ProteomicsDB (https://www.ProteomicsDB.org) started as a protein-centric in-memory database for the exploration of large collections of quantitative mass spectrometry-based proteomics data. The data types and contents grew over time to include RNA-Seq expression data, drug-target interactions and cell line viability data. In this manuscript, we summarize new developments since the previous update that was published in Nucleic Acids Research in 2017. Over the past two years, we have enriched the data content by additional datasets and extended the platform to support protein turnover data. Another important new addition is that ProteomicsDB now supports the storage and visualization of data collected from other organisms, exemplified by Arabidopsis thaliana. Due to the generic design of ProteomicsDB, all analytical features available for the original human resource seamlessly transfer to other organisms. Furthermore, we introduce a new service in ProteomicsDB which allows users to upload their own expression datasets and analyze them alongside with data stored in ProteomicsDB. Initially, users will be able to make use of this feature in the interactive heat map functionality as well as the drug sensitivity prediction, but ultimately will be able to use all analytical features of ProteomicsDB in this way.

The microbiome has a strong impact on human health and disease and is, therefore, increasingly studied in a clinical context. Metaproteomics is also attracting considerable attention, and such data can be efficiently generated today owing to improvements in mass spectrometry-based proteomics. As we will discuss in this study, there are still major challenges notably in data analysis that need to be overcome. Here, we analyzed 212 fecal samples from 56 hospitalized acute leukemia patients with multidrug-resistant Enterobactericeae (MRE) gut colonization using metagenomics and metaproteomics. This is one of the largest clinical metaproteomic studies to date, and the first metaproteomic study addressing the gut microbiome in MRE colonized acute leukemia patients. Based on this substantial data set, we discuss major current limitations in clinical metaproteomic data analysis to provide guidance to researchers in the field. Notably, the results show that public metagenome databases are incomplete and that sample-specific metagenomes improve results. Furthermore, biological variation is tremendous which challenges clinical study designs and argues that longitudinal measurements of individual patients are a valuable future addition to the analysis of patient cohorts.

Most molecular cancer therapies act on protein targets but data on the proteome status of patients and cellular models for proteome‐guided pre‐clinical drug sensitivity studies are only beginning to emerge. Here, we profiled the proteomes of 65 colorectal cancer (CRC) cell lines to a depth of > 10,000 proteins using mass spectrometry. Integration with proteomes of 90 CRC patients and matched transcriptomics data defined integrated CRC subtypes, highlighting cell lines representative of each tumour subtype. Modelling the responses of 52 CRC cell lines to 577 drugs as a function of proteome profiles enabled predicting drug sensitivity for cell lines and patients. Among many novel associations, MERTK was identified as a predictive marker for resistance towards MEK1/2 inhibitors and immunohistochemistry of 1,074 CRC tumours confirmed MERTK as a prognostic survival marker. We provide the proteomic and pharmacological data as a resource to the community to, for example, facilitate the design of innovative prospective clinical trials.

A novel 1D polymeric copper( ii ) complex of formula {[Cu( l -Arg) ₂ (μ-4,4′-bpy)]Cl ₂ ·3H ₂ O _∞ } was synthesized and characterized using X-ray diffraction, FT-IR, Raman, electron paramagnetic resonance and NIR- vis -UV spectroscopy, and its microbiological properties were analyzed.

It was suggested that minor differences in the structure of FimH are most likely associated with differences in its adhesion specificities and may determine the tropism of various Salmonella serovars to different species and tissues. We have recently shown that FimH adhesins from host-adapted serovars, e.g., Salmonella Choleraesuis (SCh), bind to other glycoprotein receptors compared to FimH from host-unrestricted Salmonella Enteritidis (SE). Here we identify porcine calreticulin expressed by swine intestinal cells as a host-specific receptor for SCh FimH adhesin, suggesting that such an interaction may contribute to SCh host specificity. Calreticulin was identified by 2D electrophoresis and mass spectrometry as a glycoprotein that was bound specifically by recombinant SCh FimH protein, but not by FimH from SE. The functionality of calreticulin as a specific receptor of SCh FimH adhesin was further confirmed by adhesion and invasion of mutated strains of SCh carrying different variants of FimH proteins to IPEC-J2 cells with overexpression and silenced expression of calreticulin. It was found that SCh carrying the active variant of FimH adhered and invaded IPEC-J2 cells with calreticulin overexpression at significantly higher numbers and IPEC-J2 with silenced expression with lower numbers than those of SCh expressing the non-active variant or SE variant of FimH. Furthermore, we observed that SCh infection induces translocation of calreticulin to cell membrane. All of the aforementioned results lead to the general conclusion that Salmonella host specificity requires not only special mechanisms and proteins expressed by the pathogen but also specifically recognized receptors expressed by a specific host.