The electronic tree of life (eToL): a net of long probes to characterize the microbiome from RNA-seq data

Abstract

Background Microbiome analysis generally requires PCR-based or metagenomic shotgun sequencing, sophisticated programs, and large volumes of data. Alternative approaches based on widely available RNA-seq data are constrained because of sequence similarities between the transcriptomes of microbes/viruses and those of the host, compounded by the extreme abundance of host sequences in such libraries. Current approaches are also limited to specific microbial groups. There is a need for alternative methods of microbiome analysis that encompass the entire tree of life. Results We report a method to specifically retrieve non-human sequences in human tissue RNA-seq data. For cellular microbes we used a bioinformatic 'net', based on filtered 64-mer sequences designed from small subunit ribosomal RNA (rRNA) sequences across the Tree of Life (the 'electronic tree of life', eToL), to comprehensively (98%) entrap all non-human rRNA sequences present in the target tissue. Using brain as a model, retrieval of matching reads, re-exclusion of human-related sequences, followed by contig building and species identification, is followed by confirmation of the abundance and identity of the corresponding species groups. We provide methods to automate this analysis. The method reduces the computation time versus metagenomics by a factor of >1000. A variant approach is necessary for viruses. Again, because of significant matches between viral and human sequences, a 'stripping' approach is essential. Contamination during workup is a potential problem, and we discuss strategies to circumvent this issue. To illustrate the versatility of the method we report the use of the eToL methodology to unambiguously identify exogenous microbial and viral sequences in human tissue RNA-seq data across the entire tree of life including Archaea, Bacteria, Chloroplastida, basal Eukaryota, Fungi, and Holozoa/Metazoa, and discuss the technical and bioinformatic challenges involved. Conclusions This generic methodology is likely to find wide application in microbiome analysis including diagnostics.

Establishment of a consensus protocol to explore the brain pathobiome in patients with mild cognitive impairment and Alzheimer's disease: Research outline and call for collaboration

“…A recently reported development is the use of longer probes: the electronic Tree of Life (eToL) method uses a net of much longer (64-mer) probes, prefiltered against human sequences, to identify (by homology; non-exact matches are detected) all non-human rRNA sequences in a given dataset. The method may be less prone to false positives because it refilters matches against human sequences and is relatively insensitive to single-nucleotide changes [54,55], and is being explored as a potential diagnostic method on patient samples.…”

“…Over recent decades multiple studies on post-mortem AD brain have reported that diverse pathogens are present, ranging from bacteria to fungi to viruses [45][46][47][48][49][50][51][52][53]. Archaea, Chloroplastida, and Holozoa have also been reported in brain [54,55]. There are multiple potential routes of entry to the brain (Figure 2).…”

“…Reverse transcription (RT) of total cellular RNA into cDNA provides a new substrate for PCR amplification. If primers corresponding to rRNA are employed, this method can take advantage of the increased copy numbers associated with rRNA -that can be present in several thousand copies per microbial cell (reviewed in [54]). The method is thus likely to be more sensitive than DNA-based PCR.…”

The Contribution of the Human Oral Microbiome to Oral Disease: A Review

“…The use of eTOL is especially important for viral sequences due to significant homology between human sequences. This can be combatted using a ‘stripping’ method where similar sequences are removed from the viral genome before characterization [ 67 ].…”

The remarkable complexity of the brain microbiome in health and disease

“…We therefore developed a different approach that is both less resource-intensive and neutral with regard to the identity of the species detected. The electronic tree of life (eToL) method is based on a net of over 1000 64-mer probes designed from the 16S/18S rRNA sequences of all known branches of life, including archaea, bacteria, chloroplastida, amoeobozoa, basal eukaryota, fungi, and metazoa; the technical details of this method were reported previously (Hu et al 2022). We now apply this methodology to the study of the human brain microbiome in health and disease.…”