Metabolomics

Buying guide

Because this setup spans sample prep through to detection, the price range on the marketplace is wider than on any single category. Listings run from EUR 1 to EUR 400.457. The low end is consumables, pipette hardware and older liquid-handling units; the high end is the detection platforms, where a high-resolution mass spectrometer or a high-field NMR accounts for most of a lab's spend. The separation hardware sits in between, and the data-processing software rarely dominates the hardware cost but often determines whether the hardware pays off.

Condition follows the same logic. 86 percent of the listings are used. On the front-end hardware that matters little, since a liquid handler is mechanical and a serviced unit performs as new. On the detection side it matters more, because a mass spectrometer's sensitivity and an NMR's field homogeneity are what the work depends on, and those are the specifications to confirm against the individual listing. Used and refurbished units are priced below new, which is the one difference the catalogue supports; where a buyer has to weigh new against used, warranty is arranged in consultation for the specific listing rather than set centrally.

A practical rule for building a setup from parts: match the detector to the question first, then work backwards to the separation that feeds it and the preparation that feeds that. Buying a platform the samples cannot keep up with, or a liquid handler for a throughput that does not exist, is the common way money goes to the wrong stage.

Types of Metabolomics

Metabolomics equipment spans two families that rarely share a bench: the separation and detection platforms (mass spectrometers, NMR spectrometers, chromatography systems with their data processing software) and the front-end hardware that feeds them (sample preparation and automated liquid handling). The work runs as a sequence, from raw sample to annotated feature table, and each stage constrains the one after it. These are the stages, in the order a lab actually performs them.

Preparing the sample

Everything downstream inherits the quality of this step. Metabolites degrade fast, so extraction has to quench enzyme activity quickly and pull the target classes into solvent without biasing toward the easy ones. Polar and non-polar compounds partition differently, which is why many protocols split a single sample into two extracts and analyse each separately. This is where sample preparation and automated liquid handling earn their place: a study comparing fifty samples cannot tolerate hand-pipetting variance between them, because that variance shows up later as a difference the biology did not cause. Liquid handlers standardise volumes, dilutions and plate layouts across the batch, and they let a lab process overnight what a technician could not finish in a day.

How much of this to automate depends on throughput. A handful of samples a week does not justify a liquid handler; a clinical cohort of several hundred does, and at that scale manual preparation is the limiting error source.

Which platform resolves the mixture?

A crude extract holds too many compounds to detect at once, so it is separated before it reaches the detector. Chromatography does this, and the choice of mode follows the chemistry: reversed-phase liquid chromatography for lipids and non-polar metabolites, hydrophilic interaction for the polar fraction, gas chromatography for volatile and derivatised species. The separation feeds directly into detection, and the two have to be matched, because a column that co-elutes two isomers hands the detector a problem it cannot always solve.

Mass spectrometry or NMR?

Detection splits into two approaches, and they answer different questions. Mass spectrometers measure mass-to-charge with high sensitivity, reaching compounds present at trace levels, and they pair naturally with the upstream separation. This is the larger platform on the marketplace and the one most untargeted studies start from. NMR spectrometers detect far fewer compounds per run and need more material, but they measure without destroying the sample and quantify without a reference standard for every analyte, which makes them the choice where reproducibility over years matters more than depth of coverage. Many labs run both, using NMR for the robust quantitative backbone and the mass spectrometer to reach what NMR cannot see.

Turning spectra into data

A single run produces thousands of features, none of them useful until peaks are picked, aligned across samples, and matched against a library. Chromatography data processing systems and spectral software do this, and the bottleneck in a large study is as often here as at the instrument. The processing step constrains the whole design: a lab that cannot align its runs cannot compare its samples, which is the entire point of the exercise.