From single cells to microbial population dynamics: modelling in biotechnology based on measurements of individual cells

Heterogeneity in Pure Microbial Systems: Experimental Measurements and Modeling

Cellular heterogeneity influences bioprocess performance in ways that until date are not completely elucidated. In order to account for this phenomenon in the design and operation of bioprocesses, reliable analytical and mathematical descriptions are required. We present an overview of the single cell analysis, and the mathematical modeling frameworks that have potential to be used in bioprocess control and optimization, in particular for microbial processes. In order to be suitable for bioprocess monitoring, experimental methods need to be high throughput and to require relatively short processing time. One such method used successfully under dynamic conditions is flow cytometry. Population balance and individual based models are suitable modeling options, the latter one having in particular a good potential to integrate the various data collected through experimentation. This will be highly beneficial for appropriate process design and scale up as a more rigorous approach may prevent a priori unwanted performance losses. It will also help progressing synthetic biology applications to industrial scale.

Ramified Challenges: Monitoring and Modeling of Hairy Root Growth in Bioprocesses--A Review

The review presents a comprehensive overview on available solutions for the monitoring and modeling of various aspects of hairy root growth processes. Several online and offline measurement principles get explained exemplary and are being compared. It was found that no direct online measurement principle for hairy root biomass in submerged and solid-state culturing environment is available. However, certain indirect methods involving one or more measurement values have been developed for biomonitoring of hairy roots especially in bioreactors. In the field of modeling of hairy root growth processes, four independent architectures (continuous models, metabolic flux analysis, agent-based models, and artificial neural networks) are described and compared including literature references. The discussion is structured into microscopic model approaches, addressing only certain aspects of growth, and macroscopic model approaches, describing the hairy root network as a whole. An agent-based macroscopic model based on phenomenological data acquired with systematic imaging of hairy roots on culture dishes together with a 3D visualization of simulation results is presented in detail.

Diversity and space-time dynamics of endophytic archaea from sugar beet in the north slope of Tianshan Mountain revealed by 454 pyrosequencing and T-RFLP

Plants harbor complex and variable microbial communities. Using molecular-based techniques targeting the 16S rRNA gene, we studied the developmental stages and geographical location diversity of endophytic archaea in two locations (Shihezi and Changji) and four periods (the seedling growth, rosette formation, tuber growth and sucrose accumulation sampling periods) in the north slope of Tianshan Mountain, China. Community structure of mixed sample from 60 sugar beet plants was examined using PCR-based 454 pyrosequencing and terminal restriction fragment length polymorphism (T-RFLP). In total, 5290 archaea 16S rRNA sequences were obtained from all sugar beet samples. The most abundant archaea groups in all sugar beet were Methanococci, the miscellaneous Crenarchaeotic Group and Thermoplasmata. There was a marked difference in diversity of endophytic archaea in sugar beet for different growth periods. The greatest number of Operational T-RFLP Units (OTUs) was detected during sucrose accumulation (298) and rosette formation (282). Endophytic archaea diversity was reduced during seedling growth (128 OTUs) and tuber growth (55 OTUs). Nine OTUs were common to all four periods of growth. There were more OTUs in Shihezi than in Changji. Clustering analysis and principal component analysis of T-RFLP data revealed distinct shifts in endophytic archaea community profiles that corresponded to plant growth stage rather than geographical location. The dynamics of endophytic archaea communities were influenced by plant growth stage. To our knowledge, this is the first report that archaea has been identified as endophytes associated with sugar beet by the culture-independent approach. The results suggest that the diversity of endophytic archaea is abundant in sugar beet.