Management system for building materials as a basis for closed loop material flow analysis considering material efficiency and climate change mitigation

Resource management is becoming increasingly important in the construction sector. In order to support the recycling of materials, it is necessary to determine the quantities in the building stock and those caused by construction activities. At present, a large number of different actors use different categories for construction materials and the raw materials they consist of as well as for waste categories, depending on their field of activity. This results in imprecisions that make it difficult to consistently track and influence mass flows and hinder targeted resource management. This is the starting point of this paper as it discusses possibilities to establish a consistent allocation of materials to context-typical groups following the approach of continuous material flow analysis. On the input-side, aspects of mineral planning and on the output-side aspects of waste and secondary raw material management are being considered and references to grey emissions are established along the entire process chain. In this way, cross-departmental planning relating to recycling management and climate protection will be supported. With regard to the object of consideration and the level of action, a distinction is made between two different spatial scale levels: on the one hand, the individual building level, where the material inventory approach is used to provide detailed information on the building\u27s material composition, and on the other hand the regional level, for which more aggregated information on building material groups is provided in the form of material cadastres. Current results of a research project in Germany are presented

Targeted online liquid chromatography electron capture dissociation mass spectrometry for the localization of sites of in vivo phosphorylation in human Sprouty2

We demonstrate a strategy employing collision-induced dissociation for phosphopeptide discovery, followed by targeted electron capture dissociation (ECD) for site localization. The high mass accuracy and low background noise of the ECD mass spectra allow facile sequencing of coeluting isobaric phosphopeptides, with up to two isobaric phosphopeptides sequenced from a single mass spectrum. In contrast to the previously described neutral loss of dependent ECD method, targeted ECD allows analysis of both phosphotyrosine peptides and lower abundance phosphopeptides. The approach was applied to phosphorylation analysis of human Sprouty2, a regulator of receptor tyrosine kinase signaling. Fifteen sites of phosphorylation were identified, 11 of which are novel

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

This work was in part supported by the PRIME-XS project, grant agreement number 262067, funded by the European Union seventh Framework Programme; The Netherlands Proteomics Centre, embedded in The Netherlands Genomics Initiative; The Netherlands Bioinformatics Centre; and the Centre for Biomedical Genetics (to S.C., B.B. and A.J.R.H); by NIH grants NCRR RR001614 and RR019934 (to the UCSF Mass Spectrometry Facility, director: A.L. Burlingame, P.B.); and by grants from the MRC, CR-UK, BBSRC and Barts and the London Charity (to P.C.

Stable Isotope Metabolic Labeling with a Novel 15N-Enriched Bacteria Diet for Improved Proteomic Analyses of Mouse Models for Psychopathologies

The identification of differentially regulated proteins in animal models of psychiatric diseases is essential for a comprehensive analysis of associated psychopathological processes. Mass spectrometry is the most relevant method for analyzing differences in protein expression of tissue and body fluid proteomes. However, standardization of sample handling and sample-to-sample variability are problematic. Stable isotope metabolic labeling of a proteome represents the gold standard for quantitative mass spectrometry analysis. The simultaneous processing of a mixture of labeled and unlabeled samples allows a sensitive and accurate comparative analysis between the respective proteomes. Here, we describe a cost-effective feeding protocol based on a newly developed 15N bacteria diet based on Ralstonia eutropha protein, which was applied to a mouse model for trait anxiety. Tissue from 15N-labeled vs. 14N-unlabeled mice was examined by mass spectrometry and differences in the expression of glyoxalase-1 (GLO1) and histidine triad nucleotide binding protein 2 (Hint2) proteins were correlated with the animals' psychopathological behaviors for methodological validation and proof of concept, respectively. Additionally, phenotyping unraveled an antidepressant-like effect of the incorporation of the stable isotope 15N into the proteome of highly anxious mice. This novel phenomenon is of considerable relevance to the metabolic labeling method and could provide an opportunity for the discovery of candidate proteins involved in depression-like behavior. The newly developed 15N bacteria diet provides researchers a novel tool to discover disease-relevant protein expression differences in mouse models using quantitative mass spectrometry

High-resolution maps of material stocks in buildings and infrastructures in Austria and Germany

The dynamics of societal material stocks such as buildings and infrastructures and their spatial patterns drive surging resource use and emissions. Two main types of data are currently used to map stocks, night-time lights (NTL) from Earth-observing (EO) satellites and cadastral information. We present an alternative approach for broad-scale material stock mapping based on freely available high-resolution EO imagery and OpenStreetMap data. Maps of built-up surface area, building height, and building types were derived from optical Sentinel-2 and radar Sentinel-1 satellite data to map patterns of material stocks for Austria and Germany. Using material intensity factors, we calculated the mass of different types of buildings and infrastructures, distinguishing eight types of materials, at 10 m spatial resolution. The total mass of buildings and infrastructures in 2018 amounted to ∼5 Gt in Austria and ∼38 Gt in Germany (AT: ∼540 t/cap, DE: ∼450 t/cap). Cross-checks with independent data sources at various scales suggested that the method may yield more complete results than other data sources but could not rule out possible overestimations. The method yields thematic differentiations not possible with NTL, avoids the use of costly cadastral data, and is suitable for mapping larger areas and tracing trends over time

Hydrophilic interaction liquid chromatography (HILIC) in proteomics

In proteomics, nanoflow multidimensional chromatography is now the gold standard for the separation of complex mixtures of peptides as generated by in-solution digestion of whole-cell lysates. Ideally, the different stationary phases used in multidimensional chromatography should provide orthogonal separation characteristics. For this reason, the combination of strong cation exchange chromatography (SCX) and reversed-phase (RP) chromatography is the most widely used combination for the separation of peptides. Here, we review the potential of hydrophilic interaction liquid chromatography (HILIC) as a separation tool in the multidimensional separation of peptides in proteomics applications. Recent work has revealed that HILIC may provide an excellent alternative to SCX, possessing several advantages in the area of separation power and targeted analysis of protein post-translational modifications

Differential Proteomic Analysis of Mammalian Tissues Using SILAM

Differential expression of proteins between tissues underlies organ-specific functions. Under certain pathological conditions, this may also lead to tissue vulnerability. Furthermore, post-translational modifications exist between different cell types and pathological conditions. We employed SILAM (Stable Isotope Labeling in Mammals) combined with mass spectrometry to quantify the proteome between mammalian tissues. Using 15N labeled rat tissue, we quantified 3742 phosphorylated peptides in nuclear extracts from liver and brain tissue. Analysis of the phosphorylation sites revealed tissue specific kinase motifs. Although these tissues are quite different in their composition and function, more than 500 protein identifications were common to both tissues. Specifically, we identified an up-regulation in the brain of the phosphoprotein, ZFHX1B, in which a genetic deletion causes the neurological disorder Mowat–Wilson syndrome. Finally, pathway analysis revealed distinct nuclear pathways enriched in each tissue. Our findings provide a valuable resource as a starting point for further understanding of tissue specific gene regulation and demonstrate SILAM as a useful strategy for the differential proteomic analysis of mammalian tissues

Network Evolution: Rewiring and Signatures of Conservation in Signaling

The analysis of network evolution has been hampered by limited availability of protein interaction data for different organisms. In this study, we investigate evolutionary mechanisms in Src Homology 3 (SH3) domain and kinase interaction networks using high-resolution specificity profiles. We constructed and examined networks for 23 fungal species ranging from Saccharomyces cerevisiae to Schizosaccharomyces pombe. We quantify rates of different rewiring mechanisms and show that interaction change through binding site evolution is faster than through gene gain or loss. We found that SH3 interactions evolve swiftly, at rates similar to those found in phosphoregulation evolution. Importantly, we show that interaction changes are sufficiently rapid to exhibit saturation phenomena at the observed timescales. Finally, focusing on the SH3 interaction network, we observe extensive clustering of binding sites on target proteins by SH3 domains and a strong correlation between the number of domains that bind a target protein (target in-degree) and interaction conservation. The relationship between in-degree and interaction conservation is driven by two different effects, namely the number of clusters that correspond to interaction interfaces and the number of domains that bind to each cluster leads to sequence specific conservation, which in turn results in interaction conservation. In summary, we uncover several network evolution mechanisms likely to generalize across peptide recognition modules