Written for industrial and academic researchers and development scientists in the life sciences industry, Bioprocessing Technology for Production of Biopharmaceuticals and Bioproducts is a guide to the tools, approaches, and useful developments in bioprocessing. This important guide:
• Summarizes state-of-the-art bioprocessing methods and reviews applications in life science industries
• Includes illustrative case studies that review six milestone bio-products
• Discuses a wide selection of host strain types and disruptive bioprocess technologies
Directed laboratory evolution is a common technique to obtain an evolved bacteria strain with a desired phenotype. This technique is especially useful as a supplement to rational engineering for complex phenotypes such as increased biocatalyst tolerance to toxic compounds. However, reverse engineering efforts are required in order to identify the mutations that occurred, including single nucleotide polymorphisms (SNPs), insertions/deletions (indels), duplications, and rearrangements. In this protocol, we describe the steps to (1) obtain and sequence the genomic DNA, (2) process and analyze the genomic DNA sequence data, and (3) verify the mutations by Sanger resequencing.
This chapter describes various components of reactive nitrogen species (RNS) response networks and their associated regulatory circuitry. It focuses on how these components are used to identify additional regulatory components and elucidate RNS response networks as a function of RNS source and growth conditions. It summarizes the complementary nature of traditional biochemical analysis and systems-wide analysis in identification and characterization of the bacterial response to RNS. Bacteria have evolved complex regulatory networks for dealing with a variety of chemical stressors. The bacterial response to RNS is relevant to both pathogenesis and denitrification and thus has been extensively characterized. Traditional biochemical analysis has identified and characterized many of the key RNS response elements, such as flavohemoglobin hmpA and response regulator NorR. Additionally, systems-wide analysis aids in the identification of additional network components and determination of their contribution to the overall network behavior. These systems-wide analyses have led to the identification of response regulator NsrR, Fe-S cluster repair agent YtfE, and the critical NO target. The extensive body of knowledge regarding the bacterial RNS response and RNS chemistry makes the RNS response network an excellent example of the combined power of traditional biochemical analysis and systems-wide analysis.
This chapter focuses on the development of two related bacteria that have proven to be effective in a variety of physical and chemical processes: Escherichia coli and Klebsiella oxytoca. Development of recombinant microbes that utilize a variety of sugars for ethanol production in laboratory media under optimum growth conditions has been repeated by several laboratories around the world. The use of dilute acid at temperatures above 140ºC is effective for the hydrolysis of hemicellulose in bagasse without significant loss of sugars or the production of degraded by-products. Dilute acid hydrolysis of hemicellulose has been used in order to produce high concentrations of hemicellulose sugars for fermentation by E. coli strain KO11-RD1. The yield of ethanol from acidic hydrolysis of cellulose is limited due to the poor recovery of glucose during the acid hydrolysis process. The degradation of glucose occurs very rapidly under conditions necessary for cellulose hydrolysis. Therefore, the use of cellulolytic enzymes has been pursued for several decades as a means of increasing the ethanol yield from cellulose. The simultaneous saccharification and fermentation (SSF) model has the following advantages over the sequential hydrolysis and fermentation process model: (i) lower enzyme dosages required for efficient conversion, (ii) compatibility with coproduction of enzymes during ethanol fermentation, and (iii) lower free-sugar concentrations during the SSF process.
N/A