scholarly journals Integrated analysis of transcriptomic and metabolomic data reveals critical metabolic pathways involved in rotenoid biosynthesis in the medicinal plant Mirabilis himalaica

2017 ◽  
Vol 293 (3) ◽  
pp. 635-647 ◽  
Author(s):  
Li Gu ◽  
Zhong-yi Zhang ◽  
Hong Quan ◽  
Ming-jie Li ◽  
Fang-yu Zhao ◽  
...  
Keyword(s):  
Medicinal Plant ◽  
Metabolic Pathways ◽  
Integrated Analysis ◽  
Metabolomic Data

Biotechnological Production of Natural Calorie Free Steviol Glycosides in Stevia rebaudiana: An Update on Current Scenario

2020 ◽  
Vol 8 (2) ◽  
pp. 70-84
Author(s):  
Abeer Kazmi ◽  
Mubarak Ali Khan ◽  
Sher Mohammad ◽  
Amir Ali ◽  
Huma Ali
Keyword(s):  
Medicinal Plant ◽  
Cell Cultures ◽  
Metabolic Pathways ◽  
Plant Material ◽  
Research Work ◽  
Stevia Rebaudiana ◽  
Steviol Glycosides ◽  
Market Demand ◽  
Biotechnological Production ◽  
Current Scenario

Stevia rebaudiana is a vital medicinal plant of the genus Stevia and family Asteraceae. It is commonly used as a natural sweetener plant and its products are 300 times sweeter than the commonly used sugarcane. The sweetening potential is due to the presence of calorie-free steviol glycosides (SGs). The plant species has been extensively profiled to identify steviol glycosides (SGs) with intensity sweetening properties. However, the limited production of plant material is not fulfilling the higher market demand worldwide. Researchers are working worldwide to enhance the production of important SGs through the intervention of different biotechnological approaches in S. rebaudiana. In this review, the research work conducted in the last twenty years, on the different aspects of biotechnology to enhance the production of SGs has been precisely reviewed. Biotechnological methods such as micropropagation, callus and cell cultures, elicitation and the metabolomics and transcriptomic elucidation of the biosynthetic metabolic pathways for the production of steviol glycosides have been concisely reviewed and discussed.

scholarly journals A Multi-Omics Study of Chicken Infected by Nephropathogenic Infectious Bronchitis Virus

Viruses ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 1070 ◽  
Author(s):  
Puzhi Xu ◽  
Ping Liu ◽  
Changming Zhou ◽  
Yan Shi ◽  
Qingpeng Wu ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Infectious Bronchitis Virus ◽  
Metabolic Pathways ◽  
Host Responses ◽  
Integrated Analysis ◽  
Specific Gene ◽  
Rna Seq ◽  
Infectious Bronchitis ◽  
Infection Processes

Chicken gout resulting from nephropathogenic infectious bronchitis virus (NIBV) has become a serious kidney disease problem in chicken worldwide with alterations of the metabolic phenotypes in multiple metabolic pathways. To investigate the mechanisms in chicken responding to NIBV infection, we examined the global transcriptomic and metabolomic profiles of the chicken’s kidney using RNA-seq and GC–TOF/MS, respectively. Furthermore, we analyzed the alterations in cecal microorganism composition in chickens using 16S rRNA-seq. Integrated analysis of these three phenotypic datasets further managed to create correlations between the altered kidney transcriptomes and metabolome, and between kidney metabolome and gut microbiome. We found that 2868 genes and 160 metabolites were deferentially expressed or accumulated in the kidney during NIBV infection processes. These genes and metabolites were linked to NIBV-infection related processes, including immune response, signal transduction, peroxisome, purine, and amino acid metabolism. In addition, the comprehensive correlations between the kidney metabolome and cecal microbial community showed contributions of gut microbiota in the progression of NIBV-infection. Taken together, our research comprehensively describes the host responses during NIBV infection and provides new clues for further dissection of specific gene functions, metabolite affections, and the role of gut microbiota during chicken gout.

scholarly journals Serum Metabolomic Patterns in Young Patients with Ischemic Stroke

2020 ◽  
Author(s):  
Jia Liu ◽  
Junliang Yuan ◽  
Jingwei Zhao ◽  
Lin Zhang ◽  
Qiu Wang ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Metabolic Pathways ◽  
Comprehensive Evaluation ◽  
Young Patients ◽  
Healthy Controls ◽  
Stroke Patients ◽  
Multivariate Statistical ◽  
Metabolomic Data ◽  
Common Risk Factors ◽  
Serum Metabolomics

Abstract Background: Ischemic stroke is one of the leading causes of death and adult disability. The incidence of ischemic stroke continues to rise in young adults. This study aimed to provide a comprehensive evaluation of metabolic changes and explore possible mechanisms in young ischemic stroke patients without common risk factors. Methods: This study investigated serum metabolomics in 50 young patients with newly suffered ischemic stroke and 50 age-, sex-, and body mass index–matched healthy controls. The metabolomic data were analyzed by performing a multivariate statistical analysis.Results: The 197 metabolites, including amino acids, bile acids, free fatty acids, and lipids, were identified in all participants. Multivariate models showed significant differences in serum metabolomic patterns between young patients with ischemic stroke and healthy controls. The stroke patients had increased L-methionine, homocysteine, glutamine, uric acid, GCDCA, and PE (18:0/20:4, 16:0/22:5), and decreased levels of L-citrulline, taurine, PC (16:2/22:6, 16:2/20:5, 15:0/18:2), and SM (d18:1/23:0, d20:0/19:1, d18:1/22:0, d16:0/26:1, d16:0/18:0, d16:0/22:1, d18:1/19:1, d16:0/17:1, d16:1/24:1, d18:1/19:0). Based on the identified metabolites, the metabolic pathways of arginine biosynthesis, glycerophospholipid metabolism, and taurine and hypotaurine metabolism were significantly enriched in the young patients with ischemic stroke. Conclusions: Serum metabolomic patterns were significantly different between young patients with ischemic stroke and healthy controls.

scholarly journals Structure and Function of Oral Microbial Community in Periodontitis Based on Integrated Data

2021 ◽  
Vol 11 ◽  
Author(s):  
Zhengwen Cai ◽  
Shulan Lin ◽  
Shoushan Hu ◽  
Lei Zhao
Keyword(s):  
Microbial Community ◽  
Metabolic Pathways ◽  
Sequence Data ◽  
Periodontal Pocket ◽  
Integrated Analysis ◽  
Pocket Depth ◽  
Screening Criteria ◽  
Related Sequence ◽  
And Function ◽  
Potential Biomarkers

ObjectiveMicroorganisms play a key role in the initiation and progression of periodontal disease. Research studies have focused on seeking specific microorganisms for diagnosing and monitoring the outcome of periodontitis treatment. Large samples may help to discover novel potential biomarkers and capture the common characteristics among different periodontitis patients. This study examines how to screen and merge high-quality periodontitis-related sequence datasets from several similar projects to analyze and mine the potential information comprehensively.MethodsIn all, 943 subgingival samples from nine publications were included based on predetermined screening criteria. A uniform pipeline (QIIME2) was applied to clean the raw sequence datasets and merge them together. Microbial structure, biomarkers, and correlation network were explored between periodontitis and healthy individuals. The microbiota patterns at different periodontal pocket depths were described. Additionally, potential microbial functions and metabolic pathways were predicted using PICRUSt to assess the differences between health and periodontitis.ResultsThe subgingival microbial communities and functions in subjects with periodontitis were significantly different from those in healthy subjects. Treponema, TG5, Desulfobulbus, Catonella, Bacteroides, Aggregatibacter, Peptostreptococcus, and Eikenella were periodontitis biomarkers, while Veillonella, Corynebacterium, Neisseria, Rothia, Paludibacter, Capnocytophaga, and Kingella were signature of healthy periodontium. With the variation of pocket depth from shallow to deep pocket, the proportion of Spirochaetes, Bacteroidetes, TM7, and Fusobacteria increased, whereas that of Proteobacteria and Actinobacteria decreased. Synergistic relationships were observed among different pathobionts and negative relationships were noted between periodontal pathobionts and healthy microbiota.ConclusionThis study shows significant differences in the oral microbial community and potential metabolic pathways between the periodontitis and healthy groups. Our integrated analysis provides potential biomarkers and directions for in-depth research. Moreover, a new method for integrating similar sequence data is shown here that can be applied to other microbial-related areas.

Intrauterine Growth Restriction Programs the Hypothalamus of Adult Male Rats: Integrated Analysis of Proteomic and Metabolomic Data

2017 ◽  
Vol 16 (4) ◽  
pp. 1515-1525 ◽  
Author(s):  
Amanda P. Pedroso ◽  
Adriana P. Souza ◽  
Ana P. S. Dornellas ◽  
Lila M. Oyama ◽  
Cláudia M. O. Nascimento ◽  
...  
Keyword(s):  
Adult Male ◽  
Intrauterine Growth Restriction ◽  
Growth Restriction ◽  
Male Rats ◽  
Integrated Analysis ◽  
Intrauterine Growth ◽  
Metabolomic Data

scholarly journals Mucosal microbiota and metabolome along the intestinal tracts reveals location specific relationship

2018 ◽  
Author(s):  
Ce Yuan ◽  
Melanie Graham ◽  
Christopher Staley ◽  
Subbaya Subramanian
Keyword(s):  
Intestinal Microbiota ◽  
Metabolic Pathways ◽  
Current Knowledge ◽  
Distal Colon ◽  
Host Tissue ◽  
Integrated Analysis ◽  
Mucosal Tissue ◽  
Interconnected Network ◽  
Metabolic Interactions ◽  
Small Intestinal

AbstractBackgroundThe intestinal microbiota has been recognized as an important component for maintaining human health. The perturbation to its structure has been implicated in many diseases, such as obesity and cancers. The microbiota is highly metabolically active and plays a role in many metabolic pathways absent from the human host. Altered microbiota metabolism has also been linked to obesity, cardiovascular disease, and colorectal cancer. However, there is a gap in the current knowledge of how the microbiota interacts with its host. Here we performed an integrated analysis between the mucosal-associated microbiota and the mucosal tissue metabolomics in healthy non-human primates (NHPs) to investigate these relationships.ResultsWe found that the overall microbiota composition is influenced by both the tissue location as well as the host individual. The NHPs intestinal microbiota predominantly comprised of members of the phyla Firmicutes, Bacteroidetes, and Proteobacteria. The large intestines contain more Spirochaetes, Tenericutes, and Lentisphaera phyla members. The small intestinal tissues have no significantly different microbiota compositions, while the cecum and distal colon differ greatly in the microbiota compositions. The metabolomics profile reveals a total of 140 metabolites with different concentration between the small and large intestines. The correlations between microbiota and tissue metabolites showed a dense and interconnected network in the small intestines while a sparse network in the large intestines.ConclusionsOur analysis revealed an intricate global relationship between the microbiota and the host tissue metabolome that is mainly driven by the distal colon. Most importantly, we found location specific microbiota-metabolite correlations that have potential implications for studying host-microbiota metabolic interactions.

scholarly journals The Importance of Metabolism for Immune Homeostasis in Allergic Diseases

2021 ◽  
Vol 12 ◽  
Author(s):  
Juan Rodriguez-Coira ◽  
Alma Villaseñor ◽  
Elena Izquierdo ◽  
Mengting Huang ◽  
Tomás Clive Barker-Tejeda ◽  
...  
Keyword(s):  
T Cells ◽  
Energy Metabolism ◽  
Metabolic Pathways ◽  
Metabolic Diseases ◽  
Immune Cell ◽  
Allergic Inflammation ◽  
Integrated Analysis ◽  
Cellular Models ◽  
Cell Functions ◽  
Analytical Approaches

There is increasing evidence that the metabolic status of T cells and macrophages is associated with severe phenotypes of chronic inflammation, including allergic inflammation. Metabolic changes in immune cells have a crucial role in their inflammatory or regulatory responses. This notion is reinforced by metabolic diseases influencing global energy metabolism, such as diabetes or obesity, which are known risk factors of severity in inflammatory conditions, due to the metabolic-associated inflammation present in these patients. Since several metabolic pathways are closely tied to T cell and macrophage differentiation, a better understanding of metabolic alterations in immune disorders could help to restore and modulate immune cell functions. This link between energy metabolism and inflammation can be studied employing animal, human or cellular models. Analytical approaches rank from classic immunological studies to integrated analysis of metabolomics, transcriptomics, and proteomics. This review summarizes the main metabolic pathways of the cells involved in the allergic reaction with a focus on T cells and macrophages and describes different models and platforms of analysis used to study the immune system and its relationship with metabolism.

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