrenergic locus coeruleus (LC) in younger (n = 69) and older adults (n = 251), we found that dopaminergic and noradrenergic integrity are differentially associated with individual differences in memory performance. While LC integrity was related to better episodic memory across several memory tasks, SN-VTA integrity was linked to working memory. Moreover, consistent with their dense interconnection and a largely shared biosynthesis, dopaminergic and noradrenergic brain regions integrity were positively related, and correlated with medial temporal lobe volumes. Longitudinally, we found that older age was associated with more-negative change in SN- VTA and LC integrity (time point 1-time point 2; mean delay [~]1.9 years). Importantly, changes in LC integrity reliably predicted future episodic memory performance (at time point 3). These findings support the feasibility of in-vivo indices for catecholaminergic integrity with potential clinical utility, given the degeneration of both neuromodulatory systems in several age-associated diseases. Moreover, they highlight differential roles of dopaminergic and noradrenergic neuromodulatory nuclei in late-life cognitive decline.

neuroscience↗

Brain Network Architecture Constrains Age-related Cortical Thinning

Age-related cortical atrophy, approximated by cortical thickness measurements from magnetic resonance imaging, follows a characteristic pattern over the lifespan. Although its determinants remain unknown, mounting evidence demonstrates correspondence between the connectivity profiles of structural and functional brain networks and cortical atrophy in health and neurological disease. Here, we performed a cross-sectional multimodal neuroimaging analysis of 2633 individuals from a large population-based cohort to characterize the association between age-related differences in cortical thickness and functional as well as structural brain network topology. We identified a widespread pattern of age-related cortical thickness differences including "hotspots" of strong age effects located in brain areas with high centrality (structural network hubs). Regional age-related differences were furthermore strongly correlated within the structurally defined node neighborhood. The overall pattern of thickness differences as well as its change throughout the later lifespan was found to be anchored in the functional network hierarchy as encoded by macroscale functional connectivity gradients. Lastly, the identified difference pattern covaried significantly with cognitive and motor performance. Our findings indicate that connectivity profiles of functional and structural brain networks might act as organizing principles behind age-related cortical thinning as an imaging surrogate of cortical atrophy.

neuroscience↗

Algae drive convergent bacterial community assembly when nutrients are scarce

The assembly of microbial communities is a complex dynamical process that determines community structure and function. Assembly can be influenced by species-species interactions, invasions, the availability of nutrients, and microbial physiology. The interdependence of these factors presents a challenge for understanding community assembly. For example, species-species interactions can be modulated by the availability of nutrients. Here we sought to understand how nutrient supply modulated interactions to affect the assembly process. We exploited algae in association with complex bacterial consortia from soils as models for ubiquitous phototroph-heterotroph communities that play an important role in global primary production. Studying bacterial communities assembled with and without the alga in environments with varying frequency of nutrient supply allowed us to differentiate the impacts of the algae from nutrient availability on the assembly process. A statistical decomposition of community taxonomic structure revealed that it is possible to separate the effects of biotic (presence of algae) and abiotic (nutrient supply rates) factors on community assembly. We found that when the supply of external nutrients is infrequent, the algae strongly impact bacterial community assembly, driving initially diverse bacterial consortia to converge to a common structure. Analysis of sequencing data revealed that this convergence is largely mediated by algal inhibition of specific bacterial taxa. Conversely, when nutrients are supplied with high frequency, bacterial community assembly is not impacted by the presence of the alga. This study shows that complex phototroph-heterotroph communities can be powerful model systems for understanding the assembly process in a context relevant to the global ecosystem functioning.

ecology↗

Vamos en bici: Study protocol of an investigation of cognitive and neural changes following language training, physical exercise training, or a combination of both

As the relative number of elderly people as well as the average life expectancy increases, identifying potential means to alter the ongoing trajectory of aging and specifically the trajectory of cognitive performance is of great importance. Some modifiable lifestyle factors, such as physical and cognitive activity, have shown positive effects on cognition and brain structure, and the combination of the two might even show a boosted, interactive effect. In this study protocol, we describe in detail our data which was acquired to explore how cognitive stimulation in the form of acquiring a new language, physical exercise on stationary bikes or the combination of the two interventions affect brain structure, cognitive performance, and psychosocial functioning. One-hundred and forty-two older healthy adults (63-78 years) were randomly assigned to one of four six-month intervention programs, comprising (a) foreign language learning, (b) physical exercise training on a bicycle ergometer, (c) a combination of language learning and physical exercise, or (d) a book club (serving as an active control condition). We collected a rich neuroimaging data set, comprising T1-weighted structural, resting state functional, high resolution hippocampal, myelin water fraction, diffusion-weighted, arterial spin labeling, and multi-parameter images. Using a cognitive battery, we collected data from the domains of episodic memory, working memory, perceptual speed, and fluid intelligence. We performed comprehensive physical assessments including cardiopulmonary exercise testing, and additionally collected data on psychosocial functioning (e.g., well-being, perceived stress, control beliefs). We assume that physical activity boosts brain plasticity per se by inducing structural and neurochemical changes in brain regions that are important for learning and memory and therefore may facilitate the effects of cognitive training. (269 words)

neuroscience↗

Fluorescent and bioluminescent calcium indicators with tuneable colors and affinities

We introduce a family of bright, rhodamine-based calcium indicators with tuneable affinities and colors. The indicators can be specifically localized to different cellular compartments and are compatible with both fluorescence and bioluminescence readouts through conjugation to HaloTag fusion proteins. Importantly, their increase in fluorescence upon localization enables no-wash live-cell imaging, which greatly facilitates their use in biological assays. Applications as fluorescent indicators in rat hippocampal neurons include the detection of single action potentials and of calcium fluxes in the endoplasmic reticulum (ER). Applications as bioluminescent indicators include the recording of the pharmacological modulation of nuclear calcium in high-throughput-compatible assays. The versatility and remarkable ease of use of these indicators make them powerful tools for bioimaging and bioassays. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/468356v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@b7aa92org.highwire.dtl.DTLVardef@1f7141org.highwire.dtl.DTLVardef@447f30org.highwire.dtl.DTLVardef@fa34c2_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

Kinetic and structural characterization of the self-labeling protein tags HaloTag7, SNAP-tag and CLIP-tag

The self-labeling protein tags (SLPs) HaloTag7, SNAP-tag and CLIP-tag allow the covalent labeling of fusion proteins with synthetic molecules for applications in bioimaging and biotechnology. To guide the selection of an SLP-substrate pair and provide guidelines for the design of substrates, we report a systematic and comparative study on the labeling kinetics and substrate specificities of HaloTag7, SNAP-tag and CLIP-tag. HaloTag7 reaches almost diffusion-limited labeling rates with certain rhodamine substrates, which are more than two orders of magnitude higher than those of SNAP-tag for the corresponding substrates. SNAP-tag labeling rates however are less affected by the structure of the label than those of HaloTag7, which vary over six orders of magnitude for commonly employed substrates. Solving the crystal structures of HaloTag7 and SNAP-tag labeled with fluorescent substrates allowed us to rationalize their substrate preferences. We also demonstrate how these insights can be exploited to design substrates with improved labeling kinetics.

biochemistry↗