Longitudinal analysis of the lung proteome reveals persistent repair months after mild to moderate COVID-19.

In order to assess homeostatic mechanisms in the lung after COVID-19, changes in the protein signature of bronchoalveolar lavage from 45 patients with mild to moderate disease at three phases (acute, recovery, and convalescent) are evaluated over a year. During the acute phase, inflamed and uninflamed phenotypes are characterized by the expression of tissue repair and host defense response molecules. With recovery, inflammatory and fibrogenic mediators decline and clinical symptoms abate. However, at 9 months, quantified radiographic abnormalities resolve in the majority of patients, and yet compared to healthy persons, all showed ongoing activation of cellular repair processes and depression of the renin-kallikrein-kinin, coagulation, and complement systems. This dissociation of prolonged reparative processes from symptom and radiographic resolution suggests that occult ongoing disruption of the lung proteome is underrecognized and may be relevant to recovery from other serious viral pneumonias.

Use of data-independent acquisition mass spectrometry to identify an objective serum indicator of the need for osteoporotic therapeutic intervention.

Osteoporosis is characterized by weakened bone microstructure and loss of bone mass. Current diagnostic criteria for osteoporosis are based on the T-score, which is a measure of bone mineral density. However, osteoporotic fragility fractures can occur regardless of the T-score, underscoring the need for additional criteria for the early detection of patients at fracture risk. To identify indicators of reduced bone strength, we performed serum proteomic analysis using data-independent acquisition mass spectrometry with serum samples from two patient groups, one with osteoporosis but no fractures and the other with osteopenia and fragility fractures. Collective evaluation of the results identified six serum proteins that changed to a similar extent in both patient groups compared with controls. Of these, extracellular matrix protein 1 (ECM1), which contributes to bone formation, showed the most significant increase in serum levels in both patient groups. An ELISA-based assay suggested that ECM1 could serve as a serum indicator of the need for therapeutic intervention; however, further prospective studies with a larger sample size are necessary to confirm these results. The present findings may contribute to the provision of early and appropriate therapeutic strategies for patients at risk of osteoporotic fractures. SIGNIFICANCE: This study aimed to identify objective serum indicators of the need for therapeutic intervention in individuals at risk of osteoporotic fracture. Comprehensive proteome analyses of serum collected from patients with osteoporosis but no fractures, patients with osteopenia and fragility fractures, and controls were performed by data-independent acquisition mass spectrometry. Collective evaluation of the proteome analysis data and ELISA-based assays identified serum ECM1 as a potential objective marker of the risk of fragility fractures in patients with osteoporosis or osteopenia. The findings are an important step toward the development of appropriate bone health management methods to improve well-being and maintain quality of life.

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, Aß1-42, Aß1-40, T-Tau, p-Tau, VEGF, TGF-ß, IL-1ß, 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.

Data-Independent Acquisition Mass Spectrometry Analysis of FFPE Rectal Cancer Samples Offers In-Depth Proteomics Characterization of the Response to Neoadjuvant Chemoradiotherapy.

Locally advanced rectal cancer (LARC) presents a challenge in identifying molecular markers linked to the response to neoadjuvant chemoradiotherapy (nCRT). This study aimed to utilize a sensitive proteomic method, data-independent mass spectrometry (DIA-MS), to extensively analyze the LARC proteome, seeking individuals with favorable initial responses suitable for a watch-and-wait approach. This research addresses the unmet need to understand the response to treatment, potentially guiding personalized strategies for LARC patients. Post-treatment assessment included MRI scans and proctoscopy. This research involved 97 LARC patients treated with intense chemoradiotherapy, comprising radiation and chemotherapy. Out of 97 LARC included in this study, we selected 20 samples with the most different responses to nCRT for proteome profiling (responders vs. non-responders). This proteomic approach shows extensive proteome coverage in LARC samples. The analysis identified a significant number of proteins compared to a prior study. A total of 915 proteins exhibited differential expression between the two groups, with certain signaling pathways associated with response mechanisms, while top candidates had good predictive potential. Proteins encoded by genes SMPDL3A, PCTP, LGMN, SYNJ2, NHLRC3, GLB1, and RAB43 showed high predictive potential of unfavorable treatment outcome, while RPA2, SARNP, PCBP2, SF3B2, HNRNPF, RBBP4, MAGOHB, DUT, ERG28, and BUB3 were good predictive biomarkers of favorable treatment outcome. The identified proteins and related biological processes provide promising insights that could enhance the management and care of LARC patients.

Identification of gravity-responsive proteins in the femur of spaceflight mice using a quantitative proteomic approach.

Although the microgravity (µ-g) environment that astronauts encounter during spaceflight can cause severe acute bone loss, the molecular mechanism of this bone loss remains unclear. To investigate the gravity-response proteins involved in bone metabolism, it is important to comprehensively determine which proteins exhibit differential abundance associated with mechanical stimuli. However, comprehensive proteomic analysis using small bone samples is difficult because protein extraction in mineralized bone tissue is inefficient. Here, we established a high-sensitivity analysis system for mouse bone proteins using data-independent acquisition mass spectrometry. This system successfully detected 40 proteins in the femoral diaphysis showing differential abundance between mice raised in a µ-g environment, where the bone mass was reduced by gravity unloading, and mice raised in an artificial 1-gravity environment on the International Space Station. Additionally, 22 proteins, including noncollagenous bone matrix proteins, showed similar abundance between the two groups in the mandible, where bone mass was unaltered due to mastication stimuli, suggesting that these proteins are responsive to mechanical stimuli. One of these proteins, SPARCL1, is suggested to promote osteoclastogenesis induced by receptor activator of nuclear factor-κB ligand. We expect these findings to lead to new insights into the mechanisms of bone metabolism induced by mechanical stimuli. SIGNIFICANCE: We aimed to investigate the gravity-response proteins involved in bone metabolism. To this end, we established a comprehensive analysis system for mouse bone proteins using data-independent acquisition mass spectrometry, which is particularly useful in comprehensively analyzing the bone proteome using small sample volumes. In addition, a comprehensive proteomic analysis of the femoral diaphysis and mandible, which exhibit different degrees of bone loss in mice raised on the International Space Station, identified proteins that respond to mechanical stimuli. SPARCL1, a mechanical stimulus-responsive protein, was consequently suggested to be involved in osteoclast differentiation associated with bone remodeling. Our findings represent an important step toward elucidating the molecular mechanism of bone metabolism induced by mechanical stimuli.

Advanced mass spectrometry workflows for accurate quantification of trace-level host cell proteins in drug products: Benefits of FAIMS separation and gas-phase fractionation DIA.

Therapeutic monoclonal antibodies (mAb) production relies on multiple purification steps before release as a drug product (DP). A few host cell proteins (HCPs) may co-purify with the mAb. Their monitoring is crucial due to the considerable risk they represent for mAb stability, integrity, and efficacy and their potential immunogenicity. Enzyme-linked immunosorbent assays (ELISA) commonly used for global HCP monitoring present limitations in terms of identification and quantification of individual HCPs. Therefore, liquid chromatography tandem mass spectrometry (LC-MS/MS) has emerged as a promising alternative. Challenging DP samples show an extreme dynamic range requiring high performing methods to detect and reliably quantify trace-level HCPs. Here, we investigated the benefits of adding high-field asymmetric ion mobility spectrometry (FAIMS) separation and gas phase fractionation (GPF) prior to data independent acquisition (DIA). FAIMS LC-MS/MS analysis allowed the identification of 221 HCPs among which 158 were reliably quantified for a global amount of 880 ng/mg of NIST mAb Reference Material. Our methods have also been successfully applied to two FDA/EMA approved DPs and allowed digging deeper into the HCP landscape with the identification and quantification of a few tens of HCPs with sensitivity down to the sub-ng/mg of mAb level.

In-depth proteomic analysis of juvenile dermatomyositis serum reveals protein expression associated with muscle-specific autoantibodies.

OBJECTIVES: The clinical symptoms and complications of JDM differ depending on the type of muscle-specific autoantibodies (MSAs) present. We aimed to identify protein expression profiles specific for MSAs that characterize various clinical features by comprehensively analyzing the proteins present in the serum of patients with JDM. METHODS: We analysed sera from patients with JDM that were positive for anti-melanoma differentiation-associated protein 5 (MDA5) antibodies (n = 5), anti-nuclear matrix protein 2 (NXP2) antibodies (n = 5) and anti-transcriptional intermediary factor 1 alpha or gamma subunit (TIF1-γ) antibodies (n = 5), and evaluated healthy controls (n = 5) via single-shot liquid chromatography-tandem mass spectrometry (MS) in data-independent acquisition mode, which is superior for comparative quantitative analysis. We identified different protein groups based on MSAs and performed pathway analysis to understand their characteristics. RESULTS: We detected 2413 proteins from serum MS analysis; 508 proteins were commonly altered in MSAs, including many myogenic enzymes and IFN-regulated proteins. Pathway analysis using the top 50 proteins that were upregulated in each MSA group revealed that the type I IFN and proteasome pathways were significantly upregulated in the anti-MDA5 antibody group alone. CONCLUSION: Although JDM serum contains many proteins commonly altered in MSAs, the pathways associated with clinical features of MSAs differ based on protein accumulation. In-depth serum protein profiles associated with MSAs may be useful for developing therapeutic target molecules and biomarkers.

Quantitative Proteomics for the Development and Manufacturing of Human-Induced Pluripotent Stem Cell-Derived Neural Stem Cells Using Data-Independent Acquisition Mass Spectrometry.

Human-induced pluripotent stem cell (iPSC)-derived neural stem cells (NSCs) have several potential applications in regenerative medicine. A deep understanding of stem cell characteristics is critical for developing appropriate products for use in the clinic. This study aimed to develop approaches for characterizing iPSC-derived NSCs. Data-independent acquisition mass spectrometry (DIA-MS) was used to obtain temporal proteomic profiles of differentiating cells. Principal component analysis of the proteome profiles allowed for the discrimination of cells cultured for different periods. Cells were characterized by Gene Ontology analysis to annotate the upregulated proteins based on their functions. We found that trophoblast glycoprotein (TPBG), a membrane glycoprotein that inhibits the Wnt/ß-catenin pathway, was elevated in NSC and that silencing TPBG promoted proliferation rather than neuronal differentiation. Treatment with Wnt/ß-catenin pathway activators and inhibitors showed that modulating the Wnt/ß-catenin pathway is crucial for differentiation into NSC. These results suggest that the level of TPBG is critical for differentiation into NSC, and TPBG is a potentially critical quality attribute of differentiating cells. In summary, DIA-MS-based proteomics is a promising multi-attribute method for characterizing stem cell-derived products.

Identification of thrombotic biomarkers in orthopedic surgery patients by plasma proteomics.

BACKGROUND: Due to the poor specificity of D-dimer, more accurate thrombus biomarkers are clinically needed to improve the diagnostic power of VTE. METHODS: The plasma samples were classified into low-risk group (n = 6) and high-risk group (n = 6) according to the Caprini Thrombosis Risk Assessment Scale score. Data-independent acquisition mass spectrometry (DIA-MS) was performed to identify the proteins in the 12 plasma samples. Bioinformatics analysis including volcano plot, heatmap, KEGG pathways and chord diagram analysis were drawn to analyze the significantly differentially expressed proteins (DEPs) between the two groups. Then, another 26 plasma samples were collected to verify the key proteins as potential biomarkers of VTE in orthopedic surgery patients. RESULTS: A total of 371 proteins were identified by DIA-MS in 12 plasma samples. Volcano plotting showed that there were 30 DEPs. KEGG pathway enrichment analysis revealed that the DEPs were majorly involved in the blood coagulation pathway. The chord diagram analysis demonstrated that proteins SAA1, VWF, FLNA, ACTB, VINC, F13B, F13A and IPSP in the DEPs were significantly related to blood coagulation. VWF and F13B were selected for validation experiments. ELISA test showed that, as compared with those in the low-risk group, the level of VWF in the high-risk sera was significantly increased. CONCLUSIONS: The level of VWF in the high-risk group of thrombosis after orthopedic surgery was significantly higher than that in the low-risk group of preoperative thrombosis, suggesting that VWF may be used as a potential thrombus biomarker in orthopedic surgery patients.

Triqler for Protein Summarization of Data from Data-Independent Acquisition Mass Spectrometry.

A frequent goal, or subgoal, when processing data from a quantitative shotgun proteomics experiment is a list of proteins that are differentially abundant under the examined experimental conditions. Unfortunately, obtaining such a list is a challenging process, as the mass spectrometer analyzes the proteolytic peptides of a protein rather than the proteins themselves. We have previously designed a Bayesian hierarchical probabilistic model, Triqler, for combining peptide identification and quantification errors into probabilities of proteins being differentially abundant. However, the model was developed for data from data-dependent acquisition. Here, we show that Triqler is also compatible with data-independent acquisition data after applying minor alterations for the missing value distribution. Furthermore, we find that it has better performance than a set of compared state-of-the-art protein summarization tools when evaluated on data-independent acquisition data.

Profiling mouse brown and white adipocytes to identify metabolically relevant small ORFs and functional microproteins.

Microproteins (MPs) are a potentially rich source of uncharacterized metabolic regulators. Here, we use ribosome profiling (Ribo-seq) to curate 3,877 unannotated MP-encoding small ORFs (smORFs) in primary brown, white, and beige mouse adipocytes. Of these, we validated 85 MPs by proteomics, including 33 circulating MPs in mouse plasma. Analyses of MP-encoding mRNAs under different physiological conditions (high-fat diet) revealed that numerous MPs are regulated in adipose tissue in vivo and are co-expressed with established metabolic genes. Furthermore, Ribo-seq provided evidence for the translation of Gm8773, which encodes a secreted MP that is homologous to human and chicken FAM237B. Gm8773 is highly expressed in the arcuate nucleus of the hypothalamus, and intracerebroventricular administration of recombinant mFAM237B showed orexigenic activity in obese mice. Together, these data highlight the value of this adipocyte MP database in identifying MPs with roles in fundamental metabolic and physiological processes such as feeding.

Clinical applications of mass spectrometry-based proteomics in cancer: Where are we?

Tumor tissue processing methodologies in combination with data-independent acquisition mass spectrometry (DIA-MS) have emerged that can comprehensively analyze the proteome of multiple tumor samples accurately and reproducibly. Increasing recognition and adoption of these technologies has resulted in a tranche of studies providing novel insights into cancer classification systems, functional tumor biology, cancer biomarkers, treatment response and drug targets. Despite this, with some limited exceptions, MS-based proteomics has not yet been implemented in routine cancer clinical practice. Here, we summarize the use of DIA-MS in studies that may pave the way for future clinical cancer applications, and highlight the role of alternative MS technologies and multi-omic strategies. We discuss limitations and challenges of studies in this field to date and propose steps for integrating proteomic data into the cancer clinic.

IL-17A and TNF-α inhibitors induce multiple molecular changes in psoriasis.

Adalimumab and secukinumab are commonly used for moderate to severe psoriasis vulgaris (PV). Although distinct individual responses to and impaired effectiveness of these biological agents occur occasionally, little is known about the underlying reasons. Here, we report a proteomic analysis of psoriatic lesions from patients treated with these drugs using data-independent acquisition mass spectrometry (DIA-MS). Thousands of differentially expressed proteins (DEPs) changed over 12 weeks of treatment. Network analysis showed that DEPs could interact and induce transformation in matrix components, metabolic regulation, and immune response. The results of parallel reaction monitoring (PRM) analysis suggested that S100s, STAT1, KRT2, TYMP, SOD2, HSP90AB1, TFRC, and COL5A1 were the most significantly changed proteins in both groups. There was a positive association between the Psoriasis Area and Severity Index (PASI) score and three proteins (TFRC, IMPDH2, KRT2). Our study findings suggest that inhibition of IL-17A and TNF-α can induce changes in multiple molecules in psoriatic lesions and have an overlapping influence on the immune response and process through direct or indirect effects.

Direct proteomic and high-resolution microscopy biopsy analysis identifies distinct ventricular fates in severe aortic stenosis.

The incidence of aortic valve stenosis (AS), the most common reason for aortic valve replacement (AVR), increases with population ageing. While untreated AS is associated with high mortality, different hemodynamic subtypes range from normal left-ventricular function to severe heart failure. However, the molecular nature underlying four different AS subclasses, suggesting vastly different myocardial fates, is unknown. Here, we used direct proteomic analysis of small left-ventricular biopsies to identify unique protein expression profiles and subtype-specific AS mechanisms. Left-ventricular endomyocardial biopsies were harvested from patients during transcatheter AVR, and inclusion criteria were based on echocardiographic diagnosis of severe AS and guideline-defined AS-subtype classification: 1) normal ejection fraction (EF)/high-gradient; 2) low EF/high-gradient; 3) low EF/low-gradient; and 4) paradoxical low-flow/low-gradient AS. Samples from non-failing donor hearts served as control. We analyzed 25 individual left-ventricular biopsies by data-independent acquisition mass spectrometry (DIA-MS), and 26 biopsies by histomorphology and cardiomyocytes by STimulated Emission Depletion (STED) superresolution microscopy. Notably, DIA-MS reliably detected 2273 proteins throughout each individual left-ventricular biopsy, of which 160 proteins showed significant abundance changes between AS-subtype and non-failing samples including the cardiac ryanodine receptor (RyR2). Hierarchical clustering segregated unique proteotypes that identified three hemodynamic AS-subtypes. Additionally, distinct proteotypes were linked with AS-subtype specific differences in cardiomyocyte hypertrophy. Furthermore, superresolution microscopy of immunolabeled biopsy sections showed subcellular RyR2-cluster fragmentation and disruption of the functionally important association with transverse tubules, which occurred specifically in patients with systolic dysfunction and may hence contribute to depressed left-ventricular function in AS.

Ultrastructural Assessment and Proteomic Analysis in Myofibrillogenesis in the Heart Primordium After Heartbeat Initiation in Rats.

Myofibrillogenesis is an essential process for cardiogenesis and is closely related to excitation-contraction coupling and the maintenance of heartbeat. It remains unclear whether the formation of myofibrils and sarcomeres is associated with heartbeat initiation in the early embryonic heart development. Here, we investigated the association between the ultrastructure of myofibrils assessed by transmission electron microscopy and their proteomic profiling assessed by data-independent acquisition mass spectrometry (DIA-MS) in the rat heart primordia before and after heartbeat initiation at embryonic day 10.0, when heartbeat begins in rats, and in the primitive heart tube at embryonic day 11.0. Bundles of myofilaments were scattered in a few cells of the heart primordium after heartbeat initiation, whereas there were no typical sarcomeres in the heart primordia both before and after heartbeat initiation. Sarcomeres with Z-lines were identified in cells of the primitive heart tube, though myofilaments were not aligned. DIA-MS proteome analysis revealed that only 43 proteins were significantly upregulated by more than 2.0 fold among a total of 7,762 detected proteins in the heart primordium after heartbeat initiation compared with that before heartbeat initiation. Indeed, of those upregulated proteins, 12 (27.9%) were constituent proteins of myofibrils and 10 (23.3%) were proteins that were accessories and regulators for myofibrillogenesis, suggesting that upregulated proteins that are associated with heartbeat initiation were enriched in myofibrillogenesis. Collectively, our results suggest that the establishment of heartbeat is induced by development of bundles of myofilaments with upregulated proteins associated with myofibrillogensis, whereas sarcomeres are not required for the initial heartbeat.

Protein Expression of AEBP1, MCM4, and FABP4 Differentiate Osteogenic, Adipogenic, and Mesenchymal Stromal Stem Cells.

Mesenchymal stem cells (MSCs) gain an increasing focus in the field of regenerative medicine due to their differentiation abilities into chondrocytes, adipocytes, and osteoblastic cells. However, it is apparent that the transformation processes are extremely complex and cause cellular heterogeneity. The study aimed to characterize differences between MSCs and cells after adipogenic (AD) or osteoblastic (OB) differentiation at the proteome level. Comparative proteomic profiling was performed using tandem mass spectrometry in data-independent acquisition mode. Proteins were quantified by deep neural networks in library-free mode and correlated to the Molecular Signature Database (MSigDB) hallmark gene set collections for functional annotation. We analyzed 4108 proteins across all samples, which revealed a distinct clustering between MSCs and cell differentiation states. Protein expression profiling identified activation of the Peroxisome proliferator-activated receptors (PPARs) signaling pathway after AD. In addition, two distinct protein marker panels could be defined for osteoblastic and adipocytic cell lineages. Hereby, overexpression of AEBP1 and MCM4 for OB as well as of FABP4 for AD was detected as the most promising molecular markers. Combination of deep neural network and machine-learning algorithms with data-independent mass spectrometry distinguish MSCs and cell lineages after adipogenic or osteoblastic differentiation. We identified specific proteins as the molecular basis for bone formation, which could be used for regenerative medicine in the future.

ABPP-HT*-Deep Meets Fast for Activity-Based Profiling of Deubiquitylating Enzymes Using Advanced DIA Mass Spectrometry Methods.

Activity-based protein profiling (ABPP) uses a combination of activity-based chemical probes with mass spectrometry (MS) to selectively characterise a particular enzyme or enzyme class. ABPP has proven invaluable for profiling enzymatic inhibitors in drug discovery. When applied to cell extracts and cells, challenging the ABP-enzyme complex formation with a small molecule can simultaneously inform on potency, selectivity, reversibility/binding affinity, permeability, and stability. ABPP can also be applied to pharmacodynamic studies to inform on cellular target engagement within specific organs when applied to in vivo models. Recently, we established separate high depth and high throughput ABPP (ABPP-HT) protocols for the profiling of deubiquitylating enzymes (DUBs). However, the combination of the two, deep and fast, in one method has been elusive. To further increase the sensitivity of the current ABPP-HT workflow, we implemented state-of-the-art data-independent acquisition (DIA) and data-dependent acquisition (DDA) MS analysis tools. Hereby, we describe an improved methodology, ABPP-HT* (enhanced high-throughput-compatible activity-based protein profiling) that in combination with DIA MS methods, allowed for the consistent profiling of 35-40 DUBs and provided a reduced number of missing values, whilst maintaining a throughput of 100 samples per day.

Mass spectrometry profiling and quantitation of changes in circulating hormones secreted over time in Cancer borealis hemolymph due to feeding behavior.

The crustacean stomatogastric ganglion (STG) is a valuable model for understanding circuit dynamics in neuroscience as it contains a small number of neurons, all easily distinguishable and most of which contribute to two complementary feeding-related neural circuits. These circuits are modulated by numerous neuropeptides, with many gaining access to the STG as hemolymph-transported hormones. Previous work characterized neuropeptides in the hemolymph of the crab Cancer borealis but was limited by low peptide abundance in the presence of a complex biological matrix and the propensity for rapid peptide degradation. To improve their detection, a data-independent acquisition (DIA) mass spectrometry (MS) method was implemented. This approach improved the number of neuropeptides detected by approximately twofold and showed greater reproducibility between experimental and biological replicates. This method was then used to profile neuropeptides at different stages of the feeding process, including hemolymph from crabs that were unfed, or 0 min, 15 min, 1 h, and 2 h post-feeding. The results show differences both in the presence and relative abundance of neuropeptides at the various time points. Additionally, 96 putative neuropeptide sequences were identified with de novo sequencing, indicating there may be more key modulators within this system than is currently known. These results suggest that a distinct cohort of neuropeptides provides modulation to the STG at different times in the feeding process, providing groundwork for targeted follow-up electrophysiological studies to better understand the functional role of circulating hormones in the neural basis of feeding behavior.

Selective Labeling and Identification of the Tumor Cell Proteome of Pancreatic Cancer In Vivo.

Pancreatic ductal adenocarcinoma (PDAC) is among the deadliest cancers. Dissecting the tumor cell proteome from that of the non-tumor cells in the PDAC tumor bulk is critical for tumorigenesis studies, biomarker discovery, and development of therapeutics. However, investigating the tumor cell proteome has proven evasive due to the tumor's extremely complex cellular composition. To circumvent this technical barrier, we have combined bioorthogonal noncanonical amino acid tagging (BONCAT) and data-independent acquisition mass spectrometry (DIA-MS) in an orthotopic PDAC model to specifically identify the tumor cell proteome in vivo. Utilizing the tumor cell-specific expression of a mutant tRNA synthetase transgene, this approach provides tumor cells with the exclusive ability to incorporate an azide-bearing methionine analogue into newly synthesized proteins. The azide-tagged tumor cell proteome is subsequently enriched and purified via a bioorthogonal reaction and then identified and quantified using DIA-MS. Applying this workflow to the orthotopic PDAC model, we have identified thousands of proteins expressed by the tumor cells. Furthermore, by comparing the tumor cell and tumor bulk proteomes, we showed that the approach can distinctly differentiate proteins produced by tumor cells from those of non-tumor cells within the tumor microenvironment. Our study, for the first time, reveals the tumor cell proteome of PDAC under physiological conditions, providing broad applications for tumorigenesis, therapeutics, and biomarker studies in various human cancers.

Lysine and Arginine Protein Post-translational Modifications by Enhanced DIA Libraries: Quantification in Murine Liver Disease.

Proteoforms containing post-translational modifications (PTMs) represent a degree of functional diversity only harnessed through analytically precise simultaneous quantification of multiple PTMs. Here we present a method to accurately differentiate an unmodified peptide from its PTM-containing counterpart through data-independent acquisition-mass spectrometry, leveraging small precursor mass windows to physically separate modified peptidoforms from each other during MS2 acquisition. We utilize a lysine and arginine PTM-enriched peptide assay library and site localization algorithm to simultaneously localize and quantify seven PTMs including mono-, di-, and trimethylation, acetylation, and succinylation in addition to total protein quantification in a single MS run without the need to enrich experimental samples. To evaluate biological relevance, this method was applied to liver lysate from differentially methylated nonalcoholic steatohepatitis (NASH) mouse models. We report that altered methylation and acetylation together with total protein changes drive the novel hypothesis of a regulatory function of PTMs in protein synthesis and mRNA stability in NASH.