[System]
You are a **scientific‐rigor auditor**. You will receive the parsed contents of a research paper. Your job is to identify **only** those errors or flaws that directly undermine the **scientific validity** of the paper’s methods, analyses, or conclusions.

Your sole focus is to identify flaws—such as errors in experimental design, data integrity, calculations, statistical inference, or reproducibility—that directly call into question the validity of a specific claim, paragraph, or the paper as a whole.

**Do not** report issues that are purely presentational, rhetorical, stylistic, or related to citation practices.

---

After you’ve done a **detailed walkthrough** of the paper, output exactly in this format—no extra keys or commentary:

```
<analysis>
{detailed walk‑through of how you checked each section/figure and why you flagged (or did not flag) any flaw}
</analysis>

<response>
{
  "has_error": <true|false>,
  "errors": [
    {
      "location": "Section 2.1",
      "description": "Claim that ‘all X are Y’ is contradicted by citation [5], which shows examples of non‑Y X."
    },
    {
      "location": "Figure 3",
      "description": "XAxis labeled ‘Time (s)’ but units appear to be milliseconds; scale bar mismatches caption."
    }
    // …more entries…
  ]
}
</response>
```

- **Do not** include any other keys or prose outside these two tagged blocks.
- **Do not** report stylistic or citation issues.
- Be as precise as possible about **where** (section ID or figure/table) and **what** the scientific flaw is.
- Each description for the errors must be rooted in a scientific rationale explaining why it is 'wrong' (not how it could be improved).

Begin your analysis now.

[User]
SCIENTIFIC REPORTS

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OPEN | Selective manipulation of the inositol metabolic pathway for induction of salt-tolerance in indica rice variety

Received: 1 August 2018
Accepted: 7 March 2019
Published online: 29 March 2019

Rajeswari Mukherjee¹, Abhishek Mukherjee¹, Subhendu Bandyopadhyay¹, Sritama Mukherjee¹,², Sonali Sengupta¹,³, Sudipta Ray¹,⁴ & Arun Lahiri Majumder¹

Halophytes are rich sources of salt stress tolerance genes which have often been utilized for introduction of salt-tolerance character in salt-sensitive plants. In the present study, we overexpressed PcINO1 and PcIMT1 gene(s), earlier characterized in this laboratory from wild halophytic rice Porteresia coarctata, into IR64 indica rice either singly or in combination and assessed their role in conferring salt-tolerance. Homozygous T₃/T₄ transgenic plants revealed that PcINO1 transformed transgenic rice lines exhibit significantly higher tolerance upto 200 mM or higher salt concentration with negligible compromise in their growth or other physiological parameters compared to the untransformed system grown without stress. The PcIMT1-lines or the double transgenic lines (DC1) having PcINO1 and PcIMT1 introgressed together, were less efficient in such respect. Comparison of inositol and/or pinitol pool in three types of transgenic plants suggests that plants whose inositol production remains uninterrupted under stress by the functional PcINO1 protein, showed normal growth as in the wild-type plants without stress. It is conceivable that inositol itself acts as a stress-ameliorator and/or as a switch for a number of other pathways important for imparting salt-tolerance. Such selective manipulation of the inositol metabolic pathway may be one of the ways to combat salt stress in plants.

Abiotic stress inflicted on the sessile plants implies ~65% loss of yield for crop plants each year¹–³ where salinity stress itself is a major contributor⁴,⁵. Hence, modified value-added crop plants with higher productivity potential under adverse conditions are of utmost importance for agriculture.

Cereals like rice (Oryza sativa L.) are well-known cost-effective source of calories⁶, rice being the staple food for millions of people⁷. Lamentably, there still remains a sizable gap in productivity to cope with escalating World’s population. Although conventional breeding programmes have resulted in development of some salt and drought-tolerant rice varieties and several lines have been released in the Philippines, Bangladesh and India⁸, the success rate of conventional breeding is not ample. Transformation of rice through genetic manipulation thus becomes a better option for stress management.

Studies with eukaryotes demonstrated, that inositol-based cytosolic solutes can function as protective compounds under stressed conditions. Thus, inositol became a critical component in biological systems since its first isolation. Inositols are essential for growth in many yeast, fungi, plants and animals⁹ and its most abundant isoform, myo-inositol, occupies a central position in cellular metabolism¹⁰,¹¹. Depletion of inositol in the fungal, plant or animal system induces cell death termed as “inositol-less death”¹². Inositol and its metabolic intermediates like inositol polyphosphates (InsPs), galactinol, raffinose-family oligosaccharides (RFOs), methylated derivatives like pinitol, cell wall polysaccharides and phosphoinositides also participate in the crucial biological processes such as signal transduction¹³,¹⁴, membrane trafficking¹³, mRNA export¹⁵, stress tolerance¹⁶,¹⁷ and phosphorus storage¹⁸,¹⁹. In addition, the primary breakdown product of inositol, d-glucuronic acid, is utilized in the

¹Division of Plant Biology, Bose Institute, Kolkata, India. ²Department of Botany, Bethune College, Kolkata, India. ³School of Plant Environment and Soil Sciences, Louisiana State University Agricultural Center, Louisiana, USA. ⁴Department of Botany, Centre of Advanced Studies, University of Calcutta, Kolkata, India. Subhendu Bandyopadhyay and Sritama Mukherjee contributed equally. Correspondence and requests for materials should be addressed to A.L.M. (email: lahiri@jcbose.ac.in)

SCIENTIFIC REPORTS | (2019) 9:5358 | https://doi.org/10.1038/s41598-019-41809-7

synthesis of various cell wall pectic and non-cellulosic compounds and ascorbic acid^10,20,21. Methylated derivatives of inositol have been found to be effective in stalking ROS and thereby protecting photosynthetic machinery^22.

A number of metabolic pathways have earlier been manipulated for production of essential metabolites along with overexpression of regulatory genes to confer salt-tolerance to different plants^23. In the present work, we attempted manipulation of the inositol metabolism which involves a major biochemical network in transgenic rice lines by overexpressing two genes from Porteresia coarctata viz. the salt-tolerant myo-inositol phosphate synthase (MIPS) coding gene (PcINO1)^24 producing inositol and the inositol methyl transferase gene (PcIMT1)^17 producing pinitol in planta. All the transgenics were studied in terms of their growth, development and other characteristics under salinity stress.

Construction of expression vectors with PcINO1 and PcIMT1 genes and generation of salt-tolerant transgenic rice lines. Two candidate genes viz. PcINO1 and PcIMT1, earlier isolated from Porteresia coarctata^17,24 were cloned into pCAMBIA1301 (Fig. 1a) under CAMV35S promoter to generate pCAMBIA1301-PcINO1/OsINO1 (Fig. 1b) and pCAMBIA1301-PcIMT1 (Fig. 1c) construct. A single pCAMBIA1301 construct (termed DC1) was also generated where both PcIMT1 and PcINO1 genes were put together under individual CAMV35S promoters (Fig. 1d).

~20 days old embryogenic calli were transformed by adopting a modified Agrobacterium-mediated rice transformation protocol (Supplementary Fig. S4) following previously reported methods^25,26. Among the T₀ putative transgenics (Supplementary Fig. S5g–m) hptII gene specific PCR positive plants were selected and advanced to next generation. Homozygous T₂ lines showing the presence of hptII gene at 1 kb, PcINO1 gene at 1.5 kb and PcIMT1 gene at 1.1 kb region respectively (Supplementary Fig. S5g–m) were selected for Southern blot analysis of plants from PcINO1-lines (110 plants), PcIMT1-lines (153 plants) and (PcINO1 + PcIMT1) i.e DC1 (98 plants) lines. PcINO1 gene probe highlighted two copies of endogenous INO1 genes in all plants. Southern positive T₃ PcINO1-plants exhibiting additional single-copy integration in another locus with specific INO1 probe (Supplementary Fig. S6a–d) were used for segregation analysis (Supplementary Tables S4a–S6a). All the single copied transgenic plants (35 PcINO1-lines, 50 PcIMT1-lines, and 25 DC1-lines) were chosen for further analysis.

Test of allergenicity for candidate protein(s). Rice being an edible crop, before introducing any external gene(s) into rice genome, cross testing for allergenicity of the protein products of the candidate gene(s) was thought to be prudent. Protein sequences of PcIMT1 and PcINO1 were analyzed through AllergenOnline Database v15 (January 12, 2015). Query sequence of PcIMT1 protein exhibited 110 amino acids match with an allergen Solenopsis invicta of 346 amino acids (protein ID: gi 51093373) and the second match was of 137 amino acids with an allergen Cupressus sempervire of 367 amino acids (Protein ID: gi 8101715). Both alignments of PcIMT1 with two allergens indicate a match of only 25.5% (E-value-0.14; Supplementary Fig. S1) and 24.8% (E-value-0.78; Supplementary Fig. S2) respectively, values indicative of non-allergenicity of the protein. The query sequence of PcINO1 protein exhibited no allergenicity when searched throughout the same database.

Identification of embryogenic stage in IR-64 calli through SEM imaging. Prior to transformation, SEM study were conducted taking ~10 days, ~20 days and ~30 days old IR-64 calli for identification of proper embryogenic state. Texture of ~10 days old calli (Supplementary Fig. S3a–e) was very tight, mostly without prominent groove, with no specific structure/shape (Supplementary Fig. S3d). The creamish ~20 days old calli were with prominent heart, torpedo and globular shaped embryos along with protrusions of non-uniform shape and size (Supplementary Fig. S3f–m) and were thought to be ideal for effective transformation. ~30 days old calli (Supplementary Fig. S3n–p) showed numerous trichomes with dead tissues and with no heart/globular/torpedo shaped embryogenic structures.

Analysis of homozygous transgenic lines. T₃ plants were grown under salt-stress of different concentrations (0 mM, 100 mM, 200 mM and 300 mM) for 7 days. Three best performing lines from each type of transgenic systems [7PcINO1, 4PcINO1 and 3PcINO1-lines (Fig. 1e); 25PcIMT1, 10PcIMT1 and 1APcIMT1-lines (Fig. 1f); 6DC1, 5DC1, 4DC1-lines (Fig. 1g)] were selected for checking stress sustenance. Selected lines remained healthy and exhibited unfolding of new leaves under (200 mM–300 mM) salt-stress even after 7 days while rest of the lines showed noticeable dechlorophyllisation under 300 mM stress

Transcript analysis of selected nine lines after 7 days of stress under different NaCl-concentrations (0 mM, 100 mM, 200 mM, 300 mM) shows the INO1 transcript in the untransformed IR-64 and all three PcINO1-transgenic lines (Fig. 2a). 37-amino acid specific PcINO1-transcript^24, specific to PcINO1 gene was present in varying proportion in PcINO1-transgenic lines while being absent in the untransformed lines (Fig. 2b). PcIMT1-transcripts were found to vary its level with increase in salt concentration in PcIMT1-transgenic lines (Fig. 2d). The 6DC1 line exhibited highest level expression of PcIMT1-transcript at 300mM salt in comparison to the other two DC1-lines (Fig. 2h).

Comparative shoot-length, root-length and fresh wt. taken after 10 days-stress indicated 7PcINO1-line, 10PcIMT1-line and 6DC1-line as the best in terms of growth parameters (Fig. 3a–c). Root growth under 200 mM/300 mM salt concentration was maximum in 7PcINO1-line, 10PcIMT1-line and 6DC1-line in comparison to other respective lines (Fig. 3d–f). Analysis through DIRT imaging software revealed generation of more lateral and adventitious roots, indicative of better stress tolerance (Fig. 3d–f and Supplementary Table S3). These three plant lines recovered best after 15 days of stress withdrawal considering growth and survivability (Fig. 4a–h). Even after 300 mM salt stress for 10 days, 7PcINO1-line, 10PcIMT1-line and 6DC1-line fully recovered their normal physiological activity. Chlorophyll estimation after 15 days of salt withdrawal prominently indicated recovery of chlorophyll content in all transgenic lines while untransformed IR-64 exhibited remarkable decline

Figure 1. Representative pictures explaining vector-designs for plant transformation and physiological response of selected transgenic lines under different NaCl concentrations kept for 7 days. (a) pCAMBIA1301 vector with no candidate gene at MCS site. (b) pCAMBIA1301-PcINO1/OsINO1 construct containing PcINO1/OsINO1 gene. (c) pCAMBIA1301-PcIMT1 construct containing PcIMT1 gene in replacement of gusA gene. (d) pCAMBIA-PcIMT1 + PcINO1 Double Construct (DC1) containing both PcIMT1 and PcINO1 genes, each under individual CAMV35S promoters. (e–g) Respectively represents PcINO1, PcIMT1, and DC1 (PcINO1 + PcIMT1) gene-transformed transgenic lines.

Selected T₄ plant lines from each type of transgenic systems viz. 7PcINO1, 10PcIMT1 and 6DC1 were subjected to 12 hrs salt stress (0 mM & 200 mM) to compare the transcript with their corresponding protein level expression for each transgene. Figure 5a–h represented all transcripts in individual gel slots. In Fig. 5a, accumulated INO1 transcript of OsINO1/PcINO1 was detected in all plants along with IR-64 untransformed line. In comparison to the untransformed control line, 7PcINO1-line recorded a ~2.61 fold increase in the INO1 transcript under stress as against ~0.5 fold in 10PcIMT1 line and 0.67 fold in 6DC1 line under similar conditions (Fig. 5a,b). PcINO1 specific 37-amino acid gene transcript level expression was maximum in 7PcINO1-lines (~10-fold higher than in 0 mM) over 6DC1 line (~5-fold higher than in 0 mM) (Fig. 5d) while it was absent in 10PcIMT1-line. In case of PcIMT1-transcript an increase of ~1.3- to ~1.4-fold for both 10PcIMT1 and 6DC1-line has been found (Fig. 5f).

Western blot analysis revealed that under stress PcINO1 protein was maximally expressed in 7PcINO1-line compared to the IR-64 or the 10PcIMT1 or the 6DC1 lines (5i,j). Accumulation of PcIMT1 protein was detected in both PcIMT1/DC1-lines, albeit, not detectable in untransformed IR-64 or the PcINO1-lines (5k,l).

Figure 3. Comparative phenotypic study for shoot-length, root-length and fresh-weight of transgenics with untransformed lines under variable NaCl stresses kept for 7 days, followed by response of roots in transgenic lines. Bar diagrams exhibiting variation in phenotypic responses in three of each (a) PcINO1; (b) PcIMT1 and (c) DC1 (PcINO1 + PcIMT1) transgenic lines under variable salt-stresses. Data represented average of three plants ± SD (P ≤ 0.05). (d–f) Representative root-responses of selected PcINO1, PcIMT1 and DC1 (PcINO1 + PcIMT1) transgenic lines under stressed and unstressed condition.

and estimation of the metabolite products of expressed transgene(s) viz. inositol and pinitol through GC-MS analysis (Fig. 5m) validated the transcript and the western blot data obtained. The metabolite accumulation was found to be in line with the trend of transcript and protein expression. Decrease in inositol content was

observed under salt stress in almost similar manner in untransformed IR-64 and 10PcIMT1-lines whereas 6DC1 (PcINO1 + PcIMT1) plants exhibited almost no change in inositol pool under salt-stress compared to no-salt condition. However, 7PcINO1-lines maintained an increasing trend of inositol production even under salt-stress.

Figure 4. Comparative physiological response in terms of stress recovery and capacity of chlorophyll retention in transgenics and untransformed lines after withdrawal of differential NaCl stresses. (a) Untransformed plants under stress for 10 days and (b) after recovery of 15 days from stress. (c) 10PcIMT1 plants under stress for 10 days and (d) after recovery of 15 days from stress. (e) 7PcINO1 plants under stress for 10 days and (f) after recovery of 15 days from stress. (g) 6DC1 plants under stress for 10 days and (h) after recovery of 15 days of from stress. (i, j) Chlorophyll retention capacity of transgenic plants along with untransformed IR-64 lines under different salt stresses. Data represented the average of three plants ± SD (P ≤ 0.05).

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Gel electrophoresis images showing band patterns for different gene expressions

(b)
Bar graph: Transcript level expression of INO1 gene

(d)
Bar graph: Transcript level expression of PcINO1 gene-specific 37 amino acid transcript

(f)
Bar graph: Transcript level expression of PcIMT1 gene

(h)
Bar graph: Transcript level expression of Actin gene

(i)
Western blot image showing protein expression patterns

(k)
Western blot image showing protein expression patterns

(j)
Bar graph: Relative expression of PcINO1 protein

(l)
Bar graph: Relative expression of PcIMT1 protein

(m)

|                     | Inositol (μmole/gm of tissue) | Pinitol (μmole/gm of tissue) |
|---------------------|-------------------------------|------------------------------|
| IR64 0mM            | 10                            | 0                            |
| IR64 200mM          | 8                             | 0                            |
| 7PcINO1 0mM         | 55                            | 0                            |
| 7PcINO1 200mM       | 68                            | 0                            |
| 10PcIMT1 0mM        | 15                            | 72                           |
| 10PcIMT1 200mM      | 8                             | 82                           |
| 6DC1 0mM            | 38                            | 88                           |
| 6DC1 200mM          | 38                            | 93                           |

Figure 5. Transcript and Western blot analysis followed by estimation of metabolites in three transgenic lines kept under 0mM & 200mM NaCl stresses for 12 hrs. (a,b) RT-PCR exhibiting differential expression of endogenous PcINO1 full-length transcript (1.5 kb) in transgenics and untransformed lines. (c,d) Exhibiting varying expression of 37-amino acid specific PcINO1 gene-transcript (111 bp) in 7PcINO1 & 6DC1-transgenic lines. No expression found in 10PcIMT1 and untransformed line. (e,f) Exhibiting varying PcIMT1 gene-transcript (1.1 kb) expression in 10PcIMT1 & 6DC1 transgenics. (g,h) Exhibiting full length Actin gene transcript (500 bp) in all lines as endogenous control. Data represented as average of three replica sets ± SD (P ≤ 0.05). (i) Representative Western Blot charged with PcINO1 (62 kD) antibody; Lane 1: Bacterial protein as positive control; Lane 2: untransformed IR-64 in 0mM salt stress, Lane 3: untransformed IR-64 in 200mM; Lane 4: 7PcINO1 transgenic in 0mM salt stress; Lane 5: 7PcINO1 200mM salt stress; Lane 6: 10PcIMT1 transgenic in 0mM salt stress; Lane 7: 10PcIMT1 transgenic in 200mM salt stress; Lane 8: 6DC1 transgenic in 0mM salt stress; Lane 9: 6DC1 transgenic in 200mM salt stress. (j) Graphical representation of PcINO1

SCIENTIFIC REPORTS | (2019) 9:5358 | https://doi.org/10.1038/s41598-019-41809-7

Content courtesy of Springer Nature, terms of use apply. Rights reserved.

protein in different transgenic lines considering, expression at 0 mM salt as 100%. (k) Blot charged with IMT1 (42 kD) antibody; Lane 1: Bacterial protein as positive control; Lane 2: untransformed IR-64 lines in 0 mM salt stress; Lane 3: 7PcINO1 transgenic in 0 mM salt stress; Lane 4: 10PcIMT1 transgenic in 0 mM salt stress; Lane 5: 10PcIMT1 transgenic in 200 mM salt stress; Lane 6: 6DC1 transgenic in 0 mM salt stress, Lane 7: 6DC1 transgenic in 200 mM salt stress. Prestained (10–180) kD protein ladder markers were used in both the gels. (l) Graphical representation of PcIMT1 protein in different transgenic lines, considering expression at 0 mM salt as 100%. Data represented average of three replica sets ± SD (P ≤ 0.05). (m) Graphical representation of comparative estimation of metabolites in transgenics through GCMS from different transgenic plants in absence (0 mM) and presence (200 mM) of salt stress for 12 hrs. Data represented average of three replica sets ± SD (P ≤ 0.05).

Pinitol, detected only in 10PcIMT1 and 6DC1-lines, was found to increase in 10PcIMT1-line, whereas 6DC1-line showed similar increase under 200 mM salt-stress compared to no-salt condition (Fig. 5m).

## Detection and study of photosynthetic ability of the transgenic plants.

7PcINO1/10PcIMT1/6DC1-transgenic lines along with untransformed line were kept under 0 mM and 200 mM NaCl-stress for 12 hrs to check for any change in their photosynthetic-capacity. Figure 6a,b represent no blockage in photo-centre during photosynthesis for untransformed IR-64 under no-salt condition while 7PcINO1, 10PcIMT1 and 6DC1-line recorded insignificant blockage. After 12 hrs of 200 mM salt-stress, IR-64 plant exhibited considerable blockage, while rest of the transgenic systems showed negligible blockage at the photo-centre (Fig. 6c,d). Further analysis showed almost unaffected photosynthetic functions in terms of Fv/Fm ratio for each set (Fig. 6e) and the absolute photosynthetic values (PIabs) as plotted in Fig. 6f. PIabs values for the transgenic systems were higher than the untransformed system.

## Agronomic characters of the transgenic plant lines.

T₃ transgenic plants from 7PcINO1, 10PcIMT1 and 6DC1 lines along with untransformed IR-64 at maturity were self-pollinated. After seed setting and maturation of the panicle, agronomic characters like grain wt., number of panicles and number of seeds per panicle were determined (Fig. 6g). Under normal condition, all these transgenic plants were able to produce matured seeds (Fig. 7a) and could maintain normal growth. Grain quality from transgenic plants, especially, of the 7PcINO1-line, as analyzed with SMART-GRAIN software was comparable or marginally better in length and width than the untransformed IR-64 control line (Fig. 7b–e).

## Generation of a potent transgenic IR-64 rice line over-expressing endogenous OsINO1 gene.

To compare in planta activity of PcINO1 gene in PcINO1-transgenic rice lines in comparison with the overexpression of OsINO1 gene, parallel attempts were made to develop IR-64 rice lines overexpressing endogenous OsINO1 gene. 22 PCR positive plants were selected out of 5 transformation events (Supplementary Fig. S7a,b). Three T₃ homozygous OsINO1-transgenic lines were selected through Southern blot analysis (Supplementary Fig. S7c). The germination percentage of the PcINO1/OsINO1 introgressed and control seeds under increasing NaCl concentrations was monitored in different independent transgenic lines (Supplementary Fig. S7d). Increase in NaCl concentration caused pronounced germination inhibition in control and OsINO1 transformed plants whilst PcINO1 transformed plants showed, albeit, less vigorous germination up to 400 mM NaCl at least for 10 days (Supplementary Fig. S7e). Growth parameters like shoot and root length (data taken after 15 days of salt stress) were also found to be affected negatively in the presence of higher concentration of salt in control and OsINO1 plants whereas most of the 7PcINO1-plants showed better performance (Supplementary Fig. S7f,g). Photosynthetic performance parameters like chlorophyll-a fluorescence of control plants and PcINO1/OsINO1-plants under saline environment, showed that PcINO1-plants are much better adapted to saline environment than the untransformed control and OsINO1-plants. These results indicate a substantial protection of photosystems, especially, PSII in PcINO1-transgenic plants (Supplementary Fig. S7h,i).

## Comparative Transcriptome analysis by cDNA microarray.

To evaluate transactivation capacity of inositol overexpression in rice under stress, comparative transcriptome of inositol-overexpressor lines were attempted through a strategy outlined in Fig. 8a. Although inositol overproduction may elevate osmoprotectant status of the plant there are several other pathways that may participate in the process either as indirect response or as causality. A total of 1252 and 1420 transcripts were up and down-regulated respectively in OsINO1-transformed plants in salt compared to control condition. A total of 1493 and 1403 transcripts were up and down-regulated in PcINO1-transformed plants in salt. However, when differential transcripts from PcINO1-transformed plants were compared with OsINO1-transformed plants in salt, the total numbers of up-regulated transcripts rise to 3183 and down-regulated transcripts were 1607 in number (Fig. 8b). Interestingly, the Venn diagram for overlapping categories shows that on overexpression of PcINO1, salt up-regulates at least 1756 unique transcripts and down-regulates no less than 1093 unique transcripts compared to OsINO1 overexpressor in salt (Fig. 8b). We analyzed the GO terms associated with up-regulated and down-regulated transcripts and enriched the significant terms using the rice genome as reference. The up-regulated genes were assigned to specific pathways according to KEGG database. 94 common pathways are up-regulated in all 3 comparative sets, whereas 71 pathways were uniquely enriched in PcINO1-transgenics in salt (Fig. 8c).

Enrichment of GO terms and KEGG pathways are shown in comparative profile of the transgenics (Fig. 8d–i). The major up-regulated KEGG pathways in PcINO1- transgenics compared to OsINO1-transgenics belong to metabolic pathways, biosynthesis of secondary metabolites, and photosynthetic carbon-fixation. The up-regulated GO terms in PcINO1-lines are majorly constituted by catalytic processes/enzymatic reactions; which signifies the

Figure 6. Representative pictures showing light entrapping capacity of transgenics and untransformed IR-64 lines during photosynthesis under salt stresses (0 & 200 mM NaCl) kept for 12 hrs. Agronomic characters in transgenic and untransformed lines have been studied. (a, b) Specific (membrane) model displaying specific fluxes per PSII reaction centre under 0 mM NaCl stress in untransformed and transgenic plants. [Yellow pentagon, absorption maxima per reaction center; Green pentagon, specific flux for trapping per reaction center and red pipe, specific flux for dissipation per reaction center]. (c, d) Phenomenological yield models per excited cross-section under 200 mM NaCl stress in untransformed and transgenic plants [Yellow triangle, absorption maxima per excited cross-section (ABS/CSm); blue pipe, electron transport rate per excited cross-section (ET0/CSm); green triangle, trapped energy per excited cross-section (TR0/CSm); red block, dissipation maxima per excited cross-section (DI0/CSm); empty circles, active reaction centers; filled circles, inactive reaction centers.] (e) Photosynthetic efficiency (in terms of maximum quantum yield of photosystem-II; Fv/Fm) measurement (f) Over all photosynthetic performance index, PI[abs] measurement in untransformed and transgenic plants under 0 and 200 mM NaCl. (g) Comparative study of agronomic characters (grain weight, no. of panicles & no. of seeds) for untransformed and transgenic plants under normal growth conditions. Data represented the average of three plants ± SD (P ≤ 0.05).

presence of salt-resistant or salt-responsive enzymatic processes in PcINO1-transgenic lines which are coordinately expressed.

An analysis of the pathways for inositol utilization (Supplementary Fig. S8) would reveal the number of pathways emanating from inositol which are intimately connected to stress responses in plants. These include the methylation by IMT1 function to generate pinitol and other methylated inositols²⁸⁻³⁰, generation of RFOs like galactinol and the raffinose series of oligosaccharides through GolS³¹'³², cell-wall polysaccharides through the MIOX³³'³⁴ and the phosphoinositides³⁵. Interestingly, all these metabolic events originate from a single evolutionarily conserved pathway namely the L-myo-inositol 1-phosphate synthase (MIPS) reaction, resulting in accumulation of inositol for conversion to other metabolites of interest³¹. Hence, generation of inositol through the MIPS reaction is of vital importance to the successful operation of the entire inositol metabolic cycle. In contrast to the other pathways for synthesis of osmoprotectants²³ such as glycine-betaine, proline, trehalose etc, which are products of specialized extension of specific pathways, synthesis of inositol is carried out by an evolutionarily conserved single enzyme³⁶⁻³⁸. Under salt-environment, however, this pathway in most glycophytes is known to record decreased MIPS activity, thus affecting the channelization of inositol flow throughout the inositol metabolic cycle.

Since halophytic plants are known to be good source of genes and promoters of salt-tolerance³⁹, our attention was initially drawn on the wild halophytic rice, Porteresia coarctata, wherein we looked for either increased or tolerant MIPS activity under salt-environment⁴⁰'⁴¹. The subsequent discovery of an unique salt-tolerant MIPS coding PcINO1 gene²⁴, elucidation of the mechanism of its salt-tolerance property¹¹ and demonstration of its capability to confer salt-tolerance to varied pro- and eukaryotic organisms including higher plants⁴², opened up the possibility of raising salt-tolerant crop plants by transgenic introgression of the PcINO1 gene. Further, the co-introgression of PcINO1 and McIMT1, from Mesembryanthemum crystallinum⁴³'⁴⁴, enabled achieving a salt-tolerant phenotype in transgenic tobacco²². Such observations validated that likewise, the PcINO1 and PcIMT1 gene, isolated from Porteresia coarctata¹⁷'²⁴, may improve salt tolerance in a crop genetic background. Based on such proof of concept, an attempt has been made to generate salt-tolerant indica rice plants through transgenic functional co-introgression of both PcINO1 and PcIMT1.

Seven different types of calli are generally induced from mature rice seeds⁴⁵, differing in morphological characteristics and potential for plant regeneration⁴⁶. Hence, identification of proper explants i.e. rice calli at exact embryogenic stage is required to improve rice transformation efficiency⁴⁷. In the present study, SEM analysis revealed maximum number of heart and/globular shaped embryos were observed in 20–21 days old tightly bound IR-64 calli (Supplementary Fig. S3) which served as the basic explants for plant transformation experiments.

Following identification of the MIPS proteins as non-allergenic (Supplementary Figs S1 and S2), plant expression cassettes were designed for PcIMT1, PcINO1 and (PcIMT1 + PcINO1) gene(s) under CAMV35S promoter for rice transformation to generate single copy transgene integrated T₂ lines as judged by Southern blot analysis (Supplementary Fig. S6). Three Southern positive transgenic lines from each type were finally selected based on their performance under salt-environment (Fig. 1e–g) as well as their transcript analysis of the respective gene(s) (Fig. 2). Expression of different gene(s) transcripts (Fig. 5b,d,f,h) matched well with corresponding protein

accumulation in immunoblots (Fig. 5j,l) and the metabolites such as inositol and pinitol in respective samples (Fig. 5m). These data confirm functional expression of the gene(s) and their protein(s) exhibiting corresponding enzymatic activities in the transgenic system suggesting a direct correlation among them. Site specificity of the transgene integration may attribute to the prominent increase in CaMV35S promoter mediated PcINO1 transcription.

Being the first organ to sense stress insult, root growth and architecture are good indicators for stress perception⁴⁸. Three lines viz. 7PcINO1, 10PcIMT1 and 6DC1 exhibited better root growth than the other lines under 300 mM NaCl stress. After 10 days of salt-stress, greater number of adventitious roots was observed to develop when analyzed through DIRT imaging software (Supplementary Table S3). Sorghum plants are known to develop adventitious roots capable of accumulation of sodium and chloride ions under stress with enhanced adventitious root imparting salt tolerance⁴⁹. Stimulation of the lateral root formation in Arabidopsis thaliana under drought stress and increased growth of roots in depth was found in rice⁵⁰⁻⁵². In our experiment, transgenics imparting better tolerance under salt stress were found to have longer primary tap root system growing deeper under the ground. They also exhibited positive geotropism under stress contrary to the earlier reports of negative geotropism⁵³,⁵⁴. While high NaCl levels inhibit lateral root formation, lower NaCl levels are known to stimulate lateral root formation in an auxin-dependent manner⁵¹,⁵⁵. Our results show that there was no remarkable decrease in number of lateral roots under salt stress despite reports of conflicting results⁴⁸,⁵¹,⁵⁶. In our experiment, transgenics (T₃) showed better average root density than the untransformed control (Fig. 3d–f). Selected transgenic lines (7PcINO1, 10PcIMT1, 6DC1) recovered from stress impact to normal growth by maintaining their physiological activity (Fig. 4a–h).

Stress generates enormous reactive oxygen species (ROS) having a negative impact on photosynthetic machinery and the total chlorophyll content of a plant⁵⁷. Chlorophyll reduction under abiotic stress symbolizes osmotic/oxidative stress, which may result from pigment photo-oxidation and chlorophyll degradation⁵⁸,⁵⁹. However, ectopic expression of various genes (viz. Annexin, VTE1 and mtlD) helps in retention of greater chlorophyll content under dehydration stress⁶⁰. Since photosynthesis is affected by leaf chlorophyll content⁶¹, chlorophyll retention capacity under salt stress was checked quantitatively. Transgenic 7PcINO1-plants retained the chlorophyll content thus maintaining normal photosynthetic potential even under high salt concentration (Fig. 4i) while untransformed line showed maximum chlorophyll depletion.

Salinity affects plant growth by inducing changes in photosynthesis⁶² indicating that prompt reaction of photosynthetic machinery is a key factor for combating such stress effects⁶³,⁶⁴. Transgenic plants under 200 mM NaCl stress showed less number of closed photoreaction centre and higher Fv/Fm value than that of untransformed IR-64 plants indicating better photosynthetic capability, 7PcINO1-line being the best identified line (Fig. 6e,f).

Agronomic characters of transgenics in T₄ generation and above were studied along with untransformed IR-64 line under green house conditions (Fig. 6g). Numbers of panicles with matured grains in T₄ transgenics (Fig. 6g) were compromised to a smaller extent in case of PcIMT1-line and DC1-transgenic lines when compared with PcINO1-transgenic lines, keeping all other agronomic characters intact with better salt-tolerance. This fact is indicative of induced conversion of inositol pool to pinitol. Agronomic data were taken in every generation from T₂ to T₅, confirming viability of the seeds in each generation as assessed by their germination potential (Supplementary Tables S4b–S6b).

Transcriptome analysis of PcINO1-transgenics through microarray presented in Fig. 8 show that 94 pathways up-regulated in all three sets are the pathways that are generally induced in presence of salt. Among them, the 71 unique pathways in PcINO1-transgenics are possibly the ones that were up-regulated due to increased inositol production affecting the salinity tolerance achieved.

Nine genes (Supplementary Table S9) up-regulated in all comparative sets are rather unrelated and less characterized. However, their broad participation in about 94 pathways indicates their widespread regulatory or signaling role in general stress-response. We pulled the previously reported expression data of these 9 genes from Genevisible, an expression search engine powered by Genevestigator. Functionality and localization of these 9 genes have been described in Supplementary Table S7 while the Genevisible expression hits are given. All 9 genes may be related to common signaling in response to stress.

In conclusion, the three types of single copied homozygous salt tolerant transgenic IR-64 rice lines with PcINO1, PcIMT1 and a combination of the two, with identified site of integration exhibiting salt tolerance without perceptible growth compromise, is indicative of the potential for manipulation of the inositol metabolic pathway. Although a number of metabolic pathways are influenced by overexpression of inositol production in the PcINO1-transgenics, not all inositol downstream processes are highly enriched, suggesting that changes in signaling and transcription may also bring the phenotypic superiority. Indeed, after catalytic activity, nucleotide binding and oxidoreductase activities are the most enriched, which suggests possibility of transactivation and signaling roles of inositol overproduction and subsequent reactions that follow leading to salt-tolerance as in the transgenic plants described here.

Allergenicity Test. Online database AllergenOnline Database v15 (January 12, 2015) (http://AllergenOnline.com/) where less than 50% identity with allergenic proteins predicts non-allergenicity⁶⁵, had been used to check the allergenicity of PcIMT1 and PcINO1 proteins.

SEM Analysis. 10, 20 and 30 days old IR-64 calli, obtained from Chinsurah Rice Research Station, West Bengal were transferred separately to a fixative solution (2% glutaraldehyde and 2% paraformaldehyde in 0.1 M cacodylate buffer, pH 7.2) and 3% sucrose, and fixed for 24 h⁶⁶. Fixed tissues were rinsed twice in 0.1 M cacodylate buffer (pH 7.2), dehydrated in graded ethanol series between 30–100% (10 min each), critical point-dried in an AUTOSAMDRI®-815 Series, and were put on metal stubs with gold–palladium ions in a Denton Desk V vacuum

Construction of plant transformation vectors.  pCAMBIA1301 vector with PcINO1/OsINO1 gene.  PcINO1 gene (Accession No: AF412340; 1500 bp; coding myo-inositol phosphate synthase) from Porteresia coarctata^24, collected from Sundarban area of West Bengal and OsINO1 gene from IR-64 rice was restriction digested to generate XbaI-KpnI fragment and cloned in pCAMBIA1301 vector (Fig. 1a) at XbaI/KpnI site of its MCS under CAMV35S promoter (HindIII/BamHI) to generate pCAMBIA1301-Pc/OsINO1 (Fig. 1b).

pCAMBIA1301 vector with PcIMT1 gene.  PcIMT1 gene (Accession No: EU240449; 1100 bp; coding inositol methyl transferase) from Porteresia coarctata^17 was re-amplified with ALM-262 & ALM-263 primers (Supplementary Table S2) to generate NcoI(5’)-PmlI(3’) flanking ends. Replacement of gusA gene at NcoI/PmlI site in pCAMBIA1301 vector with PcIMT1 gene generated the pCAMBIA1301-PcIMT1 vector (Fig. 1c) for plant transformation.

pCAMBIA1301 vector with PcIMT1 gene and PcINO1 gene.  In pCAMBIA1301-PcIMT1 vector, PcINO1/OsINO1 gene (1.5 kb) along with CAMV35S promoter (0.8 kb) and nos terminator (0.3 kb) altogether were ligated at its MCS. The resulting vector pCAMBIA1301-PcIMT1 + PcINO1 (DC1) contained both PcIMT1 and PcINO1 gene (Fig. 1d). All the constructs (Fig. 1b–d) were verified through sequence analysis and mobilized in Agrobacterium LBA4404 strain by freeze-thaw method^67.

Empty vector of pCAMBIA1301 has also been used for rice transformation followed by consecutive molecular analysis. The empty-vector transformed plants behaved exactly the same like that of the untransformed IR-64 control lines under stress. Hence, we presented untransformed IR-64 lines as the control for all the following experimentation.

Standardization of rice transformation protocol.  20 days old calli from Elite indica rice cultivar IR-64, obtained from Chinsurah Rice Research Station, West Bengal were taken for every transformation experiment. Modified steps of rice transformation protocol^68 adopted for the study is described in a flow-chart (Supplementary Fig. S4). MS^69 was used as basic nutrient medium for plant tissue culture. For callus induction 2,4-D (2.5 mg/L) supplementation was applied to the scutellar tissue, incubated in dark for 9 days at 28 ± 1 °C. For regeneration, NAA and BAP were used at 1:5 ratios respectively under 16 hrs/8 hrs photoperiod.

PCR screening of putative transformants.  Genomic DNA from fresh leaves of putative transgenic and untransformed plant lines were isolated by following CTAB method^70. PCR for presence of hptII/PcIMT1/PcINO1 gene in putative transformants were carried out with gene-specific primers ALM-68 & ALM-69, ALM-262 & ALM-263 and ALM-38 & ALM-39 respectively (Supplementary Table S2). PCR reactions were performed in BioRad PCR system using 0.625U of Taq DNA polymerase from Roche Molecular Biochemicals.

Southern analysis of transformed rice lines.  About 10 µg of genomic DNA was isolated from young fresh leaves of putative T2 transformants along with untransformed rice leaves, digested with HindIII restriction enzyme and subsequently separated on 0.8% agarose gel (USB). DNA fragments from agarose gel were transferred onto Hybond-N+ nylon membrane (Amersham Pharmacia Biotech) using vacuum blotter (Bio-Rad). The blot was soaked in 6XSSC, air dried and cross linked using UV-crosslinker (Amersham Biosciences).

~300 bp PCR product from PcIMT1 gene, amplified by primers, ALM350 and ALM351 was radiolabelled with α-[32P]-dCTP to use as probe. Likewise, 600 bp DNA fragment of PcINO1 part-gene digested with BamHI and 1000 bp DNA fragment containing hptII full-length gene from plasmid pCAMBIA1301-PcINO1 digested with XhoI were radiolabelled to use as probe. Prime labeling system of Thermo Scientific has been used for radiolabelling the DNA. Southern experiment had been carried out as per the standard protocol^71.

Physiological assay of transformants against salt stress.  Germinated plantlets (with proper rooting) of 3 weeks were placed in ½ MS medium containing different salt (NaCl) concentrations (0 mM, 100 mM, 200 mM, 300 mM) for 7 days. Experiment was repeated with best responsive nine independent transgenic lines (three from each type) in replicates to determine their root-behavior, shoot-length, root-length and fresh-weight. After measuring fresh weights, same plants were dried at 60 °C oven for 15 days, dry weights were measured. Replicate lines were withdrawn from salt-stress after 10 days and kept under no-salt condition for 15 days to check the recovery status of the selected plant lines.

Test for measurement of chlorophyll content.  0.5 g of leaf samples were taken and homogenized in presence of liq. N2 and 10 ml methanol. Mixtures were centrifuged for 10,000 rpm for 15 min at 4 °C to separate out the supernatant. To make a standard initial mixture from each sample, 0.5 ml of mixtures were taken individually and mixed with 4.5 ml of methanol. O.D were measured at 663 nm and 645 nm to analyze the mixture for Chlorophyll-a and chlorophyll-b respectively. Formula to determine the value of estimated chlorophyll was done by following the method of Nayek et al.^72

Transcript analysis.  Total RNA were extracted from fresh leaves with RNA-Xpress™ Reagent (Hi Media). c-DNAs were prepared using and following manufacturer’s instruction of kit (Thermo Scientific). RT-PCR was performed with Taq DNA polymerase from NEB. All the primers used in RT-PCR experiments are described in Supplementary Table S2.

(Single irrelevant line: "deposition system (Denton Vacuum, LLC, Moorestown, NJ, USA). Samples were then examined using a SEM (JSM-6610, JEOL Brasil Instrumentos Cientificos Ltda., São Paulo, SP, Brazil) equipped with an energy-dispersive X-ray spectrometer." should be ignored.)

Western blotting for transgenic expression of candidate proteins. About 25 μg of total protein from each plant sample was fractionated in 8% SDS-PAGE and transferred to nitrocellulose membrane (BioRad), blocked with 5% (w/v) skimmed milk (Sigma) for 2 hrs. at 37°C, primary antibody (1:20000) in 1XTBST added for overnight at 4°C, the blot washed with large volumes of TBST 4–5 times with fresh changes of wash buffer at 15 min. interval. Then the membrane was immuno-probed with a secondary antibody raised as goat anti-rabbit at 1:5000 (v/v) dilution in TBST [1XTBS and 0.1% (v/v) Tween 20] for 2 hrs. at room temperature, washed with large volumes of TBST 2 times with fresh changes of wash buffer every 10 min and incubated with horseradish peroxidase (HRP)-linked luminescence in dark for few minutes and developed with a florescent ECL detection kit reagent (Amersham Pharmacia Biotech, Little Chalfont, Bucks, UK) following manufacturer’s instruction. Fluorescence was detected by exposing the thoroughly washed membrane to KODAK [X-O(MAT)AR] film (Rochester, NY, USA).

Identification and estimation of myo-inositol and pinitol in transgenic rice. ~200 mg dried tissues were used for sugar extraction. Ground materials were extracted using methanol:chloroform:water in 12:5:3 (v/v) ratio at 75°C. Xylitol was used as internal standard. Extracts were de-ionised through resin bed (Dowex 50 W H+/Dowex 1\8 formate; Dow Chemical Co., Pevely, MA, USA), lyophilized and stored at −20°C. Trimethylsilyl derivatives of inositols and inositol O-methyl-ethers were separated by capillary gas chromatography as previously described⁷³.

Detection of site of introgression in transgenic plant lines. Hi-TAIL PCR²⁷ method utilizes nested known sequence specific primers with melting temperature (Tm) > 65°C in consecutive reactions together with a short (15–16 nucleotides) arbitrary degenerate (AD) primer (Tm 45°C) with 64–256 folds of degeneracy, so that relative amplification efficiencies of target and non-target products can be thermally controlled.

Photosynthetic efficiency analysis of transgenic lines. Measurements were taken from middle part of apical and second apical leaf using PHOTOSYNTHETIC EFFICIENCY ANALYZER (Hansatech Instruments Ltd., King’s Lynn, UK) and recorded up to 1 sec, with data acquisition every 10 μS, for 1 sec using a single flash of light intensity 3000 μmol/m²/sec without pre-illumination. The values are taken at 0.05 ms (T1), 0.10 ms (T2), 0.30 ms (T3), 2 ms (T4) and 30 ms (T5) for 1 sec.⁷⁴. Each chlorophyll-a fluorescence transient O-J-I-P was analyzed according to the JIP-test⁷⁴. The data was analyzed using HANSATECH BIOLYZER SOFTWARE.

Agronomic character analysis. Selected plants were grown to maturity in greenhouse and self-pollinated. Agronomic data were collected manually. Grain characters (grain wt., grain length, grain width ratio) were analyzed by using SMART-GRAIN VERSION 1.1 software.

Microarray. Total RNA was extracted from leaves of one-month old WT (wild type), OsINO1 and PcINO1–transformed plants either in control condition or under 5 days treatment of 150 mM NaCl for comparative transcriptome study, using Agilent cDNA microarray. Obtained transcripts were subjected to comparative microarray analysis.

22. Patra, B., Ray, S., Richter, A. & Majumder, A. L. Enhanced salt tolerance of transgenic tobacco plants by co-expression of PcINO1 and McIMT1 is accompanied by increased level of myo-inositol and methylated inositol. Protoplasma. 245, 143–152 (2010).

23. Das, P., Nutan, K. K., Pareek, S. S. & Pareek, A. Understanding salinity responses and adopting 'omics based' approaches to generate salinity tolerant cultivars of rice. Front. Plant Sci. 6, 712 (2015).

24. Majee, M. et al. A novel salt-tolerant L-myo-Inositol-1-phosphate synthase from Porteresia coarctata (Roxb.) Tateoka, a halophytic wild rice. J. Biol. Chem. 279, 28539–28552 (2004).

25. Hiei, Y., Komari, T. & Kubo, T. Transformation of rice mediated by Agrobacterium tumefaciens. Plant Mol. Biol. 35, 205–218 (1997).

26. Nishimura, A., Aichi, I. & Matsuoka, M. A protocol for Agrobacterium-mediated transformation in rice. Nat. Protoc. 1, 2796–2802 (2007).

27. Liu, Y. G. & Chen, Y. High-efficiency thermal asymmetric interlaced PCR for amplification of unknown flanking sequences. BioTechniques. 43, 649–656 (2007).

28. Krasensky, J. & Jonak, C. Drought, salt, and temperature stress-induced metabolic rearrangements and regulatory networks. J. Exp. Bot. 63, 1593–1608 (2012).

29. Gupta, B. & Huang, B. Mechanism of salinity tolerance in plants: physiological, biochemical, and molecular characterization. International Journal of Genomics. https://doi.org/10.1155/2014/701596 (2014).

30. Vernon, D. M., Ostrem, J. A. & Bohnert, H. J. Stress perception and response in a facultative halophyte: the regulation of salinity-induced genes in Mesembryanthemum crystallinum. Plant Cell Environ. 16, 437–444 (1993).

31. Sengupta, S. et al. Manipulation of inositol metabolism for improved plant survival under stress: a network engineering approach. J. Plant Biochem. Biotechnol. 21, 15–23 (2012).

32. Salvi, P. et al. Differentially expressed galactinol synthase(s) in chickpea are implicated in seed vigor and longevity by limiting the age induced ROS accumulation. Sci. Rep, https://doi.org/10.1038/srep35088 (2016).

33. Duan, J. et al. OsMIOX, a myo-inositol oxygenase gene, improves drought tolerance through scavenging of reactive oxygen species in rice (Oryza sativa L.). Plant Sci. 196, 143–151 (2012).

34. Alok, A. et al. Biochemical characterization and spatio-temporal expression of myo-inositol oxygenase (MIOX) from wheat (Triticum aestivum L.). Plant Gene. 4, 10–19 (2015).

35. Krishnamoorthy, P., Sanchez-Rodriguez, C., Heilmann, I. & Persson, S. Regulatory roles of phosphoinositides in membrane trafficking and their potential impact on cell-wall synthesis and re-modelling. Ann. Bot. 114, 1049–1057 (2014).

36. Majumder, A. L., Johnson, M. D. & Henry, S. A. 1L-myo-inositol-1-phosphate synthase. Biochim. Biophys. Acta. 1348, 245–256 (1997).

37. Majumder, A. L., Chatterjee, A., Ghosh Dastidar, K. & Majee, M. Diversification and evolution of L-myo-inositol 1-phosphate synthase. FEBS Lett. 533, 3–10 (2003).

38. Basak, P. et al. An evolutionary analysis identifies a conserved pentapeptide stretch containing the two essential lysine residues for rice L-myo-inositol 1-phosphate synthase catalytic activity. PLoS One, https://doi.org/10.1371/journal.pone.0185351 (2017).

39. Mishra, A. & Tanna, B. Halophytes: Potential Resources for Salt Stress Tolerance Genes and Promoters. Front. Plant Sci. https://doi.org/10.3389/fpls.2017.00829 (2017).

40. RayChoudhuri, A. & Majumder, A. L. Salinity induced enhancement of L-myo-inositol 1-phosphate synthase in rice (Oryza sativa L.). Plant Cell Environ. 19, 1437–1442 (1996).

41. GhoshDastidar, K., Chatterjee, A., Chatterjee, A. & Majumder, A. L. Evolutionary Divergence of L-myo-Inositol 1-Phosphate Synthase: Significance of a Core Catalytic Structure. Book chapter: Biology of Inositols and Phosphoinositides. 313–338 (2006).

42. Das-Chatterjee, A. et al. Introgression of a novel salt-tolerant L-myo-inositol 1-phosphate synthase from Porteresia coarctata (Roxb.) Tateoka (PcINO1) confers salt tolerance to evolutionary diverse organisms. FEBS Lett. 580, 3980–3988 (2006).

43. Vernon, D. M. & Bohnert, H. J. A Novel Methyl Transferase Induced by Osmotic Stress in the Facultative Halophyte M. crystallinum. EMBO J. 11, 2077–2085 (1992a).

44. Vernon, D. M. & Bohnert, H. J. Increased expression of a myo-inositol methyl transferase in Mesembryanthemum crystallinum is part of a stress response distinct from Crassulacean acid metabolism induction. Plant Physiol. 99, 1695–1698 (1992b).

45. Visarada, K. B. R. S., Sailaja, M. & Sarma, N. P. Effect of callus induction media on morphology of embryogenic callus in rice genotypes. Biol. Plant. 45, 495–502 (2002).

46. Nabors, M. W., Heyser, J. W., Dykes, T. A. & Demott, K. J. Long-duration, high frequency plant regeneration from cereal tissue cultures. Planta. 157, 385–391 (1983).

47. Bevitori, R., Popielarska-Konieczna, M., dos Santos, E. M., Grossi-de-Sá, M. F. & Petrofeza, R. Morpho-anatomical characterization of mature embryo-derived callus of rice (Oryza sativa L.) suitable for transformation. Protoplasma. 251, 545–554 (2014).

48. Wang, Y., Li, K. & Li, X. Auxin redistribution modulates plastic development of root system architecture under salt stress in Arabidopsis thaliana. J. Plant Physiol. 166, 1637–1645 (2009).

49. Boursier, P. & Läuchli, A. Growth responses and mineral nutrient relations of salt-stressed sorghum. Crop Sci. 30, 1226–1233 (1990).

50. Asch, F., Dingkuhn, M., Sow, A. & Audebert, A. Drought-induced changes in rooting patterns and assimilate partitioning between root and shoot in upland rice. Field Crop Res. 93, 223–236 (2005).

51. Zolla, G., Heimer, Y. M. & Barak, S. Mild salinity stimulates a stress-induced morphogenic response in Arabidopsis thaliana roots. J. Exp. Bot. 61, 211–224 (2010).

52. Horie, T., Karahara, I. & Katsuhara, M. Salinity tolerance mechanisms in glycophytes: An overview with central focus on rice plants. Rice. 5, 1–11 (2012).

53. Sun, F. et al. Salt modulates gravity signalling pathway to regulate growth direction of primary roots in Arabidopsis. Plant Physiol. 146, 178–188 (2008).

54. Wang, Y. et al. Salt-induced plasticity of root hair development is caused by ion disequilibrium in Arabidopsis thaliana. J. Plant Res. 121, 87–96 (2008).

55. Ji, H. et al. The salt overly sensitive (SOS) pathway: established and emerging roles. Molecular Plant 6, 275–286 (2013).

56. Galvan-Ampudia, C. S. & Testerink, C. Salt stress signals shape the plant root. Curr. Opin. Plant Biol. 14, 296–302 (2011).

57. Sarkar, T., Thankappan, R., Kumar, A., Mishra, G. P. & Dobaria, J. R. Heterologous Expression of the AtDREB1A Gene in Transgenic Peanut-Conferred Tolerance to Drought and Salinity Stresses. PLoS One 9, e110507 (2014).

58. Rai, A. C., Singh, M. & Shah, K. Engineering drought tolerant tomato plants over-expressing BcZAT12 gene encoding a C2H2 zinc finger transcription factor. Phytochem. 85, 44–50 (2013).

59. Farooq, M., Wahid, A., Kobayashi, N., Fujita, D. & Basra, S. M. A. Plant drought stress: effects, mechanisms and management. Agron. Sustain. Dev. 29, 185–212 (2009).

60. Jami, S. K. et al. Ectopic expression of an annexin from Brassica juncea confers tolerance to abiotic and biotic stress treatments in transgenic tobacco. Plant Physiol. Biochem. 46(12), 1019–1030 (2008).

61. Ravikumar, G. et al. Stress-inducible expression of AtDREB1A transcription factor greatly improves drought stress tolerance in transgenic Indica rice. Transgen. Res. 23, 421–439 (2014).

62. Kalaji, H. M. & Pietkiewicz, S. Salinity Effects on Plant Growth and Other Physiological Processes. Acta Physiol. Plant. 14, 89–124 (1993).

63. Kalaji, H. M. & Nalborczyk, E. Gas Exchange of Barley Seedlings Growing under Salinity Stress. Photosynthetica. 25, 197–202 (1991).

64. Kalaji, H. M., Govindjee, Bosa, K., Koscielniak, J. & Zuk-Golaszewska, K. Effects of salt stress on photosystem II efficiency and CO2 assimilation of two Syrian barley landraces. Environ. Exp. Bot. 73, 64–72 (2011).

Scientific Reports | (2019) 9:5358 | https://doi.org/10.1038/s41598-019-41809-7

The work was supported by research grants from Department of Biotechnology (DBT), GOI (BT/AB/05/02/2007-III dt.21/09/2010); Raja Ramanna Fellowship (10/29/2010/RRF-R&D-II/6403 dt.03/06/2011) from Department of Atomic Energy (DAE) and DBT-NWO, GOI (BT/IN/NWO/17/ALM/2015-16 dt. 02.09.2015) from Department of Biotechnology (DBT), awarded to A.L.M. R.M. was supported by a RA-ship in Biotechnology and Life Sciences and BioCare grant (BT/Bio-CARe/02/10197/2013-14 dt.18/11/2014) both awarded by DBT, GOI.

Conceived the project: A.L.M. Designed the experiments: A.L.M., R.M., S.S.G. Performed the experiments: R.M., A.M., S.B., S.M. Analyzed the data: R.M., S.B., S.M., S.S.G., A.L.M., S.R. Wrote the paper: R.M., A.L.M., with contributions from others.

Supplementary information accompanies this paper at https://doi.org/10.1038/s41598-019-41809-7.

Competing Interests: The authors declare no competing interests.

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[System]
You are a **scientific‐rigor auditor**. You will receive the parsed contents of a research paper. Your job is to identify **only** those errors or flaws that directly undermine the **scientific validity** of the paper’s methods, analyses, or conclusions.

Your sole focus is to identify flaws—such as errors in experimental design, data integrity, calculations, statistical inference, or reproducibility—that directly call into question the validity of a specific claim, paragraph, or the paper as a whole.

**Do not** report issues that are purely presentational, rhetorical, stylistic, or related to citation practices.

---

After you’ve done a **detailed walkthrough** of the paper, output exactly in this format—no extra keys or commentary:

```
<analysis>
{detailed walk‑through of how you checked each section/figure and why you flagged (or did not flag) any flaw}
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<response>
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OPEN

Hailemariam Assefa¹, Simranjeet Singh², Nabila Shehata³, Nadeem A. Khan⁴, Femi Emmanuel Olu¹✉ & Praveen C. Ramamurthy²✉

This study presents the synthesis of a green polymer-based nanocomposite by incorporating green CuO nanoparticles into polyaniline (PANI) for the adsorption of Pb (II) ions from contaminated water. The nanocomposite was extensively characterized using FTIR, XRD, BET, SEM-EDX, XPS, and Raman spectroscopy, both before and after Pb(II) adsorption. Optimization studies were performed to assess the effects of key parameters, including pH, adsorbent dosage, and initial ion concentration on the adsorption process. Adsorption isotherms and kinetic models were applied to analyze the experimental data, revealing that the Freundlich isotherm provided the best fit, with a high correlation coefficient (R²) and a (1/n) value less than 1, indicating favorable adsorption conditions. Furthermore, the Avrami and pseudo-first-order kinetic models demonstrated superior fitting compared to other models. The green nanocomposite exhibited outstanding adsorption capacity, highlighting its potential as a sustainable and efficient adsorbent for Pb(II) removal from wastewater.

Keywords: Green Polymer, Nanocomposite, Pb (II) adsorption, Kinetics

In recent years, environmental pollution by heavy metals has intensified, driven by industrial production, energy consumption, mining operations, and the widespread use of pesticides and fertilizers¹,². Lead (Pb), a widely prevalent and highly toxic metal, is found in various environmental ecosystems, including urban and residential areas. The discharge of lead-contaminated wastewater from multiple sources has surged due to economic development and increasing social demands³. Lead is a highly toxic element that persists in the environment without undergoing significant degradation. Once introduced into the environment, it can be adsorbed by plants, leading to significant accumulation within their tissues. Excessive lead uptake disrupts cellular structures, leading to physiological damage, impaired growth and in severe cases plant death⁴. Furthermore, lead can enter the human body through various pathways, including ingestion of contaminated water, air, food, and skin contact. Once absorbed, lead accumulates within the body posing significant health risks⁵. Therefore, it is essential to implement effective wastewater treatment strategies to address these challenges⁶. The primary techniques for remediating lead-contaminated wastewater include chemical precipitation, ion exchange, membrane filtration, and adsorption. Among these, adsorption is widely regarded as a highly effective method due to its simplicity and efficiency in removing pollutants. However, the high cost of adsorbents limits their use in treating heavy metal-contaminated wastewater. As a result, current research is largely focused on developing advanced adsorbent materials that are not only highly efficient but also cost effective and environmentally sustainable⁷.

Polymer-based nanocomposites have attracted significant attention across diverse scientific and technological domains due to their superior and tunable properties⁸. These advanced materials have demonstrated immense potential in a broad spectrum of applications, including water purification, photovoltaic systems, wastewater remediation, electronic devices, tissue engineering scaffolds, wound dressings, antimicrobial agents, drug

¹Faculty of Material Science and Engineering, Jimma Institute of Technology, Jimma University, Jimma, Ethiopia.
²Interdisciplinary Centre for Water Research (ICWaR), Indian Institute of Science, Bangalore 560012, India.
³Environmental Science and Industrial Development Department, Faculty of Postgraduate Studies for Advanced Sciences, Beni-Suef University, Beni Suef, Egypt.
⁴Civil Engineering Department, College of Engineering, King Khalid University, Abha 61421, Saudi Arabia. ✉email: foluemm@gmail.com; praveen@iisc.ac.in

delivery platforms, and electromagnetic interference shielding systems⁹. Among conductive polymers, polyaniline (PANI) stands out due to its unique combination of cost-efficiency, high polymerization efficiency, exceptional stability, and versatility. Commonly referred to as aniline black, PANI exists in various oxidation states, enabling its adaptability for specific applications¹⁰.

Copper oxide nanoparticles (CuO NPs) are highly versatile, having applications in electrical sensors, plant disease management, field emission, and catalysis. When incorporated into nanocomposite polymers, CuO serves as an active site for adsorption due to its high surface area and strong interactions with adsorbates, thereby significantly enhancing the overall adsorption capacity. The combination of CuO with polyaniline (PANI) generates a synergistic effect that not only improves adsorption performance but also enhances the structural stability of the composite, making it more durable and resistant to degradation during adsorption-desorption cycles. Common methods for synthesizing such nanocomposites include the reduction of metals into polymers, in situ polymerization of monomers in the presence of metal nanoparticles, and mechanical blending of polymers with nanoparticles.¹¹.

Conventional techniques for synthesizing nanomaterials often pose significant environmental challenges due to the generation of toxic by-products. Green nanoparticles made from plant extracts have gained interest due to their safety and eco-friendliness¹². The efficacy of these green nanoparticles in wastewater treatment is attributed to the physio-chemical features exhibited by plants¹³. Green synthesis techniques utilize plant extracts to mitigate the harmful effects of conventional methods that release by-products into the environment¹⁴. Researchers have developed various nanoparticles using techniques such as thermal reduction, microwave irradiation, chemical vapor deposition, photochemical, and electrochemical methods. However, these approaches often involve harsh chemicals, leading to environmental concerns and increased costs¹⁵.

In recent times, various nanocomposite materials derived from polymers, such as PANI-ZnO, Fe₃O₄-SBCTA, Fe₃O₄-PANI-MnO₂, PMMA-boehmite, PPy-Fe₃O₄, PTh–Al₂O₃, and PVA-ZnO, have been employed for the purpose of removing Cr⁶⁺, Fe³⁺, Hg²⁺, Ar³⁺, Cu²⁺, Co²⁺ and Pb²⁺ from wastewater. Polymers exhibit a favorable surface area-to-volume ratio, enhancing their effectiveness when combined with other materials to form composites¹⁶⁻²².

The current research focuses on developing a Pb (II) adsorbent by incorporating green copper oxide nanoparticles (CuO NPs) encapsulated in polyaniline (PANI). The g-CuO NPs were obtained from the stem extract of Haldinia cordifolia. The resulting composite material was employed for the adsorption of Pb (II) ions and characterized using multiple analytical techniques: X-ray diffraction (XRD), scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDX), Fourier transform infrared spectroscopy in attenuated total reflectance mode (FTIR-ATR), X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, and Brunauer-Emmett-Teller (BET) analysis. Additionally, the study investigated the influence of various parameters on adsorption efficiency, including pH, initial Pb (II) concentration, and CuO/PANI dosage. Optimization of these parameters provided insights into the adsorption mechanism and enhanced the Pb(II) removal efficiency of the composite material.

## Materials and methods

### Chemicals
Pb(NO₃)₂ (>99%) and CuSO₄ (99% purity) were procured from Merck Bangalore Karnataka and used as such without any purification. APS (ammonium persulphate) (99.9% purity) was obtained from SRL, Chemicals Ltd. Aniline (≥99.5%) and HCl (37%) were purchased from Spectrochem Karnataka, India.

### Synthesis of g-CuO NPs
In this study, g-CuO NPs were synthesized from plants using a reported study in a previous with some modifications²³. Before extraction, the stem bark of Haldinia cordifolia is typically washed with deionized (DI) water. The stem part of the plant is then dried at 30 ± 2 ºC. Subsequently, 5 g of H. cordifolia stem are ground to a fine powder, dissolved in 100 mL of DI water, and heated for 30 min at 80 ± 2 ºC on a hot plate. This mixture is then filtered using a muslin cloth and filter paper. To synthesize green CuO (g-CuO) nanoparticles, 75 mL of a 0.01 M CuSO₄ solution is added to 5 mL of the H. cordifolia plant extract in 250 mL conical flasks, as illustrated in Supplementary Fig. S (1). These solutions are stirred for 60 min at 90 ± 2 ºC at 4000 rpm on a magnetic stirrer. The precipitate is then collected by centrifugation at 8000 rpm for 10 minutes and repeatedly washed with deionized (DI) water to ensure the removal of residual impurities and obtain a high-purity product.

### Synthesis of g-CuO/PANI nanocomposite
The g-CuO/PANI nanocomposite was synthesized by the in-situ composite formation, incorporating some modifications from the previous report²⁴. First, 0.2 g of green-synthesized CuO nanoparticles (g-CuO NPs) powder was mixed with 30 mL of a 1 M HCl. The mixture was then subjected to ultrasonic waves for 30 min to ensure uniform dispersion. Subsequently, 50 µL of distilled aniline was added to the solution and further dispersed ultrasonically for another 30 min. In a separate beaker, 0.1675 g of ammonium persulfate (APS) was dissolved in 15 mL of 1 M HCl, and this solution was added dropwise to the first mixture, as depicted in Supplementary Fig. S (2). The resulting solution was then kept in an ice bath at 5–7 ºC for 6 h with continuous stirring, and then washed with DI and ethanol. The final product, the g-CuO/PANI nanocomposite, was dried overnight in a vacuum oven at 60 ºC. Pristine polyaniline (PANI) was synthesized following the same procedure as for the composite.

### Characterization techniques
FTIR measurements were performed using Bruker Tensor II instrument to identify the functional groups present in CuO NPs, PANI, CuO/PANI, and CuO/PANI after Pb (II) adsorption. The spectra was recorded at a resolution

of 4 cm⁻¹ over the wavenumber range of 4000–500 cm⁻¹. XRD analysis was performed using a Bruker D8 Advance, which emitted Cu Kα radiation with a wavelength of 1.541 Å. The chemical composition and electronic state of materials were studied using XPS to obtain the characteristic binding energy using Thermo K-alpha, Al anode. The morphology of g-CuO NPs, PANI, CuO/PANI, and CuO/PANI after Pb (II) adsorption was also studied using SEM-EDS (Zeiss ULTRA 55 Field Emission). For pore size and surface area analysis, the BELSORP MAX II instrument was used. This multifunctional tool evaluates vapour adsorption, chemisorption, and specific surface area/pore size distribution. Raman spectroscopy (Model-STR-300; Make: Seki Technotron Corp, Japan) was utilized to examine molecular information before and after the adsorption.

The adsorption experiments were conducted in batch mode to evaluate the performance of the CuO/PANI composite under various conditions. A known amount of CuO/PANI was added to 100 mL Erlenmeyer flasks containing Pb(NO₃)₂ solutions, and the mixtures were stirred at 200 rpm to determine optimal parameters such as pH, composite dosage, and initial Pb(II) concentration. A stock solution of Pb(II) (1000 mg L⁻¹) was prepared, and desired concentrations were obtained by diluting this stock solution with deionized water. For the experiments, 100 mL of Pb(II) solutions at varying concentrations were treated with 25 mg of CuO/PANI and shaken at 200 rpm. The lead concentrations were measured before and after the adsorption process. The effects of key factors, including Pb(II) concentration, CuO/PANI dosage, and solution pH, on adsorption efficiency were systematically investigated. The removal efficiency was calculated using Equation 1.

% Removal = ((C_O - C_t) / C_O) × 100    (1)

where C_t and C_O are the final and initial concentrations.

To investigate the adsorption kinetics models, five adsorption models (intraparticle diffusion (IPD), Pseudo-first-order (PFO), Pseudo-second-order (PSO), mixed first and second order (MFSO), and Avrami) were investigated for the adsorption of Pb (II). Adsorption isotherms play a crucial role in investigating the mechanism and affinity of adsorption towards Pb (II)²⁵. Different models, namely Langmuir, Freundlich, Langmuir-Freundlich, Sips, Toth, Redlich-Peterson, Dubinin–Radushkevich, Khan, Baudu, and Fritz-Schlunder models, were used to analyze the experimental data of Pb (II) adsorption onto CuO/PANI composite.

Figure 1 illustrates the XRD graph of the g-CuO NPs, PANI, g-CuO/PANI nanocomposite, and after Pb (II) adsorption. The XRD graph of pristine PANI shows two broad peaks at about 20º and 25º, as shown in Fig. 1a. These peaks associated to the (020) and (200) planes of PANI matched with JCPDS card No 53-1891²⁶ suggesting that PANI is semi-crystalline in nature²⁷. As shown in Fig. 1b, the XRD pattern of g-CuO nanoparticles has sharp peaks, indicating the nanoparticle's high crystallinity. The g-CuO NPs exhibit two characteristic peaks at 35º and 38º with hkl value of the (-111 and 111) planes respectively, along with multiple smaller peaks at

higher 2θ values (32, 49, 53, 58, 61, and 68°) which corresponding to the hkl (110, 202, 020, 202, 022, -202) planes respectively, JCPDS: card no. 48-1548 which align with the findings of prior work with chemical synthesis routes²⁸,²⁹. The average crystallite size of g-CuO NPs was calculated by Scherer's formula given by an equation:
D = 0.9λ / β cosθ, where D is the average crystalline size of the nanoparticle, β is the FWHM of significant peaks, θ is the Bragg's angle, and λ is the wavelength of Cu Kα³⁰. The average crystallite size was observed to be of g-CuO NPs to be 17.91 nm. The XRD result of the g-CuO/PANI nanocomposite is also depicted in Fig. 1c. The nanocomposite shows a diffraction peak at 32, 35, 38, 41, 45, 50, 53, and 62°, where some peaks in pristine g-CuO NPs disappear and shifted to high 2θ value with low intensity³¹,³². This is due to the interaction between PANI and the g-CuO nanoparticles during the formation of the nanocomposite and the semi-crystalline nature of PANI. Despite this interaction, all the characteristic CuO peaks were still visible. XRD analysis was also performed on the nanocomposite after the adsorption of lead ion. The results indicated no significant shift in the 2θ degrees, with the patterns remaining almost identical to those of the nanocomposite before adsorption, except for changes in intensity, as shown in Fig. 1d.

Fourier Transform Infrared (FTIR) spectroscopy was employed to identify the functional groups in PANI, g-CuO NPs, CuO/PANI, and CuO/PANI after Pb(II) adsorption within the wavenumber range of 500–4000 cm⁻¹ in Fig 2. For PANI, characteristic absorption bands were observed at 3438, 3280, 1580, 1490, 1346, 1143, 823, and 759 cm⁻¹ in figure 2 (a). The broad bands at 3438 cm⁻¹ and 3280 cm⁻¹ correspond to O–H and N–H stretching vibrations, respectively. The peaks at 1580 cm⁻¹ and 1490 cm⁻¹ are attributed to the C=C stretching of the quinoid and benzenoid rings, respectively³³. The bands between 1346 cm⁻¹ and 1143 cm⁻¹ are associated with C–N bending vibrations of secondary aromatic amines³⁴. Additionally, the benzenoid group exhibited C–H sp³ stretching and C=C stretching vibrations at 2998 cm⁻¹ and 1436 cm⁻¹, respectively. The quinonoid ring in PANI showed an absorbance band at 1020 cm⁻¹, while the band at 823 cm⁻¹ was attributed to C–H bonds³⁵. For g-CuO NPs, as shown in Fig. 2 (b), a broad peak near 3435 cm⁻¹ corresponds to O–H stretching vibrations, and a sharp peak at approximately 1637 cm⁻¹ is indicative of C=O stretching vibrations. The characteristic Cu–O stretching vibrations were observed at 590 cm⁻¹ and 830 cm⁻¹, confirming the presence of CuO³⁶,³⁷.

The FTIR spectra of the (CuO/PANI) nanocomposite are different from those of pure g-CuO NPs and PANI because the peak intensity changed, and the wavenumber shifted. This can be seen in Fig. 2 (c). Absorbance peaks at 1484 and 1570 cm⁻¹ are assigned to C=C and C=N stretching mode vibration for benzenoid & quinoid

of PANI, respectively, which shows some shift in peak position and peak intensity compared to pure PANI[38,39]. The peak that appeared at 1295 cm⁻¹ corresponds to the C-H stretching of the benzenoid ring. The peak at 586 cm⁻¹ observed in nanocomposite shows some red shift compared to g-CuO NPs, which corresponds to Cu-O stretching vibration[39]. The shift in PANI and g-CuO, characteristic peaks in composites, indicates an interaction between them. As illustrated in Fig. 2 (d), the FTIR spectra after Pb (II) adsorption differ from those taken before adsorption in terms of peak position and intensity. The absorption peak corresponding to C=C and C=N stretching mode vibration for the benzenoid and quinoid rings at 1484 and 1570 cm⁻¹ shifted to 1487 and 1559 cm⁻¹; a blue and red shift, respectively, and shows a more intense peak. The peak at 586 cm⁻¹, due to the Cu-O vibration bond, is shifted to 589 cm⁻¹ and shows little broadness compared to CuO/PANI nanocomposite before adsorption. These changes occur because of an interaction between the nanocomposite and Pb (II), which forms some complexes.

Fig. S (3) shows the BET surface area, pore volume, and pore size of the CuO/PANI nanocomposite before and after Pb adsorption. The BET study revealed an overall decrease in surface area from 17.105 to 12.217 m² g⁻¹ following the adsorption of Pb, as shown in Table S (1). The fact that the surface area has shrunk further supports the idea that Pb ions are adsorbing into the nanocomposite material. The CuO/PANI nanocomposite’s isotherm shows that it absorbs less nitrogen at low pressures, then slowly more at higher pressures until it reaches its limit. It is possible to make the adsorbent better at absorbing substances by giving it a lot of surface area and making pores of different sizes, from small micropores to larger mesopores[40].

The SEM image for g-CuO NPs, CuO/PANI nanocomposite, and the nanocomposite material after adsorption was carried out by Zeiss ULTRA 55 FESEM. From the SEM result of g-CuO NPs in Fig. 3 (a), it is observed that the surface morphology of the finely dispersed nanoparticles. The SEM image of the CuO/PANI nanocomposite shows a significant effect on morphology after PANI is incorporated into the g-CuO nanoparticle, as shown in Fig. 3 (b). Additionally, the morphology of nanocomposite after Pb (II) adsorption is depicted in Fig. 4 (c). An energy-dispersive X-ray spectrometer (EDS) was also conducted for the elemental analysis. As shown in Fig. 3 (a) and (b), there is a significant decrease in the weight (%) of the Cu element after nanocomposite (CuO/PANI) is formed; this may be due to the incorporation of PANI during in-situ polymerization. Moreover, the EDS of CuO/PANI in Fig. 3 (b) shows C, N, O, and Cu elements, in which the presence of N indicates aniline monomer is polymerized to PANI and interacts with g-CuO NPs. After the lead ion adsorbed, the EDS of nanocomposite has Pb in addition to the elements present in CuO/PANI nanocomposite, as shown in Fig. 3 (c).

XPS of CuO/PANI was carried out before and after adsorption, and Fig. 5a, b show the results. The survey spectra showed the presence of Cu1s, O1s, C1s, and N1s, which is consistent with the EDX result, as shown in Fig. 3a–c. The presence of N1s and C1s suggests the incorporation of PANI into g-CuO NPs during in-situ polymerization reactions. Fig. S (4b) shows that after C1s deconvolution, there are three peaks at 282.75, 286.23, and 290.15 eV. These correspond to C-Cu, C=C/C-C, and O-C=O, interaction between carbon atoms in the polyaniline (PANI) matrix and the copper (Cu) atoms in the CuO nanoparticles in line with previous reports[41]. The base peak at 934.80 eV corresponds to Cu 2p₃/₂ and 954.44 eV to Cu2p₁/₂, as shown by the deconvoluted peak of Cu 2p in Fig. S (4c)[41]. As shown in Fig. S (4c), the satellite peak at 943.31 eV indicates that Cu is in the Cu (II) form, which is characteristic of CuO and is consistent with previous work[42,43]. Furthermore, Fig. S (4d) illustrates the deconvolution of the O1s into three peaks: 529.41 eV (O-Cu), 531.67 eV (O=N), and 532.92 eV (C-O)[44]. Two peaks are also observed for N1s at 399.83 and 401.32 eV, attributed to –NH and positively charged N atoms respectively, as depicted in Fig. S (4a)[45]. Figure 5 also displays the XPS spectra following Pb (II) adsorption. The survey scan spectrum after adsorption confirms the incorporation of a Pb ion into our nanocomposite, as depicted in Fig. 5. The characteristic peaks of Pb 4f for Pb (II) are observed at 139.25 and 144.14 eV, which are belonged to Pb 4f₇/₂ and Pb 4f₅/₂, respectively, after deconvolution, as shown in Fig. S (4e)[46]. The XPS result after lead ion adsorption reveals that Pb⁴⁺ is responsible for the binding energy peaks at 141.08 eV and 138.43 eV, while Pb (II) is at 138.69 eV and 143.78 eV[47]. After adsorption, the survey scan shows a peak shift of C1s (284.96 eV to 285.04 eV), N1s (401.60 eV to 399.83 eV), and O1s (532.99 eV to 533.01 eV).

The Raman spectra of CuO/PANI and CuO/PANI after Pb (II) adsorption nanocomposites are depicted in Fig. S (5). For CuO/PANI nanocomposite, Fig. S (5a), the peak observed at 421 cm⁻¹ is attributed to the Ag mode, while the peaks appeared at 538 and 787 cm⁻¹ were B₁g and B₂g modes of CuO respectively. The Raman peak at 1590 cm⁻¹ is the C=C of PANI's quinonoid ring (Q), while the peak at 1501 cm⁻¹ is the C-C of the benzenoid ring (B) of PANI. The peaks at 1562 and 1412 cm⁻¹ are PANI's N-H and C=N stretching, respectively. The peaks observed at 1178 and 1268 cm⁻¹ are also belonged to the C-H and C-N bonds, respectively[47–50]. The peaks related to PANI are visible compared to CuO; this may be due to their composite proportion. After adsorption, some peaks are shifted, and their intensities are also changed. CuO/PANI nanocomposite: after Pb (II) adsorption, the peak at 1178 cm⁻¹ (C-H) was shifted to 1166 cm⁻¹. The quinonoid ring's C=C peak nearly occupies the same Raman shift position. Moreover, the peak that is associated with the C-C of the benzenoid ring at 1501 cm⁻¹ is shifted to 1490 cm⁻¹, and a more intense peak is observed, as shown in Fig. S (5b).

The pH is one factor that significantly influences the adsorption⁵¹. To check the effect of pH variation, studies were carried out with a pH range of 2 to 6, with initial ion concentration of 25 mg/L, and a CuO/PANI dosage of 25 mg/L. Figure 6(a) shows how pH influences the removal of Pb (II). It showed a progressive increase in the removal of Pb (II), with removal percentage of 48.16 to 95.25%, when pH was increased from 2 to 6. When the pH rises above 6, lead ions precipitate as hydroxides, and removal efficiency decreases⁵². Consequently, the

The effect of adsorbent dosage on Pb(II) ion removal was investigated using dosages of 25, 50, 75, 100, and 125 mg L⁻¹. As the CuO/PANI nanocomposite dosage increased, the Pb(II) removal efficiency improved; however, the adsorption efficiency began to decrease at higher dosages⁵⁴. This trend can be attributed to the increased concentration of the composite, which leads to a higher dosage and a reduced overall surface area available for adsorption of Pb(II). Removal increased with the adsorbent dosage until a saturation point was reached, as depicted in Fig. 6(b)⁵⁵. This indicates that additional active sites participate in the adsorption process until all available sites are fully occupied by the adsorbent.

Figure 6(c) depicts the effect of varying initial ion concentration of Pb (II) (from 25 to 125 ppm). As the initial ion concentration of Pb (II) increases, the CuO/PANI composite becomes better at adsorbing it, going from 96 to 295.73 mg g⁻¹. Many Pb (II) molecules were competing for an available adsorption site on the CuO/PANI, making it less able to hold molecules. As the starting concentrations grow, the absorption capacity rises, but the adsorption percentage falls due to surface saturation⁵⁴.

adsorption percentage of Pb (II) diminished as pH increased. Following previous studies, the results demonstrate that the adsorption efficiency decreases at pH levels greater than 6. The maximum adsorption was achieved at pH = 6, decreasing significantly when the pH > 6. This finding aligns with previously reported research, further supporting our experimental observations and the point of zero change (PZC) shown in Fig. S(6)⁵³.

To investigate the adsorption kinetics models, five adsorption models (intraparticle diffusion (IPD), Pseudo-first-order (PFO), Pseudo-second-order (PSO), mixed first and second order (MFSO), and Avrami) were investigated for the adsorption of Pb (II) at five initial concentrations (25, 50, 75, 100 and 125 mg/L) over time at pH 2 and dose 25 mg/L. It can be seen the maximum adsorption capacities increase as the initial concentrations of Pb (II) also increase. The adsorption of Pb (II) ions at 25, 50, 75, 100, and 125 ppm onto CuO/PANI show fast adsorption, with the corresponding removal efficiencies 29.3%, 23.78%, 14.3%, 11.8% and 10.9% in the first 30 min. This was followed by a lower removal rate of up to 240 min, and finally, the adsorption achieved the equilibrium phase at 210 min (Fig. 4a–e). The maximum adsorption capacities are 90.86, 171.04, 143.62, 256.39 and 322.844 mg/g, which are corresponding to removal efficiencies of 96.3%, 72.6%, 66.7%, 62.6%, and 59.1%, for the initial Pb (II) concentrations of 25 ppm (Fig. 4a), 50 ppm (Fig. 4b), 75 ppm (Fig. 4c), 100 ppm (Fig. 4d) and 125 ppm (Fig. 4e), respectively.

The fitting of the kinetic models for the Pb (II)@CuO/PANI adsorption system is evaluated based on the agreement of the calculated and experimental adsorption values and the correlation coefficient values. From Fig. 4; Table 1, it can be confirmed that both PFO Avrami models can describe the data at all concentrations of Pb (II) with high correction coefficients (0.97 < R² < 0.99). Although PSO and MFSO models yield high correlation coefficients (0.97 < R² < 0.99), both models can't be used to describe Pb (II)@ CuO/PANI adsorption system since the predicted values of the qₘₐₓ are higher than the calculated one. For the IPD model, there is no agreement between the experimental and the calculated data; in addition, the value of cᵢₚ is equal to zero for all

Where qe and qt (mg g^−1) are the adsorption capacity at equilibrium and time t, respectively. cip (mg g^−1), k1 (min^−1), k2 (g mg^−1 min^−1), k (mg g^−1 min^−1), and kav (min^−1) are the IPD, PFO, PSO, MFSO, and Avrami models constants, respectively. f2 (.) and kip (mg g^−1 min^−1(1/2)) are the MFSO and IPD coefficients, nav (.) is Avrami component.

concentrations under study, which means that the non-linear form is converted to the linear form (qt = kip√t). So, the linear form is further investigated, as shown in Fig (e). The results show that fitting the adsorption data of Pb (II) onto CuO/PANI at 25, 50, 75, 100 and 125 mg/L by plotting qt versus t^0.5 resulted in lines that don't pass through the origin, which suggests that the IPD is not only the rate-limiting step and the adsorption system may be controlled by both porous diffusion and film diffusion.

Adsorption isotherms play a crucial role in investigating the mechanism and affinity of adsorption towards Pb (II)^25. Different models, namely Langmuir, Freundlich, Langmuir-Freundlich, Sips, Toth, Redlich-Peterson, Dubinin–Radushkevich, Khan, Baudu, and Fritz-Schlunder models, were used to analyze the experimental data

of Pb (II) adsorption onto CuO/PANI at a temperature of 298 K. The findings obtained from the non-linear models are displayed in Fig. 7a–j; Table 2.

The data in Supplementary Table 2 illustrate the Pb (II) adsorption capacity of the g-CuO/PANI adsorbent in comparison to previously reported findings. The adsorption capacity for each adsorbent depends on various factors, including the type of pollutant, pH level, adsorption process, time, etc. The green CuO/PANI nanocomposite reported in this study exhibits high and effective adsorption capability for Pb (II).

The reusability of the adsorbent is crucial for ensuring a cost-effective and practical adsorption process. Sequential batch adsorption-desorption tests to determine the recycling potential of the CuO/PANI composite. The experiments involved mixing 15 mg of CuO/PANI with a 10 mg L⁻¹ solution of lead and then stirred this mixture for 6 h until equilibrium. This process was repeated a total of seven successive times as shown in Fig. S(7). The first cycle showed the highest recovery percentage (98.86%) in NaOH while 88.57% in HCl medium. This suggests that the synthesized material have a remarkable regeneration ability to adsorb Pb (II) ions.

Where: qe (mg g⁻¹) is the amount of Pb(II) adsorption at equilibrium, Ce is the equilibrium concentration of Pb(II) in solution, qmax (mg g⁻¹) is the maximum adsorption capacity, KL (L mg⁻¹) is Langmuir isotherm constant, KLF is the equilibrium constant for heterogeneous solid, KF (L mg⁻¹) and n are the coefficients related to adsorption capacity and strength constants of the Freundlich isotherm model, respectively, and KLF is a heterogeneous parameter, and it lies between 0 and 1, ks is Sips isotherm constant; ns is the Sips isotherm model exponent also known as heterogeneity factor, KR and aR are the Redlich-Peterson constants; βR is the exponent that can be lied between 0 and 1, KT (mg g⁻¹) is the constant, aT (mg L⁻¹) is Toth constant, z refers to the degree of heterogeneity of the adsorption systems, while m₁, m₂, K₁, and K₂, are the Fritz-Schlunder parameters.

with a high R² value, and the value of (1/n)<1 suggests that the adsorption process is favourable. Langmuir, Dubinin–Radushkevich and Baudu models failed to predict the kinetic of the Pb (II)@CuO/PANI adsorption since the calculated qmax are higher than the experimental one in addition to the corresponding low values of R² (0.73, 0.62, and 0.73 respectively). Although Langmuir-Freundlich, SiPs, Toth and Redlich-Peterson represent high values of R² Table 2, the calculated qmax according to these models is far from the experimental one. Also, both of Fritz-Schlunder and Khan models failed to describe the Pb (II)@CuO/PANI adsorption system since the predicted values of qmax are much less than the experimental one, even with the corresponding high values of R².

This study represents the green extraction of CuO nanoparticles from Haldinia cordifolia stem bark, which were subsequently composited with polyaniline (PANI) to fabricate an advanced green adsorbent for the removal of lead ions. Various characterization techniques, including FTIR, XRD, SEM-EDS, XPS, and Raman spectroscopy, validated the synthesis of CuO nanoparticles and the resulting nanocomposites. The synthesized nanocomposite exhibits favourable properties, such as a substantial surface area and a high Pb (II) adsorption capacity. Different parameters affecting the adsorption process were optimized, and various isothermal and kinetic models were applied to determine the interaction between the adsorbent and adsorbate, the maximum adsorption capacity (qmax), and the adsorption rate. The qmax for Pb (II) removal was determined to be 295.74 mg g⁻¹ at pH 6. The highly adsorptive nature of the g-CuO/PANI nanocomposite demonstrates its effectiveness as a nanomaterial

for removing Pb (II) from water. However, further research is required to confirm the nanocomposite’s efficacy in removing various heavy metals and to manage the associated risks. The CuO/PANI composite exhibits strong adsorption performance and potential for reuse, making it a promising material for practical applications. However, this study is constrained by certain limitations, including a lack of detailed investigation into the underlying adsorption mechanisms and the effect of temperature on adsorption efficiency. Future research

should focus on addressing these gaps, as well as exploring the nanocomposite’s efficacy in removing a broader spectrum of heavy metals. Such efforts will be critical in optimizing the material’s performance under diverse environmental conditions and expanding its practical applicability.

Data will be made available upon request by the corresponding author.

Received: 30 August 2024; Accepted: 2 December 2024
Published online: 28 December 2024

Hailemariam would like to thank Jimma University, Jimma Institute of Technology, Faculty of Material Sci-

ence & Engineering and Indian Institute of Science, Department of Materials Engineering. Dr. Simranjeet Singh would like to acknowledge DBT HRD Project & Management Unit, Regional Center for Biotechnology, NCR Biotech Science Cluster, Faridabad, Haryana for Research Associateship (DBT-RA). The authors wish to express their gratitude to the Ministry of Education (MoE) for their support under the fellowship MoE-STARS/ STARS-2/2023-0714, dated September 26, 2023.

H.A. and S.S.: Writing, reviewing, editing, and writing the original draft. N.S., and N.A.K.: Data analysis and editing. P.C.R. and F.E.O.: Visualization, Writing, reviewing, editing, and supervision. All authors reviewed the manuscript.

The authors declare no competing interests.

Supplementary Information The online version contains supplementary material available at https://doi.org/10.1038/s41598-024-81970-2.

Correspondence and requests for materials should be addressed to F.E.O. or P.C.R.

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