The renaissance of continuous culture in the post-genomics age

Bull, Alan T.

doi:10.1007/s10295-010-0816-4

Cited by 106 publications

(89 citation statements)

References 170 publications

(208 reference statements)

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“…Chemostat cultivation was specifically chosen to provide a well-defined physiological state, which eliminates confounding variables that often complicate transcriptome analyses (Wu et al, 2004;Bull, 2010). In chemostats, Synechococcus 7002 and Shewanella W3-18-1 were grown in the basal medium A in the absence of Tris HCl using 8 mM NaHCO 3 and 5 mM D,L-Na lactate, respectively, as the sole source of carbon.…”

Section: Chemostat Cultivationmentioning

confidence: 99%

Inference of interactions in cyanobacterial–heterotrophic co-cultures via transcriptome sequencing

et al. 2014

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We used deep sequencing technology to identify transcriptional adaptation of the euryhaline unicellular cyanobacterium Synechococcus sp. PCC 7002 and the marine facultative aerobe Shewanella putrefaciens W3-18-1 to growth in a co-culture and infer the effect of carbon flux distributions on photoautotroph-heterotroph interactions. The overall transcriptome response of both organisms to co-cultivation was shaped by their respective physiologies and growth constraints. Carbon limitation resulted in the expansion of metabolic capacities, which was manifested through the transcriptional upregulation of transport and catabolic pathways. Although growth coupling occurred via lactate oxidation or secretion of photosynthetically fixed carbon, there was evidence of specific metabolic interactions between the two organisms. These hypothesized interactions were inferred from the excretion of specific amino acids (for example, alanine and methionine) by the cyanobacterium, which correlated with the downregulation of the corresponding biosynthetic machinery in Shewanella W3-18-1. In addition, the broad and consistent decrease of mRNA levels for many Fe-regulated Synechococcus 7002 genes during co-cultivation may indicate increased Fe availability as well as more facile and energy-efficient mechanisms for Fe acquisition by the cyanobacterium. Furthermore, evidence pointed at potentially novel interactions between oxygenic photoautotrophs and heterotrophs related to the oxidative stress response as transcriptional patterns suggested that Synechococcus 7002 rather than Shewanella W3-18-1 provided scavenging functions for reactive oxygen species under co-culture conditions. This study provides an initial insight into the complexity of photoautotrophic-heterotrophic interactions and brings new perspectives of their role in the robustness and stability of the association.

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Section: Chemostat Cultivationmentioning

confidence: 99%

Inference of interactions in cyanobacterial–heterotrophic co-cultures via transcriptome sequencing

et al. 2014

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“…This perspective of cellular energetics has broad-ranging applications, from interpreting the metabolic drivers of food or biofuel production efficiency to understanding the energetics of human pathogens (22). Here we will use the Pirt model to phenomenologically motivate a relationship between single-cell growth and metabolic allocation, drawing analogies with population studies.…”

Section: Metabolic Perspectivesmentioning

confidence: 99%

Growth, metabolic partitioning, and the size of microorganisms

Kempes

Dutkiewicz

Follows

2011

Proc. Natl. Acad. Sci. U.S.A.

119

214

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Population growth rate is a fundamental ecological and evolutionary characteristic of living organisms, but individuals must balance the metabolism devoted to biosynthesis and reproduction against the maintenance of existing structure and other functionality. Here we present a mathematical model that relates metabolic partitioning to the form of growth. The model captures the observed growth trajectory of single cells and individuals for a variety of species and taxa spanning prokaryotes, unicellular eukaryotes, and small multicellular eukaryotes. Our analysis suggests that the per-unit costs of biosynthesis and maintenance are conserved across prokaryotes and eukaryotes. However, the relative metabolic expenditure on growth and maintenance of whole organisms clearly differentiates taxa: prokaryotes spend an increasing fraction of their entire metabolism on growth with increasing cell size, whereas eukaryotes devote a diminishing fraction. These differences allow us to predict the minimum and maximum size for each taxonomic group, anticipating observed evolutionary life-history transitions. The framework provides energetic insights into taxonomic tradeoffs related to growth and metabolism and constrains traits that are important for sizestructured modeling of microbial communities and their ecological and biogeochemical effects.evolutionary transitions | single cell growth | metabolic ecology | maintenance metabolism | ontogenetic growth

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“…which is invariant with respect to (5). We are now in position to state the optimal control problem.…”

Section: Hypothesismentioning

confidence: 99%

Optimization of the separation of two species in a chemostat

Bayen

Mairet

2014

Automatica

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In this work, we study a two species chemostat model with one limiting substrate, and our aim is to optimize the selection of the species of interest. More precisely, the objective is to find an optimal feeding strategy in order to reach in minimal time a target where the concentration of the first species is significantly larger than the concentration of the other one. Thanks to Pontryagin maximum principle, we introduce a singular feeding strategy which allows to reach the target, and we prove that the feedback control provided by this strategy is optimal whenever initial conditions are chosen in the invariant attractive manifold of the system. The optimal synthesis of the problem in presence of more than one singular arc and for initial conditions outside this set is also investigated.

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The renaissance of continuous culture in the post-genomics age

Cited by 106 publications

References 170 publications

Inference of interactions in cyanobacterial–heterotrophic co-cultures via transcriptome sequencing

Inference of interactions in cyanobacterial–heterotrophic co-cultures via transcriptome sequencing

Growth, metabolic partitioning, and the size of microorganisms

Optimization of the separation of two species in a chemostat

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