Glycoforest 1.0

Abstract

Tandem mass spectrometry, when combined with liquid chromatography and applied to complex mixtures, produces large amounts of raw data, which needs to be analyzed to identify molecular structures. This technique is widely used, particularly in glycomics. Due to a lack of high throughput glycan sequencing software, glycan spectra are predominantly sequenced manually. A challenge for writing glycan-sequencing software is that there is no direct template that can be used to infer structures detectable in an organism. To help alleviate this bottleneck, we present Glycoforest 1.0, a partial de novo algorithm for sequencing glycan structures based on MS/MS spectra. Glycoforest was tested on two data sets (human gastric and salmon mucosa O-linked glycomes) for which MS/MS spectra were annotated manually. Glycoforest generated the human validated structure for 92% of test cases. The correct structure was found as the best scoring match for 70% and among the top 3 matches for 83% of test cases. In addition, the Glycoforest algorithm detected glycan structures from MS/MS spectra missing a manual annotation. In total 1532 MS/MS previously unannotated spectra were annotated by Glycoforest. A portion containing 521 spectra was manually checked confirming that Glycoforest annotated an additional 50 MS/MS spectra overlooked during manual annotation.

Towards a standardized bioinformatics infrastructure for N- and O-glycomics

“…In addition to adapting the submission process to a broader range of experimental workflows, we are also aiming to automate submission to UniCarb-DR. To this end, we plan to accept direct submissions from glycan structure assignment tools such as Glycoforest 65 . In 2020, a web version of Glycoforest will manage the automation of structure assignment to MS/MS spectra.…”

“…The commitment to store glycomics MS datasets is essential. The annotation of glycomics LC-MS data is currently based only on the knowledge of the interpreters 65 , be it a software or a human researcher or both. From this it can be concluded that it is highly unlikely that all information from a glycomic raw data set will be extracted in a single analysis.…”

“…Other approaches convert mass spectra into structures relying on spectral libraries 57,62 . More advanced tools for glycomics analysis use partial de novo sequencing 63 including GlycoDeNovo 64 and the recently published Glycoforest 65 . High-throughput glycomics MS annotation tools (GRITS Toolbox 66 , www.grits-toolbox.org/) and quantitation tools 67 are now available and increase the need for a common data exchange format.…”

A Potential Golden Age to Come—Current Tools, Recent Use Cases, and Future Avenues for De Novo Sequencing in Proteomics

“…Therefore, de novo glycan sequencing is considered a challenging and computationally hard problem that has only been addressed by few research groups to date . Although different sophisticated algorithms and tools were proposed more recently, more development concerning efficient glycan structure determination is required. Overall, glycomics will strongly benefit from improvements in both MS instrumentation and de novo sequencing algorithms.…”

Proceedings of the EuBIC developer's meeting 2018

“…By making use of open modi cation searching peptides with previously unconsidered post-translational modi cations (PTMs) could be successfully identi ed [3]. Next, she explained how new computational tools can be used for the analysis of glycoproteomics data [4].…”