Researchers Develop Raman Spectroscopy Method to Sort Active Cells for Single-cell Sequencing | GenomeWeb

Researchers Develop Raman Spectroscopy Method to Sort Active Cells for Single-cell Sequencing

NEW YORK (GenomeWeb) – Over the last several years, single-cell sequencing has increasingly become a method of choice to study the genomes of rare microbes and organisms that cannot be cultured. 

Looking to improve on the method further, researchers at the US Department of Energy's Joint Genome Institute, the University of Vienna, and MIT are adapting a Raman microspectroscopy technique to select only those cells that are metabolically active out of an environmental sample.

The technique is based on a method published by the University of Vienna group last December in the Proceedings of the National Academy of Sciences.

In that paper, the researchers described a way to treat microbial communities with heavy water (D20) and then track the microbes' incorporation of deuterium via Raman microspectroscopy. The method served as a proxy for identifying physiologically active cells, since only those cells took up the deuterium.

According to Rex Malmstrom, JGI's head of micro-scale applications, JGI is interested in adapting the technique as an alternative, and more specific, way of selecting cells for single-cell sequencing.

Currently, he said, the JGI uses a high-speed sorter. Cells line up single file and a laser shines on them, determining by the size and DNA fluorescence whether the cell is actually a cell. While the method is fast and automated, Malmstrom said that the institute is developing technologies that sort cells based on other features aside from shape and DNA fluorescence, like metabolic activity.

Currently, "we sort anything that looks like a cell," he said at last week's annual JGI user meeting in Walnut Creek, Calif. But, "we're looking at better ways of identifying cells as we sort."

Márton Palatinszky, a microbial ecologist at the University of Vienna and an author of the PNAS study, described the technique in a presentation at the meeting.

He said the group chose to use Raman microspectroscopy because it would not destroy the sample, has high resolution, is fast, and can be combined with other techniques such as FISH or optical tweezers to manipulate the cells.

Raman microspectroscopy works by "bombarding" a mixed sample with a laser, Palatinszky said. The laser interacts with the molecules, shifting the laser's energy and producing different vibrational patterns that can be read out. Different peaks of the readout correspond to different molecules. More complex molecules have multiple peaks.

To detect physiologically active cells, the group applied heavy water to the microbial sample. Active cells will incorporate the deuterium, and the resulting carbon-deuterium bond is easily detectable via Raman microspectroscopy.

The group first tested the technique on Escherichia coli samples, in order to show that the label could indeed be detected. In the proof-of-principle study, the group tested the technique on Akkermansia muciniphila and Bacteroides acidifaciens, and combined it with fluorescence in situ hybridizationto show that the microbes had "totally different patterns of activity" in response to various substrates, Palatinszky said.

Once cells are identified by specific profiles via Raman spectroscopy, they can be plucked out via optical tweezers and analyzed more in depth, such as with single-cell sequencing. In the PNAS study, the group demonstrated that this was possible by stimulating cells with glucosamine and mucin; identifying and sorting them using the aforementioned methods; amplifying their genomes with multiple displacement amplification; and analyzing them using 16S rRNA gene sequencing.

Palatinszky said that the group is now optimizing the protocol and testing its accuracy.

Malmstrom told GenomeWeb that JGI is interested in the technique, but wants to automate it. He said that researchers are now building a microfluidic device that will capture cells as they flow through and interrogate them via the Raman microspectroscopy technique. Then, if active, the cell will be kept for further study, like whole-genome sequencing.

Malmstrom said that currently, aside from cell sorting, JGI uses 16S sequencing of environmental samples to get an idea of the types or organisms present, and then researchers can choose which ones are the most interesting to sequence further. The Raman microspectroscopy technique could be used in combination with or independently of the 16S sequencing method, he said. 16S genomic profiling is useful for identifying "who is there," he said, while the Raman microspectroscopy can identify "who is active." Each method has different advantages.

For example, he said, there are some environments where the bacteria are inactive, but as conditions change, growth is stimulated, for instance in biological crusts in the desert. "They are desiccated, so there's little if any activity," he said. "But as soon as a rainstorm comes, they spring to life." In those types of situations it may be useful to use both techniques to pick out cells to sequence.

In other situations, though, the Raman microspectroscopy technique could be less biased. For instance, 16S genomic profiling relies on using universal primers. "For a huge fraction of cells that we sort and amplify, we don't get a 16S sequence to identify who they are," Malmstrom said. Most of the time, that is due to a methodological reason, but there "is probably some fraction of cases where the primers didn't match," possibly because it is a new species with a very divergent genome, he said. So techniques to pick out cells that don't rely on using primers could enable the discovery of new species.

Aside from the Raman microspectroscopy approach, Malmstrom said that JGI is interested in a variety of techniques that enable the identification of single cells based on a specific function or trait. He said that JGI is also collaborating with a group at California Institute of Technology to use a method known as bio-orthogonal amino acid tagging to fluorescently tag cells based on translation activity.

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