ANEXO DIARIO DE CAMPO: Fecha: 26 de Septiembre de 2011.

microbiota

I.1.2.1 Culture-independent techniques for studying the human

microbiota

Our understanding of the indigenous human microbiota and its composition, how it interacts with the host and how it maintains the balance in human health or causes disease, has been enhanced by advances in culture-independent techniques (Fraher et al., 2012). For many years, culture and biochemical typing have been very useful and even essentials to identify bacterial species. However, since the 1990s the development of culture‐independent techniques based on 16S rRNA gene sequences has revolutionized our knowledge and helped to evaluate the composition of the human microbiota (Rajilić-Stojanović et al., 2007; Ventura et al., 2009; Marchesi, 2011). These culture‐independent techniques have allowed demonstrating the microbial diversity of the human microbiota, providing qualitative and quantitative knowledge on bacterial species and changes in the microbiota in relation to health and disease (Fraher et al., 2012). Examples of these techniques are denaturing gradient gel electrophoresis (DGGE), quantitative polymerase chain reaction (qPCR), DNA microarrays, sequencing of cloned 16S rRNA gene amplicons and next-generation sequencing of the 16S rRNA genes and microbial genomes (Table I.1). These next- generation methods are typically applied to DNA amplicons directly or to the total genomic DNA. They are described as massively parallel sequencing as ‘massive’ numbers of DNA templates can be sequenced in

parallel; that is, at the same time and in the same reaction set-up, a very large amount of short sequences can be read and thus even bacteria that are in low abundance can be detected (Rogers and Venter 2005, Fraher et al., 2012). Commercially available technologies include 454 Pyrosequencing®, Illumina®, SOLiD™ and Ion Torrent™ (Table I.1). The term metagenomics in microbiology refers to the study of the collective genomes of the microbiota from a site (named microbiome). Thus the metagenomic studies consist of sequencing all the DNA of a sample rather than a particular DNA fragment (Sekirov et al., 2010). Large metagenomic studies are that of The Human Microbiome Project, which has studied the structure, function and diversity of the healthy human microbiome from hundreds of samples and their correlations with diet and age (Huttenhower et al., 2012) and the Metagenomics of the Human Intestinal Tract (MetaHIT) project that has studied the metagenomic profile of hundreds of faecal samples from healthy adults, overweight/obese individuals and intestinal bowel disease patients (Qin et al., 2010; Arumugam et al., 2011). Due to the increasingly easy access of these culture-independent technologies, there is currently an increase of research groups performing broad spectrum studies of the human microbiota for different purposes, most of them related with health (Thomas et al., 2014).

Metagenomic approaches have started to put forward the microbial functionalities embedded into the human microbiota (Lepage et al., 2013). The easy access to the oral cavity has allowed sampling and therefore obtaining much information of the microbiota from the different surfaces inside on it, such as buccal mucosa, subgingival and supragingival plaque, saliva, tongue, etc. (Wade, 2013; Zaura et al., 2014). However, most of the studies about composition, diversity and functions of the human gut microbiota have been conducted with faecal material (De Filippo et al., 2010; Wu et al., 2011; Huttenhower et al., 2012; Methé et al., 2012; Voreades et al., 2014), due to the easy and non-invasive

methods required to obtain these samples. It is generally accepted that faecal samples could represent luminal microbiota; however, mucosal associated microbiota, as well as the microbial communities present in the different colonic regions, are not represented, being only accessible by invasive methods so far (Watt et al., 2013).

Table I.1. Techniques for studying the human microbiota.

Adapted from Fraher et al., 2012.

Technique Description Advantages Disadvantages

Culture Selective media for isolation of bacteria. Semi-quantitative, cheap. Limited to certain bacterial groups,

time consuming.

Quantitative - PCR Amplification and quantification of 16S rRNA. High sensitivity, quantitative, No identification of unknown species,

The PCR product is labeled with a fluorochrome reporter. fast, phylogenetic identification PCR bias.

Fluorescence is directly proportional to the amount of product. and gene expression.

DGGE/TGGE Gel separation of 16S rRNA amplicons in bands using Semi-quantitative, bands can No phylogenetic identification,

(denaturing gradient gel electrophoresis/ denaturant/temperature. Obtaining a molecular fingerprint. be excised and sequenced. PCR bias.

temperature gradient gel electrophoresis) Each band represents one specie.

FISH Fluorescently labelled oligonucleotide probes hybridize Phylogenetic identification, Dependent on probe sequences,

(fluorescence in situ hybridization) complementary target 16S rRNA sequences. semi-quantitative, no PCR bias, unable to identify unknown species.

When hybridization occurs, fluorescence can easily differentiate between

can be enumerated using flow cytometry. live and dead cells.

DNA microarrays Fluorescently labelled oligonucleotide probes hybridize Phylogenetic identification, Cross hybridization, PCR bias,

with complementary nucleotide sequences. semi-quantitative, fast, simultaneous species present in low levels

Fluorescence detected with a laser. identification of thousands of genes. can be difficult to detect.

Cloned 16S rRNA gene sequencing Cloning of full-length 16S rRNA amplicon, sanger Phylogenetic identification, PCR bias, laborious, expensive,

sequencing and capillary electrophoresis. quantitative. cloning bias.

Direct sequencing of 16S rRNA amplicons Massive parallel sequencing of partial 16S rRNA Phylogenetic identification and

amplicons for example, 454 Pyrosequencing® (Roche biodiversity analysis, PCR bias, expensive, laborious.

Diagnostics GMBH Ltd, Mannheim, Germany) (amplicon quantitative, fast, identification of

immobilized on beads, amplified by emulsion PCR, addition unknown bacteria, not need to insert

of luciferase results in a chemoluminescent signal) gene fragments in a host.

Microbiome shotgun sequencing Massive parallel sequencing of the whole genome Phylogenetic identification, quantitative, Expensive, analysis of data is

(e.g. 454 pyrosequencing®, Illumina®, Ion Torrent™) whole-genome sequencing, allows computationally intense.

I.1.2.2 Oral microbiota

More than 200 microbial species from the oral cavity have been isolated using classical culture techniques, while culture-independent molecular methods primarily using 16S rRNA gene-based cloning studies have identified approximately 600 more phylotypes (Dewhirst et al., 2010). Today, it is thought that the number may reach 10000 phylotypes as revealed by pyrosequencing analyses (Keijser et al., 2008; Zaura et al., 2009; Diaz, 2011). The bacterial community of the mouth is dominated by the phyla Firmicutes (Streptococcus, Veillonellaceae,

Granulicatella), Proteobacteria (Neisseria, Haemophilus), Actinobacteria

(Corynebacterium, Rothia, Actinomyces), Bacteroidetes (Prevotella,

Capnocytophaga, Porphyromonas), Spirochaetes and Fusobacteria

(Fusobacterium) (Lazarevic et al., 2009; Zaura et al., 2009; Lazarevic et al., 2010), which account for 96% of the species detected (Dewhirst et al., 2010). The proportion of the microbiota that has been cultivated (approximately 40%) is higher for the oral cavity than for many other body sites. This reflects both the ease of access to samples for analysis and the great interest shown in the oral microbiota over time due to its role in two of the most common infections of humans, caries and periodontal diseases (Fitzgerald and Keyes, 1960; Bradshaw et al,. 2013). The main species on supragingival plaque belong to Streptococcus (mainly S.

sanguis, S. oralis and S. mitis), Neisseria, Haemophilus and Actinomyces

(Marsh and Devine, 2011). Recent studies of salivary microbiota in adults have revealed a characteristic microbial community with certain stability and a persistence of subject-specificity (Lazarevic et al., 2010; Stahringer et al., 2012; Romano-Keeler et al., 2014). Despite the variety of habitats and microbial communities in the oral cavity, there are species common to all sites that have been reported to belong to the genera

Streptococcus, Abiotrophia, Gemella, Granulicatella and Veillonella

I.1.2.3 Intestinal microbiota

The intestinal microbiota is a complex and dynamic community that contains a diverse range of microorganisms. The different regions of the intestinal tract vary widely in terms of transit time, pH, oxygen and nutrient availability, host secretions, mucosal surfaces and interactions with the immune system, all of which affect microbial composition. Metagenomic studies have shown that the majority of gut microbiota sequences belong to bacteria (Eckburg et al., 2005; Qin et al., 2010; Arumugam et al., 2011). Currently, only a small minority of these bacteria -over 400 species- has been successfully isolated and cultured (Eckburg et al., 2005; Rajilić-Stojanović et al., 2007). More recently, culture-independent techniques have indicated that well over 1000 species are capable of colonizing the human gut (Huttenhower et al., 2012). Despite the high density of bacteria in the human gut and their complexity, diversity at the division level is low. Firmicutes, Bacteroidetes and Actinobacteria represent the dominant phyla, being 60-90% of the total population (Neish, 2009; Walker at el., 2011). The rest of the dominating bacterial phyla correspond to Proteobacteria, Verrucomicrobia and Fusobacteria (Eckburg et al., 2005; Tap et al., 2009; Arumugam et al., 2011). Within the Firmicutes phylum, 95% of the phylogenetic types are members of the Clostridia class, and much of them are related to butyrate‐producing bacteria, all of which fall within the clostridial clusters IV, XIVa, and XVI (Eckburg et al., 2005; Tap et al., 2009). Other bacteria commonly found in the human gut at genus level are Bacteroides, Faecalibacterium,

Bifidobacterium, Roseburia, Alistipes and Lactobacillus that vary

depending on age and individuals (Arumugam et al., 2011; Mueller et al., 2006; Frank et al., 2007). Although there is a huge inter-individual variability in the intestinal microbiota composition, it has been suggested that the microbiota of most individuals can be categorized into one of three variants or ‘‘enterotypes’’ clusters, that are not nation or continent specific, dominated by Bacteroides, Prevotella and Ruminococcus,

respectively (Arumugam et al., 2011). These clusters may in fact be more appropriately characterized as a ratio of the abundance of Bacteroides and Prevotella, with the Ruminococcus enterotype folded into the

Bacteroides group (Wu et al., 2011). These broad patterns were strongly

associated with long-term diets, particularly protein and animal fat (Bacteroides) versus carbohydrates (Prevotella) (Wu et al., 2011); it remains to be seen how important they are in understanding overall microbial community functions. More recent studies, however, suggested rethinking about the term enterotypes, as most human gut microbiome data collected to date support continuous gradients of dominant taxa rather than discrete enterotypes; furthermore, an individual’s enterotype can be highly variable (Jeffery et al., 2012; Knights et al., 2014).