Sewage Protein Information Mining: Discovery of Large Biomolecules as Biomarkers of Population and Industrial Activities.

Wastewater-based epidemiology has been revealed as a powerful approach for surveying the health and lifestyle of a population. In this context, proteins have been proposed as potential biomarkers that complement the information provided by currently available methods. However, little is known about the range of molecular species and dynamics of proteins in wastewater and the information hidden in these protein profiles is still to be uncovered. In this study, we investigated the protein composition of wastewater from 10 municipalities in Catalonia with diverse populations and industrial activities at three different times of the year. The soluble fraction of this material was analyzed using liquid chromatography high-resolution tandem mass spectrometry using a shotgun proteomics approach. The complete proteomic profile, distribution among different organisms, and semiquantitative analysis of the main constituents are described. Excreta (urine and feces) from humans, and blood and other residues from livestock were identified as the two main protein sources. Our findings provide new insights into the characterization of wastewater proteomics that allow for the proposal of specific bioindicators for wastewater-based environmental monitoring. This includes human and animal population monitoring, most notably for rodent pest control (immunoglobulins (Igs) and amylases) and livestock processing industry monitoring (albumins).

Proteomics Goes to Court: A Statistical Foundation for Forensic Toxin/Organism Identification Using Bottom-Up Proteomics.

Bottom-up proteomics is increasingly being used to characterize unknown environmental, clinical, and forensic samples. Proteomics-based bacterial identification typically proceeds by tabulating peptide "hits" (i.e., confidently identified peptides) associated with the organisms in a database; those organisms with enough hits are declared present in the sample. This approach has proven to be successful in laboratory studies; however, important research gaps remain. First, the common-practice reliance on unique peptides for identification is susceptible to a phenomenon known as signal erosion. Second, no general guidelines are available for determining how many hits are needed to make a confident identification. These gaps inhibit the transition of this approach to real-world forensic samples where conditions vary and large databases may be needed. In this work, we propose statistical criteria that overcome the problem of signal erosion and can be applied regardless of the sample quality or data analysis pipeline. These criteria are straightforward, producing a p-value on the result of an organism or toxin identification. We test the proposed criteria on 919 LC-MS/MS data sets originating from 2 toxins and 32 bacterial strains acquired using multiple data collection platforms. Results reveal a > 95% correct species-level identification rate, demonstrating the effectiveness and robustness of proteomics-based organism/toxin identification.

Differences in protein expression among five species of stream stonefly (Plecoptera) along a latitudinal gradient in Japan.

Proteome variation among natural populations along an environmental gradient may provide insights into how the biological functions of species are related to their local adaptation. We investigated protein expression in five stream stonefly species from four geographic regions along a latitudinal gradient in Japan with varying climatic conditions. The extracted proteins were separated by two-dimensional gel electrophoresis and identified by matrix-assisted laser desorption/ionization of time-of-flight (MALDI TOF/TOF), yielding 446 proteins. Low interspecies variation in the proteome profiles was observed among five species within geographical regions, presumably due to the co-occurring species sharing the environments. However, large spatial variations in protein expression were found among four geographic regions, suggesting strong regulation of protein expression in heterogeneous environments, where the spatial variations were positively correlated with water temperature. We identified 21 unique proteins expressed specifically in a geographical region and six common proteins expressed throughout all regions. In warmer regions, metabolic proteins were upregulated, whereas proteins related to cold stress, the photoperiod, and mating were downregulated. Oxygen-related and energy-production proteins were upregulated in colder regions with higher altitudes. Thus, our proteomic approach is useful for identifying and understanding important biological functions related to local adaptations by populations of stoneflies.

Exploring the Plant-Microbe Interface by Profiling the Surface-Associated Proteins of Barley Grains.

Cereal grains are colonized by a microbial community that actively interacts with the plant via secretion of various enzymes, hormones, and metabolites. Microorganisms decompose plant tissues by a collection of depolymerizing enzymes, including ß-1,4-xylanases, that are in turn inhibited by plant xylanase inhibitors. To gain insight into the importance of the microbial consortia and their interaction with barley grains, we used a combined gel-based (2-DE coupled to MALDI-TOF-TOF MS) and gel-free (LC-MS/MS) proteomics approach complemented with enzyme activity assays to profile the surface-associated proteins and xylanolytic activities of two barley cultivars. The surface-associated proteome was dominated by plant proteins with roles in defense and stress-responses, while the relatively less abundant microbial (bacterial and fungal) proteins were involved in cell-wall and polysaccharide degradation and included xylanases. The surface-associated proteomes showed elevated xylanolytic activity and contained several xylanases. Integration of proteomics with enzyme assays is a powerful tool for analysis and characterization of the interaction between microbial consortia and plants in their natural environment.

Quantitative analysis of oyster larval proteome provides new insights into the effects of multiple climate change stressors.

The metamorphosis of planktonic larvae of the Pacific oyster (Crassostrea gigas) underpins their complex life-history strategy by switching on the molecular machinery required for sessile life and building calcite shells. Metamorphosis becomes a survival bottleneck, which will be pressured by different anthropogenically induced climate change-related variables. Therefore, it is important to understand how metamorphosing larvae interact with emerging climate change stressors. To predict how larvae might be affected in a future ocean, we examined changes in the proteome of metamorphosing larvae under multiple stressors: decreased pH (pH 7.4), increased temperature (30 °C), and reduced salinity (15 psu). Quantitative protein expression profiling using iTRAQ-LC-MS/MS identified more than 1300 proteins. Decreased pH had a negative effect on metamorphosis by down-regulating several proteins involved in energy production, metabolism, and protein synthesis. However, warming switched on these down-regulated pathways at pH 7.4. Under multiple stressors, cell signaling, energy production, growth, and developmental pathways were up-regulated, although metamorphosis was still reduced. Despite the lack of lethal effects, significant physiological responses to both individual and interacting climate change related stressors were observed at proteome level. The metamorphosing larvae of the C. gigas population in the Yellow Sea appear to have adequate phenotypic plasticity at the proteome level to survive in future coastal oceans, but with developmental and physiological costs.

The MetaProteomeAnalyzer: a powerful open-source software suite for metaproteomics data analysis and interpretation.

The enormous challenges of mass spectrometry-based metaproteomics are primarily related to the analysis and interpretation of the acquired data. This includes reliable identification of mass spectra and the meaningful integration of taxonomic and functional meta-information from samples containing hundreds of unknown species. To ease these difficulties, we developed a dedicated software suite, the MetaProteomeAnalyzer, an intuitive open-source tool for metaproteomics data analysis and interpretation, which includes multiple search engines and the feature to decrease data redundancy by grouping protein hits to so-called meta-proteins. We also designed a graph database back-end for the MetaProteomeAnalyzer to allow seamless analysis of results. The functionality of the MetaProteomeAnalyzer is demonstrated using a sample of a microbial community taken from a biogas plant.

Differential proteomic responses of selectively bred and wild-type Sydney rock oyster populations exposed to elevated CO2.

Previous work suggests that larvae from Sydney rock oysters that have been selectively bred for fast growth and disease resistance are more resilient to the impacts of ocean acidification than nonselected, wild-type oysters. In this study, we used proteomics to investigate the molecular differences between oyster populations in adult Sydney rock oysters and to identify whether these form the basis for observations seen in larvae. Adult oysters from a selective breeding line (B2) and nonselected wild types (WT) were exposed for 4 weeks to elevated pCO2 (856 µatm) before their proteomes were compared to those of oysters held under ambient conditions (375 µatm pCO2 ). Exposure to elevated pCO2 resulted in substantial changes in the proteomes of oysters from both the selectively bred and wild-type populations. When biological functions were assigned, these differential proteins fell into five broad, potentially interrelated categories of subcellular functions, in both oyster populations. These functional categories were energy production, cellular stress responses, the cytoskeleton, protein synthesis and cell signalling. In the wild-type population, proteins were predominantly upregulated. However, unexpectedly, these cellular systems were downregulated in the selectively bred oyster population, indicating cellular dysfunction. We argue that this reflects a trade-off, whereby an adaptive capacity for enhanced mitochondrial energy production in the selectively bred population may help to protect larvae from the effects of elevated CO2 , whilst being deleterious to adult oysters.

Proteomic responses to environmentally induced oxidative stress.

Environmental (acute and chronic temperature, osmotic, hypoxic and pH) stress challenges the cellular redox balance and can lead to the increased production of reactive oxygen species (ROS). This review provides an overview of the reactions producing and scavenging ROS in the mitochondria, endoplasmic reticulum (ER) and peroxisome. It then compares these reactions with the findings of a number of studies investigating the proteomic responses of marine organisms to environmentally induced oxidative stress. These responses indicate that the thioredoxin-peroxiredoxin system is possibly more frequently recruited to scavenge H2O2 than the glutathione system. Isoforms of superoxide dismutase (SOD) are not ubiquitously induced in parallel, suggesting that SOD scavenging activity is sometimes sufficient. The glutathione system plays an important role in some organisms and probably also contributes to protecting protein thiols during environmental stress. Synthesis pathways of cysteine and selenocysteine, building blocks for glutathione and glutathione peroxidase, also play an important role in scavenging ROS during stress. The increased abundance of glutaredoxin and DyP-type peroxidase suggests a need for regulating the deglutathionylation of proteins and scavenging of peroxynitrite. Reducing equivalents for these scavenging reactions are generated by proteins of the pentose phosphate pathway and by NADP-dependent isocitrate dehydrogenase. Furthermore, proteins representing reactions of the tricarboxylic acid cycle and the electron transport system generating NADH and ROS, including those of complex I, II and III, are frequently reduced in abundance with stress. Protein maturation in the ER likely represents another source of ROS during environmental stress, as indicated by simultaneous changes in ER chaperones and antioxidant proteins. Although there are still too few proteomic analyses of non-model organisms exposed to environmental stress for a general pattern to emerge, hyposaline and low pH stress show different responses from temperature and hypoxic stress. Furthermore, comparisons of closely related congeners differing in stress tolerance start to provide insights into biochemical processes contributing to adaptive differences, but more of these comparisons are needed to draw general conclusions. To fully take advantage of a systems approach, studies with longer time courses, including several tissues and more species comparisons are needed.

Reprint of "Which metaproteome? The impact of protein extraction bias on metaproteomic analyses".

Culture-independent techniques such as LC-MS/MS-based metaproteomic analyses are being increasingly utilized for the study of microbial composition and function in complex environmental samples. Although several studies have documented the many challenges and sources of bias that must be considered in these types of analyses, none have systematically characterized the effect of protein extraction bias on the biological interpretation of true environmental biofilm metaproteomes. In this study, we compared three protein extraction methods commonly used in the analyses of environmental samples [guanidine hydrochloride (GuHCl), B-PER, sequential citrate-phenol (SCP)] using nano-LC-MS/MS and an environmental marine biofilm to determine the unique biases introduced by each method and their effect on the interpretation of the derived metaproteomes. While the protein extraction efficiencies of the three methods ranged from 2.0 to 4.3%, there was little overlap in the sequence (1.9%), function (8.3% of total assigned protein families) and origin of the identified proteins from each extract. Each extraction method enriched for different protein families (GuHCl--photosynthesis, carbohydrate metabolism; B-PER--membrane transport, oxidative stress; SCP--calcium binding, structural) while 23.7-45.4% of the identified proteins lacked SwissProt annotations. Taken together, the results demonstrated that even the most basic interpretations of this complex microbial assemblage (species composition, ratio of prokaryotic to eukaryotic proteins, predominant functions) varied with little overlap based on the protein extraction method employed. These findings demonstrate the heavy influence of protein extraction on biofilm metaproteomics and provide caveats for the interpretation of such data sets when utilizing single protein extraction methods for the description of complex microbial assemblages.

Data visualization in environmental proteomics.

From raw data to gene expression profiles, from single cultures to complex microbial communities, environmental proteomics works with data of different complexity levels that need to be interpreted in detail or in its entirety. Although data visualization is closely connected with data analysis approaches, this work will solely focus on data visualization. Complementing traditional tools such as bar charts or line graphs, scientists and visualization professionals have been provided sophisticated visualization tools. Many rules and concerns regarding the display of single but also complex data will be reviewed and discussed. Visual approaches such as microcharts, heat maps, stream graphs, and tree maps will be brought to the reader's attention and demonstrated by utilizing real data sets.

Environmental proteomics reveals early microbial community responses to biostimulation at a uranium- and nitrate-contaminated site.

High-performance MS instrumentation coupled with improved protein extraction techniques enables metaproteomics to identify active members of soil and groundwater microbial communities. Metaproteomics workflows were applied to study the initial responses (i.e. 4 days post treatment) of the indigenous aquifer microbiota to biostimulation with emulsified vegetable oil (EVO) at a uranium-contaminated site. Members of the Betaproteobacteria (i.e. Dechloromonas, Ralstonia, Rhodoferax, Polaromonas, Delftia, Chromobacterium) and the Firmicutes dominated the biostimulated aquifer community. Proteome characterization revealed distinct differences between the microbial biomass collected from groundwater influenced by biostimulation and groundwater collected upgradient of the EVO injection points. In particular, proteins involved in ammonium assimilation, EVO degradation, and polyhydroxybutyrate granule formation were prominent following biostimulation. Interestingly, the atypical NosZ of Dechloromonas spp. was highly abundant, suggesting active nitrous oxide (N2 O) respiration. c-Type cytochromes were barely detected, as was citrate synthase, a biomarker for hexavalent uranium reduction activity, suggesting that uranium reduction has not commenced 4 days post EVO amendment. Environmental metaproteomics identified microbial community responses to biostimulation and elucidated active pathways demonstrating the value of this technique as a monitoring tool and for complementing nucleic acid-based approaches.

Amino acid treatment enhances protein recovery from sediment and soils for metaproteomic studies.

Characterization of microbial protein expression provides information necessary to better understand the unique biological pathways that occur within soil microbial communities that contribute to atmospheric CO2 levels and the earth's changing climate. A significant challenge in studying the soil microbial community proteome is the initial dissociation of bacterial proteins from the complex mixture of particles found in natural soil. The differential extraction of intact bacterial cells limits the characterization of the complete representation of a microbial community. However, in situ lysis of bacterial cells in soil can lead to potentially high levels of protein adsorption to soil particles. Here, we investigated various amino acids for their ability to block soil protein adsorption sites prior to in situ lysis of bacterial cells, as well as their compatibility with both tryptic digestion and mass spectrometric analysis. The treatments were tested by adding proteins from lysed Escherichia coli cells to representative treated and untreated soil samples. The results show that it is possible to significantly increase protein identifications through blockage of binding sites on a variety of soil and sediment textures; use of an optimized desorption buffer further increases the number of identifications.

Proteomic response of marine invertebrate larvae to ocean acidification and hypoxia during metamorphosis and calcification.

Calcifying marine invertebrates with complex life cycles are particularly at risk to climate changes as they undergo an abrupt ontogenetic shift during larval metamorphosis. Although our understanding of the larval response to climate changes is rapidly advancing, the proteome plasticity involved in a compensatory response to climate change is still unknown. In this study, we investigated the proteomic response of metamorphosing larvae of the tubeworm Hydroides elegans, challenged with two climate change stressors, ocean acidification (OA; pH 7.6) and hypoxia (HYP; 2.8 mg O2 l(-1)), and with both combined. Using a two-dimensional gel electrophoresis (2-DE)-based approach coupled with mass spectrometry, we found that climate change stressors did not affect metamorphosis except under OA, but altered the larval proteome and phosphorylation status. Metabolism and various stress and calcification-related proteins were downregulated in response to OA. In OA and HYP combined, HYP restored the expression of the calcification-related proteins to the control levels. We speculate that mild HYP stress could compensate for the negative effects of OA. This study also discusses the potential functions of selected proteins that might play important roles in larval acclimation and adaption to climate change.

Which metaproteome? The impact of protein extraction bias on metaproteomic analyses.

Culture-independent techniques such as LC-MS/MS-based metaproteomic analyses are being increasingly utilized for the study of microbial composition and function in complex environmental samples. Although several studies have documented the many challenges and sources of bias that must be considered in these types of analyses, none have systematically characterized the effect of protein extraction bias on the biological interpretation of true environmental biofilm metaproteomes. In this study, we compared three protein extraction methods commonly used in the analyses of environmental samples [guanidine hydrochloride (GuHCl), B-PER, sequential citrate-phenol (SCP)] using nano-LC-MS/MS and an environmental marine biofilm to determine the unique biases introduced by each method and their effect on the interpretation of the derived metaproteomes. While the protein extraction efficiencies of the three methods ranged from 2.0 to 4.3%, there was little overlap in the sequence (1.9%), function (8.3% of total assigned protein families) and origin of the identified proteins from each extract. Each extraction method enriched for different protein families (GuHCl - photosynthesis, carbohydrate metabolism; B-PER - membrane transport, oxidative stress; SCP - calcium binding, structural) while 23.7-45.4% of the identified proteins lacked SwissProt annotations. Taken together, the results demonstrated that even the most basic interpretations of this complex microbial assemblage (species composition, ratio of prokaryotic to eukaryotic proteins, predominant functions) varied with little overlap based on the protein extraction method employed. These findings demonstrate the heavy influence of protein extraction on biofilm metaproteomics and provide caveats for the interpretation of such data sets when utilizing single protein extraction methods for the description of complex microbial assemblages.

PepMANDIS: A Peptide Selection Tool for Designing Function-Based Targeted Proteomic Assays in Complex Microbial Systems.

The majority of studies focusing on microbial functioning in various environments are based on DNA or RNA sequencing techniques that have inherent limitations and usually provide a distorted picture about the functional status of the studied system. Untargeted proteomics is better suited for that purpose, but it suffers from low efficiency when applied in complex consortia. In practice, the scanning capabilities of the currently employed LC-MS/MS systems provide limited coverage of key-acting proteins, hardly allowing a semiquantitative assessment of the most abundant ones from most prevalent species. When particular biological processes of high importance are under investigation, the analysis of specific proteins using targeted proteomics is a more appropriate strategy as it offers superior sensitivity and comes with the added benefits of increased throughput, dynamic range and selectivity. However, the development of targeted assays requires a priori knowledge regarding the optimal peptides to be screened for each protein of interest. In complex, multi-species systems, a specific biochemical process may be driven by a large number of homologous proteins having considerable differences in their amino acid sequence, complicating LC-MS/MS detection. To overcome the complexity of such systems, we have developed an automated pipeline that interrogates UniProt database or user-created protein datasets (e.g. from metagenomic studies) to gather homolog proteins with a defined functional role and extract respective peptide sequences, while it computes several protein/peptide properties and relevant statistics to deduce a small list of the most representative, process-specific and LC-MS/MS-amenable peptides for the microbial enzymatic activity of interest.

In-depth analysis of exoproteomes from marine bacteria by shotgun liquid chromatography-tandem mass spectrometry: the Ruegeria pomeroyi DSS-3 case-study.

Microorganisms secrete into their extracellular environment numerous compounds that are required for their survival. Many of these compounds could be of great interest for biotechnology applications and their genes used in synthetic biology design. The secreted proteins and the components of the translocation systems themselves can be scrutinized in-depth by the most recent proteomic tools. While the secretomes of pathogens are well-documented, those of non-pathogens remain largely to be established. Here, we present the analysis of the exoproteome from the marine bacterium Ruegeria pomeroyi DSS-3 grown in standard laboratory conditions. We used a shotgun approach consisting of trypsin digestion of the exoproteome, and identification of the resulting peptides by liquid chromatography coupled to tandem mass spectrometry. Three different proteins that have domains homologous to those observed in RTX toxins were uncovered and were semi-quantified as the most abundantly secreted proteins. One of these proteins clearly stands out from the catalogue, representing over half of the total exoproteome. We also listed many soluble proteins related to ABC and TRAP transporters implied in the uptake of nutrients. The Ruegeria pomeroyi DSS-3 case-study illustrates the power of the shotgun nano-LC-MS/MS strategy to decipher the exoproteome from marine bacteria and to contribute to environmental proteomics.

Can proteomics contribute to biomonitoring of aquatic pollution? A critical review.

Aquatic pollution is one of the greatest environmental problems, and therefore its control represents one of the major challenges in this century. In recent years, proteomics has emerged as a powerful tool for searching protein biomarkers in the field of pollution biomonitoring. For biomonitoring marine contamination, there is a consensus that bivalves are preferred organisms to assess organic and inorganic pollutants. Thus, the bivalve proteome was intensively studied, particularly the mussel. It is well documented that heavy metal pollution and organic chemicals altered the structural proteins causing degradation of tissues of molluscs. Also, it is well known that proteins involved in stress oxidative such as glutathione and enzymes as catalase, superoxide dismutase or peroxisomes are overexpressed in response to contaminants. Additionally, using bivalves, other groups of proteins proposed as pollution biomarkers are the metabolic proteins. Even though other marine species are used to monitor the pollution, the presence of proteomic tools in these studies is scarce. Concerning freshwater pollution field, a great variety of animal species (fish and crustaceans) are used as biomonitors in proteomics studies compared to plants that are scarcely analysed. In fish species, proteins involved in stress oxidative such as heat shock family or proteins from lipid and carbohydrate metabolism were proposed as candidate biomarkers. On the contrary, for crustaceans there is a lack of proteomic studies individually assessing the contaminants. Novel scenarios, including emerging contaminants and new threats, will require proteomic technology for a systematic search of protein biomarkers and a greater knowledge at molecular level of those cellular pathways induced by contamination.

Assessment of fipronil toxicity to the freshwater midge Chironomus riparius: Molecular, biochemical, and organismal responses.

Fipronil is a phenylpyrazole insecticide that entered the market to replace organochlorides and organophosphates. Fipronil impairs the regular inhibition of nerve impulses that ultimately result in paralysis and death of insects. Because of its use as a pest control, and due to runoff events, fipronil has been detected in freshwater systems near agricultural areas, and therefore might represent a threat to non-target aquatic organisms. In this study, the toxicity of fipronil to the freshwater midge Chironomus riparius was investigated at biochemical, molecular, and whole organism (e.g. growth, emergence, and behavior) levels. At the individual level, chronic (28 days) exposure to fipronil resulted in reduced larval growth and emergence with a lowest observed effect concentration (LOEC) of 0.081 µg L-1. Adult weight, which is directly linked to the flying performance and fecundity of midges, was also affected (LOEC = 0.040 µg L-1). Additionally, behavioral changes such as irregular burrowing behavior of C. riparius larvae (EC50 = 0.084 µg L-1) and impairment of adult flying performance were observed. At a biochemical level, acute (48 h) exposure to fipronil increased cellular oxygen consumption (as indicated by the increase of electron transport system (ETS) activity) and decreased antioxidant and detoxification defenses (as suggested by the decrease in catalase (CAT) and glutathione S-transferase (GST) activities). Exposure to fipronil also caused alterations in the fatty acid profile of C. riparius, since high levels of stearidonic acid (SDA) were observed. A comparison between exposed and non-exposed larvae also revealed alterations in the expression of globins, cytoskeleton and motor proteins, and proteins involved in protein biosynthesis. These alterations may aid in the interpretation of potential mechanisms of action that lead to the effects observed at the organism level. Present results show that environmentally relevant concentrations of fipronil are toxic to chironomid populations which call for monitoring of phenylpyrazole insecticides and of their ecological effects in freshwaters. Present results also emphasize the importance of complementing ecotoxicological data with molecular approaches such as proteomics, for a better interpretation of the mode of action of insecticides in aquatic invertebrates.

A Robust and Universal Metaproteomics Workflow for Research Studies and Routine Diagnostics Within 24 h Using Phenol Extraction, FASP Digest, and the MetaProteomeAnalyzer.

The investigation of microbial proteins by mass spectrometry (metaproteomics) is a key technology for simultaneously assessing the taxonomic composition and the functionality of microbial communities in medical, environmental, and biotechnological applications. We present an improved metaproteomics workflow using an updated sample preparation and a new version of the MetaProteomeAnalyzer software for data analysis. High resolution by multidimensional separation (GeLC, MudPIT) was sacrificed to aim at fast analysis of a broad range of different samples in less than 24 h. The improved workflow generated at least two times as many protein identifications than our previous workflow, and a drastic increase of taxonomic and functional annotations. Improvements of all aspects of the workflow, particularly the speed, are first steps toward potential routine clinical diagnostics (i.e., fecal samples) and analysis of technical and environmental samples. The MetaProteomeAnalyzer is provided to the scientific community as a central remote server solution at www.mpa.ovgu.de.

Investigation of the indigenous fungal community populating barley grains: Secretomes and xylanolytic potential.

The indigenous fungal species populating cereal grains produce numerous plant cell wall-degrading enzymes including xylanases, which could play important role in plant-pathogen interactions and in adaptation of the fungi to varying carbon sources. To gain more insight into the grain surface-associated enzyme activity, members of the populating fungal community were isolated, and their secretomes and xylanolytic activities assessed. Twenty-seven different fungal species were isolated from grains of six barley cultivars over different harvest years and growing sites. The isolated fungi were grown on medium containing barley flour or wheat arabinoxylan as sole carbon source. Their secretomes and xylanase activities were analyzed using SDS-PAGE and enzyme assays and were found to vary according to species and carbon source. Secretomes were dominated by cell wall degrading enzymes with xylanases and xylanolytic enzymes being the most abundant. A 2-DE-based secretome analysis of Aspergillus niger and the less-studied pathogenic fungus Fusarium poae grown on barley flour and wheat arabinoxylan resulted in identification of 82 A. niger and 31 F. poae proteins many of which were hydrolytic enzymes, including xylanases. BIOLOGICAL SIGNIFICANCE: The microorganisms that inhabit the surface of cereal grains are specialized in production of enzymes such as xylanases, which depolymerize plant cell walls. Integration of gel-based proteomics approach with activity assays is a powerful tool for analysis and characterization of fungal secretomes and xylanolytic activities which can lead to identification of new enzymes with interesting properties, as well as provide insight into plant-fungal interactions, fungal pathogenicity and adaptation. Understanding the fungal response to host niche is of importance to uncover novel targets for potential symbionts, anti-fungal agents and biotechnical applications.