Metabolic network reconstruction and genome-scale model of butanol-producing strain Clostridium beijerinckii NCIMB 8052

<p>Abstract</p> <p>Background</p> <p>Solventogenic clostridia offer a sustainable alternative to petroleum-based production of butanol--an important chemical feedstock and potential fuel additive or replacement. <it>C. beijerinckii </it>is an attractive microorganism for strain design to improve butanol production because it (i) naturally produces the highest recorded butanol concentrations as a byproduct of fermentation; and (ii) can co-ferment pentose and hexose sugars (the primary products from lignocellulosic hydrolysis). Interrogating <it>C. beijerinckii </it>metabolism from a systems viewpoint using constraint-based modeling allows for simulation of the global effect of genetic modifications.</p> <p>Results</p> <p>We present the first genome-scale metabolic model (<it>i</it>CM925) for <it>C. beijerinckii</it>, containing 925 genes, 938 reactions, and 881 metabolites. To build the model we employed a semi-automated procedure that integrated genome annotation information from KEGG, BioCyc, and The SEED, and utilized computational algorithms with manual curation to improve model completeness. Interestingly, we found only a 34% overlap in reactions collected from the three databases--highlighting the importance of evaluating the predictive accuracy of the resulting genome-scale model. To validate <it>i</it>CM925, we conducted fermentation experiments using the NCIMB 8052 strain, and evaluated the ability of the model to simulate measured substrate uptake and product production rates. Experimentally observed fermentation profiles were found to lie within the solution space of the model; however, under an optimal growth objective, additional constraints were needed to reproduce the observed profiles--suggesting the existence of selective pressures other than optimal growth. Notably, a significantly enriched fraction of actively utilized reactions in simulations--constrained to reflect experimental rates--originated from the set of reactions that overlapped between all three databases (<it>P </it>= 3.52 × 10^-9, Fisher's exact test). Inhibition of the hydrogenase reaction was found to have a strong effect on butanol formation--as experimentally observed.</p> <p>Conclusions</p> <p>Microbial production of butanol by <it>C. beijerinckii </it>offers a promising, sustainable, method for generation of this important chemical and potential biofuel. <it>i</it>CM925 is a predictive model that can accurately reproduce physiological behavior and provide insight into the underlying mechanisms of microbial butanol production. As such, the model will be instrumental in efforts to better understand, and metabolically engineer, this microorganism for improved butanol production.</p

Cellulose conversion in dry grind ethanol plants

The expansion of the dry grind ethanol industry provides a unique opportunity to introduce cellulose conversion technology to existing grain to ethanol plants, while enhancing ethanol yields by up to 14%, and decreasing the volume while increasing protein content of distiller’s grains. The technologies required are cellulose pretreatment, enzyme hydrolysis, fermentation, and drying. Laboratory data combined with compositional analysis and process simulations are used to present a comparative analysis of a dry grind process to a process with pretreatment and hydrolysis of cellulose in distiller’s grains. The additional processing steps are projected to give a 32% increase in net present value if process modifications are made to a 100 million gallon/year plant

Single-nucleotide resolution analysis of the transcriptome structure of Clostridium beijerinckii NCIMB 8052 using RNA-Seq

<p>Abstract</p> <p>Background</p> <p><it>Clostridium beijerinckii </it>is an important solvent producing microorganism. The genome of <it>C. beijerinckii </it>NCIMB 8052 has recently been sequenced. Although transcriptome structure is important in order to reveal the functional and regulatory architecture of the genome, the physical structure of transcriptome for this strain, such as the operon linkages and transcript boundaries are not well understood.</p> <p>Results</p> <p>In this study, we conducted a single-nucleotide resolution analysis of the <it>C. beijerinckii </it>NCIMB 8052 transcriptome using high-throughput RNA-Seq technology. We identified the transcription start sites and operon structure throughout the genome. We confirmed the structure of important gene operons involved in metabolic pathways for acid and solvent production in <it>C. beijerinckii </it>8052, including <it>pta</it>-<it>ack</it>, <it>ptb</it>-<it>buk</it>, <it>hbd</it>-<it>etfA</it>-<it>etfB</it>-<it>crt </it>(<it>bcs</it>) and <it>ald</it>-<it>ctfA</it>-<it>ctfB</it>-<it>adc </it>(<it>sol</it>) operons; we also defined important operons related to chemotaxis/motility, transcriptional regulation, stress response and fatty acids biosynthesis along with others. We discovered 20 previously non-annotated regions with significant transcriptional activities and 15 genes whose translation start codons were likely mis-annotated. As a consequence, the accuracy of existing genome annotation was significantly enhanced. Furthermore, we identified 78 putative silent genes and 177 putative housekeeping genes based on normalized transcription measurement with the sequence data. We also observed that more than 30% of pseudogenes had significant transcriptional activities during the fermentation process. Strong correlations exist between the expression values derived from RNA-Seq analysis and microarray data or qRT-PCR results.</p> <p>Conclusions</p> <p>Transcriptome structural profiling in this research provided important supplemental information on the accuracy of genome annotation, and revealed additional gene functions and regulation in <it>C. beijerinckii</it>.</p

What are the possibilities for the new bioeconomy

Resource /Energy Economics and Policy,