A Mutation in Mouse MT-ATP6 Gene Induces Respiration Defects and Opposed Effects on the Cell Tumorigenic Phenotype

Moreno‐Loshuertos, Raquel; Movilla, Nieves; Marco-Brualla, Joaquín; Soler-Agesta, Ruth; Ferreira, Patricia; Enrı́quez, José Antonio; Fernández‐Silva, Patricio

doi:10.3390/ijms24021300

Cited by 6 publications

(6 citation statements)

References 83 publications

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“…Interestingly, MT-ATP6 gene was selected by scELMo as a potential target, which implied that cells under different states might have different speeds for cell death [64] or neurodegeneration [65]. These results suggest the potential benefit of exploring the correlation between cellular function and clinical manifestations of this disease.…”

Section: Resultsmentioning

confidence: 99%

scELMo: Embeddings from Language Models are Good Learners for Single-cell Data Analysis

Zhao,

Liu,

Chen

et al. 2024

Preprint

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Various Foundation Models (FMs) have been built based on the pre-training and fine-tuning framework to analyze single-cell data with different degrees of success. In this manuscript, we propose a method named scELMo (Single-cell Embedding from Language Models), to analyze single cell data that utilizes Large Language Models (LLMs) as a generator for both the description of metadata information and the embeddings for such descriptions. We combine the embeddings from LLMs with the raw data under the zero-shot learning framework to further extend its function by using the fine-tuning framework to handle different tasks. We demonstrate that scELMo is capable of cell clustering, batch effect correction, and cell-type annotation without training a new model. Moreover, the fine-tuning framework of scELMo can help with more challenging tasks including in-silico treatment analysis or modeling perturbation. scELMo has a lighter structure and lower requirement for resources. Moreover, our method is comparable to recent large-scale FMs (such as scGPT, [1] Geneformer [2]) based on our evaluations, suggesting a promising path for developing domain-specific FMs.

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Section: Resultsmentioning

confidence: 99%

scELMo: Embeddings from Language Models are Good Learners for Single-cell Data Analysis

Zhao,

Liu,

Chen

et al. 2024

Preprint

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show abstract

“…Interestingly, MT-ATP6 gene was selected by scELMo as a potential target, which implied that cells under different states might have different speeds for cell death [56] or neurodegeneration [57]. These results suggest the potential benefit of exploring the correlation between cellular function and clinical manifestations of this disease.…”

Section: Resultsmentioning

confidence: 99%

“…Based on this figure, we found that scELMo identified six novel genes as potential therapeutic targets for cells under the Ascending only state, two novel genes as potential therapeutic targets for cells under the Ascending to descending state, and three genes as potential therapeutic targets for cells under the Ascending w/ root state. Interestingly, MT-ATP6 gene was selected by scELMo as a potential target, which implied that cells under different states might have different speeds for cell death [51] or neurodegeneration [52]. Such results can inspire researchers to explore the correlation between cellular function and clinical manifestations of this disease.…”

Section: Resultsmentioning

confidence: 99%

scELMo: Embeddings from Language Models are Good Learners for Single-cell Data Analysis

Liu,

Chen,

Zheng

et al. 2023

Preprint

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Different from a recent approach to building the Foundation Models (FMs) for analyzing single-cell data based on the pre-training and fine-tuning framework, in this manuscript, we extend the concept from GenePT [1] and propose a novel approach to leverage the advantages from Large Language Models (LLMs) to formalize a foundation model for single-cell data analysis, known as scELMo. We utilize LLMs like GPT 3.5 as a generator for both the description of metadata information and the embeddings for such description. Moreover, we also combine the embeddings from LLMs with the raw data under both zero-shot learning framework and fine-tuning framework to handle different tasks. We proved that scELMo is capable of cell clustering, batch effect correction, and cell-type annotation without training a new model. Moreover, the fine-tuning framework of scELMo can help with more challenging tasks including in-silico treatment analysis or modeling the perturbation information. scELMo has a lighter structure and lower requirement for resources but impressive performance, which poses a promising path for developing domain-specific FMs.

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“…Furthermore, the CMP3013-treated group showed decreased levels of NGAL and cytochrome C, along with an increase in SOD-1 expression (Figures c,d and S14). Additionally, CMP3013 administration in IRI mice resulted in upregulated expression of NQO-1 and SOD-1 mRNA, which are essential mitochondrial antioxidant enzymes. , It also induced elevated transcription of IL-10, an antioxidant and anti-inflammatory cytokine, and ATP6 mRNA, associated with the function of the mitochondrial electron transport complex channel 5 (Figure e). To confirm the ameliorative effects of CMP3013 on impaired kidneys, we reversed the order of treatment for CMP3013 and IRI.…”

Section: Results and Discussionmentioning

confidence: 99%

Cyclohexylalanine-Containing α-Helical Amphipathic Peptide Targets Cardiolipin, Rescuing Mitochondrial Dysfunction in Kidney Injury

Shin,

Hyun,

Kim

et al. 2023

J. Med. Chem.

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Mitochondrial dysfunction is linked to degenerative diseases, resulting from cardiolipin (CL)-induced disruption of cristae structure in the inner mitochondrial membrane (IMM); therefore, preserving cristae and preventing CL remodeling offer effective strategies to maintain mitochondrial function. To identify reactive oxygen species (ROS)-blocking agents against mitochondrial dysfunction, a library of cyclohexylamine-containing cell-penetrating αhelical amphipathic "bundle" peptides were screened. Among these, CMP3013 is selectively bound to abnormal mitochondria, preserving the cristae structure impaired by mitochondriadamaging agents. With a stronger affinity for CL compared with other IMM lipid components, CMP3013 exhibited high selectivity. Consequently, it protected cristae, reduced ROS production, and enhanced adenosine triphosphate (ATP) generation. In mouse models of acute kidney injury, a 1 mg/kg dose of CMP3013 demonstrated remarkable efficacy, highlighting its potential as a therapeutic agent for mitochondrial dysfunction-related disorders. Overall, CMP3013 represents a promising agent for mitigating mitochondrial dysfunction and associated diseases.

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A Mutation in Mouse MT-ATP6 Gene Induces Respiration Defects and Opposed Effects on the Cell Tumorigenic Phenotype

Cited by 6 publications

References 83 publications

scELMo: Embeddings from Language Models are Good Learners for Single-cell Data Analysis

scELMo: Embeddings from Language Models are Good Learners for Single-cell Data Analysis

scELMo: Embeddings from Language Models are Good Learners for Single-cell Data Analysis

Cyclohexylalanine-Containing α-Helical Amphipathic Peptide Targets Cardiolipin, Rescuing Mitochondrial Dysfunction in Kidney Injury

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