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In the framework of the presented doctoral thesis, the plant ubiquitous, non-selective vacuolar cation channel TPC1/SV was electrophysiologically studied in Arabidopsis thaliana mesophyll vacuoles to further enlighten its physiological role in plant stress responses. For this, the hyperactive channel version fou2 (D454N), gaining a non-functional vacuolar calcium sensor, strong retarded growth phenotype and upregulated JA signalling pathway, and eight fou2 reverting WT-like ouf mutants were used. Except of ouf4, all other seven ouf mutants carried a 2nd mutation in the TPC1 gene. Therefore, the TPC1 electrical features of all ouf mutants were electrophysiologically characterized with the patch clamp method and compared with fou2 and WT.
Due to a missense mutation, ouf1 and ouf7 mutants harboured a truncated TPC1 channel protein, resulting in an impaired protein integrity and in turn loss of TPC1 channel activity. Accordingly, ouf1 and ouf7 mimicked the tpc1-2 null mutant with a WT- rather fou2-like phenotype. The ouf2 (G583D D454N) mutant exhibited inactive TPC1 channels, probably because the G583D mutation located in luminal part of the S11 helix caused (i) a shift of the activation threshold to much more positive voltages (i.e. to more than +110 mV) (ii) or channel blockage. As a result of the TPC1 channel inactivity, the ouf2 mutant also imitates the WT-like phenotype of the tpc1-2 null mutant. In the ouf6 mutant (A669V D454N) the 2nd reverting mutation selectively influenced fou2-like SV channel features. Both, the fast activation kinetics and reduced luminal calcium sensitivity were similar in ouf6 and fou2. However, deviations in both, the relative and absolute open channel probability, resulted in strongly reduced (80 %) current density at 0 mM and channel inactivity in the voltage range between -30 mV to +40 mV compared to fou2 and WT. Furthermore, the TPC1 channels in ouf6 exhibited a higher susceptibility to inhibitory luminal Ca2+ than fou2. As a result of these different effects, the TPC1 channel activity almost vanished at high luminal Ca2+ loads, what is very likely the reason that ouf6 lost the fou2-like phenotype. The ouf4 mutation did not change the fou2 TPC1-channel features like fast channel activation, single channel conductance and voltage-dependent gating behaviour. Nevertheless, the TPC1 current density was 80% less in ouf4 than in fou2. Since the TPC1 gene was not the target of the 2nd mutation, it can be assumed that it is modulated via external, yet unknown factor. In the ouf8 mutant the TPC1 channels additionally possess M629I mutation within the selectivity filter II resulting in a 50% decrease in the TPC1 unitary conductance. However, the slightly increased relative open channel probability of the TPC1 channels in ouf8 compared to fou2 appeared to be sufficient to compensate the reduced transport capacity of individual TPC1 channels. As a result, a similar macroscopic outward current density of ouf8 and fou2 was detected in the absence of vacuolar Ca2+. Furthermore, ouf8 mutation did not drastically change the typical fou2 TPC1 channel features such as fast activation, vacuolar calcium insensitivity and voltage dependency. However, a reversible block of the cytosol-directed potassium efflux at increased vacuolar calcium concentration in ouf8 mutant was found. Further inspection of transiently expressed TPC1 channel variants (M629I, M629T) on the single channel level suggest that Met629 of AtTPC1 in the channel pore region is crucial for the unitary channel conductance.
Taken together, current membrane recordings from ouf mutants revealed one common feature: All of them lacked or showed a strongly impaired ability for TPC1-mediated potassium release from the vacuole into the cytosol. Additionally, considering the detected dependence of the vacuolar membrane voltage on TPC1 activity, it thus seems that the TPC1-triggered vacuolar membrane depolarization caused by vacuolar K+ release plays a key role in generation of the fou2-like phenotype. Accordingly, one can conclude that TPC1-dependent vacuolar membrane depolarization and initiation of jasmonate production are likely linked. This statement is supported also by the complete restoration of WT-like plant phenotype and JA signalling in the ouf mutants. Finally, as a control element of the vacuolar membrane voltage TPC1 is probably upstream located in JA signalling pathway and therefore a perfect junction for linking multiple physiological stimuli and response to them.
Im Rahmen der vorgelegten Doktorarbeit wurde der in Pflanzen ubiquitär exprimierte, nicht-selektive vakuoläre Kationenkanal TPC1/SV elektrophysiologisch in Arabidopsis thaliana Mesophyllvakuolen untersucht, um seine physiologische Rolle in der pflanzlichen Stressantwort weiter aufzuklären. Hierfür wurde die hyperaktive Kanalvariante fou2 (D454N), die einen nicht-funktionalen vakuolären Calciumsensor, ein stark verzögertes Pflanzenwachstum und einen hochregulierten Jasmonsäure-Signalweg aufweist, sowie acht ouf Mutanten mit fou2-umkehrenden Phänotyp benutzt. Mit Ausnahme von ouf4 enthalten alle anderen ouf Mutanten eine weitere Mutation im TPC1-Gen. Daher wurden die elektrischen Eigenschaften von TPC1 in allen ouf Mutanten elektrophysiologisch mittels der Patch clamp Technik charakterisiert und mit fou2 und dem Wildtyp verglichen.
Aufgrund einer Missense-Mutation beinhalten die Mutanten ouf1 und ouf7 ein verkürztes TPC1 Protein, woraus eine gestörte Proteinintegrität resultiert und daraus wiederum ein Fehlen der TCP1-Kanalaktivität. Dementsprechend ähneln ouf1 und ouf7 der tpc1-2 Nullmutante mit einem WT- oder eher fou2-artigen Phänotyp. Wahrscheinlich weist die ouf2 (G583D D454N) Mutante einen inaktiven TPC1-Kanal auf, weil die G583D Mutation, die in einem luminalen Teil der S11 Helix sitzt, eine Verschiebung der Aktivierungsschwelle hin zu einer höheren Spannung (z. B. mehr als +110 mV) oder einen Kanalblock verursacht. Als Folge der TPC1 Kanal Inaktivität, ahmt die ouf2 Mutante auch den WT-ähnlichen Phänotyp der tpc1-2 Nullmutante nach. In der ouf6 Mutante (A669V D454N) beeinflusst die zweite Mutation selektiv die fou2-ähnlichen SV-Kanaleigenschaften. Sowohl die schnelle Aktivierungskinetik als auch die verringerte luminale Calciumsensitivität waren denen von ouf6 und fou2 ähnlich. Die Abweichungen in der relativen sowie der absoluten Offenwahrscheinlichkeit resultierten jedoch in einer stark reduzierten (80 %) Stromdichte bei 0 mM luminalem Calcium verglichen mit fou2 und dem WT, sowie einer Kanalinaktivität bei Spannungen zwischen -30 mV und +40 mV. Darüber hinaus zeigten die TPC1 Kanäle in ouf6 eine höhere Anfälligkeit für inhibitorisches, luminales Calcium als die in fou2. Das Ergebnis der beiden unterschiedlichen Effekte ist, dass die TPC1 Kanalaktivität bei einer hohen luminalen Calciumkonzentration fast verschwindet, woraus zu schließen ist, dass ouf6 den fou2-ähnlichen Phänotyp verlor. Die ouf4 Mutation veränderte nicht die fou2 TPC1 Kanaleigenschaften, wie die schnelle Kanalaktivierung, die Einzelkanalleitfähigkeit und das spannungsabhängige Verhalten. Nichtsdestotrotz war die TCP1 Stromdichte in ouf4 um 80 % geringer als in fou2. Da das TPC1 Gen nicht das Ziel der zweiten Mutation war, kann angenommen werden, dass es durch äußere, bisher noch unbekannte Faktoren, reguliert wird. In der ouf8 Mutante haben die TPC1 Kanäle zusätzlich eine M629I Mutation innerhalb des zweiten Selektivitätsfilters, welche in einem 50 % Rückgang der TCP1 Einzelkanalleitfähigkeit resultiert. Jedoch scheint die leicht erhöhte Offenwahrscheinlichkeit der TCP1 Kanäle in ouf8, verglichen mit fou2, ausreichend zu sein, um die reduzierte Transportkapazität der individuellen TPC1 Kanäle zu kompensieren. Schlussfolgernd wurde eine ähnliche makroskopische auswärts gerichtete Stromdichte des ouf8 und des fou2 in Abwesenheit vakuolären Calciums entdeckt. Des Weiteren änderte eine ouf8 Mutation die fou2 TPC1 Kanaleigenschaften wie eine schnelle Aktivierung, vakuoläre Calciuminsensitivität und die Spannungsabhängigkeit nicht drastisch. Jedoch wurde ein reversibler Block des Zytosol-gerichteten Kalium Ausstroms bei erhöhten vakuolären Calcium Konzentrationen in ouf8 gefunden. Eine weitere Betrachtung transient exprimierter TPC1 Kanalvarianten (M629I, M629T) auf Einzelkanalebene weist darauf hin, dass das Met629 des AtTPC1 in der Kanalporenregion entscheidend ist für die Einzelkanalleitfähigkeit.
Zusammengefasst zeigt der über die Membran von ouf Mutanten gemessene Strom eine Gemeinsamkeit: Alle zeigten keinen oder einen stark beeinträchtigten TPC1-vermittelten Kaliumausstrom aus der Vakuole ins Zytosol. Unter Berücksichtigung der beobachteten Abhängigkeit der vakuolären Membranspannung von der TPC1 Aktivität, scheint es, als ob die durch TPC1 angeregte Depolarisation der Vakuolenmembran, welche durch die vakuoläre Kaliumfreisetzung bedingt wird, in der Ausbildung des fou2 Phänotyps eine Rolle spielt. Daraus lässt sich ableiten, dass die TPC1-abhängige Depolarisation der Vakuolenmembran und die Jasmonat Bildung vermutlich verbunden sind. Diese Behauptung wird auch gestützt durch die komplette Wiederherstellung des WT-ähnlichen Pflanzenphänotyps und des Jasmonsäure Signalwegs in den ouf Mutanten. Letztendlich ist TPC1 als kontrollierendes Element der vakuolären Membranspannung wahrscheinlich dem Jasmonsäure Signalweg vorgeschaltet und deswegen ein perfekter Knotenpunkt, der verschiedene physiologische Stimuli und ihre Antworten verbindet.
Ultrastructural analysis of wild-type and RIM1α knockout active zones in a large cortical synapse
(2022)
Rab3A-interacting molecule (RIM) is crucial for fast Ca\(^{2+}\)-triggered synaptic vesicle (SV) release in presynaptic active zones (AZs). We investigated hippocampal giant mossy fiber bouton (MFB) AZ architecture in 3D using electron tomography of rapid cryo-immobilized acute brain slices in RIM1α\(^{−/−}\) and wild-type mice. In RIM1α\(^{−/−}\), AZs are larger with increased synaptic cleft widths and a 3-fold reduced number of tightly docked SVs (0–2 nm). The distance of tightly docked SVs to the AZ center is increased from 110 to 195 nm, and the width of their electron-dense material between outer SV membrane and AZ membrane is reduced. Furthermore, the SV pool in RIM1α\(^{−/−}\) is more heterogeneous. Thus, RIM1α, besides its role in tight SV docking, is crucial for synaptic architecture and vesicle pool organization in MFBs.
Understanding extinction debts: spatio-temporal scales, mechanisms and a roadmap for future research
(2019)
Extinction debt refers to delayed species extinctions expected as a consequence of ecosystem perturbation. Quantifying such extinctions and investigating long‐term consequences of perturbations has proven challenging, because perturbations are not isolated and occur across various spatial and temporal scales, from local habitat losses to global warming. Additionally, the relative importance of eco‐evolutionary processes varies across scales, because levels of ecological organization, i.e. individuals, (meta)populations and (meta)communities, respond hierarchically to perturbations. To summarize our current knowledge of the scales and mechanisms influencing extinction debts, we reviewed recent empirical, theoretical and methodological studies addressing either the spatio–temporal scales of extinction debts or the eco‐evolutionary mechanisms delaying extinctions. Extinction debts were detected across a range of ecosystems and taxonomic groups, with estimates ranging from 9 to 90% of current species richness. The duration over which debts have been sustained varies from 5 to 570 yr, and projections of the total period required to settle a debt can extend to 1000 yr. Reported causes of delayed extinctions are 1) life‐history traits that prolong individual survival, and 2) population and metapopulation dynamics that maintain populations under deteriorated conditions. Other potential factors that may extend survival time such as microevolutionary dynamics, or delayed extinctions of interaction partners, have rarely been analyzed. Therefore, we propose a roadmap for future research with three key avenues: 1) the microevolutionary dynamics of extinction processes, 2) the disjunctive loss of interacting species and 3) the impact of multiple regimes of perturbation on the payment of debts. For their ability to integrate processes occurring at different levels of ecological organization, we highlight mechanistic simulation models as tools to address these knowledge gaps and to deepen our understanding of extinction dynamics.
The prediction of breeding values and phenotypes is of central importance for both livestock and crop breeding. In this study, we analyze the use of artificial neural networks (ANN) and, in particular, local convolutional neural networks (LCNN) for genomic prediction, as a region-specific filter corresponds much better with our prior genetic knowledge on the genetic architecture of traits than traditional convolutional neural networks. Model performances are evaluated on a simulated maize data panel (n = 10,000; p = 34,595) and real Arabidopsis data (n = 2,039; p = 180,000) for a variety of traits based on their predictive ability. The baseline LCNN, containing one local convolutional layer (kernel size: 10) and two fully connected layers with 64 nodes each, is outperforming commonly proposed ANNs (multi layer perceptrons and convolutional neural networks) for basically all considered traits. For traits with high heritability and large training population as present in the simulated data, LCNN are even outperforming state-of-the-art methods like genomic best linear unbiased prediction (GBLUP), Bayesian models and extended GBLUP, indicated by an increase in predictive ability of up to 24%. However, for small training populations, these state-of-the-art methods outperform all considered ANNs. Nevertheless, the LCNN still outperforms all other considered ANNs by around 10%. Minor improvements to the tested baseline network architecture of the LCNN were obtained by increasing the kernel size and of reducing the stride, whereas the number of subsequent fully connected layers and their node sizes had neglectable impact. Although gains in predictive ability were obtained for large scale data sets by using LCNNs, the practical use of ANNs comes with additional problems, such as the need of genotyping all considered individuals, the lack of estimation of heritability and reliability. Furthermore, breeding values are additive by design, whereas ANN-based estimates are not. However, ANNs also comes with new opportunities, as networks can easily be extended to account for additional inputs (omics, weather etc.) and outputs (multi-trait models), and computing time increases linearly with the number of individuals. With advances in high-throughput phenotyping and cheaper genotyping, ANNs can become a valid alternative for genomic prediction.
Although the concept of botanical carnivory has been known since Darwin's time, the molecular mechanisms that allow animal feeding remain unknown, primarily due to a complete lack of genomic information. Here, we show that the transcriptomic landscape of the Dionaea trap is dramatically shifted toward signal transduction and nutrient transport upon insect feeding, with touch hormone signaling and protein secretion prevailing. At the same time, a massive induction of general defense responses is accompanied by the repression of cell death-related genes/processes. We hypothesize that the carnivory syndrome of Dionaea evolved by exaptation of ancient defense pathways, replacing cell death with nutrient acquisition.
Personalized oncology is a rapidly evolving area and offers cancer patients therapy options that are more specific than ever. However, there is still a lack of understanding regarding transcriptomic similarities or differences of metastases and corresponding primary sites. Applying two unsupervised dimension reduction methods (t-Distributed Stochastic Neighbor Embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP)) on three datasets of metastases (n = 682 samples) with three different data transformations (unprocessed, log10 as well as log10 + 1 transformed values), we visualized potential underlying clusters. Additionally, we analyzed two datasets (n = 616 samples) containing metastases and primary tumors of one entity, to point out potential familiarities. Using these methods, no tight link between the site of resection and cluster formation outcome could be demonstrated, or for datasets consisting of solely metastasis or mixed datasets. Instead, dimension reduction methods and data transformation significantly impacted visual clustering results. Our findings strongly suggest data transformation to be considered as another key element in the interpretation of visual clustering approaches along with initialization and different parameters. Furthermore, the results highlight the need for a more thorough examination of parameters used in the analysis of clusters.
Although many genes have been identified using high throughput technologies in endometriosis (ES), only a small number of individual genes have been analyzed functionally. This is due to the complexity of the disease that has different stages and is affected by various genetic and environmental factors. Many genes are upregulated or downregulated at each stage of the disease, thus making it difficult to identify key genes. In addition, little is known about the differences between the different stages of the disease. We assumed that the study of the identified genes in ES at a system-level can help to better understand the molecular mechanism of the disease at different stages of the development. We used publicly available microarray data containing archived endometrial samples from women with minimal/mild endometriosis (MMES), mild/severe endometriosis (MSES) and without endometriosis. Using weighted gene co-expression analysis (WGCNA), functional modules were derived from normal endometrium (NEM) as the reference sample. Subsequently, we tested whether the topology or connectivity pattern of the modules was preserved in MMES and/or MSES. Common and specific hub genes were identified in non-preserved modules. Accordingly, hub genes were detected in the non-preserved modules at each stage. We identified sixteen co-expression modules. Of the 16 modules, nine were non-preserved in both MMES and MSES whereas five were preserved in NEM, MMES, and MSES. Importantly, two non-preserved modules were found in either MMES or MSES, highlighting differences between the two stages of the disease. Analyzing the hub genes in the non-preserved modules showed that they mostly lost or gained their centrality in NEM after developing the disease into MMES and MSES. The same scenario was observed, when the severeness of the disease switched from MMES to MSES. Interestingly, the expression analysis of the new selected gene candidates including CC2D2A, AEBP1, HOXB6, IER3, and STX18 as well as IGF-1, CYP11A1 and MMP-2 could validate such shifts between different stages. The overrepresented gene ontology (GO) terms were enriched in specific modules, such as genetic disposition, estrogen dependence, progesterone resistance and inflammation, which are known as endometriosis hallmarks. Some modules uncovered novel co-expressed gene clusters that were not previously discovered.