Digging deeper into ancient skeletal proteomes through consecutive digestion with multiple proteases

An increasing number of studies utilise the recovery of ancient skeletal proteomes for phylogenetic and evolutionary analysis. Although these studies manage to extract and analyse ancient peptides, the recovered proteomes are generally small in size and with low protein sequence coverage. We expand on previous observations which have shown that the parallel digestion and analysis of Pleistocene skeletal proteomes increases overall proteome size and protein sequence coverage. Furthermore, we demonstrate that the consecutive digestion of a skeletal proteome using two proteases, particularly the combination of Glu-C or chymotrypsin followed by trypsin digestion, enables the recovery of alternative proteome components not reachable through trypsin digestion alone. The proteomes preserved in Pleistocene skeletal specimens are larger than previously anticipated, but unlocking this protein sequence information requires adaptation of extraction and protein digestion protocols. The sequential utilisation of several proteases is, in this regard, a promising avenue for the study of highly degraded but unique hominin proteomes for phylogenetic purposes. SIGNIFICANCE: Palaeoproteomic analysis of archaeological materials, such as hominin skeletal elements, show great promise in studying past organisms and evolutionary relationships. However, as most proteomic methods are inherently destructive, it is essential to aim to recover as much information as possible from every sample. Currently, digestion with trypsin is the standard approach in most palaeoproteomic studies. We find that parallel or consecutive digestion with multiple proteases can improve proteome size and coverage for both Holocene and Pleistocene bone specimens. This allows for recovery of more proteomic data from a sample and maximises the chance of recovering phylogenetically relevant information.

Deep-time phylogenetic inference by paleoproteomic analysis of dental enamel

In temperate and subtropical regions, ancient proteins are reported to survive up to about 2 million years, far beyond the known limits of ancient DNA preservation in the same areas. Accordingly, their amino acid sequences currently represent the only source of genetic information available to pursue phylogenetic inference involving species that went extinct too long ago to be amenable for ancient DNA analysis. Here we present a complete workflow, including sample preparation, mass spectrometric data acquisition and computational analysis, to recover and interpret million-year-old dental enamel protein sequences. During sample preparation, the proteolytic digestion step, usually an integral part of conventional bottom-up proteomics, is omitted to increase the recovery of the randomly degraded peptides spontaneously generated by extensive diagenetic hydrolysis of ancient proteins over geological time. Similarly, we describe other solutions we have adopted to (1) authenticate the endogenous origin of the protein traces we identify, (2) detect and validate amino acid variation in the ancient protein sequences and (3) attempt phylogenetic inference. Sample preparation and data acquisition can be completed in 3-4 working days, while subsequent data analysis usually takes 2-5 days. The workflow described requires basic expertise in ancient biomolecules analysis, mass spectrometry-based proteomics and molecular phylogeny. Finally, we describe the limits of this approach and its potential for the reconstruction of evolutionary relationships in paleontology and paleoanthropology.

Phosphoproteomic investigation of targets of protein phosphatases in EGFR signaling

Receptor tyrosine kinases (RTKs) initiate cellular signaling pathways, which are regulated through a delicate balance of phosphorylation and dephosphorylation events. While many studies of RTKs have focused on downstream-activated kinases catalyzing the site-specific phosphorylation, few studies have focused on the phosphatases carrying out the dephosphorylation. In this study, we analyzed six protein phosphatase networks using chemical inhibitors in context of epidermal growth factor receptor (EGFR) signaling by mass spectrometry-based phosphoproteomics. Specifically, we focused on protein phosphatase 2C (PP2C), involved in attenuating p38-dependent signaling pathways in various cellular responses, and confirmed its effect in regulating p38 activity in EGFR signaling. Furthermore, utilizing a p38 inhibitor, we classified phosphosites whose phosphorylation status depends on PP2C inhibition into p38-dependent and p38-independent sites. This study provides a large-scale dataset of phosphatase-regulation of EGF-responsive phosphorylation sites, which serves as a useful resource to deepen our understanding of EGFR signaling.

Systematic Optimization of Automated Phosphopeptide Enrichment for High-Sensitivity Phosphoproteomics

Improving coverage, robustness, and sensitivity is crucial for routine phosphoproteomics analysis by single-shot liquid chromatography-tandem mass spectrometry (LC-MS/MS) from minimal peptide inputs. Here, we systematically optimized key experimental parameters for automated on-bead phosphoproteomics sample preparation with a focus on low-input samples. Assessing the number of identified phosphopeptides, enrichment efficiency, site localization scores, and relative enrichment of multiply-phosphorylated peptides pinpointed critical variables influencing the resulting phosphoproteome. Optimizing glycolic acid concentration in the loading buffer, percentage of ammonium hydroxide in the elution buffer, peptide-to-beads ratio, binding time, sample, and loading buffer volumes allowed us to confidently identify >16,000 phosphopeptides in half-an-hour LC-MS/MS on an Orbitrap Exploris 480 using 30 μg of peptides as starting material. Furthermore, we evaluated how sequential enrichment can boost phosphoproteome coverage and showed that pooling fractions into a single LC-MS/MS analysis increased the depth. We also present an alternative phosphopeptide enrichment strategy based on stepwise addition of beads thereby boosting phosphoproteome coverage by 20%. Finally, we applied our optimized strategy to evaluate phosphoproteome depth with the Orbitrap Astral MS using a cell dilution series and were able to identify >32,000 phosphopeptides from 0.5 million HeLa cells in half-an-hour LC-MS/MS using narrow-window data-independent acquisition (nDIA).

One-Tip enables comprehensive proteome coverage in minimal cells and single zygotes

Mass spectrometry (MS)-based proteomics workflows typically involve complex, multi-step processes, presenting challenges with sample losses, reproducibility, requiring substantial time and financial investments, and specialized skills. Here we introduce One-Tip, a proteomics methodology that seamlessly integrates efficient, one-pot sample preparation with precise, narrow-window data-independent acquisition (nDIA) analysis. One-Tip substantially simplifies sample processing, enabling the reproducible identification of >9000 proteins from ~1000 HeLa cells. The versatility of One-Tip is highlighted by nDIA identification of ~6000 proteins in single cells from early mouse embryos. Additionally, the study incorporates the Uno Single Cell Dispenser™, demonstrating the capability of One-Tip in single-cell proteomics with >3000 proteins identified per HeLa cell. We also extend One-Tip workflow to analysis of extracellular vesicles (EVs) extracted from blood plasma, demonstrating its high sensitivity by identifying >3000 proteins from 16 ng EV preparation. One-Tip expands capabilities of proteomics, offering greater depth and throughput across a range of sample types.

ETD-Based Proteomic Profiling Improves Arginine Methylation Identification and Reveals Novel PRMT5 Substrates

Protein arginine methylations are important post-translational modifications (PTMs) in eukaryotes, regulating many biological processes. However, traditional collision-based mass spectrometry methods inevitably cause neutral losses of methylarginines, preventing the deep mining of biologically important sites. Herein we developed an optimized mass spectrometry workflow based on electron-transfer dissociation (ETD) with supplemental activation for proteomic profiling of arginine methylation in human cells. Using symmetric dimethylarginine (sDMA) as an example, we show that the ETD-based optimized workflow significantly improved the identification and site localization of sDMA. Quantitative proteomics identified 138 novel sDMA sites as potential PRMT5 substrates in HeLa cells. Further biochemical studies on SERBP1, a newly identified PRMT5 substrate, confirmed the coexistence of sDMA and asymmetric dimethylarginine in the central RGG/RG motif, and loss of either methylation caused increased the recruitment of SERBP1 to stress granules under oxidative stress. Overall, our optimized workflow not only enabled the identification and localization of extensive, nonoverlapping sDMA sites in human cells but also revealed novel PRMT5 substrates whose sDMA may play potentially important biological functions.

Extending the Coverage of Lys-C/Trypsin-Based Bottom-up Proteomics by Cysteine S-Aminoethylation

To improve the coverage in bottom-up proteomics, S-aminoethylation of cysteine residues (AE-Cys) was carried out with 2-bromoethylamine, followed by cleavage with lysyl endopeptidase (Lys-C) or Lys-C/trypsin. A model study with bovine serum albumin showed that the C-terminal side of AE-Cys was successfully cleaved by Lys-C. The frequency of side reactions at amino acids other than Cys was less than that in the case of carbamidomethylation of Cys with iodoacetamide. Proteomic analysis of A549 cell extracts in the data-dependent acquisition mode after AE-Cys modification afforded a greater number of identified protein groups, especially membrane proteins. In addition, label-free quantification of proteins in mouse nonsmall cell lung cancer (NSCLC) tissue in the data-independent acquisition mode after AE-Cys modification showed improved NSCLC pathway coverage and greater reproducibility. Furthermore, the AE-Cys method could identify an epidermal growth factor receptor peptide containing the T790 M mutation site, a well-established lung-cancer-related mutation site that has evaded conventional bottom-up methods. Finally, AE-Cys was found to fully mimic Lys in terms of collision-induced dissociation fragmentation, ion mobility separation, and cleavage by Lys-C/trypsin, except for sulfoxide formation during sample preparation.

Ultra-fast label-free quantification and comprehensive proteome coverage with narrow-window data-independent acquisition

Mass spectrometry (MS)-based proteomics aims to characterize comprehensive proteomes in a fast and reproducible manner. Here we present the narrow-window data-independent acquisition (nDIA) strategy consisting of high-resolution MS1 scans with parallel tandem MS (MS/MS) scans of ~200 Hz using 2-Th isolation windows, dissolving the differences between data-dependent and -independent methods. This is achieved by pairing a quadrupole Orbitrap mass spectrometer with the asymmetric track lossless (Astral) analyzer which provides >200-Hz MS/MS scanning speed, high resolving power and sensitivity, and low-ppm mass accuracy. The nDIA strategy enables profiling of >100 full yeast proteomes per day, or 48 human proteomes per day at the depth of ~10,000 human protein groups in half-an-hour or ~7,000 proteins in 5 min, representing 3× higher coverage compared with current state-of-the-art MS. Multi-shot acquisition of offline fractionated samples provides comprehensive coverage of human proteomes in ~3 h. High quantitative precision and accuracy are demonstrated in a three-species proteome mixture, quantifying 14,000+ protein groups in a single half-an-hour run.

Homo sapiens reached the higher latitudes of Europe by 45,000 years ago

The Middle to Upper Palaeolithic transition in Europe is associated with the regional disappearance of Neanderthals and the spread of Homo sapiens. Late Neanderthals persisted in western Europe several millennia after the occurrence of H. sapiens in eastern Europe1. Local hybridization between the two groups occurred2, but not on all occasions3. Archaeological evidence also indicates the presence of several technocomplexes during this transition, complicating our understanding and the association of behavioural adaptations with specific hominin groups4. One such technocomplex for which the makers are unknown is the Lincombian-Ranisian-Jerzmanowician (LRJ), which has been described in northwestern and central Europe5-8. Here we present the morphological and proteomic taxonomic identification, mitochondrial DNA analysis and direct radiocarbon dating of human remains directly associated with an LRJ assemblage at the site Ilsenhöhle in Ranis (Germany). These human remains are among the earliest directly dated Upper Palaeolithic H. sapiens remains in Eurasia. We show that early H. sapiens associated with the LRJ were present in central and northwestern Europe long before the extinction of late Neanderthals in southwestern Europe. Our results strengthen the notion of a patchwork of distinct human populations and technocomplexes present in Europe during this transitional period.

Mapping cardiac remodeling in chronic kidney disease

Patients with advanced chronic kidney disease (CKD) mostly die from sudden cardiac death and recurrent heart failure. The mechanisms of cardiac remodeling are largely unclear. To dissect molecular and cellular mechanisms of cardiac remodeling in CKD in an unbiased fashion, we performed left ventricular single-nuclear RNA sequencing in two mouse models of CKD. Our data showed a hypertrophic response trajectory of cardiomyocytes with stress signaling and metabolic changes driven by soluble uremia-related factors. We mapped fibroblast to myofibroblast differentiation in this process and identified notable changes in the cardiac vasculature, suggesting inflammation and dysfunction. An integrated analysis of cardiac cellular responses to uremic toxins pointed toward endothelin-1 and methylglyoxal being involved in capillary dysfunction and TNFα driving cardiomyocyte hypertrophy in CKD, which was validated in vitro and in vivo. TNFα inhibition in vivo ameliorated the cardiac phenotype in CKD. Thus, interventional approaches directed against uremic toxins, such as TNFα, hold promise to ameliorate cardiac remodeling in CKD.

Comparing extraction method efficiency for high-throughput palaeoproteomic bone species identification

High-throughput proteomic analysis of archaeological skeletal remains provides information about past fauna community compositions and species dispersals in time and space. Archaeological skeletal remains are a finite resource, however, and therefore it becomes relevant to optimize methods of skeletal proteome extraction. Ancient proteins in bone specimens can be highly degraded and consequently, extraction methods for well-preserved or modern bone might be unsuitable for the processing of highly degraded skeletal proteomes. In this study, we compared six proteomic extraction methods on Late Pleistocene remains with variable levels of proteome preservation. We tested the accuracy of species identification, protein sequence coverage, deamidation, and the number of post-translational modifications per method. We find striking differences in obtained proteome complexity and sequence coverage, highlighting that simple acid-insoluble proteome extraction methods perform better in highly degraded contexts. For well-preserved specimens, the approach using EDTA demineralization and protease-mix proteolysis yielded a higher number of identified peptides. The protocols presented here allowed protein extraction from ancient bone with a minimum number of working steps and equipment and yielded protein extracts within three working days. We expect further development along this route to benefit large-scale screening applications of relevance to archaeological and human evolution research.

GLP-1R signaling neighborhoods associate with the susceptibility to adverse drug reactions of incretin mimetics

G protein-coupled receptors are important drug targets that engage and activate signaling transducers in multiple cellular compartments. Delineating therapeutic signaling from signaling associated with adverse events is an important step towards rational drug design. The glucagon-like peptide-1 receptor (GLP-1R) is a validated target for the treatment of diabetes and obesity, but drugs that target this receptor are a frequent cause of adverse events. Using recently developed biosensors, we explored the ability of GLP-1R to activate 15 pathways in 4 cellular compartments and demonstrate that modifications aimed at improving the therapeutic potential of GLP-1R agonists greatly influence compound efficacy, potency, and safety in a pathway- and compartment-selective manner. These findings, together with comparative structure analysis, time-lapse microscopy, and phosphoproteomics, reveal unique signaling signatures for GLP-1R agonists at the level of receptor conformation, functional selectivity, and location bias, thus associating signaling neighborhoods with functionally distinct cellular outcomes and clinical consequences.

Protocol for high-throughput semi-automated label-free- or TMT-based phosphoproteome profiling

Tandem mass tags data-dependent acquisition (TMT-DDA) as well as data-independent acquisition-based label-free quantification (LFQ-DIA) have become the leading workflows to achieve deep proteome and phosphoproteome profiles. We present a modular pipeline for TMT-DDA and LFQ-DIA that integrates steps to perform scalable phosphoproteome profiling, including protein lysate extraction, clean-up, digestion, phosphopeptide enrichment, and TMT-labeling. We also detail peptide and/or phosphopeptide fractionation and pre-mass spectrometry desalting and provide researchers guidance on choosing the best workflow based on sample number and input. For complete details on the use and execution of this protocol, please refer to Koenig et al.1 and Martínez-Val et al.2.

DeSUMOylation of chromatin-bound proteins limits the rapid transcriptional reprogramming induced by daunorubicin in acute myeloid leukemias

Genotoxicants have been used for decades as front-line therapies against cancer on the basis of their DNA-damaging actions. However, some of their non-DNA-damaging effects are also instrumental for killing dividing cells. We report here that the anthracycline Daunorubicin (DNR), one of the main drugs used to treat Acute Myeloid Leukemia (AML), induces rapid (3 h) and broad transcriptional changes in AML cells. The regulated genes are particularly enriched in genes controlling cell proliferation and death, as well as inflammation and immunity. These transcriptional changes are preceded by DNR-dependent deSUMOylation of chromatin proteins, in particular at active promoters and enhancers. Surprisingly, inhibition of SUMOylation with ML-792 (SUMO E1 inhibitor), dampens DNR-induced transcriptional reprogramming. Quantitative proteomics shows that the proteins deSUMOylated in response to DNR are mostly transcription factors, transcriptional co-regulators and chromatin organizers. Among them, the CCCTC-binding factor CTCF is highly enriched at SUMO-binding sites found in cis-regulatory regions. This is notably the case at the promoter of the DNR-induced NFKB2 gene. DNR leads to a reconfiguration of chromatin loops engaging CTCF- and SUMO-bound NFKB2 promoter with a distal cis-regulatory region and inhibition of SUMOylation with ML-792 prevents these changes.

Loss of N-terminal acetyltransferase A activity induces thermally unstable ribosomal proteins and increases their turnover in Saccharomyces cerevisiae

Protein N-terminal (Nt) acetylation is one of the most abundant modifications in eukaryotes, covering ~50-80 % of the proteome, depending on species. Cells with defective Nt-acetylation display a wide array of phenotypes such as impaired growth, mating defects and increased stress sensitivity. However, the pleiotropic nature of these effects has hampered our understanding of the functional impact of protein Nt-acetylation. The main enzyme responsible for Nt-acetylation throughout the eukaryotic kingdom is the N-terminal acetyltransferase NatA. Here we employ a multi-dimensional proteomics approach to analyze Saccharomyces cerevisiae lacking NatA activity, which causes global proteome remodeling. Pulsed-SILAC experiments reveals that NatA-deficient strains consistently increase degradation of ribosomal proteins compared to wild type. Explaining this phenomenon, thermal proteome profiling uncovers decreased thermostability of ribosomes in NatA-knockouts. Our data are in agreement with a role for Nt-acetylation in promoting stability for parts of the proteome by enhancing the avidity of protein-protein interactions and folding.

Galectin-1 induces a tumor-associated macrophage phenotype and upregulates indoleamine 2,3-dioxygenase-1

Galectins are a group of carbohydrate-binding proteins with a presumed immunomodulatory role and an elusive function on antigen-presenting cells. Here we analyzed the expression of galectin-1 and found upregulation of galectin-1 in the extracellular matrix across multiple tumors. Performing an in-depth and dynamic proteomic and phosphoproteomic analysis of human macrophages stimulated with galectin-1, we show that galectin-1 induces a tumor-associated macrophage phenotype with increased expression of key immune checkpoint protein programmed cell death 1 ligand 1 (PD-L1/CD274) and immunomodulator indoleamine 2,3-dioxygenase-1 (IDO1). Galectin-1 induced IDO1 and its active metabolite kynurenine in a dose-dependent manner through JAK/STAT signaling. In a 3D organotypic tissue model system equipped with genetically engineered tumorigenic epithelial cells, we analyzed the cellular source of galectin-1 in the extracellular matrix and found that galectin-1 is derived from epithelial and stromal cells. Our results highlight the potential of targeting galectin-1 in immunotherapeutic treatment of human cancers.

A seven-transmembrane methyltransferase catalysing N-terminal histidine methylation of lytic polysaccharide monooxygenases

Lytic polysaccharide monooxygenases (LPMOs) are oxidative enzymes that help break down lignocellulose, making them highly attractive for improving biomass utilization in industrial biotechnology. The catalytically essential N-terminal histidine (His1) of LPMOs is post-translationally modified by methylation in filamentous fungi to protect them from auto-oxidative inactivation, however, the responsible methyltransferase enzyme is unknown. Using mass-spectrometry-based quantitative proteomics in combination with systematic CRISPR/Cas9 knockout screening in Aspergillus nidulans, we identify the N-terminal histidine methyltransferase (NHMT) encoded by the gene AN4663. Targeted proteomics confirm that NHMT was solely responsible for His1 methylation of LPMOs. NHMT is predicted to encode a unique seven-transmembrane segment anchoring a soluble methyltransferase domain. Co-localization studies show endoplasmic reticulum residence of NHMT and co-expression in the industrial production yeast Komagataella phaffii with LPMOs results in His1 methylation of the LPMOs. This demonstrates the biotechnological potential of recombinant production of proteins and peptides harbouring this specific post-translational modification.

Optimizing Linear Ion-Trap Data-Independent Acquisition toward Single-Cell Proteomics

A linear ion trap (LIT) is an affordable, robust mass spectrometer that provides fast scanning speed and high sensitivity, where its primary disadvantage is inferior mass accuracy compared to more commonly used time-of-flight or orbitrap (OT) mass analyzers. Previous efforts to utilize the LIT for low-input proteomics analysis still rely on either built-in OTs for collecting precursor data or OT-based library generation. Here, we demonstrate the potential versatility of the LIT for low-input proteomics as a stand-alone mass analyzer for all mass spectrometry (MS) measurements, including library generation. To test this approach, we first optimized LIT data acquisition methods and performed library-free searches with and without entrapment peptides to evaluate both the detection and quantification accuracy. We then generated matrix-matched calibration curves to estimate the lower limit of quantification using only 10 ng of starting material. While LIT-MS1 measurements provided poor quantitative accuracy, LIT-MS2 measurements were quantitatively accurate down to 0.5 ng on the column. Finally, we optimized a suitable strategy for spectral library generation from low-input material, which we used to analyze single-cell samples by LIT-DIA using LIT-based libraries generated from as few as 40 cells.

Hybrid-DIA: intelligent data acquisition integrates targeted and discovery proteomics to analyze phospho-signaling in single spheroids

Achieving sufficient coverage of regulatory phosphorylation sites by mass spectrometry (MS)-based phosphoproteomics for signaling pathway reconstitution is challenging, especially when analyzing tiny sample amounts. To address this, we present a hybrid data-independent acquisition (DIA) strategy (hybrid-DIA) that combines targeted and discovery proteomics through an Application Programming Interface (API) to dynamically intercalate DIA scans with accurate triggering of multiplexed tandem mass spectrometry (MSx) scans of predefined (phospho)peptide targets. By spiking-in heavy stable isotope labeled phosphopeptide standards covering seven major signaling pathways, we benchmark hybrid-DIA against state-of-the-art targeted MS methods (i.e., SureQuant) using EGF-stimulated HeLa cells and find the quantitative accuracy and sensitivity to be comparable while hybrid-DIA also profiles the global phosphoproteome. To demonstrate the robustness, sensitivity, and biomedical potential of hybrid-DIA, we profile chemotherapeutic agents in single colon carcinoma multicellular spheroids and evaluate the phospho-signaling difference of cancer cells in 2D vs 3D culture.

Proteomic identification of beer brewing products in the ground layer of Danish Golden Age paintings

The application of mass spectrometry-based proteomics to artworks provides accurate and detailed characterization of protein-based materials used in their production. This is highly valuable to plan conservation strategies and reconstruct the artwork's history. In this work, the proteomic analysis of canvas paintings from the Danish Golden Age led to the confident identification of cereal and yeast proteins in the ground layer. This proteomic profile points to a (by-)product of beer brewing, in agreement with local artists' manuals. The use of this unconventional binder can be connected to the workshops within the Royal Danish Academy of Fine Arts. The mass spectrometric dataset generated from proteomics was also processed with a metabolomics workflow. The spectral matches observed supported the proteomic conclusions, and, in at least one sample, suggested the use of drying oils. These results highlight the value of untargeted proteomics in heritage science, correlating unconventional artistic materials with local culture and practices.

Repurposing antipsychotic drug Amisulpride for targeting synovial fibroblast activation in arthritis

Synovial Fibroblasts (SFs) are key pathogenic drivers in Rheumatoid arthritis (RA). Their in vivo activation by TNF is sufficient to orchestrate full arthritic pathogenesis in animal models and TNF blockade proved efficacious for a high percentage of RA patients albeit co-inducing rare but serious side effects. Aiming to find new potent therapeutics, we applied the L1000CDS2 search engine, in order to repurpose drugs that could reverse the pathogenic expression signature of arthritogenic human TNF transgenic (hTNFtg) SFs. We identified a neuroleptic drug, namely Amisulpride, which reduced SFs' inflammatory potential while decreasing the clinical score of hTNFtg polyarthritis. Notably, we found that Amisulpride function is neither through its known targets Dopamine receptors 2 and 3 and Serotonin Receptor 7, nor through TNF-TNFRI binding inhibition. Through a click chemistry approach, novel potential targets of Amisulpride were identified, which were further validated to repress hTNFtg SFs' inflammatory potential ex vivo (Ascc3 and Sec62), while phosphoproteomics analysis revealed that treatment altered important fibroblast activation pathways, such as adhesion. Thus, Amisulpride could prove beneficial to patients suffering from RA and the often-accompanying comorbid dysthymia, reducing SF pathogenicity along with its anti-depressive activity, serving further as a "lead" compound for the development of novel therapeutics against fibroblast activation.

Recent advances in kinase signaling network profiling by mass spectrometry

Mass spectrometry-based phosphoproteomics is currently the leading methodology for the study of global kinase signaling. The scientific community is continuously releasing technological improvements for sensitive and fast identification of phosphopeptides, and their accurate quantification. To interpret large-scale phosphoproteomics data, numerous bioinformatic resources are available that help understanding kinase network functional role in biological systems upon perturbation. Some of these resources are databases of phosphorylation sites, protein kinases and phosphatases; others are bioinformatic algorithms to infer kinase activity, predict phosphosite functional relevance and visualize kinase signaling networks. In this review, we present the latest experimental and bioinformatic tools to profile protein kinase signaling networks and provide examples of their application in biomedicine.

Matrix Gla Protein drives stemness and tumor initiation in ovarian cancer

Ovarian cancer (OC) displays the highest mortality among gynecological tumors, mainly due to early peritoneal dissemination, the high frequency of tumor relapse following primary debulking, and the development of chemoresistance. All these events are thought to be initiated and sustained by a subpopulation of neoplastic cells, termed ovarian cancer stem cells (OCSC), that are endowed with self-renewing and tumor-initiating properties. This implies that interfering with OCSC function should offer novel therapeutic perspectives to defeat OC progression. To this aim, a better understanding of the molecular and functional makeup of OCSC in clinically relevant model systems is essential. We have profiled the transcriptome of OCSC vs. their bulk cell counterpart from a panel of patient-derived OC cell cultures. This revealed that Matrix Gla Protein (MGP), classically known as a calcification-preventing factor in cartilage and blood vessels, is markedly enriched in OCSC. Functional assays showed that MGP confers several stemness-associated traits to OC cells, including a transcriptional reprogramming. Patient-derived organotypic cultures pointed to the peritoneal microenvironment as a major inducer of MGP expression in OC cells. Furthermore, MGP was found to be necessary and sufficient for tumor initiation in OC mouse models, by shortening tumor latency and increasing dramatically the frequency of tumor-initiating cells. Mechanistically, MGP-driven OC stemness was mediated by the stimulation of Hedgehog signaling, in particular through the induction of the Hedgehog effector GLI1, thus highlighting a novel MGP/Hedgehog pathway axis in OCSC. Finally, MGP expression was found to correlate with poor prognosis in OC patients, and was increased in tumor tissue after chemotherapy, supporting the clinical relevance of our findings. Thus, MGP is a novel driver in OCSC pathophysiology, with a major role in stemness and in tumor initiation.

Optimizing linear ion trap data independent acquisition towards single cell proteomics

A linear ion trap (LIT) is an affordable, robust mass spectrometer that proves fast scanning speed and high sensitivity, where its primary disadvantage is inferior mass accuracy compared to more commonly used time-of-flight (TOF) or orbitrap (OT) mass analyzers. Previous efforts to utilize the LIT for low-input proteomics analysis still rely on either built-in OTs for collecting precursor data or OT-based library generation. Here, we demonstrate the potential versatility of the LIT for low-input proteomics as a stand-alone mass analyzer for all mass spectrometry measurements, including library generation. To test this approach, we first optimized LIT data acquisition methods and performed library-free searches with and without entrapment peptides to evaluate both the detection and quantification accuracy. We then generated matrix-matched calibration curves to estimate the lower limit of quantification using only 10 ng of starting material. While LIT-MS1 measurements provided poor quantitative accuracy, LIT-MS2 measurements were quantitatively accurate down to 0.5 ng on column. Finally, we optimized a suitable strategy for spectral library generation from low-input material, which we used to analyze single-cell samples by LIT-DIA using LIT-based libraries generated from as few as 40 cells.

Proteomics to study cancer immunity and improve treatment

Cancer survival and progression depend on the ability of tumor cells to avoid immune recognition. Advances in the understanding of cancer immunity and tumor immune escape mechanisms enabled the development of immunotherapeutic approaches. In patients with otherwise incurable metastatic cancers, immunotherapy resulted in unprecedented response rates with the potential for durable complete responses. However, primary and acquired resistance mechanisms limit the efficacy of immunotherapy. Further therapeutic advances require a deeper understanding of the interplay between immune cells and tumors. Most high-throughput studies within the past decade focused on an omics characterization at DNA and RNA level. However, proteins are the molecular effectors of genomic information; therefore, the study of proteins provides deeper understanding of cellular functions. Recent advances in mass spectrometry (MS)-based proteomics at a system-wide scale may allow translational and clinical discoveries by enabling the analysis of understudied post-translational modifications, subcellular protein localization, cell signaling, and protein-protein interactions. In this review, we discuss the potential contribution of MS-based proteomics to preclinical and clinical research findings in the context of tumor immunity and cancer immunotherapies.

Divergent Molecular and Cellular Responses to Low and High-Dose Ionizing Radiation

Cancer risk after ionizing radiation (IR) is assumed to be linear with the dose; however, for low doses, definite evidence is lacking. Here, using temporal multi-omic systems analyses after a low (LD; 0.1 Gy) or a high (HD; 1 Gy) dose of X-rays, we show that, although the DNA damage response (DDR) displayed dose proportionality, many other molecular and cellular responses did not. Phosphoproteomics uncovered a novel mode of phospho-signaling via S12-PPP1R7, and large-scale dephosphorylation events that regulate mitotic exit control in undamaged cells and the G2/M checkpoint upon IR in a dose-dependent manner. The phosphoproteomics of irradiated DNA double-strand breaks (DSBs) repair-deficient cells unveiled extended phospho-signaling duration in either a dose-dependent (DDR signaling) or independent (mTOR-ERK-MAPK signaling) manner without affecting signal magnitude. Nascent transcriptomics revealed the transcriptional activation of genes involved in NRF2-regulated antioxidant defense, redox-sensitive ERK-MAPK signaling, glycolysis and mitochondrial function after LD, suggesting a prominent role for reactive oxygen species (ROS) in molecular and cellular responses to LD exposure, whereas DDR genes were prominently activated after HD. However, how and to what extent the observed dose-dependent differences in molecular and cellular responses may impact cancer development remain unclear, as the induction of chromosomal damage was found to be dose-proportional (10-200 mGy).

Characterization of TGF-β signaling in a human organotypic skin model reveals that loss of TGF-βRII induces invasive tissue growth

Transforming growth factor–β (TGF-β) signaling regulates various aspects of cell growth and differentiation and is often dysregulated in human cancers. We combined genetic engineering of a human organotypic three-dimensional (3D) skin model with global quantitative proteomics and phosphoproteomics to dissect the importance of essential components of the TGF-β signaling pathway, including the ligands TGF-β1, TGF-β2, and TGF-β3, the receptor TGF-βRII, and the intracellular effector SMAD4. Consistent with the antiproliferative effects of TGF-β signaling, the loss of TGF-β1 or SMAD4 promoted cell cycling and delayed epidermal differentiation. The loss of TGF-βRII, which abrogates both SMAD4-dependent and SMAD4-independent downstream signaling, more strongly affected cell proliferation and differentiation than did loss of SMAD4, and it induced invasive growth. TGF-βRII knockout reduced cell-matrix interactions, and the production of matrix proteins increased the production of cancer-associated cell-cell adhesion proteins and proinflammatory mediators and increased mitogen-activated protein kinase (MAPK) signaling. Inhibiting the activation of the ERK and p38 MAPK pathways blocked the development of the invasive phenotype upon the loss of TGF-βRII. This study provides a framework for exploring TGF-β signaling pathways in human epithelial tissue homeostasis and transformation using genetic engineering, 3D tissue models, and high-throughput quantitative proteomics and phosphoproteomics.

Combining mass spectrometry and machine learning to discover bioactive peptides

Peptides play important roles in regulating biological processes and form the basis of a multiplicity of therapeutic drugs. To date, only about 300 peptides in human have confirmed bioactivity, although tens of thousands have been reported in the literature. The majority of these are inactive degradation products of endogenous proteins and peptides, presenting a needle-in-a-haystack problem of identifying the most promising candidate peptides from large-scale peptidomics experiments to test for bioactivity. To address this challenge, we conducted a comprehensive analysis of the mammalian peptidome across seven tissues in four different mouse strains and used the data to train a machine learning model that predicts hundreds of peptide candidates based on patterns in the mass spectrometry data. We provide in silico validation examples and experimental confirmation of bioactivity for two peptides, demonstrating the utility of this resource for discovering lead peptides for further characterization and therapeutic development.

Phosphoproteomics of primary AML patient samples reveals rationale for AKT combination therapy and p53 context to overcome selinexor resistance

Acute myeloid leukemia (AML) is a heterogeneous disease with variable patient responses to therapy. Selinexor, an inhibitor of nuclear export, has shown promising clinical activity for AML. To identify the molecular context for monotherapy sensitivity as well as rational drug combinations, we profile selinexor signaling responses using phosphoproteomics in primary AML patient samples and cell lines. Functional phosphosite scoring reveals that p53 function is required for selinexor sensitivity consistent with enhanced efficacy of selinexor in combination with the MDM2 inhibitor nutlin-3a. Moreover, combining selinexor with the AKT inhibitor MK-2206 overcomes dysregulated AKT-FOXO3 signaling in resistant cells, resulting in synergistic anti-proliferative effects. Using high-throughput spatial proteomics to profile subcellular compartments, we measure global proteome and phospho-proteome dynamics, providing direct evidence of nuclear translocation of FOXO3 upon combination treatment. Our data demonstrate the potential of phosphoproteomics and functional phosphorylation site scoring to successfully pinpoint key targetable signaling hubs for rational drug combinations.

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Phosphoproteomics with functional scoring uncovers context for selinexor sensitivity

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Functional p53 correlates with selinexor sensitivity, which is enhanced by nutlin-3a

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Dysregulated AKT-FOXO3 drives selinexor resistance, which is overcome with MK-2206

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Spatial proteomics reveals selinexor-induced nucleocytoplasmic protein shuttling

Optimal analytical strategies for sensitive and quantitative phosphoproteomics using TMT-based multiplexing

In large-scale quantitative mass spectrometry (MS)-based phosphoproteomics, isobaric labeling with tandem mass tags (TMTs) coupled with offline high-pH reversed-phase peptide chromatographic fractionation maximizes depth of coverage. To investigate to what extent limited sample amounts affect sensitivity and dynamic range of the analysis due to sample losses, we benchmarked TMT-based fractionation strategies against single-shot label-free quantification with spectral library-free data independent acquisition (LFQ-DIA), for different peptide input per sample. To systematically examine how peptide input amounts influence TMT-fractionation approaches in a phosphoproteomics workflow, we compared two different high-pH reversed-phase fractionation strategies, microflow (MF) and stage-tip fractionation (STF), while scaling the peptide input amount down from 12.5 to 1 μg per sample. Our results indicate that, for input amounts higher than 5 μg per sample, TMT labeling, followed by microflow fractionation (MF) and phospho-enrichment, achieves the deepest phosphoproteome coverage, even compared to single shot direct-DIA analysis. Conversely, STF of enriched phosphopeptides (STF) is optimal for lower amounts, below 5 μg/peptide per sample. As a result, we provide a decision tree to help phosphoproteomics users to choose the best workflow as a function of sample amount.

Obtaining Complete Human Proteomes

Proteins are the molecular effectors of the information encoded in the genome. Proteomics aims at understanding the molecular functions of proteins in their biological context. In contrast to transcriptomics and genomics, the study of proteomes provides deeper insight into the dynamic regulatory layers encoded at the protein level, such as posttranslational modifications, subcellular localization, cell signaling, and protein-protein interactions. Currently, mass spectrometry (MS)-based proteomics is the technology of choice for studying proteomes at a system-wide scale, contributing to clinical biomarker discovery and fundamental molecular biology. MS technologies are continuously being developed to fulfill the requirements of speed, resolution, and quantitative accuracy, enabling the acquisition of comprehensive proteomes. In this review, we present how MS technology and acquisition methods have evolved to meet the requirements of cutting-edge proteomics research, which is describing the human proteome and its dynamic posttranslational modifications with unprecedented depth. Finally, we provide a perspective on studying proteomes at single-cell resolution. Expected final online publication date for the Annual Review of Genomics and Human Genetics, Volume 23 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Phosphorylation of SHP2 at Tyr62 enables acquired resistance to SHP2 allosteric inhibitors in FLT3-ITD-driven AML

The protein tyrosine phosphatase SHP2 is crucial for oncogenic transformation of acute myeloid leukemia (AML) cells expressing mutated receptor tyrosine kinases (RTK). SHP2 is required for full RAS-ERK activation to promote cell proliferation and survival programs. Allosteric SHP2 inhibitors act by stabilizing SHP2 in its auto-inhibited conformation and are currently being tested in clinical trials for tumors with overactivation of the RAS/ERK pathway, alone and in various drug combinations. In this study, we established cells with acquired resistance to the allosteric SHP2 inhibitor SHP099 from two FLT3-ITD-positive AML cell lines. Label-free and isobaric labeling quantitative mass spectrometry-based phosphoproteomics of these resistant models demonstrated that AML cells can restore phosphorylated ERK (pERK) in the presence of SHP099, thus developing adaptive resistance. Mechanistically, SHP2 inhibition induced tyrosine phosphorylation and feedback-driven activation of the FLT3 receptor, which in turn phosphorylated SHP2 on tyrosine 62. This phosphorylation stabilized SHP2 in its open conformation, preventing SHP099 binding and conferring resistance. Combinatorial inhibition of SHP2 and MEK or FLT3 prevented pERK rebound and resistant cell growth. The same mechanism was observed in a FLT3-mutated B-ALL cell line and in the inv(16)/KitD816Y AML mouse model, but allosteric inhibition of Shp2 did not impair the clonogenic ability of normal bone marrow progenitors. Together, these results support the future use of SHP2 inhibitor combinations for clinical applications.

A deeper look at carrier proteome effects for single-cell proteomics

Multiplexing approaches using tandem mass tags with a carrier proteome to boost sensitivity have advanced single cell proteomics by mass spectrometry (SCoPE-MS). Here, we probe the carrier proteome effects in single cell proteomics with mixed species TMTpro-labeled samples. We demonstrate that carrier proteomes, while increasing overall identifications, dictate which proteins are identified. We show that quantitative precision and signal intensity are limited at high carrier levels, hindering the recognition of regulated proteins. Guidelines for optimized mass spectrometry acquisition parameters and best practices for fold-change or protein copy number-based comparisons are provided.

Spatial-proteomics reveals phospho-signaling dynamics at subcellular resolution

Dynamic change in subcellular localization of signaling proteins is a general concept that eukaryotic cells evolved for eliciting a coordinated response to stimuli. Mass spectrometry-based proteomics in combination with subcellular fractionation can provide comprehensive maps of spatio-temporal regulation of protein networks in cells, but involves laborious workflows that does not cover the phospho-proteome level. Here we present a high-throughput workflow based on sequential cell fractionation to profile the global proteome and phospho-proteome dynamics across six distinct subcellular fractions. We benchmark the workflow by studying spatio-temporal EGFR phospho-signaling dynamics in vitro in HeLa cells and in vivo in mouse tissues. Finally, we investigate the spatio-temporal stress signaling, revealing cellular relocation of ribosomal proteins in response to hypertonicity and muscle contraction. Proteomics data generated in this study can be explored through https://SpatialProteoDynamics.github.io .

Regulation of the Golgi Apparatus by p38 and JNK Kinases during Cellular Stress Responses

p38 and c-Jun N-terninal kinase (JNK) are activated in response to acute stress and inflammatory signals. Through modification of a plethora of substrates, these kinases profoundly re-shape cellular physiology for the optimal response to a harmful environment and/or an inflammatory state. Here, we utilized phospho-proteomics to identify several hundred substrates for both kinases. Our results indicate that the scale of signaling from p38 and JNK are of a similar magnitude. Among the many new targets, we highlight the regulation of the transcriptional regulators grb10-interacting GYF protein 1 and 2 (GIGYF1/2) by p38-dependent MAP kinase-activated protein kinase 2 (MK2) phosphorylation and 14–3–3 binding. We also show that the Golgi apparatus contains numerous substrates, and is a major target for regulation by p38 and JNK. When activated, these kinases mediate structural rearrangement of the Golgi apparatus, which positively affects protein flux through the secretory system. Our work expands on our knowledge about p38 and JNK signaling with important biological ramifications.

Faecal proteomics as a novel method to study mammalian behaviour and physiology

Mammalian faeces can be collected noninvasively during field research and provide valuable information on the ecology and evolution of the source individuals. Undigested food remains, genome/metagenome, steroid hormones, and stable isotopes obtained from faecal samples provide evidence on diet, host/symbiont genetics, and physiological status of the individuals. However, proteins in mammalian faeces have hardly been studied, which hinders the molecular investigations into the behaviour and physiology of the source individuals. Here, we apply mass spectrometry-based proteomics to faecal samples (n = 10), collected from infant, juvenile, and adult captive Japanese macaques (Macaca fuscata), to describe the proteomes of the source individual, of the food it consumed, and its intestinal microbes. The results show that faecal proteomics is a useful method to: (i) investigate dietary changes along with breastfeeding and weaning, (ii) reveal the taxonomic and histological origin of the food items consumed, and (iii) estimate physiological status inside intestinal tracts. These types of insights are difficult or impossible to obtain through other molecular approaches. Most mammalian species are facing extinction risk and there is an urgent need to obtain knowledge on their ecology and evolution for better conservation strategy. The faecal proteomics framework we present here is easily applicable to wild settings and other mammalian species, and provides direct evidence of their behaviour and physiology.

Human METTL18 is a histidine-specific methyltransferase that targets RPL3 and affects ribosome biogenesis and function

Protein methylation occurs primarily on lysine and arginine, but also on some other residues, such as histidine. METTL18 is the last uncharacterized member of a group of human methyltransferases (MTases) that mainly exert lysine methylation, and here we set out to elucidate its function. We found METTL18 to be a nuclear protein that contains a functional nuclear localization signal and accumulates in nucleoli. Recombinant METTL18 methylated a single protein in nuclear extracts and in isolated ribosomes from METTL18 knockout (KO) cells, identified as 60S ribosomal protein L3 (RPL3). We also performed an RPL3 interactomics screen and identified METTL18 as the most significantly enriched MTase. We found that His-245 in RPL3 carries a 3-methylhistidine (3MH; τ-methylhistidine) modification, which was absent in METTL18 KO cells. In addition, both recombinant and endogenous METTL18 were found to be automethylated at His-154, thus further corroborating METTL18 as a histidine-specific MTase. Finally, METTL18 KO cells displayed altered pre-rRNA processing, decreased polysome formation and codon-specific changes in mRNA translation, indicating that METTL18-mediated methylation of RPL3 is important for optimal ribosome biogenesis and function. In conclusion, we have here established METTL18 as the second human histidine-specific protein MTase, and demonstrated its functional relevance.

Human DDK rescues stalled forks and counteracts checkpoint inhibition at unfired origins to complete DNA replication

Eukaryotic genomes replicate via spatially and temporally regulated origin firing. Cyclin-dependent kinase (CDK) and Dbf4-dependent kinase (DDK) promote origin firing, whereas the S phase checkpoint limits firing to prevent nucleotide and RPA exhaustion. We used chemical genetics to interrogate human DDK with maximum precision, dissect its relationship with the S phase checkpoint, and identify DDK substrates. We show that DDK inhibition (DDKi) leads to graded suppression of origin firing and fork arrest. S phase checkpoint inhibition rescued origin firing in DDKi cells and DDK-depleted Xenopus egg extracts. DDKi also impairs RPA loading, nascent-strand protection, and fork restart. Via quantitative phosphoproteomics, we identify the BRCA1-associated (BRCA1-A) complex subunit MERIT40 and the cohesin accessory subunit PDS5B as DDK effectors in fork protection and restart. Phosphorylation neutralizes autoinhibition mediated by intrinsically disordered regions in both substrates. Our results reveal mechanisms through which DDK controls the duplication of large vertebrate genomes.

The methyltransferase METTL9 mediates pervasive 1-methylhistidine modification in mammalian proteomes

Post-translational methylation plays a crucial role in regulating and optimizing protein function. Protein histidine methylation, occurring as the two isomers 1- and 3-methylhistidine (1MH and 3MH), was first reported five decades ago, but remains largely unexplored. Here we report that METTL9 is a broad-specificity methyltransferase that mediates the formation of the majority of 1MH present in mouse and human proteomes. METTL9-catalyzed methylation requires a His-x-His (HxH) motif, where "x" is preferably a small amino acid, allowing METTL9 to methylate a number of HxH-containing proteins, including the immunomodulatory protein S100A9 and the NDUFB3 subunit of mitochondrial respiratory Complex I. Notably, METTL9-mediated methylation enhances respiration via Complex I, and the presence of 1MH in an HxH-containing peptide reduced its zinc binding affinity. Our results establish METTL9-mediated 1MH as a pervasive protein modification, thus setting the stage for further functional studies on protein histidine methylation.

Causal integration of multi-omics data with prior knowledge to generate mechanistic hypotheses

Multi-omics datasets can provide molecular insights beyond the sum of individual omics. Various tools have been recently developed to integrate such datasets, but there are limited strategies to systematically extract mechanistic hypotheses from them. Here, we present COSMOS (Causal Oriented Search of Multi-Omics Space), a method that integrates phosphoproteomics, transcriptomics, and metabolomics datasets. COSMOS combines extensive prior knowledge of signaling, metabolic, and gene regulatory networks with computational methods to estimate activities of transcription factors and kinases as well as network-level causal reasoning. COSMOS provides mechanistic hypotheses for experimental observations across multi-omics datasets. We applied COSMOS to a dataset comprising transcriptomics, phosphoproteomics, and metabolomics data from healthy and cancerous tissue from eleven clear cell renal cell carcinoma (ccRCC) patients. COSMOS was able to capture relevant crosstalks within and between multiple omics layers, such as known ccRCC drug targets. We expect that our freely available method will be broadly useful to extract mechanistic insights from multi-omics studies.

ProAlanase is an Effective Alternative to Trypsin for Proteomics Applications and Disulfide Bond Mapping

Trypsin is the protease of choice in bottom-up proteomics. However, its application can be limited by the amino acid composition of target proteins and the pH of the digestion solution. In this study we characterize ProAlanase, a protease from the fungus Aspergillus niger that cleaves primarily on the C-terminal side of proline and alanine residues. ProAlanase achieves high proteolytic activity and specificity when digestion is carried out at acidic pH (1.5) for relatively short (2 h) time periods. To elucidate the potential of ProAlanase in proteomics applications, we conducted a series of investigations comprising comparative multi-enzymatic profiling of a human cell line proteome, histone PTM analysis, ancient bone protein identification, phosphosite mapping and de novo sequencing of a proline-rich protein and disulfide bond mapping in mAb. The results demonstrate that ProAlanase is highly suitable for proteomics analysis of the arginine- and lysine-rich histones, enabling high sequence coverage of multiple histone family members. It also facilitates an efficient digestion of bone collagen thanks to the cleavage at the C terminus of hydroxyproline which is highly prevalent in collagen. This allows to identify complementary proteins in ProAlanase- and trypsin-digested ancient bone samples, as well as to increase sequence coverage of noncollagenous proteins. Moreover, digestion with ProAlanase improves protein sequence coverage and phosphosite localization for the proline-rich protein Notch3 intracellular domain (N3ICD). Furthermore, we achieve a nearly complete coverage of N3ICD protein by de novo sequencing using the combination of ProAlanase and tryptic peptides. Finally, we demonstrate that ProAlanase is efficient in disulfide bond mapping, showing high coverage of disulfide-containing regions in a nonreduced mAb.

FRMD6 has tumor suppressor functions in prostate cancer

Available tools for prostate cancer (PC) prognosis are suboptimal but may be improved by better knowledge about genes driving tumor aggressiveness. Here, we identified FRMD6 (FERM domain-containing protein 6) as an aberrantly hypermethylated and significantly downregulated gene in PC. Low FRMD6 expression was associated with postoperative biochemical recurrence in two large PC patient cohorts. In overexpression and CRISPR/Cas9 knockout experiments in PC cell lines, FRMD6 inhibited viability, proliferation, cell cycle progression, colony formation, 3D spheroid growth, and tumor xenograft growth in mice. Transcriptomic, proteomic, and phospho-proteomic profiling revealed enrichment of Hippo/YAP and c-MYC signaling upon FRMD6 knockout. Connectivity Map analysis and drug repurposing experiments identified pyroxamide as a new potential therapy for FRMD6 deficient PC cells. Finally, we established orthotropic Frmd6 and Pten, or Pten only (control) knockout in the ROSA26 mouse prostate. After 12 weeks, Frmd6/Pten double knockouts presented high-grade prostatic intraepithelial neoplasia (HG-PIN) and hyperproliferation, while Pten single-knockouts developed only regular PIN lesions and displayed lower proliferation. In conclusion, FRMD6 was identified as a novel tumor suppressor gene and prognostic biomarker candidate in PC.

Effects of active farnesoid X receptor on GLUTag enteroendocrine L cells

Activated transcription factor (TF) farnesoid X receptor (FXR) represses glucagon-like peptide-1 (GLP-1) secretion in enteroendocrine L cells. This, in turn, reduces insulin secretion, which is triggered when β cells bind GLP-1. Preventing FXR activation could boost GLP-1 production and insulin secretion. Yet, FXR's broader role in L cell biology still lacks understanding. Here, we show that FXR is a multifaceted TF in L cells using proteomics and gene expression data generated on GLUTag L cells. Most striking, 252 proteins regulated upon glucose stimulation have their abundances neutralized upon FXR activation. Mitochondrial repression or glucose import block are likely mechanisms of this. Further, FXR physically targets bile acid metabolism proteins, growth factors and other TFs, regulates ChREBP, while extensive text-mining found 30 FXR-regulated proteins to be well-known in L cell biology. Taken together, this outlines FXR as a powerful TF, where GLP-1 secretion block is just one of many downstream effects.

Multi-omic detection of Mycobacterium leprae in archaeological human dental calculus

Mineralized dental plaque (calculus) has proven to be an excellent source of ancient biomolecules. Here we present a Mycobacterium leprae genome (6.6-fold), the causative agent of leprosy, recovered via shotgun sequencing of sixteenth-century human dental calculus from an individual from Trondheim, Norway. When phylogenetically placed, this genome falls in branch 3I among the diversity of other contemporary ancient strains from Northern Europe. Moreover, ancient mycobacterial peptides were retrieved via mass spectrometry-based proteomics, further validating the presence of the pathogen. Mycobacterium leprae can readily be detected in the oral cavity and associated mucosal membranes, which likely contributed to it being incorporated into this individual's dental calculus. This individual showed some possible, but not definitive, evidence of skeletal lesions associated with early-stage leprosy. This study is the first known example of successful multi-omics retrieval of M. leprae from archaeological dental calculus. Furthermore, we offer new insights into dental calculus as an alternative sample source to bones or teeth for detecting and molecularly characterizing M. leprae in individuals from the archaeological record.

This article is part of the theme issue ‘Insights into health and disease from ancient biomolecules’.

Alternative Translation Initiation Generates a Functionally Distinct Isoform of the Stress-Activated Protein Kinase MK2

Alternative translation is an important mechanism of post-transcriptional gene regulation leading to the expression of different protein isoforms originating from the same mRNA. Here, we describe an abundant long isoform of the stress/p38^MAPK-activated protein kinase MK2. This isoform is constitutively translated from an alternative CUG translation initiation start site located in the 5' UTR of its mRNA. The RNA helicase eIF4A1 is needed to ensure translation of the long and the known short isoforms of MK2, of which the molecular properties were determined. Only the short isoform phosphorylated Hsp27 in vivo, supported migration and stress-induced immediate early gene (IEG) expression. Interaction profiling revealed short-isoform-specific binding partners that were associated with migration. In contrast, the long isoform contains at least one additional phosphorylatable serine in its unique N terminus. In sum, our data reveal a longer isoform of MK2 with distinct physiological properties.

Author Correction: The dental proteome of Homo antecessor

An amendment to this paper has been published and can be accessed via a link at the top of the paper.