Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry

Identification of protein biomarkers in wastewater linked to the incidence of COVID-19

Wastewater-based epidemiological (WBE) surveillance is a viable disease surveillance technique capable of monitoring the spread of infectious disease agents in sewershed communities. In addition to detecting viral genomes in wastewater, WBE surveillance can identify other endogenous biomarkers that are significantly elevated and excreted in the saliva, urine, and/or stool of infected individuals. Human protein biomarkers allow the realization of real-time WBE surveillance using highly sensitive biosensors. In this study, we analyzed endogenous protein biomarkers present in wastewater influent through liquid chromatography-tandem mass spectrophotometry and scaffold data-independent acquisition to identify candidate target protein biomarkers for WBE surveillance of SARS-CoV-2. We found that out of the 1382 proteins observed in the wastewater samples, 44 were human proteins associated with infectious diseases. These included immune response substances such as immunoglobulins, cytokine-chemokines, and complements, as well as proteins belonging to antimicrobial and antiviral groups. A significant correlation was observed between the intensity of human infectious disease-related protein biomarkers in wastewater and COVID-19 case numbers. Real-time WBE surveillance using biosensors targeting immune response proteins, such as antibodies or immunoglobulins, in wastewater holds promise for expediting the implementation of relevant policies for the effective prevention of infectious diseases in the near future.

Deep Spectral Library of Mice Retina for Myopia Research: Proteomics Dataset generated by SWATH and DIA-NN

The retina plays a crucial role in processing and decoding visual information, both in normal development and during myopia progression. Recent advancements have introduced a library-independent approach for data-independent acquisition (DIA) analyses. This study demonstrates deep proteome identification and quantification in individual mice retinas during myopia development, with an average of 6,263 ± 86 unique protein groups. We anticipate that the use of a predicted retinal-specific spectral library combined with the robust quantification achieved within this dataset will contribute to a better understanding of the proteome complexity. Furthermore, a comprehensive mice retinal-specific spectral library was generated, encompassing a total identification of 9,401 protein groups, 70,041 peptides, 95,339 precursors, and 761,868 transitions acquired using SWATH-MS acquisition on a ZenoTOF 7600 mass spectrometer. This dataset surpasses the spectral library generated through high-pH reversed-phase fractionation by data-dependent acquisition (DDA). The data is available via ProteomeXchange with the identifier PXD046983. It will also serve as an indispensable reference for investigations in myopia research and other retinal or neurological diseases.

A Framework for Quality Control in Quantitative Proteomics

A thorough evaluation of the quality, reproducibility, and variability of bottom-up proteomics data is necessary at every stage of a workflow, from planning to analysis. We share vignettes applying adaptable quality control (QC) measures to assess sample preparation, system function, and quantitative analysis. System suitability samples are repeatedly measured longitudinally with targeted methods, and we share examples where they are used on three instrument platforms to identify severe system failures and track function over months to years. Internal QCs incorporated at the protein and peptide levels allow our team to assess sample preparation issues and to differentiate system failures from sample-specific issues. External QC samples prepared alongside our experimental samples are used to verify the consistency and quantitative potential of our results during batch correction and normalization before assessing biological phenotypes. We combine these controls with rapid analysis (Skyline), longitudinal QC metrics (AutoQC), and server-based data deposition (PanoramaWeb). We propose that this integrated approach to QC is a useful starting point for groups to facilitate rapid quality control assessment to ensure that valuable instrument time is used to collect the best quality data possible. Data are available on Panorama Public and ProteomeXchange under the identifier PXD051318.

Proteomic analysis of P. gingivalis-Lipopolysaccharide induced neuroinflammation in SH-SY5Y and HMC3 cells

Chronic periodontitis and its keystone pathogen, Porphyromonas gingivalis, have increasingly been linked with Alzheimer's disease (AD). However, P.gingivalis-lipopolysaccharide (LPS) mediated release of neuroinflammatory proteins contributes to AD remains underexplored. In this study, we utilized data-independent acquisition mass spectrometry to characterize P.gingivalis-LPS induced profile of differentially expressed proteins associated with the neuroinflammatory response in human neuroblastoma (SH-SY5Y) and human microglial (HMC3) cells. We reported a set of 124 proteins in SH-SY5Y cells and 96 proteins in HMC3 cells whose levels were significantly upregulated or downregulated by exposure to P. gingivalis-LPS. Our findings demonstrate that P. gingivalis-LPS contributed to the elevated expressions of dementia biomarkers and pro-inflammatory cytokines that include APP, Aβ1-42, Aβ1-40, T-Tau, p-Tau, VEGF, TGF-β, IL-1β, IL-6 and TNF-α through 2 distinct pathways of extracellular sensing by cell surface receptors and intracellular cytosolic receptors. Interestingly, intracellular signaling proteins activated with P. gingivalis-LPS transfection using Lipofectamine™ 2000 had significantly higher fold change protein expression compared to the extracellular signaling with P. gingivalis-LPS treatment. Additionally, we also explored P. gingivalis-LPS mediated activation of caspase-4 dependent non canonical inflammasome pathway in both SH-SY5Y and HMC3 cells. In summary, P. gingivalis-LPS induced neuroinflammatory protein expression in SH-SY5Y and HMC3 cells, provided insights into the specific inflammatory pathways underlying the potential link between P. gingivalis-LPS infection and the pathogenesis of Alzheimer's disease and related dementias.

Relationships between HDL subpopulation proteome and HDL function in overweight/obese people with and without coronary heart disease

BACKGROUND AND AIMS

The structure-function relationships of high-density lipoprotein (HDL) subpopulations are not well understood. Our aim was to examine the interrelationships between HDL particle proteome and HDL functionality in subjects with and without coronary heart disease (CHD).

METHODS

We isolated 5 different HDL subpopulations based on charge, size, and apolipoprotein A1 (APOA1) content from the plasma of 33 overweight/obese CHD patients and 33 age-and body mass index (BMI)-matched CHD-free subjects. We measured the relative molar concentration of HDL-associated proteins by liquid chromatography tandem mass spectrometry (LC-MS/MS) and assessed particle functionality.

RESULTS

We quantified 110 proteins associated with the 5 APOA1-containing HDL subpopulations. The relative molar concentration of these proteins spanned five orders of magnitude. Only 10 proteins were present in >1% while 73 were present in <0.1% concentration. Only 6 of the 10 most abundant proteins were apolipoproteins. Interestingly, the largest (α-1) and the smallest (preβ-1) HDL particles contained the most diverse proteomes. The protein composition of each HDL subpopulation was altered in CHD cases as compared to controls with the most prominent differences in preβ-1 and α-1 particles. APOA2 concentration was positively correlated with preβ-1 particle functionality (ABCA1-CEC/mg APOA1 in preβ-1) (R2 = 0.42, p = 0.005), while APOE concentration was inversely correlated with large-HDL particle functionality (SRBI-CEC/mg APOA1 in α-1+α-2) (R2 = 0.18, p = 0.01).

CONCLUSIONS

The protein composition of the different HDL subpopulations was altered differentially in CHD patients. The functionality of the small and large HDL particles correlated with the protein content of APOA2 and APOE, respectively. Our data indicate that distinct particle subspecies and specific particle associated proteins provide new information about the role of HDL in CHD.

Mass Spectral Feature Analysis of Ubiquitylated Peptides Provides Insights into Probing the Dark Ubiquitylome

Ubiquitylation is a structurally and functionally diverse post-translational modification that involves the covalent attachment of the small protein ubiquitin to other protein substrates. Trypsin-based proteomics is the most common approach for globally identifying ubiquitylation sites. However, we estimate that such methods are unable to detect ∼40% of ubiquitylation sites in the human proteome, i.e., "the dark ubiquitylome", including many important for human health and disease. In this meta-analysis of three large ubiquitylomic data sets, we performed a series of bioinformatic analyses to assess experimental features that could aid in uniquely identifying site-specific ubiquitylation events. Spectral predictions from Prosit were compared to experimental spectra of tryptic ubiquitylated peptides, revealing previously uncharacterized fragmentation of the diGly scar. Analysis of the LysC-derived ubiquitylated peptides reveals systematic, multidimensional peptide fragmentation, including diagnostic b-ions from fragmentation of the LysC ubiquitin scar. Comprehensively, these findings provide diagnostic spectral signatures of modification events that could be applied to new analysis methods for nontryptic ubiquitylomics.

Automated High-Throughput Biological Sex Identification from Archeological Human Dental Enamel Using Targeted Proteomics

Biological sex is key information for archeological and forensic studies, which can be determined by proteomics. However, the lack of a standardized approach for fast and accurate sex identification currently limits the reach of proteomics applications. Here, we introduce a streamlined mass spectrometry (MS)-based workflow for the determination of biological sex using human dental enamel. Our approach builds on a minimally invasive sampling strategy by acid etching, a rapid online liquid chromatography (LC) gradient coupled to a high-resolution parallel reaction monitoring (PRM) assay allowing for a throughput of 200 samples per day (SPD) with high quantitative performance enabling confident identification of both males and females. Additionally, we developed a streamlined data analysis pipeline and integrated it into a Shiny interface for ease of use. The method was first developed and optimized using modern teeth and then validated in an independent set of deciduous teeth of known sex. Finally, the assay was successfully applied to archeological material, enabling the analysis of over 300 individuals. We demonstrate unprecedented performance and scalability, speeding up MS analysis by 10-fold compared to conventional proteomics-based sex identification methods. This work paves the way for large-scale archeological or forensic studies enabling the investigation of entire populations rather than focusing on individual high-profile specimens. Data are available via ProteomeXchange with the identifier PXD049326.

Airspaces-derived exosomes contain disease-relevant protein signatures in a mouse model of cystic fibrosis (CF)-like mucoinflammatory lung disease

Exosomes, membrane-bound extracellular vesicles, ranging from approximately 30-200 nm in diameter, are released by almost all cell types and play critical roles in intercellular communication. In response to the prevailing stress, the exosome-bound protein signatures vary in abundance and composition. To identify the bronchoalveolar lavage fluid (BALF) exosome-bound proteins associated with mucoinflammatory lung disease and to gain insights into their functional implications, we compared BALF exosomes-derived proteins from adult Scnn1b transgenic (Scnn1b-Tg+) and wild type (WT) mice. A total of 3,144 and 3,119 proteins were identified in BALF exosomes from Scnn1b-Tg+ and WT mice, respectively. Using cutoff criteria (Log2 fold-change > 1 and adjusted p-value < 0.05), the comparison of identified proteins revealed 127 and 30 proteins that were significantly upregulated and downregulated, respectively, in Scnn1b-Tg+ versus WT mice. In addition, 52 and 27 proteins were exclusively enriched in Scnn1b-Tg+ and WT mice, respectively. The identified exosome-bound proteins from the homeostatic airspaces of WT mice were mostly relevant to the normal physiological processes. The protein signatures enriched in the BALF exosomes of Scnn1b-Tg+ mice were relevant to macrophage activation and mucoinflammatory processes. Ingenuity pathway analyses revealed that the enriched proteins in Scnn1b-Tg+ mice contributed to the inflammatory responses and antimicrobial defense pathways. Selective proteins including, RETNLA/FIZZ1, LGALS3/Galectin-3, S100A8/MRP8, and CHIL3/YM1 were immunolocalized to specific cell types. The comparative analysis between enriched BALF exosome proteins and previously identified differentially upregulated genes in Scnn1b-Tg+ versus WT mice suggested that the compartment-/cell-specific upregulation in gene expression dictates the enrichment of their respective proteins in the lung airspaces. Taken together, this study demonstrates that the BALF exosome-bound protein signatures reflect disease-relevant disturbances. Our findings suggest that the exosomes carry disease-relevant protein signatures that can be used as a diagnostic as well as predictive biomarkers for mucoinflammatory lung disease.

Distinct H3K9me3 heterochromatin maintenance dynamics govern different gene programs and repeats in pluripotent cells

H3K9me3-heterochromatin, established by lysine methyltransferases (KMTs) and compacted by HP1 isoforms, represses alternative lineage genes and DNA repeats. Our understanding of H3K9me3-heterochromatin stability is presently limited to individual domains and DNA repeats. We engineered Suv39h2 KO mouse embryonic stem cells to degrade remaining two H3K9me3-KMTs within one hour and found that both passive dilution and active removal contribute to H3K9me3 decay within 12-24 hours. We discovered four different H3K9me3 decay rates across the genome and chromatin features and transcription factor binding patterns that predict the stability classes. A "binary switch" governs heterochromatin compaction, with HP1 rapidly dissociating from heterochromatin upon KMTs' depletion and a particular threshold level of HP1 limiting pioneer factor binding, chromatin opening, and exit from pluripotency within 12 hr. Unexpectedly, receding H3K9me3 domains unearth residual HP1β peaks enriched with heterochromatin-inducing proteins. Our findings reveal distinct H3K9me3-heterochromatin maintenance dynamics governing gene networks and repeats that together safeguard pluripotency.

FAS Inhibited Proteomics and Phosphoproteomics Profiling of Colorectal Cancer Spheroids Shows Activation of Ferroptotic Death Mechanism

Colorectal cancer (CRC) is projected to become the third most diagnosed and third most fatal cancer in the United States by 2024, with early onset CRC on the rise. Research is constantly underway to discover novel therapeutics for the treatment of various cancers to improve patient outcomes and survival. Fatty acid synthase (FAS) has become a druggable target of interest for the treatment of many different cancers. One such inhibitor, TVB-2640, has gained popularity for its high specificity for FAS and has entered a phase 1 clinical trial for the treatment of solid tumors. However, the distinct molecular differences that occur upon inhibition of FAS have yet to be understood. Here, we conduct proteomics and phosphoproteomics analyses on HCT 116 and HT-29 CRC spheroids inhibited with either a generation 1 (cerulenin) or generation 2 (TVB-2640) FAS inhibitor. Proteins involved in lipid metabolism and cellular respiration were altered in abundance. It was also observed that proteins involved in ferroptosis─an iron mediated form of cell death─were altered. These results show that HT-29 spheroids exposed to cerulenin or TVB-2640 are undergoing a ferroptotic death mechanism. The data were deposited to the ProteomeXchange Consortium via the PRIDE repository with the identifier PXD050987.

A New Evaluation Metric for Quantitative Accuracy of LC-MS/MS-Based Proteomics with Data-Independent Acquisition

Data-independent acquisition (DIA) has improved the identification and quantitation coverage of peptides and proteins in liquid chromatography-tandem mass spectrometry-based proteomics. However, different DIA data-processing tools can produce very different identification and quantitation results for the same data set. Currently, benchmarking studies of DIA tools are predominantly focused on comparing the identification results, while the quantitative accuracy of DIA measurements is acknowledged to be important but insufficiently investigated, and the absence of suitable metrics for comparing quantitative accuracy is one of the reasons. A new metric is proposed for the evaluation of quantitative accuracy to avoid the influence of differences in false discovery rate control stringency. The part of the quantitation results with high reliability was acquired from each DIA tool first, and the quantitative accuracy was evaluated by comparing quantification error rates at the same number of accurate ratios. From the results of four benchmark data sets, the proposed metric was shown to be more sensitive to discriminating the quantitative performance of DIA tools. Moreover, the DIA tools with advantages in quantitative accuracy were consistently revealed by this metric. The proposed metric can also help researchers in optimizing algorithms of the same DIA tool and sample preprocessing methods to enhance quantitative accuracy.

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

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

Mitochondrial Transplantation Promotes Protective Effector and Memory CD4+ T Cell Response During Mycobacterium Tuberculosis Infection and Diminishes Exhaustion and Senescence in Elderly CD4+ T cells

Tuberculosis (TB), caused by Mycobacterium tuberculosis (M.tb), is a major global health concern, particularly affecting those with weakened immune systems, including the elderly. CD4+ T cell response is crucial for immunity against M.tb, but chronic infections and aging can lead to T cell exhaustion and senescence, worsening TB disease. Mitochondrial dysfunction, prevalent in aging and chronic diseases, disrupts cellular metabolism, increases oxidative stress, and impairs T-cell functions. This study investigates the effect of mitochondrial transplantation (mito-transfer) on CD4+ T cell differentiation and function in aged mouse models and human CD4+ T cells from elderly individuals. Mito-transfer in naïve CD4+ T cells is found to promote protective effector and memory T cell generation during M.tb infection in mice. Additionally, it improves elderly human T cell function by increasing mitochondrial mass and altering cytokine production, thereby reducing markers of exhaustion and senescence. These findings suggest mito-transfer as a novel approach to enhance aged CD4+ T cell functionality, potentially benefiting immune responses in the elderly and chronic TB patients. This has broader implications for diseases where mitochondrial dysfunction contributes to T-cell exhaustion and senescence.

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.

Mdm2 requires Sprouty4 to regulate focal adhesion formation and metastasis independent of p53

Although the E3 ligase Mdm2 and its homologue and binding partner MdmX are the major regulators of the p53 tumor suppressor protein, it is now evident that Mdm2 and MdmX have multiple functions that do not involve p53. As one example, it is known that Mdm2 can regulate cell migration, although mechanistic insight into this function is still lacking. Here we show in cells lacking p53 expression that knockdown of Mdm2 or MdmX, as well as pharmacological inhibition of the Mdm2/MdmX complex, not only reduces cell migration and invasion, but also impairs cell spreading and focal adhesion formation. In addition, Mdm2 knockdown decreases metastasis in vivo. Interestingly, Mdm2 downregulates the expression of Sprouty4, which is required for the Mdm2 mediated effects on cell migration, focal adhesion formation and metastasis. Further, our findings indicate that Mdm2 dampening of Sprouty4 is a prerequisite for maintaining RhoA levels in the cancer cells that we have studied. Taken together we describe a molecular mechanism whereby the Mdm2/MdmX complex through Sprouty4 regulates cellular processes leading to increase metastatic capability independently of p53.

Proteomic and Cytokine Profiling in Plasma from Patients with Normal-Tension Glaucoma and Ocular Hypertension

Primary open-angle glaucoma (POAG) is subdivided depending on eye pressure. Patients with normal-tension glaucoma (NTG) have never had high intraocular pressure (IOP) measured while patients with ocular hypertension (OHT) have high eye pressure but no signs of glaucoma. Although IOP is considered to be a risk factor for all glaucoma patients, it is reasonable to assume that other risk factors such as inflammation play a role. We aimed to characterize the proteome and cytokine profile during hypoxia in plasma from patients with NTG (n = 10), OHT (n = 10), and controls (n = 10). Participants were exposed to hypoxia for two hours, followed by 30 min of normoxia. Samples were taken before ("baseline"), during ("hypoxia"), and after hypoxia ("recovery"). Proteomics based on liquid chromatography coupled with mass spectrometry (LC-MS) was performed. Cytokines were measured by Luminex assays. Bioinformatic analyses indicated the involvement of complement and coagulation cascades in NTG and OHT. Regulation of high-density lipoprotein 3 (HDL3) apolipoproteins suggested that changes in cholesterol metabolism are related to OHT. Hypoxia decreased the level of tumor necrosis factor-α (TNF-α) in OHT patients compared to controls. Circulating levels of interleukin-1β (IL-1β) and C-reactive protein (CRP) were decreased in NTG patients compared to controls during hypoxia. After recovery, plasma interleukin-6 (IL-6) was upregulated in patients with NTG and OHT. Current results indicate an enhanced systemic immune response in patients with NTG and OHT, which correlates with pathogenic events in glaucoma. Apolipoproteins may have anti-inflammatory effects, enabling OHT patients to withstand inflammation and development of glaucoma despite high IOP.

A framework for quality control in quantitative proteomics

A thorough evaluation of the quality, reproducibility, and variability of bottom-up proteomics data is necessary at every stage of a workflow from planning to analysis. We share vignettes applying adaptable quality control (QC) measures to assess sample preparation, system function, and quantitative analysis. System suitability samples are repeatedly measured longitudinally with targeted methods, and we share examples where they are used on three instrument platforms to identify severe system failures and track function over months to years. Internal QCs incorporated at protein and peptide-level allow our team to assess sample preparation issues and to differentiate system failures from sample-specific issues. External QC samples prepared alongside our experimental samples are used to verify the consistency and quantitative potential of our results during batch correction and normalization before assessing biological phenotypes. We combine these controls with rapid analysis (Skyline), longitudinal QC metrics (AutoQC), and server-based data deposition (PanoramaWeb). We propose that this integrated approach to QC is a useful starting point for groups to facilitate rapid quality control assessment to ensure that valuable instrument time is used to collect the best quality data possible. Data are available on Panorama Public and on ProteomeXchange under the identifier PXD051318.

A Strategy to Characterize the Global Landscape of Histone Post-Translational Modifications Within Tissues of Nonmodel Organisms

Histone post-translational modifications (PTMs) are epigenetic marks that play a critical role in the expression and maintenance of DNA, but they remain largely uninvestigated in nonmodel organisms due to technical challenges. To begin alleviating this issue, we developed a workflow for histone PTM analysis in Mozambique tilapia (Oreochromis mossambicus), being a widespread and environmentally hardy fish, using mass spectrometry methods. By incorporating multiple protein digestion methods into the preparation of each sample, we reliably quantified 214 biologically relevant histone PTMs. All of these histone PTMs, collectively referred to as the global histone PTM landscape, were characterized in the gills, kidney, and testes of this fish. By comparing the global histone PTM landscape between the three tissues, we found that 91.59% of histone PTMs were tissue-dependent. The workflow and tools for histone PTM analysis described in this study are now publicly available and enable comprehensive investigation into the influence of environmental stress on histone PTMs in nonmodel organisms. Given the functionality and flexibility of histone PTMs, we anticipate that the study of histone PTMs in ecologically relevant contexts will provide ground-breaking insights into comparative physiology and evolution.

Improving Proteomic Identification Using Narrow Isolation Windows with Zeno SWATH Data-Independent Acquisition

Data-independent acquisition (DIA) techniques such as sequential window acquisition of all theoretical mass spectra (SWATH) acquisition have emerged as the preferred strategies for proteomic analyses. Our study optimized the SWATH-DIA method using a narrow isolation window placement approach, improving its proteomic performance. We optimized the acquisition parameter combinations of narrow isolation windows with different widths (1.9 and 2.9 Da) on a ZenoTOF 7600 (Sciex); the acquired data were analyzed using DIA-NN (version 1.8.1). Narrow SWATH (nSWATH) identified 5916 and 7719 protein groups on the digested peptides, corresponding to 400 ng of protein from mouse liver and HEK293T cells, respectively, improving identification by 7.52 and 4.99%, respectively, compared to conventional SWATH. The median coefficient of variation of the quantified values was less than 6%. We further analyzed 200 ng of benchmark samples comprising peptides from known ratios ofEscherichia coli, yeast, and human peptides using nSWATH. Consequently, it achieved accuracy and precision comparable to those of conventional SWATH, identifying an average of 95,456 precursors and 9342 protein groups across three benchmark samples, representing 12.6 and 9.63% improved identification compared to conventional SWATH. The nSWATH method improved identification at various loading amounts of benchmark samples, identifying 40.7% more protein groups at 25 ng. These results demonstrate the improved performance of nSWATH, contributing to the acquisition of deeper proteomic data from complex biological samples.

Gas-Phase Fractionation Data-Independent Acquisition Analysis of 3D Cocultured Spheroid Tumor Model Reveals Altered Translational Processes and Signaling Using Proteomics

Colorectal cancer (CRC) contains considerable heterogeneity; therefore, models of the disease must also reflect the multifarious components. Compared to traditional 2D models, 3D cellular models, such as tumor spheroids, have the utility to determine the drug efficacy of potential therapeutics. Monoculture spheroids are well-known to recapitulate gene expression, cell signaling, and pathophysiological gradients of avascularized tumors. However, they fail to mimic the stromal cell influence present in CRC, which is known to perturb drug efficacy and is associated with metastatic, late-stage colorectal cancer. This study seeks to develop a cocultured spheroid model using carcinoma and noncancerous fibroblast cells. We characterized the proteomic profile of cocultured spheroids in comparison to monocultured spheroids using data-independent acquisition with gas-phase fractionation. Specifically, we determined that proteomic differences related to translation and mTOR signaling are significantly increased in cocultured spheroids compared to monocultured spheroids. Proteins related to fibroblast function, such as exocytosis of coated vesicles and secretion of growth factors, were significantly differentially expressed in the cocultured spheroids. Finally, we compared the proteomic profiles of both the monocultured and cocultured spheroids against a publicly available data set derived from solid CRC tumors. We found that the proteome of the cocultured spheroids more closely resembles that of the patient samples, indicating their potential as tumor mimics.

Proteomic Analysis of Aqueous Humor in Central Retinal Artery Occlusion: Unveiling Novel Insights Into Disease Pathophysiology

Purpose

Central retinal artery occlusion (CRAO) is an ocular emergency that results from acute blockage of the blood supply to the retina and leads to a sudden vision loss. Other forms of ischemic retinopathies include diabetic retinopathy (DR), which involves chronic retinal ischemia and remains the leading cause of blindness in working-age adults. This study is the first to conduct a proteomic analysis of aqueous humor (AH) from patients with CRAO with a comparative analysis using vitreous humor (VH) samples from patients with DR.

Methods

AH samples were collected from 10 patients with CRAO undergoing paracentesis and 10 controls undergoing cataract surgery. VH samples were collected from 10 patients with DR and 10 non-diabetic controls undergoing pars plana vitrectomy (PPV). Samples were analyzed using mass spectrometry.

Results

Compared with controls, AH levels of 36 differentially expressed proteins (DEPs) were identified in patients with CRAO. Qiagen Ingenuity Pathway Analysis (IPA) revealed 11 proteins linked to ophthalmic diseases. Notably, enolase 2, a glycolysis enzyme isoform primarily expressed in neurons, was upregulated, suggesting neuronal injury and enzyme release. Additionally, clusterin, a protective glycoprotein, was downregulated. ELISA was conducted to confirm proteomics data. VH samples from patients with DR exhibited changes in a distinct set of proteins, including ones previously reported in the literature.

Conclusions

The study provides novel insights into CRAO pathophysiology with multiple hits identified. Proteomic results differed between DR and CRAO studies, likely due to the different pathophysiology and disease duration.

Translational Relevance

This is the first proteomic analysis of CRAO AH, with the potential to identify future therapeutic targets.

A conserved protein tyrosine phosphatase, PTPN-22, functions in diverse developmental processes in C. elegans

Protein tyrosine phosphatases non-receptor type (PTPNs) have been studied extensively in the context of the adaptive immune system; however, their roles beyond immunoregulation are less well explored. Here we identify novel functions for the conserved C. elegans phosphatase PTPN-22, establishing its role in nematode molting, cell adhesion, and cytoskeletal regulation. Through a non-biased genetic screen, we found that loss of PTPN-22 phosphatase activity suppressed molting defects caused by loss-of-function mutations in the conserved NIMA-related kinases NEKL-2 (human NEK8/NEK9) and NEKL-3 (human NEK6/NEK7), which act at the interface of membrane trafficking and actin regulation. To better understand the functions of PTPN-22, we carried out proximity labeling studies to identify candidate interactors of PTPN-22 during development. Through this approach we identified the CDC42 guanine-nucleotide exchange factor DNBP-1 (human DNMBP) as an in vivo partner of PTPN-22. Consistent with this interaction, loss of DNBP-1 also suppressed nekl-associated molting defects. Genetic analysis, co-localization studies, and proximity labeling revealed roles for PTPN-22 in several epidermal adhesion complexes, including C. elegans hemidesmosomes, suggesting that PTPN-22 plays a broad role in maintaining the structural integrity of tissues. Localization and proximity labeling also implicated PTPN-22 in functions connected to nucleocytoplasmic transport and mRNA regulation, particularly within the germline, as nearly one-third of proteins identified by PTPN-22 proximity labeling are known P granule components. Collectively, these studies highlight the utility of combined genetic and proteomic approaches for identifying novel gene functions.

Data acquisition approaches for single cell proteomics

Single-cell proteomics (SCP) aims to characterize the proteome of individual cells, providing insights into complex biological systems. It reveals subtle differences in distinct cellular populations that bulk proteome analysis may overlook, which is essential for understanding disease mechanisms and developing targeted therapies. Mass spectrometry (MS) methods in SCP allow the identification and quantification of thousands of proteins from individual cells. Two major challenges in SCP are the limited material in single-cell samples necessitating highly sensitive analytical techniques and the efficient processing of samples, as each biological sample requires thousands of single cell measurements. This review discusses MS advancements to mitigate these challenges using data-dependent acquisition (DDA) and data-independent acquisition (DIA). Additionally, we examine the use of short liquid chromatography gradients and sample multiplexing methods that increase the sample throughput and scalability of SCP experiments. We believe these methods will pave the way for improving our understanding of cellular heterogeneity and its implications for systems biology.

Data-Independent Acquisition: A Milestone and Prospect in Clinical Mass Spectrometry-Based Proteomics

Data-independent acquisition (DIA) has revolutionized the field of mass spectrometry (MS)-based proteomics over the past few years. DIA stands out for its ability to systematically sample all peptides in a given m/z range, allowing an unbiased acquisition of proteomics data. This greatly mitigates the issue of missing values and significantly enhances quantitative accuracy, precision, and reproducibility compared to many traditional methods. This review focuses on the critical role of DIA analysis software tools, primarily focusing on their capabilities and the challenges they address in proteomic research. Advances in MS technology, such as trapped ion mobility spectrometry, or high field asymmetric waveform ion mobility spectrometry require sophisticated analysis software capable of handling the increased data complexity and exploiting the full potential of DIA. We identify and critically evaluate leading software tools in the DIA landscape, discussing their unique features, and the reliability of their quantitative and qualitative outputs. We present the biological and clinical relevance of DIA-MS and discuss crucial publications that paved the way for in-depth proteomic characterization in patient-derived specimens. Furthermore, we provide a perspective on emerging trends in clinical applications and present upcoming challenges including standardization and certification of MS-based acquisition strategies in molecular diagnostics. While we emphasize the need for continuous development of software tools to keep pace with evolving technologies, we advise researchers against uncritically accepting the results from DIA software tools. Each tool may have its own biases, and some may not be as sensitive or reliable as others. Our overarching recommendation for both researchers and clinicians is to employ multiple DIA analysis tools, utilizing orthogonal analysis approaches to enhance the robustness and reliability of their findings.

Rapid assay development for low input targeted proteomics using a versatile linear ion trap

Advances in proteomics and mass spectrometry enable the study of limited cell populations, where high-mass accuracy instruments are typically required. While triple quadrupoles offer fast and sensitive low-mass accuracy measurements, these instruments are effectively restricted to targeted proteomics. Linear ion traps (LITs) offer a versatile, cost-effective alternative capable of both targeted and global proteomics. Here, we describe a workflow using a new hybrid quadrupole-LIT instrument that rapidly develops targeted proteomics assays from global data-independent acquisition (DIA) measurements without needing high-mass accuracy. Using an automated software approach for scheduling parallel reaction monitoring assays (PRM), we show consistent quantification across three orders of magnitude in a matched-matrix background. We demonstrate measuring low-level proteins such as transcription factors and cytokines with quantitative linearity below two orders of magnitude in a 1 ng background proteome without requiring stable isotope-labeled standards. From a 1 ng sample, we found clear consistency between proteins in subsets of CD4+ and CD8+ T cells measured using high dimensional flow cytometry and LIT-based proteomics. Based on these results, we believe hybrid quadrupole-LIT instruments represent an economical solution to democratizing mass spectrometry in a wide variety of laboratory settings.

Plasma prolactin axis shift from placental to pituitary origin in late prepartum mice

The placenta secretes a prolactin (PRL)-like hormone PRL3B1 (placental lactogen II), a luteotropic hormone essential for maintaining pregnancy until labor in mice. A report from 1984 examined the secretion pattern of PRL3B1 in prepartum mice. In the current study, we found contradictory findings in the secretion pattern that invalidate the previous report. By measuring maternal plasma PRL3B1 and PRL every 4 hrs from gestational day 17 (G17), we newly discovered that maternal plasma PRL3B1 levels decrease rapidly in prepartum C57BL/6 mice. Interestingly, the onset of this decline coincided with the PRL surge at G18, demonstrating a plasma prolactin axis shift from placental to pituitary origin. We also found that maternal plasma progesterone regression precedes the onset of the PRL shift. The level of Prl3b1 mRNA was determined by RT-qPCR in the placenta and remained stable until parturition, implying that PRL3B1 peptide production or secretion was suppressed. We hypothesized that production of the PRL family, the 25 paralogous PRL proteins exclusively expressed in mice placenta, would decrease alongside PRL3B1 during this period. To investigate this hypothesis and to seek proteomic changes, we performed a shotgun proteome analysis of the placental tissue using data-independent acquisition mass spectrometry (DIA-MS). Up to 5,891 proteins were identified, including 17 PRL family members. Relative quantitative analysis between embryonic day 17 (E17) and E18 placentas showed no significant difference in the expression of PRL3B1 and most PRL family members except PRL7C1. These results suggest that PRL3B1 secretion from the placenta is suppressed at G18 (E18).

Proteomic analysis of lung responses to SARS-CoV-2 infection in aged non-human primates: clinical and research relevance

With devastating health and socioeconomic impact worldwide, much work is left to understand the Coronavirus Disease 2019 (COVID-19), with emphasis in the severely affected elderly population. Here, we present a proteomics study of lung tissue obtained from aged vs. young rhesus macaques (Macaca mulatta) and olive baboons (Papio Anubis) infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Using age as a variable, we identified common proteomic profiles in the lungs of aged infected non-human primates (NHPs), including key regulators of immune function, as well as cell and tissue remodeling, and discuss the potential clinical relevance of such parameters. Further, we identified key differences in proteomic profiles between both NHP species, and compared those to what is known about SARS-CoV-2 in humans. Finally, we explored the translatability of these animal models in the context of aging and the human presentation of the COVID-19.

Multi-omics analysis of diabetic pig lungs reveals molecular derangements underlying pulmonary complications of diabetes mellitus

Growing evidence shows that the lung is an organ prone to injury by diabetes mellitus. However, the molecular mechanisms of these pulmonary complications have not yet been characterized comprehensively. To systematically study the effects of insulin deficiency and hyperglycaemia on the lung, we combined proteomics and lipidomics with quantitative histomorphological analyses to compare lung tissue samples from a clinically relevant pig model for mutant INS gene-induced diabetes of youth (MIDY) with samples from wild-type littermate controls. Among others, the level of pulmonary surfactant-associated protein A (SFTPA1), a biomarker of lung injury, was moderately elevated. Furthermore, key proteins related to humoral immune response and extracellular matrix organization were significantly altered in abundance. Importantly, a lipoxygenase pathway was dysregulated as indicated by 2.5-fold reduction of polyunsaturated fatty acid lipoxygenase ALOX15 levels, associated with corresponding changes in the levels of lipids influenced by this enzyme. Our multi-omics study points to an involvement of reduced ALOX15 levels and an associated lack of eicosanoid switching as mechanisms contributing to a proinflammatory milieu in the lungs of subjects with diabetes mellitus.

Calib-RT: an open source python package for peptide retention time calibration in DIA mass spectrometry data

MOTIVATION

The data independent acquisition (DIA) mass spectrometry (MS) method is increasingly popular in the field of proteomics. But the loss of the correspondence between peptide ions and their spectra in DIA makes the identification challenging. One effective approach to reduce false positive identification is to calculate the deviation between the peptide's estimated retention time (RT) and measured RT. During this process, scaling the spectral library RT into the estimated RT, known as the RT calibration, is a prerequisite for calculating the deviation. Currently, within the DIA algorithm ecosystem, there is a lack of engine-independent and readily usable RT calibration toolkits.

RESULTS

In this work, we introduce Calib-RT, a RT calibration method tailored to the characteristics of RT data. This method can achieve the nonlinear calibration across various data scales and tolerate a certain level of noise interference. Calib-RT is expected to enrich the open source DIA algorithm toolchain and assist in the development of DIA identification algorithms.

AVAILABILITY AND IMPLEMENTATION

Calib-RT is released as an open source software under the MIT license and can be installed from PyPi as a python module. The source code is available on GitHub at https://github.com/chenghui03/Calib_RT.

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.

Combining quantitative proteomics and interactomics for a deeper insight into molecular differences between human cell lines

Cellular functional pathways have evolved through selection based on fitness benefits conferred through protein intra- and inter-molecular interactions that comprise all protein conformational features and protein-protein interactions, collectively referred to as the interactome. While the interactome is regulated by proteome levels, it is also regulated independently by, post translational modification, co-factor, and ligand levels, as well as local protein environmental factors, such as osmolyte concentration, pH, ionic strength, temperature and others. In modern biomedical research, cultivatable cell lines have become an indispensable tool, with selection of optimal cell lines that exhibit specific functional profiles being critical for success in many cases. While it is clear that cell lines derived from different cell types have differential proteome levels, increased understanding of large-scale functional differences requires additional information beyond abundance level measurements, including how protein conformations and interactions are altered in certain cell types to shape functional landscapes. Here, we employed quantitative in vivo protein cross-linking coupled to mass spectrometry to probe large-scale protein conformational and interaction changes among three commonly employed human cell lines, HEK293, MCF-7, and HeLa cells. Isobaric quantitative Protein Interaction Reporter (iqPIR) technologies were used to obtain quantitative values of cross-linked peptides across three cell lines. These data illustrated highly reproducible (R2 values larger than 0.8 for all biological replicates) quantitative interactome levels across multiple biological replicates. We also measured protein abundance levels in these cells using data independent acquisition quantitative proteomics methods. Combining quantitative interactome and proteomics information allowed visualization of cell type-specific interactome changes mediated by proteome level adaptations as well as independently regulated interactome changes to gain deeper insight into possible drivers of these changes. Among the biggest detected alterations in protein interactions and conformations are changes in cytoskeletal proteins, RNA-binding proteins, chromatin remodeling complexes, mitochondrial proteins, and others. Overall, these data demonstrate the utility and reproducibility of quantitative cross-linking to study systems-level interactome variations. Moreover, these results illustrate how combined quantitative interactomics and proteomics can provide unique insight on cellular functional landscapes.

Intra-organ cell specific mitochondrial quantitative interactomics

Almost every organ consists of many cell types, each with its unique functions. Proteomes of these cell types are thus unique too. But it is reasonable to assume that interactome (inter and intra molecular interactions of proteins) are also distinct since protein interactions are what ultimately carry out the function. Podocytes and tubules are two cell types within kidney with vastly different functions: podocytes envelop the blood vessels in the glomerulus and act as filters while tubules are located downstream of the glomerulus and are responsible for reabsorption of important nutrients. It has been long known that for tubules mitochondria plays an important role as they require a lot of energy to carry out their functions. In podocytes, however, it has been assumed that mitochondria might not matter as much in both normal physiology and pathology1. Here we have applied quantitative cross-linking mass spectrometry to compare mitochondrial interactomes of tubules and podocytes using a transgenic mitochondrial tagging strategy to immunoprecipitate cell-specific mitochondria directly from whole kidney. We have uncovered that mitochondrial proteomes of these cell types are quite similar, although still showing unique features that correspond to known functions, such as high energy production through TCA cycle in tubules and requirements for detoxification in podocytes which are on the frontline of filtration where they encounter toxic compounds and therefore, as a non-renewing cell type they must have ways to protect themselves from cellular toxicity. But we gained much deeper insight with the interactomics data. We were able to find pathways differentially regulated in podocytes and tubules based on changing cross-link levels and not just protein levels. Among these pathways are betaine metabolism, lysine degradation, and many others. We have also demonstrated how quantitative interactomics could be used to detect different activity levels of an enzyme even when protein abundances of it are the same between cell types. We have validated this finding with an orthogonal activity assay. Overall, this work presents a new view of mitochondrial biology for two important, but functionally distinct, cell types within the mouse kidney showing both similarities and unique features. This data can continue to be explored to find new aspects of mitochondrial biology, especially in podocytes, where mitochondria has been understudied. In the future this methodology can also be applied to other organs to uncover differences in the function of cell types.

Development of highly multiplex targeted proteomics assays in biofluids using the Stellar mass spectrometer

The development of targeted assays that monitor biomedically relevant proteins is an important step in bridging discovery experiments to large scale clinical studies. Targeted assays are currently unable to scale to hundreds or thousands of targets. We demonstrate the generation of large-scale assays using a novel hybrid nominal mass instrument. The scale of these assays is achievable with the Stellar™ mass spectrometer through the accommodation of shifting retention times by real-time alignment, while being sensitive and fast enough to handle many concurrent targets. Assays were constructed using precursor information from gas-phase fractionated (GPF) data-independent acquisition (DIA). We demonstrate the ability to schedule methods from an orbitrap and linear ion trap acquired GPF DIA library and compare the quantification of a matrix-matched calibration curve from orbitrap DIA and linear ion trap parallel reaction monitoring (PRM). Two applications of these proposed workflows are shown with a cerebrospinal fluid (CSF) neurodegenerative disease protein PRM assay and with a Mag-Net enriched plasma extracellular vesicle (EV) protein survey PRM assay.

Obstructive sleep apnea syndrome attenuated high-density lipoprotein function

BACKGROUND

Obstructive sleep apnea (OSA) is associated with an increased risk of cardiovascular disease. High-density lipoproteins (HDLs) exert anti-atherogenic effects, even on cholesterol efflux capacity (CEC). The HDL proteome is reportedly altered in patients with coronary artery disease.

OBJECTIVE

We hypothesized that OSA attenuates HDL function through an altered HDL proteome, which could be alleviated by continuous positive airway pressure (CPAP) therapy.

METHODS

Patients aged ≥20 years (n = 115) with suspected OSA were enrolled in this cross-sectional study, with 34 patients diagnosed with moderate and severe OSA included in the interventional study and treated with CPAP therapy for 12 weeks. To further investigate the HDL proteome in OSA, we conducted a discovery study by analyzing HDL proteomes in 10 patients.

RESULTS

In this study, CEC was significantly lower in the sleep apnea syndrome (SAS) group (apnea-hypopnea index [AHI] ≥5) than in the non-SAS group (AHI <5; 0.96 ± 0.14 vs. 1.06 ± 0.15, p = 0.01). Multiple regression analysis revealed that minimal pulse oxygen saturation (MinSpO2) was positively correlated with CEC. In the interventional study, a 12-week CPAP therapy did not affect CEC. We identified orosomucoid 1 (ORM1), an acute-phase inflammatory molecule, as a candidate protein for OSA-induced HDL dysfunction. Further validation study revealed that serum ORM1 levels were inversely associated with CEC, independent of HDL-cholesterol and high-sensitivity C-reactive protein.

CONCLUSIONS

HDL function was impaired in patients with OSA and a reduced CEC. However, CPAP therapy did not affect CEC. An altered HDL proteome, particularly with increased ORM1 levels, may be associated with impaired HDL function.

TRIAL REGISTRATION

This clinical study was registered with the University Hospital Medical Information Network Clinical Trials Registry (UMIN000025335 and UMIN000025341).

Evaluation of Protein Identification and Quantification by the diaPASEF Method on timsTOF SCP

Accurate and precise quantification is crucial in modern proteomics, particularly in the context of exploring low-amount samples. While the innovative 4D-data-independent acquisition (DIA) quantitative proteomics facilitated by timsTOF mass spectrometers gives enhanced sensitivity and selectivity for protein identification, the diaPASEF (parallel accumulation-serial fragmentation combined with data-independent acquisition) parameters have not been systematically optimized, and a comprehensive evaluation of the quantification is currently lacking. In this study, we conducted a thorough optimization of key parameters on a timsTOF SCP instrument, including sample loading amount (50 ng), ramp/accumulation time (140 ms), isolation window width (20 m/z), and gradient time (60 min). To further improve the identification of proteins in low-amount samples, we utilized different column settings and introduced 0.02% n-dodecyl-β-d-maltoside (DDM) in the sample reconstitution solution, resulting in a remarkable 19-fold increase in protein identification at the single-cell-equivalent level. Moreover, a comprehensive comparison of protein quantification using a tandem mass tag reporter (TMT-reporter), complement TMT ions (TMTc), and diaPASEF revealed a strong correlation between these methods. Both diaPASEF and TMTc have effectively addressed the issue of ratio compression, highlighting the diaPASEF method's effectiveness in achieving accurate quantification data compared to TMT reporter quantification. Additionally, an in-depth analysis of in-group variation positioned diaPASEF between the TMT-reporter and TMTc methods. Therefore, diaPASEF quantification on the timsTOF SCP instrument emerges as a precise and accurate methodology for quantitative proteomics, especially for samples with small amounts.

Quantitative proteomic analysis reveals unique Hsp90 cycle-dependent client interactions

Hsp90 is an abundant and essential molecular chaperone that mediates the folding and activation of client proteins in a nucleotide-dependent cycle. Hsp90 inhibition directly or indirectly impacts the function of 10-15% of all proteins due to degradation of client proteins or indirect downstream effects. Due to its role in chaperoning oncogenic proteins, Hsp90 is an important drug target. However, compounds that occupy the ATP-binding pocket and broadly inhibit function have not achieved widespread use due to negative effects. More selective inhibitors are needed; however, it is unclear how to achieve selective inhibition. We conducted a quantitative proteomic analysis of soluble proteins in yeast strains expressing wild-type Hsp90 or mutants that disrupt different steps in the client folding pathway. Out of 2,482 proteins in our sample set (approximately 38% of yeast proteins), we observed statistically significant changes in abundance of 350 (14%) of those proteins (log2 fold change ≥ 1.5). Of these, 257/350 (∼73%) with the strongest differences in abundance were previously connected to Hsp90 function. Principal component analysis of the entire dataset revealed that the effects of the mutants could be separated into 3 primary clusters. As evidence that Hsp90 mutants affect different pools of clients, simultaneous co-expression of 2 mutants in different clusters restored wild-type growth. Our data suggest that the ability of Hsp90 to sample a wide range of conformations allows the chaperone to mediate folding of a broad array of clients and that disruption of conformational flexibility results in client defects dependent on those states.

Assessment of false discovery rate control in tandem mass spectrometry analysis using entrapment

A pressing statistical challenge in the field of mass spectrometry proteomics is how to assess whether a given software tool provides accurate error control. Each software tool for searching such data uses its own internally implemented methodology for reporting and controlling the error. Many of these software tools are closed source, with incompletely documented methodology, and the strategies for validating the error are inconsistent across tools. In this work, we identify three different methods for validating false discovery rate (FDR) control in use in the field, one of which is invalid, one of which can only provide a lower bound rather than an upper bound, and one of which is valid but under-powered. The result is that the field has a very poor understanding of how well we are doing with respect to FDR control, particularly for the analysis of data-independent acquisition (DIA) data. We therefore propose a new, more powerful method for evaluating FDR control in this setting, and we then employ that method, along with an existing lower bounding technique, to characterize a variety of popular search tools. We find that the search tools for analysis of data-dependent acquisition (DDA) data generally seem to control the FDR at the peptide level, whereas none of the DIA search tools consistently controls the FDR at the peptide level across all the datasets we investigated. Furthermore, this problem becomes much worse when the latter tools are evaluated at the protein level. These results may have significant implications for various downstream analyses, since proper FDR control has the potential to reduce noise in discovery lists and thereby boost statistical power.

HIV infection impairs the host response to Mycobacterium tuberculosis infection by altering surfactant protein D function in the human lung alveolar mucosa

Tuberculosis is the leading cause of death for people living with HIV (PLWH). We hypothesized that altered functions of innate immune components in the human alveolar lining fluid of PLWH (HIV-ALF) drive susceptibility to Mycobacterium tuberculosis (M.tb) infection. Our results indicate a significant increase in oxidation of innate proteins and chemokine levels and significantly lower levels and function of complement components and Th1/Th2/Th17 cytokines in HIV-ALF versus control-ALF (non-HIV-infected people). We further found a deficiency of surfactant protein D (SP-D) and reduced binding of SP-D to M.tb that had been exposed to HIV-ALF. Primary human macrophages infected with M.tb exposed to HIV-ALF were significantly less capable of controlling the infection, which was reversed by SP-D replenishment in HIV-ALF. Thus, based on the limited number of participants in this study, our data suggest that PLWH without antiretroviral therapy (ART) have declining host innate defense function in their lung mucosa, thereby favoring M.tb and potentially other pulmonary infections.

A workflow for targeted proteomics assay development using a versatile linear ion trap

Advances in proteomics and mass spectrometry have enabled the study of limited cell populations, such as single-cell proteomics, where high-mass accuracy instruments are typically required. While triple quadrupoles offer fast and sensitive nominal resolution measurements, these instruments are effectively limited to targeted proteomics. Linear ion traps (LITs) offer a versatile, cost-effective alternative capable of both targeted and global proteomics. We demonstrate a workflow using a newly released, hybrid quadrupole-LIT instrument for developing targeted proteomics assays from global data-independent acquisition (DIA) measurements without needing high-mass accuracy. Gas-phase fraction-based DIA enables rapid target library generation in the same background chemical matrix as each quantitative injection. Using a new software tool embedded within EncyclopeDIA for scheduling parallel reaction monitoring assays, we show consistent quantification across three orders of magnitude of input material. Using this approach, we demonstrate measuring peptide quantitative linearity down to 25x dilution in a background of only a 1 ng proteome without requiring stable isotope labeled standards. At 1 ng total protein on column, we found clear consistency between immune cell populations measured using flow cytometry and immune markers measured using LIT-based proteomics. We believe hybrid quadrupole-LIT instruments represent an economic solution to democratizing mass spectrometry in a wide variety of laboratory settings.

Proteomic analysis of sperm from fertile stallions and subfertile stallions due to impaired acrosomal exocytosis

Thoroughbred stallions that carry a double-homozygous genotype A/A-A/A for SNPs rs397316122 and rs69101140 in exon 5 of the FKBP6 gene (chr13; EquCab3.0) are uniquely subfertile due to impaired acrosomal exocytosis (IAE). In this study, the sperm proteome in frozen/thawed semen from subfertile Thoroughbred stallions was studied and compared to that of frozen/thawed sperm from fertile Thoroughbred stallions. A total of 2,220 proteins was identified, of which 140 proteins were found to be differentially abundant in sperm from the subfertile stallions compared to that of fertile stallions (83 less and 57 more abundant). Proteins of differential abundance in sperm from the subfertile stallions were mainly overrepresented in the "metabolism" and the "metabolism of lipids" pathways. One of these proteins, arylsulfatase F (ARSF), was studied by immunofluorescence. A lower proportion of sperm displaying ARSF signal at the acrosome region was observed in sperm from subfertile Thoroughbred stallions. In addition, heterologous zona pellucida binding assays revealed that sperm from subfertile Thoroughbred stallions bound at a lower proportion to zonae pellucidae than sperm from fertile Thoroughbred stallions. In conclusion, a group of differential abundance proteins, including some of acrosome origin, were identified in sperm from subfertile stallions with acrosome dysfunction.

diaTracer enables spectrum-centric analysis of diaPASEF proteomics data

Data-independent acquisition (DIA) has become a widely used strategy for peptide and protein quantification in mass spectrometry-based proteomics studies. The integration of ion mobility separation into DIA analysis, such as the diaPASEF technology available on Bruker's timsTOF platform, further improves the quantification accuracy and protein depth achievable using DIA. We introduce diaTracer, a new spectrum-centric computational tool optimized for diaPASEF data. diaTracer performs three-dimensional (m/z, retention time, ion mobility) peak tracing and feature detection to generate precursor-resolved "pseudo-MS/MS" spectra, facilitating direct ("spectral-library free") peptide identification and quantification from diaPASEF data. diaTracer is available as a stand-alone tool and is fully integrated into the widely used FragPipe computational platform. We demonstrate the performance of diaTracer and FragPipe using diaPASEF data from cerebrospinal fluid (CSF) and plasma samples, data from phosphoproteomics and HLA immunopeptidomics experiments, and low-input data from a spatial proteomics study. We also show that diaTracer enables unrestricted identification of post-translational modifications from diaPASEF data using open/mass offset searches.

Data Independent Acquisition to Inform the Development of Targeted Proteomics Assays Using a Triple Quadrupole Mass Spectrometer

Mass spectrometry based targeted proteomics methods provide sensitive and high-throughput analysis of selected proteins. To develop a targeted bottom-up proteomics assay, peptides must be evaluated as proxies for the measurement of a protein or proteoform in a biological matrix. Candidate peptide selection typically relies on predetermined biochemical properties, data from semi-stochastic sampling, or by empirical measurements. These strategies require extensive testing and method refinement due to the difficulties associated with prediction of peptide response in the biological matrix of interest. Gas-phase fractionated (GPF) narrow window data-independent acquisition (DIA) aids in the development of reproducible selected reaction monitoring (SRM) assays by providing matrix-specific information on peptide detectability and quantification by mass spectrometry. To demonstrate the suitability of DIA data for selecting peptide targets, we reimplement a portion of an existing assay to measure 98 Alzheimer's disease proteins in cerebrospinal fluid (CSF). Peptides were selected from GPF-DIA based on signal intensity and reproducibility. The resulting SRM assay exhibits similar quantitative precision to published data, despite the inclusion of different peptides between the assays. This workflow enables development of new assays without additional up-front data acquisition, demonstrated here through generation of a separate assay for an unrelated set of proteins in CSF from the same dataset.

Mapping adipocyte interactome networks by HaloTag-enrichment-mass spectrometry

Mapping protein interaction complexes in their natural state in vivo is arguably the Holy Grail of protein network analysis. Detection of protein interaction stoichiometry has been an important technical challenge, as few studies have focused on this. This may, however, be solved by artificial intelligence (AI) and proteomics. Here, we describe the development of HaloTag-based affinity purification mass spectrometry (HaloMS), a high-throughput HaloMS assay for protein interaction discovery. The approach enables the rapid capture of newly expressed proteins, eliminating tedious conventional one-by-one assays. As a proof-of-principle, we used HaloMS to evaluate the protein complex interactions of 17 regulatory proteins in human adipocytes. The adipocyte interactome network was validated using an in vitro pull-down assay and AI-based prediction tools. Applying HaloMS to probe adipocyte differentiation facilitated the identification of previously unknown transcription factor (TF)-protein complexes, revealing proteome-wide human adipocyte TF networks and shedding light on how different pathways are integrated.

Phosphoproteomic analysis of APP/PS1 mice of Alzheimer's disease by DIA based mass spectrometry analysis with PRM verification

Traditional Chinese medicine has been utilized in China for approximately thousands of years in clinical settings to prevent Alzheimer's disease (AD) and enhance memory, despite the lack of a systematic exploration of its biological underpinnings. Exciting research has corroborated the beneficial effects of tetrahydroxy stilbene glycoside (TSG), an extract derived from Polygonum multiflorum, in delaying learning and memory impairment in a model that mimics AD. Therefore, the primary objective of this study is to investigate the major function of TSG upon protein regulation in AD. Herein, a novel approach, encompassing data independent acquisition (DIA), DIA phosphorylated proteomics, and parallel reaction monitoring (PRM), was utilized to integrate quantitative proteomic data collected from APP/PS1 mouse model exhibiting toxic intracellular aggregation of Aβ. Initially, we deliberated upon both single and multi-dimensional data pertaining to AD model mice. Furthermore, we authenticated disparities in protein phosphorylation quantity and expression, phosphorylation function, and ultimately phosphorylation kinase analysis. In order to validate the results, we utilized PRM ion monitoring technology to identify potential protein or peptide biomarkers. In the mixed samples, targeted detection of 50 target proteins revealed that 26 to 33 target proteins were stably detected by PRM. In summary, our findings provide new candidates for AD biomarker, which have been identified and validated through protein researches conducted on mouse brains. This offers a wealth of potential resources for extensive biomarker validation in neurodegenerative diseases. SIGNIFICANCE: DIA phosphorylated proteomics technique was used to detect and analyze phosphorylated proteins in brain tissues of mice with AD. Data were analyzed by various bioinformatics tools to explore the phosphorylation events and characterize them related to TSG. The results of DIA were further verified by PRM. Besides, we mapped the major metabolite classes emerging from the analyses to key biological pathways implicated in AD to understand the potential roles of the molecules and the interactions in triggering symptom onset and progression of AD. Meanwhile, we clarified that in the context of AD onset and TSG intervention, the changes in proteins, protein phosphorylation, phosphorylation kinases, and the internal connections.

Comprehensive Prostate Fluid-Based Spectral Libraries for Enhanced Protein Detection in Urine

Biofluids contain molecules in circulation and from nearby organs that can be indicative of disease states. Characterizing the proteome of biofluids with DIA-MS is an emerging area of interest for biomarker discovery; yet, there is limited consensus on DIA-MS data analysis approaches for analyzing large numbers of biofluids. To evaluate various DIA-MS workflows, we collected urine from a clinically heterogeneous cohort of prostate cancer patients and acquired data in DDA and DIA scan modes. We then searched the DIA data against urine spectral libraries generated using common library generation approaches or a library-free method. We show that DIA-MS doubles the sample throughput compared to standard DDA-MS with minimal losses to peptide detection. We further demonstrate that using a sample-specific spectral library generated from individual urines maximizes peptide detection compared to a library-free approach, a pan-human library, or libraries generated from pooled, fractionated urines. Adding urine subproteomes, such as the urinary extracellular vesicular proteome, to the urine spectral library further improves the detection of prostate proteins in unfractionated urine. Altogether, we present an optimized DIA-MS workflow and provide several high-quality, comprehensive prostate cancer urine spectral libraries that can streamline future biomarker discovery studies of prostate cancer using DIA-MS.

Integrative multi-omics characterization of hepatocellular carcinoma in Hispanic patients

Background

The incidence and mortality rates of hepatocellular carcinoma (HCC) among Hispanics in the United States are much higher than those of non-Hispanic whites. We conducted comprehensive multi-omics analyses to understand molecular alterations in HCC among Hispanic patients.

Methods

Paired tumor and adjacent non-tumor samples were collected from 31 Hispanic HCC in South Texas (STX-Hispanic) for genomic, transcriptomic, proteomic, and metabolomic profiling. Additionally, serum lipids were profiled in 40 Hispanic and non-Hispanic patients with or without clinically diagnosed HCC.

Results

Exome sequencing revealed high mutation frequencies of AXIN2 and CTNNB1 in STX Hispanic HCCs, suggesting a predominant activation of the Wnt/β-catenin pathway. The TERT promoter mutation frequency was also remarkably high in the Hispanic cohort. Cell cycles and liver functions were identified as positively- and negatively-enriched, respectively, with gene set enrichment analysis. Gene sets representing specific liver metabolic pathways were associated with dysregulation of corresponding metabolites. Negative enrichment of liver adipogenesis and lipid metabolism corroborated with a significant reduction in most lipids in the serum samples of HCC patients. Two HCC subtypes from our Hispanic cohort were identified and validated with the TCGA liver cancer cohort. The subtype with better overall survival showed higher activity of immune and angiogenesis signatures, and lower activity of liver function-related gene signatures. It also had higher levels of immune checkpoint and immune exhaustion markers.

Conclusions

Our study revealed some specific molecular features of Hispanic HCC and potential biomarkers for therapeutic management of HCC and provides a unique resource for studying Hispanic HCC.

MassDash: A Web-Based Dashboard for Data-Independent Acquisition Mass Spectrometry Visualization

With the increased usage and diversity of methods and instruments being applied to analyze Data-Independent Acquisition (DIA) data, visualization is becoming increasingly important to validate automated software results. Here we present MassDash, a cross-platform DIA mass spectrometry visualization and validation software for comparing features and results across popular tools. MassDash provides a web-based interface and Python package for interactive feature visualizations and summary report plots across multiple automated DIA feature detection tools, including OpenSwath, DIA-NN, and dreamDIA. Furthermore, MassDash processes peptides on the fly, enabling interactive visualization of peptides across dozens of runs simultaneously on a personal computer. MassDash supports various multidimensional visualizations across retention time, ion mobility, m/z, and intensity, providing additional insights into the data. The modular framework is easily extendable, enabling rapid algorithm development of novel peak-picker techniques, such as deep-learning-based approaches and refinement of existing tools. MassDash is open-source under a BSD 3-Clause license and freely available at https://github.com/Roestlab/massdash, and a demo version can be accessed at https://massdash.streamlit.app.

Interactome dynamics during heat stress signal transmission and reception

Among evolved molecular mechanisms, cellular stress response to altered environmental conditions to promote survival is among the most fundamental. The presence of stress-induced unfolded or misfolded proteins and molecular registration of these events constitute early steps in cellular stress response. However, what stress-induced changes in protein conformations and protein-protein interactions within cells initiate stress response and how these features are recognized by cellular systems are questions that have remained difficult to answer, requiring new approaches. Quantitative in vivo chemical cross-linking coupled with mass spectrometry (qXL-MS) is an emerging technology that provides new insight on protein conformations, protein-protein interactions and how the interactome changes during perturbation within cells, organelles, and even tissues. In this work, qXL-MS and quantitative proteome analyses were applied to identify significant time-dependent interactome changes that occur prior to large-scale proteome abundance remodeling within cells subjected to heat stress. Interactome changes were identified within minutes of applied heat stress, including stress-induced changes in chaperone systems as expected due to altered functional demand. However, global analysis of all interactome changes revealed the largest significant enrichment in the gene ontology molecular function term of RNA binding. This group included more than 100 proteins among multiple components of protein synthesis machinery, including mRNA binding, spliceosomes, and ribosomes. These interactome data provide new conformational insight on the complex relationship that exists between transcription, translation and cellular stress response mechanisms. Moreover, stress-dependent interactome changes suggest that in addition to conformational stabilization of RNA-binding proteins, adaptation of RNA as interacting ligands offers an additional fitness benefit resultant from generally lower RNA thermal stability. As such, RNA ligands also serve as fundamental temperature sensors that signal stress through decreased conformational regulation of their protein partners as was observed in these interactome dynamics.