MSACL 2019 EU Abstract

Exploring Optimal Protein Identification and Repeatability via Sequences of Fine-Tuned LC-MS/MS Runs

Márton Gyula Milley (1,2), Ágnes Révész (1), László Drahos (1)
(1) MS Proteomics Research Group, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Magyar tudósok körútja 2., H-1117 Budapest, Hungary, (2) Budapest University of Technology and Economics, Faculty of Chemical Technology and

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Márton Gyula Milley (Presenter) RCNS, Hungarian Academy of Sciences

Presenter Bio: My name is Márton Milley and I am MSc student at Budapest University of Technology and Economics as a chemical engineer. Previously I have actively participated in biological research projects and now I am focusing on investigation of protein structures. Currently, I am working on my master thesis in Research Centre for Natural Sciences, Hungarian Academy of Sciences, group of MS Proteomics and my topic is exploring optimal protein identification and repeatability via sequences of fine-tuned LC-MS/MS run with the aim of improving the technical background the discovery of new biomarkers. I am enthusiast to find new solutions in this field and becoming an expert in order to fight against serious diseases.

Relevant Financial Disclosures (within past 24 months) No relevant financial relationship(s) to disclose. Conflict mitigation NOT REQUIRED.

INTRODUCTION: Shotgun proteomics is a high throughput method to identify peptides and proteins from complex biological samples. However, it is not an unequivocal procedure, due to the variability of LC-MS/MS experimental conditions and the search engine parameters used in data analysis. Further, in case of data-dependent approach, there may be significant run-to-run variability in the peaks selected for MS/MS analysis resulting in different set of identified peptides even from identical LC-MS/MS runs.

OBJECTIVES: This study aims to explore the combination of experimental settings leading to the largest number of identified peptides/proteins using a given measurement time frame. In the first stage, we focus on the effect of repeated identical measurements, while in the second stage investigation and optimization of chromatographic and Q-TOF instrumental settings are done to assess their influence on proteome coverage of HeLa standard sample. The performance of two commonly used sequence database search software packages, Byonic and Mascot is also investigated.

METHODS: We carry out various repeated nano-LC-MS/MS runs on HeLa tryptic digest on a Bruker Maxis II Q-TOF instrument. The data are searched against the SwissProt Human database. Further analysis and comparison of the output of the search engines files are done using the Scaffold 4 program. For optimization, according to recent literature, we test the following parameters: dynamic exclusion duration, mass-range, time of gradient. Design of experiments is used to evaluate significant factors and instrument performance is characterized with protein groups, unique peptides and spectral counts.

RESULTS: From a combined analysis of repeated LC-MS/MS runs, we found that 3 to 4 repeats are adequate to find about 90% of proteins and peptides in a sample with this complexity. A direct comparison of search engines using the LFDR-based (re)scoring system in Scaffold revealed that Byonic identifies a comparable number of proteins, but significantly more peptides. Further tests on different database sizes and mass spectrometric parameters allowed us to suggest a protocol with an optimal number of peptides or proteins for a given number of repeated measurements.

CONCLUSION: Our results demonstrate that proteomic measurements based on standard protocols can significantly benefit from targeted optimization and from using a small set of replicates to achieve appropriate coverage. Such optimization can thus lead to more efficient utilization of measurement time and enhanced repeatability, addressing a main concern in proteomics experiments.