Purdue's STEi Method Eliminates Sample Preparation for Spatial Multiomics Analysis
核心洞察
Purdue University (搜索) researchers developed a patent-pending surface touch extraction imaging (STEi) method that eliminates sample preparation, a major bottleneck in laboratory workflows.
The pressure-controlled probe samples uneven surfaces in 5–15 seconds, preserving spatial information and enabling repeated nondestructive sampling of intact tissue or food samples.
STEi couples with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to generate spatial heat maps of metabolites, lipids, proteins, and contaminants across irregular surfaces.
A patent-pending method developed and tested for multiple applications at Purdue University (搜索) eliminates sample preparation, a bottleneck that currently dominates a laboratory scientist's time and budget, and is amenable with spatial analysis using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The surface touch extraction imaging (STEi) method could benefit food scientists, toxicologists, and other laboratory scientists when spatially analyzing samples with irregular surfaces for metabolites, lipids, environmental compounds, and proteins using diverse instrumentation to generate multiomics data.
Christina Ferreira, research assistant professor at Purdue's Bindley Bioscience Center with a courtesy appointment in the Department of Food Science, and Ryan Hilger, assistant director of the Jonathan Amy Facility for Chemical Instrumentation in the James Tarpo Jr. and Margaret Tarpo Department of Chemistry, lead the team that created STEi.
Eliminating a Core Bottleneck
Ferreira explained that sample preparation for traditional LC-MS/MS analysis requires several steps, including mixing, centrifuging, transferring, and drying. "That destroys the sample and throws away spatial information about where a chemical was found in the sample," she said. "Also, if scientists want to spatially analyze an irregular surface such as a piece of liver tissue or a fish fillet, they must section it and make it flat to be able to extract the chemicals before the analysis."
The STEi workflow addresses these limitations directly. "The STEi concept workflow essentially allows the user to load a sample, press 'Run' and create a spatially resolved chemical portrait of their sample based on an instrumentation input, without ever having to cut, grind or destroy it," Ferreira said.
How STEi Works
The workflow begins with the user placing an intact, unprocessed sample—such as a tissue biopsy, food item, or piece of packaging—on the instrument stage, with no flattening or grinding required. The instrument's integrated camera/imaging module scans the sample's surface, and software computes a path across the surface to determine where the extraction probe should touch and in what sequence.
A fine probe tip descends into each programmed point on the surface, making contact between the sample and the solvent, which could be water, acetonitrile, or a mixture. A force/pressure sensor ensures the probe makes consistent, controlled contact regardless of surface shape. Ferreira noted that the pressure-controlled probe's ability to sample uneven surfaces is a critical differentiator over flat-surface methods. The software then registers the molecular data back to the original surface coordinates, generating spatial heat maps showing where specific lipids, contaminants, proteins, or metabolites are concentrated across the sample.
Advantages Over Traditional Methods
Ferreira outlined several ways STEi improves upon traditional workflows. The process is faster: "Sampling takes a few seconds (usually 5-15 seconds) through the contact of a pressure-sensitive probe and the surface of the sample, allowing extraction through a liquid bridge," she said. The collected samples can be analyzed by different instruments, paving the way for imaging sample surfaces using a high-performance liquid chromatography autosampler and performing imaging experiments with liquid chromatography coupled to tandem mass spectrometry.
Because only the surface is sampled, samples remain largely intact, allowing scientists to resample the same piece of food or tissue repeatedly over time. Spatial context is preserved: "Instead of a single blended answer, the scientist gets a chemical heat map showing, for example, where in the tissue or food product a contaminant is concentrated using the analytical method of choice," Ferreira said.
Notably, no expertise in sample preparation is required, as STEi is automated and pressure-controlled, enabling less experienced staff members to reliably run samples. "For a food safety scientist, this means going from a half-day destructive assay to a few minutes of automated scanning," Ferreira said. "For a toxicologist, it means understanding drug distribution across an organ rather than just knowing the average concentration."
Applications in Drug Development and Life Sciences
Beyond food safety—where the technology was designed to detect contaminants on food surfaces and packaging, support food quality and lipid profiling such as cattle-breed lipid fingerprinting, and monitor food spoilage through repeated nondestructive sampling—STEi holds significant potential for drug development and the life sciences.
"In the preclinical toxicology arena, STEi coupled to mass spectrometry tools could map the metabolic impact of drugs, chemicals and proteins across liver, kidney, brain and intestinal tissues from animal models," Ferreira said. "It would show tissue-specific accumulation patterns and also sample proteins as these can be extracted."
The research team is evaluating the recovery of lipids and proteins using different probe configurations. Besides lipids, they have recovered about 2,000 different proteins from bovine muscle using manual STEi, according to Venkatesh Thirumalaikumar. The proteins were functionally classified across contractile, metabolic, antioxidant, and structural categories.
Next Development Steps
Ferreira and the research team received funding from Purdue Innovates' Trask Innovation Fund to develop STEi. The team is seeking partners to work on hardware optimization, software integration for 3D path planning, and additional validation experiments including food spoilage monitoring, food packaging contamination detection, and further toxicology applications. "We also will explore regulatory alignment with the U.S. Food and Drug Administration (搜索) and the U.S. Environmental Protection Agency (搜索) analytical frameworks for selected applications," Ferreira said.
Ferreira disclosed the STEi innovation to the Purdue Innovates Office of Technology Commercialization (搜索), which applied for a patent to protect the intellectual property. Industry partners interested in developing or commercializing STEi should contact Dipak Narula, lead technology development liaison and assistant director of business development and licensing — physical sciences.
