Cerebrospinal fluid metabolomics identifies 19 brain-related phenotype associations

Communications Biology, Год журнала: 2021, Номер 4(1)

Опубликована: Янв. 12, 2021

Abstract The study of metabolomics and disease has enabled the discovery new risk factors, diagnostic markers, drug targets. For neurological psychiatric phenotypes, cerebrospinal fluid (CSF) is particular importance. However, CSF metabolome difficult to on a large scale due relative complexity procedure needed collect fluid. Here, we present metabolome-wide association (MWAS), which uses genetic metabolomic data impute metabolites into samples with genome-wide summary statistics. We conduct metabolome-wide, analysis 338 metabolites, identifying 16 genotype-metabolite associations (metabolite quantitative trait loci, or mQTLs). then build prediction models for all available test 27 19 significant metabolite-phenotype associations. Our results demonstrate feasibility MWAS omic in scarce sample types.

Язык: Английский

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Genome-scale metabolic network reconstruction of model animals as a platform for translational research

Proceedings of the National Academy of Sciences, Год журнала: 2021, Номер 118(30)

Опубликована: Июль 19, 2021

Genome-scale metabolic models (GEMs) are used extensively for analysis of mechanisms underlying human diseases and malfunctions. However, the lack comprehensive high-quality GEMs model organisms restricts translational utilization omics data accumulating from use various disease models. Here we present a unified platform that covers five major animals, including Mouse1 (Mus musculus), Rat1 (Rattus norvegicus), Zebrafish1 (Danio rerio), Fruitfly1 (Drosophila melanogaster), Worm1 (Caenorhabditis elegans). These represent most coverage network by considering both orthology-based pathways species-specific reactions. All can be interactively queried via accompanying web portal Metabolic Atlas. Specifically, through integrative with RNA-sequencing brain tissues transgenic mice identified coordinated up-regulation lysosomal GM2 ganglioside peptide degradation which appears to signature alteration in Alzheimer's (AD) mouse phenotype amyloid precursor protein overexpression. This shift was further validated proteomics cerebrospinal fluid samples patients. The elevated enzymes thus hold potential as biomarker early diagnosis AD. Taken together, foresee this evolving open-source will serve an important resource facilitate development systems medicines biomedical applications.

Язык: Английский

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Multi-omics approaches for revealing the complexity of cardiovascular disease

Briefings in Bioinformatics, Год журнала: 2021, Номер 22(5)

Опубликована: Фев. 9, 2021

The development and progression of cardiovascular disease (CVD) can mainly be attributed to the narrowing blood vessels caused by atherosclerosis thrombosis, which induces organ damage that will result in end-organ dysfunction characterized events such as myocardial infarction or stroke. It is also essential consider other contributory factors CVD, including cardiac remodelling cardiomyopathies co-morbidities with diseases chronic kidney disease. Besides, there a growing amount evidence linking gut microbiota CVD through several metabolic pathways. Hence, it utmost importance decipher underlying molecular mechanisms associated these states elucidate CVD. A wide array systems biology approaches incorporating multi-omics data have emerged an invaluable tool establishing alterations specific cell types identifying modifications signalling promote development. Here, we review recent studies apply further understand causes provide possible treatment strategies novel drug targets biomarkers. We discuss very advances research emphasis on how diet microbial composition impact Finally, present various biological network analyses independent been employed for providing mechanistic explanation developing end-stage namely

Язык: Английский

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Networks and Graphs Discovery in Metabolomics Data Analysis and Interpretation

Frontiers in Molecular Biosciences, Год журнала: 2022, Номер 9

Опубликована: Март 8, 2022

Both targeted and untargeted mass spectrometry-based metabolomics approaches are used to understand the metabolic processes taking place in various organisms, from prokaryotes, plants, fungi animals humans. Untargeted allow detect as many metabolites possible at once, identify unexpected changes, characterize novel biological samples. However, identification of interpretation such large complex datasets remain challenging. One approach address these challenges is considering that connected through informative relationships. Such relationships can be formalized networks, where nodes correspond or features (when there no only partial identification), edges connect if corresponding related. Several networks built a single dataset (or list metabolites), each network represents different relationships, statistical (correlated biochemical (known putative substrates products reactions), chemical (structural similarities, ontological relations). Once built, they subsequently mined using algorithms graph) theory gain insights into metabolism. For instance, we based on prior knowledge enzymatic reactions, then provide suggestions for potential metabolite identifications, clusters co-regulated metabolites. In this review, first aim settling nomenclature formalism avoid confusion when referring field metabolomics. Then, present state art network-based methods data analysis, well future developments expected area. We cover use applications spectrometry features, structural correlations between also describe application reaction networks. Finally, discuss possibility combining analyze interpret them simultaneously.

Язык: Английский

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Systems-based approaches to study immunometabolism

Cellular and Molecular Immunology, Год журнала: 2022, Номер 19(3), С. 409 - 420

Опубликована: Фев. 4, 2022

Abstract Technical advances at the interface of biology and computation, such as single-cell RNA-sequencing (scRNA-seq), reveal new layers complexity in cellular systems. An emerging area investigation using systems approach is study metabolism immune cells. The diverse spectra cell phenotypes, sparsity numbers vivo, limitations number metabolites identified, dynamic nature metabolic fluxes, tissue specificity, high dependence on local milieu make investigations immunometabolism challenging, especially level. In this review, we define systemic immunometabolism, summarize cell- system-based approaches, introduce mathematical modeling approaches for interrogation changes We close review by discussing applications shortcomings techniques. With systems-oriented studies expected to become a mainstay immunological research, an understanding current toward will help investigators best use resources push boundaries discipline.

Язык: Английский

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Metastatic triple negative breast cancer adapts its metabolism to destination tissues while retaining key metabolic signatures

Proceedings of the National Academy of Sciences, Год журнала: 2022, Номер 119(35)

Опубликована: Авг. 22, 2022

Triple negative breast cancer (TNBC) metastases are assumed to exhibit similar functions in different organs as the original primary tumor. However, studies of metastasis often limited a comparison metastatic tumors with their origin, and little is known about adaptation local environment sites. We therefore used transcriptomic data metabolic network analyses investigate whether adapt metabolism site found that adopt signature some similarity destinations. The extent adaptation, however, varies across organs, retain signatures associated TNBC. Our findings suggest combination anti-metastatic approaches inhibitors selected specifically for sites, rather than solely targeting TNBC tumors, may constitute more effective treatment approach.

Язык: Английский

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Characterizing cancer metabolism from bulk and single-cell RNA-seq data using METAFlux

Nature Communications, Год журнала: 2023, Номер 14(1)

Опубликована: Авг. 12, 2023

Abstract Cells often alter metabolic strategies under nutrient-deprived conditions to support their survival and growth. Characterizing reprogramming in the tumor microenvironment (TME) is of emerging importance cancer research patient care. However, recent technologies only measure a subset metabolites cannot provide situ measurements. Computational methods such as flux balance analysis (FBA) have been developed estimate from bulk RNA-seq data can potentially be extended single-cell (scRNA-seq) data. it unclear how reliable current are, particularly TME characterization. Here, we present computational framework METAFlux (METAbolic Flux analysis) infer fluxes or transcriptomic Large-scale experiments using cell-lines, genome atlas (TCGA), scRNA-seq obtained diverse immunotherapeutic contexts, including CAR-NK cell therapy, validated METAFlux’s capability characterize heterogeneity interaction amongst types.

Язык: Английский

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The human protein atlas—Integrated omics for single cell mapping of the human proteome

Protein Science, Год журнала: 2023, Номер 32(2)

Опубликована: Янв. 6, 2023

Studying the spatial distribution of proteins provides basis for understanding biology, molecular repertoire, and architecture every human cell. The Human Protein Atlas (HPA) has grown into one world's largest biological databases, in most recent version, a major update structure database was performed. data now been organized 10 different comprehensive sections, each summarizing aspects proteome protein-coding genes. In particular, large datasets with information on single cell type level have integrated, refining tissue specificity detailing expression states an increased resolution. multi-modal constitute important resource both basic translational science, hold promise integration novel emerging technologies at protein RNA level.

Язык: Английский

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A multimodal atlas of tumour metabolism reveals the architecture of gene–metabolite covariation

Nature Metabolism, Год журнала: 2023, Номер 5(6), С. 1029 - 1044

Опубликована: Июнь 19, 2023

Tumour metabolism is controlled by coordinated changes in metabolite abundance and gene expression, but simultaneous quantification of metabolites transcripts primary tissue rare. To overcome this limitation to study gene-metabolite covariation cancer, we assemble the Cancer Atlas Metabolic Profiles metabolomic transcriptomic data from 988 tumour control specimens spanning 11 cancer types published newly generated datasets. Meta-analysis reveals two classes that transcend types. The first corresponds pairs engaged direct enzyme-substrate interactions, identifying putative genes controlling pool sizes. A second class represents a small number hub metabolites, including quinolinate nicotinamide adenine dinucleotide, which correlate many specifically expressed immune cell populations. These results provide evidence cellularly heterogeneous arises, part, both mechanistic interactions between remodelling bulk metabolome specific microenvironments.

Язык: Английский

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Generation and analysis of context-specific genome-scale metabolic models derived from single-cell RNA-Seq data

Proceedings of the National Academy of Sciences, Год журнала: 2023, Номер 120(6)

Опубликована: Янв. 31, 2023

Single-cell RNA sequencing combined with genome-scale metabolic models (GEMs) has the potential to unravel differences in metabolism across both cell types and states but requires new computational methods. Here, we present a method for generating cell-type-specific from clusters of single-cell RNA-Seq profiles. Specifically, developed estimate minimum number cells required pool obtain stable models, bootstrapping strategy estimating statistical inference, faster version task-driven integrative network inference tissues algorithm context-specific GEMs. In addition, evaluated effect different normalization methods on model topology generated bulk data. We applied our data mouse cortex neurons tumor microenvironment lung cancer cases found that almost every subtype had unique profile. approach was able detect cancer-associated between healthy cells, showcasing its utility. also contextualized 202 19 human organs using Human Protein Atlas made these available web portal Metabolic Atlas, thereby providing valuable resource scientific community. With ever-increasing availability datasets continuously improved GEMs, their combination holds promise become an important study metabolism.

Язык: Английский

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