Integrated metatranscriptomics and metaproteomics for the characterization of bacterial microbiota in unfed Ixodes ricinus

Abstract

An innovative metaomics approach integrating metatranscriptomics and metaproteomics was used to characterize bacterial communities in the microbiota of the Lyme borreliosis spirochete vector, Ixodes ricinus (Acari: Ixodidae). Whole internal tissues and salivary glands from unfed larvae and female ticks, respectively were used. Reused I. ricinus RNA-sequencing data for metranscriptomics analysis together with metaproteomics provided a better characterization of tick bacterial microbiota by increasing bacteria identification and support for identified bacteria with putative functional implications. The results showed the presence of symbiotic, commensal, soil, environmental, and pathogenic bacteria in the I. ricinus microbiota, including previously unrecognized commensal and soil microorganisms. The results of the metaomics approach may have implications in the characterization of putative mechanisms by which pathogen infection manipulates tick microbiota to facilitate infection. Metaomics approaches integrating different omics datasets would provide a better description of tick microbiota compositions, and insights into tick interactions with microbiota, pathogens and hosts.

RETRACTED ARTICLE: Metagenomics for taxonomy profiling: tools and approaches

“…Recently, metaproteomics and metabolomics have emerged as effective devices for the characterization of energetic host-microbiome interactions, especially in combination with metagenomics and metatranscriptomics approaches [80]. Metaproteomics can be utilized to consider protein expression from blended cultures and thus this approach can supply coordinate to prove the metabolic and physiological exercises occurring in a given framework (Figure 3).…”

Biotic and abiotic factors shape the microbiota of wild‐caught populations of the arbovirus vectorCulicoides imicola

“…All the assembly metrics are provided in the Supplementary file 1: Table . Metagenome relative abundance at different taxonomic levels was obtained by taking the number of count reads or identifications assigned to each identified sequence, and normalized against the total number of identifications (Hernández‐Jarguín et al, ) using metaphlan (Segata et al, ; Truong et al, ), and coverage analysis with sam tools (https://samtools.sourceforge.net) (Supplementary file 2: Dataset S1). metaphlan was used to assign sequences to particular taxa using default parameters that included blastn default e ‐value threshold of 1 × 10 −6 , uclust nucleotide identity threshold of 75%, and rejected sequences as core genes if its homology pattern in the clade deviated from the expected baseline misannotation error rate with confidence greater than 95%.…”

When bacteria meet mitochondria: The strange case of the tick symbiont Midichloria mitochondrii †

“…Midichloriae have been found in several tick species, including I. ricinus (Beninati et al, ), Rhipicephalus bursa (Epis et al, ), Amblyomma maculatum (Budachetri et al, ), among others (Cafiso et al, ; Epis et al, ). These bacteria are among the most abundant members of the microbiome in multiple tick species (Di Lecce et al, ; Duron et al, ; Hernández‐Jarguín, Díaz‐Sánchez, Villar, & de la Fuente, ), suggesting a potentially mutualistic relationship (Lo et al, ) and mechanisms to avoid immune recognition by the host.…”