Metagenomic approaches to reveal insights of microbe-microbe, plant- microbiome interactions
Plant- Microbe interaction
Flow chart/ Diagram w.r.t Metagenomics
2. Strategies for deciphering the Plant micro- biome
The Rhizosphere environs
The Phyllosphere environs
The Endosphere environs
3. Metatranscriptomics analysis
SSH (Suppressive Subtractive Hybridization)
4. Host Effect on the Plant microbiome
5. Interplay of microbial complexity & metagenomics
Chapter: Metagenomic approaches to reveal insights of microbe- microbe, plant- microbiome interactions
Microbes- the players; present ubiquitously from hydrothermal vents to human intestine. They are the tiny invaders which can do wonders and at the same time harm us. These astounding adventures are the fundamental unit of life on globe which not only supports it but maintains it. Despite of being present in the whole world, only a diminutive portion is known. Enormous microorganisms have been isolated but their function is still not known. In order to decipher microbes in detail, isolation of microbes were followed by their identification using molecular technology. With the advancement in molecular techniques like PCR, metagenomics etc, it has become trouble- free to some extent. The microbiome hence can be studied (Gilbert et al. 2010; Turnbaugh et al. 2007).
From human body to plants, all are dwelled by microbes comprising of viruses, fungi, and bacteria etc. Their association with the host plays a fundamental part in their health, growth and development. Two types of plant- microbiome alliance benefit plants. First, highly specific interaction indicates significant preciseness develop in symbiotic environment. Second, Commensalism- an alliance between two organisms or microorganisms where the pathogen gets benefit while the host neither gain anything nor harm from the interaction. Secretion of nutrients from plants by the microbes (fungi, bacteria) during their growth in concurrence to the roots imparts no observable advantage to the plant. The microbiome corresponded with plants is believed as its second genome. Each single environment related with the plant (Endosphere, Phyllosphere and Rhizosphere) exhibit a particular microbial association with particular function. Molecular interpretation by implementing technologies such as NGS (next generation sequencing) reveals that by using current methods only a miniscule portion i.e. 5% of microbes have been cultured, unveiling a large number of microbes and their functions remains concealed (Mendes et al. 2013).
Earth is filthy rich with enormous variety of microbes, plants and is highly influenced by their interaction. Considering the plant outlook- Plant microbiome interaction is diverse. It can be good, bad or neutral. Good plant microbiome interaction results symbiotic relationship whereas, bad interaction can lead to negative consequences. The interaction between plants and microbes is a key determinative of plant fitness and yield and has experienced considerable attention lately. Highly compacted soil is usually colonized by a massive number of microorganisms which can be advantageous or can be malignant (Berendsen et al. 2012).
Researchers have found that the population of microorganisms is much higher than the plant cells. Soil contains many beneficial microorganisms such as Mycorrhiza which shows a symbiotic relationship with the roots of a plant by exchange of nutrients and furthermore, nitrogen fixation. Unlike, mycorrhizas there are enormous pathogens that affect plant machinery. Therefore, to counter attack, plants have developed a defence mechanism to combat such exposure. Molecular evidence nearly, 700 million years ago indicates that the alliance of green algae with mycorrhizal fungi were crucial principal to the development of terrestrial plants. Unlike, Arabidopsis thaliana and variant members of the family Brassicaceae, majority of plants have retained this symbiotic relationship which facilitates uptake of mineral nutrients (phosphate etc.) via roots. Microbes colonizing plants also plays a significant role in biogeochemical cycles (Philippot et al. 2009).
In the rhizosphere region, nearly around 5-20% of photosynthate (a product of photosynthesis) is liberated. Furthermore, every year plants liberate 1/2 kg (500g) of isoprene and 0.1 kg (100g) of methanol into the surroundings. In case of methanol this concur between 0.016% and 0.14 % of photosynthetic product (photosynthate), mainly based on the type of plant. For microbes, both are prospective reservoir of carbon and energy. Notably, plants in agricultural soils trigger microbial denitrification and methane formation, thus promoting release of nitrogen oxide (N2O) and methane (CH4). These gases contribute to greenhouse effect (Wrage et al. 2001; Conrad et al. 2006).
Plant- microbiome interaction is a systemic interaction. In soil, plants excretes massive amount of substances (exudates) such as gums, saps etc. Thus, the first step in the interaction is recognition of such exudates by microbes. There is an assumption that plants are capable of acquiring microbes by plant exudates (carbohydrates, amino acids). These plant exudates can differ according to the plant type and its biotic or physical factors. Berg et al. (2016) reported that specific microbial summation was determined by different plants. Comparing the rhizosphere inhabitation of two therapeutic plants- Babuna (Matricaria chamomilla), commonly known as chamomile and nightshade (Solanum distichum). It has been observed that inspite of being cultivated under same conditions; they propounded non- identical structural as well as functional microbial summation. Furthermore, according to plant developmental phases determining specific microbial agglomeration, the plant exudates of the similar plant differs (Chaparro et al. 2013).
Few compounds (plant exudates) responsible for particular interactions like flavonoids in pea- Rhizobia and Strigolactone as a signaling molecule for fungi namely Arbuscular mycorrhizal, were recognized by scientists so far. A model was introduced for microbial colonization by Reinhold- Hurek et al. (2015). The community of microbes shows an outspread range and effected merely by soil kind and environmental aspects. Getting nearer to rhizosphere (plant roots), more is the specialized community and a little species. Only a handful of species are capable to penetrate into the plant roots and set up a firm in the plant. Moreover, the microbial community differs among the different regions of plant after invading it (Akiyama et al. 2005).
Strategies for deciphering the Plant- microbiome
Typical microbiology includes isolation and culture of microorganisms from nature by utilizing different culture (nutrient) media and conditions for growth based on the selected organisms. However, for particularized researches of Physiology and Genetics, an axenic (pure) culture of a specific organism is needed; techniques based on culture miss the huge number of microbic diversification in an environment. In microbial ecology, a variety of non- dependent culture, molecular approaches are used. For deciphering prokaryotes, the universal 16S rRNA gene’s PCR amplification is generally used. Sequencing the mutable segments of this gene permits accurate identification of taxa. The use of Advance capacity sequencing methods has been extensively endorsed as they permit recognition of large number of sequences i.e., thousands to millions in a sample, unveiling profusions of even infrequent species of microbes. Whereas, for deciphering microorganisms like fungi (eukaryotic), the corresponding 18S rRNA gene probably cannot proffer adequate taxonomic difference so internal HVR (hypervariable) transcribed spacer is used oftentimes (Bentley et al. 2008; Margulies et al. 2005).
RhizospherePhyllosphereEndosphereMetagenomicApproachesWhole Genome ShotgunBiochemical Sequencing16S- rRNA SequencingCollect Environmental Sample DNA IsolationSequencing of DNA Assembly DNA Annotation Statistical analysis Storage of data Data sharingBinningMetadataSmall Plasmids/ Cosmids Sequencing the ends of clone librariesCompare to Database sequences Identify genes ; species Collect Environmental SampleGenomic DNA IsolationAmplification using PCRFragmentation and SequencingCompare Sequences Evolutionary treeMetatranscriptomic Analysis
The drawback of this is amplification via PCR of gDNA is indelibly unfair by design of a primer and usually recognizes the organisms of interest only. Complicated environments are colonized by creatures from all life’s kingdoms. Eukaryotic organisms like fungi, nematodes, protozoa etc are worldwide in soils. These organisms can be crucial phytopathogens, while rest are grazers of bacteria. Whereas, the domain archaea execute vital bio- chemical reactions, specifically in soils of agriculture, like oxidation of ammonia (NH3) and formation of methane (methanogenesis). Microorgansims present in a community inter- communicate as well as interact with the host plant, so it is quite crucial to catch micro- biome diversity to the fullest. For this purpose, the application of universal examination like meta- genomics, meta- proteomics and meta- transcriptomics that permit synchronous evaluation and collation of microbic populations over each and every single domain of life. Meta- genomics can unveil the functional capacity of a micro- biome, while meta- proteomics and meta- transcriptomics confer systematically depiction of protein richness and community- wide- gene- expression. Meta- transcriptomics has unveiled alterations at kingdom level in the framework of crop plant’s rhizosphere micro- biomes (Hong et al. 2009; Pinto et al. 2012).
The Rhizosphere environs
The soil has a biological active region surrounding the roots of plant that comprises of soil- borne microorganisms involving fungi and bacteria and is referred to as rhizosphere, where the roots are effected by biotic and abiotic characteristics. This region of soil is well- known to avail an ecological niche which is appropriate for many of the helpful microbes of soil. The prolific activity of microbes in this zone helps in various biotic and ecologic processes crucial for the health of a plant. Research on inter- communications amongst plants and soil- microbiome within the rhizospheric region is quite essential for comprehend a wide spectrum of fundamental processes, namely working of ecosystem, cycling of nutrients and isolation of carbon. An enormous challenge face by ecologists is to associate variety of microbes that exist in rhizosphere with the role in the natural ecosystem they play. However, the most daunting task encounter by microbiologists and phytologists while deciphering these inter- communications is that most cluster of microorganisms which reside in this rhizospheric sphere are unable to culture under artificial environment. Over 99% species of microbes existed in soil are unmanageable yet to culture under artificial environment. Analysis of communities of bacteria isolated numerous environments have discovered that the proportion of culturable cells are not indicative of the richness or microbic community diversification existing in the environment; generally it is noticed that direct microscopical enumeration outreach the viable cell enumeration by various magnitude orders. Current approaches in genomics and molecular methods proffer aggravating chances to connect structural diversification with the activities taking place in the rhizosphere (Hiltner, 1904).
Various rhizospheric microbes are plant- growth regulators encouraging growth and development of seeds, whereas mycorrhizal fungi proffer vegetation with elevated capacity for uptake of nutrient, advance production, drought tolerance and may impart to diversification of plant. Since microbe- associated with rhizosphere holds various metabolic abilities and play a fundamental part in health of a plant, understanding their community framework is crucial for the actual comprehension of roles play by them individually and metagenomics keeps the promise to unveil various significant queries about the uncultivated proportion of rhizospheric community (Dakora, 2003).
The soil- zone rhizosphere effected by roots of plant by the means of rhizodeposition of scraped cells, mucilage and excretions (exudates). Several compounds carried by exudates of root, mainly sugars and organic acids, apart from these they also contains various fatty acids, hormones, amino acids, compounds against microbes, vitamins and factors required for growth. The chief cognitive factors of rhizosphere micro- biome framework are root exudates. The composition for exudates of root can differ amongst particular species of plant and cultivars and with growth phase and age of plant. Moreover, the exudates of root are affected by the micro- biome, as plants propagated under axenic conditions have noticeably distinct compositions for Arabidopsis thaliana exhibited to have distinct compositions for root exudates and likewise different communities of rhizospheric bacteria, while the communities of rhizospheric bacteria of another successions have demonstrated great similarity (Bertin et al. 2003).
Rhizodeposition consists of several different components apart from root exudates. The mucilage release and the shedding of root cells accumulated a huge quantity of substances in the rhizosphere, involving polymers of plant cell- wall like pectin, cellulose. Degradation of cellulose is extensive between microbial inhabitants of soils having excessive quantity of organic matter. Methanol gets release as a result of pectin decomposition, which further can be utilized by microorganisms as a source of carbon and within the rhizosphere methanol’s active metabolism has been noticed. Apart from making availability for carbon source to inhabitants of rhizosphere, the roots of plant also renders a substrate to microorganisms to anchor. Therefore, this is the examination of important overlap amongst root- attaching- bacteria and to a static structure of wood (Stursova et al. 2012; Haichar et al. 2007)
Researches on micro- biomes of rhizospheric region have unveiled phenomenal identical division of microbial phyla while comparing strains and species of microorganisms the differences amongst cultivars of plant become pronounced. The samples, especially those belong to the alpha (?) and beta (?) classes are generally dominated by Proteobacteria whereas the further substantial groups involve Bacteroidetes, Actinobacteria, Acidobacteria, Firmicutes, Verrucomicrobia and Planctomycetes (Inceoglu et al. 2011; Teixeira et al. 2010).
Out of special sapidity in the environment of rhizosphere are rhizobacteria imparting plant growth, which function by means of several mechanisms. An endo- symbiotic bacteria like Rhizobium spp. and bacteria that fixes nitrogen (N2) involving aerobic and free- living Azotobacter spp.; proffer a fixed source of nitrogen for plant, whereas minerals having phosphorous can be solubilised by a number of bacteria, resulting bioavailability amplification. Manipulation of phytohormones by microbes, especially gibberellins, ethylene and auxins, may also come up to provide growth or drought stress. Several rhizobacteria that promotes growth to a plant function in opposite towards phytopathogens by generating antimicrobials or by intervening with virulence factors through effectors provided by T3SSs- type 3 secretion systems. Especially Actinomycetes, are said to generate a vast variety of compounds accompanied by anti- viral, anti- bacterial, insecticidal, anti- fungal and nematicidal properties. In soil and rhizosphere, the class Actinomycetes are usually appeared as one of the most copious classes of bacteria, and are particularly refined in communities of endophytes (Rezzonico et al. 2005).
The indorsement exhibiting the close relationships of root exudates that they have on the rhizospheric composition of microbes is setting- up (Broeckling et al. 2008; Badri et al. 2009, 2013a; Micallef et al. 2009b; Chaparro et al. 2012, 2013), wherewith in exudates of root there are numerous chemicals present which can behave as signaling molecules, substrates etc. to coordinate alterations in composition of microbes. Lately, it was revealed that the framework of root exudates of Arabidopsis alter subsequently a gradient in development of plant (Chaparro et al. 2013). The accumulative release quantities of sugars and alcohols’ sugar were much more during initial time points but got reduced through growth of plant. While on the other hand, the accumulative release quantities of phenolics and amino acids amplify over time. In that manner, it was formulated that during initial phases of development, sugars were released by root seedlings as a substrate for a vast variety of microbes, but as the plant grows it secretes certain substrates and probably compounds against microbes (antimicrobial) in an attempt to choose for specific microbial residents of rhizosphere. From the region of rhizosphere this prospective picking of microbes as the plant grows might be connected with the possibility of advantageous microbes to inhibit pathogenic microbes (Mendes et al. 2011), activate induced- systemic- tolerance (IST) to control abiotic stress (Selvakumar et al. 2012), amplify the innate immunity of plant (Zamioudis and Pieterse, 2012), aid in mineral nutrition (Bolan, 1991; van der Heijden et al, 2008) and altogether health of plant (Berendsen et al. 2012; Chaparro et al. 2012).
The Phyllosphere environs
The Phyllosphere acts as common niches for co- operation between microorganisms and plant. The leaf blade has been referred as phylloplane whereas; the region of plant above the ground occupied by microbes is called Phyllosphere. The leaves usually are exposed to air stream and dust stream and thus, leading to the development in the establishments for particular flora with the help of waxes, appendages and cuticles superficially, which further aid in the enlacement of microbes. The microorganisms present in phyllosphere may exist or multiply on leaves determined by the area of influences of substance in exudates of leaf. The exudates of leaf carry the fundamental nutrients components such as C6H12O6 (Glucose), C12H22O11 (Sucrose), amino acids etc and these particular dwelling may render niche for fixing of Nitrogen and release of compounds that are able to promote the plant growth. Moreover, the microorganisms exist in phyllospheric region may play a fundamental role in preventing diseases of plant by controlling air- borne pathogens. Microorganisms present on surface of leaf are referred as extremophiles as they can survive in extreme range of temperatures (5-55oC) and ultraviolet radiation. Several microorganisms like Pseudomonas, Pantoea, Diplococcus, Azotobacter, Xanthomonas, and Bacillus etc. have been observed in various plants of crop’s phyllosphere (Dobrovolskya et al. 2017).
The plant’s aerial surface is presumed quite low- nutrient as compare to the rhizosphere. Microorganisms which colonize the leaves are not uniform but are swayed by structures of leaf like stomata, veins and hairs. Approximately, 107 microorganisms per square centimetre colonize the surface of leaf. The phyllosphere is greatly a potent environment as compare to rhizosphere, with inhabitant microorganisms dependent on large variations in temperature, radiation and humidity all through the day- night. Abiotic factors like these accidentally influence the micro- biome of phyllosphere through alterations in metabolism of plant. Especially, precipitation and air currents are considered to cause terrestrial commutability in inhabitant microorganisms of phyllosphere. The metabolite outline of A. thaliana leaf has been changed interestingly by implementation of soil- microorganisms to roots: enhanced concentration of various amino acids in the metabolome of leaflet was matched with enhanced herbivory from insects, propounding cross- talk amongst above and beneath ground plant parts (Lindow and Brandl, 2003).
By using PCR, the rRNA- genes have been amplified to profile communities of bacteria and fungi present in phyllospheric regions of different plants. It was observed that the abundance of microbes are very high in warmer climate, more in humid as compare to temperate climate. Correspondingly, the phylum of bacteria which is found to be dominant is Proteobacteria (classes- alpha and beta) generally with Actinobacteria and Bacteroidetes. During summer, various plants’ phyllospheres were noticed to be oppressed by LAB- Lactic acid Bacteria i.e. firmicutes in the Mediterranean. Lactic acid bacteria’s metabolism mode was suggested to permit them to withstand against warm and parched weather conditions. However this was not contrasted among distinct seasons. At higher levels of taxonomy of microorganisms, the microbes of several plants’ phyllospheres can be found identical, but clear differences are visible at the strain and species levels, considering nicely modulated metabolic adaptations needed to exist in above- mentioned environment. However, the micro- biomes of rhizospheric region are homological to soil; some resemblance has been observed amongst micro-biomes of phyllosphere and micro- biomes of air (Vokou et al. 2012).
Proteogenomic analysis of several micro- biomes of phyllosphere have unveiled species that absorb and digest amino acids, carbohydrates and ammonium derived from plants, entailing these compounds as principal sources of nitrogen (N) and carbon (C) in the phyllospheric region. Researches also discovered that Methylobacterium spp. and rest methylotrophs were extensively prolific phyllospheric microorganisms, and further they were dynamically absorbing, digesting and metabolizing methyl alcohol (CH3OH) extracted from pectin of plant (Galbally and Kirstine, 2002).
The Endosphere environs
The microorganisms which reside in the internal regions of plant like root stem etc. without affecting the host plant. The term ‘Endophyte’ is derived from the two Greek words, ‘endo-‘ means ‘within’ + ‘-phyte’ means ‘plant’. In other words, endophytes are those which reside in tissues of plant for not of their whole life but at least portion of it. They are usually presumed to be non- pathogenic. They cause no noticeable symptoms, however they involve dormant (latent) pathogens that can cause infection based on an environmental situations and/ or genotype of host. The endophytic microbes are considered as a subpopulation of the rhizospheric micro- biome, however they possess different features from bacteria of rhizosphere, proposing that not every bacteria of rhizosphere can invade plants, and if they enter into the host; they can alter their own metabolism and thus become adjusted according to the host’s internal environment. Though it is usually reckoned that the microbe (bacteria) isolated from the tissues of plant after sterilization of surface are said to be ‘endophytic’, but the case is different for aerial parts and roots surfaces as there are several niches on them where the microbes may persist even after treatment with chemicals i.e., commonly used for sterilization of surface, and to confirm about that specific bacteria whether it is truly endophytic or not; techniques like confocal microscopy, TEM- Transmission electron microscopy and the samples that are embedded in resin are used (Compant et al. 2010; Monteiro et al. 2012; James, 2010). In the late researches, it was found that ‘sonication’ technique was used to eliminate plant tissue’s layers surface and the tissue that is remained is used to describe endophytic micro- biome. Researches like these has unveiled that endophytes mainly inhibit slaughtered or moribund cells and in inter- cellular apoplast, and as still the endophytes didn’t confirmatively exhibit to inhabit cells that are alive in the similar arrangement as true symbioses, like that amongst rhizobia and legumes. Generally, they exist in the vessels of xylem where they can be translocated from roots to other parts of plant above the ground (Lundberg et al. 2012; Bulgarelli et al. 2012).
But here is the question that how does endophytic bacteria invades their hosts originally? The foremost evidence indicates that they invade most probably from cracks occurring naturally. The endophytic microorganisms mainly invade in the host (plant) through punctures, happening naturally as a consequence of plant development or via hairs of root and at epidermal juxta- positions. Endophytic microbes can be spread mainly via two pathways, horizontal or vertical. An endophytic micro- biome may be altered by factors like several environmental influences, plant development phase, physicochemical soil structure etc (Lian et al. 2008; Mitter et al. 2017). The chief route taken by endophytic bacteria for colonization appears to be the rhizospheric environment. Endophytes arrives the rhizospheric region via. Chemotaxis in the direction of elements of root exudates proceeds by attachment. The elements which exhibited to play functions in attachment are exo- polysaccharide and lipopolysaccharide; they help in attaching of endophytic bacteria to tissue of plant. The favoured attachment site and following entry is the root- zone (apical) with a layer of surface root (thin- walled), for instance the zone of cell- elongation and the zone of root- hair with little cracks produced by the development of lateral roots. Furthermore, zone of differentiation and epidermis’s intercellular spaces- the root regions also propounded to be favoured locations for colonization of microbes. Wounds, crevices in roots caused by arthropods and sites for development of lateral roots are usually presumed as major doors for penetration of microbes. Cellulytic enzymes like endopolygalacturonidases and endoglucanases are needed to be produce by bacteria in order to hydrolyse exo- thermal walls for penetration (Suman et al. 2016).
Plant age is inversely proportional to bacterial concentration that means younger plants have high concentration of bacteria as compare to mature plants. In addition, the endophytic bacteria concentration is less than those of epiphytes. Analysis of meta- genome (Sessitsch et al. 2012) and Transcripts of nifH and 16S rRNA analysis (culture- independent approaches) showed enormous endophytes diversification in the thrifty fundamental crops like rice and sugarcane. Lately, 16S rRNA high throughput sequencing has been used to describe the vital endophytic micro- biome of Arabidopsis thaliana (Fischer et al. 2012).
The trends of ongoing research as stated, it appears probably that datasets of metagenome will run on to increase quickly and shortly dominate the datasets of complete genome sequence obtained from cultured microorganisms. However, these datasets will give information regarding genome matter; there is no apparent hint of dynamics expression or expression of gene. Though, techniques like qPCR i.e., quantitative PCR may be employed to natural samples for quantification of gene expression, these are finite, normally to quantify little quantity of known genes. By the accomplishment of more than 134 metagenomes sequence, the examining of universal alterations in expression of genes, would- be known as transcriptomics, is an progressively interesting mechanism for analysing the molecular motive of metabolic and ecological features (Liu and Zhu, 2005). The techniques used for metagenome gene expression analysis are discussed below:
DD- PCR or DDRT- PCR is an abbreviation for Differential display- PCR or Differential display reverse transcription PCR. It is a technique fully based on PCR that permits comparison of several samples of RNA at the same time and further help in the recognition of both induced as well as suppressed genes. This technique involves the two fundamental steps: (i) to construct a cDNA library for every single sample of RNA isolated from different communities along with a set of degenerate, has to be reverse transcribed by anchoring oligodeoxy- thymidine nucleotides to the end (ii) Amplification by PCR of partial sequences chose randomly from the library of cDNA with the authentic anchored deoxy- thymidine (dT) primer and arbitrary primer (upstream). DDRT- PCR is carried out using the same sets of primer on different cell populations (Liang and Pardee, 1992). The basis of this approach is to compare the pools of mRNA isolated from microbes grown under different conditions, subsequently reverse transcribed and amplification by PCR at random sites and following by sequencing. However earlier this methodology was employed for genes enrichment with a preferred microbe observing their induced expression when the microorganisms gets expose to controlled conditions, then it started employed to total RNA straight forwardly extracted from samples collected from environment (Fleming et al. 1998; Aneja et al. 2004; Sharma et al. 2004). In this metagenomic sphere the current examples involves the invention of a novel operon for degradation of 2, 4- dinitrophenol (Walters et al. 2001), and in mixed cultures genes for cyclohexanone monooxygenase (Brzostowicz et al. 2003). Therefore, DDRT proffers an effective strategy for deciphering expression of gene in microbes present in the environment separately of sequence understanding and without culturing. The major limitation of this approach originates from the information that, there is no transcript signal present globally in bacteria that permits for homogeneous amplification of total mRNA (Vieites et al. 2009).
cDNA- AFLP stands for cDNA- amplified fragment length polymorphism. This is another valuable advance technique of Polymerase Chain Reaction where primers (random hexamers) are used to synthesize cDNA from total RNA (Egert et al. 2006). Two restriction endonucleases are used to digest the fragments obtained; generally 4bp or 6bp long cutter is used, and then to the ends of the fragments adaptors are ligated. The amplified products are separated by electrophoresis and the lengths of the fragments obtained are approximately about 100- 400 bp. Bands intensities differences that can be visualized and thus confer a worthy evaluation of the comparable differences in the degrees of gene expression. Recognition of the corresponding whole- length cDNA is generally required for the further evaluation of fascinating transcripts. However, this technique has the ability that may connect microbial encoding capacity with function of environment, whereas its relevance to approach like Metagenomics is finite so far as the rRNAs stability is low and a few examples are confined basically to intestinal samples (Egert et al. 2006).
Suppressive Subtractive Hybridization (SSH)
SSH stands for Suppressive Subtractive Hybridization. It is an extensively used technique for DNA molecules separation that differentiates the two samples of DNA which are closely related. There are two prime applications of SSH: (i) subtraction of cDNA and (ii) subtraction of genomic DNA (Rebrikov et al., 2004). In actual, to produce either subtracted cDNA or gDNA libraries SSH is one of the highly effective and accepted technique. This technique is particularly based on PCR suppression effect and joins normalization and subtraction in a solo process. This combination works in the following manner; the normalization step equals the plentifulness of fragments of DNA within the selected population while the subtraction step scoops out the repeated sequences that exist in the compared populations. This increase the chances dramatically of making less abundance differentially manifested cDNA or DNA metagenome snippets and make the analysis easier of the subtracted library (Rebrikov et al. 2004). In ingenious study, researchers employed this method amalgamated with metagenomic strategy to discover an emergent big distinctness in the community structure of archaea amongst the rumen microorganism communities of two bulls fed similar diets and accommodated together, which might be quite tough to identify by applying other usual techniques (Galbraith et al. 2004).
Subtracted libraries of cDNA to recognise genes expressed differentially amongst samples collected from environment may be produced by applying SSH technique. This strategy will lead to the separation of exclusive novel niche and pathways of active metabolism (Rebrikov et al. 2004). Following are the steps to create subtractive libraries: (i) Isolation of mRNA from various comparable samples; (ii) Generation of cDNA; and (iii) Subtraction of cDNA populations. Preliminary examination disclosed that metagenomic data of 1-2 Gbp of polluted vs. ancient sites are transformed into 30-200 SSH clones of c. 20,000 bp each i.e., 0.001% subtractive clones. The escaping DNA fragments subtracted and may be cloned to compose short libraries of SSH, supplying a surplus of targets of gene active in opposition to pollutants in a manner completely not dependent of the coinciding roles in ancient and pollutant sites. Therein, cDNA got ready, for instance, for further subtraction to isolate snippets parallel to genes whose level of expression was enhanced. Here, the samples collected from the polluted sites were referred as ‘tester’ while the ancient samples were referred as ‘driver’ (Vieites et al. 2009).
Catalyzed Reporter Deposition Fluorescence in Situ Hybridization (CARD- FISH) is another powerful technique for qualitative evaluation of gene activity in vivo. Although, this methodology is only applicable for quantification of transcripts of genes already studied. The actual sequence of the gene must be known to construct the probe for this particular tool. Therefore, this restrains the usage of this methodology in study of metagenomes based on activity as in most of the cases; one must work with unfamiliar genes and should make efforts to unveil new roles and activities rather than working on already studied genes (Vieites et al. 2009).
DNA microarray is one of the most powerful technologies which have immense capacity to perceive the meaning of microbial systems. It is a technology developed by Stephen Fodor in the late 1980s and is also known as Biochip or DNA chip. Genomic technology based on Biochip is a robust tool for observing a large number of genes expressions in a single experiment simultaneously (Hoheisel, 2006). At the beginning this technology was though purposely intended for characterizing an individual species transcriptionally but, dramatically its usage have been developed to environmental usage in current years (Zhou &Thompson, 2002, 2004; Adamczyk et al. 2003; El Fantroussi
et al. 2003; Taroncher- Oldenburg et al. 2003; Zhou, 2003; Loy et al. 2004; Tiquia et al. 2004; Bodrossy et al. 2006; An& Parsek, 2007). One of the biggest challenges in employing DNA chip for examining samples collected from environment is the small detection sensitivity of hybridization based on microarray, in fusion with the little biomass present frequently in environmental setting’s samples. DNA chips for expression characterization can be split into two broad groups: (i) DNA chips on the basis of deposition of pre-compiled DNA probes; (ii) on the basis of oligonucleotide probes synthesised in situ. Examples of oligonucleotide probes are Affymetrix arrays etc. A lot of applications use DNA microarrays involves, for instance, Profiling of microbe communities isolated from environmental samples like water and soil (Zhou, 2003; Eyers et al. 2004), Detection of pathogens in clinical samples and those isolated from field (Bodrossy and Sessitsch, 2004) and checking of food and water contamination by bacteria (Lemarchand et al. 2004). To decipher the diversity in microbes of different environments there are several varieties of DNA microarray that have been employed. For instance, those involves oligonucleotide made up of 20-70 bp (Ward et al. 2007), fragments of amplified DNA (cDNA) by PCR (Wu et al. 2004), and complete genome DNA. Until now, Meta DNA chip research has observed gene expression worldwide in more than 20 distinct environments covering a massive diversity area of research (Bae et al. 2005).
The microarrays use to outline the libraries of metagenome may proffer a constructive proposal for quick characterization of numerous clones. For an instance, a fosmid library was procured and further arranged on a glass slide (Sebat et al. 2003). This out- lay is mentioned as MGA: Metagenome microarray. In this particular format, the notion of ‘probe’ and ‘target’ is just an inverse of those of common cDNA and oligonucleotide microarrays. Here, the fosmid clones are referred as ‘targets’ are found on a slide and a particular gene probe is tagged and employed for hybridization. This format of Biochip may proffer worthwhile approach of screening metagenome for recognizing clones quickly from libraries of metagenome without the necessity of tedious methods for screening several target genes. Researchers (Sebat et al. 2003; Park et al. 2008) employed this Biochip programme to screen the library of metagenome with complete genome of microbes and genome of communities. To assess the eukaryotic soil microbe communities’ functional diversification, an experimental strategy was evaluated by Bailey et al. (2007) on the basis of building and screening library of cDNA from a meta- transcriptome by utilizing forest soil extracted polyadenylated mRNA. The variety of organisms was analysed by sequencing a segment of rRNA genes (18S) and cDNA. The evaluation of meta- transcriptome unveiled that the taxonomic division did not match; nevertheless, there are 180 numbers of species that were not even existed in soil and sequences that were somewhat connected to protists and fungi were 70%. DNA based biochip identification strategies integrated with complete community of amplified genome has been used to examine the structure of microbic community in little- biomass groundwater microbic communities (Wu et al. 2006). Although, this strategy couldn’t be acclimatized straight and used for activity examination based on mRNA. An actual trouble in detection of mRNAs isolated from environmental samples by using Biochip hybridization is getting an adequate quantity of mRNAs for evaluation. Prior to hybridization a few type of amplification signal is required. Nevertheless, amplification based on random- PCR is not a suitable option because of amplification biasness and therefore the loss of quantitative data (Nygaard and Hovig, 2006). Furthermore, the gene after gene feature of conventional PCR strongly inhibits the turnout benefits of analysis by microarray for functional genes. To resolve this issue, a brand new technique was evolved called WCRA (whole community- RNA amplification) for amplifying complete community of RNAs randomly to provide adequate mRNAs quantity for analysis by microarray isolated from environmental samples (Gao et al. 2006).
The mRNA half- life is short which leads to one of the massive complication concerned with microarray (Selinger et al. 2003; Andersson et al. 2006) and in archaea and bacteria that very mRNA generally comprise of little function of complete RNA. Lately, various methods have been evolved for solving these challenges. It is quite a daunting task to decipher the expression of gene using DNA chip of sample isolated from an environment. First of all, in cDNA microarrays based on PCR, sensitivity may sometimes be the issue, as merely genes out of populations contributing to more than five percent of the DNA community can be detected. Secondly, the samples may carry several contaminants from environment that alter the RNA quality and hybridization of DNA (Zhou and Thompson, 2002) and hence, extraction of undegraded mRNA becomes quite tough (Burgmann et al. 2003). The specificity of extraction procedure plays a fundamental part and should differ according to the sampling location, as there must be enough differentiation amongst probes. In addition, annotation and extensive proteins’ functional characterization remain tough, error prone procedures as systems microbiology depends majorly on a overall knowledge of gene product functions (Morrison et al. 2006).
Host Effect on the Plant micro- biome
The communications among the plants and the microbes surrounding it are extremely powerful and complicated. Remarkably, the plant’s immune system is contemplated to have a significant contribution in characterizing the microbiome structure of plant. Arabidopsis thaliana mutants lacking in an innate immune response called SAR (System acquired resistance) that have manifested variations in formation of bacterial community of rhizospheric region when contrasted with wild type, while SAR activated chemically did not effect in notable switch in the bacterial community of rhizospheric region. Furthermore, in the phyllospheric region of A. thaliana, the variety of endophytes was lightened by inductance of salicylic- acid- intermediary resistance, while on the other hand plants lacking in defense mediated via jasmonate revealed greater epiphytic variety. The study proposes that outcomes of plant resistance procedures on the microbiome are inconsistent and for restraining a few bacterial communities, SAR is responsive (Kniskern et al. 2007).
Amongst various plants- related bacteria, especially the Rhizobia, the production of phytohormone like indole-3- acetic acid (IAA) is worldwide, while other phytohormone gibberellins can be produced by some species of Bacillus. Interference with the signaling of jasmonate and ethylene by hormone analogs produced by Pseudomonas syringae results in the opening of stomata and entry of pathogens. It has been reported that the Bacteria can degrade hormones as well as its precursors. For instance, plant ethylene signalling can be inhibited by microbic deamination of 1- aminocyclopropane-1- carboxylic acid (ACC), thus results in high tolerance power of plants to environmental stress (Glick, 2005).
Even though a few chemical signals liberated by plants promotes particular interactions, majority of which are identified by variant organisms. As like, flavonoids activate multiple reactions in root pathogens, mycorrhiza, rhizobia and in different plants. Furthermore, Strigolactones stimulate branching of hyphae in case of mycorrhizal fungi and foster germination of seed in parasitic plants. Whereas, not many genes of plant and pathways have contributions in formation of multiple interactions with distinct microbes; example involve the evolution pathways that are divided among mycorrhizal symbiosis and infection caused by oomycetes and the rhizobial symbiosis and infection caused by nematodes. It is still unknown that how these pathways are communicated with other members of the microbiome and also whether they are able to interact or not (Damiani et al. 2012).
An extensive variety of compounds against microbes (antimicrobial) is produce by plants both constitutively and in respond to disease causing microbes or virus. The Kingdom Plant has variety of compounds like alkaloids, phenolics and terpenoids present worldwide while rest are just limited to specific groups; glucosinolates, for instance, are produced merely by the members of the order Brassicales. In addition, glucosinolates produce naturally by Arabidopsis, whereas, an exogenous glucosinolate produced by transgenic Arabidopsis that further changes the communities of fungus and bacteria in the rhizospheris region and root tissue. Avena strigosa: species whose seeds are consumable commonly known as Oats produces avenacins, a triterpenoid saponin. It protects the plants against fungal pathogens. Mutants of oat deficient in avenacins are much sensitive to fungal pathogen has distinct communities of culturable fungi colonizing roots as compare to wild- type oat having the same genotypes. Unexpectedly, though, a present day universal study about the microbes colonizing rhizosphere of the above two genotypes observed small difference amongst the fungal communities. Amoebozoa and Alveolata, the groups belong to the domain Eukaryota were fiercely affected in the mutant due to the scarcity of avenacins, while bacterial communities remain unaffected. This explains that a minor alteration in genotype of plant can have complicated and unnoticed impacts on plant microbiome. No other research studies did find any remarkable variations in microbes colonizing rhizospheric region amongst normal maize (wild type) and maize modified genetically to produce an insecticidal toxin by a bacteria known as Bacillus thuringiensis- Bt for short and thus the toxin is called Bt toxin, whilst, being insecticidal could be the reason for no significant differences. Moreover, in case of wheat, when the gene pm3bis introduced in the rhizospheric region it conferred resistance to moulds and had negligible impacts against pseudomonads and mycorrhizal fungi colonies. Resistance against disease, involving compounds production against microbes (antimicrobial), is a characteristic suppose to be introduced as an outcome of genetic manipulation or molecular breeding in trying to handle diseases. These can or cannot influence the inhabitants of microbiome, possibility with unnoticed impacts on plant, and should be evaluated based on individuality. This is especially mentioned that the yields of disease resistance genes are usually unspecified (Meyer et al. 2013).
Interplay of microbial complexity and Metagenomics
Evolution results the microbic complexity. The universal consequence of microbial metabolic approaches is the amalgamation of interactions with a universal importance on very miniscule scales. To maintain life on this planet two types of interactions is determined that are necessary to attain biogeochemical cycles. The first type is Microbiological and the second type is chemical interdependence. The association of microbes i.e., microbic community that interacts and in alliance, achieve more in comparison to those of same organisms achieve individually (Lozupone ; knight, 2008). Coming to second type of interaction i.e., chemical interdependence. A sequence of interactions differ from obligate to nominal, is considerate to occur between representatives of microbic communities. Whatsoever be the matter, microbic communities, where the representatives communicate are different from microbic assemblages where the representatives solely co-exist. Apart from the sightedness the massive diversification of worldwide microorganism species; an issue was raised nearly 100 years before, whether microorganism species are worldwide or are much spatial and restricted to a few geographical areas. Present day indorsement suggests that a vast fraction of microbes are not cultured. However, they are confined to a particular habitation and geographical position. Although, a few completely cosmopolitan organisms are there, like the Deep-Sea Marine Group I Archaea (DeLong, 2006) and marine obligate Gammmaproteobacteria (Hydocarbon degrading), i.e., Alcanivorax. Advanced technologies have become accessible; moreover, studies may unveil other microorganisms to be more worldwide than formerly considered (Yakimov et al. 2007).
It is important to pay attention that the proportional richness of a few groups of microbes is not linked on a mandatory basis to the significance of that group in the operation of that community. In a group, ordinary organisms may not inevitably perform a crucial preface despite their figures, and organisms that only enumerate are 0.1% of the group (such as nitrogen fixers) may be of central consequence (Dinsdale et al. 2008). Efficient characterization of this central diversification will impart novel perception of metabolic pursuits and mutuality (dependency on each other) underlying microbic existence, and the function of each and every organism present in ecosystems. In this situation, it is significant to search microbic and enzymatic complements in various niches and how they negotiate functioning of the community. Additionally, ongoing and subsequent systems microbiology approaches can impart a perspective to comprehend the complicate characters of microbic communities, their dynamics, and their influence in naturalistic channel. Systems approaches to microbic summation could vindicate as well in responding the basic queries environmental microbiology, like which organisms are present and what are their activities. For such evaluation, there are few steps to follow: first of all, it is important to recognize the community members under investigation and also the interplay they are occupied in. Nevertheless, as stated in well- ordered perplexity, merely a few microbes are easily culturable. To decipher such microbic communities without culturing every single microbe inspite of their involution and commutability, an approach have been developed with the advancement in molecular techniques now popularly known as ‘Metagenomics’ or ‘Environmental genomics’ (Ferrer et al. 2008). Metagenomics- the word that has been used widely to confine evaluation ranging from studying DNA from environment in dynamic screenings and discovery of the drug to collecting the genomes sample randomly from a little subset of organisms available in an environment (Tringe et al. 2005). To rebuild the metabolism of the life forms i.e. organisms forming the community, also to envisage their functional contributions in the biological community (ecosystem) are the fundamental duties of Metagenomics (sequence- based). A comprehensive analysis of genome statistics may be concatenate with analysis of the expression of genes, usually known as a transcriptome to recognise the genes further related with abrupt interplays among genes and characteristics and produce co- expression systems utilizing a set of DNA sequences (Cavalieri and Grosu, 2004; Ferrara et al. 2008) or for particular taxon probing. Nevertheless, organisms despite pertaining to the similar species have the sequence commutability of genes and an uncompleted genomic data because of the subtlety of communities, borders application of this technique. Modern progression in Mass spectrometry, an analytical technique played a fundamental role by contributing to the solution of this very trouble, enabling an extensive development to be done for protein study (Proteomics), and Metabolomics/ interactomics (Urisman et al. 2005).
Adamczyk J, Hesselsoe M, Iversen N, Horn M, Lehner A, Nielsen PH, Schloter M, Roslev P, Wagner M (2003) The isotope array, a new tool that employs substrate- mediated labeling of rRNA for determination of microbial community structure and function. Appl Environ Microb 69:6875–6887.
Akiyama K, Matsuzaki K, Hayashi H. Plant sesquiterpenes induce hyphal branching in arbuscular mycorrhizal fungi. Nature. 2005; 435:824–827.
Akiyama K, Hayashi H: Strigolactones: chemical signals for fungal symbionts and parasitic weeds in plant roots. Ann Bot 2006, 97:925-931.
Amann RI. Mol. Ecol. 1995, 4:543-553.
An D, Parsek MR (2007) The promise and peril of transcriptional profiling in biofilm communities. Curr Opin Microbiol 3:292–296.
Andersson AF, Lundgren M, Eriksson S, Rosenlund M, Bernander R and Nilsson P (2006) Global analysis of mRNA stability in the archaeon Sulfolobus. Genome Biol 7:R99.
Aneja MK, Sharma S, Mayer J, Schloter M, Munch JC (2004) RNA fingerprinting– a new method to screen for differences in plant litter degrading microbial communities. J Microbiol Meth. 59:223–231.
Arjun JK, Harikrishnan K: Metagenomic analysis of bacterial diversity in the rice rhizosphere soil microbiome. Biotechnol. Bioinf. Bioeng. 2011, 1(3):361-367.
Badri DV, Quintana N, El Kassis EG, Kim HK, Choi YH, Sugiyama A, Verpoorte R, Martinoia E, Manter DK, Vivanco JM (2009). An ABC transporter mutation alters root exudation of phytochemicals that provoke an overhaul of natural soil microbiota. Plant Physiol 151:2006–2017.
Badri DV, Vivanco JM. (2009). Regulation and function of root exudates. Plant Cell Environ 32:666–681.
Badri DV, Chaparro JM, Zhang R, Shen Q, Vivanco JM: Application of natural blends of phytochemicals derived from the root exudates of Arabidopsis to the soil reveal that phenolic- related compounds predominantly modulate the soil microbiome. J Biol Chem 2013, 288:4502-4512.
Badri DV, Zolla G, Bakker MG, Manter DK, Vivanco JM: Potential impact of soil microbiomes on the leaf metabolome and on herbivore feeding behavior. New Phytol 2013, 198:264-273.
Bae JW, Rhee SK, Park JR, Chung WH, Nam YD, Lee I, Kim H ; Park YH (2005) Development and evaluation of genome probing microarrays for monitoring lactic acid bacteria. Appl Environ Microbiol 71:8825–8835.
Bailly J, Fraissinet- Tachet L, Verner MC, Debaud JC, Lemaire M, Wésolowski- Louvel M, Marmeisse R (2007) Soil eukaryotic functional diversity, a metatranscriptomic approach. ISME J 7:632–642.
Bais HP, Weir TL, Perry LG, Gilroy S, Vivanco JM: The role of root exudates in rhizosphere interactions with plants and other organisms. Annu Rev Plant Biol 2006, 57:233-266.
Barea JM, Pozo MJ, Azcon R, Azcon-Aguilar C: Microbial co-operation in the rhizosphere. J Exp Bot 2005, 56:1761-1778.
Bednarek P, Osbourn A: Plant-microbe interactions: chemical diversity in plant defense. Science 2009, 324:746-748.
Bentley DR, Balasubramanian S, Swerdlow HP, Smith GP, Milton J, Brown CG, Hall KP, Evers DJ, Barnes CL, Bignell HR, Boutell JM, Bryant J, Carter RJ, Keira Cheetham R, Cox AJ, Ellis DJ, Flatbush MR, Gormley NA, Humphray SJ, Irving LJ, Karbelashvili MS, Kirk SM, Li H, Liu X, Maisinger KS, Murray LJ, Obradovic B, Ost T, Parkinson ML, Pratt MR, Rasolonjatovo IM, Reed MT, Rigatti R, Rodighiero C, Ross MT, Sabot A, Sankar SV, Scally A, Schroth GP, Smith ME, Smith VP, Spiridou A, Torrance PE, Tzonev SS, Vermaas EH, Walter K, Wu X, Zhang L, Alam MD, Anastasi C, Aniebo IC, Bailey DM, Bancarz IR, Banerjee S, Barbour SG, Baybayan PA, Benoit VA, Benson KF, Bevis C, Black PJ, Boodhun A, Brennan JS, Bridgham JA, Brown RC, Brown AA, Buermann DH, Bundu AA, Burrows JC, Carter NP, Castillo N, Chiara E Catenazzi M, Chang S, Neil Cooley R, Crake NR, Dada OO, Diakoumakos KD, Dominguez- Fernandez B, Earnshaw DJ, Egbujor UC, Elmore DW, Etchin SS, Ewan MR, Fedurco M, Fraser LJ, Fuentes Fajardo KV, Scott Furey W, George D, Gietzen KJ, Goddard CP, Golda GS, Granieri PA, Green DE, Gustafson DL, Hansen NF, Harnish K, Haudenschild CD, Heyer NI, Hims MM, Ho JT, Horgan AM, Hoschler K, Hurwitz S, Ivanov DV, Johnson MQ, James T, Huw Jones TA, Kang GD, Kerelska TH, Kersey AD, Khrebtukova I, Kindwall AP, Kingsbury Z, Kokko-Gonzales PI, Kumar A, Laurent MA, Lawley CT, Lee SE, Lee X, Liao AK, Loch JA, Lok M, Luo S, Mammen RM, Martin JW, McCauley PG, McNitt P, Mehta P, Moon KW, Mullens JW, Newington T, Ning Z, Ling Ng B, Novo SM, O’Neill MJ, Osborne MA, Osnowski A, Ostadan O, Paraschos LL, Pickering L, Pike AC, Pike AC, Chris Pinkard D, Pliskin DP, Podhasky J, Quijano VJ, Raczy C, Rae VH, Rawlings SR, Chiva Rodriguez A, Roe PM, Rogers J, Rogert Bacigalupo MC, Romanov N, Romieu A, Roth RK, Rourke NJ, Ruediger ST, Rusman E, Sanches-Kuiper RM, Schenker MR, Seoane JM, Shaw RJ, Shiver MK, Short SW, Sizto NL, Sluis JP, Smith MA, Ernest Sohna Sohna J, Spence EJ, Stevens K, Sutton N, Szajkowski L, Tregidgo CL, Turcatti G, Vandevondele S, Verhovsky Y, Virk SM, Wakelin S, Walcott GC, Wang J, Worsley GJ, Yan J, Yau L, Zuerlein M, Rogers J, Mullikin JC, Hurles ME, McCooke NJ, West JS, Oaks FL, Lundberg PL, Klenerman D, Durbin R, Smith AJ : Accurate whole human genome sequencing using reversible terminator chemistry. Nature 2008, 456:53-59.
Berendsen RL, Pieterse CMJ, Bakker P: The rhizosphere microbiome and plant health. Trends Plant Sci 2012, 17:478-486.
Berg G, Rybakova D, Grube M, Koberl M. The plant microbiome explored: implications for experimental botany. J Exp Bot. 2016; 67:995–1002.
Bertin C, Yang XH, Weston LA: The role of root exudates and allelochemicals in the rhizosphere. Plant Soil 2003, 256:67-83.
Bloemberg GV, Lugtenberg BJJ: Molecular basis of plant growth promotion and biocontrol by rhizobacteria. Curr Opin Plant Biol 2001, 4:343-350.
Bodenhausen N, Horton MW, Bergelson J: Bacterial communities associated with the leaves and the roots of Arabidopsis thaliana. PLoS One 2013, 8:e56329.
Bodrossy L & Sessitsch A (2004) Oligonucleotide microarrays in microbial diagnostics. Curr Opin Microbiol 7:245–254.
Bodrossy L, Stralis- Pavese N, Konrad- K¨oszler M, Weilharter A, Reichenauer TG, Sch¨ofer D & Sessitsch A (2006) mRNA- based parallel detection of active methanotroph populations by use of a diagnostic microarray. Appl Environ Microbiol 72:1672–1676.
Bolan NS. (1991). A critical review on the role of mycorrhizal fungi in the uptake of phosphorus by plants. Plant and Soil 134:189–207.
Bonfante P: Plant-fungal interactions in mycorrhizas. In eLS. Wiley; 2010.
Braga RM, Dourado MN, Araújo WL. Microbial interactions: ecology in a molecular perspective. Brazilian Journal of Microbiology 2016, 47S:86-98.
Bressan M, Roncato M-A, Bellvert F, Comte G, Haichar FEZ, Achouak W, Berge O: Exogenous glucosinolate produced by Arabidopsis thaliana has an impact on microbes in the rhizosphere and plant roots. ISME J 2009, 3:1243-1257.
Broeckling CD, Broz AK, Bergelson J, Manter DK, Vivanco JM: Root exudates regulate soil fungal community composition and diversty. Appl Environ Microbiol 2008, 74:738-744.
Brzostowicz PC, Walters DM, Thomas SM et al. (2003) mRNA differential display in a microbial enrichment culture: simultaneous identification of three cyclohexanone monooxygenases from three species. Appl Environ Microb 69:334–342.
Bulgarelli D, Rott M, Schlaeppi K, Ver Loren van Themaat E, Ahmadinejad N, Assenza F, Rauf P, Huettel B, Reinhardt R, Schmelzer E, Peplies J, Gloeckner FO, Amann R, Eickhorst T, Schulze- Lefert P: Revealing structure and assembly cues for Arabidopsis root-inhabiting bacterial microbiota. Nature 2012, 488:91-95.
Bulgarelli D, Schlaeppi K, Spaepen S, Ver Loren van Themaat E, Schulze- Lefert P: Structure and functions of the bacterial microbiota of plants. Annu Rev Plant Biol 2013, 64:807-838.
Bürgmann H, Widmer F, Sigler WV & Zeyer J (2003) mRNA extraction and reverse transcription- PCR protocol for detection of nifH gene expression by Azotobacter vinelandii in soil. Appl Environ Microbiol 69:1928–1935.
Carter JP, Spink J, Cannon PF, Daniels MJ, Osbourn AE: Isolation, characterization, and avenacin sensitivity of a diverse collection of cereal root- colonizing fungi. Appl Environ Microbiol 1999, 65:3364-3372.
Cavalieri D & Grosu P (2004) Integrating whole- genome expression results into metabolic networks with Pathway Processor. Curr Protoc Bioinformat 7:7.
Cavaglieri L, Orlando J, Etcheverry M: Rhizosphere microbial community structure at different maize plant growth stages and root locations. Microbiol Res 2009, 164:391-399.
Chaparro JM, Sheflin AM, Manter DK, Vivanco JM. (2012). Manipulating the soil microbiome to increase soil health and plant fertility. Biol Fertil Soils 48:489–499.
Chaparro JM, Badri DV, Bakker MG, Sugiyama A, Manter DK, Vivanco JM: Root exudation of phytochemicals in Arabidopsis follows specific patterns that are developmentally programmed and correlate with soil microbial functions. PLoS One 2013, 8:10.
Chaparro JM, Badri DV, Vivanco JM: Rhizosphere microbiome assemblage is affected by plant development. The ISME Journal 2014, 8:790–803.
Compant S, Clement C, Sessitsch A: Plant growth-promoting bacteria in the rhizo- and endosphere of plants: their role, colonization, mechanisms involved and prospects for utilization. Soil Biol Biochem 2010, 42:669-678.
Conrad R, Erkel C, Liesack W: Rice Cluster I methanogens, an important group of Archaea producing greenhouse gas in soil. Curr Opin Biotechnol 2006, 17:262-267.
Cotta SR, Dias ACF, Marriel IE, Gomes EA, van Elsas JD, Seldin L: Temporal dynamics of microbial communities in the rhizosphere of two genetically modified (GM) maize hybrids in tropical agrosystems. Antonie Van Leeuwenhoek 2013, 103:589-601.
Dakora FD. New Phytol. 2003, 158:39-49.
Damiani I, Baldacci- Cresp F, Hopkins J, Andrio E, Balzergue S, Lecomte P, Puppo A, Abad P, Favery B, Herouart D: Plant genes involved in harbouring symbiotic rhizobia or pathogenic nematodes. New Phytol 2012, 194:511-522.
Darvill AG, Albersheim P: Phytoalexins and their elicitors – a defense against microbial infection in plants. Annu Rev Plant Physiol Plant Molec Biol 1984, 35:243-275.
DeAngelis KM, Brodie EL, DeSantis TZ, Andersen GL, Lindow SE, Firestone MK: Selective progressive response of soil microbial community to wild oat roots. ISME J 2009, 3:168-178.
DeLong EF (2006) Archaeal mysteries of the deep revealed. P Natl Acad Sci USA 103:6417–6418.
Delmotte N, Knief C, Chaffron S, Innerebner G, Roschitzki B, Schlapbach R, von Mering C, Vorholt JA: Community proteogenomics reveals insights into the physiology of phyllosphere bacteria. Proc Natl Acad Sci U S A 2009, 106:16428-16433.
Dennis PG, Miller AJ, Hirsch PR: Are root exudates more important than other sources of rhizodeposits in structuring rhizosphere bacterial communities? FEMS Microbiol Ecol 2010, 72:313-327.
de Weert S, Vermeiren H, Mulders IHM, Kuiper I, Hendrickx N, Bloemberg GV, Vanderleyden J, De Mot R, Lugtenberg BJ (2002). Flagella driven chemotaxis towards exudate components is an important trait for tomato root colonization by Pseudomonas fluorescens. Mol Plant Microbe Interact 15:1173–1180.
Dinsdale EA, Edwards RA, Hall D, Angly F, Breitbart M, Brulc JM, Furlan M, Desnues C, Haynes M, Li L, McDaniel L, Moran MA, Nelson KE, Nilsson C, Olson R, Paul J, Brito BR, Ruan Y, Swan BK, Stevens R, Valentine DL, Thurber RV, Wegley L, White BA, Rohwer F (2008) Functional metagenomic profiling of nine biomes. Nature 452:629–632.
Dobrovolskaya T, Khusnetdinova K, Manucharova N, Golovchenko A (2017) Structure of epiphytic bacterial communities of weeds. Microbiology 86(2) :257-263.
Dohrmann AB, Kuting M, Junemann S, Jaenicke S, Schluter A, Tebbe CC: Importance of rare taxa for bacterial diversity in the rhizosphere of Bt- and conventional maize varieties. ISME J 2013, 7:37-49.
Doornbos RF, Geraats BPJ, Kuramae EE, Van Loon LC, Bakker P: Effects of jasmonic acid, ethylene, and salicylic acid signaling on the rhizosphere bacterial community of Arabidopsis thaliana. Mol Plant Microbe Interact 2011, 24:395-407.
Egert M, de Graaf AA, Smidt H, de Vos WM, Venema K (2006) Beyond diversity: functional microbiomics of the human colon. Trends Microbiol 14:86–91.
El Fantroussi S, Urakawa H, Bernhard AE, Kelly JJ, Noble PA, Smidt H, Yershov GM, Stahl DA (2003) Direct profiling of environmental microbial populations by thermal dissociation analysis of native rRNAs hybridized to oligonucleotide microarrays. Appl Environ Microb 69:2377–2382.
Eyers L, George I, Schuler L, Stenuit B, Agathos SN, Fantroussi SEI (2004) Environmental genomics: exploring the unmined richness of microbes to degrade xenobiotics. Appl Environ Microb 66:123–130.
Ferrara FID, Oliveira ZM, Gonzales HHS, Floh EIS, Barbosa HR: Endophytic and rhizospheric enterobacteria isolated from sugar cane have different potentials for producing plant growth- promoting substances. Plant Soil 2012, 353:409-417.
Ferrer M, Beloqui A, Timmis KN & Golyshin PN (2008) Metagenomics for mining new genetic resources of microbial communities. J Mol Microb Biotech 16:109–123.
Figueiredo MVB, Vilar JJ, Burity HA, Fran?a, F. P. Plant and Soil 1999, 207:67-75.
Fischer D, Pfitzner B, Schmid M, Simões- Araújo JL, Reis VM, Pereira W, Ormeño- Orrillo E, Hai B, Hofmann A, Schloter M, Martinez- Romero E, Baldani JI, Hartmann A: Molecular characterisation of the diazotrophic bacterial community in uninoculated and inoculated field-grown sugarcane (Saccharum sp.). Plant Soil 2012, 356:83-99.
Fleming JT, Yao WH & Sayler GS (1998) Optimization of differential display of prokaryotic mRNA: application to pure culture and soil microcosms. Appl Environ Microb 64:3698–3706.
Galbally IE, Kirstine W: The production of methanol by flowering plants and the global cycle of methanol. J Atmos Chem 2002, 43:195-229.
Galbraith EA, Antonopoulos DA &White BA (2004) Suppressive subtractive hybridization as a tool for identifying genetic diversity in an environmental metagenome: the rumen as a model. Environ Microbiol 6:928–937.
Gao H, Yang ZK, Gentry TJ, Wu L, Schadt CW and Zhou J (2006) Microarray- based analysis of microbial community RNAs by whole- community RNA amplification. Appl Environ Microb 2:563–571.
Gilbert JA, Meyer F, Jansson J, Gordon J, Pace N, Tiedje J, Ley R, Fierer N, Field D, Kyrpides N, Glöckner FO, Klenk HP, Wommack KE, Glass E, Docherty K, Gallery R, Stevens R, Knight R: The Earth Microbiome Project: meeting report of the “1st EMP meeting on sample selection and acquisition” at Argonne National Laboratory October 6 2010. Stand Genomic Sci 2010, 3:249-253.
Ghosh S, Ghosh P, Maiti TK: Production and metabolism of indole acetic acid (IAA) by root nodule bacteria (Rhizobium): a review. J Pure Appl Microbiol 2011, 5:523-540.
Glick BR: Modulation of plant ethylene levels by the bacterial enzyme ACC deaminase. FEMS Microbiol Lett 2005, 251:1-7.
Gutierrez- Manero FJ, Ramos- Solano B, Probanza A, Mehouachi J, Tadeo FR, Talon M: The plant- growth- promoting rhizobacteria Bacillus pumilus and Bacillus licheniformis produce high amounts of physiologically active gibberellins. Physiol Plant 2001, 111:206-211.
Haichar FEZ, Achouak W, Christen R, Heulin T, Marol C, Marais MF, Mougel C, Ranjard L, Balesdent J, Berge O: Identification of cellulolytic bacteria in soil by stable isotope probing. Environ Microbiol 2007, 9:625-634.
Haldar S, Sengupta S. Plant- microbe cross- talk in the rhizosphere: insight and biotechnological potential. Open Microbiol J. 2015; 9:1–7.
Hallmann J, QuadtHallmann A, Mahaffee WF, Kloepper JW: Bacterial endophytes in agricultural crops. Can J Microbiol 1997, 43:895-914.
Hassan S, Mathesius U: The role of flavonoids in root- rhizosphere signalling: opportunities and challenges for improving plant-microbe interactions. J Exp Bot 2012, 63:3429-3444.
Heckman DS, Geiser DM, Eidell BR, Stauffer RL, Kardos NL, Hedges SB: Molecular evidence for the early colonization of land by fungi and plants. Science 2001, 293:1129-1133.
Hein JW, Wolfe GV, Blee KA: Comparison of rhizosphere bacterial communities in Arabidopsis thaliana mutants for systemic acquired resistance. Microb Ecol 2008, 55:333-343.
Hiltner L. Arbeiten der Deutschen Landwirtschafts- Gesellschaft H 1904, 98:59-78.
Hoheisel JD (2006) Microarray technology: beyond transcript profiling and genotype analysis. Nat Rev Genet 7:200–210.
Holben WE, Harris D. Mol. Ecol. 1995, 4:627-631.
Holland MA, Davis R, Moffitt S, OLaughlin K, Tayman B (2000) Using “leaf prints” to investigate a common bacterium. Am Biol Teach 62(2):128-131.
Hong SH, Bunge J, Leslin C, Jeon S, Epstein SS: Polymerase chain reaction primers miss half of rRNA microbial diversity. ISME J 2009, 3:1365-1373.
Horiuchi J, Prithiviraj B, Bais HP, Kimball BA, Vivanco JM. (2005). Soil nematodes mediate positive interactions between legume plants and rhizobium bacteria. Planta 222:848–857.
Hornschuh M, Grotha R, Kutschera U (2002) Epiphytic bacteria associated with the bryophyte Funaria hygrometrica: effects of Methylobacterium strains on protonema development. Plant Biol 4 (6):682-687.
Inceoglu O, Abu Al-Soud W, Salles JF, Semenov AV, van Elsas JD: Comparative analysis of bacterial communities in a potato field as determined by pyrosequencing. PLoS One 2011, 6:11.
Jain V, Nainawatee HS. (2002). Plant flavonoids: signals to legume nodulation and soil microorganisms. J Plant Biochem Biot 11:1–10.
James EK, Olivares FL: Infection and colonization of sugar cane and other graminaceous plants by endophytic diazotrophs. Crit Rev Plant Sci 1998, 17:77-119.
James EK: Nitrogen fixation in endophytic and associative symbiosis. Field Crop Res 2000, 65:197-209.
James EK, Gyaneshwar P, Mathan N, Barraquio QL, Reddy PM, Iannetta PPM, Olivares FL, Ladha JK: Infection and colonization of rice seedlings by the plant growth- promoting bacterium Herbaspirillum seropedicae Z67. MolPlant Microbe Interact 2002, 15:894-906.
Johnson D, Vandenkoornhuyse PJ, Leake JR, Gilbert L, Booth RE, Grime JP, Young JPW, Read DJ New Phytol. 2004, 161:503-515.
Klironomos JN. Ecology 2003, 84:2292-2301.
Kniskern JM, Traw MB, Bergelson J: Salicylic acid and jasmonic acid signalling defense pathways reduce natural bacterial diversity on Arabidopsis thaliana. Mol Plant Microbe Interact 2007, 20:1512-1522.
Knief C, Delmotte N, Chaffron S, Stark M, Innerebner G, Wassmann R, von Mering C, Vorholt JA: Metaproteogenomic analysis of microbial communities in the phyllosphere and rhizosphere of rice. ISME J 2012, 6:1378-1390.
Lebeis SL, Rott M, Dangl JL, Schulze- Lefert P: Culturing a plant microbiome community at the cross- Rhodes. New Phytol 2012, 196:341-344.
Leininger S, Urich T, Schloter M, Schwark L, Qi J, Nicol GW, Prosser JI, Schuster SC, Schleper C: Archaea predominate among ammonia- oxidizing prokaryotes in soils. Nature 2006, 442:806-809.
Lemarchand K, Masson L & Brousseau R (2004) Molecular biology and DNA microarray technology for microbial quality monitoring of water. Crit Rev Microbiol 30:145–172.
Lemarchand K, Masson L & Brousseau R (2004) Molecular biology and DNA microarray technology for microbial quality monitoring of water. Crit Rev Microbiol 30:145–172.
Lian J, Wang Z, Zhou S (2008) Response of endophytic bacterial communities in banana tissue culture plantlets to Fusarium wilt pathogen infection. J Gen Appl Microbiol 54(2):83-92.
Liang P & Pardee AB (1992) Differential display of eukaryotic messenger RNA by means of the polymerase chain reaction. Science 257:971–976.
Lindow SE: Role of immigration and other processes in determining epiphytic bacterial populations – implications for disease management. In Aerial Plant Surface Microbiology. New York: Plenum; 1996:155-168.
Lindow SE, Brandl MT: Microbiology of the phyllosphere. Appl Environ Microbiol 2003, 69:1875-1883.
Liu WT & Zhu L (2005) Environmental microbiology- on- a- chip and its future impacts. Trends Biotechnol 23:174–179.
Loy A, Kusel K, Lehner A, Drake HL, Wagner M (2004) Microarray and functional gene analyses of sulfate- reducing prokaryotes in low- sulfate, acidic fens reveal cooccurrence of recognized genera and novel lineages. Appl Environ Microb 70:6998–7009.
Lozupone CA & Knight R (2008) Species divergence and the measurement of microbial diversity. FEMS Microbiol Rev 32:557–578.
Lundberg DS, Lebeis SL, Paredes SH, Yourstone S, Gehring J, Malfatti S, Tremblay J, Engelbrektson A, Kunin V, del Rio TG, Edgar RC, Eickhorst T, Ley RE, Hugenholtz P, Tringe SG, Dangl JL: Defining the core Arabidopsis thaliana root microbiome. Nature 2012, 488: 86-90.
Maizel JV, Mitchell HK, Burkhardt HJ: Avenacin antimicrobial substance isolated from Avena sativa. 1. Isolation + antimicrobial activity. Biochemistry 1964, 3:424-426.
Margulies M, Egholm M, Altman WE, Attiya S, Bader JS, Bemben LA, Berka J, Braverman MS, Chen YJ, Chen Z, Dewell SB, Du L, Fierro JM, Gomes XV, Godwin BC, He W, Helgesen S, Ho CH, Irzyk GP, Jando SC, Alenquer ML, Jarvie TP, Jirage KB, Kim JB, Knight JR, Lanza JR, Leamon JH, Lefkowitz SM, Lei M, Li J, Lohman KL, Lu H, Makhijani VB, McDade KE, McKenna MP, Myers EW, Nickerson E, Nobile JR, Plant R, Puc BP, Ronan MT, Roth GT, Sarkis GJ, Simons JF, Simpson JW, Srinivasan M, Tartaro KR, Tomasz A, Vogt KA, Volkmer GA, Wang SH, Wang Y, Weiner MP, Yu P, Begley RF, Rothberg JM: Genome sequencing in microfabricated high- density picolitre reactors. Nature 2005, 437:376-380.
Mark GL, Dow JM, Kiely PD, Higgins H, Haynes J, Baysse C, Abbas A, Foley T, Franks A, Morrissey J, O’Gara F: Transcriptome profiling of bacterial responses to root exudates identifies genes involved in microbe- plant interactions. Proc Natl Acad Sci U S A 2005, 102:17454-17459.
Marschner: Mineral Nutrition in Higher Plants. 2nd edition. London: Academic Press; 1995.
Melotto M, Underwood W, Koczan J, Nomura K, He SY: Plant stomata function in innate immunity against bacterial invasion. Cell 2006, 126:969-980.
Mendes R, KruijtM, De Bruijn I, Dekkers E, van der VoortM, JHM Schneider et al. (2011). Deciphering the rhizosphere microbiome for disease-suppressive bacteria. Science 332:1097–1100.
Mendes R, Garbeva P, Raaijmakers JM. The rhizosphere microbiome: significance of plant beneficial, plant pathogenic, and human pathogenic microorganisms. FEMS Microbiol Rev. 2013; 37:634–663.
Mendes R, Raaijmakers JM. Cross- kingdom similarities in microbiome functions. ISME J. 2015; 9:1905–1907.
Meyer JB, Song- Wilson Y, Foetzki A, Luginbuhl C, Winzeler M, Kneubühler Y, Matasci C, Mascher- Frutschi F, Kalinina O, Boller T, Keel C, Maurhofer M: Does wheat genetically modified for disease resistance affect root- colonizing pseudomonads and arbuscular mycorrhizal fungi? PLoS One 2013, 8:12.
Micallef SA, Shiaris MP, Colon- Carmona A: Influence of Arabidopsis thaliana accessions on rhizobacterial communities and natural variation in root exudates. J Exp Bot 2009, 60:1729-1742.
Mitter B, Pfaffenbichler N, Flavell R, Compant S, Antonielli L (2017) A new approach to modify plant microbiomes and traits by introducing beneficial bacteria at flowering into progeny seeds. Front Microbiol 8:11.
Monteiro RA, Balsanelli E, Wassem R, Marin AM, Brusamarello- Santos LCC, Schmidt MA, Tadra- Sfeir MZ, Pankievicz VCS, Cruz LM, Chubatsu LS, Pedrosa FO, Souza EM: Herbaspirillum- plant interactions: microscopical, histological and molecular aspects. Plant Soil 2012, 356:175-196.
Morrison N, Wood AJ, Hancock D, Shah S, Hakes L, Gray T, Tiwari B, Kille P, Cossins A, Hegarty M, Allen MJ, Wilson WH, Olive P, Last K, Kramer C, Bailhache T, Reeves J, Pallett D, Warne J, Nashar K, Parkinson H, Sansone SA, Serra PR, Stevens R, Snape J, Brass A and Field D (2006) Annotation of environmental OMICS data: application to the transcriptomics domain. OMICS 2:172–178.
Neal AL, Ahmad S, Gordon-Weeks R, Ton J. (2012). Benzoxazinoids in root exudates of maize attract Pseudomonas putida to the rhizosphere. PLoS One 7:e35498.
Nygaard V ; Hovig E (2006) Options available for profiling small samples: a review of sample amplification technology when combined with microarray profiling. Nucleic Acid Res 34:996–1014.
Osbourn AE, Clarke BR, Lunness P, Scott PR, Daniels MJ: An oat species lacking avenacin is susceptible to infection by Gaeumannomyces-graminis var tritici. Physiol Mol Plant Pathol 1994, 45:457-467.
Ottesen AR, Pena AG, White JR, Pettengill JB, Li C, Allard S, Rideout S, Allard M, Hill T, Evans P, Strain E, Musser S, Knight R and Brown E. Baseline survey of the anatomical microbial ecology of an important food plant: Solanum lycopersicum (tomato). BMC Microbiol. 2013:13.
Papadopoulou K, Melton RE, Leggett M, Daniels MJ, Osbourn AE: Compromised disease resistance in saponin- deficient plants. Proc Natl Acad Sci U S A 1999, 96:12923-12928.
Park SJ, Kang CH, Chae JC ; Rhee SK (2008) Metagenome microarray for screening of fosmid clones containing specific genes. FEMS Microbiol Lett 284: 28–34.
Peters NK, Frost JW, Long SR. A plant flavone, luteolin, induces expression of rhizobium- meliloti nodulation genes. Science. 1986; 233:977–980.
Philippot L, Hallin S, Borjesson G, Baggs EM: Biochemical cycling in the rhizosphere having an impact on global change. Plant Soil 2009, 321:61-81.
Pickup RW. J. Gen. Microbiol. 1991, 137:1009-1019.
Pinto AJ, Raskin L: PCR biases distort bacterial and archaeal community structure in pyrosequencing datasets. PLoS One 2012, 7:16.
Rebrikov DV, Desai SM, Siebert PD, Lukyanov SA (2004) Suppression subtractive hybridization. Methods Mol Biol 258:107–134.
Reinhold- Hurek B, Hurek T: Living inside plants: bacterial endophytes. CurrOpin Plant Biol 2011, 14:435-443.
Reinhold- Hurek B, Bunger W, Burbano CS, Sabale M, Hurek T. Roots shaping their microbiome: global hotspots for microbial activity. Annu Rev Phytopathol. 2015; 53: 403–424.
Rezzonico F, Binder C, Defago G, Moenne- Loccoz Y: The type III secretion system of biocontrol Pseudomonas fluorescens KD targets the phytopathogenic chromista Pythium ultimum and promotes cucumber protection. Mol Plant Microbe Interact 2005, 18:991-1001.
Sebat JL, Colwell FS ; Crawford RL (2003) Metagenomic profiling: microarray analysis of an environmental genomic library. Appl Environ Microb 8:4927–4934.
Selinger DW, Saxena RM, Cheung KJ, Church GM, Rosenow C (2003) Global RNA half- life analysis in Escherichia coli reveals positional patterns of transcript degradation. Genome Res 13:216–223.
Selvakumar G, Panneerselvam P, Ganeshamurthy AN, Maheshwari DK. (2012). Bacterial mediated alleviation of abiotic stress in crops. In: Maheshwari DK (ed) Bacteria in Agrobiology: Stress Management. Springer: New York, NY, USA, pp 205–224.
Sessitsch A, Hardoim P, Doring J, Weilharter A, Krause A, Woyke T, Mitter B, Hauberg- Lotte L, Friedrich F, Rahalkar M, Hurek T, Sarkar A, Bodrossy L, vanOverbeek L, Brar D, van Elsas JD, Reinhold- Hurek B: Functional characteristics of an endophyte community colonizing rice roots as revealed by metagenomic analysis. Mol Plant Microbe Interact 2012, 25:28-36.
Sharma S, Aneja MK, Mayer J, Schloter M and Munch JC (2004) RNA fingerprinting of microbial community in the rhizosphere soil of grain legumes. FEMS Microbiol Lett 240:181–186.
Shaw CH. (1991). Swimming against the tide: Chemotaxis in Agrobacterium. BioEssays 13:25–29.
Shi SJ, Richardson AE, O’Callaghan M, DeAngelis KM, Jones EE, Stewart A, Firestone MK, Condron LM: Effects of selected root exudate components on soil bacterial communities. FEMS Microbiol Ecol 2011, 77:600-610.
Stracke S, Kistner C, Yoshida S, Mulder L, Sato S, Kaneko T, Tabata S, Sandal N, Stougaard J, Szczyglowski K, Parniske M: A plant receptor- like kinase required for both bacterial and fungal symbiosis. Nature 2002, 417:959-962.
Stursova M, Zifcakova L, Leigh MB, Burgess R, Baldrian P: Cellulose utilization in forest litter and soil: identification of bacterial and fungal decomposers. FEMS Microbiol Ecol 2012, 80:735-746.
Suman A, Yadav AN, Verma P (2016) Endophytic Microbes in Crops: Diversity and Beneficial impact for Sustainable Agriculture. Microbial Inoculants in Sustainable Agricultural Productivity, Research Perspectives. Springer- Verlag, pp. 117-143.
Tancos K, Cox K (2017) Effects of consecutive streptomycin and kasugamycin applications on epiphytic bacteria in the apple phyllosphere. Plant Dis 101(1):158-164.
Taroncher- Oldenburg G, Griner EM, Francis CA &Ward BB (2003) Oligonucleotide microarray for the study of functional gene diversity in the nitrogen cycle in the environment. Appl Environ Microb 69:1159–1171.
Teixeira L, Peixoto RS, Cury JC, Sul WJ, Pellizari VH, Tiedje J, Rosado AS: Bacterial diversity in rhizosphere soil from Antarctic vascular plants of Admiralty Bay, maritime Antarctica. ISME J 2010, 4:989-1001.
Tiquia SM, Wu L, Chong SC, Passovets S, Xu D, Xu Y, Zhou J (2004) Evaluation of 50- mer oligonucleotide arrays for detecting microbial populations in environmental samples. BioTechniques 36:664–675.
Tringe SG, von Mering C, Kobayashi A, Salamov AA, Chen K, Chang HW, Podar M, Short JM, Mathur EJ, Detter JC, Bork P, Hugenholtz P, Rubin EM (2005) Comparative metagenomics of microbial communities. Science 308:554–557.
Turnbaugh PJ, Ley RE, Hamady M, Fraser- Liggett CM, Knight R, Gordon JI: The Human Microbiome Project. Nature 2007, 449:804-810.
Turner T, Ramakrishnan K, Walshaw J, Heavens D, Alston M, Swarbreck D, Osbourn A, Grant A, Poole P: Comparative metatranscriptomics reveals kingdom level changes in the rhizosphere microbiome of plants. ISME J 2013, in press.
Turner TR, James EK, Poole PS: The Plant MIcrobiome. Genome Biology 2013, 14:209.
Urisman A, Fischer KF, Chiu CY, Kistler AL, Beck S, Wang D and DeRisi JL (2005) E-Predict: a computational strategy for species identification based on observed DNA microarray hybridization patterns. Genome Biol 9:R78.
van der Heijden MGA, Bardgett RD, Van Straalen NM. (2008). The unseen majority: soil microbes as drivers of plant diversity and productivity in terrestrial ecosystems. Ecol Lett 11:296–310.
Verma P, Yadav AN, Kazy SK, Saxena AK, Suman A (2013) Elucidating the diversity and plant growth promoting attributes of wheat (Triticum aestivum) associated acidotolerant bacteria from southern hills zone of India. Natl J Life Sci 10(2):219-227.
Verma P, Yadav AN, Kazy SK, Saxena AK, Suman A (2014) Evaluating the diversity and phylogeny of plant growth promoting bacteria associated with wheat (Triticum aestivum) growing in central zone of India. Int J Curr Microbiol Appl Sci 3(5):432-447.
Verma P, Yadav AN, Shukla L, Saxena AK, Suman A (2015) Alleviation of cold stress in wheat seedlings by Bacillus amyloliquefaciens IARI- HHS2-30, an endophytic psychrotolerant K- solubilizing bacterium from NW Indian Himalayas. Natl J Life Sci 12(2):105-110.
Vieites JM, Guazzaroni ME, Beloqui A, Golyshin PN, Ferrer M: Metagenomic approaches in systems microbiology. FEMS Microbiol Rev 33 (2009) 236–255.
Vokou D, Vareli K, Zarali E, Karamanoli K, Constantinidou HIA, Monokrousos N, Halley JM, Sainis I: Exploring biodiversity in the bacterial community of the Mediterranean phyllosphere and its relationship with airborne bacteria. Microb Ecol 2012, 64:714-724.
Vorholt JA: Microbial life in the phyllosphere. Nat Rev Microbiol 2012, 10: 828-840.
Walters DM, Russ R, Knackmuss H and Pouviere PE (2001) High-density sampling of a bacterial operon using mRNA differential display. Gene 273:305–315.
Wang ET, Schornack S, Marsh JF, Gobbato E, Schwessinger B, Eastmond P, Schultze M, Kamoun S, Oldroyd GED: A common signaling process that promotes mycorrhizal and oomycete colonization of plants. Curr Biol 2012, 22:2242-2246.
Wang KY, Shallcross DE: Modelling terrestrial biogenic isoprene fluxes and their potential impact on global chemical species using a coupled LSMCTM model. Atmos Environ 2000, 34:2909-2925.
Ward BB, Eveillard D, Kirshtein JD, Nelson JD, Voytek MA and Jackson GA (2007) Ammonia oxidizing bacterial community composition in estuarine and oceanic environments assessed using a functional gene microarray. Environ Microbiol 9:2522–2538.
Wrage N, Velthof GL, van Beusichem ML, Oenema O: Role of nitrifier denitrification in the production of nitrous oxide. Soil Biol Biochem 2001, 33:1723-1732.
Wu L, Thompson DK, Liu X, Fields MW, Bagwell CE, Tiedje JM and Zhou J (2004) Development and evaluation of microarray-based whole-genome hybridization for detection of microorganisms within the context of environmental applications. Environ Sci Technol 38:6775–6782.
Yadav AN, Verma P, Kour D, Rana KL, Kumar V, Singh B, Chauahan VS, Sugitha TCK, Saxena AK, Dhaliwal HS: Plant microbiomes and its beneficial multifunctional plant growth promoting attributes. Int J Environ Sci Nat Res. 2017, 3(1):555601.pp. 1-7.
Yakimov MM, Timmis KN & Golyshin PN (2007) Obligate oil degrading marine bacteria. Curr Opin Biotechnol 18:257–266.
Zamioudis C, Pieterse CM. (2012). Modulation of host immunity by beneficial microbes. Mol Plant Microbe Interact 25:139–150.
Zhou J & Thompson DK (2002) Challenges in applying microarrays to environmental studies. Curr Opin Biotechnol 13:204–207.
Zhou J (2003) Microarrays for bacterial detection and microbial community analysis. Curr Opin Microbiol 6:288–294.
Zhou J & Thompson DK (2004) Microarray technology and applications in environmental microbiology. Adv Agron 82:183–270.