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Researchers Profile Switchgrass Proteome as Part of Biofuel Development Efforts


NEW YORK(GenomeWeb) – A team led by scientists from Lawrence Berkeley National Laboratory has characterized the proteome of switchgrass (Panicum virgatum) as part of ongoing work to develop the plant as a biofuel.

In a paper published this week in the journal Proteomics, the researchers used LC-MS/MS analysis on a Thermo Fisher Scientific Q Exactive instrument to profile the endomembrane proteome of developing switchgrass coleoptiles – the protective sheaths that cover the growing shoot in grasses.

Their analysis identified a total of 2,514 unique switchgrass proteins including 1,750 detected in both of two biological replicates. Based on a Gene Ontology analysis, the identified proteins were highly enriched for those associated with organelles and membranes as well as processes including cellular metabolism and localization.

The study was intended as an initial proof of principle aimed at exploring the potential usefulness of proteomics for validating genomics work in the organism and identifying proteins expressed in different tissues of the plant, Benjamin Schwessinger, senior author on the paper and a researcher at LBNL and the University of California, Davis, told GenomeWeb.

Native toNorth America, switchgrass has emerged as a focus of biofuel research due to its hardy nature and potential for efficient energy production, Schwessinger said.

Currently, most ethanol is produced from corn. However, switchgrass offers the potential for much less expensive and land-intensive ethanol production.

For instance, Schwessinger said, "If we were to switch to switchgrass right now, it would be 20 times better than corn in terms of the monetary input you need to get out the same amount of ethanol."

Given switchgrass' potential, significant private and public funds have been invested in research into the plant. Among these efforts is work by the US Department of Energy's Joint Genome Institute to sequence the organism.

The current genome assembly for the grass, version 1.1, contains more than 300,000 contigs.

As Schwessinger and his co-authors noted, proteomics can be a useful tool for refining and validating this genome. Additionally, he said, because switchgrass has a polyploid and heterozygous genome, proteomics can be useful in identifying which alleles are, in fact, functional in different tissues and under different conditions.

"Proteomics can help us find the enzymes that are actually being expressed at the protein level," he said.

It could also be helpful in determining the expression patterns of different variants, he added. "If the peptides match back to the genome, then it is really clear that one SNP maps to an amino acid change in your peptide and so you can say, first of all, that it is real, and second of all, that one variant might be more expressed than another."

In the study, Schwessinger and his colleagues looked at switchgrass coleoptiles, choosing this stage of the plant's growth because it is easier to manipulate than more mature plants.

"This was just to show that [proteomics] was possible with these next-generation sequenced genomes," he said, noting that they planned within the next several weeks to begin looking at the proteome of plants that are several weeks old.

"When you talk about biofuel production you are mostly interested in the stem and leaves," he said. "So our next step is to try to do something similar for [older] plants, and then we will profile the different tissue types and see what kind of cell wall biosynthesis enzymes are expressed in different cell types."

He noted that the low abundance of most biosynthetic enzymes made them somewhat challenging to detect via mass spec, though, he said, enriching for the insoluble portion of their sample would help enrich for the membrane-associated enzymes they hoped to identify.

Longer term, proteomic analyses could help researchers in breeding switchgrass variants well suited to specific growth conditions or with protein production patterns enhanced for ethanol production, Schwessinger said.

For instance "lots of enzymes [useful in biofuel production] could be involved in synthesizing the cell walls," he said. "But you don't really know which one is expressed in the tissue you are interested in and in the compartment you are looking at. So proteomics can tell you that, and then you could later on develop plants that express those enzymes in the later stages of development when you actually want to have most of your easily accessible cell wall proteins" for optimal biofuel production.

Schwessinger noted that, despite its potential usefulness, there has been relatively little proteomics work in biofuel research.

"I think it's in its infancy," he said, noting that the Proteomics study was one of the first deep characterizations of the plant's proteome.

One challenge that has faced agricultural and industrial proteomics is the fact that reference genomes are required for making protein identifications in mass spec-based proteomics, which has limited researchers to model organisms for which there existed assembled genomes.

For instance, as Christof Rampitsch, a cereal proteomics researcher at Canada's Department of Agriculture and Agri-Food, told GenomeWeb in 2012, a lack of reference databases has hindered plant proteomics, forcing researchers to use workarounds like homology-based searches that can sometimes lead to questionable protein IDs.

"I see this quite a lot in the literature," he said. "Someone will be working on something like sugar cane or banana – something that is a relatively major crop that hasn't been sequenced – and they'll do a homology-based search and just report the best hit they get whether that hit has a score that is barely above the threshold or it's a reasonably good score."

The construction of the switchgrass genome meant this wasn't an issue for Schwessinger and his colleagues, but, more generally, the problem has been mitigated somewhat by the rise of next-generation sequencing, which has allowed researchers to generate custom-built databases to samples of interest using approaches like RNA-seq.

Nonetheless, Schwessinger said that the plant world remains very "genetics driven." Proteomics has lagged in this area in part due to technology being less readily available than it is for genomic work, he suggested.

"Proteomics cores are available but [plant] people don't really invest in those the way they do in the medical field," he said. "And proteomics tends to be more on the expensive side."