Overproduction of microbial products--facts and ideas

Overproduction of microbial metabolites is related to developmental phases of microorganisms. Inducers, effectors, inhibitors and various signal molecules play a role in different types of overproduction. Primary and secondary metabolism are interconnected. Biosynthesis of enzymes catalyzing metabolic reactions in microbial cells is controlled by well-known positive and negative mechanisms, e.g. induction, repression, catabolite repression, mechanisms controlling enzyme activity include isosteric and allosteric interactions, e.g. competitive and non-competitive inhibition, allosteric effects, molecular conversion etc. Biosynthesis of secondary metabolites is catalyzed by unaltered enzymes of primary metabolism, by altered enzymes of primary metabolism and by specific enzymes of secondary metabolism. In addition to classical mutagenesis and selection of suitable microbial cells, methods of molecular genetics are used in the overproduction of microbial products.     

Oligochaeta of the Morava and Odra River basins (Czech Republic): species distribution and community composition

Makupa creek is connected to the Indian Ocean via the Killindini creek; the study deals with the distribution of heavy metals in the Makupa and Killindini creeks.Concentrations of Cu, Cd, Fe and Zn, in sediments at the inner sections of the creeks were high compared to those measured at Likoni (ocean). Considering trace metal levels at the inner sections relative to Likoni the ratios obtained, were Cd 7:1, Cu 13:1, Fe 5:1 and Zn 21:1.The results obtained point at Makupa creek as the main source of heavy metals into the creek system, however iron behaved differently, it was significantly higher at the Killindini Habour P<0.05 (at 95% confidence level).There was a decline in concentrations of, copper and zinc from the inner stations to the frontwater zone at Makupa creek. Spatial variations of cadmium were not significant between inner and frontwater zones of the Makupa creek P>0.05 (at 95% confidence level), and also between Makupa and Harbour. There was however a significant difference P<0.05 (at 95% confidence level) between Likoni and Makupa.     

Allogeneic cell therapy bioprocess economics and optimization: Single‐use cell expansion technologies

For allogeneic cell therapies to reach their therapeutic potential, challenges related to achieving scalable and robust manufacturing processes will need to be addressed. A particular challenge is producing lot‐sizes capable of meeting commercial demands of up to 10⁹ cells/dose for large patient numbers due to the current limitations of expansion technologies. This article describes the application of a decisional tool to identify the most cost‐effective expansion technologies for different scales of production as well as current gaps in the technology capabilities for allogeneic cell therapy manufacture. The tool integrates bioprocess economics with optimization to assess the economic competitiveness of planar and microcarrier‐based cell expansion technologies. Visualization methods were used to identify the production scales where planar technologies will cease to be cost‐effective and where microcarrier‐based bioreactors become the only option. The tool outputs also predict that for the industry to be sustainable for high demand scenarios, significant increases will likely be needed in the performance capabilities of microcarrier‐based systems. These data are presented using a technology S‐curve as well as windows of operation to identify the combination of cell productivities and scale of single‐use bioreactors required to meet future lot sizes. The modeling insights can be used to identify where future R&D investment should be focused to improve the performance of the most promising technologies so that they become a robust and scalable option that enables the cell therapy industry reach commercially relevant lot sizes. The tool outputs can facilitate decision‐making very early on in development and be used to predict, and better manage, the risk of process changes needed as products proceed through the development pathway. Biotechnol. Bioeng. 2014;111: 69–83. © 2013 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.     

Apolipoprotein E Polymorphism in Hemodialyzed Patients and Healthy Controls

A possible association between end-stage renal disease (ESRD) and apolipoprotein E (APOE) polymorphism was found in some but not all studies. We have analyzed the APOE genotypes in 995 hemodialyzed patients (cases) and a sample of 6242 healthy individuals (controls) in the Czech Republic. There was a statistically significant difference in the frequency of APOE alleles between cases and controls, with more carriers of the APOE2 allele in ESRD patients (15.9%) than in controls (12.2%) (P = 0.005). The odds ratio of ESRD for the APOE2 allele, compared with APOE3E3 homozygotes, was 1.37 (95% confidence interval 1.13–1.67). The strength of the association increased with the time spent on hemodialysis: the odds ratio of all-cause ESRD in patients dialyzed for eight or more years was 1.27 (0.94–1.71), for 1–8 years 1.41 (1.09–1.81), and less than 1 year (nonsurvivors) 1.94 (0.88–4.18). This study suggests that the APOE2 allele is a possible genetic risk factor for all-cause ESRD in Caucasians.