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Zika's Molecular Effects Identified by Proteomic Analysis


NEW YORK (GenomeWeb) – A team of Brazilian researchers has characterized alterations to the proteome and transcriptome of neural stem cells resulting from infection with the Zika virus.

Published last week in Nature Scientific Reports, the study identifies several cellular processes affected by the virus that could explain the brain malformations associated with the disease and could help identify potential treatments, said Daniel Martins-de-Souza, an assistant professor and head of proteomics at São Paulo's University of Campinas and author on the study.

Specifically, the researchers identified differentially regulated proteins in pathways controlling the cell cycle, neuronal differentiation, and chromosomal stability.

Key to the study was establishing what cell population might best exhibit the effects of Zika infection, Martins-de-Souza said, noting that this was a challenge, given that relatively little is known about the timing and processes leading to Zika-related outcomes like microcephaly.

"We don't know yet when exactly these things happen," he said, noting that in previous experiments, he and his colleagues had looked at cells later in the development process and seen primarily changes in proteins related to cell death, which he said were expected.

In the recent effort, the Brazilian team looked at neurospheres, which are cultures of free-floating neural stem cells, representative of a fetal brain at around three months gestation, Martins-de-Souza said. "That was a point at which we thought we could find some interesting information. We tried to pinpoint a time where the cells were still viable but where they were showing some suffering from the infection."

"Our hypothesis is that cells that are older than this are already dying and the microcephaly is probably already established," he said. "Whereas at this point, we're getting the virus as it is doing something, which lets us look at the molecular pathways and see what they are doing that is causing the cells not to progress."

In an RNA-seq and mass spec-based analysis of Zika-infected neurospheres and controls, the researchers identified 199 proteins downregulated and 259 upregulated in response to the virus. Among the downregulated proteins were molecules involved in organelle localization and regulation and protein folding, while proteins involved in translation and the cell cycle were upregulated.

Integrating the RNA and protein data, the researchers developed an interactome of differentially regulated proteins and genes that indicated Zika-infected neurospheres would suffer from viral replications, cell cycle arrest, chromosomal instability, and reduced differentiation into neurons.

Martins-de-Souza highlighted as particularly notable the finding that among the altered proteins were a number involved in regulating differentiation of neural stem cells into neurons.

"If those proteins are affected, [differentiation] doesn't happen," he said, which could contribute to conditions like microcephaly.

Identification of these proteins could be useful in developing therapies to counter the effects of Zika, he added. For instance, researchers could monitor their behavior in response to different treatments to determine whether the treatments promote normal differentiation in infected cells.

For their mass spec analysis, Martins-de-Souza and his colleagues used a Waters Synapt G2-Si instrument running the UDMSE data-independent acquisition method. Introduced in 2013 by researchers from the Johannes-Gutenberg University Mainz in Germany, the technique takes advantage of Waters' ion mobility spectrometry (IMS) technology to optimize ion fragmentation, allowing for more comprehensive proteomic analyses.

Waters' MSE DIA workflow uses co-elution times to match precursors and fragment ions to make peptide identifications. The method fragments both high- and low-m/z ions together, and because low-m/z ions fragment best at lower collision energies and high-m/z ions fragment best a higher collision energies, the mass spec must ramp its collision energy up and down over the course of a scan cycle.

This ramping, however, means that large portions of ions are not fragmented at the ideal collision energy, a problem the Mainz researchers tackled by using the instrument's IMS technology to establish the approximate m/z of the ions being fragmented at a given time. Small ions travel faster through the IMS than large ions, making it possible to predict when ions of a particular m/z will reach the instrument's collision cell and therefore to adjust the collision energies for optimal fragmentation.

The result, said Martins-de-Souza, who was not involved in the original development of the technique, is a significant increase in the number of identified proteins. He said that his group has found that using the IMS feature on their Waters instruments as part of what the company calls its HDMSE workflow, which does not optimize collision energies, typically increases their identifications by around 40 percent compared to experiments done without IMS. Using IMS to optimize collision energies as in the UDMSE approach increases identifications by roughly another 20 percent, he said.

Additionally, he noted, the method provides more confident identifications. "It's not only the 20 percent more proteins identified, but also the fact that we have more confidence in that data because we identified more peptides [per protein]]," he said. "If when we do HDMSE we identify a given protein by, say, two peptides, then by using UDMSE we can identify it by four peptides. And that is more powerful for quantification, identification, and so on."

Martins-de-Souza said he and his colleagues are now participating in a larger, recently launched Brazilian project bringing together several academic institutions to study various aspects of Zika, including looking for biomarkers of infection and treatment options. In addition to his team, the effort will also include "experts on microcephaly, people with knowledge of potential drugs and pharmacogenomics," he said.

One area of focus will be identifying markers that will allow clinicians to distinguish between infection with Zika and other conditions that can present similarly, such as Dengue fever.

"The two are very similar, and there is no molecular signature for [distinguishing between] them," he said. The researchers plan to continue using neurospheres for their work but also hope to move into actual patient samples, looking at pregnant women with and without Zika infections, Martins-de-Souza added.