Large-Data Omics Approaches in Modern Remediation
Abstract
Background
![](/cms/10.1061/(ASCE)EE.1943-7870.0002042/asset/20801c14-3cc3-4cf1-96e1-befc21ae49b3/assets/images/large/figure1.jpg)
Using Omics to Track, Identify, and Assess the Extent of Site Contamination
Integration of Omics in Remediation
Omics in Electron Donor Injections
Interpretation of Omics Data
Approach | Focus | Methods | Advantages | Limitations |
---|---|---|---|---|
Genomics | Microbial community assessment, taxonomy classification, phylogeny | Amplicon sequencing: 16S, ITS, 18S | • Quick analysis • Chip methods have low biomass and abundance requirements (Liu et al. 2021) | • PCR amplification and primer bias • Chip-based methods only identify preselected organisms |
PhyloChip, GeoChip | ||||
Metagenomics | Functional potential, bioprospecting, novel gene annotation | Shotgun sequencing | • Can obtain whole genomes • Novel gene identification • Can assess functional potential if larger contigs are assembled | • Expensive • Complicated analysis • Data quality is highly dependent on sequencing depth (Hazen et al. 2013) |
Proteomics | Complete protein profile, assimilation pathways, post and substrate utilization | HP-LC/GC, mass spectrometry (MS), X-ray crystallography | • Versatile tool for differential expression • Can quantify abundance data for community • Scope for novel protein discovery | • Ambiguity of composition results depends on accurate measurement of peptide mass • Reproducibility and specificity |
Lipidomics | Quantitative profile of the lipids in a biological system, species identification | GC/LC-MS, NMR | • Biomarker discovery • Community profiling • Functional grouping | • Complicated analysis • Requires extensive computational resources |
Metabolomics | Total metabolite profile with respect to fluctuating environmental stress, | HP-LC, MS, FT-IR | • Allows quantification of cellular regulation in response to environment • Evaluation of enzymatic activity | • Highly specialized • Expensive • Measurements are nonquantitative • Requires extensive computational analysis |
Transcriptomics | Microbial activity, gene expression profiling, novel transcript prospecting | RNA-seq, DNA microarray, qPCR and RT-PCR | • Able to distinguish between active and sedentary community members • Able to provide transcript level resolution | • Sample collection is tedious • Expensive to sequence • Risk of contamination within the microbiome |
Note: FT-IR = Fourier-transform infrared; GC = gas chromatography; HP-LC = high performance liquid chromatography; ITS = internal transcribed spacer; LC = liquid chromatography; NMR = nuclear magnetic resonance; qPCR = quantitative polymerase chain reaction; RNA-seq = ribonucleic acid sequencing; and RT-PCR = reverse transcription polymerase chain reaction.