Efficient mapping of transgene integration sites and local structural changes in Cre transgenic mice using targeted locus amplification.

Cre/LoxP technology is widely used in the field of mouse genetics for spatial and/or temporal regulation of gene function. For Cre lines generated via pronuclear microinjection of a Cre transgene construct, the integration site is random and in most cases not known. Integration of a transgene can disrupt an endogenous gene, potentially interfering with interpretation of the phenotype. In addition, knowledge of where the transgene is integrated is important for planning of crosses between animals carrying a conditional allele and a given Cre allele in case the alleles are on the same chromosome. We have used targeted locus amplification (TLA) to efficiently map the transgene location in seven previously published Cre and CreERT2 transgenic lines. In all lines, transgene insertion was associated with structural changes of variable complexity, illustrating the importance of testing for rearrangements around the integration site. In all seven lines the exact integration site and breakpoint sequences were identified. Our methods, data and genotyping assays can be used as a resource for the mouse community and our results illustrate the power of the TLA method to not only efficiently map the integration site of any transgene, but also provide additional information regarding the transgene integration events.

Protein fabrication automation.

Facile "writing" of DNA fragments that encode entire gene sequences potentially has widespread applications in biological analysis and engineering. Rapid writing of open reading frames (ORFs) for expressed proteins could transform protein engineering and production for protein design, synthetic biology, and structural analysis. Here we present a process, protein fabrication automation (PFA), which facilitates the rapid de novo construction of any desired ORF from oligonucleotides with low effort, high speed, and little human interaction. PFA comprises software for sequence design, data management, and the generation of instruction sets for liquid-handling robotics, a liquid-handling robot, a robust PCR scheme for gene assembly from synthetic oligonucleotides, and a genetic selection system to enrich correctly assembled full-length synthetic ORFs. The process is robust and scalable.

Binding of herpes simplex virus-1 US11 to specific RNA sequences.

Herpes simplex virus-1 US11 is a RNA-binding protein with a novel RNA-binding domain. US11 has been reported to exhibit sequence- and conformation-specific RNA-binding, but the sequences and conformations important for binding are not known. US11 has also been described as a double-stranded RNA (dsRNA)-binding protein. To investigate the US11-RNA interaction, we performed in vitro selection of RNA aptamers that bind US11 from a RNA library consisting of >10(14) 80 base sequences which differ in a 30 base randomized region. US11 bound specifically to selected aptamers with an affinity of 70 nM. Analysis of 23 selected sequences revealed a strong consensus sequence. The US11 RNA-binding domain and < or =46 bases of selected RNA containing the consensus sequence were each sufficient for binding. US11 binding protected the consensus motif from hydroxyl radical cleavage. RNase digestions of a selected aptamer revealed regions of both single-stranded RNA and dsRNA. We observed that US11 bound two different dsRNAs in a sequence non-specific manner, but with lower affinity than it bound selected aptamers. The results define a relatively short specific sequence that binds US11 with high affinity and indicate that dsRNA alone does not confer high-affinity binding.

AANT: the Amino Acid-Nucleotide Interaction Database.

We have created an Amino Acid-Nucleotide Interaction Database (AANT; http://aant.icmb.utexas. edu/) that categorizes all amino acid-nucleotide interactions from experimentally determined protein-nucleic acid structures, and provides users with a graphic interface for visualizing these interactions in aggregate. AANT accomplishes this by extracting individual amino acid-nucleotide interactions from structures in the Protein Data Bank, combining and superimposing these interactions into multiple structure files (e.g. 20 amino acids x 5 nucleotides) and grouping structurally similar interactions into more readily identifiable clusters. Using the Chime web browser plug-in, users can view 3D representations of the superimpositions and clusters. The unique collection and representation of data on amino acid-nucleotide interactions facilitates understanding the specificity of protein-nucleic acid interactions at a more fundamental level, and allows comparison of otherwise extremely disparate sets of structures. Moreover, by modularly representing the fundamental interactions that govern binding specificity it may prove possible to better engineer nucleic acid binding proteins.

Automated selection of aptamers against protein targets translated in vitro: from gene to aptamer.

Reagents for proteome research must of necessity be generated by high throughput methods. Aptamers are potentially useful as reagents to identify and quantitate individual proteins, yet are currently produced for the most part by manual selection procedures. We have developed automated selection methods, but must still individually purify protein targets. Therefore, we have attempted to select aptamers against protein targets generated by in vitro transcription and translation of individual genes. In order to specifically immobilize the protein targets for selection, they are also biotinylated in vitro. As a proof of this method, we have selected aptamers against translated human U1A, a component of the nuclear spliceosome. Selected sequences demonstrated exquisite mimicry of natural binding sequences and structures. These results not only reveal a potential path to the high throughput generation of aptamers, but also yield insights into the incredible specificity of the U1A protein for its natural RNA ligands.

Mammalian Genotyping Using Acoustic Droplet Ejection for Enhanced Data Reproducibility, Superior Throughput, and Minimized Cross-Contamination.

Genetically engineered animal models are major tools of a drug discovery pipeline because they facilitate understanding of the molecular and biochemical basis of disease. These highly complex models of human disease often require increasingly convoluted genetic analysis. With growing needs for throughput and consistency, we find that traditional aspiration-and-dispense liquid-handling robots no longer have the required speed, quality, or reproducibility.We present an adaptation and installation of an acoustic droplet ejection (ADE) liquid-handling system for ultra-high-throughput screening of genetically engineered models. An ADE system is fully integrated with existing laboratory processes and platforms to facilitate execution of PCR and quantitative PCR (qPCR) reactions. Such a configuration permits interrogation of highly complex genetic models in a variety of backgrounds. Our findings demonstrate that a single ADE system replaces 8-10 traditional liquid-handling robots while increasing quality and reproducibility.We demonstrate significant improvements achieved by transitioning to an ADE device: extremely low detectable cross-contamination in PCR and qPCR despite extensive use, greatly increased data reproducibility (large increases in data quality and Cq consistency), lowered reaction volumes for large cost savings, and nearly a magnitude increase in speed per instrument. We show several comparisons between traditional- and ADE-based pipetting for a qPCR-based workflow.

Automated acquisition of aptamer sequences.

While the in vitro selection of nucleic acid binding species (aptamers) requires numerous liquid-handling steps, these steps are relatively straightforward and the overall process is therefore amenable to automation. Here we demonstrate that automated selection techniques are capable of generating aptamers against a number of diverse protein targets. Automated selection techniques can be integrated with automated analytical methods, including sequencing, determination of binding constants, and structural analysis. The methods that have so far been developed can be further multiplexed, and it should soon be possible to attempt the selection of aptamers against organismal proteomes or metabolomes.

Multifactorial determinants of protein expression in prokaryotic open reading frames.

A quantitative description of the relationship between protein expression levels and open reading frame (ORF) nucleotide sequences is important for understanding natural systems, designing synthetic systems, and optimizing heterologous expression. Codon identity, mRNA secondary structure, and nucleotide composition within ORFs markedly influence expression levels. Bioinformatic analysis of ORF sequences in 816 bacterial genomes revealed that these features show distinct regional trends. To investigate their effects on protein expression, we designed 285 synthetic genes and determined corresponding expression levels in vitro using Escherichia coli extracts. We developed a mathematical function, parameterized using this synthetic gene data set, which enables computation of protein expression levels from ORF nucleotide sequences. In addition to its practical application in the design of heterologous expression systems, this equation provides mechanistic insight into the factors that control translation efficiency. We found that expression is strongly dependent on the presence of high AU content and low secondary structure in the ORF 5' region. Choice of high-frequency codons contributes to a lesser extent. The 3' terminal AU content makes modest, but detectable contributions. We present a model for the effect of these factors on the three phases of ribosomal function: initiation, elongation, and termination.