Skip to main content
Premium Trial:

Request an Annual Quote

Protein Microarrays for All

Premium
  • Title: Assistant Professor, Johns Hopkins School of Medicine
  • Education: PhD, Clemson University, 1999
  • Recommended by: Michael Snyder

If the post-genomic era started with proteomics, Heng Zhu was there from the very beginning. As a postdoc in Mike Snyder’s lab at Yale, Zhu helped create the first protein microarray for large-scale, high-throughput protein analysis in yeast. Since then he’s continued improving the protocols to fabricate these chips at Johns Hopkins School of Medicine, where he is currently an associate professor. There, he’s helped create a protocol for purifying and spotting proteins to create arrays for E. coli, herpes virus, and human.

“It’s basically very much like the DNA microarray, so we can use this type of technology to study all kinds of protein activity,” he says. “But we think, at least in my opinion, that protein microarrays can do much more than DNA or oligo microarrays, simply because you have proteins on the chip and you can do so many different assays, not just a simple hybridization.” 

Most of Zhu’s lab work centers on identifying protein interactions, such as protein-protein and protein-DNA, to name just a few. The chips are used to discover post-translational modifications such as signaling phosphorylation events and enzyme-substrate interactions, transcription factor activity, and biomarkers. With three chips finished and two more in production (human and a fungal pathogen), Zhu’s lab is at the vanguard of protein microarray technology. “These days, not many labs can fabricate protein microarrays,” Zhu says. “Even though it’s been worked out by our laboratory, it’s still tedious, time-consuming, and expensive.”

The immediate challenges to such a new field are mostly technical. Ironing out the production protocol is one that looms especially large, considering how labor-intensive it is to clone the open reading frames and then purify the proteins before spotting them onto slides. For example, Zhu believes it will take them one or two years to purify the entire human ORF-ome. Currently, they’ve got 5,000 proteins on the human chip, which is already quite a lot, Zhu says.

Other challenges involve optimizing the slide surface chemistry, reaction conditions, and detection methods to achieve the best signal-to-noise ratio for many separate assays. “At the beginning, I thought maybe just one surface would fit for all, but it turned out that’s not the case at all,” Zhu says. An added obstacle is that slide vendors don’t always freely offer information regarding their slide surface chemistry, so there’s a lot of trial and error work involved in optimizing spotting conditions.

Looking ahead

Zhu has faith in what protein microarrays can offer. “I want to see that this technology will give a big push in the frontiers of proteomics,” he says. “For example, I want to see that five years down the road, a lot of new enzymatic activities will be discovered for the human proteome. A lot of pathways [and] networks can be established by [the] massive amount of data produced by using this protein chip technology.”

Publications of note

After graduating from Clemson University in South Carolina with a PhD in genetics, Zhu headed off to his postdoc with Snyder, where he helped develop the first protein microarray in yeast. That work was published in Nature Genetics in 2000 (“Analysis of yeast protein kinases using protein chips”). They analyzed 119 yeast protein kinases and found not only many new features, but also that many of them could phosphorylate tyrosine. It was after hearing Snyder, who was at the time studying gene function and protein localization in the budding yeast, speak at a conference that Zhu decided to change the focus of his thesis to genomics. “When I heard Mike’s talk, I said, oh, that’s definitely the future [because] you have to figure out the protein’s function after you sequence everything.”

The Scan

UCLA Team Reports Cost-Effective Liquid Biopsy Approach for Cancer Detection

The researchers report in Nature Communications that their liquid biopsy approach has high specificity in detecting all- and early-stage cancers.

Machine Learning Improves Diagnostic Accuracy of Breast Cancer MRI, Study Shows

Combining machine learning with radiologists' interpretations further increased the diagnostic accuracy of MRIs for breast cancer, a Science Translational Medicine paper finds.

Genome Damage in Neurons Triggers Alzheimer's-Linked Inflammation

Neurons harboring increased DNA double-strand breaks activate microglia to lead to neuroinflammation like that seen in Alzheimer's disease, a new Science Advances study finds.

Long COVID-19 Susceptibility Clues Contained in Blood Plasma Proteome

A longitudinal study in eBioMedicine found weeks-long blood plasma proteome shifts after SARS-CoV-2 infection, along with proteomic signatures that appeared to coincide with long Covid risk.