Visual account of protein investment in cellular functions

Directional Endothelial Communication by Polarized Extracellular Vesicle Release

BACKGROUND

Extracellular vesicles (EVs) contain bioactive cargo including miRNAs and proteins that are released by cells during cell-cell communication. Endothelial cells (ECs) form the innermost lining of all blood vessels, interfacing with cells in the circulation and vascular wall. It is unknown whether ECs release EVs capable of governing recipient cells within these 2 separate compartments. Given their boundary location, we propose ECs use bidirectional release of distinct EV cargo in quiescent (healthy) and activated (atheroprone) states to communicate with cells within the circulation and blood vessel wall.

METHODS

EVs were isolated from primary human aortic ECs (plate and transwell grown; ±IL [interleukin]-1β activation), quantified, visualized, and analyzed by miRNA transcriptomics and proteomics. Apical and basolateral EC-EV release was determined by miRNA transfer, total internal reflection fluorescence and electron microscopy. Vascular reprogramming (RNA sequencing) and functional assays were performed on primary human monocytes or smooth muscle cells±EC-EVs.

RESULTS

Activated ECs increased EV release, with miRNA and protein cargo related to atherosclerosis. EV-treated monocytes and smooth muscle cells revealed activated EC-EV altered pathways that were proinflammatory and atherogenic. ECs released more EVs apically, which increased with activation. Apical and basolateral EV cargo contained distinct transcriptomes and proteomes that were altered by EC activation. Notably, activated basolateral EC-EVs displayed greater changes in the EV secretome, with pathways specific to atherosclerosis. In silico analysis determined compartment-specific cargo released by the apical and basolateral surfaces of ECs can reprogram monocytes and smooth muscle cells, respectively, with functional assays and in vivo imaging supporting this concept.

CONCLUSIONS

Demonstrating that ECs are capable of polarized EV cargo loading and directional EV secretion reveals a novel paradigm for endothelial communication, which may ultimately enhance the design of endothelial-based therapeutics for cardiovascular diseases such as atherosclerosis where ECs are persistently activated.

Inflammatory biotype of ADHD is linked to chronic stress: a data-driven analysis of the inflammatory proteome

The association between Attention Deficit Hyperactivity Disorder (ADHD) and low-grade inflammation has been explored in children but rarely in adults. Inflammation is characteristic of some, but not all, patients with ADHD and might be influenced by ADHD medication but also lifestyle factors including nutrition, smoking, and stress. It is also still unclear if any specific symptoms are related to inflammation. Therefore, we assessed 96 inflammatory proteins in a deeply phenotyped cohort of 126 adult ADHD participants with a stable medication status using OLINK technology. A data-based, unsupervised hierarchical clustering method could identify two distinct biotypes within the 126 ADHD participants based on their inflammatory profile: a higher inflammatory potential (HIP) and a lower inflammatory protein potential (LIP) group. Biological processes that differed strongest between groups were related to the NF-κB pathway, chemokine signaling, IL-17 signaling, metabolic alterations, and chemokine attraction. A comparison of sample characteristics revealed that the HIP group was more likely to have higher levels of chronic stress (p < 0.001), a higher clinical global impression scale score (p = 0.030), and a higher risk for suicide (p = 0.032). Medication status did not influence protein levels significantly (p ≥ 0.074), but psychotropic co-medication (p ≤ 0.009) did. In conclusion, our data suggest the presence of two distinct biotypes in adults with ADHD. Higher levels of inflammatory proteins in ADHD are linked to higher levels of chronic perceived stress in a linear fashion. Further research on inflammation in adults with ADHD should take stress levels into account.

Integrating TCGA and Single-Cell Sequencing Data for Hepatocellular Carcinoma: A Novel Glycosylation (GLY)/Tumor Microenvironment (TME) Classifier to Predict Prognosis and Immunotherapy Response

The major liver cancer subtype is hepatocellular carcinoma (HCC). Studies have indicated that a better prognosis is related to the presence of tumor-infiltrating lymphocytes (TILs) in HCC. However, the molecular pathways that drive immune cell variation in the tumor microenvironment (TME) remain poorly understood. Glycosylation (GLY)-related genes have a vital function in the pathogenesis of numerous tumors, including HCC. This study aimed to develop a GLY/TME classifier based on glycosylation-related gene scores and tumor microenvironment scores to provide a novel prognostic model to improve the prediction of clinical outcomes. The reliability of the signatures was assessed using receiver operating characteristic (ROC) and survival analyses and was verified with external datasets. Furthermore, the correlation between glycosylation-related genes and other cells in the immune environment, the immune signature of the GLY/TME classifier, and the efficacy of immunotherapy were also investigated. The GLY score low/TME score high subgroup showed a favorable prognosis and therapeutic response based on significant differences in immune-related molecules and cancer cell signaling mechanisms. We evaluated the prognostic role of the GLY/TME classifier that demonstrated overall prognostic significance for prognosis and therapeutic response before treatment, which may provide new options for creating the best possible therapeutic approaches for patients.

Proteomic Profiling of Advanced Melanoma Patients to Predict Therapeutic Response to Anti-PD-1 Therapy

PURPOSE

Despite high clinical need, there are no biomarkers that accurately predict the response of patients with metastatic melanoma to anti-PD-1 therapy.

EXPERIMENTAL DESIGN

In this multicenter study, we applied protein depletion and enrichment methods prior to various proteomic techniques to analyze a serum discovery cohort (n = 56) and three independent serum validation cohorts (n = 80, n = 12, n = 17). Further validation analyses by literature and survival analysis followed.

RESULTS

We identified several significantly regulated proteins as well as biological processes such as neutrophil degranulation, cell-substrate adhesion, and extracellular matrix organization. Analysis of the three independent serum validation cohorts confirmed the significant differences between responders (R) and nonresponders (NR) observed in the initial discovery cohort. In addition, literature-based validation highlighted 30 markers overlapping with previously published signatures. Survival analysis using the TCGA database showed that overexpression of 17 of the markers we identified correlated with lower overall survival in patients with melanoma.

CONCLUSIONS

Ultimately, this multilayered serum analysis led to a potential marker signature with 10 key markers significantly altered in at least two independent serum cohorts: CRP, LYVE1, SAA2, C1RL, CFHR3, LBP, LDHB, S100A8, S100A9, and SAA1, which will serve as the basis for further investigation. In addition to patient serum, we analyzed primary melanoma tumor cells from NR and found a potential marker signature with four key markers: LAMC1, PXDN, SERPINE1, and VCAN.

Systems Pharmacodynamic Model of Combined Gemcitabine and Trabectedin in Pancreatic Cancer Cells. Part I: Effects on Signal Transduction Pathways Related to Tumor Growth

Pancreatic ductal adenocarcinoma (PDAC) is often chemotherapy-resistant, and novel drug combinations would fill an unmet clinical need. Previously we reported synergistic cytotoxic effects of gemcitabine and trabectedin on pancreatic cancer cells, but underlying protein-level interaction mechanisms remained unclear. We employed a reliable, sensitive, comprehensive, quantitative, high-throughput IonStar proteomic workflow to investigate the time course of gemcitabine and trabectedin effects, alone and combined, upon pancreatic cancer cells. MiaPaCa-2 cells were incubated with vehicle (controls), gemcitabine, trabectedin, and their combinations over 72 hours. Samples were collected at intervals and analyzed using the label-free IonStar liquid chromatography-mass spectrometry (LC-MS/MS) workflow to provide temporal quantification of protein expression for 4,829 proteins in four experimental groups. To characterize diverse signal transduction pathways, a comprehensive systems pharmacodynamic (SPD) model was developed. The analysis is presented in two parts. Here, Part I describes drug responses in cancer cell growth and migration pathways included in the full model: receptor tyrosine kinase- (RTK), integrin-, G-protein coupled receptor- (GPCR), and calcium-signaling pathways. The developed model revealed multiple underlying mechanisms of drug actions, provides insight into the basis of drug interaction synergism, and offers a scientific rationale for potential drug combination strategies.

NME4 mediates metabolic reprogramming and promotes nonalcoholic fatty liver disease progression

Nonalcoholic fatty liver disease (NAFLD) is mainly characterized by excessive fat accumulation in the liver, and it is associated with liver-related complications and adverse systemic diseases. NAFLD has become the most prevalent liver disease; however, effective therapeutic agents for NAFLD are still lacking. We combined clinical data with proteomics and metabolomics data, and found that the mitochondrial nucleoside diphosphate kinase NME4 plays a central role in mitochondrial lipid metabolism. Nme4 is markedly upregulated in mice fed with high-fat diet, and its expression is positively correlated with the level of steatosis. Hepatic deletion of Nme4 suppresses the progression of hepatic steatosis. Further studies demonstrated that NME4 interacts with several key enzymes in coenzyme A (CoA) metabolism and increases the level of acetyl-CoA and malonyl-CoA, which are the major lipid components of the liver in NAFLD. Increased level of acetyl-CoA and malonyl-CoA  lead to increased triglyceride levels and lipid accumulation in the liver. Taken together, these findings reveal that NME4 is a critical regulator of NAFLD progression and a potential therapeutic target for NAFLD.

Fitness and transcriptomic analysis of pathogenic Vibrio parahaemolyticus in seawater at different shellfish harvesting temperatures

IMPORTANCE

Given the involvement of Vibrio parahaemolyticus (Vp) in a wide range of seafood outbreaks, a systematical characterization of Vp fitness and transcriptomic changes at temperatures of critical importance for seafood production and storage is needed. In this study, one of each virulent Vp strain (tdh+ and trh+) was tested. While no difference in survival behavior of the two virulent strains was observed at 10°C, the tdh+ strain had a faster growth rate than the trh+ strain at 30°C. Transcriptomic analysis showed that a significantly higher number of genes were upregulated at 30°C than at 10°C. The majority of differentially expressed genes of Vp at 30°C were annotated to functional categories supporting cellular growth. At 10°C, the downregulation of the biofilm formation and histidine metabolism indicates that the current practice of storing seafood at low temperatures not only protects seafood quality but also ensures seafood safety.

Potential biomarkers for psoriasis topical treatment by in-depth serum proteomics

BACKGROUND

Psoriasis is a chronic skin disease, and topical sequential therapy with a combination of calcipotriol and calcipotriol betamethasone is currently approved topical treatment. However, the exact mechanism by which this treatment regimen relieves psoriasis is unknown.

METHOD

We assembled a cohort of 65 psoriasis patients and divided post-treatment cohort into responder group and non-responder group according to the Psoriasis Area Severity Index (PASI) score after 12-week treatment. We measured the expression levels of proteins in collected 130 serum samples using our in-depth proteomics platform with a data-independent acquisition mass spectrometer and antibody microarray. We performed bioinformatics analyses of the biologic processes and signaling pathways that were changed in the responder group and constructed a proteomics landscape of psoriasis pathogenesis response to treatment. We then validated the biomarkers of disease severity in an independent cohort of 88 samples using an enzyme-linked immunosorbent assay.

RESULTS

We first identified 174 differentially expressed proteins (DEPs) for comparative analysis of proteins between responders and non-responders at baseline (p < 0.05). Then pathway analysis showed that the responders focused more on signaling molecules and interaction, complement and coagulation cascades, whereas the non-responders more on signal transduction and IL-17 signaling pathways. We further identified four candidate biomarkers (COLEC11, C1QA, BNC2, ITIH4) response to treatment. We also found 125 DEPs (p < 0.05) after treatment compared with before treatment in responder group. Pathway analysis showed an enrichment in pathways related to complement and coagulation cascades, phagosome, ECM-receptor interaction, cholesterol metabolism, vitamin digestion and absorption. CD14 was validated as potential biomarkers for the disease severity of psoriasis and treatment targets.

CONCLUSION

In this work, we analyzed the response to topical sequential therapy and finally identified four biomarkers. Additionally, we found that topical sequential therapy may alleviate psoriasis by regulating lipid metabolism and modulating the immune response by affecting the complement activation process.

Integrative serum proteomics analysis reveals distinct immune and cardiovascular profile dysregulation in erythrodermic psoriasis

In-depth analysis of circulating proteome alterations identified that erythrodermic psoriasis (EP) presented a dysregulated serum proteome with distinct inflammation elevation, immune activation and metabolic disturbance. We found that EP harboured a blended immune milieu with distinct T helper (Th)17/Th1 skewing and mild Th2 activation. Additionally, atherosclerosis signalling were substantially increased in EP.

Characterisation of macrophage infiltration and polarisation based on integrated transcriptomic and histological analyses in Primary Sjögren's syndrome

Background

Primary Sjögren's syndrome (pSS) is a progressive inflammatory autoimmune disease. Immune cell infiltration into glandular lobules and ducts and glandular destruction are the pathophysiological hallmarks of pSS. Macrophages are one of the most important cells involved in the induction and regulation of an inflammatory microenvironment. Although studies have reported that an abnormal tissue microenvironment alters the metabolic reprogramming and polarisation status of macrophages, the mechanisms driving macrophage infiltration and polarisation in pSS remain unclear.

Methods

Immune cell subsets were characterised using the single-cell RNA sequencing (scRNA-seq) data of peripheral blood mononuclear cells (PBMCs) from patients with pSS (n = 5) and healthy individuals (n = 5) in a public dataset. To evaluate macrophage infiltration and polarisation in target tissues, labial salivary gland biopsy tissues were subjected to histological staining and bulk RNA-seq (pSS samples, n = 24; non-pSS samples, n = 12). RNA-seq data were analysed for the construction of macrophage co-expression modules, enrichment of biological processes and deconvolution-based screening of immune cell types.

Results

Detailed mapping of PBMCs using scRNA-seq revealed five major immune cell subsets in pSS, namely, T cells, B cells, natural killer (NK) cells, dendritic cells (DCs) and monocyte-macrophages. The monocyte-macrophage subset was large and had strong inflammatory gene signatures. This subset was found to play an important role in the generation of reactive oxygen species and communicate with other innate and adaptive immune cells. Histological staining revealed that the number of tissue-resident macrophages was high in damaged glandular tissues, with the cells persistently surrounding the tissues. Analysis of RNA-seq data using multiple algorithms demonstrated that the high abundance of pro-inflammatory M1 macrophages was accompanied by the high abundance of other infiltrating immune cells, senescence-associated secretory phenotype and evident metabolic reprogramming.

Conclusion

Macrophages are among the most abundant innate immune cells in PBMCs and glandular tissues in patients with pSS. A bidirectional relationship exists between macrophage polarisation and the inflammatory microenvironment, which may serve as a therapeutic target for pSS.

The combined signatures of G protein-coupled receptor family and immune landscape provide a prognostic and therapeutic biomarker in endometrial carcinoma

G protein-coupled receptors (GPRs) are one of the largest surface receptor superfamilies, and many of them play essential roles in biological processes, including immune responses. In this study, we aim to construct a GPR- and tumor immune environment (TME-i)-associated risk signature to predict the prognosis of patients with endometrial carcinoma (EC). The GPR score was generated by applying univariate Cox regression and the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression in succession. This involved identifying the differentially expressed genes (DEGs) in the Cancer Genome Atlas-Uterine Corpus Endometrioid Carcinoma (TCGA-UCEC) cohort. Simultaneously, the CIBERSORT algorithm was applied to identify the protective immune cells for TME score construction. Subsequently, we combined the GPR and TME scores to establish a GPR-TME classifier for conducting clinical prognosis assessments. Various functional annotation algorithms were used to conduct biological process analysis distinguished by GPR-TME subgroups. Furthermore, weighted correlation network analysis (WGCNA) was applied to depict the tumor somatic mutations landscapes. Finally, we compared the immune-related molecules between GPR-TME subgroups and resorted to the Tumor Immune Dysfunction and Exclusion (TIDE) for immunotherapy response prediction. The mRNA and protein expression of GPR-related gene P2RY14 were, respectively, validated by RT-PCR in clinical samples and HPA database. To conclude, our GPR-TME classifier may aid in predicting the EC patients' prognosis and immunotherapy responses.

Combined signature of N7-methylguanosine regulators with their related genes and the tumor microenvironment: a prognostic and therapeutic biomarker for breast cancer

Background

Identifying predictive markers for breast cancer (BC) prognosis and immunotherapeutic responses remains challenging. Recent findings indicate that N7-methylguanosine (m7G) modification and the tumor microenvironment (TME) are critical for BC tumorigenesis and metastasis, suggesting that integrating m7G modifications and TME cell characteristics could improve the predictive accuracy for prognosis and immunotherapeutic responses.

Methods

We utilized bulk RNA-sequencing data from The Cancer Genome Atlas Breast Cancer Cohort and the GSE42568 and GSE146558 datasets to identify BC-specific m7G-modification regulators and associated genes. We used multiple m7G databases and RNA interference to validate the relationships between BC-specific m7G-modification regulators (METTL1 and WDR4) and related genes. Single-cell RNA-sequencing data from GSE176078 confirmed the association between m7G modifications and TME cells. We constructed an m7G-TME classifier, validated the results using an independent BC cohort (GSE20685; n = 327), investigated the clinical significance of BC-specific m7G-modifying regulators by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis, and performed tissue-microarray assays on 192 BC samples.

Results

Immunohistochemistry and RT-qPCR results indicated that METTL1 and WDR4 overexpression in BC correlated with poor patient prognosis. Moreover, single-cell analysis revealed relationships between m7G modification and TME cells, indicating their potential as indicators of BC prognosis and treatment responses. The m7G-TME classifier enabled patient subgrouping and revealed significantly better survival and treatment responses in the m7Glow+TMEhigh group. Significant differences in tumor biological functions and immunophenotypes occurred among the different subgroups.

Conclusions

The m7G-TME classifier offers a promising tool for predicting prognosis and immunotherapeutic responses in BC, which could support personalized therapeutic strategies.

A fitness trade-off between growth and survival governed by Spo0A-mediated proteome allocation constraints in Bacillus subtilis

Growth and survival are key determinants of bacterial fitness. However, how resource allocation of bacteria could reconcile these two traits to maximize fitness remains poorly understood. Here, we find that the resource allocation strategy of Bacillus subtilis does not lead to growth maximization on various carbon sources. Survival-related pathways impose strong proteome constraints on B. subtilis. Knockout of a master regulator gene, spo0A, triggers a global resource reallocation from survival-related pathways to biosynthesis pathways, further strongly stimulating the growth of B. subtilis. However, the fitness of spo0A-null strain is severely compromised because of various disadvantageous phenotypes (e.g., abolished sporulation and enhanced cell lysis). In particular, it also exhibits a strong defect in peptide utilization, being unable to efficiently recycle nutrients from the lysed cell debris to maintain long-term viability. Our work uncovers a fitness trade-off between growth and survival that governed by Spo0A-mediated proteome allocation constraints in B. subtilis, further shedding light on the fundamental design principle of bacteria.

Natural phenolic compounds as biofilm inhibitors of multidrug-resistant Escherichia coli - the role of similar biological processes despite structural diversity

Multidrug-resistant gram-negative pathogens such as Escherichia coli have become increasingly difficult to treat and therefore alternative treatment options are needed. Targeting virulence factors like biofilm formation could be one such option. Inhibition of biofilm-related structures like curli and cellulose formation in E. coli has been shown for different phenolic natural compounds like epigallocatechin gallate. This study demonstrates this effect for other structurally unrelated phenolics, namely octyl gallate, scutellarein and wedelolactone. To verify whether these structurally different compounds influence identical pathways of biofilm formation in E. coli a broad comparative RNA-sequencing approach was chosen with additional RT-qPCR to gain initial insights into the pathways affected at the transcriptomic level. Bioinformatical analysis of the RNA-Seq data was performed using DESeq2, BioCyc and KEGG Mapper. The comparative bioinformatics analysis on the pathways revealed that, irrespective of their structure, all compounds mainly influenced similar biological processes. These pathways included bacterial motility, chemotaxis, biofilm formation as well as metabolic processes like arginine biosynthesis and tricarboxylic acid cycle. Overall, this work provides the first insights into the potential mechanisms of action of novel phenolic biofilm inhibitors and highlights the complex regulatory processes of biofilm formation in E. coli.

Physiology of trans-translation deficiency in Bacillus subtilis - a comparative proteomics study

trans-Translation is the most effective ribosome rescue system known in bacteria. While it is essential in some bacteria, Bacillus subtilis possesses two additional alternative ribosome rescue mechanisms that require the proteins BrfA or RqcH. To investigate the physiology of trans-translation deficiency in the model organism B. subtilis, we compared the proteomes of B. subtilis 168 and a ΔssrA mutant in the mid-log phase using gel-free label-free quantitative proteomics. In chemically defined medium, the growth rate of the ssrA deletion mutant was 20% lower than that of B. subtilis 168. An 35 S-methionine incorporation assay demonstrated that protein synthesis rates were also lower in the ΔssrA strain. Alternative rescue factors were not detected. Among the 34 proteins overrepresented in the mutant strain were eight chemotaxis proteins. Indeed, both on LB agar and minimal medium the ΔssrA strain showed an altered motility and chemotaxis phenotype. Despite the lower growth rate, in the mutant proteome ribosomal proteins were more abundant while proteins related to amino acid biosynthesis were less abundant than in the parental strain. This overrepresentation of ribosomal proteins coupled with a lower protein synthesis rate and down-regulation of precursor supply reflects the slow ribosome recycling in the trans-translation-deficient mutant.

Multidimensional Landscape of SA-AKI Revealed by Integrated Proteomics and Metabolomics Analysis

Sepsis-associated acute kidney injury (SA-AKI) is a severe and life-threatening condition with high morbidity and mortality among emergency patients, and it poses a significant risk of chronic renal failure. Clinical treatments for SA-AKI remain reactive and non-specific, lacking effective diagnostic biomarkers or treatment targets. In this study, we established an SA-AKI mouse model using lipopolysaccharide (LPS) and performed proteomics and metabolomics analyses. A variety of bioinformatic analyses, including gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), protein and protein interactions (PPI), and MetaboAnalyst analysis, were conducted to investigate the key molecules of SA-AKI. Integrated proteomics and metabolomics analysis revealed that sepsis led to impaired renal mitochondrial function and metabolic disorders. Immune-related pathways were found to be activated in kidneys upon septic infection. The catabolic products of polyamines accumulated in septic kidneys. Overall, our integrated analysis provides a multidimensional understanding of SA-AKI and identifies potential pathways for this condition.

The combined signatures of telomere and immune cell landscape provide a prognostic and therapeutic biomarker in glioma

Background

Gliomas, the most prevalent primary malignant tumors of the central nervous system in adults, exhibit slow growth in lower-grade gliomas (LGG). However, the majority of LGG cases progress to high-grade gliomas, posing challenges for prognostication. The tumor microenvironment (TME), characterized by telomere-related genes and immune cell infiltration, strongly influences glioma growth and therapeutic response. Therefore, our objective was to develop a Telomere-TME (TM-TME) classifier that integrates telomere-related genes and immune cell landscape to assess prognosis and therapeutic response in glioma.

Methods

This study encompassed LGG patients from the TCGA and CCGA databases. TM score and TME score were derived from the expression signatures of telomere-related genes and the presence of immune cells in LGG, respectively. The TM-TME classifier was established by combining TM and TME scores to effectively predict prognosis. Subsequently, we conducted Kaplan-Meier survival estimation, univariate Cox regression analysis, and receiver operating characteristic curves to validate the prognostic prediction capacity of the TM-TME classifier across multiple cohorts. Gene Ontology (GO) analysis, biological processes, and proteomaps were performed to annotate the functional aspects of each subgroup and visualize the cellular signaling pathways.

Results

The TM_low+TME_high subgroup exhibited superior prognosis and therapeutic response compared to other subgroups (P<0.001). This finding could be attributed to distinct tumor somatic mutations and cancer cellular signaling pathways. GO analysis indicated that the TM_low+TME_high subgroup is associated with the neuronal system and modulation of chemical synaptic transmission. Conversely, the TM_high+TME_low subgroup showed a strong association with cell cycle and DNA metabolic processes. Furthermore, the classifier significantly differentiated overall survival in the TCGA LGG cohort and served as an independent prognostic factor for LGG patients in both the TCGA cohort (P<0.001) and the CGGA cohort (P<0.001).

Conclusion

Overall, our findings underscore the significance of the TM-TME classifier in predicting prognosis and immune therapeutic response in glioma, shedding light on the complex immune landscape within each subgroup. Additionally, our results suggest the potential of integrating risk stratification with precision therapy for LGG.

A Rapid and Efficient Method for the Extraction of Histone Proteins

Current protocols used to extract and purify histones are notoriously tedious, especially when using yeast cells. Here, we describe the use of a simple filter-aided sample preparation approach enabling histone extraction from yeast and mammalian cells using acidified ethanol, which not only improves extraction but also inactivates histone-modifying enzymes. We show that our improved method prevents N-terminal clipping of H3, an artifact frequently observed in yeast cells using standard histone extraction protocols. Our method is scalable and provides efficient recovery of histones when extracts are prepared from as few as two million yeast cells. We further demonstrate the application of this approach for the analysis of histone modifications in fungal clinical isolates available in a limited quantity. Compared with standard protocols, our method enables the study of histones and their modifications in a faster, simpler, and more robust manner.

Mechanism of orphan subunit recognition during assembly quality control

Cells contain numerous abundant molecular machines assembled from multiple subunits. Imbalances in subunit production and failed assembly generate orphan subunits that are eliminated by poorly defined pathways. Here, we determined how orphan subunits of the cytosolic chaperonin CCT are recognized. Several unassembled CCT subunits recruited the E3 ubiquitin ligase HERC2 using ZNRD2 as an adaptor. Both factors were necessary for orphan CCT subunit degradation in cells, sufficient for CCT subunit ubiquitination with purified factors, and necessary for optimal cell fitness. Domain mapping and structure prediction defined the molecular features of a minimal HERC2-ZNRD2-CCT module. The structural model, whose key elements were validated in cells using point mutants, shows why ZNRD2 selectively recognizes multiple orphaned CCT subunits without engaging assembled CCT. Our findings reveal how failures during CCT assembly are monitored and provide a paradigm for the molecular recognition of orphan subunits, the largest source of quality control substrates in cells.

Integrated multiomic analysis and high-throughput screening reveal potential gene targets and synergetic drug combinations for osteosarcoma therapy

Although great advances have been made over the past decades, therapeutics for osteosarcoma are quite limited. We performed long-read RNA sequencing and tandem mass tag (TMT)-based quantitative proteome on osteosarcoma and the adjacent normal tissues, next-generation sequencing (NGS) on paired osteosarcoma samples before and after neoadjuvant chemotherapy (NACT), and high-throughput drug combination screen on osteosarcoma cell lines. Single-cell RNA sequencing data were analyzed to reveal the heterogeneity of potential therapeutic target genes. Additionally, we clarified the synergistic mechanisms of doxorubicin (DOX) and HDACs inhibitors for osteosarcoma treatment. Consequently, we identified 2535 osteosarcoma-specific genes and several alternative splicing (AS) events with osteosarcoma specificity and/or patient heterogeneity. Hundreds of potential therapeutic targets were identified among them, which showed the core regulatory roles in osteosarcoma. We also identified 215 inhibitory drugs and 236 synergistic drug combinations for osteosarcoma treatment. More interestingly, the multiomic analysis pointed out the pivotal role of HDAC1 and TOP2A in osteosarcoma. HDAC inhibitors synergized with DOX to suppress osteosarcoma both in vitro and in vivo. Mechanistically, HDAC inhibitors synergized with DOX by downregulating SP1 to transcriptionally modulate TOP2A expression. This study provided a comprehensive view of molecular features, therapeutic targets, and synergistic drug combinations for osteosarcoma.

The brain's dark transcriptome: Sequencing RNA in distal compartments of neurons and glia

Transcriptomic approaches are powerful strategies to map the molecular diversity of cells in the brain. Single-cell genomic atlases have now been compiled for entire mammalian brains. However, complementary techniques are only just beginning to map the subcellular transcriptomes from distal cellular compartments. We review single-cell datasets alongside subtranscriptome data from the mammalian brain to explore the development of cellular and subcellular diversity. We discuss how single-cell RNA-seq misses transcripts localized away from cell bodies, which form the 'dark transcriptome' of the brain: a collection of subtranscriptomes in dendrites, axons, growth cones, synapses, and endfeet with important roles in brain development and function. Recent advances in subcellular transcriptome sequencing are beginning to reveal these elusive pools of RNA. We outline the success stories to date in uncovering the constituent subtranscriptomes of neurons and glia, as well as present the emerging toolkit that is accelerating the pace of subtranscriptome discovery.

Fungus-derived protein particles as cell-adhesive matrices for cell-cultivated food

Cell-adhesive factors mediate adhesion of cells to substrates via peptide motifs such as the Arg-Gly-Asp (RGD) sequence. With the onset of sustainability issues, there is a pressing need to find alternatives to animal-derived cell-adhesive factors, especially for cell-cultivated food applications. In this paper, we show how data mining can be a powerful approach toward identifying fungal-derived cell-adhesive proteins and present a method to isolate and utilize these proteins as extracellular matrices (ECM) to support cell adhesion and culture in 3D. Screening of a protein database for fungal and plant proteins uncovered that ~5.5% of the unique reported proteins contain RGD sequences. A plot of fungi species vs RGD percentage revealed that 98% of the species exhibited an RGD percentage > = 1%. We observed the formation of protein particles in crude extracts isolated from basidiomycete fungi, which could be correlated to their stability towards particle aggregation at different temperatures. These protein particles were incorporated in 3D fiber matrices encapsulating mouse myoblast cells, showing a positive effect on cell alignment. We demonstrated a cell traction stress on the protein particles (from Flammulina velutipes) that was comparable to cells on fibronectin. A snapshot of the RGD-containing proteins in the fungal extracts was obtained by combining SDS-PAGE and mass spectrometry of the peptide fragments obtained by enzymatic cleavage. Therefore, a sustainable source of cell-adhesive proteins is widely available in the fungi kingdom. A method has been developed to identify candidate species and produce cell-adhesive matrices, applicable to the cell-cultivated food and healthcare industries.

Mitochondria-related genes and metabolic profiles of innate and adaptive immune cells in primary Sjögren's syndrome

Background

Primary Sjogren's syndrome (pSS) is a prototypical systemic autoimmune disease characterised by lymphocyte infiltration and immune-complex deposition in multiple organs. The specific distribution of immune cell populations and their relationship with mitochondria remain unknown.

Methods

Histological analysis was performed to assess the specific distribution of innate and adaptive immune cell populations in labial salivary gland (LSG) samples from 30 patients with pSS and 13 patients with non-pSS. The ultrastructural morphometric features of mitochondria within immune cells were observed under the transmission electron microscope (TEM). RNA sequencing was performed on LSG samples from 40 patients with pSS and 7 non-pSS patients. The Single-sample Gene Set Enrichment Analysis (ssGSEA), ESTIMATE, and CIBERSORT algorithms and Pearson correlation coefficients were used to examine the relationship between mitochondria-related genes and immune infiltration. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify the mitochondria-specific genes and the related pathways based on the immune cell types.

Results

HE staining revealed a massive infiltration of plasma cells with abundant immunoglobulin protein distributed around phenotypically normal-appearing acinar and ductal tissues of patients with pSS. Immunohistochemical analyses revealed that innate immune cells (macrophages, eosinophils and NK cells) were distributed throughout the glandular tissue. Dominant adaptive immune cell infiltration composed of B cells, CD4⁺T cells and CD8⁺ T cells or ectopic lymphoid follicle-like structures were observed in the LSGs of patients with pSS. TEM validated the swelling of mitochondria with disorganised cristae in some lymphocytes that had invaded the glandular tissue. Subsequently, bioinformatic analysis revealed that innate and adaptive immune cells were associated with different mitochondrial metabolism pathways. Mitochondrial electron transport and respiratory chain complexes in the glandular microenvironment were positively correlated with innate immune cells, whereas amino acid and nucleic acid metabolism were negatively correlated with adaptive immune cells. In addition, mitochondrial biogenesis and mitochondrial apoptosis in the glandular microenvironment were closely associated with adaptive immune cells.

Conclusion

Innate and adaptive immune cells have distinct distribution profiles in the salivary gland tissues of patients with pSS and are associated with different mitochondrial metabolic pathways, which may contribute to disease progression.

Dysregulation of Metabolism and Proteostasis in Skeletal Muscle of a Presymptomatic Pompe Mouse Model

Pompe disease is a rare genetic metabolic disorder caused by mutations in acid-alpha glucoside (GAA) leading to pathological lysosomal glycogen accumulation associated with skeletal muscle weakness, respiratory difficulties and cardiomyopathy, dependent from the GAA residual enzyme activity. This study aimed to investigate early proteomic changes in a mouse model of Pompe disease and identify potential therapeutic pathways using proteomic analysis of skeletal muscles from pre-symptomatic Pompe mice. For this purpose, quadriceps samples of Gaa^6neo/6neo mutant (Pompe) and wildtype mice, at the age of six weeks, were studied with three biological replicates for each group. The data were validated with skeletal muscle morphology, immunofluorescence studies and western blot analysis. Proteomic profiling identified 538 significantly upregulated and 16 significantly downregulated proteins in quadriceps muscles derived from Pompe animals compared to wildtype mice. The majority of significantly upregulated proteins were involved in metabolism, translation, folding, degrading and vesicular transport, with some having crucial roles in the etiopathology of other neurological or neuromuscular diseases. This study highlights the importance of the early diagnosis and treatment of Pompe disease and suggests potential add-on therapeutic strategies targeting protein dysregulations.

Novel treatment and insight for irradiation-induced injuries: Dibucaine ameliorates irradiation-induced testicular injury by inhibiting fatty acid oxidation in primary Leydig cells

BACKGROUND

Male infertility is a worldwide problem but few treatments, especially irradiation-induced testicular injury. The aim of this research was to investigate novel drugs for the treatment of irradiation-induced testicular injury.

METHODS

We administered dibucaine (0.8 mg/kg) intraperitoneally to male mice (6 mice per group) after five consecutive daily 0.5 Gy whole-body irradiation, and evaluated its ameliorating efficacy by testicular HE staining and morphological measurements. Drug affinity responsive target stability assay (Darts) were used to find target protein and pathway; mouse primary Leydig cells were isolated and to explore the mechanism (Flow cytometry, Western blot, and Seahorse palmitate oxidative stress assays); finally rescue experiments were completed by combining dibucaine with fatty acid oxidative pathway inhibitors and activators.

RESULTS

The testicular HE staining and morphological measurements in dibucaine treatment group was significantly better than that in irradiation group (P < 0.05); sperm motility and mRNA levels of spermatogenic cell markers were also higher than those in the latter (P < 0.05). Darts and Western blot results showed that dibucaine targets CPT1A and downregulate fatty acid oxidation. Flow cytometry, Western blot, and Palmitate oxidative stress assays of primary Leydig cells demonstrated that dibucaine inhibits fatty acid oxidation in Leydig cells. Dibucaine combined with etomoxir/baicalin confirmed that its inhibition of fatty acid oxidation was beneficial in ameliorating irradiation-induced testicular injury.

CONCLUSIONS

In conclusion, our data suggest that dibucaine ameliorates irradiation-induced testicular injury in mice by inhibiting fatty acid oxidation in Leydig cells. This will provide novel ideas for the treatment of irradiation-induced testicular injury.

Lactate mediated metabolic crosstalk between cancer and immune cells and its therapeutic implications

Metabolism is central to energy generation and cell signaling in all life forms. Cancer cells rely heavily on glucose metabolism wherein glucose is primarily converted to lactate even in adequate oxygen conditions, a process famously known as "the Warburg effect." In addition to cancer cells, Warburg effect was found to be operational in other cell types, including actively proliferating immune cells. According to current dogma, pyruvate is the end product of glycolysis that is converted into lactate in normal cells, particularly under hypoxic conditions. However, several recent observations suggest that the final product of glycolysis may be lactate, which is produced irrespective of oxygen concentrations. Traditionally, glucose-derived lactate can have three fates: it can be used as a fuel in the TCA cycle or lipid synthesis; it can be converted back into pyruvate in the cytosol that feeds into the mitochondrial TCA; or, at very high concentrations, accumulated lactate in the cytosol may be released from cells that act as an oncometabolite. In immune cells as well, glucose-derived lactate seems to play a major role in metabolism and cell signaling. However, immune cells are much more sensitive to lactate concentrations, as higher lactate levels have been found to inhibit immune cell function. Thus, tumor cell-derived lactate may serve as a major player in deciding the response and resistance to immune cell-directed therapies. In the current review, we will provide a comprehensive overview of the glycolytic process in eukaryotic cells with a special focus on the fate of pyruvate and lactate in tumor and immune cells. We will also review the evidence supporting the idea that lactate, not pyruvate, is the end product of glycolysis. In addition, we will discuss the impact of glucose-lactate-mediated cross-talk between tumor and immune cells on the therapeutic outcomes after immunotherapy.

Substantial rDNA copy number reductions alter timing of development and produce variable tissue-specific phenotypes in C. elegans

The genes that encode ribosomal RNAs are present in several hundred copies in most eukaryotes. These vast arrays of repetitive ribosomal DNA (rDNA) have been implicated not just in ribosome biogenesis, but also aging, cancer, genome stability, and global gene expression. rDNA copy number is highly variable among and within species; this variability is thought to associate with traits relevant to human health and disease. Here we investigate the phenotypic consequences of multicellular life at the lower bounds of rDNA copy number. We use the model Caenorhabditis elegans, which has previously been found to complete embryogenesis using only maternally provided ribosomes. We find that individuals with rDNA copy number reduced to ∼5% of wild type are capable of further development with variable penetrance. Such individuals are sterile and exhibit severe morphological defects, particularly in post-embryonically dividing tissues such as germline and vulva. Developmental completion and fertility are supported by an rDNA copy number ∼10% of wild type, with substantially delayed development. Worms with rDNA copy number reduced to ∼33% of wild type display a subtle developmental timing defect that was absent in worms with higher copy numbers. Our results support the hypothesis that rDNA requirements vary across tissues and indicate that the minimum rDNA copy number for fertile adulthood is substantially less than the lowest naturally observed total copy number. The phenotype of individuals with severely reduced rDNA copy number is highly variable in penetrance and presentation, highlighting the need for continued investigation into the biological consequences of rDNA copy number variation.

A Homozygous PPP1R21 Splice Variant Associated with Severe Developmental Delay, Absence of Speech, and Muscle Weakness Leads to Activated Proteasome Function

PPP1R21 acts as a co-factor for protein phosphatase 1 (PP1), an important serine/threonine phosphatase known to be essential for cell division, control of glycogen metabolism, protein synthesis, and muscle contractility. Bi-allelic pathogenic variants in PPP1R21 were linked to a neurodevelopmental disorder with hypotonia, facial dysmorphism, and brain abnormalities (NEDHFBA) with pediatric onset. Functional studies unraveled impaired vesicular transport as being part of PPP1R21-related pathomechanism. To decipher further the pathophysiological processes leading to the clinical manifestation of NEDHFBA, we investigated the proteomic signature of fibroblasts derived from the first NEDHFBA patient harboring a splice-site mutation in PPP1R21 and presenting with a milder phenotype. Proteomic findings and further functional studies demonstrate a profound activation of the ubiquitin-proteasome system with presence of protein aggregates and impact on cellular fitness and moreover suggest a cross-link between activation of the proteolytic system and cytoskeletal architecture (including filopodia) as exemplified on paradigmatic proteins including actin, thus extending the pathophysiological spectrum of the disease. In addition, the proteomic signature of PPP1R21-mutant fibroblasts displayed a dysregulation of a variety of proteins of neurological relevance. This includes increase proteins which might act toward antagonization of cellular stress burden in terms of pro-survival, a molecular finding which might accord with the presentation of a milder phenotype of our NEDHFBA patient.

Post-mortem muscle proteome of crossbred bulls and steers: Relationships with carcass and meat quality

This study investigated the skeletal muscle proteome of crossbred bulls and steers with the aim of explaining the differences in carcass and meat quality traits. Therefore, 640 post-weaning Angus-Nellore calves were fed a high-energy diet for a period of 180 days. In the feedlot trial, comparisons of steers (n = 320) and bulls (n = 320) showed lower (P < 0.01) average daily gain (1.38 vs. 1.60 ± 0.05 kg/d), final body weight (547.4 vs. 585.1 ± 9.3 kg), which resulted in lower hot carcass weight (298.4 vs. 333.7 ± 7.7 kg) and ribeye area (68.6 vs. 81.0 ± 2.56 cm²). Steers had higher (P < 0.01) carcass fatness, meat color parameters (L*, a*, b*, chroma (C*), hue (h°)) and lower ultimate pH. Moreover, lower (P < 0.01) Warner-Bratzler shear force (WBSF) were observed in steers compared to bulls (WBSF = 3.68 vs. 4.97 ± 0.08 kg; and 3.19 vs. 4.08 ± 0.08 kg). The proteomic approach using two-dimensional electrophoresis, mass spectrometry and bioinformatics procedures revealed several differentially expressed proteins between steers and bulls (P < 0.05). Interconnected pathways and substantial changes were revealed in biological processes, molecular functions, and cellular components between the post-mortem muscle proteomes of the compared animals. Steers had increased (P < 0.05) abundance of proteins related to energy metabolism (CKM, ALDOA, and GAPDH), and bulls had greater abundance of proteins associated with catabolic (glycolysis) processes (PGM1); oxidative stress (HSP60, HSPA8 and GSTP1); and muscle structure and contraction (TNNI2 and TNNT3). The better carcass (fatness and marbling degree) and meat quality traits (tenderness and color parameters) of steers were associated with higher abundance of key proteins of energy metabolism and lower abundance of enzymes related to catabolic processes, oxidative stress, and proteins of muscle contraction SIGNIFICANCE: Sexual condition of cattle is known to be an important factor affecting animal performances and growth as well as the carcass and meat quality traits. The investigation of skeletal muscle proteome help a better understanding of the origin of the differences in quality traits between bulls and steers. The inferior meat quality of bulls was found to be due to the greater expression of proteins associated with primary and catabolic processes, oxidative stress, and muscle contraction. Steers had greater expression of proteins, from which several are known biomarkers of beef quality (mainly tenderness).

A novel nomogram for predicting overall survival in peripheral T cell lymphoma patients.. [DOI: 10.21203/rs.3.rs-2823604/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Background The prognosis of peripheral T cell lymphomas (PTCLs) varies greatly. This study aimed at generating a prognostic nomogram based on differentially expressed genes (DEGs).Methods Firstly, we collected RNA transcripts from Gene Expression Omnibus and identified DEGs. Secondly we used univariate Cox regression, Least absolute shrinkage and selection operator (LASSO) to screen the independent risk factors to construct nomogram in the training cohort. Thirdly, we evaluate its prediction accuracy via decision curves analysis (DCA), receiver operating characteristic (ROC) and calibration rate to confirm its performance on survival in training and validation cohort. Then we carried out subgroup analysis in training and validation to eliminate the effects of age, gender, and pathological subtype. Lastly, to verify feasibility of nomogram in practice, we applied immunohistochemistry to clinical samples and analyzed the relationship between IHC scores and prognosis.Results The 702 DEGs between 40 PTCLs and 20 non-tumor patients were identified. Then ANGPTL2, CPSF4, CLIC4 and OTUD6B were screened out as independent risk factors via univariate Cox regression and LASSO. The DCA, ROC, Harrell’s concordance index (c-index) and calibration rate showed nomogram predicting more accurately than any single specific transcript. The results showed PTCLs with higher nomogram-score had a longer survival, regardless of age, gender and pathological subtype. Finally, the high expression level of ANGPTL2, CPSF4 and OTUD6B related to poor prognosis. Higher expression of CLIC4 related to longer survival.Conclusion This nomogram showed the favorable clinical applicability, regardless of age, gender and pathological subtype.

Protein Fitness Prediction Is Impacted by the Interplay of Language Models, Ensemble Learning, and Sampling Methods

Advances in machine learning (ML) and the availability of protein sequences via high-throughput sequencing techniques have transformed the ability to design novel diagnostic and therapeutic proteins. ML allows protein engineers to capture complex trends hidden within protein sequences that would otherwise be difficult to identify in the context of the immense and rugged protein fitness landscape. Despite this potential, there persists a need for guidance during the training and evaluation of ML methods over sequencing data. Two key challenges for training discriminative models and evaluating their performance include handling severely imbalanced datasets (e.g., few high-fitness proteins among an abundance of non-functional proteins) and selecting appropriate protein sequence representations (numerical encodings). Here, we present a framework for applying ML over assay-labeled datasets to elucidate the capacity of sampling techniques and protein encoding methods to improve binding affinity and thermal stability prediction tasks. For protein sequence representations, we incorporate two widely used methods (One-Hot encoding and physiochemical encoding) and two language-based methods (next-token prediction, UniRep; masked-token prediction, ESM). Elaboration on performance is provided over protein fitness, protein size, and sampling techniques. In addition, an ensemble of protein representation methods is generated to discover the contribution of distinct representations and improve the final prediction score. We then implement multiple criteria decision analysis (MCDA; TOPSIS with entropy weighting), using multiple metrics well-suited for imbalanced data, to ensure statistical rigor in ranking our methods. Within the context of these datasets, the synthetic minority oversampling technique (SMOTE) outperformed undersampling while encoding sequences with One-Hot, UniRep, and ESM representations. Moreover, ensemble learning increased the predictive performance of the affinity-based dataset by 4% compared to the best single-encoding candidate (F1-score = 97%), while ESM alone was rigorous enough in stability prediction (F1-score = 92%).

RBAtools: a programming interface for Resource Balance Analysis models

Motivation

Efficient resource allocation can contribute to an organism's fitness and can improve evolutionary success. Resource Balance Analysis (RBA) is a computational framework that models an organism's growth-optimal proteome configurations in various environments. RBA software enables the construction of RBA models on genome scale and the calculation of medium-specific, growth-optimal cell states including metabolic fluxes and the abundance of macromolecular machines. However, existing software lacks a simple programming interface for non-expert users, easy to use and interoperable with other software.

Results

The python package RBAtools provides convenient access to RBA models. As a flexible programming interface, it enables the implementation of custom workflows and the modification of existing genome-scale RBA models. Its high-level functions comprise simulation, model fitting, parameter screens, sensitivity analysis, variability analysis and the construction of Pareto fronts. Models and data are represented as structured tables and can be exported to common data formats for fluxomics and proteomics visualization.

Availability and implementation

RBAtools documentation, installation instructions and tutorials are available at https://sysbioinra.github.io/rbatools/. General information about RBA and related software can be found at rba.inrae.fr.

Abiotic Stress in Crop Production

The vast majority of agricultural land undergoes abiotic stress that can significantly reduce agricultural yields. Understanding the mechanisms of plant defenses against stresses and putting this knowledge into practice is, therefore, an integral part of sustainable agriculture. In this review, we focus on current findings in plant resistance to four cardinal abiotic stressors—drought, heat, salinity, and low temperatures. Apart from the description of the newly discovered mechanisms of signaling and resistance to abiotic stress, this review also focuses on the importance of primary and secondary metabolites, including carbohydrates, amino acids, phenolics, and phytohormones. A meta-analysis of transcriptomic studies concerning the model plant Arabidopsis demonstrates the long-observed phenomenon that abiotic stressors induce different signals and effects at the level of gene expression, but genes whose regulation is similar under most stressors can still be traced. The analysis further reveals the transcriptional modulation of Golgi-targeted proteins in response to heat stress. Our analysis also highlights several genes that are similarly regulated under all stress conditions. These genes support the central role of phytohormones in the abiotic stress response, and the importance of some of these in plant resistance has not yet been studied. Finally, this review provides information about the response to abiotic stress in major European crop plants—wheat, sugar beet, maize, potatoes, barley, sunflowers, grapes, rapeseed, tomatoes, and apples.

A posttranscriptional pathway regulates cell wall mRNA expression in budding yeast

The fungal cell wall provides protection and structure and is an important target for antifungal compounds. A mitogen-activated protein (MAP) kinase cascade termed the cell wall integrity (CWI) pathway regulates transcriptional responses to cell wall damage. Here, we describe a posttranscriptional pathway that plays an important complementary role. We report that the RNA-binding proteins (RBPs) Mrn1 and Nab6 specifically target the 3' UTRs of a largely overlapping set of cell wall-related mRNAs. These mRNAs are downregulated in the absence of Nab6, indicating a function in target mRNA stabilization. Nab6 acts in parallel to CWI signaling to maintain appropriate expression of cell wall genes during stress. Cells lacking both pathways are hypersensitive to antifungal compounds targeting the cell wall. Deletion of MRN1 partially alleviates growth defects associated with Δnab6, and Mrn1 has an opposing function in mRNA destabilization. Our results uncover a posttranscriptional pathway that mediates cellular resistance to antifungal compounds.

Interaction of SARS-CoV-2 Nucleocapsid Protein and Human RNA Helicases DDX1 and DDX3X Modulates Their Activities on Double-Stranded RNA

The nucleocapsid protein Np of SARS-CoV-2 is involved in the replication, transcription, and packaging of the viral genome, but it also plays a role in the modulation of the host cell innate immunity and inflammation response. Ectopic expression of Np alone was able to induce significant changes in the proteome of human cells. The cellular RNA helicase DDX1 was among the proteins whose levels were increased by Np expression. DDX1 and its related helicase DDX3X were found to physically interact with Np and to increase 2- to 4-fold its affinity for double-stranded RNA in a helicase-independent manner. Conversely, Np inhibited the RNA helicase activity of both proteins. These functional interactions among Np and DDX1 and DDX3X highlight novel possible roles played by these host RNA helicases in the viral life cycle.

Salicylic Acid Treatment and Its Effect on Seed Yield and Seed Molecular Composition of Pisum sativum under Abiotic Stress

The reproductive stage of plant development has the most critical impact on yield. Flowering is highly sensitive to abiotic stress, and increasing temperatures and drought harm crop yields. Salicylic acid is a phytohormone that regulates flowering and promotes stress resilience in plants. However, the exact molecular mechanisms and the level of protection are far from understood and seem to be species-specific. Here, the effect of salicylic acid was tested in a field experiment with Pisum sativum exposed to heat stress. Salicylic acid was administered at two different stages of flowering, and its effect on the yield and composition of the harvested seeds was followed. Plants treated with salicylic acid produced larger seed pods, and a significant increase in dry weight was found for the plants with a delayed application of salicylic acid. The analyses of the seed proteome, lipidome, and metabolome did not show any negative impact of salicylic treatment on seed composition. Identified processes that could be responsible for the observed improvement in seed yields included an increase in polyamine biosynthesis, accumulation of storage lipids and lysophosphatidylcholines, a higher abundance of components of chromatin regulation, calmodulin-like protein, and threonine synthase, and indicated a decrease in sensitivity to abscisic acid signaling.

A Simplified and Effective Approach for the Isolation of Small Pluripotent Stem Cells Derived from Human Peripheral Blood

Pluripotent stem cells are key players in regenerative medicine. Embryonic pluripotent stem cells, despite their significant advantages, are associated with limitations such as their inadequate availability and the ethical dilemmas in their isolation and clinical use. The discovery of very small embryonic-like (VSEL) stem cells addressed the aforementioned limitations, but their isolation technique remains a challenge due to their small cell size and their efficiency in isolation. Here, we report a simplified and effective approach for the isolation of small pluripotent stem cells derived from human peripheral blood. Our approach results in a high yield of small blood stem cell (SBSC) population, which expresses pluripotent embryonic markers (e.g., Nanog, SSEA-3) and the Yamanaka factors. Further, a fraction of SBSCs also co-express hematopoietic markers (e.g., CD45 and CD90) and/or mesenchymal markers (e.g., CD29, CD105 and PTH1R), suggesting a mixed stem cell population. Finally, quantitative proteomic profiling reveals that SBSCs contain various stem cell markers (CD9, ITGA6, MAPK1, MTHFD1, STAT3, HSPB1, HSPA4), and Transcription reg complex factors (e.g., STAT5B, PDLIM1, ANXA2, ATF6, CAMK1). In conclusion, we present a novel, simplified and effective isolating process that yields an abundant population of small-sized cells with characteristics of pluripotency from human peripheral blood.

The bovine uterine fluid proteome is more impacted by the stage of the estrous cycle than the proximity of the ovulating ovary in the periconception period

Uterine secretions provide a suitable environment for sperm selective migration during a couple of days preceding ovulation and for early embryo development before implantation. Our goal was to identify and quantify proteins in the bovine uterine fluid during the periovulatory period of the estrous cycle. Genital tracts with normal morphology were collected from adult cyclic Bos taurus females in a local slaughterhouse and classified into pre-ovulatory or post-ovulatory stages of cycle (around days 19-21 and 0-5 of cycle, respectively; n = 8 cows per stage) based on ovarian morphology. Proteins from uterine fluid collected from the utero-tubal junction to the base of each horn (four pools of two cows per condition) were analyzed by nanoLiquid Chromatography coupled with tandem Mass Spectrometry (nanoLC-MS/MS). A total of 1214 proteins were identified, of which 91% were shared between all conditions. Overall, 57% of proteins were predicted to be secreted and 17% were previously reported in uterine extracellular vesicles. Paired comparisons between uterine horns ipsilateral and contralateral to ovulation evidenced 12 differentially abundant proteins, including five at pre-ovulatory stage. Furthermore, 35 proteins differed in abundance between pre- and post-ovulatory stages, including 21 in the ipsilateral side of ovulation. Functional analysis of identified proteins demonstrated roles in binding, metabolism, cellular detoxification and the immune response. This study provides a valuable database of uterine proteins for functional studies on sperm physiology and early embryo development.

Differential Virulence of Aggregatibacter actinomycetemcomitans Serotypes Explained by Exoproteome Heterogeneity

Aggregatibacter actinomycetemcomitans (Aa) is a Gram-negative bacterial pathogen associated with periodontitis and nonoral diseases like rheumatoid arthritis and Alzheimer´s disease. Aa isolates with the serotypes a, b, and c are globally most prevalent. Importantly, isolates displaying these serotypes have different clinical presentations. While serotype b isolates are predominant in severe periodontitis, serotypes a and c are generally encountered in mild periodontitis or healthy individuals. It is currently unknown how these differences are reflected in the overall secretion of virulence factors. Therefore, this study was aimed at a comparative analysis of exoproteomes from different clinical Aa isolates with serotypes a, b, or c by mass spectrometry, and a subsequent correlation of the recorded exoproteome profiles with virulence. Overall, we identified 425 extracellular proteins. Significant differences in the exoproteome composition of isolates with different serotypes were observed in terms of protein identification and abundance. In particular, serotype a isolates presented more extracellular proteins than serotype b or c isolates. These differences are mirrored in their virulence in infection models based on human salivary gland epithelial cells and neutrophils. Remarkably, serotype a isolates displayed stronger adhesive capabilities and induced more lysis of epithelial cells and neutrophils than serotype b or c isolates. Conversely, serotype c isolates showed relatively low leukotoxicity, while provoking NETosis to similar extents as serotype a and b isolates. Altogether, we conclude that the differential virulence presentation by Aa isolates with the dominant serotypes a, b, or c can be explained by their exoproteome heterogeneity. IMPORTANCE Periodontitis is an inflammatory disease that causes progressive destruction of alveolar bone and supporting tissues around the teeth, ultimately resulting in tooth loss. The bacterium Aggregatibacter actinomycetemcomitans (Aa) is a prevalent causative agent of periodontitis, but this oral pathogen is also associated with serious extraoral diseases like rheumatoid arthritis and Alzheimer's disease. Clinical Aa isolates are usually distinguished by serotyping, because of known serotype-specific differences in virulence. Aa with serotype b is associated with aggressive forms of periodontitis, while isolates with serotypes a or c are usually encountered in cases of mild periodontitis or healthy individuals. The molecular basis for these differences in virulence was so far unknown. In the present study, we pinpoint serotype-specific differences in virulence factor production by clinical Aa isolates. We consider these findings important, because they provide new leads for future preventive or therapeutic approaches to fight periodontitis and associated morbidities.

A Systems Biology Approach To Disentangle the Direct and Indirect Effects of Global Transcription Factors on Gene Expression in Escherichia coli

Delineating the pleiotropic effects of global transcriptional factors (TFs) is critical for understanding the system-wide regulatory response in a particular environment. Currently, with the availability of genome-wide TF binding and gene expression data for Escherichia coli, several gene targets can be assigned to the global TFs, albeit inconsistently. Here, using a systematic integrated approach with emphasis on metabolism, we characterized and quantified the direct effects as well as the growth rate-mediated indirect effects of global TFs using deletion mutants of FNR, ArcA, and IHF regulators (focal TFs) under glucose fermentative conditions. This categorization enabled us to disentangle the dense connections seen within the transcriptional regulatory network (TRN) and determine the exact nature of focal TF-driven epistatic interactions with other global and pathway-specific local regulators (iTFs). We extended our analysis to combinatorial deletions of these focal TFs to determine their cross talk effects as well as conserved patterns of regulatory interactions. Moreover, we predicted with high confidence several novel metabolite-iTF interactions using inferred iTF activity changes arising from the allosteric effects of the intracellular metabolites perturbed as a result of the absence of focal TFs. Further, using compendium level computational analyses, we revealed not only the coexpressed genes regulated by these focal TFs but also the coordination of the direct and indirect target expression in the context of the economy of intracellular metabolites. Overall, this study leverages the fundamentals of TF-driven regulation, which could serve as a better template for deciphering mechanisms underlying complex phenotypes. IMPORTANCE Understanding the pleiotropic effects of global TFs on gene expression and their relevance underlying a specific response in a particular environment has been challenging. Here, we distinguish the TF-driven direct effects and growth rate-mediated indirect effects on gene expression using single- and double-deletion mutants of FNR, ArcA, and IHF regulators under anaerobic glucose fermentation. Such dissection assists us in unraveling the precise nature of interactions existing between the focal TF(s) and several other TFs, including those altered by allosteric effects of intracellular metabolites. We were able to recapitulate the previously known metabolite-TF interactions and predict novel interactions with high confidence. Furthermore, we determined that the direct and indirect gene expression have a strong connection with each other when analyzed using the coexpressed- or coregulated-gene approach. Deciphering such regulatory patterns explicitly from the metabolism point of view would be valuable in understanding other unpredicted complex regulation existing in nature.

Enzyme expression kinetics by Escherichia coli during transition from rich to minimal media depends on proteome reserves

Bacterial fitness depends on adaptability to changing environments. In rich growth medium, which is replete with amino acids, Escherichia coli primarily expresses protein synthesis machineries, which comprise ~40% of cellular proteins and are required for rapid growth. Upon transition to minimal medium, which lacks amino acids, biosynthetic enzymes are synthesized, eventually reaching ~15% of cellular proteins when growth fully resumes. We applied quantitative proteomics to analyse the timing of enzyme expression during such transitions, and established a simple positive relation between the onset time of enzyme synthesis and the fractional enzyme 'reserve' maintained by E. coli while growing in rich media. We devised and validated a coarse-grained kinetic model that quantitatively captures the enzyme recovery kinetics in different pathways, solely on the basis of proteomes immediately preceding the transition and well after its completion. Our model enables us to infer regulatory strategies underlying the 'as-needed' gene expression programme adopted by E. coli.

Finnish-specific AKT2 gene variant leads to impaired insulin signalling in myotubes

Finnish-specific gene variant p.P50T/AKT2 (minor allele frequency (MAF) = 1.1%) is associated with insulin resistance and increased predisposition to type 2 diabetes. Here, we have investigated in vitro the impact of the gene variant on glucose metabolism and intracellular signalling in human primary skeletal muscle cells, which were established from 14 male p.P50T/AKT2 variant carriers and 14 controls. Insulin-stimulated glucose uptake and glucose incorporation into glycogen were detected with 2-[1,2-3H]-deoxy-D-glucose and D-[14C]-glucose, respectively, and the rate of glycolysis was measured with a Seahorse XFe96 analyzer. Insulin signalling was investigated with Western blotting. The binding of variant and control AKT2-PH domains to phosphatidylinositol (3,4,5)-trisphosphate (PI(3,4,5)P3) was assayed using PIP StripsTM Membranes. Protein tyrosine kinase and serine-threonine kinase assays were performed using the PamGene® kinome profiling system. Insulin-stimulated glucose uptake and glycogen synthesis in myotubes in vitro were not significantly affected by the genotype. However, the insulin-stimulated glycolytic rate was impaired in variant myotubes. Western blot analysis showed that insulin-stimulated phosphorylation of AKT-Thr308, AS160-Thr642 and GSK3β-Ser9 was reduced in variant myotubes compared to controls. The binding of variant AKT2-PH domain to PI(3,4,5)P3 was reduced as compared to the control protein. PamGene® kinome profiling revealed multiple differentially phosphorylated kinase substrates, e.g. calmodulin, between the genotypes. Further in silico upstream kinase analysis predicted a large-scale impairment in activities of kinases participating, for example, in intracellular signal transduction, protein translation and cell cycle events. In conclusion, myotubes from p.P50T/AKT2 variant carriers show multiple signalling alterations which may contribute to predisposition to insulin resistance and T2D in the carriers of this signalling variant.

Stringent response ensures the timely adaptation of bacterial growth to nutrient downshift

Timely adaptation to nutrient downshift is crucial for bacteria to maintain fitness during feast and famine cycle in the natural niche. However, the molecular mechanism that ensures the timely adaption of bacterial growth to nutrient downshift remains poorly understood. Here, we quantitatively investigated the adaptation of Escherichia coli to various kinds of nutrient downshift. We found that relA deficient strain, which is devoid of stringent response, exhibits a significantly longer growth lag than wild type strain during adapting to both amino acid downshift and carbon downshift. Quantitative proteomics show that increased (p)ppGpp level promotes the growth adaption of bacteria to amino acid downshift via triggering the proteome resource re-allocation from ribosome synthesis to amino acid biosynthesis. Such type of proteome re-allocation is significantly delayed in the relA-deficient strain, which underlies its longer lag than wild type strain during amino acid downshift. During carbon downshift, a lack of stringent response in relA deficient strain leads to disruption of the transcription-translation coordination, thus compromising the transcription processivity and further the timely expression of related catabolic operons for utilizing secondary carbon sources. Our studies shed light on the fundamental strategy of bacteria to maintain fitness under nutrient-fluctuating environments.

A dynamical stochastic model of yeast translation across the cell cycle

Translation is a central step in gene expression, however its quantitative and time-resolved regulation is poorly understood. We developed a discrete, stochastic model for protein translation in S. cerevisiae in a whole-transcriptome, single-cell context. A "base case" scenario representing an average cell highlights translation initiation rates as the main co-translational regulatory parameters. Codon usage bias emerges as a secondary regulatory mechanism through ribosome stalling. Demand for anticodons with low abundancy is shown to cause above-average ribosome dwelling times. Codon usage bias correlates strongly both with protein synthesis rates and elongation rates. Applying the model to a time-resolved transcriptome estimated by combining data from FISH and RNA-Seq experiments, it could be shown that increased total transcript abundance during the cell cycle decreases translation efficiency at single transcript level. Translation efficiency grouped by gene function shows highest values for ribosomal and glycolytic genes. Ribosomal proteins peak in S phase while glycolytic proteins rank highest in later cell cycle phases.

Novel context-specific genome-scale modelling explores the potential of triacylglycerol production by Chlamydomonas reinhardtii

Gene expression data of cell cultures is commonly measured in biological and medical studies to understand cellular decision-making in various conditions. Metabolism, affected but not solely determined by the expression, is much more difficult to measure experimentally. Finding a reliable method to predict cell metabolism for expression data will greatly benefit metabolic engineering. We have developed a novel pipeline, OVERLAY, that can explore cellular fluxomics from expression data using only a high-quality genome-scale metabolic model. This is done through two main steps: first, construct a protein-constrained metabolic model (PC-model) by integrating protein and enzyme information into the metabolic model (M-model). Secondly, overlay the expression data onto the PC-model using a novel two-step nonconvex and convex optimization formulation, resulting in a context-specific PC-model with optionally calibrated rate constants. The resulting model computes proteomes and intracellular flux states that are consistent with the measured transcriptomes. Therefore, it provides detailed cellular insights that are difficult to glean individually from the omic data or M-model alone. We apply the OVERLAY to interpret triacylglycerol (TAG) overproduction by Chlamydomonas reinhardtii, using time-course RNA-Seq data. We show that OVERLAY can compute C. reinhardtii metabolism under nitrogen deprivation and metabolic shifts after an acetate boost. OVERLAY can also suggest possible 'bottleneck' proteins that need to be overexpressed to increase the TAG accumulation rate, as well as discuss other TAG-overproduction strategies.

Using Kinetic Modelling to Infer Adaptations in Saccharomyces cerevisiae Carbohydrate Storage Metabolism to Dynamic Substrate Conditions

Microbial metabolism is strongly dependent on the environmental conditions. While these can be well controlled under laboratory conditions, large-scale bioreactors are characterized by inhomogeneities and consequently dynamic conditions for the organisms. How Saccharomyces cerevisiae response to frequent perturbations in industrial bioreactors is still not understood mechanistically. To study the adjustments to prolonged dynamic conditions, we used published repeated substrate perturbation regime experimental data, extended it with proteomic measurements and used both for modelling approaches. Multiple types of data were combined; including quantitative metabolome, ¹³C enrichment and flux quantification data. Kinetic metabolic modelling was applied to study the relevant intracellular metabolic response dynamics. An existing model of yeast central carbon metabolism was extended, and different subsets of enzymatic kinetic constants were estimated. A novel parameter estimation pipeline based on combinatorial enzyme selection supplemented by regularization was developed to identify and predict the minimum enzyme and parameter adjustments from steady-state to dynamic substrate conditions. This approach predicted proteomic changes in hexose transport and phosphorylation reactions, which were additionally confirmed by proteome measurements. Nevertheless, the modelling also hints at a yet unknown kinetic or regulation phenomenon. Some intracellular fluxes could not be reproduced by mechanistic rate laws, including hexose transport and intracellular trehalase activity during substrate perturbation cycles.

Diagnosis of T-cell-mediated kidney rejection by biopsy-based proteomic biomarkers and machine learning

Background

Biopsy-based diagnosis is essential for maintaining kidney allograft longevity by ensuring prompt treatment for graft complications. Although histologic assessment remains the gold standard, it carries significant limitations such as subjective interpretation, suboptimal reproducibility, and imprecise quantitation of disease burden. It is hoped that molecular diagnostics could enhance the efficiency, accuracy, and reproducibility of traditional histologic methods.

Methods

Quantitative label-free mass spectrometry analysis was performed on a set of formalin-fixed, paraffin-embedded (FFPE) biopsies from kidney transplant patients, including five samples each with diagnosis of T-cell-mediated rejection (TCMR), polyomavirus BK nephropathy (BKPyVN), and stable (STA) kidney function control tissue. Using the differential protein expression result as a classifier, three different machine learning algorithms were tested to build a molecular diagnostic model for TCMR.

Results

The label-free proteomics method yielded 800-1350 proteins that could be quantified with high confidence per sample by single-shot measurements. Among these candidate proteins, 329 and 467 proteins were defined as differentially expressed proteins (DEPs) for TCMR in comparison with STA and BKPyVN, respectively. Comparing the FFPE quantitative proteomics data set obtained in this study using label-free method with a data set we previously reported using isobaric labeling technology, a classifier pool comprised of features from DEPs commonly quantified in both data sets, was generated for TCMR prediction. Leave-one-out cross-validation result demonstrated that the random forest (RF)-based model achieved the best predictive power. In a follow-up blind test using an independent sample set, the RF-based model yields 80% accuracy for TCMR and 100% for STA. When applying the established RF-based model to two public transcriptome datasets, 78.1%-82.9% sensitivity and 58.7%-64.4% specificity was achieved respectively.

Conclusions

This proof-of-principle study demonstrates the clinical feasibility of proteomics profiling for FFPE biopsies using an accurate, efficient, and cost-effective platform integrated of quantitative label-free mass spectrometry analysis with a machine learning-based diagnostic model. It costs less than 10 dollars per test.

Staphylococcus aureus populations from the gut and the blood are not distinguished by virulence traits-a critical role of host barrier integrity

BACKGROUND

The opportunistic pathogen Staphylococcus aureus is an asymptomatically carried member of the microbiome of about one third of the human population at any given point in time. Body sites known to harbor S. aureus are the skin, nasopharynx, and gut. In particular, the mechanisms allowing S. aureus to pass the gut epithelial barrier and to invade the bloodstream were so far poorly understood. Therefore, the objective of our present study was to investigate the extent to which genetic differences between enteric S. aureus isolates and isolates that caused serious bloodstream infections contribute to the likelihood of invasive disease.

RESULTS

Here, we present genome-wide association studies (GWAS) that compare the genome sequences of 69 S. aureus isolates from enteric carriage by healthy volunteers and 95 isolates from bloodstream infections. We complement our GWAS results with a detailed characterization of the cellular and extracellular proteomes of the representative gut and bloodstream isolates, and by assaying the virulence of these isolates with infection models based on human gut epithelial cells, human blood cells, and a small animal infection model. Intriguingly, our results show that enteric and bloodstream isolates with the same sequence type (ST1 or ST5) are very similar to each other at the genomic and proteomic levels. Nonetheless, bloodstream isolates are not necessarily associated with an invasive profile. Furthermore, we show that the main decisive factor preventing infection of gut epithelial cells in vitro is the presence of a tight barrier.

CONCLUSIONS

Our data show that virulence is a highly variable trait, even within a single clone. Importantly, however, there is no evidence that blood stream isolates possess a higher virulence potential than those from the enteric carriage. In fact, some gut isolates from healthy carriers were more virulent than bloodstream isolates. Based on our present observations, we propose that the integrity of the gut epithelial layer, rather than the pathogenic potential of the investigated enteric S. aureus isolates, determines whether staphylococci from the gut microbiome will become invasive pathogens. Video Abstract.

Systems-Wide Dissection of Organic Acid Assimilation in Pseudomonas aeruginosa Reveals a Novel Path To Underground Metabolism

The human pathogen Pseudomonas aeruginosa (Pa) is one of the most frequent and severe causes of nosocomial infection. This organism is also a major cause of airway infections in people with cystic fibrosis (CF). Pa is known to have a remarkable metabolic plasticity, allowing it to thrive under diverse environmental conditions and ecological niches; yet, little is known about the central metabolic pathways that sustain its growth during infection or precisely how these pathways operate. In this work, we used a combination of 'omics approaches (transcriptomics, proteomics, metabolomics, and ¹³C-fluxomics) and reverse genetics to provide systems-level insight into how the infection-relevant organic acids succinate and propionate are metabolized by Pa. Moreover, through structural and kinetic analysis of the 2-methylcitrate synthase (2-MCS; PrpC) and its paralogue citrate (CIT) synthase (GltA), we show how these two crucial enzymatic steps are interconnected in Pa organic acid assimilation. We found that Pa can rapidly adapt to the loss of GltA function by acquiring mutations in a transcriptional repressor, which then derepresses prpC expression. Our findings provide a clear example of how "underground metabolism," facilitated by enzyme substrate promiscuity, "rewires" Pa metabolism, allowing it to overcome the loss of a crucial enzyme. This pathogen-specific knowledge is critical for the advancement of a model-driven framework to target bacterial central metabolism. IMPORTANCE Pseudomonas aeruginosa is an opportunistic human pathogen that, due to its unrivalled resistance to antibiotics, ubiquity in the built environment, and aggressiveness in infection scenarios, has acquired the somewhat dubious accolade of being designated a "critical priority pathogen" by the WHO. In this work, we uncover the pathways and mechanisms used by P. aeruginosa to grow on a substrate that is abundant at many infection sites: propionate. We found that if the organism is prevented from metabolizing propionate, the substrate turns from being a convenient nutrient source into a potent poison, preventing bacterial growth. We further show that one of the enzymes involved in these reactions, 2-methylcitrate synthase (PrpC), is promiscuous and can moonlight for another essential enzyme in the cell (citrate synthase). Indeed, mutations that abolish citrate synthase activity (which would normally prevent the cell from growing) can be readily overcome if the cell acquires additional mutations that increase the expression of PrpC. This is a nice example of the evolutionary utility of so-called "underground metabolism."

A remarkable adaptive paradigm of heart performance and protection emerges in response to marked cardiac-specific overexpression of ADCY8

Adult (3 month) mice with cardiac-specific overexpression of adenylyl cyclase (AC) type VIII (TGAC8) adapt to an increased cAMP-induced cardiac workload (~30% increases in heart rate, ejection fraction and cardiac output) for up to a year without signs of heart failure or excessive mortality. Here, we show classical cardiac hypertrophy markers were absent in TGAC8, and that total left ventricular (LV) mass was not increased: a reduced LV cavity volume in TGAC8 was encased by thicker LV walls harboring an increased number of small cardiac myocytes, and a network of small interstitial proliferative non-cardiac myocytes compared to wild type (WT) littermates; Protein synthesis, proteosome activity, and autophagy were enhanced in TGAC8 vs WT, and Nrf-2, Hsp90α, and ACC2 protein levels were increased. Despite increased energy demands in vivo LV ATP and phosphocreatine levels in TGAC8 did not differ from WT. Unbiased omics analyses identified more than 2,000 transcripts and proteins, comprising a broad array of biological processes across multiple cellular compartments, which differed by genotype; compared to WT, in TGAC8 there was a shift from fatty acid oxidation to aerobic glycolysis in the context of increased utilization of the pentose phosphate shunt and nucleotide synthesis. Thus, marked overexpression of AC8 engages complex, coordinate adaptation "circuity" that has evolved in mammalian cells to defend against stress that threatens health or life (elements of which have already been shown to be central to cardiac ischemic pre-conditioning and exercise endurance cardiac conditioning) that may be of biological significance to allow for proper healing in disease states such as infarction or failure of the heart.