Optimized preparation and data-independent acquisition (DIA) liquid chromatography–mass spectrometry (LC-MS) detect up to 6500 proteins in laboratory-grown duck.
Making meat from animal cells grown in the laboratory (known as cultivated meat production) requires reliable, well-tested ways of checking exactly what the product contains. One common approach looks at which genes are switched on in the cells, which gives a useful first picture. Measuring the proteins themselves goes a step further. It shows directly which proteins are present and in what amounts, giving companies and regulators more confidence that a product is what it should be and that it is safe. But the food industry has been slow to take up proteomics. The techniques are complicated, and there are no agreed standard methods. As a result, different laboratory procedures can give quite different results, detecting more or fewer proteins depending on how the analysis is done.
To address this gap, the French cultivated food company PARIMA, working in conjunction with Graduate School Health and Drug Sciences of the University of Paris Saclay, looked at how the main steps in the testing process, including the settings used for liquid chromatography–mass spectrometry (LC-MS), affect which proteins are detected in duck cells grown in the laboratory. A paper based on their study was published in the journal Food Research International.1
Since the whole point of laboratory-grown meat is to offer people another source of protein, being able to show exactly which proteins it contains could go a long way toward winning consumers’ trust.2,3Protein analysis can do a lot for laboratory-grown meat. It can give a detailed picture of the proteins the meat contains and check for important ones, such as the muscle proteins myosin and actin, enzymes that help cells produce energy, and myoglobin, the protein that gives meat its red color. It can confirm that the cells haven’t changed genetically as they grow. It can also check for proteins known to cause allergies, such as Gal d 3 from chickens and Bos d 13 from cattle, and make sure the meat is as nutritious as meat from animals.4As the industry grows, regulators increasingly see a detailed protein profile as an important measure of quality when deciding whether to approve laboratory-grown meat. Combined with other methods that look at a cell’s genes and other molecules, protein analysis gives a much fuller picture of what lab-grown meat is made of, from individual cells to the finished product.5,6
Bringing protein analysis into the industry is not a straightforward process, though. Very few studies have looked at which proteins laboratory-grown meat contains. On top of that, for common approaches such as label-free quantitative proteomics, which measures protein amounts without adding chemical tags, there are a huge number of different methods to choose from. These vary widely in how samples are prepared, how the instrument collects data and how the results are processed.7
“Methodology differences,” write the authors of the paper,1 “currently leave a major knowledge gap regarding how these workflow variations could impact cultivated meat proteome coverage and profile. This situation underscores the critical need for method standardization.”
The researchers compared five ways of preparing samples, each of which breaks proteins down into smaller pieces called peptides for analysis. Two were traditional methods carried out in solution, using either urea or a detergent called sodium deoxycholate (SDC). Two used ready-made kits, PreOmics iST and EasyPep. The fifth was a newer method called sample preparation by easy extraction and digestion (SPEED). The ready-made kits produced the most peptides and detected the most proteins. But with some fine-tuning, two of the cheaper methods, SDC and SPEED, did almost as well. Breaking the proteins down for three hours at 37 °C and cleaning up the samples with plastic-based filter columns made the biggest difference, raising the count to around 4500 to 5000 proteins. The way the instrument collected data also mattered. Scanning all the peptides at once (data-independent acquisition, or DIA) found more proteins than picking out the most abundant ones one at a time (data-dependent acquisition, or DDA). It also gave more consistent results, detecting around 6500 proteins compared with 5000.1
“The optimized and cost-effective sample prep protocols presented here,” write the authors of the paper,1 “establish a standardized framework for bulk bottom-up proteomics in cultivated meat.”
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