Lactobacillus species ameliorate membranous nephropathy through inhibiting the aryl hydrocarbon receptor pathway via tryptophan-produced indole metabolites

BACKGROUND AND PURPOSE

Membranous nephropathy (MN) is an immune-mediated glomerular disease in adults. Antibody- and antigen-bonding mechanisms have been largely clarified, but the subepithelium immune complex deposition-mediated downstream molecular mechanisms are currently unresolved. Increasing evidence has suggested that gut microbiota contribute to MN pathogenesis.

EXPERIMENTAL APPROACH

In this study, we identified alterations in faecal gut microbiota and serum metabolites that mediate an aryl hydrocarbon receptor (AhR) mechanism in cationic bovine serum albumin (CBSA)-induced MN rats and in patients with idiopathic MN (IMN).

KEY RESULTS

Impaired renal function correlated with the relative abundance of reduced faecal probiotics, Lactobacillus and Bifidobacterium, and altered serum levels of tryptophan-produced indole derivatives (TPIDs) in MN rats. Further results showed that reduced relative abundance of five probiotics, namely Lactobacillus johnsonii, Lactobacillus murinus, Lactobacillus vaginalis, Lactobacillus reuteri and Bifidobacterium animalis, positively correlated with decreased levels of indole-3-pyruvic acid, indole-3-aldehyde and tryptamine and negatively correlated with increased levels of indole-3-lactic acid and indole-3-acetic acid in serum of MN rats. Altered five probiotics and five TPIDs also were observed in patients with IMN. Further studies showed that MN rats exhibited a significant increase in intrarenal mRNA expression of AhR and its target genes CYP1A1, CYP1A2 and CYP1B1, which were accompanied by protein expression of down-regulated cytoplasmic AhR, but up-regulated nuclear AhR, in MN rats and IMN patients.

CONCLUSION AND IMPLICATIONS

Activation of the intrarenal AhR signalling pathway may involve five TPIDs. These data suggest that gut microbiota could influence MN through TPIDs that engage host receptors.

A multiple-metabolites model to predict preliminary renal injury induced by iodixanol based on UHPLC/Q-Orbitrap-MS and 1H-NMR

BACKGROUND & AIMS

There are some problems, such as unclear pathological mechanism, delayed diagnosis, and inaccurate therapeutic target of Contrast-induced acute kidney injury (CI-AKI). It is significantly important to find biomarkers and therapeutic targets that can indicate renal injury in the early stage of CI-AKI. This study aims to establish a multiple-metabolites model to predict preliminary renal injury induced by iodixanol and explore its pathogenesis.

METHODS

Both UHPLC/Q-Orbitrap-MS and ¹H-NMR methods were applied for urine metabolomics studies on two independent cohorts who suffered from a preliminary renal injury caused by iodixanol, and the multivariate statistical analysis and random forest (RF) algorithm were used to process the related date.

RESULTS

In the discovery cohort (n = 169), 6 metabolic markers (leucine, indole, 5-hydroxy-L-tryptophan, N-acetylvaline, hydroxyhexanoycarnine, and kynurenic acid) were obtained by the cross-validation between the RF and liquid chromatography-mass spectrometry (LC-MS). Secondly, the 6 differential metabolites were confirmed by comparison of standard substance and structural identification of ¹H-NMR. Subsequently, the multiple-metabolites model composed of the 6 biomarkers was validated in a validation cohort (n = 165).

CONCLUSIONS

The concentrations of leucine, indole, N-acetylvaline, 5-hydroxy-L-tryptophan, hydroxyhexanoycarnitine and kynurenic acid in urine were proven to be positively correlated with the degree of renal injury induced by iodixanol. The multiple-metabolites model based on these 6 biomarkers has a good predictive ability to predict early renal injury caused by iodixanol, provides treatment direction for injury intervention and a reference for reducing the incidence of clinical CI-AKI further.

NMR spectroscopy spotlighting immunogenicity induced by COVID-19 vaccination to mitigate future health concerns

In this review, the disease and immunogenicity affected by COVID-19 vaccination at the metabolic level are described considering the use of nuclear magnetic resonance (NMR) spectroscopy for the analysis of different biological samples. Consistently, we explain how different biomarkers can be examined in the saliva, blood plasma/serum, bronchoalveolar-lavage fluid (BALF), semen, feces, urine, cerebrospinal fluid (CSF) and breast milk. For example, the proposed approach for the given samples can allow one to detect molecular biomarkers that can be relevant to disease and/or vaccine interference in a system metabolome. The analysis of the given biomaterials by NMR often produces complex chemical data which can be elucidated by multivariate statistical tools, such as PCA and PLS-DA/OPLS-DA methods. Moreover, this approach may aid to improve strategies that can be helpful in disease control and treatment management in the future.

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NMR analysis of various bio-samples can explore disease course and vaccine interaction.

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Immunogenicity and reactogenicity caused by COVID-19 vaccination can be studied by NMR.

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Vaccine interaction alters metabolic pathway(s) at a certain stage, and this mechanism can be probed at the metabolic level.

Molecular genetics of renal ciliopathies

Renal ciliopathies are a heterogenous group of inherited disorders leading to an array of phenotypes that include cystic kidney disease and renal interstitial fibrosis leading to progressive chronic kidney disease and end-stage kidney disease. The renal tubules are lined with epithelial cells that possess primary cilia that project into the lumen and act as sensory and signalling organelles. Mutations in genes encoding ciliary proteins involved in the structure and function of primary cilia cause ciliopathy syndromes and affect many organ systems including the kidney. Recognised disease phenotypes associated with primary ciliopathies that have a strong renal component include autosomal dominant and recessive polycystic kidney disease and their various mimics, including atypical polycystic kidney disease and nephronophthisis. The molecular investigation of inherited renal ciliopathies often allows a precise diagnosis to be reached where renal histology and other investigations have been unhelpful and can help in determining kidney prognosis. With increasing molecular insights, it is now apparent that renal ciliopathies form a continuum of clinical phenotypes with disease entities that have been classically described as dominant or recessive at both extremes of the spectrum. Gene-dosage effects, hypomorphic alleles, modifier genes and digenic inheritance further contribute to the genetic complexity of these disorders. This review will focus on recent molecular genetic advances in the renal ciliopathy field with a focus on cystic kidney disease phenotypes and the genotypes that lead to them. We discuss recent novel insights into underlying disease mechanisms of renal ciliopathies that might be amenable to therapeutic intervention.

Liquid chromatography-mass spectrometry untargeted metabolomics reveals increased levels of tryptophan indole metabolites in urine of metabolic syndrome patients

Metabolic syndrome (MetS) is a multifactor condition predisposing for diabetes, cardiovascular diseases and other degenerative disorders. Although several diagnostic criteria have been established, none of them is specific and there is a call for better pathophysiological explanation of MetS and for the discovery of molecular biomarkers. Phenotype characterization at metabolome level might be useful for both purposes. To this end, our aim was to perform comparative untargeted metabolomics of urines from MetS patients and from the control group. The study participants included 52 diagnosticated and 50 healthy individuals from Leon city in central Mexico; 23 anthropometric and clinical parameters were measured and submitted to Principal Component Analysis (PCA). The obtained PCA model allowed us for selection of 11 MetS patients and 13 control subjects, correspondingly representative for each of the two groups (clearly separated in PCA). The first morning urines from these subjects were ambulatory collected and, after methanol extraction and acidification, were submitted to capillary liquid chromatography-high resolution mass spectrometry (LC-HRMS). The obtained data were analyzed on MetaboScape® platform (Bruker Daltonics). Specifically, t-test applied to LC-HRMS data revealed several ions presenting at least 3-fold higher intensities in MetS with respect to the control samples (p < 0.05). Data analysis and complementary experiments yielded the identification of the following metabolites: indole-3-acetic acid, indole-3-acetic acid-O-glucuronide, N-(indol-3-ylacetyl) glutamine, indole-3-carbaldehyde and hydroxyhexanoycarnitine. Additionally, indole-3-carboxylic acid was annotated with 2.13-fold higher abundance in MetS patients. To assess the contribution of individual metabolites in the difference between two groups of subjects, partial least square discriminant analysis was performed for LC-HRMS data and the obtained values of variable importance in projection (VIP), confirmed the association of six above mentioned compounds with MetS. Overall, this study provides direct evidence on the disturbed catabolism of tryptophan in metabolic syndrome.