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Li J, Tian J, Liu Y, Liu Z, Tong M. Personalized analysis of human cancer multi-omics for precision oncology. Comput Struct Biotechnol J 2024; 23:2049-2056. [PMID: 38783900 PMCID: PMC11112262 DOI: 10.1016/j.csbj.2024.05.011] [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: 01/30/2024] [Revised: 04/29/2024] [Accepted: 05/07/2024] [Indexed: 05/25/2024] Open
Abstract
Multi-omics technologies, encompassing genomics, proteomics, and transcriptomics, provide profound insights into cancer biology. A fundamental computational approach for analyzing multi-omics data is differential analysis, which identifies molecular distinctions between cancerous and normal tissues. Traditional methods, however, often fail to address the distinct heterogeneity of individual tumors, thereby neglecting crucial patient-specific molecular traits. This shortcoming underscores the necessity for tailored differential analysis algorithms, which focus on particular patient variations. Such approaches offer a more nuanced understanding of cancer biology and are instrumental in pinpointing personalized therapeutic strategies. In this review, we summarize the principles of current individualized techniques. We also review their efficacy in analyzing cancer multi-omics data and discuss their potential applications in clinical practice.
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Affiliation(s)
- Jiaao Li
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen, Fujian 361102, China
- School of Informatics, Xiamen University, Xiamen 316000, China
| | - Jingyi Tian
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen, Fujian 361102, China
- School of Informatics, Xiamen University, Xiamen 316000, China
| | - Yachen Liu
- National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, Fujian 361102, China
- School of Informatics, Xiamen University, Xiamen 316000, China
| | - Zan Liu
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen, Fujian 361102, China
- National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, Fujian 361102, China
- School of Informatics, Xiamen University, Xiamen 316000, China
| | - Mengsha Tong
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen, Fujian 361102, China
- National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, Fujian 361102, China
- School of Informatics, Xiamen University, Xiamen 316000, China
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2
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Mourino-Alvarez L, Juarez-Alia C, Sastre-Oliva T, Perales-Sánchez I, Hernandez-Fernandez G, Chicano-Galvez E, Peralbo-Molina Á, Madruga F, Blanco-Lopez E, Tejerina T, Barderas MG. Dysregulation of Lipid Metabolism Serves as A Link Between Alzheimer's and Cardiovascular Disease, As Witnessed in A Cross-Sectional Study. Aging Dis 2024:AD.2024.0434. [PMID: 39012677 DOI: 10.14336/ad.2024.0434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2024] [Accepted: 05/31/2024] [Indexed: 07/17/2024] Open
Abstract
Cardiovascular risk factors and established cardiovascular disease (CVD) increase the risk of suffering dementia of the Alzheimer's type (DAT). Here, we set out to define specific molecular profiles of CVD in patients with DAT to better understand its relationship, to unravel the mechanisms underlying the high risk of developing DAT in CVD patients and to define new markers of early disease. Plasma samples from patients with DAT, with and without CVD, were analyzed through a multiomics approach, with integration of metabolomics and proteomics datasets using the OmicsNet web-based tool. Metabolomics results showed an enrichment in lipids and lipid-like molecules. Similarly, the most significant cluster identified through proteomics was formed by 5 proteins related to lipoprotein and cholesterol metabolism. After integration and functional enrichment, glycerolipid metabolism, fatty acid degradation and sphingolipid metabolism were among the most significant functions. Finally, differential expression of ABCA1 and APOH proteins was verified, in an independent cohort also including controls and patients with CVD alone. Both proteins positively correlated with phospho-Tau (181), a classical hallmark of DAT. Different molecular profiles exist in patients with DAT, with and without CVD, with exacerbated alterations in patients in which DAT and CVD co-exist. This information may help to define biomarkers like ABCA1 and APOH that identify patients with cardiovascular dysfunction that are at high risk of developing DAT. Such markers will allow more personalized interventions to be selected, a further step towards precision medicine for individuals whose molecular profiles indicate a distinct response to the same management strategies.
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Affiliation(s)
- Laura Mourino-Alvarez
- Department of Vascular Physiopathology, Hospital Nacional de Paraplejicos, SESCAM, 45071 Toledo, Spain
- Department of Vascular Physiopathology, Hospital Nacional de Paraplejicos, IDISCAM, 45071 Toledo, Spain
| | - Cristina Juarez-Alia
- Department of Vascular Physiopathology, Hospital Nacional de Paraplejicos, SESCAM, 45071 Toledo, Spain
- Department of Vascular Physiopathology, Hospital Nacional de Paraplejicos, IDISCAM, 45071 Toledo, Spain
| | - Tamara Sastre-Oliva
- Department of Vascular Physiopathology, Hospital Nacional de Paraplejicos, SESCAM, 45071 Toledo, Spain
- Department of Vascular Physiopathology, Hospital Nacional de Paraplejicos, IDISCAM, 45071 Toledo, Spain
| | - Inés Perales-Sánchez
- Department of Vascular Physiopathology, Hospital Nacional de Paraplejicos, SESCAM, 45071 Toledo, Spain
- Department of Vascular Physiopathology, Hospital Nacional de Paraplejicos, IDISCAM, 45071 Toledo, Spain
| | - German Hernandez-Fernandez
- Department of Vascular Physiopathology, Hospital Nacional de Paraplejicos, SESCAM, 45071 Toledo, Spain
- Department of Vascular Physiopathology, Hospital Nacional de Paraplejicos, IDISCAM, 45071 Toledo, Spain
| | - Eduardo Chicano-Galvez
- IMIBIC Mass Spectrometry and Molecular Imaging Unit, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba (UCO), Córdoba, Spain
| | - Ángela Peralbo-Molina
- IMIBIC Mass Spectrometry and Molecular Imaging Unit, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba (UCO), Córdoba, Spain
| | - Felipe Madruga
- Departament of Geriatrics, Hospital Virgen del Valle, SESCAM, Toledo, Spain
| | - Emilio Blanco-Lopez
- Department of Cardiology, Ciudad Real General University Hospital, Ciudad Real, Spain
| | - Teresa Tejerina
- Department of Pharmacology, School of Medicine, Universidad Complutense de Madrid, Madrid, Spain
| | - María G Barderas
- Department of Vascular Physiopathology, Hospital Nacional de Paraplejicos, SESCAM, 45071 Toledo, Spain
- Department of Vascular Physiopathology, Hospital Nacional de Paraplejicos, IDISCAM, 45071 Toledo, Spain
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Pang Z, Lu Y, Zhou G, Hui F, Xu L, Viau C, Spigelman A, MacDonald P, Wishart D, Li S, Xia J. MetaboAnalyst 6.0: towards a unified platform for metabolomics data processing, analysis and interpretation. Nucleic Acids Res 2024; 52:W398-W406. [PMID: 38587201 PMCID: PMC11223798 DOI: 10.1093/nar/gkae253] [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: 01/31/2024] [Revised: 03/14/2024] [Accepted: 03/26/2024] [Indexed: 04/09/2024] Open
Abstract
We introduce MetaboAnalyst version 6.0 as a unified platform for processing, analyzing, and interpreting data from targeted as well as untargeted metabolomics studies using liquid chromatography - mass spectrometry (LC-MS). The two main objectives in developing version 6.0 are to support tandem MS (MS2) data processing and annotation, as well as to support the analysis of data from exposomics studies and related experiments. Key features of MetaboAnalyst 6.0 include: (i) a significantly enhanced Spectra Processing module with support for MS2 data and the asari algorithm; (ii) a MS2 Peak Annotation module based on comprehensive MS2 reference databases with fragment-level annotation; (iii) a new Statistical Analysis module dedicated for handling complex study design with multiple factors or phenotypic descriptors; (iv) a Causal Analysis module for estimating metabolite - phenotype causal relations based on two-sample Mendelian randomization, and (v) a Dose-Response Analysis module for benchmark dose calculations. In addition, we have also improved MetaboAnalyst's visualization functions, updated its compound database and metabolite sets, and significantly expanded its pathway analysis support to around 130 species. MetaboAnalyst 6.0 is freely available at https://www.metaboanalyst.ca.
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Affiliation(s)
- Zhiqiang Pang
- Institute of Parasitology, McGill University,Sainte-Anne-de-Bellevue, Quebec, Canada
| | - Yao Lu
- Department of Microbiology and Immunology, McGill University, Montreal, Quebec, Canada
| | - Guangyan Zhou
- Institute of Parasitology, McGill University,Sainte-Anne-de-Bellevue, Quebec, Canada
| | - Fiona Hui
- Institute of Parasitology, McGill University,Sainte-Anne-de-Bellevue, Quebec, Canada
| | - Lei Xu
- Institute of Parasitology, McGill University,Sainte-Anne-de-Bellevue, Quebec, Canada
| | - Charles Viau
- Institute of Parasitology, McGill University,Sainte-Anne-de-Bellevue, Quebec, Canada
| | - Aliya F Spigelman
- Department of Pharmacology and Alberta Diabetes Institute, University of Alberta, Edmonton, Alberta, Canada
| | - Patrick E MacDonald
- Department of Pharmacology and Alberta Diabetes Institute, University of Alberta, Edmonton, Alberta, Canada
| | - David S Wishart
- Departments of Biological Sciences and Computing Science, University of Alberta, Edmonton, Alberta, Canada
| | - Shuzhao Li
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
- University of Connecticut School of Medicine, Farmington, CT, USA
| | - Jianguo Xia
- Institute of Parasitology, McGill University,Sainte-Anne-de-Bellevue, Quebec, Canada
- Department of Microbiology and Immunology, McGill University, Montreal, Quebec, Canada
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4
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Baumert BO, Maretti-Mira AC, Li Z, Stratakis N, Zhao Y, Walker DI, Wang H, Fischer FC, Jia Q, Valvi D, Bartell SM, Chen C, Inge T, Ryder J, Jenkins T, Sisley S, Xanthakos S, Kohli R, Rock S, Eckel SP, La Merrill MA, Aung MM, Salomon MP, McConnell R, Goodrich J, Conti DV, Golden-Mason L, Chatzi L. PFHpA alters lipid metabolism and increases the risk of metabolic dysfunction-associated steatotic liver disease in youth-a translational research framework. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.01.24309775. [PMID: 39006440 PMCID: PMC11245066 DOI: 10.1101/2024.07.01.24309775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
To address the growing epidemic of liver disease, particularly in pediatric populations, it is crucial to identify modifiable risk factors for the development and progression of metabolic dysfunction-associated steatotic liver disease (MASLD). Per- and polyfluoroalkyl substances (PFAS) are persistent ubiquitous chemicals and have emerged as potential risk factors for liver damage. However, their impact on the etiology and severity of MASLD remains largely unexplored in humans. This study aims to bridge the gap between human and in vitro studies to understand how exposure to perfluoroheptanoic acid (PFHpA), one of the emerging PFAS replacements which accumulates in high concentrations in the liver, contributes to MASLD risk and progression. First, we showed that PFHpA plasma concentrations were significantly associated with increased risk of MASLD in obese adolescents. Further, we examined the impact of PFHpA on hepatic metabolism using 3D human liver spheroids and single-cell transcriptomics to identify major hepatic pathways affected by PFHpA. Next, we integrated the in vivo and in vitro multi-omics datasets with a novel statistical approach which identified signatures of proteins and metabolites associated with MASLD development triggered by PFHpA exposure. In addition to characterizing the contribution of PFHpA to MASLD progression, our study provides a novel strategy to identify individuals at high risk of PFHpA-induced MASLD and develop early intervention strategies. Notably, our analysis revealed that the proteomic signature exhibited a stronger correlation between both PFHpA exposure and MASLD risk compared to the metabolomic signature. While establishing a clear connection between PFHpA exposure and MASLD progression in humans, our study delved into the molecular mechanisms through which PFHpA disrupts liver metabolism. Our in vitro findings revealed that PFHpA primarily impacts lipid metabolism, leading to a notable increase of lipid accumulation in human hepatocytes after PFHpA exposure. Among the pathways involved in lipid metabolism in hepatocytes, regulation of lipid metabolism by PPAR-a showed a remarkable activation. Moreover, the translational research framework we developed by integrating human and in vitro data provided us biomarkers to identify individuals at a high risk of MASLD due to PFHpA exposure. Our framework can inform policies on PFAS-induced liver disease and identify potential targets for prevention and treatment strategies.
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5
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Belding LD, Thorstensen MJ, Quijada-Rodriguez AR, Bugg WS, Yoon GR, Loeppky AR, Allen GJP, Schoen AN, Earhart ML, Brandt C, Ali JL, Weihrauch D, Jeffries KM, Anderson WG. Integrated organismal responses induced by projected levels of CO 2 and temperature exposures in the early life stages of lake sturgeon. Mol Ecol 2024; 33:e17432. [PMID: 38887831 DOI: 10.1111/mec.17432] [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] [Received: 02/19/2024] [Revised: 05/26/2024] [Accepted: 05/31/2024] [Indexed: 06/20/2024]
Abstract
Atmospheric CO2 and temperature are rising concurrently, and may have profound impacts on the transcriptional, physiological and behavioural responses of aquatic organisms. Further, spring snowmelt may cause transient increases of pCO2 in many freshwater systems. We examined the behavioural, physiological and transcriptomic responses of an ancient fish, the lake sturgeon (Acipenser fulvescens) to projected levels of warming and pCO2 during its most vulnerable period of life, the first year. Specifically, larval fish were raised in either low (16°C) or high (22°C) temperature, and/or low (1000 μatm) or high (2500 μatm) pCO2 in a crossed experimental design over approximately 8 months. Following overwintering, lake sturgeon were exposed to a transient increase in pCO2 of 10,000 μatm, simulating a spring melt based on data in freshwater systems. Transcriptional analyses revealed potential connections to otolith formation and reduced growth in fish exposed to high pCO2 and temperature in combination. Network analyses of differential gene expression revealed different biological processes among the different treatments on the edges of transcriptional networks. Na+/K+-ATPase activity increased in fish not exposed to elevated pCO2 during development, and mRNA abundance of the β subunit was most strongly predictive of enzyme activity. Behavioural assays revealed a decrease in total activity following an acute CO2 exposure. These results demonstrate compensatory and compounding mechanisms of pCO2 and warming dependent on developmental conditions in lake sturgeon. Conserved elements of the cellular stress response across all organisms provide key information for how other freshwater organisms may respond to future climate change.
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Affiliation(s)
- Luke D Belding
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Matt J Thorstensen
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | | | - William S Bugg
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
- Pacific Salmon Foundation, Vancouver, British Columbia, Canada
| | - Gwangseok R Yoon
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
- Department of Biological Sciences, University of Toronto Scarborough, Toronto, Ontario, Canada
| | - Alison R Loeppky
- Ecology and Environmental Impact, WSP Canada Inc., Winnipeg, Manitoba, Canada
| | - Garrett J P Allen
- Institute of Cellular and Organismic Biology, Academia Sinica, Taipei, Taiwan
| | - Alexandra N Schoen
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
- Department of Biology, University of Winnipeg, Winnipeg, Manitoba, Canada
| | - Madison L Earhart
- Department of Zoology, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - Jennifer L Ali
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
| | - Dirk Weihrauch
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Kenneth M Jeffries
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - W Gary Anderson
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
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6
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Sharma A, Debik J, Naume B, Ohnstad HO, Bathen TF, Giskeødegård GF. Comprehensive multi-omics analysis of breast cancer reveals distinct long-term prognostic subtypes. Oncogenesis 2024; 13:22. [PMID: 38871719 DOI: 10.1038/s41389-024-00521-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 05/20/2024] [Accepted: 05/22/2024] [Indexed: 06/15/2024] Open
Abstract
Breast cancer (BC) is a leading cause of cancer-related death worldwide. The diverse nature and heterogeneous biology of BC pose challenges for survival prediction, as patients with similar diagnoses often respond differently to treatment. Clinically relevant BC intrinsic subtypes have been established through gene expression profiling and are implemented in the clinic. While these intrinsic subtypes show a significant association with clinical outcomes, their long-term survival prediction beyond 5 years often deviates from expected clinical outcomes. This study aimed to identify naturally occurring long-term prognostic subgroups of BC based on an integrated multi-omics analysis. This study incorporates a clinical cohort of 335 untreated BC patients from the Oslo2 study with long-term follow-up (>12 years). Multi-Omics Factor Analysis (MOFA+) was employed to integrate transcriptomic, proteomic, and metabolomic data obtained from the tumor tissues. Our analysis revealed three prominent multi-omics clusters of BC patients with significantly different long-term prognoses (p = 0.005). The multi-omics clusters were validated in two independent large cohorts, METABRIC and TCGA. Importantly, a lack of prognostic association to long-term follow-up above 12 years in the previously established intrinsic subtypes was shown for these cohorts. Through a systems-biology approach, we identified varying enrichment levels of cell-cycle and immune-related pathways among the prognostic clusters. Integrated multi-omics analysis of BC revealed three distinct clusters with unique clinical and biological characteristics. Notably, these multi-omics clusters displayed robust associations with long-term survival, outperforming the established intrinsic subtypes.
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Affiliation(s)
- Abhibhav Sharma
- Department of Public Health and Nursing (ISM), Norwegian University of Science and Technology- NTNU, Trondheim, Norway.
| | - Julia Debik
- Department of Public Health and Nursing (ISM), Norwegian University of Science and Technology- NTNU, Trondheim, Norway
- Department of Circulation and Medical Imaging, NTNU, Trondheim, Norway
| | - Bjørn Naume
- Department of Oncology, Division of Cancer Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Hege Oma Ohnstad
- Department of Oncology, Division of Cancer Medicine, Oslo University Hospital, Oslo, Norway
| | - Tone F Bathen
- Department of Circulation and Medical Imaging, NTNU, Trondheim, Norway
| | - Guro F Giskeødegård
- Department of Public Health and Nursing (ISM), Norwegian University of Science and Technology- NTNU, Trondheim, Norway.
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7
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Guo Y, Luo L, Zhu J, Li C. Advance in Multi-omics Research Strategies on Cholesterol Metabolism in Psoriasis. Inflammation 2024; 47:839-852. [PMID: 38244176 DOI: 10.1007/s10753-023-01961-9] [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] [Received: 09/24/2023] [Revised: 11/29/2023] [Accepted: 12/25/2023] [Indexed: 01/22/2024]
Abstract
The skin is a complex and dynamic organ where homeostasis is maintained through the intricate interplay between the immune system and metabolism, particularly cholesterol metabolism. Various factors such as cytokines, inflammatory mediators, cholesterol metabolites, and metabolic enzymes play crucial roles in facilitating these interactions. Dysregulation of this delicate balance contributes to the pathogenic pathways of inflammatory skin conditions, notably psoriasis. In this article, we provide an overview of omics biomarkers associated with psoriasis in relation to cholesterol metabolism. We explore multi-omics approaches that reveal the communication between immunometabolism and psoriatic inflammation. Additionally, we summarize the use of multi-omics strategies to uncover the complexities of multifactorial and heterogeneous inflammatory diseases. Finally, we highlight potential future perspectives related to targeted drug therapies and research areas that can advance precise medicine. This review aims to serve as a valuable resource for those investigating the role of cholesterol metabolism in psoriasis.
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Affiliation(s)
- Youming Guo
- Hospital for Skin Diseases, Institute of Dermatology, Chinese Academy of Medical Sciences & Peking Union Medical College, Nanjing, Jiangsu, China
- Jiangsu Key Laboratory of Molecular Biology for Skin Diseases and STIs, Nanjing, Jiangsu, China
| | - Lingling Luo
- Hospital for Skin Diseases, Institute of Dermatology, Chinese Academy of Medical Sciences & Peking Union Medical College, Nanjing, Jiangsu, China
| | - Jing Zhu
- Hospital for Skin Diseases, Institute of Dermatology, Chinese Academy of Medical Sciences & Peking Union Medical College, Nanjing, Jiangsu, China
| | - Chengrang Li
- Hospital for Skin Diseases, Institute of Dermatology, Chinese Academy of Medical Sciences & Peking Union Medical College, Nanjing, Jiangsu, China.
- Jiangsu Key Laboratory of Molecular Biology for Skin Diseases and STIs, Nanjing, Jiangsu, China.
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8
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Wu S, Zhou H, Chen D, Lu Y, Li Y, Qiao J. Multi-omic analysis tools for microbial metabolites prediction. Brief Bioinform 2024; 25:bbae264. [PMID: 38859767 PMCID: PMC11165163 DOI: 10.1093/bib/bbae264] [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] [Received: 02/03/2024] [Revised: 05/08/2024] [Indexed: 06/12/2024] Open
Abstract
How to resolve the metabolic dark matter of microorganisms has long been a challenging problem in discovering active molecules. Diverse omics tools have been developed to guide the discovery and characterization of various microbial metabolites, which make it gradually possible to predict the overall metabolites for individual strains. The combinations of multi-omic analysis tools effectively compensates for the shortcomings of current studies that focus only on single omics or a broad class of metabolites. In this review, we systematically update, categorize and sort out different analysis tools for microbial metabolites prediction in the last five years to appeal for the multi-omic combination on the understanding of the metabolic nature of microbes. First, we provide the general survey on different updated prediction databases, webservers, or software that based on genomics, transcriptomics, proteomics, and metabolomics, respectively. Then, we discuss the essentiality on the integration of multi-omics data to predict metabolites of different microbial strains and communities, as well as stressing the combination of other techniques, such as systems biology methods and data-driven algorithms. Finally, we identify key challenges and trends in developing multi-omic analysis tools for more comprehensive prediction on diverse microbial metabolites that contribute to human health and disease treatment.
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Affiliation(s)
- Shengbo Wu
- School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
- Zhejiang Institute of Tianjin University, Shaoxing, Shaoxing 312300, China
| | - Haonan Zhou
- School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
| | - Danlei Chen
- School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
- Zhejiang Institute of Tianjin University, Shaoxing, Shaoxing 312300, China
| | - Yutong Lu
- Zhejiang Institute of Tianjin University, Shaoxing, Shaoxing 312300, China
| | - Yanni Li
- School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
- Key Laboratory of Systems Bioengineering, Ministry of Education (Tianjin University), Tianjin 300072, China
| | - Jianjun Qiao
- School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
- Zhejiang Institute of Tianjin University, Shaoxing, Shaoxing 312300, China
- Key Laboratory of Systems Bioengineering, Ministry of Education (Tianjin University), Tianjin 300072, China
- Frontiers Science Center for Synthetic Biology (Ministry of Education), Tianjin University, Tianjin 300072, China
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9
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Ewald JD, Zhou G, Lu Y, Kolic J, Ellis C, Johnson JD, Macdonald PE, Xia J. Web-based multi-omics integration using the Analyst software suite. Nat Protoc 2024; 19:1467-1497. [PMID: 38355833 DOI: 10.1038/s41596-023-00950-4] [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: 04/17/2023] [Accepted: 11/21/2023] [Indexed: 02/16/2024]
Abstract
The growing number of multi-omics studies demands clear conceptual workflows coupled with easy-to-use software tools to facilitate data analysis and interpretation. This protocol covers three key components involved in multi-omics analysis, including single-omics data analysis, knowledge-driven integration using biological networks and data-driven integration through joint dimensionality reduction. Using the dataset from a recent multi-omics study of human pancreatic islet tissue and plasma samples, the first section introduces how to perform transcriptomics/proteomics data analysis using ExpressAnalyst and lipidomics data analysis using MetaboAnalyst. On the basis of significant features detected in these workflows, the second section demonstrates how to perform knowledge-driven integration using OmicsNet. The last section illustrates how to perform data-driven integration from the normalized omics data and metadata using OmicsAnalyst. The complete protocol can be executed in ~2 h. Compared with other available options for multi-omics integration, the Analyst software suite described in this protocol enables researchers to perform a wide range of omics data analysis tasks via a user-friendly web interface.
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Affiliation(s)
- Jessica D Ewald
- Institute of Parasitology, McGill University, Montreal, Quebec, Canada
| | - Guangyan Zhou
- Institute of Parasitology, McGill University, Montreal, Quebec, Canada
| | - Yao Lu
- Department of Microbiology and Immunology, McGill University, Montreal, Quebec, Canada
| | - Jelena Kolic
- Life Sciences Institute, Department of Cellular and Physiological Sciences, University of British Columbia, Vancouver, British Columbia, Canada
| | - Cara Ellis
- Department of Pharmacology, University of Alberta, Edmonton, Alberta, Canada
| | - James D Johnson
- Life Sciences Institute, Department of Cellular and Physiological Sciences, University of British Columbia, Vancouver, British Columbia, Canada
| | - Patrick E Macdonald
- Department of Pharmacology, University of Alberta, Edmonton, Alberta, Canada
| | - Jianguo Xia
- Institute of Parasitology, McGill University, Montreal, Quebec, Canada.
- Department of Microbiology and Immunology, McGill University, Montreal, Quebec, Canada.
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10
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Zhang J, Chen W, Chen G, Flannick J, Fikse E, Smerin G, Degner K, Yang Y, Xu C, Li Y, Hanover JA, Simonds WF. Ancestry-specific high-risk gene variant profiling unmasks diabetes-associated genes. Hum Mol Genet 2024; 33:655-666. [PMID: 36255737 PMCID: PMC11000659 DOI: 10.1093/hmg/ddac255] [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: 05/04/2022] [Revised: 09/28/2022] [Accepted: 10/10/2022] [Indexed: 11/15/2022] Open
Abstract
How ancestry-associated genetic variance affects disparities in the risk of polygenic diseases and influences the identification of disease-associated genes warrants a deeper understanding. We hypothesized that the discovery of genes associated with polygenic diseases may be limited by the overreliance on single-nucleotide polymorphism (SNP)-based genomic investigation, as most significant variants identified in genome-wide SNP association studies map to introns and intergenic regions of the genome. To overcome such potential limitations, we developed a gene-constrained, function-based analytical method centered on high-risk variants (hrV) that encode frameshifts, stopgains or splice site disruption. We analyzed the total number of hrV per gene in populations of different ancestry, representing a total of 185 934 subjects. Using this analysis, we developed a quantitative index of hrV (hrVI) across 20 428 genes within each population. We then applied hrVI analysis to the discovery of genes associated with type 2 diabetes mellitus (T2DM), a polygenic disease with ancestry-related disparity. HrVI profiling and gene-to-gene comparisons of ancestry-specific hrV between the case (20 781 subjects) and control (24 440 subjects) populations in the T2DM national repository identified 57 genes associated with T2DM, 40 of which were discoverable only by ancestry-specific analysis. These results illustrate how a function-based, ancestry-specific analysis of genetic variations can accelerate the identification of genes associated with polygenic diseases. Besides T2DM, such analysis may facilitate our understanding of the genetic basis for other polygenic diseases that are also greatly influenced by environmental and behavioral factors, such as obesity, hypertension and Alzheimer's disease.
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Affiliation(s)
- Jianhua Zhang
- Metabolic Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD 20892, United States
| | - Weiping Chen
- Genomic Core, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD 20892, United States
- Laboratory of Cell and Molecular Biology, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD 20892, United States
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, United States
| | - Jason Flannick
- Metabolism Program, Broad Institute, Cambridge, MA 02142, United States
| | - Emma Fikse
- Metabolic Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD 20892, United States
| | - Glenda Smerin
- Metabolic Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD 20892, United States
| | - Katherine Degner
- Metabolic Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD 20892, United States
| | - Yanqin Yang
- Laboratory of Transplantation Genomics, National Heart Lung and Blood Institute; National Institutes of Health, Bethesda, MD 20892, United States
| | - Catherine Xu
- Genomic Core, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD 20892, United States
| | | | - Yulong Li
- Milton S. Hershey Medical Center, Division of Endocrinology, Diabetes and Metabolism, Penn State University, Hershey, PA 17033, United States
| | - John A Hanover
- Laboratory of Cell and Molecular Biology, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD 20892, United States
| | - William F Simonds
- Metabolic Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD 20892, United States
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11
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Ye J, Fan H, Shi R, Song G, Wu X, Wang D, Xia B, Zhao Z, Zhao B, Liu X, Wang Y, Dai X. Dietary lipoic acid alleviates autism-like behavior induced by acrylamide in adolescent mice: the potential involvement of the gut-brain axis. Food Funct 2024; 15:3395-3410. [PMID: 38465655 DOI: 10.1039/d3fo05078e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Consuming fried foods has been associated with an increased susceptibility to mental health disorders. Nevertheless, the impact of alpha-lipoic acid (α-LA, LA) on fried food-induced autism-like behavior remains unclear. This study aimed to explore how LA affects autism-related behavior and cognitive deficits caused by acrylamide in mice, a representative food hazard found in fried foods. This improvement was accomplished by enhanced synaptic plasticity, increased neurotrophin expression, elevated calcium-binding protein D28k, and restored serotonin. Additionally, LA substantially influenced the abundance of bacteria linked to autism and depression, simultaneously boosted short-chain fatty acid (SCFA) levels in fecal samples, and induced changes in serum amino acid concentrations. In summary, these findings suggested that exposure to acrylamide in adolescent mice could induce the development of social disorders in adulthood. LA showed promise as a nutritional intervention strategy to tackle emotional disorders during adolescence.
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Affiliation(s)
- Jin Ye
- College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi, China.
| | - Hua Fan
- College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi, China.
| | - Renjie Shi
- College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi, China.
| | - Ge Song
- BGI Institute of Applied Agriculture, BGI-Shenzhen, Shenzhen, China.
| | - Xiaoning Wu
- College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi, China.
| | - Danna Wang
- College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi, China.
| | - Bing Xia
- College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi, China.
| | - Zhenting Zhao
- College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi, China.
| | - Beita Zhao
- College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi, China.
| | - Xuebo Liu
- College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi, China.
| | - Yutang Wang
- College of Food Science and Engineering, Northwest A&F University, Yangling, Shaanxi, China.
| | - Xiaoshuang Dai
- BGI Institute of Applied Agriculture, BGI-Shenzhen, Shenzhen, China.
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12
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Alabed HBR, Pellegrino RM, Buratta S, Lema Fernandez AG, La Starza R, Urbanelli L, Mecucci C, Emiliani C, Gorello P. Metabolic Profiling as an Approach to Differentiate T-Cell Acute Lymphoblastic Leukemia Cell Lines Belonging to the Same Genetic Subgroup. Int J Mol Sci 2024; 25:3921. [PMID: 38612731 PMCID: PMC11011837 DOI: 10.3390/ijms25073921] [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] [Received: 02/29/2024] [Revised: 03/24/2024] [Accepted: 03/29/2024] [Indexed: 04/14/2024] Open
Abstract
T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive tumor mainly affecting children and adolescents. It is driven by multiple genetic mutations that together define the leukemic phenotype. Interestingly, based on genetic alterations and/or deregulated expression, at least six genetic subgroups have been recognized. The TAL/LMO subgroup is one of the most represented genetic subgroups, characterizing 30-45% of pediatric T-ALL cases. The study of lipid and metabolic profiles is increasingly recognized as a valuable tool for comprehending the development and progression of tumors. In this study, metabolic and lipidomic analysis via LC/MS have been carried out on four T-ALL cell lines belonging to the TAL/LMO subgroup (Jurkat, Molt-4, Molt-16, and CCRF-CEM) to identify new potential metabolic biomarkers and to provide a subclassification of T-ALL cell lines belonging to the same subgroup. A total of 343 metabolites were annotated, including 126 polar metabolites and 217 lipid molecules. The statistical analysis, for both metabolic and lipid profiles, shows significant differences and similarities among the four cell lines. The Molt-4 cell line is the most distant cell line and CCRF-CEM shows a high activity in specific pathways when compared to the other cell lines, while Molt-16 and Jurkat show a similar metabolic profile. Additionally, this study highlighted the pathways that differ in each cell line and the possible enzymes involved using bioinformatic tools, capable of predicting the pathways involved by studying the differences in the metabolic profiles. This experiment offers an approach to differentiate T-ALL cell lines and could open the way to verify and confirm the obtained results directly in patients.
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Affiliation(s)
- Husam B. R. Alabed
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06100 Perugia, Italy (R.M.P.); (S.B.); (L.U.)
| | - Roberto Maria Pellegrino
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06100 Perugia, Italy (R.M.P.); (S.B.); (L.U.)
| | - Sandra Buratta
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06100 Perugia, Italy (R.M.P.); (S.B.); (L.U.)
- Centro di Eccellenza sui Materiali Innovativi Nanostrutturati (CEMIN), University of Perugia, Via del Giochetto, 06123 Perugia, Italy
| | - Anair Graciela Lema Fernandez
- Hematology and Bone Marrow Transplantation Unit, Laboratory of Molecular Medicine (CREO), Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy; (A.G.L.F.); (C.M.)
| | - Roberta La Starza
- Hematology and Bone Marrow Transplantation Unit, Laboratory of Molecular Medicine (CREO), Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy; (A.G.L.F.); (C.M.)
| | - Lorena Urbanelli
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06100 Perugia, Italy (R.M.P.); (S.B.); (L.U.)
- Centro di Eccellenza sui Materiali Innovativi Nanostrutturati (CEMIN), University of Perugia, Via del Giochetto, 06123 Perugia, Italy
| | - Cristina Mecucci
- Hematology and Bone Marrow Transplantation Unit, Laboratory of Molecular Medicine (CREO), Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy; (A.G.L.F.); (C.M.)
| | - Carla Emiliani
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06100 Perugia, Italy (R.M.P.); (S.B.); (L.U.)
- Centro di Eccellenza sui Materiali Innovativi Nanostrutturati (CEMIN), University of Perugia, Via del Giochetto, 06123 Perugia, Italy
| | - Paolo Gorello
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06100 Perugia, Italy (R.M.P.); (S.B.); (L.U.)
- Centro di Eccellenza sui Materiali Innovativi Nanostrutturati (CEMIN), University of Perugia, Via del Giochetto, 06123 Perugia, Italy
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13
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Munk K, Ilina D, Ziemba L, Brader G, Molin EM. Holomics - a user-friendly R shiny application for multi-omics data integration and analysis. BMC Bioinformatics 2024; 25:93. [PMID: 38438871 PMCID: PMC10913680 DOI: 10.1186/s12859-024-05719-4] [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] [Received: 12/11/2023] [Accepted: 02/26/2024] [Indexed: 03/06/2024] Open
Abstract
An organism's observable traits, or phenotype, result from intricate interactions among genes, proteins, metabolites and the environment. External factors, such as associated microorganisms, along with biotic and abiotic stressors, can significantly impact this complex biological system, influencing processes like growth, development and productivity. A comprehensive analysis of the entire biological system and its interactions is thus crucial to identify key components that support adaptation to stressors and to discover biomarkers applicable in breeding programs or disease diagnostics. Since the genomics era, several other 'omics' disciplines have emerged, and recent advances in high-throughput technologies have facilitated the generation of additional omics datasets. While traditionally analyzed individually, the last decade has seen an increase in multi-omics data integration and analysis strategies aimed at achieving a holistic understanding of interactions across different biological layers. Despite these advances, the analysis of multi-omics data is still challenging due to their scale, complexity, high dimensionality and multimodality. To address these challenges, a number of analytical tools and strategies have been developed, including clustering and differential equations, which require advanced knowledge in bioinformatics and statistics. Therefore, this study recognizes the need for user-friendly tools by introducing Holomics, an accessible and easy-to-use R shiny application with multi-omics functions tailored for scientists with limited bioinformatics knowledge. Holomics provides a well-defined workflow, starting with the upload and pre-filtering of single-omics data, which are then further refined by single-omics analysis focusing on key features. Subsequently, these reduced datasets are subjected to multi-omics analyses to unveil correlations between 2-n datasets. This paper concludes with a real-world case study where microbiomics, transcriptomics and metabolomics data from previous studies that elucidate factors associated with improved sugar beet storability are integrated using Holomics. The results are discussed in the context of the biological background, underscoring the importance of multi-omics insights. This example not only highlights the versatility of Holomics in handling different types of omics data, but also validates its consistency by reproducing findings from preceding single-omics studies.
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Affiliation(s)
- Katharina Munk
- Center for Health & Bioresources, AIT Austrian Institute of Technology, Konrad-Lorenz-Straße 24, 3430, Tulln, Austria
| | - Daria Ilina
- Center for Health & Bioresources, AIT Austrian Institute of Technology, Konrad-Lorenz-Straße 24, 3430, Tulln, Austria
| | - Lisa Ziemba
- Center for Health & Bioresources, AIT Austrian Institute of Technology, Konrad-Lorenz-Straße 24, 3430, Tulln, Austria
| | - Günter Brader
- Center for Health & Bioresources, AIT Austrian Institute of Technology, Konrad-Lorenz-Straße 24, 3430, Tulln, Austria
| | - Eva M Molin
- Center for Health & Bioresources, AIT Austrian Institute of Technology, Konrad-Lorenz-Straße 24, 3430, Tulln, Austria.
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14
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Kim MJ, Kulkarni V, Goode MA, Hernandez J, Graham S, Sivesind TE, Manchadi ML. Utilizing systems genetics to enhance understanding into molecular targets of skin cancer. Exp Dermatol 2024; 33:e15043. [PMID: 38459629 PMCID: PMC11018140 DOI: 10.1111/exd.15043] [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] [Received: 12/31/2023] [Revised: 02/12/2024] [Accepted: 02/16/2024] [Indexed: 03/10/2024]
Abstract
Despite progress made with immune checkpoint inhibitors and targeted therapies, skin cancer remains a significant public health concern in the United States. The intricacies of the disease, encompassing genetics, immune responses, and external factors, call for a comprehensive approach. Techniques in systems genetics, including transcriptional correlation analysis, functional pathway enrichment analysis, and protein-protein interaction network analysis, prove valuable in deciphering intricate molecular mechanisms and identifying potential diagnostic and therapeutic targets for skin cancer. Recent studies demonstrate the efficacy of these techniques in uncovering molecular processes and pinpointing diagnostic markers for various skin cancer types, highlighting the potential of systems genetics in advancing innovative therapies. While certain limitations exist, such as generalizability and contextualization of external factors, the ongoing progress in AI technologies provides hope in overcoming these challenges. By providing protocols and a practical example involving Braf, we aim to inspire early-career experimental dermatologists to adopt these tools and seamlessly integrate these techniques into their skin cancer research, positioning them at the forefront of innovative approaches in combating this devastating disease.
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Affiliation(s)
- Minjae J Kim
- University of Tennessee Health Science Center School of Medicine, Memphis, Tennessee, USA
| | | | - Micah A Goode
- University of Tennessee Health Science Center School of Medicine, Memphis, Tennessee, USA
| | - Jacob Hernandez
- University of Tennessee Health Science Center School of Medicine, Memphis, Tennessee, USA
| | - Sean Graham
- University of Tennessee Health Science Center School of Medicine, Memphis, Tennessee, USA
| | - Torunn E Sivesind
- Department of Dermatology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
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15
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Nishida K, Maruyama J, Kaizu K, Takahashi K, Yugi K. Transomics2cytoscape: an automated software for interpretable 2.5-dimensional visualization of trans-omic networks. NPJ Syst Biol Appl 2024; 10:16. [PMID: 38374087 PMCID: PMC10876688 DOI: 10.1038/s41540-024-00342-8] [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] [Received: 04/05/2023] [Accepted: 01/22/2024] [Indexed: 02/21/2024] Open
Abstract
Biochemical network visualization is one of the essential technologies for mechanistic interpretation of omics data. In particular, recent advances in multi-omics measurement and analysis require the development of visualization methods that encompass multiple omics data. Visualization in 2.5 dimension (2.5D visualization), which is an isometric view of stacked X-Y planes, is a convenient way to interpret multi-omics/trans-omics data in the context of the conventional layouts of biochemical networks drawn on each of the stacked omics layers. However, 2.5D visualization of trans-omics networks is a state-of-the-art method that primarily relies on time-consuming human efforts involving manual drawing. Here, we present an R Bioconductor package 'transomics2cytoscape' for automated visualization of 2.5D trans-omics networks. We confirmed that transomics2cytoscape could be used for rapid visualization of trans-omics networks presented in published papers within a few minutes. Transomics2cytoscape allows for frequent update/redrawing of trans-omics networks in line with the progress in multi-omics/trans-omics data analysis, thereby enabling network-based interpretation of multi-omics data at each research step. The transomics2cytoscape source code is available at https://github.com/ecell/transomics2cytoscape .
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Affiliation(s)
- Kozo Nishida
- Laboratory for Integrated Cellular Systems, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
- Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 2-24-16 Nakamachi, Koganei-shi, Tokyo, 184-8588, Japan
| | - Junichi Maruyama
- Laboratory for Integrated Cellular Systems, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
| | - Kazunari Kaizu
- Center for Biosystems Dynamics Research (BDR), RIKEN, 6-2-3 Furuedai, Suita, Osaka, 565-0874, Japan
| | - Koichi Takahashi
- Center for Biosystems Dynamics Research (BDR), RIKEN, 6-2-3 Furuedai, Suita, Osaka, 565-0874, Japan
- Institute for Advanced Biosciences, Keio University, Fujisawa, 252-8520, Japan
| | - Katsuyuki Yugi
- Laboratory for Integrated Cellular Systems, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan.
- Institute for Advanced Biosciences, Keio University, Fujisawa, 252-8520, Japan.
- Department of Biological Sciences, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
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16
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Longin H, Broeckaert N, van Noort V, Lavigne R, Hendrix H. Posttranslational modifications in bacteria during phage infection. Curr Opin Microbiol 2024; 77:102425. [PMID: 38262273 DOI: 10.1016/j.mib.2024.102425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 12/08/2023] [Accepted: 01/02/2024] [Indexed: 01/25/2024]
Abstract
During phage infection, both virus and bacteria attempt to gain and/or maintain control over critical bacterial functions, through a plethora of strategies. These strategies include posttranslational modifications (PTMs, including phosphorylation, ribosylation, and acetylation), as rapid and dynamic regulators of protein behavior. However, to date, knowledge on the topic remains scarce and fragmented, while a more systematic investigation lies within reach. The release of AlphaFold, which advances PTM enzyme discovery and functional elucidation, and the increasing inclusivity and scale of mass spectrometry applications to new PTM types, could significantly accelerate research in the field. In this review, we highlight the current knowledge on PTMs during phage infection, and conceive a possible pipeline for future research, following an enzyme-target-function scheme.
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Affiliation(s)
- Hannelore Longin
- Computational Systems Biology, Department of Microbial and Molecular Systems, KU Leuven, Kasteelpark Arenberg 20 box 2460, 3001 Heverlee, Belgium; Laboratory of Gene Technology, Department of Biosystems, KU Leuven, Kasteelpark Arenberg 21 box 2462, 3001 Heverlee, Belgium
| | - Nand Broeckaert
- Computational Systems Biology, Department of Microbial and Molecular Systems, KU Leuven, Kasteelpark Arenberg 20 box 2460, 3001 Heverlee, Belgium; Laboratory of Gene Technology, Department of Biosystems, KU Leuven, Kasteelpark Arenberg 21 box 2462, 3001 Heverlee, Belgium
| | - Vera van Noort
- Computational Systems Biology, Department of Microbial and Molecular Systems, KU Leuven, Kasteelpark Arenberg 20 box 2460, 3001 Heverlee, Belgium; Institute of Biology, Leiden University, Sylviusweg 72, 2333 Leiden, the Netherlands
| | - Rob Lavigne
- Laboratory of Gene Technology, Department of Biosystems, KU Leuven, Kasteelpark Arenberg 21 box 2462, 3001 Heverlee, Belgium
| | - Hanne Hendrix
- Laboratory of Gene Technology, Department of Biosystems, KU Leuven, Kasteelpark Arenberg 21 box 2462, 3001 Heverlee, Belgium.
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17
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Lucena-Padros H, Bravo-Gil N, Tous C, Rojano E, Seoane-Zonjic P, Fernández RM, Ranea JAG, Antiñolo G, Borrego S. Bioinformatics Prediction for Network-Based Integrative Multi-Omics Expression Data Analysis in Hirschsprung Disease. Biomolecules 2024; 14:164. [PMID: 38397401 PMCID: PMC10886964 DOI: 10.3390/biom14020164] [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] [Received: 12/05/2023] [Revised: 01/15/2024] [Accepted: 01/27/2024] [Indexed: 02/25/2024] Open
Abstract
Hirschsprung's disease (HSCR) is a rare developmental disorder in which enteric ganglia are missing along a portion of the intestine. HSCR has a complex inheritance, with RET as the major disease-causing gene. However, the pathogenesis of HSCR is still not completely understood. Therefore, we applied a computational approach based on multi-omics network characterization and clustering analysis for HSCR-related gene/miRNA identification and biomarker discovery. Protein-protein interaction (PPI) and miRNA-target interaction (MTI) networks were analyzed by DPClusO and BiClusO, respectively, and finally, the biomarker potential of miRNAs was computationally screened by miRNA-BD. In this study, a total of 55 significant gene-disease modules were identified, allowing us to propose 178 new HSCR candidate genes and two biological pathways. Moreover, we identified 12 key miRNAs with biomarker potential among 137 predicted HSCR-associated miRNAs. Functional analysis of new candidates showed that enrichment terms related to gene ontology (GO) and pathways were associated with HSCR. In conclusion, this approach has allowed us to decipher new clues of the etiopathogenesis of HSCR, although molecular experiments are further needed for clinical validations.
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Affiliation(s)
- Helena Lucena-Padros
- Department of Maternofetal Medicine, Genetics and Reproduction, Institute of Biomedicine of Seville, University Hospital Virgen del Rocío/CSIC/University of Seville, 41013 Seville, Spain
| | - Nereida Bravo-Gil
- Department of Maternofetal Medicine, Genetics and Reproduction, Institute of Biomedicine of Seville, University Hospital Virgen del Rocío/CSIC/University of Seville, 41013 Seville, Spain
- Center for Biomedical Network Research on Rare Diseases (CIBERER), 41013 Seville, Spain
| | - Cristina Tous
- Department of Maternofetal Medicine, Genetics and Reproduction, Institute of Biomedicine of Seville, University Hospital Virgen del Rocío/CSIC/University of Seville, 41013 Seville, Spain
- Center for Biomedical Network Research on Rare Diseases (CIBERER), 41013 Seville, Spain
| | - Elena Rojano
- Department of Molecular Biology and Biochemistry, University of Malaga, 29010 Malaga, Spain
- Biomedical Research Institute of Malaga, IBIMA, 29010 Malaga, Spain
| | - Pedro Seoane-Zonjic
- Department of Molecular Biology and Biochemistry, University of Malaga, 29010 Malaga, Spain
- Biomedical Research Institute of Malaga, IBIMA, 29010 Malaga, Spain
- Center for Biomedical Network Research on Rare Diseases (CIBERER), 29071 Malaga, Spain
| | - Raquel María Fernández
- Department of Maternofetal Medicine, Genetics and Reproduction, Institute of Biomedicine of Seville, University Hospital Virgen del Rocío/CSIC/University of Seville, 41013 Seville, Spain
- Center for Biomedical Network Research on Rare Diseases (CIBERER), 41013 Seville, Spain
| | - Juan A. G. Ranea
- Department of Molecular Biology and Biochemistry, University of Malaga, 29010 Malaga, Spain
- Biomedical Research Institute of Malaga, IBIMA, 29010 Malaga, Spain
- Center for Biomedical Network Research on Rare Diseases (CIBERER), 29071 Malaga, Spain
- Spanish National Bioinformatics Institute (INB/ELIXIR-ES), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain
| | - Guillermo Antiñolo
- Department of Maternofetal Medicine, Genetics and Reproduction, Institute of Biomedicine of Seville, University Hospital Virgen del Rocío/CSIC/University of Seville, 41013 Seville, Spain
- Center for Biomedical Network Research on Rare Diseases (CIBERER), 41013 Seville, Spain
| | - Salud Borrego
- Department of Maternofetal Medicine, Genetics and Reproduction, Institute of Biomedicine of Seville, University Hospital Virgen del Rocío/CSIC/University of Seville, 41013 Seville, Spain
- Center for Biomedical Network Research on Rare Diseases (CIBERER), 41013 Seville, Spain
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18
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Mengelkoch S, Gassen J, Lev-Ari S, Alley JC, Schüssler-Fiorenza Rose SM, Snyder MP, Slavich GM. Multi-omics in stress and health research: study designs that will drive the field forward. Stress 2024; 27:2321610. [PMID: 38425100 PMCID: PMC11216062 DOI: 10.1080/10253890.2024.2321610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 02/16/2024] [Indexed: 03/02/2024] Open
Abstract
Despite decades of stress research, there still exist substantial gaps in our understanding of how social, environmental, and biological factors interact and combine with developmental stressor exposures, cognitive appraisals of stressors, and psychosocial coping processes to shape individuals' stress reactivity, health, and disease risk. Relatively new biological profiling approaches, called multi-omics, are helping address these issues by enabling researchers to quantify thousands of molecules from a single blood or tissue sample, thus providing a panoramic snapshot of the molecular processes occurring in an organism from a systems perspective. In this review, we summarize two types of research designs for which multi-omics approaches are best suited, and describe how these approaches can help advance our understanding of stress processes and the development, prevention, and treatment of stress-related pathologies. We first discuss incorporating multi-omics approaches into theory-rich, intensive longitudinal study designs to characterize, in high-resolution, the transition to stress-related multisystem dysfunction and disease throughout development. Next, we discuss how multi-omics approaches should be incorporated into intervention research to better understand the transition from stress-related dysfunction back to health, which can help inform novel precision medicine approaches to managing stress and fostering biopsychosocial resilience. Throughout, we provide concrete recommendations for types of studies that will help advance stress research, and translate multi-omics data into better health and health care.
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Affiliation(s)
- Summer Mengelkoch
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA
| | - Jeffrey Gassen
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA
| | - Shahar Lev-Ari
- Department of Genetics, Stanford University, Stanford, CA, USA
- Department of Health Promotion, Tel Aviv University, Tel Aviv, Israel
| | - Jenna C. Alley
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA
| | | | | | - George M. Slavich
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA
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19
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Heidarian Y, Tourigny JP, Fasteen TD, Mahmoudzadeh NH, Hurlburt AJ, Nemkov T, Reisz JA, D’Alessandro A, Tennessen JM. Metabolomic analysis of Drosophila melanogaster larvae lacking pyruvate kinase. G3 (BETHESDA, MD.) 2023; 14:jkad228. [PMID: 37792629 PMCID: PMC10755183 DOI: 10.1093/g3journal/jkad228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 06/02/2023] [Accepted: 09/24/2023] [Indexed: 10/06/2023]
Abstract
Pyruvate kinase (Pyk) is a rate-limiting enzyme that catalyzes the final metabolic reaction in glycolysis. The importance of this enzyme, however, extends far beyond ATP production, as Pyk is also known to regulate tissue growth, cell proliferation, and development. Studies of this enzyme in Drosophila melanogaster are complicated by the fact that the fly genome encodes 6 Pyk paralogs whose functions remain poorly defined. To address this issue, we used sequence distance and phylogenetic approaches to demonstrate that the gene Pyk encodes the enzyme most similar to the mammalian Pyk orthologs, while the other 5 Drosophila Pyk paralogs have significantly diverged from the canonical enzyme. Consistent with this observation, metabolomic studies of 2 different Pyk mutant strains revealed that larvae lacking Pyk exhibit a severe block in glycolysis, with a buildup of glycolytic intermediates upstream of pyruvate. However, our analysis also unexpectedly reveals that pyruvate levels are unchanged in Pyk mutants, indicating that larval metabolism maintains pyruvate pool size despite severe metabolic limitations. Consistent with our metabolomic findings, a complementary RNA-seq analysis revealed that genes involved in lipid metabolism and protease activity are elevated in Pyk mutants, again indicating that loss of this glycolytic enzyme induces compensatory changes in other aspects of metabolism. Overall, our study provides both insight into how Drosophila larval metabolism adapts to disruption of glycolytic metabolism as well as immediate clinical relevance, considering that Pyk deficiency is the most common congenital enzymatic defect in humans.
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Affiliation(s)
- Yasaman Heidarian
- Department of Biology, Indiana University, Bloomington, IN 47405, USA
| | - Jason P Tourigny
- Department of Biology, Indiana University, Bloomington, IN 47405, USA
| | - Tess D Fasteen
- Department of Biology, Indiana University, Bloomington, IN 47405, USA
| | | | | | - Travis Nemkov
- Department of Biochemistry and Molecular Genetics, Anschutz Medical Campus, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Julie A Reisz
- Department of Biochemistry and Molecular Genetics, Anschutz Medical Campus, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Angelo D’Alessandro
- Department of Biochemistry and Molecular Genetics, Anschutz Medical Campus, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Jason M Tennessen
- Department of Biology, Indiana University, Bloomington, IN 47405, USA
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20
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Casella C, Kiles F, Urquhart C, Michaud DS, Kirwa K, Corlin L. Methylomic, Proteomic, and Metabolomic Correlates of Traffic-Related Air Pollution in the Context of Cardiorespiratory Health: A Systematic Review, Pathway Analysis, and Network Analysis. TOXICS 2023; 11:1014. [PMID: 38133415 PMCID: PMC10748071 DOI: 10.3390/toxics11121014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 11/18/2023] [Accepted: 12/06/2023] [Indexed: 12/23/2023]
Abstract
A growing body of literature has attempted to characterize how traffic-related air pollution (TRAP) affects molecular and subclinical biological processes in ways that could lead to cardiorespiratory disease. To provide a streamlined synthesis of what is known about the multiple mechanisms through which TRAP could lead to cardiorespiratory pathology, we conducted a systematic review of the epidemiological literature relating TRAP exposure to methylomic, proteomic, and metabolomic biomarkers in adult populations. Using the 139 papers that met our inclusion criteria, we identified the omic biomarkers significantly associated with short- or long-term TRAP and used these biomarkers to conduct pathway and network analyses. We considered the evidence for TRAP-related associations with biological pathways involving lipid metabolism, cellular energy production, amino acid metabolism, inflammation and immunity, coagulation, endothelial function, and oxidative stress. Our analysis suggests that an integrated multi-omics approach may provide critical new insights into the ways TRAP could lead to adverse clinical outcomes. We advocate for efforts to build a more unified approach for characterizing the dynamic and complex biological processes linking TRAP exposure and subclinical and clinical disease and highlight contemporary challenges and opportunities associated with such efforts.
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Affiliation(s)
- Cameron Casella
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA; (C.C.); (F.K.); (C.U.); (D.S.M.); (K.K.)
| | - Frances Kiles
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA; (C.C.); (F.K.); (C.U.); (D.S.M.); (K.K.)
| | - Catherine Urquhart
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA; (C.C.); (F.K.); (C.U.); (D.S.M.); (K.K.)
| | - Dominique S. Michaud
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA; (C.C.); (F.K.); (C.U.); (D.S.M.); (K.K.)
| | - Kipruto Kirwa
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA; (C.C.); (F.K.); (C.U.); (D.S.M.); (K.K.)
- Department of Environmental Health, Boston University School of Public Health, Boston, MA 02118, USA
| | - Laura Corlin
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA; (C.C.); (F.K.); (C.U.); (D.S.M.); (K.K.)
- Department of Civil and Environmental Engineering, Tufts University School of Engineering, Medford, MA 02155, USA
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21
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Rabotnick MH, Ehlinger J, Haidari A, Goodrich JM. Prenatal exposures to endocrine disrupting chemicals: The role of multi-omics in understanding toxicity. Mol Cell Endocrinol 2023; 578:112046. [PMID: 37598796 PMCID: PMC10592024 DOI: 10.1016/j.mce.2023.112046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 08/11/2023] [Accepted: 08/16/2023] [Indexed: 08/22/2023]
Abstract
Endocrine disrupting chemicals (EDCs) are a diverse group of toxicants detected in populations globally. Prenatal EDC exposures impact birth and childhood outcomes. EDCs work through persistent changes at the molecular, cellular, and organ level. Molecular and biochemical signals or 'omics' can be measured at various functional levels - including the epigenome, transcriptome, proteome, metabolome, and the microbiome. In this narrative review, we introduce each omics and give examples of associations with prenatal EDC exposures. There is substantial research on epigenomic modifications in offspring exposed to EDCs during gestation, and a growing number of studies evaluating the transcriptome, proteome, metabolome, or microbiome in response to these exposures. Multi-omics, integrating data across omics layers, may improve understanding of disrupted function pathways related to early life exposures. We highlight several data integration methods to consider in multi-omics studies. Information from multi-omics can improve understanding of the biological processes and mechanisms underlying prenatal EDC toxicity.
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Affiliation(s)
- Margaret H Rabotnick
- Department of Environmental Health Sciences, University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor, MI, 48109, USA
| | - Jessa Ehlinger
- Department of Environmental Health Sciences, University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor, MI, 48109, USA
| | - Ariana Haidari
- Department of Environmental Health Sciences, University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor, MI, 48109, USA
| | - Jaclyn M Goodrich
- Department of Environmental Health Sciences, University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor, MI, 48109, USA.
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22
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Kim MJ, Martin CA, Kim J, Jablonski MM. Computational methods in glaucoma research: Current status and future outlook. Mol Aspects Med 2023; 94:101222. [PMID: 37925783 PMCID: PMC10842846 DOI: 10.1016/j.mam.2023.101222] [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] [Received: 08/01/2023] [Revised: 10/06/2023] [Accepted: 10/19/2023] [Indexed: 11/07/2023]
Abstract
Advancements in computational techniques have transformed glaucoma research, providing a deeper understanding of genetics, disease mechanisms, and potential therapeutic targets. Systems genetics integrates genomic and clinical data, aiding in identifying drug targets, comprehending disease mechanisms, and personalizing treatment strategies for glaucoma. Molecular dynamics simulations offer valuable molecular-level insights into glaucoma-related biomolecule behavior and drug interactions, guiding experimental studies and drug discovery efforts. Artificial intelligence (AI) technologies hold promise in revolutionizing glaucoma research, enhancing disease diagnosis, target identification, and drug candidate selection. The generalized protocols for systems genetics, MD simulations, and AI model development are included as a guide for glaucoma researchers. These computational methods, however, are not separate and work harmoniously together to discover novel ways to combat glaucoma. Ongoing research and progresses in genomics technologies, MD simulations, and AI methodologies project computational methods to become an integral part of glaucoma research in the future.
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Affiliation(s)
- Minjae J Kim
- Department of Ophthalmology, The Hamilton Eye Institute, The University of Tennessee Health Science Center, Memphis, TN, 38163, USA.
| | - Cole A Martin
- Department of Ophthalmology, The Hamilton Eye Institute, The University of Tennessee Health Science Center, Memphis, TN, 38163, USA.
| | - Jinhwa Kim
- Graduate School of Artificial Intelligence, Graduate School of Metaverse, Department of Management Information Systems, Sogang University, 1 Shinsoo-Dong, Mapo-Gu, Seoul, South Korea.
| | - Monica M Jablonski
- Department of Ophthalmology, The Hamilton Eye Institute, The University of Tennessee Health Science Center, Memphis, TN, 38163, USA.
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23
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Laputková G, Talian I, Schwartzová V. Medication-Related Osteonecrosis of the Jaw: A Systematic Review and a Bioinformatic Analysis. Int J Mol Sci 2023; 24:16745. [PMID: 38069068 PMCID: PMC10706386 DOI: 10.3390/ijms242316745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 11/23/2023] [Accepted: 11/23/2023] [Indexed: 12/18/2023] Open
Abstract
The objective was to evaluate the current evidence regarding the etiology of medication-related osteonecrosis of the jaw (MRONJ). This study systematically reviewed the literature by searching PubMed, Web of Science, and ProQuest databases for genes, proteins, and microRNAs associated with MRONJ from the earliest records through April 2023. Conference abstracts, letters, review articles, non-human studies, and non-English publications were excluded. Twelve studies meeting the inclusion criteria involving exposure of human oral mucosa, blood, serum, saliva, or adjacent bone or periodontium to anti-resorptive or anti-angiogenic agents were analyzed. The Cochrane Collaboration risk assessment tool was used to assess the quality of the studies. A total of 824 differentially expressed genes/proteins (DEGs) and 22 microRNAs were extracted for further bioinformatic analysis using Cytoscape, STRING, BiNGO, cytoHubba, MCODE, and ReactomeFI software packages and web-based platforms: DIANA mirPath, OmicsNet, and miRNet tools. The analysis yielded an interactome consisting of 17 hub genes and hsa-mir-16-1, hsa-mir-21, hsa-mir-23a, hsa-mir-145, hsa-mir-186, hsa-mir-221, and hsa-mir-424. A dominance of cytokine pathways was observed in both the cluster of hub DEGs and the interactome of hub genes with dysregulated miRNAs. In conclusion, a panel of genes, miRNAs, and related pathways were found, which is a step toward understanding the complexity of the disease.
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Affiliation(s)
- Galina Laputková
- Department of Medical and Clinical Biophysics, Faculty of Medicine, University of P. J. Šafárik, Trieda SNP 1, 040 11 Košice, Slovakia;
| | - Ivan Talian
- Department of Medical and Clinical Biophysics, Faculty of Medicine, University of P. J. Šafárik, Trieda SNP 1, 040 11 Košice, Slovakia;
| | - Vladimíra Schwartzová
- Clinic of Stomatology and Maxillofacial Surgery, Faculty of Medicine, University of P. J. Šafárik and Louis Pasteur University Hospital, 041 90 Košice, Slovakia;
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24
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Leroux C, Cuccato M, Pawłowski K, Cannizzo FT, Sacchi P, Pires JAA, Faulconnier Y. Milk fat miRNome changes in response to LPS challenge in Holstein cows. Vet Res 2023; 54:111. [PMID: 37993922 PMCID: PMC10666322 DOI: 10.1186/s13567-023-01231-4] [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: 11/10/2022] [Accepted: 09/02/2023] [Indexed: 11/24/2023] Open
Abstract
Mastitis is an inflammatory disease in dairy cows, causing economic losses and reducing animal welfare. In order to contribute for the discovery of early and noninvasive indicators, our objective was to determine the effects of a lipopolysaccharide (LPS) challenge on the microRNA profile (miRNome) of milk fat, using microarray analyses in cows. Cows were fed a lactation diet at ad libitum intake (n = 6). At 27 ± 3 days in milk, cows were injected with 50 µg of LPS Escherichia coli in one healthy rear mammary quarter. Milk samples were collected just before LPS challenge (LPS-) and 6.5 h after LPS challenge (LPS +) from the same cows. Microarray analysis was performed using customized 8 × 60 K ruminant miRNA microarrays to compare LPS- to LPS + miRNome. In silico functional analyses were performed using OmicsNet and Mienturnet software. MiRNome comparison between LPS- and LPS + identified 37 differentially abundant miRNAs (q-value ≤ 0.05). The predicted target genes of the 37 differentially abundant miRNAs are mostly involved in cell life including apoptosis, cell cycle, proliferation and differentiation and in gene expression processes. MiRNome analyses suggest that miRNAs profile is related to the inflammation response of the mammary gland. In conclusion, we demonstrated that milk fat might be an easy and rapid source of miRNAs that are potential indicators of early mastitis in cows.
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Affiliation(s)
- Christine Leroux
- INRAE, Université Clermont Auvergne, VetAgro Sup, UMR Herbivores, 63122, Saint-Genès-Champanelle, France.
| | - Matteo Cuccato
- INRAE, Université Clermont Auvergne, VetAgro Sup, UMR Herbivores, 63122, Saint-Genès-Champanelle, France
- Dipartimento di Scienze Veterinarie, Università degli Studi di Torino, Largo Paolo Braccini 2, 10095, Torino, Italy
| | - Karol Pawłowski
- INRAE, Université Clermont Auvergne, VetAgro Sup, UMR Herbivores, 63122, Saint-Genès-Champanelle, France
- Department of Pathology and Veterinary Diagnostics, Faculty of Veterinary Medicine, Warsaw Univeristy of Life Sciences, Nowoursynowska 159c, 02-776, Warsaw, Poland
| | - Francesca Tiziana Cannizzo
- Dipartimento di Scienze Veterinarie, Università degli Studi di Torino, Largo Paolo Braccini 2, 10095, Torino, Italy
| | - Paola Sacchi
- Dipartimento di Scienze Veterinarie, Università degli Studi di Torino, Largo Paolo Braccini 2, 10095, Torino, Italy
| | - José A A Pires
- INRAE, Université Clermont Auvergne, VetAgro Sup, UMR Herbivores, 63122, Saint-Genès-Champanelle, France
| | - Yannick Faulconnier
- INRAE, Université Clermont Auvergne, VetAgro Sup, UMR Herbivores, 63122, Saint-Genès-Champanelle, France
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25
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Reitz CJ, Kuzmanov U, Gramolini AO. Multi-omic analyses and network biology in cardiovascular disease. Proteomics 2023; 23:e2200289. [PMID: 37691071 DOI: 10.1002/pmic.202200289] [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] [Received: 03/17/2023] [Revised: 08/11/2023] [Accepted: 08/22/2023] [Indexed: 09/12/2023]
Abstract
Heart disease remains a leading cause of death in North America and worldwide. Despite advances in therapies, the chronic nature of cardiovascular diseases ultimately results in frequent hospitalizations and steady rates of mortality. Systems biology approaches have provided a new frontier toward unraveling the underlying mechanisms of cell, tissue, and organ dysfunction in disease. Mapping the complex networks of molecular functions across the genome, transcriptome, proteome, and metabolome has enormous potential to advance our understanding of cardiovascular disease, discover new disease biomarkers, and develop novel therapies. Computational workflows to interpret these data-intensive analyses as well as integration between different levels of interrogation remain important challenges in the advancement and application of systems biology-based analyses in cardiovascular research. This review will focus on summarizing the recent developments in network biology-level profiling in the heart, with particular emphasis on modeling of human heart failure. We will provide new perspectives on integration between different levels of large "omics" datasets, including integration of gene regulatory networks, protein-protein interactions, signaling networks, and metabolic networks in the heart.
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Affiliation(s)
- Cristine J Reitz
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Translational Biology and Engineering Program, Ted Rogers Centre for Heart Research, Toronto, Ontario, Canada
| | - Uros Kuzmanov
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Translational Biology and Engineering Program, Ted Rogers Centre for Heart Research, Toronto, Ontario, Canada
| | - Anthony O Gramolini
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Translational Biology and Engineering Program, Ted Rogers Centre for Heart Research, Toronto, Ontario, Canada
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26
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Mengelkoch S, Miryam Schüssler-Fiorenza Rose S, Lautman Z, Alley JC, Roos LG, Ehlert B, Moriarity DP, Lancaster S, Snyder MP, Slavich GM. Multi-omics approaches in psychoneuroimmunology and health research: Conceptual considerations and methodological recommendations. Brain Behav Immun 2023; 114:475-487. [PMID: 37543247 PMCID: PMC11195542 DOI: 10.1016/j.bbi.2023.07.022] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 07/04/2023] [Accepted: 07/30/2023] [Indexed: 08/07/2023] Open
Abstract
The field of psychoneuroimmunology (PNI) has grown substantially in both relevance and prominence over the past 40 years. Notwithstanding its impressive trajectory, a majority of PNI studies are still based on a relatively small number of analytes. To advance this work, we suggest that PNI, and health research in general, can benefit greatly from adopting a multi-omics approach, which involves integrating data across multiple biological levels (e.g., the genome, proteome, transcriptome, metabolome, lipidome, and microbiome/metagenome) to more comprehensively profile biological functions and relate these profiles to clinical and behavioral outcomes. To assist investigators in this endeavor, we provide an overview of multi-omics research, highlight recent landmark multi-omics studies investigating human health and disease risk, and discuss how multi-omics can be applied to better elucidate links between psychological, nervous system, and immune system activity. In doing so, we describe how to design high-quality multi-omics studies, decide which biological samples (e.g., blood, stool, urine, saliva, solid tissue) are most relevant, incorporate behavioral and wearable sensing data into multi-omics research, and understand key data quality, integration, analysis, and interpretation issues. PNI researchers are addressing some of the most interesting and important questions at the intersection of psychology, neuroscience, and immunology. Applying a multi-omics approach to this work will greatly expand the horizon of what is possible in PNI and has the potential to revolutionize our understanding of mind-body medicine.
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Affiliation(s)
- Summer Mengelkoch
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA.
| | | | - Ziv Lautman
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Jenna C Alley
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA
| | - Lydia G Roos
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA
| | - Benjamin Ehlert
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Daniel P Moriarity
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA
| | | | | | - George M Slavich
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA.
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27
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Zhan C, Tang T, Wu E, Zhang Y, He M, Wu R, Bi C, Wang J, Zhang Y, Shen B. From multi-omics approaches to personalized medicine in myocardial infarction. Front Cardiovasc Med 2023; 10:1250340. [PMID: 37965091 PMCID: PMC10642346 DOI: 10.3389/fcvm.2023.1250340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 10/17/2023] [Indexed: 11/16/2023] Open
Abstract
Myocardial infarction (MI) is a prevalent cardiovascular disease characterized by myocardial necrosis resulting from coronary artery ischemia and hypoxia, which can lead to severe complications such as arrhythmia, cardiac rupture, heart failure, and sudden death. Despite being a research hotspot, the etiological mechanism of MI remains unclear. The emergence and widespread use of omics technologies, including genomics, transcriptomics, proteomics, metabolomics, and other omics, have provided new opportunities for exploring the molecular mechanism of MI and identifying a large number of disease biomarkers. However, a single-omics approach has limitations in understanding the complex biological pathways of diseases. The multi-omics approach can reveal the interaction network among molecules at various levels and overcome the limitations of the single-omics approaches. This review focuses on the omics studies of MI, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, and other omics. The exploration extended into the domain of multi-omics integrative analysis, accompanied by a compilation of diverse online resources, databases, and tools conducive to these investigations. Additionally, we discussed the role and prospects of multi-omics approaches in personalized medicine, highlighting the potential for improving diagnosis, treatment, and prognosis of MI.
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Affiliation(s)
- Chaoying Zhan
- Department of Cardiology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
| | - Tong Tang
- Department of Cardiology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
| | - Erman Wu
- Department of Cardiology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
| | - Yuxin Zhang
- Department of Cardiology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
- KeyLaboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, China
| | - Mengqiao He
- Department of Cardiology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
| | - Rongrong Wu
- Department of Cardiology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
| | - Cheng Bi
- Department of Cardiology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
- KeyLaboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, China
| | - Jiao Wang
- Department of Cardiology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
| | - Yingbo Zhang
- Department of Cardiology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
- Tropical Crops Genetic Resources Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
| | - Bairong Shen
- Department of Cardiology and Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
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28
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Marino C, Pagano I, Castaldo G, Grimaldi M, D’Elia M, Santoro A, Conte A, Molettieri P, Parisella C, Buonocore M, D’Ursi AM, Rastrelli L. Supplementing Low-Sodium Bicarbonate-Calcic (Lete) ® Water: Effects in Women on Bone and Systemic Metabolism. Metabolites 2023; 13:1109. [PMID: 37999205 PMCID: PMC10673306 DOI: 10.3390/metabo13111109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Revised: 10/03/2023] [Accepted: 10/19/2023] [Indexed: 11/25/2023] Open
Abstract
Calcium (Ca) represents about 40% of the total mineral mass, mainly in the bone, providing mechanical strength to the skeleton and teeth. An adequate Ca intake is necessary for bone growth and development in children and adolescents and for maintaining bone mineral loss in elderly age. Ca deficiency predisposes to osteopenia and osteoporosis. Healthy nutrition, including an adequate intake of Ca-rich food, is paramount to prevent and cure osteoporosis. Recently, several clinical studies have demonstrated that, in conditions of Ca dysmetabolism, Ca-rich mineral water is beneficial as a valuable source of Ca to be used as an alternative to caloric Ca-rich dairy products. Although promising, these data have been collected from small groups of participants. Moreover, they mainly regard the effect of Ca-rich mineral water on bone metabolism. In contrast, an investigation of the effect of Ca supplementation on systemic metabolism is needed to address the spreading of systemic metabolic dysfunction often associated with Ca dysmetabolism. In the present study, we analyzed urine and blood sera of 120 women in perimenopausal condition who were subjected for six months to 2l daily consumption of bicarbonate-calcium mineral water marketed under ®Lete. Remarkably, this water, in addition to being rich in calcium and bicarbonate, is also low in sodium. A complete set of laboratory tests was carried out to investigate whether the specific water composition was such to confirm the known therapeutic effects on bone metabolism. Second, but not least, urine and blood sera were analyzed using NMR-based metabolomic procedures to investigate, other than the action on Ca metabolism, potential system-wide metabolic effects. Our data show that Lete water is a valid supplement for compensating for Ca dysmetabolism and preserving bone health and integrity.
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Affiliation(s)
- Carmen Marino
- Department of Pharmacy, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Italy; (C.M.); (I.P.); (M.G.); (M.D.); (A.S.)
- Department of Pharmacy and Ph.D. Program in Drug Discovery and Development, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Italy
| | - Imma Pagano
- Department of Pharmacy, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Italy; (C.M.); (I.P.); (M.G.); (M.D.); (A.S.)
- NutriKeto_LAB Unisa—“San Giuseppe Moscati” National Hospital (AORN), Contrada Amoretta, 83100 Avellino, Italy; (G.C.); (A.C.); (P.M.); (C.P.)
| | - Giuseppe Castaldo
- NutriKeto_LAB Unisa—“San Giuseppe Moscati” National Hospital (AORN), Contrada Amoretta, 83100 Avellino, Italy; (G.C.); (A.C.); (P.M.); (C.P.)
| | - Manuela Grimaldi
- Department of Pharmacy, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Italy; (C.M.); (I.P.); (M.G.); (M.D.); (A.S.)
| | - Maria D’Elia
- Department of Pharmacy, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Italy; (C.M.); (I.P.); (M.G.); (M.D.); (A.S.)
- National Biodiversity Future Center (NBFC), 90133 Palermo, Italy
- Department of Pharmacy, Scuola di Specializzazione in Farmacia Ospedaliera, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Italy
| | - Angelo Santoro
- Department of Pharmacy, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Italy; (C.M.); (I.P.); (M.G.); (M.D.); (A.S.)
- Department of Pharmacy, Scuola di Specializzazione in Farmacia Ospedaliera, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Italy
| | - Aurelio Conte
- NutriKeto_LAB Unisa—“San Giuseppe Moscati” National Hospital (AORN), Contrada Amoretta, 83100 Avellino, Italy; (G.C.); (A.C.); (P.M.); (C.P.)
| | - Paola Molettieri
- NutriKeto_LAB Unisa—“San Giuseppe Moscati” National Hospital (AORN), Contrada Amoretta, 83100 Avellino, Italy; (G.C.); (A.C.); (P.M.); (C.P.)
| | - Chiara Parisella
- NutriKeto_LAB Unisa—“San Giuseppe Moscati” National Hospital (AORN), Contrada Amoretta, 83100 Avellino, Italy; (G.C.); (A.C.); (P.M.); (C.P.)
| | - Michela Buonocore
- Department of Chemical Sciences, University of Naples Federico II, Complesso Universitario di Monte Sant’Angelo, Via Cinthia 21, 80126 Naples, Italy;
| | - Anna Maria D’Ursi
- Department of Pharmacy, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Italy; (C.M.); (I.P.); (M.G.); (M.D.); (A.S.)
- National Biodiversity Future Center (NBFC), 90133 Palermo, Italy
| | - Luca Rastrelli
- Department of Pharmacy, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Italy; (C.M.); (I.P.); (M.G.); (M.D.); (A.S.)
- National Biodiversity Future Center (NBFC), 90133 Palermo, Italy
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29
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Alabed HBR, Del Grosso A, Bellani V, Urbanelli L, Carpi S, De Sarlo M, Bertocci L, Colagiorgio L, Buratta S, Scaccini L, Frongia Mancini D, Tonazzini I, Cecchini M, Emiliani C, Pellegrino RM. Untargeted Lipidomic Approach for Studying Different Nervous System Tissues of the Murine Model of Krabbe Disease. Biomolecules 2023; 13:1562. [PMID: 37892244 PMCID: PMC10605133 DOI: 10.3390/biom13101562] [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: 09/18/2023] [Revised: 10/11/2023] [Accepted: 10/16/2023] [Indexed: 10/29/2023] Open
Abstract
Krabbe disease is a rare neurodegenerative disease with an autosomal recessive character caused by a mutation in the GALC gene. The mutation leads to an accumulation of psychosine and a subsequent degeneration of oligodendrocytes and Schwann cells. Psychosine is the main biomarker of the disease. The Twitcher mouse is the most commonly used animal model to study Krabbe disease. Although there are many references to this model in the literature, the lipidomic study of nervous system tissues in the Twitcher model has received little attention. This study focuses on the comparison of the lipid profiles of four nervous system tissues (brain, cerebellum, spinal cord, and sciatic nerve) in the Twitcher mouse compared to the wild-type mouse. Altogether, approximately 230 molecular species belonging to 19 lipid classes were annotated and quantified. A comparison at the levels of class, molecular species, and lipid building blocks showed significant differences between the two groups, particularly in the sciatic nerve. The in-depth study of the lipid phenotype made it possible to hypothesize the genes and enzymes involved in the changes. The integration of metabolic data with genetic data may be useful from a systems biology perspective to gain a better understanding of the molecular basis of the disease.
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Affiliation(s)
- Husam B. R. Alabed
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06100 Perugia, Italy; (H.B.R.A.); (V.B.); (L.U.); (L.B.); (S.B.); (D.F.M.); (C.E.)
| | - Ambra Del Grosso
- NEST (National Enterprise for nanoScience and nanoTechnology), Istituto Nanoscienze-CNR and Scuola Normale Superiore, Piazza San Silvestro 12, 56127 Pisa, Italy; (A.D.G.); (S.C.); (M.D.S.); (L.C.); (L.S.); (I.T.); (M.C.)
| | - Valeria Bellani
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06100 Perugia, Italy; (H.B.R.A.); (V.B.); (L.U.); (L.B.); (S.B.); (D.F.M.); (C.E.)
| | - Lorena Urbanelli
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06100 Perugia, Italy; (H.B.R.A.); (V.B.); (L.U.); (L.B.); (S.B.); (D.F.M.); (C.E.)
- Centro di Eccellenza sui Materiali Innovativi Nanostrutturati (CEMIN), University of Perugia, Via del Giochetto, 06123 Perugia, Italy
| | - Sara Carpi
- NEST (National Enterprise for nanoScience and nanoTechnology), Istituto Nanoscienze-CNR and Scuola Normale Superiore, Piazza San Silvestro 12, 56127 Pisa, Italy; (A.D.G.); (S.C.); (M.D.S.); (L.C.); (L.S.); (I.T.); (M.C.)
- Department of Health Sciences, University “Magna Graecia” of Catanzaro, Viale Europa, Località Germaneto, 88100 Catanzaro, Italy
| | - Miriam De Sarlo
- NEST (National Enterprise for nanoScience and nanoTechnology), Istituto Nanoscienze-CNR and Scuola Normale Superiore, Piazza San Silvestro 12, 56127 Pisa, Italy; (A.D.G.); (S.C.); (M.D.S.); (L.C.); (L.S.); (I.T.); (M.C.)
| | - Lorenzo Bertocci
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06100 Perugia, Italy; (H.B.R.A.); (V.B.); (L.U.); (L.B.); (S.B.); (D.F.M.); (C.E.)
| | - Laura Colagiorgio
- NEST (National Enterprise for nanoScience and nanoTechnology), Istituto Nanoscienze-CNR and Scuola Normale Superiore, Piazza San Silvestro 12, 56127 Pisa, Italy; (A.D.G.); (S.C.); (M.D.S.); (L.C.); (L.S.); (I.T.); (M.C.)
| | - Sandra Buratta
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06100 Perugia, Italy; (H.B.R.A.); (V.B.); (L.U.); (L.B.); (S.B.); (D.F.M.); (C.E.)
| | - Luca Scaccini
- NEST (National Enterprise for nanoScience and nanoTechnology), Istituto Nanoscienze-CNR and Scuola Normale Superiore, Piazza San Silvestro 12, 56127 Pisa, Italy; (A.D.G.); (S.C.); (M.D.S.); (L.C.); (L.S.); (I.T.); (M.C.)
| | - Dorotea Frongia Mancini
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06100 Perugia, Italy; (H.B.R.A.); (V.B.); (L.U.); (L.B.); (S.B.); (D.F.M.); (C.E.)
| | - Ilaria Tonazzini
- NEST (National Enterprise for nanoScience and nanoTechnology), Istituto Nanoscienze-CNR and Scuola Normale Superiore, Piazza San Silvestro 12, 56127 Pisa, Italy; (A.D.G.); (S.C.); (M.D.S.); (L.C.); (L.S.); (I.T.); (M.C.)
| | - Marco Cecchini
- NEST (National Enterprise for nanoScience and nanoTechnology), Istituto Nanoscienze-CNR and Scuola Normale Superiore, Piazza San Silvestro 12, 56127 Pisa, Italy; (A.D.G.); (S.C.); (M.D.S.); (L.C.); (L.S.); (I.T.); (M.C.)
| | - Carla Emiliani
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06100 Perugia, Italy; (H.B.R.A.); (V.B.); (L.U.); (L.B.); (S.B.); (D.F.M.); (C.E.)
- Centro di Eccellenza sui Materiali Innovativi Nanostrutturati (CEMIN), University of Perugia, Via del Giochetto, 06123 Perugia, Italy
| | - Roberto Maria Pellegrino
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06100 Perugia, Italy; (H.B.R.A.); (V.B.); (L.U.); (L.B.); (S.B.); (D.F.M.); (C.E.)
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Casella C, Kiles F, Urquhart C, Michaud DS, Kirwa K, Corlin L. Methylomic, proteomic, and metabolomic correlates of traffic-related air pollution: A systematic review, pathway analysis, and network analysis relating traffic-related air pollution to subclinical and clinical cardiorespiratory outcomes. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.09.30.23296386. [PMID: 37873294 PMCID: PMC10592990 DOI: 10.1101/2023.09.30.23296386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
A growing body of literature has attempted to characterize how traffic-related air pollution (TRAP) affects molecular and subclinical biological processes in ways that could lead to cardiorespiratory disease. To provide a streamlined synthesis of what is known about the multiple mechanisms through which TRAP could lead cardiorespiratory pathology, we conducted a systematic review of the epidemiological literature relating TRAP exposure to methylomic, proteomic, and metabolomic biomarkers in adult populations. Using the 139 papers that met our inclusion criteria, we identified the omic biomarkers significantly associated with short- or long-term TRAP and used these biomarkers to conduct pathway and network analyses. We considered the evidence for TRAP-related associations with biological pathways involving lipid metabolism, cellular energy production, amino acid metabolism, inflammation and immunity, coagulation, endothelial function, and oxidative stress. Our analysis suggests that an integrated multi-omics approach may provide critical new insights into the ways TRAP could lead to adverse clinical outcomes. We advocate for efforts to build a more unified approach for characterizing the dynamic and complex biological processes linking TRAP exposure and subclinical and clinical disease, and highlight contemporary challenges and opportunities associated with such efforts.
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Affiliation(s)
- Cameron Casella
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA
| | - Frances Kiles
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA
| | - Catherine Urquhart
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA
| | - Dominique S. Michaud
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA
| | - Kipruto Kirwa
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA
- Department of Environmental Health, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Laura Corlin
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA
- Department of Civil and Environmental Engineering, Tufts University School of Engineering, Medford, MA 02155, USA
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Rushing BR. Unlocking the Molecular Secrets of Antifolate Drug Resistance: A Multi-Omics Investigation of the NCI-60 Cell Line Panel. Biomedicines 2023; 11:2532. [PMID: 37760973 PMCID: PMC10526174 DOI: 10.3390/biomedicines11092532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 09/08/2023] [Accepted: 09/11/2023] [Indexed: 09/29/2023] Open
Abstract
Drug resistance continues to be a significant problem in cancer therapy, leading to relapse and associated mortality. Although substantial progress has been made in understanding drug resistance, significant knowledge gaps remain concerning the molecular underpinnings that drive drug resistance and which processes are unique to certain drug classes. The NCI-60 cell line panel program has evaluated the activity of numerous anticancer agents against many common cancer cell line models and represents a highly valuable resource to study intrinsic drug resistance. Furthermore, great efforts have been undertaken to collect high-quality omics datasets to characterize these cell lines. The current study takes these two sources of data-drug response and omics profiles-and uses a multi-omics investigation to uncover molecular networks that differentiate cancer cells that are sensitive or resistant to antifolates, which is a commonly used class of anticancer drugs. Results from a combination of univariate and multivariate analyses showed numerous metabolic processes that differentiate sensitive and resistant cells, including differences in glycolysis and gluconeogenesis, arginine and proline metabolism, beta-alanine metabolism, purine metabolism, and pyrimidine metabolism. Further analysis using multivariate and integrated pathway analysis indicated purine metabolism as the major metabolic process separating cancer cells sensitive or resistant to antifolates. Additional pathways differentiating sensitive and resistant cells included autophagy-related processes (e.g., phagosome, lysosome, autophagy, mitophagy) and adhesion/cytoskeleton-related pathways (e.g., focal adhesion, regulation of actin cytoskeleton, tight junction). Volcano plot analysis and the receiver operating characteristic (ROC) curves of top selected variables differentiating Q1 and Q4 revealed the importance of genes involved in the regulation of the cytoskeleton and extracellular matrix (ECM). These results provide novel insights toward mechanisms of intrinsic antifolate resistance as it relates to interactions between nucleotide metabolism, autophagy, and the cytoskeleton. These processes should be evaluated in future studies to potentially derive novel therapeutic strategies and personalized treatment approaches to improve antifolate response.
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Affiliation(s)
- Blake R. Rushing
- Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC 28081, USA;
- Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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Fujiwara M, Ferdousi F, Isoda H. Investigation into Molecular Brain Aging in Senescence-Accelerated Mouse (SAM) Model Employing Whole Transcriptomic Analysis in Search of Potential Molecular Targets for Therapeutic Interventions. Int J Mol Sci 2023; 24:13867. [PMID: 37762170 PMCID: PMC10530366 DOI: 10.3390/ijms241813867] [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] [Received: 08/09/2023] [Revised: 09/06/2023] [Accepted: 09/07/2023] [Indexed: 09/29/2023] Open
Abstract
With the progression of an aging society, cognitive aging has emerged as a pressing concern necessitating attention. The senescence-accelerated mouse-prone 8 (SAMP8) model has proven instrumental in investigating the early stages of cognitive aging. Through an extensive examination of molecular changes in the brain cortex, utilizing integrated whole-genome transcriptomics, our principal aim was to uncover potential molecular targets with therapeutic applications and relevance to drug screening. Our investigation encompassed four distinct conditions, comparing the same strain at different time points (1 year vs. 16 weeks) and the same time point across different strains (SAMP8 vs. SAMR1), namely: physiological aging, accelerated aging, early events in accelerated aging, and late events in accelerated aging. Focusing on key functional alterations associated with aging in the brain, including neurogenesis, synapse dynamics, neurometabolism, and neuroinflammation, we identified candidate genes linked to these processes. Furthermore, employing protein-protein interaction (PPI) analysis, we identified pivotal hub genes involved in interactions within these functional domains. Additionally, gene-set perturbation analysis allowed us to uncover potential upstream genes or transcription factors that exhibited activation or inhibition across the four conditions. In summary, our comprehensive analysis of the SAMP8 mouse brain through whole-genome transcriptomics not only deepens our understanding of age-related changes but also lays the groundwork for a predictive model to facilitate drug screening for cognitive aging.
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Affiliation(s)
- Michitaka Fujiwara
- Graduate School of Environmental Science Program, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8577, Japan
- Open Innovation Laboratory for Food and Medicinal Resource Engineering, National Institute of Advanced Industrial Science and Technology (AIST), 1-1-1 Tennodai, Tsukuba 305-8572, Japan
| | - Farhana Ferdousi
- Faculty of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8572, Japan
- Alliance for Research on the Mediterranean and North Africa (ARENA), University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8572, Japan
| | - Hiroko Isoda
- Open Innovation Laboratory for Food and Medicinal Resource Engineering, National Institute of Advanced Industrial Science and Technology (AIST), 1-1-1 Tennodai, Tsukuba 305-8572, Japan
- Faculty of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8572, Japan
- Alliance for Research on the Mediterranean and North Africa (ARENA), University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8572, Japan
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Lisk C, Cendali F, Setua S, Thangaraju K, Pak DI, Swindle D, Dzieciatkowska M, Gamboni F, Hassell K, Nuss R, George G, Davizon-Castillo P, Buehler PW, D'Alessandro A, Irwin DC. Metabolic and Proteomic Divergence Is Present in Circulating Monocytes and Tissue-Resident Macrophages from Berkeley Sickle Cell Anemia and β-Thalassemia Mice. J Proteome Res 2023; 22:2925-2935. [PMID: 37606205 DOI: 10.1021/acs.jproteome.3c00224] [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: 08/23/2023]
Abstract
Sickle cell disease and β-thalassemia represent hemoglobinopathies arising from dysfunctional or underproduced β-globin chains, respectively. In both diseases, red blood cell injury and anemia are the impetus for end organ injury. Because persistent erythrophagocytosis is a hallmark of these genetic maladies, it is critical to understand how macrophage phenotype polarizations in tissue compartments can inform on disease progression. Murine models of sickle cell disease and β-thalassemia allow for a basic understanding of the mechanisms and provide for translation to human disease. A multi-omics approach to understanding the macrophage metabolism and protein changes in two murine models of β-globinopathy was performed on peripheral blood mononuclear cells as well as spleen and liver macrophages isolated from Berkley sickle cell disease (Berk-ss) and heterozygous B1/B2 globin gene deletion (Hbbth3/+) mice. The results from these experiments revealed that the metabolome and proteome of macrophages are polarized to a distinct phenotype in Berk-ss and Hbbth3/+ compared with each other and their common-background mice (C57BL6/J). Further, spleen and liver macrophages revealed distinct disease-specific phenotypes, suggesting that macrophages become differentially polarized and reprogrammed within tissue compartments. We conclude that tissue recruitment, polarization, and metabolic and proteomic reprogramming of macrophages in Berk-ss and Hbbth3/+ mice may be relevant to disease progression in other tissue.
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Affiliation(s)
- Christina Lisk
- Cardiovascular and Pulmonary Research Laboratory, Department of Medicine, University of Colorado Denver - Anschutz Medical Campus, Aurora, Colorado 80045, United States
| | - Francesca Cendali
- Department of Biochemistry & Molecular Genetics, Graduate School, University of Colorado, Anschutz, Medical Campus, Aurora, Colorado 80045, United States
| | - Saini Setua
- The Center for Blood Oxygen Transport, Department of Pediatrics, University of Maryland School of Medicine, Baltimore, Maryland 21201, United States
| | - Kiruphararan Thangaraju
- The Center for Blood Oxygen Transport, Department of Pediatrics, University of Maryland School of Medicine, Baltimore, Maryland 21201, United States
| | - David I Pak
- Cardiovascular and Pulmonary Research Laboratory, Department of Medicine, University of Colorado Denver - Anschutz Medical Campus, Aurora, Colorado 80045, United States
| | - Delaney Swindle
- Cardiovascular and Pulmonary Research Laboratory, Department of Medicine, University of Colorado Denver - Anschutz Medical Campus, Aurora, Colorado 80045, United States
| | - Monika Dzieciatkowska
- Department of Biochemistry & Molecular Genetics, Graduate School, University of Colorado, Anschutz, Medical Campus, Aurora, Colorado 80045, United States
| | - Fabia Gamboni
- Department of Biochemistry & Molecular Genetics, Graduate School, University of Colorado, Anschutz, Medical Campus, Aurora, Colorado 80045, United States
| | - Kathryn Hassell
- Division of Hematology Colorado Sickle Cell Treatment and Research Center, School of Medicine, Anschutz Medical Campus, University of Colorado-Denver School of Medicine, Aurora, Colorado 80045, United States
| | - Rachelle Nuss
- Division of Hematology Colorado Sickle Cell Treatment and Research Center, School of Medicine, Anschutz Medical Campus, University of Colorado-Denver School of Medicine, Aurora, Colorado 80045, United States
| | - Gemlyn George
- Division of Hematology Colorado Sickle Cell Treatment and Research Center, School of Medicine, Anschutz Medical Campus, University of Colorado-Denver School of Medicine, Aurora, Colorado 80045, United States
| | - Pavel Davizon-Castillo
- Department of Pediatrics, Hemophilia and Thrombosis Center, University of Colorado, Anschutz, Medical Campus, Aurora, Colorado 80045, United States
| | - Paul W Buehler
- The Center for Blood Oxygen Transport, Department of Pediatrics, University of Maryland School of Medicine, Baltimore, Maryland 21201, United States
- Department of Pathology, University of Maryland School of Medicine, Baltimore, Maryland 21201, United States
| | - Angelo D'Alessandro
- Department of Biochemistry & Molecular Genetics, Graduate School, University of Colorado, Anschutz, Medical Campus, Aurora, Colorado 80045, United States
| | - David C Irwin
- Cardiovascular and Pulmonary Research Laboratory, Department of Medicine, University of Colorado Denver - Anschutz Medical Campus, Aurora, Colorado 80045, United States
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Aly A, Laszlo ZI, Rajkumar S, Demir T, Hindley N, Lamont DJ, Lehmann J, Seidel M, Sommer D, Franz-Wachtel M, Barletta F, Heumos S, Czemmel S, Kabashi E, Ludolph A, Boeckers TM, Henstridge CM, Catanese A. Integrative proteomics highlight presynaptic alterations and c-Jun misactivation as convergent pathomechanisms in ALS. Acta Neuropathol 2023; 146:451-475. [PMID: 37488208 PMCID: PMC10412488 DOI: 10.1007/s00401-023-02611-y] [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] [Received: 02/17/2023] [Revised: 07/05/2023] [Accepted: 07/06/2023] [Indexed: 07/26/2023]
Abstract
Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disease mainly affecting upper and lower motoneurons. Several functionally heterogeneous genes have been associated with the familial form of this disorder (fALS), depicting an extremely complex pathogenic landscape. This heterogeneity has limited the identification of an effective therapy, and this bleak prognosis will only improve with a greater understanding of convergent disease mechanisms. Recent evidence from human post-mortem material and diverse model systems has highlighted the synapse as a crucial structure actively involved in disease progression, suggesting that synaptic aberrations might represent a shared pathological feature across the ALS spectrum. To test this hypothesis, we performed the first comprehensive analysis of the synaptic proteome from post-mortem spinal cord and human iPSC-derived motoneurons carrying mutations in the major ALS genes. This integrated approach highlighted perturbations in the molecular machinery controlling vesicle release as a shared pathomechanism in ALS. Mechanistically, phosphoproteomic analysis linked the presynaptic vesicular phenotype to an accumulation of cytotoxic protein aggregates and to the pro-apoptotic activation of the transcription factor c-Jun, providing detailed insights into the shared pathobiochemistry in ALS. Notably, sub-chronic treatment of our iPSC-derived motoneurons with the fatty acid docosahexaenoic acid exerted a neuroprotective effect by efficiently rescuing the alterations revealed by our multidisciplinary approach. Together, this study provides strong evidence for the central and convergent role played by the synaptic microenvironment within the ALS spinal cord and highlights a potential therapeutic target that counteracts degeneration in a heterogeneous cohort of human motoneuron cultures.
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Affiliation(s)
- Amr Aly
- Institute of Anatomy and Cell Biology, Ulm University, Ulm, Germany
| | - Zsofia I Laszlo
- Division of Cellular and Systems Medicine, School of Medicine, University of Dundee, Dundee, Scotland, UK
| | - Sandeep Rajkumar
- Institute of Anatomy and Cell Biology, Ulm University, Ulm, Germany
| | - Tugba Demir
- Institute of Anatomy and Cell Biology, Ulm University, Ulm, Germany
| | - Nicole Hindley
- Division of Cellular and Systems Medicine, School of Medicine, University of Dundee, Dundee, Scotland, UK
| | - Douglas J Lamont
- FingerPrints Proteomics Facility, Discovery Centre, School of Life Sciences, University of Dundee, Dundee, Scotland, UK
| | - Johannes Lehmann
- Institute of Anatomy and Cell Biology, Ulm University, Ulm, Germany
| | - Mira Seidel
- Institute of Anatomy and Cell Biology, Ulm University, Ulm, Germany
| | - Daniel Sommer
- Institute of Anatomy and Cell Biology, Ulm University, Ulm, Germany
| | | | - Francesca Barletta
- Quantitative Biology Center (QBiC), University of Tübingen, 72076, Tübingen, Germany
| | - Simon Heumos
- Quantitative Biology Center (QBiC), University of Tübingen, 72076, Tübingen, Germany
- Biomedical Data Science, Department of Computer Science, University of Tübingen, 72076, Tübingen, Germany
| | - Stefan Czemmel
- Quantitative Biology Center (QBiC), University of Tübingen, 72076, Tübingen, Germany
| | - Edor Kabashi
- Laboratory of Translational Research for Neurological Disorders, Imagine Institute, Université de Paris, INSERM, UMR 1163, 75015, Paris, France
| | - Albert Ludolph
- Department of Neurology, Ulm University School of Medicine, Ulm, Germany
- German Center for Neurodegenerative Diseases (DZNE), Ulm Site, Germany
| | - Tobias M Boeckers
- Institute of Anatomy and Cell Biology, Ulm University, Ulm, Germany
- German Center for Neurodegenerative Diseases (DZNE), Ulm Site, Germany
| | - Christopher M Henstridge
- Division of Cellular and Systems Medicine, School of Medicine, University of Dundee, Dundee, Scotland, UK.
| | - Alberto Catanese
- Institute of Anatomy and Cell Biology, Ulm University, Ulm, Germany.
- German Center for Neurodegenerative Diseases (DZNE), Ulm Site, Germany.
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Rushing BR. Multi-Omics Analysis of NCI-60 Cell Line Data Reveals Novel Metabolic Processes Linked with Resistance to Alkylating Anti-Cancer Agents. Int J Mol Sci 2023; 24:13242. [PMID: 37686047 PMCID: PMC10487847 DOI: 10.3390/ijms241713242] [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] [Received: 07/28/2023] [Revised: 08/16/2023] [Accepted: 08/23/2023] [Indexed: 09/10/2023] Open
Abstract
This study aimed to elucidate the molecular determinants influencing the response of cancer cells to alkylating agents, a major class of chemotherapeutic drugs used in cancer treatment. The study utilized data from the National Cancer Institute (NCI)-60 cell line screening program and employed a comprehensive multi-omics approach integrating transcriptomic, proteomic, metabolomic, and SNP data. Through integrated pathway analysis, the study identified key metabolic pathways, such as cysteine and methionine metabolism, starch and sucrose metabolism, pyrimidine metabolism, and purine metabolism, that differentiate drug-sensitive and drug-resistant cancer cells. The analysis also revealed potential druggable targets within these pathways. Furthermore, copy number variant (CNV) analysis, derived from SNP data, between sensitive and resistant cells identified notable differences in genes associated with metabolic changes (WWOX, CNTN5, DDAH1, PGR), protein trafficking (ARL17B, VAT1L), and miRNAs (MIR1302-2, MIR3163, MIR1244-3, MIR1302-9). The findings of this study provide a holistic view of the molecular landscape and dysregulated pathways underlying the response of cancer cells to alkylating agents. The insights gained from this research can contribute to the development of more effective therapeutic strategies and personalized treatment approaches, ultimately improving patient outcomes in cancer treatment.
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Affiliation(s)
- Blake R. Rushing
- Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC 28081, USA;
- Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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Can H, Chanumolu SK, Nielsen BD, Alvarez S, Naldrett MJ, Ünlü G, Otu HH. Integration of Meta-Multi-Omics Data Using Probabilistic Graphs and External Knowledge. Cells 2023; 12:1998. [PMID: 37566077 PMCID: PMC10417344 DOI: 10.3390/cells12151998] [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: 05/12/2023] [Revised: 07/11/2023] [Accepted: 08/02/2023] [Indexed: 08/12/2023] Open
Abstract
Multi-omics has the promise to provide a detailed molecular picture of biological systems. Although obtaining multi-omics data is relatively easy, methods that analyze such data have been lagging. In this paper, we present an algorithm that uses probabilistic graph representations and external knowledge to perform optimal structure learning and deduce a multifarious interaction network for multi-omics data from a bacterial community. Kefir grain, a microbial community that ferments milk and creates kefir, represents a self-renewing, stable, natural microbial community. Kefir has been shown to have a wide range of health benefits. We obtained a controlled bacterial community using the two most abundant and well-studied species in kefir grains: Lentilactobacillus kefiri and Lactobacillus kefiranofaciens. We applied growth temperatures of 30 °C and 37 °C and obtained transcriptomic, metabolomic, and proteomic data for the same 20 samples (10 samples per temperature). We obtained a multi-omics interaction network, which generated insights that would not have been possible with single-omics analysis. We identified interactions among transcripts, proteins, and metabolites, suggesting active toxin/antitoxin systems. We also observed multifarious interactions that involved the shikimate pathway. These observations helped explain bacterial adaptation to different stress conditions, co-aggregation, and increased activation of L. kefiranofaciens at 37 °C.
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Affiliation(s)
- Handan Can
- Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
| | - Sree K. Chanumolu
- Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
| | - Barbara D. Nielsen
- Department of Animal, Veterinary and Food Sciences, University of Idaho, Moscow, ID 83844, USA
| | - Sophie Alvarez
- Proteomics and Metabolomics Facility, Nebraska Center for Biotechnology, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
| | - Michael J. Naldrett
- Proteomics and Metabolomics Facility, Nebraska Center for Biotechnology, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
| | - Gülhan Ünlü
- Department of Animal, Veterinary and Food Sciences, University of Idaho, Moscow, ID 83844, USA
- Department of Chemical and Biological Engineering, University of Idaho, Moscow, ID 83844, USA
- School of Food Science, Washington State University, Pullman, WA 99164, USA
| | - Hasan H. Otu
- Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
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Chen C, Wang J, Pan D, Wang X, Xu Y, Yan J, Wang L, Yang X, Yang M, Liu G. Applications of multi-omics analysis in human diseases. MedComm (Beijing) 2023; 4:e315. [PMID: 37533767 PMCID: PMC10390758 DOI: 10.1002/mco2.315] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 05/25/2023] [Accepted: 05/31/2023] [Indexed: 08/04/2023] Open
Abstract
Multi-omics usually refers to the crossover application of multiple high-throughput screening technologies represented by genomics, transcriptomics, single-cell transcriptomics, proteomics and metabolomics, spatial transcriptomics, and so on, which play a great role in promoting the study of human diseases. Most of the current reviews focus on describing the development of multi-omics technologies, data integration, and application to a particular disease; however, few of them provide a comprehensive and systematic introduction of multi-omics. This review outlines the existing technical categories of multi-omics, cautions for experimental design, focuses on the integrated analysis methods of multi-omics, especially the approach of machine learning and deep learning in multi-omics data integration and the corresponding tools, and the application of multi-omics in medical researches (e.g., cancer, neurodegenerative diseases, aging, and drug target discovery) as well as the corresponding open-source analysis tools and databases, and finally, discusses the challenges and future directions of multi-omics integration and application in precision medicine. With the development of high-throughput technologies and data integration algorithms, as important directions of multi-omics for future disease research, single-cell multi-omics and spatial multi-omics also provided a detailed introduction. This review will provide important guidance for researchers, especially who are just entering into multi-omics medical research.
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Affiliation(s)
- Chongyang Chen
- Key Laboratory of Nuclear MedicineMinistry of HealthJiangsu Key Laboratory of Molecular Nuclear MedicineJiangsu Institute of Nuclear MedicineWuxiChina
- Co‐innovation Center of NeurodegenerationNantong UniversityNantongChina
| | - Jing Wang
- Shenzhen Key Laboratory of Modern ToxicologyShenzhen Medical Key Discipline of Health Toxicology (2020–2024)Shenzhen Center for Disease Control and PreventionShenzhenChina
| | - Donghui Pan
- Key Laboratory of Nuclear MedicineMinistry of HealthJiangsu Key Laboratory of Molecular Nuclear MedicineJiangsu Institute of Nuclear MedicineWuxiChina
| | - Xinyu Wang
- Key Laboratory of Nuclear MedicineMinistry of HealthJiangsu Key Laboratory of Molecular Nuclear MedicineJiangsu Institute of Nuclear MedicineWuxiChina
| | - Yuping Xu
- Key Laboratory of Nuclear MedicineMinistry of HealthJiangsu Key Laboratory of Molecular Nuclear MedicineJiangsu Institute of Nuclear MedicineWuxiChina
| | - Junjie Yan
- Key Laboratory of Nuclear MedicineMinistry of HealthJiangsu Key Laboratory of Molecular Nuclear MedicineJiangsu Institute of Nuclear MedicineWuxiChina
| | - Lizhen Wang
- Key Laboratory of Nuclear MedicineMinistry of HealthJiangsu Key Laboratory of Molecular Nuclear MedicineJiangsu Institute of Nuclear MedicineWuxiChina
| | - Xifei Yang
- Shenzhen Key Laboratory of Modern ToxicologyShenzhen Medical Key Discipline of Health Toxicology (2020–2024)Shenzhen Center for Disease Control and PreventionShenzhenChina
| | - Min Yang
- Key Laboratory of Nuclear MedicineMinistry of HealthJiangsu Key Laboratory of Molecular Nuclear MedicineJiangsu Institute of Nuclear MedicineWuxiChina
| | - Gong‐Ping Liu
- Co‐innovation Center of NeurodegenerationNantong UniversityNantongChina
- Department of PathophysiologySchool of Basic MedicineKey Laboratory of Ministry of Education of China and Hubei Province for Neurological DisordersTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
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Seidel M, Rajkumar S, Steffke C, Noeth V, Agarwal S, Roger K, Lipecka J, Ludolph A, Guerrera CI, Boeckers T, Catanese A. Propranolol reduces the accumulation of cytotoxic aggregates in C9orf72-ALS/FTD in vitro models. CURRENT RESEARCH IN NEUROBIOLOGY 2023; 5:100105. [PMID: 37576491 PMCID: PMC10412779 DOI: 10.1016/j.crneur.2023.100105] [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: 01/25/2023] [Revised: 06/23/2023] [Accepted: 07/26/2023] [Indexed: 08/15/2023] Open
Abstract
Mutations in the C9orf72 gene are the most common cause of familial amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). The pathogenetic mechanisms linked to this gene are a direct consequence of an aberrant intronic expansion of a GGGGCC hexanucleotide located between the 1a and 1b non-coding exons, which can be transcribed to form cytotoxic RNA foci or even translated into aggregation-prone dipeptide repeat proteins. Importantly, the abnormal length of these repeats affects also the expression levels of C9orf72 itself, which suggests haploinsufficiency as additional pathomechanism. Thus, it appears that both toxic gain of function and loss of function are distinct but still coexistent features contributing to the insurgence of the disease in case of C9orf72 mutations. In this study, we aimed at identifying a strategy to address both aspects of the C9orf72-related pathobiochemistry and provide proof-of-principle information for a better understanding of the mechanisms leading to neuronal loss. By using primary neurons overexpressing toxic poly(GA), the most abundant protein product of the GGGGCC repeats, we found that the antiarrhythmic drug propranolol could efficiently reduce the accumulation of aberrant aggregates and increase the survival of C9orf72-related cultures. Interestingly, the improved catabolism appeared to not depend on major degradative pathways such as autophagy and the proteasome. By analyzing the proteome of poly(GA)-expressing neurons after exposure to propranolol, we found that the drug increased lysosomal degradation through a mechanism directly involving C9orf72 protein, whose levels were increased after treatment. Further confirmation of the beneficial effect of the beta blocker on aggregates' accumulation and survival of hiPSC-derived C9orf72-mutant motoneurons strengthened the finding that addressing both facets of C9orf72 pathology might represent a valid strategy for the treatment of these ALS/FTD cases.
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Affiliation(s)
- Mira Seidel
- Institute of Anatomy and Cell Biology, Ulm University School of Medicine, Ulm, Germany
| | - Sandeep Rajkumar
- Institute of Anatomy and Cell Biology, Ulm University School of Medicine, Ulm, Germany
| | - Christina Steffke
- Institute of Anatomy and Cell Biology, Ulm University School of Medicine, Ulm, Germany
| | - Vivien Noeth
- Institute of Anatomy and Cell Biology, Ulm University School of Medicine, Ulm, Germany
- International Graduate School in Molecular Medicine, Ulm University, Ulm, Germany
| | - Shreya Agarwal
- Institute of Anatomy and Cell Biology, Ulm University School of Medicine, Ulm, Germany
- International Graduate School in Molecular Medicine, Ulm University, Ulm, Germany
| | - Kevin Roger
- Proteomics Platform Necker, Université Paris Cité - Structure Fédérative de Recherche Necker, INSERM US24/CNRS UAR3633, Paris, France
| | - Joanna Lipecka
- Proteomics Platform Necker, Université Paris Cité - Structure Fédérative de Recherche Necker, INSERM US24/CNRS UAR3633, Paris, France
| | - Albert Ludolph
- Department of Neurology, Ulm University School of Medicine, Ulm, Germany
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Ulm site, Ulm, Germany
| | - Chiara Ida Guerrera
- Proteomics Platform Necker, Université Paris Cité - Structure Fédérative de Recherche Necker, INSERM US24/CNRS UAR3633, Paris, France
| | - Tobias Boeckers
- Institute of Anatomy and Cell Biology, Ulm University School of Medicine, Ulm, Germany
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Ulm site, Ulm, Germany
| | - Alberto Catanese
- Institute of Anatomy and Cell Biology, Ulm University School of Medicine, Ulm, Germany
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Ulm site, Ulm, Germany
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Berquez M, Chen Z, Festa BP, Krohn P, Keller SA, Parolo S, Korzinkin M, Gaponova A, Laczko E, Domenici E, Devuyst O, Luciani A. Lysosomal cystine export regulates mTORC1 signaling to guide kidney epithelial cell fate specialization. Nat Commun 2023; 14:3994. [PMID: 37452023 PMCID: PMC10349091 DOI: 10.1038/s41467-023-39261-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 06/06/2023] [Indexed: 07/18/2023] Open
Abstract
Differentiation is critical for cell fate decisions, but the signals involved remain unclear. The kidney proximal tubule (PT) cells reabsorb disulphide-rich proteins through endocytosis, generating cystine via lysosomal proteolysis. Here we report that defective cystine mobilization from lysosomes through cystinosin (CTNS), which is mutated in cystinosis, diverts PT cells towards growth and proliferation, disrupting their functions. Mechanistically, cystine storage stimulates Ragulator-Rag GTPase-dependent recruitment of mechanistic target of rapamycin complex 1 (mTORC1) and its constitutive activation. Re-introduction of CTNS restores nutrient-dependent regulation of mTORC1 in knockout cells, whereas cell-permeant analogues of L-cystine, accumulating within lysosomes, render wild-type cells resistant to nutrient withdrawal. Therapeutic mTORC1 inhibition corrects lysosome and differentiation downstream of cystine storage, and phenotypes in preclinical models of cystinosis. Thus, cystine serves as a lysosomal signal that tailors mTORC1 and metabolism to direct epithelial cell fate decisions. These results identify mechanisms and therapeutic targets for dysregulated homeostasis in cystinosis.
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Affiliation(s)
- Marine Berquez
- Institute of Physiology, University of Zurich, 8057, Zurich, Switzerland
| | - Zhiyong Chen
- Institute of Physiology, University of Zurich, 8057, Zurich, Switzerland
| | | | - Patrick Krohn
- Institute of Physiology, University of Zurich, 8057, Zurich, Switzerland
| | | | - Silvia Parolo
- Fondazione The Microsoft Research University of Trento-Centre for Computational and Systems Biology (COSBI), 38068, Rovereto, Italy
| | - Mikhail Korzinkin
- Insilico Medicine Hong Kong Ltd., Hong Kong Science and Technology Park, Hong Kong, Hong Kong SAR, China
| | - Anna Gaponova
- Insilico Medicine Hong Kong Ltd., Hong Kong Science and Technology Park, Hong Kong, Hong Kong SAR, China
| | - Endre Laczko
- Functional Genomics Center Zurich, University of Zurich, Winterthurerstrasse 190, CH-8057, Zurich, Switzerland
| | - Enrico Domenici
- Fondazione The Microsoft Research University of Trento-Centre for Computational and Systems Biology (COSBI), 38068, Rovereto, Italy
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, 38123, Trento, Italy
| | - Olivier Devuyst
- Institute of Physiology, University of Zurich, 8057, Zurich, Switzerland.
- Institute for Rare Diseases, UCLouvain Medical School, 1200, Brussels, Belgium.
| | - Alessandro Luciani
- Institute of Physiology, University of Zurich, 8057, Zurich, Switzerland.
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Kwoji ID, Aiyegoro OA, Okpeku M, Adeleke MA. 'Multi-omics' data integration: applications in probiotics studies. NPJ Sci Food 2023; 7:25. [PMID: 37277356 DOI: 10.1038/s41538-023-00199-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 05/22/2023] [Indexed: 06/07/2023] Open
Abstract
The concept of probiotics is witnessing increasing attention due to its benefits in influencing the host microbiome and the modulation of host immunity through the strengthening of the gut barrier and stimulation of antibodies. These benefits, combined with the need for improved nutraceuticals, have resulted in the extensive characterization of probiotics leading to an outburst of data generated using several 'omics' technologies. The recent development in system biology approaches to microbial science is paving the way for integrating data generated from different omics techniques for understanding the flow of molecular information from one 'omics' level to the other with clear information on regulatory features and phenotypes. The limitations and tendencies of a 'single omics' application to ignore the influence of other molecular processes justify the need for 'multi-omics' application in probiotics selections and understanding its action on the host. Different omics techniques, including genomics, transcriptomics, proteomics, metabolomics and lipidomics, used for studying probiotics and their influence on the host and the microbiome are discussed in this review. Furthermore, the rationale for 'multi-omics' and multi-omics data integration platforms supporting probiotics and microbiome analyses was also elucidated. This review showed that multi-omics application is useful in selecting probiotics and understanding their functions on the host microbiome. Hence, recommend a multi-omics approach for holistically understanding probiotics and the microbiome.
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Affiliation(s)
- Iliya Dauda Kwoji
- Discipline of Genetics, School of Life Sciences, College of Agriculture, Engineering and Sciences, University of KwaZulu-Natal, 4090, Durban, South Africa
| | - Olayinka Ayobami Aiyegoro
- Unit for Environmental Sciences and Management, North-West University, Potchefstroom, Northwest, South Africa
| | - Moses Okpeku
- Discipline of Genetics, School of Life Sciences, College of Agriculture, Engineering and Sciences, University of KwaZulu-Natal, 4090, Durban, South Africa
| | - Matthew Adekunle Adeleke
- Discipline of Genetics, School of Life Sciences, College of Agriculture, Engineering and Sciences, University of KwaZulu-Natal, 4090, Durban, South Africa.
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Kokoli M, Karatzas E, Baltoumas FA, Schneider R, Pafilis E, Paragkamian S, Doncheva NT, Jensen L, Pavlopoulos G. Arena3D web: interactive 3D visualization of multilayered networks supporting multiple directional information channels, clustering analysis and application integration. NAR Genom Bioinform 2023; 5:lqad053. [PMID: 37260509 PMCID: PMC10227371 DOI: 10.1093/nargab/lqad053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 04/25/2023] [Accepted: 05/18/2023] [Indexed: 06/02/2023] Open
Abstract
Arena3Dweb is an interactive web tool that visualizes multi-layered networks in 3D space. In this update, Arena3Dweb supports directed networks as well as up to nine different types of connections between pairs of nodes with the use of Bézier curves. It comes with different color schemes (light/gray/dark mode), custom channel coloring, four node clustering algorithms which one can run on-the-fly, visualization in VR mode and predefined layer layouts (zig-zag, star and cube). This update also includes enhanced navigation controls (mouse orbit controls, layer dragging and layer/node selection), while its newly developed API allows integration with external applications as well as saving and loading of sessions in JSON format. Finally, a dedicated Cytoscape app has been developed, through which users can automatically send their 2D networks from Cytoscape to Arena3Dweb for 3D multi-layer visualization. Arena3Dweb is accessible at http://arena3d.pavlopouloslab.info or http://arena3d.org.
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Affiliation(s)
| | | | - Fotis A Baltoumas
- Institute for Fundamental Biomedical Research, BSRC “Alexander Fleming”, Vari16672, Greece
| | - Reinhard Schneider
- University of Luxembourg, Luxembourg Centre for Systems Biomedicine, Bioinformatics Core, Esch-sur-Alzette, Luxembourg
| | - Evangelos Pafilis
- Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Former U.S. Base of Gournes, Heraklion 71003, Greece
| | - Savvas Paragkamian
- Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Former U.S. Base of Gournes, Heraklion 71003, Greece
- Department of Biology, University of Crete, Voutes University Campus, P.O. Box 2208, 70013 Heraklion, Crete, Greece
| | - Nadezhda T Doncheva
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen N DK-2200, Denmark
| | - Lars Juhl Jensen
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen N DK-2200, Denmark
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Piper M, Hoen M, Darragh LB, Knitz MW, Nguyen D, Gadwa J, Durini G, Karakoc I, Grier A, Neupert B, Van Court B, Abdelazeem KNM, Yu J, Olimpo NA, Corbo S, Ross RB, Pham TT, Joshi M, Kedl RM, Saviola AJ, Amann M, Umaña P, Codarri Deak L, Klein C, D'Alessandro A, Karam SD. Simultaneous targeting of PD-1 and IL-2Rβγ with radiation therapy inhibits pancreatic cancer growth and metastasis. Cancer Cell 2023; 41:950-969.e6. [PMID: 37116489 PMCID: PMC10246400 DOI: 10.1016/j.ccell.2023.04.001] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 01/05/2023] [Accepted: 03/31/2023] [Indexed: 04/30/2023]
Abstract
In pancreatic ductal adenocarcinoma (PDAC) patients, we show that response to radiation therapy (RT) is characterized by increased IL-2Rβ and IL-2Rγ along with decreased IL-2Rα expression. The bispecific PD1-IL2v is a PD-1-targeted IL-2 variant (IL-2v) immunocytokine with engineered IL-2 cis targeted to PD-1 and abolished IL-2Rα binding, which enhances tumor-antigen-specific T cell activation while reducing regulatory T cell (Treg) suppression. Using PD1-IL2v in orthotopic PDAC KPC-driven tumor models, we show marked improvement in local and metastatic survival, along with a profound increase in tumor-infiltrating CD8+ T cell subsets with a transcriptionally and metabolically active phenotype and preferential activation of antigen-specific CD8+ T cells. In combination with single-dose RT, PD1-IL2v treatment results in a robust, durable expansion of polyfunctional CD8+ T cells, T cell stemness, tumor-specific memory immune response, natural killer (NK) cell activation, and decreased Tregs. These data show that PD1-IL2v leads to profound local and distant response in PDAC.
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Affiliation(s)
- Miles Piper
- Department of Radiation Oncology, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Maureen Hoen
- Department of Radiation Oncology, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Laurel B Darragh
- Department of Radiation Oncology, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA; Department of Microbiology and Immunology, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Michael W Knitz
- Department of Radiation Oncology, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Diemmy Nguyen
- Department of Radiation Oncology, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Jacob Gadwa
- Department of Radiation Oncology, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Greta Durini
- Roche Innovation Center Zurich, Roche Pharma Research and Early Development (pRED), Schlieren, Switzerland
| | - Idil Karakoc
- Roche Innovation Center Zurich, Roche Pharma Research and Early Development (pRED), Schlieren, Switzerland
| | - Abby Grier
- Department of Biochemistry and Molecular Genetics, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Brooke Neupert
- Department of Radiation Oncology, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Benjamin Van Court
- Department of Radiation Oncology, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Khalid N M Abdelazeem
- Department of Radiation Oncology, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Justin Yu
- Department of Radiation Oncology, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Nicholas A Olimpo
- Department of Radiation Oncology, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Sophia Corbo
- Department of Radiation Oncology, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Richard Blake Ross
- Department of Radiation Oncology, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Tiffany T Pham
- Department of Radiation Oncology, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Molishree Joshi
- Department of Pharmacology, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Ross M Kedl
- Department of Microbiology and Immunology, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Anthony J Saviola
- Department of Biochemistry and Molecular Genetics, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Maria Amann
- Roche Innovation Center Zurich, Roche Pharma Research and Early Development (pRED), Schlieren, Switzerland
| | - Pablo Umaña
- Roche Innovation Center Zurich, Roche Pharma Research and Early Development (pRED), Schlieren, Switzerland
| | - Laura Codarri Deak
- Roche Innovation Center Zurich, Roche Pharma Research and Early Development (pRED), Schlieren, Switzerland
| | - Christian Klein
- Roche Innovation Center Zurich, Roche Pharma Research and Early Development (pRED), Schlieren, Switzerland
| | - Angelo D'Alessandro
- Department of Biochemistry and Molecular Genetics, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Sana D Karam
- Department of Radiation Oncology, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA; Department of Microbiology and Immunology, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA.
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Wang RS, Maron BA, Loscalzo J. Multiomics Network Medicine Approaches to Precision Medicine and Therapeutics in Cardiovascular Diseases. Arterioscler Thromb Vasc Biol 2023; 43:493-503. [PMID: 36794589 PMCID: PMC10038904 DOI: 10.1161/atvbaha.122.318731] [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] [Received: 11/07/2022] [Accepted: 01/30/2023] [Indexed: 02/17/2023]
Abstract
Cardiovascular diseases (CVD) are the leading cause of death worldwide and display complex phenotypic heterogeneity caused by many convergent processes, including interactions between genetic variation and environmental factors. Despite the identification of a large number of associated genes and genetic loci, the precise mechanisms by which these genes systematically influence the phenotypic heterogeneity of CVD are not well understood. In addition to DNA sequence, understanding the molecular mechanisms of CVD requires data from other omics levels, including the epigenome, the transcriptome, the proteome, as well as the metabolome. Recent advances in multiomics technologies have opened new precision medicine opportunities beyond genomics that can guide precise diagnosis and personalized treatment. At the same time, network medicine has emerged as an interdisciplinary field that integrates systems biology and network science to focus on the interactions among biological components in health and disease, providing an unbiased framework through which to integrate systematically these multiomics data. In this review, we briefly present such multiomics technologies, including bulk omics and single-cell omics technologies, and discuss how they can contribute to precision medicine. We then highlight network medicine-based integration of multiomics data for precision medicine and therapeutics in CVD. We also include a discussion of current challenges, potential limitations, and future directions in the study of CVD using multiomics network medicine approaches.
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Affiliation(s)
- Rui-Sheng Wang
- Division of Cardiovascular Medicine
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | | | - Joseph Loscalzo
- Division of Cardiovascular Medicine
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
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44
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Fu J, Zhu F, Xu CJ, Li Y. Metabolomics meets systems immunology. EMBO Rep 2023; 24:e55747. [PMID: 36916532 PMCID: PMC10074123 DOI: 10.15252/embr.202255747] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 12/24/2022] [Accepted: 02/24/2023] [Indexed: 03/16/2023] Open
Abstract
Metabolic processes play a critical role in immune regulation. Metabolomics is the systematic analysis of small molecules (metabolites) in organisms or biological samples, providing an opportunity to comprehensively study interactions between metabolism and immunity in physiology and disease. Integrating metabolomics into systems immunology allows the exploration of the interactions of multilayered features in the biological system and the molecular regulatory mechanism of these features. Here, we provide an overview on recent technological developments of metabolomic applications in immunological research. To begin, two widely used metabolomics approaches are compared: targeted and untargeted metabolomics. Then, we provide a comprehensive overview of the analysis workflow and the computational tools available, including sample preparation, raw spectra data preprocessing, data processing, statistical analysis, and interpretation. Third, we describe how to integrate metabolomics with other omics approaches in immunological studies using available tools. Finally, we discuss new developments in metabolomics and its prospects for immunology research. This review provides guidance to researchers using metabolomics and multiomics in immunity research, thus facilitating the application of systems immunology to disease research.
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Affiliation(s)
- Jianbo Fu
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and Hannover Medical School (MHH), Hannover, Germany.,TWINCORE Centre for Experimental and Clinical Infection Research, a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany.,College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Feng Zhu
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Cheng-Jian Xu
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and Hannover Medical School (MHH), Hannover, Germany.,TWINCORE Centre for Experimental and Clinical Infection Research, a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany.,Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Yang Li
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and Hannover Medical School (MHH), Hannover, Germany.,TWINCORE Centre for Experimental and Clinical Infection Research, a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany.,Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, The Netherlands
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45
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Gonzales LISA, Qiao JW, Buffier AW, Rogers LJ, Suchowerska N, McKenzie DR, Kwan AH. An omics approach to delineating the molecular mechanisms that underlie the biological effects of physical plasma. BIOPHYSICS REVIEWS 2023; 4:011312. [PMID: 38510160 PMCID: PMC10903421 DOI: 10.1063/5.0089831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 02/24/2023] [Indexed: 03/22/2024]
Abstract
The use of physical plasma to treat cancer is an emerging field, and interest in its applications in oncology is increasing rapidly. Physical plasma can be used directly by aiming the plasma jet onto cells or tissue, or indirectly, where a plasma-treated solution is applied. A key scientific question is the mechanism by which physical plasma achieves selective killing of cancer over normal cells. Many studies have focused on specific pathways and mechanisms, such as apoptosis and oxidative stress, and the role of redox biology. However, over the past two decades, there has been a rise in omics, the systematic analysis of entire collections of molecules in a biological entity, enabling the discovery of the so-called "unknown unknowns." For example, transcriptomics, epigenomics, proteomics, and metabolomics have helped to uncover molecular mechanisms behind the action of physical plasma, revealing critical pathways beyond those traditionally associated with cancer treatments. This review showcases a selection of omics and then summarizes the insights gained from these studies toward understanding the biological pathways and molecular mechanisms implicated in physical plasma treatment. Omics studies have revealed how reactive species generated by plasma treatment preferentially affect several critical cellular pathways in cancer cells, resulting in epigenetic, transcriptional, and post-translational changes that promote cell death. Finally, this review considers the outlook for omics in uncovering both synergies and antagonisms with other common cancer therapies, as well as in overcoming challenges in the clinical translation of physical plasma.
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Affiliation(s)
- Lou I. S. A. Gonzales
- School of Life and Environmental Sciences, The University of Sydney, NSW 2006, Australia
| | - Jessica W. Qiao
- School of Life and Environmental Sciences, The University of Sydney, NSW 2006, Australia
| | - Aston W. Buffier
- School of Life and Environmental Sciences, The University of Sydney, NSW 2006, Australia
| | | | | | | | - Ann H. Kwan
- Author to whom correspondence should be addressed:
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Alabed HBR, Gorello P, Pellegrino RM, Lancioni H, La Starza R, Taddei AA, Urbanelli L, Buratta S, Fernandez AGL, Matteucci C, Caniglia M, Arcioni F, Mecucci C, Emiliani C. Comparison between Sickle Cell Disease Patients and Healthy Donors: Untargeted Lipidomic Study of Erythrocytes. Int J Mol Sci 2023; 24:ijms24032529. [PMID: 36768849 PMCID: PMC9917006 DOI: 10.3390/ijms24032529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 01/19/2023] [Accepted: 01/26/2023] [Indexed: 01/31/2023] Open
Abstract
Sickle cell disease (SCD) is one of the most common severe monogenic disorders in the world caused by a mutation on HBB gene and characterized by hemoglobin polymerization, erythrocyte rigidity, vaso-occlusion, chronic anemia, hemolysis, and vasculopathy. Recently, the scientific community has focused on the multiple genetic and clinical profiles of SCD. However, the lipid composition of sickle cells has received little attention in the literature. According to recent studies, changes in the lipid profile are strongly linked to several disorders. Therefore, the aim of this study is to dig deeper into lipidomic analysis of erythrocytes in order to highlight any variations between healthy and patient subjects. 241 lipid molecular species divided into 17 classes have been annotated and quantified. Lipidomic profiling of SCD patients showed that over 24% of total lipids were altered most of which are phospholipids. In-depth study of significant changes in lipid metabolism can give an indication of the enzymes and genes involved. In a systems biology scenario, these variations can be useful to improve the understanding of the biochemical basis of SCD and to try to make a score system that could be predictive for the severity of clinical manifestations.
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Affiliation(s)
- Husam B. R. Alabed
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06100 Perugia, Italy
| | - Paolo Gorello
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06100 Perugia, Italy
| | - Roberto Maria Pellegrino
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06100 Perugia, Italy
- Correspondence:
| | - Hovirag Lancioni
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06100 Perugia, Italy
| | - Roberta La Starza
- Hematology and Bone Marrow Transplantation Unit, Laboratory of Molecular Medicine (CREO), Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy
| | - Anna Aurora Taddei
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06100 Perugia, Italy
| | - Lorena Urbanelli
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06100 Perugia, Italy
| | - Sandra Buratta
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06100 Perugia, Italy
| | - Anair Graciela Lema Fernandez
- Hematology and Bone Marrow Transplantation Unit, Laboratory of Molecular Medicine (CREO), Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy
| | - Caterina Matteucci
- Hematology and Bone Marrow Transplantation Unit, Laboratory of Molecular Medicine (CREO), Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy
| | - Maurizio Caniglia
- Pediatric Oncology-Hematology, Azienda Ospedaliera di Perugia, 06100 Perugia, Italy
| | - Francesco Arcioni
- Pediatric Oncology-Hematology, Azienda Ospedaliera di Perugia, 06100 Perugia, Italy
| | - Cristina Mecucci
- Hematology and Bone Marrow Transplantation Unit, Laboratory of Molecular Medicine (CREO), Department of Medicine and Surgery, University of Perugia, 06132 Perugia, Italy
| | - Carla Emiliani
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06100 Perugia, Italy
- Centro di Eccellenza sui Materiali Innovativi Nanostrutturati (CEMIN), University of Perugia, Via del Giochetto, 06123 Perugia, Italy
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47
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Lu Y, Pang Z, Xia J. Comprehensive investigation of pathway enrichment methods for functional interpretation of LC-MS global metabolomics data. Brief Bioinform 2023; 24:bbac553. [PMID: 36572652 PMCID: PMC9851290 DOI: 10.1093/bib/bbac553] [Citation(s) in RCA: 30] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 10/31/2022] [Accepted: 11/15/2022] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Global or untargeted metabolomics is widely used to comprehensively investigate metabolic profiles under various pathophysiological conditions such as inflammations, infections, responses to exposures or interactions with microbial communities. However, biological interpretation of global metabolomics data remains a daunting task. Recent years have seen growing applications of pathway enrichment analysis based on putative annotations of liquid chromatography coupled with mass spectrometry (LC-MS) peaks for functional interpretation of LC-MS-based global metabolomics data. However, due to intricate peak-metabolite and metabolite-pathway relationships, considerable variations are observed among results obtained using different approaches. There is an urgent need to benchmark these approaches to inform the best practices. RESULTS We have conducted a benchmark study of common peak annotation approaches and pathway enrichment methods in current metabolomics studies. Representative approaches, including three peak annotation methods and four enrichment methods, were selected and benchmarked under different scenarios. Based on the results, we have provided a set of recommendations regarding peak annotation, ranking metrics and feature selection. The overall better performance was obtained for the mummichog approach. We have observed that a ~30% annotation rate is sufficient to achieve high recall (~90% based on mummichog), and using semi-annotated data improves functional interpretation. Based on the current platforms and enrichment methods, we further propose an identifiability index to indicate the possibility of a pathway being reliably identified. Finally, we evaluated all methods using 11 COVID-19 and 8 inflammatory bowel diseases (IBD) global metabolomics datasets.
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Affiliation(s)
- Yao Lu
- Department of Microbiology and Immunology, McGill University, Quebec, Canada
| | - Zhiqiang Pang
- Institute of Parasitology, McGill University, Quebec, Canada
| | - Jianguo Xia
- Department of Microbiology and Immunology, McGill University, Quebec, Canada
- Institute of Parasitology, McGill University, Quebec, Canada
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48
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Evaluation of Two Simultaneous Metabolomic and Proteomic Extraction Protocols Assessed by Ultra-High-Performance Liquid Chromatography Tandem Mass Spectrometry. Int J Mol Sci 2023; 24:ijms24021354. [PMID: 36674867 PMCID: PMC9865896 DOI: 10.3390/ijms24021354] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 12/31/2022] [Accepted: 01/01/2023] [Indexed: 01/13/2023] Open
Abstract
Untargeted multi-omics analysis of plasma is an emerging tool for the identification of novel biomarkers for evaluating disease prognosis, and for developing a better understanding of molecular mechanisms underlying human disease. The successful application of metabolomic and proteomic approaches relies on reproducibly quantifying a wide range of metabolites and proteins. Herein, we report the results of untargeted metabolomic and proteomic analyses from blood plasma samples following analyte extraction by two frequently-used solvent systems: chloroform/methanol and methanol-only. Whole blood samples were collected from participants (n = 6) at University Hospital Sharjah (UHS) hospital, then plasma was separated and extracted by two methods: (i) methanol precipitation and (ii) 4:3 methanol:chloroform extraction. The coverage and reproducibility of the two methods were assessed by ultra-high-performance liquid chromatography-electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS). The study revealed that metabolite extraction by methanol-only showed greater reproducibility for both metabolomic and proteomic quantifications than did methanol/chloroform, while yielding similar peptide coverage. However, coverage of extracted metabolites was higher with the methanol/chloroform precipitation.
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49
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Labenz J, Borkenstein DP, Heil FJ, Madisch A, Tappe U, Schmidt H, Terjung B, Klymiuk I, Horvath A, Gross M, Stadlbauer V. Application of a multispecies probiotic reduces gastro-intestinal discomfort and induces microbial changes after colonoscopy. Front Oncol 2023; 12:1078315. [PMID: 36698396 PMCID: PMC9870247 DOI: 10.3389/fonc.2022.1078315] [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: 10/24/2022] [Accepted: 12/02/2022] [Indexed: 01/11/2023] Open
Abstract
Even after decades of research and pharmaceutical development, cancer is still one of the most common causes of death in the western population and the management of cancer will remain a major challenge of medical research. One of the most common types of cancer is colorectal cancer (CRC). Prevention by detection of early-stage precursors is the most reliable method to prevent CRC development. In dependence of age, familial predisposition, and other risk factors the preventative routine screening for CRC by colonoscopy should be performed at least twice in intervals of about ten years. Although colonoscopy is a life-saving clinical examination reducing both incidence and mortality of CRC significantly, it has still a bad reputation in the population as an uncomfortable procedure with unpleasant side effects lasting sometimes over days to weeks. These effects are most likely caused by the bowel preparation before colonoscopy, which is crucial for a successful colonoscopy with high quality. Beside pain, bleeding and other rare but severe complications of colonoscopy, cleaning of the intestinal mucosa alters the gut microbiome significantly and consistently. Abdominal pain, cramps, diarrhea, nausea, bloating, and constipation are common adverse events which can continue to affect patients for days or even weeks after the procedure. In this multicenter, placebo controlled, double blind clinical trial, we investigated the effect of an intervention with a multispecies probiotic formulation for 30 days on the adverse events due to bowel preparation. We show that the treatment of participants with the multispecies probiotic formulation decreases the number of days with constipation significantly, and reduced pain, bloating, diarrhea, and general discomfort. 16S based amplicon analyses reveal recovery of administered probiotic strains from stool samples and differences in alpha diversity dynamics with higher variability in the probiotic group compared to the placebo group. In conclusion, the probiotic ameliorates the side effects after colonoscopy and might be an important supplement to increase acceptance of this life-saving preventative examination. Further, we present here for the first time that probiotic intervention of only 30 days affects alpha diversity parameters in stool samples.
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Affiliation(s)
- Joachim Labenz
- Department of Internal Medicine, Diakonie Klinikum Jung-Stilling, Siegen, Germany
| | | | | | - Ahmed Madisch
- Department of Internal Medicine I, Hospital Clinic Siloah, Hannover, Germany
- Centrum Gastroenterologie Bethanien, Agaplesion Krankenhaus Bethanien, Frankfurt, Germany
| | - Ulrich Tappe
- Gastropraxis an der St. Barbara Klinik, Hamm, Germany
| | - Harald Schmidt
- Praxis für Innere Medizin und Gastroenterologie Dr. H. Schmidt, Berlin, Germany
| | | | - Ingeborg Klymiuk
- Division of Cell Biology, Histology and Embryology, Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria
| | - Angela Horvath
- Division for Gastroenterology and Hepatology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
- Area 3 Microbiome Modulation for Precision Medicine, Center for Biomarker Research in Medicine (CBmed), Graz, Austria
| | - Manfred Gross
- Department of Internal medicine, Internistisches Klinikum München Süd, Munich, Germany
| | - Vanessa Stadlbauer
- Division for Gastroenterology and Hepatology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
- Area 3 Microbiome Modulation for Precision Medicine, Center for Biomarker Research in Medicine (CBmed), Graz, Austria
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50
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Baltoumas FA, Karatzas E, Paez-Espino D, Venetsianou NK, Aplakidou E, Oulas A, Finn RD, Ovchinnikov S, Pafilis E, Kyrpides NC, Pavlopoulos GA. Exploring microbial functional biodiversity at the protein family level-From metagenomic sequence reads to annotated protein clusters. FRONTIERS IN BIOINFORMATICS 2023; 3:1157956. [PMID: 36959975 PMCID: PMC10029925 DOI: 10.3389/fbinf.2023.1157956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 02/21/2023] [Indexed: 03/06/2023] Open
Abstract
Metagenomics has enabled accessing the genetic repertoire of natural microbial communities. Metagenome shotgun sequencing has become the method of choice for studying and classifying microorganisms from various environments. To this end, several methods have been developed to process and analyze the sequence data from raw reads to end-products such as predicted protein sequences or families. In this article, we provide a thorough review to simplify such processes and discuss the alternative methodologies that can be followed in order to explore biodiversity at the protein family level. We provide details for analysis tools and we comment on their scalability as well as their advantages and disadvantages. Finally, we report the available data repositories and recommend various approaches for protein family annotation related to phylogenetic distribution, structure prediction and metadata enrichment.
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Affiliation(s)
- Fotis A. Baltoumas
- Institute for Fundamental Biomedical Research, BSRC “Alexander Fleming”, Vari, Greece
- *Correspondence: Fotis A. Baltoumas, ; Nikos C. Kyrpides, ; Georgios A. Pavlopoulos,
| | - Evangelos Karatzas
- Institute for Fundamental Biomedical Research, BSRC “Alexander Fleming”, Vari, Greece
| | - David Paez-Espino
- Lawrence Berkeley National Laboratory, DOE Joint Genome Institute, Berkeley, CA, United States
| | - Nefeli K. Venetsianou
- Institute for Fundamental Biomedical Research, BSRC “Alexander Fleming”, Vari, Greece
| | - Eleni Aplakidou
- Institute for Fundamental Biomedical Research, BSRC “Alexander Fleming”, Vari, Greece
| | - Anastasis Oulas
- The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
| | - Robert D. Finn
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Cambridge, United Kingdom
| | - Sergey Ovchinnikov
- John Harvard Distinguished Science Fellowship Program, Harvard University, Cambridge, MA, United States
| | - Evangelos Pafilis
- Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Heraklion, Greece
| | - Nikos C. Kyrpides
- Lawrence Berkeley National Laboratory, DOE Joint Genome Institute, Berkeley, CA, United States
- *Correspondence: Fotis A. Baltoumas, ; Nikos C. Kyrpides, ; Georgios A. Pavlopoulos,
| | - Georgios A. Pavlopoulos
- Institute for Fundamental Biomedical Research, BSRC “Alexander Fleming”, Vari, Greece
- Center of New Biotechnologies and Precision Medicine, Department of Medicine, School of Health Sciences, National and Kapodistrian University of Athens, Athens, Greece
- Hellenic Army Academy, Vari, Greece
- *Correspondence: Fotis A. Baltoumas, ; Nikos C. Kyrpides, ; Georgios A. Pavlopoulos,
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