Table 6 Advantages and constraints of common techniques in omics studies
From: Increasing the production of the bioactive compounds in medicinal mushrooms: an omics perspective
Omics study | Techniques exploited in omics studies | Advantages | Constraints | References |
|---|---|---|---|---|
Genomics | Genome mining | •Inexpensive •Can be easily performed in laboratories •Does not need any special skills •Anticipates the chemical structures of bioactive metabolites | •Challenges in formulating the chemical structures •Unable to anticipate the biological activities of bioactive metabolites | [254] |
Transcriptomics | RNA-Seq | •No need for probes that are transcript-specific or species-specific •Ability to identify new transcripts, single nucleotide variants, gene fusions, and indels (small insertions and deletions) •Expression quantification across a wider dynamic range (> 105) •Acting more specific and sensitive in contrast with Microarray technology •Easy identification of uncommon and low-abundant transcripts, single-nucleotide polymorphisms, uncommon mutations, formerly unknown gene isoforms, regulatory micro-RNAs, and microbial RNAs | •Computational challenges in the precise annotation of sequences and interpreting information •Effects of biases introduced in the course of cDNA library constitution and sequence alignment on transcript quantitation •Absence of standardization between sequencing platforms and read depth •Considerable start-up costs | [178,179,242,243,244,245,246,247,248,249,250,251,252,253,254] |
Microarray technology | •Parallel quantification of thousands of genes from various samples •Easy to use •No need for large-scale DNA sequencing | •Requiring species- or transcript-specific probes •Limited expression measurement at the low and high end by background and signal saturation, respectively •Requiring the physical disruption of cells •Lack of strict standards for data collection, analysis, and validation •Each microarray can only present data about the genes that are included on the array | ||
Proteomics | 2-dimensional gel electrophoresis (2-DE) | •The most powerful and commonly •Used technique for investigating fundamental physiological subjects in fungi •Able to separate several thousand different proteins in one gel •Demonstrating isoforms or post-translational modifications | •Difficulty in achieving membrane, cell wall, and small molecular weight (< 10 kDa) proteins besides very low and very high abundant proteins •Reproducibility concerns •Time-consuming and labor-intensive | |
Difference gel electrophoresis (DIGE) technology | •A gel-based method for relative protein quantification in complex protein samples •Providing more reproducibility and sensitivity over traditional 2D-PAGE gels for differential quantitative investigation of protein expression •Providing a wider dynamic range compared to traditional gel staining •Reducing gel-to-gel variations | •Expensive and difficult to execute •Difficulty in separating hydrophobic proteins •It might solely be utilized when the proteins contain available lysine (for minimal labeling) or cysteine residues (for saturation labeling) | ||
iTRAQ labeling technique combined with two-dimensional liquid chromatography-tandem mass spectrometry (2D LC − MS/MS) | •Powerful analysis of chronological changes of proteomic profiles and investigating candidate genes and signaling pathways related to complex developmental processes of filamentous fungi •High sensitivity and specificity •Beneficial for the identification and quantification of proteins across different isoelectric points and molecular weight ranges, functional categories, cellular locations, and abundances | •Time-consuming •Laborious •Very expensive | ||
Liquid chromatography combined with mass spectrometry (LC–MS) | •Wide proteome coverage •Suitable accuracy and precision in quantification |  | [255] | |
Gel-free proteomics | •Deeper analysis of complex proteomes by integrating labeled and label-free technologies •In-depth screening of protein synthesis and PTMs •Helping the revelation and determination of proteins (such as low-abundant •Proteins, very high-abundant proteins or proteins with drastic isoelectric points) rarely identifiable in 2DE-based proteome analysis •Utilizing multi-dimensional capillary liquid chromatography combined with tandem mass spectrometry for separation and identification of the peptides attained from the enzymatic digestion of whole protein extracts | •Not able to retain isoelectric point and molecular weight information | ||
Metabolomics | Nuclear magnetic resonance (NMR) | •Easy sample preparation •Able to perform metabolite levels quantification •High experimental reproducibility •Possessing nondestructive nature •A suitable platform for large-scale or prolonged clinical metabolomics analyses •Capable of handling different types of samples (liquids, solids, gels) and determining unknown metabolites | •Low sensitivity •Difficulty in standardization of NMR methods and data •Requiring large sample volumes | |
Gas chromatography coupled to mass spectrometry (GC–MS) | •Higher sensitivity compared to NMR •Reproducible retention times •Complete databases for identifying metabolites •Possessing more sensitivity for free fatty acids compared to LC–MS | •Requiring extensive sample preparation •Requiring sample derivitization •The possibility of variation due to sample preparation | ||
Liquid chromatography combined with single-stage mass spectrometry (LC–MS/UHPLC-MS) | •Short separation time •Easy sample preparation •High resolution •High mass accuracy •Ability to analyze a broader range of metabolites compared to GC–MS •Higher sensitivity compared to NMR | •Possessing destructive nature •Difficult reproducibility of retention times between different systems |