The intrinsic and regulated proteomes of barley seeds in response to fungal infection

Barley is an important cereal grain used for beer brewing, animal feed, and human food consumption. Fungal disease can impact barley production, as it causes substantial yield loss and lowers seed quality. We used sequential window acquisition of all theoretical ions mass spectrometry (SWATH-MS) to measure and quantify the relative abundance of proteins within seeds of different barley varieties under various fungal pathogen burdens. Fungal burden in the leaves and stems of barley resulted in changes to the seed proteome. However, these changes were minimal and showed substantial variation among barley samples infected with different pathogens. The limited effect of intrinsic disease resistance on the seed proteome is consistent with the main mediators of disease resistance being present in the leaves and stems of the plant. The seeds of barley varieties accredited for use as malt had higher levels of proteins associated with starch synthesis and beer quality. The proteomic workflows developed and implemented here have potential application in quality control, breeding and processing of barley, and other agricultural products.


Introduction
Barley is a major cereal grain used as stockfeed for animals, as food for humans, and as the main agricultural product for brewing beer. In 2016, 141 million metric tonnes of barley was produced globally, making it the fourth highest produced cereal commodity behind maize, wheat, and rice (1). As barley is the main ingredient in brewing, varieties of barley are bred and grown specifically for use as malt in the brewing industry. Many qualities are specifically targeted when breeding and growing malting barley, including high yields, disease resistance, diastase production (starch degrading enzymes), and low levels of β-glucan (2). In addition, different varieties of barley are grown in Australia for export or domestic markets. This is because the Australian brewing industry tends to use additional sucrose in fermentation, whereas brewers in export markets tend to use additional sources of starch such as rice which require higher levels of diastase enzymes.
Since barley is usually grown in a largely uncontrolled environment, the harvested grain is likely to exhibit variability in grain size, density, starch content, and proteome. As most of the steps in the process of beer brewing rely on proteins, enzymes, and starch from barley, it is expected that variability in the seed will directly affect the beer brewing process and beer quality in complex ways. Diseases are one of the biggest threats to barley production and grain quality, as they may reduce grain size, alter malting quality, and most importantly lower grain yield (3)(4)(5)(6). It is estimated that diseases cause approximately $252 M of losses per annum in barley production in Australia alone (7). Net form of net blotch (Pyrenophora teres f. teres), spot form of net blotch (P. t. f. maculata), and leaf rust (Puccinia hordei) are amongst the most common diseases affecting the yield and quality of Australian barley production.
Net blotch, named after the netting pattern that appears on the leaves of infected barley, can also form spot-like lesions. These two distinct symptoms are deemed to be the result of infection by two subspecies (formae) of P. teres: P. teres f. teres and P. teres f. maculata (8).
These symptoms lead to the corresponding common names of net form of net blotch and spot form of net blotch. Net form of net blotch may cause yield losses in excess of 50% while spot form of net blotch seldom causes losses above 30% (9). Net blotches are stubble-borne diseases, with P. teres f. teres also frequently seed-borne (10). Infection with either form of net blotch can lead to a reduction in seed size and density and can negatively affect the quality of barley for malt and feed (5). Leaf rust of barley is a disease that produces small, orange-brown pustules on the leaves and leaf sheaths of infected plants. When actively growing, the pustules produce urediniospores which are replaced by black teliospores as they age (11). The orange-brown coloration of the urediniospores gives the disease the name leaf rust. All three diseases are air-borne with leaf rust the best adapted for wind dispersal (9).
Yield losses associated with leaf rust can be as high as ~ 62% (7,(11)(12)(13). Like net blotch, leaf rust also negatively affects the quality of the grain by reducing grain weight and grain size (6).
Variability in the barley seed proteome due to diseases, barley variety, and other factors is likely to affect seed quality and downstream process efficiencies, and yet is poorly understood. Previous proteomic studies using 2D SDS-PAGE investigated how fungal disease directly affected local plant physiology either in the leaves or seeds during germination (14,15). Investigation of the leaf proteome in leaf rust infection identified changes in carbohydrate metabolism, protein degradation, and defence proteins (14), while infection of germinating barley seeds by Fusarium ear blight (Fusarium graninearum), caused an increase in proteins involved in carbohydrate metabolism (15). The use of proteomic analysis of barley seeds has been proposed to link protein abundance to grain quality and germination efficiency (16,17). These previous proteomic analyses, along with proteome studies on beer brewing, largely relied on 2D SDS-PAGE technologies (16)(17)(18).
Several proteomics studies have identified barley proteins throughout the brewing process and in the finished beer (18)(19)(20)(21)(22)(23)(24) (22,25,26), highlighting that barley proteins are important contributors to the process of beer production, and suggesting that variability in the barley seed proteome will impact beer production process efficiency and quality.
In this study, we used sequential window acquisition of all theoretical ions mass spectrometry were tested with diseased (artificially inoculated and not treated with fungicide) and nondiseased (treated with fungicide) treatments in triplicate. Exact trial information is shown in Table 1. Harvested seeds from all three trials were stored at 12 °C, milled to 0.8 mm, and stored in Falcon tubes. Preparation of milled grain for proteomics Proteins in milled samples were extracted, denatured, and reduced/alkylated essentially as described (27). 10

SWATH-MS
Peptides were desalted with C18 ZipTips (Millipore) and measured by LC-ESI-MS/MS using a Prominence nanoLC system (Shimadzu) and TripleTof 5600 instrument with a Nanospray III interface (SCIEX) as previously described (28). Approximately 1 µg or 0.2 µg desalted peptides, as estimated by ZipTip binding capacity, were injected for data dependent acquisition (DDA) or data independent acquisition (DIA), respectively. LC parameters were identical for DDA and DIA, and MS parameters were set as previously described (29).

Data analysis
Peptides and proteins were identified using ProteinPilot 5.

Results
We aimed to investigate how growth environment, pathogen burden, and barley variety affect  (Table 1). As barley at each location was infected with a single disease, location and disease were not separable variables in this study design. Six varieties of barley with varied intrinsic disease resistance were grown at each location (Table S2).
Importantly, barley plants were infected in their leaves and stems -the natural sites of infection; and we studied the proteome of the barley seed -the industrially relevant tissue.

Disease burden results in diverse proteomic responses
Proteins from milled barley seeds were extracted, denatured, reduced/alkylated, precipitated, digested by trypsin, and identified by DDA LC-MS/MS. A total of 168 unique proteins were identified across all samples, including 32 defence or biological response proteins, 12 nutrient reservoir proteins, and 17 amylase/protease inhibitor proteins, with the majority of the remainder being housekeeping or metabolic proteins (Table S3). We then used SWATH-MS to measure the relative abundance of each protein within each sample. We initially used PCA to provide an overview of the proteomic variability in the entire 106 sample set (Fig. 1).
This analysis suggested that growth environment was an important factor controlling the proteome of barley seeds, as partial clustering was visible based on location ( Fig. 1A and B).
No obvious further clustering was apparent within locations when samples were partitioned by pathogen burden (Fig. 1C and 1D). accounted for 12.53% of the total variance, the second 9.02%, and the third an additional 6.78%.
To investigate the effect of pathogen burden on the barley seed proteome we directly compared the proteomes of diseased and non-diseased samples independently for each location/disease (Table S4). This analysis revealed that disease burden significantly affected the abundance of several proteins across the three diseases/locations (Fig. 2). However, no protein was significantly different after infection with all three pathogens ( Fig. 2B and 2C).

Intrinsic disease resistance affects the barley seed proteome
Barley varieties are bred to have specific disease resistance profiles; new varieties are bred and introduced when diseases evolve or become able to infect existing varieties. It is possible that increased disease resistance comes at the cost of productivity or seed quality. We therefore tested if there were differences in the intrinsic proteomes of moderately resistant and susceptible varieties of barley. We independently compared the barley seed proteomes of varieties of barley that were resistant or susceptible to each of the three diseases. Resistance or susceptibility was defined as classified by field trial observations using the GRDC (2016) standard disease resistance rating system (Table S2). We identified a suite of proteins that were significantly different in abundance between moderately resistant and susceptible varieties ( Fig. 3 and Table S5). No protein was significantly more abundant in either moderately resistant or susceptible varieties across the three diseases (Fig. 3). However, varieties that were moderately resistant to net form of net blotch showed an overlapping proteomic profile with varieties that were moderately resistant to spot form of net blotch (Fig.   3). In both of these sets of varieties, five proteins were significantly higher in moderately

Malt quality correlates with specific features of the barley seed proteome
For barley to be used in the brewing process as malt and hence attract a premium price, specific quality measures need to be achieved. To be accredited, a barley variety must be high yielding, adequately disease resistant, and generally perform well in a brewing process. Feed barley, on the other hand, is any variety of barley that has not achieved malt accreditation, and is used for feed for cattle and other livestock. Grain from a malt-accredited variety that is affected by high levels of disease may also be downgraded to feed quality.
We compared the proteomes of barley seeds that had been classified as malt varieties or as feed varieties. Only non-diseased samples were included in this analysis, to remove variability associated with pathogen burden. This analysis showed that 36 proteins were significantly different in abundance between malt and feed varieties ( Fig. 4A and Table S6).

Discussion
Fungal infection and pathogen burden in the leaves and stem of barley resulted in changes to the barley seed proteome ( Fig. 1 and 2). This suggests that these plants responded systemically to infection, and that fungal infections in the leaves or stem can indeed affect the proteome of the seed. However, in general the changes we observed in the presence of fungal disease were minor and showed considerable variation between barley infected with different pathogens.
The innate resistance status of the barley varieties had only a small effect on the seed proteome (Fig. 3, Table S5). This limited effect of intrinsic disease resistance on the barley seed proteome is consistent with the main mediators of disease resistance being present in the leaves and stems of the plant (35).s That is, disease resistance is likely improved through breeding via altered leaf and stem proteomes, with only subtle changes in the seed. This suggests that breeding for barley disease resistance can be largely independent of seed quality, at least in terms of the proteome. This is valuable information for breeders who can pursue improved disease resistance with confidence that it is unlikely to affect grain quality.
Varieties of barley accredited for use in malting had higher levels of proteins associated with starch synthesis and beer quality (36)(37)(38). β -amylase, non-specific lipid-transfer proteins, and sucrose synthase proteins were all significantly more abundant in malt than feed varieties ( Fig. 4 and Table S6). β -amylase (AMYB) is involved in the hydrolysis of starch into fermentable sugars (39)(40)(41). High levels of β -amylase would therefore increase the efficiency of starch degradation during mashing in beer production. Sucrose synthase 1 (SUS1) and sucrose synthase 2 (SUS2) catalyse the conversion of sucrose with nucleotide activated glucose and fructose, and are key regulatory enzymes in the process of starch synthesis (42,43). Increased sucrose synthase abundance in malting barley is consistent with selection for high starch content and starch structure more suited to hydrolysis during the malting and brewing process (44). To our knowledge, this is the first time that proteomic differences have been identified between barley varieties accredited for use in feed or malting. The differences we detected suggest that similar proteomic profiling approaches may be a useful tool in accreditation of malting varieties and in improving the efficiency of variety selection in barley breeding.
PCA revealed that trial location was amongst the largest contributors to the variance in the barley seed proteome. Each geographical condition had many independent variables that could influence barley growth and quality, including soil type and nutrition, level of direct sunlight, temperature, and soil water content (45,46). Because of the high level of variability, disentangling the individual contributors to proteomic variation was not possible. In addition, in the experimental design used for the field trial under study, the effects of geographic location could not be separated from fungal disease. Targeted field trial design or use of a more controlled greenhouse setting would allow more detailed investigation of the role of environmental variables in affecting the barley seed proteome.

Conclusion
Our data provide a detailed molecular insight into the complexity and diversity of the barley