**Poster 172: P172** *The development of microbore UHPLC-MS assays to enhance sensitivity of untargeted metabolomic analysis of mammalian biofluids.*

Annie J. HARWOOD-STAMPER<fnref n="1" />; Caroline A. ROWLAND<fnref n="2" /> and Warwick DUNN<fnref n="1" />,<fnref n="3" />,<fnref n="4" />

**Introduction**

To date, there has been limited research into ultra-high performance liquid chromatography-mass spectrometry assays for untargeted metabolomics analysis of biofluid samples of low volumes including dried blood spots and tears (<20µL) Demands for these assays are growing. Currently, most biofluids achieve satisfactory results by using standard methods applying 2.1mm internal diameter (ID) columns, but these methods do not provide the optimal sensitivity needed for samples of low volumes.

**Technological and methodological innovation**

Three metabolomics assays were developed (C18 reversed-phase lipidomics, C18 aqueous reversed-phase and HILIC) using human plasma and urine along with 2.1mm and 1.0mm ID UHPLC columns of the same stationary phase composition and particle size. Data comparisons quantified the influence of column ID on assay sensitivity, reproducibility and chromatographic peak width. The 1.0mm ID column assays were next evaluated using a time-series of plasma, urine and tear samples collected during a pig study.

**Results and impact**

Overall, reducing column ID saw a sensitivity increase (number of compounds detected, peak area). Similar reproducibility levels were seen. The decrease in flow rates used for UHPLC columns may be a large contributor to any unforeseen results including increased UHPLC peak widths. Comparisons of the three biofluids using the 1.0mm ID assays allowed for the metabolite characterisation of tear samples and understanding of the correlation of metabolite relative concentrations between biofluids.

<footnote n="1">¹ School of Biosciences, University of Birmingham, Birmingham, B15 2TT, UK</footnote>

<footnote n="2">² Defence Science and Technology Laboratory, Porton Down, Salisbury, SP4 0JQ, UK</footnote>

<footnote n="3">³ Phenome Centre Birmingham, University of Birmingham, Birmingham, B15 2TT, UK</footnote>

<footnote n="4">⁴ Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, B15 2TT, UK</footnote>
**Poster 173: P173 MeTaQuaC: Quality Control Measures for Targeted Metabolomics**
**Studies**

Mathias KUHRING<sup>1,2,3</sup>; Eric BLANC<sup>1,4</sup>; Yoann GLOAGUEN<sup>1,2,3</sup>; Alina EISENBERGER<sup>1,2,3</sup>; Raphaela FRITSCHE<sup>1,2,3</sup>; Jennifer KIRWAN<sup>2,3</sup>; Dieter BEULE<sup>1,3,4</sup>

Core Unit Bioinformatics, Berlin Institute of Health (BIH), Berlin, Germany

Berlin Institute of Health Metabolomics Platform, Berlin Institute of Health (BIH), Berlin, Germany

Max Delbrück Center (MDC) for Molecular Medicine, Berlin, Germany

Charité–Universitätsmedizin Berlin, Berlin, Germany

**Introduction**

Optimized and validated targeted mass spectrometry profiling methods enable comprehensive routine applications such as the analysis of larger cohorts. However, such studies require consistent processing and reliable instrumentation to minimize technical variance and interference, including systematic and random errors. Consequently, multiple and reproducible quality controls (QCs) are required to verify data conditions with respect to quality assurance (QA) measures.

**Technological and methodological innovation**

Here we present MeTaQuaC, an extensive, easy-to-use and free quality control R package designed for targeted data acquired using Biocrates' kits and which is complementary to Biocrates' MetIDQ software. It combines several visualizations and statistics into an HTML report. These include, for instance, evaluation of measured and missing values, positional irregularities with respect to acquisition sequence or well plate coordinates as well as sample and metabolite variability and reproducibility.

**Results and impact**

MeTaQuaC enables detailed utilization of QA measures as provided by standardized kits and currently supports Biocrates' AbsoluteIDQ® p400 HR Kit and MxP® Quant 500 Kit. With defined, reproducible and viable QCs, it aids in verifying data consistency and quality or, if necessary, in identifying patterns of interference as well as removing low quality metabolites or samples, thereby increasing confidence in data and subsequent analysis. MeTaQuaC is available under MIT open source license [1].

**References**

[1] https://github.com/bihealth/metaquac