19 research outputs found
Fermentation of deproteinized cheese whey powder solutions to ethanol by engineered Saccharomyces cerevisiae : effect of supplementation with corn steep liquor and repeated-batch operation with biomass recycling by flocculation
The lactose in cheese whey is an interesting
substrate for the production of bulk commodities such as
bio-ethanol, due to the large amounts of whey surplus
generated globally. In this work, we studied the performance
of a recombinant Saccharomyces cerevisiae strain
expressing the lactose permease and intracellular ß-galactosidase
from Kluyveromyces lactis in fermentations of
deproteinized concentrated cheese whey powder solutions.
Supplementation with 10 g/l of corn steep liquor significantly
enhanced whey fermentation, resulting in the production
of 7.4% (v/v) ethanol from 150 g/l initial lactose in
shake-flask fermentations, with a corresponding productivity
of 1.2 g/l/h. The flocculation capacity of the yeast
strain enabled stable operation of a repeated-batch process
in a 5.5-l air-lift bioreactor, with simple biomass recycling
by sedimentation of the yeast flocs. During five consecutive
batches, the average ethanol productivity was 0.65 g/l/h
and ethanol accumulated up to 8% (v/v) with lactose-toethanol
conversion yields over 80% of theoretical. Yeast
viability (>97%) and plasmid retention (>84%) remained
high throughout the operation, demonstrating the stability
and robustness of the strain. In addition, the easy and
inexpensive recycle of the yeast biomass for repeated utilization
makes this process economically attractive for
industrial implementation.Fundação para a Ciência e a Tecnologia (FCT)LACTOGAL-Produtos Alimentares S.A.Companhia Portuguesa de Amidos, S.A
Pydna: a simulation and documentation tool for DNA assembly strategies using python
Background: Recent advances in synthetic biology have provided tools to efficiently construct complex DNA molecules which are an important part of many molecular biology and biotechnology projects. The planning of such constructs has traditionally been done manually using a DNA sequence editor which becomes error-prone as scale and complexity of the construction increase. A human-readable formal description of cloning and assembly strategies, which also allows for automatic computer simulation and verification, would therefore be a valuable tool.Results: We have developed pydna, an extensible, free and open source Python library for simulating basic molecular biology DNA unit operations such as restriction digestion, ligation, PCR, primer design, Gibson assembly and homologous recombination. A cloning strategy expressed as a pydna script provides a description that is complete, unambiguous and stable. Execution of the script automatically yields the sequence of the final molecule(s) and that of any intermediate constructs. Pydna has been designed to be understandable for biologists with limited programming skills by providing interfaces that are semantically similar to the description of molecular biology unit operations found in literature.Conclusions: Pydna simplifies both the planning and sharing of cloning strategies and is especially useful for complex or combinatorial DNA molecule construction. An important difference compared to existing tools with similar goals is the use of Python instead of a specifically constructed language, providing a simulation environment that is more flexible and extensible by the user.Thanks to Dr. Aric Hagberg Los Alamos National Laboratory, U.S.A and Sergio Simoes, Universidade de Sao Paulo, Brasil for help with NetworkX and graph theory in general. Thanks to Henrik Bengtsson, Dept of Epidemiology & Biostatistics, University of California San Francisco, U.S.A. for critical reading of the manuscript. Thanks to the 2013 Bioinformatics 6605 N4 students A. Coelho, A. Faria, A. Neves D. Yelshyna and E. Costa for testing. This work was supported by the Fundacao para a Ciencia e Tecnologia (FCT) [PTDC/AAC-AMB/120940/2010, EXPL/BBB-BIO/1772/2013]; and the FEDER POFC-COMPETE [PEst-C/BIA/UI4050/2011]. FA and GR were supported by FCT fellowships [SFRH/BD/80934/2011 and SFRH/BD/42565/2007, respectively].info:eu-repo/semantics/publishedVersio
Yeast diversity in relation to the production of fuels and chemicals
In addition to ethanol, yeasts have the potential to produce many other industrially-relevant chemicals from numerous different carbon sources. However there remains a paucity of information about overall capability across the yeast family tree. Here, 11 diverse species of yeasts with genetic backgrounds representative of different branches of the family tree were investigated. They were compared for their abilities to grow on a range of sugar carbon sources, to produce potential platform chemicals from such substrates and to ferment hydrothermally pretreated rice straw under simultaneous saccharification and fermentation conditions. The yeasts differed considerably in their metabolic capabilities and production of ethanol. A number could produce significant amounts of ethyl acetate, arabinitol, glycerol and acetate in addition to ethanol, including from hitherto unreported carbon sources. They also demonstrated widely differing efficiencies in the fermentation of sugars derived from pre-treated rice straw biomass and differential sensitivities to fermentation inhibitors. A new catabolic property of Rhodotorula mucilaginosa (NCYC 65) was discovered in which sugar substrate is cleaved but the products are not metabolised. We propose that engineering this and some of the other properties discovered in this study and transferring such properties to conventional industrial yeast strains could greatly expand their biotechnological utility
On the dynamics of the adenylate energy system: homeorhesis vs homeostasis.
Biochemical energy is the fundamental element that maintains both the adequate turnover of the biomolecular structures and the functional metabolic viability of unicellular organisms. The levels of ATP, ADP and AMP reflect roughly the energetic status of the cell, and a precise ratio relating them was proposed by Atkinson as the adenylate energy charge (AEC). Under growth-phase conditions, cells maintain the AEC within narrow physiological values, despite extremely large fluctuations in the adenine nucleotides concentration. Intensive experimental studies have shown that these AEC values are preserved in a wide variety of organisms, both eukaryotes and prokaryotes. Here, to understand some of the functional elements involved in the cellular energy status, we present a computational model conformed by some key essential parts of the adenylate energy system. Specifically, we have considered (I) the main synthesis process of ATP from ADP, (II) the main catalyzed phosphotransfer reaction for interconversion of ATP, ADP and AMP, (III) the enzymatic hydrolysis of ATP yielding ADP, and (IV) the enzymatic hydrolysis of ATP providing AMP. This leads to a dynamic metabolic model (with the form of a delayed differential system) in which the enzymatic rate equations and all the physiological kinetic parameters have been explicitly considered and experimentally tested in vitro. Our central hypothesis is that cells are characterized by changing energy dynamics (homeorhesis). The results show that the AEC presents stable transitions between steady states and periodic oscillations and, in agreement with experimental data these oscillations range within the narrow AEC window. Furthermore, the model shows sustained oscillations in the Gibbs free energy and in the total nucleotide pool. The present study provides a step forward towards the understanding of the fundamental principles and quantitative laws governing the adenylate energy system, which is a fundamental element for unveiling the dynamics of cellular life
Evolutionary engineering of a wine yeast strain revealed a key role of inositol and mannoprotein metabolism during low-temperature fermentation
[Background]
Wine produced at low temperature is often considered to improve sensory qualities. However, there are certain drawbacks to low temperature fermentations: e.g. low growth rate, long lag phase, and sluggish or stuck fermentations. Selection and development of new Saccharomyces cerevisiae strains well adapted at low temperature is interesting for future biotechnological applications. This study aimed to select and develop wine yeast strains that well adapt to ferment at low temperature through evolutionary engineering, and to decipher the process underlying the obtained phenotypes.[Results]
We used a pool of 27 commercial yeast strains and set up batch serial dilution experiments to mimic wine fermentation conditions at 12 °C. Evolutionary engineering was accomplished by using the natural yeast mutation rate and mutagenesis procedures. One strain (P5) outcompeted the others under both experimental conditions and was able to impose after 200 generations. The evolved strains showed improved growth and low-temperature fermentation performance compared to the ancestral strain. This improvement was acquired only under inositol limitation. The transcriptomic comparison between the evolved and parental strains showed the greatest up-regulation in four mannoprotein coding genes, which belong to the DAN/TIR family (DAN1, TIR1, TIR4 and TIR3). Genome sequencing of the evolved strain revealed the presence of a SNP in the GAA1 gene and the construction of a site-directed mutant (GAA1Thr108) in a derivative haploid of the ancestral strain resulted in improved fermentation performance. GAA1 encodes a GPI transamidase complex subunit that adds GPI, which is required for inositol synthesis, to newly synthesized proteins, including mannoproteins.[Conclusions]
In this study we demonstrate the importance of inositol and mannoproteins in yeast adaptation at low temperature and the central role of the GAA1 gene by linking both metabolisms.This work has been financially supported by grants AGL2013-47300-C3-3-R and PROMETEOII/2014/042 from the Spanish government and the Generalitat Valenciana, respectively, awarded to JMG. MLM and EGR also want to thank the Spanish government for her FPI grants. Analysis of yeast genomic sequences was made possible through the NIH P41 GM103533 grant funding the Yeast Resource Center. MJD is a Rita Allen Scholar and Fellow in the Genetic Networks program at the Canadian Institute for Advanced Research. MS was supported by NSF fellowship DGE-1256082