EBioMedicine最新文献

Background: Quantitating the contribution of phenotype-responsible elements in hypervirulent Klebsiella pneumoniae is needed.

Methods: Isogenic mutants of four hypervirulent clinical isolates that produced K1 (ST23), K2 (ST86), K20 (ST1544), or K54 (ST29) capsules (mean 2.2 log₁₀ LD₅₀ (range 1.5-2.9)) were created to measure the effects on LD₅₀ in a murine model of the hypervirulence-associated plasmid (pVir), iucA, _prmpA, _prmpA2 (truncated), irp2, and clbBC.

Findings: Curing pVir had the greatest increase in survival (mean LD₅₀ to 7.6 (range 7.0-9.0, p ≤ 0.0001), a dosage comparable to classical K. pneumoniae. Results also showed increased mean LD₅₀s for Δ_prmpA (5.9, p ≤ 0.0001), ΔiucA (3.6, p ≤ 0.0001), Δirp2 (3.4), ΔrmpAΔiucA (6.3, p ≤ 0.0001), and ΔpVirΔirp2 (8.7, p ≤ 0.0001). Notably ΔpVir had an additional mean LD₅₀ increase of 1.3 compared to the pVir-encoded Δ_prmpAΔiucA (p ≤ 0.01), suggesting presence of additional pVir-virulence genes. Truncated _pRmpA2 did not contribute to virulence. Odd ratios in the absence of pVir/yersiniabactin, pVir, _pRmpA/aerobactin, _pRmpA, aerobactin, yersiniabactin, and colibactin demonstrated a 250-fold, 67-fold, 20-fold, 16.7-fold, 9.6-fold, and 1.7-fold decrease in lethality respectively.

Interpretation: These data can guide countermeasure development.

Funding: This work was supported by NIH R21 AI123558-01 and 1R21AI141826-01A1 (Dr. Russo) and the Department of Veterans Affairs VA Merit Review (I01 BX004677-01) (Dr. Russo). This study was also partially funded by the U.S. Defense Health Program (DHP) Operations and Maintenance.

Background: MTBVAC is a live attenuated tuberculosis vaccine, currently undergoing phase III evaluation for tuberculosis prevention. In previous preclinical studies, we found that local pulmonary administration of MTBVAC via the intranasal route had a strong therapeutic effect against asthma. This effect correlated with the abrogation of allergen-specific Th2 response in the lungs.

Methods: Using different mouse models of asthma, we investigated the effect of MTBVAC administered by intravenous (IV) route and its potential as immunotherapeutic agent to induce desensitisation of allergen-specific responses at a systemic level. We explored the effects of this process in the efficacy against airway hyperresponsiveness (AHR) induced by exposure to different allergens.

Findings: IV MTBVAC was highly efficient at reducing AHR induced by different allergens. Additionally, IV MTBVAC was found to be well-tolerated, being progressively eliminated from the different organs analysed. From a mechanistic standpoint, we observed that MTBVAC intravenous, but not intranasal, impaired allergen-specific Th2 response in both lungs and spleen. This reduction at a systemic level correlated with long-term therapeutic protection against allergen exposure. Our results also revealed differential immunological mechanisms governing systemic and local pulmonary allergen desensitisation processes. Notably, in a cohort of patients with asthma sensitive to house dust mite (HDM), in vitro incubation of peripheral blood mononuclear cells (PBMCs) with MTBVAC prevented allergen-specific production of Th2 cytokines IL-4 and IL-5.

Interpretation: Altogether, our results suggest that intravenous MTBVAC could be a plausible allergen desensitising approach for treatment of asthma, and could provide long-term protection against allergen exposure.

Funding: MCIN/AEI/10.13039/501100011033 [grants number RTI2018-097625-B-I00 and PID2022-138624OB-I00]; Consorcio Centro de Investigación Biomédica en Red- (Groups CB06/06/0020 and CB06/06/0013), Instituto de Salud Carlos III.

Background: Breast cancer cells suppress the host immune system to efficiently invade the lymph nodes; however, the underlying mechanism remains incompletely understood. Here, we aimed to comprehensively characterise the effects of breast cancers on immune cells in the lymph nodes.

Methods: We collected non-metastatic and metastatic lymph node samples from 6 patients with breast cancer with lymph node metastasis. We performed bulk transcriptomics, spatial transcriptomics, and imaging mass cytometry to analyse the obtained lymph nodes. Furthermore, we conducted histological analyses against a larger patient cohort (474 slices from 58 patients).

Findings: The comparison between paired lymph nodes with and without metastasis from the same patients demonstrated that the number of CD169⁺ lymph node sinus macrophages, an initiator of anti-cancer immunity, was reduced in metastatic lymph nodes (36.7 ± 21.1 vs 7.3 ± 7.0 cells/mm², p = 0.0087), whereas the numbers of other major immune cell types were unaltered. We also detected that the infiltration of CD169⁺ macrophages into metastasised cancer tissues differed by section location within tumours, suggesting that CD169⁺ macrophages were gradually decreased after anti-cancer reactions. Furthermore, CD169⁺ macrophage elimination was prevalent in major breast cancer subtypes and correlated with breast cancer staging (p = 0.022).

Interpretation: We concluded that lymph nodes with breast cancer metastases have fewer CD169⁺ macrophages, which may be detrimental to the activity of anti-cancer immunity.

Funding: JSPS KAKENHI (16H06279, 20H03451, 20H04842, 22H04925, 19K16770, and 21K15530, 24K02236), JSPS Fellows (JP22KJ1822), AMED (JP21ck0106698), JST FOREST (JPMJFR2062), Caravel, Co., Ltd, Japan Foundation for Applied Enzymology, and Sumitomo Pharma Co., Ltd. under SKIPS.

Background: Irritable bowel syndrome (IBS) is a common and debilitating disorder manifesting with abdominal pain and bowel dysfunction. A mainstay of treatment is dietary modification, including restriction of FODMAPs (fermentable oligosaccharides, disaccharides, monosaccharides and polyols). A greater response to a low FODMAP diet has been reported in those with a distinct IBS microbiome termed IBS-P. We investigated whether this is linked to specific changes in the metabolome in IBS-P.

Methods: Solid phase microextraction gas chromatography-mass spectrometry was used to examine the faecal headspace of 56 IBS cases (each paired with a non-IBS household control) at baseline, and after four-weeks of a low FODMAP diet (39 pairs). 50% cases had the IBS-P microbial subtype, while the others had a microbiome that more resembled healthy controls (termed IBS-H). Clinical response to restriction of FODMAPs was measured with the IBS-symptom severity scale, from which a pain sub score was calculated.

Findings: Two distinct metabotypes were identified and mapped onto the microbial subtypes. IBS-P was characterised by a fermentative metabolic profile rich in short chain fatty acids (SCFAs). After FODMAP restriction significant reductions in SCFAs were observed in IBS-P. SCFA levels did not change significantly in the IBS-H group. The magnitude of pain and overall symptom improvement were significantly greater in IBS-P compared to IBS-H (p = 0.016 and p = 0.026, respectively). Using just five metabolites, a biomarker model could predict microbial subtype with accuracy (AUROC 0.797, sensitivity 78.6% (95% CI: 0.78-0.94), specificity 71.4% (95% CI: 0.55-0.88).

Interpretation: A metabotype high in SCFAs can be manipulated by restricting fermentable carbohydrate, and is associated with an enhanced clinical response to this dietary restriction. This implies that SCFAs harbour pro-nociceptive potential when produced in a specific IBS niche. By ascertaining metabotype, microbial subtype can be predicted with accuracy. This could allow targeted FODMAP restriction in those seemingly primed to respond best.

Funding: This research was co-funded by Addenbrooke's Charitable Trust, Cambridge University Hospitals and the Wellcome Sanger Institute, and supported by the NIHR Cambridge Biomedical Research Centre (BRC-1215-20014).

Background: Genome-wide association studies (GWAS) have revealed many brain disorder-associated SNPs residing in the noncoding genome, rendering it a challenge to decipher the underlying pathogenic mechanisms.

Methods: Here, we present an unsupervised Bayesian framework to identify disease-associated genes by integrating risk SNPs with long-range chromatin interactions (iGOAT), including SNP-SNP interactions extracted from ∼500,000 patients and controls from the UK Biobank, and enhancer-promoter interactions derived from multiple brain cell types at different developmental stages.

Findings: The application of iGOAT to three psychiatric disorders and three neurodegenerative/neurological diseases predicted sets of high-risk (HRGs) and low-risk (LRGs) genes for each disorder. The HRGs were enriched in drug targets, and exhibited higher expression during prenatal brain developmental stages than postnatal stages, indicating their potential to affect brain development at an early stage. The HRGs associated with Alzheimer's disease were found to share genetic architecture with schizophrenia, bipolar disorder and major depressive disorder according to gene co-expression module analysis and rare variants analysis. Comparisons of this method to the eQTL-based method, the TWAS-based method, and the gene-level GWAS method indicated that the genes identified by our method are more enriched in known brain disorder-related genes, and exhibited higher precision. Finally, the method predicted 205 risk genes not previously reported to be associated with any brain disorder, of which one top-risk gene, MLH1, was experimentally validated as being schizophrenia-associated.

Interpretation: iGOAT can successfully leverage epigenomic data, phenotype-genotype associations, and protein-protein interactions to advance our understanding of brain disorders, thereby facilitating the development of new therapeutic approaches.

Funding: The work was funded by the National Key Research and Development Program of China (2024YFF1204902), the Natural Science Foundation of China (82371482), Guangzhou Science and Technology Research Plan (2023A03J0659) and Natural Science Foundation of Guangdong (2024A1515011363).

Background: Multiplexed immunofluorescence (mIF) staining, such as CODEX and MIBI, holds significant clinical value for various fields, such as disease diagnosis, biological research, and drug development. However, these techniques are often hindered by high time and cost requirements.

Methods: Here we present a Multimodal-Attention-based virtual mIF Staining (MAS) system that utilises a deep learning model to extract potential antibody-related features from dual-modal non-antibody-stained fluorescence imaging, specifically autofluorescence (AF) and DAPI imaging. The MAS system simultaneously generates predictions of mIF with multiple survival-associated biomarkers in gastric cancer using self- and multi-attention learning mechanisms.

Findings: Experimental results with 180 pathological slides from 94 patients with gastric cancer demonstrate the efficiency and consistent performance of the MAS system in both cancer and noncancer gastric tissues. Furthermore, we showcase the prognostic accuracy of the virtual mIF images of seven gastric cancer related biomarkers, including CD3, CD20, FOXP3, PD1, CD8, CD163, and PD-L1, which is comparable to those obtained from the standard mIF staining.

Interpretation: The MAS system rapidly generates reliable multiplexed staining, greatly reducing the cost of mIF and improving clinical workflow.

Funding: Stanford 2022 HAI Seed Grant; National Institutes of Health 1R01CA256890.

Background: ¹H-NMR metabolomics and DNA methylation in blood are widely known biomarkers predicting age-related physiological decline and mortality yet exert mutually independent mortality and frailty signals.

Methods: Leveraging multi-omics data in four Dutch population studies (N = 5238, ∼40% of which male) we investigated whether the mortality signal captured by ¹H-NMR metabolomics could guide the construction of DNA methylation-based mortality predictors.

Findings: We trained DNA methylation-based surrogates for 64 metabolomic analytes and found that analytes marking inflammation, fluid balance, or HDL/VLDL metabolism could be accurately reconstructed using DNA-methylation assays. Interestingly, a previously reported multi-analyte score indicating mortality risk (MetaboHealth) could also be accurately reconstructed. Sixteen of our derived surrogates, including the MetaboHealth surrogate, showed significant associations with mortality, independent of relevant covariates.

Interpretation: The addition of our metabolic analyte-derived surrogates to the well-established epigenetic clock GrimAge demonstrates that our surrogates potentially represent valuable mortality signal.

Funding: BBMRI-NL, X-omics, VOILA, Medical Delta, NWO, ERC.

Background: Osteoarthritis is a leading cause of disability, and disease-modifying osteoarthritis drugs (DMOADs) could represent a pivotal advancement in treatment. Identifying the potential of antidiabetic medications as DMOADs could impact patient care significantly.

Methods: We designed a comprehensive analysis pipeline involving two-sample Mendelian Randomization (MR) (genetic proxies for antidiabetic drug targets), summary-based MR (SMR) (for mRNA), and colocalisation (for drug-target genes) to assess their causal relationship with 12 osteoarthritis phenotypes. Summary statistics from the largest genome-wide association meta-analysis (GWAS) of osteoarthritis and gene expression data from the eQTLGen consortium were utilised.

Findings: Seven out of eight major types of clinical antidiabetic medications were identified, resulting in fourteen potential drug targets. Sulfonylurea targets ABCC8/KCNJ11 were associated with increased osteoarthritis risk at any site (odds ratio (OR): 2.07, 95% confidence interval (CI): 1.50-2.84, P < 3 × 10^-4), while PPARG, influenced by thiazolidinediones (TZDs), was associated with decreased risk of hand (OR: 0.61, 95% CI: 0.48-0.76, P < 3 × 10^-4), finger (OR: 0.50, 95% CI: 0.35-0.73, P < 3 × 10^-4), and thumb (OR: 0.49, 95% CI: 0.34-0.71, P < 3 × 10^-4) osteoarthritis. Metformin and GLP1-RA, targeting GPD1 and GLP1R respectively, were associated with reduced risk of knee and finger osteoarthritis. In the SMR analyses, gene expression of KCNJ11, GANAB, ABCA1, and GSTP1, targeted by antidiabetic drugs, was significantly linked to at least one osteoarthritis phenotype and was replicated across at least two gene expression datasets. Additionally, increased KCNJ11 expression was related to decreased osteoarthritis risk and co-localised with at least one osteoarthritis phenotype.

Interpretation: Our findings suggest a potential therapeutic role for antidiabetic drugs in treating osteoarthritis. The results indicate that certain antidiabetic drug targets may modify disease progression, with implications for developing targeted DMOADs.

Funding: This study was funded by the Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant (2022), the Shanghai Municipal Health Commission Health Industry Clinical Research Project (Grant No. 20224Y0139), Beijing Natural Science Foundation (Grant No. 7244458), and the Postdoctoral Fellowship Program (Grade C) of China Postdoctoral Science Foundation (Grant No. GZC20230130).