Metabolomic Profiling of the Immune Stimulatory Effect of Eicosenoids on PMA-Differentiated THP-1 Cells

In Silico-Guided Discovery of Polysaccharide Derivatives as Adjuvants in Nanoparticle Vaccines for Cancer Immunotherapy

Cancer vaccines utilizing nanoparticle (NP) structures that integrate antigens and adjuvants to enhance delivery and stimulate immune responses are emerging as a promising avenue in cancer immunotherapy. However, the development of cancer vaccines has been significantly hindered by the low immunogenicity of tumor antigens. To address this challenge, substantial efforts have been made in developing innovative adjuvants to elicit effective immune responses. In this study, we develop a NP cancer vaccine assisted by a polysaccharide derivative adjuvant, designed through a computational strategy, to evoke effective antigen-specific antitumor immunity. Using TLR4 as the putative receptor, we conducted a comprehensive evaluation of a prescreening library consisting of 34 inulin derivatives through docking and molecular dynamics simulation. Consequently, a new derivative, benzoylated inulin (InBz), is selected as the most promising TLR4 agonist. The adjuvant effect of InBz is evaluated by fabricating InBz NPs encapsulating the model antigen ovalbumin (OVA). In vitro, InBz-OVA NPs effectively activate the TLR4 signaling pathways and facilitate dendritic cell maturation, thereby enhancing the antigen delivery and presentation. In vivo, InBz-OVA NPs outperform a commercial aluminum-based adjuvant, elicit robust antibody titers, induce antigen-specific cytotoxic T lymphocytes, and achieve significant tumor suppression in murine models. Besides, the adjuvant effects of other representative derivatives, namely, acetylated and chloroacetylated inulin, with moderate and low potential from the library, are also chemically synthesized and experimentally evaluated and found to be in agreement with computational predictions, confirming the credibility of the strategy. This study provides an effective platform for the pursuit of efficient polysaccharide-based vaccine adjuvants.

Multi-omics analysis identifies potential microbial and metabolite diagnostic biomarkers of bacterial vaginosis

BACKGROUND

Bacterial vaginosis (BV) is a common clinical manifestation of a perturbed vaginal ecology associated with adverse sexual and reproductive health outcomes if left untreated. The existing diagnostic modalities are either cumbersome or require skilled expertise, warranting alternate tests. Application of machine-learning tools to heterogeneous and high-dimensional multi-omics datasets finds promising potential in data integration and may aid biomarker discovery.

OBJECTIVES

The present study aimed to evaluate the potential of the microbiome and metabolome-derived biomarkers in BV diagnosis. Interpretable machine-learning algorithms were used to evaluate the utility of an integrated-omics-derived classification model.

METHODS

Vaginal samples obtained from reproductive-age group women with (n = 40) and without BV (n = 40) were subjected to 16S rRNA amplicon sequencing and LC-MS-based metabolomics. The vaginal microbiome and metabolome were characterized, and machine-learning analysis was performed to build a classification model using biomarkers with the highest diagnostic accuracy.

RESULTS

Microbiome-based diagnostic model exhibited a ROC-AUC (10-fold CV) of 0.84 ± 0.21 and accuracy of 0.79 ± 0.18, and important features were Aerococcus spp., Mycoplasma hominis, Sneathia spp., Lactobacillus spp., Prevotella spp., Gardnerella spp. and Fannyhessea vaginae. The metabolome-derived model displayed superior performance with a ROC-AUC of 0.97 ± 0.07 and an accuracy of 0.92 ± 0.08. Beta-leucine, methylimidazole acetaldehyde, dimethylethanolamine, L-arginine and beta cortol were among key predictive metabolites for BV. A predictive model combining both microbial and metabolite features exhibited a high ROC-AUC of 0.97 ± 0.07 and accuracy of 0.94 ± 0.08 with diagnostic performance only slightly superior to the metabolite-based model.

CONCLUSION

Application of machine-learning tools to multi-omics datasets aid biomarker discovery with high predictive performance. Metabolome-derived classification models were observed to have superior diagnostic performance in predicting BV than microbiome-based biomarkers.

Therapeutic Use of Omega-3 Fatty Acids for Immune Disorders In Search of the Ideal Omega-3 Supplement

There has been continuing growth in the understanding of the role that omega-3 fatty acid supplements play in the support of immune function. The progress in both the basic science and clinical research surrounding the impact of various formulations of omega-3 fatty acid supplements on immune function has resulted in the recognition that the impact of these supplements is beyond that of the omega-3 fatty acids eicosapentaenoic acid (EPA) and docasahexaenoic acid (DHA) alone, and includes other fatty acids containing omega-3 derivatives termed pro-resolving mediators, along with vitamins A and D found naturally in some marine oils. The research on omega-3 oil supplements has also highlighted the importance that the supplement formulation be derived from a certified sustainable source, free of heavy metals and organic pollutants, minimally processed, and composed of the natural triglyceride form of the fatty acids for improved safety and effectiveness in providing immune support.

Pharmacological effects and mechanisms of bee venom and its main components: Recent progress and perspective

Bee venom (BV), a type of defensive venom, has been confirmed to have favorable activities, such as anti-tumor, neuroprotective, anti-inflammatory, analgesic, anti-infectivity effects, etc. This study reviewed the recent progress on the pharmacological effects and mechanisms of BV and its main components against cancer, neurological disorders, inflammatory diseases, pain, microbial diseases, liver, kidney, lung and muscle injury, and other diseases in literature during the years 2018-2021. The related target proteins of BV and its main components against the diseases include Akt, mTOR, JNK, Wnt-5α, HIF-1α, NF-κB, JAK2, Nrf2, BDNF, Smad2/3, AMPK, and so on, which are referring to PI3K/Akt/mTOR, MAPK, Wnt/β-catenin, HIF-1α, NF-κB, JAK/STAT, Nrf2/HO-1, TrkB/CREB/BDNF, TGF-β/Smad2/3, and AMPK signaling pathways, etc. Further, with the reported targets, the potential effects and mechanisms on diseases were bioinformatically predicted via Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, disease ontology semantic and enrichment (DOSE) and protein-protein interaction (PPI) analyses. This review provides new insights into the therapeutic effects and mechanisms of BV and its main components on diseases.

Lack of Nck1 protein and Nck-CD3 interaction caused the increment of lipid content in Jurkat T cells

BACKGROUND

The non-catalytic region of tyrosine kinase (Nck) is an adaptor protein, which is ubiquitously expressed in many types of cells. In T cells, the Nck1 isoform promotes T cell receptor signalling as well as actin polymerisation. However, the role of Nck1 in the lipid metabolism in T cells is unknown. In the present study, we investigated the effect of the Nck1 protein and Nck-CD3 interaction on lipid metabolism and on the physical and biological properties of Jurkat T cells, using a newly developed holotomographic microscope.

RESULTS

Holotomographic microscopy showed that Nck1-knocked-out cells had membrane blebs and were irregular in shape compared to the rounded control cells. The cell size and volume of Nck1-deficient cells were comparable to those of the control cells. Nck1-knocked-out Jurkat T cells had a greater lipid content, lipid mass/cell mass ratio, and lipid metabolite levels than the control cells. Interestingly, treatment with a small molecule, AX-024, which inhibited Nck-CD3 interaction, also caused an increase in the lipid content in wild-type Jurkat T cells, as found in Nck1-deficient cells.

CONCLUSIONS

Knockout of Nck1 protein and hindrance of the Nck-CD3 interaction cause the elevation of lipid content in Jurkat T cells.

Toxicological and bioactivity evaluation of blackcurrant press cake, sea buckthorn leaves and bark from Scots pine and Norway spruce extracts under a green integrated approach

Aqueous extracts from blackcurrant press cake (BC), Norway spruce bark (NS), Scots pine bark (SP), and sea buckthorn leaves (SB) were obtained using maceration and pressurized hot water and tested for their bioactivities. Maceration provided the extraction of higher dry matter contents, including total phenolics (TPC), anthocyanins, and condensed tannins, which also impacted higher antioxidant activity. NS and SB extracts presented the highest mean values of TPC and antioxidant activity. Individually, NS extract presented high contents of proanthocyanidins, resveratrol, and some phenolic acids. In contrast, SB contained a high concentration of ellagitannins, ellagic acid, and quercetin, explaining the antioxidant activity and antibacterial effects. SP and BC extracts had the lowest TPC and antioxidant activity. However, BC had strong antiviral efficacy, whereas SP can be considered a potential ingredient to inhibit α-amylase. Except for BC, the other extracts decreased reactive oxygen species (ROS) generation in HCT8 and A549 cells. Extracts did not inhibit the production of TNF-alpha in lipopolysaccharide-stimulated THP-1 macrophages but inhibited the ROS generation during the THP-1 cell respiratory burst. The recovery of antioxidant compounds from these by-products is incentivized for high value-added applications.

M. tuberculosis curli pili (MTP) is associated with alterations in carbon, fatty acid and amino acid metabolism in a THP-1 macrophage infection model

The initial host-pathogen interaction is crucial for the establishment of infection. An improved understanding of the pathophysiology of Mycobacterium tuberculosis (M. tuberculosis) during macrophage infection can aid the development of intervention therapeutics against tuberculosis. M. tuberculosis curli pili (MTP) is a surface located adhesin, involved in the first point-of-contact between pathogen and host. This study aimed to better understand the role of MTP in modulating the intertwined metabolic pathways of M. tuberculosis and its THP-1 macrophage host. Metabolites were extracted from pelleted wet cell mass of THP-1 macrophages infected with M. tuberculosis wild-type V9124 (WT), Δmtp-deletion mutant and the mtp-complemented strains, respectively, via a whole metabolome extraction method using a 1:3:1 ratio of chloroform:methanol:water. Metabolites were detected by two-dimensional gas chromatography time-of-flight mass spectrometry. Significant metabolites were determined through univariate and multivariate statistical tests and online pathway databases. Relative to the WT, a total of nine and ten metabolites were significantly different in the Δmtp and complement strains, respectively. All nine significant metabolites were found in elevated levels in the Δmtp relative to the WT. Additionally, of the ten significant metabolites, eight were detected in lower levels and two were detected in higher levels in the complement relative to the WT. The absence of the MTP adhesin resulted in reduced virulence of M. tuberculosis leading to alterations in metabolites involved in carbon, fatty acid and amino acid metabolism during macrophage infection, suggesting that MTP plays an important role in the modulation of host metabolic activity. These findings support the prominent role of the MTP adhesin as a virulence factor as well as a promising biomarker for possible diagnostic and therapeutic intervention.

Systematic Review of Multi-Omics Approaches to Investigate Toxicological Effects in Macrophages

Insights into the modes of action (MoAs) of xenobiotics are of utmost importance for the definition of adverse outcome pathways (AOPs), which are essential for a mechanism-based risk assessment. A well-established strategy to reveal MoAs of xenobiotics is the use of omics. However, often an even more comprehensive approach is needed, which can be achieved using multi-omics. Since the immune system plays a central role in the defense against foreign substances and pathogens, with the innate immune system building a first barrier, we systematically reviewed multi-omics studies investigating the effects of xenobiotics on macrophages. Surprisingly, only nine publications were identified, combining proteomics with transcriptomics or metabolomics. We summarized pathways and single proteins, transcripts, or metabolites, which were described to be affected upon treatment with xenobiotics in the reviewed studies, thus revealing a broad range of effects. In summary, we show that macrophages are a relevant model system to investigate the toxicological effects induced by xenobiotics. Furthermore, the multi-omics approaches led to a more comprehensive overview compared to only one omics layer with slight advantages for combinations that complement each other directly, e.g., proteome and metabolome.