scholarly journals Meta-exoproteomics identifies active plant-microbe interactions operating in the rhizosphere

2021 ◽  
Author(s):  
Ian Dennis Edmund Alan Lidbury ◽  
Sebastien Raguideau ◽  
Senlin Lui ◽  
Andrew Murphy ◽  
Richard Stark ◽  
...  
Keyword(s):  
Protein Extraction ◽  
Soil Microbial Communities ◽  
Extracellular Proteins ◽  
Active Fraction ◽  
Bioinformatics Pipeline ◽  
Brassica Napus L ◽  
Soil Microbiota ◽  
Microbe Interactions ◽  
Clear Shift ◽  
Plant Microbiome

The advance of DNA sequencing technologies has drastically changed our perception of the complexity and structure of the plant microbiome and its role in augmenting plant health. By comparison, our ability to accurately identify the metabolically active fraction of soil microbiota and their specific functional role is relatively limited. Here, we combined our recently developed protein extraction method and an iterative bioinformatics pipeline to enable the capture and identification of extracellular proteins (meta-exoproteomics) expressed in the rhizosphere of Brassica spp. First, we validated our method in the laboratory by successfully identifying proteins related to the host plant (Brassica rapa) and a bacterial inoculant, Pseudomonas putida BIRD-1, revealing the latter expressed numerous rhizosphere specific proteins linked to the acquisition of plant-derived nutrients. Next, we analysed natural field-soil microbial communities associated with Brassica napus L (Oil Seed rape). By combining deep-sequencing metagenomics with meta-exoproteomics, a total of 1882 proteins were identified in bulk and rhizosphere samples. Importantly, meta-exoproteomics identified a clear shift (p<0.001) in the metabolically active fraction of the soil microbiota responding to the presence of B. napus roots that was not apparent in the composition of the total microbial community (metagenome). This metabolic shift was associated with the stimulation of rhizosphere-specialised bacteria, such as Gammaproteobacteria, Betaproteobacteria and Flavobacteriia and the upregulation of plant beneficial functions related to phosphorus and nitrogen mineralisation. By providing the first meta-proteomic level assessment of the active plant microbiome at the field-scale, this study demonstrates the importance of moving past a genomic assessment of the plant microbiome in order to determine ecologically important plant: microbe interactions driving plant growth.

Multifaceted Impacts of Bacteriophages in the Plant Microbiome

2018 ◽  
Vol 56 (1) ◽  
pp. 361-380 ◽  
Author(s):  
Britt Koskella ◽  
Tiffany B. Taylor
Keyword(s):  
Host Plant ◽  
Future Study ◽  
Plant Pathogens ◽  
Ecological Interactions ◽  
Selection Pressures ◽  
Bacterial Populations ◽  
Associated Bacteria ◽  
Open Questions ◽  
Microbe Interactions ◽  
Plant Microbiome

Plant-associated bacteria face multiple selection pressures within their environments and have evolved countless adaptations that both depend on and shape bacterial phenotype and their interaction with plant hosts. Explaining bacterial adaptation and evolution therefore requires considering each of these forces independently as well as their interactions. In this review, we examine how bacteriophage viruses (phages) can alter the ecology and evolution of plant-associated bacterial populations and communities. This includes influencing a bacterial population's response to both abiotic and biotic selection pressures and altering ecological interactions within the microbiome and between the bacteria and host plant. We outline specific ways in which phages can alter bacterial phenotype and discuss when and how this might impact plant-microbe interactions, including for plant pathogens. Finally, we highlight key open questions in phage-bacteria-plant research and offer suggestions for future study.

scholarly journals The relative importance of rapid evolution for plant-microbe interactions depends on ecological context

2014 ◽  
Vol 281 (1785) ◽  
pp. 20140028 ◽  
Author(s):  
Casey P. terHorst ◽  
Jay T. Lennon ◽  
Jennifer A. Lau
Keyword(s):  
Microbial Communities ◽  
Bacterial Abundance ◽  
Rapid Evolution ◽  
Soil Microbial Communities ◽  
Ecological Effect ◽  
Ecological Context ◽  
Ecological Processes ◽  
Soil Microbial ◽  
Long Term Experiment ◽  
Microbe Interactions

Evolution can occur on ecological time-scales, affecting community and ecosystem processes. However, the importance of evolutionary change relative to ecological processes remains largely unknown. Here, we analyse data from a long-term experiment in which we allowed plant populations to evolve for three generations in dry or wet soils and used a reciprocal transplant to compare the ecological effect of drought and the effect of plant evolutionary responses to drought on soil microbial communities and nutrient availability. Plants that evolved under drought tended to support higher bacterial and fungal richness, and increased fungal : bacterial ratios in the soil. Overall, the magnitudes of ecological and evolutionary effects on microbial communities were similar; however, the strength and direction of these effects depended on the context in which they were measured. For example, plants that evolved in dry environments increased bacterial abundance in dry contemporary environments, but decreased bacterial abundance in wet contemporary environments. Our results suggest that interactions between recent evolutionary history and ecological context affect both the direction and magnitude of plant effects on soil microbes. Consequently, an eco-evolutionary perspective is required to fully understand plant–microbe interactions.

scholarly journals Rhizosphere bacterial communities of wheat vary across the growing season and among dryland farming systems

2019 ◽  
Author(s):  
Suzanne L. Ishaq ◽  
Tim Seipel ◽  
Carl J. Yeoman ◽  
Fabian D. Menalled
Keyword(s):  
Rhizosphere Soil ◽  
Soil Microbial Communities ◽  
Farming Systems ◽  
Growing Season ◽  
Farming System ◽  
Maximum Temperature ◽  
Soil Microbiota ◽  
Practical Applications ◽  
Soil Microbial ◽  
Thlaspi Arvense

AbstractDespite knowledge that seasonality and plant phenology impact soil microbiota, farming system effects on soil microbiota are not often evaluated across the growing season. We assessed the bacterial diversity in wheat rhizosphere soil through the spring and summer of 2016 in winter wheat (Triticum aestivium L.) in Montana, USA, from three contrasting farming systems: a chemically-managed no-tillage system, and two USDA-certified organic systems in their fourth year, one including tillage and one where sheep grazing partially offsets tillage frequency. Bacterial richness (range 605 – 1174 OTUs) and evenness (range 0.80 – 0.92) peaked in early June and dropped by late July (range 92 – 1190, 0.62-0.92, respectively), but was not different by farming systems. Organic tilled plots contained more putative nitrogen-fixing bacterial genera than the other two systems. Bacterial community similarities were significantly altered by sampling date, minimum and maximum temperature at sampling, bacterial abundance at date of sampling, total weed richness, and coverage of Taraxacum officinale, Lamium ampleuxicaule, and Thlaspi arvense. This study highlights that weed diversity, season, and farming management system all influence rhizosphere soil microbial communities. Local environmental conditions will strongly affect any practical applications aimed at improving soil diversity and functionality, especially in semi-arid regions where abiotic stress and seasonal variability in temperature and water availability drive primary production.

scholarly journals A dual-strategy expression screen for candidate connectivity labels in the developing thalamus

2016 ◽  
Author(s):  
Olivia Bibollet-Bahena ◽  
Tatsuya Okafuji ◽  
Karsten Hokamp ◽  
Kevin J. Mitchell
Keyword(s):  
Tyrosine Kinases ◽  
Expression Patterns ◽  
Extracellular Proteins ◽  
Surface Proteins ◽  
Axonal Guidance ◽  
Brain Atlas ◽  
Thalamic Nuclei ◽  
Bioinformatics Pipeline ◽  
Genes Encoding ◽  
Developing Mouse Brain

AbstractThe thalamus or “inner chamber” of the brain is divided into ~30 discrete nuclei, with highly specific patterns of afferent and efferent connectivity. To identify genes that may direct these patterns of connectivity, we used two strategies. First, we used a bioinformatics pipeline to survey the predicted proteomes of nematode, fruitfly, mouse and human for extracellular proteins containing any of a list of motifs found in known guidance or connectivity molecules. Second, we performed clustering analyses on the Allen Developing Mouse Brain Atlas data to identify genes encoding surface proteins expressed with temporal profiles similar to known guidance or connectivity molecules. In both cases, we then screened the resultant genes for selective expression patterns in the developing thalamus. These approaches identified 82 candidate connectivity labels in the developing thalamus. These molecules include many members of the Ephrin, Eph-receptor, cadherin, protocadherin, semaphorin, plexin, Odz/teneurin, Neto, cerebellin, calsyntenin and Netrin-G families, as well as diverse members of the immunoglobulin (Ig) and leucine-rich receptor (LRR) superfamilies, receptor tyrosine kinases and phosphatases, a variety of growth factors and receptors, and a large number of miscellaneous membrane-associated or secreted proteins not previously implicated in axonal guidance or neuronal connectivity. The diversity of their expression patterns indicates that thalamic nuclei are highly differentiated from each other, with each one displaying a unique repertoire of these molecules, consistent with a combinatorial logic to the specification of thalamic connectivity.

scholarly journals Proteomic characterization of pilot scale hot-water extracts from the industrial carrageenan red seaweed Eucheuma denticulatum

2020 ◽  
Author(s):  
Simon Gregersen ◽  
Margarita Pertseva ◽  
Paolo Marcatili ◽  
Susan Løvstad Holdt ◽  
Charlotte Jacobsen ◽  
...  
Keyword(s):  
Quantitative Proteomics ◽  
De Novo ◽  
Protein Extraction ◽  
Transcriptome Assembly ◽  
Protein Composition ◽  
Pilot Scale ◽  
Extracellular Proteins ◽  
Hot Water ◽  
Label Free

AbstractSeaweeds have a long history as a resource for polysaccharides/hydrocolloids extraction for use in the food industry due to their functionality as stabilizing agents. In addition to the carbohydrate content, seaweeds also contains a significant amount of protein, which may find application in food and feed. Here, we present a novel combination of transcriptomics, proteomics, and bioinformatics to determine the protein composition in two pilot-scale extracts from Eucheuma denticilatum (Spinosum) obtained via hot-water extraction. The extracts were characterized by qualitative and quantitative proteomics using LC-MS/MS and a de-novo transcriptome assembly for construction of a novel proteome. Using label-free, relative quantification, we were able to identify the most abundant proteins in the extracts and determined that the majority of quantified protein in the extracts (>75%) is constituted by merely three previously uncharacterized proteins. Putative subcellular localization for the quantified proteins was determined by bioinformatic prediction, and by correlating with the expected copy number from the transcriptome analysis, we determined that the extracts were highly enriched in extracellular proteins. This implies that the method predominantly extracts extracellular proteins, and thus appear ineffective for cellular disruption and subsequent release of intracellular proteins. Ultimately, this study highlight the power of quantitative proteomics as a novel tool for characterization of alternative protein sources intended for use in foods. Additionally, the study showcases the potential of proteomics for evaluation of protein extraction methods and as powerful tool in the development of an efficient extraction process.

scholarly journals The National Ecological Observatory Network’s soil metagenomes: assembly and basic analysis

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 299
Author(s):  
Zoey R. Werbin ◽  
Briana Hackos ◽  
Michael C. Dietze ◽  
Jennifer M. Bhatnagar
Keyword(s):  
Open Data ◽  
Soil Microbial Communities ◽  
The United States ◽  
Annual Data ◽  
Metagenomic Sequencing ◽  
Bioinformatics Pipeline ◽  
Soil Microbial ◽  
Shotgun Metagenomic Sequencing ◽  
Metagenome Sequencing ◽  
Downstream Analysis

The National Ecological Observatory Network (NEON) annually performs shotgun metagenomic sequencing to sample genes within soils at 47 sites across the United States. NEON serves as a valuable educational resource, thanks to its open data policies and programming tutorials, but there is currently no introductory tutorial for performing analyses with the soil shotgun metagenomic dataset. Here, we describe a workflow for processing raw soil metagenome sequencing reads using the Sunbeam bioinformatics pipeline. The workflow includes cleaning and processing raw reads, taxonomic classification, assembly into contigs, annotation of predicted genes using custom protein databases, and exporting assemblies to the KBase platform for downstream analysis. This workflow is designed to be robust to annual data releases from NEON, and the underlying Snakemake framework can manage complex software dependencies. The workflow presented here aims to increase the accessibility of NEON’s shotgun metagenome data, which can provide important clues about soil microbial communities and their ecological roles.

scholarly journals Stability of microbiota in vineyard soils across consecutive years.

2021 ◽  
Author(s):  
Alessandro Cestaro ◽  
emanuela coller ◽  
Davide Albanese ◽  
erika stefani ◽  
Massimo Pindo ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Large Scale ◽  
Geographic Origin ◽  
Soil Microbial Communities ◽  
Geographical Location ◽  
Taxonomic Structure ◽  
Ecological Processes ◽  
Soil Microbiota ◽  
Soil Microbial ◽  
The Impact

Agricultural soils harbor rich and diverse microbial communities that have a deep influence on soil properties and productivity. Large scale studies have shown the impact of environmental parameters like climate or chemical composition on the distribution of bacterial and fungal species. Comparatively, little data exists documenting how soil microbial communities change between different years. Quantifying the temporal stability of soil microbial communities will allow us to better understand the relevance of the differences between environments and their impact on ecological processes on the global and local scale. We characterized the bacterial and fungal components of the soil microbiota in ten vineyards in two consecutive years. Despite differences of species richness and diversity between the two years, we found a general stability of the taxonomic structure of the soil microbiota. Temporal differences were smaller than differences due to geographical location, vineyard land management or differences between sampling sites within the same vineyard. Using machine learning, we demonstrated that each site was characterized by a distinctive microbiota, and we identified a reduced set of indicator species that could classify samples according to their geographic origin across different years with high accuracy.

scholarly journals Soil Metaproteomics for the Study of the Relationships Between Microorganisms and Plants: A Review of Extraction Protocols and Ecological Insights

2020 ◽  
Vol 21 (22) ◽  
pp. 8455
Author(s):  
Maria Tartaglia ◽  
Felipe Bastida ◽  
Rosaria Sciarrillo ◽  
Carmine Guarino
Keyword(s):  
High Performance ◽  
Ad Hoc ◽  
Protein Extraction ◽  
Soil Samples ◽  
Extracellular Proteins ◽  
Lower Amount ◽  
Functional Changes ◽  
Critical Issues ◽  
Soil Proteins ◽  
Soil Protein

Soil is a complex matrix where biotic and abiotic components establish a still unclear network involving bacteria, fungi, archaea, protists, protozoa, and roots that are in constant communication with each other. Understanding these interactions has recently focused on metagenomics, metatranscriptomics and less on metaproteomics studies. Metaproteomic allows total extraction of intracellular and extracellular proteins from soil samples, providing a complete picture of the physiological and functional state of the “soil community”. The advancement of high-performance mass spectrometry technologies was more rapid than the development of ad hoc extraction techniques for soil proteins. The protein extraction from environmental samples is biased due to interfering substances and the lower amount of proteins in comparison to cell cultures. Soil sample preparation and extraction methodology are crucial steps to obtain high-quality resolution and yields of proteins. This review focuses on the several soil protein extraction protocols to date to highlight the methodological challenges and critical issues for the application of proteomics to soil samples. This review concludes that improvements in soil protein extraction, together with the employment of ad hoc metagenome database, may enhance the identification of proteins with low abundance or from non-dominant populations and increase our capacity to predict functional changes in soil.

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