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Chen X, Zhang Y, Cao Z, Wang Y, Liao M, Guan Y, Zhu C, Wang W, Huang W, Li W, Xiao Y, Li Y, Yin J, Ding Y, Peng Q, Hu L. Huperzine A targets Apolipoprotein E: A potential therapeutic drug for diabetic nephropathy based on omics analysis. Pharmacol Res 2024; 208:107392. [PMID: 39233057 DOI: 10.1016/j.phrs.2024.107392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2024] [Revised: 08/29/2024] [Accepted: 08/30/2024] [Indexed: 09/06/2024]
Abstract
AIMS Diabetic nephropathy (DN) is a major complication of diabetes mellitus (DM) without curative interventions currently. Huperzine A (Hup A), a natural alkaloid, has demonstrated significant hypoglycemic and anti-inflammatory effects. We aim to investigate the protective effects of Hup A on DN and explore the underlying mechanisms METHODS: We applied STZ induced diabetic rats as DN model and leveraged combination analysis of the transcriptome, metabolome, microbiome, and network pharmacology (NP). The total effect of Hup A on DN was detected (i.e. urine protein, renal tissue structure) and the differential genes were further verified at the level of diabetic patients, db/db mice and cells. Clinical data and small interfering RNA (siRNA)-Apoe were adopted. RESULTS Hup A alleviated kidney injury in DN rats. Transcriptomics data and Western blot indicated that the improvement in DN was primarily associated with Apoe and Apoc2. Additionally, metabolomics data demonstrated that DN-induced lipid metabolism disruption was regulated by Hup A, potentially involving sphingosine. Hup A also enriched microbial diversity and ameliorated DN-induced microbiota imbalance. Spearman's correlation analysis demonstrated significant associations among the transcriptome, metabolome, and microbiome. Apoe level was positively correlated with clinical biomarkers in DN patients. Si-Apoe also played protective role in podocytes. NP analysis also suggested that Hup A may treat DN by modulating lipid metabolism, microbial homeostasis, and apoptosis, further validating our findings. CONCLUSIONS Collectively, we provide the first evidence of the therapeutic effect of Hup A on DN, indicating that Hup A is a potential drug for the prevention and treatment of DN.
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Affiliation(s)
- Xiangjun Chen
- Department of Nephrology, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China; Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou 310052, China; School of TCM, Hunan University of Chinese Medicine, China
| | - Ying Zhang
- Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou 310052, China
| | - Zhongkai Cao
- Department of Nephrology, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China
| | - Yue Wang
- Hubei Normal University, Huangshi 435002, China
| | - Mengqiu Liao
- Department of Nephrology, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China
| | - Yuelin Guan
- Department of Nephrology, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China
| | - Caifeng Zhu
- Department of Nephrology, Hangzhou TCM Hospital, Hangzhou, China
| | - Wenmin Wang
- Department of Nephrology, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China
| | - Wunan Huang
- The First Clinical Medical College of Lanzhou University, Lanzhou 730000, China
| | - Wei Li
- Department of Nephrology, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China
| | - Yingping Xiao
- State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-products, Institute of Agro-product Safety and Nutrition, Zhejiang Academy of Agricultural Sciences, China
| | - Yayu Li
- Department of Nephrology, Hangzhou TCM Hospital, Hangzhou, China
| | - Jiazhen Yin
- Department of Nephrology, Hangzhou TCM Hospital, Hangzhou, China
| | - Yuhan Ding
- State Key Laboratory of Membrane Biology, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Qinghua Peng
- School of TCM, Hunan University of Chinese Medicine, China
| | - Lidan Hu
- Department of Nephrology, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China.
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2
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Schweickart A, Chetnik K, Batra R, Kaddurah-Daouk R, Suhre K, Halama A, Krumsiek J. AutoFocus: a hierarchical framework to explore multi-omic disease associations spanning multiple scales of biomolecular interaction. Commun Biol 2024; 7:1094. [PMID: 39237774 PMCID: PMC11377741 DOI: 10.1038/s42003-024-06724-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 08/13/2024] [Indexed: 09/07/2024] Open
Abstract
Recent advances in high-throughput measurement technologies have enabled the analysis of molecular perturbations associated with disease phenotypes at the multi-omic level. Such perturbations can range in scale from fluctuations of individual molecules to entire biological pathways. Data-driven clustering algorithms have long been used to group interactions into interpretable functional modules; however, these modules are typically constrained to a fixed size or statistical cutoff. Furthermore, modules are often analyzed independently of their broader biological context. Consequently, such clustering approaches limit the ability to explore functional module associations with disease phenotypes across multiple scales. Here, we introduce AutoFocus, a data-driven method that hierarchically organizes biomolecules and tests for phenotype enrichment at every level within the hierarchy. As a result, the method allows disease-associated modules to emerge at any scale. We evaluated this approach using two datasets: First, we explored associations of biomolecules from the multi-omic QMDiab dataset (n = 388) with the well-characterized type 2 diabetes phenotype. Secondly, we utilized the ROS/MAP Alzheimer's disease dataset (n = 500), consisting of high-throughput measurements of brain tissue to explore modules associated with multiple Alzheimer's Disease-related phenotypes. Our method identifies modules that are multi-omic, span multiple pathways, and vary in size. We provide an interactive tool to explore this hierarchy at different levels and probe enriched modules, empowering users to examine the full hierarchy, delve into biomolecular drivers of disease phenotype within a module, and incorporate functional annotations.
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Affiliation(s)
- Annalise Schweickart
- Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Kelsey Chetnik
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Richa Batra
- Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Rima Kaddurah-Daouk
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
- Duke Institute of Brain Sciences, Duke University, Durham, NC, USA
- Department of Medicine, Duke University, Durham, NC, USA
| | - Karsten Suhre
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
- Bioinformatics Core, Weill Cornell Medical College-Qatar Education City, Doha, Qatar
| | - Anna Halama
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
- Bioinformatics Core, Weill Cornell Medical College-Qatar Education City, Doha, Qatar
| | - Jan Krumsiek
- Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA.
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA.
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3
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Moldogazieva NT, Zavadskiy SP, Astakhov DV, Terentiev AA. Lipid peroxidation: Reactive carbonyl species, protein/DNA adducts, and signaling switches in oxidative stress and cancer. Biochem Biophys Res Commun 2023; 687:149167. [PMID: 37939506 DOI: 10.1016/j.bbrc.2023.149167] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 10/15/2023] [Accepted: 10/26/2023] [Indexed: 11/10/2023]
Abstract
Under the exposure of lipids to reactive oxygen species (ROS), lipid peroxidation proceeds non-enzymatically and generates an extremely heterogeneous mixture of reactive carbonyl species (RCS). Among them, HNE, HHE, MDA, methylglyoxal, glyoxal, and acrolein are the most studied and/or abundant ones. Over the last decades, significant progress has been achieved in understanding mechanisms of RCS generation, protein/DNA adduct formation, and their identification and quantification in biological samples. In our review, we critically discuss the advancements in understanding the roles of RCS-induced protein/DNA modifications in signaling switches to provide adaptive cell response under physiological and oxidative stress conditions. At non-toxic concentrations, RCS modify susceptible Cys residue in c-Src to activate MAPK signaling and Cys, Lys, and His residues in PTEN to cause its reversible inactivation, thereby stimulating PI3K/PKB(Akt) pathway. RCS toxic concentrations cause irreversible Cys modifications in Keap1 and IKKβ followed by stabilization of Nrf2 and activation of NF-κB, respectively, for their nuclear translocation and antioxidant gene expression. Dysregulation of these mechanisms causes diseases including cancer. Alterations in RCS, RCS detoxifying enzymes, RCS-modified protein/DNA adducts, and signaling pathways have been implicated in various cancer types.
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Affiliation(s)
- Nurbubu T Moldogazieva
- Department of Pharmacology, A.P. Nelyubin Institute of Pharmacy, I.M. Sechenov First Moscow State Medical University, 119991, 8 Trubetskaya Street, Moscow, Russia.
| | - Sergey P Zavadskiy
- Department of Pharmacology, A.P. Nelyubin Institute of Pharmacy, I.M. Sechenov First Moscow State Medical University, 119991, 8 Trubetskaya Street, Moscow, Russia
| | - Dmitry V Astakhov
- Department of Biochemistry, Institute of Biodesign and Complex Systems Modelling, I.M. Sechenov First Moscow State Medical University, 119991, 8 Trubetskaya Str., Moscow, Russia
| | - Alexander A Terentiev
- Department of Biochemistry and Molecular Biology, N.I. Pirogov Russian National Research Medical University, 117997, 1 Ostrovityanov Street, Moscow, Russia
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Zhang Y, Shi J, Tan C, Liu Y, Xu YJ. Oilomics: An important branch of foodomics dealing with oil science and technology. Food Res Int 2023; 173:113301. [PMID: 37803609 DOI: 10.1016/j.foodres.2023.113301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 07/16/2023] [Accepted: 07/20/2023] [Indexed: 10/08/2023]
Abstract
Oil is one of three nutritious elements. The application of omics techniques in the field of oil science and technology is attracted increasing attention. Oilomics, which emerged as an important branch of foodomics, has been widely used in various aspects of oil science and technology. However, there are currently no articles systematically reviewing the application of oilomics. This paper aims to provide a critical overview of the advantages and value of oilomics technology compared to traditional techniques in various aspects of oil science and technology, including oil nutrition, oil processing, oil quality, safety, and traceability. Moreover, this article intends to review major issues in oilomics and give a comprehensive, critical overview of the current state of the art, future challenges and trends in oilomics, with a view to promoting the optimal application and development of oilomics technology in oil science and technology.
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Affiliation(s)
- Yu Zhang
- State Key Laboratory of Food Science and Technology, School of Food Science and Technology, National Engineering Reacher Center for Functional Food, National Engineering Laboratory for Cereal Fermentation Technology, Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, No. 1800, Lihu Road, Wuxi 214122, Jiangsu, People's Republic of China
| | - Jiachen Shi
- State Key Laboratory of Food Science and Technology, School of Food Science and Technology, National Engineering Reacher Center for Functional Food, National Engineering Laboratory for Cereal Fermentation Technology, Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, No. 1800, Lihu Road, Wuxi 214122, Jiangsu, People's Republic of China
| | - Chinping Tan
- Department of Food Technology, Faculty of Food Science and Technology, Universiti Putra Malaysia, UPM, 43400 Serdang, Selangor, Malaysia
| | - Yuanfa Liu
- State Key Laboratory of Food Science and Technology, School of Food Science and Technology, National Engineering Reacher Center for Functional Food, National Engineering Laboratory for Cereal Fermentation Technology, Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, No. 1800, Lihu Road, Wuxi 214122, Jiangsu, People's Republic of China
| | - Yong-Jiang Xu
- State Key Laboratory of Food Science and Technology, School of Food Science and Technology, National Engineering Reacher Center for Functional Food, National Engineering Laboratory for Cereal Fermentation Technology, Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, No. 1800, Lihu Road, Wuxi 214122, Jiangsu, People's Republic of China.
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5
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Zhang N, Yang Y, Li C, Zhang K, GAO X, Shen J, Wang Y, Cheng D, Lv J, Sun J. Based on 1H NMR and LC-MS metabolomics reveals biomarkers with neuroprotective effects in multi-parts ginseng powder. ARAB J CHEM 2023. [DOI: 10.1016/j.arabjc.2023.104840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023] Open
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6
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Lipidomics analysis in drug discovery and development. Curr Opin Chem Biol 2023; 72:102256. [PMID: 36586190 DOI: 10.1016/j.cbpa.2022.102256] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 11/08/2022] [Accepted: 11/28/2022] [Indexed: 12/30/2022]
Abstract
Despite being a relatively new addition to the Omics' landscape, lipidomics is increasingly being recognized as an important tool for the identification of druggable targets and biochemical markers. In this review we present recent advances of lipid analysis in drug discovery and development. We cover current state of the art technologies which are constantly evolving to meet demands in terms of sensitivity and selectivity. A careful selection of important examples is then provided, illustrating the versatility of lipidomics analysis in the drug discovery and development process. Integration of lipidomics with other omics', stem-cell technologies, and metabolic flux analysis will open new avenues for deciphering pathophysiological mechanisms and the discovery of novel targets and biomarkers.
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7
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Hao X, Cheng S, Jiang B, Xin S. Applying multi-omics techniques to the discovery of biomarkers for acute aortic dissection. Front Cardiovasc Med 2022; 9:961991. [PMID: 36588568 PMCID: PMC9797526 DOI: 10.3389/fcvm.2022.961991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Accepted: 11/28/2022] [Indexed: 12/23/2022] Open
Abstract
Acute aortic dissection (AAD) is a cardiovascular disease that manifests suddenly and fatally. Due to the lack of specific early symptoms, many patients with AAD are often overlooked or misdiagnosed, which is undoubtedly catastrophic for patients. The particular pathogenic mechanism of AAD is yet unknown, which makes clinical pharmacological therapy extremely difficult. Therefore, it is necessary and crucial to find and employ unique biomarkers for Acute aortic dissection (AAD) as soon as possible in clinical practice and research. This will aid in the early detection of AAD and give clear guidelines for the creation of focused treatment agents. This goal has been made attainable over the past 20 years by the quick advancement of omics technologies and the development of high-throughput tissue specimen biomarker screening. The primary histology data support and add to one another to create a more thorough and three-dimensional picture of the disease. Based on the introduction of the main histology technologies, in this review, we summarize the current situation and most recent developments in the application of multi-omics technologies to AAD biomarker discovery and emphasize the significance of concentrating on integration concepts for integrating multi-omics data. In this context, we seek to offer fresh concepts and recommendations for fundamental investigation, perspective innovation, and therapeutic development in AAD.
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Affiliation(s)
- Xinyu Hao
- Department of Vascular Surgery, The First Affiliated Hospital of China Medical University, China Medical University, Shenyang, China,Key Laboratory of Pathogenesis, Prevention and Therapeutics of Aortic Aneurysm, Shenyang, Liaoning, China
| | - Shuai Cheng
- Department of Vascular Surgery, The First Affiliated Hospital of China Medical University, China Medical University, Shenyang, China,Key Laboratory of Pathogenesis, Prevention and Therapeutics of Aortic Aneurysm, Shenyang, Liaoning, China
| | - Bo Jiang
- Department of Vascular Surgery, The First Affiliated Hospital of China Medical University, China Medical University, Shenyang, China,Key Laboratory of Pathogenesis, Prevention and Therapeutics of Aortic Aneurysm, Shenyang, Liaoning, China
| | - Shijie Xin
- Department of Vascular Surgery, The First Affiliated Hospital of China Medical University, China Medical University, Shenyang, China,Key Laboratory of Pathogenesis, Prevention and Therapeutics of Aortic Aneurysm, Shenyang, Liaoning, China,*Correspondence: Shijie Xin,
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8
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Shi H, An F, Lin H, Li M, Wu J, Wu R. Advances in fermented foods revealed by multi-omics: A new direction toward precisely clarifying the roles of microorganisms. Front Microbiol 2022; 13:1044820. [PMID: 36590428 PMCID: PMC9794733 DOI: 10.3389/fmicb.2022.1044820] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 11/23/2022] [Indexed: 12/15/2022] Open
Abstract
Fermented foods generally comprise a complex micro-ecosystem with beneficial microbiota, functional products, and special flavors and qualities that are welcomed globally. Single-omics analysis allows for a comprehensive characterization of the main microbial factors influencing the function, flavor, and quality of fermented foods. However, the species, relative abundance, viability, growth patterns, and metabolic processes of microorganisms vary with changes in processing and environmental conditions during fermentation. Furthermore, the mechanisms underlying the complex interaction among microorganisms are still difficult to completely understand and analyze. Recently, multi-omics analysis and the integration of multiple types of omics data allowed researchers to more comprehensively explore microbial communities and understand the precise relationship between fermented foods and their functions, flavors, and qualities. Multi-omics approaches might help clarify the mechanisms underpinning the fermentation processes, metabolites, and functional components of these communities. This review clarified the recent advances in the roles of microorganisms in fermented foods based on multi-omics data. Current research achievements may allow for the precise control of the whole industrial processing technology of fermented foods, meeting consumers' expectations of healthy products.
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Affiliation(s)
- Haisu Shi
- College of Food Science, Shenyang Agricultural University, Shenyang, China,Liaoning Engineering Research Center of Food Fermentation Technology, Shenyang Agricultural University, Shenyang, China,Shenyang Key Laboratory of Microbial Fermentation Technology Innovation, Shenyang Agricultural University, Shenyang, China
| | - Feiyu An
- College of Food Science, Shenyang Agricultural University, Shenyang, China
| | - Hao Lin
- College of Food Science, Shenyang Agricultural University, Shenyang, China
| | - Mo Li
- College of Food Science, Shenyang Agricultural University, Shenyang, China
| | - Junrui Wu
- College of Food Science, Shenyang Agricultural University, Shenyang, China,Liaoning Engineering Research Center of Food Fermentation Technology, Shenyang Agricultural University, Shenyang, China,Shenyang Key Laboratory of Microbial Fermentation Technology Innovation, Shenyang Agricultural University, Shenyang, China,Junrui Wu,
| | - Rina Wu
- College of Food Science, Shenyang Agricultural University, Shenyang, China,Liaoning Engineering Research Center of Food Fermentation Technology, Shenyang Agricultural University, Shenyang, China,Shenyang Key Laboratory of Microbial Fermentation Technology Innovation, Shenyang Agricultural University, Shenyang, China,*Correspondence: Rina Wu,
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9
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Zhang N, Peng Y, Zhao L, He P, Zhu J, Liu Y, Liu X, Liu X, Deng G, Zhang Z, Feng M. Integrated Analysis of Gut Microbiome and Lipid Metabolism in Mice Infected with Carbapenem-Resistant Enterobacteriaceae. Metabolites 2022; 12:metabo12100892. [PMID: 36295794 PMCID: PMC9609999 DOI: 10.3390/metabo12100892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Revised: 09/15/2022] [Accepted: 09/16/2022] [Indexed: 11/22/2022] Open
Abstract
The disturbance in gut microbiota composition and metabolism has been implicated in the process of pathogenic bacteria infection. However, the characteristics of the microbiota and the metabolic interaction of commensals−host during pathogen invasion remain more than vague. In this study, the potential associations of gut microbes with disturbed lipid metabolism in mice upon carbapenem-resistant Escherichia coli (CRE) infection were explored by the biochemical and multi-omics approaches including metagenomics, metabolomics and lipidomics, and then the key metabolites−reaction−enzyme−gene interaction network was constructed. Results showed that intestinal Erysipelotrichaceae family was strongly associated with the hepatic total cholesterol and HDL-cholesterol, as well as a few sera and fecal metabolites involved in lipid metabolism such as 24, 25-dihydrolanosterol. A high-coverage lipidomic analysis further demonstrated that a total of 529 lipid molecules was significantly enriched and 520 were depleted in the liver of mice infected with CRE. Among them, 35 lipid species showed high correlations (|r| > 0.8 and p < 0.05) with the Erysipelotrichaceae family, including phosphatidylglycerol (42:2), phosphatidylglycerol (42:3), phosphatidylglycerol (38:5), phosphatidylcholine (42:4), ceramide (d17:1/16:0), ceramide (d18:1/16:0) and diacylglycerol (20:2), with correlation coefficients higher than 0.9. In conclusion, the systematic multi-omics study improved the understanding of the complicated connection between the microbiota and the host during pathogen invasion, which thereby is expected to lead to the future discovery and establishment of novel control strategies for CRE infection.
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Affiliation(s)
- Ning Zhang
- School of Chemistry and Chemical Engineering, Shanghai Engineering Research Center for Pharmaceutical Intelligent Equipment, Shanghai Frontiers Science Research Center for Druggability of Cardiovascular Noncoding RNA, Shanghai University of Engineering Science, Shanghai 201620, China
| | - Yuanyuan Peng
- School of Chemistry and Chemical Engineering, Shanghai Engineering Research Center for Pharmaceutical Intelligent Equipment, Shanghai Frontiers Science Research Center for Druggability of Cardiovascular Noncoding RNA, Shanghai University of Engineering Science, Shanghai 201620, China
| | - Linjing Zhao
- School of Chemistry and Chemical Engineering, Shanghai Engineering Research Center for Pharmaceutical Intelligent Equipment, Shanghai Frontiers Science Research Center for Druggability of Cardiovascular Noncoding RNA, Shanghai University of Engineering Science, Shanghai 201620, China
- Correspondence: ; Tel.: +86-21-6779-1214
| | - Peng He
- Minhang Hospital & School of Pharmacy, Fudan University, Shanghai 200433, China
- Shanghai Engineering Research Center of Immunotherapeutic, Shanghai 201203, China
| | - Jiamin Zhu
- School of Chemistry and Chemical Engineering, Shanghai Engineering Research Center for Pharmaceutical Intelligent Equipment, Shanghai Frontiers Science Research Center for Druggability of Cardiovascular Noncoding RNA, Shanghai University of Engineering Science, Shanghai 201620, China
| | - Yumin Liu
- Instrumental Analysis Centre, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Xijian Liu
- School of Chemistry and Chemical Engineering, Shanghai Engineering Research Center for Pharmaceutical Intelligent Equipment, Shanghai Frontiers Science Research Center for Druggability of Cardiovascular Noncoding RNA, Shanghai University of Engineering Science, Shanghai 201620, China
| | - Xiaohui Liu
- School of Chemistry and Chemical Engineering, Shanghai Engineering Research Center for Pharmaceutical Intelligent Equipment, Shanghai Frontiers Science Research Center for Druggability of Cardiovascular Noncoding RNA, Shanghai University of Engineering Science, Shanghai 201620, China
| | - Guoying Deng
- Trauma Center, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 201620, China
| | - Zhong Zhang
- Nursing Department, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 201620, China
| | - Meiqing Feng
- Minhang Hospital & School of Pharmacy, Fudan University, Shanghai 200433, China
- Shanghai Engineering Research Center of Immunotherapeutic, Shanghai 201203, China
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10
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Tikunov AP, Tipton JD, Garrett TJ, Shinde SV, Kim HJ, Gerber DA, Herring LE, Graves LM, Macdonald JM. Green Chemistry Preservation and Extraction of Biospecimens for Multi-omic Analyses. Methods Mol Biol 2022; 2394:267-298. [PMID: 35094334 DOI: 10.1007/978-1-0716-1811-0_17] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
The Environmental Protection Agency's definition of "Green Chemistry" is "the design of chemical products and processes that reduces or eliminates the use or generation of hazardous substances. Green chemistry applies across the life cycle of a chemical product, including its design, manufacture, use, and ultimate disposal." Conventional omic tissue extraction procedures use solvents that are toxic and carcinogenic, such as chloroform and methyl-tert-butyl ether for lipidomics, or caustic chaotropic solutions for genomics and transcriptomics, such as guanidine or urea. A common preservation solution for pathology is formaldehyde, which is a carcinogen. Use of acetonitrile as a universal biospecimen preservation and extraction solvent will reduce these hazardous wastes, because it is less toxic and more environmentally friendly than the conventional solvents used in biorepository and biospecimen research. A new extraction method never applied to multi-omic, system biology research, called cold-induced phase separation (CIPS), uses freezing point temperatures to induce a phase separation of acetonitrile-water mixtures. Also, the CO2 exposure during CIPS will acidify the water precipitating DNA out of aqueous phase. The resulting phase separation brings hydrophobic lipids to the top acetonitrile fraction that is easily decanted from the bottom aqueous fraction, especially when the water is frozen. This CIPS acetonitrile extract contains the lipidome (lipids), the bottom aqueous fraction is sampled to obtain the transcriptome (RNA) fraction, and the remaining water and pellet is extracted with 60% acetonitrile to isolate the metabolome (<1 kD polar molecules). Finally, steps 4 and 5 use a TRIzol™ liquid-liquid extraction SOP of the pellet to isolate the genome (DNA) and proteome (proteins). This chapter details the multi-omic sequential extraction SOP and potential problems associated with each of the 5 steps, with steps 2, 4, and 5 still requiring validation. The metabolomic and lipidomic extraction efficiencies using the CIPS SOP is compared to conventional solvent extraction SOPs and is analyzed by nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography-mass spectrometry (LC-MS), respectively. Acetonitrile biospecimen preservation combined with the CIPS multi-omic extraction SOP is green chemistry technology that will eliminate the generation of the hazardous substances associated with biospecimen processing and permits separation and safe disposal of acetonitrile avoiding environmental contamination.
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Affiliation(s)
- Andrey P Tikunov
- Departments of Biomedical Engineering, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Jeremiah D Tipton
- Departments of Biomedical Engineering, University of North Carolina School of Medicine, Chapel Hill, NC, USA
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, College of Medicine, Gainesville, FL, USA
| | - Timothy J Garrett
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, College of Medicine, Gainesville, FL, USA
| | - Sachi V Shinde
- Departments of Biomedical Engineering, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Hong Jin Kim
- Departments of Surgery, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - David A Gerber
- Departments of Surgery, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Laura E Herring
- Departments of Pharmacology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Lee M Graves
- Departments of Pharmacology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Jeffrey M Macdonald
- Departments of Biomedical Engineering, University of North Carolina School of Medicine, Chapel Hill, NC, USA.
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Gonzalez-Covarrubias V, Martínez-Martínez E, del Bosque-Plata L. The Potential of Metabolomics in Biomedical Applications. Metabolites 2022; 12:metabo12020194. [PMID: 35208267 PMCID: PMC8880031 DOI: 10.3390/metabo12020194] [Citation(s) in RCA: 69] [Impact Index Per Article: 34.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 01/28/2022] [Accepted: 01/30/2022] [Indexed: 12/12/2022] Open
Abstract
The metabolome offers a dynamic, comprehensive, and precise picture of the phenotype. Current high-throughput technologies have allowed the discovery of relevant metabolites that characterize a wide variety of human phenotypes with respect to health, disease, drug monitoring, and even aging. Metabolomics, parallel to genomics, has led to the discovery of biomarkers and has aided in the understanding of a diversity of molecular mechanisms, highlighting its application in precision medicine. This review focuses on the metabolomics that can be applied to improve human health, as well as its trends and impacts in metabolic and neurodegenerative diseases, cancer, longevity, the exposome, liquid biopsy development, and pharmacometabolomics. The identification of distinct metabolomic profiles will help in the discovery and improvement of clinical strategies to treat human disease. In the years to come, metabolomics will become a tool routinely applied to diagnose and monitor health and disease, aging, or drug development. Biomedical applications of metabolomics can already be foreseen to monitor the progression of metabolic diseases, such as obesity and diabetes, using branched-chain amino acids, acylcarnitines, certain phospholipids, and genomics; these can assess disease severity and predict a potential treatment. Future endeavors should focus on determining the applicability and clinical utility of metabolomic-derived markers and their appropriate implementation in large-scale clinical settings.
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Affiliation(s)
| | - Eduardo Martínez-Martínez
- Laboratory of Cell Communication and Extracellular Vesicles, Instituto Nacional de Medicina Genómica (INMEGEN), Mexico City 14610, Mexico;
| | - Laura del Bosque-Plata
- Laboratory of Nutrigenetics and Nutrigenomics, Instituto Nacional de Medicina Genómica (INMEGEN), Mexico City 14610, Mexico
- Correspondence: ; Tel.: +52-55-53-50-1974
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12
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Multi-Omic Analysis to Characterize Metabolic Adaptation of the E. coli Lipidome in Response to Environmental Stress. Metabolites 2022; 12:metabo12020171. [PMID: 35208246 PMCID: PMC8880424 DOI: 10.3390/metabo12020171] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 02/08/2022] [Accepted: 02/09/2022] [Indexed: 12/17/2022] Open
Abstract
As an adaptive survival response to exogenous stress, bacteria undergo dynamic remodelling of their lipid metabolism pathways to alter the composition of their cellular membranes. Here, using Escherichia coli as a well characterised model system, we report the development and application of a ‘multi-omics’ strategy for comprehensive quantitative analysis of the temporal changes in the lipidome and proteome profiles that occur under exponential growth phase versus stationary growth phase conditions i.e., nutrient depletion stress. Lipidome analysis performed using ‘shotgun’ direct infusion-based ultra-high resolution accurate mass spectrometry revealed a quantitative decrease in total lipid content under stationary growth phase conditions, along with a significant increase in the mol% composition of total cardiolipin, and an increase in ‘odd-numbered’ acyl-chain length containing glycerophospholipids. The inclusion of field asymmetry ion mobility spectrometry was shown to enable the enrichment and improved depth of coverage of low-abundance cardiolipins, while ultraviolet photodissociation-tandem mass spectrometry facilitated more complete lipid structural characterisation compared with conventional collision-induced dissociation, including unambiguous assignment of the odd-numbered acyl-chains as containing cyclopropyl modifications. Proteome analysis using data-dependent acquisition nano-liquid chromatography mass spectrometry and tandem mass spectrometry analysis identified 83% of the predicted E. coli lipid metabolism enzymes, which enabled the temporal dependence associated with the expression of key enzymes responsible for the observed adaptive lipid metabolism to be determined, including those involved in phospholipid metabolism (e.g., ClsB and Cfa), fatty acid synthesis (e.g., FabH) and degradation (e.g., FadA/B,D,E,I,J and M), and proteins involved in the oxidative stress response resulting from the generation of reactive oxygen species during β-oxidation or lipid degradation.
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13
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Garikapati V, Colasante C, Baumgart-Vogt E, Spengler B. Sequential lipidomic, metabolomic, and proteomic analyses of serum, liver, and heart tissue specimens from peroxisomal biogenesis factor 11α knockout mice. Anal Bioanal Chem 2022; 414:2235-2250. [PMID: 35083512 PMCID: PMC8821073 DOI: 10.1007/s00216-021-03860-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 11/25/2021] [Accepted: 12/20/2021] [Indexed: 12/16/2022]
Abstract
Peroxisomes are versatile single membrane-enclosed cytoplasmic organelles, involved in reactive oxygen species (ROS) and lipid metabolism and diverse other metabolic processes. Peroxisomal disorders result from mutations in Pex genes-encoded proteins named peroxins (PEX proteins) and single peroxisomal enzyme deficiencies. The PEX11 protein family (α, β, and γ isoforms) plays an important role in peroxisomal proliferation and fission. However, their specific functions and the metabolic impact caused by their deficiencies have not been precisely characterized. To understand the systemic molecular alterations caused by peroxisomal defects, here we utilized untreated peroxisomal biogenesis factor 11α knockout (Pex11α KO) mouse model and performed serial relative-quantitative lipidomic, metabolomic, and proteomic analyses of serum, liver, and heart tissue homogenates. We demonstrated significant specific changes in the abundances of multiple lipid species, polar metabolites, and proteins and dysregulated metabolic pathways in distinct biological specimens of the Pex11α KO adult mice in comparison to the wild type (WT) controls. Overall, the present study reports comprehensive semi-quantitative molecular omics information of the Pex11α KO mice, which might serve in the future as a reference for a better understanding of the roles of Pex11α and underlying pathophysiological mechanisms of peroxisomal biogenesis disorders.
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Affiliation(s)
- Vannuruswamy Garikapati
- Institute of Inorganic and Analytical Chemistry, Justus Liebig University Giessen, 35392, Giessen, Germany.,Institute for Anatomy and Cell Biology II, Division of Medical Cell Biology, Justus Liebig University Giessen, 35392, Giessen, Germany
| | - Claudia Colasante
- Institute for Anatomy and Cell Biology II, Division of Medical Cell Biology, Justus Liebig University Giessen, 35392, Giessen, Germany
| | - Eveline Baumgart-Vogt
- Institute for Anatomy and Cell Biology II, Division of Medical Cell Biology, Justus Liebig University Giessen, 35392, Giessen, Germany.
| | - Bernhard Spengler
- Institute of Inorganic and Analytical Chemistry, Justus Liebig University Giessen, 35392, Giessen, Germany.
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14
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Singh RS, Angra V, Singh A, Masih GD, Medhi B. Integrative omics - An arsenal for drug discovery. Indian J Pharmacol 2022; 54:1-6. [PMID: 35343200 PMCID: PMC9012413 DOI: 10.4103/ijp.ijp_53_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Affiliation(s)
- Rahul Soloman Singh
- Department of Pharmacology, Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | - Vani Angra
- Department of Pharmacology, Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | - Ashutosh Singh
- Department of Pharmacology, Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | - Gladson David Masih
- Department of Pharmacology, Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | - Bikash Medhi
- Department of Pharmacology, Postgraduate Institute of Medical Education and Research, Chandigarh, India
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15
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Köhler N, Rose TD, Falk L, Pauling JK. Investigating Global Lipidome Alterations with the Lipid Network Explorer. Metabolites 2021; 11:metabo11080488. [PMID: 34436429 PMCID: PMC8398636 DOI: 10.3390/metabo11080488] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 07/26/2021] [Accepted: 07/27/2021] [Indexed: 11/18/2022] Open
Abstract
Lipids play an important role in biological systems and have the potential to serve as biomarkers in medical applications. Advances in lipidomics allow identification of hundreds of lipid species from biological samples. However, a systems biological analysis of the lipidome, by incorporating pathway information remains challenging, leaving lipidomics behind compared to other omics disciplines. An especially uncharted territory is the integration of statistical and network-based approaches for studying global lipidome changes. Here we developed the Lipid Network Explorer (LINEX), a web-tool addressing this gap by providing a way to visualize and analyze functional lipid metabolic networks. It utilizes metabolic rules to match biochemically connected lipids on a species level and combine it with a statistical correlation and testing analysis. Researchers can customize the biochemical rules considered, to their tissue or organism specific analysis and easily share them. We demonstrate the benefits of combining network-based analyses with statistics using publicly available lipidomics data sets. LINEX facilitates a biochemical knowledge-based data analysis for lipidomics. It is availableas a web-application and as a publicly available docker container.
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16
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Zhou M, Varol A, Efferth T. Multi-omics approaches to improve malaria therapy. Pharmacol Res 2021; 167:105570. [PMID: 33766628 DOI: 10.1016/j.phrs.2021.105570] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 03/02/2021] [Accepted: 03/16/2021] [Indexed: 01/07/2023]
Abstract
Malaria contributes to the most widespread infectious diseases worldwide. Even though current drugs are commercially available, the ever-increasing drug resistance problem by malaria parasites poses new challenges in malaria therapy. Hence, searching for efficient therapeutic strategies is of high priority in malaria control. In recent years, multi-omics technologies have been extensively applied to provide a more holistic view of functional principles and dynamics of biological mechanisms. We briefly review multi-omics technologies and focus on recent malaria progress conducted with the help of various omics methods. Then, we present up-to-date advances for multi-omics approaches in malaria. Next, we describe resistance phenomena to established antimalarial drugs and underlying mechanisms. Finally, we provide insight into novel multi-omics approaches, new drugs and vaccine developments and analyze current gaps in multi-omics research. Although multi-omics approaches have been successfully used in malaria studies, they are still limited. Many gaps need to be filled to bridge the gap between basic research and treatment of malaria patients. Multi-omics approaches will foster a better understanding of the molecular mechanisms of Plasmodium that are essential for the development of novel drugs and vaccines to fight this disastrous disease.
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Affiliation(s)
- Min Zhou
- Department of Pharmaceutical Biology, Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg University, Staudinger Weg 5, 55128 Mainz, Germany
| | - Ayşegül Varol
- Department of Pharmaceutical Biology, Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg University, Staudinger Weg 5, 55128 Mainz, Germany
| | - Thomas Efferth
- Department of Pharmaceutical Biology, Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg University, Staudinger Weg 5, 55128 Mainz, Germany.
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17
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Wörheide MA, Krumsiek J, Kastenmüller G, Arnold M. Multi-omics integration in biomedical research - A metabolomics-centric review. Anal Chim Acta 2021; 1141:144-162. [PMID: 33248648 PMCID: PMC7701361 DOI: 10.1016/j.aca.2020.10.038] [Citation(s) in RCA: 101] [Impact Index Per Article: 33.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Revised: 10/09/2020] [Accepted: 10/19/2020] [Indexed: 02/07/2023]
Abstract
Recent advances in high-throughput technologies have enabled the profiling of multiple layers of a biological system, including DNA sequence data (genomics), RNA expression levels (transcriptomics), and metabolite levels (metabolomics). This has led to the generation of vast amounts of biological data that can be integrated in so-called multi-omics studies to examine the complex molecular underpinnings of health and disease. Integrative analysis of such datasets is not straightforward and is particularly complicated by the high dimensionality and heterogeneity of the data and by the lack of universal analysis protocols. Previous reviews have discussed various strategies to address the challenges of data integration, elaborating on specific aspects, such as network inference or feature selection techniques. Thereby, the main focus has been on the integration of two omics layers in their relation to a phenotype of interest. In this review we provide an overview over a typical multi-omics workflow, focusing on integration methods that have the potential to combine metabolomics data with two or more omics. We discuss multiple integration concepts including data-driven, knowledge-based, simultaneous and step-wise approaches. We highlight the application of these methods in recent multi-omics studies, including large-scale integration efforts aiming at a global depiction of the complex relationships within and between different biological layers without focusing on a particular phenotype.
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Affiliation(s)
- Maria A Wörheide
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Jan Krumsiek
- Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Gabi Kastenmüller
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Matthias Arnold
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA.
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18
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Alves MA, Lamichhane S, Dickens A, McGlinchey A, Ribeiro HC, Sen P, Wei F, Hyötyläinen T, Orešič M. Systems biology approaches to study lipidomes in health and disease. Biochim Biophys Acta Mol Cell Biol Lipids 2020; 1866:158857. [PMID: 33278596 DOI: 10.1016/j.bbalip.2020.158857] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 11/13/2020] [Accepted: 11/27/2020] [Indexed: 12/15/2022]
Abstract
Lipids have many important biological roles, such as energy storage sources, structural components of plasma membranes and as intermediates in metabolic and signaling pathways. Lipid metabolism is under tight homeostatic control, exhibiting spatial and dynamic complexity at multiple levels. Consequently, lipid-related disturbances play important roles in the pathogenesis of most of the common diseases. Lipidomics, defined as the study of lipidomes in biological systems, has emerged as a rapidly-growing field. Due to the chemical and functional diversity of lipids, the application of a systems biology approach is essential if one is to address lipid functionality at different physiological levels. In parallel with analytical advances to measure lipids in biological matrices, the field of computational lipidomics has been rapidly advancing, enabling modeling of lipidomes in their pathway, spatial and dynamic contexts. This review focuses on recent progress in systems biology approaches to study lipids in health and disease, with specific emphasis on methodological advances and biomedical applications.
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Affiliation(s)
- Marina Amaral Alves
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku 20520, Finland
| | - Santosh Lamichhane
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku 20520, Finland
| | - Alex Dickens
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku 20520, Finland
| | - Aidan McGlinchey
- School of Medical Sciences, Örebro University, 702 81 Örebro, Sweden
| | | | - Partho Sen
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku 20520, Finland; School of Medical Sciences, Örebro University, 702 81 Örebro, Sweden
| | - Fang Wei
- Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, PR China
| | | | - Matej Orešič
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku 20520, Finland; School of Medical Sciences, Örebro University, 702 81 Örebro, Sweden.
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19
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Liu H, Li X, Deng J, Dai L, Liu W, Pan B, Wang C, Zhang D, Li Z. Molecular mechanism of the response of Zygosaccharomyces rouxii to D-fructose stress by the glutathione metabolism pathway. FEMS Yeast Res 2020; 20:5859488. [PMID: 32556118 DOI: 10.1093/femsyr/foaa034] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Accepted: 06/12/2020] [Indexed: 12/16/2022] Open
Abstract
Zygosaccharomyces rouxii produces high levels of 4-hydroxy-2,5-dimethyl-3(2H)-furanone in YPD medium supplemented with 120 g/L D-fructose and 180 g/L NaCl after 5 d. D-fructose has a stress effect on Z. rouxii, and GSH-Px is a main enzyme involved in the defense of Z. rouxii against oxygen stress according to our previous report. In order to further explore the molecular mechanism of the glutathione metabolism pathway in Z. rouxii in response to D-fructose stress, changes in the expression of genes and proteins involved in the synthesis of glutathione precursor amino acids and enzymes were observed. In addition, changes in the intermediates related to glutathione synthesis in Z. rouxii were reported. The results indicated that some gene-encoding enzymes involved in the glutamate, cysteine and glycine biosynthesis pathways and key genes involved in glutathione synthesis were upregulated. The expression levels of other genes, except SHMT, were consistent with the qRT-PCR results. The contents of γ-glutamylcysteine and glutathione amide in the D-fructose group were higher than those in the control group. In the D-fructose stress groups, the metabolic flux towards glutathione synthesis was increased. These results might provide more in-depth and detailed theoretical support for the oxidative stress defense mechanism of Z. rouxii under D-fructose stress.
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Affiliation(s)
- Hong Liu
- Department of Food and Engineering, College of Food, Heilongjiang Bayi Agricultural University, Heilongjiang, Daqing 163319, China
| | - Xin Li
- Department of Food and Engineering, College of Food, Heilongjiang Bayi Agricultural University, Heilongjiang, Daqing 163319, China
| | - Jingzhi Deng
- Department of Food and Engineering, College of Food, Heilongjiang Bayi Agricultural University, Heilongjiang, Daqing 163319, China
| | - Lingyan Dai
- Department of Bioscience, College of Science and Biotechnology, Heilongjiang Bayi Agricultural University, Heilongjiang, Daqing 163319, China
| | - Wei Liu
- Department of Food and Engineering, College of Food, Heilongjiang Bayi Agricultural University, Heilongjiang, Daqing 163319, China
| | - Bailing Pan
- Department of Food and Engineering, College of Food, Heilongjiang Bayi Agricultural University, Heilongjiang, Daqing 163319, China
| | - Chengtao Wang
- Beijing Engineering and Technology Research Center of Food Additives, Beijing Technology & Business University (BTBU), Beijing 100048, China
| | - Dongjie Zhang
- Department of Food and Engineering, College of Food, Heilongjiang Bayi Agricultural University, Heilongjiang, Daqing 163319, China
| | - Zhijiang Li
- Department of Food and Engineering, College of Food, Heilongjiang Bayi Agricultural University, Heilongjiang, Daqing 163319, China
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20
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Advances in Liquid Chromatography–Mass Spectrometry-Based Lipidomics: A Look Ahead. JOURNAL OF ANALYSIS AND TESTING 2020. [DOI: 10.1007/s41664-020-00135-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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21
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Teclemariam ET, Pergande MR, Cologna SM. Considerations for mass spectrometry-based multi-omic analysis of clinical samples. Expert Rev Proteomics 2020; 17:99-107. [PMID: 31996049 DOI: 10.1080/14789450.2020.1724540] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
Introduction: The role of mass spectrometry in biomolecule analysis has become paramount over the last several decades ranging in the analysis across model systems and human specimens. Accordingly, the presence of mass spectrometers in clinical laboratories has also expanded alongside the number of researchers investigating the protein, lipid, and metabolite composition of an array of biospecimens. With this increase in the number of omic investigations, it is important to consider the entire experimental strategy from sample collection and storage, data collection and analysis.Areas covered: In this short review, we outline considerations for working with clinical (e.g. human) specimens including blood, urine, and cerebrospinal fluid, with emphasis on sample handling, profiling composition, targeted measurements and relevance to disease. Discussions of integrated genomic or transcriptomic datasets are not included. A brief commentary is also provided regarding new technologies with clinical relevance.Expert opinion: The role of mass spectrometry to investigate clinically related specimens is on the rise and the ability to integrate multiple omics datasets from mass spectrometry measurements will be crucial to further understanding human health and disease.
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Affiliation(s)
- Esei T Teclemariam
- Department of Chemistry, University of Illinois at Chicago, Chicago, IL, USA
| | - Melissa R Pergande
- Department of Chemistry, University of Illinois at Chicago, Chicago, IL, USA
| | - Stephanie M Cologna
- Department of Chemistry, University of Illinois at Chicago, Chicago, IL, USA.,Laboratory of Integrated Neuroscience, University of Illinois at Chicago, Chicago, IL, USA
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22
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Kappler L, Lehmann R. Mass-spectrometric multi-omics linked to function – State-of-the-art investigations of mitochondria in systems medicine. Trends Analyt Chem 2019. [DOI: 10.1016/j.trac.2019.115635] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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23
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Mnatsakanyan R, Shema G, Basik M, Batist G, Borchers CH, Sickmann A, Zahedi RP. Detecting post-translational modification signatures as potential biomarkers in clinical mass spectrometry. Expert Rev Proteomics 2019; 15:515-535. [PMID: 29893147 DOI: 10.1080/14789450.2018.1483340] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
INTRODUCTION Numerous diseases are caused by changes in post-translational modifications (PTMs). Therefore, the number of clinical proteomics studies that include the analysis of PTMs is increasing. Combining complementary information-for example changes in protein abundance, PTM levels, with the genome and transcriptome (proteogenomics)-holds great promise for discovering important drivers and markers of disease, as variations in copy number, expression levels, or mutations without spatial/functional/isoform information is often insufficient or even misleading. Areas covered: We discuss general considerations, requirements, pitfalls, and future perspectives in applying PTM-centric proteomics to clinical samples. This includes samples obtained from a human subject, for instance (i) bodily fluids such as plasma, urine, or cerebrospinal fluid, (ii) primary cells such as reproductive cells, blood cells, and (iii) tissue samples/biopsies. Expert commentary: PTM-centric discovery proteomics can substantially contribute to the understanding of disease mechanisms by identifying signatures with potential diagnostic or even therapeutic relevance but may require coordinated efforts of interdisciplinary and eventually multi-national consortia, such as initiated in the cancer moonshot program. Additionally, robust and standardized mass spectrometry (MS) assays-particularly targeted MS, MALDI imaging, and immuno-MALDI-may be transferred to the clinic to improve patient stratification for precision medicine, and guide therapies.
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Affiliation(s)
- Ruzanna Mnatsakanyan
- a Protein Dynamics , Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V , Dortmund , 44227 , Germany
| | - Gerta Shema
- a Protein Dynamics , Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V , Dortmund , 44227 , Germany
| | - Mark Basik
- b Gerald Bronfman Department of Oncology , Jewish General Hospital, McGill University , Montreal , Quebec H4A 3T2 , Canada
| | - Gerald Batist
- b Gerald Bronfman Department of Oncology , Jewish General Hospital, McGill University , Montreal , Quebec H4A 3T2 , Canada
| | - Christoph H Borchers
- b Gerald Bronfman Department of Oncology , Jewish General Hospital, McGill University , Montreal , Quebec H4A 3T2 , Canada.,c University of Victoria-Genome British Columbia Proteomics Centre, University of Victoria , Victoria , British Columbia V8Z 7X8 , Canada.,d Department of Biochemistry and Microbiology , University of Victoria , Victoria , British Columbia , V8P 5C2 , Canada.,e Segal Cancer Proteomics Centre, Lady Davis Institute, Jewish General Hospital, McGill University , Montreal , Quebec H3T 1E2 , Canada
| | - Albert Sickmann
- a Protein Dynamics , Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V , Dortmund , 44227 , Germany.,f Medizinische Fakultät, Medizinische Proteom-Center (MPC), Ruhr-Universität Bochum , 44801 Bochum , Germany.,g Department of Chemistry , College of Physical Sciences, University of Aberdeen , Aberdeen AB24 3FX , Scotland , United Kingdom
| | - René P Zahedi
- a Protein Dynamics , Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V , Dortmund , 44227 , Germany.,b Gerald Bronfman Department of Oncology , Jewish General Hospital, McGill University , Montreal , Quebec H4A 3T2 , Canada.,e Segal Cancer Proteomics Centre, Lady Davis Institute, Jewish General Hospital, McGill University , Montreal , Quebec H3T 1E2 , Canada
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24
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Ghosh D, Bernstein JA, Khurana Hershey GK, Rothenberg ME, Mersha TB. Leveraging Multilayered "Omics" Data for Atopic Dermatitis: A Road Map to Precision Medicine. Front Immunol 2018; 9:2727. [PMID: 30631320 PMCID: PMC6315155 DOI: 10.3389/fimmu.2018.02727] [Citation(s) in RCA: 73] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2018] [Accepted: 11/05/2018] [Indexed: 12/14/2022] Open
Abstract
Atopic dermatitis (AD) is a complex multifactorial inflammatory skin disease that affects ~280 million people worldwide. About 85% of AD cases begin in childhood, a significant portion of which can persist into adulthood. Moreover, a typical progression of children with AD to food allergy, asthma or allergic rhinitis has been reported (“allergic march” or “atopic march”). AD comprises highly heterogeneous sub-phenotypes/endotypes resulting from complex interplay between intrinsic and extrinsic factors, such as environmental stimuli, and genetic factors regulating cutaneous functions (impaired barrier function, epidermal lipid, and protease abnormalities), immune functions and the microbiome. Though the roles of high-throughput “omics” integrations in defining endotypes are recognized, current analyses are primarily based on individual omics data and using binary clinical outcomes. Although individual omics analysis, such as genome-wide association studies (GWAS), can effectively map variants correlated with AD, the majority of the heritability and the functional relevance of discovered variants are not explained or known by the identified variants. The limited success of singular approaches underscores the need for holistic and integrated approaches to investigate complex phenotypes using trans-omics data integration strategies. Integrating omics layers (e.g., genome, epigenome, transcriptome, proteome, metabolome, lipidome, exposome, microbiome), which often have complementary and synergistic effects, might provide the opportunity to capture the flow of information underlying AD disease manifestation. Overlapping genes/candidates derived from multiple omics types include FLG, SPINK5, S100A8, and SERPINB3 in AD pathogenesis. Overlapping pathways include macrophage, endothelial cell and fibroblast activation pathways, in addition to well-known Th1/Th2 and NFkB activation pathways. Interestingly, there was more multi-omics overlap at the pathway level than gene level. Further analysis of multi-omics overlap at the tissue level showed that among 30 tissue types from the GTEx database, skin and esophagus were significantly enriched, indicating the biological interconnection between AD and food allergy. The present work explores multi-omics integration and provides new biological insights to better define the biological basis of AD etiology and confirm previously reported AD genes/pathways. In this context, we also discuss opportunities and challenges introduced by “big omics data” and their integration.
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Affiliation(s)
- Debajyoti Ghosh
- Division of Immunology, Allergy & Rheumatology, Department of Internal Medicine, University of Cincinnati, Cincinnati, OH, United States
| | - Jonathan A Bernstein
- Division of Immunology, Allergy & Rheumatology, Department of Internal Medicine, University of Cincinnati, Cincinnati, OH, United States
| | - Gurjit K Khurana Hershey
- Division of Asthma Research, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH, United States
| | - Marc E Rothenberg
- Division of Allergy and Immunology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH, United States
| | - Tesfaye B Mersha
- Division of Asthma Research, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH, United States
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25
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Gutierrez DB, Gant-Branum RL, Romer CE, Farrow MA, Allen JL, Dahal N, Nei YW, Codreanu SG, Jordan AT, Palmer LD, Sherrod SD, McLean JA, Skaar EP, Norris JL, Caprioli RM. An Integrated, High-Throughput Strategy for Multiomic Systems Level Analysis. J Proteome Res 2018; 17:3396-3408. [PMID: 30114907 DOI: 10.1021/acs.jproteome.8b00302] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Proteomics, metabolomics, and transcriptomics generate comprehensive data sets, and current biocomputational capabilities allow their efficient integration for systems biology analysis. Published multiomics studies cover methodological advances as well as applications to biological questions. However, few studies have focused on the development of a high-throughput, unified sample preparation approach to complement high-throughput omic analytics. This report details the automation, benchmarking, and application of a strategy for transcriptomic, proteomic, and metabolomic analyses from a common sample. The approach, sample preparation for multi-omics technologies (SPOT), provides equivalent performance to typical individual omic preparation methods but greatly enhances throughput and minimizes the resources required for multiomic experiments. SPOT was applied to a multiomics time course experiment for zinc-treated HL-60 cells. The data reveal Zn effects on NRF2 antioxidant and NFkappaB signaling. High-throughput approaches such as these are critical for the acquisition of temporally resolved, multicondition, large multiomic data sets such as those necessary to assess complex clinical and biological concerns. Ultimately, this type of approach will provide an expanded understanding of challenging scientific questions across many fields.
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Misra BB, Langefeld CD, Olivier M, Cox LA. Integrated Omics: Tools, Advances, and Future Approaches. J Mol Endocrinol 2018; 62:JME-18-0055. [PMID: 30006342 DOI: 10.1530/jme-18-0055] [Citation(s) in RCA: 220] [Impact Index Per Article: 36.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2018] [Revised: 07/02/2018] [Accepted: 07/12/2018] [Indexed: 12/13/2022]
Abstract
With the rapid adoption of high-throughput omic approaches to analyze biological samples such as genomics, transcriptomics, proteomics, and metabolomics, each analysis can generate tera- to peta-byte sized data files on a daily basis. These data file sizes, together with differences in nomenclature among these data types, make the integration of these multi-dimensional omics data into biologically meaningful context challenging. Variously named as integrated omics, multi-omics, poly-omics, trans-omics, pan-omics, or shortened to just 'omics', the challenges include differences in data cleaning, normalization, biomolecule identification, data dimensionality reduction, biological contextualization, statistical validation, data storage and handling, sharing, and data archiving. The ultimate goal is towards the holistic realization of a 'systems biology' understanding of the biological question in hand. Commonly used approaches in these efforts are currently limited by the 3 i's - integration, interpretation, and insights. Post integration, these very large datasets aim to yield unprecedented views of cellular systems at exquisite resolution for transformative insights into processes, events, and diseases through various computational and informatics frameworks. With the continued reduction in costs and processing time for sample analyses, and increasing types of omics datasets generated such as glycomics, lipidomics, microbiomics, and phenomics, an increasing number of scientists in this interdisciplinary domain of bioinformatics face these challenges. We discuss recent approaches, existing tools, and potential caveats in the integration of omics datasets for development of standardized analytical pipelines that could be adopted by the global omics research community.
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Affiliation(s)
- Biswapriya B Misra
- B Misra, Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, United States
| | - Carl D Langefeld
- C Langefeld, Biostatistical Sciences, Wake Forest University School of Medicine, Winston-Salem, United States
| | - Michael Olivier
- M Olivier, Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, United States
| | - Laura A Cox
- L Cox, Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, United States
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Rustam YH, Reid GE. Analytical Challenges and Recent Advances in Mass Spectrometry Based Lipidomics. Anal Chem 2017; 90:374-397. [PMID: 29166560 DOI: 10.1021/acs.analchem.7b04836] [Citation(s) in RCA: 209] [Impact Index Per Article: 29.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Affiliation(s)
- Yepy H Rustam
- Department of Biochemistry and Molecular Biology, University of Melbourne , Parkville, Victoria 3010, Australia
| | - Gavin E Reid
- Department of Biochemistry and Molecular Biology, University of Melbourne , Parkville, Victoria 3010, Australia.,School of Chemistry, University of Melbourne , Parkville, Victoria 3010, Australia.,Bio21 Molecular Science and Biotechnology Institute, University of Melbourne , Parkville, Victoria 3010, Australia
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Papaleo E, Gromova I, Gromov P. Gaining insights into cancer biology through exploration of the cancer secretome using proteomic and bioinformatic tools. Expert Rev Proteomics 2017; 14:1021-1035. [PMID: 28967788 DOI: 10.1080/14789450.2017.1387053] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
INTRODUCTION Tumor-associated proteins released by cancer cells and by tumor stroma cells, referred as 'cancer secretome', represent a valuable resource for discovery of potential cancer biomarkers. The last decade was marked by a great increase in number of studies focused on various aspects of cancer secretome including, composition and identification of components externalized by malignant cells and by the components of tumor microenvironment. Areas covered: Here, we provide an overview of achievements in the proteomic analysis of the cancer secretome, elicited through the tumor-associated interstitial fluid recovered from malignant tissues ex vivo or the protein component of conditioned media obtained from cultured cancer cells in vitro. We summarize various bioinformatic tools and approaches and critically appraise their outcomes, focusing on problems and challenges that arise when applied for the analysis of cancer secretomic databases. Expert commentary: Recent achievements in the omics- analysis of structural and metabolic aspects of altered cancer secretome contribute greatly to the various hallmarks of cancer including the identification of clinically significant biomarkers and potential targets for therapeutic intervention.
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Affiliation(s)
- Elena Papaleo
- a Danish Cancer Society Research Center, Computational Biology Laboratory , Copenhagen , Denmark
| | - Irina Gromova
- b Danish Cancer Society Research Center, Genome Integrity Unit, Breast Cancer Biology Group , Copenhagen , Denmark
| | - Pavel Gromov
- b Danish Cancer Society Research Center, Genome Integrity Unit, Breast Cancer Biology Group , Copenhagen , Denmark
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