Dr. Francis Collins
Posted on by Dr. Francis Collins
It is now possible to pull up the design of a guitar on a computer screen and print out its parts on a 3D printer equipped with special metal or plastic “inks.” The same technological ingenuity is also now being applied with bioinks—printable gels containing supportive biomaterials and/or cells—to print out tissue, bone, blood vessels, and, even perhaps one day, viable organs.
While there’s a long way to go until then, a team of researchers has reached an important milestone in bioprinting collagen and other extracellular matrix proteins that undergird every tissue and organ in the body. The researchers have become so adept at it that they now can print biomaterials that mimic the structural, mechanical, and biological properties of real human tissues.
Take a look at the video. It shows a life-size human heart valve that’s been printed with their improved collagen bioink. As fluid passes through the aortic valve in a lab test, its three leaf-like flaps open and close like the real thing. All the while, the soft, flexible valve withstands the intense fluid pressure, which mimics that of blood flowing in and out of a beating heart.
The researchers, led by NIH grantee Adam Feinberg, Carnegie Mellon University, Pittsburgh, PA, did it with their latest version of a 3D bioprinting technique featured on the blog a few years ago. It’s called: Freeform Reversible Embedding of Suspended Hydrogels v.2.0. Or, just FRESH v2.0.
The FRESH system uses a bioink that consists of collagen (or other soft biomaterials) embedded in a thick slurry of gelatin microparticles and water. While a number of technical improvements have been made to FRESH v. 2.0, the big one was getting better at bioprinting collagen.
The secret is to dissolve the collagen bioink in an acid solution. When extruded into a neutral support bath, the change in pH drives the rapid assembly of collagen. The ability to extrude miniscule amounts and move the needle anywhere in 3D space enables them to produce amazingly complex, high-resolution structures, layer by layer. The porous microstructure of the printed collagen also helps for incorporating human cells. When printing is complete, the support bath easily melts away by heating to body temperature.
As described in Science, in addition to the working heart valve, the researchers have printed a small model of a heart ventricle. By combining collagen with cardiac muscle cells, they found they could actually control the organization of muscle tissue within the model heart chamber. The 3D-printed ventricles also showed synchronized muscle contractions, just like you’d expect in a living, beating human heart!
That’s not all. Using MRI images of an adult human heart as a template, the researchers created a complete organ structure including internal valves, large veins, and arteries. Based on the vessels they could see in the MRI, they printed even tinier microvessels and showed that the structure could support blood-like fluid flow.
While the researchers have focused the potential of FRESH v.2.0 printing on a human heart, in principle the technology could be used for many other organ systems. But there are still many challenges to overcome. A major one is the need to generate and incorporate billions of human cells, as would be needed to produce a transplantable human heart or other organ.
Feinberg reports more immediate applications of the technology on the horizon, however. His team is working to apply FRESH v.2.0 for producing child-sized replacement tracheas and precisely printed scaffolds for healing wounded muscle tissue.
Meanwhile, the Feinberg lab generously shares its designs with the scientific community via the NIH 3D Print Exchange. This innovative program is helping to bring more 3D scientific models online and advance the field of bioprinting. So we can expect to read about many more exciting milestones like this one from the Feinberg lab.
 3D bioprinting of collagen to rebuild components of the human heart. Lee A, Hudson AR, Shiwarski DJ, Tashman JW, Hinton TJ, Yerneni S, Bliley JM, Campbell PG, Feinberg AW. Science. 2019 Aug 2;365(6452):482-487.
Tissue Engineering and Regenerative Medicine (National Institute of Biomedical Imaging and Bioengineering/NIH)
Regenerative Biomaterials and Therapeutics Group (Carnegie Mellon University, Pittsburgh, PA)
FluidForm (Acton, MA)
3D Bioprinting Open Source Workshops (Carnegie Mellon)
Video: Adam Feinberg on Tissue Engineering to Treat Human Disease (YouTube)
NIH Support: National Heart, Lung, and Blood Institute; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Common Fund
Posted on by Dr. Francis Collins
The NIH-led Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative is revolutionizing our understanding of how the brain works through its creation of new imaging tools. One of the latest advances—used to produce this rainbow of images—makes it possible to view dozens of proteins in rapid succession in a single tissue sample containing thousands of neural connections, or synapses.
Apart from their colors, most of these images look nearly identical at first glance. But, upon closer inspection, you’ll see some subtle differences among them in both intensity and pattern. That’s because the images capture different proteins within the complex network of synapses—and those proteins may be present in that network in different amounts and locations. Such findings may shed light on key differences among synapses, as well as provide new clues into the roles that synaptic proteins may play in schizophrenia and various other neurological disorders.
Synapses contain hundreds of proteins that regulate the release of chemicals called neurotransmitters, which allow neurons to communicate. Each synaptic protein has its own specific job in the process. But there have been longstanding technical difficulties in observing synaptic proteins at work. Conventional fluorescence microscopy can visualize at most four proteins in a synapse.
As described in Nature Communications , researchers led by Mark Bathe, Massachusetts Institute of Technology (MIT), Cambridge, and Jeffrey Cottrell, Broad Institute of MIT and Harvard, Cambridge, have just upped this number considerably while delivering high quality images. They did it by adapting an existing imaging method called DNA PAINT . The researchers call their adapted method PRISM. It is short for: Probe-based Imaging for Sequential Multiplexing.
Here’s how it works: First, researchers label proteins or other molecules of interest using antibodies that recognize those proteins. Those antibodies include a unique DNA probe that helps with the next important step: making the proteins visible under a microscope.
To do it, they deliver short snippets of complementary fluorescent DNA, which bind the DNA-antibody probes. While each protein of interest is imaged separately, researchers can easily wash the probes from a sample to allow a series of images to be generated, each capturing a different protein of interest.
In the original DNA PAINT, the DNA strands bind and unbind periodically to create a blinking fluorescence that can be captured using super-resolution microscopy. But that makes the process slow, requiring about half an hour for each protein.
To speed things up with PRISM, Bathe and his colleagues altered the fluorescent DNA probes. They used synthetic DNA that’s specially designed to bind more tightly or “lock” to the DNA-antibody. This gives a much brighter signal without the blinking effect. As a result, the imaging can be done faster, though at slightly lower resolution.
Though the team now captures images of 12 proteins within a sample in about an hour, this is just a start. As more DNA-antibody probes are developed for synaptic proteins, the team can readily ramp up this number to 30 protein targets.
Thanks to the BRAIN Initiative, researchers now possess a powerful new tool to study neurons. PRISM will help them learn more mechanistically about the inner workings of synapses and how they contribute to a range of neurological conditions.
 Multiplexed and high-throughput neuronal fluorescence imaging with diffusible probes. Guo SM, Veneziano R, Gordonov S, Li L, Danielson E, Perez de Arce K, Park D, Kulesa AB, Wamhoff EC, Blainey PC, Boyden ES, Cottrell JR, Bathe M. Nat Commun. 2019 Sep 26;10(1):4377.
 Super-resolution microscopy with DNA-PAINT. Schnitzbauer J, Strauss MT, Schlichthaerle T, Schueder F, Jungmann R. Nat Protoc. 2017 Jun;12(6):1198-1228.
Schizophrenia (National Institute of Mental Health)
Mark Bathe (Massachusetts Institute of Technology, Cambridge)
Jeffrey Cottrell (Broad Institute of MIT and Harvard, Cambridge)
NIH Support: National Institute of Mental Health; National Human Genome Research Institute; National Institute of Neurological Disorders and Stroke; National Institute of Environmental Health Sciences
Posted on by Dr. Francis Collins
You might recall learning in biology class that the cells constantly replicating and dividing in our bodies all carry the same DNA, inherited in equal parts from each parent. But it’s become increasingly clear in recent years that even seemingly healthy tissues contain neighborhoods of cells bearing their own acquired genetic mutations. The question is: What do all those altered cells mean for our health?
With support from a 2018 NIH Director’s New Innovator Award, Po-Ru Loh, Harvard Medical School, Boston, is on a quest to find out, though without the need for sequencing lots of DNA in his own lab. Loh will instead develop ultrasensitive computational tools to pick up on those often-subtle alterations within the vast troves of genomic data already stored in databases around the world.
How is that possible? The math behind it might be complex, but the underlying idea is surprisingly simple. His algorithms look for spots in the genome where a slight imbalance exists in the quantity of DNA inherited from mom versus dad.
Actually, Loh can’t tell from the data which parent provided any snippet of chromosomal DNA. But looking at DNA sequenced from a mixture of many cells, he can infer which stretches of DNA were most likely inherited together from a single parent.
Any slight skew in those quantities point the way to genomic territory where a tiny portion of chromosomal DNA either went missing or became duplicated in some cells. This common occurrence, especially in older adults, leads to a condition called genetic mosaicism, meaning that, contrary to most biology textbooks, all cells aren’t exactly the same.
By detecting those subtle imbalances in the data, Loh can pinpoint small DNA alterations, even when they occur in 1 in 1,000 cells collected from a person’s bloodstream, saliva, or tissues. That’s the kind of sensitivity that most scientists would not have thought possible.
Loh has already begun putting his new computational approach to work, as reported in Nature last year . In DNA data from blood samples of more than 150,000 participants in the United Kingdom Biobank, his method uncovered well over 8,000 mosaic chromosomal alterations.
The study showed that some of those alterations were associated with an increased risk of developing blood cancers. However, it’s important to note that most people with evidence of mosaicism won’t go on to develop cancer. The researchers also made the unexpected discovery that some individuals carried genetic variants that made them more prone than others to pick up new mutations in their blood cells.
What’s especially exciting is Loh’s computational tools now make it possible to search for signs of mosaicism within all the genetic data that’s ever been generated. Even more importantly, these tools will allow Loh and other researchers to ask and answer important questions about the consequences of mosaicism for a wide range of diseases.
 Insights into clonal haematopoiesis from 8,342 mosaic chromosomal alterations. Loh PR, Genovese G, Handsaker RE, Finucane HK, Reshef YA, Palamara PF, Birmann BM, Talkowski ME, Bakhoum SF, McCarroll SA, Price AL. Nature. 2018 Jul;559(7714):350-355.
Loh Lab (Harvard Medical School, Boston)
Loh Project Information (NIH RePORTER)
NIH Director’s New Innovator Award (Common Fund)
NIH Support: Common Fund; National Institute of Environmental Health Sciences