@article{FigueiredoKraussSteffanDewenteretal.2019, author = {Figueiredo, Ludmilla and Krauss, Jochen and Steffan-Dewenter, Ingolf and Cabral, Juliano Sarmento}, title = {Understanding extinction debts: spatio-temporal scales, mechanisms and a roadmap for future research}, series = {Ecography}, volume = {42}, journal = {Ecography}, number = {12}, doi = {10.1111/ecog.04740}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-204859}, pages = {1973-1990}, year = {2019}, abstract = {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.}, language = {en} } @phdthesis{Leidinger2020, author = {Leidinger, Ludwig Klaus Theodor}, title = {How genomic and ecological traits shape island biodiversity - insights from individual-based models}, doi = {10.25972/OPUS-20730}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-207300}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2020}, abstract = {Life on oceanic islands provides a playground and comparably easy\-/studied basis for the understanding of biodiversity in general. Island biota feature many fascinating patterns: endemic species, species radiations and species with peculiar trait syndromes. However, classic and current island biogeography theory does not yet consider all the factors necessary to explain many of these patterns. In response to this, there is currently a shift in island biogeography research to systematically consider species traits and thus gain a more functional perspective. Despite this recent development, a set of species characteristics remains largely ignored in island biogeography, namely genomic traits. Evidence suggests that genomic factors could explain many of the speciation and adaptation patterns found in nature and thus may be highly informative to explain the fascinating and iconic phenomena known for oceanic islands, including species radiations and susceptibility to biotic invasions. Unfortunately, the current lack of comprehensive meaningful data makes studying these factors challenging. Even with paleontological data and space-for-time rationales, data is bound to be incomplete due to the very environmental processes taking place on oceanic islands, such as land slides and volcanism, and lacks causal information due to the focus on correlative approaches. As promising alternative, integrative mechanistic models can explicitly consider essential underlying eco\-/evolutionary mechanisms. In fact, these models have shown to be applicable to a variety of different systems and study questions. In this thesis, I therefore examined present mechanistic island models to identify how they might be used to address some of the current open questions in island biodiversity research. Since none of the models simultaneously considered speciation and adaptation at a genomic level, I developed a new genome- and niche-explicit, individual-based model. I used this model to address three different phenomena of island biodiversity: environmental variation, insular species radiations and species invasions. Using only a single model I could show that small-bodied species with flexible genomes are successful under environmental variation, that a complex combination of dispersal abilities, reproductive strategies and genomic traits affect the occurrence of species radiations and that invasions are primarily driven by the intensity of introductions and the trait characteristics of invasive species. This highlights how the consideration of functional traits can promote the understanding of some of the understudied phenomena in island biodiversity. The results presented in this thesis exemplify the generality of integrative models which are built on first principles. Thus, by applying such models to various complex study questions, they are able to unveil multiple biodiversity dynamics and patterns. The combination of several models such as the one I developed to an eco\-/evolutionary model ensemble could further help to identify fundamental eco\-/evolutionary principles. I conclude the thesis with an outlook on how to use and extend my developed model to investigate geomorphological dynamics in archipelagos and to allow dynamic genomes, which would further increase the model's generality.}, subject = {Inselbiogeografie}, language = {en} } @article{LichterPaulPaulietal.2022, author = {Lichter, Katharina and Paul, Mila Marie and Pauli, Martin and Schoch, Susanne and Kollmannsberger, Philip and Stigloher, Christian and Heckmann, Manfred and Sir{\´e}n, Anna-Leena}, title = {Ultrastructural analysis of wild-type and RIM1α knockout active zones in a large cortical synapse}, series = {Cell Reports}, volume = {40}, journal = {Cell Reports}, number = {12}, doi = {10.1016/j.celrep.2022.111382}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-300913}, year = {2022}, abstract = {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.}, language = {en} } @phdthesis{Jaslan2020, author = {Jaslan, Dawid Artur}, title = {TPC1 mutants provide insight into SV channel function}, doi = {10.25972/OPUS-15731}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-157312}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2020}, abstract = {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 ubiquit{\"a}r exprimierte, nicht-selektive vakuol{\"a}re Kationenkanal TPC1/SV elektrophysiologisch in Arabidopsis thaliana Mesophyllvakuolen untersucht, um seine physiologische Rolle in der pflanzlichen Stressantwort weiter aufzukl{\"a}ren. Hierf{\"u}r wurde die hyperaktive Kanalvariante fou2 (D454N), die einen nicht-funktionalen vakuol{\"a}ren Calciumsensor, ein stark verz{\"o}gertes Pflanzenwachstum und einen hochregulierten Jasmons{\"a}ure-Signalweg aufweist, sowie acht ouf Mutanten mit fou2-umkehrenden Ph{\"a}notyp 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 verk{\"u}rztes TPC1 Protein, woraus eine gest{\"o}rte Proteinintegrit{\"a}t resultiert und daraus wiederum ein Fehlen der TCP1-Kanalaktivit{\"a}t. Dementsprechend {\"a}hneln ouf1 und ouf7 der tpc1-2 Nullmutante mit einem WT- oder eher fou2-artigen Ph{\"a}notyp. 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 h{\"o}heren Spannung (z. B. mehr als +110 mV) oder einen Kanalblock verursacht. Als Folge der TPC1 Kanal Inaktivit{\"a}t, ahmt die ouf2 Mutante auch den WT-{\"a}hnlichen Ph{\"a}notyp der tpc1-2 Nullmutante nach. In der ouf6 Mutante (A669V D454N) beeinflusst die zweite Mutation selektiv die fou2-{\"a}hnlichen SV-Kanaleigenschaften. Sowohl die schnelle Aktivierungskinetik als auch die verringerte luminale Calciumsensitivit{\"a}t waren denen von ouf6 und fou2 {\"a}hnlich. 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 Kanalinaktivit{\"a}t bei Spannungen zwischen -30 mV und +40 mV. Dar{\"u}ber hinaus zeigten die TPC1 Kan{\"a}le in ouf6 eine h{\"o}here Anf{\"a}lligkeit f{\"u}r inhibitorisches, luminales Calcium als die in fou2. Das Ergebnis der beiden unterschiedlichen Effekte ist, dass die TPC1 Kanalaktivit{\"a}t bei einer hohen luminalen Calciumkonzentration fast verschwindet, woraus zu schließen ist, dass ouf6 den fou2-{\"a}hnlichen Ph{\"a}notyp verlor. Die ouf4 Mutation ver{\"a}nderte nicht die fou2 TPC1 Kanaleigenschaften, wie die schnelle Kanalaktivierung, die Einzelkanalleitf{\"a}higkeit und das spannungsabh{\"a}ngige 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 {\"a}ußere, bisher noch unbekannte Faktoren, reguliert wird. In der ouf8 Mutante haben die TPC1 Kan{\"a}le zus{\"a}tzlich eine M629I Mutation innerhalb des zweiten Selektivit{\"a}tsfilters, welche in einem 50 \% R{\"u}ckgang der TCP1 Einzelkanalleitf{\"a}higkeit resultiert. Jedoch scheint die leicht erh{\"o}hte Offenwahrscheinlichkeit der TCP1 Kan{\"a}le in ouf8, verglichen mit fou2, ausreichend zu sein, um die reduzierte Transportkapazit{\"a}t der individuellen TPC1 Kan{\"a}le zu kompensieren. Schlussfolgernd wurde eine {\"a}hnliche makroskopische ausw{\"a}rts gerichtete Stromdichte des ouf8 und des fou2 in Abwesenheit vakuol{\"a}ren Calciums entdeckt. Des Weiteren {\"a}nderte eine ouf8 Mutation die fou2 TPC1 Kanaleigenschaften wie eine schnelle Aktivierung, vakuol{\"a}re Calciuminsensitivit{\"a}t und die Spannungsabh{\"a}ngigkeit nicht drastisch. Jedoch wurde ein reversibler Block des Zytosol-gerichteten Kalium Ausstroms bei erh{\"o}hten vakuol{\"a}ren 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 f{\"u}r die Einzelkanalleitf{\"a}higkeit. Zusammengefasst zeigt der {\"u}ber die Membran von ouf Mutanten gemessene Strom eine Gemeinsamkeit: Alle zeigten keinen oder einen stark beeintr{\"a}chtigten TPC1-vermittelten Kaliumausstrom aus der Vakuole ins Zytosol. Unter Ber{\"u}cksichtigung der beobachteten Abh{\"a}ngigkeit der vakuol{\"a}ren Membranspannung von der TPC1 Aktivit{\"a}t, scheint es, als ob die durch TPC1 angeregte Depolarisation der Vakuolenmembran, welche durch die vakuol{\"a}re Kaliumfreisetzung bedingt wird, in der Ausbildung des fou2 Ph{\"a}notyps eine Rolle spielt. Daraus l{\"a}sst sich ableiten, dass die TPC1-abh{\"a}ngige Depolarisation der Vakuolenmembran und die Jasmonat Bildung vermutlich verbunden sind. Diese Behauptung wird auch gest{\"u}tzt durch die komplette Wiederherstellung des WT-{\"a}hnlichen Pflanzenph{\"a}notyps und des Jasmons{\"a}ure Signalwegs in den ouf Mutanten. Letztendlich ist TPC1 als kontrollierendes Element der vakuol{\"a}ren Membranspannung wahrscheinlich dem Jasmons{\"a}ure Signalweg vorgeschaltet und deswegen ein perfekter Knotenpunkt, der verschiedene physiologische Stimuli und ihre Antworten verbindet.}, language = {en} } @unpublished{HeidenreichGassenmaierAnkenbrandetal.2021, author = {Heidenreich, Julius F. and Gassenmaier, Tobias and Ankenbrand, Markus J. and Bley, Thorsten A. and Wech, Tobias}, title = {Self-configuring nnU-net pipeline enables fully automatic infarct segmentation in late enhancement MRI after myocardial infarction}, edition = {accepted version}, doi = {10.1016/j.ejrad.2021.109817}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-323418}, year = {2021}, abstract = {Purpose To fully automatically derive quantitative parameters from late gadolinium enhancement (LGE) cardiac MR (CMR) in patients with myocardial infarction and to investigate if phase sensitive or magnitude reconstructions or a combination of both results in best segmentation accuracy. Methods In this retrospective single center study, a convolutional neural network with a U-Net architecture with a self-configuring framework ("nnU-net") was trained for segmentation of left ventricular myocardium and infarct zone in LGE-CMR. A database of 170 examinations from 78 patients with history of myocardial infarction was assembled. Separate fitting of the model was performed, using phase sensitive inversion recovery, the magnitude reconstruction or both contrasts as input channels. Manual labelling served as ground truth. In a subset of 10 patients, the performance of the trained models was evaluated and quantitatively compared by determination of the S{\o}rensen-Dice similarity coefficient (DSC) and volumes of the infarct zone compared with the manual ground truth using Pearson's r correlation and Bland-Altman analysis. Results The model achieved high similarity coefficients for myocardium and scar tissue. No significant difference was observed between using PSIR, magnitude reconstruction or both contrasts as input (PSIR and MAG; mean DSC: 0.83 ± 0.03 for myocardium and 0.72 ± 0.08 for scars). A strong correlation for volumes of infarct zone was observed between manual and model-based approach (r = 0.96), with a significant underestimation of the volumes obtained from the neural network. Conclusion The self-configuring nnU-net achieves predictions with strong agreement compared to manual segmentation, proving the potential as a promising tool to provide fully automatic quantitative evaluation of LGE-CMR.}, language = {en} } @article{BemmBeckerLarischetal.2016, author = {Bemm, Felix and Becker, Dirk and Larisch, Christina and Kreuzer, Ines and Escalante-Perez, Maria and Schulze, Waltraud X. and Ankenbrand, Markus and Van de Weyer, Anna-Lena and Krol, Elzbieta and Al-Rasheid, Khaled A. and Mith{\"o}fer, Axel and Weber, Andreas P. and Schultz, J{\"o}rg and Hedrich, Rainer}, title = {Venus flytrap carnivorous lifestyle builds on herbivore defense strategies}, series = {Genome Research}, volume = {26}, journal = {Genome Research}, number = {6}, doi = {10.1101/gr.202200.115}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-188799}, pages = {812-825}, year = {2016}, abstract = {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.}, language = {en} } @article{SchilcherHilsmannAnkenbrandetal.2022, author = {Schilcher, Felix and Hilsmann, Lioba and Ankenbrand, Markus J. and Krischke, Markus and Mueller, Martin J. and Steffan-Dewenter, Ingolf and Scheiner, Ricarda}, title = {Honeybees are buffered against undernourishment during larval stages}, series = {Frontiers in Insect Science}, volume = {2}, journal = {Frontiers in Insect Science}, issn = {2673-8600}, doi = {10.3389/finsc.2022.951317}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-304646}, year = {2022}, abstract = {The negative impact of juvenile undernourishment on adult behavior has been well reported for vertebrates, but relatively little is known about invertebrates. In honeybees, nutrition has long been known to affect task performance and timing of behavioral transitions. Whether and how a dietary restriction during larval development affects the task performance of adult honeybees is largely unknown. We raised honeybees in-vitro, varying the amount of a standardized diet (150 µl, 160 µl, 180 µl in total). Emerging adults were marked and inserted into established colonies. Behavioral performance of nurse bees and foragers was investigated and physiological factors known to be involved in the regulation of social organization were quantified. Surprisingly, adult honeybees raised under different feeding regimes did not differ in any of the behaviors observed. No differences were observed in physiological parameters apart from weight. Honeybees were lighter when undernourished (150 µl), while they were heavier under the overfed treatment (180 µl) compared to the control group raised under a normal diet (160 µl). These data suggest that dietary restrictions during larval development do not affect task performance or physiology in this social insect despite producing clear effects on adult weight. We speculate that possible effects of larval undernourishment might be compensated during the early period of adult life.}, language = {en} } @article{SchilcherHilsmannRauscheretal.2021, author = {Schilcher, Felix and Hilsmann, Lioba and Rauscher, Lisa and Değirmenci, Laura and Krischke, Markus and Krischke, Beate and Ankenbrand, Markus and Rutschmann, Benjamin and Mueller, Martin J. and Steffan-Dewenter, Ingolf and Scheiner, Ricarda}, title = {In vitro rearing changes social task performance and physiology in honeybees}, series = {Insects}, volume = {13}, journal = {Insects}, number = {1}, issn = {2075-4450}, doi = {10.3390/insects13010004}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-252305}, year = {2021}, abstract = {In vitro rearing of honeybee larvae is an established method that enables exact control and monitoring of developmental factors and allows controlled application of pesticides or pathogens. However, only a few studies have investigated how the rearing method itself affects the behavior of the resulting adult honeybees. We raised honeybees in vitro according to a standardized protocol: marking the emerging honeybees individually and inserting them into established colonies. Subsequently, we investigated the behavioral performance of nurse bees and foragers and quantified the physiological factors underlying the social organization. Adult honeybees raised in vitro differed from naturally reared honeybees in their probability of performing social tasks. Further, in vitro-reared bees foraged for a shorter duration in their life and performed fewer foraging trips. Nursing behavior appeared to be unaffected by rearing condition. Weight was also unaffected by rearing condition. Interestingly, juvenile hormone titers, which normally increase strongly around the time when a honeybee becomes a forager, were significantly lower in three- and four-week-old in vitro bees. The effects of the rearing environment on individual sucrose responsiveness and lipid levels were rather minor. These data suggest that larval rearing conditions can affect the task performance and physiology of adult bees despite equal weight, pointing to an important role of the colony environment for these factors. Our observations of behavior and metabolic pathways offer important novel insight into how the rearing environment affects adult honeybees.}, language = {en} } @article{ReinhardHelmerichBorasetal.2022, author = {Reinhard, Sebastian and Helmerich, Dominic A. and Boras, Dominik and Sauer, Markus and Kollmannsberger, Philip}, title = {ReCSAI: recursive compressed sensing artificial intelligence for confocal lifetime localization microscopy}, series = {BMC Bioinformatics}, volume = {23}, journal = {BMC Bioinformatics}, number = {1}, doi = {10.1186/s12859-022-05071-5}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-299768}, year = {2022}, abstract = {Background Localization-based super-resolution microscopy resolves macromolecular structures down to a few nanometers by computationally reconstructing fluorescent emitter coordinates from diffraction-limited spots. The most commonly used algorithms are based on fitting parametric models of the point spread function (PSF) to a measured photon distribution. These algorithms make assumptions about the symmetry of the PSF and thus, do not work well with irregular, non-linear PSFs that occur for example in confocal lifetime imaging, where a laser is scanned across the sample. An alternative method for reconstructing sparse emitter sets from noisy, diffraction-limited images is compressed sensing, but due to its high computational cost it has not yet been widely adopted. Deep neural network fitters have recently emerged as a new competitive method for localization microscopy. They can learn to fit arbitrary PSFs, but require extensive simulated training data and do not generalize well. A method to efficiently fit the irregular PSFs from confocal lifetime localization microscopy combining the advantages of deep learning and compressed sensing would greatly improve the acquisition speed and throughput of this method. Results Here we introduce ReCSAI, a compressed sensing neural network to reconstruct localizations for confocal dSTORM, together with a simulation tool to generate training data. We implemented and compared different artificial network architectures, aiming to combine the advantages of compressed sensing and deep learning. We found that a U-Net with a recursive structure inspired by iterative compressed sensing showed the best results on realistic simulated datasets with noise, as well as on real experimentally measured confocal lifetime scanning data. Adding a trainable wavelet denoising layer as prior step further improved the reconstruction quality. Conclusions Our deep learning approach can reach a similar reconstruction accuracy for confocal dSTORM as frame binning with traditional fitting without requiring the acquisition of multiple frames. In addition, our work offers generic insights on the reconstruction of sparse measurements from noisy experimental data by combining compressed sensing and deep learning. We provide the trained networks, the code for network training and inference as well as the simulation tool as python code and Jupyter notebooks for easy reproducibility.}, language = {en} } @article{DannhaeuserMrestaniGundelachetal.2022, author = {Dannh{\"a}user, Sven and Mrestani, Achmed and Gundelach, Florian and Pauli, Martin and Komma, Fabian and Kollmannsberger, Philip and Sauer, Markus and Heckmann, Manfred and Paul, Mila M.}, title = {Endogenous tagging of Unc-13 reveals nanoscale reorganization at active zones during presynaptic homeostatic potentiation}, series = {Frontiers in Cellular Neuroscience}, volume = {16}, journal = {Frontiers in Cellular Neuroscience}, issn = {1662-5102}, doi = {10.3389/fncel.2022.1074304}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-299440}, year = {2022}, abstract = {Introduction Neurotransmitter release at presynaptic active zones (AZs) requires concerted protein interactions within a dense 3D nano-hemisphere. Among the complex protein meshwork the (M)unc-13 family member Unc-13 of Drosophila melanogaster is essential for docking of synaptic vesicles and transmitter release. Methods We employ minos-mediated integration cassette (MiMIC)-based gene editing using GFSTF (EGFP-FlAsH-StrepII-TEV-3xFlag) to endogenously tag all annotated Drosophila Unc-13 isoforms enabling visualization of endogenous Unc-13 expression within the central and peripheral nervous system. Results and discussion Electrophysiological characterization using two-electrode voltage clamp (TEVC) reveals that evoked and spontaneous synaptic transmission remain unaffected in unc-13\(^{GFSTF}\) 3rd instar larvae and acute presynaptic homeostatic potentiation (PHP) can be induced at control levels. Furthermore, multi-color structured-illumination shows precise co-localization of Unc-13\(^{GFSTF}\), Bruchpilot, and GluRIIA-receptor subunits within the synaptic mesoscale. Localization microscopy in combination with HDBSCAN algorithms detect Unc-13\(^{GFSTF}\) subclusters that move toward the AZ center during PHP with unaltered Unc-13\(^{GFSTF}\) protein levels.}, language = {en} } @article{LewerentzHoffmannSarmentoCabral2021, author = {Lewerentz, Anne and Hoffmann, Markus and Sarmento Cabral, Juliano}, title = {Depth diversity gradients of macrophytes: Shape, drivers, and recent shifts}, series = {Ecology and Evolution}, volume = {11}, journal = {Ecology and Evolution}, number = {20}, doi = {10.1002/ece3.8089}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-260280}, pages = {13830-13845}, year = {2021}, abstract = {Investigating diversity gradients helps to understand biodiversity drivers and threats. However, one diversity gradient is rarely assessed, namely how plant species distribute along the depth gradient of lakes. Here, we provide the first comprehensive characterization of depth diversity gradient (DDG) of alpha, beta, and gamma species richness of submerged macrophytes across multiple lakes. We characterize the DDG for additive richness components (alpha, beta, gamma), assess environmental drivers, and address temporal change over recent years. We take advantage of yet the largest dataset of macrophyte occurrence along lake depth (274 depth transects across 28 deep lakes) as well as of physiochemical measurements (12 deep lakes from 2006 to 2017 across Bavaria), provided publicly online by the Bavarian State Office for the Environment. We found a high variability in DDG shapes across the study lakes. The DDGs for alpha and gamma richness are predominantly hump-shaped, while beta richness shows a decreasing DDG. Generalized additive mixed-effect models indicate that the depth of the maximum richness (Dmax) is influenced by light quality, light quantity, and layering depth, whereas the respective maximum alpha richness within the depth gradient (Rmax) is significantly influenced by lake area only. Most observed DDGs seem generally stable over recent years. However, for single lakes we found significant linear trends for Rmax and Dmax going into different directions. The observed hump-shaped DDGs agree with three competing hypotheses: the mid-domain effect, the mean-disturbance hypothesis, and the mean-productivity hypothesis. The DDG amplitude seems driven by lake area (thus following known species-area relationships), whereas skewness depends on physiochemical factors, mainly water transparency and layering depth. Our results provide insights for conservation strategies and for mechanistic frameworks to disentangle competing explanatory hypotheses for the DDG.}, language = {en} } @article{KaltdorfSchulzeHelmprobstetal.2017, author = {Kaltdorf, Kristin Verena and Schulze, Katja and Helmprobst, Frederik and Kollmannsberger, Philip and Dandekar, Thomas and Stigloher, Christian}, title = {Fiji macro 3D ART VeSElecT: 3D automated reconstruction tool for vesicle structures of electron tomograms}, series = {PLoS Computational Biology}, volume = {13}, journal = {PLoS Computational Biology}, number = {1}, doi = {10.1371/journal.pcbi.1005317}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-172112}, year = {2017}, abstract = {Automatic image reconstruction is critical to cope with steadily increasing data from advanced microscopy. We describe here the Fiji macro 3D ART VeSElecT which we developed to study synaptic vesicles in electron tomograms. We apply this tool to quantify vesicle properties (i) in embryonic Danio rerio 4 and 8 days past fertilization (dpf) and (ii) to compare Caenorhabditis elegans N2 neuromuscular junctions (NMJ) wild-type and its septin mutant (unc-59(e261)). We demonstrate development-specific and mutant-specific changes in synaptic vesicle pools in both models. We confirm the functionality of our macro by applying our 3D ART VeSElecT on zebrafish NMJ showing smaller vesicles in 8 dpf embryos then 4 dpf, which was validated by manual reconstruction of the vesicle pool. Furthermore, we analyze the impact of C. elegans septin mutant unc-59(e261) on vesicle pool formation and vesicle size. Automated vesicle registration and characterization was implemented in Fiji as two macros (registration and measurement). This flexible arrangement allows in particular reducing false positives by an optional manual revision step. Preprocessing and contrast enhancement work on image-stacks of 1nm/pixel in x and y direction. Semi-automated cell selection was integrated. 3D ART VeSElecT removes interfering components, detects vesicles by 3D segmentation and calculates vesicle volume and diameter (spherical approximation, inner/outer diameter). Results are collected in color using the RoiManager plugin including the possibility of manual removal of non-matching confounder vesicles. Detailed evaluation considered performance (detected vesicles) and specificity (true vesicles) as well as precision and recall. We furthermore show gain in segmentation and morphological filtering compared to learning based methods and a large time gain compared to manual segmentation. 3D ART VeSElecT shows small error rates and its speed gain can be up to 68 times faster in comparison to manual annotation. Both automatic and semi-automatic modes are explained including a tutorial.}, language = {en} } @phdthesis{Anwar2022, author = {Anwar, Ammarah}, title = {Natural variation of gene regulatory networks in \(Arabidopsis\) \(thaliana\)}, doi = {10.25972/OPUS-29154}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-291549}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2022}, abstract = {Understanding the causal relationship between genotype and phenotype is a major objective in biology. The main interest is in understanding trait architecture and identifying loci contributing to the respective traits. Genome-wide association mapping (GWAS) is one tool to elucidate these relationships and has been successfully used in many different species. However, most studies concentrate on marginal marker effects and ignore epistatic and gene-environment interactions. These interactions are problematic to account for, but are likely to make major contributions to many phenotypes that are not regulated by independent genetic effects, but by more sophisticated gene-regulatory networks. Further complication arises from the fact that these networks vary in different natural accessions. However, understanding the differences of gene regulatory networks and gene-gene interactions is crucial to conceive trait architecture and predict phenotypes. The basic subject of this study - using data from the Arabidopsis 1001 Genomes Project - is the analysis of pre-mature stop codons. These have been incurred in nearly one-third of the ~ 30k genes. A gene-gene interaction network of the co-occurrence of stop codons has been built and the over and under representation of different pairs has been statistically analyzed. To further classify the significant over and under- represented gene-gene interactions in terms of molecular function of the encoded proteins, gene ontology terms (GO-SLIM) have been applied. Furthermore, co- expression analysis specifies gene clusters that co-occur over different genetic and phenotypic backgrounds. To link these patterns to evolutionary constrains, spatial location of the respective alleles have been analyzed as well. The latter shows clear patterns for certain gene pairs that indicate differential selection.}, subject = {Arabidopsis thaliana}, language = {en} } @article{PookFreudenthalKorteetal.2020, author = {Pook, Torsten and Freudenthal, Jan and Korte, Arthur and Simianer, Henner}, title = {Using Local Convolutional Neural Networks for Genomic Prediction}, series = {Frontiers in Genetics}, volume = {11}, journal = {Frontiers in Genetics}, doi = {10.3389/fgene.2020.561497}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-216436}, year = {2020}, abstract = {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.}, language = {en} } @article{BerberichKurzReinhardetal.2021, author = {Berberich, Andreas and Kurz, Andreas and Reinhard, Sebastian and Paul, Torsten Johann and Burd, Paul Ray and Sauer, Markus and Kollmannsberger, Philip}, title = {Fourier Ring Correlation and anisotropic kernel density estimation improve deep learning based SMLM reconstruction of microtubules}, series = {Frontiers in Bioinformatics}, volume = {1}, journal = {Frontiers in Bioinformatics}, doi = {10.3389/fbinf.2021.752788}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-261686}, year = {2021}, abstract = {Single-molecule super-resolution microscopy (SMLM) techniques like dSTORM can reveal biological structures down to the nanometer scale. The achievable resolution is not only defined by the localization precision of individual fluorescent molecules, but also by their density, which becomes a limiting factor e.g., in expansion microscopy. Artificial deep neural networks can learn to reconstruct dense super-resolved structures such as microtubules from a sparse, noisy set of data points. This approach requires a robust method to assess the quality of a predicted density image and to quantitatively compare it to a ground truth image. Such a quality measure needs to be differentiable to be applied as loss function in deep learning. We developed a new trainable quality measure based on Fourier Ring Correlation (FRC) and used it to train deep neural networks to map a small number of sampling points to an underlying density. Smooth ground truth images of microtubules were generated from localization coordinates using an anisotropic Gaussian kernel density estimator. We show that the FRC criterion ideally complements the existing state-of-the-art multiscale structural similarity index, since both are interpretable and there is no trade-off between them during optimization. The TensorFlow implementation of our FRC metric can easily be integrated into existing deep learning workflows.}, language = {en} } @article{VedderLeidingerSarmentoCabral2021, author = {Vedder, Daniel and Leidinger, Ludwig and Sarmento Cabral, Juliano}, title = {Propagule pressure and an invasion syndrome determine invasion success in a plant community model}, series = {Ecology and Evolution}, volume = {11}, journal = {Ecology and Evolution}, number = {23}, doi = {10.1002/ece3.8348}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-259107}, pages = {17106-17116}, year = {2021}, abstract = {The success of species invasions depends on multiple factors, including propagule pressure, disturbance, productivity, and the traits of native and non-native species. While the importance of many of these determinants has already been investigated in relative isolation, they are rarely studied in combination. Here, we address this shortcoming by exploring the effect of the above-listed factors on the success of invasions using an individual-based mechanistic model. This approach enables us to explicitly control environmental factors (temperature as surrogate for productivity, disturbance, and propagule pressure) as well as to monitor whole-community trait distributions of environmental adaptation, mass, and dispersal abilities. We simulated introductions of plant individuals to an oceanic island to assess which factors and species traits contribute to invasion success. We found that the most influential factors were higher propagule pressure and a particular set of traits. This invasion trait syndrome was characterized by a relative similarity in functional traits of invasive to native species, while invasive species had on average higher environmental adaptation, higher body mass, and increased dispersal distances, that is, had greater competitive and dispersive abilities. Our results highlight the importance in management practice of reducing the import of alien species, especially those that display this trait syndrome and come from similar habitats as those being managed.}, language = {en} } @phdthesis{Fuellsack2019, author = {F{\"u}llsack, Simone Alexandra}, title = {Die Bedeutung von Todesdom{\"a}ne Adapterproteinen f{\"u}r die Signaltransduktion des TNFR1 und der TRAIL Todesrezeptoren}, doi = {10.25972/OPUS-18451}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-184518}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2019}, abstract = {Die NFκB-Signalwege, Apoptose und Nekroptose sind essentielle Prozesse in der Immunantwort. Außerdem sind diese Signalwege Teil der Regulation von Zelldifferenzierung, -proliferation, -tod und Entz{\"u}ndungsreaktionen. Dabei wird zuerst der Rezeptor (TNFR1 oder TRAILR 1/2) aktiviert, die rekrutierten DD-Adapterproteine TRADD, FADD und RIPK1 leiten dann die entsprechende Signalkaskade weiter und bestimmen durch ihre Zusammenwirkung, ob der NFκB-Signalweg, Apoptose oder Nekroptose induziert wird. TNFR1 und TRAILR 1/2 ben{\"o}tigen die DD-Adapterproteine TRADD, FADD und RIPK1 f{\"u}r die Zelltodinduktion, deren konkrete Bedeutung in Bezug auf Rezeptor-Spezifit{\"a}t, Zusammenwirken und Relevanz allerdings noch unklar ist. Um das Zusammenspiel dieser Proteine besser zu verstehen, wurden in dieser Arbeit Nekroptose-kompetente RIPK3-exprimierende HeLa-Zellen verwendet, bei denen die DD-Adapterproteine FADD, TRADD und RIPK1 einzeln oder in Kombination von zweien ausgeknockt wurden. Es stellte sich heraus, dass RIPK1 essentiell f{\"u}r die TNFR1- und TRAILR 1/2-vermittelte Nekroptose-Induktion ist, doch RIPK1 alleine, d.h. ohne FADD- oder TRADD-Mitbeteiligung, nur bei der TNFR1-Nekroptose-Induktion ausreicht. Wiederum inhibiert TRADD die TNFR1- und TRAILR 1/2-induzierte Nekroptose. RIPK1 und TRADD sind aber unverzichtbar f{\"u}r die NFκB-Aktivierung durch TNFR1 oder TRAILR 1/2 und spielen eine wichtige Rolle bei TNFR1-induzierter Apoptose. Andererseits ist FADD alleine ausreichend f{\"u}r die TRAILR 1/2-bezogene Caspase-8 Aktivierung. Zudem ist FADD notwendig f{\"u}r die TRAIL-induzierte NFκB-Signalaktivierung. In Abwesenheit von FADD und TRADD vermittelt RIPK1 die TNF-induzierte Caspase-8 Aktivierung. FADD wird f{\"u}r die TRAIL-induzierte Nekroptose ben{\"o}tigt, aber gegenl{\"a}ufig wirkt die TNF-induzierte Nektroptose in einer Caspase-8 abh{\"a}ngigen und unabh{\"a}ngigen Weise. Zudem sensitiviert TWEAK die TNF- und TRAIL-induzierte Nekroptose. Zusammenfassend wurde in dieser Arbeit die Auswirkung von TNFR1 und TRAILR 1/2 auf die Aktivierung der unterschiedlichen Signalkaskaden untersucht. Des Weiteren wurde gezeigt, in welcher Weise sich das Zusammenspiel von TRADD, FADD und RIPK1 auf die Induktion von NFκB, Apoptose und Nekroptose auswirkt.}, subject = {Signaltransduktion}, language = {de} } @article{MrestaniPauliKollmannsbergeretal.2021, author = {Mrestani, Achmed and Pauli, Martin and Kollmannsberger, Philip and Repp, Felix and Kittel, Robert J. and Eilers, Jens and Doose, S{\"o}ren and Sauer, Markus and Sir{\´e}n, Anna-Leena and Heckmann, Manfred and Paul, Mila M.}, title = {Active zone compaction correlates with presynaptic homeostatic potentiation}, series = {Cell Reports}, volume = {37}, journal = {Cell Reports}, number = {1}, doi = {10.1016/j.celrep.2021.109770}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-265497}, pages = {109770}, year = {2021}, abstract = {Neurotransmitter release is stabilized by homeostatic plasticity. Presynaptic homeostatic potentiation (PHP) operates on timescales ranging from minute- to life-long adaptations and likely involves reorganization of presynaptic active zones (AZs). At Drosophila melanogaster neuromuscular junctions, earlier work ascribed AZ enlargement by incorporating more Bruchpilot (Brp) scaffold protein a role in PHP. We use localization microscopy (direct stochastic optical reconstruction microscopy [dSTORM]) and hierarchical density-based spatial clustering of applications with noise (HDBSCAN) to study AZ plasticity during PHP at the synaptic mesoscale. We find compaction of individual AZs in acute philanthotoxin-induced and chronic genetically induced PHP but unchanged copy numbers of AZ proteins. Compaction even occurs at the level of Brp subclusters, which move toward AZ centers, and in Rab3 interacting molecule (RIM)-binding protein (RBP) subclusters. Furthermore, correlative confocal and dSTORM imaging reveals how AZ compaction in PHP translates into apparent increases in AZ area and Brp protein content, as implied earlier.}, language = {en} } @article{NaglerNaegeleGillietal.2018, author = {Nagler, Matthias and N{\"a}gele, Thomas and Gilli, Christian and Fragner, Lena and Korte, Arthur and Platzer, Alexander and Farlow, Ashley and Nordborg, Magnus and Weckwerth, Wolfram}, title = {Eco-Metabolomics and Metabolic Modeling: Making the Leap From Model Systems in the Lab to Native Populations in the Field}, series = {Frontiers in Plant Science}, volume = {9}, journal = {Frontiers in Plant Science}, number = {1556}, issn = {1664-462X}, doi = {10.3389/fpls.2018.01556}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-189560}, year = {2018}, abstract = {Experimental high-throughput analysis of molecular networks is a central approach to characterize the adaptation of plant metabolism to the environment. However, recent studies have demonstrated that it is hardly possible to predict in situ metabolic phenotypes from experiments under controlled conditions, such as growth chambers or greenhouses. This is particularly due to the high molecular variance of in situ samples induced by environmental fluctuations. An approach of functional metabolome interpretation of field samples would be desirable in order to be able to identify and trace back the impact of environmental changes on plant metabolism. To test the applicability of metabolomics studies for a characterization of plant populations in the field, we have identified and analyzed in situ samples of nearby grown natural populations of Arabidopsis thaliana in Austria. A. thaliana is the primary molecular biological model system in plant biology with one of the best functionally annotated genomes representing a reference system for all other plant genome projects. The genomes of these novel natural populations were sequenced and phylogenetically compared to a comprehensive genome database of A. thaliana ecotypes. Experimental results on primary and secondary metabolite profiling and genotypic variation were functionally integrated by a data mining strategy, which combines statistical output of metabolomics data with genome-derived biochemical pathway reconstruction and metabolic modeling. Correlations of biochemical model predictions and population-specific genetic variation indicated varying strategies of metabolic regulation on a population level which enabled the direct comparison, differentiation, and prediction of metabolic adaptation of the same species to different habitats. These differences were most pronounced at organic and amino acid metabolism as well as at the interface of primary and secondary metabolism and allowed for the direct classification of population-specific metabolic phenotypes within geographically contiguous sampling sites.}, language = {en} } @article{GuptaOsmanogluMinochaetal.2022, author = {Gupta, Shishir K. and Osmanoglu, {\"O}zge and Minocha, Rashmi and Bandi, Sourish Reddy and Bencurova, Elena and Srivastava, Mugdha and Dandekar, Thomas}, title = {Genome-wide scan for potential CD4+ T-cell vaccine candidates in Candida auris by exploiting reverse vaccinology and evolutionary information}, series = {Frontiers in Medicine}, volume = {9}, journal = {Frontiers in Medicine}, issn = {2296-858X}, doi = {10.3389/fmed.2022.1008527}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-293953}, year = {2022}, abstract = {Candida auris is a globally emerging fungal pathogen responsible for causing nosocomial outbreaks in healthcare associated settings. It is known to cause infection in all age groups and exhibits multi-drug resistance with high potential for horizontal transmission. Because of this reason combined with limited therapeutic choices available, C. auris infection has been acknowledged as a potential risk for causing a future pandemic, and thus seeking a promising strategy for its treatment is imperative. Here, we combined evolutionary information with reverse vaccinology approach to identify novel epitopes for vaccine design that could elicit CD4+ T-cell responses against C. auris. To this end, we extensively scanned the family of proteins encoded by C. auris genome. In addition, a pathogen may acquire substitutions in epitopes over a period of time which could cause its escape from the immune response thus rendering the vaccine ineffective. To lower this possibility in our design, we eliminated all rapidly evolving genes of C. auris with positive selection. We further employed highly conserved regions of multiple C. auris strains and identified two immunogenic and antigenic T-cell epitopes that could generate the most effective immune response against C. auris. The antigenicity scores of our predicted vaccine candidates were calculated as 0.85 and 1.88 where 0.5 is the threshold for prediction of fungal antigenic sequences. Based on our results, we conclude that our vaccine candidates have the potential to be successfully employed for the treatment of C. auris infection. However, in vivo experiments are imperative to further demonstrate the efficacy of our design.}, language = {en} } @article{LopezArboledaReinertNordborgetal.2021, author = {Lopez-Arboleda, William Andres and Reinert, Stephan and Nordborg, Magnus and Korte, Arthur}, title = {Global genetic heterogeneity in adaptive traits}, series = {Molecular Biology and Evolution}, volume = {38}, journal = {Molecular Biology and Evolution}, number = {11}, doi = {10.1093/molbev/msab208}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-270410}, pages = {4822-4831}, year = {2021}, abstract = {Understanding the genetic architecture of complex traits is a major objective in biology. The standard approach for doing so is genome-wide association studies (GWAS), which aim to identify genetic polymorphisms responsible for variation in traits of interest. In human genetics, consistency across studies is commonly used as an indicator of reliability. However, if traits are involved in adaptation to the local environment, we do not necessarily expect reproducibility. On the contrary, results may depend on where you sample, and sampling across a wide range of environments may decrease the power of GWAS because of increased genetic heterogeneity. In this study, we examine how sampling affects GWAS in the model plant species Arabidopsis thaliana. We show that traits like flowering time are indeed influenced by distinct genetic effects in local populations. Furthermore, using gene expression as a molecular phenotype, we show that some genes are globally affected by shared variants, whereas others are affected by variants specific to subpopulations. Remarkably, the former are essentially all cis-regulated, whereas the latter are predominately affected by trans-acting variants. Our result illustrate that conclusions about genetic architecture can be extremely sensitive to sampling and population structure.}, language = {en} } @phdthesis{Lewerentz2022, author = {Lewerentz, Anne F.}, title = {Spatiotemporal dynamics of freshwater macrophytes in Bavarian lakes under environmental change}, doi = {10.25972/OPUS-28770}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-287700}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2022}, abstract = {Macrophytes are key components of freshwater ecosystems because they provide habitat, food, and improve the water quality. Macrophyte are vulnerable to environmental change as their physiological processes depend on changing environmental factors, which themselves vary within a geographical region and along lake depth. Their spatial distribution is not well understood and their importance is publicly little-known. In this thesis, I have investigated the spatiotemporal dynamics of freshwater macrophytes in Bavarian lakes to understand their diversity pattern along different scales and to predict and communicate potential consequences of global change on their richness. In the introduction (Chapter 1), I provide an overview of the current scientific knowledge of the species richness patterns of macrophytes in freshwater lakes, the influences of climate and land-use change on macrophyte growth, and different modelling approaches of macrophytes. The main part of the thesis starts with a study about submerged and emergent macrophyte species richness in natural and artificial lakes of Bavaria (Chapter 2). By analysing publicly available monitoring data, I have found a higher species richness of submerged macrophytes in natural lakes than in artificial lakes. Furthermore, I showed that the richness of submerged species is better explained by physio-chemical lake parameters than the richness of emergent species. In Chapter 3, I considered that submerged macrophytes grow along a depth gradient that provides a sharp environmental gradient on a short spatial scale. This study is the first comparative assessment of the depth diversity gradient (DDG) of macrophytes. I have found a hump-shaped pattern of different diversity components. Generalised additive mixed-effect models indicate that the shape of the DDG is influenced mainly by light quality, light quantity, layering depth, and lake area. I could not identify a general trend of the DDG within recent years, but single lakes show trends leading into different directions. In Chapter 4, I used a mechanistic eco-physiological model to explore changes in the distribution of macrophyte species richness under different scenarios of environmental conditions across lakes and with depths. I could replicate the hump-shaped pattern of potential species richness along depth. Rising temperature leads to increased species richness in all lake types, and depths. The effect of turbidity and nutrient change depends on depth and lake type. Traits that characterise "loser species" under increased turbidity and nutrients are a high light consumption and a high sensibility to disturbances. "Winner species" can be identified by a high biomass production. In Chapter 5, I discuss the image problem of macrophytes. Unawareness, ignorance, and the poor accessibility of macrophytes can lead to conflicts of use. I assumed that an increased engagement and education could counteract this. Because computer games can transfer knowledge interactively while creating an immersive experience, I present in the chapter an interactive single-player game for children. Finally, I discuss the findings of this thesis in the light of their implications for ecological theory, their implications for conservation, and future research ideas (Chapter 6). The findings help to understand the regional distribution and the drivers of macrophyte species richness. By applying eco-physiological models, multiple environmental shaping factors for species richness were tested and scenarios of climate and land-use change were explored.}, subject = {{\"O}kologie}, language = {en} } @article{SahlolKollmannsbergerEwees2020, author = {Sahlol, Ahmed T. and Kollmannsberger, Philip and Ewees, Ahmed A.}, title = {Efficient Classification of White Blood Cell Leukemia with Improved Swarm Optimization of Deep Features}, series = {Scientific Reports}, volume = {10}, journal = {Scientific Reports}, number = {1}, doi = {10.1038/s41598-020-59215-9}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-229398}, year = {2020}, abstract = {White Blood Cell (WBC) Leukaemia is caused by excessive production of leukocytes in the bone marrow, and image-based detection of malignant WBCs is important for its detection. Convolutional Neural Networks (CNNs) present the current state-of-the-art for this type of image classification, but their computational cost for training and deployment can be high. We here present an improved hybrid approach for efficient classification of WBC Leukemia. We first extract features from WBC images using VGGNet, a powerful CNN architecture, pre-trained on ImageNet. The extracted features are then filtered using a statistically enhanced Salp Swarm Algorithm (SESSA). This bio-inspired optimization algorithm selects the most relevant features and removes highly correlated and noisy features. We applied the proposed approach to two public WBC Leukemia reference datasets and achieve both high accuracy and reduced computational complexity. The SESSA optimization selected only 1 K out of 25 K features extracted with VGGNet, while improving accuracy at the same time. The results are among the best achieved on these datasets and outperform several convolutional network models. We expect that the combination of CNN feature extraction and SESSA feature optimization could be useful for many other image classification tasks.}, language = {en} } @article{MarquardtSolimandoKerscheretal.2021, author = {Marquardt, Andr{\´e} and Solimando, Antonio Giovanni and Kerscher, Alexander and Bittrich, Max and Kalogirou, Charis and K{\"u}bler, Hubert and Rosenwald, Andreas and Bargou, Ralf and Kollmannsberger, Philip and Schilling, Bastian and Meierjohann, Svenja and Krebs, Markus}, title = {Subgroup-Independent Mapping of Renal Cell Carcinoma — Machine Learning Reveals Prognostic Mitochondrial Gene Signature Beyond Histopathologic Boundaries}, series = {Frontiers in Oncology}, volume = {11}, journal = {Frontiers in Oncology}, issn = {2234-943X}, doi = {10.3389/fonc.2021.621278}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-232107}, year = {2021}, abstract = {Background: Renal cell carcinoma (RCC) is divided into three major histopathologic groups—clear cell (ccRCC), papillary (pRCC) and chromophobe RCC (chRCC). We performed a comprehensive re-analysis of publicly available RCC datasets from the TCGA (The Cancer Genome Atlas) database, thereby combining samples from all three subgroups, for an exploratory transcriptome profiling of RCC subgroups. Materials and Methods: We used FPKM (fragments per kilobase per million) files derived from the ccRCC, pRCC and chRCC cohorts of the TCGA database, representing transcriptomic data of 891 patients. Using principal component analysis, we visualized datasets as t-SNE plot for cluster detection. Clusters were characterized by machine learning, resulting gene signatures were validated by correlation analyses in the TCGA dataset and three external datasets (ICGC RECA-EU, CPTAC-3-Kidney, and GSE157256). Results: Many RCC samples co-clustered according to histopathology. However, a substantial number of samples clustered independently from histopathologic origin (mixed subgroup)—demonstrating divergence between histopathology and transcriptomic data. Further analyses of mixed subgroup via machine learning revealed a predominant mitochondrial gene signature—a trait previously known for chRCC—across all histopathologic subgroups. Additionally, ccRCC samples from mixed subgroup presented an inverse correlation of mitochondrial and angiogenesis-related genes in the TCGA and in three external validation cohorts. Moreover, mixed subgroup affiliation was associated with a highly significant shorter overall survival for patients with ccRCC—and a highly significant longer overall survival for chRCC patients. Conclusions: Pan-RCC clustering according to RNA-sequencing data revealed a distinct histology-independent subgroup characterized by strengthened mitochondrial and weakened angiogenesis-related gene signatures. Moreover, affiliation to mixed subgroup went along with a significantly shorter overall survival for ccRCC and a longer overall survival for chRCC patients. Further research could offer a therapy stratification by specifically addressing the mitochondrial metabolism of such tumors and its microenvironment.}, language = {en} } @article{MarquardtLandwehrRonchietal.2021, author = {Marquardt, Andr{\´e} and Landwehr, Laura-Sophie and Ronchi, Cristina L. and di Dalmazi, Guido and Riester, Anna and Kollmannsberger, Philip and Altieri, Barbara and Fassnacht, Martin and Sbiera, Silviu}, title = {Identifying New Potential Biomarkers in Adrenocortical Tumors Based on mRNA Expression Data Using Machine Learning}, series = {Cancers}, volume = {13}, journal = {Cancers}, number = {18}, issn = {2072-6694}, doi = {10.3390/cancers13184671}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-246245}, year = {2021}, abstract = {Simple Summary Using a visual-based clustering method on the TCGA RNA sequencing data of a large adrenocortical carcinoma (ACC) cohort, we were able to classify these tumors in two distinct clusters largely overlapping with previously identified ones. As previously shown, the identified clusters also correlated with patient survival. Applying the visual clustering method to a second dataset also including benign adrenocortical samples additionally revealed that one of the ACC clusters is more closely located to the benign samples, providing a possible explanation for the better survival of this ACC cluster. Furthermore, the subsequent use of machine learning identified new possible biomarker genes with prognostic potential for this rare disease, that are significantly differentially expressed in the different survival clusters and should be further evaluated. Abstract Adrenocortical carcinoma (ACC) is a rare disease, associated with poor survival. Several "multiple-omics" studies characterizing ACC on a molecular level identified two different clusters correlating with patient survival (C1A and C1B). We here used the publicly available transcriptome data from the TCGA-ACC dataset (n = 79), applying machine learning (ML) methods to classify the ACC based on expression pattern in an unbiased manner. UMAP (uniform manifold approximation and projection)-based clustering resulted in two distinct groups, ACC-UMAP1 and ACC-UMAP2, that largely overlap with clusters C1B and C1A, respectively. However, subsequent use of random-forest-based learning revealed a set of new possible marker genes showing significant differential expression in the described clusters (e.g., SOAT1, EIF2A1). For validation purposes, we used a secondary dataset based on a previous study from our group, consisting of 4 normal adrenal glands and 52 benign and 7 malignant tumor samples. The results largely confirmed those obtained for the TCGA-ACC cohort. In addition, the ENSAT dataset showed a correlation between benign adrenocortical tumors and the good prognosis ACC cluster ACC-UMAP1/C1B. In conclusion, the use of ML approaches re-identified and redefined known prognostic ACC subgroups. On the other hand, the subsequent use of random-forest-based learning identified new possible prognostic marker genes for ACC.}, language = {en} } @article{PetersKellerLeonhardt2022, author = {Peters, Birte and Keller, Alexander and Leonhardt, Sara Diana}, title = {Diets maintained in a changing world: Does land-use intensification alter wild bee communities by selecting for flexible generalists?}, series = {Ecology and evolution}, volume = {12}, journal = {Ecology and evolution}, number = {5}, issn = {2045-7758}, doi = {10.1002/ece3.8919}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-312786}, year = {2022}, abstract = {Biodiversity loss, as often found in intensively managed agricultural landscapes, correlates with reduced ecosystem functioning, for example, pollination by insects, and with altered plant composition, diversity, and abundance. But how does this change in floral resource diversity and composition relate to occurrence and resource use patterns of trap-nesting solitary bees? To better understand the impact of land-use intensification on communities of trap-nesting solitary bees in managed grasslands, we investigated their pollen foraging, reproductive fitness, and the nutritional quality of larval food along a land-use intensity gradient in Germany. We found bee species diversity to decrease with increasing land-use intensity irrespective of region-specific community compositions and interaction networks. Land use also strongly affected the diversity and composition of pollen collected by bees. Lack of suitable pollen sources likely explains the absence of several bee species at sites of high land-use intensity. The only species present throughout, Osmia bicornis (red mason bee), foraged on largely different pollen sources across sites. In doing so, it maintained a relatively stable, albeit variable nutritional quality of larval diets (i.e., protein to lipid (P:L) ratio). The observed changes in bee-plant pollen interaction patterns indicate that only the flexible generalists, such as O. bicornis, may be able to compensate the strong alterations in floral resource landscapes and to obtain food of sufficient quality through readily shifting to alternative plant sources. In contrast, other, less flexible, bee species disappear.}, language = {en} } @article{BergerDemolombeHemetal.2022, author = {Berger, Nathalie and Demolombe, Vincent and Hem, Sonia and Rofidal, Val{\´e}rie and Steinmann, Laura and Krouk, Gabriel and Crabos, Amandine and Nacry, Philippe and Verdoucq, Lionel and Santoni, V{\´e}ronique}, title = {Root membrane ubiquitinome under short-term osmotic stress}, series = {International Journal of Molecular Sciences}, volume = {23}, journal = {International Journal of Molecular Sciences}, number = {4}, issn = {1422-0067}, doi = {10.3390/ijms23041956}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-284003}, year = {2022}, abstract = {Osmotic stress can be detrimental to plants, whose survival relies heavily on proteomic plasticity. Protein ubiquitination is a central post-translational modification in osmotic-mediated stress. In this study, we used the K-Ɛ-GG antibody enrichment method integrated with high-resolution mass spectrometry to compile a list of 719 ubiquitinated lysine (K-Ub) residues from 450 Arabidopsis root membrane proteins (58\% of which are transmembrane proteins), thereby adding to the database of ubiquitinated substrates in plants. Although no ubiquitin (Ub) motifs could be identified, the presence of acidic residues close to K-Ub was revealed. Our ubiquitinome analysis pointed to a broad role of ubiquitination in the internalization and sorting of cargo proteins. Moreover, the simultaneous proteome and ubiquitinome quantification showed that ubiquitination is mostly not involved in membrane protein degradation in response to short osmotic treatment but that it is putatively involved in protein internalization, as described for the aquaporin PIP2;1. Our in silico analysis of ubiquitinated proteins shows that two E2 Ub-conjugating enzymes, UBC32 and UBC34, putatively target membrane proteins under osmotic stress. Finally, we revealed a positive role for UBC32 and UBC34 in primary root growth under osmotic stress.}, language = {en} } @article{VedderLensMartinetal.2022, author = {Vedder, Daniel and Lens, Luc and Martin, Claudia A. and Pellikka, Petri and Adhikari, Hari and Heiskanen, Janne and Engler, Jan O. and Sarmento Cabral, Juliano}, title = {Hybridization may aid evolutionary rescue of an endangered East African passerine}, series = {Evolutionary Applications}, volume = {15}, journal = {Evolutionary Applications}, number = {7}, doi = {10.1111/eva.13440}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-287264}, pages = {1177-1188}, year = {2022}, abstract = {Abstract Introgressive hybridization is a process that enables gene flow across species barriers through the backcrossing of hybrids into a parent population. This may make genetic material, potentially including relevant environmental adaptations, rapidly available in a gene pool. Consequently, it has been postulated to be an important mechanism for enabling evolutionary rescue, that is the recovery of threatened populations through rapid evolutionary adaptation to novel environments. However, predicting the likelihood of such evolutionary rescue for individual species remains challenging. Here, we use the example of Zosterops silvanus, an endangered East African highland bird species suffering from severe habitat loss and fragmentation, to investigate whether hybridization with its congener Zosterops flavilateralis might enable evolutionary rescue of its Taita Hills population. To do so, we employ an empirically parameterized individual-based model to simulate the species' behaviour, physiology and genetics. We test the population's response to different assumptions of mating behaviour and multiple scenarios of habitat change. We show that as long as hybridization does take place, evolutionary rescue of Z. silvanus is likely. Intermediate hybridization rates enable the greatest long-term population growth, due to trade-offs between adaptive and maladaptive introgressed alleles. Habitat change did not have a strong effect on population growth rates, as Z. silvanus is a strong disperser and landscape configuration is therefore not the limiting factor for hybridization. Our results show that targeted gene flow may be a promising avenue to help accelerate the adaptation of endangered species to novel environments, and demonstrate how to combine empirical research and mechanistic modelling to deliver species-specific predictions for conservation planning.}, language = {en} } @article{MarquardtKollmannsbergerKrebsetal.2022, author = {Marquardt, Andr{\´e} and Kollmannsberger, Philip and Krebs, Markus and Argentiero, Antonella and Knott, Markus and Solimando, Antonio Giovanni and Kerscher, Alexander Georg}, title = {Visual clustering of transcriptomic data from primary and metastatic tumors — dependencies and novel pitfalls}, series = {Genes}, volume = {13}, journal = {Genes}, number = {8}, issn = {2073-4425}, doi = {10.3390/genes13081335}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-281872}, year = {2022}, abstract = {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.}, language = {en} } @article{ImhoffRahnKuenzeletal.2020, author = {Imhoff, Johannes F. and Rahn, Tanja and K{\"u}nzel, Sven and Keller, Alexander and Neulinger, Sven C.}, title = {Osmotic adaptation and compatible solute biosynthesis of phototrophic bacteria as revealed from genome analyses}, series = {Microorganisms}, volume = {9}, journal = {Microorganisms}, number = {1}, issn = {2076-2607}, doi = {10.3390/microorganisms9010046}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-220161}, year = {2020}, abstract = {Osmotic adaptation and accumulation of compatible solutes is a key process for life at high osmotic pressure and elevated salt concentrations. Most important solutes that can protect cell structures and metabolic processes at high salt concentrations are glycine betaine and ectoine. The genome analysis of more than 130 phototrophic bacteria shows that biosynthesis of glycine betaine is common among marine and halophilic phototrophic Proteobacteria and their chemotrophic relatives, as well as in representatives of Pirellulaceae and Actinobacteria, but are also found in halophilic Cyanobacteria and Chloroherpeton thalassium. This ability correlates well with the successful toleration of extreme salt concentrations. Freshwater bacteria in general lack the possibilities to synthesize and often also to take up these compounds. The biosynthesis of ectoine is found in the phylogenetic lines of phototrophic Alpha- and Gammaproteobacteria, most prominent in the Halorhodospira species and a number of Rhodobacteraceae. It is also common among Streptomycetes and Bacilli. The phylogeny of glycine-sarcosine methyltransferase (GMT) and diaminobutyrate-pyruvate aminotransferase (EctB) sequences correlate well with otherwise established phylogenetic groups. Most significantly, GMT sequences of cyanobacteria form two major phylogenetic branches and the branch of Halorhodospira species is distinct from all other Ectothiorhodospiraceae. A variety of transport systems for osmolytes are present in the studied bacteria.}, language = {en} } @article{BritzMarkertWitvlietetal.2021, author = {Britz, Sebastian and Markert, Sebastian Matthias and Witvliet, Daniel and Steyer, Anna Maria and Tr{\"o}ger, Sarah and Mulcahy, Ben and Kollmannsberger, Philip and Schwab, Yannick and Zhen, Mei and Stigloher, Christian}, title = {Structural Analysis of the Caenorhabditis elegans Dauer Larval Anterior Sensilla by Focused Ion Beam-Scanning Electron Microscopy}, series = {Frontiers in Neuroanatomy}, volume = {15}, journal = {Frontiers in Neuroanatomy}, issn = {1662-5129}, doi = {10.3389/fnana.2021.732520}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-249622}, year = {2021}, abstract = {At the end of the first larval stage, the nematode Caenorhabditis elegans developing in harsh environmental conditions is able to choose an alternative developmental path called the dauer diapause. Dauer larvae exhibit different physiology and behaviors from non-dauer larvae. Using focused ion beam-scanning electron microscopy (FIB-SEM), we volumetrically reconstructed the anterior sensory apparatus of C. elegans dauer larvae with unprecedented precision. We provide a detailed description of some neurons, focusing on structural details that were unknown or unresolved by previously published studies. They include the following: (1) dauer-specific branches of the IL2 sensory neurons project into the periphery of anterior sensilla and motor or putative sensory neurons at the sub-lateral cords; (2) ciliated endings of URX sensory neurons are supported by both ILso and AMso socket cells near the amphid openings; (3) variability in amphid sensory dendrites among dauers; and (4) somatic RIP interneurons maintain their projection into the pharyngeal nervous system. Our results support the notion that dauer larvae structurally expand their sensory system to facilitate searching for more favorable environments.}, language = {en} } @article{PauliPaulProppertetal.2021, author = {Pauli, Martin and Paul, Mila M. and Proppert, Sven and Mrestani, Achmed and Sharifi, Marzieh and Repp, Felix and K{\"u}rzinger, Lydia and Kollmannsberger, Philip and Sauer, Markus and Heckmann, Manfred and Sir{\´e}n, Anna-Leena}, title = {Targeted volumetric single-molecule localization microscopy of defined presynaptic structures in brain sections}, series = {Communications Biology}, volume = {4}, journal = {Communications Biology}, doi = {10.1038/s42003-021-01939-z}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-259830}, pages = {407}, year = {2021}, abstract = {Revealing the molecular organization of anatomically precisely defined brain regions is necessary for refined understanding of synaptic plasticity. Although three-dimensional (3D) single-molecule localization microscopy can provide the required resolution, imaging more than a few micrometers deep into tissue remains challenging. To quantify presynaptic active zones (AZ) of entire, large, conditional detonator hippocampal mossy fiber (MF) boutons with diameters as large as 10 mu m, we developed a method for targeted volumetric direct stochastic optical reconstruction microscopy (dSTORM). An optimized protocol for fast repeated axial scanning and efficient sequential labeling of the AZ scaffold Bassoon and membrane bound GFP with Alexa Fluor 647 enabled 3D-dSTORM imaging of 25 mu m thick mouse brain sections and assignment of AZs to specific neuronal substructures. Quantitative data analysis revealed large differences in Bassoon cluster size and density for distinct hippocampal regions with largest clusters in MF boutons. Pauli et al. develop targeted volumetric dSTORM in order to image large hippocampal mossy fiber boutons (MFBs) in brain slices. They can identify synaptic targets of individual MFBs and measured size and density of Bassoon clusters within individual untruncated MFBs at nanoscopic resolution.}, language = {en} } @article{VedderAnkenbrandSarmentoCabral2021, author = {Vedder, Daniel and Ankenbrand, Markus and Sarmento Cabral, Juliano}, title = {Dealing with software complexity in individual-based models}, series = {Methods in Ecology and Evolution}, volume = {12}, journal = {Methods in Ecology and Evolution}, number = {12}, doi = {10.1111/2041-210X.13716}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-258214}, pages = {2324-2333}, year = {2021}, abstract = {Individual-based models are doubly complex: as well as representing complex ecological systems, the software that implements them is complex in itself. Both forms of complexity must be managed to create reliable models. However, the ecological modelling literature to date has focussed almost exclusively on the biological complexity. Here, we discuss methods for containing software complexity. Strategies for containing complexity include avoiding, subdividing, documenting and reviewing it. Computer science has long-established techniques for all of these strategies. We present some of these techniques and set them in the context of IBM development, giving examples from published models. Techniques for avoiding software complexity are following best practices for coding style, choosing suitable programming languages and file formats and setting up an automated workflow. Complex software systems can be made more tractable by encapsulating individual subsystems. Good documentation needs to take into account the perspectives of scientists, users and developers. Code reviews are an effective way to check for errors, and can be used together with manual or automated unit and integration tests. Ecological modellers can learn from computer scientists how to deal with complex software systems. Many techniques are readily available, but must be disseminated among modellers. There is a need for further work to adapt software development techniques to the requirements of academic research groups and individual-based modelling.}, language = {en} } @article{TrinklKaluzaWallaceetal.2020, author = {Trinkl, Moritz and Kaluza, Benjamin F. and Wallace, Helen and Heard, Tim A. and Keller, Alexander and Leonhardt, Sara D.}, title = {Floral Species Richness Correlates with Changes in the Nutritional Quality of Larval Diets in a Stingless Bee}, series = {Insects}, volume = {11}, journal = {Insects}, number = {2}, issn = {2075-4450}, doi = {10.3390/insects11020125}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-200605}, pages = {125}, year = {2020}, abstract = {Bees need food of appropriate nutritional quality to maintain their metabolic functions. They largely obtain all required nutrients from floral resources, i.e., pollen and nectar. However, the diversity, composition and nutritional quality of floral resources varies with the surrounding environment and can be strongly altered in human-impacted habitats. We investigated whether differences in plant species richness as found in the surrounding environment correlated with variation in the floral diversity and nutritional quality of larval provisions (i.e., mixtures of pollen, nectar and salivary secretions) composed by the mass-provisioning stingless bee Tetragonula carbonaria (Apidae: Meliponini). We found that the floral diversity of larval provisions increased with increasing plant species richness. The sucrose and fat (total fatty acid) content and the proportion and concentration of the omega-6 fatty acid linoleic acid decreased, whereas the proportion of the omega-3 fatty acid linolenic acid increased with increasing plant species richness. Protein (total amino acid) content and amino acid composition did not change. The protein to fat (P:F) ratio, known to affect bee foraging, increased on average by more than 40\% from plantations to forests and gardens, while the omega-6:3 ratio, known to negatively affect cognitive performance, decreased with increasing plant species richness. Our results suggest that plant species richness may support T. carbonaria colonies by providing not only a continuous resource supply (as shown in a previous study), but also floral resources of high nutritional quality.}, language = {en} } @article{VoulgariKokotaSteffanDewenterKeller2020, author = {Voulgari-Kokota, Anna and Steffan-Dewenter, Ingolf and Keller, Alexander}, title = {Susceptibility of Red Mason Bee Larvae to Bacterial Threats Due to Microbiome Exchange with Imported Pollen Provisions}, series = {Insects}, volume = {11}, journal = {Insects}, number = {6}, issn = {2075-4450}, doi = {10.3390/insects11060373}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-207948}, year = {2020}, abstract = {Solitary bees are subject to a variety of pressures that cause severe population declines. Currently, habitat loss, temperature shifts, agrochemical exposure, and new parasites are identified as major threats. However, knowledge about detrimental bacteria is scarce, although they may disturb natural microbiomes, disturb nest environments, or harm the larvae directly. To address this gap, we investigated 12 Osmia bicornis nests with deceased larvae and 31 nests with healthy larvae from the same localities in a 16S ribosomal RNA (rRNA) gene metabarcoding study. We sampled larvae, pollen provisions, and nest material and then contrasted bacterial community composition and diversity in healthy and deceased nests. Microbiomes of pollen provisions and larvae showed similarities for healthy larvae, whilst this was not the case for deceased individuals. We identified three bacterial taxa assigned to Paenibacillus sp. (closely related to P. pabuli/amylolyticus/xylanexedens), Sporosarcina sp., and Bacillus sp. as indicative for bacterial communities of deceased larvae, as well as Lactobacillus for corresponding pollen provisions. Furthermore, we performed a provisioning experiment, where we fed larvae with untreated and sterilized pollens, as well as sterilized pollens inoculated with a Bacillus sp. isolate from a deceased larva. Untreated larval microbiomes were consistent with that of the pollen provided. Sterilized pollen alone did not lead to acute mortality, while no microbiome was recoverable from the larvae. In the inoculation treatment, we observed that larval microbiomes were dominated by the seeded bacterium, which resulted in enhanced mortality. These results support that larval microbiomes are strongly determined by the pollen provisions. Further, they underline the need for further investigation of the impact of detrimental bacterial acquired via pollens and potential buffering by a diverse pollen provision microbiome in solitary bees.}, language = {en} } @article{BakhtiarizadehHosseinpourShahhoseinietal.2018, author = {Bakhtiarizadeh, Mohammad Reza and Hosseinpour, Batool and Shahhoseini, Maryam and Korte, Arthur and Gifani, Peyman}, title = {Weighted gene co-expression network analysis of endometriosis and identification of functional modules associated with its main hallmarks}, series = {Frontiers in Genetics}, volume = {9}, journal = {Frontiers in Genetics}, number = {453}, doi = {10.3389/fgene.2018.00453}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-177376}, year = {2018}, abstract = {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.}, language = {en} } @article{TogninalliSerenMengetal.2018, author = {Togninalli, Matteo and Seren, {\"U}mit and Meng, Dazhe and Fitz, Joffrey and Nordborg, Magnus and Weigel, Detlef and Borgwardt, Karsten and Korte, Arthur and Grimm, Dominik G.}, title = {The AraGWAS Catalog: a curated and standardized Arabidopsis thaliana GWAS catalog}, series = {Nucleic Acids Research}, volume = {46}, journal = {Nucleic Acids Research}, number = {D1}, doi = {10.1093/nar/gkx954}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-158727}, pages = {D1150-D1156}, year = {2018}, abstract = {The abundance of high-quality genotype and phenotype data for the model organism Arabidopsis thaliana enables scientists to study the genetic architecture of many complex traits at an unprecedented level of detail using genome-wide association studies (GWAS). GWAS have been a great success in A. thaliana and many SNP-trait associations have been published. With the AraGWAS Catalog (https://aragwas.1001genomes.org) we provide a publicly available, manually curated and standardized GWAS catalog for all publicly available phenotypes from the central A. thaliana phenotype repository, AraPheno. All GWAS have been recomputed on the latest imputed genotype release of the 1001 Genomes Consortium using a standardized GWAS pipeline to ensure comparability between results. The catalog includes currently 167 phenotypes and more than 222 000 SNP-trait associations with P < 10\(^{-4}\), of which 3887 are significantly associated using permutation-based thresholds. The AraGWAS Catalog can be accessed via a modern web-interface and provides various features to easily access, download and visualize the results and summary statistics across GWAS.}, language = {en} } @article{KaltdorfTheissMarkertetal.2018, author = {Kaltdorf, Kristin Verena and Theiss, Maria and Markert, Sebastian Matthias and Zhen, Mei and Dandekar, Thomas and Stigloher, Christian and Kollmannsberger, Philipp}, title = {Automated classification of synaptic vesicles in electron tomograms of C. elegans using machine learning}, series = {PLoS ONE}, volume = {13}, journal = {PLoS ONE}, number = {10}, doi = {10.1371/journal.pone.0205348}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-176831}, pages = {e0205348}, year = {2018}, abstract = {Synaptic vesicles (SVs) are a key component of neuronal signaling and fulfil different roles depending on their composition. In electron micrograms of neurites, two types of vesicles can be distinguished by morphological criteria, the classical "clear core" vesicles (CCV) and the typically larger "dense core" vesicles (DCV), with differences in electron density due to their diverse cargos. Compared to CCVs, the precise function of DCVs is less defined. DCVs are known to store neuropeptides, which function as neuronal messengers and modulators [1]. In C. elegans, they play a role in locomotion, dauer formation, egg-laying, and mechano- and chemosensation [2]. Another type of DCVs, also referred to as granulated vesicles, are known to transport Bassoon, Piccolo and further constituents of the presynaptic density in the center of the active zone (AZ), and therefore are important for synaptogenesis [3]. To better understand the role of different types of SVs, we present here a new automated approach to classify vesicles. We combine machine learning with an extension of our previously developed vesicle segmentation workflow, the ImageJ macro 3D ART VeSElecT. With that we reliably distinguish CCVs and DCVs in electron tomograms of C. elegans NMJs using image-based features. Analysis of the underlying ground truth data shows an increased fraction of DCVs as well as a higher mean distance between DCVs and AZs in dauer larvae compared to young adult hermaphrodites. Our machine learning based tools are adaptable and can be applied to study properties of different synaptic vesicle pools in electron tomograms of diverse model organisms.}, language = {en} } @article{GuptaMinochaThapaetal.2022, author = {Gupta, Shishir K. and Minocha, Rashmi and Thapa, Prithivi Jung and Srivastava, Mugdha and Dandekar, Thomas}, title = {Role of the pangolin in origin of SARS-CoV-2: an evolutionary perspective}, series = {International Journal of Molecular Sciences}, volume = {23}, journal = {International Journal of Molecular Sciences}, number = {16}, issn = {1422-0067}, doi = {10.3390/ijms23169115}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-285995}, year = {2022}, abstract = {After the recent emergence of SARS-CoV-2 infection, unanswered questions remain related to its evolutionary history, path of transmission or divergence and role of recombination. There is emerging evidence on amino acid substitutions occurring in key residues of the receptor-binding domain of the spike glycoprotein in coronavirus isolates from bat and pangolins. In this article, we summarize our current knowledge on the origin of SARS-CoV-2. We also analyze the host ACE2-interacting residues of the receptor-binding domain of spike glycoprotein in SARS-CoV-2 isolates from bats, and compare it to pangolin SARS-CoV-2 isolates collected from Guangdong province (GD Pangolin-CoV) and Guangxi autonomous regions (GX Pangolin-CoV) of South China. Based on our comparative analysis, we support the view that the Guangdong Pangolins are the intermediate hosts that adapted the SARS-CoV-2 and represented a significant evolutionary link in the path of transmission of SARS-CoV-2 virus. We also discuss the role of intermediate hosts in the origin of Omicron.}, language = {en} } @article{MarquardtHartrampfKollmannsbergeretal.2023, author = {Marquardt, Andr{\´e} and Hartrampf, Philipp and Kollmannsberger, Philip and Solimando, Antonio G. and Meierjohann, Svenja and K{\"u}bler, Hubert and Bargou, Ralf and Schilling, Bastian and Serfling, Sebastian E. and Buck, Andreas and Werner, Rudolf A. and Lapa, Constantin and Krebs, Markus}, title = {Predicting microenvironment in CXCR4- and FAP-positive solid tumors — a pan-cancer machine learning workflow for theranostic target structures}, series = {Cancers}, volume = {15}, journal = {Cancers}, number = {2}, issn = {2072-6694}, doi = {10.3390/cancers15020392}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-305036}, year = {2023}, abstract = {(1) Background: C-X-C Motif Chemokine Receptor 4 (CXCR4) and Fibroblast Activation Protein Alpha (FAP) are promising theranostic targets. However, it is unclear whether CXCR4 and FAP positivity mark distinct microenvironments, especially in solid tumors. (2) Methods: Using Random Forest (RF) analysis, we searched for entity-independent mRNA and microRNA signatures related to CXCR4 and FAP overexpression in our pan-cancer cohort from The Cancer Genome Atlas (TCGA) database — representing n = 9242 specimens from 29 tumor entities. CXCR4- and FAP-positive samples were assessed via StringDB cluster analysis, EnrichR, Metascape, and Gene Set Enrichment Analysis (GSEA). Findings were validated via correlation analyses in n = 1541 tumor samples. TIMER2.0 analyzed the association of CXCR4 / FAP expression and infiltration levels of immune-related cells. (3) Results: We identified entity-independent CXCR4 and FAP gene signatures representative for the majority of solid cancers. While CXCR4 positivity marked an immune-related microenvironment, FAP overexpression highlighted an angiogenesis-associated niche. TIMER2.0 analysis confirmed characteristic infiltration levels of CD8+ cells for CXCR4-positive tumors and endothelial cells for FAP-positive tumors. (4) Conclusions: CXCR4- and FAP-directed PET imaging could provide a non-invasive decision aid for entity-agnostic treatment of microenvironment in solid malignancies. Moreover, this machine learning workflow can easily be transferred towards other theranostic targets.}, language = {en} } @article{PaulKollmannsberger2020, author = {Paul, Torsten Johann and Kollmannsberger, Philip}, title = {Biological network growth in complex environments: A computational framework}, series = {PLoS Computational Biology}, volume = {16}, journal = {PLoS Computational Biology}, number = {11}, doi = {10.1371/journal.pcbi.1008003}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-231373}, year = {2020}, abstract = {Spatial biological networks are abundant on all scales of life, from single cells to ecosystems, and perform various important functions including signal transmission and nutrient transport. These biological functions depend on the architecture of the network, which emerges as the result of a dynamic, feedback-driven developmental process. While cell behavior during growth can be genetically encoded, the resulting network structure depends on spatial constraints and tissue architecture. Since network growth is often difficult to observe experimentally, computer simulations can help to understand how local cell behavior determines the resulting network architecture. We present here a computational framework based on directional statistics to model network formation in space and time under arbitrary spatial constraints. Growth is described as a biased correlated random walk where direction and branching depend on the local environmental conditions and constraints, which are presented as 3D multilayer grid. To demonstrate the application of our tool, we perform growth simulations of a dense network between cells and compare the results to experimental data from osteocyte networks in bone. Our generic framework might help to better understand how network patterns depend on spatial constraints, or to identify the biological cause of deviations from healthy network function. Author summary We present a novel modeling approach and computational implementation to better understand the development of spatial biological networks under the influence of external signals. Our tool allows us to study the relationship between local biological growth parameters and the emerging macroscopic network function using simulations. This computational approach can generate plausible network graphs that take local feedback into account and provide a basis for comparative studies using graph-based methods.}, language = {en} } @article{Korte2022, author = {Korte, Arthur}, title = {Der Zusammenhang zwischen Genom und Ph{\"a}notyp}, series = {BIOspektrum}, volume = {28}, journal = {BIOspektrum}, number = {3}, issn = {0947-0867}, doi = {10.1007/s12268-022-1765-y}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-324231}, pages = {279-282}, year = {2022}, abstract = {Understanding the causal relationship between genotype and phenotype is a major objective in biology. Genome-wide association studies (GWAS) correlate genetic polymorphisms with trait variation and have already identified causative variants for various traits in many different organisms, from humans to plants. Importantly, many adaptive traits, like the regulation of flowering time in plants, are not regulated by distinct genetic effects, but by more sophisticated gene regulatory networks.}, language = {de} } @phdthesis{Schmid2024, author = {Schmid, Kerstin}, title = {Integrative, three-dimensional \(in\) \(silico\) modeling of gas exchange in the human alveolus}, doi = {10.25972/OPUS-35182}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-351823}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2024}, abstract = {Die Lunge erf{\"u}llt durch den Austausch von Atemgasen eine {\"u}berlebenswichtige Aufgabe. Der Gasaustausch erfolgt durch einen einfachen, aber entscheidenden passiven Diffusionsprozess. Dieser findet in den Alveolen statt, ballonartigen Strukturen, die an die peripheren Atemwege grenzen. Alveolen sind von einem dichten Netz aus kleinen Kapillaren umgeben. Hier kommt die eingeatmete Luft in unmittelbare N{\"a}he zu dem vom Herzen kommenden sauerstoffarmen Blut und erm{\"o}glicht den Austausch von Sauerstoff und Kohlenstoffdioxid {\"u}ber deren Konzentrationsgradienten. Die Effizienz des Gasaustauschs kann anhand von Indikatoren wie der Sauerstoffdiffusionskapazit{\"a}t der Lunge und der Reaktionshalbzeit gemessen werden. Beim Menschen besteht eine betr{\"a}chtliche Diskrepanz zwischen physiologischen Sch{\"a}tzungen der Diffusionskapazit{\"a}t und der theoretischen Maximalkapazit{\"a}t unter optimalen strukturellen Bedingungen (der morphologischen Sch{\"a}tzung). Diese Diskrepanz wird durch eine Reihe ineinandergreifender Faktoren beeinflusst, darunter strukturelle Elemente wie die Oberfl{\"a}che und die Dicke der Diffusionsbarriere sowie physiologische Faktoren wie die Blutflussdynamik. Um die verschiedenen Rollen dieser Faktoren zu entschl{\"u}sseln, untersuchten wir, wie die morphologischen und physiologischen Eigenschaften der menschlichen alveol{\"a}ren Mikroumgebung kollektiv und individuell den Prozess des Gasaustauschs beeinflussen. Zu diesem Zweck entwickelten wir einen integrativen in silico Ansatz, der 3D morphologische Modellierung und Simulation von Blutfluss und Sauerstofftransport kombiniert. Im Mittelpunkt unseres Ansatzes steht die Simulationssoftware Alvin, die als interaktive Plattform f{\"u}r das zugrundeliegende mathematische Modell des Sauerstofftransports in der Alveole dient. Unser r{\"a}umlich-zeitliches Modell wurde durch die Integration und Erweiterung bestehender mathematischer Modelle entwickelt und liefert Ergebnisse, die mit experimentellen Daten im Einklang stehen. Alvin erm{\"o}glicht eine immersive Auseinandersetzung mit dem simulierten Gasaustausch, indem sie Parameter{\"a}nderungen in Echtzeit und die Ausf{\"u}hrung mehrerer Simulationsinstanzen gleichzeitig erm{\"o}glicht w{\"a}hrend sie ein detailliertes quantitatives Feedback liefert. Die beteiligten morphologischen und physiologischen Parameter wurden mit einem Fokus auf der Mikrovaskulatur weiter untersucht. Durch die Zusammenstellung stereologischer Daten aus der Literatur und geometrischer 3D-Modellierung erstellten wir ein "sheet-flow" Modell als realistische Darstellung des menschlichen alveol{\"a}ren Kapillarnetzwerks. Blutfluss wurde mit Hilfe numerischer Str{\"o}mungsdynamik simuliert. Unsere Ergebnisse stimmen mit fr{\"u}heren Sch{\"a}tzungen {\"u}berein und unterstreichen die entscheidende Rolle von Viskosit{\"a}tsmodellen bei der Vorhersage des Druckabfalls in der Mikrovaskulatur. Dar{\"u}ber hinaus zeigten wir, wie unser Ansatz genutzt werden kann, um strukturelle Details wie die Konnektivit{\"a}t des alveol{\"a}ren Kapillarnetzes mit dem Gef{\"a}ßbaum anhand von Blutflussindizes zu untersuchen. Es ist wichtig zu betonen, dass wir uns bislang auf verschiedene Datenquellen st{\"u}tzten und dass f{\"u}r weitere Fortschritte eine experimentelle Vailidierung erforderlich ist. Die Integration unserer Ergebnisse in Alvin erm{\"o}glichte die Quantifizierung des simulierten Gasaustauschprozesses {\"u}ber die Sauerstoffdiffusionskapazit{\"a}t und die Reaktionshalbzeit. Neben der Bewertung der kollektiven Einfl{\"u}sse der morphologischen und physiologischen Eigenschaften erleichterte unsere interaktive Software auch die Bewertung einzelner Parameter{\"a}nderungen. Die Betrachtung des Blutvolumens und der f{\"u}r den Gasaustausch zur Verf{\"u}gung stehenden Oberfl{\"a}che ergab lineare Korrelationen mit der Diffusionskapazit{\"a}t. Die Blutflussgeschwindigkeit hatte einen positiven, nichtlinearen Effekt auf die Diffusionskapazit{\"a}t. Die Reaktionshalbzeit best{\"a}tigte, dass der Gasaustauschprozess in der Regel nicht diffusionslimitiert ist. Insgesamt lieferte unser Alveolenmodell einen Wert f{\"u}r die Diffusionskapazit{\"a}t, der in der Mitte der fr{\"u}heren physiologischen und morphologischen Sch{\"a}tzung lag. Daraus l{\"a}sst sich schließen, dass Ph{\"a}nomene auf Alveolarebene zu 50\% der Limitierung der Diffusionskapazit{\"a}t beitragen, die in vivo eintreten. Zusammenfassend l{\"a}sst sich sagen, dass unser integrativer in silico Ansatz verschiedene strukturelle und funktionelle Einfl{\"u}sse auf den alveol{\"a}ren Gasaustausch aufschl{\"u}sselt und damit die traditionelle Forschung in der Atemwegsforschung erg{\"a}nzt. Zus{\"a}tzlich zeigen wir seinen Nutzen in der Lehre oder bei der Interpretation ver{\"o}ffentlichter Daten auf. Um unser Verst{\"a}ndnis zu verbessern, sollten k{\"u}nftige Arbeiten vorrangig darauf ausgerichtet sein, einen zusammenh{\"a}ngenden experimentellen Datensatz zu erhalten und ein geeignetes Viskosit{\"a}tsmodell f{\"u}r Blutflusssimulationen zu finden.}, subject = {Gasaustausch}, language = {en} } @article{FischerSchardtLilaoGarzonetal.2023, author = {Fischer, Sabine C. and Schardt, Simon and Lilao-Garz{\´o}n, Joaqu{\´i}n and Mu{\~n}oz-Descalzo, Silvia}, title = {The salt-and-pepper pattern in mouse blastocysts is compatible with signaling beyond the nearest neighbors}, series = {iScience}, volume = {26}, journal = {iScience}, number = {11}, doi = {10.1016/j.isci.2023.108106}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-350184}, year = {2023}, abstract = {Summary Embryos develop in a concerted sequence of spatiotemporal arrangements of cells. In the preimplantation mouse embryo, the distribution of the cells in the inner cell mass evolves from a salt-and-pepper pattern to spatial segregation of two distinct cell types. The exact properties of the salt-and-pepper pattern have not been analyzed so far. We investigate the spatiotemporal distribution of NANOG- and GATA6-expressing cells in the ICM of the mouse blastocysts with quantitative three-dimensional single-cell-based neighborhood analyses. A combination of spatial statistics and agent-based modeling reveals that the cell fate distribution follows a local clustering pattern. Using ordinary differential equations modeling, we show that this pattern can be established by a distance-based signaling mechanism enabling cells to integrate information from the whole inner cell mass into their cell fate decision. Our work highlights the importance of longer-range signaling to ensure coordinated decisions in groups of cells to successfully build embryos. Highlights • The local cell neighborhood and global ICM population composition correlate • ICM cells show characteristics of local clustering in early and mid mouse blastocysts • ICM patterning requires integration of signals from cells beyond the first neighbors}, language = {en} } @article{FaistAnkenbrandSickeletal.2023, author = {Faist, Hanna and Ankenbrand, Markus J. and Sickel, Wiebke and Hentschel, Ute and Keller, Alexander and Deeken, Rosalia}, title = {Opportunistic bacteria of grapevine crown galls are equipped with the genomic repertoire for opine utilization}, series = {Genome Biology and Evolution}, volume = {15}, journal = {Genome Biology and Evolution}, number = {12}, doi = {10.1093/gbe/evad228}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-350172}, year = {2023}, abstract = {Young grapevines (Vitis vinifera) suffer and eventually can die from the crown gall disease caused by the plant pathogen Allorhizobium vitis (Rhizobiaceae). Virulent members of A. vitis harbor a tumor-inducing plasmid and induce formation of crown galls due to the oncogenes encoded on the transfer DNA. The expression of oncogenes in transformed host cells induces unregulated cell proliferation and metabolic and physiological changes. The crown gall produces opines uncommon to plants, which provide an important nutrient source for A. vitis harboring opine catabolism enzymes. Crown galls host a distinct bacterial community, and the mechanisms establishing a crown gall-specific bacterial community are currently unknown. Thus, we were interested in whether genes homologous to those of the tumor-inducing plasmid coexist in the genomes of the microbial species coexisting in crown galls. We isolated 8 bacterial strains from grapevine crown galls, sequenced their genomes, and tested their virulence and opine utilization ability in bioassays. In addition, the 8 genome sequences were compared with 34 published bacterial genomes, including closely related plant-associated bacteria not from crown galls. Homologous genes for virulence and opine anabolism were only present in the virulent Rhizobiaceae. In contrast, homologs of the opine catabolism genes were present in all strains including the nonvirulent members of the Rhizobiaceae and non-Rhizobiaceae. Gene neighborhood and sequence identity of the opine degradation cluster of virulent and nonvirulent strains together with the results of the opine utilization assay support the important role of opine utilization for cocolonization in crown galls, thereby shaping the crown gall community.}, language = {en} } @article{DirkFischerSchardtetal.2023, author = {Dirk, Robin and Fischer, Jonas L. and Schardt, Simon and Ankenbrand, Markus J. and Fischer, Sabine C.}, title = {Recognition and reconstruction of cell differentiation patterns with deep learning}, series = {PLoS Computational Biology}, volume = {19}, journal = {PLoS Computational Biology}, number = {10}, doi = {10.1371/journal.pcbi.1011582}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-350167}, year = {2023}, abstract = {Abstract Cell lineage decisions occur in three-dimensional spatial patterns that are difficult to identify by eye. There is an ongoing effort to replicate such patterns using mathematical modeling. One approach uses long ranging cell-cell communication to replicate common spatial arrangements like checkerboard and engulfing patterns. In this model, the cell-cell communication has been implemented as a signal that disperses throughout the tissue. On the other hand, machine learning models have been developed for pattern recognition and pattern reconstruction tasks. We combined synthetic data generated by the mathematical model with spatial summary statistics and deep learning algorithms to recognize and reconstruct cell fate patterns in organoids of mouse embryonic stem cells. Application of Moran's index and pair correlation functions for in vitro and synthetic data from the model showed local clustering and radial segregation. To assess the patterns as a whole, a graph neural network was developed and trained on synthetic data from the model. Application to in vitro data predicted a low signal dispersion value. To test this result, we implemented a multilayer perceptron for the prediction of a given cell fate based on the fates of the neighboring cells. The results show a 70\% accuracy of cell fate imputation based on the nine nearest neighbors of a cell. Overall, our approach combines deep learning with mathematical modeling to link cell fate patterns with potential underlying mechanisms. Author summary Mammalian embryo development relies on organized differentiation of stem cells into different lineages. Particularly at the early stages of embryogenesis, cells of different fates form three-dimensional spatial patterns that are difficult to identify by eye. Pattern quantification and mathematical modeling have produced first insights into potential mechanisms for the cell fate arrangements. However, these approaches have relied on classifications of the patterns such as inside-out or random, or used summary statistics such as pair correlation functions or cluster radii. Deep neural networks allow characterizing patterns directly. Since the tissue context can be readily reproduced by a graph, we implemented a graph neural network to characterize the patterns of embryonic stem cell organoids as a whole. In addition, we implemented a multilayer perceptron model to reconstruct the fate of a given cell based on its neighbors. To train and test the models, we used synthetic data generated by our mathematical model for cell-cell communication. This interplay of deep learning and mathematical modeling in combination with summary statistics allowed us to identify a potential mechanism for cell fate determination in mouse embryonic stem cells. Our results agree with a mechanism with a dispersion of the intercellular signal that links a cell's fate to those of the local neighborhood.}, language = {en} }