New Multi-Reflecting Mass Spectrometer Reads Blood Chemistry With Unprecedented Precision

Identifying the thousands of small molecules circulating in human blood has long been one of the most stubborn bottlenecks in modern biology. Metabolomics, the systematic study of metabolites and lipids in biological samples, promises to reveal the chemical fingerprints of disease, drug response, and organ dysfunction, yet the technology it depends on has struggled to keep pace with the sheer complexity of the task. Now, a team of researchers from the University of Manchester, Waters Corporation, Murdoch University, Curtin University, and the University of Surrey has demonstrated that a new class of mass spectrometer, known as a multi-reflecting time-of-flight instrument, can dramatically improve the accuracy with which metabolites are identified in real patient samples. Their proof-of-principle study, published in the journal Metabolomics, applied the platform to serum from hospitalized COVID-19 patients and uncovered clinically meaningful molecules that conventional instruments would likely have missed or misassigned.

The core problem the technology addresses is one of resolution. Biological samples such as serum contain tens of thousands of metabolites and lipids spanning an enormous range of chemical polarities and concentrations. When these compounds are separated by liquid chromatography and fed into a mass spectrometer, many arrive at the detector at nearly the same moment and with nearly identical mass-to-charge ratios. Lipids are especially troublesome: a species such as the phospholipid PC 34:2 exists in several structurally distinct isomeric forms with identical masses, and lipids from entirely different classes can share mass values so closely that their signals overlap. To make matters worse, molecules can form multiple adducts with sodium, potassium, or hydrogen ions, and the naturally occurring heavy isotopes of carbon, nitrogen, sulphur, and oxygen create additional peaks that can masquerade as entirely different compounds. The result is a forest of ambiguous signals in which confident identification, the foundation of biomarker discovery, becomes extraordinarily difficult.

Time-of-flight mass spectrometry has been a mainstay of high-resolution analysis for decades. The principle is elegant: ions are accelerated into a vacuum tube, and because heavier ions travel more slowly, their arrival times at a detector reveal their masses. Resolution improves with the length of the flight path, since ions of slightly different mass have more time and distance to separate. Classically, this meant building longer flight tubes, an approach that quickly becomes impractical in a laboratory and, crucially, degrades signal as ions travel farther. An alternative is to bounce ions back and forth between electrostatic mirrors called reflectrons, but conventional reflectrons contain wire grids that scatter and lose ions with each reflection. Over a handful of bounces the loss is tolerable; over dozens it becomes fatal to sensitivity and mass accuracy.

The multi-reflecting time-of-flight platform, or MRT, overcomes this limitation with gridless reflectron mirrors. Ions are reflected repeatedly through a series of periodic focusing lenses, extending the effective flight path to 47 metres inside an instrument of ordinary laboratory size while maintaining signal transmission. The result is a mass resolution exceeding 200,000 full width at half maximum, combined with sub-part-per-million mass accuracy and acquisition rates of up to 30 spectra per second. That combination of speed and resolution is what sets the platform apart. Fourier-transform instruments such as Orbitraps and ion cyclotron resonance analysers can achieve comparable or higher resolution, but they typically require scan times of around one second, which is far too slow to adequately sample the narrow two-to-three-second chromatographic peaks produced by modern ultra-high-performance liquid chromatography. The MRT, by contrast, collected 28 data points across a six-second peak in the demonstration study, providing the peak definition needed for both qualitative identification and quantitative analysis.

To put the instrument through its paces, the researchers analysed serum samples from eight patients recruited into the Manchester Allergy, Respiratory, and Thoracic Surgery Biobank COVID-19 cohort. The patients spanned a range of disease severity, from mild and convalescent infections to severe, active disease requiring intensive care, and were classified using the Manchester COVID-19 Severity Score, a clinical tool based on the level of respiratory intervention each patient required. Lipids and polar metabolites were extracted from the serum using a methyl-tert-butyl ether protocol and separated on an amide column over a rapid ten-minute gradient, with the mass spectrometer acquiring data in both positive and negative electrospray ionisation modes using data-independent acquisition.

The technical payoff was most vivid in the lipid region of the spectra. At a chromatographic peak eluting at 1.5 minutes, the instrument recorded four major ions. The base peak at mass-to-charge ratio 758.57019 was annotated as the phospholipid PC 34:2, but the next most intense peak, nominally at 760.58, resolved into two distinct signals separated by less than 0.01 daltons. One was the doubly carbon-13-labelled isotope of PC 34:2; the other was the monoisotopic peak of a co-eluting lipid, PC 34:1. The measured resolution of this region was 224,770, and simulations showed that even a conventional instrument operating at 100,000 resolution could not have separated the two. Similar deconvolution was achieved for the potassium adducts of the same lipids, where heavy and light isotopes of potassium and carbon combined to produce a tangle of overlapping signals that only the fine isotopic detail captured by the MRT could untangle. Because each element carries a characteristic isotope abundance pattern, this fine structure acts as a molecular fingerprint, providing an independent check on elemental composition that goes far beyond mass matching alone.

Mass accuracy proved equally transformative for compound annotation. Conventional quadrupole time-of-flight instruments typically report mass errors of one to three parts per million, and Orbitrap platforms around one to two parts per million at high resolution. The MRT delivered errors between 21 and 134 parts per billion across annotated compounds, roughly an order of magnitude tighter. This matters practically because database searching scales with the mass tolerance applied: a feature measured at 597.28739 returned nine candidate identifications when searched at two parts per million but only two when the filter was tightened to half a part per million, corresponding to isomeric forms of taurochenodeoxycholate sulphate. Narrower search spaces mean fewer false positives and far less manual curation, a persistent burden in large-scale metabolomics.

Applied to the patient cohort, the platform revealed metabolic differences associated with disease severity. Patients with severe, active infections showed broadly similar serum lipidome profiles, generally with lower feature abundance than a convalescent patient and one with mild disease, whose profiles clustered together. One severely ill patient stood apart with 152 unique mass features, compared with an average of 37.5 for the other patients. Among the annotated features in this individual were taurochenodeoxycholate sulphate and glycoursodeoxycholic acid, both bile acid derivatives. Sulphated bile acids have previously been reported as elevated in severe COVID-19 and linked to sepsis and renal dysfunction, and the patient’s clinical record of kidney failure and hypercholesterolemia was consistent with these findings. The same patient’s serum contained iohexol, an iodinated contrast agent normally cleared within 24 hours, which the researchers attributed to a recent CT scan compounded by renal failure delaying excretion. Perhaps most intriguingly, a feature was annotated as sphingofungin A, a sphingoid metabolite of the fungus Aspergillus fumigatus, the most common cause of COVID-19-associated pulmonary aspergillosis, a dangerous opportunistic infection estimated to affect roughly one in three mechanically ventilated patients. The patient had been ventilated, though the authors caution that the diagnosis could not be confirmed retrospectively.

The authors are careful to frame the work as a demonstration rather than a definitive clinical study. With only eight patients, one of whom was excluded on technical grounds, the findings cannot establish biomarkers or explain mechanisms, and the team acknowledges that the challenges of much larger metabolomics studies remain to be addressed. Several of the study’s authors are employed by Waters Corporation, the instrument’s manufacturer, a conflict of interest disclosed in the paper. Nevertheless, the proof of principle is compelling: the MRT platform resolved overlapping lipid species that would have gone undetected on conventional time-of-flight or electrostatic trap instruments, matched its annotations to the patients’ documented clinical histories, and did so at acquisition speeds compatible with the high-throughput analysis that well-powered clinical and epidemiological cohorts demand. If the technology scales as its developers hope, it could sharpen the entire pipeline of biomarker discovery, from the first chromatographic separation to the final confident assignment of a molecule’s identity, turning the chemical noise of human blood into interpretable clinical signal.

Subject of Research: High-resolution multi-reflecting time-of-flight mass spectrometry for metabolite and lipid identification in COVID-19 patient serum

Article Title: Multi-reflecting time-of-flight mass spectrometry enables high-accuracy metabolite identification in a demonstration study using serum samples from COVID-19 patients

Article References: King, A., Matthews, E., Maker, G., Trengove, R., Shareef, S., Fowler, S., Felton, T., Simpson, A., Palmer, M., Gethings, L. A., Plumb, R. S., & Mills, E. N. C. (2026). Multi-reflecting time-of-flight mass spectrometry enables high-accuracy metabolite identification in a demonstration study using serum samples from COVID-19 patients. Metabolomics, 22(5), Article 168. https://doi.org/10.1007/s11306-026-02539-w

Image Credits: AI Generated

DOI: 10.1007/s11306-026-02539-w

Keywords: metabolomics, lipidomics, mass spectrometry, time-of-flight, COVID-19, biomarkers, bile acids, isotopic fine structure, liquid chromatography, serum, renal dysfunction, aspergillosis