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Proteome-wide systems analysis of a cellulosic biofuel-producing microbe

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TLDR
The different combinations of carbohydratases used to degrade cellulose and hemicellulose, as well as the repertoires of glycolytic enzymes and alcohol dehydrogenases enabling ethanol production at near maximal yields are identified.
Abstract
Fermentation of plant biomass by microbes like Clostridium phytofermentans recycles carbon globally and can make biofuels from inedible feedstocks. We analyzed C. phytofermentans fermenting cellulosic substrates by integrating quantitative mass spectrometry of more than 2500 proteins with measurements of growth, enzyme activities, fermentation products, and electron microscopy. Absolute protein concentrations were estimated using Absolute Protein EXpression (APEX); relative changes between treatments were quantified with chemical stable isotope labeling by reductive dimethylation (ReDi). We identified the different combinations of carbohydratases used to degrade cellulose and hemicellulose, many of which were secreted based on quantification of supernatant proteins, as well as the repertoires of glycolytic enzymes and alcohol dehydrogenases (ADHs) enabling ethanol production at near maximal yields. Growth on cellulose also resulted in diverse changes such as increased expression of tryptophan synthesis proteins and repression of proteins for fatty acid metabolism and cell motility. This study gives a systems-level understanding of how this microbe ferments biomass and provides a rational, empirical basis to identify engineering targets for industrial cellulosic fermentation.

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Journal ArticleDOI

Recent progress in consolidated bioprocessing

TL;DR: The economic motivation for CBP is addressed, advances and remaining obstacles forCBP organism development are reviewed, and the underlying fundamentals of microbial cellulose utilization are likely to be useful in order to guide the choice and development of CBP systems.
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Clostridia: the importance of their exceptional substrate and metabolite diversity for biofuel and biorefinery applications.

TL;DR: Pathway engineering to combine established substrate-utilization programs, such as for cellulose, CO2/H2 or CO, with desirable metabolic programs could lead to modular design of strains suitable for many applications.
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Systematic Comparison of Label-Free, Metabolic Labeling, and Isobaric Chemical Labeling for Quantitative Proteomics on LTQ Orbitrap Velos

TL;DR: The results show that the spectral counting method provides the deepest proteome coverage for identification, but its quantification performance is worse than labeling-based approaches, especially the quantification reproducibility.
Journal ArticleDOI

Quantification of mRNA and protein and integration with protein turnover in a bacterium.

TL;DR: This study provides a detailed integrative analysis of average cellular protein abundances and the dynamic interplay of mRNA and proteins, the central biomolecules of a cell.
Journal ArticleDOI

Catalytic properties, functional attributes and industrial applications of β-glucosidases

TL;DR: A comprehensive overview on detailed functional roles of β-glucosidases in different organisms, their industrial applications, and recent cloning and expression studies with biochemical characterization of such enzymes is presented for the better understanding and efficient use of diverse β- glucOSidases.
References
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Journal ArticleDOI

Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks

TL;DR: Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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Analyzing real-time PCR data by the comparative C(T) method.

TL;DR: This protocol provides an overview of the comparative CT method for quantitative gene expression studies and various examples to present quantitative gene Expression data using this method.
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Improved Prediction of Signal Peptides: SignalP 3.0

TL;DR: Improvements of the currently most popular method for prediction of classically secreted proteins, SignalP, which consists of two different predictors based on neural network and hidden Markov model algorithms, where both components have been updated.
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The Carbohydrate-Active EnZymes database (CAZy): an expert resource for Glycogenomics

TL;DR: The Carbohydrate-Active Enzyme (CAZy) database is a knowledge-based resource specialized in the enzymes that build and breakdown complex carbohydrates and glycoconjugates and has been used to improve the quality of functional predictions of a number genome projects by providing expert annotation.
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