Visual account of protein investment in cellular functions

Trajectories for the evolution of bacterial CO2-concentrating mechanisms

Cyanobacteria rely on CO2-concentrating mechanisms (CCMs) to grow in today's atmosphere (0.04% CO2). These complex physiological adaptations require ≈15 genes to produce two types of protein complexes: inorganic carbon (Ci) transporters and 100+ nm carboxysome compartments that encapsulate rubisco with a carbonic anhydrase (CA) enzyme. Mutations disrupting any of these genes prohibit growth in ambient air. If any plausible ancestral form-i.e., lacking a single gene-cannot grow, how did the CCM evolve? Here, we test the hypothesis that evolution of the bacterial CCM was "catalyzed" by historically high CO2 levels that decreased over geologic time. Using an E. coli reconstitution of a bacterial CCM, we constructed strains lacking one or more CCM components and evaluated their growth across CO2 concentrations. We expected these experiments to demonstrate the importance of the carboxysome. Instead, we found that partial CCMs expressing CA or Ci uptake genes grew better than controls in intermediate CO2 levels (≈1%) and observed similar phenotypes in two autotrophic bacteria, Halothiobacillus neapolitanus and Cupriavidus necator. To understand how CA and Ci uptake improve growth, we model autotrophy as colimited by CO2 and HCO3-, as both are required to produce biomass. Our experiments and model delineated a viable trajectory for CCM evolution where decreasing atmospheric CO2 induces an HCO3- deficiency that is alleviated by acquisition of CA or Ci uptake, thereby enabling the emergence of a modern CCM. This work underscores the importance of considering physiology and environmental context when studying the evolution of biological complexity.

A prognostic and therapeutic hallmark developed by the integrated profile of basement membrane and immune infiltrative landscape in lung adenocarcinoma

Basement membranes (BMs) are specialised extracellular matrices that maintain cellular integrity and resist the breaching of carcinoma cells for metastases while regulating tumour immunity. The tumour immune microenvironment (TME) is essential for tumour growth and the response to and benefits from immunotherapy. In this study, the BM score and TME score were constructed based on the expression signatures of BM-related genes and the presence of immune cells in lung adenocarcinoma (LUAD), respectively. Subsequently, the BM-TME classifier was developed with the combination of BM score and TME score for accurate prognostic prediction. Further, Kaplan-Meier survival estimation, univariate Cox regression analysis and receiver operating characteristic curves were used to cross-validate and elucidate the prognostic prediction value of the BM-TME classifier in several cohorts. Findings from functional annotation analysis suggested that the potential molecular regulatory mechanisms of the BM-TME classifier were closely related to the cell cycle, mitosis and DNA replication pathways. Additionally, the guiding value of the treatment strategy of the BM-TME classifier for LUAD was determined. Future clinical disease management may benefit from the findings of our research.

The mechanical regulation of RNA binding protein hnRNPC in the failing heart

Cardiac pathologies are characterized by intense remodeling of the extracellular matrix (ECM) that eventually leads to heart failure. Cardiomyocytes respond to the ensuing biomechanical stress by reexpressing fetal contractile proteins via transcriptional and posttranscriptional processes, such as alternative splicing (AS). Here, we demonstrate that the heterogeneous nuclear ribonucleoprotein C (hnRNPC) is up-regulated and relocates to the sarcomeric Z-disc upon ECM pathological remodeling. We show that this is an active site of localized translation, where the ribonucleoprotein associates with the translation machinery. Alterations in hnRNPC expression, phosphorylation, and localization can be mechanically determined and affect the AS of mRNAs involved in mechanotransduction and cardiovascular diseases, including Hippo pathway effector Yes-associated protein 1. We propose that cardiac ECM remodeling serves as a switch in RNA metabolism by affecting an associated regulatory protein of the spliceosome apparatus. These findings offer new insights on the mechanism of mRNA homeostatic mechanoregulation in pathological conditions.

Multi-Omics of Corynebacterium Pseudotuberculosis 12CS0282 and an In Silico Reverse Vaccinology Approach Reveal Novel Vaccine and Drug Targets

Corynebacterium pseudotuberculosis is an important animal pathogen, which is also able to infect humans. An optimal treatment of infections with this pathogen is not available today and consequently, more research is necessary to understand the infection process. Here, we present a combined -omics and bioinformatics approach to characterize C. pseudotuberculosis 12CS0282. The genome sequence of strain 12CS0282 was determined, analyzed in comparison with the available 130 C. pseudotuberculosis sequences and used as a basis for proteome analyses. In a reverse vaccinology approach, putative vaccine and drug targets for 12CS0208 were identified. Mass spectrometry analyses revealed the presence of multiple virulence factors even without host contact. In macrophage interaction studies, C. pseudotuberculosis 12CS0282 was highly resistant against human phagocytes and even multiplied within human THP-1 cells. Taken together, the data indicate a high pathogenic potential of the strain.

Phytochromes and Their Role in Diurnal Variations of ROS Metabolism and Plant Proteome

Plants are sessile organisms forced to adapt to environmental variations recurring in a day-night cycle. Extensive research has uncovered the transcriptional control of plants' inner clock and has revealed at least some part of the intricate and elaborate regulatory mechanisms that govern plant diel responses and provide adaptation to the ever-changing environment. Here, we analyzed the proteome of the Arabidopsis thaliana mutant genotypes collected in the middle of the day and the middle of the night, including four mutants in the phytochrome (phyA, phyB, phyC, and phyD) and the circadian clock protein LHY. Our approach provided a novel insight into the diel regulations, identifying 640 significant changes in the night-day protein abundance. The comparison with previous studies confirmed that a large portion of identified proteins was a known target of diurnal regulation. However, more than 300 were novel oscillations hidden under standard growth chamber conditions or not manifested in the wild type. Our results indicated a prominent role for ROS metabolism and phytohormone cytokinin in the observed regulations, and the consecutive analyses confirmed that. The cytokinin signaling significantly increased at night, and in the mutants, the hydrogen peroxide content was lower, and the night-day variation seemed to be lost in the phyD genotype. Furthermore, regulations in the lhy and phyB mutants were partially similar to those found in the catalase mutant cat2, indicating shared ROS-mediated signaling pathways. Our data also shed light on the role of the relatively poorly characterized Phytochrome D, pointing to its connection to glutathione metabolism and the regulation of glutathione S-transferases.

Profound Effects of Dexamethasone on the Immunological State, Synthesis and Secretion Capacity of Human Testicular Peritubular Cells

The functions of human testicular peritubular cells (HTPCs), forming a small compartment located between the seminiferous epithelium and the interstitial areas of the testis, are not fully known but go beyond intratesticular sperm transport and include immunological roles. The expression of the glucocorticoid receptor (GR) indicates that they may be regulated by glucocorticoids (GCs). Herein, we studied the consequences of the GC dexamethasone (Dex) in cultured HTPCs, which serves as a unique window into the human testis. We examined changes in cytokines, mainly by qPCR and ELISA. A holistic mass-spectrometry-based proteome analysis of cellular and secreted proteins was also performed. Dex, used in a therapeutic concentration, decreased the transcript level of proinflammatory cytokines, e.g., IL6, IL8 and MCP1. An siRNA-mediated knockdown of GR reduced the actions on IL6. Changes in IL6 were confirmed by ELISA measurements. Of note, Dex also lowered GR levels. The proteomic results revealed strong responses after 24 h (31 significantly altered cellular proteins) and more pronounced ones after 72 h of Dex exposure (30 less abundant and 42 more abundant cellular proteins). Dex also altered the composition of the secretome (33 proteins decreased, 13 increased) after 72 h. Among the regulated proteins were extracellular matrix (ECM) and basement membrane components (e.g., FBLN2, COL1A2 and COL3A1), as well as PTX3 and StAR. These results pinpoint novel, profound effects of Dex in HTPCs. If transferrable to the human testis, changes specifically in ECM and the immunological state of the testis may occur in men upon treatment with Dex for medical reasons.

Typing characteristics of metabolism-related genes in osteoporosis

Objective: Osteoporosis is a common musculoskeletal disease. Fractures caused by osteoporosis place a huge burden on global healthcare. At present, the mechanism of metabolic-related etiological heterogeneity of osteoporosis has not been explored, and no research has been conducted to analyze the metabolic-related phenotype of osteoporosis. This study aimed to identify different types of osteoporosis metabolic correlates associated with underlying pathogenesis by machine learning.

Methods: In this study, the gene expression profiles GSE56814 and GSE56815 of osteoporosis patients were downloaded from the GEO database, and unsupervised clustering analysis was used to identify osteoporosis metabolic gene subtypes and machine learning to screen osteoporosis metabolism-related characteristic genes. Meanwhile, multi-omics enrichment was performed using the online Proteomaps tool, and the results were validated using external datasets GSE35959 and GSE7429. Finally, the immune and stromal cell types of the signature genes were inferred by the xCell method.

Results: Based on unsupervised cluster analysis, osteoporosis metabolic genotyping can be divided into three distinct subtypes: lipid and steroid metabolism subtypes, glycolysis-related subtypes, and polysaccharide subtypes. In addition, machine learning SVM identified 10 potentially metabolically related genes, GPR31, GATM, DDB2, ARMCX1, RPS6, BTBD3, ADAMTSL4, COQ6, B3GNT2, and CD9.

Conclusion: Based on the clustering analysis of gene expression in patients with osteoporosis and machine learning, we identified different metabolism-related subtypes and characteristic genes of osteoporosis, which will help to provide new ideas for the metabolism-related pathogenesis of osteoporosis and provide a new direction for follow-up research.

The combined signatures of hypoxia and cellular landscape provides a prognostic and therapeutic biomarker in hepatitis B virus-related hepatocellular carcinoma

Prognosis and treatment options of hepatitis B virus-related hepatocellular carcinoma (HBV-HCC) are generally based on tumor burden and liver function. Yet, tumor growth and therapeutic resistance of HBV-HCC are strongly influenced by intratumoral hypoxia and cells infiltrating the tumor microenvironment (TME). We, therefore, studied whether linking parameters associated with hypoxia and TME cells could have a better prediction of prognosis and therapeutic responses. Quantification of 109 hypoxia-related genes and 64 TME cells was performed in 452 HBV-HCC tumors. Prognostic hypoxia and TME cells signatures were determined based on Cox regression and meta-analysis for generating the Hypoxia-TME classifier. Thereafter, the prognosis, tumor, and immune characteristics as well as the benefit of therapies in Hypoxia-TME defined subgroups were analyzed. Patients in the Hypoxialow /TMEhigh subgroup showed a better prognosis and therapeutic responses than any other subgroups, which can be well elucidated based on the differences in terms of immune-related molecules, tumor somatic mutations, and cancer cellular signaling pathways. Notably, our analysis furthermore demonstrated the synergistic influence of hypoxia and TME on tumor metabolism and proliferation. Besides, the classifier allowed a further subdivision of patients with early- and late-HCC stages. In addition, the Hypoxia-TME classifier was validated in another independent HBV-HCC cohort (n = 144) and several pan-cancer cohorts. Overall, the Hypoxia-TME classifier showed a pretreatment predictive value for prognosis and therapeutic responses, which might provide new directions for strategizing patients with optimal therapies.

Phenotypic response of yeast metabolic network to availability of proteinogenic amino acids

Genome-scale metabolism can best be described as a highly interconnected network of biochemical reactions and metabolites. The flow of metabolites, i.e., flux, throughout these networks can be predicted and analyzed using approaches such as flux balance analysis (FBA). By knowing the network topology and employing only a few simple assumptions, FBA can efficiently predict metabolic functions at the genome scale as well as microbial phenotypes. The network topology is represented in the form of genome-scale metabolic models (GEMs), which provide a direct mapping between network structure and function via the enzyme-coding genes and corresponding metabolic capacity. Recently, the role of protein limitations in shaping metabolic phenotypes have been extensively studied following the reconstruction of enzyme-constrained GEMs. This framework has been shown to significantly improve the accuracy of predicting microbial phenotypes, and it has demonstrated that a global limitation in protein availability can prompt the ubiquitous metabolic strategy of overflow metabolism. Being one of the most abundant and differentially expressed proteome sectors, metabolic proteins constitute a major cellular demand on proteinogenic amino acids. However, little is known about the impact and sensitivity of amino acid availability with regards to genome-scale metabolism. Here, we explore these aspects by extending on the enzyme-constrained GEM framework by also accounting for the usage of amino acids in expressing the metabolic proteome. Including amino acids in an enzyme-constrained GEM of Saccharomyces cerevisiae, we demonstrate that the expanded model is capable of accurately reproducing experimental amino acid levels. We further show that the metabolic proteome exerts variable demands on amino acid supplies in a condition-dependent manner, suggesting that S. cerevisiae must have evolved to efficiently fine-tune the synthesis of amino acids for expressing its metabolic proteins in response to changes in the external environment. Finally, our results demonstrate how the metabolic network of S. cerevisiae is robust towards perturbations of individual amino acids, while simultaneously being highly sensitive when the relative amino acid availability is set to mimic a priori distributions of both yeast and non-yeast origins.

N-linked glycoproteomic profiling in esophageal squamous cell carcinoma

BACKGROUND

Mass spectrometry-based proteomics and glycomics reveal post-translational modifications providing significant biological insights beyond the scope of genomic sequencing.

AIM

To characterize the N-linked glycoproteomic profile in esophageal squamous cell carcinoma (ESCC) via two complementary approaches.

METHODS

Using tandem multilectin affinity chromatography for enrichment of N-linked glycoproteins, we performed N-linked glycoproteomic profiling in ESCC tissues by two-dimensional gel electrophoresis (2-DE)-based and isobaric tags for relative and absolute quantification (iTRAQ) labeling-based mass spectrometry quantitation in parallel, followed by validation of candidate glycoprotein biomarkers by Western blot.

RESULTS

2-DE-based and iTRAQ labeling-based quantitation identified 24 and 402 differentially expressed N-linked glycoproteins, respectively, with 15 in common, demonstrating the outperformance of iTRAQ labeling-based quantitation over 2-DE and complementarity of these two approaches. Proteomaps showed the distinct compositions of functional categories between proteins and glycoproteins with differential expression associated with ESCC. Western blot analysis validated the up-regulation of total procathepsin D and high-mannose procathepsin D, and the down-regulation of total haptoglobin, high-mannose clusterin, and GlcNAc/sialic acid-containing fraction of 14-3-3ζ in ESCC tissues. The serum levels of glycosylated fractions of clusterin, proline-arginine-rich end leucine-rich repeat protein, and haptoglobin in patients with ESCC were remarkably higher than those in healthy controls.

CONCLUSION

Our study provides insights into the aberrant N-linked glycoproteome associated with ESCC, which will be a valuable resource for future investigations.

Connections between Exoproteome Heterogeneity and Virulence in the Oral Pathogen Aggregatibacter actinomycetemcomitans

Aggregatibacter actinomycetemcomitans is a Gram-negative bacterial pathogen associated with severe periodontitis and nonoral diseases. Clinical isolates of A. actinomycetemcomitans display a rough (R) colony phenotype with strong adherent properties. Upon prolonged culturing, nonadherent strains with a smooth (S) colony phenotype emerge. To date, most virulence studies on A. actinomycetemcomitans have been performed with S strains of A. actinomycetemcomitans, whereas the virulence of clinical R isolates has received relatively little attention. Since the extracellular proteome is the main bacterial reservoir of virulence factors, the present study was aimed at a comparative analysis of this subproteome fraction for a collection of R isolates and derivative S strains, in order to link particular proteins to the virulence of A. actinomycetemcomitans with serotype b. To assess the bacterial virulence, we applied different infection models based on larvae of the greater wax moth Galleria mellonella, a human salivary gland-derived epithelial cell line, and freshly isolated neutrophils from healthy human volunteers. A total number of 351 extracellular A. actinomycetemcomitans proteins was identified by mass spectrometry, with the S strains consistently showing more extracellular proteins than their parental R isolates. A total of 50 known extracellular virulence factors was identified, of which 15 were expressed by all investigated bacteria. Importantly, the comparison of differences in exoproteome composition and virulence highlights critical roles of 10 extracellular proteins in the different infection models. Together, our findings provide novel clues for understanding the virulence of A. actinomycetemcomitans and for development of potential preventive or therapeutic avenues to neutralize this important oral pathogen.

IMPORTANCE Periodontitis is one of the most common inflammatory diseases worldwide, causing high morbidity and decreasing the quality of life of millions of people. The bacterial pathogen Aggregatibacter actinomycetemcomitans is strongly associated with aggressive forms of periodontitis. Moreover, it has been implicated in serious nonoral infections, including endocarditis and brain abscesses. Therefore, it is important to investigate how A. actinomycetemcomitans can cause disease. In the present study, we applied a mass spectrometry approach to make an inventory of the virulence factors secreted by different clinical A. actinomycetemcomitans isolates and derivative strains that emerged upon culturing. We subsequently correlated the secreted virulence factors to the pathogenicity of the investigated bacteria in different infection models. The results show that a limited number of extracellular virulence factors of A. actinomycetemcomitans have central roles in pathogenesis, indicating that they could be druggable targets to prevent or treat oral disease.

NAD kinase promotes Staphylococcus aureus pathogenesis by supporting production of virulence factors and protective enzymes

Nicotinamide adenine dinucleotide phosphate (NADPH) is the primary electron donor for reductive reactions that are essential for the biosynthesis of major cell components in all organisms. Nicotinamide adenine dinucleotide kinase (NADK) is the only enzyme that catalyzes the synthesis of NADP(H) from NAD(H). While the enzymatic properties and physiological functions of NADK have been thoroughly studied, the role of NADK in bacterial pathogenesis remains unknown. Here, we used CRISPR interference to knock down NADK gene expression to address the role of this enzyme in Staphylococcus aureus pathogenic potential. We find that NADK inhibition drastically decreases mortality of zebrafish infected with S. aureus. Furthermore, we show that NADK promotes S. aureus survival in infected macrophages by protecting bacteria from antimicrobial defense mechanisms. Proteome-wide data analysis revealed that production of major virulence-associated factors is sustained by NADK. We demonstrate that NADK is required for expression of the quorum-sensing response regulator AgrA, which controls critical S. aureus virulence determinants. These findings support a key role for NADK in bacteria survival within innate immune cells and the host during infection.

Longitudinal plasma proteomic profiling of patients with non-small cell lung cancer undergoing immune checkpoint blockade

Background

Immune checkpoint inhibitors (ICIs) have revolutionized the cancer therapy landscape due to long-term benefits in patients with advanced metastatic disease. However, robust predictive biomarkers for response are still lacking and treatment resistance is not fully understood.

Methods

We profiled approximately 800 pre-treatment and on-treatment plasma proteins from 143 ICI-treated patients with non-small cell lung cancer (NSCLC) using ELISA-based arrays. Different clinical parameters were collected from the patients including specific mutations, smoking habits, and body mass index, among others. Machine learning algorithms were used to identify a predictive signature for response. Bioinformatics tools were used for the identification of patient subtypes and analysis of differentially expressed proteins and pathways in each response group.

Results

We identified a predictive signature for response to treatment comprizing two proteins (CXCL8 and CXCL10) and two clinical parameters (age and sex). Bioinformatic analysis of the proteomic profiles identified three distinct patient clusters that correlated with multiple parameters such as response, sex and TNM (tumors, nodes, and metastasis) staging. Patients who did not benefit from ICI therapy exhibited significantly higher plasma levels of several proteins on-treatment, and enrichment in neutrophil-related proteins.

Conclusions

Our study reveals potential biomarkers in blood plasma for predicting response to ICI therapy in patients with NSCLC and sheds light on mechanisms underlying therapy resistance.

Massive expression of cysteine-containing proteins causes abnormal elongation of yeast cells by perturbing the proteasome

The enhanced green fluorescent protein (EGFP) is considered to be a harmless protein because the critical expression level that causes growth defects is higher than that of other proteins. Here, we found that overexpression of EGFP, but not a glycolytic protein Gpm1, triggered the cell elongation phenotype in the budding yeast Saccharomyces cerevisiae. By the morphological analysis of the cell overexpressing fluorescent protein and glycolytic enzyme variants, we revealed that cysteine content was associated with the cell elongation phenotype. The abnormal cell morphology triggered by overexpression of EGFP was also observed in the fission yeast Schizosaccharomyces pombe. Overexpression of cysteine-containing protein was toxic, especially at high-temperature, while the toxicity could be modulated by additional protein characteristics. Investigation of protein aggregate formation, morphological abnormalities in mutants, and transcriptomic changes that occur upon overexpression of EGFP variants suggested that perturbation of the proteasome by the exposed cysteine of the overexpressed protein causes cell elongation. Overexpression of proteins with relatively low folding properties, such as EGFP, was also found to promote the formation of SHOTA (Seventy kDa Heat shock protein-containing, Overexpression-Triggered Aggregates), an intracellular aggregate that incorporates Hsp70/Ssa1, which induces a heat shock response, while it was unrelated to cell elongation. Evolutionary analysis of duplicated genes showed that cysteine toxicity may be an evolutionary bias to exclude cysteine from highly expressed proteins. The overexpression of cysteine-less moxGFP, the least toxic protein revealed in this study, would be a good model system to understand the physiological state of protein burden triggered by ultimate overexpression of harmless proteins.

Proteome allocations change linearly with the specific growth rate of Saccharomyces cerevisiae under glucose limitation

Saccharomyces cerevisiae is a widely used cell factory; therefore, it is important to understand how it organizes key functional parts when cultured under different conditions. Here, we perform a multiomics analysis of S. cerevisiae by culturing the strain with a wide range of specific growth rates using glucose as the sole limiting nutrient. Under these different conditions, we measure the absolute transcriptome, the absolute proteome, the phosphoproteome, and the metabolome. Most functional protein groups show a linear dependence on the specific growth rate. Proteins engaged in translation show a perfect linear increase with the specific growth rate, while glycolysis and chaperone proteins show a linear decrease under respiratory conditions. Glycolytic enzymes and chaperones, however, show decreased phosphorylation with increasing specific growth rates; at the same time, an overall increased flux through these pathways is observed. Further analysis show that even though mRNA levels do not correlate with protein levels for all individual genes, the transcriptome level of functional groups correlates very well with its corresponding proteome. Finally, using enzyme-constrained genome-scale modeling, we find that enzyme usage plays an important role in controlling flux in amino acid biosynthesis.

Predicting Metabolic Adaptation Under Dynamic Substrate Conditions Using a Resource-Dependent Kinetic Model: A Case Study Using Saccharomyces cerevisiae

Exposed to changes in their environment, microorganisms will adapt their phenotype, including metabolism, to ensure survival. To understand the adaptation principles, resource allocation-based approaches were successfully applied to predict an optimal proteome allocation under (quasi) steady-state conditions. Nevertheless, for a general, dynamic environment, enzyme kinetics will have to be taken into account which was not included in the linear resource allocation models. To this end, a resource-dependent kinetic model was developed and applied to the model organism Saccharomyces cerevisiae by combining published kinetic models and calibrating the model parameters to published proteomics and fluxomics datasets. Using this approach, we were able to predict specific proteomes at different dilution rates under chemostat conditions. Interestingly, the approach suggests that the occurrence of aerobic fermentation (Crabtree effect) in S. cerevisiae is not caused by space limitation in the total proteome but rather an effect of constraints on the mitochondria. When exposing the approach to repetitive, dynamic substrate conditions, the proteome space was allocated differently. Less space was predicted to be available for non-essential enzymes (reserve space). This could indicate that the perceived “overcapacity” present in experimentally measured proteomes may very likely serve a purpose in increasing the robustness of a cell to dynamic conditions, especially an increase of proteome space for the growth reaction as well as of the trehalose cycle that was shown to be essential in providing robustness upon stronger substrate perturbations. The model predictions of proteome adaptation to dynamic conditions were additionally evaluated against respective experimentally measured proteomes, which highlighted the model’s ability to accurately predict major proteome adaptation trends. This proof of principle for the approach can be extended to production organisms and applied for both understanding metabolic adaptation and improving industrial process design.

Prosit-TMT: Deep Learning Boosts Identification of TMT-Labeled Peptides

The prediction of fragment ion intensities and retention time of peptides has gained significant attention over the past few years. However, the progress shown in the accurate prediction of such properties focused primarily on unlabeled peptides. Tandem mass tags (TMT) are chemical peptide labels that are coupled to free amine groups usually after protein digestion to enable the multiplexed analysis of multiple samples in bottom-up mass spectrometry. It is a standard workflow in proteomics ranging from single-cell to high-throughput proteomics. Particularly for TMT, increasing the number of confidently identified spectra is highly desirable as it provides identification and quantification information with every spectrum. Here, we report on the generation of an extensive resource of synthetic TMT-labeled peptides as part of the ProteomeTools project and present the extension of the deep learning model Prosit to accurately predict the retention time and fragment ion intensities of TMT-labeled peptides with high accuracy. Prosit-TMT supports CID and HCD fragmentation and ion trap and Orbitrap mass analyzers in a single model. Reanalysis of published TMT data sets show that this single model extracts substantial additional information. Applying Prosit-TMT, we discovered that the expression of many proteins in human breast milk follows a distinct daily cycle which may prime the newborn for nutritional or environmental cues.

Combined Transcriptomic and Protein Array Cytokine Profiling of Human Stem Cells from Dental Apical Papilla Modulated by Oral Bacteria

Stem cells from the apical papilla (SCAP) are a promising resource for use in regenerative endodontic treatment (RET) that may be adversely affected by oral bacteria, which in turn can exert an effect on the success of RET. Our work aims to study the cytokine profile of SCAP upon exposure to oral bacteria and their supernatants—Fusobacterium nucleatum and Enterococcus faecalis—as well as to establish their effect on the osteogenic and immunogenic potentials of SCAP. Further, we target the presence of key proteins of the Wnt/β-Catenin, TGF-β, and NF-κB signaling pathways, which play a crucial role in adult osteogenic differentiation of mesenchymal stem cells, using the Western blot (WB) technique. The membrane-based sandwich immunoassay and transcriptomic analysis showed that, under the influence of F. nucleatum (both bacteria and supernatant), the production of pro-inflammatory cytokines IL-6, IL-8, and MCP-1 occurred, which was also confirmed at the mRNA level. Conversely, E. faecalis reduced the secretion of the aforementioned cytokines at both mRNA and protein levels. WB analysis showed that SCAP co-cultivation with E. faecalis led to a decrease in the level of the key proteins of the Wnt/β-Catenin and NF-κB signaling pathways: β-Catenin (p = 0.0068 *), LRP-5 (p = 0.0059 **), and LRP-6 (p = 0.0329 *), as well as NF-kB (p = 0.0034 **) and TRAF6 (p = 0.0285 *). These results suggest that oral bacteria can up- and downregulate the immune and inflammatory responses of SCAP, as well as influence the osteogenic potential of SCAP, which may negatively regulate the success of RET.

Multi- and transgenerational biochemical effects of low-dose exposure to bisphenol A and 4-nonylphenol on testicular interstitial (Leydig) cells

Bisphenol A (BPA) and 4-nonylphenol (NP) are well-known endocrine-disrupting chemicals (EDCs) that have been proven to affect Leydig cell (LC) functions and testosterone production, but whether BPA and NP have multi- and transgenerational biochemical effects on Leydig cells (LCs) is unknown. Fourier transform infrared (FTIR) spectroscopy is a powerful analytical technique that enables label-free and non-destructive analysis of the tissue specimen. Herein we employed FTIR coupled with chemometrics analysis to identify biomolecular changes in testicular interstitial (Leydig) cells of rats after chronic exposure to low doses of BPA and NP. Cluster segregations between exposed and control groups were observed based on the fingerprint region of 1800-900 cm^-1 in all generations. The main biochemical alterations for segregation were amide I, amide II and nucleic acids. BPA and NP single and co-exposure induced significant differences in the ratio of amide I to amide II compared to the corresponding control group in all generations. BPA exposure resulted in remarkable changes of cellular gene transcription and DNA oxidative damage across all generations. Direct exposure to BPA, NP, and BPA&NP of F0 and F1 generations could significantly decrease lipid accumulation in LCs in the F2 and F3 generations. The overall findings revealed that single or co-exposure to BPA and NP at environmental concentrations affects the biochemical structures and properties of LCs.

Dynamic Changes in the Proteome of Early Bovine Embryos Developed In Vivo

Early embryo development is a dynamic process involving important molecular and structural changes leading to the embryonic genome activation (EGA) and early cell lineage differentiation. Our aim was to elucidate proteomic changes in bovine embryos developed in vivo. Eleven females were used as embryo donors and pools of embryos at the 4–6 cell, 8–12 cell, morula, compact morula and blastocyst stages were analyzed by nanoliquid chromatography coupled with label free quantitative mass spectrometry. A total of 2,757 proteins were identified, of which 1,950 were quantitatively analyzed. Principal component analysis of data showed a clear separation of embryo pools according to their developmental stage. The hierarchical clustering of differentially abundant proteins evidenced a first cluster of 626 proteins that increased in abundance during development and a second cluster of 400 proteins that decreased in abundance during development, with most significant changes at the time of EGA and blastocyst formation. The main pathways and processes overrepresented among upregulated proteins were RNA metabolism, protein translation and ribosome biogenesis, whereas Golgi vesicle transport and protein processing in endoplasmic reticulum were overrepresented among downregulated proteins. The pairwise comparison between stages allowed us to identify specific protein interaction networks and metabolic pathways at the time of EGA, morula compaction and blastocyst formation. This is the first comprehensive study of proteome dynamics in non-rodent mammalian embryos developed in vivo. These data provide a number of protein candidates that will be useful for further mechanistic and functional studies.

Absolute Proteome Quantification in the Gas-Fermenting Acetogen Clostridium autoethanogenum

Microbes that can recycle one-carbon (C₁) greenhouse gases into fuels and chemicals are vital for the biosustainability of future industries. Acetogens are the most efficient known microbes for fixing carbon oxides CO₂ and CO. Understanding proteome allocation is important for metabolic engineering as it dictates metabolic fitness. Here, we use absolute proteomics to quantify intracellular concentrations for >1,000 proteins in the model acetogen Clostridium autoethanogenum grown autotrophically on three gas mixtures (CO, CO+H₂, or CO+CO₂+H₂). We detect the prioritization of proteome allocation for C₁ fixation and the significant expression of proteins involved in the production of acetate and ethanol as well as proteins with unclear functions. The data also revealed which isoenzymes are likely relevant in vivo for CO oxidation, H₂ metabolism, and ethanol production. The integration of proteomic and metabolic flux data demonstrated that enzymes catalyze high fluxes with high concentrations and high in vivo catalytic rates. We show that flux adjustments were dominantly accompanied by changing enzyme catalytic rates rather than concentrations.

IMPORTANCE Acetogen bacteria are important for maintaining biosustainability as they can recycle gaseous C₁ waste feedstocks (e.g., industrial waste gases and syngas from gasified biomass or municipal solid waste) into fuels and chemicals. Notably, the acetogen Clostridium autoethanogenum is being used as a cell factory in industrial-scale gas fermentation. Here, we perform reliable absolute proteome quantification for the first time in an acetogen. This is important as our work advances both rational metabolic engineering of acetogen cell factories and accurate in silico reconstruction of their phenotypes. Furthermore, this absolute proteomics data set serves as a reference toward a better systems-level understanding of the ancient metabolism of acetogens.

Harnessing secretory pathway differences between HEK293 and CHO to rescue production of difficult to express proteins

Biologics represent the fastest growing group of therapeutics, but many advanced recombinant protein moieties remain difficult to produce. Here, we identify metabolic engineering targets limiting expression of recombinant human proteins through a systems biology analysis of the transcriptomes of CHO and HEK293 during recombinant expression. In an expression comparison of 24 difficult to express proteins, one third of the challenging human proteins displayed improved secretion upon host cell swapping from CHO to HEK293. Guided by a comprehensive transcriptomics comparison between cell lines, especially highlighting differences in secretory pathway utilization, a co-expression screening of 21 secretory pathway components validated ATF4, SRP9, JUN, PDIA3 and HSPA8 as productivity boosters in CHO. Moreover, more heavily glycosylated products benefitted more from the elevated activities of the N- and O-glycosyltransferases found in HEK293. Collectively, our results demonstrate the utilization of HEK293 for expression rescue of human proteins and suggest a methodology for identification of secretory pathway components for metabolic engineering of HEK293 and CHO.

A chemoresistance lncRNA signature for recurrence risk stratification of colon cancer patients with chemotherapy

Chemotherapy is considered the nonsurgical treatment of choice for colon cancer patients. However, no precise molecular markers are available to determine which patients can actually benefit from it. In this study, we identified 55 chemotherapy-specific long non-coding RNAs (lncRNAs) of colon cancer patients through a systematic assessment of lncRNA expression profiles from a public database. These were taken from multiple cohorts of colon cancer patients who had received chemotherapy, or not. Based on these data, a chemoresistance lncRNA signature, named CRLSig, was constructed and successfully applied to divide chemotherapy patients into two groups with different recurrence-free survival (RFS) rates. Gene set enrichment analysis revealed that patients with low CRLSig had more infiltrating CD8+ T cells and macrophages, while those with high CRLSig had more infiltrating natural killer T cells. KEGG pathway analysis revealed that the low CRLSig group had more activated metabolic pathways compared with those in the high CRLSig group, indicating better response to chemotherapy. Single-cell sequencing analysis revealed that stromal cells and epithelial cells had higher CRLSig. Thus, we have constructed an auxiliary prognostic tool, CRLSig, able to discriminate patients at high risk of RFS, despite having received standard adjuvant chemotherapy treatment.

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A CRLSig was constructed for the first time

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CRLSig revealed chemotherapy patients with different RFS rates

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Low CRLSig group had more activated metabolic pathways

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ScRNA-seq analysis revealed stromal cells and epithelial cells had higher CRLSig

Reconstruction and analysis of genome-scale metabolic model for thermophilic fungus Myceliophthora thermophila

Myceliophthora thermophila, a thermophilic fungus that can degrade and utilize all major polysaccharides in plant biomass, has great potential in biotechnological industries. Here, the first manually curated genome-scale metabolic model iDL1450 for M. thermophila was reconstructed using an auto-generating pipeline with thorough manual curation. The model contains 1450 genes, 2592 reactions and 1784 unique metabolites. High accuracy was shown in predictions related to carbon and nitrogen source utilization based on data obtained from Biolog experiments. Besides, metabolism profiles were analyzed using iDL1450 integrated with transcriptomics data of M. thermophila at various growth temperatures. The refined model provides new insights into thermophilic fungi metabolism and sheds light on model-driven strain design to improve biotechnological applications of this thermophilic lignocellulosic fungus. This article is protected by copyright. All rights reserved.

Comparative analyses of parasites with a comprehensive database of genome-scale metabolic models

Protozoan parasites cause diverse diseases with large global impacts. Research on the pathogenesis and biology of these organisms is limited by economic and experimental constraints. Accordingly, studies of one parasite are frequently extrapolated to infer knowledge about another parasite, across and within genera. Model in vitro or in vivo systems are frequently used to enhance experimental manipulability, but these systems generally use species related to, yet distinct from, the clinically relevant causal pathogen. Characterization of functional differences among parasite species is confined to post hoc or single target studies, limiting the utility of this extrapolation approach. To address this challenge and to accelerate parasitology research broadly, we present a functional comparative analysis of 192 genomes, representing every high-quality, publicly-available protozoan parasite genome including Plasmodium, Toxoplasma, Cryptosporidium, Entamoeba, Trypanosoma, Leishmania, Giardia, and other species. We generated an automated metabolic network reconstruction pipeline optimized for eukaryotic organisms. These metabolic network reconstructions serve as biochemical knowledgebases for each parasite, enabling qualitative and quantitative comparisons of metabolic behavior across parasites. We identified putative differences in gene essentiality and pathway utilization to facilitate the comparison of experimental findings and discovered that phylogeny is not the sole predictor of metabolic similarity. This knowledgebase represents the largest collection of genome-scale metabolic models for both pathogens and eukaryotes; with this resource, we can predict species-specific functions, contextualize experimental results, and optimize selection of experimental systems for fastidious species.

Global pleiotropic effects in adaptively evolved Escherichia coli lacking CRP reveal molecular mechanisms that define the growth physiology

Evolution facilitates emergence of fitter phenotypes by efficient allocation of cellular resources in conjunction with beneficial mutations. However, system-wide pleiotropic effects that redress the perturbations to the apex node of the transcriptional regulatory networks remain unclear. Here, we elucidate that absence of global transcriptional regulator CRP in Escherichia coli results in alterations in key metabolic pathways under glucose respiratory conditions, favouring stress- or hedging-related functions over growth-enhancing functions. Further, we disentangle the growth-mediated effects from the CRP regulation-specific effects on these metabolic pathways. We quantitatively illustrate that the loss of CRP perturbs proteome efficiency, as evident from metabolic as well as ribosomal proteome fractions, that corroborated with intracellular metabolite profiles. To address how E. coli copes with such systemic defect, we evolved Δcrp mutant in the presence of glucose. Besides acquiring mutations in the promoter of glucose transporter ptsG, the evolved populations recovered the metabolic pathways to their pre-perturbed state coupled with metabolite re-adjustments, which altogether enabled increased growth. By contrast to Δcrp mutant, the evolved strains remodelled their proteome efficiency towards biomass synthesis, albeit at the expense of carbon efficiency. Overall, we comprehensively illustrate the genetic and metabolic basis of pleiotropic effects, fundamental for understanding the growth physiology.

Novel insights into PORCN mutations, associated phenotypes and pathophysiological aspects

BACKGROUND

Goltz syndrome (GS) is a X-linked disorder defined by defects of mesodermal- and ectodermal-derived structures and caused by PORCN mutations. Features include striated skin-pigmentation, ocular and skeletal malformations and supernumerary or hypoplastic nipples. Generally, GS is associated with in utero lethality in males and most of the reported male patients show mosaicism (only three non-mosaic surviving males have been described so far). Also, precise descriptions of neurological deficits in GS are rare and less severe phenotypes might not only be caused by mosaicism but also by less pathogenic mutations suggesting the need of a molecular genetics and functional work-up of these rare variants.

RESULTS

We report two cases: one girl suffering from typical skin and skeletal abnormalities, developmental delay, microcephaly, thin corpus callosum, periventricular gliosis and drug-resistant epilepsy caused by a PORCN nonsense-mutation (c.283C > T, p.Arg95Ter). Presence of these combined neurological features indicates that CNS-vulnerability might be a guiding symptom in the diagnosis of GS patients. The other patient is a boy with a supernumerary nipple and skeletal anomalies but also, developmental delay, microcephaly, cerebral atrophy with delayed myelination and drug-resistant epilepsy as predominant features. Skin abnormalities were not observed. Genotyping revealed a novel PORCN missense-mutation (c.847G > C, p.Asp283His) absent in the Genome Aggregation Database (gnomAD) but also identified in his asymptomatic mother. Given that non-random X-chromosome inactivation was excluded in the mother, fibroblasts of the index had been analyzed for PORCN protein-abundance and -distribution, vulnerability against additional ER-stress burden as well as for protein secretion revealing changes.

CONCLUSIONS

Our combined findings may suggest incomplete penetrance for the p.Asp283His variant and provide novel insights into the molecular etiology of GS by adding impaired ER-function and altered protein secretion to the list of pathophysiological processes resulting in the clinical manifestation of GS.

Proteogenomics Integrating Reveal a Complex Network, Alternative Splicing, Hub Genes Regulating Heart Maturation

Heart maturation is an essentially biological process for neonatal heart transition to adult heart, thus illustrating the mechanism of heart maturation may be helpful to explore postnatal heart development and cardiac cardiomyopathy. This study combined proteomic analysis based on isobaric tags for relative and absolute quantitation (iTRAQ) and transcriptome analysis based on RNA sequencing to detect the proteins and genes associated with heart maturation in mice. The proteogenomics integrating analysis identified 254 genes/proteins as commonly differentially expressed between neonatal and adult hearts. Functional and pathway analysis demonstrated that these identified genes/proteins contribute to heart maturation mainly by regulating mRNA processing and energy metabolism. Genome-wide alternative splicing (AS) analysis showed that some important sarcomere and energy-associated genes undergo different AS events. Through the Cytoscape plug-in CytoHubba, a total of 23 hub genes were found and further confirmed by RT-qPCR. Next, we verified that the most up-regulated hub gene, Ogdhl, plays an essential role in heart maturation by detecting energy metabolism phenotype changes in the Ogdhl-interfering cardiomyocytes. Together, we revealed a complex gene network, AS genes and patterns, and candidate hub genes controlling heart maturation by proteome and transcriptome combination analysis.

HLA Allele-Specific Quantitative Profiling of Type 1 Diabetic B Lymphocyte Immunopeptidome

Peptide ligands presented by human leukocyte antigen (HLA) molecules on the cell surface represent the immunopeptidome that could be utilized for identification of antigenic peptides for immunotherapy and prevention of autoimmune diseases. Although T-cells are well-known key players in the destruction of pancreatic beta-cells in type 1 diabetes (T1D), increasing evidence points toward a role for B-cells in disease pathogenesis. However, as antigen presenting cells, little is known about the comprehensive immunopeptidome of B cells and their changes in the context of T1D. We performed HLA allele-specific quantitative immunopeptidomics using B lymphocytes derived from T1D patients and healthy controls. Hundreds of HLA-I and HLA-II immunopeptides were identified as differentially regulated in T1D per HLA allele for B cells sharing identical HLA alleles. The results were further validated using additional T1D and healthy B cells with partially overlapped HLA alleles. Differentially expressed immunopeptides were confirmed with targeted proteomics and for reactivity using known T-cell assays in the immune epitope database. Considering samples with identical HLA alleles are difficult to obtain for T1D and other similar HLA-restricted diseases, our work represents a viable approach to better understand HLA allele-specific antigen presentation and may facilitate identification of immunopeptides for therapeutic applications in autoimmune diseases. Data are available via ProteomeXchange with identifier PXD026184.

Improvement of 2,3-butanediol production by dCas9 gene expression system in Saccharomyces cerevisiae

Saccharomyces cerevisiae has been widely used in bioproduction. To produce a target product other than ethanol, ethanol production must be decreased to enhance target production. An ethanol non-producing yeast strain was previously constructed by knocking out pyruvate decarboxylase (PDC) genes in the ethanol synthetic pathway. However, glucose uptake by the ethanol-non-producing yeast strain was significantly decreased. In this study, dead Cas9 (dCas9) was used to reduce ethanol synthesis during 2,3-butanediol production without reduction of glucose. The binding site of guide RNA used to effectively suppress PDC1 promoter-driven red fluorescent protein expression by dCas9 was identified and applied to control PDC1 expression. The production of 2,3-butanediol rather than ethanol was improved in repetitive test tube culture. Additionally, ethanol production was decreased and 2,3-butanediol production was increased in the strain expressing dCas9 targeting the PDC1 promoter in the third round of cultivation, compared with the control strain.

Defense mechanisms promoting tolerance to aggressive Phytophthora species in hybrid poplar

Poplars are among the fastest-growing trees and significant resources in agriculture and forestry. However, rapid growth requires a large water consumption, and irrigation water provides a natural means for pathogen spread. That includes members of Phytophthora spp. that have proven to be a global enemy to forests. With the known adaptability to new hosts, it is only a matter of time for more aggressive Phytophthora species to become a threat to poplar forests and plantations. Here, the effects of artificial inoculation with two different representatives of aggressive species (P. cactorum and P. plurivora) were analyzed in the proteome of the Phytophthora-tolerant hybrid poplar clone T-14 [Populus tremula L. 70 × (Populus × canescens (Ait.) Sm. 23)]. Wood microcore samples were collected at the active necrosis borders to provide insight into the molecular processes underlying the observed tolerance to Phytophthora. The analysis revealed the impact of Phytophthora on poplar primary and secondary metabolism, including carbohydrate-active enzymes, amino acid biosynthesis, phenolic metabolism, and lipid metabolism, all of which were confirmed by consecutive metabolome and lipidome profiling. Modulations of enzymes indicating systemic response were confirmed by the analysis of leaf proteome, and sampling of wood microcores in distal locations revealed proteins with abundance correlating with proximity to the infection, including germin-like proteins, components of proteosynthesis, glutamate carboxypeptidase, and an enzyme that likely promotes anthocyanin stability. Finally, the identified Phytophthora-responsive proteins were compared to those previously found in trees with compromised defense against Phytophthora, namely, Quercus spp. and Castanea sativa. That provided a subset of candidate markers of Phytophthora tolerance, including certain ribosomal proteins, auxin metabolism enzymes, dioxygenases, polyphenol oxidases, trehalose-phosphate synthase, mannose-1-phosphate guanylyltransferase, and rhamnose biosynthetic enzymes. In summary, this analysis provided the first insight into the molecular mechanisms of hybrid poplar defense against Phytophthora and identified prospective targets for improving Phytophthora tolerance in trees.

A combined signature of glycolysis and immune landscape predicts prognosis and therapeutic response in prostate cancer

Prostate cancer (PCa) is a common malignancy that poses a major threat to the health of men. Prostate-specific antigen (PSA) and its derivatives, as FDA-approved detection assays, are insufficient to serve as optimal markers for patient prognosis and clinical decision-making. It is widely acknowledged that aberrant glycolytic metabolism in PCa is related to tumor progression and acidifies the tumor microenvironment (TME). Considering the non-negligible impacts of glycolysis and immune functions on PCa, we developed a combined classifier in prostate cancer. The Glycolysis Score containing 19 genes and TME Score including three immune cells were created, using the univariate and multivariate Cox proportional hazards model, log-rank test, least absolute shrinkage and selection operator (LASSO) regression analysis and the bootstrap approach. Combining the glycolysis and immunological landscape, the Glycolysis-TME Classifier was then constructed. It was observed that the classifier was more accurate in predicting the prognosis of patients than the current biomarkers. Notably, there were significant differences in metabolic activity, signaling pathways, mutational landscape, immunotherapeutic response, and drug sensitivity among the Glycolysis^high/TME^low, Mixed group and Glycolysis^low/TME^high identified by this classifier. Overall, due to the significant prognostic value and potential therapeutic guidance of the Glycolysis-TME Classifier, we anticipate that this classifier will be clinically beneficial in the management of patients with PCa.

Domont G, C. S. Nogueira F, Marko-Varga G, Sanchez A. Mapping the Melanoma Plasma Proteome (MPP) Using Single-Shot Proteomics Interfaced with the WiMT Database

Plasma analysis by mass spectrometry-based proteomics remains a challenge due to its large dynamic range of 10 orders in magnitude. We created a methodology for protein identification known as Wise MS Transfer (WiMT). Melanoma plasma samples from biobank archives were directly analyzed using simple sample preparation. WiMT is based on MS1 features between several MS runs together with custom protein databases for ID generation. This entails a multi-level dynamic protein database with different immunodepletion strategies by applying single-shot proteomics. The highest number of melanoma plasma proteins from undepleted and unfractionated plasma was reported, mapping >1200 proteins from >10,000 protein sequences with confirmed significance scoring. Of these, more than 660 proteins were annotated by WiMT from the resulting ~5800 protein sequences. We could verify 4000 proteins by MS1t analysis from HeLA extracts. The WiMT platform provided an output in which 12 previously well-known candidate markers were identified. We also identified low-abundant proteins with functions related to (i) cell signaling, (ii) immune system regulators, and (iii) proteins regulating folding, sorting, and degradation, as well as (iv) vesicular transport proteins. WiMT holds the potential for use in large-scale screening studies with simple sample preparation, and can lead to the discovery of novel proteins with key melanoma disease functions.

Experimental study of proteome halophilicity using nanoDSF: a proof of concept

Adaption to environmental conditions is reflected by protein adaptation. In particular, proteins of extremophiles display distinctive traits ensuring functional, structural and dynamical properties under permanently extreme physical and chemical conditions. While it has mostly been studied with approaches focusing on specific proteins, biophysical approaches have also confirmed this link between environmental and protein adaptation at the more complex and diverse scale of the proteome. However, studies of this type remain challenging and often require large amounts of biological material. We report here the use of nanoDSF as a tool to study proteome stability and solubility in cell lysates of the model halophilic archaeon Haloarcula marismortui. Notably, our results show that, as with single halophilic protein studies, proteome stability was correlated to the concentration of NaCl or KCl under which the cells were lysed and hence the proteome exposed. This work highlights that adaptation to environmental conditions can be experimentally observed at the scale of the proteome. Still, we show that the biochemical properties of single halophilic proteins can only be partially extrapolated to the whole proteome.

Pro-tumoral behavior of omental adipocyte-derived fibroblasts in tumor microenvironment at the metastatic site of ovarian cancer

Adipocyte-rich omentum offers "good soil" for disseminating ovarian cancer (OvCa), contributing to therapeutic difficulty. However, little is understood about the association between adipocytes and tumor growth at peritoneal dissemination site. Herein, we report the induction of adipocyte dedifferentiation by OvCa cells and pro-tumorigenic effects of resulted adipocyte-derived fibroblasts. We confirmed that malignant ascites promoted the dedifferentiation of the primary human adipocytes obtained from surgical omental specimen into omental adipocyte-derived fibroblast (O-ADF) that possess both mesenchymal stem cell and myofibroblast-like features. This promotion of dedifferentiation by malignant ascites was blocked by addition of Wnt signaling inhibitor. The effects of dedifferentiated adipocytes in proliferation and migration of OvCa cells were analyzed with in vitro coculturing experimental models and in vivo mice model, and we demonstrated that OvCa cell lines showed enhanced proliferative characteristics, as well as increased migratory abilities upon coculturing with O-ADF. Additionally, exogenous transforming growth factor-β1 augmented desmoplastic morphological change of O-ADF, leading to higher proliferative ability. Our results suggest that OvCa cells promote dedifferentiation of peritoneal adipocytes by activating Wnt/β-catenin signaling, and generated O-ADFs exhibit pro-tumoral hallmarks.

Palmdelphin Regulates Nuclear Resilience to Mechanical Stress in the Endothelium

Supplemental Digital Content is available in the text.

PALMD (palmdelphin) belongs to the family of paralemmin proteins implicated in cytoskeletal regulation. Single nucleotide polymorphisms in the PALMD locus that result in reduced expression are strong risk factors for development of calcific aortic valve stenosis and predict severity of the disease.

A combination strategy of solubility enhancers for effective production of soluble and bioactive human enterokinase

Enterokinase is one of the hydrolases that catalyze hydrolysis to regulate biological processes in intestinal visceral mucosa. Enterokinase plays an essential role in accelerating the process of protein digestion as it converts trypsinogen into active trypsin by accurately recognizing and cleaving a specific peptide sequence, (Asp)4-Lys. Due to its exceptional substrate specificity, enterokinase is widely used as a versatile molecular tool in various bioprocessing, especially in removing fusion tags from recombinant proteins. Despite its biotechnological importance, mass production of soluble enterokinase in bacteria still remains an unsolved challenge. Here, we present an effective production strategy of human enterokinase using tandemly linked solubility enhancers consisting of thioredoxin, phosphoglycerate kinase or maltose-binding protein. The resulting enterokinases exhibited significantly enhanced solubility and bacterial expression level while retaining enzymatic activity, which demonstrates that combinatorial design of fusion proteins has the potential to provide an efficient way to produce recombinant proteins in bacteria.

Muscle-secreted neurturin couples myofiber oxidative metabolism and slow motor neuron identity

Endurance exercise promotes skeletal muscle vascularization, oxidative metabolism, fiber-type switching, and neuromuscular junction integrity. Importantly, the metabolic and contractile properties of the muscle fiber must be coupled to the identity of the innervating motor neuron (MN). Here, we show that muscle-derived neurturin (NRTN) acts on muscle fibers and MNs to couple their characteristics. Using a muscle-specific NRTN transgenic mouse (HSA-NRTN) and RNA sequencing of MN somas, we observed that retrograde NRTN signaling promotes a shift toward a slow MN identity. In muscle, NRTN increased capillary density and oxidative capacity and induced a transcriptional reprograming favoring fatty acid metabolism over glycolysis. This combination of effects on muscle and MNs makes HSA-NRTN mice lean with remarkable exercise performance and motor coordination. Interestingly, HSA-NRTN mice largely recapitulate the phenotype of mice with muscle-specific expression of its upstream regulator PGC-1ɑ1. This work identifies NRTN as a myokine that couples muscle oxidative capacity to slow MN identity.

Protein Signatures of NK Cell-Mediated Melanoma Killing Predict Response to Immunotherapies

Despite impressive advances in melanoma-directed immunotherapies, resistance is common and many patients still succumb to metastatic disease. In this context, harnessing natural killer (NK) cells, which have thus far been sidelined in the development of melanoma immunotherapy, could provide therapeutic benefits for cancer treatment. To identify molecular determinants of NK cell-mediated melanoma killing (NKmK), we quantified NK-cell cytotoxicity against a panel of genetically diverse melanoma cell lines and observed highly heterogeneous susceptibility. Melanoma protein microarrays revealed a correlation between NKmK and the abundance and activity of a subset of proteins, including several metabolic factors. Oxidative phoshorylation, measured by oxygen consumption rate, negatively correlated with melanoma cell sensitivity toward NKmK, and proteins involved in mitochondrial metabolism and epithelial-mesenchymal transition were confirmed to regulate NKmK. Two- and three-dimensional killing assays and melanoma xenografts established that the PI₃K/AKT/mTOR signaling axis controls NKmK via regulation of NK cell-relevant surface proteins. A "protein-killing-signature" based on the protein analysis predicted NKmK of additional melanoma cell lines and the response of patients with melanoma to anti-PD-1 checkpoint therapy. Collectively, these findings identify novel NK cell-related prognostic biomarkers and may contribute to improved and personalized melanoma-directed immunotherapies. SIGNIFICANCE: NK-cell cytotoxicity assays and protein microarrays reveal novel biomarkers of NK cell-mediated melanoma killing and enable development of signatures to predict melanoma patient responsiveness to immunotherapies.

Altered Protein Abundance and Localization Inferred from Sites of Alternative Modification by Ubiquitin and SUMO

Protein modification by ubiquitin or SUMO can alter the function, stability or activity of target proteins. Previous studies have identified thousands of substrates that were modified by ubiquitin or SUMO on the same lysine residue. However, it remains unclear whether such overlap could result from a mere higher solvent accessibility, whether proteins containing those sites are associated with specific functional traits, and whether selectively perturbing their modification by ubiquitin or SUMO could result in different phenotypic outcomes. Here, we mapped reported lysine modification sites across the human proteome and found an enrichment of sites reported to be modified by both ubiquitin and SUMO. Our analysis uncovered thousands of proteins containing such sites, which we term Sites of Alternative Modification (SAMs). Among more than 36,000 sites reported to be modified by SUMO, 51.8% have also been reported to be modified by ubiquitin. SAM-containing proteins are associated with diverse biological functions including cell cycle, DNA damage, and transcriptional regulation. As such, our analysis highlights numerous proteins and pathways as putative targets for further elucidating the crosstalk between ubiquitin and SUMO. Comparing the biological and biochemical properties of SAMs versus other non-overlapping modification sites revealed that these sites were associated with altered cellular localization or abundance of their host proteins. Lastly, using S. cerevisiae as model, we show that mutating the SAM motif in a protein can influence its ubiquitination as well as its localization and abundance.

C9ORF72 Repeat Expansion Affects the Proteome of Primary Skin Fibroblasts in ALS

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by progressive degeneration of the corticospinal motor neurons, which ultimately leads to death. The repeat expansion in chromosome 9 open reading frame 72 (C9ORF72) represents the most common genetic cause of ALS and it is also involved in the pathogenesis of other neurodegenerative disorders. To offer insights into C9ORF72-mediated pathogenesis, we quantitatively analyzed the proteome of patient-derived primary skin fibroblasts from ALS patients carrying the C9ORF72 mutation compared with ALS patients who tested negative for it. Differentially expressed proteins were identified, used to generate a protein-protein interaction network and subjected to a functional enrichment analysis to unveil altered molecular pathways. ALS patients were also compared with patients affected by frontotemporal dementia carrying the C9ORF72 repeat expansion. As a result, we demonstrated that the molecular pathways mainly altered in fibroblasts (e.g., protein homeostasis) mirror the alterations observed in C9ORF72-mutated neurons. Moreover, we highlighted novel molecular pathways (nuclear and mitochondrial transports, vesicle trafficking, mitochondrial bioenergetics, glucose metabolism, ER-phagosome crosstalk and Slit/Robo signaling pathway) which might be further investigated as C9ORF72-specific pathogenetic mechanisms. Data are available via ProteomeXchange with the identifier PXD023866.

Fundamental limits on the rate of bacterial growth and their influence on proteomic composition

Despite abundant measurements of bacterial growth rate, cell size, and protein content, we lack a rigorous understanding of what sets the scale of these quantities and when protein abundances should (or should not) depend on growth rate. Here, we estimate the basic requirements and physical constraints on steady-state growth by considering key processes in cellular physiology across a collection of Escherichia coli proteomic data covering ≈4,000 proteins and 36 growth rates. Our analysis suggests that cells are predominantly tuned for the task of cell doubling across a continuum of growth rates; specific processes do not limit growth rate or dictate cell size. We present a model of proteomic regulation as a function of nutrient supply that reconciles observed interdependences between protein synthesis, cell size, and growth rate and propose that a theoretical inability to parallelize ribosomal synthesis places a firm limit on the achievable growth rate. A record of this paper's transparent peer review process is included in the supplemental information.

Mangroves are an overlooked hotspot of insect diversity despite low plant diversity

BACKGROUND

The world's fast disappearing mangrove forests have low plant diversity and are often assumed to also have a species-poor insect fauna. We here compare the tropical arthropod fauna across a freshwater swamp and six different forest types (rain-, swamp, dry-coastal, urban, freshwater swamp, mangroves) based on 140,000 barcoded specimens belonging to ca. 8500 species.

RESULTS

We find that the globally imperiled habitat "mangroves" is an overlooked hotspot for insect diversity. Our study reveals a species-rich mangrove insect fauna (>3000 species in Singapore alone) that is distinct (>50% of species are mangrove-specific) and has high species turnover across Southeast and East Asia. For most habitats, plant diversity is a good predictor of insect diversity, but mangroves are an exception and compensate for a comparatively low number of phytophagous and fungivorous insect species by supporting an unusually rich community of predators whose larvae feed in the productive mudflats. For the remaining tropical habitats, the insect communities have diversity patterns that are largely congruent across guilds.

CONCLUSIONS

The discovery of such a sizeable and distinct insect fauna in a globally threatened habitat underlines how little is known about global insect biodiversity. We here show how such knowledge gaps can be closed quickly with new cost-effective NGS barcoding techniques.

An Innovative Protocol for Metaproteomic Analyses of Microbial Pathogens in Cystic Fibrosis Sputum

Hallmarks of cystic fibrosis (CF) are increased viscosity of mucus and impaired mucociliary clearance within the airways due to mutations of the cystic fibrosis conductance regulator gene. This facilitates the colonization of the lung by microbial pathogens and the concomitant establishment of chronic infections leading to tissue damage, reduced lung function, and decreased life expectancy. Although the interplay between key CF pathogens plays a major role during disease progression, the pathophysiology of the microbial community in CF lungs remains poorly understood. Particular challenges in the analysis of the microbial population present in CF sputum is (I) the inhomogeneous, viscous, and slimy consistence of CF sputum, and (II) the high number of human proteins masking comparably low abundant microbial proteins. To address these challenges, we used 21 CF sputum samples to develop a reliable, reproducible and widely applicable protocol for sputum processing, microbial enrichment, cell disruption, protein extraction and subsequent metaproteomic analyses. As a proof of concept, we selected three sputum samples for detailed metaproteome analyses and complemented and validated metaproteome data by 16S sequencing, metabolomic as well as microscopic analyses. Applying our protocol, the number of bacterial proteins/protein groups increased from 199-425 to 392-868 in enriched samples compared to nonenriched controls. These early microbial metaproteome data suggest that the arginine deiminase pathway and multiple proteases and peptidases identified from various bacterial genera could so far be underappreciated in their contribution to the CF pathophysiology. By providing a standardized and effective protocol for sputum processing and microbial enrichment, our study represents an important basis for future studies investigating the physiology of microbial pathogens in CF in vivo – an important prerequisite for the development of novel antimicrobial therapies to combat chronic recurrent airway infection in CF.

A multi-omics study delineates new molecular features and therapeutic targets for esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a major histological subtype of esophageal cancer with inferior prognosis. Here, we conducted comprehensive transcriptomic, proteomic, phosphoproteomic, and metabolomic characterization of human, treatment-naive ESCC and paired normal adjacent tissues (cohort 1, n = 24) in an effort to identify new molecular vulnerabilities for ESCC and potential therapeutic targets. Integrative analysis revealed a small group of genes that were related to the active posttranscriptional and posttranslational regulation of ESCC. By using proteomic, phosphoproteomic, and metabolomic data, networks of ESCC-related signaling and metabolic pathways that were closely linked to cancer etiology were unraveled. Notably, integrative analysis of proteomic and phosphoproteomic data pinpointed that certain pathways involved in RNA transcription, processing, and metabolism were stimulated in ESCC. Importantly, proteins with close linkage to ESCC prognosis were identified. By enrolling an ESCC patient cohort 2 (n = 41), three top-ranked prognostic proteins X-prolyl aminopeptidase 3 (XPNPEP3), bromodomain PHD finger transcription factor (BPTF), and fibrillarin (FBL) were verified to have increased expression in ESCC. Among these prognostic proteins, only FBL, a well-known nucleolar methyltransferase, was essential for ESCC cell growth in vitro and in vivo. Furthermore, a validation study using an ESCC patient cohort 3 (n = 100) demonstrated that high FBL expression predicted unfavorable patient survival. Finally, common cancer/testis antigens and established cancer drivers and kinases, all of which could direct therapeutic decisions, were characterized. Collectively, our multi-omics analyses delineated new molecular features associated with ESCC pathobiology involving epigenetic, posttranscriptional, posttranslational, and metabolic characteristics, and unveiled new molecular vulnerabilities with therapeutic potential for ESCC.

Genetic merit for fertility alters the bovine uterine luminal fluid proteome†

Over the last decades, fertility of dairy cows has declined due to selection strategies focusing on milk yield. To study the effect of genetic merit for fertility on the proteome of the bovine uterine luminal fluid, Holstein heifers with low- and two groups of heifers with high-fertility index (high-fertility Holstein and Montbéliarde) were investigated. To focus on the maternal effect, heifers from all groups were synchronized and received on Day 7 high-quality embryos. Uterine luminal fluid from Day 19 pregnant heifers was analyzed in a holistic proteomic approach using nano-LC-MS/MS analysis combined with a label-free quantification approach. In total, 1737 proteins were identified, of which 597 differed significantly in abundance between the three groups. The vast majority of proteome differences was found comparing both high-fertility groups to the low-fertility Holstein group, showing that the genetic predisposition for fertility is prevalent regarding the uterine luminal fluid proteome. Evaluation of this dataset using bioinformatic tools revealed an assignment of higher abundant proteins in low-fertility Holstein to several metabolic processes, such as vitamin metabolic process, which comprises folate receptor alpha (FOLR1) and retinol-binding protein, indicating an involvement of disturbed metabolic processes in decreased fertility. Moreover, immune system-related proteins - lactotransferrin and chromogranin A - were enriched in low-fertility cows together with interferon tau 3 h and interferon tau-2. Our results indicate that the genetic merit for fertility leads to substantial quantitative differences at the level of proteins in uterine fluid of pregnant animals, thus altering the microenvironment for the early conceptus.

Biomaterial vaccines capturing pathogen-associated molecular patterns protect against bacterial infections and septic shock

Most bacterial vaccines work for a subset of bacterial strains or require the modification of the antigen or isolation of the pathogen before vaccine development. Here we report injectable biomaterial vaccines that trigger potent humoral and T-cell responses to bacterial antigens by recruiting, reprogramming and releasing dendritic cells. The vaccines are assembled from regulatorily approved products and consist of a scaffold with absorbed granulocyte-macrophage colony-stimulating factor and CpG-rich oligonucleotides incorporating superparamagnetic microbeads coated with the broad-spectrum opsonin Fc-mannose-binding lectin for the magnetic capture of pathogen-associated molecular patterns from inactivated bacterial-cell-wall lysates. The vaccines protect mice against skin infection with methicillin-resistant Staphylococcus aureus, mice and pigs against septic shock from a lethal Escherichia coli challenge and, when loaded with pathogen-associated molecular patterns isolated from infected animals, uninfected animals against a challenge with different E. coli serotypes. The strong immunogenicity and low incidence of adverse events, a modular manufacturing process, and the use of components compatible with current good manufacturing practice could make this vaccine technology suitable for responding to bacterial pandemics and biothreats.

Genome-scale metabolic modeling reveals key features of a minimal gene set

Mesoplasma florum, a fast-growing near-minimal organism, is a compelling model to explore rational genome designs. Using sequence and structural homology, the set of metabolic functions its genome encodes was identified, allowing the reconstruction of a metabolic network representing ˜ 30% of its protein-coding genes. Growth medium simplification enabled substrate uptake and product secretion rate quantification which, along with experimental biomass composition, were integrated as species-specific constraints to produce the functional iJL208 genome-scale model (GEM) of metabolism. Genome-wide expression and essentiality datasets as well as growth data on various carbohydrates were used to validate and refine iJL208. Discrepancies between model predictions and observations were mechanistically explained using protein structures and network analysis. iJL208 was also used to propose an in silico reduced genome. Comparing this prediction to the minimal cell JCVI-syn3.0 and its parent JCVI-syn1.0 revealed key features of a minimal gene set. iJL208 is a stepping-stone toward model-driven whole-genome engineering.

Endothelial extracellular vesicles contain protective proteins and rescue ischemia-reperfusion injury in a human heart-on-chip

Extracellular vesicles (EVs) derived from various stem cell sources induce cardioprotective effects during ischemia-reperfusion injury (IRI). These have been attributed mainly to the antiapoptotic, proangiogenic, microRNA (miRNA) cargo within the stem cell-derived EVs. However, the mechanisms of EV-mediated endothelial signaling to cardiomyocytes, as well as their therapeutic potential toward ischemic myocardial injury, are not clear. EV content beyond miRNA that may contribute to cardioprotection has not been fully illuminated. This study characterized the protein cargo of human vascular endothelial EVs (EEVs) to identify lead cardioactive proteins and assessed the effect of EEVs on human laminar cardiac tissues (hlCTs) exposed to IRI. We mapped the protein content of human vascular EEVs and identified proteins that were previously associated with cellular metabolism, redox state, and calcium handling, among other processes. Analysis of the protein landscape of human cardiomyocytes revealed corresponding modifications induced by EEV treatment. To assess their human-specific cardioprotection in vitro, we developed a human heart-on-a-chip IRI assay using human stem cell-derived, engineered cardiac tissues. We found that EEVs alleviated cardiac cell death as well as the loss in contractile capacity during and after simulated IRI in an uptake- and dose-dependent manner. Moreover, we found that EEVs increased the respiratory capacity of normoxic cardiomyocytes. These results suggest that vascular EEVs rescue hlCTs exposed to IRI possibly by supplementing injured myocytes with cargo that supports multiple metabolic and salvage pathways and therefore may serve as a multitargeted therapy for IRI.

Exploration of the Key Proteins in the Normal-Adenoma-Carcinoma Sequence of Colorectal Cancer Evolution Using In-Depth Quantitative Proteomics

Purpose

In most cases, the carcinogenesis of colorectal cancer (CRC) follows the normal-adenoma-carcinoma (N-A-C) sequence. In this study, we aimed to identify the key proteins in the N-A-C sequence.

Methods

Differentially expressed proteins (DEPs) in normal, adenoma, and carcinoma tissues were identified using the Tandem Mass Tag- (TMT-) based quantitative proteomics approach. The landscape of proteomic variation in the N-A-C sequence was explored using gene set enrichment analysis (GSEA) and Proteomaps. Key proteins in the N-A-C sequence were identified, verified, and validated based on our proteomic data, external proteomic data, and external transcriptomic data in the ProteomeXchange, CPTAC, GEO, and TCGA databases. The prognostic value of the key proteins in our database was evaluated by univariate and multivariate Cox regression analysis. The effects of the key proteins on adenoma organoids and colorectal cancer cells were explored in functional studies.

Results

Based on our proteomic profiles, we identified 1,294 DEPs between the carcinoma (CG) and normal (NG) groups, 919 DEPs between the adenoma group (AG) and NG, and 1,030 DEPs between the CG and AG. Ribosome- and spliceosome-related pathways were mainly enriched in the N-A process. Extracellular matrix- and epithelial-mesenchymal transition- (EMT-) related pathways were mainly enriched in the A-C process. RRP12 and SERPINH1 were identified, verified, and validated as candidate key proteins in the N-A and A-C processes, respectively. Furthermore, RRP12 and SERPINH1 knockdown impeded the viability and proliferation of adenoma organoids. SERPINH1 was validated as a risk factor for disease-free survival (DFS) based on the TCGA and our database, whereas RRP12 did not show prognostic value. SERPINH1 knockdown was accompanied by EMT-related protein variation, increased apoptosis, and reduced proliferation, invasion, and migration of CRC cells in vitro.

Conclusions

RRP12 and SERPINH1 may play an important role in the N-A and A-C processes, respectively. Furthermore, SERPINH1 showed favorable prognostic value for DFS in CRC patients. We speculate that SERPINH1 might promote not only the A-C process but also the development of CRC.