Sensitivity of Colletotrichum nymphaeae to six fungicides and characterization of fludioxonil resistant isolates in China

Colletotrichum nymphaeae is the dominant species causing anthracnose disease of peach in China. In this study, 140 isolates of C. nymphaeae were assessed for their sensitivity to six fungicides. It was found that C. nymphaeae was highly resistant to carbendazim, procymidone and boscalid but sensitive to pyraclostrobin and prochloraz. For fludioxonil, the fungus exhibited differential sensitivities, i.e., approximately 14% of isolates were resistant to fludioxonil and the resistance was stable. Fludioxonil-resistant isolates had a mean EC50 value of 2.2380 µg/ml, while the mean EC50 value was 0.0194 µg/ml in fludioxonil-sensitive isolates. The mean EC50 values of C. nymphaeae for pyraclostrobin and prochloraz were 0.0083 µg/ml and 0.002 µg/ml, respectively. No cross-resistance was observed between fungicides from different groups. Mycelial growth rate, control efficacy and osmotic stress responses were significantly different (P < 0.05) between fludioxonil sensitive (FluS) and resistant (FluR) isolates, but no significant difference was observed (P > 0.05) in virulence and sporulation between FluS and FluR isolates. No mutation was detected in coding regions of the CnOs-1, Cal, Hk1, Hog1, TPI and Mrr1 genes. Interestingly, with fludioxonil treatment, the expression of ABC transporter gene atrB was significantly over-expressed in some resistant isolates. However, over-expression of the atrB gene was not detected in one moderately and one highly resistant isolate, indicating that other unknown mechanisms may be involved. Current findings uncovered several effective chemicals and provided the foundation to design management strategies to practically control peach anthracnose with the most effective DMI and QoI fungicides.

Stabilisation of Antithetic Control via Molecular Buffering

A key goal in synthetic biology is the construction of molecular circuits that robustly adapt to perturbations. Although many natural systems display perfect adaptation, whereby stationary molecular concentrations are insensitive to perturbations, its de novo engineering has proven elusive. The discovery of the antithetic control motif was a significant step toward a universal mechanism for engineering perfect adaptation. Antithetic control provides perfect adaptation in a wide range of systems, but it can lead to oscillatory dynamics due to loss of stability, and moreover, it can lose perfect adaptation in fast growing cultures. Here, we introduce an extended antithetic control motif that resolves these limitations. We show that molecular buffering, a widely conserved mechanism for homeostatic control in nature, stabilises oscillations and allows for near-perfect adaptation during rapid growth. We study multiple buffering topologies and compare their performance in terms of their stability and adaptation properties. We illustrate the benefits of our proposed strategy in exemplar models for biofuel production and growth rate control in bacterial cultures. Our results provide an improved circuit for robust control of biomolecular systems.

Adaptive Control of Biomass Specific Growth Rate in Fed-Batch Biotechnological Processes. A Comparative Study

This article presents a comparative study on the development and application of two distinct adaptive control algorithms for biomass specific growth rate control in fed-batch biotechnological processes. A typical fed-batch process using Escherichia coli for recombinant protein production was selected for this research. Numerical simulation results show that both developed controllers, an adaptive PI controller based on the gain scheduling technique and a model-free adaptive controller based on the artificial neural network, delivered a comparable control performance and are suitable for application when using the substrate limitation approach and substrate feeding rate manipulation. The controller performance was tested within the realistic ranges of the feedback signal sampling intervals and measurement noise intensities. Considering the efforts for controller design and tuning, including development of the adaptation/learning algorithms, the model-free adaptive control algorithm proves to be more attractive for industrial applications, especially when only limited knowledge of the process and its mathematical model is available. The investigated model-free adaptive controller also tended to deliver better control quality under low specific growth rate conditions that prevail during the recombinant protein production phase. In the investigated simulation runs, the average tracking error did not exceed 0.01 (1/h). The temporary overshoots caused by the maximal disturbances stayed within the range of 0.025–0.11 (1/h). Application of the algorithm can be further extended to specific growth rate control in other bacterial and mammalian cell cultivations that run under substrate limitation conditions.

Practical Solutions for Specific Growth Rate Control Systems in Industrial Bioreactors

This contribution discusses the main challenges related to successful application of automatic control systems used to control specific growth rate in industrial biotechnological processes. It is emphasized that, after the implementation of basic automatic control systems, primary attention shall be paid to the specific growth rate control systems because this process variable critically affects the physiological state of microbial cultures and the formation of the desired product. Therefore, control of the specific growth rate enables improvement of the quality and reproducibility of the biotechnological processes. The main requirements have been formulated that shall be met to successfully implement the specific growth rate control systems in industrial bioreactors. The relatively easy-to-implement schemes of specific growth rate control systems have been reviewed and discussed. The recommendations for selection of particular control systems for specific biotechnological processes have been provided.

The Effects of Surface Kinetics on Crystal Growth and Homogeneous Freezing in Parcel Simulations of Cirrus

The uptake of water vapor excess by ice crystals is a key process regulating the supersaturation in cold clouds. Both the ice crystal number concentration and depositional growth rate control the vapor uptake rate and are sensitive to the deposition coefficient . The deposition coefficient depends on temperature and supersaturation; however, cloud models either ignore or assume a constant . In this study, the effects of on crystal growth and homogeneous freezing of haze solution drops in simulated cirrus are examined. A Lagrangian parcel model is used with a new ice growth model that predicts the deposition coefficients along two crystal growth axes. Parcel model results indicate that predicting can be critical for predicting ice nucleation and supersaturation at different stages of cloud development. At cloud base, model results show that surface kinetics constrain the homogeneous freezing rate primarily through the growth impact of small particle sizes in comparison to the mean free path. The deposition coefficient has little effect on homogeneous freezing rates, because the high cloud-base supersaturation produces near unity. Above the cloud-base nucleation zone, decreasing supersaturation causes to decrease to values as low as 0.001. These low values of lead to higher steady-state supersaturation. Also, the low values of produce substantial impacts on particle shape evolution and particle size, both of which are dependent on updraft strength.