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. 2020 Mar 25;10:5453. doi: 10.1038/s41598-020-62199-1

Symbiotic nitrogen fixation and endophytic bacterial community structure in Bt-transgenic chickpea (Cicer arietinum L)

Das Alok 1, Harika Annapragada 2, Shilpa Singh 2, Senthilkumar Murugesan 2,✉, Narendra Pratap Singh 1
PMCID: PMC7096491  PMID: 32214159

Abstract

Symbiotic nitrogen fixation (SNF) of transgenic grain legumes might be influenced either by the site of transgene integration into the host genome or due to constitutive expression of transgenes and antibiotic-resistant marker genes. The present investigation confirmed proper nodulation of five tested Bt-chickpea events (IPCa2, IPCa4, IPCT3, IPCT10, and IPCT13) by native Mesorhizobium under field environment. Quantitative variations for nodulation traits among Bt-chickpea were determined and IPCT3 was found superior for nodule number and nodule biomass. Diversity, as well as richness indices, confirmed the changes in bacterial community structure of root and root-nodules from Bt-chickpea events IPCa2 and IPCT10. Especially, Gram-positive bacteria belonging to Firmicutes and Actinobacteria were selectively eliminated from root colonization of IPCa2. Richness indices (CHAO1 and ACE) of the root-associated bacterial community of IPCa2 was 13–14 times lesser than that of parent cv DCP92-3. Root nodule associated bacterial community of IPCT10 was unique with high diversity and richness, similar to the roots of non-Bt and Bt-chickpea. It indicated that the root nodules of IPCT10 might have lost their peculiar characteristics and recorded poor colonization of Mesorhizobium with a low relative abundance of 0.27. The impact of Bt-transgene on bacterial community structure and nodulation traits should be analyzed across the years and locations to understand and stabilize symbiotic efficiency for ecosystem sustainability.

Subject terms: Rhizobial symbiosis, Microbiome

Introduction

Chickpea (Cicer arietinum L.) is a self-pollinating diploid (2n = 16) grain legume with a genome size of 738 Mb, grown and consumed all over the world, especially in the Afro-Asian countries1. As the major chickpea producing country, India contributes 61.49% of global production with the productivity of 0.951 t/ha2. However, chickpea productivity is stagnating (<1000 kg/ha) due to several biotic and abiotic stresses. Gram pod borer (Helicoverpa armigera Hubner) is the major devastating pest which attack chickpea starting from first fortnight after sowing, voraciously during flower and pod development stages resulting in yield loss of up to 20–30% annually. Due to the successful introduction of Bt-cotton in India, the pest sequently moves from cotton to other crops including pigeonpea and chickpea. Polyphagous, high fecundity and insecticide resistant nature of pod borer led to the damage to pods ranging from 30–95% with 400 kg/ha yield losses3,4. Conventional breeding approaches for insect resistance have limited success in chickpea due to lack of sufficient resistance source and incompatibility with many of the wild relatives5. Success of Bt-cotton in India led extensive research on developing transgenic crops especially, insect resistance Bt-chickpea6–12. Site of insertion of transgene in plant genome is critical as it could alter plant metabolism and toxicity of Bt-protein13–16. Similarly, insertion of the transgene in active coding region of genome might be responsible for hemizygous state of some Bt-chickpea events with distorted segregation ratio12. Altered plant metabolism of genetically modified (GM) plants along with constitutive expression of chimeric Bt-transgenes and neomycin phospho-transferase II (nptII) can also influence the diversity, and richness of endophytic bacterial community that are often described as an important modulating agent of plants’ fitness to adapt against environmental stresses.

The endophytic bacterial community of transgenic-maize TC1507 (Cry1F and herbicide resistance phosphinothricin-N-acetyltransferase) differed from that of MON810 (Cry1Ab) and their near-isogenic parent. Highest species diversity (Shannon) and richness (Chao 1) were reported in TC1507 and MON810, respectively, but the values were not statistically significant17. Changes in the organic carbon content in the rhizosphere of non-Bt and Bt-brinjal can be attributed to alterations in the quality and composition of root exudates that could further be responsible for fluctuations in density and diversity of actinomycetes population.

Especially in grain legumes, effect of transgenics on symbiotic nitrogen fixation that fertilizes crop and soil should be assessed. Transgenic trait impaired several BNF parameters in glyphosate-resistant (GR) or ROUNDUP READY RR-soybean, with transgene coding 5-enolpiruvylshikimic acid-3-phosphate synthase-EPSPS18. Nodule dry weight (NDW) was the attribute most negatively affected by the transgenic trait, with reductions ranging from 10 to 21% and congruent with the decrease in percent total nitrogen as ureides (%NU) in the transgenic cultivars19. Despite the lack of yield penalty in transgenic legumes, their long term impact on symbiotic efficiency and rhizosphere ecosystem should be monitored. Hence, present investigation is aimed to understand the possible changes in nodulation and bacterial community structure associated with root and nodule tissues of five Bt-chickpea lines vis a vis parent control cv DCP 92-3.

Results

Effect of Bt-transgene integration on nodulation of transgenic chickpea

Field experiment using surface sterilized seeds of non-Bt and Bt-chickpea confirmed proper germination and nodule initiation process. However, nodule number and their fresh biomass varied among the transgenic events (Table 1). IPCT 3 recorded the lowest nodule number at early vegetative stage, and recovered at later stages and recorded highest nodule number at pod initiation stage along with IPCT 4. IPCa 4 recorded the lower nodule biomass compared to parent cv DCP 92-3 while IPTC 3 recorded the highest nodule biomass. This particular transgenic event improved the nitrogen availability in the rhizosphere to 2.47 g N/kg soil (Table 2). However, the maximum nitrogen content of shoots at early vegetative stage is reported with IPCa 2 and IPCT 10 followed by IPCa 4. N-content of shoots declined in transgenic events compared to parent during later stages of plant growth except for IPCa 4.

Table 1.

Nodulation traits of Bt-transgenic chickpea.

Events Nodule Number (Unit/plant) Nodule Fresh Biomass (g/plant)
63DAS 75DAS 96DAS 63DAS 75DAS 96DAS
Parent cv. DCP 92-3 18 ± 2.5 24 ± 1.7 11 ± 2.2 1.61 ± 0.18 3.85 ± 0.32 8.62 ± 0.62
IPCa 2 19 ± 2.2 23 ± 2.5 18 ± 2.5 1.67 ± 0.17 4.85 ± 0.21 8.41 ± 0.50
IPCa 4 16 ± 2.2 24 ± 1.3 34 ± 3.1 1.28 ± 0.26 3.21 ± 0.27 7.54 ± 0.44
IPCT 3 12 ± 1.7 21 ± 2.5 32 ± 2.5 1.21 ± 0.20 4.44 ± 0.36 9.77 ± 0.67
IPCT 10 18 ± 2.9 27 ± 2.9 18 ± 1.7 1.49 ± 0.18 3.41 ± 0.19 6.12 ± 0.20
IPCT 13 16 ± 2.1 33 ± 2.6 20 ± 2.1 1.48 ± 0.21 4.29 ± 0.34 6.92 ± 0.50
CD (P = 0.05) 2.81 5.02 5.18 NA 0.70 1.09
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Table 2.

Yield and nitrogen content in the rhizosphere soil and plant tissues of Bt-chickpea.

Transgenic Events N-content of rhizosphere soil (g/kg soil) N content of chickpea root (%) N-content of chickpea shoot (%) Average grain yield (g/plant)*
Early Stage Late Stage
Parent cv. DCP 92-3 1.77 ± 0.13 1.12 ± 0.12 1.77 ± 0.12 2.26 ± 0.07 17.57 ± 2.07
IPCa 2 1.25 ± 0.15 0.77 ± 0.11 2.17 ± 0.15 1.61 ± 0.15 13.30 ± 4.40
IPCa 4 1.10 ± 0.16 0.84 ± 0.12 2.15 ± 0.18 2.20 ± 0.14 15.67 ± 0.05
IPCT 3 2.47 ± 0.13 0.91 ± 0.15 1.87 ± 0.18 1.76 ± 0.10 14.23 ± 0.97
IPCT 10 0.60 ± 0.08 1.05 ± 0.14 2.17 ± 0.19 1.68 ± 0.15 15.73 ± 2.40
IPCT 13 1.90 ± 0.16 0.77 ± 0.12 1.54 ± 0.15 1.60 ± 0.07 15.40 ± 1.35
CD (P = 0.05) 0.289 NA 0.385 0.291 NA
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*Average value of three replications in which grain yield of 30 plants per replication was considered.

Taxonomic characterization of chickpea associated bacterial community

A total of 1,033,280 bacterial (V3-V4 of 16S rDNA) sequencing reads were obtained from root samples of chickpea with counts per sample ranging from 113,671 to 248,340. Sequencing of root-nodule samples resulted in a total of 606,112 sequence reads ranging from 58,237 to 155,545 per sample. Rarefaction curve for observed OTUs in root sample of IPCa2 tended to an asymptote and this indicated the sufficiency of sequence depth (Fig. S1). On the contrary, rarefaction curves of other samples did not saturate and thus OUT richness might be higher than the observed. Among the tested root-nodule samples except IPCT 10, rarefaction curves tended to asymptote. Rarefaction curves for Shannon and Simpson diversity indices reached the saturation plateau within approximately 10,000 sequence reads in every root and nodule samples.

Read were classified taxonomically using a high performance version of the Ribosomal Database Project (RDP) Naïve Bayes taxonomic classification algorithm. Bacterial reads unclassified at phylum level is ranging from 0.3 to 10.06% with maximum in roots of transgenic event IPCT 10. Taxonomic classification of OTUs resulted in detection of 22–29 phyla in root and 15–28 phyla in root-nodule microbiome of chickpea (Table S1). However, only 7 phyla colonizing all tested root tissues and 2 phyla from root-nodules are considered as dominant phyla with relative abundance more than 0.01. Four major phyla detected in all tested chickpea tissue samples are Proteobacteria, Cyanobacteria, Firmicutes, and Actinobacteria. Phylum Bacteroidetes is detected in 75% of tested tissue samples. Roots of parent cv DCP 92-3 is colonized equally by Proteobacteria and Cyanobacteria with relative abundance of ~0.35. Other dominant bacterial phyla colonizing chickpea roots are Actinobacteria (0.17) > Firmicutes (0.07%) > Chloroflexi (0.009) > Planctomycetes (0.008) > Gemmatimonadetes (0.006). Bacterial colonization of transgenic event IPCT10 significantly differs from parent as well as other transgenic events (Fig. 1). Relative abundance of proteobacteria in nodule tissues of IPCT10 was 0.42 while that of root-nodule tissues from remaining transgenic lines is 0.85–0.92. This is followed by Cyanobacteria with relative abundance ranging from 0.08–0.15. Firmicutes and Actinobacteria are considered as rare phylum in most of the tested nodule tissues with relative abundance of <0.001.

Figure 1.

Figure 1

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Relative abundance of root and root-nodule associated endophytic bacterial phyla of non-Bt and Bt-transgenic chickpea. Phylum level bacterial composition in root tissues of IPCa2 and root-nodules of IPCT10 are unique in comparison to rest of the Bt-chickpea and parent cultivar.

Percentage of classified bacterial reads at Genus level is dropped to 34–92% in root tissues. Genus level taxonomical classification resulted in the detection of 311–655 genera in root tissues and 161–567 Genera in root-nodules. Prominent Genera associated with root tissues are Calothrix, Rickettsia, Mesorhizobium, Methylobacillus, Arthrobacter, Bacillus, Streptomyces, Saccharopolyspora, Rhodococcus, Ramlibacter, Propionivibrio, Janthinobacterium, Kaistobacter, Sphingomonas, Ammoniphilus, and Rubrobacter with relative abundance >0.01. Mesorhizobium is the most dominant bacteria in root -nodules with relative abundance ranging between 0.74–0.82. However, IPCT10 reported poor colonization of Mesorhizobium with relative abundance of 0.27. Actinocatenispora, Pseudaminobacter, Burkholderia, and Shinella are detected only in root-nodules with RA of >0.001.

α-diversity of bacterial community associated with tissues of non-Bt and Bt transgenic chickpea

Number of bacterial species detected in each root sample ranges from 1230–1529 in root tissues except IPCa 2 that reported only 425 species (Table 3). Transgenic event IPCa 4 recorded maximum number of bacterial species. Similarly, bacterial species ranging from 144–197 were detected in root-nodules except one transgenic event IPCT 10 where 1196 bacterial species are detected. Root-nodules of chickpea cv. DCP 92-3 are colonized by four different species of Mesorhizobium i.e. M. huakuii, M. septentrionale, M. camelthorni, and M. opportunistum that collectively contribute 11.13% reads of Mesorhizobium. Remaining 88.87% reads of Mesorhizobium are not classified at species level. Interestingly, root-nodules of IPCa2 supported the colonization of M. amorphae that contributed 29.76% of total Mesorhizobium reads along with other species like M. septentrionale, M. camelthorni, and M. huakuii. M. amorphae was detected only in root -nodules of IPCa2. It was observed that the total number of V3-V4 reads from root-nodules of IPCT3 and IPCT10 i.e. 152814 and 155545 respectively are significantly higher than that of remaining samples (58237–92813) and the difference reflected on abundance of Mesorhizobium reads. However, the relative abundance (%) of Mesorhizobium in IPCT3 is similar to that of parent cultivar DCP 92-3. Transgenic event IPCT10 reported very low colonization of Mesorhizobium with 27.05% of total bacterial reads, and detected the presence of single species of M. huakuii that contribute 3.25% of 42067 Mesorhizobium reads (Table S2).

Table 3.

Data Summary on metagenomic sequencing of v3-v4 regions of 16S rDNA.

Sample ID No. of OTUs No. of Phylum detected No. of Genera detected No. of Species detected Richness Indices Diversity Indices
CHAO ACE Shannon Simpson
Root- Parent cv. DCP 92-3 17666 28 595 1302 32873.4 38045.2 5.9 0.8
Root- IPCa 2 1268 22 311 426 2538.4 2663.9 2.1 0.6
Root- IPCa 4 22198 29 655 1530 33547.3 38433.7 9.5 1.0
Root- IPCT 3 13609 26 587 1231 28201.1 32088.5 8.6 0.9
Root- IPCT 10 14934 28 622 1365 27206.2 31150.8 9.1 0.9
Root- IPCT 13 17555 29 617 1381 34772.6 40299.1 7.7 0.9
Nodule-Parent cv. DCP 92-3 426 15 192 198 999.4 1174.5 2.2 0.6
Nodule-IPCa 2 359 17 161 149 785.5 932.6 2.5 0.7
Nodule-IPCa 4 320 16 170 145 987.9 896.1 1.4 0.4
Nodule-IPCT 3 623 18 239 260 1185.4 1380.4 2.3 0.7
Nodule-IPCT 10 16456 28 567 1197 30196.5 34727.2 8.7 0.9
Nodule-IPCT 13 449 17 187 185 1179.1 1319.8 2.4 0.7
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The heatmap revealed a significant difference of relative abundance of different Genus across the samples. It showed an obvious decrease in root-nodule colonization of IPCT 10 by Genera such as Shinella, Pseudaminobacter, Burkholderia, Calothrix, Mesorhizobium and Rickettsia compared to rest of the chickpea lines. Comparatively, higher abundance of Genus Saccharopolyspora, Actinocatenispora, Streptomyces, Arthrobacter and Bacillus was reported with root nodules of IPCT 10 (Fig. 2). In contrast, root tissues of IPCa 2 reported with poor colonization with Bacillus and Arthrobacter. It is the single event where the abundance of Microcoleus, Methylobacillus, Thiomonas, Calothrix and Rickettsia was increased in comparison to all other genotypes (Fig. 3). Box-Plot analysis revealed the lower bacterial diversity indices for Chao1, Shannon, and Simpson (p value < 0.05) in root-nodules compared to root tissues (Fig. 4).

Figure 2.

Figure 2

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Heat map depicting root bacterial community structure of parent and transgenic chickpea.

Figure 3.

Figure 3

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Heat map depicting root-nodule bacterial community structure of Non-Bt and Bt-chickpea. Root-nodule endophytic bacterial community structure of IPCT10 is unique and poorly colonized by Mesorhizobium.

Figure 4.

Figure 4

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Box plot showing the differences in alpha diversity indices (Chao1, Shannon, and Simpson) and beta diversity indices (weighed and un-weighed UniFrac as well as Bray-Curtis) of bacterial community associated with plant chickpea tissues. Beta distance was calculated for the data set (a) all within sample sources, (b) all between sources, (c) nodule vs nodule (d) root vs root, (e) nodule vs root.

β-diversity of bacterial community associated with non-Bt and Bt transgenic chickpea

β-distance within the samples is lower compared to the distances between samples. Similarly, β-distance between nodule samples is lower than that of root samples for weighed, unweighed UniFrac as well as Bray-Curtis analysis (Fig. 4). Significance difference in the composition of bacterial community associated with root and nodule samples of non-Bt and Bt-chickpea was demonstrated by Principal Coordinate Analysis (PCoA). First two axes of PCoA plot represented 93.42% of the total variations (Fig. 5). Root and nodule microbiomes of tested samples were clustered into two with few exceptions like 2R (IPCa2) and 5N (IPCT10). Nodule associated bacterial community of IPCT10 is clustered separately from all other nodule samples of Non-Bt and Bt-chickpea (Fig. 5a). Similarly, root bacterial community of IPCa2 clustered away from remaining samples (Fig. 5b). It also indicated that the bacterial community structure of root is highly diverse in nature compared to that of nodule (Fig. 5c). Furthermore, ADONIS differences between bacterial community of root and root-nodule of tested chickpea lines were calculated (Table 4). The p-value of 0.01 indicates that the grouping of samples by individual is statistically significant. The R2 value indicates that approximately 26.8% of the variation in distances is explained by this grouping. High R2 value proved the expected variation among root and nodule samples are significant. Venn diagram depicted the number of common OTUs shared by tested samples. Only 82 OTUs were shared by all root nodule samples while the value was 1268 for root samples. Root microbiome possesses 24972 OTUs as unique while root nodule microbiome possesses 1446 unique bacterial OTUs. Root and nodule microbiome shared 15756 OTUs as common (Fig. 6).

Figure 5.

Figure 5

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Principal Coordinate Analysis (PCoA) plot of samples using the weighted UniFrac distance metric: (a) nodule, (b) root, (c) nodule vs root. Note: Sample ID mentioned as 1N-6N and 1R -6R are as detailed in Table S1.

Table 4.

ADONIS differences between root and nodule samples:.

Df Sums of Sqs Mean Sqs F. Model R2 pr(>F)
qiime.data$map[[opts$category]] 1 0.9952 0.99519 3.6699 0.26846 0.01
Residuals 10 2.7118 0.27118 — 0.73154 —
Total 11 3.707 — — 1 —
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Figure 6.

Figure 6

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Venn diagram of root and nodule associated bacterial community of chickpea.

Discussion

Legumes derive 70% of their nitrogen requirement through SNF and contribute 50–70 million tonnes of nitrogen annually to agricultural ecosystem20,21. Potential of this complex process mainly depends on the host-phenotypic traits including nodule number and its biomass with the heritability exceeding 0.822,23. Bt-transgenic crops have the potential to influence such natural biological processes in their agro-ecosystem owing to a) release of toxic cry-proteins into the soil via root exudates, and through decomposition of crop residues and b) site of Bt-transgene integration in host genome and further alterations in plant metabolism. Hence, symbiotic potential of any transgenics/cultivars of legumes should be ensured before their commercialization for maintaining ecosystem sustainability.

In the present study, integration of Bt-genes (cry1Aabc and cry1Ac) into host genome did not influence the signal transduction between Bt-chickpea and its microsymbiont and thus all Bt-chickpea events initiated nodulation similar to parent cv DCP 92-3. Significant variations observed on nodulation traits of Bt-chickpea events might be due to altered physiology of transgenic plants that further resulted in altered ability of the host to support nodule development during active vegetative stage. Earlier studied reported such reduction in nodule biomass up to 10 to 21% in transgenic RR-soybean without any yield penalty18. A number of QTLs including D1b, A1, C2, O, B1, H, B2, E, J, and I were identified for nodulation traits in soybean and integration of Bt-gene into any one of the or similar to above QTLs/genes involving C-metabolism can hamper SNF in legumes22–26.

Bt-transgenic crops can alter the bacterial community structure in agro-ecosystem including rhizosphere soil. Constitutive expression of some of the transgenic proteins due to cauliflower mosaic virus (CaMV) 35S RNA promoter, may act as toxins towards non-target endophytic bacterial community as well as rhizobacteria27,28. Earlier Prischl et al. showed that members of Alphaproteobacteria, Actinobacteria and Gammaproteobacteria were predominant in Bt-transgenic maize29. The available reports, however, are not consistent regarding the nature of interaction of transgenic crops with the native bacterial community. Cry3Bb and the Cry1Ac toxins persist for 21 and 56 days in soil microcosm and laboratory experiments, respectively30–32 and Bt-toxin is not retrieved from field soils for 3–6 consecutive years of Bt-cotton cultivation33. Hence, instead of assessing the changes in rhizobacterial community, we have analyzed the changes in endophytic bacterial community associated with root and root-nodules where the concentration of available cry-protein and its impact is relatively higher.

Endophytic colonization by bacteria is ubiquitous in nature and plants deprived of endophytes would be more vulnerable to biotic and abiotic stresses34–37. Endophytic bacterial isolates, belonging to Enterobacteria, Pseudomonas, and Bacillus were established in several surrogate hosts and improve their growth and yield38. In addition, they conferred stress tolerance to agricultural crops against drought, flood, heavy metal toxicity, and salinity by improving antioxidant defense mechanisms, maintaining ROS levels, producing ACC deaminase, altering the selectivity of K+, Na+ and Ca2+ and maintaining higher K+/Na+ ratio39. In the present investigation, endophytic bacterial community structure of root and root-nodules of Bt-chickpea were analyzed. Four major phyla detected in all tested Bt-chickpea tissues are Proteobacteria (0.35), Cyanobacteria (0.35), Actinobacteria (0.17), and Firmicutes (0.07). Similarly, Zhang et al. reported a greater relative abundance of Proteobacteria (14% to 68%), Firmicutes (26% to 41%), Actinobacteria (6 to 23%) and Bacteroidetes (1% to 21%) in plants struggling for existence in the extreme environments38.

Diversity and richness indices for bacterial community associated with roots of Bt-chickpea IPCa2 and root nodules of IPCT10 significantly differs from parent as well as other transgenic events. Gram positive bacterial Genera Bacillus and Arthrobacter were selectively eliminated from root colonization of IPCa2, while rests of the Non-Bt/Bt-chickpea events were colonized by the same along with Streptomycetes. Several species of Streptomycetes and Bacillus cereus, B. subtilis, and B. amyloliquefaciens were well-known for their potential on plant growth promotion and biological control of phyto-pathogens. Bacterial isolates belonging to Arthrobacter conferred stress tolerance and promoted plant growth under salt stress40. Bt-chickpea deprived of such beneficial endophytic colonization may suffer under stressed field environment. IPCa2 is the single transgenic event where the abundance of Microcoleus, Methylobacillus, Thiomonas, was increased in root tissues with reference to rest of the events. Methylobacillus of β-Proteobacteria detected only in IPCa2 utilizes methane, methanol and methylated amines41,42 and considered as one of the Earth’s most important carbon recyclers. M. rhizosphaerae was isolated from rhizosphere soil of red pepper (Capsicum annuum L. cv CO 1)43 and their interaction with agriculturally important plant is still to be explored.

Relative abundance of proteobacteria in root-nodules of chickpea ranges between 0.85–0.92 except IPCT10 with 0.42. Mesorhizobium is the most dominant bacteria in root-nodules with relative abundance ranging between 0.74–0.82. However, Bt-chickpea IPCT10 reported very low colonization of Mesorhizobium with 27.05% of total bacterial reads. Unlike other chickpea transgenic genotypes, root nodules of IPCT10 were also colonized by Firmicutes, Actinobacteria and Cloroflexi and thus its bacterial colonization pattern was similar to that of root tissues (Fig. 1). Though there was only slight reduction in the nodule biomass, poor symbiotic efficiency of these nodules were evidenced with significant reduction in nitrogen content of rhizosphere soil and chickpea shoot tissues at later stages (Table 2). The changes in the bacterial community structure of root nodules of IPCT10 may be due to poor symbiotic efficiency and vice versa. Root nodules of IPCT10 were detected with the presence of single species of M. huakuii. Interestingly, M. amorphae was detected only in root-nodules of IPCa2 that contributed 29.76% of its total Mesorhizobium reads. M. septentrionale, M. camelthorni, and M. huakuii are the other species detected in IPCa2.

A sharp decline in the percent reads classified from Genus to species level was observed in all tested samples (Fig. S2a). Large proportion reads of Mesorhizobium and Rickettsia were not classified at further taxonomic level (Fig. S2b), while the reads of remaining predominant bacterial Genera via. Calothrix, Shinella, and Pseudaminobacter were classified at their respective species level. Since the diversity of plant associated Rickettsia and chickpea associated Mesorhizobium in Indian soil is poorly studied44–47, most of the reads belongs to above Genera were not matched with existing species. At the same time, we need to consider the limitations on taxonomic resolution and accuracy of V3-V4 sequences to adequately perform species-level associative studies. In this study, read classification is performed using a high performance version of the RDP Naïve Bayes taxonomic classification algorithm built for most accurate species level classification that showed a genus-level concordance rate of 96% and a species-level concordance rate of 87.5%. Current result indirectly indicated that large diversity of Mesorhizobium in Indian soils is yet to be explored.

Several reports revealed that root-nodules are colonized to certain extend by non-rhizobial endophytic bacteria along with predominant host specific rhizobia. Incredibly diverse population of these endophytic bacteria neither induces root nodulation nor fixes nitrogen48. Metagenomic approach similar to our study revealed that the extent of soybean root-nodule colonization by Bradyrhizobiaceae was only 66% and the remaining bacteria belong to Pseudomonadaceae (19.8%), Enterobacteriaceae (11.8%), and Paenibacillaceae (5.3%) were considered as non-rhizobial endophytic bacteria49. Beneficial effect of such nodule-endophytes including Micromonospora on enhancing symbiotic efficiency without interfering with the host and its nodulating and nitrogen-fixing microbes was established50. Present study revealed an obvious decrease in root-nodule colonization of Bt-chickpea IPCT 10 by Shinella, Pseudaminobacter, Burkholderia, Calothrix, and Mesorhizobium compared to rest of the chickpea lines. Shinella, Burkholderia and Pseudaminobacter were detected only in root-nodule tissues and not found in root tissues of all tested chickpea events. Shinella exhibited a range of functional diversity including nitrogen fixation, belongs to Rhizobiaceae of Alphaproteobacteria and has been isolated from various environmental samples, like root nodules of herbal legume Kummerowia stipulacea, soils, and water51. Pseudaminobacter, a member belongs to Phyllobacteriaceae of α-Proteobacteria, has characteristic ability to utilize alkylamines and thus degrade widely used herbicide Atrazine (2-chloro-4-ethylamino-6-isopropylamino-1,3,5-triazine) in agricultural soils. However, its role on nodule metabolism is still unclear.

Species richness and Shannon diversity index was much higher in IPCT10 (1196, 2.327) than that of parent genotype (197, 0.823) respectively. High Shannon index of root nodules of event IPCT10 is similar to that of root tissues of parent genotype. It indicated that root nodules of transgenic event IPCT10 lost their unique properties, and hence colonized by soil microorganisms in a similar pattern to root tissues. Root and nodule microbiomes of tested samples were formed two separate clusters with few exceptions like 2R (IPCa2) and 5N (IPCT10) during PCoA analysis. Root associated bacterial community of IPCa2 is clustered separately from all other root samples of Non-Bt and Bt-transgenic line of chickpea. Similarly, nodule bacterial community of IPCT10 clustered away from remaining samples. The above analyses clearly indicated that the bacterial community structure of root is highly diverse in nature compared to that of nodule. Similarly, da Silva et al. reported that bacterial community structure of transgenic maize TC1507 tended to separate from those of MON810 and its near-isogenic parent52.

Apart from the impact of transgenic proteins, constitutive expression of neomycin phospho-transferase II (nptII) might also be responsible for changes in endophytic/rhizobacterial community of Bt-crops. Neomycin phospho-transferase II inactivates amino-glycoside antibiotics such as kanamycin and neomycin and thus disturbs the natural regulatory mechanism to maintain particular bacterial community structure in an ecosystem. Moreover, release of such antibiotic genes into in the soil by transgenic crops raised concerns about horizontal gene transfer (HGT) to rhizobacteria. High transfer frequency of plasmids with antibiotic resistance and acquisition of kanamycin resistant genes from transgenic plant DNA to the rhizosphere bacterium Acinetobacter sp. in soil microcosms have confirmed the possibility of bacterial natural transformation53–56. Apart from above environmental risks, reductions of nodule mass and BNF rates in transgenic plants and their long term cultivation in agricultural soil lead to increased scavenging of mineral N, depletion of organic matter reserves and lower the soil fertility especially in sandy soils with limited N availability57. With the above understanding, we emphasize the need of systematic risk assessment strategies for long term monitoring of SNF and soil health before and after releasing the transgenic crops.

Materials and Methods

Geographical location, description of field site and experiments

Confined field experiment to assess the effect of five Bt-transgenic events of chickpea (IPCa2, IPCa4, IPCT3, IPCT10, IPCT13) along with parent cultivar (cv. DCP 92-3) on biological nitrogen fixation and microbiome associated with root and root nodules was laid out under randomized complete block design (RCBD) at Plot No. 5/2, main research farm, ICAR-Indian Institute of Pulses Research, Kanpur, India with Geographical Co-ordinate: 26.49132°N, 80.27282°E. Soils in the experimental field are classified as inceptisol with nitrogen content of 281.9 kg/ha at 15 cm depth and 156.6 kg/ha at 30 cm depth. The basic properties of the soil were 46.98 g/kg organic matter, 0.51 g/kg total nitrogen, 11.73 mg/kg available phosphorus, 220.40 mg/kg available potassium, and 52.81 mg/kg alkali-hydrolyzed nitrogen.

Plant/Soil sampling and analysis

Bt-transgenic lines were developed by employing Agrobacterium tumefaciens EHA105 mediated genetic transformation of chickpea cv DCP92-312. For genetic transformation, the binary vector pBinAR originally derived from pBin1958, harboring either Bt-cry1Aabc or Bt-cry1Ac and neomycin phosphotransferase II (nptII) as the plant selectable marker gene (within T-DNA) was used. Domain shuffled Bt-cry1Aabc gene is expressed in IPCa2 and IPCa4 while plant codon optimized chimeric Bt-cry1Ac is expressed in IPCT3, IPCT10, and IPCT13 under the control of constitutive promoter CaMv35S. Plants were re-confirmed for the presence and expression of transgenes, using gene specific PCR and quantitative ELIZA as described12. The transgenic chickpea lines used in the study exhibited high trait efficacy against gram pod borer. Agronomic performance of the transgenic chickpea lines vis-a-vis control were conducted based on Guidelines for conduct of test for Distinctness, Uniformity and Stability (DUS) prescribed by PPV & FRA, Government of India. Twenty characters specific to chickpea genotype articulated in the Table of Characteristics (Section VII) of the Guidelines are being evaluated and recorded in all the transgenic lines vis-a-vis parental genotype, DCP92-3, at different stages (viz. seedling, pre-flowering, post-flowering and maturity). These characters are anthocyanin colouration, stem height at initiation of first flower, 50% flowering, growth habit, colour of foliage, leaflet size (middle of plant and leaf), leaf pattern, flower: number/peduncle, flower colour, flower: Stripes on standard, peduncle: length, plant height, pod size, number of seeds/pod, seed: colour, seed: Size (100 seed weight), seed shape, seed testa texture, seed ribbing and seed type. No significant differences for the above characteristics including average grain yield/plant were observed in the transgenic lines, as compared to control. Plant samples and associated rhizosphere soil in three replicates were collected at 63, 75, and 96 days after sowing (DAS) and subjected to further analysis along with bulk soil from the same field. Nitrogen content of plant samples as well as soil was determined by Kjeldahl method. The pH of the soil was measured in a soil: water ratio of 1:2.5.

DNA extraction and next generation sequencing (NGS) of v3-v4 of 16S rDNA

Chickpea plants were uprooted from field soil carefully and transported in an ice-bucket to laboratory immediately. All samples were processed within few hours since their collection. Root and root nodules from three independent plants for each parent/transgenic lines were detached and then washed with sterile water followed by vortexed vigorously to remove adhered soil particle and dislodge surface microorganisms. Plant tissues were surface sterilized with 0.01% HgCl2 and 70% ethanol followed by several washings with sterile water to avoid residual effect. Root nodules with specific weight of 100–120 mg were selected and each ~1 g of root and root nodule tissues from parent/transgenic lines were homogenized with CTAB buffer in a Mortar and pestle and used for DNA extraction as described by Murray and Thompson59. Extracted DNA was tested for their quality and quantity through spectrophotometric analysis and stored at −20 °C. DNA from three replicated samples were pooled together and further subjected to the amplification of V3-V4 regions of 16S rDNA using Illuminia 16sRNA sequencing protocol with primer set Forward Primer = 5′ TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG, and Reverse Primer = 5′ GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTATCTAATCC. Paired end read sequencing chemistry with MiSeq platform was performed at Sandor Life Sciences Pvt Ltd, Hyderabad, India and raw reads were submitted to NCBI SRA database under Bioproject Id: PRJNA578245.

Bioinformatics

Paired end raw reads with 301 bp (Illumina MiSeq) were subjected to quality check/data processing by QIIME software60. Sequences with >97% identical are conventionally assumed to be derived from the same bacterial species. Open-reference OTU picking was used for analyzing current data. It starts with alignment to a reference database, and read does not match a known sequence is sent for de novo OTU picking. OTU information generated through OTU picking was utilized to estimate diversity within and between samples. Multiple rarefactions were generated and alpha diversity was measured on the rarefied OTU tables with tools available on QIIME. Heatmaps were drawn by using pheatmap, a package available in R-package61. The heat map depicts the relative abundance of each bacterial genus within each sample. The data is displayed in a grid where each row represents a genera and each column represents a sample. The colour and intensity of the boxes is used to represent relative values (Z-score values) for the bacterial genera. The value Zero in the color scale at the top right corner represents the mean. The value +2 represents two standard deviations above the mean and the value −2 represents two standard deviations below the mean. The green colour represents abundant genera and the blue represents less abundant genera. Principal Coordinate Analysis (PCoA) was carried out to measure of how similar or dissimilar the samples are, and is usually represented by a distance matrix which is then used to do PCoA. The result of this is an ordination plot of multiple dimensions, where each sample is a point and the distance between the points represents the similarity of those samples. The weighted UniFrac metric was used to determine the distance between samples PCoA showed similarity between normalized relative abundance of all samples. The PCoA is generated using Classical MDS on a Pearson covariance distance matrix generated from per-sample normalized classification abundance vectors. It measures differences in the distribution of taxonomic classifications between samples, up to a fixed taxonomic level.

Statistics

Data are expressed as means ± SD. Significance was defined as P < 0.05. Venn diagrams were used to represent shared and unique rare OTUs among different sample groups. ADONIS: non-parametric statistical method that takes a QIIME distance matrix file such as a UniFrac distance matrix, a mapping file, and a category in the mapping files to determine sample grouping. It computes an R2 value (effect size) which shows the percentage of variation explained by the supplied mapping file category, as well as a p-value to determine the statistical significance. The p-value of 0.01 indicates that the grouping of samples by individual is statistically significant.

Supplementary information

Supplementary Table S1 (86.5KB, doc)
Supplementary Table S2 (34KB, doc)
Supplementary Table S3 (60.3KB, xlsx)

Acknowledgements

This research was supported by Indian Council of Agricultural Research-National Agricultural Science Fund (ICAR-NASF Project ID: 7-1503/1616) and ICAR-NPFGGM.

Author contributions

D.A. conducted the field experiment with Bt-chickpea under supervision of N.P.S. Bioinformatic analyses of metagenomic data and statistical analyses were carried out by H.A. DNA extraction and nitrogen analysis were carried out by S.S. Conceptualization, designing experiments, data interpretation and manuscript preparation were done by S.M. D.A. and H.A. were contributed equally. All Authors reviewed the manuscript.

Data availability

Data generated and analyzed during this study are included in this published article

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

is available for this paper at 10.1038/s41598-020-62199-1.

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Associated Data

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Supplementary Materials

Supplementary Table S1 (86.5KB, doc)
Supplementary Table S2 (34KB, doc)
Supplementary Table S3 (60.3KB, xlsx)

Data Availability Statement

Data generated and analyzed during this study are included in this published article

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