Smartphone based portable DNA detection system

Photo: UCLA

Researchers at UCLA have developed an improved method to detect the presence of DNA biomarkers of disease that is compatible with use outside of a hospital or lab setting. The new technique leverages the sensors and optics of cellphones to read light produced by a new detector dye mixture that reports the presence of DNA molecules with a signal that is more than 10-times brighter.

Nucleic acids, such as DNA or RNA, are used in tests for infectious diseases, genetic disorders, cancer mutations that can be targeted by specific drugs, and fetal abnormality tests. The samples used in standard diagnostic tests typically contain only tiny amounts of a disease’s related nucleic acids. To assist optical detection, clinicians amplify the number of nucleic acids making them easier to find with the fluorescent dyes.

Both the amplification and the optical detection steps have in the past required costly and bulky equipment, largely limiting their use to laboratories.

In a study published online in the journal ACS Nano, researchers from three UCLA entities — the Henry Samueli School of Engineering and Applied Science, the California NanoSystems Institute, and the David Geffen School of Medicine — showed how to take detection out of the lab and for a fraction of the cost.

The collaborative team of researchers included lead author Janay Kong, a UCLA Ph.D. student in bioengineering; Qingshan Wei, a post-doctoral researcher in electrical engineering; Aydogan Ozcan, Chancellor’s Professor of Electrical Engineering and Bioengineering; Dino Di Carlo, professor of bioengineering and mechanical and aerospace engineering; and Omai Garner, assistant professor of pathology and medicine at the David Geffen School of Medicine at UCLA.

The UCLA researchers focused on the challenges with low-cost optical detection. Small changes in light emitted from molecules that associate with DNA, called intercalator dyes, are used to identify DNA amplification, but these dyes are unstable and their changes are too dim for standard cellphone camera sensors.

But the team discovered an additive that stabilized the intercalator dyes and generated a large increase in fluorescent signal above the background light level, enabling the test to be integrated with inexpensive cellphone based detection methods. The combined novel dye/cellphone reader system achieved comparable results to equipment costing tens of thousands of dollars more.

To adapt a cellphone to detect the light produced from dyes associated with amplified DNA while those samples are in standard laboratory containers, such as well plates, the team developed a cost-effective, field-portable fiber optic bundle. The fibers in the bundle routed the signal from each well in the plate to a unique location of the camera sensor area. This handheld reader is able to provide comparable results to standard benchtop readers, but at a fraction of the cost, which the authors suggest is a promising sign that the reader could be applied to other fluorescence-based diagnostic tests.

“Currently nucleic acid amplification tests have issues generating a stable and high signal, which often necessitates the use of calibration dyes and samples which can be limiting for point-of-care use,” Di Carlo said. “The unique dye combination overcomes these issues and is able to generate a thermally stable signal, with a much higher signal to noise ratio. The DNA amplification curves we see look beautiful — without any of the normalization and calibration, which is usually performed, to get to the point that we start at.”

Additionally, the authors emphasized that the dye combinations discovered should be able to be used universally to detect any nucleic acid amplification, allowing for their use in a multitude of other amplification approaches and tests.

The team demonstrated the approach using a process called loop-mediated isothermal amplification, or LAMP, with DNA from lambda phage as the target molecule, as a proof of concept, and now plan to adapt the assay to complex clinical samples and nucleic acids associated with pathogens such as influenza.

The newest demonstration is part of a suite of technologies aimed at democratizing disease diagnosis developed by the UCLA team. Including low-cost optical readout and diagnostics based on consumer-electronic devices, microfluidic-based automation and molecular assays leveraging DNA nanotechnology.

Source: UCLA

Strange ‘chimeras’ defy science’s understanding of human genetics

The human genome is far more complex than thought, with genes functioning in an unexpected fashion that scientists have wrongly assumed must indicate cancer, research from the School of Medicine indicates.

Hui Li, PhD, of the UVA School of Medicine and the UVA Cancer Center
Hui Li, PhD, of the UVA School of Medicine and the UVA Cancer Center

Hui Li, PhD, of the Department of Pathology and the UVA Cancer Center, is a pioneer in a small but emerging field that is challenging fundamental assumptions about human genetics. He seeks to understand what is called chimeric RNA – genetic material that results when genes on two different chromosomes produce “fusion” RNA in a way scientists say shouldn’t happen. Researchers have traditionally assumed these chimeric RNA are signs of cancer, of something gone wrong in the genetic transcription process. But Li’s work shows that’s not always the case. Instead, these strange fusions can also be a normal, functional part of our genetic programming.

“This is actually a double-edged sword for cancer diagnosis and treatment. … It basically says the old practice of finding any fusion RNA and claiming it’s a cancer fusion is over. We can’t just say, OK, we found a fusion, it must be a cancer marker, let’s translate it into a biomarker [to detect cancer],” Li said. “That’s actually dangerous. Because a lot of normal physiology also has fusion RNAs. There’s another layer of complexity.”

Full story can be found from University of Virginia website.

Recording analog memories in human cells

MIT biological engineers have devised a way to record complex histories in the DNA of human cells, allowing them to retrieve “memories” of past events, such as inflammation, by sequencing the DNA.

This analog memory storage system — the first that can record the duration and/or intensity of events in human cells — could also help scientists study how cells differentiate into various tissues during embryonic development, how cells experience environmental conditions, and how they undergo genetic changes that lead to disease.

“To enable a deeper understanding of biology, we engineered human cells that are able to report on their own history based on genetically encoded recorders,” says Timothy Lu, an associate professor of electrical engineering and computer science, and of biological engineering. This technology should offer insights into how gene regulation and other events within cells contribute to disease and development, he adds.

Lu, who is head of the Synthetic Biology Group at MIT’s Research Laboratory of Electronics, is the senior author of the new study, which appears in the Aug. 18 online edition of Science. The paper’s lead authors are Samuel Perli SM ’10, PhD ’15 and graduate student Cheryl Cui.

Analog memory

Many scientists, including Lu, have devised ways to record digital information in living cells. Using enzymes called recombinases, they program cells to flip sections of their DNA when a particular event occurs, such as exposure to a particular chemical. However, that method reveals only whether the event occurred, not how much exposure there was or how long it lasted.

Lu and other researchers have previously devised ways to record that kind of analog information in bacteria, but until now, no one has achieved it in human cells.

The new MIT approach is based on the genome-editing system known as CRISPR, which consists of a DNA-cutting enzyme called Cas9 and a short RNA strand that guides the enzyme to a specific area of the genome, directing Cas9 where to make its cut.

CRISPR is widely used for gene editing, but the MIT team decided to adapt it for memory storage. In bacteria, where CRISPR originally evolved, the system records past viral infections so that cells can recognize and fight off invading viruses.

“We wanted to adapt the CRISPR system to store information in the human genome,” Perli says.

When using CRISPR to edit genes, researchers create RNA guide strands that match a target sequence in the host organism’s genome. To encode memories, the MIT team took a different approach: They designed guide strands that recognize the DNA that encodes the very same guide strand, creating what they call “self-targeting guide RNA.”

Led by this self-targeting guide RNA strand, Cas9 cuts the DNA encoding the guide strand, generating a mutation that becomes a permanent record of the event. That DNA sequence, once mutated, generates a new guide RNA strand that directs Cas9 to the newly mutated DNA, allowing further mutations to accumulate as long as Cas9 is active or the self-targeting guide RNA is expressed.

By using sensors for specific biological events to regulate Cas9 or self-targeting guide RNA activity, this system enables progressive mutations that accumulate as a function of those biological inputs, thus providing genomically encoded memory.

For example, the researchers engineered a gene circuit that only expresses Cas9 in the presence of a target molecule, such as TNF-alpha, which is produced by immune cells during inflammation. Whenever TNF- alpha is present, Cas9 cuts the DNA encoding the guide sequence, generating mutations. The longer the exposure to TNF-alpha or the greater the TNF-alpha concentration, the more mutations accumulate in the DNA sequence.

By sequencing the DNA later on, researchers can determine how much exposure there was.

“This is the rich analog behavior that we are looking for, where, as you increase the amount or duration of TNF-alpha, you get increases in the amount of mutations,” Perli says.

“Moreover, we wanted to test our system in living animals. Being able to record and extract information from live cells in mice can help answer meaningful biological questions,” Cui says. The researchers showed that the system is capable of recording inflammation in mice.

Most of the mutations result in deletion of part of the DNA sequence, so the researchers designed their RNA guide strands to be longer than the usual 20 nucleotides, so they won’t become too short to function. Sequences of 40 nucleotides are more than long enough to record for a month, and the researchers have also designed 70-nucleotide sequences that could be used to record biological signals for even longer.

Tracking development and disease

The researchers also showed that they could engineer cells to detect and record more than one input, by producing multiple self-targeting RNA guide strands in the same cell. Each RNA guide is linked to a specific input and is only produced when that input is present. In this study, the researchers showed that they could record the presence of both the antibiotic doxycycline and a molecule known as IPTG.

Currently this method is most likely to be used for studies of human cells, tissues, or engineered organs, the researchers say. By programming cells to record multiple events, scientists could use this system to monitor inflammation or infection, or to monitor cancer progression. It could also be useful for tracing how cells specialize into different tissues during development of animals from embryos to adults.

“With this technology you could have different memory registers that are recording exposures to different signals, and you could see that each of those signals was received by the cell for this duration of time or at that intensity,” Perli says. “That way you could get closer to understanding what’s happening in development.”

Full story can be found from MIT website.

First computer program to detect DNA mutations in single cancer cells

Researchers at The University of Texas MD Anderson Cancer Center have announced a new method for detecting DNA mutations in a single cancer cell versus current technology that analyzes millions of cells which they believe could have important applications for cancer diagnosis and treatment. The results are published in the April 18 online issue of Nature Methods.

Existing technology, known as next-generation sequencing (NGS), measures genomes derived from millions of cells versus the newer method for single-cell sequencing, called Monovar. Developed by MD Anderson researchers, Monovar allows scientists to examine data from multiple single cells. The study was, in part, funded by MD Anderson’s Moon Shots Program, an unprecedented effort to significantly reduce deaths from cancer.

This led to development of newer technology, called single cell sequencing (SCS), that has had a major impact in many areas of biology, including cancer research, neurobiology, microbiology, and immunology, and has greatly improved understanding of certain tumor characteristics in cancer. Monovar improves further on the new SCS’s computational tools which scientists found “lacking” by more accurately detecting slight alterations in DNA makeup known as single nucleotide variants (SNVs).

Full news coverage can be found from  The University of Texas MD Anderson Cancer Center Website.