Complementary protein extraction methods increase the identification of the Park Grass Experiment metaproteome

Quinn, Gerry A.; Abdelhameed, Alyaa; Banat, İbrahim M.; Berrar, Daniel; Doerr, Stefan H.; Dudley, Ed; Francis, Lewis; Gazzè, Salvatore A.; Hallin, Ingrid; Matthews, G. Peter; Swain, Martin; Whalley, W. R.; Keulen, Geertje van

doi:10.1016/j.apsoil.2022.104388

Cited by 3 publications

(3 citation statements)

References 20 publications

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“…Peptides were most frequently assigned to the phylum Proteobacteria and this was in agreement with other soil metaproteomic studies, including both those targeting extracellular proteins (Bastida et al, 2018; Johnson‐Rollings et al, 2014) and those encompassing cell lysis steps (Keiblinger et al, 2012; Mattarozzi et al, 2017; Quinn et al, 2022; Thorn et al, 2019). Although Gram‐negative bacteria, may be regarded to be more susceptible to mechanical lysing conditions, due to their typically thinner peptidoglycan layer, Proteobacteria were found to exhibit population stability to soil drying and rewetting stress similarly to, for example, Firmicutes (Barnard et al, 2013).…”

Section: Discussionsupporting

confidence: 86%

“…Despite this, NaDoc‐TCA is regarded as a standard biochemistry preparation to precipitate proteins from dilute solutions (Bensadoun & Weinstein, 1976), and TCA precipitation is commonly applied to soil protein extracts (Keiblinger et al, 2016), even though it was also observed to co‐precipitate other soil organic substances (Qian & Hettich, 2017). Workflows using phenol/chloroform‐isoamyl alcohol and phenol phase content precipitation with ammonium acetate in methanol have led to higher number of peptide hits with LC–MS/MS (Keiblinger et al, 2012; Quinn et al, 2022; Thorn et al, 2019), perhaps due to their ability to reduce total soil organic substances, which is important for LC–MS/MS, as discussed later. This cleaning method, however, has been argued to lead to protein composition bias (Keiblinger et al, 2016; Qian & Hettich, 2017).…”

Section: Discussionmentioning

confidence: 99%

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Assessing the impact of interfering organic matter on soil metaproteomic workflow

Waibel

McDonnell

Tuohy

et al. 2023

European J Soil Science

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Soil organic matter (SOM) is biologically, chemically, and physically complex. As a major store of nutrients within the soil, it plays an important role in nutrient provision to plants. An enhanced understanding of SOM utilisation processes could underpin better fertiliser management for plant growth, with reduced environmental losses. Metaproteomics can allow the characterisation of protein profiles and could help gain insights into SOM microbial decomposition mechanisms. Here, we applied three different extraction methods to two soil types to recover SOM with different characteristics. Specifically, water‐extractable organic matter, mineral‐associated organic matter and protein‐bound organic matter were targeted with the aim to investigate the metaproteome enriched in those extractions. As a proof‐of‐concept, replicated extracts from one soil were further analysed for peptide identification using liquid chromatography followed by tandem mass spectrometry. We employed a framework for mining mass spectra for both peptide assignment and fragmentation pattern characterisation. Different extracts were found to exhibit contrasting total protein and humic substance content for the two soils investigated. Overall, water extracts displayed the lowest humic substance content (in both soils) and the highest number of peptide identifications (in the soil investigated) with the most frequent peptide hits associated with diverse substrate/ligand binding proteins of Proteobacteria and derived taxa. Our framework also highlighted a strong peptidic signal in unassigned and unmatched spectra, information that is currently not captured by the pipelines employed in this study. Taken together, this work points to specific areas for optimisation in chromatography and mass spectrometry to adequately characterise SOM‐associated metaproteomes.

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Section: Discussionsupporting

confidence: 86%

Section: Discussionmentioning

confidence: 99%

Assessing the impact of interfering organic matter on soil metaproteomic workflow

Waibel

McDonnell

Tuohy

et al. 2023

European J Soil Science

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“…could be a contributing factor to how well each extraction method performed. The use of surfactant-based extractions which do not remove humic acid substances has previously been shown to provide adequate protein extraction and can be used for a variety of soils, but arid soils with less protein content naturally contain less humic acid substances as supported by the experimental soil properties 27 . Phenol extraction has also been shown to produce a similar number of protein identifications as shown here, although within a related study a more laborious protein extraction (FASP) was used rather than the S-Trap™ protocol used here 28 .…”

Section: Protein Identifications and Replicate Reproducibilitymentioning

confidence: 99%

Comparison of Protein Extraction Methods and Data Analysis Strategies for Complete Metaproteomic Soil Analysis

Mikolitis,

Mach,

Kroeger

et al. 2024

Preprint

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Considerable microbial diversity has been discovered in soil through genomic sequencing. Despite its role in biogeochemical cycling, relatively little is known about the proteomic diversity of the soil microbiome as most commercially available soil kits focus on DNA/RNA extractions. Consequently, a plethora of protein extraction techniques have been developed for soil but have yet to be integrated into simplified, modern sample preparation techniques such as the S-Trap™. Furthermore, classical data analysis strategies for soil metaproteomics rely on genomically-informed databases for peptide/protein identification. This assumes that DNA/RNA extracts adequately represent the soil proteome. Within this study, we systematically assess several extraction techniques, developing a data processing pipeline which is driven by both proteomics and genomics to fully characterize the soil microbiome. Both pipelines reveal remarkably complementary data, with ∼60% of the protein identifications coming from Proteomically-derived databases. Sodium dodecyl sulfate-based extractions proved to provide the most unique protein identifications (∼3000 proteins), and by combining both proteomic and genomic-based results, the total protein identifications increased approximately 2-fold for each extraction. Combining these complementary data pipelines with improved extraction techniques can allow for drastically improved proteomic results (12,307 unique protein identifications), even from minute (50 mg) sample volumes. These enhancements to previous workflows can better describe the microbial diversity within soil and provide a deeper functional understanding of the soil microbiome.

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Identification of Cultured and Diazotrophic Bacterial Endophytes in Warm-Season Grasses

Sapkota¹,

Harris‐Shultz²,

Strickland

et al. 2023

PhytoFrontiers™

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Endophytes can have positive effects on plant health and growth, but endophytes of warm-season grasses are largely understudied and inocula are rarely applied to cultivated grasses. To identify endophytes in warm-season grasses, 35 endophytic bacterial isolates were cultured from root, rhizomes, and shoots of bermudagrass (Cynodon dactylon), energy cane (Saccharum spp.), Johnsongrass (Sorghum halepense), napiergrass (Cenchrus purpureus), perennial sorghum (Sorghum bicolor x S. halepense), sorghum (Sorghum bicolor), sorghum x sudangrass (Sorghum x drummondii), and peanut (outgroup). Sequencing of the 16S rRNA fragment from the endophytes revealed that the bacterial sequences were similar to Bacillus spp. (19 isolates), Burkholderia spp. (4), Pantoea spp. (4), Pseudomonas spp. (3), Enterobacter spp. (2), Kosakonia spp. (2), and Sphingomonas sp. (1). To identify diazotrophic endophytes, DNA isolated from surface disinfected tissue from warm- season grasses was used to amplify NifH. Bacteria containing NifH were similar to 13 genera and sequences similar to Pseudolabrys sp. was present in the greatest number of warm- season grasses. Bacteria similar to Bradyrhizobium frederickii strain CNPSo 3447 were identified frequently from leaves and roots of sorghum x sudangrass (and peanut roots). Using similarity to known NifH fragments, six genera were identified that had not been previously identified in grasses. Thus, a large number of endophytes were found in warm-season grasses and may enhance plant growth or enhance grass nitrogen levels by using nitrogen fixation.

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Complementary protein extraction methods increase the identification of the Park Grass Experiment metaproteome

Cited by 3 publications

References 20 publications

Assessing the impact of interfering organic matter on soil metaproteomic workflow

Assessing the impact of interfering organic matter on soil metaproteomic workflow

Comparison of Protein Extraction Methods and Data Analysis Strategies for Complete Metaproteomic Soil Analysis

Identification of Cultured and Diazotrophic Bacterial Endophytes in Warm-Season Grasses

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