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Maraslioglu-Sperber A, Pizzi E, Fisch JO, Kattler K, Ritter T, Friauf E. Molecular and functional profiling of cell diversity and identity in the lateral superior olive, an auditory brainstem center with ascending and descending projections. Front Cell Neurosci 2024; 18:1354520. [PMID: 38846638 PMCID: PMC11153811 DOI: 10.3389/fncel.2024.1354520] [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: 12/12/2023] [Accepted: 03/15/2024] [Indexed: 06/09/2024] Open
Abstract
The lateral superior olive (LSO), a prominent integration center in the auditory brainstem, contains a remarkably heterogeneous population of neurons. Ascending neurons, predominantly principal neurons (pLSOs), process interaural level differences for sound localization. Descending neurons (lateral olivocochlear neurons, LOCs) provide feedback into the cochlea and are thought to protect against acoustic overload. The molecular determinants of the neuronal diversity in the LSO are largely unknown. Here, we used patch-seq analysis in mice at postnatal days P10-12 to classify developing LSO neurons according to their functional and molecular profiles. Across the entire sample (n = 86 neurons), genes involved in ATP synthesis were particularly highly expressed, confirming the energy expenditure of auditory neurons. Two clusters were identified, pLSOs and LOCs. They were distinguished by 353 differentially expressed genes (DEGs), most of which were novel for the LSO. Electrophysiological analysis confirmed the transcriptomic clustering. We focused on genes affecting neuronal input-output properties and validated some of them by immunohistochemistry, electrophysiology, and pharmacology. These genes encode proteins such as osteopontin, Kv11.3, and Kvβ3 (pLSO-specific), calcitonin-gene-related peptide (LOC-specific), or Kv7.2 and Kv7.3 (no DEGs). We identified 12 "Super DEGs" and 12 genes showing "Cluster similarity." Collectively, we provide fundamental and comprehensive insights into the molecular composition of individual ascending and descending neurons in the juvenile auditory brainstem and how this may relate to their specific functions, including developmental aspects.
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Affiliation(s)
- Ayse Maraslioglu-Sperber
- Animal Physiology Group, Department of Biology, University of Kaiserslautern-Landau, Kaiserslautern, Germany
| | - Erika Pizzi
- Animal Physiology Group, Department of Biology, University of Kaiserslautern-Landau, Kaiserslautern, Germany
| | - Jonas O. Fisch
- Animal Physiology Group, Department of Biology, University of Kaiserslautern-Landau, Kaiserslautern, Germany
| | - Kathrin Kattler
- Genetics/Epigenetics Group, Department of Biological Sciences, Saarland University, Saarbrücken, Germany
| | - Tamara Ritter
- Animal Physiology Group, Department of Biology, University of Kaiserslautern-Landau, Kaiserslautern, Germany
| | - Eckhard Friauf
- Animal Physiology Group, Department of Biology, University of Kaiserslautern-Landau, Kaiserslautern, Germany
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Al Sultan A, Rattray Z, Rattray NJW. Toxicometabolomics-based cardiotoxicity evaluation of Thiazolidinedione exposure in human-derived cardiomyocytes. Metabolomics 2024; 20:24. [PMID: 38393619 PMCID: PMC10891199 DOI: 10.1007/s11306-024-02097-z] [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: 01/02/2024] [Accepted: 01/29/2024] [Indexed: 02/25/2024]
Abstract
INTRODUCTION Thiazolidinediones (TZDs), represented by pioglitazone and rosiglitazone, are a class of cost-effective oral antidiabetic agents posing a marginal hypoglycaemia risk. Nevertheless, observations of heart failure have hindered the clinical use of both therapies. OBJECTIVE Since the mechanism of TZD-induced heart failure remains largely uncharacterised, this study aimed to explore the as-yet-unidentified mechanisms underpinning TZD cardiotoxicity using a toxicometabolomics approach. METHODS The present investigation included an untargeted liquid chromatography-mass spectrometry-based toxicometabolomics pipeline, followed by multivariate statistics and pathway analyses to elucidate the mechanism(s)of TZD-induced cardiotoxicity using AC16 human cardiomyocytes as a model, and to identify the prognostic features associated with such effects. RESULTS Acute administration of either TZD agent resulted in a significant modulation in carnitine content, reflecting potential disruption of the mitochondrial carnitine shuttle. Furthermore, perturbations were noted in purine metabolism and amino acid fingerprints, strongly conveying aberrations in cardiac energetics associated with TZD usage. Analysis of our findings also highlighted alterations in polyamine (spermine and spermidine) and amino acid (L-tyrosine and valine) metabolism, known modulators of cardiac hypertrophy, suggesting a potential link to TZD cardiotoxicity that necessitates further research. In addition, this comprehensive study identified two groupings - (i) valine and creatine, and (ii) L-tryptophan and L-methionine - that were significantly enriched in the above-mentioned mechanisms, emerging as potential fingerprint biomarkers for pioglitazone and rosiglitazone cardiotoxicity, respectively. CONCLUSION These findings demonstrate the utility of toxicometabolomics in elaborating on mechanisms of drug toxicity and identifying potential biomarkers, thus encouraging its application in the toxicological sciences. (245 words).
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Affiliation(s)
- Abdullah Al Sultan
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, 161 Cathedral Street, Glasgow, G4 0RE, UK
- Faculty of Pharmacy, Kuwait University, Safat, 13110, Kuwait
| | - Zahra Rattray
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, 161 Cathedral Street, Glasgow, G4 0RE, UK
| | - Nicholas J W Rattray
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, 161 Cathedral Street, Glasgow, G4 0RE, UK.
- Strathclyde Centre for Molecular Bioscience, University of Strathclyde, Glasgow, G4 0RE, UK.
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Lynch C, Sakamuru S, Ooka M, Huang R, Klumpp-Thomas C, Shinn P, Gerhold D, Rossoshek A, Michael S, Casey W, Santillo MF, Fitzpatrick S, Thomas RS, Simeonov A, Xia M. High-Throughput Screening to Advance In Vitro Toxicology: Accomplishments, Challenges, and Future Directions. Annu Rev Pharmacol Toxicol 2024; 64:191-209. [PMID: 37506331 PMCID: PMC10822017 DOI: 10.1146/annurev-pharmtox-112122-104310] [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: 07/30/2023]
Abstract
Traditionally, chemical toxicity is determined by in vivo animal studies, which are low throughput, expensive, and sometimes fail to predict compound toxicity in humans. Due to the increasing number of chemicals in use and the high rate of drug candidate failure due to toxicity, it is imperative to develop in vitro, high-throughput screening methods to determine toxicity. The Tox21 program, a unique research consortium of federal public health agencies, was established to address and identify toxicity concerns in a high-throughput, concentration-responsive manner using a battery of in vitro assays. In this article, we review the advancements in high-throughput robotic screening methodology and informatics processes to enable the generation of toxicological data, and their impact on the field; further, we discuss the future of assessing environmental toxicity utilizing efficient and scalable methods that better represent the corresponding biological and toxicodynamic processes in humans.
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Affiliation(s)
- Caitlin Lynch
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland, USA; ,
| | - Srilatha Sakamuru
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland, USA; ,
| | - Masato Ooka
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland, USA; ,
| | - Ruili Huang
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland, USA; ,
| | - Carleen Klumpp-Thomas
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland, USA; ,
| | - Paul Shinn
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland, USA; ,
| | - David Gerhold
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland, USA; ,
| | - Anna Rossoshek
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland, USA; ,
| | - Sam Michael
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland, USA; ,
| | - Warren Casey
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina, USA
| | - Michael F Santillo
- Division of Toxicology, Office of Applied Research and Safety Assessment, Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, Laurel, Maryland, USA
| | - Suzanne Fitzpatrick
- Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, College Park, Maryland, USA
| | - Russell S Thomas
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Anton Simeonov
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland, USA; ,
| | - Menghang Xia
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland, USA; ,
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Liu J, Lei X, Zhang Y, Pan Y. The prediction of molecular toxicity based on BiGRU and GraphSAGE. Comput Biol Med 2023; 153:106524. [PMID: 36623439 DOI: 10.1016/j.compbiomed.2022.106524] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 12/10/2022] [Accepted: 12/31/2022] [Indexed: 01/04/2023]
Abstract
The prediction of molecules toxicity properties plays an crucial role in the realm of the drug discovery, since it can swiftly screen out the expected drug moleculars. The conventional method for predicting toxicity is to use some in vivo or in vitro biological experiments in the laboratory, which can easily pose a threat significant time and financial waste and even ethical issues. Therefore, using computational approaches to predict molecular toxicity has become a common strategy in modern drug discovery. In this article, we propose a novel model named MTBG, which primarily makes use of both SMILES (Simplified molecular input line entry system) strings and graph structures of molecules to extract drug molecular feature in the field of drug molecular toxicity prediction. To verify the performance of the MTBG model, we opt the Tox21 dataset and several widely used baseline models. Experimental results demonstrate that our model can perform better than these baseline models.
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Affiliation(s)
- Jianping Liu
- School of Computer Science, Shaanxi Normal University, Xi'an, 710119, China
| | - Xiujuan Lei
- School of Computer Science, Shaanxi Normal University, Xi'an, 710119, China.
| | - Yuchen Zhang
- School of Computer Science, Shaanxi Normal University, Xi'an, 710119, China
| | - Yi Pan
- Faculty of Computer Science and Control Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
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Abstract
Mitochondrial function, a key indicator of cell health, can be assessed through monitoring changes in mitochondrial membrane potential (MMP). Cationic fluorescent dyes are commonly used tools to assess MMP. We used a water-soluble mitochondrial membrane potential indicator (m-MPI) to detect changes in MMP in various types of cells, such as HepG2, HepaRG, and AC16 cells. A homogenous cell-based MMP assay has been optimized and performed in a 1536-well plate format, which can be used to screen several compound libraries for mitochondrial toxicity by evaluating the effects of chemical compounds on MMP.
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Dalhat MH, Mohammed MRS, Ahmad A, Khan MI, Choudhry H. Remodelin, a N-acetyltransferase 10 (NAT10) inhibitor, alters mitochondrial lipid metabolism in cancer cells. J Cell Biochem 2021; 122:1936-1945. [PMID: 34605570 DOI: 10.1002/jcb.30155] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 08/30/2021] [Accepted: 09/14/2021] [Indexed: 11/09/2022]
Abstract
Remodelin is a small molecule inhibitor of N-acetyltransferase 10 (NAT10), reported to reverse the effect of cancer conditions such as epithelial to mesenchymal transition, hypoxia, and drug resistance. We analysed RNA seq data of siNAT10 and found many metabolic pathways were altered, this made us perform unbiased metabolic analysis. Here we performed untargeted metabolomics in Remodelin treated cancer cells using high-performance liquid chromatography-tandem mass spectrometry. Statistical analysis revealed a total number of 138 of which 52 metabolites were significantly modified in Remodelin treated cells. Among the most significantly altered metabolites, we identified metabolites related with mitochondrial fatty acid elongation (MFAE) and mitochondrial beta-oxidation such as lauroyl-CoA, cholesterol, triglycerides, (S)-3-hydroxyhexadecanoyl-CoA, and NAD+ . Furthermore, assessment showed alteration in expression of Enoyl-CoA hydratase, short chain 1, mitochondrial (ECHS1), and Mitochondrial trans-2-enoyl-CoA reductase (MECR) genes, associated with MFAE pathway. We also found statistically significant decrease in total cholesterol and triglycerides in Remodelin treated cancer cells. Overall, our results showed that Remodelin alters mitochondrial fatty acid metabolism and lipid accumulation in cancer cells. Finally, we validated these results in NAT10 knockdown cancer cells and found that NAT10 reduction results in alteration in gene expression associated with mitochondrial fatty acid metabolism, clearly suggesting the possible role of NAT10 in maintaining mitochondrial fatty acid metabolism.
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Affiliation(s)
- Mahmood Hassan Dalhat
- Department of Biochemistry, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.,Centre for Artificial Intelligence in Precision Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.,Cancer and Mutagenesis Research Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Mohammed Razeeth Shait Mohammed
- Department of Biochemistry, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.,Centre for Artificial Intelligence in Precision Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.,Cancer and Mutagenesis Research Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Abrar Ahmad
- Department of Biochemistry, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.,Centre for Artificial Intelligence in Precision Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.,Cancer and Mutagenesis Research Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Mohammad Imran Khan
- Department of Biochemistry, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.,Centre for Artificial Intelligence in Precision Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.,Cancer and Mutagenesis Research Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Hani Choudhry
- Department of Biochemistry, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.,Centre for Artificial Intelligence in Precision Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.,Cancer and Mutagenesis Research Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia
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