Cells by Design: A Mini-Review of Targeting Cell Engineering Using DNA Microarrays
Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218, USA. Molecular Biotechnology
(Impact Factor: 1.88).
07/2008; 39(2):105-11. DOI: 10.1007/s12033-008-9048-5
Recent studies have demonstrated the utility of DNA microarray technology in engineering cellular properties. For instance, cellular adhesion, the necessity of cells to attach to a surface in order to to proliferate, was examined by comparing two distinct HeLa cell lines. Two genes, one encoding a type II membrane glycosylating sialyltransferase (siat7e) and the other encoding a secreted glycoprotein (lama4), were found to influence adhesion. The expression of siat7e correlated with reduced adhesion, whereas expression of lama4 correlated with increased adhesion, as shown by various assays. In a separate example, a gene encoding a mitochondrial assembly protein (cox15) and a gene encoding a kinase (cdkl3), were found to influence cellular growth. Enhanced expression of either gene resulted in slightly higher specific growth rates and higher maximum cell densities for HeLa, HEK-293, and CHO cell lines. Another investigated property was the adaptation of HEK-293 cells to serum-free media. The genes egr1 and gas6, both with anti-apoptotic properties, were identified as potentially improving adaptability by impacting viability at low serum levels. In trying to control apoptosis, researchers found that by altering the expression levels of four genes faim, fadd, alg-2, and requiem, apoptotic response could be altered. In the present work, these and related studies in microorganisms (prokaryote and eukaryote) are examined in greater detail focusing on the approach of using DNA microarrays to direct cellular behavior by targeting select genes.
Available from: ncbi.nlm.nih.gov
- "Over the past decade, new tools and strategies for engineering microorganisms have appeared including loss-of-function gene mutations (i.e., gene knock-outs) (Bailey, 1991; Lee et al., 2007; Lee et al., 2005a; Park et al., 2007; Trinh et al., 2006; Trinh et al., 2008), overexpression of gene products (Altaras and Cameron, 1999; Bailey, 1991; Park et al., 2007; Zhang et al., 2007), and introduction of homologous DNA for new or improved functionalities of cells. Today, an increasing amount of success has been achieved by rationally designing strains using these readily available methods (Jaluria et al., 2008; Santos and Stephanopoulos, 2008; Tyo et al., 2007). However, it is difficult to identify an optimal strain by rational design alone, as several parameters that should be considered simultaneously in designs are difficult to predict without a computational approach. "
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ABSTRACT: Integrated approaches utilizing in silico analyses will be necessary to successfully advance the field of metabolic engineering. Here, we present an integrated approach through a systematic model-driven evaluation of the production potential for the bacterial production organism Escherichia coli to produce multiple native products from different representative feedstocks through coupling metabolite production to growth rate. Designs were examined for 11 unique central metabolism and amino acid targets from three different substrates under aerobic and anaerobic conditions. Optimal strain designs were reported for designs which possess maximum yield, substrate-specific productivity, and strength of growth-coupling for up to 10 reaction eliminations (knockouts). In total, growth-coupled designs could be identified for 36 out of the total 54 conditions tested, corresponding to eight out of the 11 targets. There were 17 different substrate/target pairs for which over 80% of the theoretical maximum potential could be achieved. The developed method introduces a new concept of objective function tilting for strain design. This study provides specific metabolic interventions (strain designs) for production strains that can be experimentally implemented, characterizes the potential for E. coli to produce native compounds, and outlines a strain design pipeline that can be utilized to design production strains for additional organisms.
Available from: Kong-Peng Lam
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ABSTRACT: Fas-apoptosis inhibitory molecule (FAIM) is inducibly expressed in B lymphocytes and had been shown to antagonize Fas-mediated killing of B-cell lines in vitro. However, its mechanism and role in vivo are unknown. We have generated faim(-/-) mice and found these mutants to be viable. In contrast to fas(-/-) mice, faim(-/-) mice have normal B- and T-cell populations. However, faim(-/-) B cells and thymocytes show increased sensitivity to Fas-triggered apoptosis in vitro, and faim(-/-) mice suffer greater mortality and exhibit exacerbated liver damage in response to Fas (CD95) engagement in vivo. The lack of FAIM results in greater activation of caspase-8 and -3 in Fas-stimulated thymocytes. Detailed biochemical analyses further reveal the decreased expression of c-FLIP(L) and c-FLIP(R) in faim(-/-) thymocytes and increased association of caspase-8 with Fas in Fas-activated mutant cells. Decreased levels of c-FLIP(L) and c-FLIP(R) are also evident in faim(-/-) liver. Thus, FAIM plays a novel role in modulating Fas-mediated apoptosis and acts through influencing the expression of c-FLIP and regulating the physical binding of caspase-8 to Fas.
Available from: Martin Dragosits
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ABSTRACT: Systems biotechnology has been established as a highly potent tool for bioprocess development in recent years. The applicability to complex metabolic processes such as protein synthesis and secretion, however, is still in its infancy. While yeasts are frequently applied for heterologous protein production, more progress in this field has been achieved for bacterial and mammalian cell culture systems than for yeasts. A critical comparison between different protein production systems, as provided in this review, can aid in assessing the potentials and pitfalls of applying systems biotechnology concepts to heterologous protein producing yeasts. Apart from modelling, the methodological basis of systems biology strongly relies on postgenomic methods. However, this methodology is rapidly moving so that more global data with much higher sensitivity will be achieved in near future. The development of next generation sequencing technology enables an unexpected revival of genomic approaches, providing new potential for evolutionary engineering and inverse metabolic engineering.
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