Protein-SIP in environmental studies

Jehmlich, Nico; Vogt, Carsten; Lünsmann, Vanessa; Richnow, Hans H.; Bergen, Martin von

doi:10.1016/j.copbio.2016.04.010

Cited by 65 publications

(65 citation statements)

References 26 publications

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“…Sowohl Markierungsverhältnis als auch RIA können sehr exakt bestimmt werden, wobei RIAs in einfachen Systemen bis zu einem Wert von 1 % ausreichend sind, in komplexeren jedoch 10 % für eine Erkennung nötig sind. Dabei finden Isotope wie 2 H, 13 C, 15 N, 18 O, 34 S oder 36 S Anwendung [43].…”

Section: Protein Stabile-isotop-probing (Protein-sip)unclassified

Chancen und Risiken von Metaproteomik in der Mikrobiomforschung

Haange

Jehmlich

Jacobi

et al. 2019

Adipositas - Ursachen, Folgeerkrankungen, Therapie

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ZusammenfassungDie Erforschung des menschlichen Darmmikrobioms in den letzten 15 Jahren führte zu neuen Erkenntnissen wodurch Korrelationen und sogar Kausalitäten vieler Erkrankungen mit der Veränderungen der Mikrobiota beschrieben werden konnten. Wegbereitend für die Analyse der Mikrobiota von in vivo Proben war dabei die Entwicklung der sogenannten Meta-omics Methoden, insbesondere die 16 S rRNA Gensequenzierung und die Metagenomik. Jedoch hat die taxonomische Zusammensetzung der Darmmikrobiota aufgrund der hohen funktionellen Redundanz und Vielfältigkeit des Stoffwechselpotentials einzelner Bakterienarten nur geringe Vorhersagekraft bezüglich ihrer tatsächlichen Funktionalität. Aus diesem Grund wurden metaproteomische und metabolische Markierungsmethoden mit stabilen Isotopen (Protein-SIP) entwickelt. Wenn man die Gesamtanzahl der Proteine einer mikrobiellen Gemeinschaft betrachtet, können somit Informationen zur taxonomischen Verteilung, metabolischer Funktion, metabolischer Aktivität sowie für die Funktion der Mikrobiota Schlüsselarten identifiziert werden.Der Fokus des Artikels liegt auf der Methode Metaproteomik sowie der proteinbasierten Stabil-Isotopen-Markierung (Protein-SIP), weil diese Ansätze funktionelle und taxonomische Ergebnisse vereinen. Zusätzlich werden Chancen aber auch Risiken betrachtet, mit denen die Methoden naturgemäß einhergehen.

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Section: Protein Stabile-isotop-probing (Protein-sip)unclassified

Chancen und Risiken von Metaproteomik in der Mikrobiomforschung

Haange

Jehmlich

Jacobi

et al. 2019

Adipositas - Ursachen, Folgeerkrankungen, Therapie

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“…Protein-based stable isotope probing (protein-SIP) is a well-established technique to study dynamic changes in a proteome [11]. When using protein-SIP in animals, the latter are fed food enriched with stable isotopes and their incorporation into proteins are then measured by mass spectrometry.…”

Section: Introductionmentioning

confidence: 99%

“…Here we report a metaproteomic workflow that involved protein-SIP, identification, and quantification of partially labeled peptides, followed by computational analysis. Briefly, five [11][12] week old mice were fed 15 N labeled hydrolysate from Ralstonia eutropha as mouse chow for 43 days. Stool samples from these mice were collected over 10 time points and their microbiome was analyzed by metaproteomics.…”

Section: Introductionmentioning

confidence: 99%

Studying the dynamics of the gut microbiota using metabolically stable isotopic labeling and metaproteomics

Smyth

Zhang

Ning

et al. 2020

Preprint

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Background: The gut microbiome and its metabolic processes are dynamic systems. Surprisingly, our understanding of gut microbiome dynamics is limited. Here we report a metaproteomic workflow that involves protein stable isotope probing (protein-SIP) and identification and quantification of partially labeled peptides. We also developed a package, which we call MetaProfiler, that corrects for false identifications and performs phylogenetic and time series analysis for the study of gut microbiome functional dynamics.Results: From the stool sample of five mice that were fed with 15 N hydrolysate from Ralstonia eutropha, we identified 15,297 non-redundant unlabeled peptides of which 10,839 of their heavy counterparts were quantified. These peptides revealed incorporation profiles over time that were different between and within taxa, as well as between and within clusters of orthologous groups (COGs). Conclusions:Our study helps unravel the complex dynamics of protein synthesis and bacterial dynamics in the mouse microbiome.Availability: MetaProfiler and the bioinformatic pipeline are available at https://github.com/psmyth94/MetaProfiler.git.

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“…The above quantitative identity‐function methods add a great deal to the methodological tool box in microbial ecology, however, they also have certain limitations. Compared with nucleic‐acid based methods, protein‐SIP and PLFA‐SIP are limited in phylogenetic resolution; labelled peptides or labelled PLFAs can often only be assigned to bacterial families or orders (Jehmlich et al ., ) or are biomarkers for broad groups of microorganisms (Gutierrez‐Zamora and Manefield, ), respectively. For probe‐based methods, even including Chip‐SIP where multiple probes are deployed in parallel, a concern is that taxa coverage is dependent on selection of probes and therefore analysis might miss activity in unexpected taxa (Mayali et al ., ).…”

Section: Introductionmentioning

confidence: 99%

Apportioning bacterial carbon source utilization in soil using ¹⁴C isotope analysis of FISH‐targeted bacterial populations sorted by fluorescence activated cell sorting (FACS): ¹⁴C‐FISH‐FACS

Gougoulias

Meade

Shaw

2018

Environ Microbiol Rep

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An unresolved need in microbial ecology is methodology to enable quantitative analysis of in situ microbial substrate carbon use at the population level. Here, we evaluated if a novel combination of radiocarbon-labelled substrate tracing, fluorescence in situ hybridisation (FISH) and fluorescence-activated cell sorting (FACS) to sort the FISH-targeted population for quantification of incorporated radioactivity ( C-FISH-FACS) can address this need. Our test scenario used FISH probe PSE1284 targeting Pseudomonas spp. (and some Burkholderia spp.) and salicylic acid added to rhizosphere soil. We examined salicylic acid- C fate (mineralized, cell-incorporated, extractable and non-extractable) and mass balance (0-24 h) and show that the PSE1284 population captured ∼ 50% of the Nycodenz extracted biomass C. Analysis of the taxonomic distribution of the salicylic acid biodegradation trait suggested that PSE1284 population success was not due to conservation of this trait but due to competitiveness for the added carbon. Adding 50KBq of C sample enabled detection of C in the sorted population at ∼ 60-600 times background; a sensitivity which demonstrates potential extension to analysis of rarer/less active populations. Given its sensitivity and compatibility with obtaining a C mass balance, C-FISH-FACS allows quantitative dissection of C flow within the microbial biomass that has hitherto not been achieved.

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Protein-SIP in environmental studies

Cited by 65 publications

References 26 publications

Chancen und Risiken von Metaproteomik in der Mikrobiomforschung

Chancen und Risiken von Metaproteomik in der Mikrobiomforschung

Studying the dynamics of the gut microbiota using metabolically stable isotopic labeling and metaproteomics

Apportioning bacterial carbon source utilization in soil using ¹⁴C isotope analysis of FISH‐targeted bacterial populations sorted by fluorescence activated cell sorting (FACS): ¹⁴C‐FISH‐FACS

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Protein-SIP in environmental studies

Cited by 65 publications

References 26 publications

﻿Chancen und Risiken von Metaproteomik in der Mikrobiomforschung

﻿Chancen und Risiken von Metaproteomik in der Mikrobiomforschung

Studying the dynamics of the gut microbiota using metabolically stable isotopic labeling and metaproteomics

Apportioning bacterial carbon source utilization in soil using 14C isotope analysis of FISH‐targeted bacterial populations sorted by fluorescence activated cell sorting (FACS): 14C‐FISH‐FACS

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Chancen und Risiken von Metaproteomik in der Mikrobiomforschung

Chancen und Risiken von Metaproteomik in der Mikrobiomforschung

Apportioning bacterial carbon source utilization in soil using ¹⁴C isotope analysis of FISH‐targeted bacterial populations sorted by fluorescence activated cell sorting (FACS): ¹⁴C‐FISH‐FACS