A novel approach, based on BLSOMs (Batch Learning Self-Organizing Maps), to the microbiome analysis of ticks

Abstract

Ticks transmit a variety of viral, bacterial and protozoal pathogens, which are often zoonotic. The aim of this study was to identify diverse tick microbiomes, which may contain as-yet unidentified pathogens, using a metagenomic approach. DNA prepared from bacteria/archaea-enriched fractions obtained from seven tick species, namely Amblyomma testudinarium, Amblyomma variegatum, Haemaphysalis formosensis, Haemaphysalis longicornis, Ixodes ovatus, Ixodes persulcatus and Ixodes ricinus, was subjected to pyrosequencing after whole-genome amplification. The resulting sequence reads were phylotyped using a Batch Learning Self-Organizing Map (BLSOM) program, which allowed phylogenetic estimation based on similarity of oligonucleotide frequencies, and functional annotation by BLASTX similarity searches. In addition to bacteria previously associated with human/animal diseases, such as Anaplasma, Bartonella, Borrelia, Ehrlichia, Francisella and Rickettsia, BLSOM analysis detected microorganisms belonging to the phylum Chlamydiae in some tick species. This was confirmed by pan-Chlamydia PCR and sequencing analysis. Gene sequences associated with bacterial pathogenesis were also identified, some of which were suspected to originate from horizontal gene transfer. These efforts to construct a database of tick microbes may lead to the ability to predict emerging tick-borne diseases. Furthermore, a comprehensive understanding of tick microbiomes will be useful for understanding tick biology, including vector competency and interactions with pathogens and symbionts.

Figure 1

Workflow for bacterial/archaeal purification and metagenomic analysis. The present strategy employed a process for purifying of bacteria/archaea, which comprised centrifugation, DNase treatment and filtration, to enrich bacterial/archaeal cells from tick homogenates prior to whole-genome amplification and pyrosequencing.

Figure 2

Kingdom classification of the metagenomic sequences from each tick pool. Sequence reads longer than 300 bp were classified into bacteria/archaea, eukaryotes, viruses, mitochondria or chloroplasts using Kingdom-BLSOM. The percentage of sequences in each category is provided. The pool ID is shown in the centre of each pie chart.

Figure 3

Phylum classification of the metagenomic sequences from each tick pool. Sequence reads classified as bacterial/archaeal using Kingdom-BLSOM were further classified at the phylum level using Bacteria/Archaea-BLSOM. Thirty-three phyla are indicated by different colours. The pool ID is shown on the left of the graph.

Figure 4

Sequences associated with virulence-associated factors. Sequences associated with putative virulence-associated factors were identified by BLASTX against the MvirDB database (Zhou et al., 2007), applying a cut-off value of 1e-5. The resulting data are shown in seven categories denoted by different colours. The numbers at the bottom of the graph indicate the number of sequences. The numbers in parentheses indicate the percentage of total sequence reads. The pool ID is shown on the left of the graph.