Transcriptome Analysis of Komagataeibacter europaeus CGMCC 20445 Responses to Different Acidity Levels During Acetic Acid Fermentation

In the industrial production of high-acidity vinegar, the initial ethanol and acetic acid concentrations are limiting factors that will affect acetic acid fermentation. In this study, Komagataeibacter europaeus CGMCC 20445 was used for acetic acid shake flask fermentation at an initial ethanol concentration of 4.3% (v/v). We conducted transcriptome analysis of K. europaeus CGMCC 20445 samples under different acidity conditions to elucidate the changes in differentially expressed genes throughout the fermentation process. We also analyzed the expression of genes associated with acid-resistance mechanisms. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis showed that the differentially expressed genes were enriched in ribosomes, citrate cycle, butanoate metabolism, oxidative phosphorylation, pentose phosphate, and the fatty acid biosynthetic pathways. In addition, this study found that K. europaeus CGMCC 20445 regulates the gene expression levels of cell envelope proteins and stress-responsive proteins to adapt to the gradual increase in acidity during acetic acid fermentation. This study improved the understanding of the acid resistance mechanism of K. europaeus and provided relevant reference information for the further genetic engineering of this bacterium.

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Acetic Acid Fermentation ofAcetobacter pasteurianus: Relationship between Acetic Acid Resistance and Pellicle Polysaccharide Formation

Bioscience Biotechnology and Biochemistry ◽

10.1271/bbb.100183 ◽

2010 ◽

Vol 74 (8) ◽

pp. 1591-1597 ◽

Cited By ~ 46

Author(s):

Watchara KANCHANARACH ◽

Gunjana THEERAGOOL ◽

Taketo INOUE ◽

Toshiharu YAKUSHI ◽

Osao ADACHI ◽

...

Keyword(s):

Acetic Acid ◽

Acid Resistance ◽

Acid Fermentation ◽

Acetic Acid Fermentation ◽

Acetic Acid Resistance

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Physiology of Acetobacter and Komagataeibacter spp.: Acetic Acid Resistance Mechanism in Acetic Acid Fermentation

Acetic Acid Bacteria ◽

10.1007/978-4-431-55933-7_10 ◽

2016 ◽

pp. 223-234

Author(s):

Shigeru Nakano ◽

Hiroaki Ebisuya

Keyword(s):

Acetic Acid ◽

Resistance Mechanism ◽

Acid Resistance ◽

Acid Fermentation ◽

Acetic Acid Fermentation ◽

Acetic Acid Resistance

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Optimization of the Acetic Acid Fermentation Condition for Preparation of Strawberry Vinegar

Journal of the Korean Society of Food Science and Nutrition ◽

10.3746/jkfn.2003.32.6.812 ◽

2003 ◽

Vol 32 (6) ◽

pp. 812-817 ◽

Cited By ~ 13

Keyword(s):

Acetic Acid ◽

Fermentation Condition ◽

Acid Fermentation ◽

Acetic Acid Fermentation

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Lipidomics profiling of goose granulosa cell model of stearoyl-CoA desaturase function identifies a pattern of lipid droplets associated with follicle development

Cell & Bioscience ◽

10.1186/s13578-021-00604-6 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Xin Yuan ◽

Shenqiang Hu ◽

Liang Li ◽

Chunchun Han ◽

Hehe Liu ◽

...

Keyword(s):

Differentially Expressed Genes ◽

Lipid Droplets ◽

Cell Model ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Follicle Development ◽

Microscopy Analysis ◽

Stearoyl Coa Desaturase ◽

Underlying Mechanisms

Abstract Background Despite their important functions and nearly ubiquitous presence in cells, an understanding of the biology of intracellular lipid droplets (LDs) in goose follicle development remains limited. An integrated study of lipidomic and transcriptomic analyses was performed in a cellular model of stearoyl-CoA desaturase (SCD) function, to determine the effects of intracellular LDs on follicle development in geese. Results Numerous internalized LDs, which were generally spherical in shape, were dispersed throughout the cytoplasm of granulosa cells (GCs), as determined using confocal microscopy analysis, with altered SCD expression affecting LD content. GC lipidomic profiling showed that the majority of the differentially abundant lipid classes were glycerophospholipids, including PA, PC, PE, PG, PI, and PS, and glycerolipids, including DG and TG, which enriched glycerophospholipid, sphingolipid, and glycerolipid metabolisms. Furthermore, transcriptomics identified differentially expressed genes (DEGs), some of which were assigned to lipid-related Gene Ontology slim terms. More DEGs were assigned in the SCD-knockdown group than in the SCD-overexpression group. Integration of the significant differentially expressed genes and lipids based on pathway enrichment analysis identified potentially targetable pathways related to glycerolipid/glycerophospholipid metabolism. Conclusions This study demonstrated the importance of lipids in understanding follicle development, thus providing a potential foundation to decipher the underlying mechanisms of lipid-mediated follicle development.

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Transcriptome analysis identifies differentially expressed genes in the progenies of a cross between two low phytic acid soybean mutants

Scientific Reports ◽

10.1038/s41598-021-88055-4 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Hangxia Jin ◽

Xiaomin Yu ◽

Qinghua Yang ◽

Xujun Fu ◽

Fengjie Yuan

Keyword(s):

Developmental Stage ◽

Phytic Acid ◽

Differentially Expressed Genes ◽

Transcriptome Analysis ◽

Defense Mechanisms ◽

Developmental Stages ◽

Sucrose Metabolism ◽

Differentially Expressed ◽

Sequencing Analysis ◽

Seed Developmental Stage

AbstractPhytic acid (PA) is a major antinutrient that cannot be digested by monogastric animals, but it can decrease the bioavailability of micronutrients (e.g., Zn and Fe). Lowering the PA content of crop seeds will lead to enhanced nutritional traits. Low-PA mutant crop lines carrying more than one mutated gene (lpa) have lower PA contents than mutants with a single lpa mutant gene. However, little is known about the link between PA pathway intermediates and downstream regulatory activities following the mutation of these genes in soybean. Consequently, we performed a comparative transcriptome analysis using an advanced generation recombinant inbred line with low PA levels [2mlpa (mips1/ipk1)] and a sibling line with homozygous non-mutant alleles and normal PA contents [2MWT (MIPS1/IPK1)]. An RNA sequencing analysis of five seed developmental stages revealed 7945 differentially expressed genes (DEGs) between the 2mlpa and 2MWT seeds. Moreover, 3316 DEGs were associated with 128 metabolic and signal transduction pathways and 4980 DEGs were annotated with 345 Gene Ontology terms related to biological processes. Genes associated with PA metabolism, photosynthesis, starch and sucrose metabolism, and defense mechanisms were among the DEGs in 2mlpa. Of these genes, 36 contributed to PA metabolism, including 22 genes possibly mediating the low-PA phenotype of 2mlpa. The expression of most of the genes associated with photosynthesis (81 of 117) was down-regulated in 2mlpa at the late seed developmental stage. In contrast, the expression of three genes involved in sucrose metabolism was up-regulated at the late seed developmental stage, which might explain the high sucrose content of 2mlpa soybeans. Furthermore, 604 genes related to defense mechanisms were differentially expressed between 2mlpa and 2MWT. In this study, we detected a low PA content as well as changes to multiple metabolites in the 2mlpa mutant. These results may help elucidate the regulation of metabolic events in 2mlpa. Many genes involved in PA metabolism may contribute to the substantial decrease in the PA content and the moderate accumulation of InsP3–InsP5 in the 2mlpa mutant. The other regulated genes related to photosynthesis, starch and sucrose metabolism, and defense mechanisms may provide additional insights into the nutritional and agronomic performance of 2mlpa seeds.

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AB0005 IDENTIFICATION OF KEY GENES AND PATHWAYS FOR PSORIASIS BASED ON GEO DATABASES BY BIOINFORMATICS ANALYSIS

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2021-eular.1773 ◽

2021 ◽

Vol 80 (Suppl 1) ◽

pp. 1037.2-1038

Author(s):

X. Sun ◽

S. X. Zhang ◽

S. Song ◽

T. Kong ◽

C. Zheng ◽

...

Keyword(s):

Gene Expression ◽

Signaling Pathways ◽

Differentially Expressed Genes ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Shanxi Province ◽

Receptor Interaction ◽

Term Therapy ◽

Pathway Enrichment Analysis ◽

Key Genes

Background:Psoriasis is an immune-mediated, genetic disease manifesting in the skin or joints or both, and also has a strong genetic predisposition and autoimmune pathogenic traits1. The hallmark of psoriasis is sustained inflammation that leads to uncontrolled keratinocyte proliferation and dysfunctional differentiation. And it’s also a chronic relapsing disease, which often necessitates a long-term therapy2.Objectives:To investigate the molecular mechanisms of psoriasis and find the potential gene targets for diagnosis and treating psoriasis.Methods:Total 334 gene expression data of patients with psoriasis research (GSE13355 GSE14905 and GSE30999) were obtained from the Gene Expression Omnibus database. After data preprocessing and screening of differentially expressed genes (DEGs) by R software. Online toll Metascape3 was used to analyze Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs. Interactions of proteins encoded by DEGs were discovered by Protein-protein interaction network (PPI) using STRING online software. Cytoscape software was utilized to visualize PPI and the degree of each DEGs was obtained by analyzing the topological structure of the PPI network.Results:A total of 611 DEGs were found to be differentially expressed in psoriasis. GO analysis revealed that up-regulated DEGs were mostly associated with defense and response to external stimulus while down-regulated DEGs were mostly associated with metabolism and synthesis of lipids. KEGG enrichment analysis suggested they were mainly enriched in IL-17 signaling, Toll-like receptor signaling and PPAR signaling pathways, Cytokine-cytokine receptor interaction and lipid metabolism. In addition, top 9 key genes (CXCL10, OASL, IFIT1, IFIT3, RSAD2, MX1, OAS1, IFI44 and OAS2) were identified through Cytoscape.Conclusion:DEGs of psoriasis may play an essential role in disease development and may be potential pathogeneses of psoriasis.References:[1]Boehncke WH, Schon MP. Psoriasis. Lancet 2015;386(9997):983-94. doi: 10.1016/S0140-6736(14)61909-7 [published Online First: 2015/05/31].[2]Zhang YJ, Sun YZ, Gao XH, et al. Integrated bioinformatic analysis of differentially expressed genes and signaling pathways in plaque psoriasis. Mol Med Rep 2019;20(1):225-35. doi: 10.3892/mmr.2019.10241 [published Online First: 2019/05/23].[3]Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523. doi: 10.1038/s41467-019-09234-6 [published Online First: 2019/04/05].Acknowledgements:This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).Disclosure of Interests:None declared

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Transcriptome Analysis of Differentially Expressed mRNA Related to Pigeon Muscle Development

Animals ◽

10.3390/ani11082311 ◽

2021 ◽

Vol 11 (8) ◽

pp. 2311

Author(s):

Hao Ding ◽

Yueyue Lin ◽

Tao Zhang ◽

Lan Chen ◽

Genxi Zhang ◽

...

Keyword(s):

Gene Expression ◽

Skeletal Muscle ◽

Differentially Expressed Genes ◽

Growth And Development ◽

Muscle Development ◽

Expression Patterns ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Growth Stages ◽

Gene Expression And Regulation

The mechanisms behind the gene expression and regulation that modulate the development and growth of pigeon skeletal muscle remain largely unknown. In this study, we performed gene expression analysis on skeletal muscle samples at different developmental and growth stages using RNA sequencing (RNA−Seq). The differentially expressed genes (DEGs) were identified using edgeR software. Weighted gene co−expression network analysis (WGCNA) was used to identify the gene modules related to the growth and development of pigeon skeletal muscle based on DEGs. A total of 11,311 DEGs were identified. WGCNA aggregated 11,311 DEGs into 12 modules. Black and brown modules were significantly correlated with the 1st and 10th day of skeletal muscle growth, while turquoise and cyan modules were significantly correlated with the 8th and 13th days of skeletal muscle embryonic development. Four mRNA−mRNA regulatory networks corresponding to the four significant modules were constructed and visualised using Cytoscape software. Twenty candidate mRNAs were identified based on their connectivity degrees in the networks, including Abca8b, TCONS−00004461, VWF, OGDH, TGIF1, DKK3, Gfpt1 and RFC5, etc. A KEGG pathway enrichment analysis showed that many pathways were related to the growth and development of pigeon skeletal muscle, including PI3K/AKT/mTOR, AMPK, FAK, and thyroid hormone pathways. Five differentially expressed genes (LAST2, MYPN, DKK3, B4GALT6 and OGDH) in the network were selected, and their expression patterns were quantified by qRT−PCR. The results were consistent with our sequencing results. These findings could enhance our understanding of the gene expression and regulation in the development and growth of pigeon muscle.

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