A cell autonomous regulator of neuronal excitability modulates tau in Alzheimer's disease vulnerable neurons.

Neurons from layer II of the entorhinal cortex (ECII) are the first to accumulate tau protein aggregates and degenerate during prodromal Alzheimer's disease. Gaining insight into the molecular mechanisms underlying this vulnerability will help reveal genes and pathways at play during incipient stages of the disease. Here, we use a data-driven functional genomics approach to model ECII neurons in silico and identify the proto-oncogene DEK as a regulator of tau pathology. We show that epigenetic changes caused by Dek silencing alter activity-induced transcription, with major effects on neuronal excitability. This is accompanied by the gradual accumulation of tau in the somatodendritic compartment of mouse ECII neurons in vivo, reactivity of surrounding microglia, and microglia-mediated neuron loss. These features are all characteristic of early Alzheimer's disease. The existence of a cell-autonomous mechanism linking Alzheimer's disease pathogenic mechanisms in the precise neuron type where the disease starts provides unique evidence that synaptic homeostasis dysregulation is of central importance in the onset of tau pathology in Alzheimer's disease.

Gel-Assisted Proteome Position Integral Shift Assay Returns Molecular Weight to Shotgun Proteomics and Identifies Caspase 3 Substrates.

Here, we present a high-throughput virtual top-down proteomics approach that restores the molecular weight (MW) information in shotgun proteomics and demonstrates its utility in studying proteolytic events in programmed cell death. With gel-assisted proteome position integral shift (GAPPIS), we quantified over 7000 proteins in staurosporine-induced apoptotic HeLa cells and identified 84 proteins exhibiting in a statistically significant manner at least two of the following features: (i) a negative MW shift; (ii) an elevated ratio in a pair of a semitryptic and tryptic peptide, (iii) a negative shift in the standard deviation of MW estimated for different peptides, and (iv) a negative shift in skewness of the same data. Of these proteins, 58 molecules were previously unreported caspase 3 substrates. Further analysis identified the preferred cleavage sites consistent with the known caspase cleavages after the DXXD motif. As a powerful tool for high-throughput MW analysis simultaneously with the conventional expression analysis, the GAPPIS assay can prove useful in studying a broad range of biological processes involving proteolytic events.

Network analysis reveals age- and virus-specific circuits in nasal epithelial cells of extremely premature infants.

BACKGROUND AND OBJECTIVES: Viral respiratory infections significantly affect young children, particularly extremely premature infants, resulting in high hospitalization rates and increased health-care burdens. Nasal epithelial cells, the primary defense against respiratory infections, are vital for understanding nasal immune responses and serve as a promising target for uncovering underlying molecular and cellular mechanisms. METHODS: Using a trans-well pseudostratified nasal epithelial cell system, we examined age-dependent developmental differences and antiviral responses to influenza A and respiratory syncytial virus through systems biology approaches. RESULTS: Our studies revealed differences in innate-receptor repertoires, distinct developmental pathways, and differentially connected antiviral network circuits between neonatal and adult nasal epithelial cells. Consensus network analysis identified unique and shared cellular-viral networks, emphasizing highly relevant virus-specific pathways, independent of viral replication kinetics. CONCLUSION: This research highlights the importance of nasal epithelial cells in innate antiviral immune responses and offers crucial insights that allow for a deeper understanding of age-related differences in nasal epithelial cell immunity following respiratory virus infections.

Proteomic workflows for deep phenotypic profiling of 3D organotypic liver models.

Organotypic human tissue models constitute promising systems to facilitate drug discovery and development. They allow to maintain native cellular phenotypes and functions, which enables long-term pharmacokinetic and toxicity studies, as well as phenotypic screening. To trace relevant phenotypic changes back to specific targets or signaling pathways, comprehensive proteomic profiling is the gold-standard. A multitude of proteomic workflows have been applied on 3D tissue models to quantify their molecular phenotypes; however, their impact on analytical results and biological conclusions in this context has not been evaluated. The performance of twelve mass spectrometry-based global proteomic workflows that differed in the amount of cellular input, lysis protocols and quantification methods was compared for the analysis of primary human liver spheroids. Results differed majorly between protocols in the total number and subcellular compartment bias of identified proteins, which is particularly relevant for the reliable quantification of transporters and drug metabolizing enzymes. Using a model of metabolic dysfunction-associated steatotic liver disease, we furthermore show that critical disease pathways are robustly identified using a standardized high throughput-compatible workflow based on thermal lysis, even using only individual spheroids (1500 cells) as input. The results increase the applicability of proteomic profiling to phenotypic screens in organotypic microtissues and provide a scalable platform for deep phenotyping from limited biological material.

Cancer cell immunity-related protein co-expression networks are associated with early-stage solid-predominant lung adenocarcinoma.

Background: Solid-predominant lung adenocarcinoma (SPA), which is one of the high-risk subtypes with poor prognosis and unsatisfactory response to chemotherapy and targeted therapy in lung adenocarcinoma, remains molecular profile unclarified. Weighted correlation network analysis (WGCNA) was used for data mining, especially for studying biological networks based on pairwise correlations between variables. This study aimed to identify disease-related protein co-expression networks associated with early-stage SPA. Methods: We assessed cancerous cells laser-microdissected from formalin-fixed paraffin-embedded (FFPE) tissues of a SPA group (n = 5), referencing a low-risk subtype, a lepidic predominant subtype group (LPA) (n = 4), and another high-risk subtype, micropapillary predominant subtype (MPA) group (n = 3) and performed mass spectrometry-based proteomic analysis. Disease-related co-expression networks associated with the SPA subtype were identified by WGCNA and their upstream regulators and causal networks were predicted by Ingenuity Pathway Analysis. Results: Among the forty WGCNA network modules identified, two network modules were found to be associated significantly with the SPA subtype. Canonical enriched pathways were highly associated with cellular growth, proliferation, and immune response. Upregulated HLA class I molecules HLA-G and HLA-B implicated high mutation burden and T cell activation in the SPA subtype. Upstream analysis implicated the involvement of highly activated oncogenic regulators, MYC, MLXIPL, MYCN, the redox master regulator NFE2L2, and the highly inhibited LARP1, leading to oncogenic IRES-dependent translation, and also regulators of the adaptive immune response, including highly activated IFNG, TCRD, CD3-TCR, CD8A, CD8B, CD3, CD80/CD86, and highly inhibited LILRB2. Interestingly, the immune checkpoint molecule HLA-G, which is the counterpart of LILRB2, was highly expressed characteristically in the SPA subtype and might be associated with antitumor immunity. Conclusion: Our findings provide a disease molecular profile based on protein co-expression networks identified for the high-risk solid predominant adenocarcinoma, which will help develop future therapeutic strategies.

EquiCP: Targeted Single-Cell Proteomics by Mass Spectrometry with Isobaric Labeled Multiplexing.

Nontargeted single-cell proteomics analysis by mass spectrometry with sample multiplexing utilizing isobaric labeling is often performed using a carrier proteome. The presented protocol describes a targeted approach that replaces the carrier proteome with a set of synthetic peptides from selected proteins, which improves the identification and quantification of these proteins in single human cells.

A Sample Preparation Procedure for Isobaric Labeling-Based Single-Cell Proteomics.

Mass spectrometry-based proteomics has traditionally been limited by the amount of input material for analysis. Single-cell proteomics has emerged as a challenging discipline due to the ultra-high sensitivity required. Isobaric labeling-based multiplex strategies with a carrier proteome offer an approach to overcome the sensitivity limitations. Following this as the basic strategy, we show here the general workflow for preparing cells for single-cell mass spectrometry-based proteomics. This protocol can also be applied to manually isolated cells when large cells, such as cardiomyocytes, are difficult to isolate properly with conventional fluorescence-activated cell sorting (FACS) sorter methods.

A multi-platform analysis of human gingival crevicular fluid reveals ferroptosis as a relevant regulated cell death mechanism during the clinical progression of periodontitis.

Ferroptosis is implicated in the pathogenesis of numerous chronic-inflammatory diseases, yet its association with progressive periodontitis remains unexplored. To investigate the involvement and significance of ferroptosis in periodontitis progression, we assessed sixteen periodontitis-diagnosed patients. Disease progression was clinically monitored over twelve weeks via weekly clinical evaluations and gingival crevicular fluid (GCF) collection was performed for further analyses. Clinical metrics, proteomic data, in silico methods, and bioinformatics tools were combined to identify protein profiles linked to periodontitis progression and to explore their potential connection with ferroptosis. Subsequent western blot analyses validated key findings. Finally, a single-cell RNA sequencing (scRNA-seq) dataset (GSE164241) for gingival tissues was analyzed to elucidate cellular dynamics during periodontitis progression. Periodontitis progression was identified as occurring at a faster rate than traditionally thought. GCF samples from progressing and non-progressing periodontal sites showed quantitative and qualitatively distinct proteomic profiles. In addition, specific biological processes and molecular functions during progressive periodontitis were revealed and a set of hub proteins, including SNCA, CA1, HBB, SLC4A1, and ANK1 was strongly associated with the clinical progression status of periodontitis. Moreover, we found specific proteins - drivers or suppressors - associated with ferroptosis (SNCA, FTH1, HSPB1, CD44, and GCLC), revealing the co-occurrence of this specific type of regulated cell death during the clinical progression of periodontitis. Additionally, the integration of quantitative proteomic data with scRNA-seq analysis suggested the susceptibility of fibroblasts to ferroptosis. Our analyses reveal proteins and processes linked to ferroptosis for the first time in periodontal patients, which offer new insights into the molecular mechanisms of progressive periodontal disease. These findings may lead to novel diagnostic and therapeutic strategies.

Genetic variants and down-regulation of CACNA1H in pheochromocytoma.

Pheochromocytoma (PCC) and abdominal paraganglioma (aPGL) (together abbreviated PPGL) frequently present with an underlying genetic event in a PPGL driver gene, and additional susceptibility genes are anticipated. Here, we re-analyzed whole-exome sequencing data for PCC patients and identified two patients with rare missense variants in the calcium voltage-gated channel subunit 1H gene (CACNA1H). CACNA1H variants were also found in the clinical setting in PCC patients using targeted sequencing and from analysis of The Cancer Genome Atlas database. In total, CACNA1H variants were found in six PCC cases. Three of these were constitutional, and two are known to have functional consequences on hormone production and gene expression in primary aldosteronism and aldosterone-producing adrenocortical adenoma. In general, PPGL exhibited reduced CACNA1H mRNA expression as compared to normal adrenal. Immunohistochemistry showed strong CACNA1H (CaV3.2) staining in adrenal medulla while PPGL typically had weak or negative staining. Reduced CACNA1H gene expression was especially pronounced in PCC compared to aPGL and in PPGL with cluster 2 kinase signaling phenotype. Furthermore, CACNA1H levels correlated with HIF1A and HIF2A. Moreover, TCGA data revealed a correlation between CACNA1H methylation density and gene expression. Expression of rCacna1h in PC12 cells induced differential protein expression profiles, determined by mass spectrometry, as well as a shift in the membrane potential where maximum calcium currents were observed, as determined by electrophysiology. The findings suggest the involvement of CACNA1H/CaV3.2 in pheochromocytoma development and establish a potential link between the etiology of adrenomedullary and adrenocortical tumor development.

Multifaceted Proteome Analysis at Solubility, Redox, and Expression Dimensions for Target Identification.

Multifaceted interrogation of the proteome deepens the system-wide understanding of biological systems; however, mapping the redox changes in the proteome has so far been significantly more challenging than expression and solubility/stability analyses. Here, the first high-throughput redox proteomics approach integrated with expression analysis (REX) is devised and combined with the Proteome Integral Solubility Alteration (PISA) assay. The whole PISA-REX experiment with up to four biological replicates can be multiplexed into a single tandem mass tag TMTpro set. For benchmarking this compact tool, HCT116 cells treated with auranofin are analyzed, showing great improvement compared with previous studies. PISA-REX is then applied to study proteome remodeling upon stimulation of human monocytes by interferon α (IFN-α). Applying this tool to study the proteome changes in plasmacytoid dendritic cells (pDCs) isolated from wild-type versus Ncf1-mutant mice treated with interferon α, shows that NCF1 deficiency enhances the STAT1 pathway and modulates the expression, solubility, and redox state of interferon-induced proteins. Providing comprehensive multifaceted information on the proteome, the compact PISA-REX has the potential to become an industry standard in proteomics and to open new windows into the biology of health and disease.

Epigenetic modulators link mitochondrial redox homeostasis to cardiac function in a sex-dependent manner.

While excessive production of reactive oxygen species (ROS) is a characteristic hallmark of numerous diseases, clinical approaches that ameliorate oxidative stress have been unsuccessful. Here, utilizing multi-omics, we demonstrate that in cardiomyocytes, mitochondrial isocitrate dehydrogenase (IDH2) constitutes a major antioxidative defense mechanism. Paradoxically reduced expression of IDH2 associated with ventricular eccentric hypertrophy is counterbalanced by an increase in the enzyme activity. We unveil redox-dependent sex dimorphism, and extensive mutual regulation of the antioxidative activities of IDH2 and NRF2 by a feedforward network that involves 2-oxoglutarate and L-2-hydroxyglutarate and mediated in part through unconventional hydroxy-methylation of cytosine residues present in introns. Consequently, conditional targeting of ROS in a murine model of heart failure improves cardiac function in sex- and phenotype-dependent manners. Together, these insights may explain why previous attempts to treat heart failure with antioxidants have been unsuccessful and open new approaches to personalizing and, thereby, improving such treatment.

Proteomic analysis of the urothelial cancer landscape.

Urothelial bladder cancer (UC) has a wide tumor biological spectrum with challenging prognostic stratification and relevant therapy-associated morbidity. Most molecular classifications relate only indirectly to the therapeutically relevant protein level. We improve the pre-analytics of clinical samples for proteome analyses and characterize a cohort of 434 samples with 242 tumors and 192 paired normal mucosae covering the full range of UC. We evaluate sample-wise tumor specificity and rank biomarkers by target relevance. We identify robust proteomic subtypes with prognostic information independent from histopathological groups. In silico drug prediction suggests efficacy of several compounds hitherto not in clinical use. Both in silico and in vitro data indicate predictive value of the proteomic clusters for these drugs. We underline that proteomics is relevant for personalized oncology and provide abundance and tumor specificity data for a large part of the UC proteome ( www.cancerproteins.org ).