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Li S, Xu Y, Hu X, Chen H, Xi X, Long F, Rong Y, Wang J, Yuan C, Liang C, Wang F. Crosstalk of non-apoptotic RCD panel in hepatocellular carcinoma reveals the prognostic and therapeutic optimization. iScience 2024; 27:109901. [PMID: 38799554 PMCID: PMC11126946 DOI: 10.1016/j.isci.2024.109901] [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: 11/15/2023] [Revised: 03/12/2024] [Accepted: 05/01/2024] [Indexed: 05/29/2024] Open
Abstract
Non-apoptotic regulated cell death (RCD) of tumor cells profoundly affects tumor progression and plays critical roles in determining response to immune checkpoint inhibitors (ICIs). Prognosis-distinctive HCC subtypes were identified by consensus cluster analysis based on the expressions of 507 non-apoptotic RCD genes obtained from databases and literature. Meanwhile, a set of bioinformatic tools was integrated to analyze the differences of the tumor immune microenvironment infiltration, genetic mutation, copy number variation, and epigenetics alternations within two subtypes. Finally, a non-apoptotic RCDRS signature was constructed and its reliability was evaluated in HCC patients' tissues. The high-RCDRS HCC subgroup showed a significantly lower overall survival and less sensitivity to ICIs compared to low-RCDRS subgroup, but higher sensitivity to cisplatin, paclitaxel, and sorafenib. Overall, we established an RCDRS panel consisting of four non-apoptotic RCD genes, which might be a promising predictor for evaluating HCC prognosis, guiding therapeutic decision-making, and ultimately improving patient outcomes.
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Affiliation(s)
- Shuo Li
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
- Center for Single-Cell Omics and Tumor Liquid Biopsy, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
| | - Yaqi Xu
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
- Center for Single-Cell Omics and Tumor Liquid Biopsy, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
| | - Xin Hu
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
- Center for Single-Cell Omics and Tumor Liquid Biopsy, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
| | - Hao Chen
- Department of Pathology, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
| | - Xiaodan Xi
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
- Center for Single-Cell Omics and Tumor Liquid Biopsy, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
| | - Fei Long
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
- Center for Single-Cell Omics and Tumor Liquid Biopsy, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
| | - Yuan Rong
- Center for Single-Cell Omics and Tumor Liquid Biopsy, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
- Forensic Center of Justice, Zhongnan Hospital of Wuhan University, Wuhan China
| | - Jun Wang
- Department of Laboratory Medicine, Wuhan Children’s Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430016, China
| | - Chunhui Yuan
- Center for Single-Cell Omics and Tumor Liquid Biopsy, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
- Department of Laboratory Medicine, Wuhan Children’s Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430016, China
| | - Chen Liang
- Department of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, No. 169 Donghu Road, Wuchang District, Wuhan 430071, China
| | - Fubing Wang
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
- Center for Single-Cell Omics and Tumor Liquid Biopsy, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
- Wuhan Research Center for Infectious Diseases and Cancer, Chinese Academy of Medical Sciences, Wuhan, China
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He Y, Qi W, Xie X, Jiang H. Identification and validation of a novel predictive signature based on hepatocyte-specific genes in hepatocellular carcinoma by integrated analysis of single-cell and bulk RNA sequencing. BMC Med Genomics 2024; 17:103. [PMID: 38654290 DOI: 10.1186/s12920-024-01871-1] [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: 09/12/2023] [Accepted: 04/09/2024] [Indexed: 04/25/2024] Open
Abstract
BACKGROUND Hepatocellular carcinoma represents a significant global burden in terms of cancer-related mortality, posing a substantial risk to human health. Despite the availability of various treatment modalities, the overall survival rates for patients with hepatocellular carcinoma remain suboptimal. The objective of this study was to explore the potential of novel biomarkers and to establish a novel predictive signature utilizing multiple transcriptome profiles. METHODS The GSE115469 and CNP0000650 cohorts were utilized for single cell analysis and gene identification. The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets were utilized in the development and evaluation of a predictive signature. The expressions of hepatocyte-specific genes were further validated using the GSE135631 cohort. Furthermore, immune infiltration results, immunotherapy response prediction, somatic mutation frequency, tumor mutation burden, and anticancer drug sensitivity were analyzed based on various risk scores. Subsequently, functional enrichment analysis was performed on the differential genes identified in the risk model. Moreover, we investigated the expression of particular genes in chronic liver diseases utilizing datasets GSE135251 and GSE142530. RESULTS Our findings revealed hepatocyte-specific genes (ADH4, LCAT) with notable alterations during cell maturation and differentiation, leading to the development of a novel predictive signature. The analysis demonstrated the efficacy of the model in predicting outcomes, as evidenced by higher risk scores and poorer prognoses in the high-risk group. Additionally, a nomogram was devised to forecast the survival rates of patients at 1, 3, and 5 years. Our study demonstrated that the predictive model may play a role in modulating the immune microenvironment and impacting the anti-tumor immune response in hepatocellular carcinoma. The high-risk group exhibited a higher frequency of mutations and was more likely to benefit from immunotherapy as a treatment option. Additionally, we confirmed that the downregulation of hepatocyte-specific genes may indicate the progression of hepatocellular carcinoma and aid in the early diagnosis of the disease. CONCLUSION Our research findings indicate that ADH4 and LCAT are genes that undergo significant changes during the differentiation of hepatocytes into cancer cells. Additionally, we have created a unique predictive signature based on genes specific to hepatocytes.
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Affiliation(s)
- Yujian He
- Department of Gastroenterology, The Second Hospital of Hebei Medical University, Hebei Key Laboratory of Gastroenterology, Hebei Institute of Gastroenterology, Hebei Clinical Research Center for Digestive Diseases, Shijiazhuang, Hebei, China
| | - Wei Qi
- Department of Gastroenterology, The Second Hospital of Hebei Medical University, Hebei Key Laboratory of Gastroenterology, Hebei Institute of Gastroenterology, Hebei Clinical Research Center for Digestive Diseases, Shijiazhuang, Hebei, China
| | - Xiaoli Xie
- Department of Gastroenterology, The Second Hospital of Hebei Medical University, Hebei Key Laboratory of Gastroenterology, Hebei Institute of Gastroenterology, Hebei Clinical Research Center for Digestive Diseases, Shijiazhuang, Hebei, China
| | - Huiqing Jiang
- Department of Gastroenterology, The Second Hospital of Hebei Medical University, Hebei Key Laboratory of Gastroenterology, Hebei Institute of Gastroenterology, Hebei Clinical Research Center for Digestive Diseases, Shijiazhuang, Hebei, China.
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Lu Y, Wen W, Huang Q, Duan N, Li M, Zhang K, Li Z, Sun L, Wang Q. Development and experimental validation of an energy metabolism-related gene signature for diagnosing of osteoporosis. Sci Rep 2024; 14:8153. [PMID: 38589566 PMCID: PMC11001872 DOI: 10.1038/s41598-024-59062-y] [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: 09/23/2023] [Accepted: 04/06/2024] [Indexed: 04/10/2024] Open
Abstract
Osteoporosis is usually caused by excessive bone resorption and energy metabolism plays a critical role in the development of osteoporosis. However, little is known about the role of energy metabolism-related genes in osteoporosis. This study aimed to explore the important energy metabolism-related genes involved in the development of osteoporosis and develop a diagnosis signature for osteoporosis. The GSE56814, GSE62402, and GSE7158 datasets were downloaded from the NCBI Gene Expression Omnibus. The intersection of differentially expressed genes between high and low levels of body mineral density (BMD) and genes related to energy metabolism were screened as differentially expressed energy metabolism genes (DE-EMGs). Subsequently, a DE-EMG-based diagnostic model was constructed and differential expression of genes in the model was validated by RT-qPCR. Furthermore, a receiver operating characteristic curve and nomogram model were constructed to evaluate the predictive ability of the diagnostic model. Finally, the immune cell types in the merged samples and networks associated with the selected optimal DE-EMGs were constructed. A total of 72 overlapped genes were selected as DE-EMGs, and a five DE-EMG based diagnostic model consisting B4GALT4, ADH4, ACAD11, B4GALT2, and PPP1R3C was established. The areas under the curve of the five genes in the merged training dataset and B4GALT2 in the validation dataset were 0.784 and 0.790, respectively. Moreover, good prognostic prediction ability was observed using the nomogram model (C index = 0.9201; P = 5.507e-14). Significant differences were observed in five immune cell types between the high- and low-BMD groups. These included central memory, effector memory, and activated CD8 T cells, as well as regulatory T cells and activated B cells. A network related to DE-EMGs was constructed, including hsa-miR-23b-3p, DANCR, 17 small-molecule drugs, and two Kyoto Encyclopedia of Genes and Genomes pathways, including metabolic pathways and pyruvate metabolism. Our findings highlighted the important roles of DE-EMGs in the development of osteoporosis. Furthermore, the DANCR/hsa-miR-23b-3p/B4GALT4 axis might provide novel molecular insights into the process of osteoporosis development.
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Affiliation(s)
- Yao Lu
- Department of Orthopaedics, Honghui Hospital, Xi'an Jiaotong University, 555 Youyi East Road, Xi'an, 710054, Shaan'xi Province, China
| | - Wen Wen
- Department of Orthopedics, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Qiang Huang
- Department of Orthopaedics, Honghui Hospital, Xi'an Jiaotong University, 555 Youyi East Road, Xi'an, 710054, Shaan'xi Province, China
| | - Ning Duan
- Department of Orthopaedics, Honghui Hospital, Xi'an Jiaotong University, 555 Youyi East Road, Xi'an, 710054, Shaan'xi Province, China
| | - Ming Li
- Department of Orthopaedics, Honghui Hospital, Xi'an Jiaotong University, 555 Youyi East Road, Xi'an, 710054, Shaan'xi Province, China
| | - Kun Zhang
- Department of Orthopaedics, Honghui Hospital, Xi'an Jiaotong University, 555 Youyi East Road, Xi'an, 710054, Shaan'xi Province, China
| | - Zhong Li
- Department of Orthopaedics, Honghui Hospital, Xi'an Jiaotong University, 555 Youyi East Road, Xi'an, 710054, Shaan'xi Province, China
| | - Liang Sun
- Department of Orthopaedics, Honghui Hospital, Xi'an Jiaotong University, 555 Youyi East Road, Xi'an, 710054, Shaan'xi Province, China.
| | - Qian Wang
- Department of Orthopaedics, Honghui Hospital, Xi'an Jiaotong University, 555 Youyi East Road, Xi'an, 710054, Shaan'xi Province, China.
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Guo Y, Yang J, Gao H, Tian X, Zhang X, Kan Q. Development and Verification of a Combined Immune- and Metabolism-Related Prognostic Signature for Hepatocellular Carcinoma. Front Immunol 2022; 13:927635. [PMID: 35874741 PMCID: PMC9304746 DOI: 10.3389/fimmu.2022.927635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Accepted: 06/10/2022] [Indexed: 12/09/2022] Open
Abstract
Immune escape and metabolic reprogramming are becoming important characteristics of tumor biology, which play critical roles in tumor initiation and progression. However, the integrative analysis of immune and metabolic characteristics for the tumor microenvironment in hepatocellular carcinoma (HCC) remains unclear. Herein, by univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses, a prognostic signature associated with tumor microenvironment was established based on five immune- and metabolism-related genes (IMRGs), which was fully verified and evaluated in both internal and external cohorts. The C-index was superior to previously published HCC signatures, indicating the robustness and reliability of IMRGs prognostic signature. A nomogram was built based on IMRGs prognostic signature and various clinical parameters, such as age and T stage. The AUCs of nomogram at 1-, 3-, and 5-year (AUC = 0.829, 0.749, 0.749) were slightly better than that of IMRGs signature (AUC = 0.809, 0.734, 0.711). The relationship of risk score (RS) with immune checkpoint expressions, immunophenoscore (IPS), as well as microsatellite instability (MSI) together accurately predicted the treatment efficacy. Collectively, the IMRGs signature might have the potential to better predict prognostic risk, evaluate immunotherapy efficacy, and help personalize immunotherapy for HCC patients.
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Affiliation(s)
- Yuanyuan Guo
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University, Zhengzhou, China
| | - Jing Yang
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University, Zhengzhou, China
| | - Hua Gao
- Department of Radiotherapy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xin Tian
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University, Zhengzhou, China
- *Correspondence: Xin Tian, ; Xiaojian Zhang, ; Quancheng Kan,
| | - Xiaojian Zhang
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University, Zhengzhou, China
- *Correspondence: Xin Tian, ; Xiaojian Zhang, ; Quancheng Kan,
| | - Quancheng Kan
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University, Zhengzhou, China
- *Correspondence: Xin Tian, ; Xiaojian Zhang, ; Quancheng Kan,
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Xu B, Peng Z, An Y, Yan G, Yao X, Guan L, Sun M. Identification of Energy Metabolism-Related Gene Signatures From scRNA-Seq Data to Predict the Prognosis of Liver Cancer Patients. Front Cell Dev Biol 2022; 10:858336. [PMID: 35602603 PMCID: PMC9114438 DOI: 10.3389/fcell.2022.858336] [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: 01/19/2022] [Accepted: 04/18/2022] [Indexed: 11/13/2022] Open
Abstract
The increasingly common usage of single-cell sequencing in cancer research enables analysis of tumor development mechanisms from a wider range of perspectives. Metabolic disorders are closely associated with liver cancer development. In recent years, liver cancer has been evaluated from different perspectives and classified into different subtypes to improve targeted treatment strategies. Here, we performed an analysis of liver cancer from the perspective of energy metabolism based on single-cell sequencing data. Single-cell and bulk sequencing data of liver cancer patients were obtained from GEO and TCGA/ICGC databases, respectively. Using the Seurat R package and protocols such as consensus clustering analysis, genes associated with energy metabolism in liver cancer were identified and validated. An energy metabolism-related score (EM score) was established based on five identified genes. Finally, the sensitivity of patients in different scoring groups to different chemotherapeutic agents and immune checkpoint inhibitors was analyzed. Tumor cells from liver cancer patients were found to divide into nine clusters, with cluster 4 having the highest energy metabolism score. Based on the marker genes of this cluster and TCGA database data, the five most stable key genes (ADH4, AKR1B10, CEBPZOS, ENO1, and FOXN2) were identified as energy metabolism-related genes in liver cancer. In addition, drug sensitivity analysis showed that patients in the low EM score group were more sensitive to immune checkpoint inhibitors and chemotherapeutic agents AICAR, metformin, and methotrexate.
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Affiliation(s)
- Boyang Xu
- Department of Gastroenterology, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Ziqi Peng
- Department of Breast Surgery, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Yue An
- Department of Endoscopy, The First Hospital of China Medical University, Shenyang, China
| | - Guanyu Yan
- Department of Gastroenterology, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Xue Yao
- Department of Surgical Oncology, The First Hospital of China Medical University, Shenyang, China
| | - Lin Guan
- Department of Gastroenterology, The First Affiliated Hospital of China Medical University, Shenyang, China
- *Correspondence: Lin Guan, ; Mingjun Sun,
| | - Mingjun Sun
- Department of Gastroenterology, The First Affiliated Hospital of China Medical University, Shenyang, China
- *Correspondence: Lin Guan, ; Mingjun Sun,
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de Lima LA, Ingelman H, Brahmbhatt K, Reinmets K, Barry C, Harris A, Marcellin E, Köpke M, Valgepea K. Faster Growth Enhances Low Carbon Fuel and Chemical Production Through Gas Fermentation. Front Bioeng Biotechnol 2022; 10:879578. [PMID: 35497340 PMCID: PMC9039284 DOI: 10.3389/fbioe.2022.879578] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Accepted: 03/14/2022] [Indexed: 12/13/2022] Open
Abstract
Gas fermentation offers both fossil carbon-free sustainable production of fuels and chemicals and recycling of gaseous and solid waste using gas-fermenting microbes. Bioprocess development, systems-level analysis of biocatalyst metabolism, and engineering of cell factories are advancing the widespread deployment of the commercialised technology. Acetogens are particularly attractive biocatalysts but effects of the key physiological parameter–specific growth rate (μ)—on acetogen metabolism and the gas fermentation bioprocess have not been established yet. Here, we investigate the μ-dependent bioprocess performance of the model-acetogen Clostridium autoethanogenum in CO and syngas (CO + CO2+H2) grown chemostat cultures and assess systems-level metabolic responses using gas analysis, metabolomics, transcriptomics, and metabolic modelling. We were able to obtain steady-states up to μ ∼2.8 day−1 (∼0.12 h−1) and show that faster growth supports both higher yields and productivities for reduced by-products ethanol and 2,3-butanediol. Transcriptomics data revealed differential expression of 1,337 genes with increasing μ and suggest that C. autoethanogenum uses transcriptional regulation to a large extent for facilitating faster growth. Metabolic modelling showed significantly increased fluxes for faster growing cells that were, however, not accompanied by gene expression changes in key catabolic pathways for CO and H2 metabolism. Cells thus seem to maintain sufficient “baseline” gene expression to rapidly respond to CO and H2 availability without delays to kick-start metabolism. Our work advances understanding of transcriptional regulation in acetogens and shows that faster growth of the biocatalyst improves the gas fermentation bioprocess.
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Affiliation(s)
- Lorena Azevedo de Lima
- ERA Chair in Gas Fermentation Technologies, Institute of Technology, University of Tartu, Tartu, Estonia
| | - Henri Ingelman
- ERA Chair in Gas Fermentation Technologies, Institute of Technology, University of Tartu, Tartu, Estonia
| | - Kush Brahmbhatt
- ERA Chair in Gas Fermentation Technologies, Institute of Technology, University of Tartu, Tartu, Estonia
| | - Kristina Reinmets
- ERA Chair in Gas Fermentation Technologies, Institute of Technology, University of Tartu, Tartu, Estonia
| | - Craig Barry
- Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, St. Lucia, QLD, Australia
| | | | - Esteban Marcellin
- Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, St. Lucia, QLD, Australia
| | | | - Kaspar Valgepea
- ERA Chair in Gas Fermentation Technologies, Institute of Technology, University of Tartu, Tartu, Estonia
- *Correspondence: Kaspar Valgepea,
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Moon J, Müller V. Physiology and genetics of ethanologenesis in the acetogenic bacterium Acetobacterium woodii. Environ Microbiol 2021; 23:6953-6964. [PMID: 34448343 DOI: 10.1111/1462-2920.15739] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 08/22/2021] [Indexed: 11/28/2022]
Abstract
The acetogenic model bacterium Acetobacterium woodii is well-known to produce acetate by homoacetogenesis from sugars, but under certain conditions minor amounts of ethanol are produced in addition. Here, we have aimed to identify physiological conditions that increase electron and carbon flow towards ethanol production. Ethanol was only produced from fructose but not from H2 + CO2 , formate, pyruvate, lactate or alanine. In the absence of Na+ , the Wood-Ljungdahl pathway (WLP) of acetate formation is not functional. Therefore, the ethanol yield increased to 0.42 mol/mol (ethanol/fructose) with an ethanol/acetate ratio of 0.28 mol/mol. The presence of bicarbonate/CO2 stimulated electron and carbon flow through the WLP and led to less ethanol produced. Of the 11 potential alcohol dehydrogenase genes, the most upregulated during ethanologenesis was adh4. A deletion of adh4 led to an increase in ethanol production by 100% to a yield of 0.79 mol/mol (ethanol/fructose); this correlated with an increase in transcript abundance of adh6. In sum, our studies revealed low Na+ and bicarbonate/CO2 as factors that trigger ethanol formation and that a deletion of adh4 drastically increased ethanol formation in A. woodii.
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Affiliation(s)
- Jimyung Moon
- Molecular Microbiology & Bioenergetics, Institute of Molecular Biosciences, Johann Wolfgang Goethe University, Max-von-Laue Str. 9, Frankfurt, D-60438, Germany
| | - Volker Müller
- Molecular Microbiology & Bioenergetics, Institute of Molecular Biosciences, Johann Wolfgang Goethe University, Max-von-Laue Str. 9, Frankfurt, D-60438, Germany
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