A new prototype takes mass spectrometry from analyzing a few molecules at a time to handling billions at once.

Mass spectrometry is already a cornerstone technology for identifying what molecules are present in a sample and how much of each is there. However, most current instruments still examine molecules one at a time or in very small groups. This slow, step-by-step process can be expensive and inefficient, and it increases the chance that rare but important molecules will go undetected.

A more advanced version of this technology could eventually allow scientists to map the complete molecular makeup of a single cell, monitor thousands of chemical reactions simultaneously, and speed up research in areas such as drug discovery.

A new study reports an important step toward that goal with the development of a prototype called MultiQ-IT. This system is designed to process extremely large numbers of molecules at once. The results provide a roadmap for building faster, more sensitive instruments and suggest that mass spectrometry could undergo a transformation similar to those seen in genomics and computing.

“What revolutionized DNA sequencing wasn’t any change in the underlying chemistry. That’s remained fundamentally the same,” says Brian T. Chait, Laboratory of Mass Spectrometry and Gaseous Ion Chemistry at Rockefeller. “It was the ability to run so many chemical reactions in parallel, which took genome sequencing from a billion-dollar effort to something that costs around $100. The same thing happened in computing with GPUs. And that’s what we’re trying to do with mass spectrometry.”

A Longstanding Bottleneck in Mass Spectrometry

Mass spectrometry dates back to around 1913 and has become one of the most powerful analytical tools in biology. It works by ionizing molecules, giving them an electric charge, and then measuring their mass-to-charge ratio to identify and quantify them. Despite its capabilities, most systems still analyze ions sequentially, handling only one or a few types at a time. This limits sensitivity, especially when trying to detect rare molecules within complex biological samples.

“It’s a wonderful technique—you can do unimaginably wonderful, analytical things with it,” Chait says. “But I was always a little frustrated by its limitations. I knew, in my heart, it could be better.”

Improving this limitation could have a major impact on fields like single-cell proteomics and metabolomics, which aim to measure all proteins or metabolites within a single cell. Unlike DNA, these molecules cannot be copied or amplified, and the most common molecules can outnumber rare ones by millions to one. While mass spectrometry already contributes to these areas, it still struggles to pick out faint signals from overwhelming background noise.

Chait and his team believed the solution would require bringing “massive parallelization” to this century-old technology. In computing, breaking large problems into smaller tasks and processing them at the same time with graphics processing units, or GPUs, greatly improved performance. DNA sequencing advanced in a similar way, enabling millions of reactions to be analyzed simultaneously at much lower cost.

“It was a very obvious idea,” says Andrew Krutchinsky, a senior research associate in the lab. “But how to do it with mass spectrometry wasn’t obvious.”

A Parallel Design Inspired by Cells

The concept behind MultiQ-IT emerged from decades of research on how molecules pass in and out of a cell’s nucleus through structures known as nuclear pore complexes. These pores allow traffic to move through many openings at once rather than forcing everything through a single pathway. The researchers asked whether a similar strategy could be applied to mass spectrometry.

They created a new ion-trapping chamber to replace a key component of traditional instruments. This cube-shaped chamber contains hundreds of tiny, electrically controlled openings. Inside, ions collide with gas molecules, slow down, and move randomly through the space. The system can then hold, filter, and redirect many groups of ions simultaneously instead of processing them one by one.

The design was scaled from just six openings to more than 1,000. Experiments showed that a single stream of incoming ions could be divided into multiple parallel streams for simultaneous analysis.

Dramatic Gains in Sensitivity and Capacity

The performance improvements were substantial. A version of MultiQ-IT with 486 ports could hold up to ten billion charges at once, about a thousand times more than conventional ion traps.

The system also improves detection by allowing common background molecules to escape while keeping rarer, more informative ones inside. This boosts signal-to-noise ratios by up to 100-fold, making previously undetectable proteins visible. The researchers achieved this by applying a small voltage barrier at the exits of the trap. Ions with a single charge can escape, while multiply charged ions, which are often more biologically relevant, remain confined.

In a larger design with 1,134 ports, only 39 open ports were needed to reach half of the maximum filtering efficiency, similar to how cells rely on a limited number of nuclear pores. The team also found that spreading ions across many channels reduces the electrical repulsion that occurs when large numbers of similarly charged particles are packed together.

This boost in sensitivity could improve the detection of low-abundance crosslinked peptides, which are valuable for studying the structure of large protein complexes. “The least abundant things can be more important than the more abundant things,” Krutchinsky says.

A Blueprint for the Future of Molecular Analysis

At this stage, MultiQ-IT is not yet a commercial instrument but a proof of concept. The researchers view it as a foundational design that could eventually be developed into practical tools for clinical and research applications.There was a lot of development between the discovery of a reaction for sequencing DNA and modern genomics; decades between the first transistor and putting a billion transistors on a chip,” Chait says. “In both cases, someone first had to show it could be done, and then industry took over. I think we’ve shown one way mass spectrometry can be done more efficiently.”