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.

Eichner classification based on panoramic X-ray images using deep learning: A pilot study.

BACKGROUND: Research using panoramic X-ray images using deep learning has been progressing in recent years. There is a need to propose methods that can classify and predict from image information. OBJECTIVE: In this study, Eichner classification was performed on image processing based on panoramic X-ray images. The Eichner classification was based on the remaining teeth, with the aim of making partial dentures. This classification was based on the condition that the occlusal position was supported by the remaining teeth in the upper and lower jaws. METHODS: Classification models were constructed using two convolutional neural network methods: the sequential and VGG19 models. The accuracy was compared with the accuracy of Eichner classification using the sequential and VGG19 models. RESULTS: Both accuracies were greater than 81%, and they had sufficient functions for the Eichner classification. CONCLUSION: We were able to build a highly accurate prediction model using deep learning scratch sequential model and VGG19. This predictive model will become part of the basic considerations for future AI research in dentistry.

Integrated proteogenomic analysis for inherited bone marrow failure syndrome.

Recent advances in in-depth data-independent acquisition proteomic analysis have enabled comprehensive quantitative analysis of >10,000 proteins. Herein, an integrated proteogenomic analysis for inherited bone marrow failure syndrome (IBMFS) was performed to reveal their biological features and to develop a proteomic-based diagnostic assay in the discovery cohort; dyskeratosis congenita (n = 12), Fanconi anemia (n = 11), Diamond-Blackfan anemia (DBA, n = 9), Shwachman-Diamond syndrome (SDS, n = 6), ADH5/ALDH2 deficiency (n = 4), and other IBMFS (n = 18). Unsupervised proteomic clustering identified eight independent clusters (C1-C8), with the ribosomal pathway specifically downregulated in C1 and C2, enriched for DBA and SDS, respectively. Six patients with SDS had significantly decreased SBDS protein expression, with two of these not diagnosed by DNA sequencing alone. Four patients with ADH5/ALDH2 deficiency showed significantly reduced ADH5 protein expression. To perform a large-scale rapid IBMFS screening, targeted proteomic analysis was performed on 417 samples from patients with IBMFS-related hematological disorders (n = 390) and healthy controls (n = 27). SBDS and ADH5 protein expressions were significantly reduced in SDS and ADH5/ALDH2 deficiency, respectively. The clinical application of this first integrated proteogenomic analysis would be useful for the diagnosis and screening of IBMFS, where appropriate clinical screening tests are lacking.

The integration of metabolic and proteomic data uncovers an augmentation of the sphingolipid biosynthesis pathway during T-cell differentiation.

Recent studies have highlighted the significance of cellular metabolism in the initiation of clonal expansion and effector differentiation of T cells. Upon exposure to antigens, naïve CD4+ T cells undergo metabolic reprogramming to meet their metabolic requirements. However, only few studies have simultaneously evaluated the changes in protein and metabolite levels during T cell differentiation. Our research seeks to fill the gap by conducting a comprehensive analysis of changes in levels of metabolites, including sugars, amino acids, intermediates of the TCA cycle, fatty acids, and lipids. By integrating metabolomics and proteomics data, we discovered that the quantity and composition of cellular lipids underwent significant changes in different effector Th cell subsets. Especially, we found that the sphingolipid biosynthesis pathway was commonly activated in Th1, Th2, Th17, and iTreg cells and that inhibition of this pathway led to the suppression of Th17 and iTreg cells differentiation. Additionally, we discovered that Th17 and iTreg cells enhance glycosphingolipid metabolism, and inhibition of this pathway also results in the suppression of Th17 and iTreg cell generation. These findings demonstrate that the utility of our combined metabolomics and proteomics analysis in furthering the understanding of metabolic transition during Th cell differentiation.

Universal Pretreatment Development for Low-input Proteomics Using Lauryl Maltose Neopentyl Glycol.

In recent years, there has been a growing demand for low-input proteomics, particularly in the context of single-cell proteomics (SCP). In this study, we have developed a lauryl maltose neopentyl glycol (LMNG)-assisted sample preparation (LASP) method. This method effectively reduces protein and peptide loss in samples by incorporating LMNG, a surfactant, into the digestion solution and subsequently removing the LMNG simply via reversed phase solid-phase extraction. The advantage of removing LMNG during sample preparation for general proteomic analysis is the prevention of mass spectrometry (MS) contamination. When we applied the LASP method to the low-input SP3 method and on-bead digestion in coimmunoprecipitation-MS, we observed a significant improvement in the recovery of the digested peptides. Furthermore, we have established a simple and easy sample preparation method for SCP based on the LASP method and identified a median of 1175 proteins from a single HEK239F cell using liquid chromatography (LC)-MS/MS with a throughput of 80 samples per day.

Galectin-10 in serum extracellular vesicles reflects asthma pathophysiology.

BACKGROUND: Novel biomarkers (BMs) are urgently needed for bronchial asthma (BA) with various phenotypes and endotypes. OBJECTIVE: We sought to identify novel BMs reflecting tissue pathology from serum extracellular vesicles (EVs). METHODS: We performed data-independent acquisition of serum EVs from 4 healthy controls, 4 noneosinophilic asthma (NEA) patients, and 4 eosinophilic asthma (EA) patients to identify novel BMs for BA. We confirmed EA-specific BMs via data-independent acquisition validation in 61 BA patients and 23 controls. To further validate these findings, we performed data-independent acquisition for 6 patients with chronic rhinosinusitis without nasal polyps and 7 patients with chronic rhinosinusitis with nasal polyps. RESULTS: We identified 3032 proteins, 23 of which exhibited differential expression in EA. Ingenuity pathway analysis revealed that protein signatures from each phenotype reflected disease characteristics. Validation revealed 5 EA-specific BMs, including galectin-10 (Gal10), eosinophil peroxidase, major basic protein, eosinophil-derived neurotoxin, and arachidonate 15-lipoxygenase. The potential of Gal10 in EVs was superior to that of eosinophils in terms of diagnostic capability and detection of airway obstruction. In rhinosinusitis patients, 1752 and 8413 proteins were identified from EVs and tissues, respectively. Among 11 BMs identified in EVs and tissues from patients with chronic rhinosinusitis with nasal polyps, 5 (including Gal10 and eosinophil peroxidase) showed significant correlations between EVs and tissues. Gal10 release from EVs was implicated in eosinophil extracellular trapped cell death in vitro and in vivo. CONCLUSION: Novel BMs such as Gal10 from serum EVs reflect disease pathophysiology in BA and may represent a new target for liquid biopsy approaches.

Prediction of Binding Pose and Affinity of Nelfinavir, a SARS-CoV-2 Main Protease Repositioned Drug, by Combining Docking, Molecular Dynamics, and Fragment Molecular Orbital Calculations.

A novel in silico drug design procedure is described targeting the Main protease (Mpro) of the SARS-CoV-2 virus. The procedure combines molecular docking, molecular dynamics (MD), and fragment molecular orbital (FMO) calculations. The binding structure and properties of Mpro were predicted for Nelfinavir (NFV), which had been identified as a candidate compound through drug repositioning, targeting Mpro. Several poses of the Mpro and NFV complexes were generated by docking, from which four docking poses were selected by scoring with FMO energy. Then, each pose was subjected to MD simulation, 100 snapshot structures were sampled from each of the generated MD trajectories, and the structures were evaluated by FMO calculations to rank the pose based on binding energy. Several residues were found to be important in ligand recognition, including Glu47, Asp48, Glu166, Asp187, and Gln189, all of which interacted strongly with NFV. Asn142 is presumably regarded to form hydrogen bonds or CH/π interaction with NFV; however, in the present calculation, their interactions were transient. Moreover, the tert-butyl group of NFV had no interaction with Mpro. Identifying such strong and weak interactions provides candidates for maintaining and substituting ligand functional groups and important suggestions for drug discovery using drug repositioning. Besides the interaction between NFV and the amino acid residues of Mpro, the desolvation effect of the binding pocket also affected the ranking order. A similar procedure of drug design was applied to Lopinavir, and the calculated interaction energy and experimental inhibitory activity value trends were consistent. Our approach provides a new guideline for structure-based drug design starting from a candidate compound whose complex crystal structure has not been obtained.

Proteome Analysis of Serum Purified Using Solanum tuberosum and Lycopersicon esculentum Lectins.

Serum and plasma exhibit a broad dynamic range of protein concentrations, posing challenges for proteome analysis. Various technologies have been developed to reduce this complexity, including high-abundance depletion methods utilizing antibody columns, extracellular vesicle enrichment techniques, and trace protein enrichment using nanobead cocktails. Here, we employed lectins to address this, thereby extending the scope of biomarker discovery in serum or plasma using a novel approach. We enriched serum proteins using 37 different lectins and subjected them to LC-MS/MS analysis with data-independent acquisition. Solanum tuberosum lectin (STL) and Lycopersicon esculentum lectin (LEL) enabled the detection of more serum proteins than the other lectins. STL and LEL bind to N-acetylglucosamine oligomers, emphasizing the significance of capturing these oligomer-binding proteins when analyzing serum trace proteins. Combining STL and LEL proved more effective than using them separately, allowing us to identify over 3000 proteins from serum through single-shot proteome analysis. We applied the STL/LEL trace-protein enrichment method to the sera of systemic lupus erythematosus model mice. This revealed differences in >1300 proteins between the systemic lupus erythematosus model and control mouse sera, underscoring the utility of this method for biomarker discovery.

GeLC-FAIMS-MS workflow for in-depth middle-down proteomics.

Middle-down proteomics (MDP) is an analytical approach in which protein samples are digested with proteases such as Glu-C to generate large peptides (>3 kDa) that are analyzed by mass spectrometry (MS). This method is useful for characterizing high-molecular-weight proteins that are difficult to detect by top-down proteomics (TDP), in which intact proteins are analyzed by MS. In this study, we applied GeLC-FAIMS-MS, a multidimensional separation workflow that combines gel-based prefractionation with LC-FAIMS MS, for deep MDP. Middle-down peptides generated by optimized limited Glu-C digestion conditions were first size-fractionated by polyacrylamide gel electrophoresis, followed by C4 reversed-phase liquid chromatography separation and additional ion mobility fractionation, resulting in a significant increase in peptide length detectable by MS. In addition to global analysis, the GeLC-FAIMS-MS concept can also be applied to targeted MDP, where only proteins in the desired molecular weight range are gel-fractionated and their Glu-C digestion products are analyzed, as demonstrated by targeted analysis of integrins in exosomes. In-depth MDP achieved by global and targeted GeLC-FAIMS-MS supports the exploration of proteoform information not covered by conventional TDP by increasing the number of detectable protein groups or post-translational modifications (PTMs) and improving the sequence coverage.

Using Texture Analysis of Neck Computed Tomography Images to Differentiate Primary Hyperparathyroidism From Normal Controls.

OBJECTIVE: To investigate the utility of texture analysis in detecting osseous changes associated with hyperparathyroidism on neck CT examinations compared with control patients and to explore the best regions in the head and neck to evaluate changes in the trabecular architecture secondary to hyperparathyroidism. METHODS: Patients with hyperparathyroidism who underwent a 4D CT of the neck with contrast were included in this study. Age-matched control patients with no history of hyperparathyroidism who underwent a contrast-enhanced neck CT were also included. Mandibular condyles, bilateral mandibular bodies, the body of the C4 vertebra, the manubrium of the sternum, and bilateral clavicular heads were selected for analysis, and oval-shaped regions of interest were manually placed. These segmented areas were imported into an in-house developed texture analysis program, and 41 texture analysis features were extracted. A mixed linear regression model was used to compare differences in the texture analysis features contoured at each of the osseous structures between patients with hyperparathyroidism and age-matched control patients. RESULTS: A total of 30 patients with hyperparathyroidism and 30 age-matched control patients were included in this study. Statistically significant differences in texture features between patients with hyperparathyroidism and control patients in all 8 investigated osseous regions. The sternum showed the greatest number of texture features with statistically significant differences between these groups. CONCLUSIONS: Some CT texture features demonstrated statistically significant differences between patients with hyperparathyroidism and control patients. The results suggest that texture features may discriminate changes in the osseous architecture of the head and neck in patients with hyperparathyroidism.

Triplet dynamic nuclear polarization of pyruvate via supramolecular chemistry.

Dynamic nuclear polarization (DNP) significantly improves the sensitivity of magnetic resonance imaging, and its most important medical application is cancer diagnosis via hyperpolarized 13C-labeled pyruvate. Unlike cryogenic DNP, triplet-DNP uses photoexcited triplet electrons under mild conditions. However, triplet-DNP of pyruvate has not been observed because of incompatibility of the hydrophobic polarizing agent with hydrophilic pyruvate. This work demonstrates that supramolecular complexation with ß-cyclodextrin can disperse 4,4'-(pentacene-6,13-diyl)dibenzoate (NaPDBA), a pentacene derivative with hydrophilic substituents, even in the presence of high sodium pyruvate concentrations. The polarization of photoexcited triplet electron spins in NaPDBA was transferred to the 13C spins of sodium pyruvate via triplet-DNP of 1H spins in water and 1H-to-13C cross-polarization. This provides an important step toward the widespread use of ultra-sensitive MRI for cancer diagnosis.

1-Oleoyl-lysophosphatidylethanolamine stimulates RORγt activity in TH17 cells.

Metabolic fluxes involving fatty acid biosynthesis play essential roles in controlling the differentiation of T helper 17 (TH17) cells. However, the exact enzymes and lipid metabolites involved, as well as their link to promoting the core gene transcriptional signature required for the differentiation of TH17 cells, remain largely unknown. From a pooled CRISPR-based screen and unbiased lipidomics analyses, we identified that 1-oleoyl-lysophosphatidylethanolamine could act as a lipid modulator of retinoid-related orphan receptor gamma t (RORγt) activity in TH17 cells. In addition, we specified five enzymes, including Gpam, Gpat3, Lplat1, Pla2g12a, and Scd2, suggestive of the requirement of glycerophospholipids with monounsaturated fatty acids being required for the transcription of Il17a. 1-Oleoyl-lysophosphatidylethanolamine was reduced in Pla2g12a-deficient TH17 cells, leading to the abolition of interleukin-17 (IL-17) production and disruption to the core transcriptional program required for the differentiation of TH17 cells. Furthermore, mice with T cell-specific deficiency of Pla2g12a failed to develop disease in an experimental autoimmune encephalomyelitis model of multiple sclerosis. Thus, our data indicate that 1-oleoyl-lysophosphatidylethanolamine is a lipid metabolite that promotes RORγt-induced TH17 cell differentiation and the pathogenicity of TH17 cells.

Efficacy of texture analysis of ultrasonographic images in the differentiation of metastatic and non-metastatic cervical lymph nodes in patients with squamous cell carcinoma of the tongue.

OBJECTIVE: We investigated the efficacy of using texture analysis of ultrasonographic images of the cervical lymph nodes of patients with squamous cell carcinoma of the tongue to differentiate between metastatic and non-metastatic lymph nodes. STUDY DESIGN: We analyzed 32 metastatic and 28 non-metastatic lymph nodes diagnosed by histopathologic examination on presurgical US images. Using the LIFEx texture analysis program, we extracted 36 texture features from the images and calculated the statistical significance of differences in texture features between metastatic and non-metastatic lymph nodes using the t test. To assess the diagnostic ability of the significantly different texture features to discriminate between metastatic and non-metastatic nodes, we performed receiver operating characteristic curve analysis and calculated the area under the curve. We set the cutoff points that maximized the sensitivity and specificity for each curve according to the Youden J statistic. RESULTS: We found that 20 texture features significantly differed between metastatic and non-metastatic lymph nodes. Among them, only the gray-level run length matrix feature of run length non-uniformity and the gray-level zone length matrix features of gray-level non-uniformity and zone length non-uniformity showed an excellent ability to discriminate between metastatic and non-metastatic lymph nodes as indicated by the area under the curve and the sum of sensitivity and specificity. CONCLUSIONS: Analysis of the texture features of run length non-uniformity, gray-level non-uniformity, and zone length non-uniformity values allows for differentiation between metastatic and non-metastatic lymph nodes, with the use of gray-level non-uniformity appearing to be the best means of predicting metastatic lymph nodes.

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.

A complementary approach for genetic diagnosis of inborn errors of immunity using proteogenomic analysis.

Advances in next-generation sequencing technology have identified many genes responsible for inborn errors of immunity (IEI). However, there is still room for improvement in the efficiency of genetic diagnosis. Recently, RNA sequencing and proteomics using peripheral blood mononuclear cells (PBMCs) have gained attention, but only some studies have integrated these analyses in IEI. Moreover, previous proteomic studies for PBMCs have achieved limited coverage (approximately 3000 proteins). More comprehensive data are needed to gain valuable insights into the molecular mechanisms underlying IEI. Here, we propose a state-of-the-art method for diagnosing IEI using PBMCs proteomics integrated with targeted RNA sequencing (T-RNA-seq), providing unique insights into the pathogenesis of IEI. This study analyzed 70 IEI patients whose genetic etiology had not been identified by genetic analysis. In-depth proteomics identified 6498 proteins, which covered 63% of 527 genes identified in T-RNA-seq, allowing us to examine the molecular cause of IEI and immune cell defects. This integrated analysis identified the disease-causing genes in four cases undiagnosed in previous genetic studies. Three of them could be diagnosed by T-RNA-seq, while the other could only be diagnosed by proteomics. Moreover, this integrated analysis showed high protein-mRNA correlations in B- and T-cell-specific genes, and their expression profiles identified patients with immune cell dysfunction. These results indicate that integrated analysis improves the efficiency of genetic diagnosis and provides a deep understanding of the immune cell dysfunction underlying the etiology of IEI. Our novel approach demonstrates the complementary role of proteogenomic analysis in the genetic diagnosis and characterization of IEI.

Development of a Simple and Stable NanoESI Spray System Using Suction Wind from the MS Inlet.

Improving the reproducibility of proteome analysis systems presents a challenge; therefore, in this study, we developed a new insertion spray ionization (InSpIon) system wherein an InSpIon tube was designed with a spray tip inserted into the tube. This system stabilized the spray and subsequently improved the reproducibility of the analysis.

Singlet fission as a polarized spin generator for dynamic nuclear polarization.

Singlet fission (SF), converting a singlet excited state into a spin-correlated triplet-pair state, is an effective way to generate a spin quintet state in organic materials. Although its application to photovoltaics as an exciton multiplier has been extensively studied, the use of its unique spin degree of freedom has been largely unexplored. Here, we demonstrate that the spin polarization of the quintet multiexcitons generated by SF improves the sensitivity of magnetic resonance of water molecules through dynamic nuclear polarization (DNP). We form supramolecular assemblies of a few pentacene chromophores and use SF-born quintet spins to achieve DNP of water-glycerol, the most basic biological matrix, as evidenced by the dependence of nuclear polarization enhancement on magnetic field and microwave power. Our demonstration opens a use of SF as a polarized spin generator in bio-quantum technology.

Bile proteome analysis by high-precision mass spectrometry to examine novel biomarkers of primary sclerosing cholangitis.

BACKGROUND: Primary sclerosing cholangitis (PSC) is a chronic inflammatory disease of unknown etiology that affects the intra- and extrahepatic bile ducts. The present study examined the utility of a bile proteome analysis using a high-sensitivity mass spectrometer to comprehensively screen for novel PSC biomarkers. METHODS: Bile endoscopically collected from patients with PSC, common bile duct stones, and biliary tract cancer were subjected to high-precision liquid chromatography/mass spectrometry. Some of the proteins specifically up-regulated in the bile of the PSC group were re-examined by an enzyme-linked immunosorbent assay. RESULTS: A total of 8094 proteins were successfully identified and 332 were specifically up-regulated in the PSC group. The bioinformatics analysis showed that proteins involved in the proliferation and activation of diverse inflammatory cells were up-regulated in the PSC group. A receiver operating characteristic curve analysis showed good area under the curve values for interleukin-8 and annexin A1 (ANXA1) (0.836 and 0.914, respectively). Immunostaining for ANXA1 revealed its strong expression in inflammatory cells infiltrating the peripheral biliary tract in PSC livers. CONCLUSION: A bile proteome analysis is a useful tool for elucidating the pathogenesis of PSC and developing new diagnostic approaches. Therefore, ANXA1 has potential as a bile biomarker for PSC.

Characterization of proteogenomic signatures of differentiation of CD4+ T cell subsets.

Functionally distinct CD4+ helper T (Th) cell subsets, including Th1, Th2, Th17, and regulatory T cells (Treg), play a pivotal role in the regulation of acquired immunity. Although the key proteins involved in the regulation of Th cell differentiation have already been identified how the proteogenomic landscape changes during the Th cell activation remains unclear. To address this issue, we characterized proteogenomic signatures of differentiation to each Th cell subsets by RNA sequencing and liquid chromatography-assisted mass spectrometry, which enabled us to simultaneously quantify more than 10,000 protein-coding transcripts and 8,000 proteins in a single-shot. The results indicated that T cell receptor activation affected almost half of the transcript and protein levels in a low correlative and gene-specific manner, and specific cytokine treatments modified the transcript and protein profiles in a manner specific to each Th cell subsets: Th17 and Tregs particularly exhibited unique proteogenomic signatures compared to other Th cell subsets. Interestingly, the in-depth proteome data revealed that mRNA profiles alone were not enough to delineate functional changes during Th cell activation, suggesting that the proteogenomic dataset obtained in this study serves as a unique and indispensable data resource for understanding the comprehensive molecular mechanisms underlying effector Th cell differentiation.