Protease S of entomopathogenic bacterium Photorhabdus laumondii: expression, purification and effect on greater wax moth Galleria mellonella.

BACKGROUND: Protease S (PrtS) from Photorhabdus laumondii belongs to the group of protealysin-like proteases (PLPs), which are understudied factors thought to play a role in the interaction of bacteria with other organisms. Since P. laumondii is an insect pathogen and a nematode symbiont, the analysis of the biological functions of PLPs using the PrtS model provides novel data on diverse types of interactions between bacteria and hosts. METHODS AND RESULTS: Recombinant PrtS was produced in Escherichia coli. Efficient inhibition of PrtS activity by photorin, a recently discovered emfourin-like protein inhibitor from P. laumondii, was demonstrated. The Galleria mellonella was utilized to examine the insect toxicity of PrtS and the impact of PrtS on hemolymph proteins in vitro. The insect toxicity of PrtS is reduced compared to protease homologues from non-pathogenic bacteria and is likely not essential for the infection process. However, using proteomic analysis, potential PrtS targets have been identified in the hemolymph. CONCLUSIONS: The spectrum of identified proteins indicates that the function of PrtS is to modulate the insect immune response. Further studies of PLPs' biological role in the PrtS and P. laumondii model must clarify the details of PrtS interaction with the insect immune system during bacterial infection.

Neutrophils cultured ex vivo from CD34+ stem cells are immature and genetically tractable.

BACKGROUND: Neutrophils are granulocytes with essential antimicrobial effector functions and short lifespans. During infection or sterile inflammation, emergency granulopoiesis leads to release of immature neutrophils from the bone marrow, serving to boost circulating neutrophil counts. Steady state and emergency granulopoiesis are incompletely understood, partly due to a lack of genetically amenable models of neutrophil development. METHODS: We optimised a method for ex vivo production of human neutrophils from CD34+ haematopoietic progenitors. Using flow cytometry, we phenotypically compared cultured neutrophils with native neutrophils from donors experiencing emergency granulopoiesis, and steady state neutrophils from non-challenged donors. We carry out functional and proteomic characterisation of cultured neutrophils and establish genome editing of progenitors. RESULTS: We obtain high yields of ex vivo cultured neutrophils, which phenotypically resemble immature neutrophils released into the circulation during emergency granulopoiesis. Cultured neutrophils have similar rates of ROS production and bacterial killing but altered degranulation, cytokine release and antifungal activity compared to mature neutrophils isolated from peripheral blood. These differences are likely due to incomplete synthesis of granule proteins, as demonstrated by proteomic analysis. CONCLUSION: Ex vivo cultured neutrophils are genetically tractable via genome editing of precursors and provide a powerful model system for investigating the properties and behaviour of immature neutrophils.

Selection of texture-associated biomarkers in chilled and iced grass carp (Ctenopharyngodon idella) fillets via DIA-based proteomics.

Consumers care about the texture of fresh fish flesh, but a rapid quantitative analytical method for this has not been properly established. In this study, texture-associated biomarkers were selected by DIA-based proteomics for possible future application. Results indicated a significant decline in texture and moisture characteristics with extended storage under chilled and iced conditions, and flesh quality was categorized into three intervals. A total of 8 texture-associated biomarkers were identified in the chilled storage group, and 3 distinct ones in the iced storage group. Biomarkers were further refined based on their expression levels. Isobutyryl-CoA dehydrogenase, mitochondrial and [Phosphatase 2A protein]-leucine-carboxy methyltransferase were identified as effective texture-associated biomarkers for chilled fish, and Staphylococcal nuclease domain-containing protein 1 for iced fish. This study provided suitable proteins as indicators of fresh fish flesh texture, which could help establish a rapid and convenient texture testing method in future studies.

Immunoinformatics assisted profiling of West Nile virus proteome to determine immunodominant epitopes for the development of next-generation multi-peptide vaccine.

Emerging infectious diseases represent a significant threat to global health, with West Nile virus (WNV) being a prominent example due to its potential to cause severe neurological disorders alongside mild feverish conditions. Particularly prevalent in the continental United States, WNV has emerged as a global concern, with outbreaks indicating the urgent need for effective prophylactic measures. The current problem is that the absence of a commercial vaccine against WNV highlights a critical gap in preventive strategies against WNV. This study aims to address this gap by proposing a novel, multivalent vaccine designed using immunoinformatics approaches to elicit comprehensive humoral and cellular immune responses against WNV. The objective of the study is to provide a theoretical framework for experimental scientists to formulate of vaccine against WNV and tackle the current problem by generating an immune response inside the host. The research employs reverse vaccinology and subtractive proteomics methodologies to identify NP_041724.2 polyprotein and YP_009164950.1 truncated flavivirus polyprotein NS1 as the prime antigens. The selection process for epitopes focused on B and T-cell reactivity, antigenicity, water solubility, and non-allergenic properties, prioritizing candidates with the potential for broad immunogenicity and safety. The designed vaccine construct integrates these epitopes, connected via GPGPG linkers, and supplemented with an adjuvant with the help of another linker EAAAK, to enhance immunogenicity. Preliminary computational analyses suggest that the proposed vaccine could achieve near-universal coverage, effectively targeting approximately 99.74% of the global population, with perfect coverage in specific regions such as Sweden and Finland. Molecular docking and immune simulation studies further validate the potential efficacy of the vaccine, indicating strong binding affinity with toll-like receptor 3 (TLR-3) and promising immune response profiles, including significant antibody-mediated and cellular responses. These findings present the vaccine construct as a viable candidate for further development and testing. While the theoretical and computational results are promising, advancing from in-silico predictions to a tangible vaccine requires comprehensive laboratory validation. This next step is essential to confirm the vaccine's efficacy and safety in eliciting an immune response against WNV. Through this study, we propose a novel approach to vaccine development against WNV and contribute to the broader field of immunoinformatics, showcasing the potential to accelerate the design of effective vaccines against emerging viral threats. The journey from hypothesis to practical solution embodies the interdisciplinary collaboration essential for modern infectious disease management and prevention strategies.

Plasma proteomics analysis of Chinese HIV-1 infected individuals focusing on the immune and inflammatory factors afford insight into the viral control mechanism.

Background: Long-term non-progressors (LTNPs) with HIV infection can naturally control viral replication for up to a decade without antiretroviral therapy (ART), but the underlying mechanisms of this phenomenon remain elusive. Methods: To investigate the relevant immune and inflammatory factors associated with this natural control mechanism, we collected plasma samples from 16 LTNPs, 14 untreated viral progressors (VPs), 17 successfully ART-treated patients (TPs), and 16 healthy controls (HCs). The OLINK immune response panel and inflammation panel were employed to detect critical proteins, and the plasma neutralizing activity against a global panel of pseudoviruses was assessed using TZM-bl cells. Results: The combination of IL17C, IL18, DDX58, and NF2 contributed to discriminating LTNPs and VPs. IL18 and CCL25 were positively associated with CD4+ T cell counts but negatively correlated with viral load. Furthermore, CXCL9 and CXCL10 emerged as potential supplementary diagnostic markers for assessing the efficacy of antiretroviral therapy (ART). Finally, TNFRSF9 displayed positive correlations with neutralization breadth and Geometry Median Titer (GMT) despite the lack of significant differences between LTNPs and VPs. Conclusion: In summary, this study identified a set of biomarkers in HIV-infected individuals at different disease stages. These markers constitute a potential network for immune balance regulation in HIV infection, which is related to the long-term control of HIV by LTNPs. It provides important clues for further exploring the immune regulatory mechanism of HIV.

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

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

Proteomic analysis of the urothelial cancer landscape.

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

Phenotypical and biochemical characterization of tomato plants treated with triacontanol.

Biostimulants are heterogeneous products designed to support plant development and to improve the yield and quality of crops. Here, we focused on the effects of triacontanol, a promising biostimulant found in cuticle waxes, on tomato growth and productivity. We examined various phenological traits related to vegetative growth, flowering and fruit yield, the metabolic profile of fruits, and the response of triacontanol-treated plants to salt stress. Additionally, a proteomic analysis was conducted to clarify the molecular mechanisms underlying triacontanol action. Triacontanol application induced advanced and increased blooming without affecting plant growth. Biochemical analyses of fruits showed minimal changes in nutritional properties. The treatment also increased the germination rate of seeds by altering hormone homeostasis and reduced salt stress-induced damage. Proteomics analysis of leaves revealed that triacontanol increased the abundance of proteins related to development and abiotic stress, while down-regulating proteins involved in biotic stress resistance. The proteome of the fruits was not significantly affected by triacontanol, confirming that biostimulation did not alter the nutritional properties of fruits. Overall, our findings provide evidence of the effects of triacontanol on growth, development, and stress tolerance, shedding light on its mechanism of action and providing new insights into its potential in agricultural practices.

Direct comparison of mass cytometry and single-cell RNA sequencing of human peripheral blood mononuclear cells.

Single-cell methods offer a high-resolution approach for characterizing cell populations. Many studies rely on single-cell transcriptomics to draw conclusions regarding cell state and behavior, with the underlying assumption that transcriptomic readouts largely parallel their protein counterparts and subsequent activity. However, the relationship between transcriptomic and proteomic measurements is imprecise, and thus datasets that probe the extent of their concordance will be useful to refine such conclusions. Additionally, novel single-cell analysis tools often lack appropriate gold standard datasets for the purposes of assessment. Integrative (combining the two data modalities) and predictive (using one modality to improve results from the other) approaches in particular, would benefit from transcriptomic and proteomic data from the same sample of cells. For these reasons, we performed single-cell RNA sequencing, mass cytometry, and flow cytometry on a split-sample of human peripheral blood mononuclear cells. We directly compare the proportions of specific cell types resolved by each technique, and further describe the extent to which protein and mRNA measurements correlate within distinct cell types.

ProMENDA: an updated resource for proteomic and metabolomic characterization in depression.

Depression is a prevalent mental disorder with a complex biological mechanism. Following the rapid development of systems biology technology, a growing number of studies have applied proteomics and metabolomics to explore the molecular profiles of depression. However, a standardized resource facilitating the identification and annotation of the available knowledge from these scattered studies associated with depression is currently lacking. This study presents ProMENDA, an upgraded resource that provides a platform for manual annotation of candidate proteins and metabolites linked to depression. Following the establishment of the protein dataset and the update of the metabolite dataset, the ProMENDA database was developed as a major extension of its initial release. A multi-faceted annotation scheme was employed to provide comprehensive knowledge of the molecules and studies. A new web interface was also developed to improve the user experience. The ProMENDA database now contains 43,366 molecular entries, comprising 20,847 protein entries and 22,519 metabolite entries, which were manually curated from 1370 human, rat, mouse, and non-human primate studies. This represents a significant increase (more than 7-fold) in molecular entries compared to the initial release. To demonstrate the usage of ProMENDA, a case study identifying consistently reported proteins and metabolites in the brains of animal models of depression was presented. Overall, ProMENDA is a comprehensive resource that offers a panoramic view of proteomic and metabolomic knowledge in depression. ProMENDA is freely available at https://menda.cqmu.edu.cn .

Proteomic analysis of sperm from fertile stallions and subfertile stallions due to impaired acrosomal exocytosis.

Thoroughbred stallions that carry a double-homozygous genotype A/A-A/A for SNPs rs397316122 and rs69101140 in exon 5 of the FKBP6 gene (chr13; EquCab3.0) are uniquely subfertile due to impaired acrosomal exocytosis (IAE). In this study, the sperm proteome in frozen/thawed semen from subfertile Thoroughbred stallions was studied and compared to that of frozen/thawed sperm from fertile Thoroughbred stallions. A total of 2,220 proteins was identified, of which 140 proteins were found to be differentially abundant in sperm from the subfertile stallions compared to that of fertile stallions (83 less and 57 more abundant). Proteins of differential abundance in sperm from the subfertile stallions were mainly overrepresented in the "metabolism" and the "metabolism of lipids" pathways. One of these proteins, arylsulfatase F (ARSF), was studied by immunofluorescence. A lower proportion of sperm displaying ARSF signal at the acrosome region was observed in sperm from subfertile Thoroughbred stallions. In addition, heterologous zona pellucida binding assays revealed that sperm from subfertile Thoroughbred stallions bound at a lower proportion to zonae pellucidae than sperm from fertile Thoroughbred stallions. In conclusion, a group of differential abundance proteins, including some of acrosome origin, were identified in sperm from subfertile stallions with acrosome dysfunction.

Proteomics and metabolic burden analysis to understand the impact of recombinant protein production in E. coli.

The impact of recombinant protein production (RPP) on host cells and the metabolic burden associated with it undermine the efficiency of the production system. This study utilized proteomics to investigate the dynamics of parent and recombinant cells induced at different time points for RPP. The results revealed significant changes in both transcriptional and translational machinery that may have impacted the metabolic burden, growth rate of the culture and the RPP. The timing of protein synthesis induction also played a critical role in the fate of the recombinant protein within the host cell, affecting protein and product yield. The study identified significant differences in the expression of proteins involved in fatty acid and lipid biosynthesis pathways between two E. coli host strains (M15 and DH5⍺), with the E. coli M15 strain demonstrating superior expression characteristics for the recombinant protein. Overall, these findings contribute to the knowledge base for rational strain engineering for optimized recombinant protein production.

Trans-omic profiling uncovers molecular controls of early human cerebral organoid formation.

Defining the molecular networks orchestrating human brain formation is crucial for understanding neurodevelopment and neurological disorders. Challenges in acquiring early brain tissue have incentivized the use of three-dimensional human pluripotent stem cell (hPSC)-derived neural organoids to recapitulate neurodevelopment. To elucidate the molecular programs that drive this highly dynamic process, here, we generate a comprehensive trans-omic map of the phosphoproteome, proteome, and transcriptome of the exit of pluripotency and neural differentiation toward human cerebral organoids (hCOs). These data reveal key phospho-signaling events and their convergence on transcriptional factors to regulate hCO formation. Comparative analysis with developing human and mouse embryos demonstrates the fidelity of our hCOs in modeling embryonic brain development. Finally, we demonstrate that biochemical modulation of AKT signaling can control hCO differentiation. Together, our data provide a comprehensive resource to study molecular controls in human embryonic brain development and provide a guide for the future development of hCO differentiation protocols.

Improving obesity research: Unveiling metabolic pathways through a 3D In vitro model of adipocytes using 3T3-L1 cells.

Obesity, a burgeoning global health crisis, has tripled in prevalence over the past 45 years, necessitating innovative research methodologies. Adipocytes, which are responsible for energy storage, play a central role in obesity. However, most studies in this field rely on animal models or adipocyte monolayer cell cultures, which are limited in their ability to fully mimic the complex physiology of a living organism, or pose challenges in terms of cost, time consumption, and ethical considerations. These limitations prompt a shift towards alternative methodologies. In response, here we show a 3D in vitro model utilizing the 3T3-L1 cell line, aimed at faithfully replicating the metabolic intricacies of adipocytes in vivo. Using a workable cell line (3T3-L1), we produced adipocyte spheroids and differentiated them in presence and absence of TNF-α. Through a meticulous proteomic analysis, we compared the molecular profile of our adipose spheroids with that of adipose tissue from lean and obese C57BL/6J mice. This comparison demonstrated the model's efficacy in studying metabolic conditions, with TNF-α treated spheroids displaying a notable resemblance to obese white adipose tissue. Our findings underscore the model's simplicity, reproducibility, and cost-effectiveness, positioning it as a robust tool for authentically mimicking in vitro metabolic features of real adipose tissue. Notably, our model encapsulates key aspects of obesity, including insulin resistance and an obesity profile. This innovative approach has the potential to significantly impact the discovery of novel therapeutic interventions for metabolic syndrome and obesity. By providing a nuanced understanding of metabolic conditions, our 3D model stands as a transformative contribution to in vitro research, offering a pathway for the development of small molecules and biologics targeting these pervasive health issues in humans.

Increasing protein identifications in bottom-up proteomics of T. castaneum - Exploiting synergies of protein biochemistry and bioinformatics.

Depending on the respective research question, LC-MS/MS based bottom-up proteomics poses challenges from the initial biological sample all the way to data evaluation. The focus of this study was to investigate the influence of sample preparation techniques and data analysis parameters on protein identification in Tribolium castaneum by applying free software proteomics platform Max Quant. Multidimensional protein extraction strategies in combination with electrophoretic or chromatographic off-line protein pre-fractionation were applied to enhance the spectrum of isolated proteins from T. castaneum and reduce the effect of co-elution and ion suppression effects during nano-LC-MS/MS measurements of peptides. For comprehensive data analysis, MaxQuant was used for protein identification and R for data evaluation. A wide range of parameters were evaluated to gain reproducible, reliable, and significant protein identifications. A simple phosphate buffer, pH 8, containing protease and phosphatase inhibitor cocktail and application of gentle extraction conditions were used as a first extraction step for T.castaneum proteins. Furthermore, a two-dimensional extraction procedure in combination with electrophoretic pre-fractionation of extracted proteins and subsequent in-gel digest resulted in almost 100% increase of identified proteins when compared to chromatographic fractionation as well as one-pot-analysis. The additionally identified proteins could be assigned to new molecular functions or cell compartments, emphasizing the positive effect of extended sample preparation in bottom-up proteomics. Besides the number of peptides during post-processing, MaxQuant's Match between Runs exhibited a crucial effect on the number of identified proteins. A maximum relative standard deviation of 2% must be considered for the data analysis. Our work with Tribolium castaneum larvae demonstrates that sometimes - depending on matrix and research question - more complex and time-consuming sample preparation can be advantageous for isolation and identification of additional proteins in bottom-up proteomics.

Prognostic implications of unbiased molecular categorization in kidney disease.

In this commentary, a novel approach to the reclassification of chronic kidney disease is reviewed. In the revisited study, the investigators identify 4 distinct subtypes of kidney disease derived from an unbiased self-organizing map of transcriptomic data from kidney biopsy samples. These molecular subtypes then are characterized by biologic cell processes, clinical and histopathologic features, urinary proteomics, and disease progression. The strengths and limitations of the self-organizing map approach are assessed; the prognostic, diagnostic, and therapeutic implications are considered briefly.

[Multi-omics research progress in early-onset colorectal cancer].

Globally, the incidence of early-onset colorectal cancer (EOCRC) among individuals younger than 50 is escalating. Compared to late-onset colorectal cancer, EOCRC exhibits distinct clinical, pathological, and molecular features, with a higher prevalence in the left colon and rectum. However, the occurrence and development of EOCRC is a multi-factor and multi-stage evolution process, which is the result of the mutual effect of environmental, genetic and biological factors, and involves the multi-level regulation mechanism of other organisms. With the development and improvement of high-throughput sequencing technology, the application of multi-omics analysis has become an important development direction to resolve the pathogenesis of complex diseases and individualized treatment plans. This article aims to review the research progress of EOCRC at the multi-omics level, providing a theoretical foundation for earlier diagnosis and more precise treatment of this diseases.

REMEMProt: a resource of membrane-enriched proteome profiles, their disease associations, and biomarker status.

The differential expression of plasma membrane proteins is integrally analyzed for their diagnosis, prognosis, and therapeutic applications in diverse clinical manifestations. Necessarily, distinct membrane protein enrichment methods and mass spectrometry platforms are employed for their global and relative quantitation. First of its kind to explore, we compiled membrane-associated proteomes in human and mouse systems into a database named, Resource of Experimental Membrane-Enriched Mass spectrometry-derived Proteome (REMEMProt). It currently hosts 14,626 proteins (9,507 proteins in Homo sapiens; 5,119 proteins in Mus musculus) with information on their membrane-protein enrichment methods, experimental/physiological context of detection in cells or tissues, transmembrane domain analysis, and their current attribution as biomarkers. Based on these annotations and the transmembrane domain analysis in proteins or their binary/complex protein-protein interactors, REMEMProt facilitates the assessment of the plasma membrane localization potential of proteins through batch query. A cross-study enrichment analysis platform is enabled in REMEMProt for comparative analysis of proteomes using novel/modified membrane enrichment methods and evaluation of methods for targeted enrichment of membrane proteins. REMEMProt data are made freely accessible to explore and download at https://rememprot.ciods.in/.

Energy flux couples sulfur isotope fractionation to proteomic and metabolite profiles in Desulfovibrio vulgaris.

Microbial sulfate reduction is central to the global carbon cycle and the redox evolution of Earth's surface. Tracking the activity of sulfate reducing microorganisms over space and time relies on a nuanced understanding of stable sulfur isotope fractionation in the context of the biochemical machinery of the metabolism. Here, we link the magnitude of stable sulfur isotopic fractionation to proteomic and metabolite profiles under different cellular energetic regimes. When energy availability is limited, cell-specific sulfate respiration rates and net sulfur isotope fractionation inversely covary. Beyond net S isotope fractionation values, we also quantified shifts in protein expression, abundances and isotopic composition of intracellular S metabolites, and lipid structures and lipid/water H isotope fractionation values. These coupled approaches reveal which protein abundances shift directly as a function of energy flux, those that vary minimally, and those that may vary independent of energy flux and likely do not contribute to shifts in S-isotope fractionation. By coupling the bulk S-isotope observations with quantitative proteomics, we provide novel constraints for metabolic isotope models. Together, these results lay the foundation for more predictive metabolic fractionation models, alongside interpretations of environmental sulfur and sulfate reducer lipid-H isotope data.