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October 2014 Archive

Posted by Karen on October 1st, 2014  ⟩  0 comments

Lifesaving, man-made “nano-bots,” something long imagined in fiction, are now being brought to life through DNA origami. What started out as a nanoscale 3-D box sculpted from DNA, and later, 2-D renderings of DNA-drawn world maps, smiley faces, snowflakes and geometric figures, measuring only 100 nm across, has opened the door to a world of potential for nanotechnology.

DNA origami is the precise self-folding of DNA using a long, single-stranded scaffolding piece derived from the M13 phage, as well as smaller strands of nucleic acids or oligonucleotides called “staples.” These staples are what govern the folds of the larger DNA strand into a shape made of linear pleats known as a raster filled shape.

You have probably taken a single sheet of paper and folded it into a two-dimensional or three-dimensional shape. Maybe it even had some functionality. Or you have rolled out a long strand of clay and coiled it into a round or cube-shaped container. The idea of DNA origami is well-illustrated through these techniques, but the objects produced are approximately 1/1000 the size of a strand of hair.

DNA nanotechnology has its roots with Ned Seeman who, in 1991, created a nanosize DNA cube. His research won him the Feynman Prize in 1995. And in 2006, Nature featured Paul Rothemund’s work which describes a simplified folding method for single-stranded DNA to achieve complex, nanoscale DNA shapes. Rothemund’s results meant efficient, accurate folding that could lead to more intricate, biocompatible nanotools produced at low cost.

For nearly 10 years, a flood of subsequent research papers from labs around the world have shown promising results from experimental applications of DNA origami. Not only has the advent of this technology spurred intriguing options for disease treatment, but the very technique has also evolved. Now researchers no longer have to perform manual calculations for their designs; instead, open CAD software such as caDNAno is able to assist researchers and eliminate errors. 

As this technology continues to advance, scientists are finding several avenues for its use. Its small size and accuracy has allowed researchers to overcome resistance resulting from targeted cancer therapy.

In 2012, the Journal of the American Chemical Society published “DNA Origami as a Carrier for Circumvention of Drug Resistance.” This piece detailed the process of creating both triangular DNA origami structures and 3D tubular DNA origami structures. These structures were then used to carry doxorubicin into human breast adenocarcinoma cancer cells (MCF 7). While doxorubicin is a known treatment against MCF 7 cancer cells, resistance is often a side effect of targeted cancer therapy.

In this experiment, researchers not only tested the two carrier structures along with free doxorubicin in MCF 7 cells, they also tested in doxorubicin-resistant MCF 7 cells. The results were positive. Using DNA origami structures capable of targeting cancer cells showed efficacy against treatment-resistant cells.

DNA origami delivery structures are continuing to advance. Some of these structures are built with doors and hinges to open up and unload a drug into desired cells. They are even becoming more capable of carrying out programmed tasks.

Recently, Shawn Douglas of the University of California, San Francisco, Ido Bachelet of Bar-IIan University in Israel and George Church of Harvard University have opened the horizon for this technology even more by developing “ DNA origami robots.” These researchers examined DNA origami robot responses to VEGF within cockroaches to study how their carefully crafted suite of nano-bots would interact with one another and other biological molecules, especially for drug delivery. What their results showed is that these robots are able to imitate logical commands, almost acting like a computer within an organism.

Along with robotics, DNA origami is allowing scientists to accurately study distances between interacting proteins and molecules.

Swedish researchers from Karolinksa Institutet used DNA origami to build “ DNA calipers.” Using this tool, they studied interactions between the EphA2 receptor and ephrin molecules that act as its ligand. Their nanotool allowed them to test whether the distance between ephrin molecules had an impact on ligand-receptor communication. By accurately fusing ephrin molecules at varying distance along a DNA origami rod, the researchers were able to analyze how those distances between the ligands were able to induce a receptor response from neighboring cells. The results showed higher EphA2 activity observed in cancer cells when ligands were spaced closer together.

While the outcome of this experiment provides important clues about cancer cell behavior, it also affirms that DNA origami can be used as a powerful tool to study other protein relationships.

Unfortunately, we are probably a long way from seeing the clinical use of DNA origami drug carriers or tools, but as we move into the future, we can be assured that promising treatments will be there to meet us. In the meantime, the science behind it will become further refined and advance into new frontiers we have yet to discover.


Douglas, S., Bachelet, I., Church, G. (2012). A logic-gated nanorobot for targeted transport of molecular payloads. Science 335, pages 831-834. PMID: 22344439.

Jiang, Q., Song, C., Nangreave, J., Liu, X., Qiu, D., Wang, Z. G., … Ding, B. (2012). DNA origami as a carrier for circumvention of drug resistance. Journal of the American Chemical Society. Doi: 10.1021/ja304263n

Rothemund, P. (2006). Folding DNA to create nanoscale shapes and patterns. Nature. Doi: 10.1038/nature04586

Shaw, A., Lundin, V., Petrova, E., Fordos, F., Benson, E., Al-Amin, A., … Teixeira, A. (2014). Spatial control of membrane receptor function using ligand nanocalipers. Nature Methods 11, pages 841-846. Doi: 10.1038/nmeth.3025  

              Karen Martin
GoldBio Marketing Coordinator

"To understand the universe is to understand math." My 8th grade
math teacher's quote meant nothing to me at the time. Then came
college, and the revelation that the adults in my past were right all
along. But since math feels less tangible, I fell for biology and have
found pure happiness behind my desk at GoldBio, learning, writing
and loving everything science. 

Category Code: 79105 79102 88221

Posted by Chris on October 28th, 2014  ⟩  0 comments

When I was a young research associate, having just recently started down a career of molecular biology and facing the insurmountable task of figuring out what to work on, I received some of the best research advice from an equally young and unequivocally wise post-doc. As I sat at the lab bench one afternoon complaining that I just couldn't think of anything original to work toward, he advised me start reading as many papers as I could, and to constantly write down every question and idea I had based on those articles. Then, he told me to start searching for those ideas on PubMed to see if someone else had already published on it. To be sure, he continued, at the early stages of the search, I would find that my ideas would be published 10 or so years previous. But eventually, as I became more nuanced and cognizant of the literature, that number would continually decrease until I was asking questions that were being answered within the last few months of publications. And finally, after all of that, I would soon have an idea or ask a question to which I could not find the answer. That question would be my first testable hypothesis, something to build a graduate or post graduate life around.

IBM Watson - Hypothesis Generation

At the time, I found that answer daunting. Exactly how much did I really have to read? And when would I find the time to read all those papers when I was also expected to get work done in the lab as well? To many scientists, the answers to those two questions are no mystery: a LOT, and every available, waking minute. But being realistic, there is virtually no plausible way that a researcher in today’s world can keep up with the literature that is being produced at an ever-expanding rate. It was estimated that roughly 1 million articles were being published daily as of 2008, and there were estimated to be more than 50 million journal articles in existence as of 2009! Small wonder then that, as scientists, we have become increasingly specialized in increasingly narrow fields. There is simply too much to attempt to take in and little way for our brains to adequately absorb it all.

Even specialized fields can be inundated with such a surplus of journal articles that it makes any review process overwhelming. These article rich areas, such as biomedical research, often populate tens of thousands of published studies and reports. For perspective, in a field with just 10,000 published articles, a grad student would need to read nine papers a day, every day, for three years straight! And for a field of study for a highly cited protein like the p53 kinase, there are an estimated 70,000 published papers which would require a scientist to read almost 20 papers a day for 10 years! Sifting through so many papers is realistically only something a computer could adequately accomplish.

Instead, most of us cherry pick the papers that we read, skipping over (or perhaps not even noticing) papers that we think provide less value or ones that may harder to read for whatever reason. That behavior, as necessary as it is, may lead down research paths that have already proven to have negative or false positive results.

These problems are not new, nor have we been unaware of the problem. Developers and scientists have been working on various methods to build better and more articulate search algorithms for decades; to parse out relevant research from the bulk, to separate the chaff from the wheat, so to speak. Additionally, these search algorithms are being used to find novel research opportunities: avenues that may simply have been overlooked or lost in the shuffle of constant research results. Generally speaking, these systems have been collectively called “Automated Hypothesis Generators.” To one degree or another they work about as well as any Google search might, generating a list of papers to sift through and awarding some kind of power ranking to each paper which hopefully corresponds to the relevance of the original search.

Search queries are just queries though. They do not typically possess the understanding of the subtleties of our quixotic languages. They can spit out paper after paper that align word or even phrase association, but they just can’t answer a simple question: “What [insert Gene or protein of interest here] should I look for next?” There is, however, one computer that has shown that it can do just that: IBM’s Watson.

Most of us will probably remember Watson from its debut on Jeopardy several years ago when the computer managed to beat two of the all-time best Jeopardy champions, Brad Rutter and Ken Jennings, a feat long believed impossible to do. It was an amazing achievement, not just from the standpoint that a computer could outperform a human at trivia, but that Watson could reason through a spoken or written language and understand its context enough to generate correct answers.

Watson achieves this through a variety of technologies, including natural language processing (NLP), machine learning, and open domain question answering architecture. These “programs” are then backed by over 2500 GHz of processors and 16 terabytes of RAM (which STILL isn’t enough to merit being a member of the Top 500 Supercomputer List) and can likely process the equivalent of 1 million books per second. But it’s the human-question/computer-answer interaction that really makes Watson stand out compared to other powerhouse computer systems. There are potentially vast opportunities that such a system might present to the numerous fields of study in the world, and researchers led by Oliver Lichtarge at the Baylor College of Medicine wanted to see exactly how useful Watson could be for the scientific world and hypothesis generation.

When you’re a computer, there is an advantage in reading scientific literature over many other forms of literature. The dry, bare-bones and strictly analytical writing style of a medical study is the bane of sleep-deprived grad students everywhere, but it is also the perfect read for a computer that traditionally struggles with things like obscure allusions or tone. Even more so, the abstracts of those papers, written as the terse and tidy summary of the paper overall, drill down to the bare essentials that a computer actually needs in order to comprehend the primary points of an article.

Lichtarge’s group decided to test Watson with a selection of papers on the p53 kinase. P53 is an important protein that is in charge of the body’s defense system, responding to the presence of genomic problems, such as cancerous cells, and dispatching hundreds of other proteins to correct the error, or if that fails, to cause the affected cell to kill itself. There are more than 500 known kinases, and currently only 33 of those are known to modify p53. Finding novel, testable, p53 kinase targets would be a boon to cancer research and an excellent proof of concept of Watson’s power and resourcefulness. Lichtarge selectively truncated his list of papers to include only those of 259 kinases, of which 23 were known to be p53 kinase. Next, his team restricted Watson to only papers written prior to 2003, with 10 known p53 kinases at the time while 9 more were discovered over the next decade.

Watson was able crunch those a priori abstracts and accurately predict the existence of 7 of those 9 “undiscovered” p53 kinases! Imagine what the medical field would be like if scientists didn’t have to spend a decade of research to discover just one novel protein, followed by another decade of clinical trials to determine its effectiveness. Imagine how many of those novel proteins end up as dead ends in clinical trials and all the time and money that’s wasted investigating them. Watson could effectively eliminate that guessing, the lead time from discovery to production and the false positives that invariably raise drug costs!

The future of our research and discovery is upon us! Over the last 70 years, computers have progressively helped us save, catalog, categorize and locate the information that the human race has meticulously documented over the last 5000 years. But our ability to mentally codify and comprehend the extent of our own ever-increasing accrual of knowledge is failing to progress at the rate that we need. With computers such as Watson, we are standing on the cusp of an age of enlightenment in which computers quantifiably correlate our abundances of knowledge into an exponential era of discovery. It is an era I am excited to watch unfold.

As that most famous detective himself remarked, “It is one of those instances where the reasoner can produce an effect which seems remarkable to his neighbor, because the latter has missed the one little point which is the basis of the deduction.” Elementary indeed, Watson.

Spangler, S., Wilkins, A. D., Bachman, B. J., Nagarajan, M., Dayaram, T., Haas, P., ... & Lichtarge, O. (2014, August). Automated hypothesis generation based on mining scientific literature. In Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 1877-1886). ACM.

BJÖRK, B.-C., ROOSR, A., and LAURI, M., Global annual volume of peer reviewed scholarly articles and the share available via different open access options. In Sustainability in the Age of Web 2.0 - Proceedings of the 12th International Conference on Electronic Publishing, Toronto, Canada.

Jinha, A. E. (2010). Article 50 million: an estimate of the number of scholarly articles in existence. Learned Publishing, 23(3), 258-263.

Category Code: 79105 79101 88241 79102

Posted by David on October 8th, 2014  ⟩  0 comments

In part two of our series of blogs highlighting recently published research involving the use of bialaphos and PPT, we now present a summary of exciting research utilizing Gold Biotechnology’s bialaphos and phosphinothricin (PPT) to demonstrate dramatically improved Agrobacterium-mediated ryegrass transformation.

Perennial ryegrass, or Lolium perenne, stands as the preferred cool-weather pasture and forage grass in many regions throughout the world and it serves as an important groundcover. Although perennial ryegrass is suitable for all grazing livestock, it is primarily used as the main source of nutrition for lactating dairy cows, due to the superior quality and digestibility of this species. Ryegrass is also widely utilized as a turf grass and southern state `overseed’, comprising about 40% of the nearly 50 million acres of US lawns, and it is a favorite for use in sporting fields, such as the Kansas City Royals’ Kauffman Stadium, the Seattle Mariners’ Safeco Field and golf courses worldwide.

Despite the broad cultivation of this diploid monocot, it has been quite recalcitrant to genetic modification methods, save traditional breeding, with previous transformation efficiencies reaching only about 1%.  In a recent publication, North Carolina State scientists working under a grant from Bayer Crop Science and using GoldBio’s bialaphos and PPT, reported a dramatic improvement in transformation of Lolium perenne. The researchers achieved a level of 20% transformation efficiency via cocultivation of ryegrass callus with an Agrobacterium tumefaciens strain harboring a binary vector. This plasmid contained the bar gene, which provides resistance to bialaphos and PPT, and a gene encoding green fluorescent protein (GFP).

To take this significant step forward, the researchers at North Carolina State developed a variety of modifications to traditional methods of transforming perennial ryegrass. Transformation efficiency during each experiment was measured by counting the number of GFP-expressing callus and dividing this sum by the total number of callus cocultivated with the Agrobacterium strain.

The group first demonstrated a two-fold improvement in transformation efficiency via a change in infection culture medium. The scientists employed a Murashigie and Skoog (MS)-type media, instead of the more traditional YEP infection medium, when culturing the Agrobacterium strain. The strain was then used to infect two-to-six month old ryegrass callus tissue.

Next, the team determined that a three minute 42 °C heating treatment during the initial infection with the Agrobacterium strain allowed them to achieve a four-fold increase in GFP-expressing callus selected on GoldBio’s bialaphos or PPT (Figure 2 below). Further experiments (Figure 3) showed that increasing the maltose concentration from 3% to 6% in the cocultivation medium and switching to NS6 medium (similar to MS) for that step gave an additional four-fold increase in efficiency.

Catching GoldBio Ryegrass Fig 2-3

When transgenic bialaphos-resistant GFP-expressing plants were eventually grown from callus tissue transformed using a combination of the medium modifications and heating step described above, the efficiency was shown to be more than 20%, marking a 20-fold improvement over previous efficiency in this agriculturally important plant species. This equates to an average of 20 GFP-expressing plants, like those pictured in Figure 7, per 100 callus transformed. The authors proceeded to apply this learning to transformation of rice, Oryza sativa, and observed significant improvements in efficiency with that critical crop as well.

Catching GoldBio Ryegrass Fig 7

Our third blog entry in this series will discuss the generation of bialaphos-resistant soybean, using GoldBio products, that was developed at Nanjing University. GoldBio is excited to be the choice of researchers seeking to further understanding of the biology of crop plants important to populations throughout the world.

Patel, M., Dewey, R. E., & Qu, R. (2013). Enhancing Agrobacterium tumefaciens-mediated transformation efficiency of perennial ryegrass and rice using heat and high maltose treatments during bacterial infection. Plant Cell, Tissue and Organ Culture (PCTOC), 114(1), 19-29. Plant Cell Tiss Organ Cult (2013) 114:19–29 DOI 10.1007/s11240-013-0301-7

Zhang, W. J., Dewey, R. E., Boss, W., Phillippy, B. Q., & Qu, R. (2013). Enhanced Agrobacterium-mediated transformation efficiencies in monocot cells is associated with attenuated defense responses. Plant molecular biology, 81(3), 273-286. Plant Mol Biol (2013) 81:273–286

Category Code: 88241

Posted by Chris on October 14th, 2014  ⟩  0 comments

Our modern day view of our bodies has changed quite drastically over the last century. With increased medical knowledge and the ability to detect ever-smaller and rarer life, we have continuously advanced our awareness of the world beyond that which even science fiction could have envisioned in the early 1900s. Our appreciation of life has evolved from the quaint early 20 th century belief that our bodies are pristine and pure vessels of life that are occasionally invaded by malevolent unseen forces of evil. In this modern era, we are coming to grips with the knowledge that we are fortunate symbionts, providing an ideal environment for unseen and untold communities of bacterial life who in return work tirelessly to keep us sustained, stable and productive.

As the host, it is our responsibility to maintain the proper and healthy living conditions that our bacterial tenants require. That primarily means providing timely nourishment; and our body is constructed in such a manner to remind us, like the blinking of a “low fuel” light in a car, when we need to eat or drink. As long as we are healthy, this system works and has worked spectacularly for millions of years! But when we get really sick, when our system is either severely compromised or invaded and plundered by rogue bacteria and viruses, it can be the equivalent of a Chicxulub crater-like meteor impact on the biodiversity of life within our bodies.

However, even in situations that aren’t as dire as all that, in those times when we are plagued only by the more routine dilemmas of life like the common cold, our internal stability can be compromised, albeit to a somewhat lesser extent. Throughout the millennia, our bodies have developed their systems of emergency response. One of those responses is the temporary reallocation of energy demand. When we get sick, our bodies press all available resources into fighting the infection. Consequently, that also means that our bodies aren’t worrying about finding or ingesting food. That’s a great, short-term solution…just like temporarily pulling in army reserves to bolster troops in times of need.

Just like in a prolonged war, though, that doesn’t work so well in the event of a long-term infection. Without regular and continued nourishment, the bacteria that are helping to fight the infection starve and die off, unbalancing our delicately bacterial ecosystem or allowing the existing infection to gain traction. Neither is ideal, and it makes sense that our bodies would have accounted for such an annoying dilemma with its usual flare of resourcefulness and grace. Featured in this October's issue of Nature, Joseph Pickard and Alexander Chervonsky illustrate the novel way in which mice bodies handle a similar situation.

In an ensuing infection, gut microbes need to eat even as the body is forced into starvation mode. So the body utilizes a unique system that adds a fucose sugar onto globules of fats and proteins that the bacteria can use for nourishment in times of stress. It’s not ideal and is probably similar to a military MRE (Meal Ready-to-Eat) in terms of deliciousness, but it gets the job done. In order to generate that microbial MRE, the body uses Interleukin-22 (IL22) inside of intestinal epithelial cells to express the Fut2 gene. As proof of its nourishing ability, when mice that were genetically bred to lack the Fut2 gene were stressed with a simulation of an infection, they required an extra day to return to their normal weight than the control mice.

Pickard stated in the article, the mouse fitness could either be related to decreased pathogen burden (aka resistance) or increased pathogen tolerance. To prove their hypothesis, they measured the abundance and activity of the C. rodentium bacterial infection from each test group of mice using a GoldBio L-fucose substrate called 4-Methylumbelliferyl fucopyranoside (Cat # M-580). There was no difference in the pathogen loads between the test and control groups, which showed that the Fut2 expression most likely provides beneficial tolerance as opposed to resistance to infection.

Interestingly, Pickard also noted that there is a very similar pathway that regulates antimicrobial proteins and acts as a resistance mechanism inside the body. So perhaps tolerance and resistance goes hand in hand after all. Regardless, the entire story is shaping up to be a fascinating situation and one that definitely needs further investigation. For instance, the genetic deletion of the Fut2 gene happens in 1 out of every 5 people. Fut2 has also been associated with the inflammatory bowel disorder, Crohn’s disease. Crohn’s is a terrible disease that can affect any part of the GI tract and is a life-long, debilitating condition. Crohn’s disease also happens to be genetically predisposed to run in families.

There might not be a direct link to humans yet. But it may be that without the beneficial Fut2 gene, and the timely delivery of fucose nutrients to our microbial partners, our beneficial bacteria cannot survive in the wake of intestinal infection, their loss leading to more severe physical repercussions and disabilities that otherwise might be mitigated in a healthy individual. One thing is for certain, in sickness or in health, our very lives and the quality of those lives depend on a relationship we have with organisms we cannot see, creatures we do not know, and life of which we are just now becoming aware.

I can only imagine what amazing things we will learn throughout the next century of science!

Pickard, J. M., Maurice, C. F., Kinnebrew, M. A., Abt, M. C., Schenten, D., Golovkina, T. V., ... & Chervonsky, A. V. (2014). Rapid fucosylation of intestinal epithelium sustains host-commensal symbiosis in sickness. Nature.

Category Code: 79102 88241