TMTpro reagents: a set of isobaric labeling mass tags enables simultaneous proteome-wide measurements across 16 samples

Fibre-specific mitochondrial protein abundance is linked to resting and post-training mitochondrial content in the muscle of men

Analyses of mitochondrial adaptations in human skeletal muscle have mostly used whole-muscle samples, where results may be confounded by the presence of a mixture of type I and II muscle fibres. Using our adapted mass spectrometry-based proteomics workflow, we provide insights into fibre-specific mitochondrial differences in the human skeletal muscle of men before and after training. Our findings challenge previous conclusions regarding the extent of fibre-type-specific remodelling of the mitochondrial proteome and suggest that most baseline differences in mitochondrial protein abundances between fibre types reported by us, and others, might be due to differences in total mitochondrial content or a consequence of adaptations to habitual physical activity (or inactivity). Most training-induced changes in different mitochondrial functional groups, in both fibre types, were no longer significant in our study when normalised to changes in markers of mitochondrial content.

Cellular thermal shift assay: an approach to identify and assess protein target engagement

INTRODUCTION

A comprehensive and global knowledge of protein target engagement is of vital importance for mechanistic studies and in drug development. Since its initial introduction, the cellular thermal shift assay (CETSA) has proven to be a reliable and flexible technique that can be widely applied to multiple contexts and has profound applications in facilitating the identification and assessment of protein target engagement.

AREAS COVERED

This review introduces the principle of CETSA, elaborates on western blot-based CETSA and MS-based thermal proteome profiling (TPP) as well as the major applications and prospects of these approaches.

EXPERT OPINION

CETSA primarily evaluates a given ligand binding to a particular target protein in cells and tissues with the protein thermal stabilities analyzed by western blot. When coupling mass spectrometry with CETSA, thermal proteome profiling allows simultaneous proteome-wide experiment that greatly increased the efficiency of target engagement evaluation, and serves as a promising strategy to identify protein targets and off-targets as well as protein-protein interactions to uncover the biological effects. The CETSA approaches have broad applications and potentials in drug development and clinical research.

Multi-omics revealed the mechanism of feed efficiency in sheep by the combined action of the host and rumen microbiota

This study was conducted to investigate potential regulatory mechanisms of feed efficiency (FE) in sheep by linking rumen microbiota with its host by the multi-omics analysis. One hundred and ninety-eight hybrid female sheep (initial body weight = 30.88 ± 4.57 kg; 4-month-old) were selected as candidate sheep. Each test sheep was fed in an individual pen for 60 days, and the residual feed intake (RFI) was calculated. The ten candidate sheep with the highest RFI were divided into the Low-FE group, and the ten with the lowest RFI were divided into the High-FE group, all selected for sample collection. The RFI, average daily gain and average daily feed intake were highly significantly different between the two experimental groups (P < 0.05). Compared with Low-FE group, the insulin-like growth factor-1 and very low-density lipoprotein in serum and the propionate in rumen significantly increased in High-FE group (P < 0.01), but the acetate:propionate ratio in rumen significantly decreased in High-FE group (P = 0.034). Metagenomics revealed Selenomonas ruminantium, Selenomonas sp. and Faecalibacterium prausnitzi i were key bacteria, and increased abundance of the genes encoding the enzymes for cellulose degradation and production of propionate in High-FE group. The results of proteomics and section showed the rumen papilla length (P < 0.001) and expression of carbonic anhydrase and Na+/K+-ATPase were significantly higher in High-FE group (P < 0.05). On the other hand, the acetyl-CoA content significantly increased in the liver of High-FE group (P = 0.002). The relative expression levels of insulin-like growth factor-1 and apolipoprotein A4 genes were significantly up-regulated in the liver of High-FE group (P < 0.01), but relative expression level of monoacylglycerol O-acyltransferase 3 gene was significantly down-regulated (P = 0.037). These findings provide the mechanism by which the collaborative interaction between rumen microbiota fermentation and host uptake and metabolism of fermentation products impacts feed efficiency traits in sheep.

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.

Time-resolved interactome profiling deconvolutes secretory protein quality control dynamics

Many cellular processes are governed by protein-protein interactions that require tight spatial and temporal regulation. Accordingly, it is necessary to understand the dynamics of these interactions to fully comprehend and elucidate cellular processes and pathological disease states. To map de novo protein-protein interactions with time resolution at an organelle-wide scale, we developed a quantitative mass spectrometry method, time-resolved interactome profiling (TRIP). We apply TRIP to elucidate aberrant protein interaction dynamics that lead to the protein misfolding disease congenital hypothyroidism. We deconvolute altered temporal interactions of the thyroid hormone precursor thyroglobulin with pathways implicated in hypothyroidism pathophysiology, such as Hsp70-/90-assisted folding, disulfide/redox processing, and N-glycosylation. Functional siRNA screening identified VCP and TEX264 as key protein degradation components whose inhibition selectively rescues mutant prohormone secretion. Ultimately, our results provide novel insight into the temporal coordination of protein homeostasis, and our TRIP method should find broad applications in investigating protein-folding diseases and cellular processes.

A Tutorial Review of Labeling Methods in Mass Spectrometry-Based Quantitative Proteomics

Recent advancements in mass spectrometry (MS) have revolutionized quantitative proteomics, with multiplex isotope labeling emerging as a key strategy for enhancing accuracy, precision, and throughput. This tutorial review offers a comprehensive overview of multiplex isotope labeling techniques, including precursor-based, mass defect-based, reporter ion-based, and hybrid labeling methods. It details their fundamental principles, advantages, and inherent limitations along with strategies to mitigate the limitation of ratio-distortion. This review will also cover the applications and latest progress in these labeling techniques across various domains, including cancer biomarker discovery, neuroproteomics, post-translational modification analysis, cross-linking MS, and single-cell proteomics. This Review aims to provide guidance for researchers on selecting appropriate methods for their specific goals while also highlighting the potential future directions in this rapidly evolving field.

High-Throughput Metabolomics using 96-plex Isotope Tagging

Liquid chromatography-mass spectrometry (LC-MS) based metabolomics suffers from extended duty cycles and matrix-dependent quantitation. Chemical tags with 96 unique masses are reported, which alleviate the metabolomic workflow bottleneck and allow for absolute quantitation. A metabolic screen for carboxylic acids was performed on mammalian cells deprived of various nutrients and showed 24% RSD and analysis of 288 samples in 2 h.

Multisensory gamma stimulation mitigates the effects of demyelination induced by cuprizone in male mice

Demyelination is a common pathological feature in a wide range of diseases, characterized by the loss of myelin sheath and myelin-supporting oligodendrocytes. These losses lead to impaired axonal function, increased vulnerability of axons to damage, and result in significant brain atrophy and neuro-axonal degeneration. Multiple pathomolecular processes contribute to neuroinflammation, oligodendrocyte cell death, and progressive neuronal dysfunction. In this study, we use the cuprizone mouse model of demyelination to investigate long-term non-invasive gamma entrainment using sensory stimulation as a potential therapeutic intervention for promoting myelination and reducing neuroinflammation in male mice. Here, we show that multisensory gamma stimulation mitigates demyelination, promotes oligodendrogenesis, preserves functional integrity and synaptic plasticity, attenuates oligodendrocyte ferroptosis-induced cell death, and reduces brain inflammation. Thus, the protective effects of multisensory gamma stimulation on myelin and anti-neuroinflammatory properties support its potential as a therapeutic approach for demyelinating disorders.

Mass Spectrometry Acquisition and Fractionation Recommendations for TMT11 and TMT16 Labeled Samples

Proteome coverage and accurate protein quantification are both important for evaluating biological systems; however, compromises between quantification, coverage, and mass spectrometry (MS) resources are often necessary. Consequently, experimental parameters that impact coverage and quantification must be adjusted, depending on experimental goals. Among these parameters is offline prefractionation, which is utilized in MS-based proteomics to decrease sample complexity resulting in higher overall proteome coverage upon MS analysis. Prefractionation leads to increases in required MS analysis time, although this is often mitigated by isobaric labeling using tandem-mass tags (TMT), which allow samples to be multiplexed. Here we evaluate common prefractionation schemes, TMT variants, and MS acquisition methods and their impact on protein quantification and coverage. Furthermore, we provide recommendations for experimental design depending on the experimental goals.

Mass spectrometry-based proteomic landscape of rice reveals a post-transcriptional regulatory role of N6-methyladenosine

Rice is one of the most important staple food and model species in plant biology, yet its quantitative proteomes are largely uncharacterized. Here we quantify the relative protein levels of over 15,000 genes across major rice tissues using a tandem mass tag strategy followed by intensive fractionation and mass spectrometry. We identify tissue-specific and tissue-enriched proteins that are linked to the functional specificity of individual tissues. Proteogenomic comparison of rice and Arabidopsis reveals conserved proteome expression, which differs from mammals in that there is a strong separation of species rather than tissues. Notably, profiling of N6-methyladenosine (m6A) across the rice major tissues shows that m6A at untranslated regions is negatively correlated with protein abundance and contributes to the discordance between RNA and protein levels. We also demonstrate that our data are valuable for identifying novel genes required for regulating m6A methylation. Taken together, this study provides a paradigm for further research into rice proteogenome.

DNA O-MAP uncovers the molecular neighborhoods associated with specific genomic loci

The accuracy of crucial nuclear processes such as transcription, replication, and repair, depends on the local composition of chromatin and the regulatory proteins that reside there. Understanding these DNA-protein interactions at the level of specific genomic loci has remained challenging due to technical limitations. Here, we introduce a method termed "DNA O-MAP", which uses programmable peroxidase-conjugated oligonucleotide probes to biotinylate nearby proteins. We show that DNA O-MAP can be coupled with sample multiplexed quantitative proteomics and next-generation sequencing to quantify DNA-protein and DNA-DNA interactions at specific genomic loci.

6-Plex Tandem Phosphorus Tags (TPT) for Accurate Quantitative Proteomics

Isobaric chemical labeling is a widely used strategy for high-throughput quantitative proteomics based on mass spectrometry. However, commercially available reagents have high costs in applications as well as the sensitivity limitations for detection of the trace protein samples. Previously, we developed a 2-plex isobaric labeling strategy based on phosphorus chemistry for ultrasensitive proteome quantification with high accuracy. In this work, 6-plex tandem phosphorus tags (TPT) were developed with 3-fold increase in the multiplexing quantitative capacity compared to the 2-plex isobaric phosphorus reagents introduced previously. High isotope enrichment of 18O labeling was incorporated into the phosphoryl group with three exchangeable oxygen atoms by using commercially available H218O. The combinational incorporations of 18O atom in reporter ions and balance group set up the low-cost foundation for development of multiplex TPT reagents. The novel 6-plex TPT reagents could produce phosphoramidate as unique reporter ions with approximately 1 Da mass difference and thus enable 6-plex quantitative analysis in high-resolution ESI-MS/MS analysis. Using HeLa cell tryptic peptides, we concluded that 6-plex TPT reagents could facilitate large-scale accurate quantitative proteomics with very high labeling efficiency.

Suppression of the Escherichia coli rnpA49 conditionally lethal phenotype by different compensatory mutations

RNase P is an essential enzyme found across all domains of life that is responsible for the 5'-end maturation of precursor tRNAs. For decades, numerous studies have sought to elucidate the mechanisms and biochemistry governing RNase P function. However, much remains unknown about the regulation of RNase P expression, the turnover and degradation of the enzyme, and the mechanisms underlying the phenotypes and complementation of specific RNase P mutations, especially in the model bacterium, Escherichia coli In E. coli, the temperature-sensitive (ts) rnpA49 mutation in the protein subunit of RNase P has arguably been one of the most well-studied mutations for examining the enzyme's activity in vivo. Here, we report for the first time naturally occurring temperature-resistant suppressor mutations of E. coli strains carrying the rnpA49 allele. We find that rnpA49 strains can partially compensate the ts defect via gene amplifications of either RNase P subunit (rnpA49 or rnpB) or by the acquisition of loss-of-function mutations in Lon protease or RNase R. Our results agree with previous plasmid overexpression and gene deletion complementation studies, and importantly suggest the involvement of Lon protease in the degradation and/or regulatory pathway(s) of the mutant protein subunit of RNase P. This work offers novel insights into the behavior and complementation of the rnpA49 allele in vivo and provides direction for follow-up studies regarding RNase P regulation and turnover in E. coli.

Proteome-scale tissue mapping using mass spectrometry based on label-free and multiplexed workflows

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ~3500 proteins at a spatial resolution of 50 µm and the highest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provide robust protein quantifications in identifying differentially abundant proteins and spatially co-variable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial co-expression analysis.

Protein Thermal Stability Changes Induced by the Global Methylation Inhibitor 3-Deazaneplanocin A (DZNep)

DZNep (3-deazaneplanocin A) is commonly used to reduce lysine methylation. DZNep inhibits S-adenosyl-l-homocysteine hydrolase (AHCY), preventing the conversion of S-adenosyl-l-homocysteine (SAH) into L-homocysteine. As a result, the SAM-to-SAH ratio decreases, an indicator of the methylation potential within a cell. Many studies have characterized the impact of DZNep on histone lysine methylation or in specific cell or disease contexts, but there has yet to be a study looking at the potential downstream impact of DZNep treatment on proteins other than histones. Recently, protein thermal stability has provided a new dimension for studying the mechanism of action of small-molecule inhibitors. In addition to ligand binding, post-translational modifications and protein-protein interactions impact thermal stability. Here, we sought to characterize the protein thermal stability changes induced by DZNep treatment in HEK293T cells using the Protein Integral Solubility Alteration (PISA) assay. DZNep treatment altered the thermal stability of 135 proteins, with over half previously reported to be methylated at lysine residues. In addition to thermal stability, we identify changes in transcript and protein abundance after DZNep treatment to distinguish between direct and indirect impacts on thermal stability. Nearly one-third of the proteins with altered thermal stability had no changes at the transcript or protein level. Of these thermally altered proteins, CDK6 had a stabilized methylated peptide, while its unmethylated counterpart was unaltered. Multiple methyltransferases were among the proteins with thermal stability alteration, including DNMT1, potentially due to changes in the SAM/SAH levels. This study systematically evaluates DZNep's impact on the transcriptome, the proteome, and the thermal stability of proteins.

Double Cyclization Tandem Mass for Identification and Quantification of Phosphatidylcholines Using Isobaric Six-Plex Capillary nLC-MS/MS

Multiplexing of phosphatidylcholine analysis is hindered by a lack of appropriate derivatization. Presented here is a tagging scheme that uses a quaternary amine tag and targets the hydroxy group of the phosphate, which switches the net charge from neutral to +2. Quantitative yields were achieved from >99% reaction completion derived by dimethoxymethyl morpholinium (DMTMM) activation. Fragmentation of phosphatidylcholines (PCs) and lysophosphatidylcholines (LPCs) releases two trimethylamines and the acyl chains through neutral loss and generates a unique double cyclization constant mass reporter. Selective incorporation of isotopes onto the tag produces a six-plex set of isobaric reagents. For equivalent six-plex-labeled samples, <14% RSD was achieved, followed by a dynamic range of 1:10 without signal compression. Quantification of PCs/LPCs in human hepatic cancer cells was conducted as six-plex using data-dependent analysis tandem MS. We report a six-plex qualitative and quantitative isobaric tagging strategy expanding the limits of analyzing PCs/LPCs.

Promises and Challenges of populational Proteomics in Health and Disease

Advances in proteomic assay technologies have significantly increased coverage and throughput, enabling recent increases in the number of large-scale population-based proteomic studies of human plasma and serum. Improvements in multiplexed protein assays have facilitated the quantification of thousands of proteins over a large dynamic range, a key requirement for detecting the lowest-ranging, and potentially the most disease-relevant, blood-circulating proteins. In this perspective, we examine how populational proteomic datasets in conjunction with other concurrent omic measures can be leveraged to better understand the genomic and non-genomic correlates of the soluble proteome, constructing biomarker panels for disease prediction, among others. Mass spectrometry workflows are discussed as they are becoming increasingly competitive with affinity-based array platforms in terms of speed, cost, and proteome coverage due to advances in both instrumentation and workflows. Despite much success, there remain considerable challenges such as orthogonal validation and absolute quantification. We also highlight emergent challenges associated with study design, analytical considerations, and data integration as population-scale studies are run in batches and may involve longitudinal samples collated over many years. Lastly, we take a look at the future of what the nascent next-generation proteomic technologies might provide to the analysis of large sets of blood samples, as well as the difficulties in designing large-scale studies that will likely require participation from multiple and complex funding sources and where data sharing, study designs, and financing must be solved.

Evaluation of proteome dynamics: Implications for statistical confidence in mass spectrometric determination

Single-cell proteomics is currently far less productive than other approaches. Still, the proteomic community is having trouble adapting to the limitation of having to examine fewer cells than they would like. Studies on a small number of cells should be carefully planned to maximize the chances of success in this situation. This study aims to determine how sample size and measurement speed (slope)/variation affect the accuracy of a protein proteome mass spectrometric determination. The determination accuracy was shown to increase, and the false positive rate was shown to decrease as the sample size increased from 7 to 100 cells and the measurement slope/variation (S/V) ratio increased from 1 to 6. Furthermore, it was discovered that the number of cells in the sample increased the accuracy of this estimate. Thus, for 100 cells, the measurement S/V ratio was typically estimated to be very close to the real-world value, with a standard deviation of 0.35. For sample sizes from 7 to 100 cells, this accuracy was seen when calculating the measurement S/V ratio. The findings can help researchers plan experiments for mass spectroscopic protein proteome determination and other research purposes.

Identification of molecular determinants of gene-specific bursting patterns by high-throughput imaging screens

Stochastic transcriptional bursting is a universal property of active genes. While different genes exhibit distinct bursting patterns, the molecular mechanisms for gene-specific stochastic bursting are largely unknown. We have developed and applied a high-throughput-imaging based screening strategy to identify cellular factors and molecular mechanisms that determine the bursting behavior of human genes. Focusing on epigenetic regulators, we find that protein acetylation is a strong acute modulator of burst frequency, burst size and heterogeneity of bursting. Acetylation globally affects the Off-time of genes but has gene-specific effects on the On-time. Yet, these effects are not strongly linked to promoter acetylation, which do not correlate with bursting properties, and forced promoter acetylation has variable effects on bursting. Instead, we demonstrate acetylation of the Integrator complex as a key determinant of gene bursting. Specifically, we find that elevated Integrator acetylation decreases bursting frequency. Taken together our results suggest a prominent role of non-histone proteins in determining gene bursting properties, and they identify histone-independent acetylation of a transcription cofactor as an allosteric modulator of bursting via a far-downstream bursting checkpoint.

An Efficient, Amine-Specific, and Cost-Effective Method for TMT 6/11-plex Labeling Improves the Proteome Coverage, Quantitative Accuracy and Precision

Tandem mass tags (TMT) are widely used in proteomics to simultaneously quantify multiple samples in a single experiment. The tags can be easily added to the primary amines of peptides/proteins through chemical reactions. In addition to amines, TMT reagents also partially react with the hydroxyl groups of serine, threonine, and tyrosine residues under alkaline conditions, which significantly compromises the analytical sensitivity and precision. Under alkaline conditions, reducing the TMT molar excess can partially mitigate overlabeling of histidine-free peptides, but has a limited effect on peptides containing histidine and hydroxyl groups. Here, we present a method under acidic conditions to suppress overlabeling while efficiently labeling amines, using only one-fifth of the TMT amount recommended by the manufacturer. In a deep-scale analysis of a yeast/human two-proteome sample, we systematically evaluated our method against the manufacturer's method and a previously reported TMT-reduced method. Our method reduced overlabeled peptides by 9-fold and 6-fold, respectively, resulting in the substantial enhancement in peptide/protein identification rates. More importantly, the quantitative accuracy and precision were improved as overlabeling was reduced, endowing our method with greater statistical power to detect 42% and 12% more statistically significant yeast proteins compared to the standard and TMT-reduced methods, respectively. Mass spectrometric data have been deposited in the ProteomeXchange Consortium via the iProX partner repository with the data set identifier PXD047052.

The MYCN oncoprotein is an RNA-binding accessory factor of the nuclear exosome targeting complex

The MYCN oncoprotein binds active promoters in a heterodimer with its partner protein MAX. MYCN also interacts with the nuclear exosome, a 3'-5' exoribonuclease complex, suggesting a function in RNA metabolism. Here, we show that MYCN forms stable high-molecular-weight complexes with the exosome and multiple RNA-binding proteins. MYCN binds RNA in vitro and in cells via a conserved sequence termed MYCBoxI. In cells, MYCN associates with thousands of intronic transcripts together with the ZCCHC8 subunit of the nuclear exosome targeting complex and enhances their processing. Perturbing exosome function results in global re-localization of MYCN from promoters to intronic RNAs. On chromatin, MYCN is then replaced by the MNT(MXD6) repressor protein, inhibiting MYCN-dependent transcription. RNA-binding-deficient alleles show that RNA-binding limits MYCN's ability to activate cell growth-related genes but is required for MYCN's ability to promote progression through S phase and enhance the stress resilience of neuroblastoma cells.

The impact of abstinence from chronic alcohol consumption on the mouse striatal proteome: sex and subregion-specific differences

Alcohol misuse is the third leading preventable cause of death in the world. The World Health Organization currently estimates that 1 in 20 deaths are directly alcohol related. One of the ways in which consuming excessive levels of alcohol can both directly and indirectly affect human mortality and morbidity, is through chronic inflammation. Recently, studies have suggested a link between increased alcohol use and the incidence of neuroinflammatory-related diseases. However, the mechanism in which alcohol potentially influences neuroinflammatory processes is still being uncovered. We implemented an unbiased proteomics exploration of alcohol-induced changes in the striatum, with a specific emphasis on proteins related to inflammation. The striatum is a brain region that is critically involved with the progression of alcohol use disorder. Using mass spectrometry following voluntary alcohol self-administration in mice, we show that distinct protein abundances and signaling pathways in different subregions of the striatum are disrupted by chronic exposure to alcohol compared to water drinking control mice. Further, in mice that were allowed to experience abstinence from alcohol compared to mice that were non-abstinent, the overall proteome and signaling pathways showed additional differences, suggesting that the responses evoked by chronic alcohol exposure are dependent on alcohol use history. To our surprise we did not find that chronic alcohol drinking or abstinence altered protein abundance or pathways associated with inflammation, but rather affected proteins and pathways associated with neurodegeneration and metabolic, cellular organization, protein translation, and molecular transport processes. These outcomes suggest that in this drinking model, alcohol-induced neuroinflammation in the striatum is not a primary outcome controlling altered neurobehavioral function, but these changes are rather mediated by altered striatal neuronal structure and cellular health.

Overcoming the detrimental O-acylation in TMTpro labeling improves the proteome depth and quantification precision

BACKGROUND

With the advent of proline-based reporter isobaric Tandem Mass Tag (TMTpro) reagents, the sample multiplexing capacity of tandem mass tags (TMTs) has been expanded, and up to 18 samples can be quantified in a multiplexed manner. Like classic TMT reagents, TMTpro reagents contain a tertiary amine group, which markedly enhances their reactivity toward hydroxyl groups and results in O-acylation of serine, threonine and tyrosine residues. This overlabeling significantly compromises proteome analysis in terms of depth and precision. In particular, the reactivity of hydroxyl-containing residues can be dramatically enhanced when coexisting with a histidine in the same peptides, leading to a severe systematic bias against the analysis of these peptides. Although some protocols using a reduced molar excess of TMT under alkaline conditions can alleviate overlabeling of histidine-free peptides to some extent, they have a limited effect on histidyl- and hydroxyl-containing peptides.

RESULTS

Here, we report a novel TMTpro labeling method that overcomes detrimental overlabeling while providing high labeling efficiency of amines. Additionally, our method is cost-effective, as it requires only half the amount of TMTpro reagents recommended by the reagent manufacturer. In a deep-scale analysis of a yeast/human two-proteome model sample, we compared our method with a typical alkaline labeling method using a reduced molar excess of TMTpro. Even at a depth of over 10,000 proteins, our method detected 23.7% more unique peptides and 8.7% more protein groups compared to the alkaline labeling method. Moreover, our method significantly improved the quantitative precision due to the reduced variability in labeling and increased protein sequence coverage. This substantially enhanced the statistical power of our method for detecting differentially abundant proteins, providing an average of 13% more yeast proteins that reached statistical significance.

SIGNIFCANCE

We presented a novel TMTpro labeling method that overcomes the detrimental O-acylation and thus significantly improves the depth and quantitative precision for proteome analysis.

DrugMap: A quantitative pan-cancer analysis of cysteine ligandability

Cysteine-focused chemical proteomic platforms have accelerated the clinical development of covalent inhibitors for a wide range of targets in cancer. However, how different oncogenic contexts influence cysteine targeting remains unknown. To address this question, we have developed "DrugMap," an atlas of cysteine ligandability compiled across 416 cancer cell lines. We unexpectedly find that cysteine ligandability varies across cancer cell lines, and we attribute this to differences in cellular redox states, protein conformational changes, and genetic mutations. Leveraging these findings, we identify actionable cysteines in NF-κB1 and SOX10 and develop corresponding covalent ligands that block the activity of these transcription factors. We demonstrate that the NF-κB1 probe blocks DNA binding, whereas the SOX10 ligand increases SOX10-SOX10 interactions and disrupts melanoma transcriptional signaling. Our findings reveal heterogeneity in cysteine ligandability across cancers, pinpoint cell-intrinsic features driving cysteine targeting, and illustrate the use of covalent probes to disrupt oncogenic transcription-factor activity.

A complex interplay of intra- and extracellular factors regulates the outcome of fetal- and adult-derived MLL-rearranged leukemia

Infant and adult MLL1/KMT2A-rearranged (MLLr) leukemia represents a disease with a dismal prognosis. Here, we present a functional and proteomic characterization of in utero-initiated and adult-onset MLLr leukemia. We reveal that fetal MLL::ENL-expressing lymphomyeloid multipotent progenitors (LMPPs) are intrinsically programmed towards a lymphoid fate but give rise to myeloid leukemia in vivo, highlighting a complex interplay of intra- and extracellular factors in determining disease subtype. We characterize early proteomic events of MLL::ENL-mediated transformation in fetal and adult blood progenitors and reveal that whereas adult pre-leukemic cells are mainly characterized by retained myeloid features and downregulation of ribosomal and metabolic proteins, expression of MLL::ENL in fetal LMPPs leads to enrichment of translation-associated and histone deacetylases signaling proteins, and decreased expression of inflammation and myeloid differentiation proteins. Integrating the proteome of pre-leukemic cells with their secretome and the proteomic composition of the extracellular environment of normal progenitors highlights differential regulation of Igf2 bioavailability, as well as of VLA-4 dimer and its ligandome, upon initiation of fetal- and adult-origin leukemia, with implications for human MLLr leukemia cells' ability to communicate with their environment through granule proteins. Our study has uncovered opportunities for targeting ontogeny-specific proteomic vulnerabilities in in utero-initiated and adult-onset MLLr leukemia.

Quantification Quality Control Emerges as a Crucial Factor to Enhance Single-Cell Proteomics Data Analysis

Mass spectrometry (MS)-based single-cell proteomics (SCP) provides us the opportunity to unbiasedly explore biological variability within cells without the limitation of antibody availability. This field is rapidly developed with the main focuses on instrument advancement, sample preparation refinement, and signal boosting methods; however, the optimal data processing and analysis are rarely investigated which holds an arduous challenge because of the high proportion of missing values and batch effect. Here, we introduced a quantification quality control to intensify the identification of differentially expressed proteins (DEPs) by considering both within and across SCP data. Combining quantification quality control with isobaric matching between runs (IMBR) and PSM-level normalization, an additional 12% and 19% of proteins and peptides, with more than 90% of proteins/peptides containing valid values, were quantified. Clearly, quantification quality control was able to reduce quantification variations and q-values with the more apparent cell type separations. In addition, we found that PSM-level normalization performed similar to other protein-level normalizations but kept the original data profiles without the additional requirement of data manipulation. In proof of concept of our refined pipeline, six uniquely identified DEPs exhibiting varied fold-changes and playing critical roles for melanoma and monocyte functionalities were selected for validation using immunoblotting. Five out of six validated DEPs showed an identical trend with the SCP dataset, emphasizing the feasibility of combining the IMBR, cell quality control, and PSM-level normalization in SCP analysis, which is beneficial for future SCP studies.

Synthetic Knockout Protein Standard for Evaluating Interference in Tandem Mass Tag-Based Proteomics

Isobaric labeling is widely used for unbiased, proteome-wide studies, and it provides several advantages, such as fewer missing values among samples and higher quantitative precision. However, ion interference may lead to compressed or distorted observed ratios due to the coelution and coanalysis of peptides. Here, we introduced a synthetic KnockOut standard (sKO) for evaluating interference in tandem mass tags-based proteomics. sKO is made by mixing TMTpro-labeled tryptic peptides derived from four nonhuman proteins and a whole human proteome as background at different proportions. We showcased the utility of the sKO standard by exploring ion interference at different peptide concentrations (up to a 30-fold change in abundance) and using a variety of mass spectrometer data acquisition strategies. We also demonstrated that the sKO standard could provide valuable information for the rational design of acquisition strategies to achieve optimal data quality and discussed its potential applications for high-throughput proteomics workflows development.

Large-scale chemoproteomics expedites ligand discovery and predicts ligand behavior in cells

Chemical modulation of proteins enables a mechanistic understanding of biology and represents the foundation of most therapeutics. However, despite decades of research, 80% of the human proteome lacks functional ligands. Chemical proteomics has advanced fragment-based ligand discovery toward cellular systems, but throughput limitations have stymied the scalable identification of fragment-protein interactions. We report proteome-wide maps of protein-binding propensity for 407 structurally diverse small-molecule fragments. We verified that identified interactions can be advanced to active chemical probes of E3 ubiquitin ligases, transporters, and kinases. Integrating machine learning binary classifiers further enabled interpretable predictions of fragment behavior in cells. The resulting resource of fragment-protein interactions and predictive models will help to elucidate principles of molecular recognition and expedite ligand discovery efforts for hitherto undrugged proteins.

Neuroprotective effects of acteoside in a glaucoma mouse model by targeting Serta domain-containing protein 4

AIM

To explore the therapeutic effect and main molecular mechanisms of acteoside in a glaucoma model in DBA/2J mice.

METHODS

Proteomics was used to compare the differentially expressed proteins of C57 and DBA/2J mice. After acteoside administration in DBA/2J mice, anterior segment observation, intraocular pressure (IOP) monitoring, electrophysiology examination, and hematoxylin and eosin staining were used to analyze any potential effects. Immunohistochemistry (IHC) assays were used to verify the proteomics results. Furthermore, retinal ganglion cell 5 (RGC5) cell proliferation was assessed with cell counting kit-8 (CCK-8) assays. Serta domain-containing protein 4 (Sertad4) mRNA and protein expression levels were measured by qRT-PCR and Western blot analysis, respectively.

RESULTS

Proteomics analysis suggested that Sertad4 was the most significantly differentially expressed protein. Compared with the saline group, the acteoside treatment group showed decreased IOP, improved N1-P1 wave amplitudes, thicker retina, and larger numbers of cells in the ganglion cell layer (GCL). The IHC results showed that Sertad4 expression levels in DBA/2J mice treated with acteoside were significantly lower than in the saline group. Acteoside treatment could improve RGC5 cell survival and reduce the Sertad4 mRNA and protein expression levels after glutamate injury.

CONCLUSION

Sertad4 is differentially expressed in DBA/2J mice. Acteoside can protect RGCs from damage, possibly through the downregulation of Sertad4, and has a potential use in glaucoma treatment.

Lipid Isobaric Mass Tagging for Enhanced Relative Quantification of Unsaturated sn-Positional Isomers

Changes in the levels of lipid sn-positional isomers are associated with perturbation of the physiological environment within the biological system. Consequently, knowing the concentrations of these lipids holds significant importance for unraveling their involvement in disease diagnosis and pathological mechanisms. However, existing methods for lipid quantification often fall short in accuracy due to the structural diversity and isomeric forms of lipids. To address this challenge, we have developed an aziridine-based isobaric tag labeling strategy that allows (i) differentiation and (ii) enhanced relative quantification of lipid sn-positional isomers from distinct samples in a single run. The methodology enabled by aziridination, isobaric tag labeling, and lithiation has been applied to various phospholipids, enabling the determination of the sn-positions of fatty acyl chains and enhanced relative quantification. The analysis of Escherichia coli lipid extracts demonstrated the enhanced determination of the concentration ratios of lipid isomers by measuring the intensity ratios of mass reporters released from sn-positional diagnostic ions. Moreover, we applied the method to the analysis of human colon cancer plasma. Intriguingly, 17 PC lipid sn-positional isomers were identified and quantified simultaneously, and among them, 7 showed significant abundance changes in the colon cancer plasma, which can be used as potential plasma markers for diagnosis of human colon cancer.

Stability-based approaches in chemoproteomics

Target deconvolution can help understand how compounds exert therapeutic effects and can accelerate drug discovery by helping optimise safety and efficacy, revealing mechanisms of action, anticipate off-target effects and identifying opportunities for therapeutic expansion. Chemoproteomics, a combination of chemical biology with mass spectrometry has transformed target deconvolution. This review discusses modification-free chemoproteomic approaches that leverage the change in protein thermodynamics induced by small molecule ligand binding. Unlike modification-based methods relying on enriching specific protein targets, these approaches offer proteome-wide evaluations, driven by advancements in mass spectrometry sensitivity, increasing proteome coverage and quantitation methods. Advances in methods based on denaturation/precipitation by thermal or chemical denaturation, or by protease degradation are evaluated, emphasising the evolving landscape of chemoproteomics and its potential impact on future drug-development strategies.

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.

Functionalizing tandem mass tags for streamlining click-based quantitative chemoproteomics

Mapping the ligandability or potential druggability of all proteins in the human proteome is a central goal of mass spectrometry-based covalent chemoproteomics. Achieving this ambitious objective requires high throughput and high coverage sample preparation and liquid chromatography-tandem mass spectrometry analysis for hundreds to thousands of reactive compounds and chemical probes. Conducting chemoproteomic screens at this scale benefits from technical innovations that achieve increased sample throughput. Here we realize this vision by establishing the silane-based cleavable linkers for isotopically-labeled proteomics-tandem mass tag (sCIP-TMT) proteomic platform, which is distinguished by early sample pooling that increases sample preparation throughput. sCIP-TMT pairs a custom click-compatible sCIP capture reagent that is readily functionalized in high yield with commercially available TMT reagents. Synthesis and benchmarking of a 10-plex set of sCIP-TMT reveal a substantial decrease in sample preparation time together with high coverage and high accuracy quantification. By screening a focused set of four cysteine-reactive electrophiles, we demonstrate the utility of sCIP-TMT for chemoproteomic target hunting, identifying 789 total liganded cysteines. Distinguished by its compatibility with established enrichment and quantification protocols, we expect sCIP-TMT will readily translate to a wide range of covalent chemoproteomic applications.

A new era of cysteine proteomics - Technological advances in thiol biology

Cysteines are amenable to a diverse set of modifications that exhibit critical regulatory functions over the proteome and thereby control a wide range of cellular processes. Proteomic technologies have emerged as a powerful strategy to interrogate cysteine modifications across the proteome. Recent advancements in enrichment strategies, multiplexing capabilities and increased analytical sensitivity have enabled deeper quantitative cysteine profiling, capturing a substantial proportion of the cysteine proteome. This is complemented by a rapidly growing repertoire of analytical strategies illuminating the diverse landscape of cysteine modifications. Cysteine chemoproteomics technologies have evolved into a powerful strategy to facilitate the development of covalent drugs, opening unprecedented opportunities to target the extensive undrugged proteome. Herein we review recent technological and scientific advances that shape the cysteine proteomics field.

Accelerating multiplexed profiling of protein-ligand interactions: High-throughput plate-based reactive cysteine profiling with minimal input

Chemoproteomics has made significant progress in investigating small-molecule-protein interactions. However, the proteome-wide profiling of cysteine ligandability remains challenging to adapt for high-throughput applications, primarily due to a lack of platforms capable of achieving the desired depth using low input in 96- or 384-well plates. Here, we introduce a revamped, plate-based platform which enables routine interrogation of either ∼18,000 or ∼24,000 reactive cysteines based on starting amounts of 10 or 20 μg, respectively. This represents a 5-10X reduction in input and 2-3X improved coverage. We applied the platform to screen 192 electrophiles in the native HEK293T proteome, mapping the ligandability of 38,450 reactive cysteines from 8,274 human proteins. We further applied the platform to characterize new cellular targets of established drugs, uncovering that ARS-1620, a KRASG12C inhibitor, binds to and inhibits an off-target adenosine kinase ADK. The platform represents a major step forward to high-throughput proteome-wide evaluation of reactive cysteines.

Orthogonal IMiD-Degron Pairs Induce Selective Protein Degradation in Cells

Immunomodulatory imide drugs (IMiDs) including thalidomide, lenalidomide, and pomalidomide, can be used to induce degradation of a protein of interest that is fused to a short zinc finger (ZF) degron motif. These IMiDs, however, also induce degradation of endogenous neosubstrates, including IKZF1 and IKZF3. To improve degradation selectivity, we took a bump-and-hole approach to design and screen bumped IMiD analogs against 8380 ZF mutants. This yielded a bumped IMiD analog that induces efficient degradation of a mutant ZF degron, while not affecting other cellular proteins, including IKZF1 and IKZF3. In proof-of-concept studies, this system was applied to induce efficient degradation of TRIM28, a disease-relevant protein with no known small molecule binders. We anticipate that this system will make a valuable addition to the current arsenal of degron systems for use in target validation.

Parallel control of cold-triggered adipocyte thermogenesis by UCP1 and CKB

That uncoupling protein 1 (UCP1) is the sole mediator of adipocyte thermogenesis is a conventional viewpoint that has primarily been inferred from the attenuation of the thermogenic output of mice genetically lacking Ucp1 from birth (germline Ucp1-/-). However, germline Ucp1-/- mice harbor secondary changes within brown adipose tissue. To mitigate these potentially confounding ancillary changes, we constructed mice with inducible adipocyte-selective Ucp1 disruption. We find that, although germline Ucp1-/- mice succumb to cold-induced hypothermia with complete penetrance, most mice with the inducible deletion of Ucp1 maintain homeothermy in the cold. However, inducible adipocyte-selective co-deletion of Ucp1 and creatine kinase b (Ckb, an effector of UCP1-independent thermogenesis) exacerbates cold intolerance. Following UCP1 deletion or UCP1/CKB co-deletion from mature adipocytes, moderate cold exposure triggers the regeneration of mature brown adipocytes that coordinately restore UCP1 and CKB expression. Our findings suggest that thermogenic adipocytes utilize non-paralogous protein redundancy-through UCP1 and CKB-to promote cold-induced energy dissipation.

Monocarboxylate transporters facilitate succinate uptake into brown adipocytes

Uptake of circulating succinate by brown adipose tissue (BAT) and beige fat elevates whole-body energy expenditure, counteracts obesity and antagonizes systemic tissue inflammation in mice. The plasma membrane transporters that facilitate succinate uptake in these adipocytes remain undefined. Here we elucidate a mechanism underlying succinate import into BAT via monocarboxylate transporters (MCTs). We show that succinate transport is strongly dependent on the proportion that is present in the monocarboxylate form. MCTs facilitate monocarboxylate succinate uptake, which is promoted by alkalinization of the cytosol driven by adrenoreceptor stimulation. In brown adipocytes, we show that MCT1 primarily facilitates succinate import. In male mice, we show that both acute pharmacological inhibition of MCT1 and congenital depletion of MCT1 decrease succinate uptake into BAT and consequent catabolism. In sum, we define a mechanism of succinate uptake in BAT that underlies its protective activity in mouse models of metabolic disease.

A multiomics analysis-assisted deep learning model identifies a macrophage-oriented module as a potential therapeutic target in colorectal cancer

Colorectal cancer (CRC) is a common malignancy involving multiple cellular components. The CRC tumor microenvironment (TME) has been characterized well at single-cell resolution. However, a spatial interaction map of the CRC TME is still elusive. Here, we integrate multiomics analyses and establish a spatial interaction map to improve the prognosis, prediction, and therapeutic development for CRC. We construct a CRC immune module (CCIM) that comprises FOLR2+ macrophages, exhausted CD8+ T cells, tolerant CD8+ T cells, exhausted CD4+ T cells, and regulatory T cells. Multiplex immunohistochemistry is performed to depict the CCIM. Based on this, we utilize advanced deep learning technology to establish a spatial interaction map and predict chemotherapy response. CCIM-Net is constructed, which demonstrates good predictive performance for chemotherapy response in both the training and testing cohorts. Lastly, targeting FOLR2+ macrophage therapeutics is used to disrupt the immunosuppressive CCIM and enhance the chemotherapy response in vivo.

Glioblastoma extracellular vesicles modulate immune PD-L1 expression in accessory macrophages upon radiotherapy

Glioblastoma (GBM) is the most aggressive brain tumor, presenting major challenges due to limited treatment options. Standard care includes radiation therapy (RT) to curb tumor growth and alleviate symptoms, but its impact on GBM is limited. In this study, we investigated the effect of RT on immune suppression and whether extracellular vesicles (EVs) originating from GBM and taken up by the tumor microenvironment (TME) contribute to the induced therapeutic resistance. We observed that (1) ionizing radiation increases immune-suppressive markers on GBM cells, (2) macrophages exacerbate immune suppression in the TME by increasing PD-L1 in response to EVs derived from GBM cells which is further modulated by RT, and (3) RT increases CD206-positive macrophages which have the most potential in inducing a pro-oncogenic environment due to their increased uptake of tumor-derived EVs. In conclusion, RT affects GBM resistance by immuno-modulating EVs taken up by myeloid cells in the TME.

NAK-associated protein 1/NAP1 activates TBK1 to ensure accurate mitosis and cytokinesis

Subcellular location and activation of Tank Binding Kinase 1 (TBK1) govern precise progression through mitosis. Either loss of activated TBK1 or its sequestration from the centrosomes causes errors in mitosis and growth defects. Yet, what regulates its recruitment and activation on the centrosomes is unknown. We identified that NAK-associated protein 1 (NAP1) is essential for mitosis, binding to and activating TBK1, which both localize to centrosomes. Loss of NAP1 causes several mitotic and cytokinetic defects due to inactivation of TBK1. Our quantitative phosphoproteomics identified numerous TBK1 substrates that are not only confined to the centrosomes but are also associated with microtubules. Substrate motifs analysis indicates that TBK1 acts upstream of other essential cell cycle kinases like Aurora and PAK kinases. We also identified NAP1 as a TBK1 substrate phosphorylating NAP1 at S318 to promote its degradation by the ubiquitin proteasomal system. These data uncover an important distinct function for the NAP1-TBK1 complex during cell division.

High-Throughput Identification of Calcium Regulated Proteins Across Diverse Proteomes

Calcium ions play important roles in nearly every biological process, yet whole-proteome analysis of calcium effectors has been hindered by lack of high-throughput, unbiased, and quantitative methods to identify proteins-calcium engagement. To address this, we adapted protein thermostability assays in the budding yeast, human cells, and mouse mitochondria. Based on calcium-dependent thermostability, we identified 2884 putative calcium-regulated proteins across human, mouse, and yeast proteomes. These data revealed calcium engagement of novel signaling hubs and cellular processes, including metabolic enzymes and the spliceosome. Cross-species comparison of calcium-protein engagement and mutagenesis experiments identified residue-specific cation engagement, even within well-known EF-hand domains. Additionally, we found that the dienoyl-CoA reductase DECR1 binds calcium at physiologically-relevant concentrations with substrate-specific affinity, suggesting direct calcium regulation of mitochondrial fatty acid oxidation. These unbiased, proteomic analyses of calcium effectors establish a key resource to dissect cation engagement and its mechanistic effects across multiple species and diverse biological processes.

Phosphate starvation signaling increases mitochondrial membrane potential through respiration-independent mechanisms

Mitochondrial membrane potential directly powers many critical functions of mitochondria, including ATP production, mitochondrial protein import, and metabolite transport. Its loss is a cardinal feature of aging and mitochondrial diseases, and cells closely monitor membrane potential as an indicator of mitochondrial health. Given its central importance, it is logical that cells would modulate mitochondrial membrane potential in response to demand and environmental cues, but there has been little exploration of this question. We report that loss of the Sit4 protein phosphatase in yeast increases mitochondrial membrane potential, both by inducing the electron transport chain and the phosphate starvation response. Indeed, a similarly elevated mitochondrial membrane potential is also elicited simply by phosphate starvation or by abrogation of the Pho85-dependent phosphate sensing pathway. This enhanced membrane potential is primarily driven by an unexpected activity of the ADP/ATP carrier. We also demonstrate that this connection between phosphate limitation and enhancement of mitochondrial membrane potential is observed in primary and immortalized mammalian cells as well as in Drosophila. These data suggest that mitochondrial membrane potential is subject to environmental stimuli and intracellular signaling regulation and raise the possibility for therapeutic enhancement of mitochondrial function even in defective mitochondria.

Quantitative proteomics and applications in covalent ligand discovery

The development of multiplexing technologies for proteomics has enabled the quantification of proteins on a global scale across samples with high confidence. In the covalent ligand discovery pipeline, quantitative proteomics can be used to establish selectivity profiles and provide critical mechanistic insight into the action of lead compounds. Current multiplexing systems allow for the analysis of up to eighteen samples in a single run, allowing proteomic analyses to match the pace of high-throughput covalent ligand discovery workflows. This review discusses several quantitative proteomic techniques and their applications in the field of covalent ligand discovery.

Adapting an Isobaric Tag-Labeled Yeast Peptide Standard to Develop Targeted Proteomics Assays

Targeted proteomics strategies present a streamlined hypothesis-driven approach to analyze specific sets of pathways or disease related proteins. goDig is a quantitative, targeted tandem mass tag (TMT)-based assay that can measure the relative abundance differences for hundreds of proteins directly from unfractionated mixtures. Specific protein groups or entire pathways of up to 200 proteins can be selected for quantitative profiling, while leveraging sample multiplexing permits the simultaneous analysis of up to 18 samples. Despite these benefits, implementing goDig is not without challenges, as it requires access to an instrument application programming interface (iAPI), an elution order and spectral library, a web-based method builder, and dedicated companion software. In addition, the absence of an example test assay may dissuade researchers from testing or implementing goDig. Here, we repurpose the TKO11 standard─which is commercially available but may also be assembled in-lab─and establish it as a de facto test assay for goDig. We build a proteome-wide goDig yeast library, quantify protein expression across several gene ontology (GO) categories, and compare these results to a fully fractionated yeast gold-standard data set. Essentially, we provide a guide detailing the goDig-based quantification of TKO11, which can also be used as a template for user-defined assays in other species.

A comprehensive landscape of the zinc-regulated human proteome

Zinc is an essential micronutrient that regulates a wide range of physiological processes, principally through Zn 2+ binding to protein cysteine residues. Despite being critical for modulation of protein function, for the vast majority of the human proteome the cysteine sites subject to regulation by Zn 2+ binding remain undefined. Here we develop ZnCPT, a comprehensive and quantitative mapping of the zinc-regulated cysteine proteome. We define 4807 zinc-regulated protein cysteines, uncovering protein families across major domains of biology that are subject to either constitutive or inducible modification by zinc. ZnCPT enables systematic discovery of zinc-regulated structural, enzymatic, and allosteric functional domains. On this basis, we identify 52 cancer genetic dependencies subject to zinc regulation, and nominate malignancies sensitive to zinc-induced cytotoxicity. In doing so, we discover a mechanism of zinc regulation over Glutathione Reductase (GSR) that drives cell death in GSR-dependent lung cancers. We provide ZnCPT as a resource for understanding mechanisms of zinc regulation over protein function.

Current trends and future prospects of drug repositioning in gastrointestinal oncology

Gastrointestinal (GI) cancers comprise a significant number of cancer cases worldwide and contribute to a high percentage of cancer-related deaths. To improve survival rates of GI cancer patients, it is important to find and implement more effective therapeutic strategies with better prognoses and fewer side effects. The development of new drugs can be a lengthy and expensive process, often involving clinical trials that may fail in the early stages. One strategy to address these challenges is drug repurposing (DR). Drug repurposing is a developmental strategy that involves using existing drugs approved for other diseases and leveraging their safety and pharmacological data to explore their potential use in treating different diseases. In this paper, we outline the existing therapeutic strategies and challenges associated with GI cancers and explore DR as a promising alternative approach. We have presented an extensive review of different DR methodologies, research efforts and examples of repurposed drugs within various GI cancer types, such as colorectal, pancreatic and liver cancers. Our aim is to provide a comprehensive overview of employing the DR approach in GI cancers to inform future research endeavors and clinical trials in this field.

Proteomic analysis reveals activation of platelet- and fibrosis-related pathways in hearts of ApoE-/- mice exposed to diesel exhaust particles

Air pollution is an environmental risk factor linked to multiple human diseases including cardiovascular diseases (CVDs). While particulate matter (PM) emitted by diesel exhaust damages multiple organ systems, heart disease is one of the most severe pathologies affected by PM. However, the in vivo effects of diesel exhaust particles (DEP) on the heart and the molecular mechanisms of DEP-induced heart dysfunction have not been investigated. In the current study, we attempted to identify the proteomic signatures of heart fibrosis caused by diesel exhaust particles (DEP) in CVDs-prone apolipoprotein E knockout (ApoE-/-) mice model using tandem mass tag (TMT)-based quantitative proteomic analysis. DEP exposure induced mild heart fibrosis in ApoE-/- mice compared with severe heart fibrosis in ApoE-/- mice that were treated with CVDs-inducing peptide, angiotensin II. TMT-based quantitative proteomic analysis of heart tissues between PBS- and DEP-treated ApoE-/- mice revealed significant upregulation of proteins associated with platelet activation and TGFβ-dependent pathways. Our data suggest that DEP exposure could induce heart fibrosis, potentially via platelet-related pathways and TGFβ induction, causing cardiac fibrosis and dysfunction.