Structural and functional metagenomic analyses of a tropical agricultural soil

Understanding the intricate link between the soil microbiota and their metabolic functions is important for agricultural and ecological processes and could be used as a biomarker of soil health. To understand the relationship between soil microbial community structure and functions, a soil microcosm designated 2S (agricultural soil) was set up. Metagenomic DNA was extracted from the soil microcosm and sequenced using Miseq Illumina next generation sequencing and analysed for their structural and functional properties. Structural analysis of the soil microcosm by MG-RAST revealed 40 phyla, 78 classes, 157 orders, 273 families and 750 genera. Actinobacteria (54.0%) and Proteobacteria (17.5%) are the dominant phyla while Conexibacter (8.38%), Thermoleophilum (7.40%), and Streptomyces (4.14%) are the dominant genera. Further assignment of the metagenomics using Cluster of Orthologous Groups (COG), Kyoto Encyclopedia of Genes and Genomes (KEGG), GhostKOALA, and NCBI’s CDD revealed diverse metabolic pathways utilized by the microbial community for the metabolism of carbohydrates, amino acids, lipids, biosynthesis of secondary metabolites and resistance to antibiotics. Taxonomic analysis of the annotated genes also revealed the preponderance of members of Actinobacteria and Proteobacteria. This study has established that members of the phyla Actinobacteria and Proteobacteria are the key drivers of the majority of important metabolic activities in the soil ecosystem and are thus an integral part of the soil microbial community.


Introduction
Microorganisms found in natural environments are responsible for most of the biological transformations that lead to formation of soil nutrients (Asadu et al. 2015;Costa et al. 2015).The role these organisms play in driving various biogeochemical cycles of elements, fixing carbon and nitrogen, mineralizing dead organic matter and protection of plants from biotic and abiotic stresses is replete in the literature.They play a very important role in the health and ecological balance of these environments.Their cardinal role in influencing soil function and determining overall soil quality in the terrestrial environment, including agricultural soil, cannot be overemphasized (Nannipieri et al. 2003;Wardle et al. 2004;Arias et al. 2005).
Furthermore, soil microbes are important in provisioning and regulating services provided by the soil ecosystem.This includes growth medium for plants, soil aggregation improvement and stability, buffering waterflow, recycling of waste and detoxification, increasing nutrient bioavailability to plants, filtering contaminants, biological control of pests, weeds and pathogens, carbon storage and regulation of greenhouse gases (Aislabie and Deslippe 2013; Rashid et al. 2016). Trivedi et al. (2016) noted that changes in microbial population or activity could precede detectable changes in soil physical and chemical properties, thereby providing an early sign of soil improvement or an early warning of soil degradation.Thus, shifts in microbial community structure and function could be used as biomarkers of soil ecological health.
[ STRUCTURAL AND FUNCTIONAL METAGENOMIC ANALYSES OF A TROPICAL AGRICULTURAL SOIL ] Recognition of the essential role of microbial communities in life and in the functioning of the ecosystem has engendered aggressive efforts to discern their diversity and harness their hidden metabolic and genetic potentials (Mocali and Benedetti 2010;Paul et al. 2016).Traditionally, methods that involve culturing of microorganisms were employed for this purpose.However, such methods often reveal < 1% of the total soil populations, in most cases excluding some of the most important contributors to soil functions (Maier and Pepper 2009).One major factor responsible for this is the fastidious nature of some of these organisms or their slow growth relative to other members of the community, which overgrow and overshadow them on routine media (Cheung and Kinkle 2001).Therefore, in the last two decades, molecular approaches targeting 16S rRNA genes useful in taxonomic affiliation or marker genes specific for certain metabolic functions have become the favoured strategy for unravelling the structure, functional diversity and dynamics of microbial communities in soil and other environments (Stach and Burns 2002).Some of the methods that have revolutionarily transformed research in this area include Denaturing Gradient Gel Electrophoresis-PCR (DGGE-PCR), Length Heterogeneity-PCR (LH-PCR), Clone Libraries and terminal Restriction Fragment Length Polymorphism (tRFLP) (Muyzer et al. 1993;Liu et al. 1997;Suzuki et al. 1998).The advances made notwithstanding, these methods are limited by the fact that they are laborious, time consuming and offer access to only a target group or populations within the broader microbial community (Paul et al. 2016).However, with advances in highthroughput sequencing technologies such as illumina next generation shotgun sequencing, construction of clone libraries is no longer necessary, greater yield of sequence data can be obtained and information can be provided about which organisms are present and what metabolic processes are possible in a community (Segata et al. 2013).Metagenomics using next generation sequencing demonstrably gives unprecedented insight into the genetic potentials of microbial communities as well as underrepresented populations (Handelsman 2004;Newby et al. 2009;Oulas et al. 2015).It is cheaper and enables the identification of novel molecules with significant functionalities and applications (Streit and Schmitz 2004;Bashir et al. 2014).
Although the metagenomic approach is increasingly gaining ascendancy as the gold standard for discerning microbial community structure and functions, much of the ecosystems in the world remain unexplored and even fewer have been investigated using this approach.In the Nigerian environment, there have been only a handful of reports employing this approach (Ogbulie and Nwaokorie 2016;Salam et al. 2017).However, globally, very few published works utilized sequence data generated from illumina next generation shotgun sequencing for functional characterization of environmental samples.Elucidation of microbial community structure and functions as designed in this study allows for quantitative and qualitative assessment of soil health, which is pivotal in the field of agriculture and soil ecology.Here, we report the use of illumina next generation shotgun sequencing to decipher the microbial community structure and functions of a tropical agricultural soil in Ilorin, Nigeria and determine the possible role of dominant members of the microbial community in driving core metabolic functions in the soil.

Sampling site description
Soil samples were collected from an Agricultural farm in Ilorin, Kwara State, Nigeria.The coordinates of the sampling site were latitude 8° 29' 18.11ʺ N and longitude 4° 28' 58.19ʺ E. The soil is dark-brown in colour and consists of fine, medium coarse silty sand (sand 72%, silt 27%, traces of fine gravel; Soil Survey Division Staff 1993) and is used to plant majorly millet, maize and vegetables.
[ LATEEF BABATUNDE SALAM & OLUWAFEMI SUNDAY OBAYORI ] 2.2.Sampling and microcosms set up Soil samples were collected at a depth of 10-12 cm with sterile trowel after clearing debris from the soil surface.Soil sample was passed through a 2-mm mesh size sieve.The sieved soil was thoroughly mixed in a large plastic bag to avoid variability among the results of replicate soil samples and used without air-drying.Sieved soil (2 kg) was measured and placed in open aluminum pans (37 cm x 14 cm x 7 cm).It was designated 2S.The set up (in triplicates) was incubated at room temperature (25 ± 3 °C) and flooded with 100 ml sterile distilled water to maintain moisture level of about 25%.Samples (in triplicates) were taken for physicochemical analysis.The physicochemistry of the soil sample has been described previously (Salam et al. 2014).

DNA extraction and Shotgun Metagenomics
Genomic DNA used for metagenomic analysis was extracted directly from 2S soil microcosm.Genomic DNA was extracted from the agricultural soil (2S) immediately after sampling to determine the microbial community structure of the soil.Genomic DNA were extracted from the sieved soil samples (0.25 g) using ZYMO soil DNA extraction Kit (Model D 6001, Zymo Research, USA) following the manufacturer's instructions.Genomic DNA concentration and quality was ascertained using NanoDrop spectrophotometer and electrophoresed on a 0.9% (w/v) agarose gel, respectively.Shotgun metagenomics of 2S microcosm was prepared using the Illumina Nextera XT sample processing kit and sequenced on a MiSeq.Genomic DNA (50 ng) were fragmented and tagmented and unique indexes were added using reduced-cycle PCR amplification consisting 8 cycles of 95 °C for 30 s, 55 °C for 30 s, and 72 °C for 30 s, and a final extension at 72 °C for 5 min before cooling to 4 °C.Constructed metagenomic libraries were purified with Agencourt AMPure XP beads and quantified with Quant-iT PicoGreen.The library size and quality were validated on Agilent Technologies 2100 Bioanalyzer.Libraries were normalized, pooled in equal volumes and run on a 600 cycles MiSeq Reagent kit v3 (Illumina Inc., San Diego, CA).All samples were multiplexed and sequenced in a single lane on the MiSeq using 2 x 300 bp paired-end sequencing, which generates 20 Mb of data for each sample.Sequence reads were generated in < 65 h, while image analysis and base calling were performed directly on MiSeq.The sequences of 2S metagenome were deposited on the MG-RAST server with the ID 4704691.3.Sequences generated from the microcosm set up were assembled individually by VelvetOptimiser v2.2.5 and the contigs generated were fed into the MG-RAST metagenomic analysis pipeline.

Taxonomic characterization of metagenomic reads
The taxonomic characterization of the metagenomic reads was determined using the MG-RAST server.A BLAT similarity search for the longest cluster representative in the metagenomes was performed against the MG-RAST M5rna database, which integrated SILVA, Greengenes and RDP databases.The abundance data were identified through the lowest common ancestor (LCA) with the default parameters 1e -05 as the maximum e-value, 60% as the minimum identity, and a minimum alignment length of 15 as cutoff.In addition, a rarefaction curve was generated for 2S sequence reads according to the data obtained from MG-RAST server and various diversity indices of the metagenome was determined using Mothur v. 1.30.2 (Schloss et al. 2009).

Functional analyses of metagenomic reads
Gene calling was performed on the 2S contigs using FragGeneScan (Rho et al. 2010) to predict open reading frames (ORFs), which were functionally annotated using KEGG GhostKOALA, the Clusters of Orthologous Groups of proteins (COG) (Tatusov et al. 2001), and the NCBI's conserved domain database (CDD;Marchler-Bauer et al. 2015).

[ STRUCTURAL AND FUNCTIONAL METAGENOMIC ANALYSES OF A TROPICAL AGRICULTURAL SOIL ]
In GhostKOALA, each query gene is assigned a taxonomic category according to the besthit gene in the Cd-hit cluster supplemented version of the non-redundant pangenome dataset (Kanehisa et al. 2016).In addition, the ORFs were functionally annotated and assigned to the COG database that compares protein sequences encoded in complete genomes, representing major phylogenetic lineage.The 2S metagenome sequence reads was further functionally annotated using the NCBI's conserved domain database (CDSEARCH/cdd v 3.15) using the default blast search parameters.The CDD is a protein annotation resource that consists of a collection of well annotated multiple sequence alignment models for ancient domains and full-length proteins.

Physicochemistry of the soil microcosm
The physicochemical properties of 2S soil microcosm showed that the pH was slightly above neutral (7.20 ± 0.01) while the organic matter content was 1.10%.The total nitrogen, phosphorus and potassium content of the agricultural soil were 0.09%, 3.80 mg/kg, and 0.94 mg/kg respectively.

General characteristics of 2S metagenome
Illumina sequencing of the DNA from 2S microcosm resulted in 1,512,514 sequence reads.These sequences were assembled into 36,503 unique contigs with a total of 5,779,527 bp, an average length of 158 ± 37 bp, and GC content of 58 ± 4%.After dereplication and quality control by the MG-RAST, the total number of unique contigs in 2S metagenome reduced to 27,320 with 4,197,699 bp, an average length of 154 ± 26 bp, and the GC content of 58 ± 4%.Statistical analysis of the rarefaction curve was conducted to assess the species richness and abundance of the metagenome.As shown in the rarefaction curve, there are 18,484 unique species (phylotypes) in the 2S microcosm with 52% coverage at species delineation (0.03; 97%).Analysis of species abundance and richness revealed that the Shannon index (H') is 9.63, Simpson's index (D) and Simpson's reciprocal index (1/D) are 0.00005 and 19941.53,Chao index was 47974.87,and Shannon and Simpson's evenness are 0.981 and 1.08, respectively (Figure 1).unclassified sequence reads that cannot be placed in any of the three domains.

Structural diversity of 2S metagenome
Structural analysis of the biota of 2S soil metagenome was conducted using the taxonomic profiles generated by MG-RAST.The three domains, Bacteria, Archaea and Eukarya were duly represented.As expected, the domain Bacteria is predominant contributing 96.51% of the domain architecture of the soil biota.This is followed by Eukarya and Archaea contributing 3.47% and 0.02%, respectively.Other members of the soil biota detected are viruses and In class delineation of 2S metagenome, 78 classes were retrieved from the metagenome.The predominant classes were Actinobacteria (55.96%),Alphaproteobacteria (5.48%), Gammaproteobacteria (4.84%), Bacilli (4.83%), and Deltaproteobacteria (4.04%), respectively.Other classes detected in 2S metagenome and their corresponding % abundance is presented in Figure 3.
Taxonomic characterization of the annotated genes for amino acid metabolism revealed the predominance of members of the phyla Proteobacteria and Actinobacteria.Other phyla with interesting representations are Verrucomicrobia, Bacteroidetes, Chlamydiae, Euryarchaeota, Cyanobacteria, Firmicutes, Deinococcus-Thermus, and Basidiomycota.
Taxonomic characterization of the annotated enzymes for lipid metabolism revealed the dominance of member of the phyla Proteobacteria (Alphaproteobacteria class) and Actinobacteria.

Energy metabolism
Functional characterization of 2S metagenome for energy metabolism revealed energy generation of the microbial community via diverse routes such as oxidative phosphorylation, photosynthesis and carbon fixation.It also revealed the presence of F-ATPases, the prime producers of ATP, using the proton generated by oxidative phosphorylation or photosynthesis.Also detected are genes coding for enzymes that participated in Calvin cycle (Fructose bisphosphate aldolase, class II), reductive TCA cycle (pyruvate ferredoxin oxidoreductase beta subunit; succinate dehydrogenase/fumarate reductase, iron sulfur subunit; fumarate reductase flavoprotein subunit; isocitrate dehydrogenase), and pathways used by microorganisms for carbon fixation (Table 2).Other carbon fixation pathways detected in 2S metagenome are 3-hydroxypropionate bi-cycle, hydroxypropionate/hydroxybutyrate cycle and dicarboxylate/hydroxybutyrate cycle, respectively.

Biosynthesis of secondary metabolites and antibiotic resistance
Functional characterization of 2S metagenome showed the presence of type I and type II polyketide synthases and backbone such as candicidin polyketide synthase FscD, amphN, nysN, fscP, pimG, cytochrome P450 monooxygenase, Minimal PKS chain-length factor (CLF/KS beta); genes for enzymes that catalyse the biosynthesis of ansamycins, tetracyclines, monobactam, streptomycin and novobiocin, among others.Also detected were various genes for enzymes implicated in resistance to beta-lactam antibiotics, vancomycin, fluoroquinolones and cationic antimicrobial peptide (CAMP) (Table 2).Taxonomic characterization of the detected genes for biosynthesis of secondary metabolites revealed the predominance of the phylum Actinobacteria.However, for antibiotic resistance genes, the phylum Proteobacteria dominates.

Discussion
Soil microbial community structure and functions are highly influenced by a combination of factors, including soil structure and available nutrient, and these could be veritable predictors of soil health.It is not surprising; therefore, that one major objective of metagenomic studies is to gain insight into soil elemental cycles (Myrold et al. 2013).Nitrogen, phosphorus and potassium are essential nutrients that play a major role in crop production and rapid depletion of these nutrients because of intensive and sometimes poor agricultural practices has occasioned reliance on chemical fertilizers to amend the nutrient deficiency (Sharma et al. 2013;Rashid et al. 2016).
The pH value (7.2) of the soil is close to neutral, which is considered favourable for most microorganisms, particularly bacteria that are essential for soil fertility and health (Lauber et al. 2009).The amounts of these nutrients recorded in 2S soil are very low compared with the values acceptable for fertile agricultural soils.However, these values are similar to those earlier reported by Salam et al. (2017) with N, P, K values of 0.04, 3.21 and 0.89 mg/kg respectively.Low levels of these nutrients in soils may also reflect a high level of microbial activity with demand on these nutrients, especially in soil with high organic matter (Ilori et al. 2015).
The identification of Actinobacteria, Proteobacteria, Firmicutes, Chloroflexi, and Planctomycetes as the predominant phyla among the identifiable 40 phyla in the sequences recovered from 2S soil is in consonance with previous reports, which had shown this group as preponderant members in agricultural soils (Trivedi et al. 2016;Salam et al. 2017;Yin et al. 2017).Cheema et al. (2015) identified twelve known bacterial groups in an unpolluted agricultural soil with the predominant ones being Proteobacteria (41%) and Actinobacteria (34%).
It is quite noteworthy that in our study, Actinobacteria alone accounted for 54.0% of the bacterial phyla identified.This is not surprising as members of the group are the largest taxonomic group among the recognized lineages of bacteria [ STRUCTURAL AND FUNCTIONAL METAGENOMIC ANALYSES OF A TROPICAL AGRICULTURAL SOIL ] (Ludwig et al. 2012) well adapted to oligotrophic conditions and are known to produce cocktails of enzymes which have growth promoting effects on plants (Sathya et al. 2017).They are reputable colonizers of soils and have also been linked with soil organic matter production and humus formation, perhaps on account of their ability to produce extracellular enzymes for degradation of macromolecules such as lignin, cellulose, chitin and starch (Silva et al. 2013).
The Proteobacteria, which constitute the second most abundant phyla in this study is notable not only as the largest group of Gramnegative bacteria but also as one with a huge morphological, physiological and metabolic diversity (Spain et al. 2009).They are highly represented in soils receiving high rate of carbon input and boasts of a significantly high number of unculturable or yet to be cultured species (Spain et al. 2009;Fierer et al. 2012).The Firmicutes are Gram-positive bacteria with many of the terrestrial species demonstrating high level of hardihood as spore formers.Members of this group may be favoured in agricultural soil systems because of their remarkable ability to resist desiccation because of sharp variation in soil surface temperature (Montecchia et al. 2015).
It is noteworthy that in terms of class delineation, all classes of Proteobacteria were represented in the 2S metagenome, with Alphaproteobacteria (5.48%), Gammaproteobacteria (4.84%) and Deltaproteobacteria (4.04%) as the most prominent.Some of the Alphaproteobacteria are particularly important as plant mutualists and pathogens and are equally well represented among primary producers (Williams et al. 2007).The prominence of Gammaproteobacteria in 2S metagenome may be attributed to the fact that this group that harbors the richest number of genera among bacterial classes and exhibits broad tropism, aerobicity and temperature tolerance, with symbiotic relationship towards plants, invertebrates and vertebrates (Garrity et al. 2005;Williams et al. 2010).
The predominance of the families belonging to Actinobacteria among the classified reads of the 2S metagenome further buttresses the importance of the Actinobacteria as the major player in the 2S soil biodiversity.

[ LATEEF BABATUNDE SALAM & OLUWAFEMI SUNDAY OBAYORI ]
Micromonosporaceae, well represented as the third most abundant family identified in the 2S metagenome have many strains that have been isolated from soil samples from both temperate and tropical environments (Ara and Kudo 2007;Monciardini et al. 2009) and roots of plants (Wang et al. 2013;Matsumoto et al. 2014).As endophytes of several crop plants, they have recently gained attention because of their importance in nitrogen fixation (Trujillo et al. 2015).Their possible role in the degradation of organics due to several cellulases they produce is well highlighted in the literature (de Menezes et al. 2008(de Menezes et al. , 2012)).It is therefore not surprising that they are part of the predominant clade in this study.
Conexibacter, which is the genus with the most abundant sequence read in the metagenome, is a very small genus of soil organisms with only two species so far characterized.They are aerobic and motile and tolerate pH in both acidic and alkali ranges and psychrophilic and mesophilic temperature (Monciardini et al. 2003;Seki et al. 2012).Their predominance in the agricultural soil may be connected with their ability to withstand the diurnal and seasonal changes in temperature characteristic of such tropical soil.The fact that they are also motile may also have played a role in their prompt colonization of wider reaches of the soil than other non-motile members of the community.
The presence of Streptomyces (in the family Streptomycetaceae) as one of the most abundant classified reads is not unexpected as previous reports from diverse environments had shown similar trend (Lipson and Schmidt 2004;Koberl et al. 2011;Shivlata and Satyanarayana 2015;Salam et al. 2017).Members of this genus are not only known to be highly ubiquitous but are mostly responsible for the decomposition of dead plant matter and maintenance of soil fertility (Thakur et al. 2007;Seipke et al. 2011).Their dominant role in this regard may be attributed to their ability to efficiently degrade cellulose and other complex plant material and production of antibiotics (Mellouli et al. 2003;Chater 2006).
A general review of the functional diversity of the 2S metagenome revealed that core metabolic pathways for carbohydrates, amino acid and lipid metabolism are well represented as indicated by the annotation of the genes for the key enzymes of these pathways.Furthermore, the Actinobacteria, which constitutes the predominant phylum in the metagenome in the community, was also revealed as the predominant group annotated for most enzyme/ genes for carbohydrate metabolism and was second only to the Proteobacteria in annotation of genes for amino acids and lipid metabolism (Table 1).
It had previously been noted that while it might be difficult to correlate individual functional genes with community structures, overall functional attributes of soil microbial communities could be broadly predicted based on the taxonomic or phylogenetic structure of the communities (Fierer et al. 2012).Therefore, the Actinobacteria and Proteobacteria, which constitute the major phyla in the soil community structure are likely to be the key functional players.Screening of forest soil samples in Brazil for functional key enzymes showed that the Actinobacteria and Proteobacteria were the predominant players (Pacchioni et al. 2014). Qin et al. (2016) unequivocally highlighted the fact that the Actinobacteria play diverse functional roles in the soil environment, which makes them the key drivers of the microbial community structure and functions.
Glycolysis is the major pathway used by most microorganisms to break down hexose sugars (Moats et al. 2002).The decarboxylation of pyruvate and CoA activation to produce Acetyl CoA, a key precursor in the TCA cycle and lipid metabolism, is a very important precondition for aerobic metabolism of carbohydrates.The annotation of the genes for some of the key enzymes in these processes is not surprising as the predominant families in the microbiome are aerobic organisms.Also, of interest is the annotation of the enzymes of the pentose phosphate pathway.Usually a subsidiary pathway of hexose breakdown, it is a very important pathway, which provide the precursors for riboses found in other sugars and nucleic acids and generates NADPH, which is a major source of reducing power in biosynthetic reactions for many prokaryotes and eukaryotes (Zubay et al. 1995).It is also the source of other precursors and sugars such as erythrose-phosphate which is the precursor of aromatic amino acids and sedoheptulose-phosphate which is required in small amounts by most cells.
The annotation of enzymes for starch and sucrose metabolism, particularly enzyme such as β-glucosidase suggests that these carbohydrates are a major source of metabolizable primary substrates in the community.Furthermore, our result underscores the presupposed role of the Actinobacteria as the group mainly responsible for degradation of organic matters.Members of the Actinobacteria are known to possess a variety of cellulases and other enzyme for metabolism of carbohydrate hetero-and homopolymers.Wibberg et al. (2016) reported that Streptomyces recticuli has an estimated 456 genes for proteins involved in the utilization of cellulose and other complex and simple carbohydrate substrates.
A cursory look at the genes annotated for amino acids metabolism show that generally, members of the phylum Proteobacteria were more predominant players than other phyla including Actinobacteria even though it is second in the entire community (Table 1).This is in line with previous reports, which highlighted the predominance of genes annotated for this group in soil metagenomic functions related to amino acid degradation, ammonia assimilation and nitrate and nitrite ammonification (Li et al. 2014;Castaneda and Barbosa 2017).Also noteworthy is the annotation of genes for the major enzymes of ammonia assimilation including glutamate dehydrogenase, alanine dehydrogenase, proline dehydrogenase, glutamate synthase and glutamine synthetase and the preponderance of these genes in less prominent phyla of the 2S metagenome such as Verrucomicrobia, Firmicutes and Bacteroidetes.
The characterization of Basidiomycota among the genes annotated for the amino acids arginine and proline (Table 1) is interesting but equally explicable.The predominant species among these, Ustilago maydis, is edible smut fungus and an endophytic parasite of grass (Pan et al. 2008), which is rich in free amino acids content including lysine, glycine, valine, leucine and glutamic acid and other unusual amino acids (Lizarraga-Guerra and López 1996).Thus, this fungus would appear to be an important contributor to the metabolism of these amino acids in the 2S microbiome.
Lipid metabolism is generally well represented in various ecosystems as lipid derivatives are an important part of the cell envelope as the lipid bilayer (phospholipids) or cell wall components.Thus, it is widely used as an important community structure marker and measure of soil health (Bossio et al. 1998;Calderón et al. 2001;Islam et al. 2009;Kunihiro et al. 2014;Jiang et al. 2016;Castaneda and Barbosa 2017).The enzymes annotated for metabolism of fatty acids, glycerolipid, glycerophospholipid and sphingolipid in the 2S soil metagenome are in the classes that have been well elucidated in the literature.The irreversible conversion of acetyl-CoA to malonyl-CoA by the enzyme acetyl-CoA carboxylase (Table 1) which is a multicomponent enzyme system is a universal link between the carbohydrates metabolism and fatty acid synthetic pathways (Zubay et al. 1995).The dominance of members of the phyla Proteobacteria and Actinobacteria in the enzyme annotated for lipid metabolism is in consonance with their dominant role within the 2S soil metagenome.
Energy metabolism by the 2S community encompassed oxidative phosphorylation, photosynthesis, carbon fixation and methane metabolism (Table 2).Genes for oxidative phosphorylation were most abundantly annotated for members of the Actinobacteria and Proteobacteria.This is reasonable as they are equally the most abundant groups in the community.Both groups are known to be well equipped with a cocktail of genes with functional propensity for cycling of carbon, nitrogen, sulfur and other elements in the biogeochemical cycle (Trujillo et al. 2015;Shivlata and Satyanarayana 2015).
The major transformations of nitrogen are nitrogen fixation, nitrification, denitrification, anammox and ammonification and these have been shown to be all highly dependent on diverse assemblage of microorganisms in the environment (Costa et al. 2015).In the 2S metagenome analysis, it was revealed that nitrate reductase/nitrate oxidoreductase alpha subunit played a key role in the community.Since this multicomponent enzyme system is involved in dissimilatory nitrate reduction, denitrification and comammox, it is a pointer to the fact that certain amount of the ammonia is generated by either ammonification or nitrogen fixation or ammonia fertilizer is converted to nitrate which is more readily available to plants but at the same time prone to leaching from the soil.
The annotation of the genes for the transport of nitrogen and biosynthesis of nitrogen-rich amino acids is indicative of certain role for nitrogen fixers even though they are not a major player in the 2S soil based on the most abundant taxonomic affiliation detected in the 2S metagenome.Free-living organisms present in bulk soil and spanning the phyla Cyanobacteria, Proteobacteria, Archaea and Firmicutes are well documented as nitrogen-fixers and are known to contribute to soil nutrient availability (Rashid et al. 2015).
The three predominant enzymes whose genes were annotated for sulfur metabolism in the 2S metagenome, namely sulfate adenyltransferase subunit 2, thiosulfate/ 3-mercaptopyruvate sulfurtransferase and cysteine synthase are core enzymes of the sulfur cycle coupled in organic system.Sulfur is an important component of sulfur containing amino acid cysteine and methionine and equally important in the synthesis of CoA enzyme as well as synthesis of vitamins (Kertesz et al. 2007).Although microbial sulfur oxidation is a dynamic process occupying an important place in the biogeochemical cycle of sulfur (Yousuf et al. 2014), majority of sulfur in soil is bound to organic molecules and is not readily available to plants unless saprobes present in the soil degrade such organic molecules (Kertesz and Mirleau 2004).
The revelation of the presence of type I and type II polyketide synthases and several genes involved in the synthesis of various antibiotics as well as resistance to antibiotics in the 2S metagenome is in consonance with prevailing knowledge on antibiotic functionalities in soil microbial community.Production of antibiotics, which often give competitive advantage to the producers and resistance to antibiotics are common attributes of soil microorganism, some of which are known to thrive solely on antibiotics (Dantas et al. 2008;Allen et al. 2010).It has been shown that consonant with the revelation on preponderance in soil of uncultured majority of diverse species; natural product diversity is potentially much larger than appreciated from culture-based studies (Reddy et al. 2012).
Since polyketides synthases are not only involved in the synthesis of antibiotics but are also known to be involved in formation of the polyketide backbones of immunosuppressive agents and anticancer compounds (Vandova et al. 2017), it is likely that apart from the antibiotic biosynthetic enzymes that were annotated, the 2S metagenome also contains yet to be identified functionalities for other value-added natural biosynthetic products.
One of the polyketide synthases genes identified, the type II PKS gene, is characterized by high amino acids sequence homology and conserved sequence expression and the enzymes it encodes are involved in the synthesis of structurally complex molecules with potent functionalities (Wawrik et al. 2005;Selvin et al. 2016).
Members of the phylum Actinobacteria were revealed as the predominant producers of secondary metabolites in the 2S soil community.This is not surprising as they are the major natural source of antimicrobial agents and the number one antibiotic producing genus, Streptomyces, is a member of this group (Chater 2006).Indeed, in recent times, using a shotgun metagenomic approach, many rare members of the phylum with novel biosynthetic functionalities for compounds with potential for use as drugs and other biotechnological processes have been revealed in unique soil environments (Azman et al. 2015).
The annotation of genes for resistance to antibiotics in the 2S metagenome is not surprising, as antibiotic resistance is a widespread phenomenon in the environment and recent finding using metagenomic approach have shown that it is increasingly becoming important, particularly in cultivated lands and environmental compartments influenced by human activities (Durso et al. 2012;Xiong et al. 2014).The Proteobacteria, which constitute the phylum with the highest taxonomic annotation for antimicrobial resistance in the 2S metagenome are known to exhibit a plethora of mechanisms for resistance to antibiotics produced in the environment.This may be connected with their pliability and propensity for horizontal gene transfer, which is crucial to the evolution of resistance to antimicrobials.Such resistance may account for their co-existence with Actinobacteria as the two dominant phyla in the soil microbiome.

Conclusions
In summary, shotgun metagenomic analysis of the metagenome of a tropical agricultural soil in Ilorin, Nigeria revealed that the phyla Actinobacteria and Proteobacteria were the predominant members of the community and were equally responsible for the diverse metabolic potentials and functionalities that constituted the major drivers of the ecosystem.Whereas the majority of the microbial community participated in heterotrophic metabolism of both an assimilatory and dissimilatory nature, the community also contained a diverse minority of autotrophic metabolic potentials, which were annotated for several rare but cultured species as well as some very common taxa.Generally, identification of functions for key metabolic pathways of elemental cycles indicated a system of intricately linked microbiomes.Furthermore, the community exhibited remarkable richness of both antimicrobial production potentials and resistance functions, which deserve further investigation in the quest for new antibiotics as well as the drive towards resolving the challenges posed by emerging resistance to antimicrobial agents.
[ STRUCTURAL AND FUNCTIONAL METAGENOMIC ANALYSES OF A TROPICAL AGRICULTURAL SOIL ]

Figure 1 .
Figure 1.Rarefaction curve of number of unique sequences recovered vs. number of clones sequenced for 2S microcosm.The number of unique sequences (phylotypes) at species delineation (0.03, 97%) is 18,484, the coverage is 51% and the Shannon, Chao, and Simpson's reciprocal indices are 9.63, 47974.87 and 19941.53,respectively.

Figure 2 .
Figure 2. Phylum classification of 2S metagenome.Unclassified reads were not used for the analysis.All the 40 phyla detected in 2S metagenome were used.

Figure 3 .
Figure 3. Class delineation of sequence reads from 2S soil microcosm.Unclassified sequence reads were not used.Of the 78 classes recovered from 2S metagenome, only 43 that have sequence reads of > 10 were used for this analysis.

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STRUCTURAL AND FUNCTIONAL METAGENOMIC ANALYSES OF A TROPICAL AGRICULTURAL SOIL ]

Table 1 .
List of the genes (coding for various enzymes) and microorganisms detected in 2S microcosm involved in diverse metabolism of carbohydrates, amino acids, and lipids

Table 1 .
List of the genes (coding for various enzymes) and microorganisms detected in 2S microcosm involved in diverse metabolism of carbohydrates, amino acids, and lipids [ STRUCTURAL AND FUNCTIONAL METAGENOMIC ANALYSES OF A TROPICAL AGRICULTURAL SOIL ]