Metabolomics of mammalian brain reveals regional differences

In-Depth Chemical Analysis of the Brain Extracellular Space Using In Vivo Microdialysis with Liquid Chromatography-Tandem Mass Spectrometry

Metabolomic analysis of samples acquired in vivo from the brain extracellular space by microdialysis sampling can provide insights into chemical underpinnings of a given brain state and how it changes over time. Small sample volumes and low physiological concentrations have limited the identification of compounds from this compartment, so at present, we have scant knowledge of its composition. As a result, most in vivo measurements have limited depth of analysis. Here, we describe an approach to (1) identify hundreds of compounds in brain dialysate and (2) routinely detect many of these compounds in 5 μL microdialysis samples to enable deep monitoring of brain chemistry in time-resolved studies. Dialysate samples collected over 12 h were concentrated 10-fold and then analyzed using liquid chromatography with iterative tandem mass spectrometry (LC-MS/MS). Using this approach on dialysate from the rat striatum with both reversed-phase and hydrophilic interaction liquid chromatography yielded 479 unique compound identifications. 60% of the identified compounds could be detected in 5 μL of dialysate without further concentration using a single 20 min LC-MS analysis, showing that once identified, most compounds can be detected using small sample volumes and shorter analysis times compatible with routine in vivo monitoring. To detect more neurochemicals, LC-MS analysis of dialysate derivatized with light and isotopically labeled benzoyl chloride was employed. 872 nondegenerate benzoylated features were detected with this approach, including most small-molecule neurotransmitters and several metabolites involved in dopamine metabolism. This strategy allows deeper annotation of the brain extracellular space than previously possible and provides a launching point for defining the chemistry underlying brain states.

Multiscale metabolomics techniques: Insights into neuroscience research

The field of metabolomics examines the overall composition and dynamic patterns of metabolites in living organisms. The primary methods used in metabolomics include liquid chromatography (LC), nuclear magnetic resonance (NMR), and mass spectrometry (MS) analysis. These methods enable the identification and examination of metabolite types and contents within organisms, as well as modifications to metabolic pathways and their connection to the emergence of diseases. Research in metabolomics has extensive value in basic and applied sciences. The field of metabolomics is growing quickly, with the majority of studies concentrating on biomedicine, particularly early disease diagnosis, therapeutic management of human diseases, and mechanistic knowledge of biochemical processes. Multiscale metabolomics is an approach that integrates metabolomics techniques at various scales, including the holistic, tissue, cellular, and organelle scales, to enable more thorough and in-depth studies of metabolic processes in organisms. Multiscale metabolomics can be combined with methods from systems biology and bioinformatics. In recent years, multiscale metabolomics approaches have become increasingly important in neuroscience research due to the nervous system's high metabolic demands. Multiscale metabolomics can offer novel concepts and approaches for the diagnosis, treatment, and development of medication for neurological illnesses in addition to a more thorough understanding of brain metabolism and nervous system function. In this review, we summarize the use of multiscale metabolomics techniques in neuroscience, address the promise and constraints of these techniques, and provide an overview of the metabolome and its applications in neuroscience.

Luteolin alleviates depression-like behavior by modulating glycerophospholipid metabolism in the hippocampus and prefrontal cortex of LOD rats

BACKGROUND

Late-onset depression (LOD) is defined as primary depression that first manifests after the age of 65. Luteolin (LUT) is a natural flavonoid that has shown promising antidepressant effects and improvement in neurological function in previous studies.

AIMS

In this study, we utilized UPLC-MS/MS non-targeted metabolomics techniques, along with molecular docking technology and experimental validation, to explore the mechanism of LUT in treating LOD from a metabolomics perspective.

RESULTS

The behavioral results of our study demonstrate that LUT significantly ameliorated anxiety and depression-like behaviors while enhancing cognitive function in LOD rats. Metabolomic analysis revealed that the effects of LUT on LOD rats were primarily mediated through the glycerophospholipid metabolic pathway in the hippocampus and prefrontal cortex. The levels of key lipid metabolites, phosphatidylserine (PS), phosphatidylcholine (PC), and phosphatidylethanolamine (PE), in the glycerophospholipid metabolic pathway were significantly altered by LUT treatment, with PC and PE showing significant correlations with behavioral indices. Molecular docking analysis indicated that LUT had strong binding activity with phosphatidylserine synthase 1 (PTDSS1), phosphatidylserine synthase 2 (PTDSS2), and phosphatidylserine decarboxylase (PISD), which are involved in the transformation and synthesis of PC, PE, and PS. Lastly, our study explored the reasons for the opposing trends of PC, PE, and PS in the hippocampus and prefrontal cortex from the perspective of autophagy, which may be attributable to the bidirectional regulation of autophagy in distinct brain regions.

CONCLUSIONS

Our results revealed significant alterations in the glycerophospholipid metabolism pathways in both the hippocampus and prefrontal cortex of LOD rats. Moreover, LUT appears to regulate autophagy disorders by specifically modulating glycerophospholipid metabolism in different brain regions of LOD rats, consequently alleviating depression-like behavior in these animals.

A metabolome atlas of mouse brain on the global metabolic signature dynamics following short-term fasting

Calorie restriction (CR) or a fasting regimen is considered one of the most potent non-pharmacological interventions to prevent chronic metabolic disorders, ameliorate autoimmune diseases, and attenuate aging. Despite efforts, the mechanisms by which CR improves health, particularly brain health, are still not fully understood. Metabolic homeostasis is vital for brain function, and a detailed metabolome atlas of the brain is essential for understanding the networks connecting different brain regions. Herein, we applied gas chromatography-mass spectrometry-based metabolomics and lipidomics, covering 797 structurally annotated metabolites, to investigate the metabolome of seven brain regions in fasted (3, 6, 12, and 24 h) and ad libitum fed mice. Using multivariate and univariate statistical techniques, we generated a metabolome atlas of mouse brain on the global metabolic signature dynamics across multiple brain regions following short-term fasting (STF). Significant metabolic differences across brain regions along with STF-triggered region-dependent metabolic remodeling were identified. We found that STF elicited triacylglycerol degradation and lipolysis to compensate for energy demand under fasting conditions. Besides, changes in amino acid profiles were observed, which may play crucial roles in the regulation of energy metabolism, neurotransmitter signaling, and anti-inflammatory and antioxidant in response to STF. Additionally, this study reported, for the first time, that STF triggers a significant elevation of N-acylethanolamines, a class of neuroprotective lipids, in the brain and liver. These findings provide novel insights into the molecular basis and mechanisms of CR and offer a comprehensive resource for further investigation.

Mass spectrometry imaging as an emerging tool for studying metabolism in human brain organoids

Human brain organoids are emerging models to study human brain development and pathology as they recapitulate the development and characteristics of major neural cell types, and enable manipulation through an in vitro system. Over the past decade, with the advent of spatial technologies, mass spectrometry imaging (MSI) has become a prominent tool for metabolic microscopy, providing label-free, non-targeted molecular and spatial distribution information of the metabolites within tissue, including lipids. This technology has never been used for studies of brain organoids and here, we set out to develop a standardized protocol for preparation and mass spectrometry imaging of human brain organoids. We present an optimized and validated sample preparation protocol, including sample fixation, optimal embedding solution, homogenous deposition of matrices, data acquisition and processing to maximize the molecular information derived from mass spectrometry imaging. We focus on lipids in organoids, as they play critical roles during cellular and brain development. Using high spatial and mass resolution in positive- and negative-ion modes, we detected 260 lipids in the organoids. Seven of them were uniquely localized within the neurogenic niches or rosettes as confirmed by histology, suggesting their importance for neuroprogenitor proliferation. We observed a particularly striking distribution of ceramide-phosphoethanolamine CerPE 36:1; O2 which was restricted within rosettes and of phosphatidyl-ethanolamine PE 38:3, which was distributed throughout the organoid tissue but not in rosettes. This suggests that ceramide in this particular lipid species might be important for neuroprogenitor biology, while its removal may be important for terminal differentiation of their progeny. Overall, our study establishes the first optimized experimental pipeline and data processing strategy for mass spectrometry imaging of human brain organoids, allowing direct comparison of lipid signal intensities and distributions in these tissues. Further, our data shed new light on the complex processes that govern brain development by identifying specific lipid signatures that may play a role in cell fate trajectories. Mass spectrometry imaging thus has great potential in advancing our understanding of early brain development as well as disease modeling and drug discovery.

The role of selenium in shaping mice brain metabolome and selenoproteome through the gut-brain axis by combining metabolomics, metallomics, gene expression and amplicon sequencing

Selenium (Se) is a trace element crucial for human health. Recently, the impact of Se supplementation on gut microbiota has been pointed out as well as its influence on the expression of certain selenoproteins and gut metabolites. This study aims to elucidate the link between Se supplementation, brain selenoproteins and brain metabolome as well as the possible connection with the gut-brain axis. To this end, an in vivo study with 40 BALB/c mice was carried out. The study included conventional (n=20) and mice model with microbiota depleted by antibiotics (n=20) under a regular or Se supplemented diet. Brain selenoproteome was determined by a transcriptomic/gene expression profile, while brain metabolome and gut microbiota profiles were accomplished by untargeted metabolomics and amplicon sequencing, respectively. The total content of Se in brain was also determined. The selenoproteins genes Dio and Gpx isoenzymes, SelenoH, SelenoI, SelenoT, SelenoV and SelenoW and 31 metabolites were significantly altered in the brain after Se supplementation in conventional mice, while 11 selenoproteins and 26 metabolites were altered in microbiota depleted mice. The main altered brain metabolites were related to glyoxylate and dicarboxylate metabolism, amino acid metabolism, and gut microbiota that have been previously related with the gut-brain axis (e.g., members of Lachnospiraceae and Ruminococcaceae families). Moreover, specific associations were determined between brain selenoproteome and metabolome, which correlated with the same bacteria, suggesting an intertwined mechanism. Our results demonstrated the effect of Se on brain metabolome through specific selenoproteins gene expression and gut microbiota.

Brain regions show different metabolic and protein arginine methylation phenotypes in frontotemporal dementias and Alzheimer's disease

Frontotemporal dementia (FTD) is a heterogeneous neurodegenerative disease with multiple histopathological subtypes. FTD patients share similar symptoms with Alzheimer's disease (AD). Hence, FTD patients are commonly misdiagnosed as AD, despite the consensus clinical diagnostic criteria. It is therefore of great clinical need to identify a biomarker that can distinguish FTD from AD and control individuals, and potentially further differentiate between FTD pathological subtypes. We conducted a metabolomic analysis on post-mortem human brain tissue from three regions: cerebellum, frontal cortex and occipital cortex from control, FTLD-TDP type A, type A-C9, type C and AD. Our results indicate that the brain subdivisions responsible for different functions show different metabolic patterns. We further explored the region-specific metabolic characteristics of different FTD subtypes and AD patients. Different FTD subtypes and AD share similar metabolic phenotypes in the cerebellum, but AD exhibited distinct metabolic patterns in the frontal and occipital regions compared to FTD. The identified brain region-specific metabolite biomarkers could provide a tool for distinguishing different FTD subtypes and AD and provide the first insights into the metabolic changes of FTLD-TDP type A, type A-C9, type C and AD in different regions of the brain. The importance of protein arginine methylation in neurodegenerative disease has come to light, so we investigated whether the arginine methylation level contributes to disease pathogenesis. Our findings provide new insights into the relationship between arginine methylation and metabolic changes in FTD subtypes and AD that could be further explored, to study the molecular mechanism of pathogenesis.

Defining the pig microglial transcriptome reveals its core signature, regional heterogeneity, and similarity with human and rodent microglia

Microglia play key roles in brain homeostasis as well as responses to neurodegeneration and neuroinflammatory processes caused by physical disease and psychosocial stress. The pig is a physiologically relevant model species for studying human neurological disorders, many of which are associated with microglial dysfunction. Furthermore, pigs are an important agricultural species, and there is a need to understand how microglial function affects their welfare. As a basis for improved understanding to enhance biomedical and agricultural research, we sought to characterize pig microglial identity at genome-wide scale and conduct inter-species comparisons. We isolated pig hippocampal tissue and microglia from frontal cortex, hippocampus, and cerebellum, as well as alveolar macrophages from the lungs and conducted RNA-sequencing (RNAseq). By comparing the transcriptomic profiles between microglia, macrophages, and hippocampal tissue, we derived a set of 239 highly enriched genes defining the porcine core microglial signature. We found brain regional heterogeneity based on 150 genes showing significant (adjusted p < 0.01) regional variations and that cerebellar microglia were most distinct. We compared normalized gene expression for microglia from human, mice and pigs using microglia signature gene lists derived from each species and demonstrated that a core microglial marker gene signature is conserved across species, but that species-specific expression subsets also exist. Our data provide a valuable resource defining the pig microglial transcriptome signature that validates and highlights pigs as a useful large animal species bridging between rodents and humans in which to study the role of microglia during homeostasis and disease.

Metabolomics detects clinically silent neuroinflammatory lesions earlier than neurofilament-light chain in a focal multiple sclerosis animal model

Background

Despite widespread searches, there are currently no validated biofluid markers for the detection of subclinical neuroinflammation in multiple sclerosis (MS). The dynamic nature of human metabolism in response to changes in homeostasis, as measured by metabolomics, may allow early identification of clinically silent neuroinflammation. Using the delayed-type hypersensitivity (DTH) MS rat model, we investigated the serum and cerebrospinal fluid (CSF) metabolomics profiles and neurofilament-light chain (NfL) levels, as a putative marker of neuroaxonal damage, arising from focal, clinically silent neuroinflammatory brain lesions and their discriminatory abilities to distinguish DTH animals from controls.

Methods

¹H nuclear magnetic resonance (NMR) spectroscopy metabolomics and NfL measurements were performed on serum and CSF at days 12, 28 and 60 after DTH lesion initiation. Supervised multivariate analyses were used to determine metabolomics differences between DTH animals and controls. Immunohistochemistry was used to assess the extent of neuroinflammation and tissue damage.

Results

Serum and CSF metabolomics perturbations were detectable in DTH animals (vs. controls) at all time points, with the greatest change occurring at the earliest time point (day 12) when the neuroinflammatory response was most intense (mean predictive accuracy [SD]—serum: 80.6 [10.7]%, p < 0.0001; CSF: 69.3 [13.5]%, p < 0.0001). The top discriminatory metabolites at day 12 (serum: allantoin, cytidine; CSF: glutamine, glucose) were all reduced in DTH animals compared to controls, and correlated with histological markers of neuroinflammation, particularly astrogliosis (Pearson coefficient, r—allantoin: r = − 0.562, p = 0.004; glutamine: r = − 0.528, p = 0.008). Serum and CSF NfL levels did not distinguish DTH animals from controls at day 12, rather, significant differences were observed at day 28 (mean [SEM]—serum: 38.5 [4.8] vs. 17.4 [2.6] pg/mL, p = 0.002; CSF: 1312.0 [379.1] vs. 475.8 [74.7] pg/mL, p = 0.027). Neither serum nor CSF NfL levels correlated with markers of neuroinflammation; serum NfL did, however, correlate strongly with axonal loss (r = 0.641, p = 0.001), but CSF NfL did not (p = 0.137).

Conclusions

While NfL levels were elevated later in the pathogenesis of the DTH lesion, serum and CSF metabolomics were able to detect early, clinically silent neuroinflammation and are likely to present sensitive biomarkers for the assessment of subclinical disease activity in patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12974-022-02614-8.

Sex-specific differences in zebrafish brains

In this systematic review, we highlight the differences between the male and female zebrafish brains to understand their differentiation and their use in studying sex-specific neurological diseases. Male and female brains display subtle differences at the cellular level which may be important in driving sex-specific signaling. Sex differences in the brain have been observed in humans as well as in non-human species. However, the molecular mechanisms of brain sex differentiation remain unclear. The classical model of brain sex differentiation suggests that the steroid hormones derived from the gonads are the primary determinants in establishing male and female neural networks. Recent studies indicate that the developing brain shows sex-specific differences in gene expression prior to gonadal hormone action. Hence, genetic differences may also be responsible for differentiating the brain into male and female types. Understanding the signaling mechanisms involved in brain sex differentiation could help further elucidate the sex-specific incidences of certain neurological diseases. The zebrafish model could be appropriate for enhancing our understanding of brain sex differentiation and the signaling involved in neurological diseases. Zebrafish brains show sex-specific differences at the hormonal level, and recent advances in RNA sequencing have highlighted critical sex-specific differences at the transcript level. The differences are also evident at the cellular and metabolite levels, which could be important in organizing sex-specific neuronal signaling. Furthermore, in addition to having one ortholog for 70% of the human gene, zebrafish also shares brain structural similarities with other higher eukaryotes, including mammals. Hence, deciphering brain sex differentiation in zebrafish will help further enhance the diagnostic and pharmacological intervention of neurological diseases.

Post-Stroke Administration of the p75 Neurotrophin Receptor Modulator, LM11A-31, Attenuates Chronic Changes in Brain Metabolism, Increases Neurotransmitter Levels, and Improves Recovery

The aim of this study was to test whether poststroke oral administration of a small molecule p75 neurotrophin receptor (p75NTR) modulator (LM11A-31) can augment neuronal survival and improve recovery in a mouse model of stroke. Mice were administered LM11A-31 for up to 12 weeks, beginning 1 week after stroke. Metabolomic analysis revealed that after 2 weeks of daily treatment, mice that received LM11A-31 were distinct from vehicle-treated mice by principal component analysis and had higher levels of serotonin, acetylcholine, and dopamine in their ipsilateral hemisphere. LM11A-31 treatment also improved redox homeostasis by restoring reduced glutathione. It also offset a stroke-induced reduction in glycolysis by increasing acetyl-CoA. There was no effect on cytokine levels in the infarct. At 13 weeks after stroke, adaptive immune cell infiltration in the infarct was unchanged in LM11A-31-treated mice, indicating that LM11A-31 does not alter the chronic inflammatory response to stroke at the site of the infarct. However, LM11A-31-treated mice had less brain atrophy, neurodegeneration, tau pathology, and microglial activation in other regions of the ipsilateral hemisphere. These findings correlated with improved recovery of motor function on a ladder test, improved sensorimotor and cognitive abilities on a nest construction test, and less impulsivity in an open field test. These data support small molecule modulation of the p75NTR for preserving neuronal health and function during stroke recovery. SIGNIFICANCE STATEMENT: The findings from this study introduce the p75 neurotrophin receptor as a novel small molecule target for promotion of stroke recovery. Given that LM11A-31 is in clinical trials as a potential therapy for Alzheimer's disease, it could be considered as a candidate for assessment in stroke or vascular dementia studies.

Small phenolic and indolic gut-dependent molecules in the primate central nervous system: levels vs. bioactivity

INTRODUCTION

A rapidly growing body of data documents associations between disease of the brain and small molecules generated by gut-microbiota (GMB). While such metabolites can affect brain function through a variety of mechanisms, the most direct action would be on the central nervous system (CNS) itself.

OBJECTIVE

Identify indolic and phenolic GMB-dependent small molecules that reach bioactive concentrations in primate CNS.

METHODS

We conducted a PubMed search for metabolomic studies of the primate CNS [brain tissue or cerebrospinal fluid (CSF)] and then selected for phenolic or indolic metabolites that (i) had been quantified, (ii) were GMB-dependent. For each chemical we then conducted a search for studies of bioactivity conducted in vitro in human cells of any kind or in CNS cells from the mouse or rat.

RESULTS

36 metabolites of interests were identified in primate CNS through targeted metabolomics. Quantification was available for 31/36 and in vitro bioactivity for 23/36. The reported CNS range for 8 metabolites 2-(3-hydroxyphenyl)acetic acid, 2-(4-hydroxyphenyl)acetic acid, 3-(3-hydroxyphenyl)propanoic acid, (E)-3-(3,4-dihydroxyphenyl)prop-2-enoic acid [caffeic acid], 3-hydroxybenzoic acid, 4-hydroxybenzoic acid, 2-acetamido-3-(1H-indol-3-yl)propanoic acid [N-acetyltryptophan], 1H-indol-3-yl hydrogen sulfate [indoxyl-3-sulfate] overlapped with a bioactive concentration. However, the number and quality of relevant studies of CNS neurochemistry as well as of bioactivity were highly limited. Structural isomers, multiple metabolites and potential confounders were inadequately considered.

CONCLUSION

The potential direct bioactivity of GMB-derived indolic and phenolic molecules on primate CNS remains largely unknown. The field requires additional strategies to identify and prioritize screening of the most promising small molecules that enter the CNS.

Regional Brain Analysis of Modified Amino Acids and Dipeptides during the Sleep/Wake Cycle

Sleep is a state in which important restorative and anabolic processes occur. Understanding changes of these metabolic processes during the circadian rhythm in the brain is crucial to elucidate neurophysiological mechanisms important for sleep function. Investigation of amino acid modifications and dipeptides has recently emerged as a valuable approach in the metabolic profiling of the central nervous system. Nonetheless, very little is known about the effects of sleep on the brain levels of amino acid analogues. In the present study, we examined brain regional sleep-induced alterations selective for modified amino acids and dipeptides using Ultra-high performance liquid chromatography-MS/MS (UHPLC-MS/MS) based metabolomics. Our approach enabled the detection and identification of numerous amino acid-containing metabolites in the cortex, the hippocampus, the midbrain, and the cerebellum. In particular, analogues of the aromatic amino acids phenylalanine, tyrosine and tryptophan were significantly altered during sleep in the investigated brain regions. Cortical levels of medium and long chain N-acyl glycines were higher during sleep. Regional specific changes were also detected, especially related to tyrosine analogues in the hippocampus and the cerebellum. Our findings demonstrate a strong correlation between circadian rhythms and amino acid metabolism specific for different brain regions that provide previously unknown insights in brain metabolism.

Differential regulation of oxidative stress, microbiota-derived, and energy metabolites in the mouse brain during sleep

Sleep has evolved as a universal core function to allow for restorative biological processes. Detailed knowledge of metabolic changes necessary for the sleep state in the brain is missing. Herein, we have performed an in-depth metabolic analysis of four mouse brain regions and uncovered region-specific circadian variations. Metabolites linked to oxidative stress were altered during sleep including acylcarnitines, hydroxylated fatty acids, phenolic compounds, and thiol-containing metabolites. These findings provide molecular evidence of a significant metabolic shift of the brain energy metabolism. Specific alterations were observed for brain metabolites that have previously not been associated with a circadian function including the microbiome-derived metabolite ergothioneine that suggests a regulatory function. The pseudopeptide β-citryl-glutamate has been linked to brain development and we have now discovered a previously unknown regioisomer. These metabolites altered by the circadian rhythm represent the foundation for hypothesis-driven studies of the underlying metabolic processes and their function.

Exploring the metabolomic profile of cerebellum after exposure to acute stress

Psychological stress and stress-related disorders constitute a major health problem in modern societies. Although the brain circuits involved in emotional processing are intensively studied, little is known about the implication of cerebellum in stress responses whereas the molecular changes induced by stress exposure in cerebellum remain largely unexplored. Here, we investigated the effects of acute stress exposure on mouse cerebellum. We used a forced swim test (FST) paradigm as an acute stressor. We then analyzed the cerebellar metabolomic profiles of stressed (n = 11) versus control (n = 11) male CD1 mice by a Nuclear Magnetic Resonance (NMR)-based, untargeted metabolomics approach. Our results showed altered levels of 19 out of the 47 annotated metabolites, which are implicated in neurotransmission and N-acetylaspartic acid (NAA) turnover, as well as in energy and purine/pyrimidine metabolism. We also correlated individual metabolite levels with FST behavioral parameters, and reported associations between FST readouts and levels of 4 metabolites. This work indicates an altered metabolomic signature after acute stress in the cerebellum and highlights a previously unexplored involvement of cerebellum in stress responses.

A metabolome atlas of the aging mouse brain

The mammalian brain relies on neurochemistry to fulfill its functions. Yet, the complexity of the brain metabolome and its changes during diseases or aging remain poorly understood. Here, we generate a metabolome atlas of the aging wildtype mouse brain from 10 anatomical regions spanning from adolescence to old age. We combine data from three assays and structurally annotate 1,547 metabolites. Almost all metabolites significantly differ between brain regions or age groups, but not by sex. A shift in sphingolipid patterns during aging related to myelin remodeling is accompanied by large changes in other metabolic pathways. Functionally related brain regions (brain stem, cerebrum and cerebellum) are also metabolically similar. In cerebrum, metabolic correlations markedly weaken between adolescence and adulthood, whereas at old age, cross-region correlation patterns reflect decreased brain segregation. We show that metabolic changes can be mapped to existing gene and protein brain atlases. The brain metabolome atlas is publicly available ( https://mouse.atlas.metabolomics.us/ ) and serves as a foundation dataset for future metabolomic studies.

Multiblock metabolomics: An approach to elucidate whole-body metabolism with multiblock principal component analysis

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“Multiblock metabolomics” elucidates the global metabolic network in a whole body.

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“Multiblock metabolomics” combines LC/MS-based metabolomics with multiblock PCA.

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“Multiblock metabolomics” highlights and elicits organ-specific metabolism.

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TGs with less unsaturated fatty acids were highly accumulated in the diabetic liver.

Principal component analysis (PCA) is a useful tool for omics analysis to identify underlying factors and visualize relationships between biomarkers. However, this approach is limited in addressing life complexity and further improvement is required. This study aimed to develop a new approach that combines mass spectrometry-based metabolomics with multiblock PCA to elucidate the whole-body global metabolic network, thereby generating comparable metabolite maps to clarify the metabolic relationships among several organs. To evaluate the newly developed method, Zucker diabetic fatty (ZDF) rats (n = 6) were used as type 2 diabetic models and Sprague Dawley (SD) rats (n = 6) as controls. Metabolites in the heart, kidney, and liver were analyzed by capillary electrophoresis and liquid chromatography mass spectrometry, respectively, and the detected metabolites were analyzed by multiblock PCA. More than 300 metabolites were detected in the heart, kidney, and liver. When the metabolites obtained from the three organs were analyzed with multiblock PCA, the score and loading maps obtained were highly synchronized and their metabolism patterns were visually comparable. A significant finding in this study was the different expression patterns in lipid metabolism among the three organs; notably triacylglycerols with polyunsaturated fatty acids or less unsaturated fatty acids showed specific accumulation patterns depending on the organs.

Stop the rot. Enzyme inactivation at brain harvest prevents artifacts: A guide for preservation of the in vivo concentrations of brain constituents

Post-mortem metabolism is widely recognized to cause rapid and prolonged changes in the concentrations of multiple classes of compounds in brain, that is, they are labile. Post-mortem changes from levels in living brain include components of pathways of metabolism of glucose and energy compounds, amino acids, lipids, signaling molecules, neuropeptides, phosphoproteins, and proteins. Methods that stop enzyme activity at brain harvest were developed almost 50 years ago and have been extensively used in studies of brain functions and diseases. Unfortunately, these methods are not commonly used to harvest brain tissue for mass spectrometry-based metabolomic studies or for imaging mass spectrometry studies (IMS, also called mass spectrometry imaging, MSI, or matrix-assisted laser desorption/ionization-MSI, MALDI-MSI). Instead these studies commonly kill animals, decapitate, dissect out brain and regions of interest if needed, then 'snap' freeze the tissue to stop enzymatic activity after harvest, with post-mortem intervals typically ranging from ~0.5 to 3 min. To increase awareness of the importance of stopping metabolism at harvest and preventing the unnecessary complications of not doing so, this commentary provides examples of labile metabolites and the magnitudes of their post-mortem changes in concentrations during brain harvest. Brain harvest methods that stop metabolism at harvest eliminate post-mortem enzymatic activities and can improve characterization of normal and diseased brain. In addition, metabolomic studies would be improved by reporting absolute units of concentration along with normalized peak areas or fold changes. Then reported values can be evaluated and compared with the extensive neurochemical literature to help prevent reporting of artifactual data.

The Status of Bile Acids and Farnesoid X Receptor in Brain and Liver of Rats with Thioacetamide-Induced Acute Liver Failure

Acute liver failure (ALF) leads to neurological symptoms defined as hepatic encephalopathy (HE). Although accumulation of ammonia and neuroinflammation are generally accepted as main contributors to HE pathomechanism, a buildup of bile acids (BA) in the blood is a frequent component of liver injury in HE patients. Recent studies have identified the nuclear farnesoid X receptor (FXR) acting via small heterodimer partner (SHP) as a mediator of BA-induced effects in the brain of ALF animals. The present study investigated the status of the BA–FXR axis in the brain and the liver, including selective changes in pertinent genes in thioacetamide (TAA)-induced ALF in Sprague–Dawley rats. FXR was found in rat neurons, confirming earlier reports for mouse and human brain. BA accumulated in blood but not in the brain tissue. Expression of mRNAs coding for Fxr and Shp was reduced in the hippocampus and of Fxr mRNA also in the cerebellum. Changes in Fxr mRNA levels were not followed by changes in FXR protein. The results leave open the possibility that mobilization of the BA–FXR axis in the brain may not be necessarily pathognomonic to HE but may depend upon ALF-related confounding factors.

Metabolomic and Imaging Mass Spectrometric Assays of Labile Brain Metabolites: Critical Importance of Brain Harvest Procedures

Metabolomic technologies including imaging mass spectrometry (IMS; also called mass spectrometry imaging, MSI, or matrix-assisted laser desorption/ionization-mass spectrometry imaging, MALDI MSI) are important methods to evaluate levels of many compounds in brain with high spatial resolution, characterize metabolic phenotypes of brain disorders, and identify disease biomarkers. ATP is central to brain energetics, and reports of its heterogeneous distribution in brain and regional differences in ATP/ADP ratios reported in IMS studies conflict with earlier studies. These discordant data were, therefore, analyzed and compared with biochemical literature that used rigorous methods to preserve labile metabolites. Unequal, very low regional ATP levels and low ATP/ADP ratios are explained by rapid metabolism during postmortem ischemia. A critical aspect of any analysis of brain components is their stability during and after tissue harvest so measured concentrations closely approximate their physiological levels in vivo. Unfortunately, the requirement for inactivation of brain enzymes by freezing or heating is not widely recognized outside the neurochemistry discipline, and procedures that do not prevent postmortem autolysis, including decapitation, brain removal/dissection, and 'snap freezing' are commonly used. Strong emphasis is placed on use of supplementary approaches to calibrate metabolite abundance in units of concentration in IMS studies and comparison of IMS results with biochemical data obtained by different methods to help identify potential artifacts.

Engineered Perineural Vascular Plexus for Modeling Developmental Toxicity

There is a vital need to develop in vitro models of the developing human brain to recapitulate the biological effects that toxic compounds have on the brain. To model perineural vascular plexus (PNVP) in vitro, which is a key stage in embryonic development, human embryonic stem cells (hESC)-derived endothelial cells (ECs), neural progenitor cells, and microglia (MG) with primary pericytes (PCs) in synthetic hydrogels in a custom-designed microfluidics device are cocultured. The formation of a vascular plexus that includes networks of ECs (CD31+, VE-cadherin+), MG (IBA1+), and PCs (PDGFRβ+), and an overlying neuronal layer that includes differentiated neuronal cells (βIII Tubulin+, GFAP+) and radial glia (Nestin+, Notch2NL+), are characterized. Increased brain-derived neurotrophic factor secretion and differential metabolite secretion by the vascular plexus and the neuronal cells over time are consistent with PNVP functionality. Multiple concentrations of developmental toxicants (teratogens, microglial disruptor, and vascular network disruptors) significantly reduce the migration of ECs and MG toward the neuronal layer, inhibit formation of the vascular network, and decrease vascular endothelial growth factor A (VEGFA) secretion. By quantifying 3D cell migration, metabolic activity, vascular network disruption, and cytotoxicity, the PNVP model may be a useful tool to make physiologically relevant predictions of developmental toxicity.

Imaging Mass Spectrometry: A New Tool to Assess Molecular Underpinnings of Neurodegeneration

Neurodegenerative diseases are prevalent and devastating. While extensive research has been done over the past decades, we are still far from comprehensively understanding what causes neurodegeneration and how we can prevent it or reverse it. Recently, systems biology approaches have led to a holistic examination of the interactions between genome, metabolome, and the environment, in order to shed new light on neurodegenerative pathogenesis. One of the new technologies that has emerged to facilitate such studies is imaging mass spectrometry (IMS). With its ability to map a wide range of small molecules with high spatial resolution, coupled with the ability to quantify them at once, without the need for a priori labeling, IMS has taken center stage in current research efforts in elucidating the role of the metabolome in driving neurodegeneration. IMS has already proven to be effective in investigating the lipidome and the proteome of various neurodegenerative diseases, such as Alzheimer's, Parkinson's, Huntington's, multiple sclerosis, and amyotrophic lateral sclerosis. Here, we review the IMS platform for capturing biological snapshots of the metabolic state to shed more light on the molecular mechanisms of the diseased brain.

The International Conference on Intelligent Biology and Medicine (ICIBM) 2018: systems biology on diverse data types

Between June 10–12, 2018, the International Conference on Intelligent Biology and Medicine (ICIBM 2018) was held in Los Angeles, California, USA. The conference included 11 scientific sessions, four tutorials, one poster session, four keynote talks and four eminent scholar talks that covered a wide range of topics in 3D genome structure analysis and visualization, next generation sequencing analysis, computational drug discovery, medical informatics, cancer genomics and systems biology. Systems biology has been a main theme in ICIBM 2018, with exciting advances presented in many areas of systems biology, covering various different data types such as gene regulation, circular RNAs expression, single-cell RNA-Seq, inter-chromosomal interactions, metabolomics, proteomics and phosphoproteomics. Here, we describe ten high quality papers to be published in BMC Systems Biology.