The Deepest Proteome Coverage Available with Spectronaut® 16

The Deepest Proteome Coverage Available with Spectronaut® 16 and AI-augmented Analysis

Data Independent Acquisition (DIA) in MS-based proteomics is regarded as the best-performing approach for LFQ workflows by the proteomics community. For the analysis of DIA data, Biognosys’ Spectronaut® software has been considered the gold standard for over a decade.

 

The recent release of Spectronaut 16 proves the value of introducing AI to the analysis of MS bottom-up proteomics data. With the new version of Spectronaut, users benefit from the most AI-augmented software for DIA analysis on the market, enabling them to identify more from their data than with any other solution available. Improvements include a better-performing directDIA workflow, new deep learning scores, and an enhanced user experience.

Record Number of Identifications

 

One of the key improvements in Spectronaut 16, compared to previous versions, is its ability to identify more proteins and precursors than ever before. This is partly thanks to the addition of DeepXIC, a deep neural network that uses extraction ion chromatograms to score identifications.

 

This unprecedented boost in identifications applies to both library-based and library-free workflows (Figure 1). In addition, identification numbers are consistently higher across instrument vendors which ensures that all Spectronaut users will see significant improvements in their data analysis.

 

 

Figure 1. Relative improvements and average identifications between Spectronaut 15 and 16.

Unparalleled High-throughput DIA

 

Spectronaut 16 demonstrates significant improvements when analyzing high-throughput DIA data and consistently outperforms other solutions.

 

We tested Spectronaut 16 against exemplary short-gradient DIA data1 and compared them against published data2. Our analysis clearly showed that Spectronaut 16 identifies more precursors and protein groups than other solutions on the market (Figure 2). Comparable results were observed for FAIMS data.

 

 

 

Figure 2. Average number of precursors identified with high-throughput DIA. A comparison between Spectronaut 16 and dia-NN.

Gain a Deeper Understanding of Your Plasma Data

 

We recognize the importance of plasma analysis in detecting and monitoring the progression of many diseases. In Spectronaut 16, plasma analysis is even more accurate than before, with a significant increase in identifications when compared to Spectronaut 15 (Figure 3).

 

When measuring mixed proteome samples spiked in different amounts (human depleted plasma 1:1, E. coli 1:0.4, S. cerevisiae 1:1.3) Spectronaut 16 also recovers significantly more true candidates than before.

 

 

 

Figure 3. Improvements in plasma biomarker discovery between Spectronaut 15 and 16. 

The Best User Experience Just Got Better

 

Biognosys places emphasis on offering a seamless user experience. With Spectronaut 16, users can take advantage of our new one-step directDIA workflow and new visualizations, including a DIA acquisition method overview and a condition box plot available in the grid view. In addition, Spectronaut includes reporting options that help users gain an even deeper insight into their DIA data.
While Spectronaut 16 offers many options for visualizations and reporting, we understand the benefit of having access to the data behind the results. Therefore, we ensure that the raw results are always available to view or export.

 

Spectronaut: The Best Companion for Your DIA Proteomics Projects

 

Spectronaut’s unmatched identification capabilities coupled with a seamless user experience and dedicated customer support make Spectronaut the ideal software solution for any DIA proteomics project.

 

Try Spectronaut 16 yourself by requesting a free trial or getting in touch with us through our Helpdesk.

 

This article was first published in The French Proteomics Society’s Newsletter.

 

 

References

1. Meier et al. diaPASEF: parallel accumulation–serial fragmentation combined with data-independent acquisition. Nat Methods 17, 1229–1236 (2020)
2. Demichev et al. High sensitivity dia-PASEF proteomics with DIA-NN and FragPipe. bioRxiv, 08.434385 (2021)

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