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LAP-MALDI MS coupled with machine learning: an ambient mass spectrometry approach for high-throughput diagnostics.

ABSTRACT: Large-scale population screening for early and accurate detection of disease is a key objective for future diagnostics. Ideally, diagnostic tests that achieve this goal are also cost-effective, fast and easily adaptable to new diseases with the potential of multiplexing. Mass spectrometry (MS), particularly MALDI MS profiling, has been explored for many years in disease diagnostics, most successfully in clinical microbiology but less in early detection of diseases. Here, we present liquid atmospheric pressure (LAP)-MALDI MS profiling as a rapid, large-scale and cost-effective platform for disease analysis. Using this new platform, two different types of tests exemplify its potential in early disease diagnosis and response to therapy. First, it is shown that LAP-MALDI MS profiling detects bovine mastitis two days before its clinical manifestation with a sensitivity of up to 70% and a specificity of up to 100%. This highly accurate, pre-symptomatic detection is demonstrated by using a large set of milk samples collected weekly over six months from approximately 500 dairy cows. Second, the potential of LAP-MALDI MS in antimicrobial resistance (AMR) detection is shown by employing the same mass spectrometric setup and similarly simple sample preparation as for the early detection of mastitis.

SUBMITTER: Piras C

PROVIDER: S-EPMC8826629 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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LAP-MALDI MS coupled with machine learning: an ambient mass spectrometry approach for high-throughput diagnostics.

Piras Cristian C Hale Oliver J OJ Reynolds Christopher K CK Jones A K Barney AKB Taylor Nick N Morris Michael M Cramer Rainer R

Chemical science 20220118 6

Large-scale population screening for early and accurate detection of disease is a key objective for future diagnostics. Ideally, diagnostic tests that achieve this goal are also cost-effective, fast and easily adaptable to new diseases with the potential of multiplexing. Mass spectrometry (MS), particularly MALDI MS profiling, has been explored for many years in disease diagnostics, most successfully in clinical microbiology but less in early detection of diseases. Here, we present liquid atmosp ...[more]

PMID: 35282613

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Project description:Oral tumors, including highly invasive and metastatic oral melanoma (OM), non-tonsillar oral squamous cell carcinoma (OSCC) and benign tumors (BN), are common neoplasms in dogs. Although these tumors behave differently, limited data of their protein expression profiles have been exhibited, particularly at the proteome level. The present study aimed to i.) characterize peptide-mass fingerprints (PMFs) and identify potential protein candidates of OM, OSCC, BN and normal control subjects, using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and liquid chromatography tandem mass spectrometry (LC-MS/MS), ii.) identify potential protein candidates associated with the diseases, using in-gel digestion coupled with mass spectrometric analysis (GeLC-MS/MS) and iii.) search for relationships between chemotherapy drugs and disease-perturbed proteins. A distinct cluster of each sample group and unique PMFs with identified protein candidates were revealed. The unique peptide fragment at 2,274 Da of sacsin molecular chaperone (SACS) was observed in early-stage OM whereas the fragment at 1,958 Da of sodium voltage-gated channel alpha subunit 10 (SCN10A) was presented in early- and late-stage OM. The peptide mass at 2,316 Da of Notch1 appeared in early-stage OM and benign oral tumors while the peptide mass at 2,505 Da of glutamate ionotropic receptor N-methyl-D-aspartate type subunit 3A (GRIN3A) was identified in all groups. Markedly expressed proteins from GeLC-MS/MS included Jumonji domain containing 1C (JMJD1C) in benign tumors, inversin (INVS) and rho guanine nucleotide exchange factor 28 (ARHGEF28) in OM, BTB domain-containing 16 (BTBD16) in OSCC, and protein tyrosine phosphatase non-receptor type 1 (PTPN1), BRCA2, DNA repair associated (BRCA2), WW domain binding protein 2 (WBP2), purinergic receptor P2Y1 and proteasome activator subunit 4 (PSME4) in all cancerous groups. The network connections between these proteins and chemotherapy drugs, cisplatin and doxorubicin, were also demonstrated. In conclusion, this study unveiled the unique PMFs and novel candidate protein markers of canine oral tumors.

Project description:A liquid matrix-assisted laser desorption/ionization (liquid MALDI) method has been developed for high-throughput atmospheric pressure (AP) mass spectrometry (MS) analysis of the molecular content of crude bioliquids for disease diagnostics. The presented method is rapid and highly robust, enabling its application in environments where speed and low-cost high-throughput analyses are required. Importantly, because of the creation of multiply charged analyte ions, it provides additional functionalities that conventional solid MALDI MS profiling is lacking, including the use of high-performance mass analyzers with limited m/z range. The concomitant superior MS/MS performance that is achieved similar to ESI MS/MS adds greater analytical power and specificity to MALDI MS profiling while retaining the advantages of a fast laser-based analysis system and off-line large-scale sample preparation. The potential of this MALDI MS profiling method is demonstrated on the detection of dairy cow mastitis, which is a substantial economic burden on the dairy industry with losses of hundreds of dollars per diseased cow per year, equating to a total annual loss of billions of dollars, as well as leading to the use of large quantities of antibiotics, adding to the proliferation of antimicrobial resistance. Only small amounts of aliquots obtained from the daily farm milking process were prepared for liquid MALDI MS profiling using a simple one-pot/two-step analyte extraction. Automated analysis was performed using a custom-built AP-MALDI ion source, enabling the simultaneous detection of lipids, peptides, and proteins. Diagnostic, multiply charged, proteinaceous ions were easily sequenced and identified by MS/MS experiments. Samples were classified according to mastitis status using multivariate analysis, achieving 98.5% accuracy (100% specificity) determined by "leave 20% out" cross-validation. The methodology is generally applicable to AP-MALDI MS profiling on most commercial high-resolution mass spectrometers, with the potential for expansion into hospitals for rapid assessment of human and other biofluids.

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LAP-MALDI MS coupled with machine learning: an ambient mass spectrometry approach for high-throughput diagnostics.

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LAP-MALDI MS coupled with machine learning: an ambient mass spectrometry approach for high-throughput diagnostics.

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