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

Palaeotemperature trend for Precambrian life inferred from resurrected proteins

Biosignatures and structures in the geological record indicate that microbial life has inhabited Earth for the past 3.5 billion years or so. Research in the physical sciences has been able to generate statements about the ancient environment that hosted this life. These include the chemical compositions and temperatures of the early ocean and atmosphere. Only recently have the natural sciences been able to provide experimental results describing the environments of ancient life. Our previous work with resurrected proteins indicated that ancient life lived in a hot environment. Here we expand the timescale of resurrected proteins to provide a palaeotemperature trend of the environments that hosted life from 3.5 to 0.5 billion years ago. The thermostability of more than 25 phylogenetically dispersed ancestral elongation factors suggest that the environment supporting ancient life cooled progressively by 30 degrees C during that period. Here we show that our results are robust to potential statistical bias associated with the posterior distribution of inferred character states, phylogenetic ambiguity, and uncertainties in the amino-acid equilibrium frequencies used by evolutionary models. Our results are further supported by a nearly identical cooling trend for the ancient ocean as inferred from the deposition of oxygen isotopes. The convergence of results from natural and physical sciences suggest that ancient life has continually adapted to changes in environmental temperatures throughout its evolutionary history.

A syntactic model to design and verify synthetic genetic constructs derived from standard biological parts

MOTIVATION

The sequence of artificial genetic constructs is composed of multiple functional fragments, or genetic parts, involved in different molecular steps of gene expression mechanisms. Biologists have deciphered structural rules that the design of genetic constructs needs to follow in order to ensure a successful completion of the gene expression process, but these rules have not been formalized, making it challenging for non-specialists to benefit from the recent progress in gene synthesis.

RESULTS

We show that context-free grammars (CFG) can formalize these design principles. This approach provides a path to organizing libraries of genetic parts according to their biological functions, which correspond to the syntactic categories of the CFG. It also provides a framework for the systematic design of new genetic constructs consistent with the design principles expressed in the CFG. Using parsing algorithms, this syntactic model enables the verification of existing constructs. We illustrate these possibilities by describing a CFG that generates the most common architectures of genetic constructs in Escherichia coli.

AVAILABILITY

A web site allows readers to experiment with the algorithms presented in this article: www.genocad.org.

SUPPLEMENTARY INFORMATION

Sequences and models are available at Bioinformatics online.

OPTIMIZER: a web server for optimizing the codon usage of DNA sequences

OPTIMIZER is an on-line application that optimizes the codon usage of a gene to increase its expression level. Three methods of optimization are available: the ‘one amino acid–one codon’ method, a guided random method based on a Monte Carlo algorithm, and a new method designed to maximize the optimization with the fewest changes in the query sequence. One of the main features of OPTIMIZER is that it makes it possible to optimize a DNA sequence using pre-computed codon usage tables from a predicted group of highly expressed genes from more than 150 prokaryotic species under strong translational selection. These groups of highly expressed genes have been predicted using a new iterative algorithm. In addition, users can use, as a reference set, a pre-computed table containing the mean codon usage of ribosomal protein genes and, as a novelty, the tRNA gene-copy numbers. OPTIMIZER is accessible free of charge at http://genomes.urv.es/OPTIMIZER.

Sequence similarity is more relevant than species specificity in probabilistic backtranslation

BACKGROUND

Backtranslation is the process of decoding a sequence of amino acids into the corresponding codons. All synthetic gene design systems include a backtranslation module. The degeneracy of the genetic code makes backtranslation potentially ambiguous since most amino acids are encoded by multiple codons. The common approach to overcome this difficulty is based on imitation of codon usage within the target species.

RESULTS

This paper describes EasyBack, a new parameter-free, fully-automated software for backtranslation using Hidden Markov Models. EasyBack is not based on imitation of codon usage within the target species, but instead uses a sequence-similarity criterion. The model is trained with a set of proteins with known cDNA coding sequences, constructed from the input protein by querying the NCBI databases with BLAST. Unlike existing software, the proposed method allows the quality of prediction to be estimated. When tested on a group of proteins that show different degrees of sequence conservation, EasyBack outperforms other published methods in terms of precision.

CONCLUSION

The prediction quality of a protein backtranslation methis markedly increased by replacing the criterion of most used codon in the same species with a Hidden Markov Model trained with a set of most similar sequences from all species. Moreover, the proposed method allows the quality of prediction to be estimated probabilistically.