Here, we present the Comparative Metatranscriptomic Workflow (CoMW) implemented using the de novo assembly-based approach, standardized and validated for functional annotation and quantitative expression analysis. Benchmarking provides a critical view of the efficiency and precision of different workflows, and use of simulated communities for benchmarking enables the analysis to be independent of experimental variation and biases.

Thus, standardization of computational analysis is necessary to enable further propagation of metatranscriptomics approaches and their integration into microbial ecology research. Because no independent and direct comparison between them has been performed, various metatranscriptomics analysis approaches may at times produce inconsistent observations, even if identical databases are used in the analysis. The choice of either of these 2 alternatives for metatranscriptomics analyses may depend on lack of thorough comparisons. to analyse metatranscriptomics datasets also aligns short reads directly to a protein database before annotation. Similarly, an open source pipeline developed by Martinez et al. , aligning short reads to reference genomes of lactic acid bacterial strains associated with the kimchi microbial community. The assembly-free approach has instead been used by, e.g., Jung et al. An open-source pipeline, IMP also uses this approach in integrated metagenomic and metatranscriptomic analyses. Various studies have used either of these 2 general approaches. Typically, short sequence reads are used, which can be either individually aligned directly to external reference databases (hereafter “assembly-free”) or assembled into longer contiguous fragments (contigs) for alignment (hereafter “assembly-based”).

To date, several studies have used various analytic workflows. However, curation and annotation of these complex data has emerged as a major challenge. Using high-throughput sequencing techniques such as Illumina, metatranscriptomics offers a non-PCR–biased method for looking at transcriptional activity occurring within a complex and diverse microbial population at a specific point in time. The method is typically used to identify, quantify, and compare the functional response of microbial communities in natural habitats or in relation to environmental or physio-chemical impacts. Metatranscriptomics has also been used to study the functional human gut microbiota. applied metatranscriptomics to evaluate root microbiome response to soil contamination. The method has been applied to study the microbial activity in thawing permafrost and the related biogeochemical mechanisms contributing to greenhouse gas emissions, and Gonzalez et al. Metatranscriptomics provides an unprecedented insight to complex functional dynamics of microbial communities in various environments. We evaluate their accuracy in precision and recall using generic and specialized hierarchical protein databases.

We also compare CoMW (assembly-based implementation) with an assembly-free alternative workflow, using simulated and real-world metatranscriptomes from Arctic and temperate terrestrial environments. Metatranscriptomics typically uses short sequence reads, which can either be directly aligned to external reference databases (“assembly-free approach”) or first assembled into contigs before alignment (“assembly-based approach”). Here, we present a de novo assembly-based Comparative Metatranscriptomics Workflow (CoMW) implemented in a modular, reproducible structure. By assessing the genes expressed, metatranscriptomics provides an understanding of the interactions between different major functional guilds and the environment. Metatranscriptomics has been used widely for investigation and quantification of microbial communities’ activity in response to external stimuli.

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