Three‐dimensional neural differentiation of embryonic stem cells with ACM induction in microfibrous matrices in bioreactors

The clinical use of pluripotent stem cell (PSC)‐derived neural cells requires an efficient differentiation process for mass production in a bioreactor. Toward this goal, neural differentiation of murine embryonic stem cells (ESCs) in three‐dimensional (3D) polyethylene terephthalate microfibrous matrices was investigated in this study. To streamline the process and provide a platform for process integration, the neural differentiation of ESCs was induced with astrocyte‐conditioned medium without the formation of embryoid bodies, starting from undifferentiated ESC aggregates expanded in a suspension bioreactor. The 3D neural differentiation was able to generate a complex neural network in the matrices. When compared to 2D differentiation, 3D differentiation in microfibrous matrices resulted in a higher percentage of nestin‐positive cells (68% vs. 54%) and upregulated gene expressions of nestin, Nurr1, and tyrosine hydroxylase. High purity of neural differentiation in 3D microfibrous matrix was also demonstrated in a spinner bioreactor with 74% nestin + cells. This study demonstrated the feasibility of a scalable process based on 3D differentiation in microfibrous matrices for the production of ESC‐derived neural cells. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 29:1013–1022, 2013     

A dynamic metabolic flux balance based model of fed‐batch fermentation of bordetella pertussis

A mathematical model based on a dynamic metabolic flux balance (DMFB) is developed for a process of fed‐batch fermentation of Bordetella pertussis. The model is based on the maximization of growth rate at each time interval subject to stoichiometric constraints. The model is calibrated and verified with experimental data obtained in two different bioreactor experimental systems. It was found that the model calibration was mostly sensitive to the consumption or production rates of tyrosine and, for high supplementation rates, to the consumption rate of glutamate. Following this calibration the model correctly predicts biomass and by‐products concentrations for different supplementation rates. Comparisons of model predictions to oxygen uptake and carbon emission rates measurements indicate that the TCA cycle is fully functional. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 29: 520–531, 2013     

Continuous rhamnolipid production using denitrifying Pseudomonas aeruginosa cells in hollow‐fiber bioreactor

Rhamnolipids are high‐value effective biosurfactants produced by Pseudomonas aeruginosa. Large‐scale production of rhamnolipids is still challenging especially under free‐cell aerobic conditions in which the highly foaming nature of the culture broth reduces the productivity of the process. Immobilized systems relying on oxygen as electron acceptor have been previously investigated but oxygen transfer limitation presents difficulties for continuous rhamnolipid production. A coupled system using immobilized cells and nitrate instead of oxygen as electron acceptor taking advantage of the ability of P. aeruginosa to perform nitrate respiration was evaluated. This denitrification‐based immobilized approach based on a hollow‐fiber setup eliminated the transfer limitation problems and was found suitable for continuous rhamnolipid production in a period longer than 1,500 h. It completely eliminated the foaming difficulties related to aerobic systems with a comparable specific productivity of 0.017 g/(g dry cells)‐h and allowed easy recovery of rhamnolipids from the cell‐free medium. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 29: 346–351, 2013     

Dissecting the energy metabolism in Mycoplasma pneumoniae through genome‐scale metabolic modeling

Mycoplasma pneumoniae, a threatening pathogen with a minimal genome, is a model organism for bacterial systems biology for which substantial experimental information is available. With the goal of understanding the complex interactions underlying its metabolism, we analyzed and characterized the metabolic network of M. pneumoniae in great detail, integrating data from different omics analyses under a range of conditions into a constraint‐based model backbone. Iterating model predictions, hypothesis generation, experimental testing, and model refinement, we accurately curated the network and quantitatively explored the energy metabolism. In contrast to other bacteria, M. pneumoniae uses most of its energy for maintenance tasks instead of growth. We show that in highly linear networks the prediction of flux distributions for different growth times allows analysis of time‐dependent changes, albeit using a static model. By performing an in silico knock‐out study as well as analyzing flux distributions in single and double mutant phenotypes, we demonstrated that the model accurately represents the metabolism of M. pneumoniae. The experimentally validated model provides a solid basis for understanding its metabolic regulatory mechanisms.     

Promoters maintain their relative activity levels under different growth conditions

Most genes change expression levels across conditions, but it is unclear which of these changes represents specific regulation and what determines their quantitative degree. Here, we accurately measured activities of ～900 S. cerevisiae and ～1800 E. coli promoters using fluorescent reporters. We show that in both organisms 60–90% of promoters change their expression between conditions by a constant global scaling factor that depends only on the conditions and not on the promoter's identity. Quantifying such global effects allows precise characterization of specific regulation—promoters deviating from the global scale line. These are organized into few functionally related groups that also adhere to scale lines and preserve their relative activities across conditions. Thus, only several scaling factors suffice to accurately describe genome‐wide expression profiles across conditions. We present a parameter‐free passive resource allocation model that quantitatively accounts for the global scaling factors. It suggests that many changes in expression across conditions result from global effects and not specific regulation, and provides means for quantitative interpretation of expression profiles.     

Population specific fitness response of Drosophila subobscura to lead pollution

Abstract Differences in heavy metal tolerance among separate populations of the same species have often been interpreted as local adaptation. Persistence of differences after removing the stressor indicates that mechanisms responsible for the increased tolerance were genetically determined. Drosophila subobscura Collin (Diptera: Drosophilidae) populations were sampled from two localities with different history of heavy metal pollution, and reared for eight generations in the laboratory on a standard medium and on media with different concentrations of lead (Pb). To determine whether flies from different natural populations exposed to the Pb‐contaminated media in the laboratory show population specific variability in fitness components over generations, experimental groups with different concentrations of lead were assayed in three generations (F₂, F₅, and F₈) for fecundity, developmental time, and egg‐to‐adult viability. On the contaminated medium, fecundity was reduced in later generations and viability was increased, irrespective of the environmental origin of populations. For both populations, developmental time showed a tendency of slowing down on media with lead. Faster development was observed in later generations. Preadaptation to contamination, meaning higher fecundity, higher viability, and faster egg to adult development in all studied generations, was found in D. subobscura originating from the locality with a higher level of heavy metal pollution.     

Genome‐wide analysis of Nilaparvata lugens nymphal responses to high‐density and low‐quality rice hosts

The brown planthopper (BPH) Nilaparvata lugens is an economically important pest on rice plants. In this study, the higher population density and yellow‐ripe stage of rice plants were used to construct adverse survival conditions (ASC) against BPH nymphs. Simultaneously, the low population density and tillering stage of rice plants were used to establish a suitable survival condition (SSC) as a control. Solexa/Illumina sequencing was used to identify genes of BPH nymphs responding to ASC. Significantly longer duration development of BPH nymphs and significantly lower brachypterous ratio of BPH adults were observed by ASC compared with SSC. A total of 2 544 differentially expressed genes (DEGs) were obtained and analyzed by BLASTx, Gene Ontology and KEGG Orthology. Gene ontology analysis revealed that the DEGs were mainly involved in categories of cell, cell part, cellular process, binding, catalytic, organelle and metabolic processes. 1 138 DEGs having enzyme commission numbers were assigned to different metabolic pathways. The largest clusters were neurodegenerative diseases (137, 12.0%), followed by carbohydrate metabolism (113, 9.9%), amino acid metabolism (94, 8.3%), nucleotide metabolism (76, 6.7%), energy metabolism (64, 5.6%), translation (60, 5.3%), lipid metabolism (58, 5.1%), and folding, sorting and degradation (52, 4.6%). Expressing profile of 11 DEGs during eight nymphal developmental stages of BPH were analyzed by quantitative real‐time polymerase chain reaction. The 11 genes exhibited differential expression between ASC and SSC during at least one developmental stage. The DEGs identified in this study provide molecular proof of how BPH reconfigures its gene expression profile to adapt to overcrowding and low‐quality hosts.     

Confidence interval of intrinsic optimum temperature estimated using thermodynamic SSI model

The intrinsic optimum temperature for the development of ectotherms is one of the most important factors not only for their physiological processes but also for ecological and evolutional processes. The Sharpe–Schoolfield–Ikemoto (SSI) model succeeded in defining the temperature that can thermodynamically meet the condition that at a particular temperature the probability of an active enzyme reaching its maximum activity is realized. Previously, an algorithm was developed by Ikemoto (Tropical malaria does not mean hot environments. Journal of Medical Entomology, 45, 963–969) to estimate model parameters, but that program was computationally very time consuming. Now, investigators can use the SSI model more easily because a full automatic computer program was designed by Shi et al. (A modified program for estimating the parameters of the SSI model. Environmental Entomology, 40, 462–469). However, the statistical significance of the point estimate of the intrinsic optimum temperature for each ectotherm has not yet been determined. Here, we provided a new method for calculating the confidence interval of the estimated intrinsic optimum temperature by modifying the approximate bootstrap confidence intervals method. For this purpose, it was necessary to develop a new program for a faster estimation of the parameters in the SSI model, which we have also done.     

Gene expression profiles of sodium-dependent vitamin C transporters in mice after alcohol consumption

Alcoholic liver disease （ALD） is a serious fiver problem in western countries. Our previous study has demonstrated that vitamin C plays a protective role in ALD. The vitamin C homeostasis is tightly regulated by sodium-dependent vitamin C transporters （SVCTs） 1 and 2. But the role of two SVCTs in ALD is less understood. In this study, we exam- ined the expression patterns of two SVCTs in mice after alcohol consumption. Our results suggested that alcohol con- sumption obviously increased the expression of two SVCTs in liver and SVCT1 in kidney and intestine, which is important for vitamin C absorption. Vitamin C supplement increased the sera vitamin C content and ameliorated the symptom of ALD. Intestinal absorption and renal re-absorption mediated by SVCTI are key factors to increase the sera vitamin C content after alcohol consumption. We proposed that both reactive oxygen species and low vitamin C concentration regulate the expression of SVCTs, and the protective role of vitamin C is mediated by suppressing the stability of hypoxia-inducible factor-loL. Thus, our study is significant for the understanding of vitamin C homeostasis in ALD and for better use of other antioxidants in ALD therapy.