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The plant family Brassicaceae includes some of the most studied hosts of plant microbiomes, targeting microbial diversity, community assembly rules, and effects on host performance. Compared to bacteria, eukaryotes in the brassicaceous microbiome remain understudied, especially under natural settings. Here, we assessed the impact of host identity and age on the assembly of fungal and oomycete root communities, using DNA metabarcoding of roots and associated soil of three annual co-habiting Brassicaceae collected at two time points. Our results showed that fungal communities are more diverse and structured than those of oomycetes. In both cases, plant identity and sampling time had little influence on community variation, whereas root/soil compartment had a strong effect by exerting control on the entry of soil microorganisms into the roots. The enrichment in roots of specific fungi suggests a specialization towards the asymptomatic colonization of plant tissues, which could be relevant to host’s fitness and health.
Wildfires are relatively rare in subarctic tundra ecosystems, but they can strongly change ecosystem properties. Short-term fire effects on subarctic tundra vegetation are well documented, but long-term vegetation recovery has been studied less. The frequency of tundra fires will increase with climate warming. Understanding the long-term effects of fire is necessary to predict future ecosystem changes.
We used a space-for-time approach to assess vegetation recovery after fire over more than four decades. We studied soil and vegetation patterns on three large fire scars (>44, 28 and 12 years old) in dry, lichen-dominated forest tundra in Western Siberia. On 60 plots, we determined soil temperature and permafrost thaw depth, sampled vegetation and measured plant functional traits. We assessed trends in NDVI to support the field-based results on vegetation recovery.
Soil temperature, permafrost thaw depth and total vegetation cover had recovered to pre-fire levels after >44 years, as well as total vegetation cover. In contrast, after >44 years, functional groups had not recovered to the pre-fire state. Burnt areas had lower lichen and higher bryophyte and shrub cover. The dominating shrub species, Betula nana, exhibited a higher vitality (higher specific leaf area and plant height) on burnt compared with control plots, suggesting a fire legacy effect in shrub growth. Our results confirm patterns of shrub encroachment after fire that were detected before in other parts of the Arctic and Subarctic. In the so far poorly studied Western Siberian forest tundra we demonstrate for the first time, long-term fire-legacies on the functional composition of relatively dry shrub- and lichen-dominated vegetation.
Seed harvesting from wild plant populations is key for ecological restoration, but may threaten the persistence of source populations. Consequently, several countries have set guidelines limiting the proportions of harvestable seeds. Here, we use high-resolution data from 298 plant species to model the demographic consequences of seed harvesting. We find that the current guidelines only protect some species, but are insufficient or overly restrictive for others. We show that the maximum possible fraction of seed harvesting is strongly associated with harvesting frequency and generation time of the target species, ranging from 100% in long-lived species to <1% in the most annuals. Our results provide quantitative basis to guide seed harvesting legislation based on species’ generation time and harvesting regime.
Animals sense ambient temperature so that they can adjust their behavior to the environment; they avoid noxious heat and coldness and stay within a survivable temperature range. C. elegans can sense temperature, memorize past cultivation temperature and navigate towards preferable temperature, for which a thermosensory neuron, AFD, is essential. AFD responds to temperature increase from the past cultivation temperature by increasing intracellular Ca2+ level. We aimed to reveal how AFD encodes and memorizes the information of temperature. Although cGMP synthesis is crucial for thermosensation by AFD, whether and how cGMP level temporally fluctuates in AFD remained elusive. We therefore monitored cGMP level in AFD and found that cGMP dynamically responded to temperature change in a manner dependent on past cultivation temperature. Given that cGMP dynamics is supposed to be upstream of Ca2+ dynamics, our results suggest that AFD’s memory is formed by simpler molecular mechanisms than previously expected from the Ca2+ dynamics. Moreover, we analyzed how guanylyl cyclases and phosphodiesterases, which synthesize and degrade cGMP, respectively, contributed to cGMP and Ca2+ dynamics and thermotaxis behavior.
Signal transfer of visual stimuli to V4 occurs in gamma-rhythmic, pulsed information packages
(2020)
Summary Selective visual attention allows the brain to focus on behaviorally relevant information while ignoring irrelevant signals. As a possible mechanism, routing by synchronization was proposed: neural populations sending attended signals align their gamma-rhythmic activities with receiving populations, such that spikes from the senders arrive at excitability peaks of the receivers, enhancing signal transfer. Conversely, the non-attended signals arrive unaligned to the receiver’s oscillation, reducing signal transfer. Therefore, visual signals should be transferred through periodically pulsed information packages, resulting in a modulation of the stimulus content within the receiver’s activity by its gamma phase and amplitude. To test this prediction, we quantified gamma phase-specific stimulus content within neural activity from area V4 of macaques performing a visual attention task. For the attended stimulus we find enhanced stimulus content reaching its maximum near excitability peaks, with effect magnitude increasing with oscillation amplitude, establishing a functional link between selective processing and gamma activity.
No disease modifying therapy is currently available for Parkinson’s disease (PD), the second most common neurodegenerative disease. The long non-motor prodromal phase of PD is a window of opportunity for early detection and intervention. However, we lack the pathophysiological understanding to develop selective biomarkers and interventions. By developing a mutant α-synuclein selective-overexpression mouse model of prodromal PD, we identified a cell-autonomous selective Kv4 channelopathy in dorsal motor nucleus of the vagus (DMV) neurons. This functional remodeling of intact DMV neurons leads to impaired pacemaker function in vitro and in vivo, which in turn reduces gastrointestinal motility which is a common, very early symptom of prodromal PD. We show for the first time a causal chain of events from α-synuclein via a biophysical dysfunction of specific neuronal populations to a clinically relevant prodromal symptom. These findings can facilitate the rational design of clinical biomarkers to identify people at risk for PD.
Substantia nigra dopamine (SN DA) neurons are progressively lost in Parkinson disease (PD). While the molecular and cellular mechanisms of their differential vulnerability and degeneration have been extensively studied, we still know very little about potential functional adaptations of those SN DA neurons that – at least for some time – manage to survive during earlier stages of PD. We utilized a partial lesion 6-OHDA mouse model to characterize initial electrophysiological impairments and chronic adaptations of surviving identified SN DA neurons, both in vivo and in vitro. Early after lesion (3 weeks), we detected a selective loss of in vivo burst firing in surviving SN DA neurons, which was accompanied by in vitro pacemaker instability. In contrast, late after lesion (>2 months), in vivo firing properties of surviving SN DA neurons had recovered in the presence of 2-fold accelerated pacemaking in vitro. Finally, we show that this chronic cell-autonomous adaptation in surviving SN DA neurons was mediated by Kv4.3 channel downregulation. Our study demonstrates substantial homeostatic plasticity of surviving SN DA neurons after a single-hit non-progressive lesion, which might contribute to the phenotype of initially surviving SN DA neurons in PD.
Parkinson disease (PD), one of the most common neurodegenerative disorder, is believed to be driven by toxic α-synuclein aggregates eventually resulting in selective loss of vulnerable neuron populations, prominent among them, nigrostriatal dopamine (DA) neurons in the lateral substantia nigra (l-SN). How α-synuclein aggregates initiate a pathophysiological cascade selectively in vulnerable neurons is still unclear. Here, we show that the exposure to low nanomolar concentrations of α-synuclein aggregates (i.e. fibrils) but not its monomeric forms acutely and selectively disrupted the electrical pacemaker function of the DA subpopulation most vulnerable in PD. This implies that only dorsolateral striatum projecting l-SN DA neurons were electrically silenced by α-synuclein aggregates, while the activity of neither neighboring DA neurons in medial SN projecting to dorsomedial striatum nor mesolimbic DA neurons in the ventral tegmental area (VTA) were affected. Moreover, we demonstrate functional K-ATP channels comprised of Kir6.2 subunit in DA neurons to be necessary to mediate this acute pacemaker disruption by α-synuclein aggregates. Our study thus identifies a molecularly defined target that quickly translates the presence of α-synuclein aggregates into an immediate impairment of essential neuronal function. This constitutes a novel candidate process how a protein-aggregation-driven sequence in PD is initiated that might eventually lead to selective neurodegeneration.
Mechanisms by which specific histone modifications regulate distinct gene regulatory networks remain little understood. We investigated how H3K79me2, a modification catalyzed by DOT1L and previously considered a general transcriptional activation mark, regulates gene expression in mammalian cardiogenesis. Early embryonic cardiomyocyte ablation of Dot1l revealed that H3K79me2 does not act as a general transcriptional activator, but rather regulates highly specific gene regulatory networks at two critical cardiogenic junctures: left ventricle patterning and postnatal cardiomyocyte cell cycle withdrawal. Mechanistic analyses revealed that H3K79me2 in two distinct domains, gene bodies and regulatory elements, synergized to promote expression of genes activated by DOT1L. Surprisingly, these analyses also revealed that H3K79me2 in specific regulatory elements contributed to silencing genes usually not expressed in cardiomyocytes. As DOT1L mutants had increased numbers of postnatal mononuclear cardiomyocytes and prolonged cardiomyocyte cell cycle activity, controlled inhibition of DOT1L might be a strategy to promote cardiac regeneration post-injury.
Background Transposable elements (TEs) are an important source of genome plasticity across the tree of life. Accumulating evidence suggests that TEs may not be randomly distributed in the genome. Drift and natural selection are important forces shaping TE distribution and accumulation, acting directly on the TE element or indirectly on the host species. Fungi, with their multifaceted phenotypic diversity and relatively small genome size, are ideal models to study the role of TEs in genome evolution and their impact on the host’s ecological and life history traits. Here we present an account of all TEs found in a high-quality reference genome of the lichen-forming fungus Umbilicaria pustulata, a macrolichen species comprising two climatic ecotypes: Mediterranean and cold-temperate. We trace the occurrence of the newly identified TEs in populations along three replicated elevation gradients using a Pool-Seq approach, to identify TE insertions of potential adaptive significance.
Results We found that TEs cover 21.26 % of the 32.9 Mbp genome, with LTR Gypsy and Copia clades being the most common TEs. Out of a total of 182 TE copies we identified 28 insertions displaying consistent insertion frequency differences between the two host ecotypes across the elevation gradients. Most of the highly differentiated insertions were located near genes, indicating a putative function.
Conclusions This pioneering study into the content and climate niche-specific distribution of TEs in a lichen-forming fungus contributes to understanding the roles of TEs in fungal evolution. Particularly, it may serve as a foundation for assessing the impact of TE dynamics on fungal adaptation to the abiotic environment, and the impact of TE activity on the evolution and maintenance of a symbiotic lifestyle.
A candidate gene cluster for the bioactive natural product gyrophoric acid in lichen-forming fungi
(2022)
Natural products of lichen-forming fungi are structurally diverse and have a variety of medicinal properties. Despite this, they a have limited implementation in industry, because the corresponding genes remain unknown for most of the natural products. Here we implement a long-read sequencing and bioinformatic approach to identify the biosynthetic gene cluster of the bioactive natural product gyrophoric acid (GA). Using 15 high-quality genomes representing nine GA-producing species of the lichen-forming fungal genus Umbilicaria, we identify the most likely GA cluster and investigate cluster gene organization and composition across the nine species. Our results show that GA clusters are promiscuous within Umbilicaria, with only three genes that are conserved across species, including the PKS gene. In addition, our results suggest that the same cluster codes for different but structurally similar NPs, i.e., GA, umbilicaric acid and hiascic acid, bringing new evidence that lichen metabolite diversity is also generated through regulatory mechanisms at the molecular level. Ours is the first study to identify the most likely GA cluster, and thus provides essential information to open new avenues for biotechnological approaches to producing and modifying GA and similar lichen-derived compounds. We show that bioinformatics approaches are useful in linking genes and potentially associated natural products. Genome analyses help unlocking the pharmaceutical potential of organisms such as lichens, which are biosynthetically diverse but slow growing, and difficult to cultivate due to their symbiotic nature.
Intraspecific genomic variability affects a species’ adaptive potential towards climatic conditions. Variation in gene content across populations and environments may point at genomic adaptations to specific environments. The lichen symbiosis, a stable association of fungal and photobiont partners, offers an excellent system to study environmentally driven gene content variation. Many species have remarkable environmental tolerances, and often form populations in different climate zones. Here we combine comparative and population genomics to assess the presence and absence of genes in high elevation and low elevation genomes of two lichenized fungi of the genus Umbilicaria. The two species have non-overlapping ranges, but occupy similar climatic niches in North America (U. phaea) and Europe (U. pustulata): high elevation populations are located in the cold temperate zone and low elevation populations in the Mediterranean zone. We assessed gene content variation along replicated elevation gradients in each of the two species, based on a total of 2050 individuals across 26 populations. Specifically, we assessed shared orthologs across species within the same climate zone, and tracked which genes increase or decrease in abundance within populations along elevation. In total, we found 16 orthogroups with shared orthologous genes in genomes at low elevation and 13 at high elevation. Coverage analysis revealed one ortholog that is exclusive to genomes at low elevation. Conserved domain search revealed domains common to the protein kinases (PKs) superfamily. We traced the discovered ortholog in populations along five replicated elevation gradients on both continents. The protein kinase gene linearly declined in abundance with increasing elevation, and was absent in the highest populations. We consider the parallel loss of an ortholog in two species and in two geographic settings a rare find, and a step forward in understanding the genomic underpinnings of climatic tolerances in lichenized fungi. In addition, the tracking of gene content variation provides a widely applicable framework for retrieving biogeographical determinants of gene presence/absence patterns. Our work provides insights into gene content variation of lichenized fungi in relation to climatic gradients, suggesting a new research direction with implications for understanding evolutionary trajectories of complex symbioses in relation to climatic change.
Afterimages result from a prolonged exposure to still visual stimuli. They are best detectable when viewed against uniform backgrounds and can persist for multiple seconds. Consequently, the dynamics of afterimages appears to be slow by their very nature. To the contrary, we report here that about 50% of an afterimage intensity can be erased rapidly—within less than a second. The prerequisite is that subjects view a rich visual content to erase the afterimage; fast erasure of afterimages does not occur if subjects view a blank screen. Moreover, we find evidence that fast removal of afterimages is a skill learned with practice as our subjects were always more effective in cleaning up afterimages in later parts of the experiment. These results can be explained by a tri-level hierarchy of adaptive mechanisms, as has been proposed by the theory of practopoiesis.
Tree bark constitutes ideal habitat for microbial communities, because it is a stable substrate, rich in micro-niches. Bacteria, fungi, and terrestrial microalgae together form microbial communities, which in turn support more bark-associated organisms, such as mosses, lichens, and invertebrates, thus contributing to forest biodiversity. We have a limited understanding of the diversity and biotic interactions of the bark-associated microbiome, as investigations have mainly focussed on agriculturally relevant systems and on single taxonomic groups. Here we implemented a multi-kingdom metabarcoding approach to analyse diversity and community structure of the green algal, bacterial, and fungal components of the bark-associated microbial communities of beech, the most common broadleaved tree of Central European forests. We identified the most abundant taxa, hub taxa, and co-occurring taxa. We found that tree size (as a proxy for age) is an important driver of community assembly, suggesting that environmental filtering leads to less diverse fungal and algal communities over time. Conversely, forest management intensity had negligible effects on microbial communities on bark. Our study suggests the presence of undescribed, yet ecologically meaningful taxa, especially in the fungi, and highlights the importance of bark surfaces as a reservoir of microbial diversity. Our results constitute a first, essential step towards an integrated framework for understanding microbial community assembly processes on bark surfaces, an understudied habitat and neglected component of terrestrial biodiversity. Finally, we propose a cost-effective sampling strategy to study bark-associated microbial communities across large spatial or environmental scales.
Genome mining as a biotechnological tool for the discovery of novel biosynthetic genes in lichens
(2022)
The ever-increasing demand for novel drugs highlights the need for bioprospecting unexplored taxa for their biosynthetic potential. Lichen-forming fungi (LFF) are a rich source of natural products but their implementation in pharmaceutical industry is limited, mostly because the genes corresponding to a majority of their natural products is unknown. Furthermore, it is not known to what extent these genes encode structurally novel molecules. Advance in next-generation sequencing technologies has expanded the range of organisms that could be exploited for their biosynthetic potential. In this study, we mine the genomes of nine lichen-forming fungal species of the genus Umbilicaria for biosynthetic genes, and categorize the BGCs as “associated product structurally known”, and “associated product putatively novel”. We found that about 25-30% of the biosynthetic genes are divergent when compared to the global database of BGCs comprising of 1,200,000 characterized biosynthetic genes from planta, bacteria and fungi. Out of 217 total BGCs, 43 were only distantly related to known BGCs, suggesting they encode structurally and functionally unknown natural products. Clusters encoding the putatively novel metabolic diversity comprise PKSs (30), NRPSs (12) and terpenes (1). Our study emphasizes the utility of genomic data in bioprospecting microorganisms for their biosynthetic potential and in advancing the industrial application of unexplored taxa. We highlight the untapped structural metabolic diversity encoded in the lichenized fungal genomes. To the best of our knowledge, this is the first investigation identifying genes coding for NPs with potentially novel therapeutic properties in LFF.
Cross-frequency coupling (CFC) has been proposed to coordinate neural dynamics across spatial and temporal scales. Despite its potential relevance for understanding healthy and pathological brain function, the standard CFC analysis and physiological interpretation come with fundamental problems. For example, apparent CFC can appear because of spectral correlations due to common non-stationarities that may arise in the total absence of interactions between neural frequency components. To provide a road map towards an improved mechanistic understanding of CFC, we organize the available and potential novel statistical/modeling approaches according to their biophysical interpretability. While we do not provide solutions for all the problems described, we provide a list of practical recommendations to avoid common errors and to enhance the interpretability of CFC analysis.
Untangling the cell immune response dynamic for severe and critical cases of SARS-CoV-2 infection
(2021)
COVID-19 is a global pandemic leading high death tolls worldwide day by day. Clinical evidence suggests that COVID-19 patients can be classified as non-severe, severe and critical cases. In particular, studies have highlighted the relationship between the lymphopenia and the severity of the illness, where CD8+ T cells have the lowest levels in critical cases. In this work, we aim to elucidate the key parameters that define the course of the disease deviating from severe to critical case. To this end, several mathematical models are proposed to represent the dynamic of the immune response in patients with SARS-CoV-2 infection. The best model had a good fit to reported experimental data, and in accordance with values found in the literature. Our results suggest that a rapid proliferation of CD8+ T cells is decisive in the severity of the disease.
Tracking influenza a virus infection in the lung from hematological data with machine learning
(2022)
The tracking of pathogen burden and host responses with minimal-invasive methods during respiratory infections is central for monitoring disease development and guiding treatment decisions. Utilizing a standardized murine model of respiratory Influenza A virus (IAV) infection, we developed and tested different supervised machine learning models to predict viral burden and immune response markers, i.e. cytokines and leukocytes in the lung, from hematological data. We performed independently in vivo infection experiments to acquire extensive data for training and testing purposes of the models. We show here that lung viral load, neutrophil counts, cytokines like IFN-γ and IL-6, and other lung infection markers can be predicted from hematological data. Furthermore, feature analysis of the models shows that blood granulocytes and platelets play a crucial role in prediction and are highly involved in the immune response against IAV. The proposed in silico tools pave the path towards improved tracking and monitoring of influenza infections and possibly other respiratory infections based on minimal-invasively obtained hematological parameters.
Abstract
Co-infections by multiple pathogens have important implications in many aspects of health, epidemiology and evolution. However, how to disentangle the contributing factors of the immune response when two infections take place at the same time is largely unexplored. Using data sets of the immune response during influenza-pneumococcal co-infection in mice, we employ here topological data analysis to simplify and visualise high dimensional data sets.
We identified persistent shapes of the simplicial complexes of the data in the three infection scenarios: single viral infection, single bacterial infection, and co-infection. The immune response was found to be distinct for each of the infection scenarios and we uncovered that the immune response during the co-infection has three phases and two transition points. During the first phase, its dynamics is inherited from its response to the primary (viral) infection. The immune response has an early (few hours post co-infection) and then modulates its response to finally react against the secondary (bacterial) infection. Between 18 to 26 hours post co-infection the nature of the immune response changes again and does no longer resembles either of the single infection scenarios.
Author summary
The mapper algorithm is a topological data analysis technique used for the qualitative analysis, simplification and visualisation of high dimensional data sets. It generates a low-dimensional image that captures topological and geometric information of the data set in high dimensional space, which can highlight groups of data points of interest and can guide further analysis and quantification.
To understand how the immune system evolves during the co-infection between viruses and bacteria, and the role of specific cytokines as contributing factors for these severe infections, we use Topological Data Analysis (TDA) along with an extensive semi-unsupervised parameter value grid search, and k-nearest neighbour analysis.
We find persistent shapes of the data in the three infection scenarios, single viral and bacterial infections and co-infection. The immune response is shown to be distinct for each of the infections scenarios and we uncover that the immune response during the co-infection has three phases and two transition points, a previously unknown property regarding the dynamics of the immune response during co-infection.
Intrinsically disordered regions (IDRs) are essential for membrane receptor regulation but often remain unresolved in structural studies. TRPV4, a member of the TRP vanilloid channel family involved in thermo- and osmosensation, has a large N-terminal IDR of approximately 150 amino acids. With an integrated structural biology approach, we analyze the structural ensemble of the TRPV4 IDR and identify a network of regulatory elements that modulate channel activity in a hierarchical lipid-dependent manner through transient long-range interactions. A highly conserved autoinhibitory patch acts as a master regulator by competing with PIP2 binding to attenuate channel activity. Molecular dynamics simulations show that loss of the interaction between the PIP2-binding site and the membrane reduces the force exerted by the IDR on the structured core of TRPV4. This work demonstrates that IDR structural dynamics are coupled to TRPV4 activity and highlights the importance of IDRs for TRP channel function and regulation.