Fecal Metabolites As Non-Invasive Biomarkers of Gut Diseases

CD1d-dependent neuroinflammation impairs tissue repair and functional recovery following a spinal cord injury

Tissue damage resulting from a spinal cord injury (SCI) is primarily driven by a robust neuroimmune/neuroinflammatory response. This intricate process is mainly governed by a multitude of cytokines and cell surface proteins in the central nervous system (CNS). However, the critical components of the neuroimmune/neuroinflammatory response during SCI are still not well-defined. In this study, we investigated the impact of CD1d, an MHC class I-like molecule mostly known for presenting lipid antigens to natural killer T (NKT) cells and regulating immune/inflammatory responses, on neuroimmune/neuroinflammatory responses induced by SCI. We observed an increased expression of CD1d on various cell types within the spinal cord, including microglia/macrophages, oligodendrocytes (ODCs), and endothelial cells (DCs), but not on neurons or astrocytes post-SCI. In comparison to wildtype (WT) mice, a T10 contusive SCI in CD1d knockout (CD1dKO or Cd1d -/- ) mice resulted in markedly reduced proinflammatory cytokine release, microglia/macrophage activation and proliferation. Following SCI, the levels of inflammatory cytokines and activation/proliferation of microglia/macrophages were dramatically reduced, while anti-inflammatory cytokines such as IL-4 and growth factors like VEGF were substantially increased in the spinal cord tissues of CD1dKO mice when compared to WT mice. In the post-acute phase of SCI (day 7 post-SCI), CD1dKO mice had a significantly higher frequency of tissue-repairing macrophages, but not other types of immune cells, in the injured spinal cord tissues compared to WT mice. Moreover, CD1d-deficiency protected spinal cord neuronal cells and tissue, promoting functional recovery after a SCI. However, the neuroinflammation in WT mouse spinal cords was independent of the canonical CD1d/NKT cell axis. Finally, treatment of injured mice with a CD1d-specific monoclonal antibody significantly enhanced neuroprotection and improved functional recovery. Therefore, CD1d promotes the proinflammatory response following a SCI and represents a potential therapeutic target for spinal cord repair.

Significance Statement

The cell surface molecule, CD1d, is known to be recognized by cells of the immune system. To our knowledge, this is the first observation that the CD1d molecule significantly contributes to neuroinflammation following a spinal cord injury (SCI) in a manner independent of the CD1d/NKT cell axis. This is important, because this work reveals CD1d as a potential therapeutic target following an acute SCI for which there are currently no effective treatments.

Integrated analysis of the transcriptome and its interaction with the metabolome in metabolic associated fatty liver disease: Gut microbiome signatures, correlation networks, and effect of PNPLA3 genotype

Interactions between communities of the gut microbiome and with the host could affect the onset and progression of metabolic associated fatty liver disease (MAFLD), and can be useful as new diagnostic and prognostic biomarkers. In this study, we performed a multi-omics approach to unravel gut microbiome signatures from 32 biopsy-proven patients (10 simple steatosis -SS- and 22 steatohepatitis -SH-) and 19 healthy volunteers (HV). Human and microbial transcripts were differentially identified between groups (MAFLD vs. HV/SH vs. SS), and analyzed for weighted correlation networks together with previously detected metabolites from the same set of samples. We observed that expression of Desulfobacteraceae bacterium, methanogenic archaea, Mushu phage, opportunistic pathogenic fungi Fusarium proliferatum and Candida sorbophila, protozoa Blastocystis spp. and Fonticula alba were upregulated in MAFLD and SH. Desulfobacteraceae bacterium and Mushu phage were hub species in the onset of MAFLD, whereas the activity of Fonticula alba, Faecalibacterium prausnitzii, and Mushu phage act as key regulators of the progression to SH. A combination of clinical, metabolomic, and transcriptomic parameters showed the highest predictive capacity for MAFLD and SH (AUC = 0.96). In conclusion, faecal microbiome markers from several community members contribute to the switch in signatures characteristic of MAFLD and its progression towards SH.

The Metabolome and the Gut Microbiota for the Prediction of Necrotizing Enterocolitis and Spontaneous Intestinal Perforation: A Systematic Review

Necrotizing enterocolitis (NEC) is the most devastating gastrointestinal emergency in preterm neonates. Research on early predictive biomarkers is fundamental. This is a systematic review of studies applying untargeted metabolomics and gut microbiota analysis to evaluate the differences between neonates affected by NEC (Bell’s stage II or III), and/or by spontaneous intestinal perforation (SIP) versus healthy controls. Five studies applying metabolomics (43 cases, 95 preterm controls) and 20 applying gut microbiota analysis (254 cases, 651 preterm controls, 22 term controls) were selected. Metabolomic studies utilized NMR spectroscopy or mass spectrometry. An early urinary alanine/histidine ratio >4 showed good sensitivity and predictive value for NEC in one study. Samples collected in proximity to NEC diagnosis demonstrated variable pathways potentially related to NEC. In studies applying untargeted gut microbiota analysis, the sequencing of the V3−V4 or V3 to V5 regions of the 16S rRNA was the most used technique. At phylum level, NEC specimens were characterized by increased relative abundance of Proteobacteria compared to controls. At genus level, pre-NEC samples were characterized by a lack or decreased abundance of Bifidobacterium. Finally, at the species level Bacteroides dorei, Clostridium perfringens and perfringens-like strains dominated early NEC specimens, whereas Clostridium butyricum, neonatale and Propionibacterium acnei those at disease diagnosis. Six studies found a lower Shannon diversity index in cases than controls. A clear separation of cases from controls emerged based on UniFrac metrics in five out of seven studies. Importantly, no studies compared NEC versus SIP. Untargeted metabolomics and gut microbiota analysis are interrelated strategies to investigate NEC pathophysiology and identify potential biomarkers. Expression of quantitative measurements, data sharing via biorepositories and validation studies are fundamental to guarantee consistent comparison of results.

Evaluation of different stool extraction methods for metabolomics measurements in human faecal samples

Background

Metabolomics analysis of human stool samples is of great interest for a broad range of applications in biomedical research including early detection of colorectal neoplasms. However, due to the complexity of metabolites there is no consensus on how to process samples for stool metabolomics measurements to obtain a broad coverage of hydrophilic and hydrophobic substances.

Methods

We used frozen stool samples (50 mg) from healthy study participants. Stool samples were processed after thawing using eight different processing protocols and different solvents (solvents such as phosphate-buffered saline, isopropanol, methanol, ethanol, acetonitrile and solvent mixtures with or without following evaporation and concentration steps). Metabolites were measured afterwards using the MxP Quant 500 kit (Biocrates). The best performing protocol was subsequently applied to compare stool samples of participants with different dietary habits.

Results

In this study, we were able to determine up to 340 metabolites of various chemical classes extracted from stool samples of healthy study participants with eight different protocols. Polar metabolites such as amino acids could be measured with each method while other metabolite classes, particular lipid species (better with isopropanol and ethanol or methanol following a drying step), are more dependent on the solvent or combination of solvents used. Only a small number of triglycerides or acylcarnitines were detected in human faeces. Extraction efficiency was higher for protocols using isopropanol (131 metabolites>limit of detection (LOD)) or those using ethanol or methanol and methyl tert-butyl ether (MTBE) including an evaporation and concentration step (303 and 342 metabolites>LOD, respectively) than for other protocols. We detected significant faecal metabolite differences between vegetarians, semivegetarians and non-vegetarians.

Conclusion

For the evaluation of metabolites in faecal samples, we found protocols using solvents like isopropanol and those using ethanol or methanol, and MTBE including an evaporation and concentration step to be superior regarding the number of detected metabolites of different chemical classes over others tested in this study.

Plasma and stool metabolomics to identify microbiota derived-biomarkers of metabolic dysfunction-associated fatty liver disease: effect of PNPLA3 genotype

INTRODUCTION

Non-invasive biomarkers are needed for metabolic dysfunction-associated fatty liver disease (MAFLD), especially for patients at risk of disease progression in high-prevalence areas. The microbiota and its metabolites represent a niche for MAFLD biomarker discovery. However, studies are not reproducible as the microbiota is variable.

OBJECTIVES

We aimed to identify microbiota-derived metabolomic biomarkers that may contribute to the higher MAFLD prevalence and different disease severity in Latin America, where data is scarce.

METHODS

We compared the plasma and stool metabolomes, gene patatin-like phospholipase domain-containing 3 (PNPLA3) rs738409 single nucleotide polymorphism (SNP), diet, demographic and clinical data of 33 patients (12 simple steatosis and 21 steatohepatitis) and 19 healthy volunteers (HV). The potential predictive utility of the identified biomarkers for MAFLD diagnosis and progression was evaluated by logistic regression modelling and ROC curves.

RESULTS

Twenty-four (22 in plasma and 2 in stool) out of 424 metabolites differed among groups. Plasma triglyceride (TG) levels were higher among MAFLD patients, whereas plasma phosphatidylcholine (PC) and lysoPC levels were lower among HV. The PNPLA3 risk genotype was related to higher plasma levels of eicosenoic acid or fatty acid 20:1 (FA(20:1)). Body mass index and plasma levels of PCaaC24:0, FA(20:1) and TG (16:1_34:1) showed the best AUROC for MAFLD diagnosis, whereas steatosis and steatohepatitis could be discriminated with plasma levels of PCaaC24:0 and PCaeC40:1.

CONCLUSION

This study identified for the first time MAFLD potential non-invasive biomarkers in a Latin American population. The association of PNPLA3 genotype with FA(20:1) suggests a novel metabolic pathway influencing MAFLD pathogenesis.