Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry

Differences in complement activation of serum-resistant and serum-sensitive Klebsiella pneumoniae isolates

The gram-negative bacteria Klebsiella pneumoniae are genetically heterogeneous and a common cause of sepsis and bacteremia in humans. The complement system is the first line of defence against bacteria when they invade the body. We previously investigated K. pneumoniae isolates from sepsis patients. We found that complement factor (C) 3 is deposited on all isolates independent of serum sensitivity, but the membrane attack complex (MAC) was only formed on the serum-sensitive isolates. To investigate the mechanism for serum resistance, we incubated one serum-sensitive and one serum-resistant isolate in human serum and identified bound complement factors by mass spectrometry. The serum-sensitive isolate had all expected complement factors bound, including C4, while the serum-resistant isolate had only C3 bound. The serum resistance was caused by a fast cleavage of C3b to iC3b. Thereby, the C5 convertase, and thus MAC, cannot be formed. To confirm the role of C4 in serum sensitivity, C4 was inhibited by the nanobody hC4Nb8, resulting in the survival of the serum-sensitive isolate. This suggests that C4 is indispensable for MAC formation through the classical and lectin pathways. In contrast, when activated selectively, the alternative pathway primarily leads to the generation of iC3b, thereby enabling serum resistance by bypassing MAC assembly.

CRISPR screens and quantitative proteomics reveal remodeling of the aryl hydrocarbon receptor-driven proteome through PARP7 activity

PARP7 is an enzyme that uses donor substrate NAD+ to attach a single ADP-ribose moiety onto proteins related to immunity, transcription, and cell growth and motility. Despite the importance of PARP7 in these processes, PARP7 signaling networks remain underresearched. Here, we used genome-wide CRISPR screens and multiplex quantitative proteomics in distinct lung cancer cell lines treated with a PARP7 inhibitor to better understand PARP7 molecular functions. We find that manipulating the aryl hydrocarbon receptor (AHR) transcriptional activity mediates PARP7 inhibitor sensitivity and triggers robust changes to the AHR-controlled proteome (AHR-ome). One of the striking features of such AHR-ome remodeling was the downregulation of filamins A and B concurrent with the induction of the corresponding E3 ubiquitin ligase ASB2. We also show that suppressor of cytokine signaling 3 (SOCS3) crosstalks to AHR. Inhibition of PARP7 in SOCS3 knockout cells leads to reduced viability compared to wild-type cells treated with a PARP7 inhibitor. Our results reveal signaling interplay between PARP7, AHR, and SOCS3 and establish an invaluable resource to study the role of PARP7 in the regulation of AHR signaling and innate immunity through its ADP-ribosyl transferase activity.

Synaptic activity causes minute-scale changes in BAF complex composition and function

Genes encoding subunits of the BAF ATP-dependent chromatin remodeling complex are among the most enriched for deleterious de novo mutations in intellectual disabilities and autism spectrum disorder, but the causative molecular pathways are not understood. Synaptic activity in neurons is critical for learning, memory, and proper neural development. While BAF is required for activity-dependent developmental processes, such as dendritic outgrowth, the immediate molecular consequences of neuronal activity on BAF complexes are unknown. Here, we report that neuronal activity induces dramatic remodeling of the subunit composition of BAF complexes within 15 min, concurrent with both phosphorylation and dephosphorylation of its subunits. These biochemical effects are a convergent phenomenon downstream of multiple calcium-activated signaling pathways in mouse neurons and mouse fibroblasts and correspond to changes in BAF-dependent chromatin accessibility. Our studies imply that BAF decodes signals at the membrane by altering the combinatorial composition of its subunits.

Depletion-dependent activity-based protein profiling using SWATH/DIA-MS detects serine hydrolase lipid remodeling in lung adenocarcinoma progression

Systematic inference of enzyme activity in human tumors is key to understanding cancer progression and resistance to therapy. However, standard protein or transcript abundances are blind to the activity status of the measured enzymes, regulated, for example, by active-site amino acid mutations or post-translational protein modifications. Current methods for activity-based proteome profiling (ABPP), which combine mass spectrometry (MS) with chemical probes, quantify the fraction of enzymes that are catalytically active. Here, we describe depletion-dependent ABPP (dd-ABPP) combined with automated SWATH/DIA-MS, which simultaneously determines three molecular layers of studied enzymes: i) catalytically active enzyme fractions, ii) enzyme and background protein abundances, and iii) context-dependent enzyme-protein interactions. We demonstrate the utility of the method in advanced lung adenocarcinoma (LUAD) by monitoring nearly 4000 protein groups and 200 serine hydrolases (SHs) in tumor and adjacent tissue sections routinely collected for patient histopathology. The activity profiles of 23 SHs and the abundance of 59 proteins associated with these enzymes retrospectively classified aggressive LUAD. The molecular signature revealed accelerated lipoprotein depalmitoylation via palmitoyl(protein)hydrolase activities, further confirmed by excess palmitate and its metabolites. The approach is universal and applicable to other enzyme families with available chemical probes, providing clinicians with a biochemical rationale for tumor sample classification.

Expanding the landscape of aging via orbitrap astral mass spectrometry and tandem mass tag integration

Aging results in a progressive decline in physiological function due to the deterioration of essential biological processes. While proteomics offers insights into aging mechanisms, prior studies are limited in proteome coverage and lifespan range. To address this, we integrate the Orbitrap Astral Mass Spectrometer with the multiplex tandem mass tag (TMT) technology to profile the proteomes of cortex, hippocampus, striatum and kidney in the C57BL/6JN mice, quantifying 8,954 to 9,376 proteins per tissue (12,749 total). Samples spanned both sexes and three age groups (3, 12, and 20 months), representing early to late adulthood. To improve TMT quantitation accuracy, we develop a peptide-spectrum match-based filtering strategy that leverages resolution and signal-to-noise thresholds. Our analysis uncovers distinct tissue-specific patterns of protein abundance, with age and sex differences in the kidney and primarily age-related changes in brain tissues. We also identify both linear and non-linear proteomic trajectories with age, revealing complex protein dynamics over the adult lifespan. Integrating our findings with early developmental proteomic data from brain tissues highlights further divergent age-related trajectories, particularly in synaptic proteins. This study provides a robust data analysis workflow for Orbitrap Astral-based TMT analysis and expands the proteomic understanding of aging across tissues, ages, and sexes.

The TetR-like regulator Sco4385 and Crp-like regulator Sco3571 modulate heterologous production of antibiotics in Streptomyces coelicolor M512

Heterologous expression in well-studied model strains is a routinely applied method to investigate biosynthetic pathways. Here, we pursue a comparative approach of large-scale DNA-affinity-capturing assays (DACAs) coupled with semi-quantitative mass spectrometry (MS) to identify putative regulatory proteins from Streptomyces coelicolor M512, which bind to the heterologously expressed biosynthetic gene clusters (BGCs) of the liponucleoside antibiotics caprazamycin and liposidomycin. Both gene clusters share an almost identical genetic arrangement, including the location of promoter regions, as detected by RNA sequencing. A total of 2,214 proteins were trapped at the predicted promoter regions, with only three binding to corresponding promoters in both gene clusters. Among these, the overexpression of a yet uncharacterized TetR-family regulator (TFR), Sco4385, increased caprazamycin but not liposidomycin production. Protein-DNA interaction experiments using biolayer interferometry confirmed the binding of Sco4385 to Pcpz10 and PlpmH at different locations within both promoter regions, which might explain its functional variance. Sequence alignment allowed the determination of a consensus sequence present in both promoter regions, to which Sco4385 was experimentally shown to bind. Furthermore, we found that the overexpression of the Crp regulator, Sco3571, leads to a threefold increase in caprazamycin and liposidomycin production yields, possibly due to an increased expression of a precursor pathway.IMPORTANCEStreptomycetes are well-studied model organisms for the biosynthesis of pharmaceutically, industrially, and biotechnologically valuable metabolites. Their naturally broad repertoire of natural products can be further exploited by heterologous expression of biosynthetic gene clusters (BGCs) in non-native host strains. This approach forces the host to adapt to a new regulatory and metabolic environment. In our study, we demonstrate that a host regulator not only interacts with newly incorporated gene clusters but also regulates precursor supply for the produced compounds. We present a comprehensive study of regulatory proteins that interact with two genetically similar gene clusters for the biosynthesis of liponucleoside antibiotics. Thereby, we identified regulators of the heterologous host that influence the production of the corresponding antibiotic. Surprisingly, the regulatory interaction is highly specific for each biosynthetic gene cluster, even though they encode largely structurally similar metabolites.

Compositional profiling of protein hydrolysates by high resolution liquid chromatography-mass spectrometry and chemometric analysis

Protein hydrolysates have attracted growing research and commercial attention due to their numerous nutritional, functional, and biological activities. However, only a limited range of proximate properties are determined routinely due to their substantial structural complexity and compositional variability. From both a manufacturing and functional perspective, it is of critical importance to monitor the compositional variations and identify potential similar or disparate features between different protein hydrolysates. In the current study, a single-approached method employing reverse phase ultra-high performance liquid chromatography coupled to high resolution electrospray ionization tandem mass spectrometry (RP-UHPLC-HR-ESI-MS/MS) was developed, optimized, and cross-validated for comprehensive structural and compositional profiling of a range of protein hydrolysates of varying raw materials, including soy, cotton, wheat, rice, and meat. Untargeted chemometric analysis and feature-based molecular network demonstrated potential for large-scale compositional assessment of protein hydrolysates without the need of prior component annotation. Signature features were identified to differentiate soy hydrolysates prepared from different batches of raw material and by different manufacturing processes. A hybrid approach combining de novo sequencing and target-decoy database homology search for peptide annotation is also described. Short peptides of 2 to 5 amino acids represented the most abundant components in soy protein hydrolysates (SPHs). A simple yet reliable integrated workflow for comprehensive structural and compositional profiling of protein hydrolysates was developed to enable an eventual correlation between their structure and function.

Microbial metabolism in laboratory reared marine snow as revealed by a multi-omics approach

BACKGROUND

Marine snow represents an organic matter-rich habitat and provides substrates for diverse microbial populations in the marine ecosystem. However, the functional diversity and metabolic interactions within the microbial community inhabiting marine snow remain largely underexplored, particularly for specific metabolic pathways involved in marine snow degradation. Here, we used a multi-omics approach to explore the microbial response to laboratory-reared phytoplankton-derived marine snow.

RESULTS

Our results demonstrated a dramatic shift in both taxonomic and functional profiles of the microbial community after the formation of phytoplankton-derived marine snow using a rolling tank system. The changes in microbial metabolic processes were more pronounced in the metaproteome than in the metagenome in response to marine snow. Fast-growing taxa within the Gammaproteobacteria were the most dominant group at both the metagenomic and metaproteomic level. These Gammaproteobacteria possessed a variety of carbohydrate-active enzymes (CAZymes) and transporters facilitating substrate cleavage and uptake, respectively. Analysis of metagenome-assembled genomes (MAGs) revealed that the response to marine snow amendment was primarily mediated by Alteromonas, Vibrio, and Thalassotalea. Among these, Alteromonas exclusively expressing auxiliary activities 2 (AA2) of the CAZyme subfamily were abundant in both the free-living (FL) and marine snow-attached (MA) microbial communities. Thus, Alteromonas likely played a pivotal role in the degradation of marine snow. The enzymes of AA2 produced by these Alteromonas MAGs are capable of detoxifying peroxide intermediates generated during the breakdown of marine snow into smaller poly- and oligomers, providing available substrates for other microorganisms within the system. In addition, Vibrio and Thalassotalea MAGs exhibited distinct responses to these hydrolysis products of marine snow in different size fractions, suggesting a distinct niche separation. Although chemotaxis proteins were found to be enriched in the proteome of all three MAGs, differences in transporter proteins were identified as the primary factor contributing to the niche separation between these two groups. Vibrio in the FL fraction predominantly utilized ATP-binding cassette transporters (ABCTs), while Thalassotalea MAGs in the MA fraction primarily employed TonB-dependent outer membrane transporters (TBDTs).

CONCLUSIONS

Our findings shed light on the essential metabolic interactions within marine snow-degrading microbial consortia, which employ complementary physiological mechanisms and survival strategies to effectively scavenge marine snow. This work advances our understanding of the fate of marine snow and the role of microbes in carbon sequestration in the ocean. Video Abstract.

Glycoproteomic and Single-Protein Glycomic Analyses Reveal Zwitterionic N-Glycans on Natural and Recombinant Proteins Derived From Insect Cells

Insect cells are a convenient cell factory to produce recombinant glycoproteins. Their glycosylation potential is believed to be simple, needing primarily addition of glycosyltransferases to humanize the recombinant products. In this study, the native glycoproteome of Spodoptera frugiperda Sf9 and Trichoplusia ni High Five cells, examined using an LC-MS/MS approach, revealed not only which proteins are N-glycosylated but also indicated that the N-glycomes contain novel glucuronylated and phosphorylcholine-modified glycans, in addition to typical oligomannosidic and fucosylated structures. These data were corroborated by a parallel MALDI-TOF MS/MS analysis of N-glycosidase-released oligosaccharides. Molecular modeling analysis of one endogenous Sf9 glycoprotein correlated the occurrence of complex and oligomannosidic N-glycans with the accessibility of the occupied N-glycosylation sites. Further, we showed that the N-glycans of influenza hemagglutinins and SARS-CoV-2 spike glycoprotein produced in Spodoptera cells possess a number of glycan structures modified with phosphorylcholine, but core difucosylation was minimal; in contrast, the Trichoplusia-produced hemagglutinin had only traces of the former type, while the latter was dominant. Detection of phosphorylcholine on these glycoproteins correlated with binding to human C-reactive protein. In conclusion, not just oligomannosidic or truncated paucimannosidic N-glycans, but structures with immunogenic features occur on both natural and recombinant glycoproteins derived from insect cell lines.

EZH2 inhibition mitigates HIV immune evasion, reduces reservoir formation, and promotes skewing of CD8+ T cells toward less-exhausted phenotypes

Persistent HIV reservoirs in CD4+ T cells pose a barrier to curing HIV infection. We identify overexpression of enhancer of zeste homolog 2 (EZH2) in HIV-infected CD4+ T cells that survive cytotoxic T lymphocyte (CTL) exposure, suggesting a mechanism of CTL resistance. Inhibition of EZH2 with the US Food and Drug Administration-approved drug tazemetostat increases surface expression of major histocompatibility complex (MHC) class I on CD4+ T cells, counterbalancing HIV Nef-mediated MHC class I downregulation. This improves CTL-mediated elimination of HIV-infected cells and suppresses viral replication in vitro. In a participant-derived xenograft mouse model, tazemetostat elevates MHC class I and the pro-apoptotic protein BIM in CD4+ T cells, facilitating CD8+ T cell-mediated reductions of HIV reservoir seeding. Additionally, tazemetostat promotes sustained skewing of CD8+ T cells toward less-differentiated and exhausted phenotypes. Our findings reveal EZH2 overexpression as a mechanism of CTL resistance and support the clinical evaluation of tazemetostat as a method of enhancing clearance of HIV reservoirs and improving CD8+ T cell function.

How to Train a Postprocessor for Tandem Mass Spectrometry Proteomics Database Search While Maintaining Control of the False Discovery Rate

Decoy-based methods are a popular choice for the statistical validation of peptide detection in tandem mass spectrometry and proteomics data. Such methods can achieve a substantial boost in statistical power when coupled with postprocessors such as Percolator that use auxiliary features to learn a better-discriminating scoring function. However, we recently showed that Percolator can struggle to control the false discovery rate (FDR) when reporting the list of discovered peptides. To address this problem, we introduce Percolator-RESET, which is an adaptation of our recently developed RESET meta-procedure to the peptide detection problem. Specifically, Percolator-RESET fuses Percolator's iterative SVM training procedure with RESET's general framework to provide valid false discovery rate control. Percolator-RESET operates in both a standard single-decoy mode and a two-decoy mode, with the latter requiring the generation of two decoys per target. We demonstrate that Percolator-RESET controls the FDR in both modes, both theoretically and empirically, while typically reporting only a marginally smaller number of discoveries than Percolator in the single-decoy mode. The two-decoy mode is marginally more powerful than both Percolator and the single-decoy mode and exhibits less variability than the latter.

LKB1 regulates JNK-dependent stress signaling and apoptotic dependency of KRAS-mutant lung cancers

The efficacy of molecularly targeted therapies may be limited by co-occurring mutations within a tumor. Conversely, these alterations may confer collateral vulnerabilities that can be therapeutically leveraged. KRAS-mutant lung cancers are distinguished by recurrent loss of the tumor suppressor STK11/LKB1. Whether LKB1 modulates cellular responses to therapeutic stress seems unknown. Here we show that in LKB1-deficient KRAS-mutant lung cancer cells, inhibition of KRAS or its downstream effector MEK leads to hyperactivation of JNK due to loss of NUAK-mediated PP1B phosphatase activity. JNK-mediated inhibitory phosphorylation of BCL-XL rewires apoptotic dependencies, rendering LKB1-deficient cells vulnerable to MCL-1 inhibition. These results uncover an unknown role for LKB1 in regulating stress signaling and mitochondrial apoptosis independent of its tumor suppressor activity mediated by AMPK and SIK. Additionally, our study reveals a therapy-induced vulnerability in LKB1-deficient KRAS-mutant lung cancers that could be exploited as a genotype-informed strategy to improve the efficacy of KRAS-targeted therapies.

Deep Learning-Based Prediction of Decoy Spectra for False Discovery Rate Estimation in Spectral Library Searching

With the advantage of extensive coverage, predicted spectral libraries are becoming an attractive alternative in proteomic data analysis. As a popular false discovery rate estimation method, target decoy search has been adopted in library search workflows. While existing decoy methods for curated experimental libraries have been tested, their performance in predicted library scenarios remains unknown. Current methods rely on perturbing real spectra templates, limiting the diversity and number of decoy spectra that can be generated for a given library. In this study, we explore the shuffle-and-predict decoy library generation approach, which can generate decoy spectra without the need for template spectra. Our experiments shed light on decoy method performance for predicted library scenarios and demonstrate the quality of predicted decoys in FDR estimation.

Temporal Proteomic Profiling of Pheromone-Induced Cell Cycle Re-Entry in Saccharomyces cerevisiae

The regulation of cell cycle progression in response to environmental cues is essential for cellular adaptation. In Saccharomyces cerevisiae, the BAR1 gene modulates sensitivity to the mating pheromone α-factor, which induces cell cycle arrest in G1. Here, we investigated the dynamic proteomic response in the bar1 deletion strain using a 27-plex experimental design with TMTproD isobaric labeling. Asynchronous bar1Δ cells were treated with α-factor and then released from the pheromone-induced cell cycle arrest in G1. Using higher-order TMTpro sample multiplexing, we generated global temporal profiles of protein abundance associated with recovery from this arrest, with triplicate samples collected at eight time points from 0 to 165 min after washing out the pheromone. We identify specific proteins involved in cell cycle re-entry and in the attenuation of the pheromone signal, providing insights into the regulatory mechanisms of mating response in yeast. This study also contributes significantly to dynamic proteomic analysis of cell cycle progression. We present a versatile approach for investigating complex cellular processes and showcase cell cycle progression following release from pheromone-induced arrest in yeast.

Plasma Proteomics of the Fontan Circulation Reveal Signatures of Oxidative Stress and Cell Death

BACKGROUND

Single ventricle congenital heart disease like hypoplastic left heart syndrome with a Fontan circulation constitutes, the largest group of children hospitalized with circulation failure, experiencing an in-hospital mortality rate of 20% to 50%. We investigated the mechanisms leading to Fontan failure to identify novel therapeutic targets.

METHODS

Blood was collected from patients with hypoplastic left heart syndrome post-Fontan and controls (n=6/group). Plasma microvesicles were isolated, and proteomics assessed using data-independent acquisition mass spectroscopy. Dysregulated proteins with a fold change >1.5 or ≤1.5, P<0.05, were evaluated using the Database for Annotation, Visualization, and Integrated Discovery and Ingenuity pathway analysis. Correlation of highly dysregulated proteins was assessed with New York Heart Association class, right ventricular fractional area change, oxygen saturation, and hemoglobin.

RESULTS

The age of Fontan patients versus controls was 16.0±2.1 versus 15.3±2.2. Three of 6 Fontan patients were in New York Heart Association class II, and 3 of 6 were in New York Heart Association III/IV; 4 of 6 had Fontan-associated liver disease. Overall, 72 proteins were upregulated, and 187 proteins were downregulated in Fontan failure. Proteins upregulated in Fontan failure predicted cell death pathways (Solute carrier family 2, Angiotensinogen, CD14) and mitochondrial reactive oxygen species signaling (ATP5F1A, S100A8); downregulated proteins predicted impaired cell survival (tyrosine-protein kinase, endothelial growth factors) and mitochondrial antioxidant enzymes (GPX1, PRDX5) Increasing expression of the following proteins was associated with worsening New York Heart Association class, ventricular function and cyanosis: complement system (C1QA, r=0.91), mitochondrial reactive oxygen species generation (HSPD1, r=0.81; ATP5F1A, r=0.75), and cytoskeletal proteins (ANK1, r=0.63; ACTN1, r=0.76).

CONCLUSIONS

Proteins from circulating microvesicles from patients with hypoplastic left heart syndrome post-Fontan are mostly from the liver. While this pilot study is limited by its sample size and may not represent the broader Fontan population, the proteomic changes were associated with worsening heart failure and cyanosis, suggesting their potential utility as biomarkers.

Nuclear SREBP2 condensates regulate the transcriptional activation of lipogenic genes and cholesterol homeostasis

The precursor of sterol regulatory element-binding protein-2 (SREBP2) is a membrane-bound transcription factor regulating cholesterol biosynthesis. Under cholesterol-deficient conditions, mature SREBP2 is released from membrane-bound precursors through proteolytic cleavage and enters the nucleus. However, regulation of the transcriptional activity of nuclear SREBP2 (nSREBP2) is poorly understood. In the present study, we reported that nSREBP2 forms nuclear condensates through its amino-terminal, intrinsically disordered region (IDR) and works together with transcription coactivators, partly on superenhancers, for the transcriptional activation of SREBP2 target genes. Substitution of a conserved phenylalanine by alanine within the IDR abolishes the formation of nSREBP2 condensates and reduces its transcriptional activity. This can be effectively rescued by fusion with a phase separation driving FUS-IDR. Knock-in of the phenylalanine-to-alanine substitution in male mice compromises feeding-induced nSREBP2 activity and lowers hepatic and circulating cholesterol levels, underscoring the functional significance of nSREBP2 condensates. Together, the present study reveals that nuclear condensates driven by nSREBP2 N-terminal IDR facilitate the efficient activation of lipogenic genes and play an important role in cholesterol homeostasis.

Validation studies and multiomics analysis of Zhx2 as a candidate quantitative trait gene underlying brain oxycodone metabolite (oxymorphone) levels and behavior

Sensitivity to the subjective reinforcing properties of opioids has a genetic component and can predict addiction liability of opioid compounds. We previously identified Zhx2 as a candidate gene underlying increased brain concentration of the oxycodone (OXY) metabolite oxymorphone (OMOR) in BALB/cJ (J) versus BALB/cByJ (By) females that could increase OXY state-dependent reward. A large structural intronic variant is associated with a robust reduction of Zhx2 expression in J mice, which we hypothesized enhances OMOR levels and OXY addiction-like behaviors. We tested this hypothesis by restoring the Zhx2 loss-of-function in J mice (mouse endogenous retroviral element knockout) and modeling the loss-of-function variant through knocking out the Zhx2 coding exon (exon 3 knockout [E3KO]) in By mice and assessing brain OXY metabolite levels and behavior. Consistent with our hypothesis, Zhx2 E3KO females showed an increase in brain OMOR levels and OXY-induced locomotor activity. However, contrary to our hypothesis, state-dependent expression of OXY conditioned place preference decreased in E3KO females and increased in E3KO males. We also overexpressed Zhx2 in the livers and brains of J mice and observed Zhx2 overexpression in select brain regions that was associated with reduced OXY state-dependent learning. Integrative transcriptomic and proteomic analysis of E3KO mice identified astrocyte function, cell adhesion, extracellular matrix properties, and endothelial cell functions as pathways influencing brain OXY metabolite concentration and behavior. These results support Zhx2 as a quantitative trait gene underlying brain OMOR concentration that is associated with changes in OXY behavior and implicate potential quantitative trait mechanisms that together inform our overall understanding of Zhx2 in brain function. SIGNIFICANCE STATEMENT: This study validated Zhx2 as a gene whose dysfunction increases brain levels of a highly potent and addictive metabolite of oxycodone, oxymorphone, in a female-specific manner. This result has broad implications for understanding the role of oxycodone metabolism and brain oxymorphone levels in the addiction liability of oxycodone (the active ingredient in OxyContin) and highlights the need for the study of sex differences in opioid metabolism as it relates to the addiction liability of opioids and opioid use disorder.

O-GlcNAcylation reduces proteome solubility and regulates the formation of biomolecular condensates in human cells

O-GlcNAcylation plays critical roles in the regulation of protein functions and cellular activities, including protein interactions with other macromolecules. While the formation of biomolecular condensates (or biocondensates) regulated by O-GlcNAcylation in a few individual proteins has been reported, systematic investigation of O-GlcNAcylation on the regulation of biocondensate formation remains to be explored. Here we systematically study the roles of O-GlcNAcylation in regulating protein solubility and its impacts on RNA-protein condensates using mass spectrometry-based chemoproteomics. Unexpectedly, we observe a system-wide decrease in the solubility of proteins modified by O-GlcNAcylation, with glycoproteins involved in focal adhesion and actin binding exhibiting the most significant decrease. Furthermore, O-GlcNAcylation sites located in disordered regions and with fewer acidic and aromatic residues nearby are related to a greater drop in protein solubility. Additionally, we discover that a specific group of O-GlcNAcylation events promotes the dissociation of RNA-protein condensates under heat stress, while some enhance the formation of RNA-protein condensates during the recovery phase. Using site mutagenesis, inhibition of O-GlcNAc transferase, and fluorescence microscopy, we validate that O-GlcNAcylation regulates the formation of biocondensates for YTHDF3 and NUFIP2. This work advances our understanding of the functions of protein O-GlcNAcylation and its roles in the formation of biomolecular condensates.

The YEATS domain is a selective reader of histone methacrylation

Metabolically regulated lysine acylation modifications in proteins play a major role in epigenetic processes and cellular homeostasis. A new type of histone acylation, lysine methacrylation, has recently been identified but remains poorly characterized. Here, we show that lysine methacrylation can be generated through metabolism of sodium methacrylate and enzymatically removed in cells, and that the YEATS domain but not bromodomain recognizes this modification. Structural and biochemical analyses reveal the π-π-π-stacking mechanism for binding of the YEATS domain of ENL to methacrylated histone H3K18 (H3K18mc). Using mass spectrometry proteomics, we demonstrate that methacrylate induces global methacrylation of a set of proteins that differs from the set of methacrylated proteins associated with valine metabolism. These findings suggest that high levels of methacrylate may potentially perturb cellular functions of these proteins by altering protein methacrylation profiles.

Exploring Diversity of Conopeptides and Revealing Novel Conoinsulins from Conus betulinus by Proteomic Analyses

The venom of cone snails, a potent weapon for predation and defense, contains diverse bioactive peptides (known as conopeptides, or conotoxins) that target various ion channels and receptors, offering potential as pharmacological tools or therapeutics. While transcriptomic studies have expanded conopeptide databases, proteomic validation remains limited. Here, we integrated two high-resolution mass spectrometry platforms to explore conopeptide diversity in Conus betulinus. A total of 283 conopeptides were identified, with 268 classifiable into known gene superfamilies or homology classes, while 15 unclassified conopeptides represent novel superfamilies. There were 46 newly discovered sequences and five new cysteine frameworks. Notably, we report the first proteomic identification of two novel conoinsulins in C. betulinus, Con-ins Be1 and Con-ins Be2. Both of them were predicted to retain insulin's canonical A/B-chain architecture. Structure modeling using the AlphaFold2 multimer suggested that Con-ins Be1 has a four-disulfide-bond arrangement, differing from the three disulfide bonds found in vertebrate insulin. In contrast, Con-ins Be2 was predicted to have three disulfide bonds, consistent with the structure of the vertebrate insulin. In summary, our study not only expanded the conopeptide repository but also provided two novel conoinsulins that may serve as pharmacological tools for insulin system research and merit further investigation.

Quantitative proteomics analysis of triple-negative breast cancers

Triple-negative breast cancer (TNBC) accounts for approximately 15% of all Breast Cancer (BC) cases with poorer prognosis and clinical outcomes compared to other BC subtypes due to greater tumor heterogeneity and few therapeutically targetable oncogenic drivers. To reveal actionable pathways for anti-cancer treatment, we use a proteomic approach to quantitatively compare the abundances of 6306 proteins across 55 formalin-fixed and paraffin-embedded (FFPE) TNBC tumors. We identified four major TNBC clusters by unsupervised clustering analysis of protein abundances. Analyses of clinicopathological characteristics revealed associations between the proteomic profiles and clinical phenotypes exhibited by each subtype. We validate the findings by inferring immune and stromal cell type composition from genome-wide DNA methylation profiles. Finally, quantitative proteomics on TNBC cell lines was conducted to identify in vitro models for each subtype. Collectively, our data provide subtype-specific insights into molecular drivers, clinicopathological phenotypes, tumor microenvironment (TME) compositions, and potential pharmacologic vulnerabilities for further investigations.

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.

Traffic Jam activates the Flamenco piRNA cluster locus and the Piwi pathway to ensure transposon silencing and Drosophila fertility

Flamenco (Flam) is a prominent Piwi-interacting RNA (piRNA) locus expressed in Drosophila ovarian follicle cells that silences gypsy/mdg4 transposons to ensure female fertility. Promoter-bashing reporter assays in ovarian somatic sheet (OSS) cells uncover compact enhancer sequences within Flam. We confirm the enhancer sequence relevance in vivo with Drosophila Flam deletion mutants that compromise Flam piRNA levels and female fertility. Proteomic analysis of proteins associated with Flam enhancer sequences discover the transcription factor Traffic Jam (TJ). Tj knockdown in OSS cells causes a decrease in Flam transcripts, Flam piRNAs, and multiple Piwi pathway genes. TJ chromatin immunoprecipitation sequencing (ChIP-seq) analysis confirms TJ binding at enhancer sequences deleted in our distinct Flam mutants. TJ also binds multiple Piwi pathway gene enhancers and long terminal repeats of transposons that decrease in expression after Tj knockdown. TJ plays an integral role in the ongoing arms race between selfish transposons and their suppression by the host Piwi pathway and Flam piRNA locus.

Unveiling the substrate specificity of the ABC transporter Tba and its role in glycopeptide biosynthesis

Glycopeptide antibiotics (GPA) such as vancomycin are essential last-resort antibiotics produced by actinomycetes. Their biosynthesis is encoded within biosynthetic gene clusters, also harboring genes for regulation, and transport. Diverse types of GPAs have been characterized that differ in peptide backbone composition and modification patterns. However, little is known about the ATP-binding cassette (ABC) transporters facilitating GPA export. Employing a multifaceted approach, we investigated the substrate specificity of GPA ABC-transporters toward the type-I GPA balhimycin. Phylogenetic analysis suggested and trans-complementation experiments confirmed that balhimycin is exported only by the related type I GPA transporters Tba and Tva (transporter of vancomycin). Molecular dynamics simulations and mutagenesis experiments showed that Tba exhibits specificity toward the peptide backbone rather than the modifications. Unexpectedly, deletion or functional inactivation of Tba halted balhimycin biosynthesis. Combined with proximity biotinylation experiments, this suggested that the interaction of the active transporter with the biosynthetic machinery is required for biosynthesis.

The network response to Egf is tissue-specific

Epidermal growth factor receptor (Egfr)-driven signaling regulates fundamental homeostatic processes. Dysregulated signaling via Egfr is implicated in numerous disease pathologies and distinct Egfr-associated disease etiologies are known to be tissue-specific. The molecular basis of this tissue-specificity remains poorly understood. Most studies of Egfr signaling to date have been performed in vitro or in tissue-specific mouse models of disease, which has limited insight into Egfr signaling patterns in healthy tissues. Here, we carried out integrated phosphoproteomic, proteomic, and transcriptomic analyses of signaling changes across various mouse tissues in response to short-term stimulation with the Egfr ligand Egf. We show how both baseline and Egf-stimulated signaling dynamics differ between tissues. Moreover, we propose how baseline phosphorylation and total protein levels may be associated with clinically relevant tissue-specific Egfr-associated phenotypes. Altogether, our analyses illustrate tissue-specific effects of Egf stimulation and highlight potential links between underlying tissue biology and Egfr signaling output.

Study on the Mechanism of Action of the Pt(IV) Complex with Lonidamine Ligands by Ultrafast Chemical Proteomics

Platinum(II) complexes such as cisplatin, among a few others, are well-known anticancer metal-based drugs approved for clinical use. In spite of their wide acceptance, the respective chemotherapy is associated with severe side effects and the ability of tumors to quickly develop resistance. To overcome these drawbacks, the novel strategy is considered, which is based on the use of platinum complexes with bioactive ligands attached to act in synergy with platinum and to further improve its pharmacological properties. Among the recently introduced multiaction prodrugs is the Pt(IV) complex with two lonidamine ligands, the latter selectively inhibiting hexokinase and, thus, glycolysis in cancer cells. While platinum-based multiaction prodrugs exhibit increased levels of activity toward cancer cells and, thus, are considered potent to overcome the resistance to cisplatin, there is a crucial need to uncover their mechanism of action by revealing all possibly affected processes and targets across the whole cellular proteome. These are challenging tasks in proteomics requiring high-throughput analysis of hundreds of samples for just a single drug-to-proteome system. In this work, we performed these analyses for 8-azaguanine and the experimental Pt(IV)-lonidamine complex applied to ovarian cancer cell line A2780 employing both mechanism- and compound-centric ultrafast chemical proteomics approaches. These approaches were based on protein expression analysis and thermal proteome profiling, respectively. Data obtained for the Pt(IV)-lonidamine complex revealed regulation of proteins involved in the glucose metabolic process associated with lonidamine, further supporting the multiaction mechanism of this prodrug action.

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.

MS-RT: A Method for Evaluating MS/MS Clustering Performance for Metabolomics Data

The clustering of tandem mass spectra (MS/MS) is a crucial computational step to deduplicate repeated acquisitions in data-dependent experiments. This technique is essential in untargeted metabolomics, particularly with high-throughput mass spectrometers capable of generating hundreds of MS/MS spectra per second. Despite advancements in MS/MS clustering algorithms in proteomics, their performance in metabolomics has not been extensively evaluated due to the lack of database search tools with false discovery rate control for molecule identification. To bridge this gap, this study introduces the MS1-retention time (MS-RT) method to assess MS/MS clustering performance in metabolomics data sets. Here, we validate MS-RT by comparing MS-RT to established proteomics clustering evaluation approaches that utilize database search identifications. Additionally, we evaluate the performance of several MS/MS clustering tools on metabolomics data sets, highlighting their advantages and drawbacks. This MS-RT method and the MS/MS clustering tool benchmarking will provide valuable real world practical recommendations for tools and set the stage for future advancements in metabolomics MS/MS clustering.

Discovery of RNA-Protein Molecular Clamps Using Proteome-Wide Stability Assays

Uncompetitive inhibition is an effective strategy for suppressing dysregulated enzymes and their substrates, but discovery of suitable ligands depends on often-unavailable structural knowledge and serendipity. Hence, despite surging interest in mass spectrometry-based target identification, proteomic studies of substrate-dependent target engagement remain sparse. Herein, we describe a strategy for the discovery of substrate-dependent ligand binding. Using proteome integral solubility alteration (PISA) assays, we show that simple biochemical additives can enable detection of RNA-protein-small molecule complexes in native cell lysates. We apply our approach to rocaglates, molecules that specifically clamp RNA to eukaryotic translation initiation factor 4A (eIF4A), DEAD-box helicase 3X (DDX3X), and potentially other members of the DEAD-box (DDX) helicase family. To identify unexpected interactions, we used a target class-specific thermal window and compared ATP analog and RNA base dependencies for key rocaglate-DDX interactions. We report novel DDX targets of high-profile rocaglates-including the clinical candidate Zotatifin-and validate our findings using limited proteolysis-mass spectrometry and fluorescence polarization (FP) experiments. We also provide structural insight into divergent DDX3X affinities between synthetic rocaglates. Taken together, our study provides a model for screening uncompetitive inhibitors using a chemical proteomics approach and uncovers actionable DDX clamping targets, clearing a path toward characterization of novel molecular clamps and associated RNA helicases.

Classification of Collagens via Peptide Ambiguation, in a Paleoproteomic LC-MS/MS-Based Taxonomic Pipeline

Liquid chromatography-mass spectrometry (LC-MS/MS) extends the matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) Zooarcheology by Mass Spectrometry (ZooMS) "mass fingerprinting" approach to species identification by providing fragmentation spectra for each peptide. However, ancient bone samples generate sparse data containing only a few collagen proteins, rendering target-decoy strategies unusable and increasing uncertainty in peptide annotation. To ameliorate this issue, we present a ZooMS/MS data pipeline that builds on a manually curated Collagen database and comprises two novel algorithms: isoBLAST and ClassiCOL. isoBLAST first extends peptide ambiguity by generating all "potential peptide candidates" isobaric to the annotated precursor. The exhaustive set of candidates created is then used to retain or reject different potential paths at each taxonomic branching point from superkingdom to species, until the greatest possible specificity is reached. Uniquely, ClassiCOL allows for the identification of taxonomic mixtures, including contaminated samples, as well as suggesting taxonomies not represented in sequence databases, including extinct taxa. All considered ambiguity is then graphically represented with clear prioritization of the potential taxa in the sample. Using public as well as in-house data acquired on different instruments, we demonstrate the performance of this universal postprocessing and explore the identification of both genetic and sample mixtures. Diet reconstruction from 40,000-year-old cave hyena coprolites illustrates the exciting potential of this approach.

SWAPS: A Modular Deep-Learning Empowered Peptide Identity Propagation Framework Beyond Match-Between-Run

Mass spectrometry (MS)-based proteomics relies heavily on MS/MS (MS2) data, which do not fully exploit the available MS1 information. Traditional peptide identity propagation (PIP) methods, such as match-between-runs (MBR), are limited to similar runs, particularly with the same liquid chromatography (LC) gradients, thus potentially underutilizing available proteomics libraries. We introduce SWAPS, a novel and modular MS1-centric framework incorporating advances in peptide property prediction, extensive proteomics libraries, and deep-learning-based postprocessing to enable and explore PIP across more diverse experimental conditions and LC gradients. SWAPS substantially enhances precursor identification, especially in shorter gradients. On the example of 30, 15, and 7.5 min gradients, SWAPS achieves increases of 46.3, 86.2, and 112.1% on precursor level over MaxQuant's MS2-based identifications. Despite the inherent challenges in controlling false discovery rates (FDR) with MS1-based methods, SWAPS demonstrates strong efficacy in deconvoluting MS1 signals, offering powerful discrimination and deeper sequence exploration, while maintaining quantitative accuracy. By building on and applying peptide property predictions in practical contexts, SWAPS reveals that current models, while advanced, are still not fully comparable to experimental measurements, sparking the need for further research. Additionally, its modular design allows seamless integration of future improvements, positioning SWAPS as a forward-looking tool in proteomics.

Identification of a molecular resistor that controls UCP1-independent Ca2+ cycling thermogenesis in adipose tissue

Adipose tissue thermogenesis contributes to energy balance via mitochondrial uncoupling protein 1 (UCP1) and UCP1-independent pathways. Among UCP1-independent thermogenic mechanisms, one involves Ca2+ cycling via SERCA2b in adipose tissue; however, the underlying molecular basis remains elusive. Here, we report that an endoplasmic reticulum (ER) membrane-anchored peptide, C4orf3 (also known as another regulin [ALN]), uncouples SERCA2b Ca2+ transport from its ATP hydrolysis, rendering the SERCA2b-C4orf3 complex exothermic. Loss of C4orf3/ALN improved the energetic efficiency of SERCA2b-dependent Ca2+ transport without affecting SERCA2 expression, thereby reducing adipose tissue thermogenesis and increasing the adiposity of mice. Notably, genetic depletion of C4orf3 resulted in compensatory activation of UCP1-dependent thermogenesis following cold challenge. We demonstrated that genetic loss of both C4orf3 and Ucp1 additively impaired cold tolerance in vivo. Together, this study identifies C4orf3 as the molecular resistor to SERCA2b-mediated Ca2+ import that plays a key role in UCP1-independent thermogenesis and energy balance.

Endothelial Neurogranin Regulates Blood-Brain Barrier Permeability via Modulation of the AKT Pathway

Neurogranin (Ng) expression is a biomarker for Alzheimer's disease. A loss of brain Ng and an increase in CSF Ng positively correlate with cognitive decline. Ng is known to regulate neuronal calcium-calmodulin binding and synaptic plasticity, which are critical for learning/memory. Interestingly, we discovered that Ng is also expressed in mouse and human blood-brain barrier (BBB). However, the role of Ng expression in brain vasculature remains largely undefined. In this study, we investigated the role of Ng expression on neurovascular structure and function using Ng null mice and human cerebral microvascular endothelial (hCMEC/D3) cells. We performed brain clearing and immunolabeling of blood vessels from whole brains and brain slices. Deletion of Ng significantly decreases neurovascular density in mice. Using in vivo permeability assays, we found increased neurovascular permeability in Ng null mice. We also observed significant changes in the expression of tight junction proteins using western blot and immunofluorescent staining. To identify the molecular pathways involved, we carried out label-free proteomics on brain lysates from endothelial-specific Ng knockout mice. Ingenuity Pathway Analysis indicated that the AKT pathway is attenuated in the vasculature of endothelial-specific Ng knockout mice. To validate these in vivo findings, we pharmacologically manipulated AKT signaling in hCMEC/D3 cells and observed that inhibition of AKT activation causes increased permeability. Our results indicate that the loss of Ng expression alters neurovascular structure and permeability, potentially contributing to neurological dysfunction. Therefore, modulating Ng expression in the BBB may offer a novel therapeutic approach for Alzheimer's disease.

Intracellular diffusion in the cytoplasm increases with cell size in fission yeast

Diffusion in the cytoplasm can greatly impact cellular processes, yet regulation of macromolecular diffusion remains poorly understood. There is increasing evidence that cell size affects the density and macromolecular composition of the cytoplasm. Here, we studied whether cell size affects diffusion at the scale of macromolecules tens of microns in diameter. We analyzed the diffusive motions of intracellular genetically-encoded multimeric 40 nm nanoparticles (cytGEMs) in the cytoplasm of the fission yeast Schizosaccharomyces pombe. Using cell size mutants, we showed that cytGEMs diffusion coefficients decreased in smaller cells and increased in larger cells. This increase in diffusion in large cells may be due to a decrease in the DNA-to-cytoplasm ratio, as diffusion was not affected in large multinucleate cytokinesis mutant cells. In investigating the underlying causes of altered cytGEMs diffusion, we found that the proteomes of large and small cells exhibited size-specific changes, including the subscaling of ribosomal proteins in large cells. Comparison with a similar dataset from human cells revealed that features of size-dependent proteome remodeling were conserved. These studies demonstrate that cell size is an important parameter in determining the biophysical properties and the composition of the cytoplasm.

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.

Midkine Attenuates Aβ Fibril Assembly and Amyloid Plaque Formation

Proteomic profiling of Alzheimer's disease (AD) brains has identified numerous understudied proteins, including midkine (MDK), that are highly upregulated and correlated with Aβ since the early disease stage, but their roles in disease progression are not fully understood. Here we present that MDK attenuates Aβ assembly and influences amyloid formation in the 5xFAD amyloidosis mouse model. MDK protein mitigates fibril formation of both Aβ40 and Aβ42 peptides in Thioflavin T fluorescence assay, circular dichroism, negative stain electron microscopy, and NMR analysis. Knockout of Mdk gene in 5xFAD increases amyloid formation and microglial activation. Further comprehensive mass spectrometry-based profiling of whole proteome and detergent-insoluble proteome in these mouse models indicates significant accumulation of Aβ and Aβ-correlated proteins, along with microglial components. Thus, our structural and mouse model studies reveal a protective role of MDK in counteracting amyloid pathology in Alzheimer's disease.

Environmental matrix and moisture influence soil microbial phenotypes in a simplified porous media incubation

Soil moisture and porosity regulate microbial metabolism by influencing factors, such as system chemistry, substrate availability, and soil connectivity. However, accurately representing the soil environment and establishing a tractable microbial community that limits confounding variables is difficult. Here, we use a reduced-complexity microbial consortium grown in a glass bead porous media amended with chitin to test the effects of moisture and a structural matrix on microbial phenotypes. Leveraging metagenomes, metatranscriptomes, metaproteomes, and metabolomes, we saw that our porous media system significantly altered microbial phenotypes compared with the liquid incubations, denoting the importance of incorporating pores and surfaces for understanding microbial phenotypes in soils. These phenotypic shifts were mainly driven by differences in expression of Streptomyces and Ensifer, which included a significant decrease in overall chitin degradation between porous media and liquid. Our findings suggest that the success of Ensifer in porous media is likely related to its ability to repurpose carbon via the glyoxylate shunt amidst a lack of chitin degradation byproducts while potentially using polyhydroxyalkanoate granules as a C source. We also identified traits expressed by Ensifer and others, including motility, stress resistance, and carbon conservation, that likely influence the metabolic profiles observed across treatments. Together, these results demonstrate that porous media incubations promote structure-induced microbial phenotypes and are likely a better proxy for soil conditions than liquid culture systems. Furthermore, they emphasize that microbial phenotypes encompass not only the multi-enzyme pathways involved in metabolism but also include the complex interactions with the environment and other community members.IMPORTANCESoil moisture and porosity are critical in shaping microbial metabolism. However, accurately representing the soil environment in tractable laboratory experiments remains a challenging frontier. Through our reduced complexity microbial consortium experiment in porous media, we reveal that predicting microbial metabolism from gene-based pathways alone often falls short of capturing the intricate phenotypes driven by cellular interactions. Our findings highlight that porosity and moisture significantly affect chitin decomposition, with environmental matrix (i.e., glass beads) shifting community metabolism towards stress tolerance, reduced resource acquisition, and increased carbon conservation, ultimately invoking unique microbial strategies not evident in liquid cultures. Moreover, we find evidence that changes in moisture relate to community shifts regarding motility, transporters, and biofilm formation, which likely influence chitin degradation. Ultimately, our incubations showcase how reduced complexity communities can be informative of microbial metabolism and present a useful alternative to liquid cultures for studying soil microbial phenotypes.

The denitrosylase SCoR2 controls cardioprotective metabolic reprogramming

Acute myocardial infarction (MI) is a leading cause of morbidity and mortality, and therapeutic options remain limited. Endogenously generated nitric oxide (NO) is highly cardioprotective, but protection is not replicated by nitroso-vasodilators (e.g., nitrates, nitroprusside) used in clinical practice, highlighting specificity in NO-based signaling and untapped therapeutic potential. Signaling by NO is mediated largely by S-nitrosylation, entailing specific enzymes that form and degrade S-nitrosothiols in proteins (SNO-proteins), termed nitrosylases and denitrosylases, respectively. SNO-CoA Reductase 2 (SCoR2; product of the Akr1a1 gene) is a recently discovered protein denitrosylase. Genetic variants in SCoR2 have been associated with cardiovascular disease, but its function is unknown. Here we show that mice lacking SCoR2 exhibit robust protection in an animal model of MI. SCoR2 regulates ketolytic energy availability, antioxidant levels and polyol homeostasis via S-nitrosylation of key metabolic effectors. Human cardiomyopathy shows reduced SCoR2 expression and an S-nitrosylation signature of metabolic reprogramming, mirroring SCoR2-/- mice. Deletion of SCoR2 thus coordinately reprograms multiple metabolic pathways-ketone body utilization, glycolysis, pentose phosphate shunt and polyol metabolism-to limit infarct size, establishing SCoR2 as a novel regulator in the injured myocardium and a potential drug target.

Impact statement

Mice lacking the denitrosylase enzyme SCoR2/AKR1A1 demonstrate robust cardioprotection resulting from reprogramming of multiple metabolic pathways, revealing widespread, coordinated metabolic regulation by SCoR2.

Muscle-specific increased expression of JAG1 improves skeletal muscle phenotype in dystrophin-deficient mice

Therapeutic strategies for Duchenne Muscular Dystrophy (DMD) will likely require complementary approaches. One possibility is to explore genetic modifiers that improve muscle regeneration and function. The beneficial effects of the overexpression of Jagged-1 were described in escaper golden retriever muscular dystrophy (GRMD) dogs that had a near-normal life and validated in dystrophin-deficient zebrafish (1). To clarify the underlying biology of JAG1 overexpression in dystrophic muscles, we generated a transgenic mouse (mdx5cv-JAG1) model that lacks dystrophin and overexpresses human JAG1 in striated muscles. Skeletal muscles from mdx5cv-JAG1 and mdx5cv mice were studied at one, four, and twelve-month time points. JAG1 expression in mdx5cv-JAG1 increased by three to five times compared to mdx5cv. Consequently, mdx5cv-JAG1 muscles were significantly bigger and stronger than dystrophic controls, along with an increased number of myofibers. Proteomics data show increased dysferlin in mdx5cv-JAG1 muscles and an association of Nsd1 with the phenotype. Our data supports the positive effect of JAG1 overexpression in dystrophic muscles.

Hypertrophic Cardiomyopathy-Associated CRYABR123W Activates Calcineurin, Reduces Calcium Sequestration, and Alters the CRYAB Interactome and the Proteomic Response to Pathological Hypertrophy

Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiovascular condition in the world, affecting around 1 in 500 people. HCM is characterized by ventricular wall thickening, decreased ventricular chamber volume, and diastolic dysfunction. Inherited HCM is most commonly caused by sarcomere gene mutations; however, approximately 50% of patients do not present with a known mutation, highlighting the need for further research into additional pathological mutations. The alpha-B crystallin (CRYAB) mutation CRYABR123W was previously identified as a novel sarcomere-independent mutation causing HCM associated with pathological NFAT signaling in the setting of pressure overload. We generated stable H9C2 cell lines expressing FLAG-tagged wild-type and mutant CRYAB, which demonstrated that CRYABR123W increases calcineurin activity. Using AlphaFold to predict structural and interaction changes, we generated a model where CRYABR123W uniquely binds to the autoinhibitory domain of calcineurin. Co-immunoprecipitation using the CRYAB FLAG tag followed by mass spectrometry showed novel and distinct changes in the protein interaction patterns of CRYABR123W. Finally, mouse heart extracts from our wild-type CRYAB and CRYABR123W models with and without pressure overload caused by transverse aortic constriction (TAC) were used in global proteomic and phosphoproteomic mass spectrometry analysis, which showed dysregulation in cytoskeletal, metabolomic, cardiac, and immune function. Our data illustrate how CRYABR123W drives calcineurin activation and exhibits distinct changes in protein interaction and cellular pathways during the development of HCM and pathological cardiac hypertrophy.

Query Mix-Max Method for FDR Estimation Supported by Entrapment Queries

Estimating the false discovery rate (FDR) is one of the key steps in ensuring appropriate error control in the analysis of shotgun proteomics data. Traditional estimation methods typically rely on decoy sequence databases or spectral libraries, which may not always provide satisfactory results due to limitations of decoy construction methods. This study introduces the query mix-max (QMM) method, a decoy-free alternative for FDR estimation in proteomics. The QMM framework builds upon the existing mix-max procedure but replaces decoy matches with entrapment queries to estimate the number of false positive discoveries. Through simulations and real data set analyses, the QMM method was demonstrated to provide reasonably accurate FDR estimation across various scenarios, particularly when smaller sample-to-entrapment spectra ratios were achieved. The QMM method tends to be conservatively biased, particularly at higher FDR values, which can ensure stringent FDR control. While flexible, the protocol's effectiveness may vary depending on the evolutionary distance between the sample and entrapment organisms. It also requires a sufficient number of entrapment queries to provide stable FDR estimates, especially for low FDR values. Despite these limitations, the QMM method is a promising alternative as one of the first query-based FDR estimation approaches in shotgun proteomics.

Isobaric Tagging and Data Independent Acquisition as Complementary Strategies for Proteome Profiling on an Orbitrap Astral Mass Spectrometer

Comprehensive global proteome profiling that is amenable to high throughput processing will broaden our understanding of complex biological systems. Here, we evaluate two leading mass spectrometry techniques, Data Independent Acquisition (DIA) and Tandem Mass Tagging (TMT), for extensive protein abundance profiling. DIA provides label-free quantification with a broad dynamic range, while TMT enables multiplexed analysis using isobaric tags for efficient cross-sample comparisons. We analyzed 18 samples, including four cell lines (IHCF, HCT116, HeLa, MCF7) under standard growth conditions, in addition to IHCF treated with two H2O2 concentrations, all in triplicate. Experiments were conducted on an Orbitrap Astral mass spectrometer, employing Field Asymmetric Ion Mobility Spectrometry (FAIMS). Despite utilizing different acquisition strategies, both the DIA and TMT approaches achieved comparable proteome depth and quantitative consistency, with each method quantifying over 10,000 proteins across all samples, with marginally higher protein-level precision for the TMT strategy. Relative abundance correlation analysis showed strong agreement at both peptide and protein levels. Our findings highlight the complementary strengths of DIA and TMT for high-coverage proteomic studies, providing flexibility in method selection based on specific experimental needs.

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.

Emerging protein sequencing technologies: proteomics without mass spectrometry?

INTRODUCTION

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has been a leading method for proteomics for 30 years. Advantages provided by LC-MS/MS are offset by significant disadvantages, including cost. Recently, several non-mass spectrometric methods have emerged, but little information is available about their capacity to analyze the complex mixtures routine for mass spectrometry.

AREAS COVERED

We review recent non-mass-spectrometric methods for sequencing proteins and peptides, including those using nanopores, sequencing by degradation, reverse translation, and short-epitope mapping, with comments on bioinformatics challenges, fundamental limitations, and areas where new technologies will be more or less competitive with LC-MS/MS. In addition to conventional literature searches, instrument vendor websites, patents, webinars, and preprints were also consulted to give a more up-to-date picture.

EXPERT OPINION

Many new technologies are promising. However, demonstrations that they outperform mass spectrometry in terms of peptides and proteins identified have not yet been published, and astute observers note important disadvantages, especially relating to the dynamic range of single-molecule measurements of complex mixtures. Still, even if the performance of emerging methods proves inferior to LC-MS/MS, their low cost could create a different kind of revolution: a dramatic increase in the number of biology laboratories engaging in new forms of proteomics research.

Incorporating Bone-Derived ECM into Macroporous Microribbon Scaffolds Accelerates Bone Regeneration

Tissue-derived extracellular matrix (tdECM) hydrogels serve as effective scaffolds for tissue regeneration by promoting a regenerative immune response. While most tdECM hydrogels are nanoporous and tailored for soft tissue, macroporosity is crucial for bone regeneration. Yet, there's a shortage of macroporous ECM-based hydrogels for this purpose. The study aims to address this gap by developing a co-spinning technique to integrate bone-derived ECM (bECM) into gelatin-based, macroporous microribbon (µRB) scaffolds. The effect of varying doses of bECM on scaffold properties was characterized. In vitro studies revealed 15% bECM as optimal for promoting MSC osteogenesis and macrophage (Mφ) polarization. When implanted in a mouse critical-sized cranial bone defect model, 15% bECM with tricalcium phosphate (TCP) microparticles significantly accelerated bone regeneration and vascularization, filling over 55% of the void by week 2. Increasing bECM to 25% enhanced mesenchymal stem cell (MSC) recruitment and decreased M1 Mφ polarization but reduced overall bone formation and vascularization. The findings demonstrate co-spun gelatin/bECM hydrogels as promising macroporous scaffolds for robust endogenous bone regeneration, without the need for exogenous cells or growth factors. While this study focused on bone regeneration, this platform holds the potential for incorporating various tdECM into macroporous scaffolds for diverse tissue regeneration applications.

An engineered trafficking biosensor reveals a role for DNAJC13 in DOR downregulation

Trafficking of G protein-coupled receptors (GPCRs) through the endosomal-lysosomal pathway is critical to homeostatic regulation of GPCRs following activation with agonist. Identifying the genes involved in GPCR trafficking is challenging due to the complexity of sorting operations and the large number of cellular proteins involved in the process. Here, we developed a high-sensitivity biosensor for GPCR expression and agonist-induced trafficking to the lysosome by leveraging the ability of the engineered peroxidase APEX2 to activate the fluorogenic substrate Amplex UltraRed (AUR). We used the GPCR-APEX2/AUR assay to perform a genome-wide CRISPR interference screen focused on identifying genes regulating expression and trafficking of the δ-opioid receptor (DOR). We identified 492 genes consisting of both known and new regulators of DOR function. We demonstrate that one new regulator, DNAJC13, controls trafficking of multiple GPCRs, including DOR, through the endosomal-lysosomal pathway by regulating the composition of the endosomal proteome and endosomal homeostasis.

Color-neutral and reversible tissue transparency enables longitudinal deep-tissue imaging in live mice

Light scattering in biological tissue presents a significant challenge for deep in vivo imaging. Our previous work demonstrated the ability to achieve optical transparency in live mice using intensely absorbing dye molecules, which created transparency in the red spectrum while blocking shorter-wavelength photons. In this paper, we extend this capability to achieve optical transparency across the entire visible spectrum by employing molecules with strong absorption in the ultraviolet spectrum and sharp absorption edges that rapidly decline upon entering the visible spectrum. This new color-neutral and reversible tissue transparency method enables optical transparency for imaging commonly used fluorophores in the green and yellow spectra. Notably, this approach facilitates tissue transparency for structural and functional imaging of the live mouse brain labeled with yellow fluorescent protein and GCaMP through the scalp and skull. We show that this method enables longitudinal imaging of the same brain regions in awake mice over multiple days during development. Histological analyses of the skin and systemic toxicology studies indicate minimal acute or chronic damage to the skin or body using this approach. This color-neutral and reversible tissue transparency technique opens new opportunities for noninvasive deep-tissue optical imaging, enabling long-term visualization of cellular structures and dynamic activity with high spatiotemporal resolution and chronic tracking capabilities.

An Aurora kinase A-BOD1L1-PP2A B56 axis promotes chromosome segregation fidelity

Cancer cells are often aneuploid and frequently display elevated rates of chromosome mis-segregation, called chromosomal instability (CIN). CIN is caused by hyperstable kinetochore-microtubule (K-MT) attachments that reduce the correction efficiency of erroneous K-MT attachments. UMK57, a chemical agonist of the protein MCAK (mitotic centromere-associated kinesin), improves chromosome segregation fidelity in CIN cancer cells by destabilizing K-MT attachments, but cells rapidly develop resistance. To determine the mechanism, we performed unbiased screens, which revealed increased phosphorylation in cells adapted to UMK57 at Aurora kinase A phosphoacceptor sites on BOD1L1 (protein biorientation defective 1-like-1). BOD1L1 depletion or Aurora kinase A inhibition eliminated resistance to UMK57. BOD1L1 localizes to spindles/kinetochores during mitosis, interacts with the PP2A phosphatase, and regulates phosphorylation levels of kinetochore proteins, chromosome alignment, mitotic progression, and fidelity. Moreover, the BOD1L1 gene is mutated in a subset of human cancers, and BOD1L1 depletion reduces cell growth in combination with clinically relevant doses of Taxol or Aurora kinase A inhibitor.

The Hao-Fountain syndrome protein USP7 regulates neuronal connectivity in the brain via a novel p53-independent ubiquitin signaling pathway

Mutation or deletion of the deubiquitinase USP7 causes Hao-Fountain syndrome (HAFOUS), which is characterized by speech delay, intellectual disability, and aggressive behavior and highlights important unknown roles of USP7 in the nervous system. Here, we conditionally delete USP7 in glutamatergic neurons in the mouse forebrain, triggering disease-relevant phenotypes, including sensorimotor deficits, impaired cognition, and aggressive behavior. Although USP7 deletion induces p53-dependent neuronal apoptosis, most behavioral abnormalities in USP7 conditional knockout mice persist following p53 loss. Strikingly, USP7 deletion perturbs the synaptic proteome and dendritic spinogenesis independent of p53. Integrated proteomics and biochemical analyses identify the RNA splicing factor Ppil4 as a key substrate of USP7. Ppil4 knockdown phenocopies the effect of USP7 loss on dendritic spines. Accordingly, USP7 loss disrupts splicing of synaptic genes. These findings reveal that USP7-Ppil4 signaling regulates neuronal connectivity in the developing brain with implications for our understanding of HAFOUS pathogenesis and other neurodevelopmental disorders.