High-pH reversed-phase chromatography with fraction concatenation for 2D proteomic analysis

Inhibition of NLRP3 enhances pro-apoptotic effects of FLT3 inhibition in AML

FLT3 mutations occur in approximately 25% of all acute myeloid leukemia (AML) patients. While several FLT3 inhibitors have received FDA approval, their use is currently limited to combination therapies with chemotherapy, as resistance occurs, and efficacy decreases when the inhibitors are used alone. Given the highly heterogeneous nature of AML, there is an urgent need for novel targeted therapies that address the disease from multiple angles. Recent research has identified the NLRP3 inflammasome as a potential new driver in AML. Here, we investigated the efficacy of different NLRP3 inhibitors in targeting AML cells in vitro. Our findings reveal that NLRP3 inhibition induces cell cycle arrest as well as signs of senescence in multiple AML cell lines. In contrast, NLRP3 inhibition selectively induced apoptosis in FLT3 mutant AML cell lines, but not in FLT3 wild-type AML cells. Moreover, we show that NLRP3 inhibition impairs FLT3 signaling by reducing both FLT3 expression as well as downstream signaling in FLT3 mutant cells. A database analysis revealed a strong positive correlation between FLT3 and NLRP3 in cancer, which was particularly evident in AML patients. Strikingly, the simultaneous inhibition of NLRP3 and FLT3 markedly enhanced apoptosis in FLT3-ITD mutant AML cells, but not in FLT3 wild-type cells. In summary, this study reveals a promising combined therapeutic strategy specifically targeting NLRP3/FLT3-ITD positive AML blasts in vitro, highlighting a potential new avenue for AML treatment.

Application of Proteomic Methods in Oomycete Biology

The biochemical makeup of any organism provides insight into key factors regarding its biological functions. These factors can be explored using proteomics, which allows us to obtain a snapshot of the protein content and abundance in an organism, cell type or sub-cellular compartment. Here, we describe proteomic methodologies that can be used to dissect the biochemical mechanism of phytopathogenicity in oomycetes. These methodologies include protein extraction, purification, subsequent processing, mass spectrometry analysis, and qualitative and quantitative data processing of oomycete proteomes for comparative studies. Additionally, the use of mass spectra to assist in gene validation and modelling in unfinished oomycete genomes is also described.

Challenges of MS-based small extracellular vesicles proteomics

Proteomic profiling of small extracellular vesicles (sEV) is a powerful tool for discovering biomarkers of various diseases. This process most often assisted by mass spectrometry (MS) usually lacks standardization and recognition of challenges which may lead to unreliable results. General recommendations for sEV MS analyses have been briefly given in the MISEV2023 guidelines. The present work goes into detail for every step of sEV protein profiling with an overview of factors influencing such analyses. This includes reporting and defining the sEV source and vesicle isolation, protein solubilization and digestion, 'offline' and 'online' sample complexity reduction, the analysis type itself, and subsequent data analysis. Every stage in this process affects the others, which could result in different outcomes. Although characterization and comparisons of different sEV isolation methods are known and accessible and MS-based profiling details are provided for cell or tissue samples, no consensus work has been ever published to describe the whole process of sEV proteomic analysis. Reliable results can be obtained from sEV profiling provided that the analysis is well planned, prepared for, and backed by pilot studies or appropriate research.

TermineR: Extracting information on endogenous proteolytic processing from shotgun proteomics data

State-of-the-art mass spectrometers combined with modern bioinformatics algorithms for peptide-to-spectrum matching (PSM) with robust statistical scoring allow for more variable features (i.e., post-translational modifications) being reliably identified from (tandem-) mass spectrometry data, often without the need for biochemical enrichment. Semi-specific proteome searches, that enforce a theoretical enzymatic digestion to solely the N- or C-terminal end, allow to identify of native protein termini or those arising from endogenous proteolytic activity (also referred to as "neo-N-termini" analysis or "N-terminomics"). Nevertheless, deriving biological meaning from these search outputs can be challenging in terms of data mining and analysis. Thus, we introduce TermineR, a data analysis approach for the (1) annotation of peptides according to their enzymatic cleavage specificity and known protein processing features, (2) differential abundance and enrichment analysis of N-terminal sequence patterns, and (3) visualization of neo-N-termini location. We illustrate the use of TermineR by applying it to tandem mass tag (TMT)-based proteomics data of a mouse model of polycystic kidney disease, and assess the semi-specific searches for biological interpretation of cleavage events and the variable contribution of proteolytic products to general protein abundance. The TermineR approach and example data are available as an R package at https://github.com/MiguelCos/TermineR.

Metabolic labeling based methylome profiling enables functional dissection of histidine methylation in C3H1 zinc fingers

Protein methylation is a functionally important post-translational modification that occurs on diverse amino acid residues. The current proteomics approaches are inefficient to discover the methylation on residues other than Arg and Lys, which hinders the deep understanding of the functional role of rare protein methylation. Herein, we present a methyl-specific metabolic labeling approach for global methylome mapping, which enable the acquisition of methylome dataset covering diverse methylation types. Interestingly, of the identified methylation events, His methylation is found to be preferably occurred in C3H1 zinc fingers (ZFs). These His methylation events are determined to be Nπ specific and catalyzed by CARNMT1. The His methylation is found to stabilize the structure of ZFs. U2AF1 is used as a proof-of-concept to highlight the functional importance of His methylation in ZFs in RNA binding and RNA metabolism. The results of this study enable novel understanding of how protein methylation regulates cellular processes.

Comprehensive Overview of Bottom-Up Proteomics Using Mass Spectrometry

Proteomics is the large scale study of protein structure and function from biological systems through protein identification and quantification. "Shotgun proteomics" or "bottom-up proteomics" is the prevailing strategy, in which proteins are hydrolyzed into peptides that are analyzed by mass spectrometry. Proteomics studies can be applied to diverse studies ranging from simple protein identification to studies of proteoforms, protein-protein interactions, protein structural alterations, absolute and relative protein quantification, post-translational modifications, and protein stability. To enable this range of different experiments, there are diverse strategies for proteome analysis. The nuances of how proteomic workflows differ may be challenging to understand for new practitioners. Here, we provide a comprehensive overview of different proteomics methods. We cover from biochemistry basics and protein extraction to biological interpretation and orthogonal validation. We expect this Review will serve as a handbook for researchers who are new to the field of bottom-up proteomics.

An optimized protocol for pig intestinal mucosa proteomics

The overall well-being of organisms is widely recognized to be closely intertwined with their intestinal health. The intestinal mucosal layer plays a pivotal role in ensuring the proper functioning of the intestine, a fact observed not only in humans but also in animals like pigs. Any alterations to the mucosal layer of a pig's intestine can potentially disrupt its functionality, thereby impacting the animal's health and productivity. Mass spectrometry-based proteome analysis serves as a valuable tool in investigating the intricate dynamics of the proteome within the intestinal mucosa. Such studies hold promise in uncovering causal relationships between mucosal changes and overall health outcomes in pigs. It is anticipated that insights gathered from proteome studies will inform future strategies aimed at enhancing the health and productivity of pigs. However, the research field lacks a standardized and detailed method to extract proteins from pig intestinal mucosa and prepare proteins for proteome analysis. In the present study, we evaluated three alternative S-Trap-based protocols for analyzing ileal mucosal scrapings from pigs. Samples were either freeze-dried and treated as solid samples or ground in liquid nitrogen, categorized as either solid or liquid samples. In our analysis, a total of 2840 proteins were identified across all samples. Through statistical analysis and gene ontology examinations, we investigated potential differences between the three approaches. Even though our findings revealed no significant differences among the three methods, we propose the use of the protocol wherein samples are freeze-dried and treated as solid for protein extraction. This protocol stands out as the most convenient and practical option, offering ease of use and ensuring consistent and reliable results. By establishing a standardized approach, we aim to advance research efforts in understanding pig intestinal health. SIGNIFICANCE: The development of an optimized protocol for protein extraction of intestinal mucosal scrapings in pigs addresses a gap in the field and enhances future research on pig intestinal health. By use of the protocol and mass spectrometry-based proteome analysis, valuable insights for improving the health and productivity of pigs can be presented. Studying the complex dynamics of the proteome within the intestinal mucosa, potentially identifying links between mucosal changes and health outcomes, provides us with information about the critical connection between intestinal health and the overall well-being and productivity of pigs. By creating a standardized approach, consistent, reliable, and reproducible results can be obtained for this type of research.

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.

Enhancing Proteome Coverage by Using Strong Anion-Exchange in Tandem with Basic-pH Reversed-Phase Chromatography for Sample Multiplexing-Based Proteomics

Sample multiplexing-based proteomic strategies rely on fractionation to improve proteome coverage. Tandem mass tag (TMT) experiments, for example, can currently accommodate up to 18 samples with proteins spanning several orders of magnitude, thus necessitating fractionation to achieve reasonable proteome coverage. Here, we present a simple yet effective peptide fractionation strategy that partitions a pooled TMT sample with a two-step elution using a strong anion-exchange (SAX) spin column prior to gradient-based basic pH reversed-phase (BPRP) fractionation. We highlight our strategy with a TMTpro18-plex experiment using nine diverse human cell lines in biological duplicate. We collected three data sets, one using only BPRP fractionation and two others of each SAX-partition followed by BPRP. The three data sets quantified a similar number of proteins and peptides, and the data highlight noticeable differences in the distribution of peptide charge and isoelectric point between the SAX partitions. The combined SAX partition data set contributed 10% more proteins and 20% more unique peptides that were not quantified by BPRP fractionation alone. In addition to this improved fractionation strategy, we provide an online resource of relative abundance profiles for over 11,000 proteins across the nine human cell lines, as well as two additional experiments using ovarian and pancreatic cancer cell lines.

A Carrier-Based Quantitative Proteomics Method Applied to Biomarker Discovery in Pericardial Fluid

Data-dependent liquid chromatography tandem mass spectrometry is challenged by the large concentration range of proteins in plasma and related fluids. We adapted the SCoPE method from single-cell proteomics to pericardial fluid, where a myocardial tissue carrier was used to aid protein quantification. The carrier proteome and patient samples were labeled with distinct isobaric labels, which allowed separate quantification. Undepleted pericardial fluid from patients with type 2 diabetes mellitus and/or heart failure undergoing heart surgery was analyzed with either a traditional liquid chromatography tandem mass spectrometry method or with the carrier proteome. In total, 1398 proteins were quantified with a carrier, compared to 265 without, and a higher proportion of these proteins were of myocardial origin. The number of differentially expressed proteins also increased nearly four-fold. For patients with both heart failure and type 2 diabetes mellitus, pathway analysis of upregulated proteins demonstrated the enrichment of immune activation, blood coagulation, and stress pathways. Overall, our work demonstrates the applicability of a carrier for enhanced protein quantification in challenging biological matrices such as pericardial fluid, with potential applications for biomarker discovery. Mass spectrometry data are available via ProteomeXchange with identifier PXD053450.

High-throughput proteomics-guided biomarker discovery of hepatocellular carcinoma

Liver cancer stands as the fifth leading cause of cancer-related deaths globally. Hepatocellular carcinoma (HCC) comprises approximately 85%-90% of all primary liver malignancies. However, only 20-30% of HCC patients qualify for curative therapy, primarily due to the absence of reliable tools for early detection and prognosis of HCC. This underscores the critical need for molecular biomarkers for HCC management. Since proteins reflect disease status directly, proteomics has been utilized in biomarker developments for HCC. In particular, proteomics coupled with liquid chromatography-mass spectrometer (LC-MS) methods facilitate the process of discovering biomarker candidates for diagnosis, prognosis, and therapeutic strategies. In this work, we investigated LC-MS-based proteomics methods through recent reference reviews, with a particular focus on sample preparation and LC-MS methods appropriate for the discovery of HCC biomarkers and their clinical applications. We classified proteomics studies of HCC according to sample types, and we examined the coverage of protein biomarker candidates based on LC-MS methods in relation to study scales and goals. Comprehensively, we proposed protein biomarker candidates categorized by sample types and biomarker types for appropriate clinical use. In this review, we summarized recent LC-MS-based proteomics studies on HCC and proposed potential protein biomarkers. Our findings are expected to expand the understanding of HCC pathogenesis and enhance the efficiency of HCC diagnosis and prognosis, thereby contributing to improved patient outcomes.

Fit for Purpose Approach To Evaluate Detection of Amino Acid Substitutions in Shotgun Proteomics

Amino acid substitutions (AASs) alter proteins from their genome-expected sequences. Accumulation of substitutions in proteins underlies numerous diseases and antibiotic mechanisms. Accurate global detection of AASs and their frequencies is crucial for understanding these mechanisms. Shotgun proteomics provides an untargeted method for measuring AASs but introduces biases when extrapolating from the genome to identify AASs. To characterize these biases, we created a "ground-truth" approach using the similarities betweenEscherichia coli and Salmonella typhimurium to model the complexity of AAS detection. Shotgun proteomics on mixed lysates generated libraries representing ∼100,000 peptide-spectra and 4161 peptide sequences with a single AAS and defined stoichiometry. Identifying S. typhimurium peptide-spectra with only the E. coli genome resulted in 64.1% correctly identified library peptides. Specific AASs exhibit variable identification efficiencies. There was no inherent bias from the stoichiometry of the substitutions. Short peptides and AASs localized near peptide termini had poor identification efficiency. We identify a new class of "scissor substitutions" that gain or lose protease cleavage sites. Scissor substitutions also had poor identification efficiency. This ground-truth AAS library reveals various sources of bias, which will guide the application of shotgun proteomics to validate AAS hypotheses.

Early Chronic Fluoxetine Treatment of Ts65Dn Mice Rescues Synaptic Vesicular Deficits and Prevents Aberrant Proteomic Alterations

Down syndrome (DS) is the most common form of inherited intellectual disability caused by trisomy of chromosome 21, presenting with intellectual impairment, craniofacial abnormalities, cardiac defects, and gastrointestinal disorders. The Ts65Dn mouse model replicates many abnormalities of DS. We hypothesized that investigation of the cerebral cortex of fluoxetine-treated trisomic mice may provide proteomic signatures that identify therapeutic targets for DS. Subcellular fractionation of synaptosomes from cerebral cortices of age- and brain-area-matched samples from fluoxetine-treated vs. water-treated trisomic and euploid male mice were subjected to HPLC-tandem mass spectrometry. Analysis of the data revealed enrichment of trisomic risk genes that participate in regulation of synaptic vesicular traffic, pre-synaptic and post-synaptic development, and mitochondrial energy pathways during early brain development. Proteomic analysis of trisomic synaptic fractions revealed significant downregulation of proteins involved in synaptic vesicular traffic, including vesicular endocytosis (CLTA, CLTB, CLTC), synaptic assembly and maturation (EXOC1, EXOC3, EXOC8), anterograde axonal transport (EXOC1), neurotransmitter transport to PSD (SACM1L), endosomal-lysosomal acidification (ROGDI, DMXL2), and synaptic signaling (NRXN1, HIP1, ITSN1, YWHAG). Additionally, trisomic proteomes revealed upregulation of several trafficking proteins, involved in vesicular exocytosis (Rab5B), synapse elimination (UBE3A), scission of endocytosis (DBN1), transport of ER in dendritic spines (MYO5A), presynaptic activity-dependent bulk endocytosis (FMR1), and NMDA receptor activity (GRIN2A). Chronic fluoxetine treatment of Ts65Dn mice rescued synaptic vesicular abnormalities and prevented abnormal proteomic changes in adult Ts65Dn mice, pointing to therapeutic targets for potential treatment of DS.

A compendium of multi-omics data illuminating host responses to lethal human virus infections

Human infections caused by viral pathogens trigger a complex gamut of host responses that limit disease, resolve infection, generate immunity, and contribute to severe disease or death. Here, we present experimental methods and multi-omics data capture approaches representing the global host response to infection generated from 45 individual experiments involving human viruses from the Orthomyxoviridae, Filoviridae, Flaviviridae, and Coronaviridae families. Analogous experimental designs were implemented across human or mouse host model systems, longitudinal samples were collected over defined time courses, and global multi-omics data (transcriptomics, proteomics, metabolomics, and lipidomics) were acquired by microarray, RNA sequencing, or mass spectrometry analyses. For comparison, we have included transcriptomics datasets from cells treated with type I and type II human interferon. Raw multi-omics data and metadata were deposited in public repositories, and we provide a central location linking the raw data with experimental metadata and ready-to-use, quality-controlled, statistically processed multi-omics datasets not previously available in any public repository. This compendium of infection-induced host response data for reuse will be useful for those endeavouring to understand viral disease pathophysiology and network biology.

Schistosoma mansoni infection induces hepatic metallothionein and S100 protein expression alongside metabolic dysfunction in hamsters

Schistosomiasis, a widespread neglected tropical disease, presents a complex and multifaceted clinical-pathological profile. Using hamsters as final hosts, we dissected molecular events following Schistosoma mansoni infection in the liver-the organ most severely affected in schistosomiasis patients. Employing tandem mass tag-based proteomics, we studied alterations in the liver proteins in response to various infection modes and genders. We examined livers from female and male hamsters that were: noninfected (control), infected with either unisexual S. mansoni cercariae (single-sex) or both sexes (bisex). The infection induced up-regulation of proteins associated with immune response, cytoskeletal reorganization, and apoptotic signaling. Notably, S. mansoni egg deposition led to the down-regulation of liver factors linked to energy supply and metabolic processes. Gender-specific responses were observed, with male hamsters showing higher susceptibility, supported by more differentially expressed proteins than found in females. Of note, metallothionein-2 and S100a6 proteins exhibited substantial up-regulation in livers of both genders, suggesting their pivotal roles in the liver's injury response. Immunohistochemistry and real-time-qPCR confirmed strong up-regulation of metallothionein-2 expression in the cytoplasm and nucleus upon the infection. Similar findings were seen for S100a6, which localized around granulomas and portal tracts. We also observed perturbations in metabolic pathways, including down-regulation of enzymes involved in xenobiotic biotransformation, cellular energy metabolism, and lipid modulation. Furthermore, lipidomic analyses through liquid chromatography-tandem mass spectrometry and matrix-assisted laser desorption/ionization mass spectrometry imaging identified extensive alterations, notably in cardiolipin and triacylglycerols, suggesting specific roles of lipids during pathogenesis. These findings provide unprecedented insights into the hepatic response to S. mansoni infection, shedding light on the complexity of liver pathology in this disease.

Comparing and integrating TMT-SPS-MS3 and label-free quantitative approaches for proteomics scrutiny in recalcitrant Mango (Mangifera indica L.) peel tissue during postharvest period

Despite substantial advances in the use of proteomic technologies, their widespread application in fruit tissues of non-model and recalcitrant species remains limited. This hampers the understanding of critical molecular events during the postharvest period of fleshy tropical fruits. Therefore, we evaluated label-free quantitation (LFQ) and TMT-SPS-MS3 (TMT) approaches to analyse changes in the protein profile of mango peels during postharvest period. We compared two extraction methods (phenol and chloroform/methanol) and two peptide fractionation schemes (SCX and HPRP). We accurately identified 3065 proteins, of which, 1492 were differentially accumulated over at 6 days after harvesting (DAH). Both LFQ and TMT approaches share 210 differential proteins including cell wall proteins associated with fruit softening, as well as aroma and flavour-related proteins, which were increased during postharvest period. The phenolic protein extraction and the high-pH reverse-phase peptide fractionation was the most effective pipeline for relative quantification. Nevertheless, the information provided by the other tested strategies was significantly complementary. Besides, LFQ spectra allowed us to track down intact N-glycopeptides corroborating N-glycosylations on the surface of a desiccation-related protein. This work represents the largest proteomic comparison of mango peels during postharvest period made so far, shedding light on the molecular foundation of edible fruit during ripening.

Comparative Hippocampal Proteome and Phosphoproteome in a Niemann-Pick, Type C1 Mouse Model Reveal Insights into Disease Mechanisms

Niemann-Pick disease, type C (NPC) is a neurodegenerative, lysosomal storage disorder in individuals carrying two mutated copies of either the NPC1 or NPC2 gene. Consequently, impaired cholesterol recycling and an array of downstream events occur. Interestingly, in NPC, the hippocampus displays lysosomal lipid storage but does not succumb to progressive neurodegeneration as significantly as other brain regions. Since defining the neurodegeneration mechanisms in this disease is still an active area of research, we use mass spectrometry to analyze the overall proteome and phosphorylation pattern changes in the hippocampal region of a murine model of NPC. Using 3 week old mice representing an early disease time point, we observed changes in the expression of 47 proteins, many of which are consistent with the previous literature. New to this study, changes in members of the SNARE complex, including STX7, VTI1B, and VAMP7, were identified. Furthermore, we identified that phosphorylation of T286 on CaMKIIα and S1303 on NR2B increased in mutant animals, even at the late stage of the disease. These phosphosites are crucial to learning and memory and can trigger neuronal death by altering protein-protein interactions.

RNA-dependent proteome solubility maintenance in Escherichia coli lysates analysed by quantitative mass spectrometry: Proteomic characterization in terms of isoelectric point, structural disorder, functional hub, and chaperone network

Protein aggregation, a consequence of misfolding and impaired proteostasis, can lead to cellular malfunctions such as various proteinopathies. The mechanisms protecting proteins from aggregation in complex cellular environments have long been investigated, often from a protein-centric viewpoint. However, our study provides insights into a crucial, yet overlooked actor: RNA. We found that depleting RNAs from Escherichia coli lysates induces global protein aggregation. Our quantitative mass spectrometry analysis identified over 900 statistically significant proteins from the Escherichia coli proteome whose solubility depends on RNAs. Proteome-wide characterization showed that the RNA dependency is particularly enriched among acidic proteins, intrinsically disordered proteins, and structural hub proteins. Moreover, we observed distinct differences in RNA-binding mode and Gene Ontology categories between RNA-dependent acidic and basic proteins. Notably, the solubility of key molecular chaperones [Trigger factor, DnaJ, and GroES] is largely dependent on RNAs, suggesting a yet-to-be-explored hierarchical relationship between RNA-based chaperone (termed as chaperna) and protein-based chaperones, both of which constitute the whole chaperone network. These findings provide new insights into the RNA-centric role in maintaining healthy proteome solubility in vivo, where proteins associate with a variety of RNAs, either stably or transiently.

Mitochondrial electron transport chain, ceramide, and coenzyme Q are linked in a pathway that drives insulin resistance in skeletal muscle

Insulin resistance (IR) is a complex metabolic disorder that underlies several human diseases, including type 2 diabetes and cardiovascular disease. Despite extensive research, the precise mechanisms underlying IR development remain poorly understood. Previously we showed that deficiency of coenzyme Q (CoQ) is necessary and sufficient for IR in adipocytes and skeletal muscle (Fazakerley et al., 2018). Here, we provide new insights into the mechanistic connections between cellular alterations associated with IR, including increased ceramides, CoQ deficiency, mitochondrial dysfunction, and oxidative stress. We demonstrate that elevated levels of ceramide in the mitochondria of skeletal muscle cells result in CoQ depletion and loss of mitochondrial respiratory chain components, leading to mitochondrial dysfunction and IR. Further, decreasing mitochondrial ceramide levels in vitro and in animal models (mice, C57BL/6J) (under chow and high-fat diet) increased CoQ levels and was protective against IR. CoQ supplementation also rescued ceramide-associated IR. Examination of the mitochondrial proteome from human muscle biopsies revealed a strong correlation between the respirasome system and mitochondrial ceramide as key determinants of insulin sensitivity. Our findings highlight the mitochondrial ceramide-CoQ-respiratory chain nexus as a potential foundation of an IR pathway that may also play a critical role in other conditions associated with ceramide accumulation and mitochondrial dysfunction, such as heart failure, cancer, and aging. These insights may have important clinical implications for the development of novel therapeutic strategies for the treatment of IR and related metabolic disorders.

A micro-flow, high-pH, reversed-phase peptide fractionation and collection system for targeted and in-depth proteomics of low-abundance proteins in limiting samples

We present a method and a simple system for high-pH RP-LC peptide fractionation of small sample amounts (30-60 µg), at micro-flow rates with micro-liter fraction collection using ammonium bicarbonate as an optimized buffer for system stability and robustness. The method is applicable to targeted mass spectrometry approaches and to in-depth proteomic studies where the amount of sample is limited. Using targeted proteomics with peptide standards, we present the method's analytical parameters, and potential in increasing the detection of low-abundance proteins that are difficult to quantify with direct targeted or global LC-MS analyses. This fractionation system increased peptide signals by up to 18-fold, while maintaining high quantitative precision, with high fractionation reproducibility across varied sample sets. In real applications, it increased the detection of targeted endogenous peptides by two-fold in a 25 cell-cycle-control protein panel, and in-depth MS analyses of nuclear extracts, it allowed the detection of up to 8,896 proteins with 138,417 peptides in 24-concatenated fractions compared to 3,344 proteins with 23,093 peptides without fractionation. In a relevant biological problem of CDK4/6-inhibitors and breast cancer, the method reproduced known information and revealed novel insights, highlighting that it can be successfully applied in studies involving low-abundance proteins and limited samples. •Tested nine high-pH buffer/solvent systems to obtain a robust, effective, and reproducible micro-flow fractionation method which was devoid of commonly encountered LC clogging/pressure issues after months of use.•Peptide enrichment method to improve detection and quantitation of low-abundance proteins in targeted and in-depth proteomic studies.•Can be applied to diverse protein samples where the available amount is limited.

Comprehensive Overview of Bottom-Up Proteomics using Mass Spectrometry

Proteomics is the large scale study of protein structure and function from biological systems through protein identification and quantification. "Shotgun proteomics" or "bottom-up proteomics" is the prevailing strategy, in which proteins are hydrolyzed into peptides that are analyzed by mass spectrometry. Proteomics studies can be applied to diverse studies ranging from simple protein identification to studies of proteoforms, protein-protein interactions, protein structural alterations, absolute and relative protein quantification, post-translational modifications, and protein stability. To enable this range of different experiments, there are diverse strategies for proteome analysis. The nuances of how proteomic workflows differ may be challenging to understand for new practitioners. Here, we provide a comprehensive overview of different proteomics methods to aid the novice and experienced researcher. We cover from biochemistry basics and protein extraction to biological interpretation and orthogonal validation. We expect this work to serve as a basic resource for new practitioners in the field of shotgun or bottom-up proteomics.

Identification of Plasma Biomarkers from Rheumatoid Arthritis Patients Using an Optimized Sequential Window Acquisition of All THeoretical Mass Spectra (SWATH) Proteomics Workflow

Rheumatoid arthritis (RA) is a systemic autoimmune and inflammatory disease. Plasma biomarkers are critical for understanding disease mechanisms, treatment effects, and diagnosis. Mass spectrometry-based proteomics is a powerful tool for unbiased biomarker discovery. However, plasma proteomics is significantly hampered by signal interference from high-abundance proteins, low overall protein coverage, and high levels of missing data from data-dependent acquisition (DDA). To achieve quantitative proteomics analysis for plasma samples with a balance of throughput, performance, and cost, we developed a workflow incorporating plate-based high abundance protein depletion and sample preparation, comprehensive peptide spectral library building, and data-independent acquisition (DIA) SWATH mass spectrometry-based methodology. In this study, we analyzed plasma samples from both RA patients and healthy donors. The results showed that the new workflow performance exceeded that of the current state-of-the-art depletion-based plasma proteomic platforms in terms of both data quality and proteome coverage. Proteins from biological processes related to the activation of systemic inflammation, suppression of platelet function, and loss of muscle mass were enriched and differentially expressed in RA. Some plasma proteins, particularly acute-phase reactant proteins, showed great power to distinguish between RA patients and healthy donors. Moreover, protein isoforms in the plasma were also analyzed, providing even deeper proteome coverage. This workflow can serve as a basis for further application in discovering plasma biomarkers of other diseases.

Deep Proteome of the Developing Chick Midbrain

The epithelial-to-mesenchymal transition (EMT) and migration of cranial neural crest cells within the midbrain are critical processes that permit proper craniofacial patterning in the early embryo. Disruptions in these processes not only impair development but also lead to various diseases, underscoring the need for their detailed understanding at the molecular level. The chick embryo has served historically as an excellent model for human embryonic development, including cranial neural crest cell EMT and migration. While these developmental events have been characterized transcriptionally, studies at the protein level have not been undertaken to date. Here, we applied mass spectrometry (MS)-based proteomics to establish a deep proteomics profile of the chick midbrain region during early embryonic development. Our proteomics method combines optimal lysis conditions, offline fractionation, separation on a nanopatterned stationary phase (μPAC) using nanoflow liquid chromatography, and detection using quadrupole-ion trap-Orbitrap tribrid high-resolution tandem MS. Identification of >5900 proteins and >450 phosphoproteins in this study marks the deepest coverage of the chick midbrain proteome to date. These proteins have known roles in pathways related to neural crest cell EMT and migration such as signaling, proteolysis/extracellular matrix remodeling, and transcriptional regulation. This study offers valuable insight into important developmental processes occurring in the midbrain region and demonstrates the utility of proteomics for characterization of tissue microenvironments during chick embryogenesis.

Caveolin-1 Autonomously Regulates Hippocampal Neurogenesis Via Mitochondrial Dynamics

The mechanisms underlying adult hippocampal neurogenesis (AHN) are not fully understood. AHN plays instrumental roles in learning and memory. Understanding the signals that regulate AHN has implications for brain function and therapy. Here we show that Caveolin-1 (Cav-1), a protein that is highly enriched in endothelial cells and the principal component of caveolae, autonomously regulates AHN. Conditional deletion of Cav-1 in adult neural progenitor cells (nestin +) led to increased neurogenesis and enhanced performance of mice in contextual discrimination. Proteomic analysis revealed that Cav-1 plays a role in mitochondrial pathways in neural progenitor cells. Importantly, Cav-1 was localized to the mitochondria in neural progenitor cells and modulated mitochondrial fission-fusion, a critical process in neurogenesis. These results suggest that Cav-1 is a novel regulator of AHN and underscore the impact of AHN on cognition.

Mitochondrial electron transport chain, ceramide and Coenzyme Q are linked in a pathway that drives insulin resistance in skeletal muscle

Insulin resistance (IR) is a complex metabolic disorder that underlies several human diseases, including type 2 diabetes and cardiovascular disease. Despite extensive research, the precise mechanisms underlying IR development remain poorly understood. Here, we provide new insights into the mechanistic connections between cellular alterations associated with IR, including increased ceramides, deficiency of coenzyme Q (CoQ), mitochondrial dysfunction, and oxidative stress. We demonstrate that elevated levels of ceramide in the mitochondria of skeletal muscle cells results in CoQ depletion and loss of mitochondrial respiratory chain components, leading to mitochondrial dysfunction and IR. Further, decreasing mitochondrial ceramide levels in vitro and in animal models (under chow and high fat diet) increased CoQ levels and was protective against IR. CoQ supplementation also rescued ceramide-associated IR. Examination of the mitochondrial proteome from human muscle biopsies revealed a strong correlation between the respirasome system and mitochondrial ceramide as key determinants of insulin sensitivity. Our findings highlight the mitochondrial Ceramide-CoQ-respiratory chain nexus as a potential foundation of an IR pathway that may also play a critical role in other conditions associated with ceramide accumulation and mitochondrial dysfunction, such as heart failure, cancer, and aging. These insights may have important clinical implications for the development of novel therapeutic strategies for the treatment of IR and related metabolic disorders.

In-depth proteome analysis of brain tissue from Ewsr1 knockout mouse by multiplexed isobaric tandem mass tag labeling

EWS RNA binding protein 1 (EWSR1) is a multifunctional protein whose epigenetic signatures contribute to the pathogenesis of various human diseases, such as neurodegenerative disorders, skin development, and tumorigenic processes. However, the specific cellular functions and physiological characteristics of EWSR1 remain unclear. In this study, we used quantitative mass spectrometry-based proteomics with tandem mass tag labeling to investigate the global proteome changes in brain tissue in Ewsr1 knockout and wild-type mice. From 9115 identified proteins, we selected 118 differentially expressed proteins, which is common to three quantitative data processing strategies including only protein level normalizations and spectrum-protein level normalization. Bioinformatics analysis of these common differentially expressed proteins revealed that proteins up-regulated in Ewsr1 knockout mouse are mostly related to the positive regulation of bone remodeling and inflammatory response. The down-regulated proteins were associated with the regulation of neurotransmitter levels or amino acid metabolic processes. Collectively, these findings provide insight into the physiological function and pathogenesis of EWSR1 on protein level. Better understanding of EWSR1 and its protein interactions will advance the field of clinical research into neuronal disorders. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD026994.

A global view of the human post-translational modification landscape

Post-translational modifications (PTMs) provide a rapid response to stimuli, finely tuning metabolism and gene expression and maintain homeostasis. Advances in mass spectrometry over the past two decades have significantly expanded the list of known PTMs in biology and as instrumentation continues to improve, this list will surely grow. While many PTMs have been studied in detail (e.g. phosphorylation, acetylation), the vast majority lack defined mechanisms for their regulation and impact on cell fate. In this review, we will highlight the field of PTM research as it currently stands, discussing the mechanisms that dictate site specificity, analytical methods for their detection and study, and the chemical tools that can be leveraged to define PTM regulation. In addition, we will highlight the approaches needed to discover and validate novel PTMs. Lastly, this review will provide a starting point for those interested in PTM biology, providing a comprehensive list of PTMs and what is known regarding their regulation and metabolic origins.

Structural insights into human co-transcriptional capping

Co-transcriptional capping of the nascent pre-mRNA 5' end prevents degradation of RNA polymerase (Pol) II transcripts and suppresses the innate immune response. Here, we provide mechanistic insights into the three major steps of human co-transcriptional pre-mRNA capping based on six different cryoelectron microscopy (cryo-EM) structures. The human mRNA capping enzyme, RNGTT, first docks to the Pol II stalk to position its triphosphatase domain near the RNA exit site. The capping enzyme then moves onto the Pol II surface, and its guanylyltransferase receives the pre-mRNA 5'-diphosphate end. Addition of a GMP moiety can occur when the RNA is ∼22 nt long, sufficient to reach the active site of the guanylyltransferase. For subsequent cap(1) methylation, the methyltransferase CMTR1 binds the Pol II stalk and can receive RNA after it is grown to ∼29 nt in length. The observed rearrangements of capping factors on the Pol II surface may be triggered by the completion of catalytic reaction steps and are accommodated by domain movements in the elongation factor DRB sensitivity-inducing factor (DSIF).

A Pseudomonas aeruginosa small RNA regulates chronic and acute infection

The ability to switch between different lifestyles allows bacterial pathogens to thrive in diverse ecological niches1,2. However, a molecular understanding of their lifestyle changes within the human host is lacking. Here, by directly examining bacterial gene expression in human-derived samples, we discover a gene that orchestrates the transition between chronic and acute infection in the opportunistic pathogen Pseudomonas aeruginosa. The expression level of this gene, here named sicX, is the highest of the P. aeruginosa genes expressed in human chronic wound and cystic fibrosis infections, but it is expressed at extremely low levels during standard laboratory growth. We show that sicX encodes a small RNA that is strongly induced by low-oxygen conditions and post-transcriptionally regulates anaerobic ubiquinone biosynthesis. Deletion of sicX causes P. aeruginosa to switch from a chronic to an acute lifestyle in multiple mammalian models of infection. Notably, sicX is also a biomarker for this chronic-to-acute transition, as it is the most downregulated gene when a chronic infection is dispersed to cause acute septicaemia. This work solves a decades-old question regarding the molecular basis underlying the chronic-to-acute switch in P. aeruginosa and suggests oxygen as a primary environmental driver of acute lethality.

An optimized workflow for MS-based quantitative proteomics of challenging clinical bronchoalveolar lavage fluid (BALF) samples

BACKGROUND

Clinical bronchoalveolar lavage fluid (BALF) samples are rich in biomolecules, including proteins, and useful for molecular studies of lung health and disease. However, mass spectrometry (MS)-based proteomic analysis of BALF is challenged by the dynamic range of protein abundance, and potential for interfering contaminants. A robust, MS-based proteomics compatible sample preparation workflow for BALF samples, including those of small and large volume, would be useful for many researchers.

RESULTS

We have developed a workflow that combines high abundance protein depletion, protein trapping, clean-up, and in-situ tryptic digestion, that is compatible with either qualitative or quantitative MS-based proteomic analysis. The workflow includes a value-added collection of endogenous peptides for peptidomic analysis of BALF samples, if desired, as well as amenability to offline semi-preparative or microscale fractionation of complex peptide mixtures prior to LC-MS/MS analysis, for increased depth of analysis. We demonstrate the effectiveness of this workflow on BALF samples collected from COPD patients, including for smaller sample volumes of 1-5 mL that are commonly available from the clinic. We also demonstrate the repeatability of the workflow as an indicator of its utility for quantitative proteomic studies.

CONCLUSIONS

Overall, our described workflow consistently provided high quality proteins and tryptic peptides for MS analysis. It should enable researchers to apply MS-based proteomics to a wide-variety of studies focused on BALF clinical specimens.

Spin column-based peptide fractionation alternatives for streamlined tandem mass tag (SL-TMT) sample processing

Fractionation is essential to achieving deep proteome coverage for sample multiplexing experiments where currently up to 18 samples can be analyzed concurrently. However, peptide fractionation (i.e., upstream of LC-MS/MS analysis) with a liquid chromatography system constrains sample processing as only a single sample can be fractionated at once. Here, we highlight the use of spin column-based methods which permit multiple multiplexed samples to be fractionated simultaneously. These methods require only a centrifuge and eliminate the need for a dedicated liquid chromatography system. We investigate peptide fractionation with strong anion exchange (SAX) and high-pH reversed phase (HPRP) spin columns, as well as a combination of both. In two separate experiments, we acquired deep proteome coverage (>8000 quantified proteins), while starting with <25 μg of protein per channel. Our datasets showcase the proteome alterations in two human cell lines resulting from treatment with inhibitors acting on the ubiquitin-proteasome system. We recommend this spin column-based peptide fractionation strategy for high-throughput screening applications or whenever a liquid chromatograph is not readily available. SIGNIFICANCE: Fractionation is a means to achieve deep proteome coverage for global proteomics analysis. Typical liquid chromatography systems may be a prohibitive expense for many laboratories. Here, we investigate prefractionation with strong anion exchange (SAX) and high-pH reversed phase (HPRP) spin columns, as well as a combination of both, as peptide fractionation methods. These spin columns have advantages over liquid chromatography systems, which include relative affordability, higher throughput capability, no carry over, and fewer potential instrument-related malfunctions. In two separate experiments, we acquired deep proteome coverage (>8000 quantified proteins), thereby showing the utility of each or a combination of both spin columns for global proteome analysis.

Tandem mass tag-based thermal proteome profiling for the discovery of drug-protein interactions in cancer cells

Identification of effector targets is imperative to the characterization of the mechanisms of action of novel small molecules. Here, we describe steps to identify effector drug-protein interactions in lysates derived from cancer cell lines using a thermal proteome profiling (TPP) protocol. Building on existing TTP approaches, we detail the use of an in-solution trypsin digestion technique to streamline sample preparation, a nonparametric analysis to rank proteins for prioritization, and a follow-up strategy for identifying effector interactors. For complete details on the use and execution of this protocol, please refer to Johnson et al. (2022).1.

Cryptosporidium uses multiple distinct secretory organelles to interact with and modify its host cell

Cryptosporidium is a leading cause of diarrheal disease in children and an important contributor to early childhood mortality. The parasite invades and extensively remodels intestinal epithelial cells, building an elaborate interface structure. How this occurs at the molecular level and the contributing parasite factors are largely unknown. Here, we generated a whole-cell spatial proteome of the Cryptosporidium sporozoite and used genetic and cell biological experimentation to discover the Cryptosporidium-secreted effector proteome. These findings reveal multiple organelles, including an original secretory organelle, and generate numerous compartment markers by tagging native gene loci. We show that secreted proteins are delivered to the parasite-host interface, where they assemble into different structures including a ring that anchors the parasite into its unique epicellular niche. Cryptosporidium thus uses a complex set of secretion systems during and following invasion that act in concert to subjugate its host cell.

Don't let go: co-fractionation mass spectrometry for untargeted mapping of protein-metabolite interactomes

The chemical complexity of metabolomes goes hand in hand with their functional diversity. Small molecules have many essential roles, many of which are executed by binding and modulating the function of a protein partner. The complex and dynamic protein-metabolite interaction (PMI) network underlies most if not all biological processes, but remains under-characterized. Herein, we highlight how co-fractionation mass spectrometry (CF-MS), a well-established approach to map protein assemblies, can be used for proteome and metabolome identification of the PMIs. We will review recent CF-MS studies, discuss the main advantages and limitations, summarize the available CF-MS guidelines, and outline future challenges and opportunities.

A peptide-centric approach to analyse quantitative proteomics data- an application to prostate cancer biomarker discovery

Bottom-up proteomics is a popular approach in molecular biomarker research. However, protein analysts have realized the limitations of protein-based approaches for identifying and quantifying proteins in complex samples, such as the identification of peptides sequences shared by multiple proteins and the difficulty in identifying modified peptides. Thus, there are many exciting opportunities to improve analysis methods. Here, an alternative method focused on peptide analysis is proposed as a complement to the conventional proteomics data analysis. To investigate this hypothesis, a peptide-centric approach was applied to reanalyse a urine proteome dataset of samples from prostate cancer patients and controls. The results were compared with the conventional protein-centric approach. The relevant proteins/peptides to discriminate the groups were detected based on two approaches, p-value and VIP values obtained by a PLS-DA model. A comparison of the two strategies revealed high inconsistency between protein and peptide information and greater involvement of peptides in key PCa processes. This peptide analysis unveiled discriminative features that are lost when proteins are analyzed as homogeneous entities. This type of analysis is innovative in PCa and integrated with the widely used protein-centric approach might provide a more comprehensive view of this disease and revolutionize biomarker discovery. SIGNIFICANCE: In this study, the application of a protein and peptide-centric approaches to reanalyse a urine proteome dataset from prostate cancer (PCa) patients and controls showed that many relevant proteins/peptides are missed by the conservative nature of p-value in statistical tests, therefore, the inclusion of variable selection methods in the analysis of the dataset reported in this work is fruitful. Comparison of protein- and peptide-based approaches revealed a high inconsistency between protein and peptide information and a greater involvement of peptides in key PCa processes. These results provide a new perspective to analyse proteomics data and detect relevant targets based on the integration of peptide and protein information. This data integration allows to unravel discriminative features that normally go unnoticed, to have a more comprehensive view of the disease pathophysiology and to open new avenues for the discovery of biomarkers.

Quantitative omics analyses of NCOA4 deficiency reveal an integral role of ferritinophagy in iron homeostasis of hippocampal neuronal HT22 cells

Introduction

Neurons require iron to support their metabolism, growth, and differentiation, but are also susceptible to iron-induced oxidative stress and cytotoxicity. Ferritin, a cytosolic iron storage unit, mediates cellular adaptation to fluctuations in iron delivery. NCOA4 has been characterized as a selective autophagic cargo receptor facilitating the mobilization of intracellular iron from ferritin. This process named ferritinophagy results in the degradation of ferritin and the consequent release of iron into the cytosol.

Methods

Here we demonstrate that NCOA4 is important for the adaptation of the HT22 mouse hippocampal neuronal cell line to cellular iron restriction. Additionally, we determined the pathophysiological implications of impaired ferritinophagy via functional analysis of the omics profile of HT22 cells deficient in NCOA4.

Results

NCOA4 silencing impaired ferritin turnover and was cytotoxic when cells were restricted of iron. Quantitative proteomics identified IRP2 accumulation among the most prominent protein responses produced by NCOA4 depletion in HT22 cells, which is indicative of functional iron deficiency. Additionally, proteins of apoptotic signaling pathway were enriched by those responsive to NCOA4 deficiency. Transcriptome profiles of NCOA4 depletion revealed neuronal cell death, differentiation of neurons, and development of neurons as potential diseases and bio functions affected by impaired ferritinophagy, particularly, when iron was restricted.

Discussion

These findings identify an integral role of NCOA4-mediated ferritinophagy in the maintenance of iron homeostasis by HT22 cells, and its potential implications in controlling genetic pathways of neurodevelopment and neurodegenerative diseases.

Chromatographic separation of peptides and proteins for characterization of proteomes

Characterization of proteomes aims to comprehensively characterize proteins in cells or tissues via two main strategies: (1) bottom-up strategy based on the separation and identification of enzymatic peptides; (2) top-down strategy based on the separation and identification of intact proteins. However, it is challenged by the high complexity of proteomes. Consequently, the improvements in peptide and protein separation technologies for simplifying the sample should be critical. In this feature article, separation columns for peptide and protein separation were introduced, and peptide separation technologies for bottom-up proteomic analysis as well as protein separation technologies for top-down proteomic analysis were summarized. The achievement, recent development, limitation and future trends are discussed. Besides, the outlook on challenges and future directions of chromatographic separation in the field of proteomics was also presented.

Tandem mass tag-based quantitative proteomic analysis of cervical cancer

BACKGROUND

Cervical cancer is a common cancer in women caused by high-risk human papillomavirus (Hr-HPV). Many potential biomarkers have been proposed for precancerous lesions and cancer diagnosis and some of these markers studied for prognosis. This study determined potential biomarkers for cervical cancer diagnosis in regard to HPV genotype by using isobaric labeling quantitative proteomics.

METHODS

in the current study, there were 75 formalin fixed paraffin embedded (FFPE) uterine cervical samples that used to determine the 14 HPV genotypes and the viral load of each genotype was determined. The tandem mass tag (TMT) proteomic work was performed on four FFPE samples of cervical cancer and four FFPE of control samples. The validation of biomarkers from cervical proteome were evaluated using Immunohistochemistry (IHC) testing.

RESULTS

The most frequent HPV genotype among all other genotypes was HPV 16. There were 2753 proteins quantified by TMT and 336 of these proteins had significant differential abundances. KPNA2, MCM2, COL1A1, and DCN were selected based on functional enrichment analysis and validated by Immunohistochemistry (IHC) testing. The staining of IHC confirmed the upregulation of KPNA2 and MCM2 expression in cervical neoplasia and the downregulation of DCN and COL1A1 in some cervical cancer group subjects.

CONCLUSION

The KPNA2 marker was compared to other previously reported biomarkers and is a putative biomarker to be validated in further studies, specifically the relationship with HPV load.

Identification of Deubiquitinase Substrates in Xenopus Egg Extract

Deubiquitinases (DUBs) antagonize protein ubiquitination by removing ubiquitin from substrates. Identifying the physiological substrates of each DUB is critical for understanding DUB function and the principles that govern the specificity of this class of enzymes. Since multiple DUBs can act on the same substrate, it can be challenging to identify substrates using inactivating a single enzyme. Here, we outline a method that enables the identification of proteins whose stability depends on DUB activity and an approach to profile DUB specificity in Xenopus egg extract. By coupling broad DUB inhibition with quantitative proteomics, we circumvent DUB redundancy to identify DUB substrates. By adding back recombinant DUBs individually to the extract, we pinpoint DUBs sufficient to counteract proteasomal degradation of these newly identified substrates. We apply this method to Xenopus egg extract but suggest that it can also be adapted to other cell lysates.

Heavy Methyl SILAC Metabolic Labeling of Human Cell Lines for High-Confidence Identification of R/K-Methylated Peptides by High-Resolution Mass Spectrometry

Protein methylation is a widespread post-translational modification (PTM) involved in several important biological processes including, but not limited to, RNA splicing, signal transduction, translation, and DNA repair. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is considered today the most versatile and accurate technique to profile PTMs with high precision and proteome-wide depth; however, the identification of protein methylations by MS is still prone to high false discovery rates. In this chapter, we describe the heavy methyl SILAC metabolic labeling strategy that allows high-confidence identification of in vivo methyl-peptides by MS-based proteomics. We provide a general protocol that covers the steps of heavy methyl labeling of cultured cells, protein sample preparation, LC-MS/MS analysis, and downstream computational analysis of the acquired MS data.

Unique and Shared Proteome Responses of Rice Plants (Oryza sativa) to Individual Abiotic Stresses

Food safety of staple crops such as rice is of global concern and is at the top of the policy agenda worldwide. Abiotic stresses are one of the main limitations to optimizing yields for sustainability, food security and food safety. We analyzed proteome changes in Oryza sativa cv. Nipponbare in response to five adverse abiotic treatments, including three levels of drought (mild, moderate, and severe), soil salinization, and non-optimal temperatures. All treatments had modest, negative effects on plant growth, enabling us to identify proteins that were common to all stresses, or unique to one. More than 75% of the total of differentially abundant proteins in response to abiotic stresses were specific to individual stresses, while fewer than 5% of stress-induced proteins were shared across all abiotic constraints. Stress-specific and non-specific stress-responsive proteins identified were categorized in terms of core biological processes, molecular functions, and cellular localization.

Impact of dietary walnuts, a nutraceutical option, on circulating markers of metabolic dysregulation in a rodent cachectic tumor model

BACKGROUND

Nutraceutical foods, like walnuts which are rich in immunonutrients, can have medicinal benefits. Dietary walnuts have been shown to slow or prevent tumor growth in mice genetically programmed to grow breast or prostate tumors. This study investigated whether walnuts could exert the same preventable effect in a transplantable carcinoma rat model.

METHODS

Eighteen rats were randomly fed a diet containing walnuts (10% of food by weight), and 36 were fed a diet without walnuts (control) for 21 days. On day 22, 18 control diet rats were switched to the walnut diet. All other animals remained on their same diet. Within each diet group, 6 rats were implanted with the Ward colon carcinoma (TB), and 12 were sham-operated. Five days later, 6 sham-operated animals were weight-matched to a TB and then pair-fed for the remainder of the study. The remaining 6 sham-operated, or non-tumor-bearing rats, were ad-lib fed.

RESULTS

The tissue of the walnut-eating rats showed higher omega-3 fatty acid (immunonutrient) content which did not slow or prevent tumor growth or the loss of lean and fat mass typical of this TB model. In addition, blood glucose, insulin, IGF-1, and adiponectin levels were significantly lower in the TB, demonstrating metabolic dysregulation. Again, these changes were unaltered by consuming walnuts. Plasma proteomics identified six proteins elevated in the TB, but none could be connected with the observed metabolic dysregulation.

CONCLUSION

Although walnuts' rich immunonutrient content prevented tumor growth in genetically programmed mice models, there was no effect in this model.

Mass spectrometry and the cellular surfaceome

The collection of exposed plasma membrane proteins, collectively termed the surfaceome, is involved in multiple vital cellular processes, such as the communication of cells with their surroundings and the regulation of transport across the lipid bilayer. The surfaceome also plays key roles in the immune system by recognizing and presenting antigens, with its possible malfunctioning linked to disease. Surface proteins have long been explored as potential cell markers, disease biomarkers, and therapeutic drug targets. Despite its importance, a detailed study of the surfaceome continues to pose major challenges for mass spectrometry-driven proteomics due to the inherent biophysical characteristics of surface proteins. Their inefficient extraction from hydrophobic membranes to an aqueous medium and their lower abundance compared to intracellular proteins hamper the analysis of surface proteins, which are therefore usually underrepresented in proteomic datasets. To tackle such problems, several innovative analytical methodologies have been developed. This review aims at providing an extensive overview of the different methods for surfaceome analysis, with respective considerations for downstream mass spectrometry-based proteomics.

Boost-DiLeu: Enhanced Isobaric N,N-Dimethyl Leucine Tagging Strategy for a Comprehensive Quantitative Glycoproteomic Analysis

Intact glycopeptide analysis has been of great interest because it can elucidate glycosylation site information and glycan structural composition at the same time. However, mass spectrometry (MS)-based glycoproteomic analysis is hindered by the low abundance and poor ionization efficiency of glycopeptides. Relatively large amounts of starting materials are needed for the enrichment, which makes the identification and quantification of intact glycopeptides from samples with limited quantity more challenging. To overcome these limitations, we developed an improved isobaric labeling strategy with an additional boosting channel to enhance N,N-dimethyl leucine (DiLeu) tagging-based quantitative glycoproteomic analysis, termed as Boost-DiLeu. With the integration of a one-tube sample processing workflow and high-pH fractionation, 3514 quantifiable N-glycopeptides were identified from 30 μg HeLa cell tryptic digests with reliable quantification performance. Furthermore, this strategy was applied to human cerebrospinal fluid (CSF) samples to differentiate N-glycosylation profiles between Alzheimer's disease (AD) patients and non-AD donors. The results revealed processes and pathways affected by dysregulated N-glycosylation in AD, including platelet degranulation, cell adhesion, and extracellular matrix, which highlighted the involvement of N-glycosylation aberrations in AD pathogenesis. Moreover, weighted gene coexpression network analysis (WGCNA) showed nine modules of glycopeptides, two of which were associated with the AD phenotype. Our results demonstrated the feasibility of using this strategy for in-depth glycoproteomic analysis of size-limited clinical samples. Taken together, we developed and optimized a strategy for the enhanced comprehensive quantitative intact glycopeptide analysis with DiLeu labeling, showing significant promise for identifying novel therapeutic targets or biomarkers in biological systems with a limited sample quantity.

Predictive value of proteomic markers for advanced rectal cancer with neoadjuvant chemoradiotherapy

Background

Preoperative neoadjuvant chemoradiation (nCRT) has been the standard treatment for locally advanced rectal cancer. Serum biomarkers to stratify patients with respect to prognosis and response to nCRT are needed due to the diverse response to the therapy.

Methods

Thirteen paired pre- and post-nCRT sera from rectal cancer patients were analyzed by isobaric tags for relative and absolute quantitation (iTRAQ) method. Twenty-five proteins were selected for validation by parallel reaction monitoring (PRM) in ninety-one patients.

Results

Totally, 310 proteins were identified and quantified in sera samples. Reactome pathway analysis showed that the immune activation-related pathways were enriched in response to nCRT. Twenty-five proteins were selected for further validation. PRM result showed that the level of PZP was higher in pathological complete response (pCR) patients than non-pCR patients. The Random Forest algorithm identified a prediction model composed of 10 protein markers, which allowed discrimination between pCR patients and non-pCR patients (area under the curve (AUC) = 0.886 on testing set). Higher HEP2 and GELS or lower S10A8 in baseline sera were associated with better prognosis. Higher APOA1 in post nCRT sera was associated with better disease-free survival (DFS).

Conclusions

We identified and confirmed a 10-protein panel for nCRT response prediction and four potential biomarkers HEP2, GELS, S10A8 and APOA1 for prognosis of rectal cancer based on iTRAQ-based comparative proteomics screening and PRM-based targeted proteomic validation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09960-z.

Enhancement of Proteome Coverage by Ion Mobility Fractionation Coupled to PASEF on a TIMS-QTOF Instrument

Trapped ion-mobility spectrometry (TIMS) was used to fractionate ions in the gas phase based on their ion mobility (V s/cm2), followed by parallel accumulation-serial fragmentation (PASEF) using a quadrupole time-of-flight instrument to determine the effect on the depth of proteome coverage. TIMS fractionation (up to four gas-phase fractions) coupled to data-dependent acquisition (DDA)-PASEF resulted in the detection of ∼7000 proteins and over 70,000 peptides overall from 200 ng of human (HeLa) cell lysate per injection using a commercial 25 cm ultra high performance liquid chromatography (UHPLC) column with a 90 min gradient. This result corresponded to ∼19 and 30% increases in protein and peptide identifications, respectively, when compared to a default, single-range TIMS DDA-PASEF analysis. Quantitation precision was not affected by TIMS fractionation as demonstrated by the average and median coefficient of variation values that were less than 4% upon label-free quantitation of technical replicates. TIMS fractionation was utilized to generate a DDA-based spectral library for downstream data-independent acquisition (DIA) analysis of lower sample input using a shorter LC gradient. The TIMS-fractionated library, consisting of over 7600 proteins and 82,000 peptides, enabled the identification of ∼4000 and 6600 proteins from 10 and 200 ng of human (HeLa) cell lysate input, respectively, with a 20 min gradient, single-shot DIA analysis. Data are available in ProteomeXchange: identifier PXD033129.

Advances in glycopeptide enrichment methods for the analysis of protein glycosylation over the past decade

Advances in bioanalytical technology have accelerated the analysis of complex protein glycosylation, which is beneficial to understanding glycosylation in drug discovery and disease diagnosis. Due to its biological uniqueness in the course of disease occurrence and development, disease-specific glycosylation requires quantitative characterization of protein glycosylation. We provide a comprehensive review of recent advances in glycosylation analysis, including workflows for glycoprotein digestion, glycopeptide separation and enrichment, and mass-spectrometry sequencing. We specifically focus on different strategies for glycopeptide enrichment through physical interaction, chemical oxidation, or metabolic labeling of intact glycopeptides. The recent advances and challenges of O-glycosylation analysis are presented, and the development of improved enrichment methods combining different proteases to analyze O-glycosylation is also proposed. This article is protected by copyright. All rights reserved.

Reprogramming of sorghum proteome in response to sugarcane aphid infestation

Sugarcane aphid (SCA; Melanaphis sacchari Zehntner) is a key piercing-sucking pest of sorghum (Sorghum bicolor) that cause significant yield losses. While feeding on host plants, complex signaling networks are invoked from recognition of insect attack to induction of plant defenses. Consequently, these signaling networks lead to the production of insecticidal compounds or limited access of nutrients to insects. Previously, several studies were published on the transcriptomics analysis of sorghum in response to SCA infestation, but no information is available on the physiological changes of sorghum at the proteome level. We used the SCA resistant sorghum genotype SC265 for the global proteomics analysis after 1 and 7 days of SCA infestation using the TMT-plex technique. Peptides matching a total of 4211 proteins were identified and 158 proteins were differentially expressed at day 1 and 7. Overall, proteome profiling of SC265 after SCA infestation at days 1 and 7 revealed the suppression of plant defense-related proteins and upregulation of plant defense and signaling-related proteins, respectively. The plant defense responses based on proteome data were validated using electrical penetration graph (EPG) technique to observe changes in aphid feeding. Feeding behavior analyses revealed that SCA spent significantly longer time in phloem phase on SCA infested plants for day 1 and lesser time in day 7 SCA infested sorghum plants, compared to their respective control plants. Overall, our study provides insights into underlying mechanisms that contribute to sorghum resistance to SCA.

Differences in Antioxidant and Lipid Handling Protein Expression Influence How Cells Expressing Distinct Mutant TP53 Subtypes Maintain Iron Homeostasis

The tumor suppressor TP53 is the most commonly mutated gene in human cancers, and iron is necessary for cancer cell growth and proliferation, but there is a significant gap in knowledge for how the two cooperate to affect cellular physiology. Elucidating this role is complicated, however, because each TP53 mutation subtype exhibits unique phenotypic responses to changes in iron availability. The goal of this work was to determine how cells expressing distinct TP53 mutation subtypes respond to iron restriction. Utilizing a reverse genetics approach, we generated eight isogenic cell lines that either lacked TP53 expression, expressed wild-type TP53, or expressed one of the six most common TP53 “hotspot” mutations. We then employed isobaric peptide labeling and mass spectrometry to quantitively measure changes in global protein expression, both in response to induction of mutant TP53 expression, and in response to iron chelation. Our findings indicate that mutant TP53-dependent sensitivities to iron restriction are not driven by differences in responsiveness to iron chelation, but more so by mutant TP53-dependent differences in cellular antioxidant and lipid handling protein expression. These findings reinforce the importance of distinguishing between TP53 mutation subtypes when investigating approaches to target mutant TP53. We also identify unique TP53-dependent perturbances in protein expression patterns that could be exploited to improve iron-targeted chemotherapeutic strategies.

An antibody-free platform for multiplexed, sensitive quantification of protein biomarkers in complex biomatrices

Sensitive, multiplexed protein quantification remains challenging despite recent advancements in LC-MS assays for targeted protein biomarker quantification. High-sensitivity protein biomarker measurements usually require immuno-affinity enrichment of target protein; a process which is highly dependent on capture reagent and limited in capability to measure multiple analytes. Herein, we report a novel antibody-free platform, which measures multiple biomarkers from complex matrices employing a strategically optimized solid-phase extraction cleanup and orthogonal multidimensional LC-MS. Eight human protein biomarkers with different specifications were spiked into canine plasma as a model investigation system. The developed strategy achieved the desired sensitivity, robustness, and throughput via the following steps: (1) post digestion mixed-mode cation exchange-reverse phase SPE enrichment cleaned up the sample initially; (2) rapid, high-pH peptide fractionation further eliminated background components efficiently while selectively enriched signature peptides (SP) to provide sufficient sensitivity for multiple targets; and (3) trapping-micro-LC-MS analysis delivered high sensitivity comparable to a nano-LC-MS method but with much better robustness and throughput for the final analysis. Compared with a conventional LC-MS assay with direct protein digestion and limited clean-up, analysis with this antibody-free platform improved the LLOQ by 1-2 orders of magnitude for the eight protein biomarkers, reaching as low as 5 ng/mL in plasma, with feasible robustness and throughput. This platform was applied for the quantification of biomarkers of respiratory conditions in patients with various lung diseases, demonstrating real-world applicability.