Proteomic Stratification of Prognosis and Treatment Options for Small Cell Lung Cancer.

Small cell lung cancer (SCLC) is a highly malignant and heterogeneous cancer with limited therapeutic options and prognosis prediction models. Here, we analyzed formalin-fixed, paraffin-embedded (FFPE) samples of surgical resections by proteomic profiling, and stratified SCLC into three proteomic subtypes (S-I, S-II, and S-III) with distinct clinical outcomes and chemotherapy responses. The proteomic subtyping was an independent prognostic factor and performed better than current tumor-node-metastasis or Veterans Administration Lung Study Group staging methods. The subtyping results could be further validated using FFPE biopsy samples from an independent cohort, extending the analysis to both surgical and biopsy samples. The signatures of the S-II subtype in particular suggested potential benefits from immunotherapy. Differentially overexpressed proteins in S-III, the worst prognostic subtype, allowed us to nominate potential therapeutic targets, indicating that patient selection may bring new hope for previously failed clinical trials. Finally, analysis of an independent cohort of SCLC patients who had received immunotherapy validated the prediction that the S-II patients had better progression-free survival and overall survival after first-line immunotherapy. Collectively, our study provides the rationale for future clinical investigations to validate the current findings for more accurate prognosis prediction and precise treatments.

Unveiling novel targets in melanoma under melanogenesis stimulation and photodynamic therapy by redox proteomics.

Melanogenesis-stimulated B16-F10 cells enter in a quiescent state, present inhibited mitochondrial respiration and increased reactive oxygen species levels. These alterations suggest that these cells may be under redox signaling, allowing tumor survival. The aim of this study was to evaluate redox-modified proteins in B16-F10 cells after melanogenesis stimulation and rose bengal-photodynamic therapy (RB-PDT). A redox proteomics label-free approach based on the biotin switch assay technique with biotin-HPDP and N-ethylmaleimide was used to assess the thiol-oxidized protein profile. Aconitase was oxidized at Cys-448 and Cys-451, citrate synthase was oxidized at Cys-202 and aspartate aminotransferase (Got2) was oxidized at Cys-272 and Cys-274, exclusively after melanogenesis stimulation. After RB-PDT, only guanine nucleotide-binding protein subunit beta-2-like 1 (Gnb2l1) was oxidized (Cys-168). In contrast, melanogenesis stimulation followed by RB-PDT led to the oxidation of different cysteines in Gnb2l1 (Cys-153 and Cys-249). Besides that, glyceraldehyde-3-phosphate dehydrogenase (Gapdh) presented oxidation at Cys-245, peptidyl-prolyl cis-trans isomerase A (Ppia) was oxidized at Cys-161 and 5,6-dihydroxyindole-2-carboxylic acid oxidase (Tyrp1) was oxidized at Cys-65, Cys-30, and Cys-336 after melanogenesis stimulation followed by RB-PDT. The redox alterations observed in murine melanoma cells and identification of possible target proteins are of great importance to further understand tumor resistance mechanisms.

Evolution of the Umbilical Cord Blood Proteome Across Gestational Development.

Neonatal health is dependent on early risk stratification, diagnosis, and timely management of potentially devastating conditions, particularly in the setting of prematurity. Many of these conditions are poorly predicted in real-time by clinical data and current diagnostics. Umbilical cord blood may represent a novel source of molecular signatures that provides a window into the state of the fetus at birth. In this study, we comprehensively characterized the cord blood proteome of infants born between 24 to 42 weeks using untargeted mass spectrometry and functional enrichment analysis. We determined that the cord blood proteome at birth varies significantly across gestational development. Proteins that function in structural development and growth (e.g., extracellular matrix organization, lipid particle remodeling, and blood vessel development) are more abundant earlier in gestation. In later gestations, proteins with increased abundance are in immune response and inflammatory pathways, including complements and calcium-binding proteins. Furthermore, these data contribute to the knowledge of the physiologic state of neonates across gestational age, which is crucial to understand as we strive to best support postnatal development in preterm infants, determine mechanisms of pathology causing adverse health outcomes, and develop cord blood biomarkers to help tailor our diagnosis and therapeutics for critical neonatal conditions.

Clinical serum lipidomic profiling revealed potential lipid biomarkers for early diabetic retinopathy.

Diabetic retinopathy (DR) is a serious complication of diabetes featuring abnormal lipid metabolism. However, the specific lipid molecules associated with onset and progression remain unclear. We used a broad-targeted lipidomics approach to assess the lipid changes that occur before the proliferative retinopathy stage and to identify novel lipid biomarkers to distinguish between patients without DR (NDR) and with non-proliferative DR (NPDR). Targeted lipomics analysis was carried out on serum samples from patients with type I diabetes, including 20 NDRs and 20 NPDRs. The results showed that compared with the NDR group, 102 lipids in the NPDR group showed specific expressions. Four lipid metabolites including TAG58:2-FA18:1 were obtained using the Least Absolute Shrink And Selection Operator (LASSO) and Support Vector Machine Recursive Feature Elimination (SVM-RFE) methods. The four-lipid combination diagnostic models showed good predictive ability in both the discovery and validation sets, and were able to distinguish between NDR patients and NPDR patients. The identified lipid markers significantly improved diagnostic accuracy within the NPDR group. Our findings help to better understand the complexity and individual differences of DR lipid metabolism.

Two-Step Enrichment Facilitates Background Reduction for Proteomic Analysis of Lysosomes.

Lysosomes constitute the main degradative compartment of most mammalian cells and are involved in various cellular functions. Most of them are catalyzed by lysosomal proteins, which typically are low abundant, complicating their analysis by mass spectrometry-based proteomics. To increase analytical performance and to enable profiling of lysosomal content, lysosomes are often enriched. Two approaches have gained popularity in recent years, namely, superparamagnetic iron oxide nanoparticles (SPIONs) and immunoprecipitation from cells overexpressing a 3xHA-tagged version of TMEM192 (TMEM-IP). The effect of these approaches on the lysosomal proteome has not been investigated to date. We addressed this topic through a combination of both techniques and proteomic analysis of lysosome-enriched fractions. For SPIONs treatment, we identified altered cellular iron homeostasis and moderate changes of the lysosomal proteome. For overexpression of TMEM192, we observed more pronounced effects in lysosomal protein expression, especially for lysosomal membrane proteins and those involved in protein trafficking. Furthermore, we established a combined strategy based on the sequential enrichment of lysosomes with SPIONs and TMEM-IP. This enabled increased purity of lysosome-enriched fractions and, through TMEM-IP-based lysosome enrichment from SPIONs flow-through and eluate fractions, additional insights into the properties of individual approaches. All data are available via ProteomeXchange with PXD048696.

Plasma and CSF biomarkers of aging and cognitive decline in Caribbean vervets.

INTRODUCTION: Vervets are non-human primates that share high genetic homology with humans and develop amyloid beta (Aß) pathology with aging. We expand current knowledge by examining Aß pathology, aging, cognition, and biomarker proteomics. METHODS: Amyloid immunoreactivity in the frontal cortex and temporal cortex/hippocampal regions from archived vervet brain samples ranging from young adulthood to old age was quantified. We also obtained cognitive scores, plasma samples, and cerebrospinal fluid (CSF) samples in additional animals. Plasma and CSF proteins were quantified with platforms utilizing human antibodies. RESULTS: We found age-related increases in Aß deposition in both brain regions. Bioinformatic analyses assessed associations between biomarkers and age, sex, cognition, and CSF Aß levels, revealing changes in proteins related to immune-related inflammation, metabolism, and cellular processes. DISCUSSION: Vervets are an effective model of aging and early-stage Alzheimer's disease, and we provide translational biomarker data that both align with previous results in humans and provide a basis for future investigations. HIGHLIGHTS: We found changes in immune and metabolic plasma biomarkers associated with age and cognition. Cerebrospinal fluid (CSF) biomarkers revealed changes in cell signaling indicative of adaptative processes. TNFRSF19 (TROY) and Artemin co-localize with Alzheimer's disease pathology. Vervets are a relevant model for translational studies of early-stage Alzheimer's disease.

Application of Proteomics and Machine Learning Methods to Study the Pathogenesis of Diabetic Nephropathy and Screen Urinary Biomarkers.

Diabetic nephropathy (DN) has become the main cause of end-stage renal disease worldwide, causing significant health problems. Early diagnosis of the disease is quite inadequate. To screen urine biomarkers of DN and explore its potential mechanism, this study collected urine from 87 patients with type 2 diabetes mellitus (which will be classified into normal albuminuria, microalbuminuria, and macroalbuminuria groups) and 38 healthy subjects. Twelve individuals from each group were then randomly selected as the screening cohort for proteomics analysis and the rest as the validation cohort. The results showed that humoral immune response, complement activation, complement and coagulation cascades, renin-angiotensin system, and cell adhesion molecules were closely related to the progression of DN. Five overlapping proteins (KLK1, CSPG4, PLAU, SERPINA3, and ALB) were identified as potential biomarkers by machine learning methods. Among them, KLK1 and CSPG4 were positively correlated with the urinary albumin to creatinine ratio (UACR), and SERPINA3 was negatively correlated with the UACR, which were validated by enzyme-linked immunosorbent assay (ELISA). This study provides new insights into disease mechanisms and biomarkers for early diagnosis of DN.

Labeled-free quantitative proteomic analysis of cervical squamous cell carcinoma identifies potential protein biomarkers.

Background: Cervical cancer remains a prevalent cancer among women, and reliance on surgical and radio-chemical therapies can irreversibly affect patients' life span and quality of life. Thus, early diagnosis and further exploration into the pathogenesis of cervical cancer are crucial. Mass spectrometry technology is widely applied in clinical practice and can be used to further investigate the protein alterations during the onset of cervical cancer. Methods: Employing labeled-free quantitative proteomics technology and bioinformatics tools, we analyzed and compared the differential protein expression profiles between normal cervical squamous cell tissues and cervical squamous cell cancer tissues. GEPIA is an online website for analyzing the RNA sequencing expression data of tumor and normal tissue data from the TCGA and the GTEx databases. This approach aided in identifying qualitative and quantitative changes in key proteins related to the progression of cervical cancer. Results: Compared to normal samples, a total of 562 differentially expressed proteins were identified in cervical cancer samples, including 340 up-regulated and 222 down-regulated proteins. Gene ontology functional annotation, and KEGG pathway, and enrichment analysis revealed that the differentially expressed proteins mainly participated in metabolic pathways, spliceosomes, regulation of the actin cytoskeleton, and focal adhesion signaling pathways. Specifically, desmoplakin (DSP), protein phosphatase 1, regulatory (inhibitor) subunit 13 like (PPP1R13L) and ANXA8 may be involved in cervical tumorigenesis by inhibiting apoptotic signal transmission. Moreover, we used GEPIA database to validate the expression of DSP, PPP1R13L and ANXA8 in human cancers and normal cervix. Conclusion: In this study, we identified 562 differentially expressed proteins, and there were three proteins expressed higher in the cervical cancer tissues. The functions and signaling pathways of these differentially expressed proteins lay a theoretical foundation for elucidating the molecular mechanisms of cervical cancer.

Proteome signatures reveal homeostatic and adaptive oxidative responses by a putative co-chaperone, Wos2, to influence fungal virulence determinants in cryptococcosis.

The increasing prevalence of invasive fungal pathogens is dramatically changing the clinical landscape of infectious diseases, posing an imminent threat to public health. Specifically, Cryptococcus neoformans, the human opportunistic pathogen, expresses elaborate virulence mechanisms and is equipped with sophisticated adaptation strategies to survive in harsh host environments. This study extensively characterizes Wos2, an Hsp90 co-chaperone homolog, featuring bilateral functioning for both cryptococcal adaptation and the resulting virulence response. In this study, we evaluated the proteome and secretome signatures associated with wos2 deletion in enriched and infection-mimicking conditions to reveal Wos2-dependent regulation of the oxidative stress response through global translational reprogramming. The wos2Δ strain demonstrates defective intracellular and extracellular antioxidant protection systems, measurable through a decreased abundance of critical antioxidant enzymes and reduced growth in the presence of peroxide stress. Additional Wos2-associated stress phenotypes were observed upon fungal challenge with heat shock, osmotic stress, and cell membrane stressors. We demonstrate the importance of Wos2 for intracellular lifestyle of C. neoformans during in vitro macrophage infection and provide evidence for reduced phagosomal replication levels associated with wos2Δ. Accordingly, wos2Δ featured significantly reduced virulence within impacting fungal burden in a murine model of cryptococcosis. Our study highlights a vulnerable point in the fungal chaperone network that offers a therapeutic opportunity to interfere with both fungal virulence and fitness.IMPORTANCEThe global impact of fungal pathogens, both emerging and emerged, is undeniable, and the alarming increase in antifungal resistance rates hampers our ability to protect the global population from deadly infections. For cryptococcal infections, a limited arsenal of antifungals and increasing rates of resistance demand alternative therapeutic strategies, including an anti-virulence approach, which disarms the pathogen of critical virulence factors, empowering the host to remove the pathogens and clear the infection. To this end, we apply state-of-the-art mass spectrometry-based proteomics to evaluate the impact of a recently defined novel co-chaperone, Wos2, toward cryptococcal virulence using in vitro and in vivo models of infection. We explore global proteome and secretome remodeling driven by the protein and uncover the novel role in modulating the fungal oxidative stress response. Complementation of proteome findings with in vitro infectivity assays demonstrated the protective role of Wos2 within the macrophage phagosome, influencing fungal replication and survival. These results underscore differential cryptococcal survivability and weakened patterns of dissemination in the absence of wos2. Overall, our study establishes Wos2 as an important contributor to fungal pathogenesis and warrants further research into critical proteins within global stress response networks as potential druggable targets to reduce fungal virulence and clear infection.

Comprehensive proteomic analysis of HCoV-OC43 virions and virus-modulated extracellular vesicles.

Viruses are obligate parasites that depend on the cellular machinery for their propagation. Several viruses also incorporate cellular proteins that facilitate viral spread. Defining these cellular proteins is critical to decipher viral life cycles and delineate novel therapeutic strategies. While numerous studies have explored the importance of host proteins in coronavirus spread, information about their presence in mature virions is limited. In this study, we developed a protocol to highly enrich mature HCoV-OC43 virions and characterize them by proteomics. Recognizing that cells release extracellular vesicles whose content is modulated by viruses, and given our ability to separate virions from these vesicles, we also analyzed their protein content in both uninfected and infected cells. We uncovered 69 unique cellular proteins associated with virions including 31 high-confidence hits. These proteins primarily regulate RNA metabolism, enzymatic activities, vesicular transport, cell adhesion, metabolite interconversion, and translation. We further discovered that the virus had a profound impact on exosome composition, incorporating 47 novel cellular proteins (11 high confidence) and excluding 92 others (61 high confidence) in virus-associated extracellular vesicles compared to uninfected cells. Moreover, a dsiRNA screen revealed that 11 of 18 select targets significantly impacted viral yields, including proteins found in virions or extracellular vesicles. Overall, this study provides new and important insights into the incorporation of numerous host proteins into HCoV-OC43 virions, their biological significance, and the ability of the virus to modulate extracellular vesicles. IMPORTANCE: In recent years, coronaviruses have dominated global attention, making it crucial to develop methods to control them and prevent future pandemics. Besides viral proteins, host proteins play a significant role in viral propagation and offer potential therapeutic targets. Targeting host proteins is advantageous because they are less likely to mutate and develop resistance compared to viral proteins, a common issue with many antiviral treatments. In this study, we examined the protein content of the less virulent biosafety level 2 HCoV-OC43 virus as a stand-in for the more virulent SARS-CoV-2. Our findings reveal that several cellular proteins incorporated into the virion regulate viral spread. In addition, we report that the virus extensively modulates the content of extracellular vesicles, enhancing viral dissemination. This underscores the critical interplay between the virus, host proteins, and extracellular vesicles.

Investigating food production-associated DNA methylation changes in paleogenomes: Lack of consistent signals beyond technical noise.

The Neolithic transition introduced major diet and lifestyle changes to human populations across continents. Beyond well-documented bioarcheological and genetic effects, whether these changes also had molecular-level epigenetic repercussions in past human populations has been an open question. In fact, methylation signatures can be inferred from UDG-treated ancient DNA through postmortem damage patterns, but with low signal-to-noise ratios; it is thus unclear whether published paleogenomes would provide the necessary resolution to discover systematic effects of lifestyle and diet shifts. To address this we compiled UDG-treated shotgun genomes of 13 pre-Neolithic hunter-gatherers (HGs) and 21 Neolithic farmers (NFs) individuals from West and North Eurasia, published by six different laboratories and with coverage c.1×-58× (median = 9×). We used epiPALEOMIX and a Monte Carlo normalization scheme to estimate methylation levels per genome. Our paleomethylome dataset showed expected genome-wide methylation patterns such as CpG island hypomethylation. However, analyzing the data using various approaches did not yield any systematic signals for subsistence type, genetic sex, or tissue effects. Comparing the HG-NF methylation differences in our dataset with methylation differences between hunter-gatherers versus farmers in modern-day Central Africa also did not yield consistent results. Meanwhile, paleomethylome profiles did cluster strongly by their laboratories of origin. Using larger data volumes, minimizing technical noise and/or using alternative protocols may be necessary for capturing subtle environment-related biological signals from paleomethylomes.

Mutant Nrf2E79Q enhances the promotion and progression of a subset of oncogenic Ras keratinocytes and skin tumors.

Squamous cell carcinomas (SCCs), including lung, head & neck, bladder, and skin SCCs often display constitutive activation of the KEAP1-NRF2 pathway. Constitutive activation is achieved through multiple mechanisms, including activating mutations in NFE2L2 (NRF2). To determine the functional consequences of Nrf2 activation on skin SCC development, we assessed the effects of mutant Nrf2E79Q expression, one of the most common activating mutations in human SCCs, on tumor promotion and progression in the mouse skin multistage carcinogenesis model using a DMBA-initiation/TPA-promotion protocol where the Hras A->T mutation (Q61L) is the canonical driver mutation. Nrf2E79Q expression was temporally and conditionally activated in the epidermis at two stages of tumor development: 1) after DMBA initiation in the epidermis but before cutaneous tumor development and 2) in pre-existing DMBA-initiated/TPA-promoted squamous papillomas. Expression of Nrf2E79Q in the epidermis after DMBA initiation but before tumor occurrence inhibited the development/promotion of 70% of squamous papillomas. However, the remaining papillomas often displayed non-canonical Hras and Kras mutations and enhanced progression to SCCs compared to control mice expressing wildtype Nrf2. Nrf2E79Q expression in pre-existing tumors caused rapid regression of 60% of papillomas. The remaining papillomas displayed the expected canonical Hras A->T mutation (Q61L) and enhanced progression to SCCs. These results demonstrate that mutant Nrf2E79Q enhances the promotion and progression of a subset of skin tumors and alters the frequency and diversity of oncogenic Ras mutations when expressed early after initiation.

Unraveling the mechanisms of benzo[a]pyrene degradation by Pigmentiphaga kullae strain KIT-003 using a multi-omics approach.

Polycyclic aromatic hydrocarbons (PAHs), notably benzo[a]pyrene (BaP), are environmental contaminants with multiple adverse ecological implications. Numerous studies have suggested the use of BaP biodegradation using various bacterial strains to remove BaP from the environment. This study investigates the BaP biodegradation capability of Pigmentiphaga kullae strain KIT-003, isolated from the Nak-dong River (South Korea) under specific environmental conditions. The optimum conditions of biodegradation were found to be pH 7.0, 35°C, and a salinity of 0 %. GC-MS analysis suggested alternative pathways by which KIT-003 produced catechol from BaP through several intermediate metabolites, including 4-formylchrysene-5-carboxylic acid, 5,6-dihydro-5,6-dihydroxychrysene-5-carboxylic acid (isomer: 3,4-dihydro-3,4-dihydroxychrysene-4-carboxylic acid), naphthalene-1,2-dicarboxylic acid, and 2-hydroxy-1-naphthoic acid. Proteomic profiles indicated upregulation of enzymes associated with aromatic compound degradation, such as nahAc and nahB, and of those integral to the tricarboxylic acid cycle, reflecting the strain's adaptability to and degradation of BaP. Lipidomic analysis of KIT-003 demonstrated that BaP exposure induced an accumulation of glycerolipids such as diacylglycerol and triacylglycerol, indicating their crucial role in bacterial adaptation mechanisms under BaP stress. This study provides significant scientific knowledge regarding the intricate mechanisms involved in BaP degradation by microorganisms.

Disruption of the peripheral biological clock may play a role in sleep deprivation-induced dysregulation of lipid metabolism in both the daytime and nighttime phases.

STUDY OBJECTIVES: This study aimed to examine the effect of sleep deprivation (SD) on lipid metabolism or lipid metabolism regulation in the liver and white adipose tissue (WAT) during the light and dark phases and explored the possible mechanisms underlying the diurnal effect of SD on lipid metabolism associated with clock genes. METHODS: Male C57BL/6J mice aged 2 months were deprived of sleep daily for 20 h for ten consecutive days with weakly forced locomotion. The body weights and food consumption levels of the SD and control mice were recorded, and the mice were then sacrificed at ZT (zeitgeber time) 2 and ZT 14. The peripheral clock genes, enzymes involved in fat synthesis and catabolism in the WAT, and melatonin signalling pathway-mediated lipid metabolism in the liver were assessed. Untargeted metabolomics and tandem mass tag (TMT) proteomics were used to identify differential lipid metabolism pathways in the liver. RESULTS: Bodyweight gain and daily food consumption were dramatically elevated after SD. Profound disruptions in the diurnal regulation of the hepatic peripheral clock and enzymes involved in fat synthesis and catabolism in the WAT were observed, with a strong emphasis on hepatic lipid metabolic pathways, while melatonin signalling pathway-mediated lipid metabolism exhibited moderate changes. CONCLUSIONS: In mice, ten consecutive days of SD increased body weight gain and daily food consumption. In addition, SD profoundly disrupted lipid metabolism in the WAT and liver during the light and dark periods. These diurnal changes may be related to disorders of the peripheral biological clock.

Longitudinal analysis of wound healing response post SMILE and LASIK surgery using proteomic profiling of tears.

Different types of refractive surgeries often exhibit differences in wound healing responses. The current study investigated post-operative tear protein profiles in subjects who underwent LASIK and SMILE to elucidate global changes to the proteomic profile during the period the patient cornea undergoes healing. In this study, 10 patients underwent LASIK and SMILE surgery with a contralateral paired eye design. Tear samples were collected using Schirmer's strips preoperatively, at 1 month, 3 months and 6 months postoperatively. Quantitative ITRAQ labelled proteomics was performed and the tear protein ratios were normalized to pre-operative protein levels for each subject. Whole proteomics identified 1345 proteins in tears from LASIK and 1584 proteins in SMILE across time points. About 67 proteins were common in LASIK and SMILE tears across all the time points. Wound healing responses were differentially regulated between two refractive surgeries (SMILE and LASIK). The proteins Ceruloplasmin, Clusterin, Serotransferrin were upregulated at 1 month and 3 months and downregulated at 6 months post operatively in LASIK surgery where as in SMILE these were downregulated. Galectin 3 binding protein showed upregulation at 1 month and the levels decreased at 3 months and 6 months postop in LASIK tears whereas the levels increased at 3 months and 6 months post-op in SMILE tears. The levels of proteins that protect from oxidative stress were higher in SMILE as compared to LASIK postoperatively. The extracellular matrix proteins showed an increase in expression at 6 months in SMILE tears and it was stabilized at 6 months in LASIK tears post operatively. Different refractive surgeries induce distinct wound healing responses as identified in tears. This study has implications in targeting key proteins for improving the clinical outcome postrefractive surgery.

Proceedings of the EuBIC-MS developers meeting 2023.

The 2023 European Bioinformatics Community for Mass Spectrometry (EuBIC-MS) Developers Meeting was held from January 15th to January 20th, 2023, in Congressi Stefano Franscin at Monte Verità in Ticino, Switzerland. The participants were scientists and developers working in computational mass spectrometry (MS), metabolomics, and proteomics. The 5-day program was split between introductory keynote lectures and parallel hackathon sessions focusing on "Artificial Intelligence in proteomics" to stimulate future directions in the MS-driven omics areas. During the latter, the participants developed bioinformatics tools and resources addressing outstanding needs in the community. The hackathons allowed less experienced participants to learn from more advanced computational MS experts and actively contribute to highly relevant research projects. We successfully produced several new tools applicable to the proteomics community by improving data analysis and facilitating future research.

Comparing the BAD Protein Interactomes in 2D and 3D Cell Culture Using Proximity Labeling.

Protein-protein interaction studies using proximity labeling techniques, such as biotin ligase-based BioID, have become integral in understanding cellular processes. Most studies utilize conventional 2D cell culture systems, potentially missing important differences in protein behavior found in 3D tissues. In this study, we investigated the protein-protein interactions of a protein, Bcl-2 Agonist of cell death (BAD), and compared conventional 2D culture conditions to a 3D system, wherein cells were embedded within a 3D extracellular matrix (ECM) mimic. Using BAD fused to the engineered biotin ligase miniTurbo (BirA*), we identified both overlapping and distinct BAD interactomes under 2D and 3D conditions. The known BAD binding proteins 14-3-3 isoforms and Bcl-XL interacted with BAD in both 2D and 3D. Of the 131 BAD-interactors identified, 56% were specific to 2D, 14% were specific to 3D, and 30% were common to both conditions. Interaction network analysis demonstrated differential associations between 2D and 3D interactomes, emphasizing the impact of the culture conditions on protein interactions. The 2D-3D overlap interactome encapsulated the apoptotic program, which is a well-known role of BAD. The 3D unique pathways were enriched in ECM signaling, suggestive of hitherto unknown functions for BAD. Thus, exploring protein-protein interactions in 3D provides novel clues into cell behavior. This exciting approach has the potential to bridge the knowledge gap between tractable 2D cell culture and organoid-like 3D systems.

Identification of disease phenotypes in acetylcholine receptor-antibody myasthenia gravis using proteomics-based consensus clustering.

BACKGROUND: The clinical heterogeneity of myasthenia gravis (MG), an autoimmune disease defined by antibodies (Ab) directed against the postsynaptic membrane, constitutes a challenge for patient stratification and treatment decision making. Novel strategies are needed to classify patients based on their biological phenotypes aiming to improve patient selection and treatment outcomes. METHODS: For this purpose, we assessed the serum proteome of a cohort of 140 patients with anti-acetylcholine receptor-Ab-positive MG and utilised consensus clustering as an unsupervised tool to assign patients to biological profiles. For in-depth analysis, we used immunogenomic sequencing to study the B cell repertoire of a subgroup of patients and an in vitro assay using primary human muscle cells to interrogate serum-induced complement formation. FINDINGS: This strategy identified four distinct patient phenotypes based on their proteomic patterns in their serum. Notably, one patient phenotype, here named PS3, was characterised by high disease severity and complement activation as defining features. Assessing a subgroup of patients, hyperexpanded antibody clones were present in the B cell repertoire of the PS3 group and effectively activated complement as compared to other patients. In line with their disease phenotype, PS3 patients were more likely to benefit from complement-inhibiting therapies. These findings were validated in a prospective cohort of 18 patients using a cell-based assay. INTERPRETATION: Collectively, this study suggests proteomics-based clustering as a gateway to assign patients to a biological signature likely to benefit from complement inhibition and provides a stratification strategy for clinical practice. FUNDING: CN and CBS were supported by the Forschungskommission of the Medical Faculty of the Heinrich Heine University Düsseldorf. CN was supported by the Else Kröner-Fresenius-Stiftung (EKEA.38). CBS was supported by the Deutsche Forschungsgemeinschaft (DFG-German Research Foundation) with a Walter Benjamin fellowship (project 539363086). The project was supported by the Ministry of Culture and Science of North Rhine-Westphalia (MODS, "Profilbildung 2020" [grant no. PROFILNRW-2020-107-A]).

Proteomic predictors of individualized nutrient-specific insulin secretion in health and disease.

Population-level variation and mechanisms behind insulin secretion in response to carbohydrate, protein, and fat remain uncharacterized. We defined prototypical insulin secretion responses to three macronutrients in islets from 140 cadaveric donors, including those with type 2 diabetes. The majority of donors' islets exhibited the highest insulin response to glucose, moderate response to amino acid, and minimal response to fatty acid. However, 9% of donors' islets had amino acid responses, and 8% had fatty acid responses that were larger than their glucose-stimulated insulin responses. We leveraged this heterogeneity and used multi-omics to identify molecular correlates of nutrient responsiveness, as well as proteins and mRNAs altered in type 2 diabetes. We also examined nutrient-stimulated insulin release from stem cell-derived islets and observed responsiveness to fat but not carbohydrate or protein-potentially a hallmark of immaturity. Understanding the diversity of insulin responses to carbohydrate, protein, and fat lays the groundwork for personalized nutrition.