Theodor-Boveri-Institut für Biowissenschaften
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The monitoring of species and functional diversity is of increasing relevance for the development of strategies for the conservation and management of biodiversity. Therefore, reliable estimates of the performance of monitoring techniques across taxa become important. Using a unique dataset, this study investigates the potential of airborne LiDAR-derived variables characterizing vegetation structure as predictors for animal species richness at the southern slopes of Mount Kilimanjaro. To disentangle the structural LiDAR information from co-factors related to elevational vegetation zones, LiDAR-based models were compared to the predictive power of elevation models. 17 taxa and 4 feeding guilds were modeled and the standardized study design allowed for a comparison across the assemblages. Results show that most taxa (14) and feeding guilds (3) can be predicted best by elevation with normalized RMSE values but only for three of those taxa and two of those feeding guilds the difference to other models is significant. Generally, modeling performances between different models vary only slightly for each assemblage. For the remaining, structural information at most showed little additional contribution to the performance. In summary, LiDAR observations can be used for animal species prediction. However, the effort and cost of aerial surveys are not always in proportion with the prediction quality, especially when the species distribution follows zonal patterns, and elevation information yields similar results.
TelAP1 links telomere complexes with developmental expression site silencing in African trypanosomes
(2018)
During its life cycle, Trypanosoma brucei shuttles between a mammalian host and the tsetse fly vector. In the mammalian host, immune evasion of T. brucei bloodstream form (BSF) cells relies on antigenic variation, which includes monoallelic expression and periodic switching of variant surface glycoprotein (VSG) genes. The active VSG is transcribed from only 1 of the 15 subtelomeric expression sites (ESs). During differentiation from BSF to the insect-resident procyclic form (PCF), the active ES is transcriptionally silenced. We used mass spectrometry-based interactomics to determine the composition of telomere protein complexes in T. brucei BSF and PCF stages to learn more about the structure and functions of telomeres in trypanosomes. Our data suggest a different telomere complex composition in the two forms of the parasite. One of the novel telomere-associated proteins, TelAP1, forms a complex with telomeric proteins TbTRF, TbRAP1 and TbTIF2 and influences ES silencing kinetics during developmental differentiation.
Meniscal pathologies are among the most common injuries of the femorotibial joint in both human and equine patients. Pathological forces and ensuing injuries of the cranial horn of the equine medial meniscus are considered analogous to those observed in the human posterior medial horn. Biomechanical properties of human menisci are site-and depth-specific. However, the influence of equine meniscus topography and composition on its biomechanical properties is yet unknown. A better understanding of equine meniscus composition and biomechanics could advance not only veterinary therapies for meniscus degeneration or injuries, but also further substantiate the horse as suitable translational animal model for (human) meniscus tissue engineering. Therefore, the aim of this study was to investigate the composition and structure of the equine knee meniscus in a site-and age-specific manner and their relationship with potential site-specific biomechanical properties. The meniscus architecture was investigated histologically. Biomechanical testing included evaluation of the shore hardness (SH), stiffness and energy loss of the menisci. The SH was found to be subjected to both age and site-specific changes, with an overall higher SH of the tibial meniscus surface and increase in SH with age. Stiffness and energy loss showed neither site nor age related significant differences. The macroscopic and histologic similarities between equine and human menisci described in this study, support continued research in this field.
Background
The honeybee (Apis mellifera) represents a model organism for social insects displaying behavioral plasticity. This is reflected by an age-dependent task allocation. The most protruding tasks are performed by young nurse bees and older forager bees that take care of the brood inside the hive and collect food from outside the hive, respectively. The molecular mechanism leading to the transition from nurse bees to foragers is currently under intense research. Circular RNAs, however, were not considered in this context so far. As of today, this group of non-coding RNAs was only known to exist in two other insects, Drosophila melanogaster and Bombyx mori. Here we complement the state of circular RNA research with the first characterization in a social insect.
Results
We identified numerous circular RNAs in the brain of A. mellifera nurse bees and forager bees using RNA-Seq with exonuclease enrichment. Presence and circularity were verified for the most abundant representatives. Back-splicing in honeybee occurs further towards the end of transcripts and in transcripts with a high number of exons. The occurrence of circularized exons is correlated with length and CpG-content of their flanking introns. The latter coincides with increased DNA-methylation in the respective loci. For two prominent circular RNAs the abundance in worker bee brains was quantified in TaqMan assays. In line with previous findings of circular RNAs in Drosophila, circAmrsmep2 accumulates with increasing age of the insect. In contrast, the levels of circAmrad appear age-independent and correlate with the bee's task. Its parental gene is related to amnesia-resistant memory.
Conclusions
We provide the first characterization of circRNAs in a social insect. Many of the RNAs identified here show homologies to circular RNAs found in Drosophila and Bombyx, indicating that circular RNAs are a common feature among insects. We find that exon circularization is correlated to DNA-methylation at the flanking introns. The levels of circAmrad suggest a task-dependent abundance that is decoupled from age. Moreover, a GO term analysis shows an enrichment of task-related functions. We conclude that circular RNAs could be relevant for task allocation in honeybee and should be investigated further in this context.
Epithelial-to-mesenchymal transition (EMT) is discussed to be centrally involved in invasion, stemness, and drug resistance. Experimental models to evaluate this process in its biological complexity are limited. To shed light on EMT impact and test drug response more reliably, we use a lung tumor test system based on a decellularized intestinal matrix showing more in vivo-like proliferation levels and enhanced expression of clinical markers and carcinogenesis-related genes. In our models, we found evidence for a correlation of EMT with drug resistance in primary and secondary resistant cells harboring KRAS\(^{G12C}\) or EGFR mutations, which was simulated in silico based on an optimized signaling network topology. Notably, drug resistance did not correlate with EMT status in KRAS-mutated patient-derived xenograft (PDX) cell lines, and drug efficacy was not affected by EMT induction via TGF-β. To investigate further determinants of drug response, we tested several drugs in combination with a KRAS\(^{G12C}\) inhibitor in KRAS\(^{G12C}\) mutant HCC44 models, which, besides EMT, display mutations in P53, LKB1, KEAP1, and high c-MYC expression. We identified an aurora-kinase A (AURKA) inhibitor as the most promising candidate. In our network, AURKA is a centrally linked hub to EMT, proliferation, apoptosis, LKB1, and c-MYC. This exemplifies our systemic analysis approach for clinical translation of biomarker signatures.
Mammalian embryonic development is subject to complex biological relationships that need to be understood. However, before the whole structure of development can be put together, the individual building blocks must first be understood in more detail. One of these building blocks is the second cell fate decision and describes the differentiation of cells of the inner cell mass of the embryo into epiblast and primitive endoderm cells. These cells then spatially segregate and form the subsequent bases for the embryo and yolk sac, respectively. In organoids of the inner cell mass, these two types of progenitor cells are also observed to form, and to some extent to spatially separate. This work has been devoted to these phenomena over the past three years. Plenty of studies already provide some insights into the basic mechanics of this cell differentiation, such that the first signs of epiblast and primitive endoderm differentiation, are the expression levels of transcription factors NANOG and GATA6. Here, cells with low expression of GATA6 and high expression of NANOG adopt the epiblast fate. If the expressions are reversed, a primitive endoderm cell is formed. Regarding the spatial segregation of the two cell types, it is not yet clear what mechanism leads to this. A common hypothesis suggests the differential adhesion of cell as the cause for the spatial rearrangement of cells. In this thesis however, the possibility of a global cell-cell communication is investigated. The approach chosen to study these phenomena follows the motto "mathematics is biology's next microscope". Mathematical modeling is used to transform the central gene regulatory network at the heart of this work into a system of equations that allows us to describe the temporal evolution of NANOG and GATA6 under the influence of an external signal. Special attention is paid to the derivation of new models using methods of statistical mechanics, as well as the comparison with existing models. After a detailed stability analysis the advantages of the derived model become clear by the fact that an exact relationship of the model parameters and the formation of heterogeneous mixtures of two cell types was found. Thus, the model can be easily controlled and the proportions of the resulting cell types can be estimated in advance. This mathematical model is also combined with a mechanism for global cell-cell communication, as well as a model for the growth of an organoid. It is shown that the global cell-cell communication is able to unify the formation of checkerboard patterns as well as engulfing patterns based on differently propagating signals. In addition, the influence of cell division and thus organoid growth on pattern formation is studied in detail. It is shown that this is able to contribute to the formation of clusters and, as a consequence, to breathe some randomness into otherwise perfectly sorted patterns.
Rhodopsin-cyclases for photocontrol of cGMP/cAMP and 2.3 Å structure of the adenylyl cyclase domain
(2018)
The cyclic nucleotides cAMP and cGMP are important second messengers that orchestrate fundamental cellular responses. Here, we present the characterization of the rhodopsinguanylyl cyclase from Catenaria anguillulae (CaRhGC), which produces cGMP in response to green light with a light to dark activity ratio > 1000. After light excitation the putative signaling state forms with tau = 31 ms and decays with tau = 570 ms. Mutations (up to 6) within the nucleotide binding site generate rhodopsin-adenylyl cyclases (CaRhACs) of which the double mutated YFP-CaRhAC (E497K/C566D) is the most suitable for rapid cAMP production in neurons. Furthermore, the crystal structure of the ligand-bound AC domain (2.25 angstrom) reveals detailed information about the nucleotide binding mode within this recently discovered class of enzyme rhodopsin. Both YFP-CaRhGC and YFP-CaRhAC are favorable optogenetic tools for non-invasive, cell-selective, and spatio-temporally precise modulation of cAMP/cGMP with light.
The fast and accurate yield estimates with the increasing availability and variety of global satellite products and the rapid development of new algorithms remain a goal for precision agriculture and food security. However, the consistency and reliability of suitable methodologies that provide accurate crop yield outcomes still need to be explored. The study investigates the coupling of crop modeling and machine learning (ML) to improve the yield prediction of winter wheat (WW) and oil seed rape (OSR) and provides examples for the Free State of Bavaria (70,550 km2), Germany, in 2019. The main objectives are to find whether a coupling approach [Light Use Efficiency (LUE) + Random Forest (RF)] would result in better and more accurate yield predictions compared to results provided with other models not using the LUE. Four different RF models [RF1 (input: Normalized Difference Vegetation Index (NDVI)), RF2 (input: climate variables), RF3 (input: NDVI + climate variables), RF4 (input: LUE generated biomass + climate variables)], and one semi-empiric LUE model were designed with different input requirements to find the best predictors of crop monitoring. The results indicate that the individual use of the NDVI (in RF1) and the climate variables (in RF2) could not be the most accurate, reliable, and precise solution for crop monitoring; however, their combined use (in RF3) resulted in higher accuracies. Notably, the study suggested the coupling of the LUE model variables to the RF4 model can reduce the relative root mean square error (RRMSE) from −8% (WW) and −1.6% (OSR) and increase the R
2 by 14.3% (for both WW and OSR), compared to results just relying on LUE. Moreover, the research compares models yield outputs by inputting three different spatial inputs: Sentinel-2(S)-MOD13Q1 (10 m), Landsat (L)-MOD13Q1 (30 m), and MOD13Q1 (MODIS) (250 m). The S-MOD13Q1 data has relatively improved the performance of models with higher mean R
2 [0.80 (WW), 0.69 (OSR)], and lower RRMSE (%) (9.18, 10.21) compared to L-MOD13Q1 (30 m) and MOD13Q1 (250 m). Satellite-based crop biomass, solar radiation, and temperature are found to be the most influential variables in the yield prediction of both crops.
Neisseria gonorrhoeae is a human-specific pathogen that causes gonorrhea, the second most common sexually transmitted infection worldwide. Disease progression, drug discovery, and basic host-pathogen interactions are studied using different approaches, which rely on models ranging from 2D cell culture to complex 3D tissues and animals. In this review, we discuss the models used in N. gonorrhoeae research. We address both in vivo (animal) and in vitro cell culture models, discussing the pros and cons of each and outlining the recent advancements in the field of three-dimensional tissue models. From simple 2D monoculture to complex advanced 3D tissue models, we provide an overview of the relevant methodology and its application. Finally, we discuss future directions in the exciting field of 3D tissue models and how they can be applied for studying the interaction of N. gonorrhoeae with host cells under conditions closely resembling those found at the native sites of infection.
Einflüsse der Photophysik und Photochemie von Cyaninfarbstoffen auf die Lokalisationsmikroskopie
(2023)
In den letzten Jahren haben sich hochauflösende Fluoreszenzmikroskopiemethoden, basierend auf der Lokalisation einzelner Fluorophore, zu einem leistungsstarken Werkzeug etabliert, um Fluoreszenzbilder weit unterhalb der Auflösungsgrenze zu generieren. Hiermit können räumliche Auflösungen von ~ 20 nm erzielt werden, was weit unterhalb der Beugungsgrenze liegt. Dabei haben zahlreiche Optimierungen und Entwicklungen neuer Methoden in der Einzelmolekül-Lokalisationsmikroskopie die Genauigkeit der orstspezifischen Bestimmung einzelner Fluorophore auf bis zu ~ 1 – 3 nm erhöht. Eine Auflösung im molekularen Bereich, weit unterhalb von ~ 10 nm bleibt allerdings herausfordernd, da die Lokalisationsgenauigkeit nur ein Kriterium hierfür ist. Allerdings wurde sich in den letzten Jahren überwiegend auf die Verbesserung dieses Parameters konzentriert. Weitere Kriterien für die fluoreszenzmikroskopische Auflösung sind dabei unter anderem die Markierungsdichte und die Kopplungseffizienz der Zielstruktur, sowie der Kopplungsfehler (Abstand zur Zielstruktur nach Farbstoffkopplung), die sich herausfordernd für eine molekulare Auflösung darstellen. Auch wenn die Kopplungseffizienz und -dichte hoch und der Kopplungsfehler gering ist, steigt bei Interfluorophordistanzen < 5nm, abhängig von den Farbstoffen, die Wahrscheinlichkeit von starken und schwachen Farbstoffwechselwirkungen und damit von Energieübertragungsprozessen zwischen den Farbstoffen, stark an. Daneben sollten Farbstoffe, abhänging von der Lokalisationsmikroskopiemethode, spezifische Kriterien, wie beispielsweise die Photoschaltbarkeit bei dSTORM, erfüllen, was dazu führt, dass diese Methoden häufig nur auf einzelne Farbstoffe beschränkt sind. In dieser Arbeit konnte mithilfe von definierten DNA-Origami Konstrukten gezeigt werden, dass das Blinkverhalten von Cyaninfarbstoffen unter dSTORM-Bedingungen einer Abstandsabhängigkeit aufgrund von spezifischen Energieübertragungsprozessen folgt, womit Farbstoffabstände im sub-10 nm Bereich charakterisiert werden konnten. Darüber hinaus konnte diese Abstandsabhängigkeit an biologischen Proben gezeigt werden. Hierbei konnten verschiedene zelluläre Rezeptoren effizient und mit geringem Abstandsfehler zur Zielstruktur mit Cyaninfarbstoffen gekoppelt werden. Diese abstandsabhänigen Prozesse und damit Charakterisierungen könnten dabei nicht nur spezifisch für die häufig unter dSTORM-Bedingungen verwendeten Cyaninfarbstoffen gültig sein, sondern auch auf andere Farbstoffklassen, die einen Auszustand zeigen, übertragbar sein. Darüber hinaus konnte gezeigt werden, dass hochauflösende dSTORM Aufnahmen unabhängig vom Farbstoffkopplungsgrad der Antikörpern sind, welche häufig für Standardfärbungen von zellulären Strukturen verwendet werden. Dabei konnte durch Photonenkoinzidenzmessungen dargelegt werden, dass aufgrund komplexer Farbstoffwechselwirkungen im Mittel nur ein Farbstoff aktiv ist, wobei höhere Kopplungsgrade ein komplexes Blinkverhalten zu Beginn der Messung zeigen. Durch die undefinierten Farbstoffabstände an Antikörpern konnte hier kein eindeutiger Energieübertragungsmechanismus entschlüsselt werden. Dennoch konnte gezeigt werden, dass Farbstoffaggregate bzw. H-Dimere unter dSTORM-Bedingungen destabilisiert werden. Durch die zuvor erwähnten DNA-Origami Konstrukte definierter Interfluorophordistanzen konnten Energieübertragungsmechanismen entschlüsselt werden, die auch für die Antikörper diverser Kopplungsgrade gültig sind. Des Weiteren konnten, ausgelöst durch komplexe Energieübertragungsprozesse höherer Kopplungsgrade am Antikörper, Mehrfarbenaufnahmen zellulärer Strukturen generiert werden, die über die spezifische Fluoreszenzlebenszeit separiert werden konnten. Dies stellt hier eine weitere Möglichkeit dar, unter einfachen Bedingungen, schnelle Mehrfarbenaufnahmen zellulärer Strukturen zu generieren. Durch die Verwendung des selben Farbstoffes unterschiedlicher Kopplungsgrade kann hier nur mit einer Anregungswellenlänge und frei von chromatischer Aberration gearbeitet werden. Neben den photophysikalischen Untersuchungen der Cyaninfarbstoffe Cy5 und Alexa Fluor 647 wurden diese ebenso photochemisch näher betrachtet. Dabei konnte ein neuartiger chemischer Mechanismus entschlüsselt werden. Dieser Mechanismus führt, ausgelöst durch Singulett-Sauerstoff (1O2), zu einer Photozerschneidung des konjugierten Doppelbindungssystems um zwei Kohlenstoffatome, was zu strukturellen und spektroskopischen Veränderungen dieser Farbstoffe führt. Auf Grundlage dieses Mechanismus konnte eine neue DNA-PAINT Methode entwickelt werden, die zu einer Beschleunigung der Aufnahmezeit führt.