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Analyses Find DIA Mass Spec Approaching, Surpassing Shotgun Methods for Protein Identification


NEW YORK (GenomeWeb News) – With a new crop of instruments and methods hitting the market some analyses show data-independent acquisition mass spec approaching, or even surpassing, traditional data-dependent workflows.

In an interview with ProteoMonitor last November, Swiss Federal Institute of Technology Zurich researcher Ruedi Aebersold noted that while DDA methods typically identified more total peptides, when measuring several replicates DIA methods generate "a higher number of consistently identified peptides."

He added that an analysis by targeted proteomics firm Biognosys – of which he is a co-founder – had determined this crossover point to be around three to four samples.

A more recent analysis by Biognosys, though, has found that now even in a single run, current DIA methods identify more peptides than traditional DDA techniques, company Co-founder and CEO Oliver Rinner told ProteoMonitor last week.

Today, "even if you look at just a single injection, if you are using large, high-quality spectral libraries, you identify significantly more peptides" with DIA than DDA, he said.

This improvement in DIA workflows is due to a number of factors, Rinner said, including better instrumentation, improved algorithms, and more carefully constructed spectral libraries.

In DDA mass spec, the instrument performs an initial scan of precursor ions entering the instrument and selects a sampling of those ions for fragmentation and generation of MS/MS spectra. Because instruments can't scan quickly enough to acquire all the precursors entering at a given moment, many ions – particularly low-abundance ions – are never selected for MS/MS fragmentation and so are not detected.

In DIA, on the other hand, the mass spec selects broad m/z windows and fragments all precursors in that window, allowing the machine to collect MS/MS spectra on all ions in a sample.

DIA was first put forth as a potential workflow by Scripps Institute researcher John Yates III in 2004 and became commercially available in 2006 with the launch of Waters' MSE system. The method grew in popularity with the 2011 release of AB Sciex's Swath method – developed in collaboration with Aebersold – for its TripleTOF 5600 machine.

Last month at the American Society for Mass Spectrometry annual conference, AB Sciex released Swath 2.0 for use on its new TripleTOF 6600 instrument. Also at the meeting Thermo Fisher released its first DIA products – four different workflows for use on their Q Exactive and Orbitrap Fusion machines.

Biognosys did their updated DIA-DDA comparison on the Q Exactive using Thermo Fisher's Swath-DIA method, which is comparable to AB Sciex's Swath 2.0 product. Looking at HEK-293 cell lysate, Rinner and his colleagues found that even in their first run the Q Exactive run in DIA mode identified more peptides than in DDA mode – around 29,000 compared to around 17,000 for DDA.

Running additional replicates, the number of peptides identified consistently by DDA dropped off significantly – down to around 6,000 by run 24 – while with DIA they were able to consistently identify 90 percent of the proteins they detected in their first run, he said.

Rinner also cited work done by Thermo Fisher and presented at ASMS by Alexander Makarov, the company's director of global research for life science mass spectrometry. In that work, the researchers used DIA-Swath on the Q Exactive HF instrument for an analysis of HeLa lysate, identifying more than 4,000 proteins, two-thirds of which they were able to quantify across replicates with coefficients of variation below 10 percent and 95 percent of which they quantified with CVs of below 20 percent.

Rinner said that Biognosys had not yet performed a similar DIA-DDA analysis using AB Sciex's TripleTOF 6600 instrument and Swath 2.0 workflow, but, he said, he anticipated that it would show comparable improvement.

"Many of the improvements [in DIA methodology] made over the last year apply equally to the process of AB Sciex Swath data," he said. "So we would think that with regards to DIA versus DDA, it would be the same [on the AB Sciex] system."

Regarding improvements in DIA workflows, Rinner said one of the keys has been increased attention to the spectral libraries used for making identifications in DIA mass spec.

These libraries are typically generated by DDA runs of the samples of interest prior to DIA analysis, and, Rinner noted, in the past researchers have at times been somewhat careless in their construction.

"Some people have just kind of dumped data from repositories [to make] spectral libraries and they didn't care much about things like [false discovery rates]," he said. "But if you use libraries that have very accurate retention time estimates in there and you do some optimization" it can improve DIA analysis.

Additional attention paid to calibration of parameters like retention time have also made a difference, Rinner said, as has improved detection of interferences.

Biognosys' sells its Spectronaut software and HRM Calibration Kit for generating spectral libraries and calibrating and analyzing DIA experiments.

Aside from Biognosys' analysis, another recent indication of DIA's growing power came from a Nature Methods study published in December by researchers at the Johannes Gutenberg University Mainz, in which they used an MSE method termed USMSE that incorporates ion mobility drift times to improve precursor fragmentation efficiency.

Applying the approach to an analysis of HeLa cell lysate on a Waters Synapt G2-S instrument, the team identified 36,551 peptides and 3,795 proteins with a 90-minute nanoLC gradient. They found that this surpassed the performance of a comparable DDA analysis on a Q Exactive.