Dissecting metabolic behavior of lipid over-producing strain of Mucor circinelloides through genome-scale metabolic network and multi-level data integration

Vongsangnak, Wanwipa; Kingkaw, Amornthep; Yang, Junhuan; Song, Yuanda; Laoteng, Kobkul

doi:10.1016/j.gene.2018.05.085

Cited by 13 publications

(8 citation statements)

References 43 publications

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“…Besides, the added/updated genes, EC numbers, and metabolic reactions in i NI1159 can be seen in File S1. The data in blanket are in vivo data.a i WV1213 model was taken from Vongsangnak et al (2016).b i WV1122 network was taken from Vongsangnak et al (2018).cIn vivo data were taken from Zhao et al (2015).d In vivo data were taken from Tang et al (2016).e In vivo data of specific growth rate for validation i WV1213 from Wynn et al (2001).…”

Section: Resultsmentioning

confidence: 99%

“…A draft metabolic network of M. circinelloides WJ11 (Vongsangnak et al, 2018) was basically used for GEM development of this strain. Initially, the improved annotation of genes and relevant enzyme functions was performed using M. circinelloides WJ11 protein sequence homology searches for reconstructing GEM.…”

Section: Methodsmentioning

confidence: 99%

“…As a consequence, the cellular metabolic mechanisms governing the oleaginicity of this particular strain have been addressed through several approaches, such as multilevel omics analysis (Tang et al, 2016; Tang et al, 2015a; Tang et al, 2015b; Tang et al, 2017). Recently, the constructed genome-scale metabolic network of M. circinelloides WJ11 was employed to explain its metabolic routes, focusing on lipid metabolism and carotenoid biosynthesis (Vongsangnak et al, 2018). To gain a more precise scaffold for the predictive analysis of the metabolic control involved in the oleaginicity of the WJ11 strain, a functional GEM of M. circinelloides WJ11 was developed in this work.…”

Section: Introductionmentioning

confidence: 99%

“…To gain a more precise scaffold for the predictive analysis of the metabolic control involved in the oleaginicity of the WJ11 strain, a functional GEM of M. circinelloides WJ11 was developed in this work. Briefly, the metabolic network of M. circinelloides WJ11 (Vongsangnak et al, 2018) was initially used as a scaffold for improving gene annotation through metabolic reconstruction. For metabolic modeling and analysis, flux balance analysis (FBA), phenotype phase plane analysis (PhPP), fast flux variability analysis (fastFVA), and uniform sampling with coordinate hit-and-run with rounding (CHRR) were afterwards executed for observing cellular phenotypes of M. circinelloides WJ11.…”

Section: Introductionmentioning

confidence: 99%

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Metabolic traits specific for lipid-overproducing strain of Mucor circinelloides WJ11 identified by genome-scale modeling approach

Ayudhya

Laoteng

Song

et al. 2019

PeerJ

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The genome-scale metabolic model of a lipid-overproducing strain of Mucor circinelloides WJ11 was developed. The model (iNI1159) contained 1,159 genes, 648 EC numbers, 1,537 metabolites, and 1,355 metabolic reactions, which were localized in different compartments of the cell. Using flux balance analysis (FBA), the iNI1159 model was validated by predicting the specific growth rate. The metabolic traits investigated by phenotypic phase plane analysis (PhPP) showed a relationship between the nutrient uptake rate, cell growth, and the triacylglycerol production rate, demonstrating the strength of the model. A putative set of metabolic reactions affecting the lipid-accumulation process was identified when the metabolic flux distributions under nitrogen-limited conditions were altered by performing fast flux variability analysis (fastFVA) and relative flux change. Comparative analysis of the metabolic models of the lipid-overproducing strain WJ11 (iNI1159) and the reference strain CBS277.49 (iWV1213) using both fastFVA and coordinate hit-and-run with rounding (CHRR) showed that the flux distributions between these two models were significantly different. Notably, a higher flux distribution through lipid metabolisms such as lanosterol, zymosterol, glycerolipid and fatty acids biosynthesis in iNI1159 was observed, leading to an increased lipid production when compared to iWV1213. In contrast, iWV1213 exhibited a higher flux distribution across carbohydrate and amino acid metabolisms and thus generated a high flux for biomass production. This study demonstrated that iNI1159 is an effective predictive tool for the pathway engineering of oleaginous strains for the production of diversified oleochemicals with industrial relevance.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Metabolic traits specific for lipid-overproducing strain of Mucor circinelloides WJ11 identified by genome-scale modeling approach

Ayudhya

Laoteng

Song

et al. 2019

PeerJ

Self Cite

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“…The increasing number of infections associated with Mucor species, as well as the biotechnological potential of the genus, have led to a large effort to better know these fungi. In this context, Vongsangnak et al proposed a metabolic network of the oleaginous strain Mucor circicinelloides WJ11 [10,11], Corrochano et al shed new light on Mucor sensory perception [12], and multiple genes potentially involved in virulence were investigated and discovered in Mucor spp. [13][14][15][16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Comparative genomics applied to Mucor species with different lifestyles

et al. 2020

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Background: Despite a growing number of investigations on early diverging fungi, the corresponding lineages have not been as extensively characterized as Ascomycota or Basidiomycota ones. The Mucor genus, pertaining to one of these lineages is not an exception. To this date, a restricted number of Mucor annotated genomes is publicly available and mainly correspond to the reference species, Mucor circinelloides, and to medically relevant species. However, the Mucor genus is composed of a large number of ubiquitous species as well as few species that have been reported to specifically occur in certain habitats. The present study aimed to expand the range of Mucor genomes available and identify potential genomic imprints of adaptation to different environments and lifestyles in the Mucor genus. Results: In this study, we report four newly sequenced genomes of Mucor isolates collected from non-clinical environments pertaining to species with contrasted lifestyles, namely Mucor fuscus and Mucor lanceolatus, two species used in cheese production (during ripening), Mucor racemosus, a recurrent cheese spoiler sometimes described as an opportunistic animal and human pathogen, and Mucor endophyticus, a plant endophyte. Comparison of these new genomes with those previously available for six Mucor and two Rhizopus (formerly identified as M. racemosus) isolates allowed global structural and functional description such as their TE content, core and species-specific genes and specialized genes. We proposed gene candidates involved in iron metabolism; some of these genes being known to be involved in pathogenicity; and described patterns such as a reduced number of CAZymes in the species used for cheese ripening as well as in the endophytic isolate that might be related to adaptation to different environments and lifestyles within the Mucor genus. Conclusions: This study extended the descriptive data set for Mucor genomes, pointed out the complexity of obtaining a robust phylogeny even with multiple genes families and allowed identifying contrasting potentially lifestyle-associated gene repertoires. The obtained data will allow investigating further the link between genetic and its biological data, especially in terms of adaptation to a given habitat.

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Current Status and Applications of Genome‐Scale Metabolic Models of Oleaginous Microorganisms

Hu,

Qian,

Wang

et al. 2024

Food Bioengineering

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Oleaginous microorganisms have the unique ability to accumulate lipids that can exceed 20% of their dry cell weight under certain conditions. Despite their potential for efficient lipid production, the metabolic pathways involved are not yet fully understood, largely due to the complexity of intracellular processes and the challenges in phenotypic prediction. This review synthesizes the latest research on the application of Genome‐scale Metabolic Network Models (GSMMs) to study oleaginous microorganisms, including bacteria, cyanobacteria, yeast, microalgae, and fungi, and provides a comprehensive analysis of how GSMMs have been utilized to decipher the metabolic mechanisms behind lipid accumulation and to identify key genes involved in lipid synthesis. The review highlights the role of GSMMs in predicting cellular behavior, optimizing metabolic engineering strategies, and discusses the future directions and potential of GSMMs in enhancing lipid production in microorganisms. This comprehensive overview not only summarizes the current state of research but also identifies gaps and opportunities for further investigation in the field.

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Dissecting metabolic behavior of lipid over-producing strain of Mucor circinelloides through genome-scale metabolic network and multi-level data integration

Cited by 13 publications

References 43 publications

Metabolic traits specific for lipid-overproducing strain of Mucor circinelloides WJ11 identified by genome-scale modeling approach

Metabolic traits specific for lipid-overproducing strain of Mucor circinelloides WJ11 identified by genome-scale modeling approach

Comparative genomics applied to Mucor species with different lifestyles

Current Status and Applications of Genome‐Scale Metabolic Models of Oleaginous Microorganisms

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