Keywords

5.1 Introduction

The soil is the most common home of more than 1016 diverse microbes/ton due to its heterogeneity, favoring the formation of micro-niches (Olaniran et al. 2013). Soil contamination is a change in the biological and physiochemical nature of the soil which has a detrimental effect on the living organisms residing in it. The different types of soil contamination (Fig. 5.1) are agricultural waste, industrial waste, urban waste, and radioactive waste. The fertilizers, pesticides, industrial effluents, and radionuclides flow down to the nearby water bodies or any other soil location resulting in biomagnification. This creates an interruption in the biochemical pathways and leads to harmful diseases. Improper dumping of waste in landfills and public places results in erroneous disintegration of the waste and deposition of contaminants in the soil. Limitless deposition of waste results in increased bacterial growth that causes a rise in the generation of methane gas which eventually leads to global warming. Nuclear power plants and nuclear testing add wavering amount of radioactive material to the soil (Mishra et al. 2015).

Fig. 5.1
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Classification of soil contamination pertaining to their source

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Earlier, the disposal of waste was done by throwing the waste in a hole, but due to the lack of new areas, the practice was difficult. With the emerging techniques like chemical decomposition and incineration at high temperature, the disposal of waste became effective, but they came with several disadvantages like obscure methods, expensive, and others. Alternative techniques like bioremediation were hence implemented (Karigar and Rao 2011).

Bioremediation is the process of speeding up the process of natural biodegradation in the contaminated areas by the application of microbes (Calvo et al. 2009). The various strategies that are being used to remediate the soil are either removing the pollutant present in the soil or reducing its effect by stabilizing it (containment) (Cunningham and Berti 1993 ). In general, bioremediation strategies can be classified into the following three processes:

  1. 1.

    Biodegradation: Organic compounds are fragmented down into reduced inorganic or organic compounds.

  2. 2.

    Biotransformation: The hazardous molecules are reformed into a reduced or nonhazardous molecule.

  3. 3.

    Biomineralization: The organic compounds are entirely degraded into inorganic compounds like carbon dioxide or H2O4.

The type of contaminant determines the remediation process that will be implemented. The soil remediation cost depends on soil properties, site conditions, volume to be remediated, and type of contaminant. The increasing urbanization and industrialization lead to contamination of soil by organic and inorganic pollutants and, hence, have led to the deterioration of the environment and the human health (Dong et al. 2013).

5.2 Traditional Technologies for Soil Remediation

Along with biological, physical, and chemical concerns, remediation strategy depends upon the legitimate and economic considerations as well. Such strategies are preferred that result in minimum adulteration to the soil.

Different strategies for bioremediation of contaminated soil (Fig. 5.2) are:

Fig. 5.2
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Conventional methods for treatment of soil contamination

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5.2.1 Physical Remediation

It includes predominantly thermal desorption and soil replacement. It can be further done by replacing clean soil with contaminated soil, followed by its treatment, soil spading (the contaminated area is dug deep to spread the contaminants into deep sites and naturally degrading the pollutant), and soil importing (clean soil is added to the affected site on the surface, and mixing is done to decrease the concentration of the pollutant).

Thermal desorption is the removal of the pollutant by its volatility.

5.2.2 Chemical Remediation

  1. 1.

    Chemical leaching: Soil washing/flushing is done with reagents, surfactants, water, and chelating agents. Soil washing is a strategy where liquids like aqueous solutions are used to separate the pollutants from the soil. The contaminants adhere to the soil particles, but they have low water solubility. To increase the solubility, additives like surfactants and chelating agents are applied along with the process (Mao et al. 2015).

  2. 2.

    Chemical fixation: The movement of heavy metals is decreased by adding reagents. The reagents make the heavy metals insoluble in soil, thereby decreasing its toxicity (Yao et al. 2012).

  3. 3.

    Electrokinetic remediation: In this strategy, voltage is applied at the two sides of the soil to create an electric field gradient. This technique provides minimum disturbance to the topsoil and treats the lower surface contaminants (in situ) (Gan et al. 2009).

  4. 4.

    Vitrify remediation: The organic matter present in the soil is heated at 1400–2000 °C, and it is volatized. The end products (after pyrolysis and steam) are collected and cooled to form a rock-type substance that creates hindrance in the movement of the heavy metals. This technique can be applied in situ as well as ex situ (Yao et al. 2012).

  5. 5.

    Ball mill process: Soil sample along with grinding media is added to the reactor (i.e., mill pot). In the absence of any chemical agents, the grinding process removes the contaminants and maintains the soil property as well (Shin et al. 2016).

  6. 6.

    Subcritical water extraction process: Instead of organic solvent, superheated water is used as a solvent. The water is heated at a pressure less than 22.1 MPa and temperature range of 100–374 °C. It follows the principle of pressurized liquid extraction (PLE) (Islam et al. 2013).

5.2.3 Biological Remediation

  1. 1.

    Phytoremediation is containment or removal of the contaminants by the use of green plants. Phytoremediation generally includes three processes: phytostabilization (adsorption, reduction, and precipitation of the pollutants at the roots of the plants), phytovolatilization (converting pollutant to a gaseous state), and phytoextraction (tolerant and accumulating plants are used) (Yao et al. 2012).

  2. 2.

    Bio-augmentation is the introduction of microorganisms at the contaminated site. The microbes are generally added to such areas where the microbes that can degrade the pollutants are in a low amount (autochthonous microorganisms) or the population present at the site does not have the catabolic pathway to degrade the pollutants (Yao et al. 2012).

  3. 3.

    Biosorption: Biomass (containing inactive, dead microbes) can bind to heavy metals and concentrate them. First, physical adsorption at the cell surface occurs, and then the metal ions gain access to the cytoplasm via the cell membrane. The type of microorganisms used defines the type and quantity of metal binding on them (Yao et al. 2012).

5.3 Traditional Tools of Omics

Specific genes (often 16s rRNA gene) were cloned in early environmental gene sequencing to produce a microbial diversity profile unlike microbial genome sequencing and traditional microbiology which depends upon cultivated cultures. The inherent soil microbial functions are nutrient recycling along with essential elements, the formation of organic matter, and decomposition aiding the natural process of soil bioremediation (Garbeva et al. 2004). The microbial world primarily constitutes of the organisms that are already cultured consisting of 1% of the overall soil microbial community. Using culture-based techniques, Bacteroidetes, Proteobacteria, Actinobacteria, and Firmicutes are the most governing phyla isolated from soil (Schloss and Handelsman 2004). The viable and nonculturable microorganisms inherently propagate in habitual environments, but then they are dormant in the laboratory or artificial surroundings. Standard culture-based approaches cannot culture these organisms, but they embrace a copious standing in the ecosystem. Hence lipids, nucleic acids, or proteins were used from the soil samples for direct assessment of their function to overcome this problem. Familiar genes such as ITS, 18S rRNA, and 16S rRNA are used as a biomarker for identification of microbial community population in the culture-independent techniques. Hence for an enhanced phylogenetic and functional categorization of the microbial community in the soil, amalgamation of specific molecular tools such as genetic fingerprinting, quantitative PCR, fluorescence in situ hybridization technique (FISH), microbial lipid analysis, stable isotope probing, microradiography, clone library method, and DNA microarray has been developed to understand the interaction of the microorganisms with various natural factors in the soil microenvironment.

Genetic fingerprinting techniques perform the direct analysis of specific molecular biomarker genes using their amplified PCR products. The relationship between diverse communities of microbes is studied using cluster-assisted analysis which compares fingerprints from various samples using software such as GelCompar. Temperature gradient gel electrophoresis and denaturing gradient gel electrophoresis (TGGE/DGGE), single-stranded conformation polymorphism (SSCP), random amplified polymeric DNA (RAPD), terminal restriction fragment length polymorphism (T-RFLP), ribosomal intergenic spacer analysis (RISA), amplified ribosomal DNA restriction analysis (ARDRA), and length heterogeneity PCR (LH-PCR) are the most prominent techniques used in genetic fingerprinting. Multiple samples are evaluated at a glance through a generated community fingerprint based on sequence polymorphism.

Amplified ribosomal DNA fragments get separated using DGGE and TGGE. Identical length DNA fragments get separated based on their variable and nucleotide composition. At the 5′ end, a GC-rich primer prevents the thorough alienation of the PCR fragments. The illustration of a solo species by several bands is the constraint associated with this method (Dowd et al. 2008). The solicitation of traditional omic tools along with their sampling source is presented in Table 5.1. Using this technique, analysis of rhizospheric bacterial populations and assessment of the microbial soil community have been done in paddy agricultural soils in recent times (Srivastava et al. 2016; Schloter et al. 2018). RAPD, due to its high speed and ease of use, is considered a simpler technique for the assessment of inherently allied bacterial species, functional and structural interpretation of the microbial communities in the soil, and genetic fingerprinting. Synthetic oligonucleotide primers having random nucleotide sequences are annealed at multiple locations on the genomes at low temperature. Assessment of laboratory-scale biodegradation of fuel oil-contaminated soil has been studied using this technique (Piñón-Castillo et al. 2017). SSCP uses the principle of separation of a single-stranded DNA by electrophoresis. T-RFLP uses fluorescently labeled 5′ primers. Advanced throughput analysis and evaluation of numerous assorted samples at a lone time is the major advantage of this technique. Using bacterial 16S rRNA or 18S rRNA gene amplicon and fungal communities to breed restriction fragment contours, ARDRA serves as the most crucial tool in the process of unique clone identification obtained from the environment. Analysis of nitrogen-fixing bacterial communities in peak rice-growing season has been done using this technique (Chakraborty and Islam 2018). RISA analyzes the phylogenetic diversity of the microbes built on the intergenic length adjustment in the transcribed spacer region within the 23S and 16S genes for prokaryotes and 23S and 18S encoding rRNA genes for eukaryotes (Fuhrman et al. 2008). Quantitative PCR determines the manifestation and plethora of operative and taxonomic gene markers in the exploration of soil microbial communities (Bustin et al. 2005). SYBR green fluorescent dyes or fluorescent probes measure the accumulated amplicons in each cycle of PCR. Quantification of Fusarium species in root rot complex in field pea soil has been studied using quantitative PCR (Zitnick-Anderson et al. 2018). The conjugation of a fluorochrome with an oligonucleotide probe is the basic principle behind FISH. Due to its immense genetic stability and high copy number, probes of 16S rRNA are conventionally exploited in this technique. On hybridizing the homologous sequence to its fluorescent probe, the fluorescent intensity is measured using a fluorescent microscope. Lipids as opposed to nucleic acids are used in microbial lipid analysis for the assessment of soil microbial communities (Banowetz et al. 2006). The biomass of a cell has a constant amount of fatty acids which is stable in nature and gives a clear differentiating picture between the different taxonomic populations of microbes. Extraction of fatty acids is done using saponification and derivatization, generating FAMEs which are further analyzed through gas chromatography. The radiolabelled substrate is used in microradiography by metabolic active cells. Combining microradiography with FISH identifies the phylogenetic active cells which are radioactive in nature and consume the substrate (Rogers et al. 2007). The individual gene fragments are sequenced following cloning in the clone library method. The PCR-obtained sequences are compared to green gene, ribosomal data projects, and gene banks (DeSantis et al. 2007). Characterization of the microorganisms in environmental samples is also done using DNA microarrays. DNA from the environmental samples generates fluorescently labeled amplified PCR products which are directly hybridized to the microarrays having known sequence molecular probes (Gentry et al. 2006). The overall evaluation process is enhanced due to the rapid replication by the DNA microarray, aiding as a significant advantage. The intensity of the signal on the microarray is directly related to the ampleness of the target organism in the sample. Besides having enhanced responses, these conventional techniques also have their specific limitations. However, with the integration of advanced omic tools, the process of microbial community analysis has been undergoing an enhanced revolution with improved understanding and application to decipher the role of microbial communities in soil bioremediation.

Table 5.1 Application of traditional omic approaches in soil bioremediation
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5.4 Advanced Omic Tools

The DNA-based molecular techniques do not provide detailed information about gene expressions under in situ conditions. Hence sequences within the metagenomic databases from uncultured microbes provide fruitful insight into the functional microbial diversity. Therefore, post-genomic methodologies such as metagenomics, metatranscriptomics, proteogenomics, and metaproteomics provide a potential connection among the genetic and functional resemblances between numerous communities of microbes, hastening the process of soil bioremediation.

The direct collection of microbial genomes from ecological samples is known as metagenomics, community genomics, or environmental genomics (Riesenfeld et al. 2004). The communication of uncultured organisms with altered environmental factors and their biochemical role can hence be studied using metagenomics. Using functional metagenomic libraries, various functional molecules such as microbial enzymes (lipase, amylase, cellulase) and antibiotics, by companies such as Terragen are derived (Rondon et al. 2000). In the aerobic conditions, the acid sulfate soil microbial community was characterized to study the structural and functional genes, using the tools of metagenomics. Both the topsoil and parent materials underwent significant changes on incubating in aerobic conditions. The archaeal community significantly decreased, whereas the sulfur-cycling genes enhanced in the parent material (Su et al. 2017). However, at the genetic level, the relationship between community composition and taxonomic diversity remains to be determined.

Metatranscriptomics or environmental transcriptomics is the study of the variations in the microbial expression of genes under specific conditions by capturing the total mRNA (Moran 2009). Recently, the overall phylogenetic pool of the functionally and taxonomically appropriate microbial communities has been analyzed using the double-RNA method or both the rRNA and mRNA, noticing a considerable diversity among the microbial communities. Recently, through direct species electron transfer, the interaction between Methanothrix and Geobacter was studied in paddy soils under methanogenic terrestrial environments. Methanothrix is the prominent microbial contributor in the global methane production, but very little is known about its physiology and ecology. The transformation of methane from acetate serves as an important contribution by Methanothrix in terrestrial ecosystems (Holmes et al. 2017). Nitrogen-transforming reductive gene transcripts were identified through metatranscriptomics in waterlogged paddy soils. Reductive nitrogen transformation was actively induced due to the presence of anoxic environments (Masuda et al. 2017). Using rice straw as a source of carbon, the severity of seawater salinity on paddy fields was studied to observe the significant changes in mRNA expression throughout the whole community (Peng et al. 2017). The diversity of microorganisms is crucially analyzed using metatranscriptomics, elucidating the community composition and deciphering their potential in soil bioremediation.

Metaproteomics or environmental proteomics is the qualitative and quantitative study of proteins on a large scale of diverse microbial species (Wilmes and Bond 2006). Under stressful conditions, proteofingerprints are generated to indicate the functional status of microbial societies (Keller and Hettich 2009). In recent times, metaproteomics has been exercised in various environments such as sediments, soil, freshwater, and marine systems. However incorrect metagenomic information, flush variety of microbial organisms, and soil heterogeneity have a negative influence on the process described (Wang et al. 2016). The bacterial metabolic functions correlated with a plant in serpentine soil contaminated with nickel, cobalt, and chromium were also interpreted using metaproteomic approach. (Mattarozzi et al. 2017). A bacterial protein database was constructed through the genera identified using 16S DNA profiling. A continuum of bacteria is revealed by the proteins involved in response to stimulus and transportation of nutrients. The bacterial biocatalysts play a vital part in the evolution of a post-petroleum bio-based economy, but the difficulty in analyzing the genetic information limits the biocatalyst’s capability (Sukul et al. 2017). The bioactivity from the proteome of an environmental sample can hence be efficiently analyzed using functional metaproteomics. Hence biomass quantification in metaproteomics serves as an important tool to interpret the correlation between various soil microbial communities in a sustainable environment.

Metabolomics characterizes the response of soil microbial communities to specific biological factors, abiotic pressures, and its immediate environment. Organic, low molecular weight biomolecules occurring naturally in a cell, tissue, or biofluid are known as metabolites. A comprehensive study of metabolomics is the production of a range of metabolites or metabolomes in communication with a natural environmental stimulation (Miller 2007). Recently, metabolomics has had numerous prominent applications in the field of environmental sciences such as the development of biomarkers, feedback to altered levels of environmental stress, assessment of risks on toxicant exposure, and disease monitoring and diagnosis (Viant 2009). Prominent deviations were observed in the metabolic pathways of S. meliloti. Simultaneously this could be related to other bacteria experiencing a series of abiotic pressure. Some of the noticeable modification changes were the presence of intermediates in myoinositol degradation and changes in the biosynthesis of exopolysaccharides and pentose phosphate pathway (PPP). In accordance to metabolic adaptation, enhanced acid tolerance phenotypes and improved competitiveness in nodulation are associated with the same in rhizobia (Draghi et al. 2017). Osmotic adjustment and osmoprotection were calculated in the classical species of cowpea (Goufo et al. 2017). The organic solutes in plants uphold an optimal turgor by enacting as osmolytes or as radical scavengers to protect the metabolic functions and hence survive the extreme drought conditions. By analyzing the salt-tolerant mechanisms and the metabolic profile of plants, enhanced sustainable crop production can be achieved worldwide, leading to the development and protection of natural plant reserves and hence aiding the bioremediation potential of the soil microbial community.

5.5 Application of Omic Tools in Bioremediation

Microorganism utilizes organic compounds as a sole carbon source and to manage their biomass and assemble suitable enzymes and cofactors for their oxidation/reduction. Hence, the organic compounds should be nontoxic or less damaging to microbial growth. The microorganisms participating in the metabolic degradation of organic compounds are heterotrophic. Molecular methods like cloning, fingerprinting, ARISA, RFLP, etc. are used to study microbial diversity (Fig. 5.3). These techniques yield information on how environmental factors change the microbial community structure. More advanced techniques like Illumina and 454 sequencing are also being used to study the microbial diversity of the polluted areas. Different approaches are used to remediate contaminated soils (Yergeau et al. 2014). The present scenario includes the implementation of various omic tools (Table 5.2) to study the microbial diversity of the contaminated soil with that of uncontaminated soil, thus providing better insight for the development of the new remediation technique or improving the already existing methods.

Fig. 5.3
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Application of omic tools in soil bioremediation: a conceptual framework

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Table 5.2 Application of advanced omic approaches in soil bioremediation
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The uptake of heavy metals like mercury can lead to biomagnification. The heavy metals interrupt with the energy metabolism of the plants. Transcriptomics helps in the early detection at molecular levels. The changes in the genes in the presence of a low and high concentration of metals can also be studied (Villiers et al. 2012; Beauvais-Flück et al. 2017). The tools of genomics like DGGE (denaturing gradient gel electrophoresis) of 16S rRNA enhance the study of several communities of microbes in non-polluted and polluted soils and, therefore, help in the isolation of the heavy metal-resistant bacterial strains (Altimira et al. 2012; Utturkar et al. 2013). The adaptation of any organisms to the surroundings is reflected in their biological activities which can be calculated by doing transcriptomics, proteomics, and metabolomics analysis. Thus, the techniques of the bioremediation can be enhanced, and the scope of remediation technique can be improved (Hediji et al. 2010; Tripathi et al. 2012). The bacterial soil community affects the uptake of metals by plants by either stimulating the plant growth or by metabolizing the heavy metals. Pyrosequencing, a next-generation tool, of 16S rRNA provides a better picture of plant-metal-microbe interaction in the soil (Muehe et al. 2015).

Phytoremediation is one of the cost-effective remediation techniques in use for years now. The purpose of plants to attenuate the xenobiotics makes them more feasible method than the physical and chemical processes. The transgenic plants result in either degradation of the xenobiotics or increased resistance of the plant to the pollutant (Abhilash et al. 2009). The industrial effluents are estimated to be 5% saline and hypersaline. Microbial diversity is less as compared to non-extreme environments. Thus degradation of the pollutant becomes a significant problem in such regions. The halophilic microorganisms are proposed to be a favorable applicant for the remediation of the hypersaline environments. Though the metabolization of hydrocarbon reduces at high salt concentration, a lengthy exposition period has shown a significant amount of degradation and metabolized hydrocarbons (Le Borgne et al. 2008). The genomic sequence analysis discloses the genes that might be involved in the degradation. Further, proteomic analysis of the microbe in the presence of different concentrations of hydrocarbons affirms the genes involved in the degradation (Yun et al. 2014; Wei et al. 2017). Application of techniques like RT-qPCR quantifies the expression of various hydrocarbon-degrading genes and thus provides an insight into the shift in the microbial communities (Yergeau et al. 2012).

5.6 Future Prospects

There have been unprecedented changes in the field of microbial ecology with the augmentation and advancement of numerous molecular-based omic tools. The inherent functional and taxonomical diversity of the innate communities of microbes present in the soil has been investigated using diverse post-genomic approaches, revealing the superficial knowledge about the metabolic and genetic heterogeneity present in the most copious organisms in the planet, known as the prokaryotes. Implicit questions, for instance, “How the physical, chemical, and biological factors regulate the microbial communities?” and “How many bacterial species are currently present in the planet?”, and the broad knowledge about the metabolic diversity in the elementally present microorganisms still remain to be understood. As most of the classified genes have no autologous sequences in the present databases, deciphering the utilitarian roles of uncultured organisms has become an appalling task. Numerous technical challenges still remain to be overcome although there has been immense progress in the field of identification and classification of the intrinsic microbial communities in the soil by the application of proteogenomic, transcriptomic, and metagenomic approaches. New insights into the soil microbiology can be provided using interdisciplinary omic system technologies, revealing the interaction between proteins, genes, and environmental factors. Hence the upcoming years will see a prioritized area of research in the development of consequential multi-omics approaches.