TIPP2: metagenomic taxonomic profiling using phylogenetic markers

Abstract

Motivation Metagenomics has revolutionized microbiome research by enabling researchers to characterize the composition of complex microbial communities. Taxonomic profiling is one of the critical steps in metagenomic analyses. Marker genes, which are single-copy and universally found across Bacteria and Archaea, can provide accurate estimates of taxon abundances in the sample. Results We present TIPP2, a marker gene-based abundance profiling method, that combines phylogenetic placement with statistical techniques to control classification precision and recall. TIPP2 includes an updated set of reference packages and several algorithmic improvements over the original TIPP method. We find that TIPP2 provides comparable or better estimates of abundance than other profiling methods (including Bracken, mOTUsv2, and MetaPhlAn2), and strictly dominates other methods when there are under-represented (novel) genomes present in the dataset. Availability and Implementation The code for our method is freely available in open source form at https://github.com/smirarab/sepp/blob/tipp2/README.TIPP.md The code and procedure to create new reference packages for TIPP2 are available at https://github.com/shahnidhi/TIPP_reference_package Supplementary information Not available online.

Critical Assessment of Metagenome Interpretation: the second round of challenges

“…DUDes v.0.08 and LSHVec v.gsa had high purity, while Centrifuge v.1.0.4 beta, DUDes v.cami1, TIPP v.4.3.10 (ref. 55 ) and TIPP v.cami1 high completeness.…”

<strong></strong> Recent Progress on Methods for Estimating and Updating Large Phylogenies

“…The methods described in this section are also relevant to understanding microbial diversity: given a sequence, placing it into a taxonomy makes it possible to taxonomically characterize the sequence, and so also enables an assessment of microbial diversity in a population (Nguyen et al, 2014;Segata et al, 2013;Czech et al, 2020;Shah et al, 2021). This approach is particularly relevant for characterizing novel sequences (i.e., sequences that are not in public databases) and the accuracy of the taxonomic assignment improves on larger trees (Shah et al, 2021). Therefore, methods for placing sequences into large trees also have utility for assessment of microbial diversity.…”

Tapping the Role of Microbial Biosurfactants in Pesticide Remediation: An Eco-Friendly Approach for Environmental Sustainability

“…Quite a few bioinformatic pipelines have been developed ( Table 2 ), such as QIIME (quantitative insights into microbial ecology), PICRUSt (phylogenetic investigation of communities by reconstruction of unobserved states), MG-RAST (metagenomic rapid annotations using subsystems technology), Mothur, CLARK, MetaPhlAn2 (metagenomic phylogenetic analysis), MICCA, Metaphyler, MOCAT 2 , TIPP2, mOTU sv2 , Bracken, etc., for sequence classification and taxonomic profiling of metagenomic data ( Liu et al, 2010 ; Albanese et al, 2015 ; Truong et al, 2015 ; Douglas et al, 2020 ; Singh et al, 2020b ). Metagenomics coupled with in-silico bioinformatic tools or repositories such as KEGG (Kyoto encyclopedia of genes and genomes), COG (clusters of orthologous groups), EAWAG-BBD pathway prediction system, enviPath, BIOWIN, etc., helps in predictive degradation of pesticides along with the metabolite/biosurfactant identification involved in degradation mechanism ( Awasthi et al, 2020 ; Rodríguez et al, 2020 ; Shah et al, 2021 ; Singh et al, 2021 ). A repository named BioSurfDB (biosurfactant degradation database) consists of about 1,077 microbes, 3,763 genes, 3,430 proteins, and 47 detailed bioremediation pathways using biosurfactants ( Araújo et al, 2020 ; Meenatchi et al, 2020 ; Kumari and Kumar, 2021 ).…”