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View ORCID ProfileGuntur V. Subbarao, Masahiro Kishii, View ORCID ProfileAdrian Bozal-Leorri, View ORCID ProfileIvan Ortiz-Monasterio, View ORCID ProfileXiang Gao, Maria Itria Ibba, View ORCID ProfileHannes Karwat, M. B. Gonzalez-Moro, Carmen Gonzalez-Murua, View ORCID ProfileTadashi Yoshihashi, View ORCID ProfileSatoshi Tobita, View ORCID ProfileVictor Kommerell, Hans-Joachim Braun, and Masa IwanagaaCrop, Livestock and Environment Division, Japan International Research Center for Agricultural Sciences, Ibaraki 305-8686, Japan;bGlobal Wheat Program, International Maize and Wheat Improvement Center, 56237 Texcoco, Mexico;cDepartment of Plant Biology and Ecology, University of the Basque Country, E-48080 Bilbao, Spain;dCollege of Bioresources Sciences, Nihon University, Kanagawa 252-0880, Japan
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Edited by Donald R. Ort, University of Illinois at Urbana-Champaign, Urbana, IL, and approved July 13, 2021 (received for review May 3, 2021)
SignificanceGlobally, wheat farming is a major source of nitrogen pollution. Rapid generation of soil nitrates cause nitrogen leakage and damage ecosystems and human health. Here, we show the 3NsbS chromosome arm in wild grass (Leymus racemosus) that controls root nitrification inhibitor production can be transferred into elite wheat cultivars, without disrupting the elite agronomic features. Biological nitrification inhibition (BNI)–enabled wheats can improve soil ammonium levels by slowing down its oxidation and generate significant synergistic benefits from assimilating dual nitrogen forms and improving adaptation to low N systems. Deploying BNI-enabled wheat on a significant proportion of current global wheat area (ca. 225 M ha) could be a powerful nature-based solution for reducing N fertilizer use and nitrogen losses while maintaining productivity.AbstractActive nitrifiers and rapid nitrification are major contributing factors to nitrogen losses in global wheat production. Suppressing nitrifier activity is an effective strategy to limit N losses from agriculture. Production and release of nitrification inhibitors from plant roots is termed “biological nitrification inhibition” (BNI). Here, we report the discovery of a chromosome region that controls BNI production in “wheat grass” Leymus racemosus (Lam.) Tzvelev, located on the short arm of the “Lr#3Nsb” (Lr#n), which can be transferred to wheat as T3BL.3NsbS (denoted Lr#n-SA), where 3BS arm of chromosome 3B of wheat was replaced by 3NsbS of L. racemosus. We successfully introduced T3BL.3NsbS into the wheat cultivar “Chinese Spring” (CS-Lr#n-SA, referred to as “BNI-CS”), which resulted in the doubling of its BNI capacity. T3BL.3NsbS from BNI-CS was then transferred to several elite high-yielding hexaploid wheat cultivars, leading to near doubling of BNI production in “BNI-MUNAL” and “BNI-ROELFS.” Laboratory incubation studies with root-zone soil from field-grown BNI-MUNAL confirmed BNI trait expression, evident from suppression of soil nitrifier activity, reduced nitrification potential, and N2O emissions. Changes in N metabolism included reductions in both leaf nitrate, nitrate reductase activity, and enhanced glutamine synthetase activity, indicating a shift toward ammonium nutrition. Nitrogen uptake from soil organic matter mineralization improved under low N conditions. Biomass production, grain yields, and N uptake were significantly higher in BNI-MUNAL across N treatments. Grain protein levels and breadmaking attributes were not negatively impacted. Wide use of BNI functions in wheat breeding may combat nitrification in high N input–intensive farming but also can improve adaptation to low N input marginal areas.BNInitrogen pollutionnitrification inhibitiongenetic improvementwheatNitrification and denitrification are critical soil biological processes, which, left unchecked, can accelerate generation of harmful reactive nitrogen (N) forms (NO3−, N2O, and NOx) that trigger a “nitrogen cascade,” damaging ecosystems, water systems, and soil fertility (1⇓⇓⇓⇓⇓⇓–8). Excessive nitrifier activity and a rapid generation of soil nitrates plague modern cereal production systems. This has led to shifting crop N nutrition toward an “all nitrate form,” which is largely responsible for N losses and a decline in agronomic nitrogen-use efficiency (NUE) (6, 7, 9⇓–11).Wheat, one of the three founding crops for food security (12), consumes nearly a fifth of factory-produced N fertilizers, and it has an average NUE of 33%, which has remained unchanged for the last two decades (13⇓–15). Regulating soil nitrifier activity to slow the rate of soil nitrate formation should provide more balanced N forms (NH4+ and NO3−) for plant uptake (rather than nearly “all NO3−” at present), reduce N losses, and facilitate the assimilation of dual N forms. This optimizes the utilization of biochemical machinery for N assimilation, improving stability and possibly enhancing yield potential (16). In addition, the assimilation of NH4+ is energetically more efficient (requiring 40% less metabolic energy) than NO3− assimilation (16). Often, a stimulatory growth response is observed in wheat, when 15 to 30% of NO3− is replaced with NH4+ in nutrient solutions (17, 18).Synthetic nitrification inhibitors (SNIs) have been shown to suppress N2O emissions, reduce N losses, and improve agronomic NUE in several cereal crops including wheat (6, 19⇓–21). However, the lack of cost effectiveness, inconsistency in field performance, inability to function in tropical environments, and the concerns related to the entering of SNIs into food chains have limited their adoption in production agriculture (6, 7, 19, 20).Biological nitrification inhibition (BNI) is a plant function whereby nitrification inhibitors (BNIs) are produced from root systems to suppress soil nitrifier activity (22⇓⇓⇓–26). Earlier, we reported that the BNI capacity in the root systems of cultivated wheat lack adequate strength to effectively suppress soil nitrifier activity in the rhizosphere (24, 25). Leymus racemosus (hereafter referred to as “wild grass”), a perennial Triticeae evolutionarily related to wheat, produces extensive root systems (SI Appendix, Fig. S1) and was discovered to have a high BNI capacity several times higher than cultivated wheat. It was also effective in suppressing soil nitrifier activity and in reducing soi -nitrate formation (SI Appendix, Fig. S2) (25). Subsequently, the chromosome Lr#n = 3Nsb was found to be controlling a major part of BNI capacity in wild grass, and it is the focus of our current research (25, 27, 28). Earlier, we reported that Lr#I and Lr#J had a minor impact on BNI capacity, but they are not the focus of this research (25).We transferred the Lr#n chromosome (Lr#n-SA = T3BL.3NsbS) controlling BNI capacity (hereafter referred to as BNI trait) into the cultivated wheat, Chinese Spring (CS). The results of the transfer of this BNI trait into several elite wheat types with a grain-yield (GY) potential >10 t ha−1, resulting in substantial improvements of BNI capacity in root systems, are reported in this paper.ResultsBNI Capacity Has Not Increased over Five Decades of Wheat Breeding.We evaluated 20 International Maize and Wheat Improvement Center (CIMMYT)–derived wheat varieties released between 1950 and 2010 (belonging to both pre-Green Revolution [GR] and post-GR era wheat varieties) to determine the impact of five decades of breeding under high nitrogen input conditions on the BNI capacity of wheat root systems (SI Appendix, Study 1). We observed no clear trend in the 20 varieties’ BNI capacity (SI Appendix, Fig. S3). There were significant differences (P 10 t ⋅ ha−1 (SI Appendix, Tables S2D and S3 and https://www.orderseed.cimmyt.org/iwin/iwin-results-1.php). This was achieved by utilizing at least four backcrosses and selection for T3BL.3NsbS using fluorescence in situ hybridization following Kishii et al. (29) (Fig. 3 A and B and SI Appendix, Fig. S6 A and B). We conformed an enhanced BNI capacity, as there were significant improvements (P < 0.001) in BNI activity release from the root systems of the most BNI elite wheats (Table 3 and SI Appendix, Study 5a). We also observed a near doubling (P < 0.001) in the release of BNI activity from root systems of BNI-MUNAL and BNI-ROELFS (compared to MUNAL control and ROELFS control). For “BNI-QUAIU,” we observed only a 50% increase (P < 0.001) in BNI activity release. For “BNI-NAVOJOA,” there was no significant improvement in BNI release compared to “NAVOJOA control” (Table 3), indicating that BNI trait expression is wheat genetic background dependent. Subsequent studies (SI Appendix, Study 5b) with BNI-MUNAL revealed that BNI release rates were between two and five times higher than in MUNAL control (monitored over 6 d, during which time root exudates were collected using different trap solutions), indicating enormous plasticity in the phenotypic expression of BNI trait (Fig. 4). Such plasticity in the magnitude of BNI release is needed to deliver the required dosage of BNIs (determined by amounts of NH4+ available at soil sites) for suppressing and/or moderating nitrifier activity (23, 26); root systems constantly face the challenge of temporal and spatial variation in rhizosphere environment.Fig. 3.Karyotype analysis of BNI isogenic wheat lines. (A) Wheat line MUNAL. (B) BNI-MUNAL carrying Lr#n-SA translocation (complete short arm) on wheat chromosome 3B (T3BL.3NsbS) Genomic in situ hybridization (GISH)/Florescence in situ hybridization (FISH) (red: L. racemosus genomic DNA, green AAG probe).Fig. 4.Two- to fivefold higher BNI activity is released from BNI-MUNAL (i.e., MUNAL carrying T3BL.3NsbS) compared to MUNAL control (BNI isogenic lines) during a 6-d monitoring period using various root exudate trap solutions (SI Appendix, Study 5b). 1) RE-NH4-1 (1.8 L aerated solutions of 0.5 mM NH4Cl + 200 μM CaCl2 for 24 h—first day collection); 2) RE-nutr-NH4-1 (1.8 L aerated solutions of one-quarter strength nutrient solution with 0.5 mM NH4Cl for 24 h—second day collection); 3) RE-water-1 (1.8 L aerated solutions of 200 μM CaCl2 for 24 h—third day collection); 4) RE-NH4-2 (1.8 L aerated solutions of 1.0 mM NH4Cl + 200 μM CaCl2 for 24 h—fourth day collection); 5) RE-nutr-NH4-2 (1.8 L aerated solutions of one-quarter strength nutrient solution with 1.0 mM NH4Cl for 24 h—fifth day collection); and 6) RE-water-2 (1.8 L aerated solutions of 200 μM CaCl2 for 24 h—sixth day collection). Values are means ± SE from four replications.BNI Trait (T3BL.3NsbS) Suppresses Nitrification and Improves N Uptake, Biomass Production, and GY in a Range of Nitrogen Inputs under Field Conditions—Proof of Concept.Based on conservative estimates of root biomass being 1.95 Mg ⋅ ha−1 (assuming that 10% of the total aboveground biomass measured is allocated to roots) with maximum BNI activity release rates of 182 ATU ⋅ g−1 root dry weight d−1 (Table 3 and Fig. 4), we estimate that 354.9 × 106 ATU ⋅ ha−1 ⋅ d−1 can potentially be released from the root systems of BNI-MUNAL at its peak (i.e., booting stage—GS51, Zadoks scale), measured in hydroponics (30). This estimate amounts to an inhibitory potential equivalent to the application of 212.9 g nitrapyrin ha−1 ⋅ d−1 [based on 1 ATU being equivalent to 0.6 μg of nitrapyrin (26, 31)]. Such high levels of BNI release may not be sustained over extended periods under field conditions. Nevertheless, this is large enough to have significant suppressive effect on nitrifier populations.Field studies on acidic soils (soil pH 5.0 to 5.5) at Japan International Research Center for Agricultural Sciences (JIRCAS; Tsukuba, Japan; SI Appendix, Study 6a) indicated a 30% reduction in soil nitrate levels (P < 0.05) and substantial improvements in soil ammonium levels (P < 0.001) (in core soil samples taken at a 20-cm depth near plant roots) (SI Appendix, Table S4A) (compared to MUNAL control field plots), indicating the expression of BNI function in BNI-MUNAL root systems. In root-zone soils (defined as “soil that is in close proximity to roots”) (SI Appendix, Fig. S7A, 1), the nitrate percentage of inorganic N pool (%) declined by 26% (P < 0.001), potential net nitrification rates declined by 17% (P < 0.05) (Table 4), and potential nitrification declined by 28% (SI Appendix, Fig. S7A). The slopes of regression lines are significantly different (P < 0.001) based on analysis of covariance (ANCOVA). Also, N2O emissions based on laboratory incubation studies declined by 25% (P < 0.01) (Fig. 5A; SI Appendix, Fig. S7B) and soil archaea (AOA) populations declined by 20 to 36% (P < 0.005) (Fig. 5B). BNI function had a stronger inhibitory effect on archaea compared to ammonium oxidizing bacteria (AOB) populations, as AOBs did not show significant decline in BNI-MUNAL (SI Appendix, Fig. S7C). This lends support to recent reports of BNIs being more potent on AOAs (32, 33), whereas SNIs are more effective on AOBs (34). Furthermore, soil microcosm studies (SI Appendix, Study 6b) with alkaline soils suggested a 45% decline (P < 0.05) in AOBs with BNI-MUNAL but did not influence AOAs (SI Appendix, Table S4B).Table 4.Nitrate percentage of inorganic N pool and potential net nitrification rates in root-zone soils of field-grown plants of BNI isogenic lines, MUNAL control versus BNI-MUNAL after 21-d incubation period (SI Appendix, Study 6a)Fig. 5.BNI function impact on N2O emissions and nitrifying populations in root-zone soils of field-grown wheat lines (SI Appendix, Study 6a). (A) N2O emissions from root-zone soils of BNI isogenic lines, MUNAL control versus BNI-MUNAL. The root-zone soils used in this study were collected from MUNAL control and BNI-MUNAL (from 250 kg ⋅ N ⋅ ha−1 field plots). A total of 5 g air-dried soil was incubated with 250 ppm N [as (NH4)2SO4] using a 100-mL glass vial at 20 °C with 80% relative humidity in the incubator; soil moisture levels were maintained at 60% water-filled pore space during the incubation period. Values are means ± SE of four replications (see SI Appendix, Fig. S7B for cumulative N2O emissions over the 21-d period and for a statistical analysis of these results). (B) Influence of BNI-MUNAL on AOA populations in root-zone soils of field-grown plants. These results suggest that BNI-MUNAL suppressed AOA ranging from 20 to 36% depending on the nitrogen treatment of field plots. Root-zone soil samples were taken 16 d after the application of the second split nitrogen fertilizer. Values are means ± SE of four replications. Based on a three-way analysis of data using a General Linear Model model with SYSTAT 14.0; significant (P < 0.005) genetic stock effect on AOA; significant (P < 0.005) nitrogen treatment effect on AOA populations in rhizosphere soils.However, this requires additional studies because most available evidence indicates that BNI function is mostly effective in soils that are acidic or neutral (5, 6, 23⇓⇓–26). Functionally, AOAs are most active and dominant in acid soils (34), whereas AOBs are active and dominate in neutral alkaline soils (35⇓–37). The possibility for BNI trait expression under a wide range of soil pH conditions can potentially expand the scope for soil types in which BNI wheats can be deployed. The above observations were, however, based on laboratory incubation studies using root-zone soils from field-grown plants. The magnitude of BNI impact on bulk soils remains unknown, as is the BNI pathway that could influence nitrifier populations beyond the rhizosphere root zone.In addition, nitrogen metabolism in BNI-MUNAL was fundamentally altered. This is evident from radical changes in the relationship between leaf nitrate levels and nitrate reductase activity (NRA) in BNI-MUNAL (compared to MUNAL control) (SI Appendix, Study 6a). The slopes of regression lines are significantly different (P < 0.001) based on ANCOVA (Fig. 6). Further, BNI trait introduction led to a substantial decline in leaf nitrate levels (about 30 to 40%; P < 0.001; SI Appendix, Table S5) and leaf NRA (around 20%; P < 0.001) (SI Appendix, Table S6) and an increase (about 15%; P < 0.001) in glutamine synthetase activity (GSA) in leaves; GSA is an enzyme that is at the forefront of ammonium assimilation (SI Appendix, Table S6). Likely due to enhanced ammonium nutrition (uptake and assimilation), the root-zone soil pH was consistently lower (about 0.1 to 0.2 unit; P < 0.001) in BNI-MUNAL (SI Appendix, Fig. S7D).Fig. 6.Relationship between leaf nitrate levels and NRA activity in field-grown BNI isogenic lines, MUNAL control, and BNI-MUNAL (SI Appendix, Study 6a). The slopes of regression lines are significantly different (P < 0.001) based on ANCOVA. Leaf sample data from all three nitrogen treatments are used in this presentation; first sampling data are used. NRA and leaf nitrate analysis from leaf samples collected from four plants for each experimental plot represent each data point. Leaf nitrate levels and NRA levels were substantially lower in BNI-MUNAL compared to MUNAL control. The relationship between NRA and leaf nitrate levels is fundamentally different in BNI-MUNAL compared to MUNAL control. Also, see SI Appendix, Tables S5 and S6 for detailed results on NRA and leaf nitrate levels and for the statistical analysis of results.BNI-MUNAL had improved total biomass production (P < 0.001) and GY (P < 0.001) across treatments (Fig. 7 and SI Appendix, Study 6a and Table S7) based on field evaluations at the JIRCAS experimental station in 2019, with improved (P < 0.001) agronomic attributes: harvest index, tiller numbers, and 100 seed wt. (SI Appendix, Table S7). The biggest impact from introducing a BNI trait is evident in no N application field plots in which N deficiency symptoms are visible (also based on Soil Plant Analysis Development chlorophyll meter readings that reflect chlorophyll and nitrogen content in leaves) only in MUNAL control but not in BNI-MUNAL (SI Appendix, Fig. S8 A–C). Its biomass production and GYs were 50% higher (P < 0.001) than MUNAL control (Fig. 7 and SI Appendix, Table S7; SI Appendix, Fig. S8D). With N fertilization (100 to 250 kg ⋅ N ⋅ ha−1), BNI-MUNAL yielded about 10 to 14% (P < 0.001) higher than MUNAL control (Fig. 7). This is possibly due to improved NH4+ assimilation, which is energetically more efficient than NO3− assimilation (16) and can have a synergistic impact on growth and GYs. Supplemental NH4+ in nutrient solutions has been reported to stimulate growth in wheat and maize (15, 17).Fig. 7.GY of BNI isogenic lines, MUNAL control, and BNI-MUNAL under various nitrogen fertilizer applications in the field (SI Appendix, Study 6a). Three-way ANOVA using General Linear Model with SYSTAT 14.0; SE of Least Square mean (genetic stock) 0.164 (P < 0.001); SE of LS mean (N-Tr) 0.201 (P < 0.001); values are means ± SE of four replications. P < 0.001; *P < 0.05.Nitrogen uptake (aboveground biomass that includes grain) improved by about 28% (P < 0.001) (ranging from 9 to 58% depending on N fertilizer treatment) in BNI-MUNAL (Fig. 8 and SI Appendix, Study 6a and Fig. S9 A and B). It is likely that the root systems of perennial wild grass have the ability to mineralize N more efficiently from soil organic matter (SOM) than cultivated wheat, as they are highly adapted to low fertility and low N environments (38). Efficient N uptake from SOM can be part of the adaptation to low N environments. The exceptional performance of BNI-MUNAL under low N conditions (58% higher N uptake; P < 0.001) supports the hypothesis that T3BL.3NsbS, in addition to the BNI trait, is also carrying genes that improve the uptake of native soil N by efficient SOM mineralization, introduced as part of the BNI trait package. SOM mineralization rates were nearly doubled (P < 0.05) in root-zone soils of BNI-MUNAL compared to MUNAL control within low to medium N treatments but not under high N treatment (250 kg ⋅ N ⋅ ha−1) (SI Appendix, Fig. S9C), further supporting such a hypothesis. Nevertheless, the potential impact of BNI function on SOM mineralization beyond root-zone soils (i.e., bulk soils) remains unknown at this stage.Fig. 8.Total nitrogen uptake (based on aboveground dry matter that includes grain) in wheat BNI isogenic lines (MUNAL control and BNI-MUNAL) under various nitrogen fertilizer applications in the field (SI Appendix, Study 6a). Introduction of BNI trait (T3BL.3NsbS) resulted in substantial improvements in nitrogen uptake in BNI-MUNAL compared to MUNAL control. Three-way ANOVA using General Linear Model with SYSTAT 14.0; SE of Least Square mean (genetic stock) 5.79 (P