Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1031994 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR26512817.fastq.gz | Fastqsanger.gz | |||
| SRR26512818.fastq.gz | Fastqsanger.gz | |||
| SRR26512819.fastq.gz | Fastqsanger.gz | |||
| SRR26512820.fastq.gz | Fastqsanger.gz | |||
| SRR26512821.fastq.gz | Fastqsanger.gz |
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Project description:Various saprotrophic microorganisms, especially filamentous fungi, can efficiently degrade lignocellulose that is one of the most abundant natural material on earth. It consists of complex carbohydrates and aromatic polymers found in plant cell wall and thus in plant debris. Aspergillus fumigatus Z5 was isolated from compost heaps and showed highly efficient plant biomass-degradation capability.Genome analysis revealed an impressive array of genes encoding cellulases, hemicellulases, and pectinases involved in lignocellulosic biomass degradation. We sequenced the transcriptomes of Aspergillus fumigatus Z5 induced by sucrose, xylan, cellulose and rice straw, respectively. There were 444, 1711 and 1386 significantly differently (q-value ⤠0.0001 and |log2 of the ratio of the RPM values| ⥠2) expressed genes in xylan, cellulose and rice straw,respectively, relative to sucrose control. After incubation at 45 â, 145rpm for 20 hours with sucrose as the carbon source, mycelia were induced for 16 hours using xylan, cellulose and rice straw, respectively. Transcriptome induced by sucrose was used as the control when comparing the differences between other three transcriptomes (induced by xylan, cellulose and rice straw, respectively).
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2023-12-30 | E-MTAB-13326 | biostudies-arrayexpress
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Project description:Ahmad2017 - Genome-scale metabolic model
(iGT736) of Geobacillus thermoglucosidasius (C56-YS93)
This model is described in the article:
A Genome Scale Model of
Geobacillus thermoglucosidasius (C56-YS93) reveals its
biotechnological potential on rice straw hydrolysate
Ahmad Ahmada, Hassan B. Hartmanb, S.
Krishnakumara, David A. Fellb, Mark G. Poolmanb, Shireesh
Srivastavaa
Journal of Biotechnology
Abstract:
Rice straw is a major crop residue which is burnt in many
countries, creating significant air pollution. Thus,
alternative routes for disposal of rice straw are needed.
Biotechnological treatment of rice straw hydrolysate has
potential to convert this agriculture waste into valuable
biofuel(s) and platform chemicals. Geobacillus
thermoglucosidasius is a thermophile with properties specially
suited for use as a biocatalyst in lignocellulosic
bioprocesses, such as high optimal temperature and tolerance to
high levels of ethanol. However, the capabilities of
Geobacillus thermoglucosidasius to utilize sugars in rice straw
hydrolysate for making bioethanol and other platform chemicals
have not been fully explored. In this work, we have created a
genome scale metabolic model (denoted iGT736) of the organism
containing 736 gene products, 1159 reactions and 1163
metabolites. The model was validated both by purely theoretical
approaches and by comparing the behaviour of the model to
previously published experimental results. The model was then
used to determine the yields of a variety of platform chemicals
from glucose and xylose — two primary sugars in rice
straw hydrolysate. A comparison with results from a model of
Escherichia coli shows that Geobacillus thermoglucosidasius is
capable of producing a wider range of products, and that for
the products also produced by Escherichia coli, the yields are
comparable. We also discuss strategies to utilise arabinose, a
minor component of rice straw hydrolysate, and propose
additional reactions to lead to the synthesis of xylitol, not
currently produced by Geobacillus thermoglucosidasius. Our
results provide additional motivation for the current
exploration of the industrial potential of Geobacillus
thermoglucosidasius and we make our model publicly available to
aid the development of metabolic engineering strategies for
this organism.
This model is hosted on
BioModels Database
and identified by:
MODEL1703060000.
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2017-04-12 | MODEL1703060000 | BioModels