By Dava Stewart
April 18, 2018 | Engineers at the New York Genome Center have designed a low-cost droplet microfluidic control instrument that can be 3-D printed and deployed in a clinical environment to perform single-cell transcriptome profiling.
In a Nature Communications paper published in February (doi:10.1038/s41467-017-02659-x), researchers from the Hospital for Special Surgery (HSS) in New York and the NYGC describe how the instrument, dubbed miniDrops, was developed and validated and used to analyze the gene expression of single-cells from the joints of five rheumatoid arthritis patients.
The technology to perform single cell RNA sequencing has been around for several years, so the fact that this machine could perform droplet-based, single cell transcriptomic profiling is not the breakthrough part of the study. Instead, the authors write, access can be a problem. “A major barrier to widespread adoption of droplet microfluidic techniques is the lack of cost-effective and reliable instrumentation.”
The NYGC instrument can be 3-D printed at a low cost, is portable, and performs reliably. Laura Donlin, co-director of the Derfner Foundation Precision Medicine Laboratory at HSS, and co-author of the paper, praised her collaborative partner, Will Stephenson, senior research engineer, NYGC Technology Innovation Lab, saying, “Will Stephenson designed and built an all-around impressive machine that is now open source for others to build for a fraction of the cost of commercial products.”
“The single-cell technology referred to as ‘Drop-seq’ had been developed a few years prior,” she continues, “Will miniaturized the design and made it portable,” says Donlin.
The instrument is comprised of electronic and pneumatic components affixed to a 3-D printed frame with a Raspberry Pi computer. It uses a modified Drop-seq chip. The entire system is operated through software control using a graphical user interface on a touchscreen. It operates with standard power and fits on a benchtop. The materials cost is approximately $575.
Amr Sawalha, Professor of Internal Medicine at the University of Michigan agrees about the importance of the instrument. “The technology has been in existence for a long time, but they made it cheaper and more portable, and accessible,” he says.
miniDrops has been fully open-sourced. Stephenson posted instructions and assembly manuals for the instrument online at Metafluidics. He says, “We hope that this instrument lowers the hurdles associated with performing single-cell transcriptome profiling experiments in basic research and clinical settings.”
miniDrops in Action
HSS researchers used the miniDrops with the Drop-seq chip to do single-cell RNA-seq of rheumatoid arthritis synovial tissue, the membrane lining a joint. At first glance, a study that only involves five patients may not seem like it could be terribly important. However, this was one of the first examples of single cell sequencing being performed on human tissue affected by autoimmunity.
“Particularly in clinical settings,” the authors write in the paper, “microfluidic instrumentation is not always proximal to the site of cell sample generation requiring transport to external sites or cell preservation, both of which can alter cellular transcriptomes or result in extensive cell death.”
The miniDrops allowed for a much more efficient workload. “The tissue came out of the operating room straight to the bench,” says Donlin, excitement evident in her voice. “[We] put cells from the tissue into the machine within an hour.” That kind of speed increases the chance of making discoveries true to the tissue. And, the team did make discoveries about the tissues they examined.
The researchers looked at the gene expression patterns of 20,387 cells, found 13 distinct groups, and classified some fibroblast subtypes that were unrecognized. The pathogenesis of RA is not clearly understood, which makes treatment more difficult, and this work could lead to more targeted, precise treatment.
Stratification in RA
Sawalha explains that clinicians treating RA have a standard approach following diagnosis. Most patients are first treated with methotrexate, “then we move other disease-modifying agents or combinations, or biologics, by trial and error, basically,” he says. A clearer understanding of the pathology of the disease would help clinicians know what treatments would be more effective for which patients.
“If you look at a larger number of patients, like those who are seropositive RA, you might be able to sub-classify them,” says Sawalha, “a subset of patients with prominent involvement B cells, specific fibroblast subsets, for example. Then, based on those findings predict which treatment might work best.”
Previous studies using human tissue have examined particular things like B cells or macrophages, “But we were able to study cells from an unbiased and comprehensive perspective,” says Donlin. She says they looked for patterns in genes expressed by the cells and used what they already knew about what genes different cell types express in order to identify what was there. “What this is allowing us to do is see all the cell types that are there, and some that are completely new,” she says.
By analyzing the cell types, Donlin says researchers should be able to start diagnosing subtypes of disease. “With this technology you can begin to figure out among patients how differences in cell compositions relate to treatment responses,” she says.
Donlin says the results from this research could now be applied to studies focused on treating the individual patient, and says, “This work can be readily used in a precision medicine laboratory, taking samples from patients with autoimmune disorders and testing which cells respond to medication.” She adds that previously, she couldn’t say for sure that a drug was targeting particular cell types, saying, “But now I can do that with this machine and if a patient has an abundance of a given cell type that responds to a particular medication, then we may have a more rational guide to the treatment of their specific case of RA.”
Sawalha is enthusiastic about the potential that identifying subtypes of RA holds for improving treatment, but cautions that there are caveats. For starters, synovial biopsies—biopsies of the membrane lining a joint—are “rather invasive.” But he adds, “Now, if investigations like this show us we will get sufficiently important information, we might change the way we do things. There are ways to do synovial biopsy in clinical or outpatient settings.”
This work is leading to better classification of autoimmune diseases, and Sawalha says that getting a molecular look at diseases will help with diagnostics and determining the best treatment plan for an individual patient.
The work of Donlin, Stephenson, and their colleagues has expanded scientific knowledge of RA as well as opened the door to using the technology in broader settings. It represents another step toward more personalized, targeted, precision medicine.