570 Biowissenschaften; Biologie
Refine
Year of publication
- 2021 (379)
- 2020 (269)
- 2022 (261)
- 2017 (181)
- 2023 (173)
- 2018 (165)
- 2016 (157)
- 2019 (138)
- 2012 (137)
- 2010 (132)
- 2013 (130)
- 2009 (114)
- 2014 (111)
- 2015 (106)
- 2011 (100)
- 2008 (94)
- 2024 (81)
- 2007 (73)
- 2006 (70)
- 2005 (46)
- 2004 (38)
- 2003 (37)
- 2002 (22)
- 2001 (16)
- 1998 (14)
- 2000 (12)
- 1999 (9)
- 1981 (8)
- 1975 (7)
- 1990 (7)
- 1976 (6)
- 1977 (6)
- 1985 (6)
- 1971 (5)
- 1974 (5)
- 1984 (5)
- 1996 (5)
- 1980 (4)
- 1982 (3)
- 1989 (3)
- 1994 (3)
- 1995 (3)
- 1898 (2)
- 1901 (2)
- 1909 (2)
- 1920 (2)
- 1924 (2)
- 1957 (2)
- 1969 (2)
- 1970 (2)
- 1972 (2)
- 1979 (2)
- 1983 (2)
- 1986 (2)
- 1992 (2)
- 1993 (2)
- 1997 (2)
- 1597 (1)
- 1842 (1)
- 1843 (1)
- 1856 (1)
- 1859 (1)
- 1860 (1)
- 1875 (1)
- 1876 (1)
- 1881 (1)
- 1883 (1)
- 1897 (1)
- 1900 (1)
- 1903 (1)
- 1908 (1)
- 1910 (1)
- 1914 (1)
- 1918 (1)
- 1923 (1)
- 1927 (1)
- 1928 (1)
- 1933 (1)
- 1934 (1)
- 1937 (1)
- 1940 (1)
- 1945 (1)
- 1946 (1)
- 1959 (1)
- 1960 (1)
- 1961 (1)
- 1962 (1)
- 1963 (1)
- 1966 (1)
- 1967 (1)
- 1973 (1)
- 1978 (1)
- 1987 (1)
- 1991 (1)
Document Type
- Article (2119)
- Doctoral Thesis (740)
- Preprint (227)
- Part of Periodical (78)
- Book (16)
- Conference Proceeding (12)
- Part of a Book (10)
- Periodical (3)
- Report (2)
- Working Paper (2)
Language
- English (3211) (remove)
Is part of the Bibliography
- no (3211)
Keywords
- RNA (21)
- aging (20)
- SARS-CoV-2 (19)
- inflammation (18)
- taxonomy (18)
- Biochemistry (16)
- Biodiversity (16)
- Podospora anserina (16)
- autophagy (16)
- mitochondria (16)
Institute
- Biowissenschaften (1238)
- Biochemie und Chemie (552)
- Medizin (458)
- Biochemie, Chemie und Pharmazie (349)
- Institut für Ökologie, Evolution und Diversität (176)
- Senckenbergische Naturforschende Gesellschaft (165)
- Biodiversität und Klima Forschungszentrum (BiK-F) (123)
- Exzellenzcluster Makromolekulare Komplexe (116)
- MPI für Biophysik (108)
- Buchmann Institut für Molekulare Lebenswissenschaften (BMLS) (95)
Background: The causative agent of Chagas disease, Trypanosoma cruzi, and its nonpathogenic relative, Trypanosoma rangeli, are transmitted by haematophagous triatomines and undergo a crucial ontogenetic phase in the insect’s intestine. In the process, the parasites interfere with the host immune system as well as the microbiome present in the digestive tract potentially establishing an environment advantageous for development. However, the coherent interactions between host, pathogen and microbiota have not yet been elucidated in detail. We applied a metagenome shotgun sequencing approach to study the alterations in the microbiota of Rhodnius prolixus, a major vector of Chagas disease, after exposure to T. cruzi and T. rangeli focusing also on the functional capacities present in the intestinal microbiome of the insect.
Results: The intestinal microbiota of R. prolixus was dominated by the bacterial orders Enterobacterales, Corynebacteriales, Lactobacillales, Clostridiales and Chlamydiales, whereas the latter conceivably originated from the blood used for pathogen exposure. The anterior and posterior midgut samples of the exposed insects showed a reduced overall number of organisms compared to the control group. However, we also found enriched bacterial groups after exposure to T. cruzi as well as T rangeli. While the relative abundance of Enterobacterales and Corynebacteriales decreased considerably, the Lactobacillales, mainly composed of the genus Enterococcus, developed as the most abundant taxonomic group. This applies in particular to vectors challenged with T. rangeli and at early timepoints after exposure to vectors challenged with T. cruzi. Furthermore, we were able to reconstruct four metagenome-assembled genomes from the intestinal samples and elucidate their unique metabolic functionalities within the triatomine microbiome, including the genome of a recently described insect symbiont, Candidatus Symbiopectobacterium, and the secondary metabolites producing bacteria Kocuria spp.
Conclusions: Our results facilitate a deeper understanding of the processes that take place in the intestinal tract of triatomine vectors during colonisation by trypanosomal parasites and highlight the influential aspects of pathogen-microbiota interactions. In particular, the mostly unexplored metabolic capacities of the insect vector’s microbiome are clearer, underlining its role in the transmission of Chagas disease.
Coronavirus disease 2019 (COVID-19) is a global pandemic posing significant health risks. The diagnostic test sensitivity of COVID-19 is limited due to irregularities in specimen handling. We propose a deep learning framework that identifies COVID-19 from medical images as an auxiliary testing method to improve diagnostic sensitivity. We use pseudo-coloring methods and a platform for annotating X-ray and computed tomography images to train the convolutional neural network, which achieves a performance similar to that of experts and provides high scores for multiple statistical indices (F1 scores > 96.72% (0.9307, 0.9890) and specificity >99.33% (0.9792, 1.0000)). Heatmaps are used to visualize the salient features extracted by the neural network. The neural network-based regression provides strong correlations between the lesion areas in the images and five clinical indicators, resulting in high accuracy of the classification framework. The proposed method represents a potential computer-aided diagnosis method for COVID-19 in clinical practice.
Understanding how species relate mechanistically to their environment via traits is a central goal in ecology. Many macroecological rules were found for macroorganisms, however, whether they can explain microorganismal macroecological patterns still requires investigation. Further, whether macroecological rules are also applicable in microclimates is largely unexplored. Here we use fruit body-forming fungi to understand both aspects better. A recent study showed first evidence for the thermal-melanism hypothesis (Bogert’s rule) in fruit body-forming fungi and relied on a continental spatial scale with large grid size. At large spatial extent and grid sizes, other factors like dispersal limitation or local microclimatic variability might influence observed patterns besides the rule of interest. Therefore, we test fungal assemblage fruit body color lightness along a local elevational gradient (mean annual temperature gradient of 7°C) while considering the vegetation cover as a proxy for local variability in microclimate. Using multivariate linear modeling, we found that fungal fruiting assemblages are significantly darker at lower mean annual temperatures supporting the thermal-melanism hypothesis. Further, we found a non-significant trend of assemblage color lightness with vegetation cover. Our results support Bogert’s rule for microorganisms with macroclimate, which was also found for macroorganisms.
Out-of-school laboratories, also called student labs, are an advantageous opportunity to teach biological subjects. Particularly in the case of complex fields such as neurobiology, student labs offer the opportunity to learn about difficult topics in a practical way. Due to numerous advantages, digital student labs are becoming increasingly popular nowadays. In this study, we investigated the effect of an electrophysiological setup for a virtual experiment with and without hands-on elements on participant motivation and technology acceptance. For this purpose, 235 students were questioned during a student laboratory day. The surveyed students showed high motivation and technology acceptance for the virtual experiment. In the comparison, the electrophysiological setup with hands-on elements performs better in the intrinsic components than the setup without hands-on elements: Thus, the hands-on approach is rated as more interesting and the perceived enjoyment scores higher. Nevertheless, both experimental groups show high values, so that the results of the study support the positive influence of digital laboratory as well as a positive influence of hands-on elements.
Single-particle tracking enables the analysis of the dynamics of biomolecules in living cells with nanometer spatial and millisecond temporal resolution. This technique reports on the mobility of membrane proteins and is sensitive to the molecular state of a biomolecule and to interactions with other biomolecules. Trajectories describe the mobility of single particles over time and provide information such as the diffusion coefficient and diffusion state. Changes in particle dynamics within single trajectories lead to segmentation, which allows to extract information on transitions of functional states of a biomolecule. Here, mean-squared displacement analysis is developed to classify trajectory segments into immobile, confined diffusing, and freely diffusing states, and to extract the occurrence of transitions between these modes. We applied this analysis to single-particle tracking data of the membrane receptor MET in live cells and analyzed state transitions in single trajectories of the un-activated receptor and the receptor bound to the ligand internalin B. We found that internalin B-bound MET shows an enhancement of transitions from freely and confined diffusing states into the immobile state as compared to un-activated MET. Confined diffusion acts as an intermediate state between immobile and free, as this state is most likely to change the diffusion state in the following segment. This analysis can be readily applied to single-particle tracking data of other membrane receptors and intracellular proteins under various conditions and contribute to the understanding of molecular states and signaling pathways.
Gene therapy has garnered increasing interest over recent decades. Several therapies employing gene transfer mechanisms have been developed, and, of these, adeno-associated virus (AAV) vectors have demonstrated viability for use with in vivo gene therapy. Several AAV-based therapeutics have received regulatory approval in the last few years including those for retinal disease, spinal muscular atrophy or aromatic L-amino acid decarboxylase deficiency. Lately, with the introduction of novel liver-directed AAV vector-based therapeutics for the treatment of haemophilia A and B, gene therapy has attracted significant attention in the hepatology community, with the liver increasingly recognised as a target for gene therapy. However, the introduction of foreign DNA into hepatocytes is associated with a risk of hepatic reactions, with raised ALT (alanine aminotransferase) and AST (aspartate aminotransferase) being – so far – the most commonly reported side effects. The complete mechanisms underlying the ALT flairs remain to be determined and the long-term risks associated with these new treatments is not yet known. The liver community is increasingly being asked to support liver-directed gene therapy to mitigate potential liver associated harm. In this review, we focus on AAV vector-based gene therapy, shedding light on this promising technique and its remarkable success in haemophilia, with a special focus on hepatic complications and their management in daily clinical practice.
The ubiquitin (Ub) code denotes the complex Ub architectures, including Ub chains of different length, linkage-type and linkage combinations, which enable ubiquitination to control a wide range of protein fates. Although many linkage-specific interactors have been described, how interactors are able to decode more complex architectures is not fully understood. We conducted a Ub interactor screen, in humans and yeast, using Ub chains of varying length, as well as, homotypic and heterotypic branched chains of the two most abundant linkage types – K48- and K63-linked Ub. We identified some of the first K48/K63 branch-specific Ub interactors, including histone ADP-ribosyltransferase PARP10/ARTD10, E3 ligase UBR4 and huntingtin-interacting protein HIP1. Furthermore, we revealed the importance of chain length by identifying interactors with a preference for Ub3 over Ub2 chains, including Ub-directed endoprotease DDI2, autophagy receptor CCDC50 and p97-adaptor FAF1. Crucially, we compared datasets collected using two common DUB inhibitors – Chloroacetamide and N-ethylmaleimide. This revealed inhibitor-dependent interactors, highlighting the importance of inhibitor consideration during pulldown studies. This dataset is a key resource for understanding how the Ub code is read.
LIN-2/7 (L27) domains are protein interaction modules that preferentially hetero-oligomerize, a property critical for their function in directing specific assembly of supramolecular signaling complexes at synapses and other polarized cell-cell junctions. We have solved the solution structure of the heterodimer composed of the L27 domains from LIN-2 and LIN-7. Comparison of this structure with other L27 domain structures has allowed us to formulate a general model for why most L27 domains form an obligate heterodimer complex. L27 domains can be divided in two types (A and B), with each heterodimer comprising an A/B pair. We have identified two keystone positions that play a central role in discrimination. The residues at these positions are energetically acceptable in the context of an A/B heterodimer, but would lead to packing defects or electrostatic repulsion in the context of A/A and B/B homodimers. As predicted by the model, mutations of keystone residues stabilize normally strongly disfavored homodimers. Thus, L27 domains are specifically optimized to avoid homodimeric interactions.
Highlights
• High resolution profile of C. pipiens' sugar diet has been obtained using UHPLC-MS.
• Artificial feeding using ornamental plants provides similar sugar profiles as observed in field collected mosquitoes.
• Metabolomic profiling found secondary metabolites and pollutants of anthropogenic use.
Abstract: Culex pipiens (Linnaeus, 1758) mosquitoes search plant sources of sugars to cope with the energetic demand of various physiological processes. The crop as part of the digestive system is devoted to the storage of sugar-based meal obtained from various nectars sources. The profiling of sugars and metabolites in the Culex pipiens’ crop is scarce, and only few studies used Liquid Chromatography – Mass Spectrometry (LC-MS), which provides broad detection for biomonitoring environmental substances and even contaminants in the sugar diet of mosquitoes populations.
Therefore, sugar and metabolite profiling were performed on crops obtained from mosquitoes exposed to plant nectar under laboratory or natural conditions by Ultra High-Performance LC-MS (UHPLC-MS). This method allowed us a precise quantitative and qualitative identification of sugar diet and associated environmental compounds in the crop of the mosquito C. pipiens. Under laboratory condition, mosquitoes were allowed to feed on either glucose solution, commercially-available flowers or field collected flowers. In addition, we collected mosquitoes from the field to compare those crop metabolomes with metabolome patterns occurring after nectar feeding in the lab.
The sugar quantities and quality obtained from the crops of mosquitoes collected in the field were similar to those crops obtained from mosquitoes that fed on commercially-available flowers and from field collected flowers with a limit of detection of 10 μg/L for sucrose, glucose and sucrose. Next to sugar compounds, we identified 2 types of amino acids, 12 natural products, and 9 pesticides.
Next to the diversity of sugar compounds, we could confirm that secondary metabolites and environmental pollutants are typically up taken from floral nectar sources by C. pipiens. The in-depth knowledge on mosquito–plant interactions may inspire the development and further optimization of mosquito trap systems and arboviral surveillance systems.
The human growth factor receptor MET is a receptor tyrosine kinase involved in cell proliferation, migration, and survival. MET is also hijacked by the intracellular pathogen Listeria monocytogenes. Its invasion protein, internalin B (InlB), binds to MET and promotes the formation of a signaling dimer that triggers the internalization of the pathogen. Here, we use a combination of structural biology, modeling, molecular dynamics simulations, and in situ single-molecule Förster resonance energy transfer (smFRET) experiments to elucidate the early events in MET activation by Listeria. Simulations show that InlB binding stabilizes MET in a conformation that promotes dimer formation. smFRET identifies the organization of the in situ signaling dimer. Further MD simulations of the dimer model are in quantitative agreement with smFRET. We accurately describe the structural dynamics underpinning an important cellular event and introduce a powerful methodological pipeline applicable to studying the activation of other plasma membrane receptors.