A Scalable Approach for Protein False Discovery Rate Estimation in Large Proteomic Data Sets

Identification of liver proteins as biomarker for postmortem diagnosis of heat stroke through proteomics

Recently, the incidence and mortality of heat stroke (HS) have risen catastrophically. However, postmortem diagnosis of HS is challenging owing to the lack of characteristic morphological markers. Liver damage can often serve as a direct cause of death in HS. Therefore, this study aimed to identify protein biomarkers in the liver and to evaluate their utility as diagnostic biomarkers for HS. The morphological and biochemical tests of HS rats models revealed hydropic degeneration, hepatocyte necrosis, and impaired liver function. 283 differentially expressed proteins between the HS and control groups were screened by proteomic analysis. Subsequently, HSPA4, GGCX, and CYP2B6 were selected as candidate biomarkers based on Proteomic results, Western blotting and immunohistochemistry results in HS rats. These three candidate biomarkers were further validated as diagnostic protein biomarkers for HS death based on the immunohistochemistry results of 29 human cases. Finally, receiver operating characteristic analysis indicated that the combination of HSPA4, GGCX and CYP2B6 provided optimal diagnostic efficacy for HS, with an area under the curve of over 0.999. In conclusion, we propose that the integrating morphological findings, liver function analysis, and protein biomarkers (HSPA4, GGCX, and CYP2B6) in liver could be used for HS diagnosis in forensic practices.

TOM20-driven E3 ligase recruitment regulates mitochondrial dynamics through PLD6

Mitochondrial homeostasis is maintained through complex regulatory mechanisms, including the balance of mitochondrial dynamics involving fusion and fission processes. A central player in this regulation is the ubiquitin-proteasome system (UPS), which controls the degradation of pivotal mitochondrial proteins. In this study, we identified cullin-RING E3 ligase 2 (CRL2) and its substrate receptor, FEM1B, as critical regulators of mitochondrial dynamics. Through proteomic analysis, we demonstrate here that FEM1B controls the turnover of PLD6, a key regulator of mitochondrial dynamics. Using structural and biochemical approaches, we show that FEM1B physically interacts with PLD6 and that this interaction is facilitated by the direct association of FEM1B with the mitochondrial import receptor TOM20. Ablation of FEM1B or disruption of the FEM1B-TOM20 interaction impairs PLD6 degradation and induces mitochondrial defects, phenocopying PLD6 overexpression. These findings underscore the importance of FEM1B in maintaining mitochondrial morphology and provide further mechanistic insights into how the UPS regulates mitochondrial homeostasis.

ARMC1 partitions between distinct complexes and assembles MIRO with MTFR to control mitochondrial distribution

Maintaining an optimal mitochondrial distribution is critical to ensure an adequate supply of energy and metabolites to support important cellular functions. How cells balance dynamic mitochondrial processes to achieve homeostasis is incompletely understood. Here, we show that ARMC1 partitioning between distinct mitochondrial protein complexes is a key determinant of mitochondrial distribution. In one complex, the mitochondrial trafficking adaptor MIRO recruits ARMC1, which mediates the assembly of a mitochondrial fission regulator (MTFR). MTFR stability depends on ARMC1, and MIRO-MTFR complexes specifically antagonize retrograde mitochondrial movement. In another complex, DNAJC11 facilitates ARMC1 release from mitochondria. Disrupting MIRO-MTFR assembly fails to rescue aberrant mitochondrial distributions clustered in the perinuclear area observed with ARMC1 deletion, while disrupting ARMC1 interaction with DNAJC11 leads to excessive mitochondrially localized ARMC1 and distinct mitochondrial defects. Thus, the abundance and trafficking impact of MIRO-MTFR complexes require ARMC1, whose mito-cytoplasmic shuttling balanced by DNAJC11 tunes steady-state mitochondrial distributions.

Offset Mass Carrier Proteome Improves Quantification of Multiplexed Single Cell Proteomics

Multiplexed single cell proteomics by mass spectrometry (scpMS) approaches currently offer the highest throughput as measured by cells analyzed per day. These methods employ isobaric labels and typically a carrier proteome, a sample added at 20 to 500× the single cell level that improves peptide sampling and identification. Peptides from the carrier and single cell proteomes exist within the same precursor isotopic cluster and are co-isolated for identification and quantification. This represents a challenge as high levels of carrier proteome limit the sampling of peptide ions from single cell samples and can potentially lead to decreased accuracy of quantitative measurements. Here, we address this limitation by introducing a triggered by offset mass acquisition method for scpMS (toma-scpMS) that utilizes a carrier proteome labeled with nonisobaric tags that have the same chemical composition but different mass as the labels used for quantitative multiplexing. Within toma-scpMS, the carrier proteome and single cell proteome are separated at the precursor level, enabling separate isolation, fragmentation, and quantitation of the single cell samples. To enable this workflow, we implemented a custom data acquisition scheme within inSeqAPI, an instrument application programming interface program that performed real-time identification of carrier proteome peptides and subsequent triggering of offset single cell quantification scans. We demonstrate that toma-scpMS is more robust to high levels of carrier proteome and offers superior quantitative accuracy as compared to traditional multiplexed scpMS approaches when similar carrier proteome levels are employed.

Site-specific activation of the proton pump inhibitor rabeprazole by tetrathiolate zinc centres

Proton pump inhibitors have become top-selling drugs worldwide. Serendipitously discovered as prodrugs that are activated by protonation in acidic environments, proton pump inhibitors inhibit stomach acid secretion by covalently modifying the gastric proton pump. Despite their widespread use, alternative activation mechanisms and potential target proteins in non-acidic environments remain poorly understood. Employing a chemoproteomic approach, we found that the proton pump inhibitor rabeprazole selectively forms covalent conjugates with zinc-binding proteins. Focusing on DENR, a protein with a C4 zinc cluster (that is, zinc coordinated by four cysteines), we show that rabeprazole is activated by the zinc ion and subsequently conjugated to zinc-coordinating cysteines. Our results suggest that drug binding, activation and conjugation take place rapidly within the zinc coordination sphere. Finally, we provide evidence that other proton pump inhibitors can be activated in the same way. We conclude that zinc acts as a Lewis acid, obviating the need for low pH, to promote the activation and conjugation of proton pump inhibitors in non-acidic environments.

Comparative Analysis of Data-Driven Rescoring Platforms for Improved Peptide Identification in HeLa Digest Samples

Mass spectrometry is a critical tool to understand complex changes in biological processes. Despite significant advances in search engine technology, many spectra remain unassigned. This research evaluates the performance of three rescoring platforms, Oktoberfest, MS2Rescore, and inSPIRE, using MaxQuant output. The results indicated a substantial increase in identifications at the peptide level (40%-53%) and PSM level (64%-67%). However, some peptides were lost due to limitations in processing posttranslational modifications (PTMs)-with up to 75% of lost peptides exhibiting PTMs. Each platform displayed distinct strengths and weaknesses. For instance, inSPIRE performed best in terms of peptide identifications and unique peptides, while MS2Rescore performed better for PSMs at higher FDR values. Differences in platform performance stemmed from different sources: original search engine feature selection, type of ion series predicted, retention time predictor, and PTMs compatibility. Overall, inSPIRE showed a superior ability to harness original search engine results. Taken all together, rescoring platforms clearly outperformed original search results; however, they demanded additional computation time (up to 77%) and manual adjustments. The findings here underline the necessity of integrating rescoring platforms into current proteomics pipelines but also address some challenges in their implementation and optimization. Future integrated platforms may help enhance adoption.

Ergothioneine controls mitochondrial function and exercise performance via direct activation of MPST

Ergothioneine (EGT) is a diet-derived, atypical amino acid that accumulates to high levels in human tissues. Reduced EGT levels have been linked to age-related disorders, including neurodegenerative and cardiovascular diseases, while EGT supplementation is protective in a broad range of disease and aging models. Despite these promising data, the direct and physiologically relevant molecular target of EGT has remained elusive. Here, we use a systematic approach to identify how mitochondria remodel their metabolome in response to exercise training. From these data, we find that EGT accumulates in muscle mitochondria upon exercise training. Proteome-wide thermal stability studies identify 3-mercaptopyruvate sulfurtransferase (MPST) as a direct molecular target of EGT; EGT binds to and activates MPST, thereby boosting mitochondrial respiration and exercise training performance in mice. Together, these data identify the first physiologically relevant EGT target and establish the EGT-MPST axis as a molecular mechanism for regulating mitochondrial function and exercise performance.

The DNA methylation landscape of primary triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a clinically challenging and molecularly heterogenous breast cancer subgroup. Here, we investigate the DNA methylation landscape of TNBC. By analyzing tumor methylome profiles and accounting for the genomic context of CpG methylation, we divide TNBC into two epigenetic subtypes corresponding to a Basal and a non-Basal group, in which characteristic transcriptional patterns are correlated with DNA methylation of distal regulatory elements and epigenetic regulation of key steroid response genes and developmental transcription factors. Further subdivision of the Basal and non-Basal subtypes identifies subgroups transcending genetic and proposed TNBC mRNA subtypes, demonstrating widely differing immunological microenvironments, putative epigenetically-mediated immune evasion strategies, and a specific metabolic gene network in older patients that may be epigenetically regulated. Our study attempts to target the epigenetic backbone of TNBC, an approach that may inform future studies regarding tumor origins and the role of the microenvironment in shaping the cancer epigenome.

Relative quantification of proteins and post-translational modifications in proteomic experiments with shared peptides: a weight-based approach

MOTIVATION

Bottom-up mass spectrometry-based proteomics studies changes in protein abundance and structure across conditions. Since the currency of these experiments are peptides, i.e. subsets of protein sequences that carry the quantitative information, conclusions at a different level must be computationally inferred. The inference is particularly challenging in situations where the peptides are shared by multiple proteins or post-translational modifications. While many approaches infer the underlying abundances from unique peptides, there is a need to distinguish the quantitative patterns when peptides are shared.

RESULTS

We propose a statistical approach for estimating protein abundances, as well as site occupancies of post-translational modifications, based on quantitative information from shared peptides. The approach treats the quantitative patterns of shared peptides as convex combinations of abundances of individual proteins or modification sites, and estimates the abundance of each source in a sample together with the weights of the combination. In simulation-based evaluations, the proposed approach improved the precision of estimated fold changes between conditions. We further demonstrated the practical utility of the approach in experiments with diverse biological objectives, ranging from protein degradation and thermal proteome stability, to changes in protein post-translational modifications.

AVAILABILITY AND IMPLEMENTATION

The approach is implemented in an open-source R package MSstatsWeightedSummary. The package is currently available at https://github.com/Vitek-Lab/MSstatsWeightedSummary (doi: 10.5281/zenodo.14662989). Code required to reproduce the results presented in this article can be found in a repository https://github.com/mstaniak/MWS_reproduction (doi: 10.5281/zenodo.14656053).

RBM43 controls PGC1α translation and a PGC1α-STING signaling axis

Obesity is associated with systemic inflammation that impairs mitochondrial function. This disruption curtails oxidative metabolism, limiting adipocyte lipid metabolism and thermogenesis, a metabolically beneficial program that dissipates chemical energy as heat. Here, we show that PGC1α, a key governor of mitochondrial biogenesis, is negatively regulated at the level of its mRNA translation by the RNA-binding protein RBM43. RBM43 is induced by inflammatory cytokines and suppresses mitochondrial biogenesis in a PGC1α-dependent manner. In mice, adipocyte-selective Rbm43 disruption elevates PGC1α translation and oxidative metabolism. In obesity, Rbm43 loss improves glucose tolerance, reduces adipose inflammation, and suppresses activation of the innate immune sensor cGAS-STING in adipocytes. We further identify a role for PGC1α in safeguarding against cytoplasmic accumulation of mitochondrial DNA, a cGAS ligand. The action of RBM43 defines a translational regulatory axis by which inflammatory signals dictate cellular energy metabolism and contribute to metabolic disease pathogenesis.

Potent and selective SETDB1 covalent negative allosteric modulator reduces methyltransferase activity in cells

A promising drug target, SETDB1, is a dual methyl-lysine (Kme) reader and methyltransferase implicated in cancer and neurodegenerative disease progression. To help understand the role of the triple Tudor domain (3TD) of SETDB1, its Kme reader, we first identify a low micromolar potency small molecule ligand, UNC6535, which occupies simultaneously both the TD2 and TD3 reader binding sites. Further optimization leads to the discovery of UNC10013, a covalent 3TD ligand targeting Cys385 of SETDB1. UNC10013 is potent with a kinact/KI of 1.0 × 106 M-1s-1 and demonstrates proteome-wide selectivity. In cells, negative allosteric modulation of SETDB1-mediated Akt methylation occurs after treatment with UNC10013. Therefore, UNC10013 is a potent, selective, and cell-active covalent ligand for the 3TD of SETDB1, demonstrating negative allosteric modulator properties and making it a promising tool to study the biological role of SETDB1 in disease progression.

Functional-proteomics-based investigation of the cellular response to farnesyltransferase inhibition in lung cancer

Farnesylation is a lipid post-translational modification of proteins crucial for protein membrane anchoring and cellular signaling. Farnesyltransferase inhibitors (FTIs), such as tipifarnib, are being tested in cancer therapy. However, the full impact of FTIs on farnesylation substrates remains poorly understood, thus limiting their use in precision medicine. In this study, we performed a global proteomics analysis to investigate farnesylation and the effects of tipifarnib in lung cancer cell lines. Using metabolic labeling and mass spectrometry, we identified farnesylated proteins and mapped their subcellular localization. We also analyzed tipifarnib-dependent protein relocalization and proteome-wide changes. Key findings include the potential therapeutic value of FTIs for NRAS-mutated melanoma and GNAQ/GNA11-mutated uveal melanoma by inhibiting INPP5A farnesylation. Additionally, we identified a synergistic drug combination involving tipifarnib and a ferroptosis inducer and discovered PTP4A1 as a regulator of interferon signaling. Our data, covering 15,080 proteins, offer valuable insights for future studies of farnesylation and FTIs.

Sensitive and Accurate Proteome Profiling of Embryogenesis Using Real-Time Search and TMTproC Quantification

Multiplexed proteomics has become a powerful tool for investigating biological systems. Using balancer-peptide conjugates (e.g., TMTproC complementary ions) in the MS2 spectra for quantification circumvents the ratio distortion problem inherent in multiplexed proteomics. However, TMTproC quantification scans require long Orbitrap transients and extended ion injection times to achieve sufficient ion statistics and spectral resolution. Real-time search (RTS) algorithms have demonstrated increased speed and sensitivity by selectively informing precursor peak quantification. Here, we combine complementary ion quantification with RTS (TMTproC-RTS) to enhance sensitivity while maintaining accuracy and precision in quantitative proteomics at the MS2 level. We demonstrate the utility of this method by quantifying protein dynamics during the embryonic development of Drosophila melanogaster (fly), Ciona robusta (sea squirt), and Xenopus laevis (frog). We quantify 7.8k, 8.6k, and 12.7k proteins in each organism, which is an improvement of 12%, 13%, and 14%, respectively, compared with naive TMTproC analysis. For all three organisms, the newly acquired data outperform previously published datasets and provide a diverse, deep, and accurate database of protein dynamics during embryogenesis, which will advance the study of evolutionary comparison in early embryogenesis.

A protein corona modulates the function of mineralization-competent matrix vesicles

Mineralizing cells release a special class of extracellular vesicles known as matrix vesicles (MV), crucial for bone mineralization. Following their release, MV anchor to the extracellular matrix (ECM), where their highly specialized enzymatic machinery facilitates the formation of seed mineral within the MV's lumen, subsequently releasing it onto the ECM. However, how MV propagate mineral onto the collagenous ECM remains unclear. In this study, we address these questions by exploring the "protein corona" paradigm whereby nanoparticles entering a biological milieu become cloaked by a corona of soluble proteins modifying their biological functions. We isolated native MV from the growth plates of chicken embryos. After removing the protein corona from the native MV using high ionic strength buffer, we obtained shaved MV. Reconstituted MVs were produced by incubating shaved MV with the removed protein corona constituents. Our results show that both the removal and reconstitution of protein corona significantly affect the biochemical and physicochemical properties of MV, resulting in 3 well-defined groups. Shaved MV exhibited an increase in tissue nonspecific alkaline phosphatase (TNAP) activity and a decrease in mineral deposition compared to native MV. Reconstituted MV partially recovered these functions, showing a reduction of TNAP activity and mineral deposition compared to native MV. Furthermore, changes in the protein corona affect the MV ability to anchor to the collagenous ECM, which is crucial for initiating the propagation of the mineral phase within this organic matrix. Proteomic analyses revealed changes in the protein profile of the MV resulting from the removal of the protein corona, indicating that shaved proteins were primarily related to external structural and ECM organization and catabolism. These findings underscore the role of the protein corona in modulating the mineralization capabilities of MV. Understanding these interactions could lead to new therapeutic strategies for enhancing bone repair and regeneration.

mTORC1 regulates the pyrimidine salvage pathway by controlling UCK2 turnover via the CTLH-WDR26 E3 ligase

One critical aspect of cell proliferation is increased nucleotide synthesis, including pyrimidines. Pyrimidines are synthesized through de novo and salvage pathways. Prior studies established that the mammalian target of rapamycin complex 1 (mTORC1) promotes pyrimidine synthesis by activating the de novo pathway for cell proliferation. However, the involvement of mTORC1 in regulating the salvage pathway remains unclear. Here, we report that mTORC1 controls the half-life of uridine cytidine kinase 2 (UCK2), the rate-limiting enzyme in the salvage pathway. Specifically, UCK2 is degraded via the CTLH-WDR26 E3 complex during mTORC1 inhibition, which is prevented when mTORC1 is active. We also find that UCK1, an isoform of UCK2, affects the turnover of UCK2 by influencing its cellular localization. Importantly, altered UCK2 levels through the mTORC1-CTLH E3 pathway affect pyrimidine salvage and the efficacy of pyrimidine analog prodrugs. Therefore, mTORC1-CTLH E3-mediated degradation of UCK2 adds another layer of complexity to mTORC1's role in regulating pyrimidine metabolism.

Global cellular proteo-lipidomic profiling of diverse lysosomal storage disease mutants using nMOST

Lysosomal storage diseases (LSDs) comprise ~50 monogenic disorders marked by the buildup of cellular material in lysosomes, yet systematic global molecular phenotyping of proteins and lipids is lacking. We present a nanoflow-based multiomic single-shot technology (nMOST) workflow that quantifies HeLa cell proteomes and lipidomes from over two dozen LSD mutants. Global cross-correlation analysis between lipids and proteins identified autophagy defects, notably the accumulation of ferritinophagy substrates and receptors, especially in NPC1-/- and NPC2-/- mutants, where lysosomes accumulate cholesterol. Autophagic and endocytic cargo delivery failures correlated with elevated lysophosphatidylcholine species and multilamellar structures visualized by cryo-electron tomography. Loss of mitochondrial cristae, MICOS complex components, and OXPHOS components rich in iron-sulfur cluster proteins in NPC2-/- cells was largely alleviated when iron was provided through the transferrin system. This study reveals how lysosomal dysfunction affects mitochondrial homeostasis and underscores nMOST as a valuable discovery tool for identifying molecular phenotypes across LSDs.

Optimization of protein identifications through the use of different chromatographic approaches and bioinformatic pipelines

RATIONALE

Selection of proteomic workflows for a given project can be a daunting task. This research provides a guide outlining the impact on protein identification of different steps such as chromatographic separation, data acquisition strategies, and bioinformatic pipelines. The data presented here will help experts and nonexpert proteomic users to increase proteome coverage and peptide identification.

METHODS

HeLa protein digests were analyzed through different C18 chromatographic columns (15 and 50 cm in length), using top 12 data-dependent acquisition (DDA), top 20 DDA, and data-independent acquisition (DIA) with a nanospray source in positive mode in a Thermo Q Exactive instrument. The raw data were analyzed using different search engines, rescoring approaches, and multi-engine searches. The results were analyzed in the context of peptide and protein identifications, precursor properties, and computation requirements to understand the differences between methods.

RESULTS

Our results showed that higher column lengths and top N DDA approaches were able to significantly increase protein identifications. The use of multiple search engines yielded limited gains, whereas the use of rescoring methods clearly outperformed other strategies. Finally, DIA approaches, although successful at generating new identifications, had a limited performance influenced by the previous collection of DDA data, which could prohibitively increase instrument time. Nonetheless, the use of library-free methods showed promising results.

CONCLUSIONS

Our results highlight the impact of different experimental approaches on proteome coverage. Changes in chromatographic columns, data acquisition, or bioinformatic analysis can significantly increase the number of protein identifications (>400%). Thus, this research provides a reference upon which to build a successful proteomic workflow with different considerations at every step.

N88S seipin-related seipinopathy is a lipidopathy associated with loss of iron homeostasis

BACKGROUND

Seipin is a protein encoded by the BSCL2 gene in humans and SEI1 gene in yeast, forming an Endoplasmic Reticulum (ER)-bound homo-oligomer. This oligomer is crucial in targeting ER-lipid droplet (LD) contact sites, facilitating the delivery of triacylglycerol (TG) to nascent LDs. Mutations in BSCL2, particularly N88S and S90L, lead to seipinopathies, which correspond to a cohort of motor neuron diseases (MNDs) characterized by the accumulation of misfolded N88S seipin into inclusion bodies (IBs) and cellular dysfunctions.

METHODS

Quantitative untargeted mass spectrometric proteomic and lipidomic analyses were conducted to examine changes in protein and lipid abundance in wild-type (WT) versus N88S seipin-expressing mutant cells. Differentially expressed proteins were categorized into functional networks to highlight altered protein functions and signaling pathways. Statistical comparisons were made using unpaired Student's t-tests or two-way ANOVA followed by Tukey´s / Šídák's multiple comparisons tests. P-values < 0.05 are considered significant.

RESULTS

In a well-established yeast model of N88S seipinopathy, misfolded N88S seipin forms IBs and exhibits higher levels of ER stress, leading to decreased cell viability due to increased reactive oxygen species (ROS), oxidative damage, lipid peroxidation, and reduced antioxidant activity. Proteomic and lipidomic analyses revealed alterations in phosphatidic acid (PA) levels, associated with disrupted inositol metabolism and decreased flux towards phospholipid biosynthesis. Importantly, deregulation of lipid metabolism contributed to ER stress beyond N88S seipin misfolding and IB formation. Additionally, the model exhibited deregulated iron (Fe) homeostasis during lifespan. N88S seipin-expressing cells showed impaired ability to cope with iron deficiency. This was linked to changes in the expression of Aft1p-controlled iron regulon genes, including the mRNA-binding protein CTH2 and the high-affinity iron transport system member FET3, in a p38/Hog1p- and Msn2p/Msn4p-dependent manner. Importantly, we unraveled a novel link between inositol metabolism and activation of the iron regulon in cells expressing the N88S seipin mutation. Despite iron accumulation, this was not associated with oxidative stress.

CONCLUSIONS

The study highlights that the effects of N88S seipin mutation extend beyond protein misfolding, with significant disruptions in lipid metabolism and iron homeostasis. This research marks a substantial advance in understanding and defining the roles of proteins and signaling pathways that contribute to human seipinopathy. Altered cellular processes, as well as potential therapeutic targets and biomarkers, were identified and can be explored in translational studies using human cell models.

Proteomic signatures of Alzheimer's disease and Lewy body dementias: A comparative analysis

INTRODUCTION

We aimed to identify unique proteomic signatures of Alzheimer's disease (AD), dementia with Lewy bodies (DLB), and Parkinson's disease dementia (PDD).

METHODS

We conducted a comparative proteomic analysis of 33 post mortem brains from AD, DLB, and PDD individuals without dementia focusing on prefrontal, cingulate, and parietal cortices, using weighted gene co-expression network analyses with differential enrichment analysis.

RESULTS

Network modules revealed hub proteins common to all dementias. Lewy body dementias differed from AD by reduced levels of the autophagy protein p62 (SQSTM1), whereas DLB was distinguished from both AD and PDD by altered TRIM33 and cysteine/glutamate transporter (SLC7A11) across brain regions. An increase in mitochondrial and synaptic proteins was related to better cognition whereas enrichment in the extracellular matrix, complement system, and autophagy proteins was associated with greater cognitive impairment.

DISCUSSION

Our study offers valuable insights into the network-based biomarker characterization of molecular signatures of AD, DLB, and PDD.

HIGHLIGHTS

Reduced levels of the autophagy protein p62 (SQSTM1) differentiated Lewy body dementias from Alzheimer's disease (AD) across multiple brain regions. Dementia with Lewy bodies (DLB) was distinguished from both AD and Parkinson's disease dementia (PDD) by altered TRIM33 and cysteine/glutamate transporter (SLC7A11) levels across brain regions. Key mitochondrial oxidative phosphorylation proteins (e.g., COX7A2, TOMM40L, NDUFV1), and synaptic proteins (e.g., GABRB3, GABRB2, GLUA3, GLUA4, SNAP47, dynamin1) were more abundant in preserved cognitive states. Extracellular matrix proteins and members of the complement system (decorin, biglycan, C4A, C4B) showed a strong positive correlation with cognitive decline.

Redesigning error control in cross-linking mass spectrometry enables more robust and sensitive protein-protein interaction studies

Cross-linking mass spectrometry (XL-MS) allows characterizing protein-protein interactions (PPIs) in native biological systems by capturing cross-links between different proteins (inter-links). However, inter-link identification remains challenging, requiring dedicated data filtering schemes and thorough error control. Here, we benchmark existing data filtering schemes combined with error rate estimation strategies utilizing concatenated target-decoy protein sequence databases. These workflows show shortcomings either in sensitivity (many false negatives) or specificity (many false positives). To ameliorate the limited sensitivity without compromising specificity, we develop an alternative target-decoy search strategy using fused target-decoy databases. Furthermore, we devise a different data filtering scheme that takes the inter-link context of the XL-MS dataset into account. Combining both approaches maintains low error rates and minimizes false negatives, as we show by mathematical simulations, analysis of experimental ground-truth data, and application to various biological datasets. In human cells, inter-link identifications increase by 75% and we confirm their structural accuracy through proteome-wide comparisons to AlphaFold2-derived models. Taken together, target-decoy fusion and context-sensitive data filtering deepen and fine-tune XL-MS-based interactomics.

Cerebrospinal fluid proteomics reveals the innate immunity and blood-brain barrier dysregulation in a patient with multidrug-resistant Acinetobacter baumannii ventriculitis treated with intrathecal and intravenous polymyxin B

Acinetobacter baumannii is a major pathogen of nosocomial meningitis and ventriculitis. Due to very limited antibiotic treatment options, polymyxins are often used as a last-line therapy. To optimise polymyxin use in the intraventricular environment, cerebrospinal fluid (CSF) proteomics was employed to investigate host-pathogen-polymyxin interactions in a 69-year-old patient with multidrug-resistant A. baumannii ventriculitis treated with a combination of intrathecal (ITH; 50,000 IU q24h/q48h), intraventricular (IVT; 50,000 IU q48h), and intravenous (500,000 IU, q12h) polymyxin B. CSF was collected before the first ITH dose in the ICU (0 h) and at 24 h, Day 7 and Day 26. The proteome was quantified at each time point and proteins with Qvalue <0.05 and fold change >1.2 were considered differentially expressed. Within 24 h of ITH/IVT polymyxin B administration, the innate immune system and neuroimmunity were highly active, evidenced by up-regulation of various pathways related to pathogen invasion, endocytosis and neutrophil degranulation. Blood-brain barrier impairment had worsened at 24 h but signs of repair were evident on Day 7 and Day 26. This is the first CSF proteomic study with polymyxins. Our findings provide critical mechanistic insights into optimizing ITH/IVT polymyxin administration.

Dextromethorphan inhibits collagen and collagen-like cargo secretion to ameliorate lung fibrosis

Excessive deposition of fibrillar collagen in the interstitial extracellular matrix (ECM) of human lung tissue causes fibrosis, which can ultimately lead to organ failure. Despite our understanding of the molecular mechanisms underlying the disease, no cure for pulmonary fibrosis has yet been found. We screened a drug library and found that dextromethorphan (DXM), a cough expectorant, reduced the amount of excess fibrillar collagen deposited in the ECM in cultured primary human lung fibroblasts, a bleomycin mouse model, and a cultured human precision-cut lung slice model of lung fibrosis. The reduced extracellular fibrillar collagen upon DXM treatment was due to reversible trafficking inhibition of collagen type I (COL1) in the endoplasmic reticulum (ER) in TANGO1- and HSP47-positive structures. Mass spectrometric analysis showed that DXM promoted hyperhydroxylation of proline and lysine residues on various collagens (COL1, COL3, COL4, COL5, COL7, and COL12) and latent transforming growth factor-β-binding protein (LTBP1 and LTBP2) peptides, coinciding with their secretion block. Additionally, proteome profiling of DXM-treated cells showed increased thermal stability of prolyl-hydroxylases P3H2, P3H3, P3H4, P4HA1, and P4HA2, suggesting a change in their activity. Transcriptome analysis of profibrotic stimulated primary human lung fibroblasts and human ex vivo lung slices after DXM treatment showed activation of an antifibrotic program through regulation of multiple pathways, including the MMP-ADAMTS axis, WNT signaling, and fibroblast-to-myofibroblast differentiation. Together, these data obtained from in vitro, in vivo, and ex vivo models of lung fibrogenesis show that DXM has the potential to limit fibrosis through inhibition of COL1 membrane trafficking in the ER.

Integrated stress response plasticity governs normal cell adaptation to chronic stress via the PP2A-TFE3-ATF4 pathway

The integrated stress response (ISR) regulates cell fate during conditions of stress by leveraging the cell's capacity to endure sustainable and efficient adaptive stress responses. Protein phosphatase 2A (PP2A) activity modulation has been shown to be successful in achieving both therapeutic efficacy and safety across various cancer models. However, the molecular mechanisms driving its selective antitumor effects remain unclear. Here, we show for the first time that ISR plasticity relies on PP2A activation to regulate drug response and dictate cellular survival under conditions of chronic stress. We demonstrate that genetic and chemical modulation of the PP2A leads to chronic proteolytic stress and triggers an ISR to dictate whether the cell lives or dies. More specifically, we uncovered that the PP2A-TFE3-ATF4 pathway governs ISR cell plasticity during endoplasmic reticular and cellular stress independent of the unfolded protein response. We further show that normal cells reprogram their genetic signatures to undergo ISR-mediated adaptation and homeostatic recovery thereby avoiding toxicity following PP2A-mediated stress. Conversely, oncogenic specific cytotoxicity induced by chemical modulation of PP2A is achieved by activating chronic and irreversible ISR in cancer cells. Our findings propose that a differential response to chemical modulation of PP2A is determined by intrinsic ISR plasticity, providing a novel biological vulnerability to selectively induce cancer cell death and improve targeted therapeutic efficacy.

Nanopore sequencing enables novel detection of deuterium incorporation in DNA

Identifying active microbes is crucial to understand their role in ecosystem functions. Metabolic labeling with heavy, non-radioactive isotopes, i.e., stable isotope probing (SIP), can track active microbes by detecting heavy isotope incorporation in biomolecules such as DNA. However, the detection of heavy isotope-labeled nucleotides directly during sequencing has, to date, not been achieved. In this study, Oxford nanopore sequencing was utilized to detect heavy isotopes incorporation in DNA molecules. Two isotopes widely used in SIP experiments were employed to label a bacterial isolate: deuterium (D, as D2O) and carbon-13 (13C, as glucose). We hypothesize that labeled DNA is distinguishable from unlabeled DNA by changes in the nanopore signal. To verify this distinction, we employed a Bayesian classifier trained on signal distributions of short oligonucleotides (k-mers) from labeled and unlabeled sequencing reads. Our results show a clear distinction between D-labeled and unlabeled reads, based on changes in median and median absolute deviation (MAD) of the nanopore signals for different k-mers. In contrast, 13C-labeled DNA cannot be distinguished from unlabeled DNA. For D, the model employed correctly predicted more than 85% of the reads. Even when metabolic labeling was conducted with only 30% D2O, 80% of the obtained reads were correctly classified with a 5% false discovery rate. Our work demonstrates the feasibility of direct detection of deuterium incorporation in DNA molecules during Oxford nanopore sequencing. This finding represents a first step in establishing the combined use of nanopore sequencing and SIP for tracking active organisms in microbial ecology.

Large-scale characterization of drug mechanism of action using proteome-wide thermal shift assays

In response to an ever-increasing demand of new small molecules therapeutics, numerous chemical and genetic tools have been developed to interrogate compound mechanism of action. Owing to its ability to approximate compound-dependent changes in thermal stability, the proteome-wide thermal shift assay has emerged as a powerful tool in this arsenal. The most recent iterations have drastically improved the overall efficiency of these assays, providing an opportunity to screen compounds at a previously unprecedented rate. Taking advantage of this advance, we quantified more than one million thermal stability measurements in response to multiple classes of therapeutic and tool compounds (96 compounds in living cells and 70 compounds in lysates). When interrogating the dataset as a whole, approximately 80% of compounds (with quantifiable targets) caused a significant change in the thermal stability of an annotated target. There was also a wealth of evidence portending off-target engagement despite the extensive use of the compounds in the laboratory and/or clinic. Finally, the combined application of cell- and lysate-based assays, aided in the classification of primary (direct ligand binding) and secondary (indirect) changes in thermal stability. Overall, this study highlights the value of these assays in the drug development process by affording an unbiased and reliable assessment of compound mechanism of action.

Global cellular proteo-lipidomic profiling of diverse lysosomal storage disease mutants using nMOST

Lysosomal storage diseases (LSDs) comprise ~50 monogenic disorders marked by the buildup of cellular material in lysosomes, yet systematic global molecular phenotyping of proteins and lipids is lacking. We present a nanoflow-based multi-omic single-shot technology (nMOST) workflow that quantifies HeLa cell proteomes and lipidomes from over two dozen LSD mutants. Global cross-correlation analysis between lipids and proteins identified autophagy defects, notably the accumulation of ferritinophagy substrates and receptors, especially in NPC1 -/- and NPC2 -/- mutants, where lysosomes accumulate cholesterol. Autophagic and endocytic cargo delivery failures correlated with elevated lyso-phosphatidylcholine species and multi-lamellar structures visualized by cryo-electron tomography. Loss of mitochondrial cristae, MICOS-complex components, and OXPHOS components rich in iron-sulfur cluster proteins in NPC2 -/- cells was largely alleviated when iron was provided through the transferrin system. This study reveals how lysosomal dysfunction affects mitochondrial homeostasis and underscores nMOST as a valuable discovery tool for identifying molecular phenotypes across LSDs.

Targeting IRE1α reprograms the tumor microenvironment and enhances anti-tumor immunity in prostate cancer

Unfolded protein response (UPR) is a central stress response pathway that is hijacked by tumor cells for their survival. Here, we find that IRE1α signaling, one of the canonical UPR arms, is increased in prostate cancer (PCa) patient tumors. Genetic or small molecule inhibition of IRE1α in syngeneic mouse PCa models and an orthotopic model decreases tumor growth. IRE1α ablation in cancer cells potentiates interferon responses and activates immune system related pathways in the tumor microenvironment (TME). Single-cell RNA-sequencing analysis reveals that targeting IRE1α in cancer cells reduces tumor-associated macrophage abundance. Consistently, the small molecule IRE1α inhibitor MKC8866, currently in clinical trials, reprograms the TME and enhances anti-PD-1 therapy. Our findings show that IRE1α signaling not only promotes cancer cell growth and survival but also interferes with anti-tumor immunity in the TME. Thus, targeting IRE1α can be a promising approach for improving anti-PD-1 immunotherapy in PCa.

Potent and Selective SETDB1 Covalent Negative Allosteric Modulator Reduces Methyltransferase Activity in Cells

A promising drug target, SETDB1, is a dual Kme reader and methyltransferase, which has been implicated in cancer and neurodegenerative disease progression. To help understand the role of the triple Tudor domain (3TD) of SETDB1, its Kme reader, we first identified a low micromolar small molecule ligand, UNC6535, which occupies simultaneously both the TD2 and TD3 reader binding sites. Further optimization led to the discovery of UNC10013, the first covalent 3TD ligand targeting Cys385 of SETDB1. UNC10013 is potent with a k inact /K I of 1.0 x 10 6 M -1 s -1 and demonstrated proteome-wide selectivity. In cells, negative allosteric modulation of SETDB1-mediated Akt methylation was observed after treatment with UNC10013. Therefore, UNC10013 is a potent, selective and cell-active covalent ligand for the 3TD of SETDB1, demonstrating negative allosteric modulator properties and making it a promising tool to study the biological role of SETDB1 in disease progression.

Proteo-metabolomics and patient tumor slice experiments point to amino acid centrality for rewired mitochondria in fibrolamellar carcinoma

Fibrolamellar carcinoma (FLC) is a rare, lethal, early-onset liver cancer with a critical need for new therapeutics. The primary driver in FLC is the fusion oncoprotein, DNAJ-PKAc, which remains challenging to target therapeutically. It is critical, therefore, to expand understanding of the FLC molecular landscape to identify druggable pathways/targets. Here, we perform the most comprehensive integrative proteo-metabolomic analysis of FLC. We also conduct nutrient manipulation, respirometry analyses, as well as key loss-of-function assays in FLC tumor tissue slices from patients. We propose a model of cellular energetics in FLC pointing to proline anabolism being mediated by ornithine aminotransferase hyperactivity and ornithine transcarbamylase hypoactivity with serine and glutamine catabolism fueling the process. We highlight FLC's potential dependency on voltage-dependent anion channel (VDAC), a mitochondrial gatekeeper for anions including pyruvate. The metabolic rewiring in FLC that we propose in our model, with an emphasis on mitochondria, can be exploited for therapeutic vulnerabilities.

The proteomic landscape and temporal dynamics of mammalian gastruloid development

Gastrulation is the highly coordinated process by which the early embryo breaks symmetry, establishes germ layers and a body plan, and sets the stage for organogenesis. As early mammalian development is challenging to study in vivo, stem cell-derived models have emerged as powerful surrogates, e.g. human and mouse gastruloids. However, although single cell RNA-seq (scRNA-seq) and high-resolution imaging have been extensively applied to characterize such in vitro embryo models, a paucity of measurements of protein dynamics and regulation leaves a major gap in our understanding. Here, we sought to address this by applying quantitative proteomics to human and mouse gastruloids at four key stages of their differentiation (naïve ESCs, primed ESCs, early gastruloids, late gastruloids). To the resulting data, we perform network analysis to map the dynamics of expression of macromolecular protein complexes and biochemical pathways, including identifying cooperative proteins that associate with them. With matched RNA-seq and phosphosite data from these same stages, we investigate pathway-, stage- and species-specific aspects of translational and post-translational regulation, e.g. finding peri-gastrulation stages of human and mice to be discordant with respect to the mitochondrial transcriptome vs. proteome, and nominating novel kinase-substrate relationships based on phosphosite dynamics. Finally, we leverage correlated dynamics to identify conserved protein networks centered around congenital disease genes. Altogether, our data (https://gastruloid.brotmanbaty.org/) and analyses showcase the potential of intersecting in vitro embryo models and proteomics to advance our understanding of early mammalian development in ways not possible through transcriptomics alone.

Machine Learning Strategies to Tackle Data Challenges in Mass Spectrometry-Based Proteomics

In computational proteomics, machine learning (ML) has emerged as a vital tool for enhancing data analysis. Despite significant advancements, the diversity of ML model architectures and the complexity of proteomics data present substantial challenges in the effective development and evaluation of these tools. Here, we highlight the necessity for high-quality, comprehensive data sets to train ML models and advocate for the standardization of data to support robust model development. We emphasize the instrumental role of key data sets like ProteomeTools and MassIVE-KB in advancing ML applications in proteomics and discuss the implications of data set size on model performance, highlighting that larger data sets typically yield more accurate models. To address data scarcity, we explore algorithmic strategies such as self-supervised pretraining and multitask learning. Ultimately, we hope that this discussion can serve as a call to action for the proteomics community to collaborate on data standardization and collection efforts, which are crucial for the sustainable advancement and refinement of ML methodologies in the field.

Structural insight into the DNMT1 reaction cycle by cryo-electron microscopy

DNMT1 is an essential DNA methyltransferase that catalyzes the transfer of methyl groups to CpG islands in DNA and generates a prominent epigenetic mark. The catalytic activity of DNMT1 relies on its conformational plasticity and ability to change conformation from an auto-inhibited to an activated state. Here, we present four cryo-EM reconstructions of apo DNMT1 and DNTM1: non-productive DNA, DNTM1: H3Ub2-peptide, DNTM1: productive DNA complexes. Our structures demonstrate the flexibility of DNMT1's N-terminal regulatory domains during the transition from an apo 'auto-inhibited' to a DNA-bound 'non-productive' and finally a DNA-bound 'productive' state of DNMT1. Furthermore, we address the regulation of DNMT1's methyltransferase activity by a DNMT1-selective small-molecule inhibitor and ubiquitinated histone H3. We observe that DNMT1 binds DNA in a 'non-productive' state despite the presence of the inhibitor and present the cryo-EM reconstruction of full-length DNMT1 in complex with a di-ubiquitinated H3 peptide analogue. Taken together, our results provide structural insights into the reaction cycle of DNMT1.

Mitochondrial ATP generation is more proteome efficient than glycolysis

Metabolic efficiency profoundly influences organismal fitness. Nonphotosynthetic organisms, from yeast to mammals, derive usable energy primarily through glycolysis and respiration. Although respiration is more energy efficient, some cells favor glycolysis even when oxygen is available (aerobic glycolysis, Warburg effect). A leading explanation is that glycolysis is more efficient in terms of ATP production per unit mass of protein (that is, faster). Through quantitative flux analysis and proteomics, we find, however, that mitochondrial respiration is actually more proteome efficient than aerobic glycolysis. This is shown across yeast strains, T cells, cancer cells, and tissues and tumors in vivo. Instead of aerobic glycolysis being valuable for fast ATP production, it correlates with high glycolytic protein expression, which promotes hypoxic growth. Aerobic glycolytic yeasts do not excel at aerobic growth but outgrow respiratory cells during oxygen limitation. We accordingly propose that aerobic glycolysis emerges from cells maintaining a proteome conducive to both aerobic and hypoxic growth.

quantms: a cloud-based pipeline for quantitative proteomics enables the reanalysis of public proteomics data

The volume of public proteomics data is rapidly increasing, causing a computational challenge for large-scale reanalysis. Here, we introduce quantms ( https://quant,ms.org/ ), an open-source cloud-based pipeline for massively parallel proteomics data analysis. We used quantms to reanalyze 83 public ProteomeXchange datasets, comprising 29,354 instrument files from 13,132 human samples, to quantify 16,599 proteins based on 1.03 million unique peptides. quantms is based on standard file formats improving the reproducibility, submission and dissemination of the data to ProteomeXchange.

Micronuclear collapse from oxidative damage

Chromosome-containing micronuclei are a hallmark of aggressive cancers. Micronuclei frequently undergo irreversible collapse, exposing their enclosed chromatin to the cytosol. Micronuclear rupture catalyzes chromosomal rearrangements, epigenetic abnormalities, and inflammation, yet mechanisms safeguarding micronuclear integrity are poorly understood. In this study, we found that mitochondria-derived reactive oxygen species (ROS) disrupt micronuclei by promoting a noncanonical function of charged multivesicular body protein 7 (CHMP7), a scaffolding protein for the membrane repair complex known as endosomal sorting complex required for transport III (ESCRT-III). ROS retained CHMP7 in micronuclei while disrupting its interaction with other ESCRT-III components. ROS-induced cysteine oxidation stimulated CHMP7 oligomerization and binding to the nuclear membrane protein LEMD2, disrupting micronuclear envelopes. Furthermore, this ROS-CHMP7 pathological axis engendered chromosome shattering known to result from micronuclear rupture. It also mediated micronuclear disintegrity under hypoxic conditions, linking tumor hypoxia with downstream processes driving cancer progression.

Pollen-Food Allergy Syndrome: From Food Avoidance to Deciphering the Potential Cross-Reactivity between Pru p 3 and Ole e 7

BACKGROUND

Cross-reactivity between nonspecific lipid transfer proteins could cause anaphylaxis, further influencing food avoidance and nutrient deficiencies. The one affecting olive pollen (Ole e 7) and peach (Pru p 3) may underlie a variety of pollen-food syndromes, though a deep molecular analysis is necessary.

METHODS

Three Ole e 7-monosensitised patients (MON_OLE), three Pru p 3-monosensitised patients (MON_PRU) and three bisensitised patients (BI) were selected. For epitope mapping, both digested proteins were incubated with patient sera, and the captured IgE-bound peptides were characterised by LC-MS.

RESULTS

The analysis revealed two Ole e 7 epitopes and the three Pru p 3 epitopes previously described. Interestingly, the "KSALALVGNKV" Ole e 7 peptide was recognised by MON_OLE, BI and MON_PRU patients. Conversely, all patients recognised the "ISASTNCATVK" Pru p 3 peptide. Although complete sequence alignment between both proteins revealed 32.6% identity, local alignment considering seven residue fragments showed 50 and 57% identity when comparing "ISASTNCATVK" with Ole e 7 and "KSALALVGNKV" with Pru p 3.

CONCLUSIONS

This study mapped sIgE-Ole e 7-binding epitopes, paving the way for more precise diagnostic tools. Assuming non-significant sequence similarity, structural homology and shared key residues may underlie the potential cross-reactivity between Ole e 7 and Pru p 3 nsLTPs.

Large-scale characterization of drug mechanism of action using proteome-wide thermal shift assays

In response to an ever-increasing demand of new small molecules therapeutics, numerous chemical and genetic tools have been developed to interrogate compound mechanism of action. Owing to its ability to approximate compound-dependent changes in thermal stability, the proteome-wide thermal shift assay has emerged as a powerful tool in this arsenal. The most recent iterations have drastically improved the overall efficiency of these assays, providing an opportunity to screen compounds at a previously unprecedented rate. Taking advantage of this advance, we quantified more than one million thermal stability measurements in response to multiple classes of therapeutic and tool compounds (96 compounds in living cells and 70 compounds in lysates). When interrogating the dataset as a whole, approximately 80% of compounds (with quantifiable targets) caused a significant change in the thermal stability of an annotated target. There was also a wealth of evidence portending off-target engagement despite the extensive use of the compounds in the laboratory and/or clinic. Finally, the combined application of cell- and lysate-based assays, aided in the classification of primary (direct ligand binding) and secondary (indirect) changes in thermal stability. Overall, this study highlights the value of these assays in the drug development process by affording an unbiased and reliable assessment of compound mechanism of action.

Covalent inhibition of pro-apoptotic BAX

BCL-2-associated X protein (BAX) is a promising therapeutic target for activating or restraining apoptosis in diseases of pathologic cell survival or cell death, respectively. In response to cellular stress, BAX transforms from a quiescent cytosolic monomer into a toxic oligomer that permeabilizes the mitochondria, releasing key apoptogenic factors. The mitochondrial lipid trans-2-hexadecenal (t-2-hex) sensitizes BAX activation by covalent derivatization of cysteine 126 (C126). In this study, we performed a disulfide tethering screen to discover C126-reactive molecules that modulate BAX activity. We identified covalent BAX inhibitor 1 (CBI1) as a compound that selectively derivatizes BAX at C126 and inhibits BAX activation by triggering ligands or point mutagenesis. Biochemical and structural analyses revealed that CBI1 can inhibit BAX by a dual mechanism of action: conformational constraint and competitive blockade of lipidation. These data inform a pharmacologic strategy for suppressing apoptosis in diseases of unwanted cell death by covalent targeting of BAX C126.

Specificity profiling of deubiquitylases against endogenously generated ubiquitin-protein conjugates

Deubiquitylating enzymes (DUBs) remove ubiquitin from proteins thereby regulating their stability or activity. Our understanding of DUB-substrate specificity is limited because DUBs are typically not compared to each other against many physiological substrates. By broadly inhibiting DUBs in Xenopus egg extract, we generated hundreds of ubiquitylated proteins and compared the ability of 30 DUBs to deubiquitylate them using quantitative proteomics. We identified five high-impact DUBs (USP7, USP9X, USP36, USP15, and USP24) that each reduced ubiquitylation of over 10% of the isolated proteins. Candidate substrates of high-impact DUBs showed substantial overlap and were enriched for disordered regions, suggesting this feature may promote substrate recognition. Other DUBs showed lower impact and non-overlapping specificity, targeting distinct non-disordered proteins including complexes such as the ribosome or the proteasome. Altogether our study identifies candidate DUB substrates and defines patterns of functional redundancy and specificity, revealing substrate characteristics that may influence DUB-substrate recognition.

Global protein turnover quantification in Escherichia coli reveals cytoplasmic recycling under nitrogen limitation

Protein turnover is critical for proteostasis, but turnover quantification is challenging, and even in well-studied E. coli, proteome-wide measurements remain scarce. Here, we quantify the turnover rates of ~3200 E. coli proteins under 13 conditions by combining heavy isotope labeling with complement reporter ion quantification and find that cytoplasmic proteins are recycled when nitrogen is limited. We use knockout experiments to assign substrates to the known cytoplasmic ATP-dependent proteases. Surprisingly, none of these proteases are responsible for the observed cytoplasmic protein degradation in nitrogen limitation, suggesting that a major proteolysis pathway in E. coli remains to be discovered. Lastly, we show that protein degradation rates are generally independent of cell division rates. Thus, we present broadly applicable technology for protein turnover measurements and provide a rich resource for protein half-lives and protease substrates in E. coli, complementary to genomics data, that will allow researchers to study the control of proteostasis.

The ribotoxic stress response drives UV-mediated cell death

While ultraviolet (UV) radiation damages DNA, eliciting the DNA damage response (DDR), it also damages RNA, triggering transcriptome-wide ribosomal collisions and eliciting a ribotoxic stress response (RSR). However, the relative contributions, timing, and regulation of these pathways in determining cell fate is unclear. Here we use time-resolved phosphoproteomic, chemical-genetic, single-cell imaging, and biochemical approaches to create a chronological atlas of signaling events activated in cells responding to UV damage. We discover that UV-induced apoptosis is mediated by the RSR kinase ZAK and not through the DDR. We identify two negative-feedback modules that regulate ZAK-mediated apoptosis: (1) GCN2 activation limits ribosomal collisions and attenuates ZAK-mediated RSR and (2) ZAK activity leads to phosphodegron autophosphorylation and its subsequent degradation. These events tune ZAK's activity to collision levels to establish regimes of homeostasis, tolerance, and death, revealing its key role as the cellular sentinel for nucleic acid damage.

A hidden proteome encoded by circRNAs in human placentas: Implications for uncovering preeclampsia pathogenesis

BACKGROUND

CircRNA-encoded proteins (CEPs) are emerging as new players in health and disease, and function as baits for the common partners of their cognate linear-spliced RNA encoded proteins (LEPs). However, their prevalence across human tissues and biological roles remain largely unexplored. The placenta is an ideal model for identifying CEPs due to its considerable protein diversity that is required to sustain fetal development during pregnancy. The aim of this study was to evaluate circRNA translation in the human placenta, and the potential roles of the CEPs in placental development and dysfunction.

METHODS

Multiomics approaches, including RNA sequencing, ribosome profiling, and LC-MS/MS analysis, were utilised to identify novel translational events of circRNAs in human placentas. Bioinformatics methods and the protein bait hypothesis were employed to evaluate the roles of these newly discovered CEPs in placentation and associated disorders. The pathogenic role of a recently identified CEP circPRKCB119aa in preeclampsia was investigated through qRT-PCR, Western blotting, immunofluorescence imaging and phenotypic analyses.

RESULTS

We found that 528 placental circRNAs bound to ribosomes with active translational elongation, and 139 were translated to proteins. The CEPs showed considerable structural homology with their cognate LEPs, but are more stable, hydrophobic and have a lower molecular-weight than the latter, all of which are conducive to their function as baits. On this basis, CEPs are deduced to be closely involved in placental function. Furthermore, we focused on a novel CEP circPRKCB119aa, and illuminated its pathogenic role in preeclampsia; it enhanced trophoblast autophagy by acting as a bait to inhibit phosphorylation of the cognate linear isoform PKCβ.

CONCLUSIONS

We discovered a hidden circRNA-encoded proteome in the human placenta, which offers new insights into the mechanisms underlying placental development, as well as placental disorders such as preeclampsia. Key points A hidden circRNA-encoded proteome in the human placenta was extensively identified and systematically characterised. The circRNA-encoded proteins (CEPs) are potentially related to placental development and associated disorders. A novel conserved CEP circPRKCB119aa enhanced trophoblast autophagy by inhibiting phosphorylation of its cognate linear-spliced isoform protein kinase C (PKC) β in preeclampsia.

Alkylamine-tethered molecules recruit FBXO22 for targeted protein degradation

Targeted protein degradation (TPD) relies on small molecules to recruit proteins to E3 ligases to induce their ubiquitylation and degradation by the proteasome. Only a few of the approximately 600 human E3 ligases are currently amenable to this strategy. This limits the actionable target space and clinical opportunities and thus establishes the necessity to expand to additional ligases. Here we identify and characterize SP3N, a specific degrader of the prolyl isomerase FKBP12. SP3N features a minimal design, where a known FKBP12 ligand is appended with a flexible alkylamine tail that conveys degradation properties. We found that SP3N is a precursor and that the alkylamine is metabolized to an active aldehyde species that recruits the SCFFBXO22 ligase for FKBP12 degradation. Target engagement occurs via covalent adduction of Cys326 in the FBXO22 C-terminal domain, which is critical for ternary complex formation, ubiquitylation and degradation. This mechanism is conserved for two recently reported alkylamine-based degraders of NSD2 and XIAP, thus establishing alkylamine tethering and covalent hijacking of FBXO22 as a generalizable TPD strategy.

Investigating Antiprotozoal Chemotherapies with Novel Proteomic Tools-Chances and Limitations: A Critical Review

Identification of drug targets and biochemical investigations on mechanisms of action are major issues in modern drug development. The present article is a critical review of the classical "one drug"-"one target" paradigm. In fact, novel methods for target deconvolution and for investigation of resistant strains based on protein mass spectrometry have shown that multiple gene products and adaptation mechanisms are involved in the responses of pathogens to xenobiotics rather than one single gene or gene product. Resistance to drugs may be linked to differential expression of other proteins than those interacting with the drug in protein binding studies and result in complex cell physiological adaptation. Consequently, the unraveling of mechanisms of action needs approaches beyond proteomics. This review is focused on protozoan pathogens. The conclusions can, however, be extended to chemotherapies against other pathogens or cancer.

Top-down proteomics

Proteoforms, which arise from post-translational modifications, genetic polymorphisms and RNA splice variants, play a pivotal role as drivers in biology. Understanding proteoforms is essential to unravel the intricacies of biological systems and bridge the gap between genotypes and phenotypes. By analysing whole proteins without digestion, top-down proteomics (TDP) provides a holistic view of the proteome and can decipher protein function, uncover disease mechanisms and advance precision medicine. This Primer explores TDP, including the underlying principles, recent advances and an outlook on the future. The experimental section discusses instrumentation, sample preparation, intact protein separation, tandem mass spectrometry techniques and data collection. The results section looks at how to decipher raw data, visualize intact protein spectra and unravel data analysis. Additionally, proteoform identification, characterization and quantification are summarized, alongside approaches for statistical analysis. Various applications are described, including the human proteoform project and biomedical, biopharmaceutical and clinical sciences. These are complemented by discussions on measurement reproducibility, limitations and a forward-looking perspective that outlines areas where the field can advance, including potential future applications.

mTORC1-CTLH E3 ligase regulates the degradation of HMG-CoA synthase 1 through the Pro/N-degron pathway

Mammalian target of rapamycin (mTOR) senses changes in nutrient status and stimulates the autophagic process to recycle amino acids. However, the impact of nutrient stress on protein degradation beyond autophagic turnover is incompletely understood. We report that several metabolic enzymes are proteasomal targets regulated by mTOR activity based on comparative proteome degradation analysis. In particular, 3-hydroxy-3-methylglutaryl (HMG)-coenzyme A (CoA) synthase 1 (HMGCS1), the initial enzyme in the mevalonate pathway, exhibits the most significant half-life adaptation. Degradation of HMGCS1 is regulated by the C-terminal to LisH (CTLH) E3 ligase through the Pro/N-degron motif. HMGCS1 is ubiquitylated on two C-terminal lysines during mTORC1 inhibition, and efficient degradation of HMGCS1 in cells requires a muskelin adaptor. Importantly, modulating HMGCS1 abundance has a dose-dependent impact on cell proliferation, which is restored by adding a mevalonate intermediate. Overall, our unbiased degradomics study provides new insights into mTORC1 function in cellular metabolism: mTORC1 regulates the stability of limiting metabolic enzymes through the ubiquitin system.

Critical steps in an environmental metaproteomics workflow

Environmental metaproteomics is a rapidly advancing field that provides insights into the structure, dynamics, and metabolic activity of microbial communities. As the field is still maturing, it lacks consistent workflows, making it challenging for non-expert researchers to navigate. This review aims to introduce the workflow of environmental metaproteomics. It outlines the standard practices for sample collection, processing, and analysis, and offers strategies to overcome the unique challenges presented by common environmental matrices such as soil, freshwater, marine environments, biofilms, sludge, and symbionts. The review also highlights the bottlenecks in data analysis that are specific to metaproteomics samples and provides suggestions for researchers to obtain high-quality datasets. It includes recent benchmarking studies and descriptions of software packages specifically built for metaproteomics analysis. The article is written without assuming the reader's familiarity with single-organism proteomic workflows, making it accessible to those new to proteomics or mass spectrometry in general. This primer for environmental metaproteomics aims to improve accessibility to this exciting technology and empower researchers to tackle challenging and ambitious research questions. While it is primarily a resource for those new to the field, it should also be useful for established researchers looking to streamline or troubleshoot their metaproteomics experiments.

Spatiotemporal proteomic profiling of cellular responses to NLRP3 agonists

Nucleotide-binding domain and leucine-rich repeat pyrin-domain containing protein 3 (NLRP3) is an innate immune sensor that forms an inflammasome in response to various cellular stressors. Gain-of-function mutations in NLRP3 cause autoinflammatory diseases and NLRP3 signalling itself exacerbates the pathogenesis of many other human diseases. Despite considerable therapeutic interest, the primary drivers of NLRP3 activation remain controversial due to the diverse array of signals that are integrated through NLRP3. Here, we mapped subcellular proteome changes to lysosomes, mitochondrion, EEA1-positive endosomes, and Golgi caused by the NLRP3 inflammasome agonists nigericin and CL097. We identified several common disruptions to retrograde trafficking pathways, including COPI and Shiga toxin-related transport, in line with recent studies. We further characterized mouse NLRP3 trafficking throughout its activation using temporal proximity proteomics, which supports a recent model of NLRP3 recruitment to endosomes during inflammasome activation. Collectively, these findings provide additional granularity to our understanding of the molecular events driving NLRP3 activation and serve as a valuable resource for cell biological research. We have made our proteomics data accessible through an open-access Shiny browser to facilitate future research within the community, available at: https://harperlab.connect.hms.harvard.edu/inflame/. We will display anonymous peer review for this manuscript on pubpub.org (https://harperlab.pubpub.org/pub/nlrp3/) rather than a traditional journal. Moreover, we invite community feedback on the pubpub version of this manuscript, and we will address criticisms accordingly.

Quantitative proteome dynamics across embryogenesis in a model chordate

The evolution of gene expression programs underlying the development of vertebrates remains poorly characterized. Here, we present a comprehensive proteome atlas of the model chordate Ciona, covering eight developmental stages and ∼7,000 translated genes, accompanied by a multi-omics analysis of co-evolution with the vertebrate Xenopus. Quantitative proteome comparisons argue against the widely held hourglass model, based solely on transcriptomic profiles, whereby peak conservation is observed during mid-developmental stages. Our analysis reveals maximal divergence at these stages, particularly gastrulation and neurulation. Together, our work provides a valuable resource for evaluating conservation and divergence of multi-omics profiles underlying the diversification of vertebrates.

Ergothioneine boosts mitochondrial respiration and exercise performance via direct activation of MPST

Ergothioneine (EGT) is a diet-derived, atypical amino acid that accumulates to high levels in human tissues. Reduced EGT levels have been linked to age-related disorders, including neurodegenerative and cardiovascular diseases, while EGT supplementation is protective in a broad range of disease and aging models in mice. Despite these promising data, the direct and physiologically relevant molecular target of EGT has remained elusive. Here we use a systematic approach to identify how mitochondria remodel their metabolome in response to exercise training. From this data, we find that EGT accumulates in muscle mitochondria upon exercise training. Proteome-wide thermal stability studies identify 3-mercaptopyruvate sulfurtransferase (MPST) as a direct molecular target of EGT; EGT binds to and activates MPST, thereby boosting mitochondrial respiration and exercise training performance in mice. Together, these data identify the first physiologically relevant EGT target and establish the EGT-MPST axis as a molecular mechanism for regulating mitochondrial function and exercise performance.