The extracellular matrix (ECM) is a complex and dynamic meshwork of cross-linked proteins that supports cell polarization and functions and tissue organization and homeostasis. Over the past few decades, mass-spectrometry-based proteomics has emerged as the method of choice to characterize the composition of the ECM of normal and diseased tissues. Here, we present a new release of MatrisomeDB, a searchable collection of curated proteomic data from 17 studies on the ECM of 15 different normal tissue types, six cancer types (different grades of breast cancers, colorectal cancer, melanoma, and insulinoma) and other diseases including vascular defects and lung and liver fibroses. MatrisomeDB (http://www.pepchem.org/matrisomedb) was built by retrieving raw mass spectrometry data files and reprocessing them using the same search parameters and criteria to allow for a more direct comparison between the different studies. The present release of MatrisomeDB includes 847 human and 791 mouse ECM proteoforms and over 350 000 human and 600 000 mouse ECM-derived peptide-to-spectrum matches. For each query, a hierarchically-clustered tissue distribution map, a peptide coverage map, and a list of post-translational modifications identified, are generated. MatrisomeDB is the most complete collection of ECM proteomic data to date and allows the building of a comprehensive ECM atlas.

The extracellular matrix (ECM) is a complex assembly of proteins that constitutes the scaffold organizing cells, tissues, and organs. Over the past decade, mass-spectrometry-based proteomics has become the method of choice to profile the composition of the ECM, or the matrisome, of tissues. To assist non-specialists with the reuse of ECM proteomic datasets, we released MatrisomeDB (https://matrisomedb.org) in 2020. Here, we report the expansion of the database to include 25 new curated studies on the ECM of 24 new tissues in addition to datasets on tissues previously included, more than doubling the size of the original database and achieving near-complete coverage of the in-silico predicted matrisome. We further enhanced data visualization by maps of peptides and post-translational-modifications detected onto domain-based representations and 3D structures of ECM proteins. We also referenced external resources to facilitate the design of targeted mass spectrometry assays. Last, we implemented an abstract-mining tool that generates an enrichment word cloud from abstracts of studies in which a queried protein is found with higher confidence and higher abundance relative to other studies in MatrisomeDB.

Biochemical studies suggested that the antimicrobial peptide apidaecin (Api) inhibits protein synthesis by binding in the nascent peptide exit tunnel and trapping the release factor associated with a terminating ribosome. The mode of Api action in bacterial cells had remained unknown. Here genome-wide analysis reveals that in bacteria, Api arrests translating ribosomes at stop codons and causes pronounced queuing of the trailing ribosomes. By sequestering the available release factors, Api promotes pervasive stop codon bypass, leading to the expression of proteins with C-terminal extensions. Api-mediated translation arrest leads to the futile activation of the ribosome rescue systems. Understanding the unique mechanism of Api action in living cells may facilitate the development of new medicines and research tools for genome exploration.

There has been much discussion of the potential desirability of macrocyclic molecules for the development of tool compounds and drug leads. But there is little experimental data comparing otherwise equivalent macrocyclic and linear compound libraries as a source of protein ligands. In this Letter, we probe this point in the context of peptoid libraries. Bead-displayed libraries of macrocyclic and linear peptoids containing four variable positions and 0–2 fixed residues, to vary the ring size, were screened against streptavidin and the affinity of every hit for the target was measured. The data show that macrocyclization is advantageous, but only when the ring contains 17 atoms, not 20 or 23 atoms. This technology will be useful for conducting direct comparisons between many different types of chemical libraries to determine their relative utility as a source of protein ligands.

Antenatal hypoxia caused epigenetic reprogramming of methylome and transcriptome in the developing heart and increased the risk of heart disease later in life. Herein, we investigated the impact of gestational hypoxia in proteome and metabolome in the hearts of fetus and adult offspring. Pregnant rats were treated with normoxia or hypoxia (10.5% O₂) from day 15 to 21 of gestation. Hearts were isolated from near-term fetuses and 5 month-old offspring, and proteomics and metabolomics profiling was determined. The data demonstrated that antenatal hypoxia altered proteomics and metabolomics profiling in the heart, impacting energy metabolism, lipid metabolism, oxidative stress, and inflammation-related pathways in a developmental and sex dependent manner. Of importance, integrating multi-omics data of transcriptomics, proteomics, and metabolomics profiling revealed reprogramming of the mitochondrion, especially in two clusters: (a) the cluster associated with “mitochondrial translation”/“aminoacyl t-RNA biosynthesis”/“one-carbon pool of folate”/“DNA methylation”; and (b) the cluster with “mitochondrion”/“TCA cycle and respiratory electron transfer”/“acyl-CoA dehydrogenase”/“oxidative phosphorylation”/“complex I”/“troponin myosin cardiac complex”. Our study provides a powerful means of multi-omics data integration and reveals new insights into phenotypic reprogramming of the mitochondrion in the developing heart by fetal hypoxia, contributing to an increase in the heart vulnerability to disease later in life.