The President recently visited the NIH and let everyone in on his secret, world-class, molecular biology lab. Flow cytometer included!
H/T NIH
Posts Tagged ‘molecular biology’
President Obama Secretly Tinkering with Molecular Biology
:: Posted by American Biotechnologist on 12-09-2014
The Challenge of Modern Day Science
:: Posted by American Biotechnologist on 10-14-2014In recent years, there have been incredible advances in scientific tools available at our disposal. As a result, the rate of scientific discovery and the amount of data produced by molecular biologists and proteomic specialists has been astounding. Projects such as the Cancer Genome Atlas and the ENCODE Project have generated billions of data points and provide opportunities for original researchers and other investigators to use these results in their own work to advance our knowledge of biology and biomedicine. This data explosion has challenged scientists and funding agencies to come up with new models for dealing with this massive amount of data in the most efficient way possible.
In order to tackle this challenge, the National Institute of Health (NIH), has created a Big Data to Knowledge (BD2K) initiative to enable biomedical research as a digital research enterprise, to facilitate discovery and support new knowledge, and to maximize community engagement. So far this year, the NIH has invested $32 Million in BD2K with an additional $624 Million expected to be injected into the project by the year 2020.
According to NIH director Francis S. Collins:
Mammoth data sets are emerging at an accelerated pace in today’s biomedical research and these funds will help us overcome the obstacles to maximizing their utility. The potential of these data, when used effectively, is quite astounding.
Note Dr. Collins’ use of the words “when used effectively.” Effective use and analysis of massive data sets requires open collaboration between scientists across various disciplines and nationalities. Governments play a critical role in facilitating such collaboration and science-friendly collaborative policies are not always forthcoming. Furthermore, lack of data standards for many types of data, and the low adoption of data standards across the research community has also proven to be a significant obstacle to the efficient used of Big Data. In addition, many scientists also do not have the opportunity or facility to use big data and have not been trained in the computational skills to access and analyze large data sets.
Let’s hope that the recent grants awarded by the NIH strengthen the effective use of Big Data so that the time and effort spent in creating this data does not go to waste.
A Revolution in Pipetting
:: Posted by American Biotechnologist on 08-05-2014A team of Whitehead Institute researchers is bringing new levels of efficiency and accuracy to one of the most essential albeit tedious tasks of bench science: pipetting. And, in an effort to aid the scientific community at large, the group has established an open source system that enables anyone to benefit from this development free of charge.
Dubbed “iPipet,” the system converts an iPad or any tablet computer into a “smart bench” that guides the execution of complex pipetting protocols. iPipet users can also share their pipetting designs with each other, distributing expertise across the research community. The system, created by researchers in the lab of Whitehead Fellow Yaniv Erlich, is described in detail in a letter appearing this week in the journal Nature Methods.
Erlich says that today’s experiments frequently rely on high-throughput methods that combine large numbers of samples with large scale, complex pipetting designs. Pipetting errors can lead to experimental failure. Although liquid-handling robots would seem to be a logical choice for such work, they are also extremely expensive, difficult to program, and require trained personnel. Moreover, they can be plagued by technical snafus, ranging from bent or clogged tips to an inability to capture liquids lying close to the bottoms of individual wells.
“We needed an alternative to costly robots that would allow us to execute complex pipetting protocols,” says Erlich. “This is especially important when working with human samples that are often in limited supply.”
iPipet illuminates individual wells of standard 96- or 384-well plates placed on top of a tablet screen, guiding users through the transfer of samples or reagents from source to destination plates according to specific designs. Users create their own protocols in Microsoft Excel files in comma-separated format and upload them to the iPipet website, which generates a downloadable link for execution on a tablet computer. Included on the iPipet site are a variety demos and an instructional video.
So, how well does iPipet work? Beautifully, according to members of the Erlich lab. In a test of the tool against a liquid-handling robot, iPipet enabled nearly 3,000 fixed-volume pipetting steps in approximately seven hours. After significant time spent on calibration, the robot accomplished only half that number of steps in the same allotted time. To date, one of the only challenges lab users have encountered is keeping well plates in a fixed position on the tablet screen. For that, Erlich’s team provides a solution: a 3D printed plastic adaptor that users can create with a file accessible via the iPipet website.
“The entire iPipet system is open source,” says Erlich. “We want to maximize the benefit for the community and allow them to further develop this new man-machine interface for biological experiments”
Thanks to Whitehead Institute for Biomedical Research for contributing this story.
Scientists capture most detailed images yet of tiny cellular machines
:: Posted by American Biotechnologist on 06-03-2014A grandfather clock is, on its surface, a simple yet elegant machine. Tall and stately, its job is to steadily tick away the time. But a look inside reveals a much more intricate dance of parts, from precisely-fitted gears to cable-embraced pulleys and bobbing levers.
Like exploring the inner workings of a clock, a team of University of Wisconsin-Madison researchers is digging into the inner workings of the tiny cellular machines called spliceosomes, which help make all of the proteins our bodies need to function. In a recent study published in the journal Nature Structural and Molecular Biology, UW-Madison’s David Brow, Samuel Butcher and colleagues have captured images of this machine, revealing details never seen before.
In their study, they reveal parts of the spliceosome — built from RNA and protein — at a greater resolution than has ever been achieved, gaining valuable insight into how the complex works and also how old its parts may be.
By better understanding the normal processes that make our cells tick, this information could some day act as a blueprint for when things go wrong. Cells are the basic units of all the tissues in our bodies, from our hearts to our brains to our skin and lungs.
It may also help other scientists studying similar cellular machinery and, moreover, it provides a glimpse back in evolutionary time, showing a closer link between proteins and RNA, DNA’s older cousin, than was once believed.
“It gives us a much better idea of how RNA and proteins interact than ever before,” says Brow, a UW-Madison professor of biomolecular chemistry.
The spliceosome is composed of six complexes that work together to edit the raw messages that come from genes, cutting out (hence, splicing) unneeded parts of the message. Ultimately, these messages are translated into proteins, which do the work of cells. The team created crystals of a part of the spliceosome called U6, made of RNA and two proteins, including one called Prp24.
Crystals are packed forms of a structure that allow scientists to capture three-dimensional images of the atoms and molecules within it. The crystals were so complete, and the resolution of the images so high, the scientists were able to see crucial details that otherwise would have been missed.
The team found that in U6, the Prp24 protein and RNA — like two partners holding hands — are intimately linked together in a type of molecular symbiosis. The structure yields clues about the relationship and the relative ages of RNA and proteins, once thought to be much wider apart on an evolutionary time scale.
“What’s so cool is the degree of co-evolution of RNA and protein,” Brow says. “It’s obvious RNA and protein had to be pretty close friends already to evolve like this.”
The images revealed that a part of Prp24 dives through a small loop in the U6 RNA, a finding that represents a major milestone on Brow and Butcher’s quest to determine how U6’s protein and RNA work together. It also confirms other findings Brow has made over the last two decades.
“No one has ever seen that before and the only way it can happen is for the RNA to open up, allow the protein to pass through, and then close again,” says Butcher, a UW-Madison professor of biochemistry.
Ultimately, Butcher says they want to understand what the entire spliceosome looks like, how the machines get built in cells and how they work.
While this is the first protein-RNA link like this seen, Brow doesn’t believe it is unique. Once more complete, high-resolution images are captured of other RNA-protein machines and their components, he thinks these connections will appear more commonly.
He hopes the findings mark a transition in the journey to understand these cellular workhorses.
“It’s exciting studying these machines,” he says. “There are only three big RNA machines. Ours evolved 2 billion years ago. But once it’s figured out, it’s done.”
The U6 crystal structure was imaged using the U.S. Department of Energy Office of Science’s Advanced Photon Source at Argonne National Laboratory. The work was funded by a joint grant from the National Institutes of Health shared by Brow and Butcher.
Thanks to University of Wisconsin-Madison for contributing this story.
Suprise! mRNA and Protein Levels Do Not Always Correspond!
:: Posted by American Biotechnologist on 03-27-2014The central dogma of molecular biology states that DNA codes for RNA and RNA codes for protein. It was widely understood that because protein is translated from mRNA, the amount of mRNA in a cell would somewhat correspond to the quantity of cellular protein. In a new study out of Notre Dame, scientists have shown that this theory is not always correct. While in many cases mRNA and protein levels do correspond, there are a surprisingly high number of exceptions, demonstrating that the amounts of a particular protein can be controlled by multiple mechanisms.
Bioanalytical chemist Norman Dovichi and molecular biologist Paul Huber identified and measured the levels of about 4,000 proteins, which exhibited patterns of expression that reflect key events during early Xenopus development resulting in the largest data set on developmental proteomics for any organism.
The study was conducted in Xenopus laevis embryos, which is a favored model for this type of research. In Xenopus, development takes place in well-defined stages outside the mother, thereby allowing embryogenesis to be monitored in real time. Additionally, embryos develop rapidly, achieving a nearly fully developed nervous system within four days.
Their results are available open access in Scientific Reports.