Omics to Explore Amyotrophic Lateral Sclerosis Evolution: the Central Role of Arginine and Proline Metabolism

Dietary Marine Oils Selectively Decrease Obesogenic Diet-Derived Carbonylation in Proteins Involved in ATP Homeostasis and Glutamate Metabolism in the Rat Cerebellum

The regular intake of diets high in saturated fat and sugars increases oxidative stress and has been linked to cognitive decline and premature brain aging. The cerebellum is highly vulnerable to oxidative stress and thus, obesogenic diets might be particularly detrimental to this tissue. However, the precise molecular mechanisms behind obesity-related brain damage are still not clear. Since protein carbonylation, a biomarker of oxidative stress, influences protein functions and is involved in metabolic control, the current investigation addressed the effect of long-term high-fat and high-sucrose diet intake on the cerebellum of Sprague-Dawley rats by deciphering the changes caused in the carbonylated proteome. The antioxidant effects of fish oil supplementation on cerebellar carbonylated proteins were also investigated. Lipid peroxidation products and carbonylated proteins were identified and quantified using immunoassays and 2D-LC-MS/MS in the cerebellum. After 21 weeks of nutritional intervention, the obesogenic diet selectively increased carbonylation of the proteins that participate in ATP homeostasis and glutamate metabolism in the cerebellum. Moreover, the data demonstrated that fish oil supplementation restrained carbonylation of the main protein targets oxidatively damaged by the obesogenic diet, and additionally protected against carbonylation of several other proteins involved in amino acid biosynthesis and neurotransmission. Therefore, dietary interventions with fish oils could help the cerebellum to be more resilient to oxidative damage. The results could shed some light on the effect of high-fat and high-sucrose diets on redox homeostasis in the cerebellum and boost the development of antioxidant-based nutritional interventions to improve cerebellum health.

Effects of leucism on organ development and molecular mechanisms in Northern snakehead (Channa argus) beyond pigmentation alterations

Leucism, a widespread occurrence observed in Northern snakehead (Channa argus), bestows a striking white jade-like body coloration upon affected individuals and has gained substantial popularity in commercial breeding. While the visible manifestation of leucism in snakeheads is primarily limited to body coloration, it is crucial to explore the potential influence of leucism on organ development and elucidate the underlying molecular mechanisms. Through a comparative analysis of growth differences, our study revealed that at 150 days post-fertilization, the white variety exhibited an 8.5% higher liver index and intestinal index, but experienced a 20% and 38% decreased in spleen index and renal interstitial index, respectively, suggesting an enlarged digestive area but relatively smaller immune tissues. Nonetheless, no significant differences were observed in the intestinal flora between the two varieties, suggesting the exclusion of any exogenous impacts from symbiotic flora on the growth and development of the white variety. Importantly, transcriptome analysis demonstrated that the white variety exhibited higher expression levels of innate immune genes. Furthermore, annotation of the gene sets expressed in the liver and spleen revealed 76 and 35 genes respectively, with the white variety displaying lower expression in genes associated with "Viral protein interaction with cytokine and cytokine receptor", "Protein processing in endoplasmic reticulum", and "TNF signaling pathway", while exhibiting higher expression in "Estrogen signaling pathway". Notably, three genes, namely pcdhf 4, nlrc3 card 15-like, and a pol-like were identified in both the liver and spleen, indicating their potential involvement in altering the development and innate immunity of the white variety. This study reveals the systemic impact of leucism that extends beyond mere pigmentation alterations, highlighting the prominent characteristics of this phenotype and providing a foundation for future molecular breeding programs aimed at enhancing this variety.

Applications of multi-omics analysis in human diseases

Multi-omics usually refers to the crossover application of multiple high-throughput screening technologies represented by genomics, transcriptomics, single-cell transcriptomics, proteomics and metabolomics, spatial transcriptomics, and so on, which play a great role in promoting the study of human diseases. Most of the current reviews focus on describing the development of multi-omics technologies, data integration, and application to a particular disease; however, few of them provide a comprehensive and systematic introduction of multi-omics. This review outlines the existing technical categories of multi-omics, cautions for experimental design, focuses on the integrated analysis methods of multi-omics, especially the approach of machine learning and deep learning in multi-omics data integration and the corresponding tools, and the application of multi-omics in medical researches (e.g., cancer, neurodegenerative diseases, aging, and drug target discovery) as well as the corresponding open-source analysis tools and databases, and finally, discusses the challenges and future directions of multi-omics integration and application in precision medicine. With the development of high-throughput technologies and data integration algorithms, as important directions of multi-omics for future disease research, single-cell multi-omics and spatial multi-omics also provided a detailed introduction. This review will provide important guidance for researchers, especially who are just entering into multi-omics medical research.

Adaptation to hypoxic stress involves amino acid metabolism: A case in sea cucumber

Low dissolved oxygen (LO) in seawater negatively affects aquatic animals and has received considerable attention. However, there is still much to learn about how echinoderms, which are keystone species in benthic ecosystems, respond to hypoxic stress. Here, we detected differentially expressed metabolites (DEMs) in sea cucumber (Apositchopus japonicus) between normoxic conditions (NC group) and hypoxic conditions (2 mg L^-1) for 3 and 7 days (i.e., LO3 and LO7 groups). A total of 156, 180, and 95 DEMs were found in the NC versus LO3, NC vs. LO7, and LO3 vs. LO7 comparisons, respectively. Amino acids were the most abundant class of DEMs, and "biosynthesis of amino acids" was an enriched pathway in all three comparisons. Most of the enriched metabolite sets under hypoxic stress were related to metabolism. As the duration of the hypoxia treatment extended, the metabolism-related process maintained an upward trend, and signaling pathways maintained a downward trend. Thus, metabolism-related processes are affected in hypoxia-stressed sea cucumber, and amino acid metabolism is the most important process for adaption to hypoxic conditions, potentially function in osmotic regulation and energy regulation. Our results shed light on the adaptative strategies of sea cucumber to challenging environmental conditions.

An integrated multi-omic approach demonstrates distinct molecular signatures between human obesity with and without metabolic complications: a case-control study

OBJECTIVES

To examine the hypothesis that obesity complicated by the metabolic syndrome, compared to uncomplicated obesity, has distinct molecular signatures and metabolic pathways.

METHODS

We analyzed a cohort of 39 participants with obesity that included 21 with metabolic syndrome, age-matched to 18 without metabolic complications. We measured in whole blood samples 754 human microRNAs (miRNAs), 704 metabolites using unbiased mass spectrometry metabolomics, and 25,682 transcripts, which include both protein coding genes (PCGs) as well as non-coding transcripts. We then identified differentially expressed miRNAs, PCGs, and metabolites and integrated them using databases such as mirDIP (mapping between miRNA-PCG network), Human Metabolome Database (mapping between metabolite-PCG network) and tools like MetaboAnalyst (mapping between metabolite-metabolic pathway network) to determine dysregulated metabolic pathways in obesity with metabolic complications.

RESULTS

We identified 8 significantly enriched metabolic pathways comprising 8 metabolites, 25 protein coding genes and 9 microRNAs which are each differentially expressed between the subjects with obesity and those with obesity and metabolic syndrome. By performing unsupervised hierarchical clustering on the enrichment matrix of the 8 metabolic pathways, we could approximately segregate the uncomplicated obesity strata from that of obesity with metabolic syndrome.

CONCLUSIONS

The data suggest that at least 8 metabolic pathways, along with their various dysregulated elements, identified via our integrative bioinformatics pipeline, can potentially differentiate those with obesity from those with obesity and metabolic complications.

Integrative analysis of metabolomics and proteomics unravels purine metabolism disorder in the SOD1G93A mouse model of amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with progressive paralysis of limbs and bulb in patients, the cause of which remains unclear. Accumulating studies suggest that motor neuron degeneration is associated with systemic metabolic impairment in ALS. However, the metabolic reprogramming and underlying mechanism in the longitudinal progression of the disease remain poorly understood. In this study, we aimed to investigate the molecular changes at both metabolic and proteomic levels during disease progression to identify the most critical metabolic pathways and underlying mechanisms involved in ALS pathophysiological changes. Utilizing liquid chromatography-mass spectrometry-based metabolomics, we analyzed the metabolites' levels of plasma, lumbar spinal cord, and motor cortex from SOD1^G93A mice and wildtype (WT) littermates at different stages. To elucidate the regulatory network underlying metabolic changes, we further analyzed the proteomics profile in the spinal cords of SOD1^G93A and WT mice. A group of metabolites implicated in purine metabolism, methionine cycle, and glycolysis were found differentially expressed in ALS mice, and abnormal expressions of enzymes involved in these metabolic pathways were also confirmed. Notably, we first demonstrated that dysregulation of purine metabolism might contribute to the pathogenesis and disease progression of ALS. Furthermore, we discovered that fatty acid metabolism, TCA cycle, arginine and proline metabolism, and folate-mediated one‑carbon metabolism were also significantly altered in this disease. The identified differential metabolites and proteins in our study could complement existing data on metabolic reprogramming in ALS, which might provide new insight into the pathological mechanisms and novel therapeutic targets of ALS.

Is substrate choice an overlooked variable in ecotoxicology experiments?

It is crucial to understand the effects caused by experimental parameters such as temperature, light, and food type on lab and field-based ecotoxicology experiments, as these variables, and combinations thereof, can affect results. The type of substrate used in exposure experiments, however, is generally assumed to have no effect. This may not always be correct. The metabolic changes in the freshwater crustacean, Austrochiltonia subtenuis exposed to copper, using three common substrates, gauze; toilet paper; and cellulose were investigated. Substrate alone did not affect survival, but each substrate elicited a different metabolic response and adult and juvenile amphipods had different substrate preferences. Several classes of metabolites were shown to change in response to different substrates and toxicant. These included disaccharides, monosaccharides, fatty acids, and tricarboxylic acid cycle intermediates. The results illustrate that metabolomic responses can differ in response to experimental factors that were previously thought not to be significant. In fact, our data indicate that substrate should be viewed as an experimental factor as important to control for as more well-known confounders such as temperature or food, thus challenging the current paradigm. Assuming substrate type has no effect on the experiment could potentially lead to errors in contaminant toxicity assessments. We propose that ideal good practise would be that all experimental factors should be evaluated for their potential influence on metabolomic profiles prior to contaminant response experiments being undertaken.

Metabolomics identifies shared lipid pathways in independent amyotrophic lateral sclerosis cohorts

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease lacking effective treatments. This is due, in part, to a complex and incompletely understood pathophysiology. To shed light, we conducted untargeted metabolomics on plasma from two independent cross-sectional ALS cohorts versus control participants to identify recurrent dysregulated metabolic pathways. Untargeted metabolomics was performed on plasma from two ALS cohorts (cohort 1, n = 125; cohort 2, n = 225) and healthy controls (cohort 1, n = 71; cohort 2, n = 104). Individual differential metabolites in ALS cases versus controls were assessed by Wilcoxon, adjusted logistic regression and partial least squares-discriminant analysis, while group lasso explored sub-pathway level differences. Adjustment parameters included age, sex and body mass index. Metabolomics pathway enrichment analysis was performed on metabolites selected using the above methods. Additionally, we conducted a sex sensitivity analysis due to sex imbalance in the cohort 2 control arm. Finally, a data-driven approach, differential network enrichment analysis (DNEA), was performed on a combined dataset to further identify important ALS metabolic pathways. Cohort 2 ALS participants were slightly older than the controls (64.0 versus 62.0 years, P = 0.009). Cohort 2 controls were over-represented in females (68%, P < 0.001). The most concordant cohort 1 and 2 pathways centred heavily on lipid sub-pathways, including complex and signalling lipid species and metabolic intermediates. There were differences in sub-pathways that were enriched in ALS females versus males, including in lipid sub-pathways. Finally, DNEA of the merged metabolite dataset of both ALS and control cohorts identified nine significant subnetworks; three centred on lipids and two encompassed a range of sub-pathways. In our analysis, we saw consistent and important shared metabolic sub-pathways in both ALS cohorts, particularly in lipids, further supporting their importance as ALS pathomechanisms and therapeutics targets.

Integrated network pharmacology approach shows a potential role of Ginseng catechins and ginsenosides in modulating protein aggregation in Amyotrophic Lateral Sclerosis

Amyotrophic lateral Sclerosis is an incurable, progressive neurodegenerative motor neuron disease. The disease is characterized by protein aggregates. The symptoms include weakness, denervation of muscles, atrophy and progressive paralysis of bulbar and respiratory muscles and dysphagia. Various secondary metabolites are evaluated for their ability to improve symptoms in ALS. Ginseng has been traditionally used for treating several neurodegenerative diseases. Several studies using model systems have shown a potential role of Ginseng catechins and Ginsenosides in clearing protein aggregation associated with ALS. We focus on Network pharmacology approach to understand the effect of Ginseng catechins or ginsenosides on protein aggregation associated with ALS. A catechin/ginsenoside-protein interaction network was generated and the pathways obtained were compared with those obtained from transcriptomic datasets of ALS from GEO database. Knock out of MAPK14, AKT and GSK from Catechin and BACE 1 from ginsenoside modulated pathways inhibited protein aggregation. Catechins and ginsenosides have potential as therapeutic agents in the management of ALS.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03401-1.

Interrogating the Metabolomic Profile of Amyotrophic Lateral Sclerosis in the Post-Mortem Human Brain by Infrared Matrix-Assisted Laser Desorption Electrospray Ionization (IR-MALDESI) Mass Spectrometry Imaging (MSI)

Amyotrophic lateral sclerosis (ALS) is an idiopathic, fatal neurodegenerative disease characterized by progressive loss of motor function with an average survival time of 2-5 years after diagnosis. Due to the lack of signature biomarkers and heterogenous disease phenotypes, a definitive diagnosis of ALS can be challenging. Comprehensive investigation of this disease is imperative to discovering unique features to expedite the diagnostic process and improve diagnostic accuracy. Here, we present untargeted metabolomics by mass spectrometry imaging (MSI) for comparing sporadic ALS (sALS) and C9orf72 positive (C9Pos) post-mortem frontal cortex human brain tissues against a control cohort. The spatial distribution and relative abundance of metabolites were measured by infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) MSI for association to biological pathways. Proteomic studies on the same patients were completed via LC-MS/MS in a previous study, and results were integrated with imaging metabolomics results to enhance the breadth of molecular coverage. Utilizing METASPACE annotation platform and MSiPeakfinder, nearly 300 metabolites were identified across the sixteen samples, where 25 were identified as dysregulated between disease cohorts. The dysregulated metabolites were further examined for their relevance to alanine, aspartate, and glutamate metabolism, glutathione metabolism, and arginine and proline metabolism. The dysregulated pathways discussed are consistent with reports from other ALS studies. To our knowledge, this work is the first of its kind, reporting on the investigation of ALS post-mortem human brain tissue analyzed by multiomic MSI.

Deciphering lipid dysregulation in ALS: from mechanisms to translational medicine

Lipids, defined by low solubility in water and high solubility in nonpolar solvents, can be classified into fatty acids, glycerolipids, glycerophospholipids, sphingolipids, and sterols. Lipids not only regulate integrity and fluidity of biological membranes, but also serve as energy storage and bioactive molecules for signaling. Causal mutations in SPTLC1 (serine palmitoyltransferase long chain subunit 1) gene within the lipogenic pathway have been identified in amyotrophic lateral sclerosis (ALS), a paralytic and fatal motor neuron disease. Furthermore, lipid dysmetabolism within the central nervous system and circulation is associated with ALS. Here, we aim to delineate the diverse roles of different lipid classes and understand how lipid dysmetabolism may contribute to ALS pathogenesis. Among the different lipids, accumulation of ceramides, arachidonic acid, and lysophosphatidylcholine is commonly emerging  as detrimental to motor neurons. We end with exploring the potential ALS therapeutics by reducing these toxic lipids.

Recent Advances in Fluorescent Methods for Polyamine Detection and the Polyamine Suppressing Strategy in Tumor Treatment

The biogenic aliphatic polyamines (spermine, spermidine, and putrescine) are responsible for numerous cell functions, including cell proliferation, the stabilization of nucleic acid conformations, cell division, homeostasis, gene expression, and protein synthesis in living organisms. The change of polyamine concentrations in the urine or blood is usually related to the presence of malignant tumors and is regarded as a biomarker for the early diagnosis of cancer. Therefore, the detection of polyamine levels in physiological fluids can provide valuable information in terms of cancer diagnosis and in monitoring therapeutic effects. In this review, we summarize the recent advances in fluorescent methods for polyamine detection (supramolecular fluorescent sensing systems, fluorescent probes based on the chromophore reaction, fluorescent small molecules, and fluorescent nanoparticles). In addition, tumor polyamine-suppressing strategies (such as polyamine conjugate, polyamine analogs, combinations that target multiple components, spermine-responsive supramolecular chemotherapy, a combination of polyamine consumption and photodynamic therapy, etc.) are highlighted. We hope that this review promotes the development of more efficient polyamine detection methods and provides a comprehensive understanding of polyamine-based tumor suppressor strategies.

Metabolic Profile and Pathological Alterations in the Muscle of Patients with Early-Stage Amyotrophic Lateral Sclerosis

Diverse biomarkers and pathological alterations have been found in muscle of patients with Amyotrophic lateral sclerosis (ALS), but the relation between such alterations and dysfunction in energetic metabolism remains to be investigated. We established the metabolome of muscle and serum of ALS patients and correlated these findings with the clinical status and pathological alterations observed in the muscle. We obtained data from 20 controls and 17 ALS patients (disease duration: 9.4 ± 6.8 months). Multivariate metabolomics analysis identified a distinct serum metabolome for ALS compared to controls (p-CV-ANOVA < 0.035) and revealed an excellent discriminant profile for muscle metabolome (p-CV-ANOVA < 0.0012). Citramalate was discriminant for both muscle and serum. High lauroylcarnitine levels in muscle were associated with low Forced Vital Capacity. Transcriptomics analysis of key antioxidant enzymes showed an upregulation of SOD3 (p = 0.0017) and GLRX2(1) (p = 0.0022) in ALS muscle. Analysis of mitochondrial enzymatic activity in muscle revealed higher complex II/CS (p = 0.04) and lower LDH (p = 0.03) activity in ALS than in controls. Our study showed, for the first time, a global dysfunction in the muscle of early-stage ALS patients. Furthermore, we identified novel metabolites to be employed as biomarkers for diagnosis and prognosis of ALS patients.

Altered Metabolic Profiles of the Plasma of Patients with Amyotrophic Lateral Sclerosis

Currently, there is no objective biomarker to indicate disease progression and monitor therapeutic effects for amyotrophic lateral sclerosis (ALS). This study aimed to identify plasma biomarkers for ALS using a targeted metabolomics approach. Plasma levels of 185 metabolites in 36 ALS patients and 36 age- and sex-matched normal controls (NCs) were quantified using an assay combining liquid chromatography with tandem mass spectrometry and direct flow injection. Identified candidates were correlated with the scores of the revised ALS Functional Rating Scale (ALSFRS-r). Support vector machine (SVM) learning applied to selected metabolites was used to differentiate ALS and NC subjects. Forty-four metabolites differed significantly between ALS and NC subjects. Significant correlations with ALSFRS-r score were seen in 23 metabolites. Six of them showing potential to distinguish ALS from NC-asymmetric dimethylarginine (area under the curve (AUC): 0.829), creatinine (AUC: 0.803), methionine (AUC: 0.767), PC-acyl-alkyl C34:2 (AUC: 0.808), C34:2 (AUC: 0.763), and PC-acyl-acyl C42:2 (AUC: 0.751)-were selected for machine learning. The SVM algorithm using selected metabolites achieved good performance, with an AUC of 0.945. In conclusion, our findings indicate that a panel of metabolites were correlated with disease severity of ALS, which could be potential biomarkers for monitoring ALS progression and therapeutic effects.

A Transcriptome Insight During Early Fish Larval Development Followed by Starvation in Seriola rivoliana

We investigated a time-course larval transcriptional analysis (RNA-seq) in the longfin yellowtail Seriola rivoliana, from hatching to day four at 22 °C, without providing zooplankton as food. Larval starvation is a critical physiological stage that must be prevented to ensure survival. However, the transcriptional mechanisms to endure starvation have not been investigated in marine fish. Differential gene expression showed newly day-specific transcriptome events during larval development. On day 1 (yolk sac absorption), the predominant upregulated developmental processes were larval growth, muscle and vision development, cytoskeletal structure, protein synthesis, protein and fat digestion-absorption, and hormone biosynthesis, whereas the cell cycle was suppressed. On day 2 (yolk sac exhaustion), a new stage of energy regeneration (ATP) was supplied by the oil drop reserve, whereas protein digestion-absorption and growth were suppressed. On day 3 (mouth opening and starvation), stress signals and nutrition deprivation upregulated the p53 signal and triggered autophagy and the AMP-activated protein kinase (AMPK) pathways as an alternative catabolic pathway to enduring starvation, and the circadian rhythm was established. On day 4 (starving and weakened larvae condition), autophagy supported subsequent protein synthesis, activated the immune system, and promoted estrogen signaling and skeleton renovation. However, larvae suppressed muscle development, vision and carbohydrate, and fat digestion-absorption and became lethargic, evidencing limited physiological support by autophagy to maintain survival without exogenous nutrition in this species.

Application of Metabolomics to the Discovery of Biomarkers for Ischemic Stroke in the Murine Model: a Comparison with the Clinical Results

Ischemic stroke (IS) is a major cause of mortality and disability worldwide. However, the pathogenesis of IS remains unknown, and methods for early prediction and diagnosis of IS are lacking. Metabolomics can be applied to biomarker discovery and mechanism exploration of IS by exploring metabolic alterations. In this review, 62 IS metabolomics studies in the murine model published from January 2006 to December 2020 in the PubMed and Web of Science databases were systematically reviewed. Twenty metabolites (e.g., lysine, phenylalanine, methionine, tryptophan, leucine, lactate, serine, N-acetyl-aspartic acid, and glutathione) were reported consistently in more than two-third murine studies. The disturbance of metabolic pathways, such as arginine biosynthesis; alanine, aspartate and glutamate metabolism; aminoacyl-tRNA biosynthesis; and citrate cycle, may be implicated in the development of IS by influencing the biological processes such as energy failure, oxidative stress, apoptosis, and glutamate toxicity. The transient middle cerebral artery occlusion model and permanent middle cerebral artery occlusion model exhibit both common and distinct metabolic patterns. Furthermore, five metabolites (proline, serine, LysoPC (16:0), uric acid, glutamate) in the blood sample and 7 metabolic pathways (e.g., alanine, aspartate, and glutamate metabolism) are shared in animal and clinical studies. The potential biomarkers and related pathways of IS in the murine model may facilitate the biomarker discovery for early diagnosis of IS and the development of novel therapeutic targets.

Metabolic and immune dysfunction of glia in neurodegenerative disorders: Focus on iPSC models

The research on neurodegenerative disorders has long focused on neuronal pathology and used transgenic mice as disease models. However, our understanding of the chronic neurodegenerative process in the human brain is still very limited. It is increasingly recognized that neuronal loss is not caused solely by intrinsic degenerative processes but rather via impaired interactions with surrounding glia and other brain cells. Dysfunctional astrocytes do not provide sufficient nutrients and antioxidants to the neurons, while dysfunctional microglia cannot efficiently clear pathogens and cell debris from extracellular space, thus resulting in chronic inflammatory processes in the brain. Importantly, human glia, especially the astrocytes, differ significantly in morphology and function from their mouse counterparts, and therefore more human-based disease models are needed. Recent advances in stem cell technology make it possible to reprogram human patients' somatic cells to induced pluripotent stem cells (iPSC) and differentiate them further into patient-specific glia and neurons, thus providing a virtually unlimited source of human brain cells. This review summarizes the recent studies using iPSC-derived glial models of Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis and discusses the applicability of these models to drug testing. This line of research has shown that targeting glial metabolism can improve the survival and function of cocultured neurons and thus provide a basis for future neuroprotective treatments.

Untargeted metabolomics yields insight into ALS disease mechanisms

OBJECTIVE

To identify dysregulated metabolic pathways in amyotrophic lateral sclerosis (ALS) versus control participants through untargeted metabolomics.

METHODS

Untargeted metabolomics was performed on plasma from ALS participants (n=125) around 6.8 months after diagnosis and healthy controls (n=71). Individual differential metabolites in ALS cases versus controls were assessed by Wilcoxon rank-sum tests, adjusted logistic regression and partial least squares-discriminant analysis (PLS-DA), while group lasso explored sub-pathway-level differences. Adjustment parameters included sex, age and body mass index (BMI). Metabolomics pathway enrichment analysis was performed on metabolites selected by the above methods. Finally, machine learning classification algorithms applied to group lasso-selected metabolites were evaluated for classifying case status.

RESULTS

There were no group differences in sex, age and BMI. Significant metabolites selected were 303 by Wilcoxon, 300 by logistic regression, 295 by PLS-DA and 259 by group lasso, corresponding to 11, 13, 12 and 22 enriched sub-pathways, respectively. 'Benzoate metabolism', 'ceramides', 'creatine metabolism', 'fatty acid metabolism (acyl carnitine, polyunsaturated)' and 'hexosylceramides' sub-pathways were enriched by all methods, and 'sphingomyelins' by all but Wilcoxon, indicating these pathways significantly associate with ALS. Finally, machine learning prediction of ALS cases using group lasso-selected metabolites achieved the best performance by regularised logistic regression with elastic net regularisation, with an area under the curve of 0.98 and specificity of 83%.

CONCLUSION

In our analysis, ALS led to significant metabolic pathway alterations, which had correlations to known ALS pathomechanisms in the basic and clinical literature, and may represent important targets for future ALS therapeutics.

Inbreeding Alters the Gut Microbiota of the Banna Minipig

Simple Summary

The mammalian gut microbiota is an indispensable part of host health. The gut microbiota plays a crucial role in nutrient digestibility, preventing colonization of pathogens and maintaining the host immune system. Host genetics has been conclusively shown to closely related to gut microbiota. Inbreeding can cause a decrease of the host’s genetic diversity, however, remarkably little is understood about the gut microbiota of pigs during inbreeding. The Banna minipig inbred is the world’s first successful large mammalian experimental animal inbred line since 1980 from full and half-siblings of the Diannan small-ear pig. Now, Banna minipig inbred has been inbred for over 37 generations, and the inbreeding coefficient is more than 99%. This study is the first to characterize and compare the composition and function of gut microbiota between the Diannan small-ear pig and Banna minipig inbred, aiming to better understand the influence of inbreeding on the gut microbiota.

Abstract

The gut microbiota coevolve with the host and can be stably transmitted to the offspring. Host genetics plays a crucial role in the composition and abundance of gut microbiota. Inbreeding can cause a decrease of the host’s genetic diversity and the heterozygosity. In this study, we used 16S rRNA gene sequencing to compare the differences of gut microbiota between the Diannan small-ear pig and Banna minipig inbred, aiming to understand the impact of inbreeding on the gut microbiota. Three dominant bacteria (Stenotrophlomonas, Streptococcus, and Lactobacillus) were steadily enriched in both the Diannan small-ear pig and Banna minipig inbred. After inbreeding, the gut microbiota alpha diversity and some potential probiotics (Bifidobacterium, Tricibacter, Ruminocaccae, Christensenellaceae, etc.) were significantly decreased, while the pathogenic Klebsiella bacteria was significantly increased. In addition, the predicted metagenomic analysis (PICRUSt2) indicated that several amino acid metabolisms (‘‘Valine, leucine, and isoleucine metabolism’’, ‘‘Phenylalanine, tyrosine, and tryptophan biosynthesis’’, ‘‘Histidine metabolism’’) were also markedly decreased after the inbreeding. Altogether our data reveal that host inbreeding altered the composition and the predicted function of the gut microbiome, which provides some data for the gut microbiota during inbreeding.

Circulating Metabolites as Potential Biomarkers for Neurological Disorders-Metabolites in Neurological Disorders

There are, still, limitations to predicting the occurrence and prognosis of neurological disorders. Biomarkers are molecules that can change in different conditions, a feature that makes them potential tools to improve the diagnosis of disease, establish a prognosis, and monitor treatments. Metabolites can be used as biomarkers, and are small molecules derived from the metabolic process found in different biological media, such as tissue samples, cells, or biofluids. They can be identified using various strategies, targeted or untargeted experiments, and by different techniques, such as high-performance liquid chromatography, mass spectrometry, or nuclear magnetic resonance. In this review, we aim to discuss the current knowledge about metabolites as biomarkers for neurological disorders. We will present recent developments that show the need and the feasibility of identifying such biomarkers in different neurological disorders, as well as discuss relevant research findings in the field of metabolomics that are helping to unravel the mechanisms underlying neurological disorders. Although several relevant results have been reported in metabolomic studies in patients with neurological diseases, there is still a long way to go for the clinical use of metabolites as potential biomarkers in these disorders, and more research in the field is needed.

Promoting identification of amyotrophic lateral sclerosis based on label-free plasma spectroscopy

Objective

Amyotrophic lateral sclerosis (ALS) is an adult‐onset fatal neurodegenerative disease which lacks identified biological markers. A label‐free plasma surface‐enhanced Raman spectroscopy (SERS) method was developed to explore a simple and noninvasive test for ALS.

Methods

ALS patients were enrolled serially and plasma samples were collected at the time of diagnosis prior to the start of ALS treatment. SERS spectra were recorded using a Renishaw micro‐Raman system.

Results

To exclude the interference by varying disease severity, we enrolled three groups of ALS patients, including ALS‐1 (n = 60; ALSFRS‐R ≥ 42 and time interval ≤ 12 months), ALS‐2 (n = 61; ALSFRS‐R < 42 and time interval ≤ 12 months), and ALS‐3 (n = 61; ALSFRS‐R ≥ 38 and time interval> 12 months). The SERS spectra were analyzed using principal component analysis (PCA), which showed that ALS‐1, ALS‐2, ALS‐3, and control groups were separated significantly. Then, decision tree (DT) models and receiver operating characteristic curves were employed and identified that bands at 722 and 739 cm⁻¹, and ratios of 635–722 cm⁻¹ and 635–739 cm⁻¹ were able to distinguish ALS from controls significantly. Finally, we highlighted six metabolism pathways correlated with ALS, including phenylalanine‐tyrosine‐tryptophan biosynthesis, aminoacyl‐tRNA biosynthesis, phenylalanine metabolism, pantothenate and CoA biosynthesis, porphyrin and chlorophyll metabolism, and pyrimidine metabolism.

Interpretation:

Plasma SERS could be a promising tool for the detection of ALS. The bands at 722 and 739 cm⁻¹, and the ratios of 635–722 cm⁻¹ and 635–739 cm⁻¹ could serve as potential indicator for ALS.

Why TDP-43? Why Not? Mechanisms of Metabolic Dysfunction in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a rapidly progressive and fatal neurodegenerative disorder for which there is no effective curative treatment available and minimal palliative care. Mutations in the gene encoding the TAR DNA-binding protein 43 (TDP-43) are a well-recognized genetic cause of ALS, and an imbalance in energy homeostasis correlates closely to disease susceptibility and progression. Considering previous research supporting a plethora of downstream cellular impairments originating in the histopathological signature of TDP-43, and the solid evidence around metabolic dysfunction in ALS, a causal association between TDP-43 pathology and metabolic dysfunction cannot be ruled out. Here we discuss how TDP-43 contributes on a molecular level to these impairments in energy homeostasis, and whether the protein's pathological effects on cellular metabolism differ from those of other genetic risk factors associated with ALS such as superoxide dismutase 1 (SOD1), chromosome 9 open reading frame 72 (C9orf72) and fused in sarcoma (FUS).

Bioprospection of Natural Sources of Polyphenols with Therapeutic Potential for Redox-Related Diseases

Plants are a reservoir of high-value molecules with underexplored biomedical applications. With the aim of identifying novel health-promoting attributes in underexplored natural sources, we scrutinized the diversity of (poly)phenols present within the berries of selected germplasm from cultivated, wild, and underutilized Rubus species. Our strategy combined the application of metabolomics, statistical analysis, and evaluation of (poly)phenols' bioactivity using a yeast-based discovery platform. We identified species as sources of (poly)phenols interfering with pathological processes associated with redox-related diseases, particularly, amyotrophic lateral sclerosis, cancer, and inflammation. In silico prediction of putative bioactives suggested cyanidin-hexoside as an anti-inflammatory molecule which was validated in yeast and mammalian cells. Moreover, cellular assays revealed that the cyanidin moiety was responsible for the anti-inflammatory properties of cyanidin-hexoside. Our findings unveiled novel (poly)phenolic bioactivities and illustrated the power of our integrative approach for the identification of dietary (poly)phenols with potential biomedical applications.

Metabolomics: A Tool to Understand the Impact of Genetic Mutations in Amyotrophic Lateral Sclerosis

Metabolomics studies performed in patients with amyotrophic lateral sclerosis (ALS) reveal a set of distinct metabolites that can shed light on the pathological alterations taking place in each individual. Metabolites levels are influenced by disease status, and genetics play an important role both in familial and sporadic ALS cases. Metabolomics analysis helps to unravel the differential impact of the most common ALS-linked genetic mutations (as C9ORF72, SOD1, TARDBP, and FUS) in specific signaling pathways. Further, studies performed in genetic models of ALS reinforce the role of TDP-43 pathology in the vast majority of ALS cases. Studies performed in differentiated cells from ALS-iPSC (induced Pluripotent Stem Cells) reveal alterations in the cell metabolism that are also found in ALS models and ultimately in ALS patients. The development of metabolomics approaches in iPSC derived from ALS patients allow addressing and ultimately understanding the pathological mechanisms taking place in any patient. Lately, the creation of a "patient in a dish" will help to identify patients that may benefit from specific treatments and allow the implementation of personalized medicine.

Prognostic analysis of amyotrophic lateral sclerosis based on clinical features and plasma surface-enhanced Raman spectroscopy

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a wide range of survival times. We aimed to explore prognostic factors related to short survival based on clinical features and plasma metabolic signatures using surface-enhanced Raman spectroscopy (SERS). One hundred and thirty-eight sporadic ALS cases were enrolled serially, including 62 for the short-duration group (≤3 years) and 76 for the long-duration group (>3 years). Multivariate analysis showed that an older age of onset (>60 years; odds ratio [OR] = 3.98, 95% CI: 1.09-14.53), lower body mass index (BMI) (<18.5; OR = 6.80, 95% CI: 1.36-33.92), and lower ALSFRS-R score (<35; OR = 6.03, 95% CI: 1.42-25.63) were associated with higher odds of tracheotomy or death, while a higher uric acid (UA) level showed a protective effect (>356.36 μmol/L; OR = 0.19, 95% CI: 0.05-0.73). SERS analysis showed significant differences between the two groups, and pathway analysis highlighted five main metabolic pathways, including metabolisms of glutathione, pyrimidine, phenylalanine, galactose, and phenylalanine-tyrosine-tryptophan biosynthesis. In conclusion, age of onset, BMI, ALSFRS-R score and UA, together with dysregulation of glucose, amino acid, nucleic acid, and antioxidant metabolism contributed to disease progression, and are therefore potential therapeutic targets for ALS.

Astrocyte alterations in neurodegenerative pathologies and their modeling in human induced pluripotent stem cell platforms

Astrocytes are the most abundant cell type in the brain. They were long considered only as passive support for neuronal cells. However, recent data have revealed many active roles for these cells both in maintenance of the normal physiological homeostasis in the brain as well as in neurodegeneration and disease. Moreover, human astrocytes have been found to be much more complex than their rodent counterparts, and to date, astrocytes are known to actively participate in a multitude of processes such as neurotransmitter uptake and recycling, gliotransmitter release, neuroenergetics, inflammation, modulation of synaptic activity, ionic balance, maintenance of the blood-brain barrier, and many other crucial functions of the brain. This review focuses on the role of astrocytes in human neurodegenerative disease and the potential of the novel stem cell-based platforms in modeling astrocytic functions in health and in disease.

A Systematic Review of Suggested Molecular Strata, Biomarkers and Their Tissue Sources in ALS

Amyotrophic lateral sclerosis (ALS), also known as motor neuron disease, is an incurable neurodegenerative condition, characterized by the loss of upper and lower motor neurons. It affects 1–1.8/100,000 individuals worldwide, and the number of cases is projected to increase as the population ages. Thus, there is an urgent need to identify both therapeutic targets and disease-specific biomarkers–biomarkers that would be useful to diagnose and stratify patients into different sub-groups for therapeutic strategies, as well as biomarkers to follow the efficacy of any treatment tested during clinical trials. There is a lack of knowledge about pathogenesis and many hypotheses. Numerous “omics” studies have been conducted on ALS in the past decade to identify a disease-signature in tissues and circulating biomarkers. The first goal of the present review was to group the molecular pathways that have been implicated in monogenic forms of ALS, to enable the description of patient strata corresponding to each pathway grouping. This strategy allowed us to suggest 14 strata, each potentially targetable by different pharmacological strategies. The second goal of this review was to identify diagnostic/prognostic biomarker candidates consistently observed across the literature. For this purpose, we explore previous biomarker-relevant “omics” studies of ALS and summarize their findings, focusing on potential circulating biomarker candidates. We systematically review 118 papers on biomarkers published during the last decade. Several candidate markers were consistently shared across the results of different studies in either cerebrospinal fluid (CSF) or blood (leukocyte or serum/plasma). Although these candidates still need to be validated in a systematic manner, we suggest the use of combinations of biomarkers that would likely reflect the “health status” of different tissues, including motor neuron health (e.g., pNFH and NF-L, cystatin C, Transthyretin), inflammation status (e.g., MCP-1, miR451), muscle health (miR-338-3p, miR-206) and metabolism (homocysteine, glutamate, cholesterol). In light of these studies and because ALS is increasingly perceived as a multi-system disease, the identification of a panel of biomarkers that accurately reflect features of pathology is a priority, not only for diagnostic purposes but also for prognostic or predictive applications.

Manganese-induced cellular disturbance in the baker's yeast, Saccharomyces cerevisiae with putative implications in neuronal dysfunction

Manganese (Mn) is an essential element, but in humans, chronic and/or acute exposure to this metal can lead to neurotoxicity and neurodegenerative disorders including Parkinsonism and Parkinson’s Disease by unclear mechanisms. To better understand the effects that exposure to Mn²⁺ exert on eukaryotic cell biology, we exposed a non-essential deletion library of the yeast Saccharomyces cerevisiae to a sub-inhibitory concentration of Mn²⁺ followed by targeted functional analyses of the positive hits. This screen produced a set of 43 sensitive deletion mutants that were enriched for genes associated with protein biosynthesis. Our follow-up investigations demonstrated that Mn reduced total rRNA levels in a dose-dependent manner and decreased expression of a β-galactosidase reporter gene. This was subsequently supported by analysis of ribosome profiles that suggested Mn-induced toxicity was associated with a reduction in formation of active ribosomes on the mRNAs. Altogether, these findings contribute to the current understanding of the mechanism of Mn-triggered cytotoxicity. Lastly, using the Comparative Toxicogenomic Database, we revealed that Mn shared certain similarities in toxicological mechanisms with neurodegenerative disorders including amyotrophic lateral sclerosis, Alzheimer’s, Parkinson’s and Huntington’s diseases.

The Metabolome and Osteoarthritis: Possible Contributions to Symptoms and Pathology

Osteoarthritis (OA) is a progressive, deteriorative disease of articular joints. Although traditionally viewed as a local pathology, biomarker exploration has shown that systemic changes can be observed. These include changes to cytokines, microRNAs, and more recently, metabolites. The metabolome is the set of metabolites within a biological sample and includes circulating amino acids, lipids, and sugar moieties. Recent studies suggest that metabolites in the synovial fluid and blood could be used as biomarkers for OA incidence, prognosis, and response to therapy. However, based on clinical, demographic, and anthropometric factors, the local synovial joint and circulating metabolomes may be patient specific, with select subsets of metabolites contributing to OA disease. This review explores the contribution of the local and systemic metabolite changes to OA, and their potential impact on OA symptoms and disease pathogenesis.

Disease-modifying effects of metabolic perturbations in ALS/FTLD

Amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) are two fatal neurodegenerative disorders with considerable clinical, pathological and genetic overlap. Both disorders are characterized by the accumulation of pathological protein aggregates that contain a number of proteins, most notably TAR DNA binding protein 43 kDa (TDP-43). Surprisingly, recent clinical studies suggest that dyslipidemia, high body mass index, and type 2 diabetes mellitus are associated with better clinical outcomes in ALS. Moreover, ALS and FTLD patients have a significantly lower incidence of cardiovascular disease, supporting the idea that an unfavorable metabolic profile may be beneficial in ALS and FTLD. The two most widely studied ALS/FTLD models, super-oxide dismutase 1 (SOD1) and TAR DNA binding protein of 43 kDA (TDP-43), reveal metabolic dysfunction and a positive effect of metabolic strategies on disease onset and/or progression. In addition, molecular studies reveal a role for ALS/FTLD-associated proteins in the regulation of cellular and whole-body metabolism. Here, we systematically evaluate these observations and discuss how changes in cellular glucose/lipid metabolism may result in abnormal protein aggregations in ALS and FTLD, which may have important implications for new treatment strategies for ALS/FTLD and possibly other neurodegenerative conditions.

A pharmaco-metabolomics approach in a clinical trial of ALS: Identification of predictive markers of progression

There is an urgent and unmet need for accurate biomarkers in Amyotrophic Lateral Sclerosis. A pharmaco-metabolomics study was conducted using plasma samples from the TRO19622 (olesoxime) trial to assess the link between early metabolomic profiles and clinical outcomes. Patients included in this trial were randomized into either Group O receiving olesoxime (n = 38) or Group P receiving placebo (n = 36). The metabolomic profile was assessed at time-point one (V1) and 12 months (V12) after the initiation of the treatment. High performance liquid chromatography coupled with tandem mass spectrometry was used to quantify 188 metabolites (Biocrates® commercial kit). Multivariate analysis based on machine learning approaches (i.e. Biosigner algorithm) was performed. Metabolomic profiles at V1 and V12 and changes in metabolomic profiles between V1 and V12 accurately discriminated between Groups O and P (p<5×10–6), and identified glycine, kynurenine and citrulline/arginine as the best predictors of group membership. Changes in metabolomic profiles were closely linked to clinical progression, and correlated with glutamine levels in Group P and amino acids, lipids and spermidine levels in Group O. Multivariate models accurately predicted disease progression and highlighted the discriminant role of sphingomyelins (SM C22:3, SM C24:1, SM OH C22:2, SM C16:1). To predict SVC from SM C24:1 in group O and SVC from SM OH C22:2 and SM C16:1 in group P+O, we noted a median sensitivity between 67% and 100%, a specificity between 66.7 and 71.4%, a positive predictive value between 66 and 75% and a negative predictive value between 70% and 100% in the test sets. This proof-of-concept study demonstrates that the metabolomics has a role in evaluating the biological effect of an investigational drug and may be a candidate biomarker as a secondary outcome measure in clinical trials.

Skeletal Muscle Pathophysiology: The Emerging Role of Spermine Oxidase and Spermidine

Skeletal muscle comprises approximately 40% of the total body mass. Preserving muscle health and function is essential for the entire body in order to counteract chronic diseases such as type II diabetes, cardiovascular diseases, and cancer. Prolonged physical inactivity, particularly among the elderly, causes muscle atrophy, a pathological state with adverse outcomes such as poor quality of life, physical disability, and high mortality. In murine skeletal muscle C2C12 cells, increased expression of the spermine oxidase (SMOX) enzyme has been found during cell differentiation. Notably, SMOX overexpression increases muscle fiber size, while SMOX reduction was enough to induce muscle atrophy in multiple murine models. Of note, the SMOX reaction product spermidine appears to be involved in skeletal muscle atrophy/hypertrophy. It is effective in reactivating autophagy, ameliorating the myopathic defects of collagen VI-null mice. Moreover, spermidine treatment, if combined with exercise, can affect D-gal-induced aging-related skeletal muscle atrophy. This review hypothesizes a role for SMOX during skeletal muscle differentiation and outlines its role and that of spermidine in muscle atrophy. The identification of new molecular pathways involved in the maintenance of skeletal muscle health could be beneficial in developing novel therapeutic lead compounds to treat muscle atrophy.

Global Metabolic Profiling Identifies a Pivotal Role of Proline and Hydroxyproline Metabolism in Supporting Hypoxic Response in Hepatocellular Carcinoma

Purpose: Metabolic reprogramming is frequently identified in hepatocellular carcinoma (HCC), which is the most common type of liver malignancy. The reprogrammed cellular metabolisms promote tumor cell survival, proliferation, angiogenesis, and metastasis. However, the mechanisms of this process remain unclear in HCC.Experimental Design: The global nontargeted metabolic study in 69 paired hepatic carcinomas and adjacent tissue specimens was performed using capillary electrophoresis-time of flight mass spectrometry-based approach. Key findings were validated by targeted metabolomic approach. Biological studies were also performed to investigate the role of proline biosynthesis in HCC pathogenesis.Results: Proline metabolism was markedly changed in HCC tumor tissue, characterized with accelerated consumption of proline and accumulation of hydroxyproline, which significantly correlated with α-fetoprotein levels and poor prognosis in HCC. In addition, we found that hydroxyproline promoted hypoxia- and HIF-dependent phenotype in HCC. Moreover, we demonstrated that hypoxia activated proline biosynthesis via upregulation of ALDH18A1, subsequently leading to accumulation of hydroxyproline via attenuated PRODH2 activity. More importantly, we showed that glutamine, proline, and hydroxyproline metabolic axis supported HCC cell survival through modulating HIF1α stability in response to hypoxia. Finally, inhibition of proline biosynthesis significantly enhanced cytotoxicity of sorafenib in vitro and in vivoConclusions: Our results demonstrate that hypoxic microenvironment activates proline metabolism, resulting in accumulation of hydroxyproline that promotes HCC tumor progression and sorafenib resistance through modulating HIF1α. These findings provide the proof of concept for targeting proline metabolism as a potential therapeutic strategy for HCC. Clin Cancer Res; 24(2); 474-85. ©2017 AACR.

Lipidomics Reveals Cerebrospinal-Fluid Signatures of ALS

Amyotrophic lateral sclerosis (ALS), the commonest adult-onset motor neuron disorder, is characterized by a survival span of only 2–5 years after onset. Relevant biomarkers or specific metabolic signatures would provide powerful tools for the management of ALS. The main objective of this study was to investigate the cerebrospinal fluid (CSF) lipidomic signature of ALS patients by mass spectrometry to evaluate the diagnostic and predictive values of the profile. We showed that ALS patients (n = 40) displayed a highly significant specific CSF lipidomic signature compared to controls (n = 45). Phosphatidylcholine PC(36:4), higher in ALS patients (p = 0.0003) was the most discriminant molecule, and ceramides and glucosylceramides were also highly relevant. Analysis of targeted lipids in the brain cortex of ALS model mice confirmed the role of some discriminant lipids such as PC. We also obtained good models for predicting the variation of the ALSFRS-r score from the lipidome baseline, with an accuracy of 71% in an independent set of patients. Significant predictions of clinical evolution were found to be correlated to sphingomyelins and triglycerides with long-chain fatty acids. Our study, which shows extensive lipid remodelling in the CSF of ALS patients, provides a new metabolic signature of the disease and its evolution with good predictive performance.