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Transcriptomic and Proteomic Analysis of Arion vulgaris--Proteins for Probably Successful Survival Strategies?

ABSTRACT: The Spanish slug, Arion vulgaris, is considered one of the hundred most invasive species in Central Europe. The immense and very successful adaptation and spreading of A. vulgaris suggest that it developed highly effective mechanisms to deal with infections and natural predators. Current transcriptomic and proteomic studies on gastropods have been restricted mainly to marine and freshwater gastropods. No transcriptomic or proteomic study on A. vulgaris has been carried out so far, and in the current study, the first transcriptomic database from adult specimen of A. vulgaris is reported. To facilitate and enable proteomics in this non-model organism, a mRNA-derived protein database was constructed for protein identification. A gel-based proteomic approach was used to obtain the first generation of a comprehensive slug mantle proteome. A total of 2128 proteins were unambiguously identified; 48 proteins represent novel proteins with no significant homology in NCBI non-redundant database. Combined transcriptomic and proteomic analysis revealed an extensive repertoire of novel proteins with a role in innate immunity including many associated pattern recognition, effector proteins and cytokine-like proteins. The number and diversity in gene families encoding lectins point to a complex defense system, probably as a result of adaptation to a pathogen-rich environment. These results are providing a fundamental and important resource for subsequent studies on molluscs as well as for putative antimicrobial compounds for drug discovery and biomedical applications.

SUBMITTER: Bulat T

PROVIDER: S-EPMC4795696 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Transcriptomic and Proteomic Analysis of Arion vulgaris--Proteins for Probably Successful Survival Strategies?

Bulat Tanja T Smidak Roman R Sialana Fernando J FJ Jung Gangsoo G Rattei Thomas T Bilban Martin M Sattmann Helmut H Lubec Gert G Lubec Gert G Aradska Jana J

PloS one 20160317 3

The Spanish slug, Arion vulgaris, is considered one of the hundred most invasive species in Central Europe. The immense and very successful adaptation and spreading of A. vulgaris suggest that it developed highly effective mechanisms to deal with infections and natural predators. Current transcriptomic and proteomic studies on gastropods have been restricted mainly to marine and freshwater gastropods. No transcriptomic or proteomic study on A. vulgaris has been carried out so far, and in the cur ...[more]

PMID: 26986963

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Project description:Gene expression profiling technologies can generally produce mRNA abundance data for all genes in a genome. A dearth of proteomic data persists because identification range and sensitivity of proteomic measurements lag behind those of transcriptomic measurements. Using partial proteomic data, it is likely that integrative transcriptomic and proteomic analysis may introduce significant bias. Developing methodologies to accurately estimate missing proteomic data will allow better integration of transcriptomic and proteomic datasets and provide deeper insight into metabolic mechanisms underlying complex biological systems.In this study, we present a non-linear data-driven model to predict abundance for undetected proteins using two independent datasets of cognate transcriptomic and proteomic data collected from Desulfovibrio vulgaris. We use stochastic gradient boosted trees (GBT) to uncover possible non-linear relationships between transcriptomic and proteomic data, and to predict protein abundance for the proteins not experimentally detected based on relevant predictors such as mRNA abundance, cellular role, molecular weight, sequence length, protein length, guanine-cytosine (GC) content and triple codon counts. Initially, we constructed a GBT model using all possible variables to assess their relative importance and characterize the behavior of the predictive model. A strong plateau effect in the regions of high mRNA values and sparse data occurred in this model. Hence, we removed genes in those areas based on thresholds estimated from the partial dependency plots where this behavior was captured. At this stage, only the strongest predictors of protein abundance were retained to reduce the complexity of the GBT model. After removing genes in the plateau region, mRNA abundance, main cellular functional categories and few triple codon counts emerged as the top-ranked predictors of protein abundance. We then created a new tuned GBT model using the five most significant predictors. The construction of our non-linear model consists of a set of serial regression trees models with implicit strength in variable selection. The model provides variable relative importance measures using as a criterion mean square error. The results showed that coefficients of determination for our nonlinear models ranged from 0.393 to 0.582 in both datasets, providing better results than linear regression used in the past. We evaluated the validity of this non-linear model using biological information of operons, regulons and pathways, and the results demonstrated that the coefficients of variation of estimated protein abundance values within operons, regulons or pathways are indeed smaller than those for random groups of proteins.Supplementary data are available at Bioinformatics online.

Dataset Information

Transcriptomic and Proteomic Analysis of Arion vulgaris--Proteins for Probably Successful Survival Strategies?

Publications

Transcriptomic and Proteomic Analysis of Arion vulgaris--Proteins for Probably Successful Survival Strategies?

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