Anaerobiosis revisited: growth of Saccharomyces cerevisiae under extremely low oxygen availability

The budding yeast Saccharomyces cerevisiae plays an important role in biotechnological applications, ranging from fuel ethanol to recombinant protein production. It is also a model organism for studies on cell physiology and genetic regulation. Its ability to grow under anaerobic conditions is of interest in many industrial applications. Unlike industrial bioreactors with their low surface area relative to volume, ensuring a complete anaerobic atmosphere during microbial cultivations in the laboratory is rather difficult. Tiny amounts of O2 that enter the system can vastly influence product yields and microbial physiology. A common procedure in the laboratory is to sparge the culture vessel with ultrapure N2 gas; together with the use of butyl rubber stoppers and norprene tubing, O2 diffusion into the system can be strongly minimized. With insights from some studies conducted in our laboratory, we explore the question ‘how anaerobic is anaerobiosis?’. We briefly discuss the role of O2 in non-respiratory pathways in S. cerevisiae and provide a systematic survey of the attempts made thus far to cultivate yeast under anaerobic conditions. We conclude that very few data exist on the physiology of S. cerevisiae under anaerobiosis in the absence of the anaerobic growth factors ergosterol and unsaturated fatty acids. Anaerobicity should be treated as a relative condition since complete anaerobiosis is hardly achievable in the laboratory. Ideally, researchers should provide all the details of their anaerobic set-up, to ensure reproducibility of results among different laboratories. A correction to this article is available online at http://eprints.whiterose.ac.uk/131930/ https://doi.org/10.1007/s00253-018-9036-

Cryogenic Fountain Development at NIST and INRIM: Preliminary Characterization

This paper describes the new twin laser-cooled Cs fountain primary frequency standards NIST-F2 and IT-CsF2, and presents some of their design features. Most significant is a cryogenic microwave interrogation region which dramatically reduces the blackbody radiation shift. We also present a preliminary accuracy evaluation of IT-CsF2

Genetic analysis of soybean resistance to Fusarium solani f.sp. glycines

In order to study the genetic control of soybean resistance to sudden death syndrome (SDS), a 5 x 5 diallel with the F2 generation, without the reciprocals, was carried out in a greenhouse. The following parents were used: Forrest, MG/BR-46 (Conquista), IAC-4, FT-Cristalina, and FT-Estrela. The first two cultivars are more resistant to SDS than IAC-4, which is considered to be moderately resistant to SDS, and the last two cultivars are highly susceptible. The fungus was inoculated with three colonized sorghum grains placed at the bottom of the holes with two soybean seeds. Single plants were evaluated between 14 and 37 days after emergency based on foliar severity symptoms (1-5) of SDS. The disease incidence and a disease index were also calculated for each plot (clay pots with five plants each). The analysis for severity and disease index was performed only with the data of the 37th day after emergence. Additive and dominant genetic effects were detected by Jinks-Hayman's analysis, but the dominant genetic effects were higher. The genetic parameters estimated indicated that the average degree of dominance showed the presence of overdominance; at least three loci or genic blocks that exhibited dominance were responsible for the genetic control of SDS resistance; the estimates of narrow-sense heritabilities were moderate (0.48 to 0.62), but in the broad-sense they were higher (0.90 to 0.95), thus reinforcing the presence of dominance effects; and the resistance to SDS was controlled mostly by dominant alleles. Five microsatellite markers (Satt163, Satt309, Satt354, Satt371 and Satt570), reported as linked to five QRLs of the SDS, were used to genotype the parents and showed the possibility of occurrence of multiallelism in those loci, but this evidence did not invalidate the fitting of the data to the Jinks-Hayman's model