With the rapid development of high-throughput sequencing technology over the past ten years, the cost of DNA sequencing is decreasing much faster than data processing. Given that such research creates huge amounts of data, cloud computing is becoming a favorable solution for large-scale bioinformatic analysis, both in terms of resource utilization, flexibility, and efficiency, as well as time and cost savings for massive data generation and computation.

“To meet the increasing demand for bioinformatics analysis, BGI has developed a high performance platform for researchers, comprising the distributed cloud computing pipelines and tools.” said Ye Yin, Director of Research and Cooperation Division at BGI, “From the beginning of this year, BGI has conducted many testing and adjustment on the system in several different centers. I’m so excited that BGI-BOX has been successfully launched as scheduled. With this server, researchers could conduct the bioinformatics analysis with fast turnaround time and lower cost.”

The system of BGI-BOX contains a series of BGI’s standard bioinformatics analysis pipelines and software, including assembly tools, genetic variation analysis software, among others. There are two ways for remote users to easily access BGI’s cluster computing and storage resources: one is logging on to BGI-BOX directly and locally, the other is logging on to BGI’s computing centers by remote access. With this cloud computing terminal server, users not only can perform basic bioinformatics analysis based on the genomic data, but also can conduct customized analysis on a variety of biological data sets by choosing relevant software and adjusting specific parameters under each analysis module.

“The debut performance of BGI-BOX is satisfactory. Many of our collaborators have expressed their willingness to install BGI-BOX in their labs in order to share and exchange data in a cloud environment.” said Yin Ye. “In the first quarter of next year, we plan to install 50 BGI-BOXs worldwide to build a powerful and efficient cloud platform and support our partners with convenient access of bioinformatics analysis at hand.” He added.

Nekrutenko said that he and his team first developed the Galaxy computing system in 2005 because “biology is in a state of shock. Biochemistry and biology labs generate mountains of data, and then scientists wonder, ‘What do we do now? How do we analyze all these data?’” Galaxy, which was developed at Penn State and continues to use the University’s servers for its computing power, solves many of the problems that researchers encounter by pulling together a variety of tools that allow for easy retrieval and analysis of large amounts of data, simplifying the process of genomic analysis. As described in one of the team’s early papers in the journal Genome Research, Galaxy “combines the power of existing genome-annotation databases with a simple Web portal to enable users to search remote resources, combine data from independent queries, and visualize the results.” Galaxy also allows other researchers to be able to review the steps that have been taken, for example, in the analysis of a string of genetic code. “Galaxy offers scientific transparency — the option of creating a public report of analyses. So, after a paper has been published, scientists in other labs can do studies in order to reproduce the results described,” Nekrutenko said.

Now, Nekrutenko’s team has taken Galaxy to the next level by developing an “in the cloud” option using, for example, the popular Amazon Web Services cloud. “A cloud is basically a network of powerful computers that can be accessed remotely without the need to worry about heating, cooling, and system administration. Such a system allows users, no matter where they are in the world, to shift the workload of software storage, data storage, and hardware infrastructure to this remote location of networked computers,” Nekrutenko explained. “Rather than run Galaxy on one’s own computer or use Penn State’s servers to access Galaxy, now a researcher can harness the power of the cloud, which allows almost unlimited computing power.” As a case study, the authors report on recent research published in Genome Biology in which scientists, with the help of Ian Paul, a professor of pediatrics at Penn State’s Hershey Medical Center, analyzed DNA from nine individuals across three families using Galaxy Cloud. Thanks to the enormous computing power of the platform, the researchers were able to identify four heteroplasmic sites — variations in mitochondria, the part of the genome passed exclusively from mother to child.

“Galaxy Cloud offers many advantages other than the obvious ones, such as computing power for large amounts of data and the ability for a scientist without much computer training to use DNA-analysis tools that might not otherwise be accessible,” Nekrutenko said. “For example, researchers need not invest in expensive computer infrastructure to be able to perform data-intensive, sophisticated scientific analyses.”

Yet another advantage of Galaxy Cloud is its data-storage capacity. Using the Amazon Web Services cloud, researchers have the option of storing vast amounts of data in a secure location. “There are emerging technologies that will produce 100 times more data than existing ‘next-generation’ DNA sequencing, which already has reached the point where even more storage becomes an issue, not to mention analysis,” Nekrutenko said.

Perera and his team of biologists operate a state-of-the-art genome sequencing laboratory to compare patterns of microRNAs and their target gene expression in melanoma cells and normal melanocytes in hopes of finding differences that could be targeted for new diagnostics or therapeutics.

Their research found that melanocyte growth and the cancer’s ability to invade other tissue is partially controlled by abnormal expression of microRNAs. “We’ve identified two specific microRNAs, called miR-375 and miR-34b, which could be used not only as novel diagnostic markers for early melanoma detection, but may also serve as therapeutic targets,” explained Perera.

Because the team looked at so many different cells and patient samples, they generated a lot of data through next-generation sequencing technology that needed to be annotated and interpreted. Perera set out to find someone with the expertise and computing power to help him analyze the data. That’s when he met Shaojie Zhang, Ph.D., an assistant professor of engineering and computer science at UCF, whose expertise is in bioinformatics. Dr. Zhang and his graduate students analyzed the data using a computer program to identify differences in gene expression and methylation patterns between healthy and diseased cells.

“The collaboration between genomics and bioinformatics, two of the most advanced technologies in biomedical research, empowered this important research. These discoveries offer the possibility that the microRNAs we identified could be used as biomarkers to assist in earlier diagnoses of this fatal cancer,” Perera said.

For Zhang, the partnership has also meant an opportunity to give his graduate students real-world experience. “The collaboration provides an interdisciplinary education opportunity to the graduate students from the College of Engineering and Computer Science who are interested in applying their computational skills to biomedical research,” Zhang said. “The partnership not only helps advance science, but it also helps train future scientists. I’m very pleased to be a part of it.”

http://miami.blogger.cbslocal.com/most-valuable-blogger/vote/misc/

Chemistry students at IRSC

by Michael Adams, Chair, IRSC Foundation Board of Directors

To compete in the global economy, we need to prepare our students to out-think and out-perform their counterparts around the world. Indian River State College is at the center of a regional effort to boost interest and achievement in science, technology, engineering and math. These “STEM” disciplines are at the root of discoveries that lead to business expansion and new jobs.

IRSC has launched a wide range of initiatives that foster scientific aspiration. This summer, future science teachers engaged in marine research, developing fascinating videos and experiments to bring back to their classrooms and build enthusiasm about science among teens. The program is one of several elements of Florida’s Center for Ocean Sciences Education Excellence (COSEE Florida), based at IRSC in partnership with nationally recognized science organizations. High school students at the Clark Advanced Learning Center, a charter high school on the IRSC campus in Stuart, conduct field studies of Florida ecology. This hands-on experience helps them consistently earn top science scores on Florida’s assessment test.

The College’s state-of-the-art science laboratories are utilized by an increasing number of students each semester to develop the skills they need for a career in biotechnology – skills sought by the biomedical research firms moving here. In fact, an IRSC chemistry student Jason Fenwick was one of the first laboratory technicians hired by Torrey Pines Institute for Molecular Studies when the California firm expanded to this area. IRSC graduate Michael Cartwright is working at his dream career as a research technician helping find cures for diseases at the Vaccine and Gene Therapy Institute (VGTI) in Port St. Lucie.

It is vitally important that we pave the way for the “next generation” of scientists and that other students like Jason and Michael have the opportunity to develop the knowledge and expertise they need for a rewarding career.

Now under construction, IRSC’s STEM Center at the St. Lucie West Campus will serve as a feeder program, providing skilled employees for nearby research institutes. With the College experiencing 20% enrollment growth in the sciences, the three-story facility will provide much-needed classroom space and sophisticated teaching laboratories in genetics, chemistry, ecology, molecular science, botany and microbiology. The focus will be on linking math and science concepts to real-world applications.

State funding will help support construction of the 56,000 square-foot facility, but private support is needed to enhance the technology that will provide students with experience in the latest procedures and research methods. The IRSC Foundation’s goal is to raise $1 million in support of technology and laboratory equipment, ensuring that graduates are well-prepared to move into research-based technician positions and continue their education at the graduate level.

Nine US metropolitan regions are well-known for their biotechnology focus, because they have created a favorable climate for research and conversion of ideas into products. As our region diversifies its economy and transitions to the “Research Coast,” it is essential that we provide our young people and career-changers with the knowledge and skills they need to become employed and advance with these types of research enterprises. The availability of an educated workforce is a vital component in building that supportive business climate.

We invite you to contact the IRSC Foundation and visit our campuses to see first-hand how IRSC is using education as the springboard for economic development, individual empowerment and the realization of our community’s full potential. For more information or to schedule a tour, please contact adecker@irsc.edu

“Our j5 is the only software package today that both standardizes and cost-optimizes the DNA construction process,” says Hillson, who directs JBEI’s Synthetic Biology program and also holds an appointment with the Lawrence Berkeley National Laboratory (Berkeley Lab)’s Physical Biosciences Division. “Through the design of short DNA sequences that can be used to join longer sequences together in recombinant DNA assemblies, the j5 software improves the accuracy, scalability, and cost-effectiveness of DNA construction.”

DNA construction is the process by which multiple genes or fragments of DNA sequences are physically assembled together. Such constructs are valuable for developing new medical treatments and for engineering microbes to efficiently carry out a specific task, such as converting cellulosic biomass into clean, green, renewable transportation fuels.

DNA construction incorporates DNA sequence fragments – often referred to as “parts” – from a variety of organisms  into a self-replicating genetic element, such as a bacterial plasmid, that will propagate the assembled parts in a host cell. Traditionally, this has been accomplished through the use of a panoply of restriction enzymes for splicing desired DNA sequence fragments, and ligation enzymes for bonding the fragments to plasmid cloning sites.

“As the size and number of parts to be incorporated into the plasmid increases, traditional construction of recombinant DNA assemblies becomes ever more difficult,” says Hillson. “The process must often be repeated from scratch for alternate combinations of parts, and every time you clone a different gene or fragment, you might have to use a different pair of restriction sites. This has been a labor-intensive and time-consuming process.”

With modern DNA construction techniques, Hillson says, a small number of enzymes can be used over and over again, independent of the DNA sequence fragments being assembled, and thereby enabling automation with robotic platforms. However, designing protocols for these modern DNA construction approaches can be as labor-intensive, time-consuming and error-prone as the traditional approach. Furthermore, it is now increasingly important to consider outsourcing portions of DNA construction – to companies that chemically synthesize long sequences of DNA – as a cost-effective alternative. To address these considerations Hillson created the j5 software package.

“The j5 software package is a Web-based computer application that automatically designs and optimizes state-of-the-art DNA construction protocols,” Hillson says. “Within minutes it can determine the optimal flanking sequences that should be attached to each DNA part to produce the desired recombinant DNA at the least expense, in a manner that is executable by hand or robotics.”

As a result, researchers can direct their resources to investigating their primary interests, rather than preparing the DNA that is merely a tool in their experiments.

“At JBEI, we want researchers spending their time designing their DNA constructs and assaying their function,” Hillson says. “We don’t want them to waste their time building these things in the lab, so we’re trying to go after ways of taking that burden off them.”

In addition to identifying the most cost-effective strategies for DNA cloning, j5 also makes it possible to construct combinatorial libraries – collections of hundreds to millions of related DNA assemblies, each with a different combination of genes or parts that perform similar functions in different organisms. Combinatorial libraries enable scientists to select the most effective genetic combination for achieving a desired result, e.g., the most efficient production of a biofuel or medication in a given host. No other automated DNA cloning software does this on the same scale and as fast and effectively as j5.

“Combinatorial libraries can be screened to identify the gene combination that, when transferred into a desirable host organism, results in the most productive enzyme pathway,” says Hillson. “The j5 software is the only program that enables the combinatorial design of scarless DNA construction methods.”

Traditional DNA construction methods result in scars – uncontrolled portions of the DNA sequence – at DNA fragment junctions that can adversely impact function. Says Hillson, “The gold standard for combinatorial libraries is the ability to control the DNA sequence at every single base pair and this is what j5 allows you to do.”

The j5 software package features a graphical interface that enables users to design a DNA construct or combinatorial libraries through the arrangement of individual part icons that abstractly represent underlying DNA sequences. Outputs are in the form of user-friendly spreadsheets that detail the resulting designed experimental protocols, providing instructions that can either be followed by a person in the laboratory or fed directly into a robotic platform for a machine to carry out.

“Our j5 software is already allowing a growing number of scientists to save financial resources and months of work that was previously devoted to constructing recombinant DNA, and has now been redirected to other fruitful aspects of their work,” Hillson says. Currently, over 110 institutions worldwide are registered users of j5.

Other members of Hillson’s j5 development team were Rafael Rosengarten, Joanna Chen, Douglas Densmore and Timothy Ham.

The Web-based version of j5 is available to non-commercial users under a no-cost license agreement. Commercial users can access the Web-based version of j5 on a 14-day trial basis before entering into a licensing agreement. To view a demonstration video of the software and the j5 user’s manual, visit the j5 Website at http://j5.jbei.org/

“It’s similar to how an engineer designs a plane or a car,” said Howard M. Salis, assistant professor in agricultural and biological engineering, and chemical engineering. “When designing a biological organism, there are many combinations that the engineer must test to find the best combination. This technology allows us to quickly identify the best DNA sequence for a particular biotechnological application.”

The program, called a DNA compiler, designs synthetic DNA sequences to control protein production inside simple organisms. Salis said narrowing down the exact genetic plans from the billions of possible sequence combinations will save biotechnology companies money and time.

To produce proteins, which are integral for creating and maintaining cells, an organism’s DNA sequence controls the proteins that it makes and how much of each protein is produced.

DNA serves as a genetic template to create messenger RNA — mRNA. Another form of RNA, transfer RNA, carries amino acids, the components of proteins, as ingredients for the proteins.

The software predicts how fast an organism will produce a specific protein. It can also design new DNA sequences to increase or decrease protein production across a large scale and to find the best protein production rates.

Salis, whose work appears in a recent issue of Methods in Enzymology, said that synthetic DNA sequences will play a more important role in industries as diverse as medicine and manufacturing. The biofuel industry is particularly interested in maximizing the amount of proteins produced to optimize metabolism. To be profitable, companies have to produce large quantities of biofuels.

“We’re learning how to predict, control and design the behavior of biological organisms,” said Salis. “We can do it much faster than evolution.”

In one of the software’s modes, genetic engineers can type strings of letters A, T, G and C that represent adenine, thymine, guanine and cystosine — molecules in DNA— into the software, which then calculates which protein will be made and how much protein will be produced, said Salis. In another mode, engineers select a protein’s production rate inside the organism and the software optimizes a synthetic DNA sequence to achieve that rate.

Currently, genomic data is analyzed mainly by information specialists rather than by the biologists who designed the experiments that produce the data. GenPlay was created with the goal of offering biologists a user-friendly, multi-purpose tool that can help them visualize, analyze and transform their raw data into biologically relevant tracks.

“The first human genome was sequenced 10 years ago by an international consortium at a cost of $7 billion,” notes GenPlay co-developer Eric Bouhassira, Ph.D., professor of medicine and of cell biology, and the Ingeborg and Ira Leon Rennert Professor of Stem Cell Biology and Regenerative Medicine at Einstein. “But today, a complete genome can be sequenced for less than $10,000 and the cost is predicted to drop to less than $1,000 in a few years. The dramatic dip in cost has led to the creation of an avalanche of new data that biologists are having trouble analyzing. GenPlay is intended to make it easier for biologists to make sense of their data.”

A dozen or so genome browsers are currently available. GenPlay offers a major advantage over the others, says Dr. Bouhassira, because it “emphasizes letting biologists take control of their own data by providing continuous visual feedback together with extremely rapid browsing at every decision point during an analysis.”

GenPlay handles three major types of data: data from gene expression studies, epigenetic data, and single nucleotide polymorphism (SNP) data. The free GenPlay software is available from http://www.genplay.net.