Protein painting for structural and binding site analysis via intracellular lysine reactivity profiling with o-phthalaldehyde.

The three-dimensional structure and the molecular interaction of proteins determine their roles in many cellular processes. Chemical protein painting with protein mass spectrometry can identify changes in structural conformations and molecular interactions of proteins including their binding sites. Nevertheless, most current protein painting techniques identify protein targets and binding sites of drugs in vitro using a cell lysate or purified protein. Here, we tested 11 membrane-permeable lysine-reactive chemical probes for intracellular covalent labeling of endogenous proteins, which reveals ortho-phthalaldehyde (OPA) as the most reactive probe in the intracellular environment. An MS workflow and a new data analysis strategy termed RAPID (Reactive Amino acid Profiling by Inverse Detection) was developed to enhance detection sensitivity. RAPID with OPA successfully identified structural changes induced by the allosteric drug TEPP-46 on its target protein PKM2 and was applied to profile the conformation change of the proteome occurring in cells during thermal denaturation. The application of RAPID-OPA on cells treated with geldanamycin, selumetinib, and staurosporine successfully revealed their binding sites on target proteins. Thus, RAPID-OPA for cellular protein painting enables the identification of ligand-binding sites and detection of protein structural changes occurring in cells.

High-throughput drug target discovery using a fully automated proteomics sample preparation platform.

Drug development is plagued by inefficiency and high costs due to issues such as inadequate drug efficacy and unexpected toxicity. Mass spectrometry (MS)-based proteomics, particularly isobaric quantitative proteomics, offers a solution to unveil resistance mechanisms and unforeseen side effects related to off-targeting pathways. Thermal proteome profiling (TPP) has gained popularity for drug target identification at the proteome scale. However, it involves experiments with multiple temperature points, resulting in numerous samples and considerable variability in large-scale TPP analysis. We propose a high-throughput drug target discovery workflow that integrates single-temperature TPP, a fully automated proteomics sample preparation platform (autoSISPROT), and data independent acquisition (DIA) quantification. The autoSISPROT platform enables the simultaneous processing of 96 samples in less than 2.5 hours, achieving protein digestion, desalting, and optional TMT labeling (requires an additional 1 hour) with 96-channel all-in-tip operations. The results demonstrated excellent sample preparation performance with >94% digestion efficiency, >98% TMT labeling efficiency, and >0.9 intra- and inter-batch Pearson correlation coefficients. By automatically processing 87 samples, we identified both known targets and potential off-targets of 20 kinase inhibitors, affording over a 10-fold improvement in throughput compared to classical TPP. This fully automated workflow offers a high-throughput solution for proteomics sample preparation and drug target/off-target identification.

Improved in situ characterization of protein complex dynamics at scale with thermal proximity co-aggregation.

Cellular activities are carried out vastly by protein complexes but large repertoire of protein complexes remains functionally uncharacterized which necessitate new strategies to delineate their roles in various cellular processes and diseases. Thermal proximity co-aggregation (TPCA) is readily deployable to characterize protein complex dynamics in situ and at scale. We develop a version termed Slim-TPCA that uses fewer temperatures increasing throughputs by over 3X, with new scoring metrics and statistical evaluation that result in minimal compromise in coverage and detect more relevant complexes. Less samples are needed, batch effects are minimized while statistical evaluation cost is reduced by two orders of magnitude. We applied Slim-TPCA to profile K562 cells under different duration of glucose deprivation. More protein complexes are found dissociated, in accordance with the expected downregulation of most cellular activities, that include 55S ribosome and respiratory complexes in mitochondria revealing the utility of TPCA to study protein complexes in organelles. Protein complexes in protein transport and degradation are found increasingly assembled unveiling their involvement in metabolic reprogramming during glucose deprivation. In summary, Slim-TPCA is an efficient strategy for characterization of protein complexes at scale across cellular conditions, and is available as Python package at https://pypi.org/project/Slim-TPCA/ .

Scaled-Down Thermal Profiling and Coaggregation Analysis of the Proteome for Drug Target and Protein Interaction Analysis.

Thermal proteome profiling (TPP), an experimental technique combining the cellular thermal shift assay (CETSA) with quantitative protein mass spectrometry (MS), identifies interactions of drugs and chemicals with endogenous proteins. Thermal proximity coaggregation (TPCA) profiling extended TPP to study the intracellular dynamics of protein complexes. In TPP and TPCA, samples are subjected to multiple denaturing temperatures, each requiring over 100 µg of proteins, which restricts their applications for rare cells and precious clinical samples. We developed a workflow termed STASIS (scaled-down thermal profiling and coaggregation analysis with SISPROT) that scales down the required protein to as low as 1 µg per temperature. This is achieved by heating and centrifugation using the same PCR tube, processing samples with the SISPROT technology (simple and integrated spintip-based proteomics technology), and tip-based manual fractionation of TMT-labeled peptides. We evaluate the STASIS workflow with starting protein quantities of 10, 5, and 1 µg per temperature prior to heating, identifying between 4000 and 5000 proteins with 6 h of acquisition time. Importantly, we observed a high correlation in the Tm of proteins with minimal difference in TPCA performance for predicting protein complexes. Moreover, STASIS could identify the targets of methotrexate and panobinostat with high precision with 1 µg of proteins per temperature. In conclusion, STASIS is a robust cost-effective technique for target deconvolution and extended TPCA to rare primary cells and precious clinical samples for the analysis of protein complexes.

Target deconvolution with matrix-augmented pooling strategy reveals cell-specific drug-protein interactions.

Target deconvolution is a crucial but costly and time-consuming task that hinders large-scale profiling for drug discovery. We present a matrix-augmented pooling strategy (MAPS) which mixes multiple drugs into samples with optimized permutation and delineates targets of each drug simultaneously with mathematical processing. We validated this strategy with thermal proteome profiling (TPP) testing of 15 drugs concurrently, increasing experimental throughput by 60x while maintaining high sensitivity and specificity. Benefiting from the lower cost and higher throughput of MAPS, we performed target deconvolution of the 15 drugs across 5 cell lines. Our profiling revealed that drug-target interactions can differ vastly in targets and binding affinity across cell lines. We further validated BRAF and CSNK2A2 as potential off-targets of bafetinib and abemaciclib, respectively. This work represents the largest thermal profiling of structurally diverse drugs across multiple cell lines to date.

Corynoxine B targets at HMGB1/2 to enhance autophagy for α-synuclein clearance in fly and rodent models of Parkinson's disease.

Parkinson's disease (PD) is the most common neurodegenerative movement disease. It is featured by abnormal alpha-synuclein (α-syn) aggregation in dopaminergic neurons in the substantia nigra. Macroautophagy (autophagy) is an evolutionarily conserved cellular process for degradation of cellular contents, including protein aggregates, to maintain cellular homeostasis. Corynoxine B (Cory B), a natural alkaloid isolated from Uncaria rhynchophylla (Miq.) Jacks., has been reported to promote the clearance of α-syn in cell models by inducing autophagy. However, the molecular mechanism by which Cory B induces autophagy is not known, and the α-syn-lowering activity of Cory B has not been verified in animal models. Here, we report that Cory B enhanced the activity of Beclin 1/VPS34 complex and increased autophagy by promoting the interaction between Beclin 1 and HMGB1/2. Depletion of HMGB1/2 impaired Cory B-induced autophagy. We showed for the first time that, similar to HMGB1, HMGB2 is also required for autophagy and depletion of HMGB2 decreased autophagy levels and phosphatidylinositol 3-kinase III activity both under basal and stimulated conditions. By applying cellular thermal shift assay, surface plasmon resonance, and molecular docking, we confirmed that Cory B directly binds to HMGB1/2 near the C106 site. Furthermore, in vivo studies with a wild-type α-syn transgenic drosophila model of PD and an A53T α-syn transgenic mouse model of PD, Cory B enhanced autophagy, promoted α-syn clearance and improved behavioral abnormalities. Taken together, the results of this study reveal that Cory B enhances phosphatidylinositol 3-kinase III activity/autophagy by binding to HMGB1/2 and that this enhancement is neuroprotective against PD.

Understanding Discordant Perceptions of Disease Severity Between Physicians and Patients With Eczema and Psoriasis Using Structural Equation Modeling.

Importance: Patients and physicians often have differing opinions on the patient's disease severity. This phenomenon, termed discordant severity grading (DSG), hinders the patient-physician relationship and is a source of frustration. Objective: To test and validate a model explaining the cognitive, behavioral, and disease factors associated with DSG. Design, Setting, and Participants: A qualitative study was first performed to derive a theoretical model. In this subsequent prospective cross-sectional quantitative study, the qualitatively derived theoretical model was validated using structural equation modeling (SEM). Recruitment was conducted between October 2021 and September 2022. This was a multicenter study in 3 Singapore outpatient tertiary dermatological centers. Dermatology patients and their attending physicians were recruited by convenience sampling. Patients were aged 18 to 99 years with psoriasis or eczema of at least 3 months' duration and recruited only once. The data were analyzed between October 2022 to May 2023. Main Outcomes and Measures: The outcome was the difference between global disease severity (0-10 numerical rating scale with a higher score indicating greater severity) as independently scored by the patient and the dermatologist. Positive discordance was defined as patient-graded severity more than 2 points higher (graded more severely) than physicians, and negative discordance if more than 2 points lower than physicians. Confirmatory factor analysis followed by SEM was used to assess the associations between preidentified patient, physician, and disease factors with the difference in severity grading. Results: Of the 1053 patients (mean [SD] age, 43.5 [17.5] years), a total of 579 (55.0%) patients were male, 802 (76.2%) had eczema, and 251 (23.8%) had psoriasis. Of 44 physicians recruited, 20 (45.5%) were male, 24 (54.5%) were aged between 31 and 40 years, 20 were senior residents or fellows, and 14 were consultants or attending physicians. The median (IQR) number of patients recruited per physician was 5 (2-18) patients. Of 1053 patient-physician pairs, 487 pairs (46.3%) demonstrated discordance (positive, 447 [42.4%]; negative, 40 [3.8%]). Agreement between patient and physician rating was poor (intraclass correlation, 0.27). The SEM analyses showed that positive discordance was associated with higher symptom expression (standardized coefficient B = 0.12; P = .02) and greater quality-of-life impairment (B = 0.31; P < .001), but not patient or physician demographics. A higher quality-of-life impairment was in turn associated with lower resilience and stability (B = -0.23; P < .001), increased negative social comparisons (B = 0.45; P < .001), lower self-efficacy (B = -0.11; P = .02), increased disease cyclicity (B = 0.47; P < .001), and greater expectation of chronicity (B = 0.18; P < .001). The model was well-fitted (Tucker-Lewis: 0.94; Root Mean Square Error of Approximation: 0.034). Conclusions and Relevance: This cross-sectional study identified various modifiable contributory factors to DSG, increased understanding of the phenomenon, and set a framework for targeted interventions to bridge this discordance.

Biomechanical Comparison of Cortical Lag Screws and Cortical Position Screws for Their Generation of Interfragmentary Compression and Area of Compression in Simulated Lateral Humeral Condylar Fractures.

OBJECTIVE: The aim of this study was to compare the interfragmentary compressive force and area of compression generated by cortical screws inserted as either a lag screw or position screw in simulated lateral humeral condylar fractures. STUDY DESIGN: Ex vivo biomechanical study. MATERIALS AND METHODS: Thirteen pairs of cadaveric humeri from skeletally mature Merinos with simulated lateral humeral condylar fractures were used. Pressure sensitive film was inserted into the interfragmentary interface prior to fracture reduction with fragment forceps. A cortical screw was inserted as a lag screw or a position screw and tightened to 1.8Nm. Interfragmentary compression and area of compression were quantified and compared between the two treatments groups at three time points. RESULTS: After fracture reduction using fragment forceps (Time point 1: T1), there was no significant difference in interfragmentary compression and area of compression between the two treatments. A combination of fragment forceps and a cortical screw inserted as a lag screw (Time point 2: T2) produced significantly greater interfragmentary compression and area of compression compared with the same screw inserted as a positional screw. After removal of the fragment forceps, leaving only the cortical screw (Time point 3: T3), both the interfragmentary compression and area of compression remain significantly greater in the lag screw group. CONCLUSION: Lag screws generate a greater force of compression and area of compression compared with position screws in this mature ovine humeral condylar fracture model.

Targeting macrophage autophagy for inflammation resolution and tissue repair in inflammatory bowel disease.

Inflammatory bowel disease (IBD) is a chronic, non-specific, recurrent inflammatory disease, majorly affecting the gastrointestinal tract. Due to its unclear pathogenesis, the current therapeutic strategy for IBD is focused on symptoms alleviation. Autophagy is a lysosome-mediated catabolic process for maintaining cellular homeostasis. Genome-wide association studies and subsequent functional studies have highlighted the critical role of autophagy in IBD via a number of mechanisms, including modulating macrophage function. Macrophages are the gatekeepers of intestinal immune homeostasis, especially involved in regulating inflammation remission and tissue repair. Interestingly, many autophagic proteins and IBD-related genes have been revealed to regulate macrophage function, suggesting that macrophage autophagy is a potentially important process implicated in IBD regulation. Here, we have summarized current understanding of macrophage autophagy function in pathogen and apoptotic cell clearance, inflammation remission and tissue repair regulation in IBD, and discuss how this knowledge can be used as a strategy for IBD treatment.

A partially shared joint clustering framework for detecting protein complexes from multiple state-specific signed interaction networks.

Detecting protein complexes is critical for studying cellular organizations and functions. The accumulation of protein-protein interaction (PPI) data enables the identification of protein complexes computationally. Although a great number of computational methods have been proposed to identify protein complexes from PPI networks, most of them ignore the signs of PPIs that reflect the ways proteins interact (activation or inhibition). As not all PPIs imply co-complex relationships, taking into account the signs of PPIs can benefit the identification of protein complexes. Moreover, PPI networks are not static, but vary with the change of cell states or environments. However, existing methods are primarily designed for single-network clustering, and rarely consider joint clustering of multiple PPI networks. In this study, we propose a novel partially shared signed network clustering (PS-SNC) model for identifying protein complexes from multiple state-specific signed PPI networks jointly. PS-SNC can not only consider the signs of PPIs, but also identify the common and unique protein complexes in different states. Experimental results on synthetic and real datasets show that our PS-SNC model can achieve better performance than other state-of-the-art protein complex detection methods. Extensive analysis on real datasets demonstrate the effectiveness of PS-SNC in revealing novel insights about the underlying patterns of different cell lines.

Malignancy-associated generalised exfoliative dermatitis: A retrospective study in a single-centre Asian cohort.

BACKGROUND: Erythroderma is an inflammatory skin condition that causes extensive erythema and skin scaling amounting ≥90% of the body surface area. This retrospective cohort study describes the prevalence of malignancy-associated erythroderma in a single centre where there was concerted effort to systematically offer malignancy screens to all adult erythroderma patients above the age of 65 years. METHODS: Clinical charts were reviewed for all adult inpatients and outpatients with erythroderma who attended the National University Hospital (NUH) from 1 July 2019 to 31 December 2021. Data collected included patient demographics, clinical findings, laboratory investigations, disease-specific investigations such as endoscopic procedures and biopsies, follow-up duration and mortality data. RESULTS: Seventy-four patients were analysed. The median age of the patients was 73 years old (interquartile range: 59-81 years old). An underlying dermatosis was the most common cause of erythroderma-63 patients having atopic dermatitis/asteatotic eczema or psoriasis. Three patients had erythroderma from drug eruptions, and 1 patient had chronic actinic dermatitis. Four patients had associated malignancies (5.4%). Half of our patients completed further evaluation for malignancy (52.7%). The rest had either declined or were eventually unable to complete the investigations. There was a higher prevalence of associated malignancy (7.8%) in elderly patients above 65 years old. CONCLUSION: When compared to existing literature, our cohort reflects a higher observed occurrence of malignancy in association with erythroderma. As delays in evaluation for underlying malignancy could result in potentially deleterious outcomes, it is prudent to consider systematic screening for malignancy in high-risk populations such as elderly erythroderma patients.

Toosendanin, a late-stage autophagy inhibitor, sensitizes triple-negative breast cancer to irinotecan chemotherapy.

BACKGROUND: Triple-negative breast cancer (TNBC) is a highly aggressive subtype of breast cancer that develops resistance to chemotherapy frequently. Autophagy has been reported as a pro-survival response to chemotherapeutic drugs in TNBC, and suppression of autophagy can be a strategy to overcome drug resistance. METHODS: The efficacy of toosendanin (TSN) in blocking autophagy flux was measured by western blot analysis of autophagy markers, and the fluorescent imaging of RFP-GFP-LC3 probe. The co-localization of autophagosomes and lysosomes was analyzed by fluorescent imaging. Then, lysosome function was determined by measuring the lysosomal pH value and the activity of lysosomal hydrolytic proteases. For in vitro study, human triple-negative breast cancer MDA-MB-231 and MDA-MB-436 cell lines were used for evaluating the anti-proliferative effect. For in vivo study, the RFP-GFP-LC3 MDA-MB-231 xenograft nude mice received intraperitoneal injection of irinotecan (10 mg/kg), TSN (0.5 mg/kg) or a combination, and the autophagy activity and cell apoptosis were determined in tumor tissue. The degree of pathological injury of tissue was evaluated by liver index. RESULTS: The natural autophagy inhibitor TSN, a triterpenoid extracted from Melia toosenda Sieb. et Zucc, potently inhibited late-stage autophagy in TNBC cells. This effect was achieved via elevating lysosome pH rather than blocking the fusion of autophagosomes and lysosomes. We further investigated the effects of TSN on the in vitro and in vivo TNBC models, in combination with chemotherapeutic drug irinotecan (or its active metabolite 7-ethyl-10-hydroxycamptothecin), a topoisomerase I inhibitor showing therapeutic potential for TNBC. The data showed that TSN blocked 7-ethyl-10-hydroxycamptothecin (SN-38)/irinotecan-induced protective autophagy, and significantly induced apoptosis in TNBC cells and tumor xenograft models when compared to SN-38/irinotecan alone group.

ProSAP: a GUI software tool for statistical analysis and assessment of thermal stability data.

The Cellular Thermal Shift Assay (CETSA) plays an important role in drug-target identification, and statistical analysis is a crucial step significantly affecting conclusion. We put forward ProSAP (Protein Stability Analysis Pod), an open-source, cross-platform and user-friendly software tool, which provides multiple methods for thermal proteome profiling (TPP) analysis, nonparametric analysis (NPA), proteome integral solubility alteration and isothermal shift assay (iTSA). For testing the performance of ProSAP, we processed several datasets and compare the performance of different algorithms. Overall, TPP analysis is more accurate with fewer false positive targets, but NPA methods are flexible and free from parameters. For iTSA, edgeR and DESeq2 identify more true targets than t-test and Limma, but when it comes to ranking, the four methods show not much difference. ProSAP software is available at https://github.com/hcji/ProSAP and https://zenodo.org/record/5763315.

Recent progress in mass spectrometry-based strategies for elucidating protein-protein interactions.

Protein-protein interactions are fundamental to various aspects of cell biology with many protein complexes participating in numerous fundamental biological processes such as transcription, translation and cell cycle. MS-based proteomics techniques are routinely applied for characterising the interactome, such as affinity purification coupled to mass spectrometry that has been used to selectively enrich and identify interacting partners of a bait protein. In recent years, many orthogonal MS-based techniques and approaches have surfaced including proximity-dependent labelling of neighbouring proteins, chemical cross-linking of two interacting proteins, as well as inferring PPIs from the co-behaviour of proteins such as the co-fractionating profiles and the thermal solubility profiles of proteins. This review discusses the underlying principles, advantages, limitations and experimental considerations of these emerging techniques. In addition, a brief account on how MS-based techniques are used to investigate the structural and functional properties of protein complexes, including their topology, stoichiometry, copy number and dynamics, are discussed.

Neutrophil-to-Lymphocyte Ratio Predicts Development of Immune-Related Adverse Events and Outcomes from Immune Checkpoint Blockade: A Case-Control Study.

The utility of neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) utility in predicting immune-related adverse events (irAEs) and survival have not been well studied in the context of treatment with immune checkpoint inhibitors (ICIs). We performed a case-control study of cancer patients who received at least one dose of ICI in a tertiary hospital. We examined NLR and PLR in irAE cases and controls. Logistic and Cox regression models were used to identify independent risk factors for irAEs, progression-free survival (PFS), and overall survival (OS). The study included 91 patients with irAEs and 56 controls. Multiple logistic regression showed that NLR < 3 at baseline was associated with higher occurrence of irAEs. Multivariate Cox regression showed that development of irAEs and reduction in NLR from baseline to week 6 were associated with longer PFS. Higher NLR values at baseline and/or week 6 were independently associated with shorter OS. A reduction in NLR from baseline to week 6 was associated with longer OS. In this study of cancer patients treated with ICIs, NLR has a bidirectional relationship with adverse outcomes. Lower NLR was associated with increased occurrence of irAEs while higher NLR values were associated with worse clinical outcomes.

Supportive oncodermatology-a narrative review of its utility and the way forward.

Supportive oncodermatology is an interdisciplinary field, emerging due to increasing dermatological morbidity in patients with cancer and the recognition of the need for greater collaborative and integrated care to improve patient outcomes. These two unique fields (Oncology and Dermatology) may be integrated in various ways, such as through specialised combined clinics, protocols for expedited access, multidisciplinary groups and meetings, and the development of best practices guidelines. This narrative review consolidates the small but growing literature surrounding supportive oncodermatology; discusses the potential benefit and disadvantages, and areas for future research; and suggests a framework for implementation.