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More Is Not Always Better: Evaluation of 1D and 2D-LC-MS/MS Methods for Metaproteomics.

ABSTRACT: Metaproteomics, the study of protein expression in microbial communities, is a versatile tool for environmental microbiology. Achieving sufficiently high metaproteome coverage to obtain a comprehensive picture of the activities and interactions in microbial communities is one of the current challenges in metaproteomics. An essential step to maximize the number of identified proteins is peptide separation via liquid chromatography (LC) prior to mass spectrometry (MS). Thorough optimization and comparison of LC methods for metaproteomics are, however, currently lacking. Here, we present an extensive development and test of different 1D and 2D-LC approaches for metaproteomic peptide separations. We used fully characterized mock community samples to evaluate metaproteomic approaches with very long analytical columns (50 and 75 cm) and long gradients (up to 12 h). We assessed a total of over 20 different 1D and 2D-LC approaches in terms of number of protein groups and unique peptides identified, peptide spectrum matches (PSMs) generated, the ability to detect proteins of low-abundance species, the effect of technical replicate runs on protein identifications and method reproducibility. We show here that, while 1D-LC approaches are faster and easier to set up and lead to more identifications per minute of runtime, 2D-LC approaches allow for a higher overall number of identifications with up to >10,000 protein groups identified. We also compared the 1D and 2D-LC approaches to a standard GeLC workflow, in which proteins are pre-fractionated via gel electrophoresis. This method yielded results comparable to the 2D-LC approaches, however with the drawback of a much increased sample preparation time. Based on our results, we provide recommendations on how to choose the best LC approach for metaproteomics experiments, depending on the study aims.

SUBMITTER: Hinzke T

PROVIDER: S-EPMC6383543 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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More Is Not Always Better: Evaluation of 1D and 2D-LC-MS/MS Methods for Metaproteomics.

Hinzke Tjorven T Kouris Angela A Hughes Rebecca-Ayme RA Strous Marc M Kleiner Manuel M

Frontiers in microbiology 20190214

Metaproteomics, the study of protein expression in microbial communities, is a versatile tool for environmental microbiology. Achieving sufficiently high metaproteome coverage to obtain a comprehensive picture of the activities and interactions in microbial communities is one of the current challenges in metaproteomics. An essential step to maximize the number of identified proteins is peptide separation via liquid chromatography (LC) prior to mass spectrometry (MS). Thorough optimization and co ...[more]

PMID: 30837968

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Project description:BackgroundThe observed molecular weight of a protein on a 1D polyacrylamide gel can provide meaningful insight into its biological function. Differences between a protein's observed molecular weight and that predicted by its full length amino acid sequence can be the result of different types of post-translational events, such as alternative splicing (AS), endoproteolytic processing (EPP), and post-translational modifications (PTMs). The characterization of these events is one of the important goals of total proteome profiling (TPP). LC/MS/MS has emerged as one of the primary tools for TPP, but since this method identifies tryptic fragments of proteins, it has not generally been used for large-scale determination of the molecular weight of intact proteins in complex mixtures.ResultsWe have developed a set of computational tools for extracting molecular weight information of intact proteins from total proteome profiles in a high throughput manner using 1D-PAGE and LC/MS/MS. We have applied this technology to the proteome profile of a human lymphoblastoid cell line under standard culture conditions. From a total of 1 x 10(7) cells, we identified 821 proteins by at least two tryptic peptides. Additionally, these 821 proteins are well-localized on the 1D-SDS gel. 656 proteins (80%) occur in gel slices in which the observed molecular weight of the protein is consistent with its predicted full-length sequence. A total of 165 proteins (20%) are observed to have molecular weights that differ from their predicted full-length sequence. We explore these molecular-weight differences based on existing protein annotation.ConclusionWe demonstrate that the determination of intact protein molecular weight can be achieved in a high-throughput manner using 1D-PAGE and LC/MS/MS. The ability to determine the molecular weight of intact proteins represents a further step in our ability to characterize gene expression at the protein level. The identification of 165 proteins whose observed molecular weight differs from the molecular weight of the predicted full-length sequence provides another entry point into the high-throughput characterization of protein modification.

Project description:Animal-associated microbes are highly variable, contributing to a diverse set of symbiont-mediated phenotypes. Given that host and symbiont genotypes, and their interactions, can impact symbiont-based phenotypes across environments, there is potential for extensive variation in fitness outcomes. Pea aphids, Acyrthosiphon pisum, host a diverse assemblage of heritable facultative symbionts (HFS) with characterized roles in host defense. Protective phenotypes have been largely studied as single infections, but pea aphids often carry multiple HFS species, and particular combinations may be enriched or depleted compared to expectations based on chance. Here, we examined the consequences of single infection versus coinfection with two common HFS exhibiting variable enrichment, the antiparasitoid Hamiltonella defensa and the antipathogen Regiella insecticola, across three host genotypes and environments. As expected, single infections with either H. defensa or R. insecticola raised defenses against their respective targets. Single infections with protective H. defensa lowered aphid fitness in the absence of enemy challenge, while R. insecticola was comparatively benign. However, as a coinfection, R. insecticola ameliorated H. defensa infection costs. Coinfected aphids continued to receive antiparasitoid protection from H. defensa, but protection was weakened by R. insecticola in two clones. Notably, H. defensa eliminated survival benefits conferred after pathogen exposure by coinfecting R. insecticola Since pathogen sporulation was suppressed by R. insecticola in coinfected aphids, the poor performance likely stemmed from H. defensa-imposed costs rather than weakened defenses. Our results reveal a complex set of coinfection outcomes which may partially explain natural infection patterns and suggest that symbiont-based phenotypes may not be easily predicted based solely on infection status.IMPORTANCE The hyperdiverse arthropods often harbor maternally transmitted bacteria that protect against natural enemies. In many species, low-diversity communities of heritable symbionts are common, providing opportunities for cooperation and conflict among symbionts, which can impact the defensive services rendered. Using the pea aphid, a model for defensive symbiosis, we show that coinfections with two common defensive symbionts, the antipathogen Regiella and the antiparasite Hamiltonella, produce outcomes that are highly variable compared to single infections, which consistently protect against designated enemies. Compared to single infections, coinfections often reduced defensive services during enemy challenge yet improved aphid fitness in the absence of enemies. Thus, infection with multiple symbionts does not necessarily create generalist aphids with "Swiss army knife" defenses against numerous enemies. Instead, particular combinations of symbionts may be favored for a variety of reasons, including their abilities to lessen the costs of other defensive symbionts when enemies are not present.

Dataset Information

More Is Not Always Better: Evaluation of 1D and 2D-LC-MS/MS Methods for Metaproteomics.

Publications

More Is Not Always Better: Evaluation of 1D and 2D-LC-MS/MS Methods for Metaproteomics.

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