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- 2D/3D imageanalysis (1)
- Biogene Amine (1)
- Black yeast (1)
- Chaetothyriales (1)
- Comparative genomics (1)
- Computed tomography (1)
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Organisationseinheit der BAM
- 1 Analytische Chemie; Referenzmaterialien (2)
- 1.3 Instrumentelle Analytik (2)
- 8 Zerstörungsfreie Prüfung (2)
- 8.0 Abteilungsleitung und andere (2)
- 5 Werkstofftechnik (1)
- 5.1 Mikrostruktur Design und Degradation (1)
- 5.2 Metallische Hochtemperaturwerkstoffe (1)
- 7 Bauwerkssicherheit (1)
- 7.7 Modellierung und Simulation (1)
- VP Vizepräsident (1)
The order Chaetothyriales (Pezizomycotina, Ascomycetes) harbours obligatorily melanised fungi and includes numerous etiologic agents of chromoblastomycosis, phaeohyphomycosis and other diseases of vertebrate hosts. Diseases range from mild cutaneous to fatal cerebral or disseminated infections and affect humans and cold-blooded animals globally. In addition, Chaetothyriales comprise species with aquatic, rock-inhabiting, ant-associated, and mycoparasitic life-styles, as well as species that tolerate toxic compounds, suggesting a high degree of versatile extremotolerance. To understand their biology and divergent niche occupation, we sequenced and annotated a set of 23 genomes of main the human opportunists within the Chaetothyriales as well as related environmental species. Our analyses included fungi with diverse life-styles, namely opportunistic pathogens and closely related saprobes, to identify genomic adaptations related to pathogenesis. Furthermore, ecological preferences of Chaetothyriales were analysed, in conjuncture with the order-level phylogeny based on conserved ribosomal genes. General characteristics, phylogenomic relationships, transposable elements, sex-related genes, protein family evolution, genes related to protein degradation (MEROPS), carbohydrate-active enzymes (CAZymes), melanin synthesis and secondary metabolism were investigated and compared between species. Genome assemblies varied from 25.81 Mb (Capronia coronata) to 43.03 Mb (Cladophialophora immunda). The bantiana-clade contained the highest number of predicted genes (12 817 on average) as well as larger genomes. We found a low content of mobile elements, with DNA transposons from Tc1/Mariner superfamily being the most abundant across analysed species. Additionally, we identified a reduction of carbohydrate degrading enzymes, specifically many of the Glycosyl Hydrolase (GH) class, while most of the Pectin Lyase (PL) genes were lost in etiological agents of chromoblastomycosis and phaeohyphomycosis. An expansion was found in protein degrading peptidase enzyme families S12 (serine-type D-Ala-D-Ala carboxypeptidases) and M38 (isoaspartyl dipeptidases). Based on genomic information, a wide range of abilities of melanin biosynthesis was revealed; genes related to metabolically distinct DHN, DOPA and pyomelanin pathways were identified. The MAT (MAting Type) locus and other sexrelated genes were recognized in all 23 black fungi. Members of the asexual genera Fonsecaea and Cladophialophora appear to be heterothallic with a single copy of either MAT-1-1 or MAT-1-2 in each individual. All Capronia species are homothallic as both MAT1-1 and MAT1-2 genes were found in each single genome. The genomic synteny of the MAT-locus flanking genes (SLA2-APN2-COX13) is not conserved in black fungi as is commonly observed in Eurotiomycetes, indicating a unique genomic context for MAT in those species. The heterokaryon (het) genes expansion associated with the low selective pressure at the MAT-locus suggests that a parasexual cycle may play an important role in generating diversity among those fungi.
Sensory hybrid host materials for the selective chromo-fluorogenic detection of biogenic amines
(2006)
A method for the analysis of Pt–protein complexes in biological samples, previously subjected to cisplatin treatment, has been developed. Proteins were separated by gel electrophoresis, and those bound to Pt were detected with high sensitivity by LA-ICP-(SF)-MS. Pt-containing spots were in-gel digested with trypsin, and the peptides produced identified using nHPLC-ESI-LTQ-FT-MS/MS. The influence of protein separation conditions, staining and gel processing prior to laser ablation on Ptprotein bonds preservation have been evaluated using standard proteins incubated with cisplatin. 2-DE separation under non-reducing conditions followed by either Coomassie blue brilliant or silver staining is appropriate for Pt–protein complexes, achieving a good separating resolution of the proteins in biological samples. Direct LA-ICP-MS analysis of glycerol-treated dried gels for Pt–protein monitoring resulted in better sensitivity, more reliable relative Pt signals and a simpler and less time-consuming approach compared to the analysis of blotted membranes. Ablation of gels allowed tackling protein identification of Pt-spots in the remaining non-ablated material in the gel, making it unnecessary to run several gels in parallel for separate Pt detection and protein identification. By using this approach, Pt coordinated to proteins, such as α-2-macroglobulin, transferrin, albumin or hemoglobin, was detected in the serum from a rat treated in vivo with cisplatin after nrSDS-PAGE separation. Furthermore, the first complete LA-ICP-MS metalloprotein contour map in a 2-DE gel has been produced, in this case for the detection of Pt–protein complexes in renal proximal tubule epithelial cells (RPTECs) incubated with cisplatin. Several proteins were identified in those spots containing Pt, which may have a connection with the drug-induced nephrotoxicity mainly affecting this cell type in the kidney.
Coarsening of grain-refined semi-solid Al-Ge32 alloy: X-ray microtomography and in situ radiography
(2007)
A laser ablation inductively coupled plasma mass spectrometry (LA–ICP–MS)-based methodology is presented for Pt, Cu, and Zn bioimaging on whole kidney 3 µm sagittal sections from rats treated with pharmacological doses of cisplatin, which were sacrificed once renal damage had taken place. Pt turned out to accumulate in the kidney cortex and corticomedullary junction, corresponding to areas where the proximal tubule S3 segments (the most sensitive cells to cisplatin nephrotoxicity) are located. This demonstrates the connection between platinum accumulation and renal damage proved by histological examination of HE-stained sections and evaluation of serum and urine biochemical parameters. Cu and Zn distribution maps revealed a significant displacement in cells by Pt, as compared to control tissues. A dramatic decrease in the Pt accumulation in the cortex was observed when cilastatin was coadministered with cisplatin, which can be related to its nephroprotective effect. Excellent imaging reproducibility, sensitivity (LOD 50 fg), and resolution (down to 8 µm) were achieved, demonstrating that LA–ICP–MS can be applied as a microscopic metal detector at cellular level in certain tissues. A simple and quick approach for the estimation of Pt tissue levels was proposed, based on tissue spiking.
Inelastic neutron scattering for investigating the dynamics of confined glass-forming liquids
(2005)
Inelastic neutron scattering was employed over recent years to investigate the influence of spatial confinement on the dynamics of glass-forming systems. We review the common phenomena observed by neutron scattering in such different confining hosts like porous glasses, molecular sieves, clays or free standing polymer films, which impose a spatial limitation to the motion of small organic molecules, oligomers or polymers. Near the glass transition temperature the mean squared displacements of the confined molecules show clear deviations from the bulk behavior. The observed increase or decrease of the mean squared displacements confirms the high relevance of the interface interaction near walls of confining media without excluding additional real confinement effects. We show a new comparison of the mean squared displacement for PDMS and PMPS in bulk and in different type of restricting geometries, which evidence a weak influence of the restricting geometry on the local methyl group motion, but a strong influence on the glass transition dynamics, if wall interactions are taken into account. Strong wall interaction is also supported by the intermediate scattering function, measured either by combining neutron backscattering and time-of-flight experiments to cover 3 decades in time from ns to ps or by neutron spin echo, which reveal above Tg an increasing elastic fraction with decreasing pore size and a slowing down of the dynamics. Furthermore we show that a reduction of modes below the Boson peak frequency is a more general feature of confined glass-forming systems.
Incomplete tomographic data sets such as limited view (missing wedge) data represent a well-known challenge
for reconstruction algorithms, since they unavoidably lead to substantial image artefacts. Such data sets may
occur in industrial computed tomography of limited access (e.g. extended components, fixed objects), directional
opacity, limited sample life time or laminographic set-up. We present strategies to effectively suppress the
typical elongation artefacts (e.g. lemon-like deformed pores) by our iterative algorithm DIRECTT which offers
the opportunity to vary the versatile reconstruction parameters within each cycle. Those strategies are applied to
experimental data obtained from metallic foams as well as model simulations. Comparison is drawn to state-ofthe-
art techniques (filtered backprojection and algebraic techniques). Further reference is made to reconstructions
of complete data sets serving as gold standards. For quantitative assessment of the reconstruction
quality adapted techniques based on spatial statistics are introduced.
Living organisms constantly interact with their environment, including through the exchange of gases. Respiration and the release and uptake of volatile organic compounds (VOCs) create dynamic microenvironments in biological systems. Studying the kinetics of volatiles in biological systems requires expensive instruments, and data analysis is challenging. Therefore, we aimed to design a minimal analytical device for measuring the composition of gaseous mixtures in realtime.
We built the ‘Modular Biological Mass Spectrometer’ (MoBiMS) from 3D-printed parts and custom sensors to fit a wide array of experimental set-ups. We tested the chemical detection range and temporal resolution of the MoBiMS employing pure compounds and complex biological samples.
Compounds with a higher than 0.4 mmHg vapor pressure and a molecular weight up to 154 g/mol were reliably sensed within seconds. The generated electron impact (EI) spectra were directly comparable with standard databases like the NIST EI library. Under a direct analysis approach, the MoBiMS identified the characteristic odor of banana (Musa sp.), that is, isoamyl acetate; tracked the dynamics of CO2 release while the Alka-Seltzer® reaction occurred showed the kinetics of the transient production and consumption of carbon dioxide during photosynthesis. MoBiMS also discriminated between volatile compounds ions coming from tobacco (Nicotiana benthamiana) leaves and the surrounding air through untargeted analysis. The small footprint of the MoBiMS and its relatively low energy consumption facilitate in situ analyses, as an additional gas supply is not necessary with EI ionization. The MoBiMS is easy to assemble, and its construction and operation are very cost-efficient compared to commercial devices. The analytical performance of the MoBiMS is suitable for real-time studies of biological systems, environmental monitoring, and medical diagnostics.
The amount of data generated worldwide is constantly increasing. These data come from a wide variety of sources and systems, are processed differently, have a multitude of formats, and are stored in an untraceable and unstructured manner, predominantly in natural language in data silos. This problem can be equally applied to the heterogeneous research data from materials science and engineering. In this domain, ways and solutions are increasingly being generated to smartly link material data together with their contextual information in a uniform and well-structured manner on platforms, thus making them discoverable, retrievable, and reusable for research and industry. Ontologies play a key role in this context. They enable the sustainable representation of expert knowledge and the semantically structured filling of databases with computer-processable data triples.
In this perspective article, we present the project initiative Materials-open-Laboratory (Mat-o-Lab) that aims to provide a collaborative environment for domain experts to digitize their research results and processes and make them fit for data-driven materials research and development. The overarching challenge is to generate connection points to further link data from other domains to harness the promised potential of big materials data and harvest new knowledge.
With 8% of man-made CO2 emissions, cement production is an important driver of the climate crisis. By using alkali-activated binders, part of the energy-intensive clinker production process can be dispensed. However, as numerous raw materials are involved in the manufacturing process here, the complexity of the materials increases by orders of magnitude. Finding a properly balanced binder formulation is like looking for a needle in a haystack. We have shown for the first time that artificial intelligence (AI)-based optimization of alkali-activated binder formulations can significantly accelerate research.
The "Sequential Learning App for Materials Discovery" (SLAMD) aims to accelerate practice transfer. With SLAMD, materials scientists have low-threshold access to AI through interactive and intuitive user interfaces. The value added by AI can be determined directly. For example, the CO2 emissions saved per ton of cement can be determined for each development cycle: the more efficient the AI optimization, the greater the savings.
Our material database already includes more than 120,000 data points of alternative binders and is constantly being expanded with new parameters. We are currently driving the enrichment of the data with a life cycle analysis of the building materials.
Based on a case study we show how intuitive access to AI can drive the adoption of techniques that make a real contribution to the development of resource-efficient and sustainable building materials of the future and make it easy to identify when classical experiments are more efficient.