A diurnal flux balance model of Synechocystis sp. PCC 6803 metabolism

Abstract

Phototrophic organisms such as cyanobacteria utilize the sun’s energy to convert atmospheric carbon dioxide into organic carbon, resulting in diurnal variations in the cell’s metabolism. Flux balance analysis is a widely accepted constraint-based optimization tool for analyzing growth and metabolism, but it is generally used in a time-invariant manner with no provisions for sequestering different biomass components at different time periods. Here we present CycleSyn, a periodic model of Synechocystis sp. PCC 6803 metabolism that spans a 12-hr light/12-hr dark cycle by segmenting it into 12 Time Point Models (TPMs) with a uniform duration of two hours. The developed framework allows for the flow of metabolites across TPMs while inventorying metabolite levels and only allowing for the utilization of currently or previously produced compounds. The 12 TPMs allow for the incorporation of time-dependent constraints that capture the cyclic nature of cellular processes. Imposing bounds on reactions informed by temporally-segmented transcriptomic data enables simulation of phototrophic growth as a single linear programming (LP) problem. The solution provides the time varying reaction fluxes over a 24-hour cycle and the accumulation/consumption of metabolites. The diurnal rhythm of metabolic gene expression driven by the circadian clock and its metabolic consequences is explored. Predicted flux and metabolite pools are in line with published studies regarding the temporal organization of phototrophic growth in Synechocystis PCC 6803 paving the way for constructing time-resolved genome-scale models (GSMs) for organisms with a circadian clock. In addition, the metabolic reorganization that would be required to enable Synechocystis PCC 6803 to temporally separate photosynthesis from oxygen-sensitive nitrogen fixation is also explored using the developed model formalism.

A comprehensive time‐course metabolite profiling of the model cyanobacterium Synechocystis sp. PCC 6803 under diurnal light:dark cycles

“…6803) is decreased in diurnal light:dark (LD) cycles as compared with CL (Cheah et al ., ). Thus, it is important to understand how metabolism changes under realistic light conditions to appropriately engineer industrial production strains (Peers, ), and has only very recently been addressed in the field (Broddrick et al ., ; Sarkar et al ., ).…”

An integrated computational and experimental study to investigate Staphylococcus aureus metabolism

“…At this step, the model was checked for erroneous generation of energetic cofactors and confirmed that it could not produce unlimited amount of them without any nutrient input, as described by Zomorrodi and Maranas 53 and followed in previous modeling studies by us [54][55][56][57][58] and other groups. 59,60 The annotation of S. aureus USA300_FPR3757 genome in the KEGG database was next used to bridge several network gaps in the model. At this stage, the model contained 528 blocked reactions compared with 784 in the preliminary reconstruction.…”

Integration of Time-Series Transcriptomic Data with Genome-Scale CHO Metabolic Models for mAb Engineering

“…The constraint model accurately predicted the growth rate under heterotrophic and photoautotrophic conditions [42]. Another study conducted by Sarkar et al (2019) developed a diurnal flux balance model that enabled considerations of varying nature of metabolism and different biomass composition under diurnal variations in phototrophic organisms [43]. Lachance et al (2019) recently developed a software package to define a biomass objective function from experimental data, for example, the multiple omic datasets.…”