Biology subjects

Kuehn, S.

Publications and source records attributed to Kuehn, S..

At least 55 records · Page 3Linked to original sources

bioRxiv2020

A sparse mapping of structure to function in microbial communities

The metabolic function of microbial communities has played a defining role in the evolution and persistence of life on Earth, driving redox reactions that form the basis of global biogeochemical cycles. Community metabolism emerges from a hierarchy of processes including gene expression, ecological interactions, and environmental factors. In wild communities, gene content is correlated with environmental context, but predicting metabolic dynamics from genomic structure remains elusive. Here we show, for the process of denitrification, that community metabolism is predictable from the genes each member of the community possesses. Machine learning reveals a sparse and generalizable mapping from gene content to metabolite dynamics across a genomically-diverse library of bacteria. A consumer-resource model correctly predicts community metabolism from single-strain phenotypes. Our results demonstrate that the conserved impacts of metabolic genes can predict community function, enabling the prediction of metabolite dynamics from metagenomes, designing denitrifying communities, and discovering how genome evolution impacts metabolism.

ecology↗

bioRxiv2020

Closed microbial communities self-organize to persistently cycle carbon

Nutrient cycling is an emergent property of ecosystems at all scales, from microbial communities to the entire biosphere. Understanding how nutrient cycles emerge from the collective metabolism of ecosystems is a challenging problem. Here we use closed microbial ecosystems (CES), hermetically sealed consortia that sustain nutrient cycles when provided with only light, to learn how microbial communities cycle carbon. A new technique for quantifying carbon exchange shows that CES comprised of an alga and diverse bacteria self-organize to robustly cycle carbon. Comparing a library of CES, we find that carbon cycling does not depend strongly on the taxonomy of the bacteria present. Metabolic profiling reveals functional redundancy across CES: despite strong taxonomic differences, self-organized CES exhibit a conserved set of metabolic capabilities. SummaryClosed microbial communities of algae and bacteria self-organize to robustly cycle carbon via emergent metabolite exchange.

ecology↗

bioRxiv2020

Locus coeruleus MRI contrast is associated with cortical thickness in older adults

There is growing evidence that neuronal integrity of the noradrenergic locus coeruleus (LC) is important for later-life cognition. Less understood is how LC integrity relates to brain correlates of cognition, such as brain structure. Here, we examined the relationship between cortical thickness and a measure reflecting LC integrity in older (n = 229) and younger adults (n = 67). Using a magnetic resonance imaging sequence which yields high signal intensity in the LC, we assessed the contrast between signal intensity of the LC and that of neighboring pontine reference tissue. The Freesurfer software suite was used to quantify cortical thickness. LC contrast was positively related to cortical thickness in older adults, and this association was prominent in parietal, frontal, and occipital regions. Brain regions where LC contrast was related to cortical thickness include portions of the frontoparietal network which have been implicated in noradrenergically modulated cognitive functions. These findings provide novel evidence for a link between LC structure and cortical brain structure in later adulthood.

neuroscience↗

bioRxiv2020

Hippocampal and parahippocampal grey matter structural integrity assessed by multimodal imaging is associated with episodic memory in old age

Maintained structural integrity of hippocampal and cortical grey matter may explain why some older adults show rather preserved episodic memory. However, viable measurement models for estimating individual differences in grey matter structural integrity are lacking; instead, findings rely on fallible single indicators of integrity. Here, we introduce multitrait-multimethod (MTMM) methodology to capture individual differences in grey matter integrity, based on multimodal structural imaging in a large sample of 1,522 healthy adults aged 60 to 88 years from the Berlin Aging Study II, including 331 participants who underwent MR imaging. Structural integrity factors expressed the common variance of voxel-based morphometry (VBM), mean diffusivity (MD), and magnetization transfer ratio (MT) for each of four regions of interest (ROI): hippocampus, parahippocampal gyrus, prefrontal cortex, and precuneus. Except for precuneus, the integrity factors correlated with episodic memory. Associations with hippocampal and parahippocampal integrity persisted after controlling for age, sex, and education. Our results support the proposition that episodic memory ability in old age benefits from maintained structural integrity of hippocampus and parahippocampal gyrus. Exploratory follow-up analyses on sex differences showed that this effect is restricted to men. Multimodal factors of structural brain integrity might help improve our biological understanding of human memory aging.

neuroscience↗

bioRxiv2019

Evolution of generalists by phenotypic plasticity

Adapting organisms face a tension between specializing their phenotypes for certain ecological tasks or developing generalist strategies which permit persistence in multiple environmental conditions. Understanding when and how generalists or specialists evolve is therefore an important question in evolutionary dynamics. Here we study the evolution of bacterial range expansions by selecting Escherichia coli for faster migration through porous media containing one of four different sugars supporting growth and chemotaxis. We find that selection in any one sugar drives the evolution of faster migration in all sugars relative to the ancestral strain. Measurements of growth and motility of all evolved lineages in all nutrient conditions reveal that the ubiquitous evolution of fast migration arises via phenotypic plasticity. Phenotypic plasticity permits evolved strains to exploit distinct phenotypic strategies to achieve fast migration in each environment irrespective of the environment in which they were evolved. Our work suggests that plasticity plays an important role in the evolution of generalist phenotypes.

evolutionary biology↗

bioRxiv2019

Stereoscopic Rendering in a Head Mounted Display Elicits Higher Functional Connectivity During Virtual Reality

Virtual reality (VR) simulates real world scenarios by creating a presence in users. Such immersive scenarios lead to more similar behaviour to that displayed in real world settings, which may facilitate the transfer of knowledge and skills acquired in VR to real world situations. VR has already been used in education, psychotherapy, rehabilitation and it is an appealing choice for training intervention. The aim was to investigate to what extend VR technology can be used in a magnetic resonance imaging scanner(MRI), addressing the question of whether brain connectivity differs between VR and screen via mirror projection presentations. Moreover, we investigate whether stereoscopic goggle stimulation, where eyes receive different input, would elicit more brain connectivity than stimulation where both eyes receive the same input (monoscopic). To our knowledge, there is no previous research addressing this question. Multiple analyses were performed to cover different aspects of brain connectivity: fractional low frequency fluctuation, independent component analysis, seed-based functional connectivity and graph analysis. In goggles (mono and stereoscopic) vs. screen, we found connectivity differences in cerebellum and postcentral gyrus and in visual and frontal inferior cortex in visual/default-mode networks. Considering specific areas, we found higher connectivity between superior frontal cortex and temporal lobe, as well as inferior parietal cortex with calcarine and lingual. Furthermore, superior frontal cortex and insula/putamen were more strongly connected in stereoscopic, in line with our hypothesis. We assume that conditions eliciting most connectivity should be suited for long-term interventions as extended training under these conditions could permanently improve functional/structural connectivity.

neuroscience↗

bioRxiv2019

Efficient small-world and scale-free functional brain networks at rest using k-nearest neighbors thresholding

In recent years, there has been a massive effort to analyze the topological properties of brain networks. Yet, one of the challenging questions in the field is how to construct brain networks based on the connectivity values derived from neuroimaging methods. From a theoretical point of view, it is plausible that the brain would have evolved to minimize energetic costs of information processing, and therefore, maximizes efficiency as well as to redirect its function in an adaptive fashion, that is, resilience. A brain network with such features, when characterized using graph analysis, would present small-world and scale-free properties.\n\nIn this paper, we focused on how the brain network is constructed by introducing and testing an alternative method: k-nearest neighbor (kNN). In addition, we compared the kNN method with one of the most common methods in neuroscience: namely the density threshold. We performed our analyses on functional connectivity matrices derived from resting state fMRI of a big imaging cohort (N=434) of young and older healthy participants. The topology of networks was characterized by the graph measures degree, characteristic path length, clustering coefficient and small world. In addition, we verified whether kNN produces scale-free networks. We showed that networks built by kNN presented advantages over traditional thresholding methods, namely greater values for small-world (linked to efficiency of networks) than those derived by means of density thresholds and moreover, it presented also scale-free properties (linked to the resilience of networks), where density threshold did not. A brain network with such properties would have advantages in terms of efficiency, rapid adaptive reconfiguration and resilience, features of brain networks that are relevant for plasticity and cognition as well as neurological diseases as stroke and dementia.\n\nHighlightsO_LIA novel thresholding method for brain networks based on k-nearest neighbors (kNN)\nC_LIO_LIkNN applied on resting state fMRI from a big cohort of healthy subjects BASE-II\nC_LIO_LIkNN built networks present greater small world properties than density threshold\nC_LIO_LIkNN built networks present scale-free properties whereas density threshold did not\nC_LI

neuroscience↗

bioRxiv2019

Higher-order interaction inhibits bacterial invasion of a phototroph-predator microbial community

In nature, the composition of an ecosystem is thought to be important for determining its resistance to invasion by new species. Studies of invasions in natural ecosystems, from plant to microbial communities, have found that more diverse communities are more resistant to invasion. It is thought that more diverse communities resist invasion by more completely consuming the resources necessary for would-be invaders. Here we show that Escherichia coli can successfully invade cultures of the alga Chlamydomonas reinhardtii (phototroph) or the ciliate Tetrahymena thermophila (predator), but cannot invade a community where both are present. The invasion resistance of the algae-ciliate community is due to a higher-order (3-way) interaction that is unrelated to resource consumption. We show that the mechanism of this interaction is the algal inhibition of bacterial aggregation which leaves bacteria vulnerable to ciliate predation. This mechanism of invasion resistance requires both the algae and the ciliate to be present and provides an example of invasion resistance through a trait-mediated higher-order interaction.

ecology↗

bioRxiv2018

Altered resting state functional connectivity in a thalamo-cortico-cerebellar network in patients with schizophrenia

Schizophrenia is described as a disease in which complex psychopathology together with cognitive and behavioral impairments are related to widely disrupted brain circuitry causing a failure in coordinating information across multiple brain sites. This led to the hypothesis of schizophrenia as a network disease e.g. in the cognitive dysmetria model and the dysconnectivity theory. Nevertheless, there is no consensus regarding localized mechanisms, namely dysfunction of certain networks underlying the multifaceted symptomatology.\n\nIn this study, we investigated potential functional disruptions in 35 schizophrenic patients and 41controls using complex cerebral network analysis, namely network-based statistic (NBS) and graph theory in resting state fMRI. NBS can reveal locally impaired subnetworks whereas graph analysis characterizes whole brain network topology.\n\nUsing NBS we observed a local hyperconnected thalamo-cortico-cerebellar subnetwork in the schizophrenia group. Furthermore, nodal graph measures retrieved from the thalamo-cortico-cerebellar subnetwork revealed that the total number of connections from/to (degree) of the thalamus is higher in patients with schizophrenia. Interestingly, graph analysis on the whole brain functional networks did not reveal group differences. Together, our results suggest that disruptions in the brain networks of schizophrenia patients are situated at the local level of the hyperconnected thalamo-cortico-cerebellar rather than globally spread in brain.\n\nOur results provide further evidence for the importance of the thalamus and cerebellum in schizophrenia and to the notion that schizophrenia is a network disease in line with the dysconnectivity theory and cognitive dysmetria model.

neuroscience↗

bioRxiv2018

Reduced Resting-State Connectivity in the Precuneus is correlated with Apathy in Patients with Schizophrenia

A diagnosis of schizophrenia is associated with a heterogeneous psychopathology including positive and negative symptoms. The disconnection hypothesis, an early pathophysiological framework conceptualizes the diversity of symptoms as a result from disconnections in neural networks. In line with this hypothesis, previous neuroimaging studies of patients with schizophrenia reported alterations within the default mode network (DMN), the most prominent network at rest.\n\nAim of the present study was to investigate the functional connectivity during rest in patients with schizophrenia and healthy individuals and explore whether observed functional alterations are related to the psychopathology of patients. Therefore, functional magnetic resonance images at rest were recorded of 35 patients with schizophrenia and 41 healthy individuals. Independent component analysis (ICA) was used to extract resting state networks.\n\nComparing ICA results between groups indicated alterations only within the network of the DMN. More explicitly, reduced connectivity in the precuneus was observed in patients with schizophrenia compared to healthy controls. Connectivity in this area was negatively correlated with the severity of negative symptoms, more specifically with the domain of apathy.\n\nTaken together, the current results provide further evidence for a role DMN alterations might play in schizophrenia and especially in negative symptom such as apathy.

neuroscience↗

bioRxiv2018

New graph-theoretical-multimodal approach using temporal and structural correlations reveal disruption in the thalamo-cortical network in patients with schizophrenia

Schizophrenia has been understood as a network disease with altered functional and structural connectivity in multiple brain networks compatible to the extremely broad spectrum of psychopathological, cognitive and behavioral symptoms in this disorder.\n\nWhen building brain networks, functional and structural networks are typically modelled independently: functional network models are based on temporal correlations among brain regions, whereas structural network models are based on anatomical characteristics. Combining both features may give rise to more realistic and reliable models of brain networks.\n\nIn this study, we applied a new flexible graph-theoretical-multimodal model called FD (F, the functional connectivity matrix, and D, the structural matrix) to construct brain networks combining functional, structural and topological information of MRI measurements (structural and resting state imaging) to patients with schizophrenia (N=35) and matched healthy individuals (N=41). As a reference condition, the traditional pure functional connectivity (pFC) analysis was carried out.\n\nBy using the FD model, we found disrupted connectivity in the thalamo-cortical network in schizophrenic patients, whereas the pFC model failed to extract group differences after multiple comparison correction. We interpret this observation as evidence that the FD model is superior to conventional connectivity analysis, by stressing relevant features of the whole brain connectivity including functional, structural and topological signatures. The FD model can be used in future research to model subtle alterations of functional and structural connectivity resulting in pronounced clinical syndromes and major psychiatric disorders. Lastly, FD is not limited to the analysis of resting state fMRI, and can be applied to EEG, MEG etc.

neuroscience↗

bioRxiv2018

3-D navigation: A core driver of brain plasticity in video game interventions

Recent evidence has repeatedly shown that 3D platform video game training leads to substantial brain structural plasticity in hippocampus, prefrontal cortex and cerebellum. However, a great disadvantage of using complex video game interventions is the difficulty to attribute the observed effects to specific game mechanics.\n\nIn order to address this caveat, we conducted a longitudinal training study in which 40 participants were randomly assigned to train with a 3D platformer game or a 2D platformer game. The main difference between the two games lies within their affordance for spatial exploration. After a training phase of two months, we observed extended brain structural increases in the 3D in comparison to the 2D condition in bilateral prefrontal areas, hippocampus/ entorhinal cortex as well as precuneus and the temporal lobe. In the reverse contrast an increase in bilateral caudate nucleus was observed.\n\nThe results demonstrate a crucial role of 3D spatial navigation for widespread brain plasticity effects within a two-months training setup. Given the vast complexity of video games, spatial navigation seems to play an outstanding role in structural plasticity. Since prefrontal, temporal and hippocampal volume deficits are prominent risk factors for several psychiatric disorders, daily navigation habits (outdoor movement, using GPS devices etc.) have to be considered in future mental disorders prevention research.

neuroscience↗

bioRxiv2018

Influence of nutritional tyrosine on cognition and functional connectivity in healthy old humans

Tyrosine is precursor for monoamine neurotransmitters such as dopamine (DA), which is one of the key neurotransmitters in the frontostriatal network and of crucial relevance for mental disorders. Recent research reported that high dose tyrosine application resulted in increased brain DA synthesis, which is consistent with the observation of positive associations between daily tyrosine intake and cognitive test performance. In the present study, we investigated the associations between working memory (WM) dependent tasks and self-reported nutritional tyrosine intake within a large group of healthy elderly humans (286 subjects) by additionally including brain functional data. We observed a negative correlation between tyrosine intake and resting-state functional connectivity (rsFC) between the striatum (putamen) and the prefrontal cortex. That is to say, we found higher rsFC in individuals consuming less tyrosine per day. At the same time, this increased rsFC or hyperconnectivity was associated with lower WM performance. These findings suggest that lower or insufficient supply of tyrosine might result in dysfunctional connectivity between striatal and frontal regions leading to lower WM capacity in healthy elderly humans.

neuroscience↗

bioRxiv2018

I know that I don’t know: Structural and functional connectivity underlying meta-ignorance in pre-schoolers

Research Highlights[1] Children develop the ability to report that they do not know something at around five years of age.\n\n[2] Children who could correctly report their own ignorance in a partial-knowledge task showed thicker cortices within medial orbitofrontal cortex.\n\n[3] This region was functionally connected to parts of the default-mode network.\n\n[4] The default-mode network might support the development of correct metacognitive monitoring.\n\nAbstractMetacognition plays a pivotal role in human development. The ability to realize that we do not know something, or meta-ignorance, emerges after approximately five years of age. We aimed at identifying the brain systems that underlie the developmental emergence of this ability in a preschool sample.\n\nTwenty-four children aged between five and six years answered questions under three conditions of a meta-ignorance task twice. In the critical partial knowledge condition, an experimenter first showed two toys to a child, then announced that she would place one of them in a box behind a screen, out of sight from the child. The experimenter then asked the child whether or not she knew which toy was in the box.\n\nChildren who answered correctly both times to the metacognitive question in the partial knowledge condition (n=9) showed greater cortical thickness in a cluster within left medial orbitofrontal cortex than children who did not (n=15). Further, seed-based functional connectivity analyses of the brain during resting state revealed that this region is functionally connected to the medial orbitofrontal gyrus, posterior cingulate gyrus and precuneus, and mid- and inferior temporal gyri.\n\nThis finding suggests that the default mode network, critically through its prefrontal regions, supports introspective processing. It leads to the emergence of metacognitive monitoring allowing children to explicitly report their own ignorance.

neuroscience↗

bioRxiv2018

Hitchhiking, collapse and contingency in phage infections of migrating bacterial populations

Natural bacterial populations are subject to constant predation pressure by phages. Bacteria use a variety of well-studied molecular mechanisms to defend themselves from phage predation. However, since phage are non-motile, perhaps the simplest defense against phage would be for bacteria to outrun their predators. In particular, chemotaxis, the active migration of bacteria up attractant gradients, may help the bacteria escape slowly diffusing phages. Here we study phage infection dynamics in migrating bacterial populations driven by chemotaxis through low viscosity agar plates. We find that expanding phage-bacteria populations support two migrating fronts, an outermost \"bacterial\" front driven by nutrient uptake and chemotaxis and an inner \"phage\" front at which bacterial population collapses due to phage predation. We show that with increasing adsorption rate and initial phage population, the rate of migration of the phage front increases, eventually overtaking the bacterial front and driving the system across a \"phage transition\" from a regime where bacteria outrun a phage infection to one where they must evolve phage resistance to survive. We confirm experimentally that this process requires phages to \"surf\" the bacterial front by repeatedly reinfecting the fastest moving bacteria. A deterministic model recapitulates the transition. Macroscopic fluctuations in bacterial densities at the phage front suggest that a feedback mechanism, possibly due to growth rate dependent phage infection rates, drives millimeter scale spatial structure in phage-bacteria populations. Our work opens a new, spatiotemporal, line of investigation into the eco-evolutionary struggle between bacteria and their phage predators.\n\nSignificance StatementThe infection of bacteria by phage requires physical contact. This fact means that motile bacteria may avoid non-motile phage by simply running away. By this mechanism bacterial chemotaxis may help bacteria to escape phages. Here we show that when phage infect bacteria moving in soft agar plates, high phage populations or infectivity rates result in phages stopping and killing all bacteria. Conversely, when initial phage numbers or infectivity rates are low, bacteria are able to migrate away from phage successfully, despite phage ability to \"surf\" bacterial fronts for more than 24 hours. Between these regimes we document a \"phage transition\" where bacterial physiology and contingency in phage infection manifest through large-scale fluctuations in spatio-temporal dynamics.

ecology↗

bioRxiv2018

Locus coeruleus integrity preserves memory performance across the adult life span

For decades, research into memory decline in human cognitive aging has focused on neocortical regions, the hippocampus, and dopaminergic neuromodulation. Recent findings indicate that the locus coeruleus (LC) and noradrenergic neuromodulation may also play an important role in shaping memory development in later life. However, technical challenges in quantifying LC integrity have hindered the study of LC-cognition associations in humans. Using high-resolution neuromelanin-sensitive magnetic resonance imaging, we found that individual differences in learning and memory were positively associated with LC integrity across a variety of memory tasks in younger (n = 66), and older adults (n = 228). Moreover, we observed functionally relevant age differences confined to rostral LC. Older adults with a more youth-like rostral LC also showed higher memory performance. These findings link non-invasive, in vivo indices of LC integrity to memory in aging and highlight the role of the LC norepinephrine system in the decline of cognition.

neuroscience↗

bioRxiv2017

Subject- and behavior-specific signatures extracted from fMRI data using whole-brain effective connectivity

The study of brain communication based on fMRI data is often limited because such measurements are a mixture of session-to-session variability with subject- and condition-related information. Disentangling these contributions is crucial for real-life applications, in particular when only a few recording sessions are available. The present study aims to define a reliable standard for the extraction of multiple signatures from fMRI data, while verifying that they do not mix information about the different modalities. In particular, condition-specific signature should not be contaminated by subject-related information. Practically, signatures correspond to subnetworks of directed interactions between brain regions (typically 100 covering the whole brain) supporting the subject and condition identification for single fMRI sessions. The key for robust prediction is using effective connectivity instead of functional connectivity. Our method demonstrates excellent generalization capabilities for subject identification in two datasets, using only a few sessions per subject as reference. Using another dataset with resting state and movie viewing, we show that the two signatures related to subjects and tasks correspond to distinct subnetworks, which are thus topologically orthogonal. Our results set solid foundations for applications tailored to individual subjects, such as clinical diagnostic.

neuroscience↗

bioRxiv2016

Environment determines evolutionary trajectory in a constrained phenotypic space

Constraints on phenotypic variation limit the capacity of organisms to adapt to the multiple selection pressures encountered in natural environments. To better understand evolutionary dynamics in this context, we select Escherichia coli for faster migration through a porous environment, a process which depends on both motility and growth. We find that a trade-off between swimming speed and growth rate constrains the evolution of faster migration. Evolving faster migration in rich medium results in slow growth and fast swimming, while evolution in minimal medium results in fast growth and slow swimming. In each condition parallel genomic evolution drives adaptation through different mutations. We show that the trade-off is mediated by antagonistic pleiotropy through mutations that affect negative regulation. A model of the evolutionary process shows that the genetic capacity of an organism to vary traits can qualitatively alter the evolutionary trajectory when selection pressures are complex.

evolutionary biology↗