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Previous morpho-molecular studies of evolutionary relationships within the economically important genus of honey bees ( Apis ), including the Western Honey Bee ( A. mellifera L.), have suggested Out of Africa or Asia origins and subsequent spread to Europe. I test these hypotheses by a meta-analysis of complete mitochondrial DNA coding regions (11.0 kbp) from 22 nominal subspecies represented by 78 individual sequences in A. mellifera . Parsimony, distance, and likelihood analyses identify six nested clades: Things Fall Apart with Out of Africa or Asia hypotheses. Molecular clock-calibrated phylogeographic analysis shows instead a basal origin of A. m. mellifera in Europe ~ 780 Kya, and expansion to Southeast Europe and Asia Minor ~ 720 Kya. Eurasian bees spread southward via a Levantine/Nilotic/Arabian corridor into Africa ~ 540 Kya. An African clade re-established in Iberia ~ 100 Kya spread thereafter to westerly Mediterranean islands and back into North Africa. Nominal subspecies within the Asia Minor and Mediterranean clades are less differentiated than are individuals within other subspecies. Names matter: paraphyletic anomalies are artefacts of mis-referral in GenBank of sequences to the wrong subspecies, or use of faulty sequences, which are clarified by inclusion of multiple sequences from available subspecies.

The role of targeted mass spectrometry technology in the field of clinical proteomics is discussed in this Perspective. Targeted mass spectrometry (MS) is becoming widely used in academia and in pharmaceutical and biotechnology industries for sensitive and quantitative detection of proteins, peptides and post-translational modifications. Here we describe the increasing importance of targeted MS technologies in clinical proteomics and the potential key roles these techniques will have in bridging biomedical discovery and clinical implementation.

RNA–protein interactions underlie a wide range of cellular processes. Improved methods are needed to systematically map RNA–protein interactions in living cells in an unbiased manner. We used two approaches to target the engineered peroxidase APEX2 to specific cellular RNAs for RNA-centered proximity biotinylation of protein interaction partners. Both an MS2-MCP system and an engineered CRISPR-Cas13 system were used to deliver APEX2 to the human telomerase RNA hTR with high specificity. One-minute proximity biotinylation captured candidate binding partners for hTR, including more than a dozen proteins not previously linked to hTR. We validated the interaction between hTR and the N⁶-methyladenosine (m⁶A) demethylase ALKBH5 and showed that ALKBH5 is able to erase the m⁶A modification on endogenous hTR. ALKBH5 also modulates telomerase complex assembly and activity. MS2- and Cas13-targeted APEX2 may facilitate the discovery of novel RNA–protein interactions in living cells.

Genomic analyses in cancer have been enormously impactful, leading to the identification of driver mutations and development of targeted therapies. But the functions of the vast majority of somatic mutations and copy number variants in tumours remain unknown, and the causes of resistance to targeted therapies and methods to overcome them are poorly defined. Recent improvements in mass spectrometry-based proteomics now enable direct examination of the consequences of genomic aberrations, providing deep and quantitative characterization of tumour tissues. Integration of proteins and their post-translational modifications with genomic, epigenomic and transcriptomic data constitutes the new field of proteogenomics, and is already leading to new biological and diagnostic knowledge with the potential to improve our understanding of malignant transformation and therapeutic outcomes. In this Review we describe recent developments in proteogenomics and key findings from the proteogenomic analysis of a wide range of cancers. Considerations relevant to the selection and use of samples for proteogenomics and the current technologies used to generate, analyse and integrate proteomic with genomic data are described. Applications of proteogenomics in translational studies and immuno-oncology are rapidly emerging, and the prospect for their full integration into therapeutic trials and clinical care seems bright.This Review examines recent developments in proteogenomics, key findings from the proteogenomic analyses of a wide range of cancers and emerging applications of proteogenomics to translational studies and immuno-oncology, as well as discussing future prospects regarding integration into clinical trials and patient care.

O-GlcNAc transferase (OGT) modifies serine and threonine residues on nuclear and cytosolic proteins with O-linked N-acetylglucosamine (GlcNAc). OGT is essential for mammalian cell viability, but the underlying mechanisms are still enigmatic. We performed a genome-wide CRISPR–Cas9 screen in mouse embryonic stem cells (mESCs) to identify candidates whose depletion rescued the block in cell proliferation induced by OGT deficiency. We show that the block in cell proliferation in OGT-deficient cells stems from mitochondrial dysfunction secondary to mTOR (mechanistic target of rapamycin) hyperactivation. In normal cells, OGT maintains low mTOR activity and mitochondrial fitness through suppression of proteasome activity; in the absence of OGT, increased proteasome activity results in increased steady-state amino acid levels, which in turn promote mTOR lysosomal translocation and activation, and increased oxidative phosphorylation. mTOR activation in OGT-deficient mESCs was confirmed by an independent phospho-proteomic screen. Our study highlights a unique series of events whereby OGT regulates the proteasome/ mTOR/ mitochondrial axis in a manner that maintains homeostasis of intracellular amino acid levels, mitochondrial fitness, and cell viability. A similar mechanism operates in CD8⁺ T cells, indicating its generality across mammalian cell types. Manipulating OGT activity may have therapeutic potential in diseases in which this signaling pathway is impaired.

Proximity labeling catalyzed by promiscuous enzymes, such as TurboID, have enabled the proteomic analysis of subcellular regions difficult or impossible to access by conventional fractionation-based approaches. Yet some cellular regions, such as organelle contact sites, remain out of reach for current PL methods. To address this limitation, we split the enzyme TurboID into two inactive fragments that recombine when driven together by a protein–protein interaction or membrane–membrane apposition. At endoplasmic reticulum–mitochondria contact sites, reconstituted TurboID catalyzed spatially restricted biotinylation, enabling the enrichment and identification of >100 endogenous proteins, including many not previously linked to endoplasmic reticulum–mitochondria contacts. We validated eight candidates by biochemical fractionation and overexpression imaging. Overall, split-TurboID is a versatile tool for conditional and spatially specific proximity labeling in cells.

This protocol describes the use of TurboID and split-TurboID in proximity labeling applications for mapping protein–protein interactions and subcellular proteomes in live mammalian cells. TurboID is an engineered biotin ligase that uses ATP to convert biotin into biotin–AMP, a reactive intermediate that covalently labels proximal proteins. Optimized using directed evolution, TurboID has substantially higher activity than previously described biotin ligase–related proximity labeling methods, such as BioID, enabling higher temporal resolution and broader application in vivo. Split-TurboID consists of two inactive fragments of TurboID that can be reconstituted through protein–protein interactions or organelle–organelle interactions, which can facilitate greater targeting specificity than full-length enzymes alone. Proteins biotinylated by TurboID or split-TurboID are then enriched with streptavidin beads and identified by mass spectrometry. Here, we describe fusion construct design and characterization (variable timing), proteomic sample preparation (5–7 d), mass spectrometric data acquisition (2 d), and proteomic data analysis (1 week). This protocol describes proximity labeling approaches using TurboID and split-TurboID, which can be used for mapping protein–protein interactions and organelle proteomes in live mammalian cells with nanometer spatial resolution.

Ubiquitination is essential for the regulation of cellular protein homeostasis. It also has a central role in numerous signaling events. Recent advances in the production and availability of antibodies that recognize the Lys-ɛ-Gly-Gly (K-ɛ-GG) remnant produced by trypsin digestion of proteins having ubiquitinated lysine side chains have markedly improved the ability to enrich and detect endogenous ubiquitination sites by mass spectrometry (MS). The following protocol describes the steps required to complete a large-scale ubiquitin experiment for the detection of tens of thousands of distinct ubiquitination sites from cell lines or tissue samples. Specifically, we present detailed, step-by-step instructions for sample preparation, off-line fractionation by reversed-phase chromatography at pH 10, immobilization of an antibody specific to K-ɛ-GG to beads by chemical cross-linking, enrichment of ubiquitinated peptides using these antibodies and proteomic analysis of enriched samples by LC–tandem MS (MS/MS). Relative quantification can be achieved by performing stable isotope labeling by amino acids in cell culture (SILAC) labeling of cells. After cell or tissue samples have been prepared for lysis, the described protocol can be completed in ∼5 d.

The recent technological and computational advances in mass spectrometry-based single-cell proteomics have pushed the boundaries of sensitivity and throughput. However, reproducible quantification of thousands of proteins within a single cell remains challenging. To address some of those limitations, we present a dedicated sample preparation chip, the proteoCHIP EVO 96 that directly interfaces with the Evosep One. This, in combination with the Bruker timsTOF demonstrates double the identifications without manual sample handling and the newest generation timsTOF Ultra identifies up to 4000 with an average of 3500 protein groups per single HEK-293T without a carrier or match-between runs. Our workflow spans 4 orders of magnitude, identifies over 50 E3 ubiquitin-protein ligases, and profiles key regulatory proteins upon small molecule stimulation. This study demonstrates that the proteoCHIP EVO 96-based sample preparation with the timsTOF Ultra provides sufficient proteome depth to study complex biology beyond cell-type classifications. Profiling of single mammalian cells has revolutionized our understanding of complex biological processes. Here, the authors describe a novel mass spectrometry-based sample preparation and acquisition strategy to deeply characterize the proteome at single cell resolution.

Proximity labeling (PL) with genetically-targeted promiscuous enzymes has emerged as a powerful tool for unbiased proteome discovery. By combining the spatiotemporal specificity of PL with methods for functional protein enrichment, we show that it is possible to map specific protein subclasses within distinct compartments of living cells. In particular, we develop a method to enrich subcompartment-specific RNA binding proteins (RBPs) by combining peroxidase-catalyzed PL with organic-aqueous phase separation of crosslinked protein-RNA complexes (“APEX-PS”). We use APEX-PS to generate datasets of nuclear, nucleolar, and outer mitochondrial membrane (OMM) RBPs, which can be mined for novel functions. For example, we find that the OMM RBP SYNJ2BP retains specific nuclear-encoded mitochondrial mRNAs at the OMM during translation stress, facilitating their local translation and import of protein products into the mitochondrion during stress recovery. Functional PL in general, and APEX-PS in particular, represent versatile approaches for the discovery of proteins with novel function in specific subcellular compartments. Proximity labeling is used to map and discover proteins in specific subcellular compartments. Here the authors combine APEX-mediated proximity labeling with organic-aqueous phase separation to identify nuclear, nucleolar, and outer mitochondrial membrane RNA binding proteins.