Quasiparticle interfacial level alignment of highly hybridized frontier levels: H2_2O on TiO2_2(110)

Knowledge of the frontier levels' alignment prior to photo-irradiation is necessary to achieve a complete quantitative description of H$_2$O photocatalysis on TiO$_2$(110). Although H$_2$O on rutile TiO$_2$(110) has been thoroughly studied both experimentally and theoretically, a quantitative value for the energy of the highest H$_2$O occupied levels is still lacking. For experiment, this is due to the H$_2$O levels being obscured by hybridization with TiO$_2$(110) levels in the difference spectra obtained via ultraviolet photoemission spectroscopy (UPS). For theory, this is due to inherent difficulties in properly describing many-body effects at the H$_2$O-TiO$_2$(110) interface. Using the projected density of states (DOS) from state-of-the-art quasiparticle (QP) $G_0W_0$, we disentangle the adsorbate and surface contributions to the complex UPS spectra of H$_2$O on TiO$_2$(110). We perform this separation as a function of H$_2$O coverage and dissociation on stoichiometric and reduced surfaces. Due to hybridization with the TiO$_2$(110) surface, the H$_2$O 3a$_1$ and 1b$_1$ levels are broadened into several peaks between 5 and 1 eV below the TiO$_2$(110) valence band maximum (VBM). These peaks have both intermolecular and interfacial bonding and antibonding character. We find the highest occupied levels of H$_2$O adsorbed intact and dissociated on stoichiometric TiO$_2$(110) are 1.1 and 0.9 eV below the VBM. We also find a similar energy of 1.1 eV for the highest occupied levels of H$_2$O when adsorbed dissociatively on a bridging O vacancy of the reduced surface. In both cases, these energies are significantly higher (by 0.6 to 2.6 eV) than those estimated from UPS difference spectra, which are inconclusive in this energy region. Finally, we apply self-consistent QP$GW$ (scQP$GW$1) to obtain the ionization potential of the H$_2$O-TiO$_2$(110) interface.Comment: 12 pages, 12 figures, 1 tabl

CORUM: the comprehensive resource of mammalian protein complexes

Protein complexes are key molecular entities that integrate multiple gene products to perform cellular functions. The CORUM (http://mips.gsf.de/genre/proj/corum/index.html) database is a collection of experimentally verified mammalian protein complexes. Information is manually derived by critical reading of the scientific literature from expert annotators. Information about protein complexes includes protein complex names, subunits, literature references as well as the function of the complexes. For functional annotation, we use the FunCat catalogue that enables to organize the protein complex space into biologically meaningful subsets. The database contains more than 1750 protein complexes that are built from 2400 different genes, thus representing 12% of the protein-coding genes in human. A web-based system is available to query, view and download the data. CORUM provides a comprehensive dataset of protein complexes for discoveries in systems biology, analyses of protein networks and protein complex-associated diseases. Comparable to the MIPS reference dataset of protein complexes from yeast, CORUM intends to serve as a reference for mammalian protein complexes

Towards a multisensor station for automated biodiversity monitoring

Rapid changes of the biosphere observed in recent years are caused by both small and large scale drivers, like shifts in temperature, transformations in land-use, or changes in the energy budget of systems. While the latter processes are easily quantifiable, documentation of the loss of biodiversity and community structure is more difficult. Changes in organismal abundance and diversity are barely documented. Censuses of species are usually fragmentary and inferred by often spatially, temporally and ecologically unsatisfactory simple species lists for individual study sites. Thus, detrimental global processes and their drivers often remain unrevealed. A major impediment to monitoring species diversity is the lack of human taxonomic expertise that is implicitly required for large-scale and fine-grained assessments. Another is the large amount of personnel and associated costs needed to cover large scales, or the inaccessibility of remote but nonetheless affected areas. To overcome these limitations we propose a network of Automated Multisensor stations for Monitoring of species Diversity (AMMODs) to pave the way for a new generation of biodiversity assessment centers. This network combines cutting-edge technologies with biodiversity informatics and expert systems that conserve expert knowledge. Each AMMOD station combines autonomous samplers for insects, pollen and spores, audio recorders for vocalizing animals, sensors for volatile organic compounds emitted by plants (pVOCs) and camera traps for mammals and small invertebrates. AMMODs are largely self-containing and have the ability to pre-process data (e.g. for noise filtering) prior to transmission to receiver stations for storage, integration and analyses. Installation on sites that are difficult to access require a sophisticated and challenging system design with optimum balance between power requirements, bandwidth for data transmission, required service, and operation under all environmental conditions for years. An important prerequisite for automated species identification are databases of DNA barcodes, animal sounds, for pVOCs, and images used as training data for automated species identification. AMMOD stations thus become a key component to advance the field of biodiversity monitoring for research and policy by delivering biodiversity data at an unprecedented spatial and temporal resolution. (C) 2022 Published by Elsevier GmbH on behalf of Gesellschaft fur Okologie

The BridgeDb framework: standardized access to gene, protein and metabolite identifier mapping services

BACKGROUND: Many complementary solutions are available for the identifier mapping problem. This creates an opportunity for bioinformatics tool developers. Tools can be made to flexibly support multiple mapping services or mapping services could be combined to get broader coverage. This approach requires an interface layer between tools and mapping services. RESULTS: Here we present BridgeDb, a software framework for gene, protein and metabolite identifier mapping. This framework provides a standardized interface layer through which bioinformatics tools can be connected to different identifier mapping services. This approach makes it easier for tool developers to support identifier mapping. Mapping services can be combined or merged to support multi-omics experiments or to integrate custom microarray annotations. BridgeDb provides its own ready-to-go mapping services, both in webservice and local database forms. However, the framework is intended for customization and adaptation to any identifier mapping service. BridgeDb has already been integrated into several bioinformatics applications. CONCLUSION: By uncoupling bioinformatics tools from mapping services, BridgeDb improves capability and flexibility of those tools. All described software is open source and available at http://www.bridgedb.org

Current Status and Future Prospects of Next-Generation Data Management and Analytical Decision Support Tools for Enhancing Genetic Gains in Crops

Agricultural disciplines are becoming data intensive and the agricultural research data generation technologies are becoming sophisticated and high throughput. On the one hand, high-throughput genotyping is generating petabytes of data; on the other hand, high-throughput phenotyping platforms are also generating data of similar magnitude. Under modern integrated crop breeding, scientists are working together by integrating genomic and phenomic data sets of huge data volumes on a routine basis. To manage such huge research data sets and use them appropriately in decision making, Data Management Analysis & Decision Support Tools (DMASTs) are a prerequisite. DMASTs are required for a range of operations including generating the correct breeding experiments, maintaining pedigrees, managing phenotypic data, storing and retrieving high-throughput genotypic data, performing analytics, including trial analysis, spatial adjustments, identifications of MTAs, predicting Genomic Breeding Values (GEBVs), and various selection indices. DMASTs are also a prerequisite for understanding trait dynamics, gene action, interactions, biology, GxE, and various other factors contributing to crop improvement programs by integrating data generated from various science streams. These tools have simplified scientists’ lives and empowered them in terms of data storage, data retrieval, data analytics, data visualization, and sharing with other researchers and collaborators. This chapter focuses on availability, uses, and gaps in present-day DMASTs

ESTs in Plants: Where Are We Heading?

Expressed sequence tags (ESTs) are the most important resources for transcriptome exploration. Next-generation sequencing technologies have been generating gigabytes of genetic codes representing genes, partial and whole genomes most of which are EST datasets. Niche of EST in plants for breeding, regulation of gene expression through miRNA studies, and their application for adapting to climatic changes are discussed. Some of the recent tools for analysis of EST exclusive to plants are listed out. Systems biology though in its infancy in plants has influenced EST mapping for unraveling gene regulatory circuits, which is illustrated with a few significant examples. This review throws a glance at the evolving role of ESTs in plants

Development of the first marmoset-specific DNA microarray (EUMAMA): a new genetic tool for large-scale expression profiling in a non-human primate.

Contains fulltext : 185803.pdf (publisher's version ) (Open Access)BACKGROUND: The common marmoset monkey (Callithrix jacchus), a small non-endangered New World primate native to eastern Brazil, is becoming increasingly used as a non-human primate model in biomedical research, drug development and safety assessment. In contrast to the growing interest for the marmoset as an animal model, the molecular tools for genetic analysis are extremely limited. RESULTS: Here we report the development of the first marmoset-specific oligonucleotide microarray (EUMAMA) containing probe sets targeting 1541 different marmoset transcripts expressed in hippocampus. These 1541 transcripts represent a wide variety of different functional gene classes. Hybridisation of the marmoset microarray with labelled RNA from hippocampus, cortex and a panel of 7 different peripheral tissues resulted in high detection rates of 85% in the neuronal tissues and on average 70% in the non-neuronal tissues. The expression profiles of the 2 neuronal tissues, hippocampus and cortex, were highly similar, as indicated by a correlation coefficient of 0.96. Several transcripts with a tissue-specific pattern of expression were identified. Besides the marmoset microarray we have generated 3215 ESTs derived from marmoset hippocampus, which have been annotated and submitted to GenBank [GenBank: EF214838-EF215447, EH380242-EH382846]. CONCLUSION: We have generated the first marmoset-specific DNA microarray and demonstrated its use to characterise large-scale gene expression profiles of hippocampus but also of other neuronal and non-neuronal tissues. In addition, we have generated a large collection of ESTs of marmoset origin, which are now available in the public domain. These new tools will facilitate molecular genetic research into this non-human primate animal model

Why It Is Time to Look Beyond Algal Genes in Photosynthetic Slugs

Eukaryotic organelles depend on nuclear genes to perpetuate their biochemical integrity. This is true for mitochondria in all eukaryotes and plastids in plants and algae. Then how do kleptoplasts, plastids that are sequestered by some sacoglossan sea slugs, survive in the animals digestive gland cells in the absence of the algal nucleus encoding the vast majority of organellar proteins? For almost two decades, lateral gene transfer (LOT) from algae to slugs appeared to offer a solution, but RNA-seq analysis, later supported by genome sequencing of slug DNA, failed to find any evidence for such LOT events. Yet, isolated reports continue to be published and are readily discussed by the popular press and social media, making the data on LGT and its support for kleptoplast longevity appear controversial. However, when we take a sober look at the methods used, we realize that caution is warranted in how the results are interpreted. There is no evidence that the evolution of kleptoplasty in sea slugs involves LOT events. Based on what we know about photosystem maintenance in embryophyte plastids, we assume kleptoplasts depend on nuclear genes. However, studies have shown that some isolated algal plastids are, by nature, more robust than those of land plants. The evolution of kleptoplasty in green sea slugs involves many promising and unexplored phenomena, but there is no evidence that any of these require the expression of slug genes of algal origin