1
|
Mora I, Puiggròs F, Serras F, Gil-Cardoso K, Escoté X. Emerging models for studying adipose tissue metabolism. Biochem Pharmacol 2024; 223:116123. [PMID: 38484851 DOI: 10.1016/j.bcp.2024.116123] [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: 11/28/2023] [Revised: 03/11/2024] [Accepted: 03/11/2024] [Indexed: 03/17/2024]
Abstract
Understanding adipose metabolism is essential for addressing obesity and related health concerns. However, the ethical and scientific pressure to animal testing, aligning with the 3Rs, has triggered the implementation of diverse alternative models for analysing anomalies in adipose metabolism. In this review, we will address this issue from various perspectives. Traditional adipocyte cell cultures, whether animal or human-derived, offer a fundamental starting point. These systems have their merits but may not fully replicate in vivo complexity. Established cell lines are valuable for high-throughput screening but may lack the authenticity of primary-derived adipocytes, which closely mimic native tissue. To enhance model sophistication, spheroids have been introduced. These three-dimensional cultures better mimicking the in vivo microenvironment, enabling the study of intricate cell-cell interactions, gene expression, and metabolic pathways. Organ-on-a-chip (OoC) platforms take this further by integrating multiple cell types into microfluidic devices, simulating tissue-level functions. Adipose-OoC (AOoC) provides dynamic environments with applications spanning drug testing to personalized medicine and nutrition. Beyond in vitro models, genetically amenable organisms (Caenorhabditis elegans, Drosophila melanogaster, and zebrafish larvae) have become powerful tools for investigating fundamental molecular mechanisms that govern adipose tissue functions. Their genetic tractability allows for efficient manipulation and high-throughput studies. In conclusion, a diverse array of research models is crucial for deciphering adipose metabolism. By leveraging traditional adipocyte cell cultures, primary-derived cells, spheroids, AOoCs, and lower organism models, we bridge the gap between animal testing and a more ethical, scientifically robust, and human-relevant approach, advancing our understanding of adipose tissue metabolism and its impact on health.
Collapse
Affiliation(s)
- Ignasi Mora
- Brudy Technology S.L., 08006 Barcelona, Spain
| | - Francesc Puiggròs
- Eurecat, Centre Tecnològic de Catalunya, Biotechnology Area, 43204 Reus, Spain
| | - Florenci Serras
- Department of Genetics, Microbiology and Statistics, School of Biology, University of Barcelona and Institute of Biomedicine of the University of Barcelona, Diagonal 643, 08028 Barcelona, Spain
| | - Katherine Gil-Cardoso
- Eurecat, Centre Tecnològic de Catalunya, Nutrition and Health Unit, 43204 Reus, Spain
| | - Xavier Escoté
- Eurecat, Centre Tecnològic de Catalunya, Nutrition and Health Unit, 43204 Reus, Spain.
| |
Collapse
|
2
|
Chakravorty A, Sheeba V, Manjithaya R. Drosophila melanogaster Neuromuscular Junction as a Model to Study Synaptopathies and Neuronal Autophagy. Methods Mol Biol 2024; 2761:97-120. [PMID: 38427233 DOI: 10.1007/978-1-0716-3662-6_9] [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] [Indexed: 03/02/2024]
Abstract
Neuronal synapse dysfunction is a key characteristic of several neurodegenerative disorders, such as Alzheimer's disease, spinocerebellar ataxias, and Huntington's disease. Modeling these disorders to study synaptic dysfunction requires a robust and reproducible method for assaying the subtle changes associated with synaptopathies in terms of structure and function of the synapses. Drosophila melanogaster neuromuscular junctions (NMJs) serve as good models to study such alterations. Further, modifications in the microenvironment of synapses can sometimes reflect in the behavior of the animal, which can also be assayed in a high-throughput manner. The methods outlined in this chapter highlight assays to study the behavioral changes associated with synaptic dysfunction in a spinocerebellar ataxia type 3 (SCA3) model. Further, molecular assessment of alterations in NMJ structure and function is also summarized, followed by effects of autophagy pathway upregulation in providing neuroprotection. These methods can be further extended and modified to study the therapeutic effects of drugs or small molecules in providing neuroprotection for any synaptopathy models.
Collapse
Affiliation(s)
- Anushka Chakravorty
- Autophagy Laboratory, Molecular Biology and Genetics Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, Bangalore, India
| | - Vasu Sheeba
- Chronobiology and Behavioural Neurogenetics Laboratory, Neuroscience Unit, Bangalore, India.
| | - Ravi Manjithaya
- Autophagy Laboratory, Molecular Biology and Genetics Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, Bangalore, India.
- Chronobiology and Behavioural Neurogenetics Laboratory, Neuroscience Unit, Bangalore, India.
| |
Collapse
|
3
|
Hu Qian S, Shi MW, Wang DY, Fear JM, Chen L, Tu YX, Liu HS, Zhang Y, Zhang SJ, Yu SS, Oliver B, Chen ZX. Integrating massive RNA-seq data to elucidate transcriptome dynamics in Drosophila melanogaster. Brief Bioinform 2023; 24:bbad177. [PMID: 37232385 PMCID: PMC10505420 DOI: 10.1093/bib/bbad177] [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: 12/15/2022] [Revised: 04/19/2023] [Accepted: 04/20/2023] [Indexed: 05/27/2023] Open
Abstract
The volume of ribonucleic acid (RNA)-seq data has increased exponentially, providing numerous new insights into various biological processes. However, due to significant practical challenges, such as data heterogeneity, it is still difficult to ensure the quality of these data when integrated. Although some quality control methods have been developed, sample consistency is rarely considered and these methods are susceptible to artificial factors. Here, we developed MassiveQC, an unsupervised machine learning-based approach, to automatically download and filter large-scale high-throughput data. In addition to the read quality used in other tools, MassiveQC also uses the alignment and expression quality as model features. Meanwhile, it is user-friendly since the cutoff is generated from self-reporting and is applicable to multimodal data. To explore its value, we applied MassiveQC to Drosophila RNA-seq data and generated a comprehensive transcriptome atlas across 28 tissues from embryogenesis to adulthood. We systematically characterized fly gene expression dynamics and found that genes with high expression dynamics were likely to be evolutionarily young and expressed at late developmental stages, exhibiting high nonsynonymous substitution rates and low phenotypic severity, and they were involved in simple regulatory programs. We also discovered that human and Drosophila had strong positive correlations in gene expression in orthologous organs, revealing the great potential of the Drosophila system for studying human development and disease.
Collapse
Affiliation(s)
- Sheng Hu Qian
- Hubei Hongshan Laboratory, College of Biomedicine and Health, Huazhong Agricultural University, Wuhan 430070, China
| | - Meng-Wei Shi
- Hubei Hongshan Laboratory, College of Biomedicine and Health, Huazhong Agricultural University, Wuhan 430070, China
| | - Dan-Yang Wang
- Hubei Hongshan Laboratory, College of Biomedicine and Health, Huazhong Agricultural University, Wuhan 430070, China
| | - Justin M Fear
- Section of Developmental Genomics, National Institute of Diabetes and Kidney and Digestive Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Lu Chen
- Hubei Hongshan Laboratory, College of Biomedicine and Health, Huazhong Agricultural University, Wuhan 430070, China
| | - Yi-Xuan Tu
- Hubei Hongshan Laboratory, College of Biomedicine and Health, Huazhong Agricultural University, Wuhan 430070, China
| | - Hong-Shan Liu
- Hubei Hongshan Laboratory, College of Biomedicine and Health, Huazhong Agricultural University, Wuhan 430070, China
| | - Yuan Zhang
- Hubei Hongshan Laboratory, College of Biomedicine and Health, Huazhong Agricultural University, Wuhan 430070, China
| | - Shuai-Jie Zhang
- Hubei Hongshan Laboratory, College of Biomedicine and Health, Huazhong Agricultural University, Wuhan 430070, China
| | - Shan-Shan Yu
- Hubei Hongshan Laboratory, College of Biomedicine and Health, Huazhong Agricultural University, Wuhan 430070, China
| | - Brian Oliver
- Section of Developmental Genomics, National Institute of Diabetes and Kidney and Digestive Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Zhen-Xia Chen
- Hubei Hongshan Laboratory, College of Biomedicine and Health, Huazhong Agricultural University, Wuhan 430070, China
- Section of Developmental Genomics, National Institute of Diabetes and Kidney and Digestive Diseases, National Institutes of Health, Bethesda, MD 20892, USA
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Life Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
- Interdisciplinary Sciences Institute, Huazhong Agricultural University, Wuhan 430070, China
- Shenzhen Institute of Nutrition and Health, Huazhong Agricultural University, Shenzhen 518000, China
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518000, China
| |
Collapse
|
4
|
Haddadi M, Ataei R. wde, calpA, if, dap160, and poe genes knock down Drosophila models exhibit neurofunctional deficit. Gene 2022; 829:146499. [PMID: 35447243 DOI: 10.1016/j.gene.2022.146499] [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: 01/07/2022] [Revised: 03/14/2022] [Accepted: 04/14/2022] [Indexed: 11/27/2022]
Abstract
Intellectual disability (ID) is a heterogeneous disorder with high prevalence and remarkable social and cost burdens. Novel genetic variants of ATF7IP, CAPN9, ITGAV, ITSN1, and UBR4 genes are reported to be associated with the ID among Iranian families. However, in vivo validation is required to confirm the functional role of these variants in ID development. Drosophila melanogaster is a convenient model for such functional investigations as its genome bears ortholog of more than 75% of the disease-causing genes in human and represents numerous approaches to study defects in neuronal function. In this connection, RNAi gene silencing was applied to wde, calpA, if, dap160, and poe genes, the Drosophila ortholog of the selected human genes, and then consequent structural and functional changes in neurons were studied by means of immunohistochemistry and confocal microscopy of mushroom bodies (MBs) and validated behavioural assays including larvae and adult conditioning learning and memories, and ethanol sensitivity. Down-regulation of these genes led to neuronal loss which was evident by decline in total fluorescent signal intensity in micrographs of MBs structure. The gene silencing caused neuronal dysfunction and induction of ID-like symptoms manifested by deficits in larval preference learning, and short-term olfactory memory and courtship suppression learning in adults. Moreover, the RNAi flies showed higher sensitivity to ethanol vapour. Interestingly, the poe knock-down flies exhibited the most severe phenotypes among other genes. Altogether, we believe this study is first-of-its-kind and findings are highly applicable to confirm pathogenecity of the selected ID gene variants in Iranian population.
Collapse
Affiliation(s)
- Mohammad Haddadi
- Department of Biology, Faculty of Science, University of Zabol, Zabol, Iran.
| | - Reza Ataei
- Department of Biology, Faculty of Science, University of Zabol, Zabol, Iran
| |
Collapse
|