TY - JOUR
AU - Nannipieri,, Paolo
AB - ABSTRACT Nitrification is the microbial conversion of reduced forms of nitrogen (N) to nitrate (NO3−), and in fertilized soils it can lead to substantial N losses via NO3− leaching or nitrous oxide (N2O) production. To limit such problems, synthetic nitrification inhibitors have been applied but their performance differs between soils. In recent years, there has been an increasing interest in the occurrence of biological nitrification inhibition (BNI), a natural phenomenon according to which certain plants can inhibit nitrification through the release of active compounds in root exudates. Here, we synthesize the current state of research but also unravel knowledge gaps in the field. The nitrification process is discussed considering recent discoveries in genomics, biochemistry and ecology of nitrifiers. Secondly, we focus on the ‘where’ and ‘how’ of BNI. The N transformations and their interconnections as they occur in, and are affected by, the rhizosphere, are also discussed. The NH4+ and NO3− retention pathways alternative to BNI are reviewed as well. We also provide hypotheses on how plant compounds with putative BNI ability can reach their targets inside the cell and inhibit ammonia oxidation. Finally, we discuss a set of techniques that can be successfully applied to solve unresearched questions in BNI studies. biological nitrification inhibition, BNI compounds, nitrification, ammonia oxidizers, root exudates, rhizosphere INTRODUCTION Nitrification is the microbial conversion of reduced forms of nitrogen (N) to nitrate (NO3−) and represents a key transformation of N in soil-plant systems (Stevenson and Cole 1999). Aerobic nitrification was considered to be a two-step process where ammonia (NH3) was first oxidized to nitrite (NO2−) before subsequent oxidation to NO3−, with these reactions mediated by two autotrophic groups of nitrifying microorganisms or nitrifiers: the ammonia oxidizers (AO), which include the ammonia-oxidizing archaea (AOA) and ammonia-oxidizing bacteria (AOB), and the nitrite-oxidizing bacteria (NOB). However, complete oxidation of NH3 to NO3− (comammox) can also be performed by some members of the Nitrospira genus (Daims et al. 2015; Kartal et al. 2015), which are also common in soil (Pjevac et al. 2017; Wang et al. 2019b). As detailed below, the nitrification process can also be mediated by heterotrophic microorganisms (De Boer and Kowalchuk 2001). The overuse of N in agriculture, mainly applied to soils as urea and ammonium- and nitrate-based fertilizers (Drinkwater and Snapp 2007; Lassaletta et al. 2014), increase the N availability to plants but also creates conditions favoring soil nitrifier activity. Nearly half of N fertilizer input is not utilized by crops (Tilman 2002), and a significant amount of N applied is lost to the environment via nitrification and subsequent denitrification pathways. These N losses cause both environmental impact and increased production costs for farmers. As the nitrification process leads to soil acidification, it also facilitates the leaching of important cations, i.e. Ca2+, Mg2+ and K+ (Likens, Bormann and Johnson 1969; Homann et al. 1994). To limit the problems related to nitrification, several nitrification inhibitors have been synthetized, although only few of them such as nitrapyrin (2-chloro-6-(tri-chloromethyl)-pyridine), dicyandiamide (DCD) and 3,4-dimethylpyrazole phosphate (DMPP) are generally used in agriculture (McCarty 1999; Zerulla et al. 2001). Although the mode of action of these chemicals are not completely understood, they all act by binding to the key enzyme in the first step of nitrification, i.e. the ammonia monooxygenase (AMO) of chemolithoautotrophs (Vannelli and Hooper 1992; Prasad and Power 1995; McCarty 1999). For instance, nitrapyrin inibitis NH3 oxidation by binding to the AMO enzyme after its conversion to 6-chloropicolinic acid (Vannelli and Hooper 1992), or by chelating the copper components of AMO (Campbell and Aleem 1965). In addition, while DCD supresses AMO activity, most likely by impairing the uptake or utilization of NH3 (Zacherl and Amberger 1990), DMPP binds indiscriminately to the complex of membrane-bound proteins including AMO (Chaves et al. 2006). However, the performance of these chemicals vary substantially in different soils (Aulakh and Doran 2001; Barth, Von Tucher and Schmidhalter 2001), particularly in relation to soil texture and clay type, the soil organic carbon content (Shi et al. 2016a), soil temperature and moisture (Chen et al. 2010), that limit their efficacy (Davies and Williams 1995; Merino et al. 2002). Studies have also highlighted a limited capacity of DCD and DMPP to inhibit archaeal NH3 oxidation (Kleineidam et al. 2011). These chemicals may have an additional environmental impact, with adverse effects on non-target microorganisms, i.e. microorganisms not directly involved in the nitrification process. For example, it has been demonstrated that DCD significantly lowered the abundance of the total bacterial community in an arable soil (Patra, Kiran and Pande 2006), whereas DMPP-induced changes in the soil microbial community composition by limiting heterotrophic bacterial and fungal growth (Maienza et al. 2014). Following a cost/benefit analysis of farming practices, the European Commission (EC) does not fully support the use of nitrification inhibitor-stabilized N fertilizers, despite their use can lower the N2O emissions by 26% to 49%, due to their high cost and insufficient testing of effects on non-target organisms (PICCMAT 2011). Therefore, finding other effective strategies to manage soil nitrification represents an important goal in sustainable agriculture. The concept that plants can inhibit soil nitrification was first proposed in the early 1900s by empirical observations of high ammonium (NH4+)/NO3− ratios and low numbers of AOB and NOB in grassland soils (Russell 1914; Richardson 1938; Theron 1951; Basaraba 1964; Munro 1966; Meiklejohn 1968). Control of nitrification by plants may be a factor in improving N use efficiency by crops, and sustaining primary production with zero or limited use of synthetic chemicals (Rice and Pancholy 1972; Boudsocq et al. 2009). Herewith, the Biological Nitrification Inhibition (BNI) postulate was born. It has been hypothesized that the low NO3− content observed in soils under climax vegetation was due to the inhibition of nitrification exerted by plants (Rice and Pancholy 1972). Condensed and hydrolysable tannins, caffeic acid, ferulic acid, ellagic acid, gallic acid and chlorogenic acid were all found to inhibit nitrification at concentrations as low as 10−4-10−8 M (Rice and Pancholy 1973). Later, other organic compounds such as the flavonoids isoquercitrin, myricetin and quercetin, were observed to inhibit ammonia oxidation by a Nitrosomonas AOB, whilst NOB, i.e. a Nitrobacter strain, were less affected by the tested compounds (Rice and Pancholy 1974). However, while these studies are usually cited in support for the inhibitory effects of plant compounds on nitrification, the experimental approach used was not suitable for testing the underlying hypothesis. Specifically, chemicals were first added to a soil suspension before aliquots (1 ml) of the soil suspension were added to a nutrient solution (3 ml) containing ammonium (NH4+) or NO2−, for inhibition studies with Nitrosomonas or Nitrobacter, respectively. Therefore, the soil suspension itself might have affected nitrification. In addition, neither decreases in NH4+ concentration nor NO3− production were measured during these experiments, but only NO2− -N, which is not an univocal indicator of nitrification in nutrient solution, with the oxidation of NO2− to NO3− typically occurring more rapidly than the oxidation of NH4+ to NO2−. On the contrary, some of these compounds such as ferulic acid, caffeic acid, and p-coumaric were tested at the same concentrations on pure cultures of AOB such as Nitrosomonas europaea and Nitrosospira sp., and no inhibitory effect was observed (McCarty, Bremner and Schmidt 1991). Foliar leachates and extracts of balsam fir (Abies balsamea) (Thibault, Fortin and Smirnoff 1982) and the phenolic compound gallocatechin extracted from Leucaena leucocephala roots inhibited nitrification in culture of N. europaea (Erickson et al. 2000). Determining the ability of plants to inhibit nitrification in soil by release of specific compounds can be controversial due to methodological difficulties in demonstrating a direct, rather than simply correlative, link. Indeed, inferring a direct effect of plants on nitrification by measuring low net nitrification rates, low NO3− concentration in soil or by counting nitrifying microorganisms using the most probable number (MPN) technique can be misleading (Robertson and Vitousek 1981). For example, the use of the MPN technique underestimates nitrifier abundance with culturable microorganisms only representing a minor proportion of those inhabiting soil (Torsvik, Sørheim and Goksøyr 1996), therefore limiting the efficiency of this approach (Belser and Schmidt 1978; Belser 1979). In addition, although DNA-based techniques are not constrained by cultivation, the detection of genes coding for enzymes involved in nitrification do not indicate activity. Therefore, if not complemented with other techniques, these approaches cannot discriminate between direct effects, with plants influencing the process through the release of toxic/inhibitory compounds, and indirect effects such as enhanced competition for NH4+ between ammonia oxidizers, heterotrophic microorganisms, plants and arbuscular mycorrhizal fungi (Verhagen, Duyts and Laanbroek 1993; Clein and Schimel 1995; Boyle-Yarwood, Bottomley and Myrold 2008; Chen et al. 2013). There has been a recent renewed interest in this research area, supported by the intriguing possibilities of using plants to regulate NH3 oxidation (Pariasca-Tanaka, Nardi and Wissuwa 2010; Subbarao et al. 2012) and by the use of omic approaches to gain more insights into this plant-mediated process (Nannipieri 2014). A methodology based on the cultivation of plants in nutrient solutions (hydroponics) combined with laboratory bioassays has been developed to obtain direct measures of the capacity of plant-derived compounds to inhibit NH3 oxidation by pure cultures of the AO N. europaea (Iizumi, Mizumoto and Nakamura 1998; Subbarao et al. 2006), and the term biological nitrification inhibition (BNI) was coined to define such plant ability (Subbarao et al. 2012). Using this approach, inhibition of N. europaea activity has been demonstrated by the compound brachialactone, isolated from root exudates of the pasture grass brachiaria (Brachiaria humidicola) (Subbarao et al. 2009), methyl 3-(4-hydroxyphenyl) propionate (MHPP) (Zakir et al. 2008), sorgoleone and sakuranetin (Subbarao et al. 2012) exuded by sorghum roots (Sorghum bicolor), 1,9-decanediol isolated from rice (Oriza sativa) (Sun et al. 2016), plus mixed extracts from rice (Oriza sativa) (Pariasca-Tanaka, Nardi and Wissuwa 2010), and a wild variety of wheat (Leymus racemosus) (Subbarao et al. 2007a). This approach also demonstrated that root tissue extracts and exudates from wheat landraces inhibited NH3 oxidation by N. europaea and Nitrosospira multiformis in pure culture (O'Sullivan et al. 2016). However, as the above-mentioned bioassays rely mostly on a pure culture of Nitrosomonas, rarely testing other strains of AOB (O'Sullivan et al. 2016), and generally not involving AOA and comammox bacteria, it is unclear whether these compounds can inhibit NH3 oxidation by the diverse soil nitrifiers. However, amending soil with MHPP at a concentration equivalent to 350 μg C g−1 soil was observed to reduce NO3− concentration, soil nitrification potential and the abundance of AOA and AOB, suggesting that this compound can inhibit nitrification in soil by repressing the growth and activity of different AO (Nardi et al. 2013). While plants that naturally inhibit nitrification in soil, i.e. BNI plants, represent a fascinating alternative to the use of synthetic inhibitors and may represent a revolutionary practice to control nitrification in agricultural soils, testing their activity is technically challenging due to the complexity of plant-microorganisms interactions occurring in the rhizosphere. In situ experiments are required to find causal links between plant compounds and soil nitrification inhibition to confirm results from in vitro studies. The aim of this review is to discuss the mechanisms of BNI, to underline current gaps in our knowledge, and to promote future research in this field. Specifically, our aims are to: (i) define the theoretical framework of BNI together with other concurrent processes involved in N transformations in the rhizosphere, being the transition zone between plant root and soil microorganisms and (ii) propose a polyphasic approach involving a set of techniques to test the BNI postulate in the soil system. THE NITRIFICATION PROCESS Nitrification in soil is a microbe-mediated process whereby NH3, the most reduced form of nitrogen, is oxidised to NO3−, its most oxidized form. This process is performed by chemolithoautotrophic and chemoorganotrophic (heterotrophic) microorganisms (De Boer and Kowalchuk 2001; Prosser 2005) that differ widely with respect to the sources of carbon, energy and reductant used. Chemolithoautotrophic nitrifiers use either CO2 (AOB, NOB, comammox) or HCO3− (AOA) as their main carbon source (autotrophy), with AO and NOB oxidizing NH3 or NO2−, respectively, as a source of energy (chemotrophy) and reductant (lithotrophy) (Kelly 1971; Kelly and Wood 2006). Chemoorganotrophic nitrifiers, performing heterotrophic nitrification, can oxidize both NH3 or ammonium from reduced organic nitrogen compounds, to NO2− and NO3−, while using organic compounds with two or more carbon bonds as a source of both energy and carbon (De Boer and Kowalchuk 2001; Bock and Wagner 2006). However, AO and NOB can use different substrates as carbon and energy sources. For example, some AOB show intracellular urea hydrolysis activity which allow them to use the hydrolyzation products NH3 and CO2 as energy and carbon sources (Burton and Prosser 2001). This mechanism also explains the ability of some AOB to grow in acidic soils where free NH3 is limited because of its ionization to NH4+. Although urea can also be used by AOA, it remains to be clarified whether its hydrolysis occurs inside or outside the cell (Lu et al. 2012; Tolar et al. 2017). The ammonia-oxidizing bacterium N. europaea can grow on pyruvate and fructose as source of carbon while using NH3 as a source of energy and reductant, thus showing a chemolithoheterotrophic metabolism (Hommes, Sayavedra-Soto and Arp 2003). AOB can grow mixotrophycally using NH3 or urea (an organic one-carbon compound) as energy sources and complex organic compounds such as pyruvate as source of carbon (Clark and Schmidt 1967). The ammonia-oxidizer archaeon Nitrososphaera gargensis, expressing cyanase actvity, can grow on cyanate as the sole source of energy and reductant (Palatinszky et al. 2015). A central distinction between lithoautotrophic and heterotrophic nitrification is that the former supports cell growth by providing energy that is used to fix inorganic carbon, while heterotrophic nitrification represents a form of co-metabolism not coupled with energy conservation and cellular growth (Wood 1987). Thus, for lithoautotrophs, nitrification represents the main strategy to gain energy. We will briefly discuss both chemolithoautotrophic (hereafter referred to as lithoautotrophic) and heterotrophic nitrification by considering nitrifier diversity and ecology, the enzymes involved and their regulation, and relate these to the mechanisms responsible of BNI. However, for an in-depth analysis of nitrifier biology the reader is referred to previously published reviews (Kowalchuk and John 2001; Arp, Sayavedra-Soto and Hommes 2002; Norton et al. 2002; Fiencke, Spieck and Bock 2005; Islam, Chen and White 2007; Schleper and Nicol 2010; Stein 2019). Phylogeny of ammonia-oxidizing microorganisms While aerobic AOB can be found within the Beta- and Gammaproteobacteria, the analysis of 16S rRNA gene sequences from both environmental surveys and cultured isolates reveals that AOB communities from soil are dominated by representatives of the Nitrosomonas and Nitrosospira genera within the Betaproteobacteria (Head et al. 1993; Purkhold et al. 2000), although a gammaproteobacterial AOB (Candidatus Nitrosoglobus terrae) was recently isolated from soil (Hayatsu et al. 2017). The Nitrosomonas genus can be further subdivided into seven major lineages, whereas the Nitrosospira lineage includes four clusters plus organisms unaffiliated to a cluster (Prosser, Head and Stein 2014). The AOA are represented by four orders within the phylum Thaumarchaeota; the Nitrosopumilales, Nitrososphaerales, Nitrosotaleales, and Nitrosocaldales, each of which includes cultivated representatives obtained from soil with the exception of the hyperthermophilic Nitrosocaldales (Könneke et al. 2005; de La Torre et al. 2008; Lehtovirta-Morley et al. 2011; Tourna et al. 2011). Bacterial lithoautotrophic ammonia oxidation NH3 oxidation by AOB was considered a two-step reaction: the oxidation of NH3 to hydroxylamine (NH2OH), which represents the rate-limiting step in the NH3 oxidation and its subsequent conversion to NO2−, catalysed by the enzymes AMO and hydroxylamine dehydrogenase (HAO), respectively. However, a recent study demonstrated that nitric oxide (NO), and not NO2–, is the product of NH2OH oxidation by N. europaea, therefore implying that AOB require three steps to oxidize NH3 to NO2−, with NO acting as obligate intermediate product (Fig. 1) Caranto and Lancaster (2017). Importantly, this finding was consistent with earlier reports indicating the importance of NO on the physiology of AOB, with the addition of NO (i) stimulating the production of AMO (Schmidt, Zart and Bock 2001), NH3 oxidation activity and growth rate of N. eutropha (Zart and Bock 1998) and (ii) enhancing the ability of N. europaea, Nitrosolobus multiformis and Nitrosospira briensis to form biofilms (Schmidt et al. 2004). Figure 1. Open in new tabDownload slide Hypothetical routes of entry of some BNI compounds into AOB cells proposed by this study. NH3 oxidation in AOB according to Caranto and Lancaster (2017). Figure 1. Open in new tabDownload slide Hypothetical routes of entry of some BNI compounds into AOB cells proposed by this study. NH3 oxidation in AOB according to Caranto and Lancaster (2017). AMO is a membrane-bound enzyme that consists of three proteins (AmoA, AmoB and AmoC) encoded by the amoCAB operon (Norton et al. 2002) with the catalytic site containing non-heme iron and at least one copper center (Hyman and Arp 1992; Simon and Klotz 2013). Using the quantitative immunoblot technique, it was found that during cell growth of Nitrosomonas eutropha N904, the amount of AMO was regulated by NH4+ concentration in the medium (Pinck et al. 2001). The authors found high amounts of AMO but low NH3 oxidation activity at limiting NH4+ concentrations, i.e. in starved cells, and low amounts of AMO but high NH3 oxidation activity at high substrate concentration. This implies that (i) the AMO enzyme persists in cells under substrate starvation and (ii) the amount of AMO does not directly correlate with NH3 oxidation rate. In addition, under starvation, AOB have the ability to maintain high levels of rRNA (Johnstone and Jones 1988; Wagner et al. 1996). Furthermore, it has been demonstrated that although the half-life of mRNA in most bacteria has an average of 3 min (Takayama and Kjelleberg 2000), cells of Nitrosomonas briensis maintain high level of amoA transcripts after a starvation period of 12 days (Bollmann et al. 2005). Therefore, to obtain information on AO activity in soil, transcript abundance may not be the best indicator for activity, and thus it should be coupled with process rate measurements. The bacterial AMO enzyme has a broad spectrum of activity which is mirrored by the capacity of AOB to co-metabolize a wide range of non-growth-sustaining compounds (McCarty 1999). The AMO enzyme can be inhibited in a reversible or irreversible manner. Reversible inhibitors form non-covalent interactions with the AMO enzyme and are usually divided into two groups: competitive and noncompetitive, with the first binding only to free enzyme. As the binding of a competitive inhibitor and the binding of substrate are mutually exclusive events, this type of inhibition leads to an increase in the local concentration of the substrate. In addition, when competitive inhibitors share structural similarities with the substrate, the binding occurs at the active site of the enzyme, with examples including alkanes (Hyman and Wood 1983), alkenes (Hyman, Murton and Arp 1988), and aromatic hydrocarbons (Keener and Arp 1994). In contrast, non-competitive inhibitors bind both the free enzyme and the enzyme-substrate complex, thus leading to enzyme conformation changes and reduced catalytic activity. These inhibitors bind exclusively at a site distinct from the active site of the enzyme. Examples of non-competitive inhibitors are chelating agents such as allylthiourea, guanidine, L-histidine and diethyldithiocarbamate (Ward, Courtney and Langenheim 1997). Irreversible inhibitors form stable covalent bonds with the active-site residues of the enzyme. Suicide-inhibitors, also called mechanism-based inactivators, represent a subset of irreversible inhibitors. Acetylene (C2H2), (Hyman and Wood 1985; Kester, Boer and Laanbroek 1996; Schmidt, Bock and Jetten 2001), allylsulfide and allyldisulfide, which are produced by allium species (Allium sp.) and released into the surrounding bulb environment, represent two well-known irreversible bacterial AMO inhibitors (Juliette, Hyman and Arp 1993). The HAO enzyme, which is encoded by the hao gene (Arp, Sayavedra-Soto and Hommes 2002), catalyzes the oxidation of NH2OH to NO. This enzyme is located in the periplasmic space, and is organized into three subunits each containing one iron P460 heme that is the active site of NH2OH oxidation and seven c-type iron hemes that shuttle electrons from the hemes P460 to their acceptor cytochromes (Arp, Sayavedra-Soto and Hommes 2002; Pearson et al. 2007). Considering that oxygen is not required for HAO activity, this enzyme converts NH2OH to NO under both oxic and anoxic conditions. On the other hand, under both oxic and anoxic conditions NH3 oxidation is also coupled with N2O emissions. However, such biochemical mechanism implies the presence of a NO oxidoreductase (NOO) enzyme catalysing the oxidation of NO into NO2-. Thus far, the Cu-containing NO2− reductase (Caranto and Lancaster 2017) and red Cu nitrosocyanin (Lancaster et al. 2018; Zorz et al. 2018) encoded by nirK and ncyA genes, respectively, represent two candidates for the oxidation of NO in AOB, although arguments supporting for or against each of these enzymes have been reported (Kozlowski, Kits and Stein 2016; Stein 2019) and other genes may be responsible for encoding a NOO. The oxidation of NH2OH to NO releases three electrons, while one electron is released from the oxidation of NO to NO2− (Stein 2019). These electrons are shuttled via cytochromes c554 and cM552 to the ubiquinone pool where two molecules of ubiquinone (UQ) are reduced to two ubiquinols (UQH2), which represent the only source of reductive power generated in the entire catabolic process (Hooper and DiSpirito 2013). One UQH2 is reoxidized by providing the AMO enzyme with two electrons that are required for the oxidation of NH3, while the remaining UQH2 electrons are used for the generation of proton motive force to regenerate ATP (Hollocher, Kumar and Nicholas 1982; Bock and Wagner 2006). Importantly, the above three-step model of NH3 oxidation (Fig. 1) calls for a revision of bioassay experiments that were performed to clarify the mode of action of BNI compounds that were tested using pure cultures of AOB incubated with or without NH2OH (Subbarao et al. 2006). In these experiments, the BNI compound, i.e. brachialactone, sorgoleone and sakuranetin, was postulated to act on both AMO and HAO enyzmes if a lack of recovery of AOB activity was observed in the presence of NH2OH (Subbarao et al. 2009, 2013). However, considering that NO, and not NO2−, is the NH2OH oxidation product and an unidentified NOO enzyme is responsible for the formation of NO2−, the lack of AOB activity in the presence of NH2OH might also be attributed to NOO enzyme inhibition by BNI compounds. Archaeal lithoautotrophic ammonia oxidation For over a century, AOB were considered to be the main microbial group driving NH3 oxidation. However, this view was challenged when amo genes were first discovered on archaeal genomic fragments recovered from the ocean (Venter et al. 2004), and soil (Treusch et al. 2005), and confirmed by the isolation of Nitrosopumilus maritimus in culture (Könneke et al. 2005). Many studies have subsequently demonstrated their ubiquitous distribution, with AOA often being numerically dominant over the bacterial counterparts in a broad range of terrestrial environments, including agricultural soils (Leininger et al. 2006; Nicol et al. 2008), volcanic grassland soils (Daebeler et al. 2015), alkaline soils (Shen et al. 2008), acidic soils (Qin et al. 2013), and semiarid soils (Adair and Schwartz 2008). Moreover, with AOA directly contributing to lithoautotrophic NH3 oxidation in soil, and often dominating the process, they have been demonstrated to be a major contributor to the global nitrogen biogeochemical cycle (Offre et al. 2009; Zhang et al. 2010; Pratscher, Dumont and Conrad 2011; Yao et al. 2011; Zhang et al. 2011). After the initial observation that AOA and AOB coexist in most soils, evidence has been provided for substantial niche differentiation between these two functionally analogous groups (Prosser and Nicol 2012). This includes the preference of AOA and AOB for low and high NH4+ concentrations, respectively. AOA often dominate growth when NH4+ is gradually released through the N mineralization process (Levičnik-Höfferle et al. 2012; Hink et al. 2018), whereas the use of soluble fertilizers that quickly increase soil NH4+ concentrations, creates conditions for AOB to dominate growth (Di et al. 2009; Verhamme, Prosser and Nicol 2011). In many acidic soils, while AOB are present, it appears that AOA are the functionally dominant AO group (Gubry-Rangin, Nicol and Prosser 2010; Zhang et al. 2012). Similarly to AOB, the AMO of AOA also contains AmoA, AmoB and AmoC (Kozlowski et al. 2016), although a fourth gene (amoX, Bartossek et al. 2012) is typically associated with the AOA amo gene cluster. Both archaeal and bacterial AMO enzymes are members of the copper membrane monooxygenase (CuMMO) family, which also includes the particulate methane monooxygenase (pMMO). However, studies on amino acid sequence homology revealed that archaeal and bacterial AMO enzymes only share ∼ 40% of amino acid identity, whereas bacterial AMO and pMMO share up to share ∼ 70% of amino acid identity (Sayavedra-Soto and Arp 2011; Stahl and de la Torre 2012). While the amoA, amoB and amoC gene organization is conserved in AOB as amoCAB, it varies between the different lineages of AOA (Lehtovirta-Morley 2018). The crystal structures of archaeal and bacterial AMO have not yet been determined, although differences in amino acid sequence and genes organization strongly suggests that the two enzymes are structurally different (Walker et al. 2010; Alves et al. 2018). Such differences may also explain why the two AMO enzymes have different activity-based inhibition profiles (Wright et al. 2020). AOB are fully or partially inhibited by linear terminal alkynes from C1 to C9, whereas AOA are partially or unaffected by longer-chain-length alkenes, i.e. C6 to C9 1-alkynes (Taylor et al. 2013, 2015). Indeed, among the above alkynes, 1-octyne (C8) is used to specifically inhibit NH3 oxidation in AOB, therefore allowing differentiating the relative contributions of AOA and AOB to nitrification (Taylor, Myrold and Bottomley 2019). While a functional homologue of HAO has yet to be identified in AOA (Schleper and Nicol 2010; Walker et al. 2010; Tourna et al. 2011), AOA oxidize NH2OH. Importantly, similarly to AOB, NO represents an obligate intermediate in the NH3 oxidation carried out by AOA (Stahl and de la Torre 2012; Martens-Habbena et al. 2015). Currently, there are two models for NH3 oxidation in AOA. The first model hypothesizes that an enzyme complex, i.e. Cu-HAO, co-oxidize both NH2OH and NO to form two molecules on NO2−, with one molecule reduced to NO by NirK that returns to the Cu-HAO complex (Kozlowski, Kits and Stein 2016; Stein 2019), the second model suggests that AOA and AOB share a similar pathway for the oxidation of NH2OH and NO (Carini, Dupont and Santoro 2018; Lehtovirta-Morley 2018) (Fig. 2). Figure 2. Open in new tabDownload slide Proposed NH3 oxidation in AOA according to: (A), (Lehtovirta-Morley 2018) and (B), (Kozlowski et al. 2016). Figure 2. Open in new tabDownload slide Proposed NH3 oxidation in AOA according to: (A), (Lehtovirta-Morley 2018) and (B), (Kozlowski et al. 2016). An ecologically important difference between AOA and AOB is the yield of N2O generated during NH3 oxidation. AOB cultures produce substantially greater yields of N2O during NH3 oxidation compared to AOA, likley due to additional enzymatic mechanisms in the former (Hink et al. 2017), and in soil, AOA produce approximately 50% less N2O than AOB when oxidizing an equivalent amount of NH3 (Hink, Nicol and Prosser 2017). As AOB are assumed to dominate NH3 oxidation in highly fertilized soils, it is their activity which likely dominates N2O production in agricultural systems (Prosser et al. 2020). Anammox In addition to the aerobic NH3 oxidation pathway, the anaerobic oxidation of ammonium (anammox) can also occur in anoxic habitats by lithoautotrophic bacteria that use NO2− as an electron acceptor resulting in the production of N2 (Kuenen 2008). The process also oxidizes a portion of NO2− to NO3− to generate reducing equivalent for CO2 fixation (Jetten et al. 2009). While anammox bacteria were considered strictly anaerobic, they can tolerate oxygen (∼70 µM) (Abbas et al. 2019) and are present in a wide range of soil types such as rice paddy soils under both continuous flooding or alternate wetting and drying regimes (Abbas et al. 2020), forest soils (Xi et al. 2016), acidic red soils (Wu et al. 2018), permafrost soils (Philippot, Hallin and Schloter 2007) and peat soils (Hu et al. 2011). The activity of anammox bacteria is stimulated by the availability of N, i.e. NH4+ and NO2−, coupled with the presence of oxic/anoxic zone (Abbas et al. 2020). In the rhizosphere, plant roots and microbial respiration reduce oxigen concentration and create suitable oxic/anoxic interfaces for anammox bacteria. Indeed, several studies demonstrated that amommox bacteria are generally more abundant and active in plant rhizospheres than in the bulk soil (Nie et al. 2015; Li et al. 2016). In such conditions, anammox bacteria activity is supported by AO which provide the substrates, i.e. NH4+ and NO2−, while outcompeting denitrifiers and becoming the dominant pathway of N loss (Pitcher et al. 2010; Abbas et al. 2020). Nitrite oxidation The process of NO2− oxidation, carried out by NOB, involves the transformation of NO2− to NO3−. Contrary to AOB, the NOB are more phylogenetically diverse, with representatives placed within seven bacteria genera: Nitrobacter, Nitrospira, Nitrotoga, Nitrococcus, Nitrospina, Nitrolancetus and Candidatus Nitromaritima (Daims et al. 2016). However, while representatives of Nitrotoga have been cultivated from soil (Alawi et al. 2007), it is Nitrobacter and Nitrospira-like NOB that appear to be functionally important in most terrestrial ecosystems (Freitag et al. 2005). The genus Nitrobacter belongs to the class Alphaproteobacteria, whereas the genus Nitrospira is affiliated with the distinct phylum of Nitrospirae (Ehrich et al. 1995). Nitrobacter-like NOB have been considered as r-strategists with low affinities to NO2− and a relatively high growth rate and require high NO2− concentrations, whereas Nitrospira-like NOB are K-strategists, with low growth rate and well adapted to low NO2− and oxygen concentrations (Schramm et al. 1999). In addition, the genus Nitrospira, the most widespread NOB in different habitats, possess a high metabolic flexibility as they can i) grow under oxic or anoxic conditions, thus coupling or uncoupling the NO2− oxidation rate to energy conservation, respectively, and ii) use hydrogen and formate as alternative energy sources in the absence of NO2−, therefore showing mixotrophic metabolism (Koch et al. 2015). In addition, nitrite-oxidizers from the genus Nitrospira are capable of using cyanate as energy source (Palatinszky et al. 2015). It is worth noting that a part of the NH4+ produced from cyanate degradation is directly assimilated, while another part is excreted, thus feeding AO with their substrate, which also challenges the paradigm of obligate trophic dependence of NOB on AO. NOB use the enzyme nitrite oxidoreductase (NXR) to convert NO2− to NO3− (Starkenburg et al. 2006), but also to reduce NO3− to NO2−, therefore making the NO2− oxidation a reversible reaction (Starkenburg et al. 2006). NXR is a membrane bound enzyme with its active site facing the cytoplasm in Nitrobacter and the periplasmic spaces in Nitrospira (Spieck et al. 1998; Lücker et al. 2010). The different locations of the enzyme's active site have been hypothesized to be responsible for the better adaptation of Nitrospira to low NO2− concentrations (Lücker et al. 2010). Noteworthy, the paradigm of nitrification as a two-step process changed after the discovery of some Nitrospira species capable of complete oxidation of NH3 to NO3− in a process called comammox (complete ammonium oxidation) (Daims et al. 2015; Kartal et al. 2015). Comammox nitrification While aerobic nitrification was considered a strictly canonical two-step process involving aerobic AO and NOB, strains of Nitrospira capable of complete oxidation of NH3 to NO3− (comammox) were recently discovered (Daims et al. 2015; van Kessel et al. 2015). The bioenergetics of complete NH3 oxidation to NO3− in a single step, rather than separating into two steps, is highly favourable and it was hypothesized over one decade ago that the metabolism should exist in nature (Costa et al. 2006)), with comammox bacteria being competitive with cross-feeding AO/NOB consortia and potentially favouring growth yield over growth rate. While all Nitrospira were historically considered as obligate nitrite oxidisers, comammox bacteria cultivated from an aquaculture-associated trickling filter (van Kessel et al. 2015) and a thermophilic biofilm (Daims et al 2015) possessed genes encoding AMO and HAO and were thus capable of performing both nitrification steps. Subsequently, comammox bacteria have been found in a wide range of environments, including soil (Pjevac et al. 2017; Wang et al. 2019b). This finding was particularly startling given that Nitrospira are found in large abundances in soils and typically outnumber AOA and AOB in soil (Daims et al. 2016). Analysis of amoA genes from cultivated representatives and metagenome studies indicated two phylogenetic groups (clades A and B) and potentially associated with ecological differentiation(Pjevac et al. 2017). Currently all cultivated species belong to clade A only although both clade A and B are found in soil, and growth of comammox bacteria in soil has only been demonstrated for clade B (Shi et al. 2018; Wang et al. 2019b). While the ecology of comammox in soil is still largely unknown, results indicate that their ecological niche(s) may be more similar to those of AOA, utilizing low concentrations of ammonia, and may not directly compete with AOB when high concentrations of inorganic NH4+ fertilizer are applied. Heterotrophic nitrification In addition to aerobic and anaerobic nitrification performed by autotrophic microorganisms, heterotrophic nitrification represents a third process of NO3− production in soils. Several fungi and heterotrophic bacteria can produce NO2− or NO3− using NH4+ or organic N as substrates (De Boer and Kowalchuk 2001; Zhang et al. 2014). Heterotrophic nitrifiers such as Paracoccus denitrificans (Moir et al. 1996) and Pseudomans putida (Daum et al. 1998), express an AMO-like enzyme and a non-heme hydroxylamine oxidase enzyme, using NH4+ as substrate to produce NO2− and thus differentiating it from both archaeal and bacterial AMO enzymes, which use NH3 as substrate. In the heterotrophic bacterium Alcaligenis faecalis, the oxidation of NH4+ to NO2− occurs from the concerted action between AMO and the pyruvic oxime dioxygenase (POD) enzyme (Tsujino et al. 2017). Heterotrophic nitrifiers, mainly fungi, can nitrify reduced forms of N such as amine or amide with substituted hydroxylamine, nitroso (R-NO) and nitro (R-NO2) compounds as intermediate products (Killham 1990). Indeed, several studies demonstrated that in forest soils the organic pathway using organic N, and not NH4+, was the main N substrate accessed by heterotrophic nitrifiers (Schimel, Firestone and Killham 1984; Pedersen, Dunkin and Firestone 1999). Studies employing a 15N labelling technique in the presence of acetylene, suggest that both heterotrophic nitrification pathways, i.e. organic and inorganic, coexist in soil and that substrate availability plays an important role in determining the relative contribution of the two pathways (Zhang et al. 2014). Due to denitrifying activity, a metabolic characteristic shared by several heterotrophic nitrifiers (Hayatsu, Tago and Saito 2008), heterotrophic nitrification represents an important source of N2O in soils (Baggs 2011; Zhang, Cai and Zhu 2011; Müller et al. 2014). However, as both NO2− and NO3− can be rapidly reduced to N-oxides with little or no accumulation of NO3− (Matheson et al. 2003), current indicators of heterotrophic nitrification might underestimate actual process rates (Amoo and Babalola 2017). Several studies revealed that heterotrophic nitrification occurs or even represents the predominant pathway for NO3− production in acidic soils such as forest soils (Hart, Binkley and Perry 1997; Zhang et al. 2013), cropland soils (Chen et al. 2015), grassland soils (Müller et al. 2014) and pasture soils (Islam, Chen and White 2007). However, other studies indicated that autotrophic nitrification, not heterotrophic nitrification, is the main source of NO3− in various acidic soils, e.g. heathland soils (De Boer, Duyts and Laanbroek 1988; De Boer et al. 1989), woodland soils (Barraclough and Puri 1995), arable soils (Zhang et al. 2013) and acid tea soils (Hayatsu, Kosuge and Kosuge 1993). Globally, these results indicate that the soil pH value alone is not predictive of the relative importance of autotrophic and heterotrophic nitrification pathways. Indeed, there is evidence that high soil C content and C:N ratios stimulate heterotrophic nitrification (Kreitinger et al. 1985; Zhang et al. 2013). These recent findings highlight how the heterotrophic nitrification can be an important NO3− production pathway in the rhizosphere, where various C compounds are released as root exudates. CELL ENVELOPES OF BACTERIAL AND ARCHAEAL AMMONIA-OXIDIZERS A fundamental characteristic of BNI compounds is their ability to act directly on AOA and AOB activity, or otherwise reduce AO growth. However, before examining such abilities and their putative mode of action, it is useful to discuss the main characteristics of cell envelopes in AOB and AOA. In fact, depending on the structural arrangement and chemical composition, the cell envelopes represent an important barrier for the cells, thus limiting the influx and uptake of external compounds (Hancock and Wong 1984). AOB cell envelope As Gram-negative bacteria, AOB can possess a very complex envelope system composed of an outer membrane (OM) and an inner or cytoplasmic membrane (CM), that are separated by the periplasm which contains peptidoglycan (PGN) (Fig. 1). The OM serves as a molecular sieve that permits the passage of small hydrophilic molecules and excludes potentially harmful enzymes or other large molecules. It is an asymmetrical bilayer composed of lipopolysaccharide (LPS) and of phospholipids in the outer and inner leaflets, respectively. Three structures confer hydrophilic and hydrophobic characteristic to the LPS. These are: the O-antigenic side chain (O-side chain) composed of repeating polysaccharides, a central core of oligosaccharide, and lipid A, a phosphorylated glucosamine disaccharide unit to which a number of saturated fatty acids are attached (Wiese et al. 1999). Lipid A, which is indispensable for bacterial viability (Steimle, Autenrieth and Frick 2016), represents the hydrophobic region through which LPS is anchored to the phospholipids (Doerrler 2006). In addition, the saturation of all fatty acids, which confer low fluidity to lipid A, the presence of negative charges in the LPS that are neutralized by divalent cations such as Mg2+ and cross-link LPS, and the fact that LPS in the OM outer leaflet can extend out from the membrane surface by as much as 3 nm, make the OM a very effective barrier for both hydrophilic and hydrophobic compounds (Nikaido 2003; Wiener and Horanyi 2011). In fact, although the penetration of hydrophobic molecules through OM is possible, its rate is 50–100 times slower than through phospholipid-containing bilayers (Denyer and Maillard 2002). In addition, both O-side chains and the core oligosaccharides regions of LPS have been identified in the genome of Nitrosospira multiformis (Norton et al. 2008). On the contrary, hydrophilic compounds with masses of up to 600–650 Da, can pass the OM because of the presence of water-filled open channels termed outer membrane proteins or porins (Nikaido 2003). In addition, it has been demonstrated that specific porins are involved in the transport of hydrophobic compounds through the OM of Gram-negative bacteria (Hearn, Patel and van den Berg 2008). Below, we discuss the implications of these structures in relation to the passing of both hydrophilic and hydrophobic plant compounds with putative BNI activity through AOB cell envelopes. AOA cell envelope Compared to bacteria, archaeal cell envelopes have a range of different features including the presence of the proteinaceous surface layer (S-layer), lipids composed of isoprenoid units, i.e. long chain alcohols (phytanols), linked to glycerol via ether bonds (rather than fatty acids linked by ester bonds) and a pseudo-periplasm space, which lacks peptidoglycan (Ellen et al. 2010). The archaeal S-layer, the outermost component of the cell envelope, is a two-dimensional crystal layer and represents one of the simplest protein or glycoprotein membranes (Sleytr et al. 2014). S-layers mediate cell shape, adhesion for exoenzymes, and form a protective coat against high and low-molecular-weight substances (Sleytr 1997; Schuster and Sleytr 2014). One important feature of S-layers is the ability to form an isoporous ordered lattice with oblique (p1 or p2), square (p4) or hexagonal (p3 or p6) space group symmetries (Albers and Meyer 2011). An ultrastructural study of the AOA Nitrososphaera viennensis revealed an S-layer trimeric protein with p3 symmetry forming pores triangular in shape (Stieglmeier et al. 2014). Moreover, a proteogenomic analysis revealed that the N. viennensis S-layer possesses protein N-glycosylation, wherein short sugar chains are covalently linked to the asparagine (N) residue of an NXS/T tri-peptide (where X is any amino acid except proline, S is serine and T is threonine) (Kerou et al. 2016). It should be noted that glycosylation of S-layer proteins, a co/post-translational process (Gavel and Heijne 1990; Spiro 2002), is considered of crucial importance in protecting the cells from external proteases (Sleytr and Messner 1983). Glycosylated S-layers however can bind hydrophilic, hydrophobic, positively, and negatively charged materials to a comparable extent (Sleytr et al. 2014). Within the lattice, pore diameters vary depending on the archaeal species. For example, the S-layer of the hyperthermophilic archaea Thermoproteus tenax and Thermoproteus neutrophilus have pores with a diameter of 6 nm (Messner et al. 1986), while channels of 5 nm have been measured for the S-layer of Sulfolobus acidocaldarius. A recent study revealed that the porous mesh of the AOA Nitrosopumilus maritimus is composed of nanopores 1.3 nm in diameter (Li et al. 2018b). It is interesting to note that pore sizes in the range of 2–3 nm enable the passage of compounds with small molecular weight, but prevent the entry of larger moieties such as lysogenic enzymes, parasites and phages (Sleytr and Sára 1986). Microscopic analysis coupled with simulation modelling suggests that AOA nanopores are coated by negative charges, facilitating the entry of NH4+, but not NH3, into the pseudo-periplasmic space (Li et al. 2018b). Accordingly, such AOA S-layer features may represent a selective advantage in N-limited ecosystems where competition for N is stronger. The observation that the production of proteinaceous S-layer proteins is linked to cell stress supports the hypothesis that it provides an adaptive advantage (Sleytr and Messner 1983). In addition, AOA cytoplasmic membranes are composed of a lipid monolayer rather than a bilayer as found in AOB. In fact, C20 isoprenoid chains are linked to each other to form a monolayer of C40 side chains and therefore the nonpolar core of membrane lipids is composed of glycerol dialkyl glycerol tetraether lipid (GDGTs). The most common GDGT in AOA membranes is crenarchaeol consisting of two dibiphytanyl hydrocarbon chains, containing a cyclohexane moiety, four cyclopentane moieties and covalently polar bound head groups (Schleper and Nicol 2010; Sinninghe Damsté et al. 2012, 2018). Crenarchaeol is asymmetrical and bipolar as it harbors a phosphatidyl moiety at one end of the lipid and a sugar moiety at the other (Sinninghe Damsté et al. 2012). Although the content of crenarchaeol can vary among different AOA (Lehtovirta-Morley et al. 2016), its presence confers high viscosity and low water and ions permeability to AOA membranes (Chugunov et al. 2014). The distinct features of AOA cell envelopes compared to AOB may therefore affect permeability and sensitivity to nitrification inhibitors (Shen et al. 2013). INDIRECT INHIBITION OF NITRIFICATION Although BNI postulates that plant-derived compounds inhibit the nitrification process by acting directly on AO (Rice and Pancholy 1972, 1973), other mechanisms have been identified as controlling N transformations (Robertson and Vitousek 1981; Verhagen and Laanbroek 1991; Clein and Schimel 1995; Stark and Hart 1997). As such, direct and indirect routes of inhibiting nitrification can occur simultaneously, which makes the single cause-effect model of testing inadequate for the BNI postulate. Below, we outline such interactions whilst providing a framework for studies on the BNI phenomenon. The N mineralization refers to the release of NH4+ during the decomposition of soil organic matter (SOM), the N immobilization is the N assimilation by microbes (Powlson and Barraclough 1993). A wide range of microorganisms perform N mineralization and immobilization under both oxic and anoxic conditions. It is important to differentiate between gross N mineralization, i.e. the total amount of NH4+ released during the degradation of SOM, and gross rates of microbial assimilation of both NH4+ and NO3−. In fact, mineralization and immobilization of N co-occur in soil, but not necessary at the same rates. Gross nitrification is the actual rate of conversion of NH4+ or NH3 to NO3− regardless of the rate of N immobilization (Hart et al. 1994b; Murphy et al. 2003). Conversely, net nitrification refers to differences between two or more gross processes (Hart et al. 1994b). The dominance of NH4+ over NO3− concentrations, low net nitrification rates, reduced potential nitrification activity, and low numbers of AOB and NOB have been used to infer direct inhibitory effects of plant derived compounds on nitrification (Lyttleton Lyon and Bizzell 1911; Richardson 1938; Theron 1951; Munro 1966; Smits et al. 2010). Many of the putative BNI compounds studied belong to the chemical class of polyphenolics (Table 1), which are known to decrease N availability by inhibiting N mineralization and increasing N immobilization (Lewis and Starkey 1968; Schimel et al. 1996; Fierer et al. 2001), thereby exacerbating the competition for N. Table 1. Main chemical and physical properties of plant compounds tested as natural nitrification inhibitors. Open in new tab Table 1. Main chemical and physical properties of plant compounds tested as natural nitrification inhibitors. Open in new tab Several N isotope-based studies have demonstrated that phenolics can negatively affect nitrification rates indirectly, i.e. reduced gross N mineralization or increased microbial N immobilization, rather than through direct inhibitory mechanisms (Clein and Schimel 1995; Fierer et al. 2001; Castells, Peñuelas and Valentine 2004). On the contrary, phenolic compounds with low molecular weight can be used as a C source by soil microorganisms which stimulate microbial activity and, concurrently, increase their demand for N (Fierer et al. 2001). However, once NH4+ is produced via mineralization, its utilization by AO represents only one of its possible fates. In fact, NH4+ can be fixed by expansible clay minerals, adsorbed onto the exchange complex, react with SOM to form quinone-NH2 complexes and thereby becoming stabilized for long periods (Paul and Clark 1996; Haider and Schäffer 2009). Interestingly, it has been shown that NH4+ availability to nitrifiers is related to NH4+ production via N mineralization, with potential nitrification activity having good correlation to total inorganic N, while net nitrification rates have poor correlation to NH4+ concentration (Verhagen, Duyts and Laanbroek 1992; Clein and Schimel 1995). The availability of C in the rhizosphere stimulates the activity of heterotrophs, which in turn maintain a high demand for N (Cheng et al. 1996). When organic C is not limiting, heterotrophs outcompete nitrifiers for NH4+ due to their higher growth rate and higher affinity for NH4+ (Rosswall 1982), thus indirectly inhibiting nitrification by decreasing NH4+ availability. It is noteworthy that N immobilization not only co-occurs but can also exceed mineralization rates (Nadelhoffer, Aber and Melillo 1984; Giblin et al. 1991). The C/N ratio, which represents a functional link between organic C, nitrification and competition for N, plays a pivotal role in regulating N immobilization-nitrification patterns (Verhagen, Duyts and Laanbroek 1992). In a chemostat study in which glucose was the sole C source, a C/N ratio ranging between 9.6 and 11.9 was shown to be a critical value for nitrification to occur (Verhagen and Laanbroek 1991). At higher C/N ratios, heterotrophs became N limited and nitrification was indirectly inhibited due to N immobilization (Verhagen and Laanbroek 1991). Some putative BNI compounds such as tannins could indeed inhibit nitrification in soil indirectly by enhancing heterotrophic activity and increase N consumption, e.g. N immobilization (Basaraba 1964; McCarty, Bremner and Schmidt 1991; Kraus et al. 2004). Inhibition of net nitrification coupled with no changes in net N mineralization was observed in soils treated with mixtures of monoterpenes such as limonene, myrcene, α- and β-pinene, β-phellandrene, camphene, 3-carene or with individual compounds such as α- and β-pinene (Paavolainen, Kitunen and Smolander 1998; Uusitalo, Kitunen and Smolander 2008). However, by comparing the effect of different amounts of six terpenoids (α-pinene and β-pinene, α-terpinene, limonene, myrcene and α-phellandrene), it was found that these compounds did not significantly affect nitrification in soil (Bremner and McCarty 1988). The authors also reported that the C added as terpenes was as effective as glucose in enhancing NH4+ immobilization, and concluded that monoterpenes repress nitrification indirectly due to substrate limitations. However, monoterpenes and others BNI compounds inhibited NH3 oxidation in pure cultures of N. europaea (Ward, Courtney and Langenheim 1997), which suggests that these compounds possess some potential to act as direct inhibitors of the nitrification process. It should also be noted that, although N immobilization generally refers to the immobilization of NH4+, NO3− can be taken up by microbes as well (Kaye and Hart 1997; Stark and Hart 1997) with NO3− immobilization occurring in microsites of NH4+ depletion (Schimel, Jackson and Firestone 1989), although such depletion zones are not a prerequisite for N immobilization to occur (Bengtson and Bengtsson 2005; Kaštovská and Šantrůčková 2011). In addition, the composition of the soil microbial community may be an important factor for determining rates of NH4+ and NO3− immobilization as assimilation of NO3−, compared to NH4+, can be increased by the presence of microorganisms with higher affinity for NO3− than for NH4+ (Bengtson and Bengtsson 2005; Myrold and Posavatz 2007). A fast turnover of the NO3− pool (Jackson, Schimel and Firestone 1989; Burger and Jackson 2003) can also explain why soils with higher nitrification rates also show low concentration of NO3− (Kaštovská and Šantrůčková 2011). Moreover, high concentrations of NH4+ may inhibit NOB (Philips, Laanbroek and Verstraete 2002) and therefore NO2− oxidation, thus repressing NO3− production. Therefore, interpreting high NH4+/NO3− ratios as an indication of nitrification inhibition could be misleading as in situations where NO2− and N2O are the major end products of NH3 oxidation. An aspect characterizing the nitrification process is its connection with other N transformations such as denitrification and the dissimilatory nitrate reduction to ammonium (DNRA), also known as nitrate ammonification. Both denitrification and DNRA are dissimilatory NO3− reducing processes that use NO3− as substrate with NO2− as intermediate product (Philippot and Højberg 1999). The relevance of denitrification and DNRA in relation to BNI is that both processes are sinks for NO3− and therefore have the same effect of reducing NO3− concentration in soils. Several studies have highlighted a positive relationship between denitrification and NO3− concentration (Davidson, Swank and Perry 1986; Vermes and Myrold 1992), between denitrification enzyme activity (DEA) and potential nitrification activity (Griffiths, Homann and Riley 1998), and between N2O emissions and net N mineralization (Matson and Vitousek 1987). These findings provide additional evidence for a strong functional connection among N pools and processes. In addition, as NO3− represses the reduction of N2O to N2 (Blackmer and Bremner 1978), N2O and N2 will be the predominant denitrification products at high and low NO3− concentrations, respectively. Therefore, plants that inhibit NH3 oxidation should theoretically repress denitrification whilst decreasing the N2O/N2 ratio due to less NO3− being produced. A field study aiming to evaluate N2O emissions under the two Brachiaria cultivars Tully (BT) and Mulato (BM), characterized by high and low BNI capacity, respectively, revealed more suppression of nitrification, denitrification, AOA abundance, but not AOB, in soils under BT than under BM (Byrnes et al. 2017). It should be noted that, considering the known BNI activity of brachialactone when tested in a bioassay, and the high BNI activity of the cultivar BT, a decrease in AOB abundance, and not only in AOA, could be expected. The fact that such a difference did not occur, highlights the importance of in situ trials to confirm bioassay findings. The three compounds tannic, vanillic and ferulic acids have been shown to reduce N2O emissions (Frimpong et al. 2014), while supporting protein binding and N immobilization as driving mechanisms for lowering N2O emissions (Chaves et al. 2005). As already mentioned, DNRA is a microbially mediated process in which NO3− is used as electron acceptor and reduced to NH4+ via NO2− as an intermediate product with N2O also produced (Tiedje 1988; Kelso et al. 1997). DNRA should be promoted under NO3− limiting conditions with a C/NO3− ratio of ≥ 4 (Fazzolari, Nicolardot and Germon 1998), while a C/NO3− ratio of 2 should favor denitrification (Bowman and Focht 1974). Importantly, it has been demonstrated that low and high C/NO3− ratios lead to an increase in the production of NO2− and N2O (low C/NO3− ratio) and NH4+ (high C/NO3− ratio), respectively (Stremińska et al. 2012). Based on this, we hypothesize that the inhibition of nitrification should increase the rhizosphere C/NO3− ratio, thus making the rhizosphere of BNI plants a suitable environment for the DNRA process which can fuel plants with additional NH4+, as well as a microenvironment with increased competition between denitrifiers and NO3− ammonifiers. In fact, the production of NO3− is ultimately the result of NOB activity which can remain active even under NH4+ limitations if NO2− is provided by other processes. By studying potential nitrification activities in the rhizosphere of barley (Hordeum vulgare) it was found lower NH4+ availability and higher NH3 and NO2− oxidation rates in the rhizosphere than in the bulk soil, respectively, with the NO2− oxidation rate being 1.5 times higher than the NH3 oxidation rate (Højberg, Binnerup and Sørensen 1996). These results suggest that processes other than NH3 oxidation, such as the dissimilatory reduction of NO3− to NO2− (Belser 1979), can fuel NOB with NO2− leading to NO3− production. Therefore, inhibition of NH3 oxidation does not necessarily imply the absence of NO2− production and its subsequent transformation to NO3−. Plant N uptake, which is neither uniform along the root axis nor constant in time, also influences the availability of both organic and inorganic (NH4+ and NO3−) N pools in the rhizosphere. For example, gross N mineralization was found to be ten times higher in the rhizosphere of Avena barbata than in the bulk soil, and the gross nitrification rates along the root axis were repressed in the upper part of the root, where competition for NH4+ is high due to active NH4+ plant uptake, and similar to those of the bulk soil at the root tip, where plant NH4+ uptake is negligible (Herman et al. 2006). This experiment demonstrated that A. barbata inhibits nitrification in the rhizosphere and showed that competition for NH4+ was the mechanism responsible for such inhibition. Arbuscular mycorrhizal fungi (AMF) are soil fungi belonging to the phylum Glomeromycota that form symbiotic relationships with more than 85% of terrestrial plants (Strullu-Derrien et al. 2018), including those negatively affecting nitrification such as brachiaria (Posada et al. 2007), sorghum (Cobb et al. 2016), rice (Bernaola et al. 2018), sunflower (Helianthus annuus) (Davies et al. 2001) and Hyparrhenia (Rodríguez-Caballero, Caravaca and Roldán 2018). While AMF can acquire N from organic sources, i.e. amino acids (Whiteside, Garcia and Treseder 2012) as well as NO3− (Bago et al. 1996), they preferentially (Govindarajulu et al. 2005) or exclusively (Tanaka and Yano 2005), absorb NH4+ at a high rate (Hodge and Fitter 2010). In a N-limited Mediterranean grassland soil AMF strongly suppressed potential nitrification activity (Veresoglou et al. 2011), although such inhibitory effects declined with increasing soil N availability (Veresoglou et al. 2018). Therefore, the interaction between AMF and AO could shift from negative to neutral depending on the soil N status. Under conditions of low N availability, AMF can indirectly inhibit nitrification as they outcompete ammonia oxidizers for available NH4+ (Nuccio et al. 2013; Veresoglou et al. 2018), whereas competition is theoretically less important at high N availability (Veresoglou et al. 2018). The effect of AMF on AO abundance goes from negative (Chen et al. 2013) to neutral (Cavagnaro et al. 2007; Veresoglou et al. 2018). In addition, while AMF caused a shift in AOA but not AOB community composition (Chen et al. 2013), the opposite was observed by Cavagnaro et al. (2007) and Veresoglou et al. (2018). Importantly, as the induced shift in the AOB community composition was mirrored by low NH4+ availability, these authors hypothesized that competition for NH4+ was the mechanism underlying the interactions between AMF and AOB community composition. Moreover, it is becoming evident that AMF can also reduce NO3− leaching (Asghari and Cavagnaro 2012) and denitrification (Storer et al. 2018). Collectively, these findings suggest that AMF play a significant role in modulating N transformations in the rhizosphere and reducing N losses. In addition, AMF also acidify the mycorrhizosphere (Li, George and Marschener 1991), i.e. the mycorrhized roots (Andrade et al. 1997), creating unfavorable conditions for nitrification. It has been also shown that acidification of the sorghum rhizosphere is an important factor for nitrification inhibition (Watanabe et al. 2015). Enhancement of phosphorus (P) uptake is the most recognized benefit of AMF association for the host plant (Smith and Read 2008). As NOB are sensitive to P deficiency, a reduction of P availability can inhibit their growth rate and suppress NO2− oxidation (Purchase 1974). Interestingly, mycorrhizal associations not only modify both the quantity and quality of root exudates (Smith and Read 2008), but they can actively exude an array of low molecular weight compounds such as sugars and organic acids (Toljander et al. 2007). It is generally accepted that plants showing BNI capacity have evolved in N-limited ecosystems. In these ecosystems however, AMF may play an important role in controlling nitrification (Veresoglou et al. 2011, 2018). Therefore, there could be positive relationships between BNI and AMF as they could work synergistically to improve plant N use efficiency. Protozoa are heterotrophic, single-celled or colonial eukaryotes organisms that are ubiquitous in soils (Finlay 2002). Although protozoa can eat fungi, algae, yeasts, nematodes as well as other protozoa, they mainly rely on slow-growing Gram-negative bacteria as a food source (Koller et al. 2013), thus having potential to inhibit the nitrification process through predation of nitrifiers. Such top-down control is supported by studies showing a significant reduction of nitrifier populations in the presence of protozoa than in their absence (Lee and Welander 1994; Pogue and Gilbride 2007), although decreased abundances of nitrifiers was not always coupled with reduced nitrification rates (Verhagen and Laanbroek 1992). This suggests that that protozoan grazing and BNI can additively inhibit nitrification. It has been demonstrated that in the rhizosphere protozoa interact with AMF, and this leads to the increase of root length and root tips, plants N supply and uptake (Kuikman et al. 1990; Jentschke et al. 1995; Koller et al. 2013). As protozoa have low nutrient assimilation efficiency and share similar C:N ratios with their bacterial prey, they excrete substantial parts of N previously immobilized in bacterial biomass, which is then captured by AMF and translocated to the host plant (Bonkowski 2004). THE BIOLOGICAL NITRIFICATION INHIBITION POSTULATE: THE WHERE AND THE HOW Rhizosphere nitrification In the rhizosphere, the soil volume at the root-soil interface (Brimecombe, De Leij and Lynch 2001), plants allocate up to 20% of the photosynthetically assimilated carbon (C) as root exudates, and release rhizodeposits consisting of mucilage, root cap and epidermal and cortical cells (Farrar et al. 2003; Bais et al. 2006). Many studies report an increase in gross N mineralization (Norton and Firestone 1996; Bengtson, Barker and Grayston 2012; Zhu et al. 2014) and net N mineralization in the rhizosphere (Dijkstra et al. 2009). Because gross rates of mineralization and nitrification are correlated, high gross mineralization rates can be indicative of NH4+ availability to nitrifiers (Hart, Binkley and Perry 1997). This may explain why higher activity and abundances of ammonia oxidizers have been observed in the rhizosphere of several plants such as wheat (Triticum aestivum L.) and maize (Zea mays L.) (Ai et al. 2013), barley (Hordeum vulgare) (Højberg, Binnerup and Sørensen 1996) and rice (Oryza sativa) (Li, Fan and Shen 2008). Increased AOA or AOB amoA gene abundance was also found in the rhizosphere of rice (Chen et al. 2008; Hussain et al. 2011), potato (Cavalcante et al. 2012), quailbush (Atriplex lentiformis) (Nelson et al. 2015), eucalyptus (Eucalyptus camaldulensis) (Tsiknia, Tzanakakis and Paranychianakis 2013), cauliflower (Brassica oleracea) (Kleineidam et al. 2011), wheat and maize (Ai et al. 2013). Studies have demonstrated the dominance of AOB over AOA in the rhizosphere (Glaser et al. 2010; Wei et al. 2011; Trias et al. 2012), but also the opposite (Chen et al. 2008; Herrmann, Saunders and Schramm 2008; Hussain et al. 2011). Furthermore, potential nitrification rates correlated with AOA (He et al. 2007; Hallin et al. 2009), or AOB population sizes (Jia and Conrad 2009; Glaser et al. 2010; Ai et al. 2013; Rudisill, Turco and Hoagland 2016), with AOA and AOB contributing differently to NH3 oxidation depending on environmental factors (Hu, Xu and He 2014; Ouyang, Norton and Stark 2017) as well as on agronomic practices such as fertilization (Chu et al. 2008; Strauss, Reardon and Mazzola 2014). Hypothetical mechanisms of BNI The influence of plants on nitrification has been studied with respect to a plethora of compounds released both aboveground and belowground or after plant tissue degradation. By considering the physicochemical characteristics of these compounds (Table 1) as well as the physiology and the cell envelope features of AO, two important yet poorly investigated aspects of BNI research are: (i) how do such compounds pass through cell barriers and (ii) what is the mode of action against nitrifiers. Movement of BNI compounds to targets inside the cell The bacterial outer membrane acts as a protective barrier that limits the penetration of potentially toxic compounds, whilst imposing different routes of entry for hydrophilic and hydrophobic compounds (Denyer and Maillard 2002). Considering that BNI targets can be in the cytoplasm (see below), BNI compounds must possess the appropriate physicochemical properties such as low molecular mass, lipophilicity and polarity to pass the cytoplasmic membrane (Lipinski et al. 2001; Shityakov et al. 2013). By integrating the information from the physicochemical properties of BNI compounds and the knowledge of AOB and AOA cell features, we hypothesize that BNI compounds may use different routes of entry into these microorganisms and that some compounds may also act on the cytoplasmic membrane by affecting fluidity or acting as cell wall permeabilizers, thus negatively affecting AOB and AOA without the need to bypass the cell wall. A measure of a compound's lipophilicity is represented by the partition coefficient in 1-octanol/water (Bannan et al. 2016), expressed as logP values, with compounds equally soluble in octanol/water having logP = 0. Hydrophilic and lipophilic compounds have logP less or greater than 0, respectively. Compounds with a logP > 4 are considered very hydrophobic, whereas compounds with logP < 1, are regarded as relatively hydrophilic. Regarding the passage through the outer membrane, small hydrophilic molecules of limited size can diffuse within non-specific water-filled porins (aquaporins). The Escherichia coli outer membrane, for example, contains about 200 000 aquaporin channels, which represent the major gates for small hydrophilic molecules with masses up to 600–650 Da (Nikaido 2003). Therefore, we hypothesize that low molecular weight and hydrophilic BNI compounds such as sinigrin, gallocatechin, gallic acid and chlorogenic acid, methyl isothiocyanate and isoquercitrin and other molecules may enter microbial cells via diffusion through aquaporins. A long-standing question has been how do hydrophobic compounds pass the outer membrane of Gram-negative cells. However, the discovery of the FadL porins in the outer membrane of E. coli as channels responsible for the transport of hydrophobic compounds such as fatty acids across the cell membrane provided important mechanistic insights (Lepore et al. 2011). Considering that similarities have been observed between porins from different species and between porins of different specificity within the same species, we propose that the entry of hydrophobic BNI compounds such as sorgoleone, 1.9 decanediol, α-linolenic acid, linoleic acid, methyl linoleate into the periplasm of AOB may occur through these specific channels (Fig. 1). Once in the periplasmic space, the polarity of BNI compounds is also an important factor facilitating the passage across the lipid bilayer. Molecular polarity is measured by the topological polar surface area (TPSA), a widespread descriptor used for the optimization of membrane permeability (Abram et al. 2013). In general, low polarity compounds are considered those with a TPSA lower than 75 Å2 (Silver 2011). For example, an area less than 60 Å2 is usually needed for molecules to penetrate the blood-brain barrier, while molecules with a TPSA higher than 120–140 Å2 are less efficient in permeating cell membranes (Palm et al. 1997). In a recent study on the effect of different organic acids on soil AOA strains Nitrosotalea devanaterra Nd1 and Nitrosotalea sp. Nd2, the TPSA was calculated in order to predict the permeability potentials of the compounds used and the value of 60 Å2 was considered the threshold for permeability (Lehtovirta-Morley et al. 2014). Interestingly, the authors found that pyruvate, among seven organic acids tested, had the lowest TPSA (54.4 Å2) and the highest inhibitory activity. However, the predicted TPSA for the BNI compounds covers a wide range of polarity values such as 207 and 203 Å2 for the flavanol isoquercitrin and the isothiocyanate sinigrin, respectively, to zero Å2 for different monoterpenes such as limonene or α-pinene (Table 1). Therefore, compounds such as the fatty alcohol 1,9-decanediol, α-linolenic and linoleic fatty acids, sorgoleone, brachialactone, MHPP and karanjin with a polarity lower than 60 Å2, have the potential to pass through cytoplasmic membranes. In general, higher toxicity is associated with higher lipophilicity (logP > 3) and lower polarity (TPSA < 75 Å2) (Hughes et al. 2008). An optimal logP for Gram-negative bacteria of four have been reported for several antibacterial compounds (Lien and Wang 1980), while aromatic solvents with logP values in the range 2–4 cause major changes in the cytoplasmic membrane (Segura et al. 1999). Importantly, because the cytoplasmic membranes of AOA and AOB differ in their lipid composition, it remains to tested whether compounds with a TPSA and lipophilicity enabling them to permeate the cell membranes of AOB are suited to pass across the cytoplasmic membrane of AOA, and vice versa (see below). Mode of action of BNI compounds against microbial ammonia oxidizers Compounds released by plants include sugars, alcohol sugars, aldehyde sugars, amino acids, phenolic compounds, fatty acids, fatty alcohols, isothiocyanates and sterols (Bertin, Yang and Weston 2003; Uren 2009; Cesco et al. 2010), and putative nitrification inhibitors studied so far are widely distributed among many of these categories (Table 1). Historically, the majority of BNI research relates to the inhibition of AMO or both AMO and HAO enzymes. For instance, it has been proposed that some terpenes (White 1988) and different root exudates such as MHPP (Zakir et al. 2008) and 1,9-decanediol (Sun et al. 2016) inhibit the AMO enzyme, while sorgoleone and sakuranetin (Subbarao et al. 2013) and brachialactone (Subbarao et al. 2009) act on both AMO and HAO enzymes. However, the inhibition of other enzymes or mode of action cannot be ruled out. BNI compounds as outer membrane permeabilizers Many BNI compounds have the potential to act as outer membrane permeation enhancers, increasing susceptibility of microorganisms to the entry of external compounds, or allow internal contents to escape from the cell (Vaara 1992; Nikaido 2003). Permeabilizers can alter the integrity of the bacterial outer membrane by causing the release of lipopolysaccharide, by their intercalation or insertion in the outer membrane, or acting as chelating agents of divalent cations (Vaara 1992). Known antimicrobial activity of phenolics, flavones, flavonoids and flavonols is attributed to their ability to interact with cell walls (Cowan 1999), and disintegrate the outer membrane of Gram-negative bacteria (Nohynek et al. 2006). Interestingly, gallic acid (trihydroxybenzoic acid) and ferulic acid (3-methoxy,4-hydroxycinnamic acid), also known for their BNI activity, can change outer membrane physicochemical properties such as the surface charge in Gram-negative bacteria. Both acids increase the hydrophilicity of the Pseudomonas aeruginosa cell wall and reduce the negative charge in P. aeruginosa as well as in E. coli (Borges et al. 2013). Moreover, berry-derived phenolic compounds such as 3,4-dihydroxyphenylacetic acid, 3-(3,4-dihydroxyphenyl)propionic acid and 3-(4-hydroxyphenyl)propionic acid, disintegrate the outer membrane of the Gram-negative bacterium Salmonella, while increasing the susceptibility of the bacteria to the antibiotic novobiocin (Alakomi et al. 2007). Proanthocyanidins, or condensed tannins, composed mainly of the monomeric flavan subunits catechin and epicatechin and their derivatives, have the ability to bind to lipid A, the cell-binding domain on lipopolysaccharide, indicating that condensed tannins can predominantly bind and neutralize the lipopolysaccharide of several Gram-negative bacteria (Delehanty et al. 2008). Condensed tannins can also form complexes with outer membrane proteins such as permeases and porins, thus altering the metabolic fundamental pathways of respiration and synthesis of the wall components. Interestingly, the flavonol quercetin can neutralize the porin amino acids charges (Alvarez, Debattista and Pappano 2008) and the electric field at the pore eyelet. As the porin electric field represents an energy barrier for non-polar compounds (Galdiero et al. 2013), its neutralization can facilitate the entrance of non-polar molecules to the bacterial cell cytoplasm. Cell wall synthesis and maintenance pathways can also be altered by the action of terpenes such as limonene and myrcene which lead to changes in the outer membrane permeability and microbial death (Sieniawska et al. 2017). It has been demonstrated that the invasive species Fallopia spp. can inhibit denitrification in soil by procyanidins (Bardon et al. 2016a), which are oligomeric compounds of catechin and epicatechin monomers (Rue, Rush and van Breemen 2018), and that such compounds were able to permeabilize and induce structural changes in the cell membrane of the denitrifying bacterium Psudomonas brassicacearum NFM 421 (Bardon et al. 2016b). BNI compounds targeting cytoplasmic membranes Several studies identified the microbial cytoplasmic membrane as an important target for many plant secondary metabolites (Cowan 1999; Papuc et al. 2017; Górniak, Bartoszewski and Króliczewski 2019). Perturbation of the cytoplasmic membrane causes metabolic dysfunction with devastating effects on the physiology of AO. More lipophilic (high logP values) flavonoids partition into the hydrophobic core of the lipid bilayer, while more hydrophilic flavonoids (low logP values) are able to quench polar head groups of lipid bilayers through hydrogen bonds (Oteiza et al. 2005). Interaction of flavonoids with membrane proteins leads to the disruption of the lipid bilayer, increasing membrane permeability, affecting membrane fluidity, inhibiting respiration, and altering ion transport processes (Nazzaro et al. 2013). The flavonoid quercetin significantly inhibited bacterial motility, thus providing evidence of the negative effects on the proton motive force (Mirzoeva et al. 1997). Moreover, naringenin can negatively affect bacteria by reducing the fluidity of both inner and outer cell membranes (Tsuchiya and Iinuma 2000). It is worth noting that due to the ability of some flavonoids, i.e. quercetin, to chelate metal cations such as Fe2+ and Cu2+, they form complexes with increased lipophilicity (logP) which in turn increases the ability of these compounds to penetrate into the lipid bilayer. Owing to their metal chelating capacity, flavonoids also inhibit free radical generation. In addition to flavonoids, other compounds such as cyclic terpenes, limonene, allylisothiocyanate and phenylethyl isothiocyanate interact with the cytoplasmic membranes of Gram-negative bacteria, resulting in loss of membrane integrity, dissipation of the proton-motive force, and inhibition of respiratory enzymes (Sikkema, de Bont and Poolman 1995; Mirzoeva, Grishanin and Calder 1997; Borges et al. 2013). It should be noted the distruption of the proton-motive force in AO would deprive the AMO enzyme of the two electrons required to catalyze the oxidaion of NH3. Gallic acid and ferulic acid change the hydrophicity of the bacterial cytoplasmic membrane, decreasing the negative surface charge and forming pores resulting in loss of intracellular constituents (Papuc et al. 2017). Fatty acids interact with the cytoplasmic membrane and create pores of variable size, which allow the escape of low-molecular-weight proteins from the cell (Parsons et al. 2012). Fatty acids can also express bactericidal or bacteriostatic action through different mechanisms such as disruption of the electron transport chain (Peters and Chin 2003), uncoupling of oxidative phosphorylation (Beck et al. 2007), cell lysis (Chamberlain et al. 1991) and inhibition of enzyme activity (Sado-Kamdem, Vannini and Guerzoni 2009). However, differences in the lipid membrane composition between AOA and AOB can result in differences in susceptibility to compounds that target the cytoplasmic membrane. In fact, it is known that the presence of tetraether lipids spanning the cytoplasmic confer to archaeal membranes high stability and rigidity, whereas the presence of five-membered rings, i.e. one cyclohexane moiety and four cyclopentane moieties, enhance membrane packing and reduced membrane fluidity (Jacquemet et al. 2009). Based on these chatracteristics, AOA may have greater resistence to BNI compounds targating cell membranes compared to AOB. Once through the inner membrane, BNI compounds might also inhibit enzymes located in the cytoplasm. The cytoplasmic hydroxyacyl-acyl carrier protein dehydratase (FabZ) is an essential enzyme for the biosynthesis of fatty acids and lipid A in AOB (Chain et al. 2003). It has been demonstrated that the three flavonoids sakuranetin, quercetin and apigenin all inhibit the FabZ enzyme activity in the Gram-negative bacterium Helicobacter pylori, by binding to the substrate tunnel thus preventing the substrate from accessing the active site and therefore acting as competitive inhibitors (Zhang et al. 2008). The presence of a methoxy group in the C-7 position of the sakuranetin has been identified as a key chemical trait for the establishment of hydrophobic interactions with the FabZ enzyme, thus increasing binding affinities and the inhibitory effect of this flavanone (Zhang et al. 2008). BNI compounds as NO scavengers Phenolic compounds have the acclaimed ability to scavenge reactive oxygen species (ROS) and NO, and to act as metal chelating agents (Quideau et al. 2011). Such functions are directly related to the compound's structure and the position of functional groups in the molecule, referred to as structure-activity relationships (SAR) (Heim, Tagliaferro and Bobilya 2002; Balasundram, Sundram and Samman 2006). In particular, the number and positions of the hydroxyl groups in relation to the carboxyl functional group are key determinants of the scavenging activity of phenolics compounds (Rice-Evans, Miller and Paganga 1997; Boora, Chirisa and Mukanganyama 2014). For example, the strong antioxidant activity of gallic acid is related to its degree of hydroxylation (Table 1). The higher antioxidant activity of hydroxycinnamic acids, as compared to hydroxybenzoic acids, is related to the CH = CH-COOH group, a chemical trait that ensures greater H-donating ability and radical stabilization than the COOH group in the hydroxybenzoic acids (Rice-Evans, Miller and Paganga 1997). Flavonoids are also radical scavengers with donation of a hydrogen atom to radicals (Pietta 2000) and the degree of hydroxylation and position of OH groups in the B ring important to the scavenging ability of these compounds (van Acker et al. 1996; Balasundram, Sundram and Samman 2006). The presence of OH groups at positions 3′-, 4′- and 5′ of ring B, e.g. quercetin and myricetin, has been reported to enhance the antioxidant activity of flavonoids compared to other compounds like sakuranetin, having a single hydroxyl group. Furthermore, the tea tannins (-)-epigallocatechin 3-O-gallate, (-)-gallocatechin 3-O-gallate and (-)-epicatechin 3-O-gallate have additional high antioxidant properties through a direct NO scavenging action (Nakagawa and Yokozawa 2002). Considering the central role of NO in AOA and AOB NH3 oxidation, BNI compounds might act by scavenging this process intermediate. Indeed, NO can be directly scavenged by compounds with suspected BNI activity such as quercetin, a flavonoid commonly found in many plants such as broccoli, tea, onions, nuts, berries, cauliflower and cabbage (Lopez-Lopez 2004; Lakhanpal and Rai 2007), and by caffeic acid (Sueishi et al. 2011). The NO scavenger activity of caffeic acid and curcumin, have been tested against three distinct AOA, i.e. N. maritimus SCM1, AOA-6f and AOA-G6, and against N. europaea by Sauder, Ross and Neufeld (2016). It was reported that caffeic acid completely inhibited NH3 oxidation by AOA over a concentration range of 10–300 μM, with an EC50 < 10 μM for N. maritimus and AOA-6f and an EC50 value of 84.3 μM for AOA-G6. In contrast, N. europaea was not inhibited by caffeic acid at all concentrations tested with an EC50 of > 300 μM. The authors also found similar results for curcumin treatments, thus showing that these phenolics, in the concentration range used, could inhibit AOA and AOB. In addition, known synthetic NO scavengers such as 2-phenyl-4,4,5,5- tetramethylimidazoline-1-oxyl 3-oxide (PTIO) (Martens-Habbena et al. 2015) or its water‐soluble derivative 2-(4-carboxyphenyl)-4,4,5,5-tetramethylimidazoline-1-oxyl-3-oxide (carboxy-PTIO) (Shen et al. 2013), have been found to selectively inhibit AOA in the presence of AOB. The different sensititivity of AOA and AOB to NO scavengers may be explained by differences in the amount of free NO that can be scavenged (Kozlowski, Kits and Stein 2016; Stein 2019). It is hypothesized that in AOB NO is subjected to faster enzymatic oxidation, which avoid its accumulation and hence the possibility for it to be scavenged (Lancaster et al. 2018). However, as NO represents an obligate intermediate product in NH3 oxidation by both AOA and AOB, the ability of NO scavengers to selectively inhibit AOA and AOB is lost when they are used at high concentrations (Shen et al. 2013; Sauder, Ross and Neufeld 2016). BNI compounds as inhibitors of quorum sensing molecules Gram-negative bacteria, but also some Archaea (Paggi et al. 2003), regulate some fundamental physiological processes such as gene expression, as a function of their cell density through the synthesis of small signal molecules and their perception between individual cells in a process termed ‘quorum sensing’ (QS) (Hawver, Jung and Ng 2016). QS allows several species of bacteria (Skogman et al. 2016), including AOB (Burton et al. 2005), to recognize their cell density and form biofilms. Importantly, as QS is required for the production of extracellular chitinase and protease enzymes, which catalyze the degradation of SOM to low molecular weight organic-N compounds, it has been hypothesized that such social behaviour of microbial populations may be an important factor controlling nitrogen cycling in the rhizosphere (DeAngelis, Lindow and Firestone 2008). QS signal molecule classes include γ-butyrolactones, 2-alkyl-4-quinolones, furanones with fatty acids, and N-acylhomoserinelactones. The latter represents one of the most studied groups and are produced by representatives of the genera Nitrosomonas (Burton et al. 2005), Nitrosospira, Nitrospira and Nitrobacter (Mellbye, Bottomley and Sayavedra-Soto 2015; Mellbey et al. 2016; Mellbye et al. 2017). Interestingly, compounds such as quercetin (Gopu, Meena and Shetty 2015), curcumin (Li et al. 2018a), chlorogenic acid (Wang et al. 2019a), naringenin (Vandeputte et al. 2011), apigenin, ferulic acid and gallic acid, can act as QS inhibitors quenching biofilm formation (Vikram et al. 2010; Borges et al. 2013). These studies suggest that these putative BNI compounds may negatively affect ammonia oxidizers by interfering with QS signals. Morevoer, as NO can regulate biofilm production in N. europaea (Schmidt et al. 2004), BNI compounds with NO scavenging activity may indeed inhibit ammonia oxidation by (i) blocking biochemical reactions, i.e. the conversion of NO to NO2− and (ii) intrefering with biofilm formation. Interestingly, the compound 2-ethynylpyridine, a known nitrification inibitor (McCarty 1999), impeded biofilm formation and dispersed the pre-formed biofilms in N. europaea, although such effects were influenced by the presence in the medium of organic C (Keshvardoust et al. 2019). TESTING BNI Collecting root exudates: moving beyond hydroponic experiments The cultivation of plants in sterile or non-sterile solutions rather than in soil i.e. the hydroponic approach, has been employed to collect the BNI compounds brachialactone (Subbarao et al. 2009), sorgoleone and sakuranetin (Subbarao et al. 2013), MHPP (Zakir et al. 2008), 1.9-decanediol (Sun et al. 2016), and to elucidate the functional role of NH4+ (Zakir et al. 2008) on the release of BNI compounds (Subbarao et al. 2007b). This approach limits root damage and microbial degradation or uptake of exudates. However, hydroponic systems do not model plant growth in real soil as roots grow in the absence of mechanical impedance and therefore with an altered physiology, which in turn also affects the production and chemical composition of exudates (Barber and Gunn 1974; Neumann and Römheld 2009). Moreover, hydroponic experiments obscure the effects of plant-microbe interactions which play a pivotal role in determining quantity and chemodiversity of root exudates (Neumann et al. 2014). Therefore, the release of root exudates in hydroponics does not imply that these compounds would be released at similar rates (or even at all) when grown in soil. Yet, open questions remain on how biotic and abiotic components of soils influence the release of BNI compounds from plants growing in soil. Collection of exudates from plants grown in solid media e.g. glass beads (Sandnes, Eldhuset and Wollebæk 2005), quartz sand (Hodge, Grayston and Ord 1996) or soil included in rhizoboxes allowing precise rhizosphere sampling (Mimmo et al. 2011), can be carried out by percolating the culture media with leaching solutions and may represent a step forward in approaching the more complex growing conditions in natural soil (Vranova et al. 2013). The relative importance of the most reactive soil solid phases could be assessed by using sterile artificial soils containing gradients of clays minerals and Fe-(hydro)-oxides inoculated with selected ammonia oxidizers, to understand the extent of the complexity of the soil systems that can be analyzed with current methodologies. Shortcomings of these approaches include the adsorption of positively charged compounds onto the solid phases and the microbial degradation of exuded compounds. In addition, there are difficulties in separating compounds produced by plants from those produced by other organisms (Vranova et al. 2013). However, using a soil-sand mixture or sandy soils and applying continuous percolations instead of single leaching events, the retention of compounds on the solid phase as well as their re-adsorption by roots can be decreased (Mimmo et al. 2011). Tang and Young (1982) developed a percolation system equipped with an Amberlite XAD polymeric adsorbent resin which allowed the collection of several plant phenolics originating from the shikimic acid pathway (e.g. ferulic acid), which are frequently associated with allelopathic interactions, but also suspected of BNI activity. A restriction of these systems is that they do not provide spatial resolution of exudation. Micro-suction cups that allow the collection of soluble compounds and ions from the soil solution represent another approach used in rhizosphere research. In combination with rhizoboxes, these systems allow the sampling of soil solutions with high-spatial and temporal resolution (Puschenreiter et al. 2005; Sandnes, Eldhuset and Wollebæk 2005; Dessureault-Rompré et al. 2006). In recent years, the use of sorptive materials to collect root exudates from undisturbed rhizosphere soil has gained increasing interest. For example, sorption filters have been successfully applied to collect root exudates from lettuce (Lactuca sativa) plants (Neumann et al. 2014). Other studies demonstrated the feasibility of using polydimethylsiloxane (PDMS)-based materials such as solid phase root extraction (SPRE), matrix-SPME, PDMS microtubing (silicone tubing microextraction, STME), to extract lipophilic compounds from soils (Mohney et al. 2009; Weidenhamer, Boes and Wilcox 2009). It is worth nothing that PDMS tubing have already been used to collect the BNI compound sorgoleone from undisturbed rhizosphere soils (Weidenhamer 2005), while providing insights into the temporal and spatial dynamics of root exudates in the rhizosphere (Weidenhamer et al. 2014). Although higher recovery performances were found for nonpolar compounds, thus mirroring the nonpolar characteristics of PDMS material (Baltussen et al. 1999), the application of the stir bar sorptive extraction (SBSE) technique, by which a stir bar is coated with PDMS, has also been used successfully to extract the polar compound benzoic acid (Tredoux et al. 2000). Thus, these materials can be used to extract both polar and non-polar compounds (Weidenhamer 2005). Moreover, the combination of SPRE with microscopy techniques such as confocal laser scanning microscopy has been used to monitor the presence of specific plant secondary compounds into the root periderm and rhizosphere of living Echium plantagineum plants (Zhu et al. 2016). In addition, a tripartite mesocosm in which different plant-growing media, i.e. sand, vermiculite and soil, were used in combination with PDMS tubes and aqueous extraction allowed the collection of both hydrophobic and hydrophilic root exudates (Eilers et al. 2015). However, when soil was used as a plant growing medium, the recovery rate of root exudates was reduced probably due to their adsorption by organic matter or interaction with clay minerals. Using soils with low content of clay minerals and organic matter or mixing soil with other media, i.e. sand or vermiculite, may limit such issues. Therefore, the use of PDMS material should have strong potential in BNI research. Chemical characterization of root exudates—rhizosphere metabolomics Comprehensive chemical characterization and quantification of root exudates is an analytical challenge due to their localized deposition, low concentration in the soil solution and difficulties associated with proper sampling of the exudates (Kuzyakov and Domanski 2000; Rugova et al. 2017). Mass spectrometric techniques contributed significantly to an increased understanding of the rhizosphere (van Dam and Bouwmeester 2016). Separation techniques such as gas chromatography (GC), liquid chromatography (LC), capillary electrophoresis (CE), 13C- and 15N-labeling strategies play a pivotal role in the advancement of rhizosphere research (Rugova et al. 2017). Metabolomics is a well-established approach for high-throughput non-targeted metabolite analysis in biological and environmental samples (Weckwerth and Fiehn 2002; Ghatak, Chaturvedi and Weckwerth 2018; Weckwerth et al. 2020). Identification of rhizosphere metabolites largely depends on gas and liquid chromatography-mass spectrometry (GC-LC-MS) platforms with databases covering primary and secondary metabolisms (Weckwerth 2003; van Dam and Bouwmeester 2016; Wang et al. 2017) as well as NMR spectroscopy (Chaudhry et al. 2015; Ghatak, Chaturvedi and Weckwerth 2018). Water-soluble secondary metabolites in exudates like phenolics or flavonoids can be analyzed using liquid chromatography-mass spectrometry (LC-MS) platforms or nuclear magnetic resonance (1H-NMR) (Sumner et al. 2015). The combination of platforms can also be used if there is no prior knowledge about the type of molecules present in root exudates (Escudero et al. 2014). For data analysis, chemometry multivariate analysis e.g. Principal Component Analysis (PCA), ANOVA, Partial least square (PLS), SIMCA (Soft Independent Modelling of Class Analogy)) and mathematical modelling approaches are used to extract the information from the metabolomic techniques (Weckwerth 2011a,b; Valledor et al. 2014). Metabolomics profiles of root exudates from several plant species are listed in Table 2. The chemical composition of the semipolar fraction of root exudates from six weeks old plants of Arabidopsis thaliana was explored using a non-targeted approach (Strehmel et al. 2014). Based on the analysis and the workflow presented, more than 100 compounds were identified and structurally characterized using reversed phase UHPLC/ESI-QTOFMS, while 90 of these compounds were characterized based on mass accuracy. Similarly, a UHPLC-TOF-MS based metabolomics approach has been used to evaluate local and systemic herbivore effects in the maize leaves, vascular sap, roots and root exudates (Marti et al. 2013). Using UPLC-TQ-MS-MS, seven putative strigolactones were identified from root exudate and root extracts of the maize hybrid cv NK Falkone (Charnikhova et al. 2017). The structure of two of the seven compounds was elucidated by NMR spectroscopy as methyl (2E,3E)-4-(3,3-dimethyl-5-oxo-2-(prop-1-en-2-yl)tetrahydrofuran-2-yl)-2-(((4-methyl-5-oxo-2,5-dihydrofuran-2-yl)oxy)methylene)but-3enoate (two diastereomers 1a and 1b) (Charnikhova et al. 2017). More than fifty metabolites were identified in Arabidopsis root cell types, with glucosinolates (GSLs), phenylpropanoids (PPs) and dipeptides (DPs) being the most predominant classes detected (Moussaieff et al. 2013). Furthermore, GSLs and PPs were found to accumulate in the inner cell layer, the cortex, whereas the downstream products of these two pathways are reported to be secreted in the rhizosphere (Halkier and Gershenzon 2006). Similarly, it has been determined that the triterpenoid arabidiol undergoes enzymatic oxidative cleavage in the stele of the Arabidopsis root, while the non-volatile breakdown product, apo-arabidiol, is partly secreted in the rhizosphere (Sohrabi et al. 2015, 2017). Such results raise the possibility for metabolite transport between different root layers (Sohrabi et al. 2015, 2017). Recently, the composition of root exudate of holm oak (Quercus ilex) under varying drought conditions was identified by untargeted profiling using liquid chromatography–mass spectrometry (LC–MS). Most of the identified metabolites showed increase concentration under drought stress and a decrease concentration under-recovery. The metabolite composition under-recovery shifted towards a composition dominated mainly by amino acids (Asparagine) and with decreases in the majority of saccharides and secondary compounds (Gargallo-Garriga et al. 2018). Table 2. Metabolomics studies of root exudates. Plant species . Metabolomics platform . Compounds identified . Reference . Arabidopsis thaliana LC-TOF-MS Aromatic amino acids, dipeptides, salicylic acid, jasmonates, pphytohormones, fatty acids, phenylpropanoids (Strehmel et al. 2014) Arabidopsis thaliana UPLC/ESI-QTOF-MS Glycosylated and sulfated compounds, Amines, Carbaldehydes, Isothiocyanates, Phenylpropanoids (Monchgesang et al. 2016) Musa acuminata Triple Quad LC-MS Oxalic acid, malic acid, fumaric acid (Yuan et al. 2015) Phaseolus vulgaris L. CE-TOF MS Polyols, sugars, organic acids, amino acids (Tawaraya et al. 2014) Medicago trancatula GC-MS, LC-TOF-MS Amino acids, sugars, urea, ß-alanine, phenolics, saponins/sapogenins (Watson et al. 2015) Solanum lycopersicum 1H-NMR, LC-MS Amino acids, organic acids (acetate, lactate, malate, formic acid and succinate), sugars, polyalcohols Escudero et al. 2014) H. mantegazzianum LC-TOF-MS Amino acids, dipeptides, Malonyl monoglycosides, C18-oxylipins (Jandová et al. 2015) Eperua falcate (Aublet) LC-TOF-MS Flavonoids (Iso-liquiritigen and liquiritigen (Michalet et al. 2013) Beta vulgaris HPLC-MS Salicyclic acid and citramalic acid (Khorassani et al. 2011) Solanum tuberosum HILIC UPLC-MS Amino acids, sugars, organic acids (Balendres et al. 2016) Sorghum sudanense GC-MS Fatty acids, resorcinol and hydroquinones (Erickson et al. 2001) Zea mays UPLC-PDA-TOF-MS 1,3-benzoxazin-4-ones (Marti et al. 2013) Brachiaria humidicola ESI-FTICR mass spectrometer Brachialactone (Subbarao et al. 2009) Sorghum Bicolor EI-GC-MS methyl 3-(4-hydroxyphenyl) propionate) (Zakir et al. 2008) Oryza sativa GC-MS 1,9-decanediol (Sun et al. 2016) Sorghum bicolor EI-GC-MS Sakuranetin, sorgoleone (Subbarao et al. 2013) Brachiaria humidicola ESI-FTICR-MS Linoleic acid (LA), Linolenic acid (LN) (Subbarao et al. 2008) Plant species . Metabolomics platform . Compounds identified . Reference . Arabidopsis thaliana LC-TOF-MS Aromatic amino acids, dipeptides, salicylic acid, jasmonates, pphytohormones, fatty acids, phenylpropanoids (Strehmel et al. 2014) Arabidopsis thaliana UPLC/ESI-QTOF-MS Glycosylated and sulfated compounds, Amines, Carbaldehydes, Isothiocyanates, Phenylpropanoids (Monchgesang et al. 2016) Musa acuminata Triple Quad LC-MS Oxalic acid, malic acid, fumaric acid (Yuan et al. 2015) Phaseolus vulgaris L. CE-TOF MS Polyols, sugars, organic acids, amino acids (Tawaraya et al. 2014) Medicago trancatula GC-MS, LC-TOF-MS Amino acids, sugars, urea, ß-alanine, phenolics, saponins/sapogenins (Watson et al. 2015) Solanum lycopersicum 1H-NMR, LC-MS Amino acids, organic acids (acetate, lactate, malate, formic acid and succinate), sugars, polyalcohols Escudero et al. 2014) H. mantegazzianum LC-TOF-MS Amino acids, dipeptides, Malonyl monoglycosides, C18-oxylipins (Jandová et al. 2015) Eperua falcate (Aublet) LC-TOF-MS Flavonoids (Iso-liquiritigen and liquiritigen (Michalet et al. 2013) Beta vulgaris HPLC-MS Salicyclic acid and citramalic acid (Khorassani et al. 2011) Solanum tuberosum HILIC UPLC-MS Amino acids, sugars, organic acids (Balendres et al. 2016) Sorghum sudanense GC-MS Fatty acids, resorcinol and hydroquinones (Erickson et al. 2001) Zea mays UPLC-PDA-TOF-MS 1,3-benzoxazin-4-ones (Marti et al. 2013) Brachiaria humidicola ESI-FTICR mass spectrometer Brachialactone (Subbarao et al. 2009) Sorghum Bicolor EI-GC-MS methyl 3-(4-hydroxyphenyl) propionate) (Zakir et al. 2008) Oryza sativa GC-MS 1,9-decanediol (Sun et al. 2016) Sorghum bicolor EI-GC-MS Sakuranetin, sorgoleone (Subbarao et al. 2013) Brachiaria humidicola ESI-FTICR-MS Linoleic acid (LA), Linolenic acid (LN) (Subbarao et al. 2008) Open in new tab Table 2. Metabolomics studies of root exudates. Plant species . Metabolomics platform . Compounds identified . Reference . Arabidopsis thaliana LC-TOF-MS Aromatic amino acids, dipeptides, salicylic acid, jasmonates, pphytohormones, fatty acids, phenylpropanoids (Strehmel et al. 2014) Arabidopsis thaliana UPLC/ESI-QTOF-MS Glycosylated and sulfated compounds, Amines, Carbaldehydes, Isothiocyanates, Phenylpropanoids (Monchgesang et al. 2016) Musa acuminata Triple Quad LC-MS Oxalic acid, malic acid, fumaric acid (Yuan et al. 2015) Phaseolus vulgaris L. CE-TOF MS Polyols, sugars, organic acids, amino acids (Tawaraya et al. 2014) Medicago trancatula GC-MS, LC-TOF-MS Amino acids, sugars, urea, ß-alanine, phenolics, saponins/sapogenins (Watson et al. 2015) Solanum lycopersicum 1H-NMR, LC-MS Amino acids, organic acids (acetate, lactate, malate, formic acid and succinate), sugars, polyalcohols Escudero et al. 2014) H. mantegazzianum LC-TOF-MS Amino acids, dipeptides, Malonyl monoglycosides, C18-oxylipins (Jandová et al. 2015) Eperua falcate (Aublet) LC-TOF-MS Flavonoids (Iso-liquiritigen and liquiritigen (Michalet et al. 2013) Beta vulgaris HPLC-MS Salicyclic acid and citramalic acid (Khorassani et al. 2011) Solanum tuberosum HILIC UPLC-MS Amino acids, sugars, organic acids (Balendres et al. 2016) Sorghum sudanense GC-MS Fatty acids, resorcinol and hydroquinones (Erickson et al. 2001) Zea mays UPLC-PDA-TOF-MS 1,3-benzoxazin-4-ones (Marti et al. 2013) Brachiaria humidicola ESI-FTICR mass spectrometer Brachialactone (Subbarao et al. 2009) Sorghum Bicolor EI-GC-MS methyl 3-(4-hydroxyphenyl) propionate) (Zakir et al. 2008) Oryza sativa GC-MS 1,9-decanediol (Sun et al. 2016) Sorghum bicolor EI-GC-MS Sakuranetin, sorgoleone (Subbarao et al. 2013) Brachiaria humidicola ESI-FTICR-MS Linoleic acid (LA), Linolenic acid (LN) (Subbarao et al. 2008) Plant species . Metabolomics platform . Compounds identified . Reference . Arabidopsis thaliana LC-TOF-MS Aromatic amino acids, dipeptides, salicylic acid, jasmonates, pphytohormones, fatty acids, phenylpropanoids (Strehmel et al. 2014) Arabidopsis thaliana UPLC/ESI-QTOF-MS Glycosylated and sulfated compounds, Amines, Carbaldehydes, Isothiocyanates, Phenylpropanoids (Monchgesang et al. 2016) Musa acuminata Triple Quad LC-MS Oxalic acid, malic acid, fumaric acid (Yuan et al. 2015) Phaseolus vulgaris L. CE-TOF MS Polyols, sugars, organic acids, amino acids (Tawaraya et al. 2014) Medicago trancatula GC-MS, LC-TOF-MS Amino acids, sugars, urea, ß-alanine, phenolics, saponins/sapogenins (Watson et al. 2015) Solanum lycopersicum 1H-NMR, LC-MS Amino acids, organic acids (acetate, lactate, malate, formic acid and succinate), sugars, polyalcohols Escudero et al. 2014) H. mantegazzianum LC-TOF-MS Amino acids, dipeptides, Malonyl monoglycosides, C18-oxylipins (Jandová et al. 2015) Eperua falcate (Aublet) LC-TOF-MS Flavonoids (Iso-liquiritigen and liquiritigen (Michalet et al. 2013) Beta vulgaris HPLC-MS Salicyclic acid and citramalic acid (Khorassani et al. 2011) Solanum tuberosum HILIC UPLC-MS Amino acids, sugars, organic acids (Balendres et al. 2016) Sorghum sudanense GC-MS Fatty acids, resorcinol and hydroquinones (Erickson et al. 2001) Zea mays UPLC-PDA-TOF-MS 1,3-benzoxazin-4-ones (Marti et al. 2013) Brachiaria humidicola ESI-FTICR mass spectrometer Brachialactone (Subbarao et al. 2009) Sorghum Bicolor EI-GC-MS methyl 3-(4-hydroxyphenyl) propionate) (Zakir et al. 2008) Oryza sativa GC-MS 1,9-decanediol (Sun et al. 2016) Sorghum bicolor EI-GC-MS Sakuranetin, sorgoleone (Subbarao et al. 2013) Brachiaria humidicola ESI-FTICR-MS Linoleic acid (LA), Linolenic acid (LN) (Subbarao et al. 2008) Open in new tab Testing the effects of BNI compounds on N transformations through 15N-isotope techniques As mentioned previously, soil N transformations can be measured in terms of net, gross and potential rates (Hart et al. 1994b). Net rate measurements only provide information on overall N cycling and are only indicative of the amount of plant-available N and N leaching (Lang et al. 2016). Surprisingly, despite these limitations, net nitrification rate measurements form the majority of the BNI research carried out so far. It is noteworthy that this approach has left two fundamental BNI working hypotheses untested, that is, (i) plant compounds with BNI ability inhibit gross nitrification and (ii) inhibition occurs through direct mechanisms. To this end, the application of stable isotope 15N methods represents an ideal choice for testing the BNI postulate as they enable gross production and gross consumption rates of N to be differentiated. 15N tracer and dilution approaches have been used to measure gross N transformations (Hart and Myrold 1996). In the tracer approach, gross process rates are determined by adding 15N to the source pool (Hart et al. 1994b). However, the addition of the substrate to the source pool in the 15N tracer approach can stimulate the measured process and lead to an overestimation of its rate. In addition, process rates can also be underestimated if producing or consuming processes alter the isotopic composition of the substrate and product pools, respectively (Hart et al. 1994b), e.g. by enzymatic discrimination between 14N and 15N in both microbes and plants (Köster et al. 2011; Carlisle et al. 2014). The 15N isotope dilution method can avoid the disadvantages of the tracer approach (Davidson et al. 1991; Hart et al. 1994b; Murphy et al. 2003). This method consists of the labeling of the product pool and then monitoring the dilution of the 15N atom % by the process that produces unlabeled N (14N). Gross N transformation rates can then be calculated analytically using the equations developed by Kirkham and Bartholomew (1954) relating the decline in 15N abundance over time with the process rate. The 15N isotope dilution method has been applied to study N transformations in a wide range of systems such as agricultural soils (Burger and Jackson 2003), forest soils (Myrold and Tiedje 1986; Davidson et al. 1991; Stark and Hart 1997) and grassland soils (Jackson, Schimel and Firestone 1989; Schimel, Jackson and Firestone 1989; Norton and Firestone 1996), using intact soil cores (Schimel, Jackson and Firestone 1989; Davidson et al. 1991), rhizoboxes (Herman et al. 2006) and model root systems (Landi et al. 2006), while deepening the mechanistic understanding of the N cycle. In coniferous forest soils, NO3− consumption (e.g. microbial assimilation of NO3−) and the fast turnover of microbial biomass were important factors controlling the size of the NO3− pool, thus challenging the hypothesis of allelopathic inhibition of nitrification (Hart et al. 1994a). Using a 15N microdilution approach to study N transformations in the rhizosphere of O. sativa plants, it was found that plant NH4+ uptake was an important controller of gross nitrification rate (Herman et al. 2006). In addition, the combination of the 15N isotope dilution method and use of selective nitrification inhibitors, i.e. acetylene, allows heterotrophic and autotrophic nitrification to be measured separately, thus providing insights into the contribution of these two nitrification pathways to the gross nitrification rate (Barraclough and Puri 1995). Heterotrophic nitrification can be a significant process for the production of NO3− in the rhizosphere and the isotope dilution approach can help to better understand how the two nitrification pathways are affected by BNI plants. A combination of stable isotopes, i.e. 15NH415NO3 and acetylene (0.01% v/v), enabled quantification of the relative contribution of denitrification, autotrophic nitrification and heterotrophic nitrification to N2O emissions (Bateman and Baggs 2005). Analytical approaches enable the quantification of the total gross production and consumption rates of the labeled pool, but fail to provide information on gross rates for specific N processes (Schimel 1996). For example, in the case of the nitrification process, the measured gross production rate includes the contribution of both heterotrophic and lithoautotrophic nitrification pathways to NO3− flux, while the determination of gross NO3− consumption rates includes processes such as denitrification, microbial immobilization, plant uptake and DNRA. Importantly, although the inhibition of gross nitrification by plant metabolites should be observed for any putative BNI compounds, it is not a sufficient condition to verify the BNI postulate since gross nitrification rate can also be indirectly repressed by NH4+ consuming processes such as NH4+ immobilization, plant NH4+ uptake, or reduction of N mineralization, which can create condition of NH4+ limitations. Therefore, testing the effects of BNI compounds on gross nitrification rate, which would represent an important step toward the testing of the BNI postulate, should be coupled with measurements of other gross N processes rate associated with NH4+ and NO3− cycling. Importantly, the potentialities of the isotope dilution technique can be improved using so-called true paired experiments which consist in the application of 15NH4+ and 15NO3− to different soil samples. Using this approach, different gross N fluxes that affect NH4+ and NO3− pools can be estimated (Herman et al. 2006). At the same time, approaches such as 15N tracing models (Rütting et al. 2011; Daebeler et al. 2017) which are based on numerical data analysis, overcome the restrictions dictated by the analytical solution approach. In numerical data analysis experiments, both source and sink pools are labeled with 15N, thus combining the principles of both dilution and tracer approaches, while concentrations of NH4+, NO3− and 15N enrichment in soil samples are used as input data for the model. Then, the utilization of kinetic parameters optimization techniques which control the agreement between modelled and observed concentrations of NH4+, NO3− and their 15N enrichment, enables the calculation of several gross N transformation rates based on zero order, first order, or Michaelis-Menten kinetics (Müller et al. 2007; Rütting et al. 2011). An unquestionable advantage of this tool over the analytical approaches is that the multiple specific process rates of simultaneously occurring N transformations can be determined (Lang et al. 2016; Zhang et al. 2018), thus enhancing the power of the 15N isotope technique in the study of N process interconnections. Detection of genes and their transcripts involved in nitrification As with most molecular studies examining the ecology of organisms involved in soil nitrification, determining the effect of BNI (e.g. Byrnes et al. 2017) or synthetic nitrification inhibitors (Vasileiadis et al. 2018) in soil have focused on using polymerase chain reaction (PCR) techniques to determine their effects on AO rather than NOB. The growth and activity of ammonia and nitrite oxidizing prokaryotes in soil is routinely done through the detection of functional genes encoding key enzymes involved in N oxidation using the PCR (Nicol and Prosser 2011). Over the past two decades, a range of techniques were widely used for profiling amplicons derived from nitrifier communities including terminal restriction fragment length polymorphism (T-RFLP) (Yao et al. 2011) or denaturing gradient gel electrophoresis (DGGE) (Tourna et al. 2008). However, these semi-quantitative approaches have now been superseded by the routine combination of two approaches. Firstly, gene abundance (as a proxy for cell abundance) is determined in genomic DNA extracted from soil or other environmental samples by quantitative PCR (qPCR). This technique combines standard PCR with the detection of fluorescence derived from an DNA-binding dye (SYBR-Green I), where fluorescence is proportional to the abundance of a target gene. Secondly, high throughput sequencing of PCR amplicons and bioinformatic analysis, potentially using databases with representative sequences (Alves et al. 2018; Aigle, Prosser and Gubry-Rangin 2019), is used for determining community structure and taxonomic composition. In soil, all AOA belong to a monophyletic 16S rRNA-defined lineage within the phylum Thaumarchaeota, and generally, all AOB belong to a monophyletic lineage within the Betaproteobacteria (Purkhold et al. 2000). As such, PCR primers targeting the 16S rRNA genes of specific lineages of AO have been used (Kowalchuk et al. 1997; Ochsenreiter et al. 2003). However, in most of the studies primers targeting the gene coding for the alpha sub-unit of ammonia monooxygenase, amoA are used. While 16S rRNA assays have been used to target NOB (Freitag et al. 2005), primers amplifying nitrite oxidoreductase sub-units A and B (nxrA and nxrB, respectively) are also widely used for detecting NOB (e.g. Wertz et al. 2008; Pester et al. 2014). The functional genes of each of these AO and NOB functional groups are sufficiently divergent from each other to allow the use of specific PCR assays for the amoA genes of AOA (Tourna et al. 2008), AOB (Rotthauwe, Witzel and Liesack 1997) and comammox (Pjevac et al. 2017) and nxrB genes of Nitrobacter (Vanparys et al. 2007) and Nitrospira (Pester et al. 2014) communities. While the detection of genes by PCR informs on abundance and community composition, this does not necessarily relate to activity in soil. As such, monitoring changes in mRNA expression associated with functional genes is often used to study which organisms are potentially metabolically active in an environmental sample. mRNA transcripts of functional genes often (but not always) have short half-lifes and are therefore more likely to be indicative of in situ activity in an environmental sample. After removing co-extracted DNA and proteins (including degrading RNases), the production of cDNA from extracted RNA for DNA-dependent PCR is performed by reverse transcription with either gene-specific or random primers facilitating analysis of all transcribed genes (Nicol and Prosser 2011). Stable Isotope Probing While changes in nitrifier communities, determined by differences in the abundance or composition of functional genes, has been used to examine the growth or inhibition of nitrifier groups, these approaches target the whole community, i.e. both active and inactive cells. As such, it may be difficult to determine which specific populations are active under a particular incubation condition. Also, if changes in the relative proportion of populations in a community occurs, but overall cell abundance, as determined by qPCR, does not, then it may appear that there are no effects on any members of that community. Therefore, to identify specific populations growing in a complex environmental sample, stable isotope probing (SIP) is often used. A range of techniques are available that facilitate the identification of growing populations within complex microbial communities via the incorporation of heavy stable isotopes (e.g. 13C, 15N, 18O) present in a supplied substrate. Following incorporation into biomass, biomarkers (e.g. PLFA, DNA, RNA, protein) can then be extracted and those containing heavy isotopes separated and identified to provide taxonomic identification (Neufeld et al. 2007). By using particular substrates, the contribution of different populations to a particular functional process may be inferred. As autotrophic ammonia and nitrite oxidizers typically use CO2 or bicarbonate as a sole carbon source during growth, the most commonly used substrate is 13C-CO2, although SIP can use other heavy isotopes such as O (H218O) for targeting all growing organisms, including nitrifiers (Papp et al. 2018). The first approaches using inorganic 13C demonstrating autotrophic growth of (not yet known) nitrifiers used bicarbonate in marine water incubations to look at the incorporation into archaeal glycerol dibiphytanyl glycerol tetraethers via GC-MS analysis (Wuchter et al. 2003). For soil systems, incubation of soil in microcosms with 13CO2 in the headspace (typically at 5% vol/vol) has been widely used to examine the growth of AOA, AOB, NOB and comammox bacteria (Zhang et al. 2010; Xia et al. 2011; Wang et al. 2019b) following DNA extraction and isopycnic centrifugation in CsCl gradients (for a detailed description of the technique, see Nicol and Prosser 2011). Fully enriched 13C-DNA has a higher buoyant density (> ∼0.04 g/ml) than equivalent unlabelled or 12C-enriched DNA. By fractionating CsCl gradients and recovering DNA of different buoyant densities after precipitation and purification, qPCR of specific gene targets (e.g. amoA or nxrB genes), functional gene amplicon sequencing or metagenomic DNA sequencing of recovered genomic DNA can then be performed to quantitatively determine the enrichment of 13C into the genomes of target organisms. DNA-SIP is a powerful tool when the used isotope can be linked to a particular functional group and process e.g. incubation with 13CO2 coupled with incorporation of 13C into genomes with a specific functional gene (amoA). As such, this approach has not been used for heterotrophic nitrifiers where to incorporation of organic sources of C is not linked to a functionally or taxonomically restricted groups of organisms, and nitrification being a dissimilatory process. DNA-SIP has therefore been routinely used for examining nitrifiers fixing inorganic CO2 or −HCO3 only. This has included demonstrating niche differentiation between different populations of AOA, AOB and comammox activity under different concentrations and sources of N (e.g. mineralization of native organic N vs applied inorganic N) and inhibitor amendment. AOA have been routinely demonstrated to preferentially grow in soils where nitrification is fuelled from organic N sources (Zhang et al. 2010), while AOB grow only when inorganic ammonium is supplied at a high rate (Jiang et al. 2019). The dominance of AOA growth in acidic soils has also been demonstrated using DNA-SIP (Zhang et al. 2012). Recent work on comammox bacteria indicates that they may possess oligotrophic lifestyles and have growth characteristics more similar to AOA rather than AOB, only growing in soil in the absence of inorganic ammonium amendment (Jiang et al. 2019). Incubations in combination with synthetic inhibitors, DNA-SIP has been used to demonstrate inhibition of AOB, but not AOA, in soil amended with DMPP (Shi et al. 2016b). Combining culture-dependent and-independent approaches The majority of recent BNI studies examining the effect of particular plant species and their active compounds on communities of AO have focused on in situ studies, whereby changes in AOA or AOB abundance in soil are determined (e.g. Nuñez et al. 2018; Sarr et al. 2020). While this approach demonstrates overall changes in community structure linked to process rates, it is difficult to determine whether effects occur through direct interaction with nitrifying organisms or represent an indirect effect, which may even include different cultivars causing differences in soil physicochemical properties (e.g. pH). While determining the effect of individual compounds on isolated cultures may result in inhibition profiles that differ from those observed in soil (Lehtovirta-Morley et al. 2014), these approaches do allow determination of direct effects on nitrifying organisms, and are essential for identifying modes of action, allowing identification of genes and gene regulation. Upon identification of genes encoding for a specific physiological response, PCR-based approaches can then be used for the subsequent detection and quantification of genes and gene transcripts in the complex soil environment. However, they require an a priori knowledge of extant sequence diversity. Metagenomic and metatranscriptomic approaches utilizing high-throughput sequencing and bioinformatic analysis of all DNA or RNA transcripts circumvent these biases by targeting the entire microbial community and may therefore allow identification of novel gene variants (Nesme et al. 2016). Due to the vast diversity of soil microorganims, these approaches can also be used in conjunction with isotopes to allow separation of enriched from unlabeled nucleic acids, facilitating the recovery of genomes or transcripts contributing to a particular process (Coyotzi et al. 2017). Isolated AOA and AOB often have different sensitivities to synthetic nitrification inhibitors. For example, (Shen et al. 2013) observed that the AOB N. multiformis was more sensitive to allylthiourea, amidinothiourea and DCD, compared to the AOA N. viennensis. Using a combination of both culture dependent and soil microcosm incubations, (Zhao et al. 2020) demonstrated that simvastatin is a AOA-specific inhibitor, in both soil and culture. It has been observed that the compound 3,5-dichloroaniline (3,5-DCA) inhibited nitrate production and potential nitrification assays in a dose-dependent manner application in soil (Vasileiadis et al. 2018). Using AO cultures, they also determined that for two isolated AOA, Nitrosotalea sinensis ND2 was more sensitive to the 3,5-DCA than Nitrosocosmicus franklandus using in vitro growth assays, and both strains were more sensitive than the AOB Nitrosospira multiformis. While soil-based in situ studies are essential for determining inhibition on nitrification, combining these analyses with culture-based approaches provides more detailed information for determining variation in sensitivity to nitrification inhibitors both within and between AOA and AOB communities. Microscopic techniques Visualization of microbial population in their natural habitats allows the gaining of critical information about the ecology of target microorganisms, as well as host−microbe and microbe−microbe interactions. In microbial ecology, microscopy (which is a low-throughput method) can be used to complement, support and verify data obtained by high-throughput methods, such as the so called ‘omics’ (Bulgarelli et al. 2012; Cardinale et al. 2015). Molecular, non-in situ, approaches have the disadvantage of disrupting the micro-scale environment, thus causing the loss of the spatial information at microscale that is relevant to how microbes live and interact with both each other and hosts. Quantification of microbial cells in their natural habitats is a challenging task that can be achieved with direct methods, i.e. microscopy, or indirect methods, i.e. CFU- or MPN counts (only for microbes that can be cultivated) and PCR. Microscopy, as a direct method for microbial quantification, can deliver reliable results, since it allows single-cell recognition and quantification in a well-defined and measurable micro-space. The required resolution for such analysis can be achieved only by sophisticated optical imaging techniques, such as confocal laser scanning microscopy (CLSM) (Cardinale 2014). CLSM has several potential applications in BNI studies, which range from the localization of active cells on the rhizoplane (the root surface) to the quantification of different taxonomical or functional populations in different root zones (Fig. 3). Specific staining of taxonomic or functional populations can be achieved by specific tagging, e.g. with green fluorescent protein (GFP) transformation. Figure 3. Open in new tabDownload slide Discrimination of different microbial populations at single-cell level in the rhizosphere of lettuce (Lactuca sativa). In yellow/orange: cells of Gammaproteobacteria (white arrows); in pink/magenta: cells of Betaproteobacteriales (white arrowsheads); in red; other bacterial cells (blue arrows). Figure 3. Open in new tabDownload slide Discrimination of different microbial populations at single-cell level in the rhizosphere of lettuce (Lactuca sativa). In yellow/orange: cells of Gammaproteobacteria (white arrows); in pink/magenta: cells of Betaproteobacteriales (white arrowsheads); in red; other bacterial cells (blue arrows). Fluorescence in situ hybridization (FISH) is a method based on the application of oligonucleotide probes, whose sequences define their level of specificity (Moter and Göbel 2000). These probes are modified with one, two or more fluorescent molecules of cyanine-derivates such as fluorescein, to allow detection by CLSM. The FISH is a powerful and robust technique, that can be further combined with other methods such as secondary ion mass spectrometry (SIMS), microautoradiography (MAR) or RAMAN spectroscopy to simultaneously identify taxonomy and function of target organisms at the single-cell level (Musat et al. 2012). Specific FISH probes for functional microbial groups directly or indirectly involved in BNI, such as AO, NOB, denitrifiers or DNRA microorganisms, are available. Among the most relevant taxa involved in nitrification, specific FISH probes targeting the genera Nitrosomonas, Nitrosospira, Nitrobacter and Nitrospira have already been designed and tested (Kim, Lee and Keller 2006; Noophan et al. 2009; Daims et al. 2015). A great advantage of FISH is that a universal probe, such as the bacterial probe EUB338, may be used together with one or more specific probes, by using different fluorochromes to differentiate different probes and to distinguish from background autofluorescence. Considering the very slow growth of autotrophic nitrifiers, catalyzed reported deposition (CARD)-FISH is recommended to enhance the otherwise too low fluorescent signal (Hatzenpichler et al. 2008). Maximum projections of a confocal stack enabled to show the differential colonization pattern of salad root (Lactuca sativa) by different microbial populations of the native bacterial community stained by FISH (Fig. 3). Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM) are high resolution imaging techniques using electrons, instead of visible light sources used in fluorescence microscopy, to obtain images of the investigated objects (Dashek 2000; Klein, Buhr and Frase 2012). Despite the known limitations of these techniques, e.g. fixation and dehydration of the biological specimen, SEM has proven useful to study cell topography, morphology and size, whereas the use of TEM provided highly detailed information on the structural organization of internal cell components of both AOA (Tourna et al. 2011; Stieglmeier et al. 2014) and AOB (Fujitani et al. 2015). In addition, cryogenic electron tomography (cryo-ET) which combine electron microscopy with cryo techniques circumventing SEM and TEM limitations (Milne and Subramaniam 2009), can provide insights into the ability of AOA to use NH4+ in N limiting environments (Li et al. 2018b). SEM and TEM based studies demonstrated damage or even disruption of cell membranes in bacteria treated with the chlorogenic acid (Lou et al. 2011). Morphological changes in the cell membrane of the denitrifier Psudomonas brassicacearum were observed by TEM and helped to elucidate the mechanism of action of the natural denitrification inhibitors procyanidins (Bardon et al. 2016b). It is worth noting that SEM and TEM have been successfully applied to the study of nitrifying biofilms (Hirata, Meutia and Tsuneda 2001) and to test the anti-quorum and anti-biofilm activities of antibiotics (Gomes and Mergulhão 2017) and tannins (Trentin et al. 2013). SEM imaging coupled with energy dispersive X-ray microanalysis (SEM-EDX) allows elemental spectra to be obtained and are used to study the inhibitor effect of metallic nanoparticles on nitrifying bacteria (Yuan et al. 2013). Furthermore, the combination of SEM with other techniques such as CLSM, RAMAN spectroscopy and CG-MS has demonstrated that several plant natural compounds act as quorum sensing inhibitors and control biofilm formation in Pseudomonas fluorescens (Ding, Li and Li 2018), raising the possibility of such techniques to be applied for testing the hypothesized anti-biofilm activity of BNI compounds. CONCLUSIONS AND FUTURE RESEARCH TRAJECTORIES BNI plants have the potential to develop agricultural soils with low NO3− producing and low N2O emitting capacities (Subbarao et al. 2017), thus increasing the N-flow to the plants and N retention in soils and help agricultural systems to buffer human pressure. In combination with other N management strategies such as localized application of N fertilizers, more complex rotations that make use of cash crops and their intercropping with a living mulch (Xie et al. 2016), BNI can play a pivotal role in redrawing a new and more environmentally friendly agriculture. In this review, we provided a general framework for testing BNI along with alternative hypotheses, while discussing a set of methodological approaches that can be successfully applied in BNI research. Below, we specify a number of research needs. As AOA can functionally dominate NH3 oxidation in soils and be insensitive to AOB inhibitors, future BNI studies should beextended to AOA and address the question whether BNI compounds affect both in-vitro and in-situ activity of these AO. The recentdiscovery of comammox calls for studies on the effects of BNI compounds on these organisms as well. Plants such as Brachiaria and Sorghumthat utilize a C4 photosynthetic pathway are obligatesymbionts with AMF, which together with protozoa have the potential to limit nitrification in the rhizosphere. Therefore, studies are needed to clarify putative synergisms between plant-protozoa-AMF interactions and BNI. Collection of root exudates directly from soil represents an important step to better understand their effects on rhizosphere nitrogen cycling. Therefore, there is a need for BNI research to move beyond hydroponic experiments and apply approaches such as those discussed in this review that allow the collection of both hydrophilic and hydrophobic root exudates from plants growing in soil. Importantly, although the coupling of these techniques with metabolomics is challenging, this approach will provide fundamentalunderstanding on how plant-soil interactions affect spatial and temporal root exudateprofiles in the rhizosphere, which represents an outstandingquestion in BNI research. A major frontier for future BNI research lies in demonstrating that not only do some plants inhibit nitrification in soil, a fact that has been known since decades, but also determine whether such inhibitionoccurs via direct or indirect mechanisms. In this regard, there is a wealth of untapped potential for the use of 15N isotope techniques that allow the measurements of gross N process rates. Using 15N isotope-based experiments of differentcomplexity, mechanistic insights into the role of root exudates on nitrification and other N transforming processes can be obtained, while allowing the testing of alternative hypotheses, e.g. competition for N. Using 15N isotopes in combination with molecular-based tools such as, for example, qPCR, SIP and meta-omics approaches, will provide insights into how plants with BNI ability affect not only N gross transformationrates but also abundance, activity and diversity of microorganisms carrying out such transformations. These approaches will also allow to link in vitro assays with in situ experiments, i.e. using bioassays that provide evidence of direct inhibition of AO activity together with determining effects in soil, the latter being an area of research where evidence is still lacking. The use of microscopic techniques such as CLSM and FISH, their combination (CLSM-FISH), as well as their integration with SEM, TEM, SIMS, MAR or RAMAN spectroscopy techniques represents an exciting opportunity to study changes in morphology, activity and physiology of AO in response to BNI compounds. These approaches have the potential to provide insights into the mechanisms driving nitrification inhibition, while allowing the testing of hypotheses on mode of action of BNI compounds developed in this review. ACKNOWLEDGEMENTS We sincerely thank the anonymous reviewers for their insightful comments and suggestions. 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TI - Biological nitrification inhibition in the rhizosphere: determining interactions and impact on microbially mediated processes and potential applications
JF - FEMS Microbiology Reviews
DO - 10.1093/femsre/fuaa037
DA - 2020-11-24
UR - https://www.deepdyve.com/lp/oxford-university-press/biological-nitrification-inhibition-in-the-rhizosphere-determining-uWLg3QrtGn
SP - 874
EP - 908
VL - 44
IS - 6
DP - DeepDyve
ER -