J. Colin Cox

The gain of three mitochondrial introns identifies liverworts as the earliest land plants

The first evidence for the emergence of land plants (embryophytes) consists of mid-Ordovician spore tetrads (∼476 Myr old),. The identity of the early plants that produced these spores is unclear; they are sometimes claimed to be liverworts,, but there are no associated megafossils, and similar spores can be produced by a diversity of plants. Indeed, the earliest unequivocal megafossils of land plants consist of early vascular plants and various plants of uncertain affinity. Different phylogenetic analyses have identified liverworts, hornworts and bryophytes as each being the first lineage of land plants,,; the consensus of these conflicting topologies yields an unresolved polychotomy at the base of land plants. Here we survey 352 diverse land plants and find that three mitochondrial group II introns are present, with occasional losses, in mosses, hornworts and all major lineages of vascular plants, but are entirely absent from liverworts, green algae and all other eukaryotes. These results indicate that liverworts are the earliest land plants, with the three introns having been acquired in a common ancestor of all other land plants, and have important implications concerning the early stages of plant evolution.

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.

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.

The complexities of DNA computation.

Over the past few years, a handful of insightful researchers have bridged the gap between biological computing theory and actual DNA-based computation. By using ingenious encoding techniques and clever molecular-biological manipulations, simple versions of computationally complex problems have been experimentally approached or resolved. However, the technical problems revealed during the execution of these scientific set pieces make it unlikely that DNA will ever rival silicon for the solution of any real-world problem.

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 >1014 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 ≤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.

Automated Selection of Aminoglycoside Aptamers

The in vitro selection of aptamers that bind to low molecular weight targets is commonly a tedious, time-consuming project. We have expanded current automated selection protocols to include aptamer selections against small molecules including the aminoglycosides neomycin, kanamycin, and tobramycin. This modified procedure decreases both the frequency of manual handling of the selection reagents and the time required to perform the experiment, generating aptamers against the chosen target at a much greater rate. Using this process, we have selected aptamers of good affinity against all three aminoglycosides chosen. The method is suitable for integration with high-throughput technologies, greatly expanding the possibility of discovering useful aptamers against other low weight targets. (JALA 2004;9:150-4)

DNA computation function

Some folks certainly think so. But at some level a cellular computer is really no different than metabolism and gene regulation.Where can I find out more, especially from someone with opinions different from yours?

Automated Optimization of Aptamer Selection Buffer Conditions

Optimizing the buffer conditions of the selection of nucleic acid binding species (aptamers), increases the likelihood of producing a target aptamer. Aptamers, with high target affinity and specificity, are often compared to antibodies, as aptamers emerge in the industry as diagnostic and therapeutic tools. The increased demand for aptamers encourages high-throughput aptamer generation. The selection buffer conditions may vary as widely as the selection targets, and therefore buffer optimization is helpful if not required for effective aptamer selections. Such optimization work is time consuming and repetitious, which bodes well for high-throughput applications. To accommodate this, an automated buffer testing protocol has been developed to test target-to-unselected RNA pool binding in the presence of 96 different buffer conditions. The dynamic program may vary the monovalent salt(s) identity, monovalent salt(s) concentration, divalent salt(s) identity, divalent salt concentration, buffer identity, buffer concentration, and pH. The optimized buffer conditions likely increase the probability of a successful selection and therefore promote higher ratios of successful aptamer selections against a variety of targets. Preliminary results show trends with the buffer matrix solutions and lysozyme:unselected pool binding. In general, an inverse relationship between lysozyme binding and monovalent salt concentration is observed. (JALA 2004;9:117-22)

Exploring Sequence Space through Automated Aptamer Selection

Theoretical studies focusing on the nature of landscapes that correlate molecular sequences to molecular function have mainly been carried out in silico due to the vast amounts of data that are needed. Automated in vitro selection is capable of producing significant amounts of data in a short time, making theoretical modeling with real experimental data attainable. A Biomek 2000 Laboratory Automation Workstation has been outfitted to carry out multiple in vitro nucleic acid selections in parallel, yielding substantial amounts of data for theoretical studies. A random sequence population of nucleic acids is initially generated by a combination of chemical synthesis and enzymatic amplification. On the workstation, this population is parsed for its ability to bind a protein, lysozyme. After each round of selection, the selected nucleic acid binding species (also known as aptamers) are amplified by a combination of reverse transcription polymerase chain reaction (PCR) and in vitro transcription. All eight pools that have undergone selection have yielded different sequences.

24 Automated In Vitro Selection and Microarray Applications for Functional RNA Sequences

As experimental biology begins to address questions at the systems level, where data from multiple genes or proteins must be analyzed in parallel, laboratory-based automation of experimental procedures becomes increasingly important. Indeed, the various fields of genomics, proteomics, metabolomics, combinatorial chemistry, and high-throughput screening deal with so many individual molecules and conditions that experiments can be daunting or intractable to perform without mechanization. Initial forays into laboratory automation yielded robotically performed experimental procedures that replaced repetitive and laborious practices such as microarray creation and processing, plasmid purification, and polymerase chain reaction (PCR), or DNA sequencing reactions (Hunkapiller et al. 1991; Civitello et al. 1992; Meier-Ewert et al. 1993; Boland et al 1994; Gonzalez et al. 1996; Macas et al. 1998; Saborio et al. 1998; Wang et al. 1998). More recently, the integration of these individual procedures into fully automated systems has facilitated the execution of larger-scale experiments. These include projects such as automated protein crystallization and analysis (Weselak et al. 2003), mass spectroscopy for protein–ligand interactions (Benkestock et al. 2003), expression of soluble recombinant proteins (Busso et al. 2003), mammalian cell-line propagation and preparation (Chapman 2003), and the sequencing of the human genome (McPherson et al. 2001; Venter et al. 2001). As laboratory robotics becomes more modular and pervasive in common research settings, it is likely that molecular and cellular biology labs will possess robust robotic platforms that routinely tend to lengthy and repetitive tasks and thus provide the end-user with more analysis and management time. For instance, scientists...