Introduction 1916 1987 1997 2005 2005 1984 1994 2005 1990 2000 2004 2002 2002 2004 4 2 2 1995 1997 1999 2001 1990 1999 2002 2004 2003 2002 2005 2 2002 Systems biology seeks to integrate high-throughput and comprehensive analytical techniques such as DNA and RNA microarrays, proteomics and protein interaction analyses, and metabolite measurements with computational biology (i.e., modeling) to describe the structure of the system and responses to individual perturbations. Such knowledge can be used, for example, to predict systems level responses to environmental changes/perturbations. In our opinion, a key element of systems microbiology research is the use of controlled cultivation techniques to generate samples under well-defined conditions where variations in intra- as well as inter-culture variability, are minimized. 2002 2005 2002 2002 2004 2005 2006 2006 Materials and methods Materials 2 Cell cultivation and harvesting Shake flask cultures Shewanella oneidensis 2005 600 2 2005 http://www.sartorius.com/ g g Controlled batch cultures 2 2 2 2 600 Chemostat cultures 600 Organic acid quantitation 2 4 2 4 2002 2004 2D-gel proteomic analysis g 1985 1978a 1975 1978b 1991 t 1991 18 1994 2002 S. oneidensis  Mass spectrometry proteomic analysis Cell lysis and tryptic digestion 2005 2 Mass spectrometric analysis 2005 2001 2002 2005 2002 2005 1994 2005 5 2005 Results Effect of cultivation method on growth and metabolism 2 1 2 1 2  1 2 Fig. 1 right S. oneidensis a 2 dark filled diamond, open diamond dark filled triangle, open triangle b c, d dark filled diamond, open diamond dark filled square, open square dark filled triangle, open triangle  1 2 2 1 2 1 2 2 2 1 Relating cultivation data to metabolic activity 2 2 2 2 2 1 2 2 Fig. 2 a b c S. oneidensis a dark filled square dark filled circle dark filled triangle b 2 c dark filled diamond dark filled square dark filled triangle 2 solid arrow broken arrow  2 2 2 2 2 2 2 2 2 Correlating protein expression with culture conditions 1992 2003 c 2002 2005 2006 2003 3 1 2 Fig. 3 S. oneidensis spot number 1 right left top bottom  Table 1 Differential protein detection between flask and controlled batch cultures as determined by 2DE and MS ORF Protein name Spot number 2DE MS Avg flask Avg CB P Flask/CB ratio Avg flask Avg CB Flask/CB ratio SO0970 Fumarate reductase 432 4900 ND – – 106 ± 34 b 6.3 SO4349 Ketol-acid reductoisomerase 636 1148 3150 0.003 0.4 22 ± 6 139 ± 26 0.2 SO1931 2-Oxoglutarate dehydrogenase 763 a 951 a 0.5 36 ± 1 46 ± 4 0.8 SO3237 Flagellin 999 2711 1223 9.9E-05 2.2 108 ± 36 73 ± 14 1.5 – ND 1048 1196 196 8.8E-04 6.1 – – – SO3549 Hypothetical protein 1275 648 ND – – – – – SO3681 Universal stress protein family 1382 2600 701 3.5E-06 3.7 51 ± 12 13 ± 2 3.9 – ND 1426 313 ND – – – – – SO1673 OmpW 1945 2927 ND – – 62 ± 24 8 ± 1 8.1 SO4410 Glutamine synthetase, type I 1946 1001 1747 1.8E-04 0.6 58 ± 12 63 ± 3 0.9 SO1776 MtrB      7 ± 1 4 ± 1 2.1 SO1777 c      8 ± 1 2 ± 0 5.5 SO1778 c      36 ± 6 18 ± 1 2.0 SO1779 c      21 ± 3 11 ± 1 1.9 ORF Protein name Spot number 3 5 Avg flask Avg CB P value P t Flask/CB ratio a b Chemostats provide enhanced experimental consistency 1950 1950 1985  oneidensis 2 600 nm 4 Fig. 4 Shewanella oneidensis  2  Culture and proteome variability t 1991 5 P P Fig. 5 P P SS CB right left top bottom  6 5 5 5 5 2 Fig. 6 left middle right a c e b d f a, c, e b, d, f  Discussion 1994 2004 2005 2006 2006 1984 1990 2005 2002 2 2 S. oneidensis  2 2007 2 2 S. oneidensis 1989 1992 2 S. oneidensis 2004 2002 2005 2006 1998 2001 2002 2003 2006 Achieving a systems-level understanding of microorganisms, including the underlying metabolic and regulatory networks that control cell physiology and the ability to predict responses to perturbations, is indeed an ambitious goal. Systems biology takes full advantage of the state-of-the-science technology and genomic information, with the scientific as well as the practical benefits expected to be plentiful. Our results emphasize that functional genomics can greatly benefit from well-defined and homogeneous cell cultures provided by controlled cultivation techniques. The use of controlled cultivation techniques ensures that the large and comprehensive datasets used in systems biology research are derived from well-characterized and homogeneous biological samples, thus reducing the inherent variability that often complicates drawing biological conclusions and will allow for more accurate and robust identifications of metabolic and regulatory networks.