John A. Boyle

Sequential folding of transfer RNA: A nuclear magnetic resonance study of successively longer tRNA fragments with a common 5′ end

Abstract Most folding studies on proteins and nucleic acids have been addressed to the transition between the folded and unfolded states of an intact molecule, where an entire residue sequence is present during the folding event. However, since these polymers are synthesized sequentially from one terminus to the other in vivo, their folding pathways may be influenced greatly by the sequential appearance of the residues as a function of time. The three-dimensional structure of yeast tRNAPhe in the crystalline state is correlated with 360 MHz proton nuclear magnetic resonances from three fragments plus an intact molecule of the tRNA that share a common 5′ end and are in a solution condition similar to that of the crystal structure. This has allowed identification of folded structures present in the fragments and presumably present in the growing tRNA molecule as it is being synthesized from the 5′ end. The experiments show that only the correct stems are formed in the fragments; no additional or competing helical region is produced. This suggests that in the biosynthesis of this tRNA, correct folding of helical stems occurs before the entire molecule is formed. Further, some of the tertiary interactions (hydrogen bonds) found in the crystal structure are also probably present before the synthesis is completed. These findings are generalized to consider the precursor of the tRNA as well as other tRNAs.

Bioinformatics in undergraduate education: Practical examples

Bioinformatics has emerged as an important research tool in recent years. The ability to mine large databases for relevant information has become increasingly central to many different aspects of biochemistry and molecular biology. It is important that undergraduates be introduced to the available information and methodologies. We present a problem‐based approach for incorporation of bioinformatics into existing courses. Examples of exercises are presented along with resources available on the World‐Wide Web.

Adapting the polymerase chain reaction to a double-stranded RNA genome

We have adapted the polymerase chain reaction (PCR) to a double-stranded RNA (dsRNA) target without possessing unambiguous sequence information. Infectious bursal disease virus of chickens, a member of the binavirus group, has a dsRNA genome which is resistant to denaturation and subsequent enzyme modification. The only published sequence information was for a strain of virus unavailable to us. We have used a quick primer binding assay to select appropriate primers and have combined a simple denaturation method with reverse transcription and subsequent polymerization using the cDNA template to yield amplified product easily detectable by ethidium bromide staining. By varying the times of denaturation, annealing, and polymerization and by reducing the total number of amplification cycles, artifacts have been eliminated when using purified genome as the template. This allowed us to obtain partial sequence information for one viral strain. We have enhanced the utility of our method by optimizing a rapid cell lysis and capsid digestion protocol such that no purification steps are required from initial tissue handling through final PCR product. Total time for all procedures involved no more than 6 h. This technique should be applicable to all other members of the Birnaviradae family and to any other species of dsRNA.

Biology must develop its own big-data systems

The last week of April was designated Big Data Week. But in modern biology, every week is big-data week: life-sciences research now routinely churns out more information than scientists can analyse without help. That help increasingly comes in the form of expensive data-management systems, but these are hard to design and most are even harder to use. As a result, a long line of data-management projects in the life sciences — many of which I have been involved with — have failed. The size, complexity and heterogeneity of the data generated in labs across the world can only increase, and the introduction of cloud computing will encourage the same mistakes. Just a stone’s throw from where I work, at least three computer companies are already touting cloud-based data-management systems for the life sciences. We need to find ways to manage and integrate data to make discoveries in fields such as genomics, and we need to do this quickly. At their most basic, data-management systems allow people to organize and share information. In the case of small amounts of uniform data from a single experiment, this can be done with a spreadsheet. But with multiple experiments that produce diverse data — on gene expression, metabolites and protein abundance, for example — we need something more sophisticated. An ideal data-management system would store data, provide common and secure access methods, and allow for linking, annotation and a way to query and retrieve information. It would be able to cope with data in different locations — on remote servers, on desktops, in a database or spread across different machines — and formats, including spreadsheets, badly named files, blogs or even scanned-in notebooks. That ideal system does not exist. Most academic organizations have, through trial and error, developed their own in-house systems that work — or just about. The systems have limited functionality and cannot be connected, which makes collaboration difficult. The situation is as unworkable as if every lab in the country had decided to devise its own (poor) document-editing software. Efforts to introduce overarching data-management systems, to which any and all scientists in a particular field could plug in, have failed for two main reasons. Either they demand that scientists change the format of their data, to allow information to be entered into the system, or they demand that scientists change the way they work, to generate standardized sets of results. The systems are thrust on scientists who are then expected to change, rather than taking the work of scientists as a starting point. It should not be scientists who are required to be flexible; it should be the system that they are being asked to use. These problems are exemplified by the expensive flop that was the US National Cancer Institute’s caBIG data-integration project, scrapped last year after almost a decade and tens or even hundreds of millions of dollars. It had admirable goals and seemed workable in theory, but in the end it was too complicated to use. Crucially, caBIG relied on standardized data formats, which called for standardized experiments. Its one-size-fits-all approach fit nearly nobody. There have been some successes. A widely used system called SRS allows the linking of data held in separate well-structured repositories. And the Biomart project joins up specially designed databases. But these were both fairly bespoke research applications; computer giants Microsoft and IBM are among the commercial firms that have introduced systems that aimed at a wider reach but had little impact. To be useful to the life-sciences community, a data-management system probably needs to be devised and developed by the life-sciences community. The US National Institutes of Health has a ‘Big Data’ initiative, and agency head Francis Collins has spoken many times of the need to address the problem. Now is the time for researchers to plan an open data-management system that scientists will want to adopt. Many of the software pieces are already available. As a starting point, here are three lessons from the successes and failures of the past. First, the data are going to change. Biological information will always come in varied formats, and these formats cannot be defined in advance. Software engineers hate this. But a useful system must be flexible and updatable. Second, people are not going to change. Busy scientists will adopt a new system only if it offers substantial benefit and is painless. Many commercial systems are unpopular because they make simple steps such as data retrieval complicated, to stop scientists using several (rival) systems at once. Third, the problem is not technical. Although the latest kit is always alluring to funders, today’s cutting-edge devices will be blunt tomorrow. Data-management systems must be driven by the need to find a workable solution to the problem, not by a desire to make the problem fit the latest fashionable technology. Development of a biology-friendly system is possible, but it will require a change in mentality. As a useful test, a good data-management system should cost more to maintain, update and change with the times than it does to develop. Otherwise the price is too high. ■

Detection of Channel Catfish Virus in Adult Channel Catfish by Use of a Nested Polymerase Chain Reaction

Abstract Optimal polymerase chain reaction (PCR) conditions were determined with nested primers targeted to the DNA polymerase gene of channel catfish virus (CCV). Serial dilutions of CCV DNA in the presence or absence of DNA of channel catfish Ictalurus punctatus were used as templates throughout the optimization procedure. The final PCR product was detected by visualization in acrylamide gels stained with ethidium bromide. Fewer than 10 copies of CCV DNA (about 1 fg) could be detected in the presence of 108 times as much channel catfish DNA. The optimized two-step PCR assay allowed detection of latent CCV in blood samples from healthy broodfish. Our results make possible the development of a routine testing procedure for catfish broodstock so that CCV can be eliminated in young catfish.

Revealing gene transcription and translation initiation patterns in archaea, using an interactive clustering model.

An interactive clustering model based on positional weight matrices is described and results obtained using the model to analyze gene regulation patterns in archaea are presented. The 5′ flanking sequences of ORFs identified in four archaea, Sulfolobus solfataricus, Pyrobaculum aerophilum, Halobacterium sp. NRC-1, and Pyrococcus abyssi, were clustered using the model. Three regular patterns of clusters were identified for most ORFs. One showed genes with only a ribosome-binding site; another showed genes with a transcriptional regulatory region located at a constant location with respect to the start codon. A third pattern combined the previous two. Both P. aerophilum and Halobacterium sp. NRC-1 exhibited clusters of genes that lacked any regular pattern. Halobacterium sp. NRC-1 also presented regular features not seen in the other organisms. This group of archaea seems to use a combination of eubacterial and eukaryotic regulatory features as well as some unique to individual species. Our results suggest that interactive clustering may be used to examine the divergence of the gene regulatory machinery in archaea and to identify the presence of archaea-specific gene regulation patterns.

The Embryo Lethality of Escherichia coli Isolates and Its Relationship to Various In Vitro Attributes

Abstract Based on the hypothesis that bacteria with minimal embryo lethality might be good candidates for vertical transmission, 103 lactose-positive Escherichia coli isolates were collected from different broiler-related conditions (sources) and analyzed using a variety of in vitro assays: biochemical profiles, sensitivity to antimicrobials, and the presence of plasmids in the 2000- to 16,000-base pair range. The results of these assays were analyzed to determine if they were associated with, or could be used as predictors of, the degree of lethality these isolates produced in 12-day-old embryos. In addition, the in vitro assay results were analyzed to determine if there was any correlation between any particular pair of factors. On the basis of biochemical profiles, the isolates were classified into 17 different groups; however, only a limited number of biochemical reactions separated a majority of the isolates. The isolates varied considerably in the number and size of plasmids they contained and in their sensitivity to the antimicrobials evaluated. The isolates also varied in their ability to kill chicken embryos—killing from 0% to 100% of those inoculated—yet significant differences were detected in lethality based on source and biochemical profile of the isolate. In addition, a predictive model for embryo lethality was constructed and evaluated based on three characteristics of these 103 isolates, namely, their ability to ferment raffinose and sorbose and their sensitivity to gentamicin.

Random cDNA probes to infectious bursal disease virus.

Viruses from three commercially available modified-live infectious bursal disease virus vaccines were propagated in tissue culture. Following this, a series of 32P-labeled probes was generated using the entire RNA genome as template for formation of randomly primed cDNAs. These probes were tested against dot blots of the three vaccine strains, as well as the USDA standard challenge strain and one field-origin strain. Dot blots were made of both crude tissue extract and LiCl-precipitated RNA genome. All three probes detected the standard challenge and field strains. Although differences in probe binding could be quantified among the strains, cross-hybridization indicated considerable homology within genomic regions preferentially transcribed under the experimental conditions.

Antigenic relatedness of small ribonucleoprotein particles

We have examined the relationships among small ribonucleoprotein particles found in eucaryotic cells by an antigen depletion technique using autoimmune antibodies. We have confirmed that the (U1) ribonucleoprotein particle antigen is found on the same complex as the Sm antigen. We have also shown that the Ro antigen is found on the same complexes as the La antigen. However, both Sm and La antigens are also found on complexes that are never associated with (U1) ribonucleoprotein particle and Ro, respectively. Further, U1 containing complexes can exist that contain the Sm antigen but not the (U1) ribonucleoprotein particle antigen. In a similar manner, we find several La-Ro RNA containing complexes that carry the La antigen but do not always carry the Ro antigen. Sm and La antigen are quantitatively associated with their specific ribonucleoprotein complexes.

Visualization of aligned genomic open reading frame data

Students can better appreciate the value of genomic data if they are asked to use the data themselves. However, in general the enormous volume of data involved makes detailed examination difficult. Here we present a web site that allows students to study one particular aspect of sequenced genomes. They are able to align the open reading frames (ORFs) of any available genome that is of reasonable size. The ORFs may be aligned using either the start codon or the stop codon as the starting points. Results will readily show the presence of common ribosome binding sites as well as reveal interesting order within the ORFs that is nonexistent outside of them. Students will be able to ask various questions involving comparisons of genomes and see the results presented in both a tabular and graphic format. An example problem is presented under “Results.”