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Organ-specific proteins (OSPs) possess great medical potential both in clinics and in biomedical research. Applications of them—such as alanine transaminase, aspartate transaminase, and troponins—in clinics have raised certain concerns of their organ specificity. The dynamics and diversity of protein expression in heterogeneous human populations are well known, yet their effects on OSPs are less addressed. Here, we used mice as a model and implemented a breadth study to examine the panorgan proteome for potential variations in organ specificity in different genetic backgrounds. Using reasonable resources, we generated panorgan proteomes of four in-bred mouse strains. The results revealed a large diversity that was more profound among OSPs than among proteomes overall. We defined a robustness score to quantify such variation and derived three sets of OSPs with different stringencies. In the meantime, we found that the enriched biological functions of OSPs are also organ-specific and are sensitive and useful to assess the quality of OSPs. We hope our breadth study can open doors to explore the molecular diversity and dynamics of organ specificity at the protein level.

Plants are essential for life and are extremely diverse organisms with unique molecular capabilities 1 . Here we present a quantitative atlas of the transcriptomes, proteomes and phosphoproteomes of 30 tissues of the model plant Arabidopsis thaliana . Our analysis provides initial answers to how many genes exist as proteins (more than 18,000), where they are expressed, in which approximate quantities (a dynamic range of more than six orders of magnitude) and to what extent they are phosphorylated (over 43,000 sites). We present examples of how the data may be used, such as to discover proteins that are translated from short open-reading frames, to uncover sequence motifs that are involved in the regulation of protein production, and to identify tissue-specific protein complexes or phosphorylation-mediated signalling events. Interactive access to this resource for the plant community is provided by the ProteomicsDB and ATHENA databases, which include powerful bioinformatics tools to explore and characterize Arabidopsis proteins, their modifications and interactions. A quantitative atlas of the transcriptomes, proteomes and phosphoproteomes of 30 tissues of the model plant Arabidopsis thaliana provides a valuable resource for plant research.

The sequencing of ancient DNA has enabled the reconstruction of speciation, migration and admixture events for extinct taxa 1 . However, the irreversible post-mortem degradation 2 of ancient DNA has so far limited its recovery—outside permafrost areas—to specimens that are not older than approximately 0.5 million years (Myr) 3 . By contrast, tandem mass spectrometry has enabled the sequencing of approximately 1.5-Myr-old collagen type I 4 , and suggested the presence of protein residues in fossils of the Cretaceous period 5 —although with limited phylogenetic use 6 . In the absence of molecular evidence, the speciation of several extinct species of the Early and Middle Pleistocene epoch remains contentious. Here we address the phylogenetic relationships of the Eurasian Rhinocerotidae of the Pleistocene epoch 7 – 9 , using the proteome of dental enamel from a Stephanorhinus tooth that is approximately 1.77-Myr old, recovered from the archaeological site of Dmanisi (South Caucasus, Georgia) 10 . Molecular phylogenetic analyses place this Stephanorhinus as a sister group to the clade formed by the woolly rhinoceros ( Coelodonta antiquitatis ) and Merck’s rhinoceros ( Stephanorhinus kirchbergensis ). We show that Coelodonta evolved from an early Stephanorhinus lineage, and that this latter genus includes at least two distinct evolutionary lines. The genus Stephanorhinus is therefore currently paraphyletic, and its systematic revision is needed. We demonstrate that sequencing the proteome of Early Pleistocene dental enamel overcomes the limitations of phylogenetic inference based on ancient collagen or DNA. Our approach also provides additional information about the sex and taxonomic assignment of other specimens from Dmanisi. Our findings reveal that proteomic investigation of ancient dental enamel—which is the hardest tissue in vertebrates 11 , and is highly abundant in the fossil record—can push the reconstruction of molecular evolution further back into the Early Pleistocene epoch, beyond the currently known limits of ancient DNA preservation. Palaeoproteomic analysis of dental enamel from an Early Pleistocene Stephanorhinus resolves the phylogeny of Eurasian Rhinocerotidae, by enabling the reconstruction of molecular evolution beyond the limits of ancient DNA preservation.

Compartmentalization is a defining characteristic of eukaryotic cells, and partitions distinct biochemical processes into discrete subcellular locations. Microscopy 1 and biochemical fractionation coupled with mass spectrometry 2 – 4 have defined the proteomes of a variety of different organelles, but many intracellular compartments have remained refractory to such approaches. Proximity-dependent biotinylation techniques such as BioID provide an alternative approach to define the composition of cellular compartments in living cells 5 – 7 . Here we present a BioID-based map of a human cell on the basis of 192 subcellular markers, and define the intracellular locations of 4,145 unique proteins in HEK293 cells. Our localization predictions exceed the specificity of previous approaches, and enabled the discovery of proteins at the interface between the mitochondrial outer membrane and the endoplasmic reticulum that are crucial for mitochondrial homeostasis. On the basis of this dataset, we created humancellmap.org as a community resource that provides online tools for localization analysis of user BioID data, and demonstrate how this resource can be used to understand BioID results better. A proximity-dependent biotinylation technique defines the location of more than 4,000 proteins in a human cell, and almost 36,000 proximal interactions between proteins, including those at the interface of the mitochondria and ER.

Defining specific protein interactions and spatially or temporally restricted local proteomes improves our understanding of all cellular processes, but obtaining such data is challenging, especially for rare proteins, cell types, or events. Proximity labeling enables discovery of protein neighborhoods defining functional complexes and/or organellar protein compositions. Recent technological improvements, namely two highly active biotin ligase variants (TurboID and miniTurbo), allowed us to address two challenging questions in plants: (1) what are in vivo partners of a low abundant key developmental transcription factor and (2) what is the nuclear proteome of a rare cell type? Proteins identified with FAMA-TurboID include known interactors of this stomatal transcription factor and novel proteins that could facilitate its activator and repressor functions. Directing TurboID to stomatal nuclei enabled purification of cell type- and subcellular compartment-specific proteins. Broad tests of TurboID and miniTurbo in Arabidopsis and Nicotiana benthamiana and versatile vectors enable customization by plant researchers. Cells contain thousands of different proteins that work together to control processes essential for life. To fully understand how these processes work it is important to know which proteins interact with each other, and which proteins are present at specific times or in certain cellular locations. Investigating this is particularly difficult if the proteins of interest are rare, either because they are present only at low levels or because they are unique to a particular type of cell. One such protein known as FAMA is only found in young guard cells in plants. Guard cells are rare cells that surround pores on the surface of leaves. They help open or close the pores to allow carbon dioxide and water in and out of the plant. Inside these cells, FAMA regulates the activity of genes in the nucleus, the compartment in the cell that houses the plant’s DNA. Two recently developed molecular biology tools, called TurboID and miniTurbo, allow researchers to identify proteins that are in close contact with a protein of interest or are present at a specific place inside living animal cells. These tools use a modified enzyme to add a small chemical tag to proteins that are close to it, or anything to which it is anchored. Mair et al. adapted these tools for use in plants and tested their utility in two species that are commonly used in research: a tobacco relative called Nicotiana benthamiana, and the thale cress Arabidopsis thaliana . Their experiments showed that TurboID and miniTurbo can be used to tag proteins in different types of plant cells and organs, as well as at different stages of the plants’ lives. To test whether the tools are suitable for identifying partners of rare proteins, Mair et al. used FAMA as their protein of interest. Using TurboID, they detected several proteins in close proximity to FAMA, including some that FAMA was not previously known to interact with. Mair et al. also found that TurboID could identify a number of proteins that were present in the nuclei of guard cells. This shows that the tool can be used to detect proteins in sub-compartments of rare plant cell types. Taken together, these findings show that TurboID and miniTurbo may be customized to study plant protein interactions and to explore local protein ‘neighborhoods’, even for rare proteins or specific cell types. To enable other plant biology researchers to easily access the TurboID and miniTurbo toolset developed in this work, it has been added to the non-profit molecular biology repository Addgene.

Obesity and type 2 diabetes are prevalent chronic diseases effectively managed by semaglutide. Here we studied the effects of semaglutide on the circulating proteome using baseline and end-of-treatment serum samples from two phase 3 trials in participants with overweight or obesity, with or without diabetes: STEP 1 ( n  = 1,311) and STEP 2 ( n  = 645). We identified evidence supporting broad effects of semaglutide, implicating processes related to body weight regulation, glycemic control, lipid metabolism and inflammatory pathways. Several proteins were regulated with semaglutide, after accounting for changes in body weight and HbA 1c at end of trial, suggesting effects of semaglutide on the proteome beyond weight loss and glucose lowering. A comparison of semaglutide with real-world proteomic profiles revealed potential benefits on disease-specific proteomic signatures including the downregulation of specific proteins associated with cardiovascular disease risk, supporting its reported effects of lowering cardiovascular disease risk and potential drug repurposing opportunities. This study showcases the potential of proteomics data gathered from randomized trials for providing insights into disease mechanisms and drug repurposing opportunities. These data also highlight the unmet need for, and importance of, examining proteomic changes in response to weight loss pharmacotherapy in future trials. Using serum samples collected from participants of the STEP 1 and STEP 2 trials, the authors have uncovered changes to the proteome upon semaglutide treatment, which can shed light on the mechanism of action of the drug driving its benefits in obesity-related conditions.

The ability of living systems to adapt to changing conditions originates from their capacity to change their molecular constitution. This is achieved by multiple mechanisms that modulate the quantitative composition and the diversity of the molecular inventory. Molecular diversification is particularly pronounced on the proteome level, at which multiple proteoforms derived from the same gene can in turn combinatorially form different protein complexes, thus expanding the repertoire of functional modules in the cell. The study of molecular and modular diversity and their involvement in responses to changing conditions has only recently become possible through the development of new ‘omics’-based screening technologies. This Review explores our current knowledge of the mechanisms regulating functional diversification along the axis of gene expression, with a focus on the proteome and interactome. We explore the interdependence between different molecular levels and how this contributes to functional diversity. Finally, we highlight several recent techniques for studying molecular diversity, with specific focus on mass spectrometry-based analysis of the proteome and its organization into functional modules, and examine future directions for this rapidly growing field.Cells maximize the repertoire of functions produced from their genome through introducing diversity at each stage of the gene expression process, including at the post-translational level. New advances in proteomics and interactomics have begun to shed light on the extent to which diversity is introduced on the proteome level and by the organization of proteins into modular interaction networks.