Dataset Information

Metabolic Profiling of Geobacter sulfurreducens during Industrial Bioprocess Scale-Up.

ABSTRACT: During the industrial scale-up of bioprocesses it is important to establish that the biological system has not changed significantly when moving from small laboratory-scale shake flasks or culturing bottles to an industrially relevant production level. Therefore, during upscaling of biomass production for a range of metal transformations, including the production of biogenic magnetite nanoparticles by Geobacter sulfurreducens, from 100-ml bench-scale to 5-liter fermentors, we applied Fourier transform infrared (FTIR) spectroscopy as a metabolic fingerprinting approach followed by the analysis of bacterial cell extracts by gas chromatography-mass spectrometry (GC-MS) for metabolic profiling. FTIR results clearly differentiated between the phenotypic changes associated with different growth phases as well as the two culturing conditions. Furthermore, the clustering patterns displayed by multivariate analysis were in agreement with the turbidimetric measurements, which displayed an extended lag phase for cells grown in a 5-liter bioreactor (24 h) compared to those grown in 100-ml serum bottles (6 h). GC-MS analysis of the cell extracts demonstrated an overall accumulation of fumarate during the lag phase under both culturing conditions, coinciding with the detected concentrations of oxaloacetate, pyruvate, nicotinamide, and glycerol-3-phosphate being at their lowest levels compared to other growth phases. These metabolites were overlaid onto a metabolic network of G. sulfurreducens, and taking into account the levels of these metabolites throughout the fermentation process, the limited availability of oxaloacetate and nicotinamide would seem to be the main metabolic bottleneck resulting from this scale-up process. Additional metabolite-feeding experiments were carried out to validate the above hypothesis. Nicotinamide supplementation (1 mM) did not display any significant effects on the lag phase of G. sulfurreducens cells grown in the 100-ml serum bottles. However, it significantly improved the growth behavior of cells grown in the 5-liter bioreactor by reducing the lag phase from 24 h to 6 h, while providing higher yield than in the 100-ml serum bottles.

SUBMITTER: Muhamadali H

PROVIDER: S-EPMC4407208 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature

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Metabolic Profiling of Geobacter sulfurreducens during Industrial Bioprocess Scale-Up.

Muhamadali Howbeer H Xu Yun Y Ellis David I DI Allwood J William JW Rattray Nicholas J W NJ Correa Elon E Alrabiah Haitham H Lloyd Jonathan R JR Goodacre Royston R

Applied and environmental microbiology 20150306 10

During the industrial scale-up of bioprocesses it is important to establish that the biological system has not changed significantly when moving from small laboratory-scale shake flasks or culturing bottles to an industrially relevant production level. Therefore, during upscaling of biomass production for a range of metal transformations, including the production of biogenic magnetite nanoparticles by Geobacter sulfurreducens, from 100-ml bench-scale to 5-liter fermentors, we applied Fourier tra ...[more]

PMID: 25746987

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Project description:Biomineralization of Cu has been shown to control contaminant dynamics and transport in soils. However, very little is known about the role that subsurface microorganisms may play in the biogeochemical cycling of Cu. In this study, we investigate the bioreduction of Cu(II) by the subsurface metal-reducing bacterium Geobacter sulfurreducens Rapid removal of Cu from solution was observed in cell suspensions of G. sulfurreducens when Cu(II) was supplied, while transmission electron microscopy (TEM) analyses showed the formation of electron-dense nanoparticles associated with the cell surface. Energy-dispersive X-ray spectroscopy (EDX) point analysis and EDX spectrum image maps revealed that the nanoparticles are rich in both Cu and S. This finding was confirmed by X-ray absorption near-edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) analyses, which identified the nanoparticles as Cu2S. Biomineralization of CuxS nanoparticles in soils has been reported to enhance the colloidal transport of a number of contaminants, including Pb, Cd, and Hg. However, formation of these CuxS nanoparticles has only been observed under sulfate-reducing conditions and could not be repeated using isolates of implicated organisms. As G. sulfurreducens is unable to respire sulfate, and no reducible sulfur was supplied to the cells, these data suggest a novel mechanism for the biomineralization of Cu2S under anoxic conditions. The implications of these findings for the biogeochemical cycling of Cu and other metals as well as the green production of Cu catalysts are discussed.IMPORTANCE Dissimilatory metal-reducing bacteria are ubiquitous in soils and aquifers and are known to utilize a wide range of metals as terminal electron acceptors. These transformations play an important role in the biogeochemical cycling of metals in pristine and contaminated environments and can be harnessed for bioremediation and metal bioprocessing purposes. However, relatively little is known about their interactions with Cu. As a trace element that becomes toxic in excess, Cu can adversely affect soil biota and fertility. In addition, biomineralization of Cu nanoparticles has been reported to enhance the mobilization of other toxic metals. Here, we demonstrate that when supplied with acetate under anoxic conditions, the model metal-reducing bacterium Geobacter sulfurreducens can transform soluble Cu(II) to Cu2S nanoparticles. This study provides new insights into Cu biomineralization by microorganisms and suggests that contaminant mobilization enhanced by Cu biomineralization could be facilitated by Geobacter species and related organisms.

Dataset Information

Metabolic Profiling of Geobacter sulfurreducens during Industrial Bioprocess Scale-Up.

Publications

Metabolic Profiling of Geobacter sulfurreducens during Industrial Bioprocess Scale-Up.

Similar Datasets

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