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Biomedical subjects

Claes Gustafsson

Publications and source records attributed to Claes Gustafsson.

11 recordsLinked to original sources
PubMed2006

Gene Designer: a synthetic biology tool for constructing artificial DNA segments.

BACKGROUND: Direct synthesis of genes is rapidly becoming the most efficient way to make functional genetic constructs and enables applications such as codon optimization, RNAi resistant genes and protein engineering. Here we introduce a software tool that drastically facilitates the design of synthetic genes. RESULTS: Gene Designer is a stand-alone software for fast and easy design of synthetic DNA segments. Users can easily add, edit and combine genetic elements such as promoters, open reading frames and tags through an intuitive drag-and-drop graphic interface and a hierarchical DNA/Protein object map. Using advanced optimization algorithms, open reading frames within the DNA construct can readily be codon optimized for protein expression in any host organism. Gene Designer also includes features such as a real-time sliding calculator of oligonucleotide annealing temperatures, sequencing primer generator, tools for avoidance or inclusion of restriction sites, and options to maximize or minimize sequence identity to a reference. CONCLUSION: Gene Designer is an expandable Synthetic Biology workbench suitable for molecular biologists interested in the de novo creation of genetic constructs.

Base Sequence↗
PubMed2006

Validation of RNAi silencing specificity using synthetic genes: salicylic acid-binding protein 2 is required for innate immunity in plants.

RNA interference (RNAi) is widely used to specifically silence the expression of any gene to study its function and to identify and validate therapeutic targets. Despite the popularity of this technology, recent studies have shown that RNAi may also silence non-targeted genes. Here we demonstrate the utility of a quick, efficient and robust approach to directly validate the specificity of RNAi as an alternative to indirect validation of RNAi through gene expression profiling. Our approach involves reversing (complementing) the RNAi-induced phenotype by introducing a synthetic version of the target gene that is designed to escape silencing. This synthetic gene complementation approach can also be used for mutational analysis of the target gene, or to provide a functional version of a defective protein after silencing the defective gene by RNAi. Using this approach we demonstrate that the loss of systemic acquired resistance, a form of innate immunity in plants, is indeed due to the silencing of salicylic acid-binding protein 2 rather than to off-target effects.

Esterases↗
PubMed2005

Predicting enzyme function from protein sequence.

There are two main reasons to try to predict an enzyme's function from its sequence. The first is to identify the components and thus the functional capabilities of an organism, the second is to create enzymes with specific properties. Genomics, expression analysis, proteomics and metabonomics are largely directed towards understanding how information flows from DNA sequence to protein functions within an organism. This review focuses on information flow in the opposite direction: the applicability of what is being learned from natural enzymes to improve methods for catalyst design.

Animals↗
PubMed2005

Semi-synthetic DNA shuffling of aveC leads to improved industrial scale production of doramectin by Streptomyces avermitilis.

The avermectin analog doramectin (CHC-B1), sold commercially as Dectomax, is biosynthesized by Streptomyces avermitilis. aveC, a gene encoding an unknown mechanistic function, plays an essential role in the production of doramectin (avermectin CHC-B1), modulating the production ratio of CHC-B1 to other avermectins, most notably the undesirable analog CHC-B2. To improve the production ratio for doramectin, the aveC gene was subjected to iterative rounds of semi-synthetic DNA shuffling. Libraries of shuffled aveC gene variants were transformed into S. avermitilis, screened using a miniaturized 96-well growth and production format, and analyzed by high throughput mass spectrometry to determine CHC-B2:CHC-B1 ratios. Several improved aveC variants were identified; the best shuffled gene encoded 10 amino acid mutations, and conferred a final CHC-B2:CHC-B1 ratio of 0.07:1, a 23-fold improvement over the starting gene (aveC wild type). Chromosomal insertion of an improved aveC shuffled gene into a high titer S. avermitilis strain yielded an improved doramectin production strain. This strain is under development to be used commercially, and is expected to provide considerable cost savings in large-scale manufacture, as well as significantly reducing by-product levels of CHC-B2 requiring disposal.

DNA Shuffling↗
PubMed2004

Codon bias and heterologous protein expression.

The expression of functional proteins in heterologous hosts is a cornerstone of modern biotechnology. Unfortunately, proteins are often difficult to express outside their original context. They might contain codons that are rarely used in the desired host, come from organisms that use non-canonical code or contain expression-limiting regulatory elements within their coding sequence. Improvements in the speed and cost of gene synthesis have facilitated the complete redesign of entire gene sequences to maximize the likelihood of high protein expression. Redesign strategies are discussed here, including modification of translation initiation regions, alteration of mRNA structural elements and use of different codon biases.

Cloning, Molecular↗
PubMed2004

Engineered protein function by selective amino acid diversification.

Almost all protein engineering methods rely upon making changes to naturally occurring proteins that already possess some of the desired properties. This will probably remain the case as long as we lack a complete understanding of the way that an amino acid sequence gives rise to a protein with a precisely defined biological function. Common to all methods for altering an existing protein is the selection of a subset of amino acids in the protein for variation and a choice of which substitutions to make at each position. Variants are then tested empirically and further variants are created based upon their performance. Differences between protein engineering methods are the ways in which amino acids are chosen for variation, the protocols followed for creating the variants, and how information regarding variant properties is used in creating subsequent variants. In this article, we describe these differences and provide examples of how the experimental parameters of specific projects determine which method is most suitable.

Amino Acids↗
PubMed2003

Systematic variation of amino acid substitutions for stringent assessment of pairwise covariation.

During protein evolution, amino acids change due to a combination of functional constraints and genetic drift. Proteins frequently contain pairs of amino acids that appear to change together (covariation). Analysis of covariation from naturally occurring sets of orthologs cannot distinguish between residue pairs retained by functional requirements of the protein and those pairs existing due to changes along a common evolutionary path. Here, we have separated the two types of covariation by independently recombining every naturally occurring amino acid variant within a set of 15 subtilisin orthologs. Our analysis shows that in this family of subtilisin orthologs, almost all possible pairwise combinations of amino acids can coexist. This suggests that amino acid covariation found in the subtilisin orthologs is almost entirely due to common ancestral origin of the changes rather than functional constraints. We conclude that naturally occurring sequence diversity can be used to identify positions that can vary independently without destroying protein function.

Amino Acid Sequence↗
PubMed2003

Engineering the aveC gene to enhance the ratio of doramectin to its CHC-B2 analogue produced in Streptomyces avermitilis.

Avermectin and its analogues are produced by the actinomycete Streptomyces avermitilis and are major commercial products for parasite control in the fields of animal health, agriculture, and human infections. Historically, the avermectin analogue doramectin (CHC-B1), which is sold commercially as Dectomax is co-produced during fermentation with the undesired analogue CHC-B2 at a CHC-B2:CHC-B1 ratio of 1.6:1. Although the identification of the avermectin gene cluster has allowed for characterization of most of the biosynthetic pathway, the mechanism for determining the avermectin B2:B1 ratio remains unclear. The aveC gene, which has an essential role in avermectin biosynthesis, was inactivated by insertional inactivation and mutated by site-specific mutagenesis and error-prone PCR. Several unrelated mutations were identified that resulted in improved ratios of the desirable avermectin analogue CHC-B1, produced relative to the undesired CHC-B2 fermentation component. High-throughput (HTP) screening of cultures grown on solid-phase fermentation plates and analysis using electrospray mass spectrometry was implemented to significantly increase screening capability. An aveC gene with mutations that result in a 4-fold improvement in the ratio of doramectin to CHC-B2 was identified. Subsequent integration of the enhanced aveC gene into the chromosome of the S. avermitilis production strain demonstrates the successful engineering of a specific biosynthetic pathway gene to significantly improve fermentation productivity of a commercially important product.

Base Sequence↗
PubMed2003

Putting engineering back into protein engineering: bioinformatic approaches to catalyst design.

Complex multivariate engineering problems are commonplace and not unique to protein engineering. Mathematical and data-mining tools developed in other fields of engineering have now been applied to analyze sequence-activity relationships of peptides and proteins and to assist in the design of proteins and peptides with specified properties. Decreasing costs of DNA sequencing in conjunction with methods to quickly synthesize statistically representative sets of proteins allow modern heuristic statistics to be applied to protein engineering. This provides an alternative approach to expensive assays or unreliable high-throughput surrogate screens.

Algorithms↗
PubMed2003

Optimizing the search algorithm for protein engineering by directed evolution.

An in silico protein model based on the Kauffman NK-landscape, where N is the number of variable positions in a protein and K is the degree of coupling between variable positions, was used to compare alternative search strategies for directed evolution. A simple genetic algorithm (GA) was used to model the performance of a standard DNA shuffling protocol. The search effectiveness of the GA was compared to that of a statistical approach called the protein sequence activity relationship (ProSAR) algorithm, which consists of two steps: model building and library design. A number of parameters were investigated and found to be important for the comparison, including the value of K, the screening size, the system noise and the number of replicates. The statistical model was found to accurately predict the measured activities for small values of the coupling between amino acids, K <or= 1. The ProSAR strategy was found to perform well for small to moderate values of coupling, 0 <or= K <or= 3, and was found to be robust to noise. Some implications for protein engineering are discussed.

Algorithms↗