El equipo MAS-100 N

Direct observation of predation of insect in bats is very difficult (Clare et al., 2009). Traditional analysis of bat diets has relied heavily on

microscopic analysis of digested insect fragments found in guano (Clare et al., 2011). However, bats thoroughly masticate and digest their prey, often discarding the hard to digest fragments such as the carapace or elytra (Bohmann et al., 2011, Rabinowitz and Tuttle, 1982, Zeale et al., 2011). This increases the likelihood of misidentification, and over representation of the tougher remains that were not discarded.

Identifications made in this manner are rarely more specific than order level (Clare et al., 2009).

Other methods used to measure bat diets include the dissection of

stomach contents, the identification of discarded prey remains, and stable isotope analysis. These methods are discussed in detail in chapter two.

1.4.1. Using environmental DNA sequencing

With the development of next generation ‘high throughput’ DNA

sequencing methods, it has become possible to generate millions of DNA sequence reads in parallel, dramatically reducing time and costs. This has been widely exploited for studying environmental DNA (eDNA) from a variety of sources (Bohmann et al., 2011). Increasingly, molecular

metagenomic techniques are used in analysing the diets of vertebrates.

1.4.2. Metagenomics

There are two main approaches used in metagenomics. The first is metabarcoding (sometimes referred to as amplicon metagenomics), PCR directed sequencing is used to target regions which are conserved

enough across the organisms of interest to amplify using universal primers, but which are variable enough to allow (ideally) species level identification. Additionally, the target chosen often has a high copy

number within each cell, such as is the case with plastid or mitochondrial targets. 16S ribosomal DNA (rDNA) amplicons have been widely used in the identification of a range of un-culturable prokaryotes (Wang and Qian, 2009). However, increasingly, a wider range of amplicon targets are being used, allowing eukaryotic targets to be studied alongside prokaryotic species. One example is cytochrome c oxidase subunit 1 (CO1) which is used by the Barcode Of Life Database (Ratnasingham and Hebert, 2007).

The metabarcoding approach can provide a high resolution picture of the species present in the sample, although there are a number of key

limitations. First is the assumption that the primers used to amplify the target DNA will amplify only the appropriate DNA, and will amplify all of

12

the target species equally. This is particularly an issue where proportions of sequences classified to an organism is used as a proxy for the

proportion of said organism’s DNA in the sample, highlighting the

requirement for good PCR primer design. The issue with the design of PCR primers is that they require some a-priori knowledge of the target

organisms expected to be present in the sample; ideal primers will amplify all of the (for example) arthropod DNA from a sample, and nothing else, to maximise the efficiency of the sequencing. However, primers are designed based on knowledge of target sequences from sequence databases, and poorly studied taxa may be under represented in the databases. This means that these taxa can be missed during the primer design process, and as a result the primers may fail to amply DNA from these taxa despite their presence in the sample, leading to issues of bias. Alternatively, these primers may spuriously amplify non-target DNA. These issues can be further confounded by stochastic errors introduced during the PCR enrichment, whereby some PCR templates may be

preferentially amplified over others (Best et al., 2015). The reference DNA sequence database (such as the NCBI’s nt database (Altschul et al., 1990)) used to assign taxonomic classifications to the output sequences can have large impacts on the success of taxonomic classifications; using a patchy database in which many taxa are not represented will not only increase the chance of sequences being unassigned, but will increase the likelihood of sequences being misassigned (Smith et al., 2015).

Furthermore, where poor quality DNA is used, fragmentation of the target region can cause PCR failure, resulting in a type II error.

The second major approach used is shotgun metagenomics. This is the sequencing of DNA in a sample without selecting for a particular target region. As a result, the endogenous DNA of the organisms of interest, such as bat prey, can be low in comparison to other DNA sources, depending on the type of sample used. Additionally, the database coverage is typically far more restricted than those for amplicon targets for any one genomic region. This causes a greater risk of

misassignments of sequences to over-represented (e.g. model organism) sequences in the database. However, without the need for the a-priori

knowledge required for primer design, some ascertainment biases are avoided. Additionally, due to the use of fewer rounds of PCR in the sample preparation process used for preparing shotgun metagenome, there is less PCR stochastic bias. Shotgun metagenomics can also be used to provide metadata for the target data, such as gut microbiome data when studying diet. Direct sequencing allows identification of organisms which cannot be cultured, or cannot be distinguished from other species by using targeted sequencing such as 16S rDNA (Tringe et al., 2005). A major advantage of this approach is that it exploits more of the DNA laid down by the organisms than barcodes, and so has the potential to be more sensitive than metabarcoding especially in degraded samples (Smith et al., 2015). This is particularly true where the barcodes used cannot distinguish between taxa at a species level due to

ambiguities in the sequences (Srivathsan et al., 2015). The development of methods that account for patchy database representation is of key importance when working with metagenomic data, and will be discussed at greater length in chapter three.

1.4.3. Applying faecal metagenomics to study mammalian diets

Metagenomics using faeces often focuses on the microbiome

(Handelsman, 2004, Riesenfeld et al., 2004). Using many standard library preparation methods (such as Illumina TruSeq) bacterial DNA can easily be studied. Of the viruses, only dsDNA can be prepared without the further processing required for ssDNA and RNA viruses.

Increasingly faecal metagenomics is being used in order to study eukaryotic DNA to measure the diets of mammals, birds and reptiles (Jedlicka et al., 2013, Deagle et al., 2005, Tollit et al., 2009, Pompanon et al., 2012). A number of bat diets have also been characterised in this way, demonstrating the applicability of faecal metagenomic methods for studying bat diets (Bohmann et al., 2011, Razgour et al., 2011, Zeale et

14

al., 2011, Clare et al., 2009) amongst a number of other studies. However, to date, all studies have taken a metabarcoding approach, many of which used the primer set designed by Zeale et al. (2011). Furthermore, the diets of all of the different bat species present in Great Britain have not been comprehensively studied. Here we employ both metagenomic (metabarcoding and shotgun metagenomics) approaches to characterise the diets of Great British bats in an unbiased manner.

1.4.4. Technical considerations when working with DNA from guano

DNA from guano is typically of low quality; it may have a very low concentration, and, due to the degradation of DNA post cell-death, is often highly fragmented (Deagle et al., 2006). This can lead to issues related to contamination, allelic dropout, false alleles, or to the failure of the PCR primers to anneal or extend on the target DNA (Pompanon et al., 2005, Puechmaille et al., 2007). Additionally, there may be exogenous and endogenous nucleases, as well as components of bat guano, such as bile salts, complex polysaccharides, and urea, which may act as PCR inhibitors (Idaghdour et al., 2003, Khan et al., 1991, Lantz et al., 1997, Monteiro et al., 1997).

The field of aDNA research has been instrumental in developing methods to avoid contamination, and to deal with other technical challenges arising from inhibition, fragmentation and other damage such as cytosine

deamination (Kistler et al., 2015, Pääbo et al., 2004, Smith et al., 2003). Fragmented DNA with low endogenous concentration and target copy number, such as the DNA from guano, is vulnerable to contamination. PCR contamination is likely to be the most problematic as it could give confounding or false positive result, particularly where PCR products are from potential target organisms. Consideration of these factors is crucial when working with DNA from guano and must be considered as the field of faecal metagenomics develops. Methods used to address these issues will be discussed in chapters three and four, and appendix A.1.

To address the problems of DNA fragmentation, primers used to identify the bat species, and those for arthropod barcoding, have short amplicons and amplify mitochondrial genes which have a high copy number which increases the likelihood of an intact target region, thus increasing the likelihood of successful amplification. Additionally, mitochondrial genes have a higher mutation rate than genes located within nuclear DNA, enhancing their power to discriminate between species. Furthermore, these PCR targets are well represented on the databases such as GenBank (Altschul et al., 1990, Benson et al., 2000, Ratnasingham and Hebert, 2007). Primers must be able to amplify the range of target species required. Where the target gene is not highly conserved across the target species, a mixture of degenerate primers (i.e. some positions on the oligonucleotide may have one or more of the possible bases represented) may be used.