Comparative Lipidomics of Different Yeast Species Associated to Drosophila suzukii

Yeasts constitute a dietary source for the spotted wing drosophila (SWD) and produce compounds that attract these flies. The study of the chemical composition of the yeast communities associated with SWD should therefore help to understand the relationship between the biology of the insect and the yeast’s metabolism. In the present study, the lipidome of five yeast species isolated from grapes infested by SWD (three Hanseniaspora uvarum strains, Candida sp., Issatchenkia terricola, Metschnikowia pulcherrima and Saccharomycopsis vini) and a laboratory strain of Saccharomyces cerevisiae was explored using an untargeted approach. Additionally, the lipid profile of two species, S. cerevisiae and H. uvarum, which were reported to elicit different responses on SWD flies based on feeding and behavioral trials, was compared with a chemical enrichment approach. Overall, 171 lipids were annotated. The yeast species could be distinguished from each other based on their lipid profile, except for the three strains of H. uvarum, which were very similar to each other. The chemical enrichment analysis emphasized diversities between S. cerevisiae and H. uvarum, that could not be detected based on their global lipid profile. The information concerning differences between species in their lipidome may be of interest to future entomological studies concerning the yeast-insect interaction and could help to explain the responses of SWD to diverse yeast species.

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Separate and combined Hanseniaspora uvarum and Metschnikowia pulcherrima metabolic volatiles are attractive to Drosophila suzukii in the laboratory and field

Scientific Reports ◽

10.1038/s41598-020-79691-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

R. Jones ◽

M. T. Fountain ◽

C. S. Günther ◽

P. E. Eady ◽

M. R. Goddard

Keyword(s):

Yeast Species ◽

Field Trapping ◽

Field Trials ◽

Economic Losses ◽

Drosophila Suzukii ◽

Control Efficacy ◽

Hanseniaspora Uvarum ◽

Metschnikowia Pulcherrima ◽

Rich Diversity ◽

Relative Attractiveness

AbstractDrosophila suzukii flies cause economic losses to fruit crops globally. Previous work shows various Drosophila species are attracted to volatile metabolites produced by individual fruit associated yeast isolates, but fruits naturally harbour a rich diversity of yeast species. Here, we report the relative attractiveness of D. suzukii to yeasts presented individually or in combinations using laboratory preference tests and field trapping data. Laboratory trials revealed four of 12 single yeast isolates were attractive to D. suzukii, of which Metschnikowia pulcherrima and Hanseniaspora uvarum were also attractive in field trials. Four out of 10 yeast combinations involving Candida zemplinina, Pichia pijperi, M. pulcherrima and H. uvarum were attractive in the laboratory. Whilst a combination of M. pulcherrima + H. uvarum trapped the greatest number of D. suzukii in the field, the efficacy of the M. pulcherrima + H. uvarum combination to trap D. suzukii was not significantly greater than traps primed with volatiles from only H. uvarum. While volatiles from isolates of M. pulcherrima and H. uvarum show promise as baits for D. suzukii, further research is needed to ascertain how and why flies are attracted to certain baits to optimise control efficacy.

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Associations of Yeasts with Spotted-Wing Drosophila (Drosophila suzukii; Diptera: Drosophilidae) in Cherries and Raspberries

Applied and Environmental Microbiology ◽

10.1128/aem.00841-12 ◽

2012 ◽

Vol 78 (14) ◽

pp. 4869-4873 ◽

Cited By ~ 109

Author(s):

Kelly A. Hamby ◽

Alejandro Hernández ◽

Kyria Boundy-Mills ◽

Frank G. Zalom

Keyword(s):

Fruit Juice ◽

Fragment Length Polymorphism ◽

Yeast Species ◽

Spotted Wing Drosophila ◽

Drosophila Suzukii ◽

Content Type ◽

Hanseniaspora Uvarum ◽

Larval Frass ◽

History Of ◽

Rich History

ABSTRACTA rich history of investigation documents variousDrosophila-yeast mutualisms, suggesting thatDrosophila suzukiisimilarly has an association with a specific yeast species or community. To discover candidate yeast species, yeasts were isolated from larval frass, adult midguts, and fruit hosts ofD. suzukii. Terminal restriction fragment length polymorphism (TRFLP) technology and decimal dilution plating were used to identify and determine the relative abundance of yeast species present in fruit juice samples that were either infested withD. suzukiior not infested. Yeasts were less abundant in uninfested than infested samples. A total of 126 independent yeast isolates were cultivated from frass, midguts, and fruit hosts ofD. suzukii, representing 28 species of yeasts, withHanseniaspora uvarumpredominating. This suggests an association betweenD. suzukiiandH. uvarumthat could be utilized for pest management of the highly pestiferousD. suzukii.

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Study the relationship between various bacterial infections and lipid profile in Samarra hospital patients

10.36295/asro.2020.2368 ◽

2020 ◽

Vol 23 (06) ◽

pp. 52-63

Author(s):

Osama Nadhom Nijris ◽

Faesal Ghaz Hassen ◽

Asmaa Easa Mahmood

Keyword(s):

Lipid Profile ◽

Bacterial Infections ◽

Hospital Patients ◽

The Relationship

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High Expression of PRMT6 Associated With Prognosis and Immune Infiltration in Glioma

10.21203/rs.3.rs-133309/v1 ◽

2020 ◽

Author(s):

Yi Yang ◽

Zhenshuang Wang ◽

Shengrong Long ◽

Jinhai Huang ◽

Chengran Xu ◽

...

Keyword(s):

Enrichment Analysis ◽

Clinical Work ◽

High Expression ◽

Clinical Indicators ◽

Immune Infiltration ◽

Tumor Tissues ◽

Potential Biomarker ◽

Patient Prognosis ◽

The Relationship

Abstract Background: Gliomas are characterised by easy invasion of surrounding tissues, high mortality and poor prognosis. Moreover, with the increase of grade, the prognosis of glioma is increasingly poor and not optimistic. Therefore, biological markers for glioma are needed in clinical work, which can be utilized to detect and evaluate the situation and prognosis of glioma patients. Many studies have found that the protein arginine methyltransferase 6 (PRMT6) expression is elevated in various tumors and is associated with patient prognosis. However, the role of PRMT6 in glioma has not been reported or analyzed. Methods: In this study, we used a variety of tumor related databases to analyze the mechanism of PRMT6 in tumors, especially gliomas, from the perspective of bioinformatics, and carried out relevant experimental verification with tumor tissues extracted from patients during surgery. In addition, we analyzed the relationship between PRMT6 expression and immune infiltration and immune-related cells, and discussed the possible mechanisms. We also discussed the role of PRMT6 expression in glioma from the perspectives of mutation, clinical indicators, enrichment analysis, and immunohistochemical results. Results: PRMT6 is significantly differentially expressed in a variety of tumors and is associated with survival and prognosis. Especially in gliomas, the expression of PRMT6 gradually increased with the increase of grade. In addition, PRMT6 can be used as an independent prognostic risk factor in the nomogram and has been verified in a variety of databases. Conclusions: Our results indicate that high expression of PRMT6 is a potential biomarker for predicting glioma prognosis and progression.

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Prevalence of Hyperuricemia and the Relationship Between Serum Uric Acid Concentrations and Lipid Parameters Among King Abdulaziz University Hospital Patients

10.21203/rs.3.rs-306744/v1 ◽

2021 ◽

Author(s):

Ranya A. Ghamri ◽

Tala A. Qalai ◽

Raghad A. Ismail ◽

Joud M. Aljehani ◽

Dina S. Alotaibi ◽

...

Keyword(s):

Uric Acid ◽

Lipid Profile ◽

Serum Uric Acid ◽

Acid Concentration ◽

Density Lipoprotein ◽

University Hospital ◽

Uric Acid Concentration ◽

Serum Uric Acid Concentration ◽

King Abdulaziz University ◽

The Relationship

Abstract Background: Hyperuricemia is a metabolic defect caused by high purine consumption, overproduction of uric acid, or reduced uric acid excretion. Hyperuricemia is the second most common metabolic disease after diabetes mellitus and can mediate proinflammatory endocrine imbalance in adipose tissue, which contributed to dyslipidemia. Furthermore, several studies have associated uric acid with dyslipidemia. However, no previous studies have examined patients without chronic illness. Thus, we aimed to assess the relationship between serum uric acid concentration and lipid profile parameters and to estimate the prevalence of hyperuricemia in the city of Jeddah. Methods: A retrospective study was conducted among 1206 patients without chronic illness after applying the exclusion criteria. Patients had undergone laboratory blood testing over a 3-year period (2018–2020) at King Abdulaziz University Hospital, which was ethically approved. We used a predesigned checklist to collect data from electronic hospital records using Google Forms. Bivariate analysis, tables, and graphs were used to represent and identify the relationships between variables. A P-value of <0.05 was considered significant.Results: Our study revealed a prevalence of 12% for hyperuricemia in the study population. Males were more frequently affected than females (8.13% vs. 3.73%, respectively). There was no association between serum uric acid concentration and lipid profile parameters, including total cholesterol (P = 0.92), triglyceride (P = 0.42), high-density lipoprotein (P = 0.47), and low-density lipoprotein (P = 0.66). There was a strong association between serum uric acid concentration and high body mass index (P < 0.001), older age (P = 0.002), male sex (P < 0.001), and nationality (P < 0.001). Furthermore, there was an association between sex and mean erythrocyte sedimentation rate (P = 0.02) and mean triglyceride concentration (P = 0.02).Conclusion: We observed a low prevalence of hyperuricemia, and our results indicate no association between serum uric acid concentration and lipid profile parameters.

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ImReLnc: Identifying Immune-Related LncRNA Characteristics in Human Cancers Based on Heuristic Correlation Optimization

Frontiers in Genetics ◽

10.3389/fgene.2021.792541 ◽

2022 ◽

Vol 12 ◽

Author(s):

Meihong Gao ◽

Shuhui Liu ◽

Yang Qi ◽

Xinpeng Guo ◽

Xuequn Shang

Keyword(s):

Correlation Coefficient ◽

Enrichment Analysis ◽

Highly Pathogenic ◽

Prognostic Effect ◽

Human Cancers ◽

Cancer Pathogenesis ◽

Specific Cancer ◽

Cancer Types ◽

Non Coding Rnas ◽

The Relationship

Long non-coding RNAs (lncRNAs) play critical roles in cancer through gene expression and immune regulation. Identifying immune-related lncRNA (irlncRNA) characteristics would contribute to dissecting the mechanism of cancer pathogenesis. Some computational methods have been proposed to identify irlncRNA characteristics in human cancers, but most of them are aimed at identifying irlncRNA characteristics in specific cancer. Here, we proposed a new method, ImReLnc, to recognize irlncRNA characteristics for 33 human cancers and predict the pathogenicity levels of these irlncRNAs across cancer types. We first calculated the heuristic correlation coefficient between lncRNAs and mRNAs for immune-related enrichment analysis. Especially, we analyzed the relationship between lncRNAs and 17 immune-related pathways in 33 cancers to recognize the irlncRNA characteristics of each cancer. Then, we calculated the Pscore of the irlncRNA characteristics to evaluate their pathogenicity levels. The results showed that highly pathogenic irlncRNAs appeared in a higher proportion of known disease databases and had a significant prognostic effect on cancer. In addition, it was found that the expression of irlncRNAs in immune cells was higher than that of non-irlncRNAs, and the proportion of irlncRNAs related to the levels of immune infiltration was much higher than that of non-irlncRNAs. Overall, ImReLnc accurately identified the irlncRNA characteristics in multiple cancers based on the heuristic correlation coefficient. More importantly, ImReLnc effectively evaluated the pathogenicity levels of irlncRNAs across cancer types. ImReLnc is freely available at https://github.com/meihonggao/ImReLnc.

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Data integration uncovers the metabolic bases of phenotypic variation in yeast

10.1101/2020.06.23.166405 ◽

2020 ◽

Author(s):

Marianyela Petrizzelli ◽

Dominique de Vienne ◽

Thibault Nidelet ◽

Camille Noûs ◽

Christine Dillmann

Keyword(s):

Phenotypic Variation ◽

Enrichment Analysis ◽

Production Traits ◽

Phenotypic Complexity ◽

Powerful Approach ◽

Novel Method ◽

Constraint Based Modeling ◽

The Relationship ◽

Yeast Genetic ◽

Levels Of Integration

The relationship between different levels of integration is a key feature for understanding the genotype-phenotype map.Here, we describe a novel method of integrated data analysis that incorporates protein abundance data into constraint-based modeling to elucidate the biological mechanisms underlying phenotypic variation. Specifically, we studied yeast genetic diversity at three levels of phenotypic complexity in a population of yeast obtained by pairwise crosses of eleven strains belonging to two species, Saccha-romyces cerevisiae and S. uvarum. The data included protein abundances, integrated traits (life-history/fermentation) and computational estimates of metabolic fluxes.Results highlighted that the negative correlation between production traits such as population carrying capacity (K) and traits associated with growth and fermentation rates (Jmax) is explained by a differential usage of energy production pathways: a high K was associated with high TCA fluxes, while a high Jmax was associated with high glycolytic fluxes. Enrichment analysis of protein sets confirmed our results.This powerful approach allowed us to identify the molecular and metabolic bases of integrated trait variation, and therefore has a broad applicability domain.

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