**Gut Microbiota in Disease Diagnostics**

Knut Rudi1,2,3 and Morten Isaksen1

*1Genetic Analysis AS, OSLO 2The Norwegian University for Life Sciences, Ås 3Hedmark University College, Hamar Norway* 

### **1. Introduction**

100 New Advances in the Basic and Clinical Gastroenterology

Zulkifli, I., Abdullah, N., Azrin, N. & Ho, Y. (2000). Growth performance and immune

Vol. 41, No. 5, pp. 593-597, ISSN 0007-1668

response of two commercial broiler strains fed diets containing Lactobacillus cultures and oxytetracycline under heat stress conditions. *British Poultry Science*,

> A substantial amount of scientific documentation is mounting for the significance of the gastrointestinal microbiota (gut or GI microbiota) on human health. In addition to the obvious connection between the gut microbiota and inflammation in the colon (leading to IBD, IBS and possibly colon cancer), recent articles have highlighted the not-so-obvious connection between the gut microbiota and the brain (Heijtz et al., 2011)) and cardiovascular system (Wang et al., 2011).

> Despite several major breakthrough discoveries of the importance of the gut microbiota in human health, this information has not yet been transformed into diagnostic or therapeutic approaches. A major bottleneck in the gut microbiota diagnostics is the reproducibility and throughput of the analytical approaches used.

> Since we do not know the growth conditions for most gut bacteria, traditional cultivation based analysis of bacteria cannot be used for a comprehensive overview of the gut microbiota. Currently, quantitative PCR are quite extensively being used to detect the presence of specific pathogens. However, since the gut microbiota is complex and contains hundreds of different microbes, such technology does not hold the promise to be used as a general analysis tool to monitor changes in the gut microbiota that affect health conditions. The current focus in human gut microbiota screenings are based on explorative deep sequencing. It is expected that it will take considerable time and further development before sequencing of the gut microbiota could become a routine diagnostic tool. However, since the human gut microbiota is getting more thoroughly characterized, it is time to look for more targeted approaches rather than the current explorative screenings.

> The most widely applied targeted approach to describe microbial diversity are by probes targeting the gene encoding 16S ribosomal RNA. This gene is ancient, universally distributed and comprise highly conserved sequence domains interspersed with more variable regions (Woese, 1987). The conserved regions provide information for classification of higher taxa, while the variable regions can be used for differentiation between closely related species. An average bacterial 16S rRNA molecule has a length of approximately 1 500 nucleotides, making it experimentally manageable by e.g. PCR amplification.

Gut Microbiota in Disease Diagnostics 103

this inflation of diversity, but it is still uncertain if the number of different Operational Taxonomic Units (OTUs) obtained by next generation sequencing techniques gives a correct

Perhaps the largest challenge in gut microbiota diagnostics is the establishment of the correlation between microbiota patterns and disease. Since the characterization of the gut microbiota is in its infancy, there are not many diseases that have actually been characterized with respect to specific dysbiosis of the gut microbiota. Furthermore, since the analysis represent patterns rather than single bacteria, new diagnostic principles must also

Diagnostic approaches related to dysbiosis of the gut microbiota have until now been dominated by culture dependent techniques which only detect a minor portion of the true diversity. Doctors used to such techniques may find it challenging to adapt knowledge about non-cultivable bacteria in their diagnostics because that would include bacteria that

We have for instance found that the clostridal family Lachnospiraceae is the most stable and dominant phylogroup in the human gut (Sekelja et al., 2011).This phylogroup has been overlooked by the traditional cultivation dependent techniques, probably because it is strictly anaerobic and that it has special growth requirements that are difficult to simulate

A long standing debate is how well functionality of bacteria in the gut correlates to phylogeny. There are recent reports suggesting that the function of gut bacteria is a relatively stable feature, while the microbiota composition is unstable (Turnbaugh et al.,

Although functions cannot directly be deduced from the gut microbiota 16S rRNA gene analyses, correlations between gut microbiota phylogenetic composition and function can be established. We have recently addressed this issue by mapping functions onto a phylogenetic map as illustrated in Figure 1. As seen in this figure, there are good correlations between functions and phylogeny, with different functions being clustered in

The take home message from this analysis is that the phylogenetic framework can be used to deduce the probability of functions in the gut microbiota, and aid in identifying functions through other targeted approaches. Still, however, our knowledge about the correlations between function and phylogeny is limited. The current major genomic sequencing efforts will aid in these investigations. It will be particularly interesting to determine which

For genes located on mobile elements, such as those encoding antibiotic resistance, an important aspect would be to determine the host range of the mobile elements. For instance, given that there are antibiotic resistance genes present on mobile elements in the commensal microbiota with a host range that include pathogens, there will be a severe risk that the

functions follow a phylogenetic distribution pattern, and which do not.

antibiotic resistance genes can be transferred to the pathogen.

representation of the actual number of different bacteria present in the sample.

be implemented.

on plates.

2009).

different phylogroups.

they are not familiar with.

**3. Function vs phylogeny of gut bacteria** 

The first step in 16S rRNA gene microbiota analyses is to purify DNA from all bacteria present in a sample without introducing bias due to e.g. differential lysis or recovery. Subsequent to DNA purification, all bacterial 16S rRNA genes in the samples are amplified using primers targeting generally conserved regions in the 16S rRNA gene. The ratio between 16S rRNA gene copies for different bacteria is (in theory) conserved during the PCR amplification process.

Currently the most widely used approach to analyze 16S rRNA gene diversity is through next generation sequencing (Kunin et al 2010). The depth of the information that can be obtained form such sequencing efforts are dependent on the number of reads that are being done.

An alternative approach is the use of high-density microarrays based on 16S rRNA sequence variations. These approaches are explorative, and intended for discovery rather than diagnostics. A major challenge with traditional 16S rRNA gene microarrays is probe specificity, and cross-reactivity between closely related species (Cox et al 2010). For microarrays, this challenge has recently been addressed by tilling probes covering the variable region of the 16S rRNA gene (Rajilic-Stojanovic et al 2009). The principle by tilling is that a large number of overlapping probes cover the region of interest, with the combined probe signals providing a relatively good signal-to-noise ratio. Both for next generation sequencing and microarray analysis, a comprehensive data analysis of the information is required in order to obtain interpretable results.

A more direct approach for characterizing the gut microbiota is the use of highly specific single nucleotide primer extension (SNuPE) probes (Eggesbo et al 2011).The high specificity of the SNuPE assay is obtained by DNA polymerase based incorporation of a labeled dideoxynucleotide (Syvanen et al 1990). The SNuPE probes are constructed so that the probes hybridize adjacent to discriminative gene positions. If the target bacterium is present, a labeled dideoxynucleotide is incorporated by the polymerase.

A technology platform have been developed that can readily be applied to analyze the gut microbiota based on the SNuPE principle. The method – called GA-map™ (Genetic Analysis' Microbiota Analysis Platform) - has already demonstrated its usefulness in applications for assessing various disease states based on analysis of the composition of the gut microbiota.

Here, we discuss the possibility of using a novel comprehensive targeted approach for quantifying the inhabitants of the human gut microbiota in disease diagnostics.
