Comparative Metaproteomics and Diversity Analysis of Human Intestinal Microbiota Testifies for Its Temporal Stability and Expression of Core Functions

Kolmeder, Carolin A.; Been, Mark de; Nikkilä, Janne; Ritamo, Ilja; Mättö, Jaana; Valmu, Leena; Salojärvi, Jarkko; Palva, Airi; Salonen, Anne; Vos, Willem M. de

doi:10.1371/journal.pone.0029913

Cited by 172 publications

(201 citation statements)

References 56 publications

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“…The total number of proteins identified in the mouse cecal samples that we analyzed (n ¼ 1760) is comparable to results obtained using human fecal samples (n ¼ 1500 to 1800 proteins) (Verberkmoes et al, 2009;Kolmeder et al, 2012). After functional category assignment of identified proteins, our data confirmed that, regardless of diet, the dominant mammalian gut metaproteome is involved in energy production from carbohydrate metabolism.…”

Section: Discussionsupporting

confidence: 79%

“…Since the first gel-based metaproteome published in 2007 (Klaassens et al, 2007) and the state-of-the art LC-MS/MS work by Verberkmoes et al (2009), the size of genomic databases has been rising exponentially. Nevertheless, annotation of peptide spectra remains challenging and functional interpretation based on the occurrence of dominant proteins is limited, that is, taking into account the high degree of diversity of the intestinal microbial ecosystem, we still profit only from a narrow window of analysis at the proteome level (Rooijers et al, 2011;Haange et al, 2012;Kolmeder et al, 2012;Perez-Cobas et al, 2012). This challenge is reflected in the present study by the fact that only 5% of all tandem MS spectra acquired could be matched to protein sequences from the databases.…”

Section: Discussionmentioning

confidence: 98%

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High-fat diet alters gut microbiota physiology in mice

Daniel¹,

Gholami²,

Berry³

et al. 2013

The ISME Journal

588

386

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The intestinal microbiota is known to regulate host energy homeostasis and can be influenced by highcalorie diets. However, changes affecting the ecosystem at the functional level are still not well characterized. We measured shifts in cecal bacterial communities in mice fed a carbohydrate or high-fat (HF) diet for 12 weeks at the level of the following: (i) diversity and taxa distribution by high-throughput 16S ribosomal RNA gene sequencing; (ii) bulk and single-cell chemical composition by Fourier-transform infrared-(FT-IR) and Raman micro-spectroscopy and (iii) metaproteome and metabolome via highresolution mass spectrometry. High-fat diet caused shifts in the diversity of dominant gut bacteria and altered the proportion of Ruminococcaceae (decrease) and Rikenellaceae (increase). FT-IR spectroscopy revealed that the impact of the diet on cecal chemical fingerprints is greater than the impact of microbiota composition. Diet-driven changes in biochemical fingerprints of members of the Bacteroidales and Lachnospiraceae were also observed at the level of single cells, indicating that there were distinct differences in cellular composition of dominant phylotypes under different diets. Metaproteome and metabolome analyses based on the occurrence of 1760 bacterial proteins and 86 annotated metabolites revealed distinct HF diet-specific profiles. Alteration of hormonal and anti-microbial networks, bile acid and bilirubin metabolism and shifts towards amino acid and simple sugars metabolism were observed. We conclude that a HF diet markedly affects the gut bacterial ecosystem at the functional level.

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Section: Discussionsupporting

confidence: 79%

Section: Discussionmentioning

confidence: 98%

High-fat diet alters gut microbiota physiology in mice

Daniel¹,

Gholami²,

Berry³

et al. 2013

The ISME Journal

588

386

View full text Add to dashboard Cite

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“…Denaturing Gradient Gel Electrophoresis (DGGE) and Temperature Gradient Gel Electrophoresis (TGGE) are examples of molecular fingerprinting methods that separate amplicons based on this principle. In particular, DGGE has been shown to be useful to assess qualitative variations in the GI microbiota of dogs among different Kolmeder et al (2012) compartments of the intestinal tract (Suchodolski et al 2005). The result of DGGE or TGGE analysis is a specific banding pattern for every sample analysed, therefore providing a qualitative view of the microbial composition of the sample.…”

Section: Polymerase Chain Reaction (Pcr)mentioning

confidence: 99%

Gastrointestinal microorganisms in cats and dogs: a brief review

Garcia-Mazcorro¹,

Minamoto

2013

Arch. med. vet.

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RESUMENEl tracto gastrointestinal (GI) de animales contiene diferentes tipos de microorganismos conocido como la microbiota GI. Por mucho tiempo, la microbiota GI ha generado interés porque los microorganismos GI están involucrados en múltiples procesos fisiológicos en el hospedero, así perpetuando salud o enfermedad. Estudios recientes han demostrado que la microbiota GI de gatos y perros es tan compleja como en humanos y otros animales, revelado con el uso de tecnologías de secuencia modernas y otras técnicas moleculares. La microbiota GI incluye miembros de todos los tres dominios principales de vida (Archaea, Bacterias y Eucariotas), pero las bacterias son el grupo de microorganismos más abundante y metabólicamente activo. El estómago de gatos y perros esta principalmente poblado de Helicobacter spp., el cual en perros puede representar tanto como el 98% de toda la microbiota bacteriana en el estómago. El intestino delgado contiene una microbiota más diversa, conteniendo representantes de al menos cinco diferentes filos bacterianos (principalmente Firmicutes y Bacteroidetes). El intestino grueso contiene el grupo de bacterias más abundante (~10 11 células bacterianas por gramo de contenido intestinal), diverso (al menos diez diferentes filos han sido detectados) y metabólicamente relevante en el tracto GI. La mayoría de las bacterias en el intestino grueso son anaerobios estrictos, los cuales dependen de la fermentación de sustancias no digeridas para subsistir. Aunque estudios recientes han dilucidado las complejidades de la microbiota GI en gatos y perros, más investigación todavía es necesaria para encontrar maneras de manipular exitosamente los microorganismos GI para prevenir y/o tratar enfermedades GI.Palabras clave: gastrointestinal, microbiota, gatos, perros. SUMMARYThe gastrointestinal (GI) tract of animals contains different types of microorganisms known as the GI microbiota. The GI microbiota has long been of interest because of its involvement in multiple physiological processes in the host, influencing health or disease. Recent studies have shown that the GI microbiota of cats and dogs is as complex as the one present in humans and other animals, according to state-of-the-art sequencing technologies and other molecular techniques. The GI microbiota includes members of all three main life domains (Archaea, Bacteria, and Eukaryotes), with bacteria being the most abundant and metabolically active group of microorganisms. The stomach of cats and dogs is mainly inhabited by Helicobacter spp., which in dogs may account for as much as 98% of all gastric bacterial microbiota. The small intestine harbors a more diverse microbiota as it contains representatives from at least five bacterial phyla (mainly Firmicutes and Bacteroidetes). The large intestine harbors the most abundant (~10 11 bacterial cells per gram of intestinal content), diverse (at least 10 bacterial phyla have been identified) and physiologically relevant group of bacteria in the GI tract. Most bacteria in the large intestine are strict an...

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“…These approaches, compared to 16S rRNA gene-targeted approaches such as DGGE-and PITChip analysis, can more directly provide information regarding the metabolic activity of intestinal microorganisms based on the identification of active pathways (Kolmeder et al, 2012;Zoetendal et al, 2012).…”

Section: Discussionmentioning

confidence: 99%

Adaptation of faecal microbiota in sows after diet changes and consequences for in vitro fermentation capacity

Sappok

Gutiérrez

Smidt

et al. 2015

Animal

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In vitro gas production studies are routinely used to assess the metabolic capacity of intestinal microbiota to ferment dietary fibre sources. The faecal inocula used during the in vitro gas production procedure are most often obtained from animals adapted to a certain diet. The present study was designed to assess whether 19 days of adaptation to a diet are sufficient for faecal inocula of pigs to reach a stable microbial composition and activity as determined by in vitro gas production. Eighteen multiparous sows were allotted to one of two treatments for three weeks: a diet high in fibre (H) or a diet low in fibre (L). After this 3-week period, the H group was transferred to the low fibre diet (HL-treatment) while the L group was transferred to the diet high in fibre (LH-treatment). Faecal samples were collected from each sow at 1, 4, 7, 10, 13, 16 and 19 days after the diet change and prepared as inoculum used for incubation with three contrasting fermentable substrates: oligofructose, soya pectin and cellulose. In addition, inocula were characterised using a phylogenetic microarray targeting the pig gastrointestinal tract microbiota. Time after diet change had an effect ( P < 0.05) on total gas production for the medium-fast fermentable substrates; soya pectin and oligofructose. For the more slowly fermentable cellulose, all measured fermentation parameters were consistently higher ( P < 0.05) for animals in the HL-treatment. Diet changes led to significant changes in relative abundance of specific bacteria, especially for members of the Bacteroidetes and Bacilli, which, respectively, increased or decreased for the LH-treatment, while changes were opposite for the HL-treatment. Changing the diet of sows led to changes in fermentation activity of the faecal microbiota and in composition of the microbiota over time. Adaptation of the microbiota as assessed by gas production occurred faster for LH-animals for fast fermentable substrates compared with HL-animals. Overall, adaptation of the large intestinal microbiota of sows as a result of ingestion of low and high fibre diets seems to take longer than 19 days, especially for the ability to ferment slowly fermentable substrates.

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Comparative Metaproteomics and Diversity Analysis of Human Intestinal Microbiota Testifies for Its Temporal Stability and Expression of Core Functions

Cited by 172 publications

References 56 publications

High-fat diet alters gut microbiota physiology in mice

High-fat diet alters gut microbiota physiology in mice

Gastrointestinal microorganisms in cats and dogs: a brief review

Adaptation of faecal microbiota in sows after diet changes and consequences for in vitro fermentation capacity

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