Elucidating the Importance of Numeracy Skills for Undergraduate Students in Life Sciences Using the Oxygen Requirement in Yeast as an Example

Current education in biology is devoid of mathematics in many countries, probably because many relevant biological processes are explained from a qualitative point of view rather than addressing the quantitative aspects of these phenomena. Here, we employ a case study from the yeast physiology to illustrate the importance of numeracy skills for a deeper understanding of relevant biological problems. Yeast anaerobic growth on sugars is a widespread process as it is the basis for beer, bread, and winemaking and it is much akin to lactic acid fermentation in muscle cells in response to an increased energy demand. To study the physiology of yeasts under controlled conditions and being able to compare the results quantitatively, one ought to perform measurements and calculations involving concentrations of oxygen, biomass, and organic compounds. To set-up an “anaerobic” culture of Saccharomyces cerevisiae in a defined medium, one needs to calculate how much oxygen must enter the cultivation system, to meet the requirements for ergosterol and oleic acid biosyntheses, both of which require oxygen. Using basic physicochemical principles and simple mathematical skills, students will be able to compute the oxygen requirement for yeast growth under such “anaerobic” conditions

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

The published online version contains mistake in Figure1. In the x-axis, instead of "1000", the number should be "100". The online version of the original article can be found at http://eprints.whiterose.ac.uk/128754/ https://doi.org/10.1007/s00253-017-8732-

Increasing ATP conservation in maltose consuming yeast, a challenge for industrial organic acid production in non-aerated reactors

BiotechnologyApplied Science

Identifying branched metabolic pathways by merging linear metabolic pathways

This paper presents a graph-based algorithm for identifying complex metabolic pathways in multi-genome scale metabolic data. These complex pathways are called branched pathways because they can arrive at a target compound through combinations of pathways that split compounds into smaller ones, work in parallel with many compounds, and join compounds into larger ones. While most previous work has focused on identifying linear metabolic pathways, branched metabolic pathways predominate in metabolic networks. Automatic identification of branched pathways has a number of important applications in areas that require deeper understanding of metabolism, such as metabolic engineering and drug target identification. Our algorithm utilizes explicit atom tracking to identify linear metabolic pathways and then merges them together into branched metabolic pathways. We provide results on two well-characterized metabolic pathways that demonstrate that this new merging approach can efficiently find biologically relevant branched metabolic pathways with complex structures

Functional characterization of the oxaloacetase encoding gene and elimination of oxalate formation in the β-lactam producer Penicillium chrysogenum

Penicillium chrysogenum is widely used as an industrial antibiotic producer, in particular in the synthesis of β-lactam antibiotics such as penicillins and cephalosporins. In industrial processes, oxalic acid formation leads to reduced product yields. Moreover, precipitation of calcium oxalate complicates product recovery. We observed oxalate production in glucose-limited chemostat cultures of P. chrysogenum grown with or without addition of adipic acid, side-chain of the cephalosporin precursor adipoyl-6-aminopenicillinic acid (ad-6-APA). Oxalate accounted for up to 5% of the consumed carbon source. In filamentous fungi, oxaloacetate hydrolase (OAH; EC3.7.1.1) is generally responsible for oxalate production. The P. chrysogenum genome harbours four orthologs of the A. niger oahA gene. Chemostat-based transcriptome analyses revealed a significant correlation between extracellular oxalate titers and expression level of the genes Pc18g05100 and Pc22g24830. To assess their possible involvement in oxalate production, both genes were cloned in Saccharomyces cerevisiae, yeast that does not produce oxalate. Only the expression of Pc22g24830 led to production of oxalic acid in S. cerevisiae. Subsequent deletion of Pc22g28430 in P. chrysogenum led to complete elimination of oxalate production, whilst improving yields of the cephalosporin precursor ad-6-APA.