Jinwook Lee, Sungyoun Kim, Hye-Weon Yu et al.

Desalination • 2009

Jisun Jong, Jaejin Lee, Joonkyu Kim et al.

Desalination • 2009

Bin Dong, Shuangying Jiang

Desalination • 2009

Xiao-Mao Wang, T. David Waite

Desalination and Water Treatment • 2009

Jill Ruhsing Pan, Yuchun Su, Chihpin Huang

Desalination • 2009

G. Schaule, S. Rapenne, M. Strathmann et al.

Desalination and Water Treatment • 2009

Rajindar Singh

Desalination • 2008

A. Trusek-Holownia

Desalination • 2008

Tae Hoon Yang, Maddalena V Coppi, Derek R Lovley et al.

Microbial Cell Factories • 2009

Hongqiang Hu, Yanzhen Fan, Hong Liu

International Journal of Hydrogen Energy • 2009

Priscilla A. Selembo, Matthew D. Merrill, Bruce E. Logan

International Journal of Hydrogen Energy • 2009

Neus Ferrer-Miralles, Joan Domingo-Espín, José Luis Corchero et al.

Microbial Cell Factories • 2009

Abstract Most of the hosts used to produce the 151 recombinant pharmaceuticals so far approved for human use by the Food and Drug Administration (FDA) and/or by the European Medicines Agency (EMEA) are microbial cells, either bacteria or yeast. This fact indicates that despite the diverse bottlenecks and obstacles that microbial systems pose to the efficient production of functional mammalian proteins, namely lack or unconventional post-translational modifications, proteolytic instability, poor solubility and activation of cell stress responses, among others, they represent convenient and powerful tools for recombinant protein production. The entering into the market of a progressively increasing number of protein drugs produced in non-microbial systems has not impaired the development of products obtained in microbial cells, proving the robustness of the microbial set of cellular systems (so far Escherichia coli and Saccharomyces cerevisae ) developed for protein drug production. We summarize here the nature, properties and applications of all those pharmaceuticals and the relevant features of the current and potential producing hosts, in a comparative way.

Baley A Fong, David W Wood

Microbial Cell Factories • 2009

Elastin-like polypeptides (ELPs) are useful tools that can be used to non-chromatographically purify proteins. When paired with self-cleaving inteins, they can be used as economical self-cleaving purification tags. However, ELPs and ELP-tagged target proteins have been traditionally expressed using highly enriched media in shake flask cultures, which are generally not amenable to scale-up.

Swaranjit Cameotra, Pooja Singh

Microbial Cell Factories • 2008

Hongqiang Hu, Yanzhen Fan, Hong Liu

International Journal of Hydrogen Energy • 2010

Robert LJ Graham, Ciaren Graham, Geoff McMullan

Microbial Cell Factories • 2007

Abstract It is now more than 10 years since the publication of the first microbial genome sequence and science is now moving towards a post genomic era with transcriptomics and proteomics offering insights into cellular processes and function. The ability to assess the entire protein network of a cell at a given spatial or temporal point will have a profound effect upon microbial science as the function of proteins is inextricably linked to phenotype. Whilst such a situation is still beyond current technologies rapid advances in mass spectrometry, bioinformatics and protein separation technologies have produced a step change in our current proteomic capabilities. Subsequently a small, but steadily growing, number of groups are taking advantage of this cutting edge technology to discover more about the physiology and metabolism of microorganisms. From this research it will be possible to move towards a systems biology understanding of a microorganism. Where upon researchers can build a comprehensive cellular map for each microorganism that links an accurately annotated genome sequence to gene expression data, at a transcriptomic and proteomic level. In order for microbiologists to embrace the potential that proteomics offers, an understanding of a variety of analytical tools is required. The aim of this review is to provide a basic overview of mass spectrometry (MS) and its application to protein identification. In addition we will describe how the protein complexity of microbial samples can be reduced by gel-based and gel-free methodologies prior to analysis by MS. Finally in order to illustrate the power of microbial proteomics a case study of its current application within the Bacilliaceae is given together with a description of the emerging discipline of metaproteomics.

J. Udagawa, P. Aguiar, N.P. Brandon

Journal of Power Sources • 2007

Shaoan Cheng, Bruce E. Logan

Water Science and Technology • 2009

Publisher's note. We very much regret that in the course of production the correct version of Figure 2 of this article was replaced by a figure from another article. The correct version of Figure 2 is shown below.

Juan-Juan WANG, Yong ZHANG, Jiang-Rong KONG et al.

Journal of Inorganic Materials • 2010

J. Udagawa, P. Aguiar, N.P. Brandon

Journal of Power Sources • 2008

Špela Peternel, Radovan Komel

Microbial Cell Factories • 2009

In recent years bacterial inclusion bodies (IBs) were recognised as highly pure deposits of active proteins inside bacterial cells. Such active nanoparticles are very interesting for further downstream protein isolation, as well as for many other applications in nanomedicine, cosmetic, chemical and pharmaceutical industry.To prepare large quantities of a high quality product, the whole bioprocess has to be optimised. This includes not only the cultivation of the bacterial culture, but also the isolation step itself, which can be of critical importance for the production process.To determine the most appropriate method for the isolation of biologically active nanoparticles, three methods for bacterial cell disruption were analyzed.

Nuria B Centeno, Joan Planas-Iglesias, Baldomero Oliva

Microbial Cell Factories • 2005

Abstract Comparative modeling is becoming an increasingly helpful technique in microbial cell factories as the knowledge of the three-dimensional structure of a protein would be an invaluable aid to solve problems on protein production. For this reason, an introduction to comparative modeling is presented, with special emphasis on the basic concepts, opportunities and challenges of protein structure prediction. This review is intended to serve as a guide for the biologist who has no special expertise and who is not involved in the determination of protein structure. Selected applications of comparative modeling in microbial cell factories are outlined, and the role of microbial cell factories in the structural genomics initiative is discussed.

Maria Freigassner, Harald Pichler, Anton Glieder

Microbial Cell Factories • 2009

Abstract The last four years have brought exciting progress in membrane protein research. Finally those many efforts that have been put into expression of eukaryotic membrane proteins are coming to fruition and enable to solve an ever-growing number of high resolution structures. In the past, many skilful optimization steps were required to achieve sufficient expression of functional membrane proteins. Optimization was performed individually for every membrane protein, but provided insight about commonly encountered bottlenecks and, more importantly, general guidelines how to alleviate cellular limitations during microbial membrane protein expression. Lately, system-wide analyses are emerging as powerful means to decipher cellular bottlenecks during heterologous protein production and their use in microbial membrane protein expression has grown in popularity during the past months. This review covers the most prominent solutions and pitfalls in expression of eukaryotic membrane proteins using microbial hosts (prokaryotes, yeasts), highlights skilful applications of our basic understanding to improve membrane protein production. Omics technologies provide new concepts to engineer microbial hosts for membrane protein production.

J. Udagawa, P. Aguiar, N.P. Brandon

Journal of Power Sources • 2008

Arvind K Bansal

Microbial Cell Factories • 2005

Abstract The revolutionary growth in the computation speed and memory storage capability has fueled a new era in the analysis of biological data. Hundreds of microbial genomes and many eukaryotic genomes including a cleaner draft of human genome have been sequenced raising the expectation of better control of microorganisms. The goals are as lofty as the development of rational drugs and antimicrobial agents, development of new enhanced bacterial strains for bioremediation and pollution control, development of better and easy to administer vaccines, the development of protein biomarkers for various bacterial diseases, and better understanding of host-bacteria interaction to prevent bacterial infections. In the last decade the development of many new bioinformatics techniques and integrated databases has facilitated the realization of these goals. Current research in bioinformatics can be classified into: (i) genomics – sequencing and comparative study of genomes to identify gene and genome functionality, (ii) proteomics – identification and characterization of protein related properties and reconstruction of metabolic and regulatory pathways, (iii) cell visualization and simulation to study and model cell behavior, and (iv) application to the development of drugs and anti-microbial agents. In this article, we will focus on the techniques and their limitations in genomics and proteomics. Bioinformatics research can be classified under three major approaches: (1) analysis based upon the available experimental wet-lab data, (2) the use of mathematical modeling to derive new information, and (3) an integrated approach that integrates search techniques with mathematical modeling. The major impact of bioinformatics research has been to automate the genome sequencing, automated development of integrated genomics and proteomics databases, automated genome comparisons to identify the genome function, automated derivation of metabolic pathways, gene expression analysis to derive regulatory pathways, the development of statistical techniques, clustering techniques and data mining techniques to derive protein-protein and protein-DNA interactions, and modeling of 3D structure of proteins and 3D docking between proteins and biochemicals for rational drug design, difference analysis between pathogenic and non-pathogenic strains to identify candidate genes for vaccines and anti-microbial agents, and the whole genome comparison to understand the microbial evolution. The development of bioinformatics techniques has enhanced the pace of biological discovery by automated analysis of large number of microbial genomes. We are on the verge of using all this knowledge to understand cellular mechanisms at the systemic level. The developed bioinformatics techniques have potential to facilitate (i) the discovery of causes of diseases, (ii) vaccine and rational drug design, and (iii) improved cost effective agents for bioremediation by pruning out the dead ends. Despite the fast paced global effort, the current analysis is limited by the lack of available gene-functionality from the wet-lab data, the lack of computer algorithms to explore vast amount of data with unknown functionality, limited availability of protein-protein and protein-DNA interactions, and the lack of knowledge of temporal and transient behavior of genes and pathways.

Godfrey Kyazze, Arseniy Popov, Richard Dinsdale et al.

International Journal of Hydrogen Energy • 2010

Kyu-Jung Chae, Mi-Jin Choi, Kyoung-Yeol Kim et al.

Environmental Science & Technology • 2009

Hongqiang Hu, Yanzhen Fan, Hong Liu

Water Research • 2008

Microbial electrohydrogenesis provides a new approach for hydrogen generation from renewable biomass. Membranes were used in all the reported microbial electrolysis cells (MECs) to separate the anode and cathode chambers. To reduce the potential losses associated with membrane and increase the energy recovery of this process, single-chamber membrane-free MECs were designed and used to investigate hydrogen production by one mixed culture and one pure culture: Shewanella oneidensis MR-1. At an applied voltage of 0.6 V, this system with a mixed culture achieved a hydrogen production rate of 0.53 m(3)/day/m(3) (0.11 m(3)/day/m(2)) with a current density of 9.3A/m(2) at pH 7 and 0.69 m(3)/day/m(3) (0.15m(3)/day/m(2)) with a current density of 14 A/m(2) at pH 5.8. Stable hydrogen production from lactic acid by S. oneidensis was also observed. Methane was detected during the hydrogen production process with the mixed culture and negatively affected hydrogen production rate. However, by employing suitable approaches, such as exposure of cathodes to air, the hydrogenotrophic methanogens can be suppressed. The current density and volumetric hydrogen production rate of this system have potential to increase significantly by further reducing the electrode spacing and increasing the ratio of electrode surface area/cell volume.

Aijie Wang, Lihong Liu, Dan Sun et al.

International Journal of Hydrogen Energy • 2010

Peter Clauwaert, Willy Verstraete

Applied Microbiology and Biotechnology • 2009

S. Hrapovic, M.-F. Manuel, J.H.T. Luong et al.

International Journal of Hydrogen Energy • 2010

Kun Guo, Xinhua Tang, Zhuwei Du et al.

Biochemical Engineering Journal • 2010

Lu Lu, Nanqi Ren, Defeng Xing et al.

Biosensors and Bioelectronics • 2009

Hydrogen can be produced by bacterial fermentation of sugars, but substrate conversion to hydrogen is incomplete. Using a single-chamber microbial electrolysis cell (MEC), we show that additional hydrogen can be produced from the effluent of an ethanol-type dark-fermentation reactor. An overall hydrogen recovery of 83+/-4% was obtained using a buffered effluent (pH 6.7-7.0), with a hydrogen production rate of 1.41+/-0.08 m(3) H(2)/m(3) reactor/d, at an applied voltage of E(ap)=0.6 V. When the MEC was combined with the fermentation system, the overall hydrogen recovery was 96%, with a production rate of 2.11 m(3) H(2)/m(3)/d, corresponding to an electrical energy efficiency of 287%. High cathodic hydrogen recoveries (70+/-5% to 94+/-4%) were obtained at applied voltages of 0.5-0.8 V due to shorter cycle times, and repression of methanogen growth through exposure of the cathode to air after each cycle. Addition of a buffer to the fermentation effluent was critical to MEC performance as there was little hydrogen production using unbuffered effluent (0.0372 m(3) H(2)/m(3)/d at E(ap)=0.6 V, pH 4.5-4.6). These results demonstrate that hydrogen yields from fermentation can be substantially increased by using MECs.

W.Z. Liu, A.J. Wang, D. Sun et al.

Journal of Biotechnology • 2010

Adriaan W. Jeremiasse, Hubertus V.M. Hamelers, Michel Saakes et al.

International Journal of Hydrogen Energy • 2010

Leonardo DeSilva Munoz, Benjamin Erable, Luc Etcheverry et al.

Electrochemistry Communications • 2010

A. Escapa, M.-F. Manuel, A. Morán et al.

Energy & Fuels • 2009

Hyung-Sool Lee, Bruce E. Rittmann

Environmental Science & Technology • 2009

B TARTAKOVSKY, M MANUEL, H WANG et al.

International Journal of Hydrogen Energy • 2008

Hyung-Sool Lee, Bruce E. Rittmann

International Journal of Hydrogen Energy • 2010