Deciphering Core-Microbiome Rice Leaf Endosphere Metagenomic Microbiological Analysis Aromatic and Nonaromatic Genotypes

Microbiological Research 246 (2021) 126704
Contents lists available at ScienceDirect
Microbiological Research
journal homepage: www.elsevier.com/locate/micres
Deciphering core-microbiome of rice leaf endosphere: Revelation by

metagenomic and microbiological analysis of aromatic and non-aromatic
genotypes grown in three geographical zones
Mukesh Kumar a, Aundy Kumar a, *, Kuleshwar Prasad Sahu a, Asharani Patel a, Bhaskar Reddy a,
Neelam Sheoran a, Krishnappa Charishmaa, Hosahatti Rajashekara b, Someshwar Bhagat c,
Rajeev Rathour d
a
ICAR-Indian Agricultural Research Institute, New Delhi, India
b
ICAR-Vivekananda Institute of Hill Agriculture, Almora, Uttarakhand, India
c
ICAR-Central Rainfed Upland Rice Research Station (NRRI), Hazaribagh, Jharkhand, India
d
CSK-Himachal Pradesh Agricultural University, Palampur, Himachal Pradesh, India
A R T I C L E I N F O A B S T R A C T
Keywords: We have deciphered the leaf endophytic-microbiome of aromatic (cv. Pusa Basmati-1) and non-aromatic (cv.
Core-microbiome BPT-5204) rice-genotypes grown in the mountain and plateau-zones of India by both metagenomic NGS (mNGS)
Rice leaf and conventional microbiological methods. Microbiome analysis by sequencing V3-V4 region of ribosomal gene
Endophyte
revealed marginally more bacterial operational taxonomic units (OTU) in the mountain zone at Palampur and
Climate zone
Aromatic rice
Almora than plateau zone at Hazaribagh. Interestingly, the rice leaf endophytic microbiomes in mountain zone
mNGS were found clustered separately from that of plateau-zone. The Bray-Curtis dissimilarity indices indicated in
fluence of geographical location as compared to genotype per se for shaping rice endophytic microbiome
composition. Bacterial phyla, Proteobacteria followed by Bacteroidetes, Firmicutes, and Actinobacteria were
found abundant in all three locations. The core-microbiome analysis devulged association of Acidovorax; Aci
netobacter; Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium; Aureimonas; Bradyrhizobium; Burkholderia-
Caballeronia-Paraburkholderia; Enterobacter; Pantoea; Pseudomonas; Sphingomonas; and Stenotrophomonas with
the leaf endosphere. The phyllosphere and spermosphere microbiota appears to have contributed to endophytic
microbiota of rice leaf. SparCC network analysis of the endophytic-microbiome showed complex cooperative and
competitive intra-microbial interactions among the microbial communities. Microbiological validation of mNGS
data further confirmed the presence of core and transient genera such as Acidovorax, Alcaligenes, Bacillus,
Chryseobacterium, Comamonas, Curtobacterium, Delftia, Microbacterium, Ochrobactrum, Pantoea, Pseudomonas,
Rhizobium, Rhodococcus, Sphingobacterium, Staphylococcus, Stenotrophomonas, and Xanthomonas in the rice ge
notypes. We isolated, characterized and identified core-endophytic microbial communities of rice leaf for
developing microbiome assisted crop management by microbiome reengineering in future.
1. Introduction ecological functions of the plant microbiome contributing to plant

growth, development, and survival against biotic and abiotic stresses are
Rice, Oryza sativa L., is colonized by a diverse community of well documented (Turner et al., 2013; Müller and Ruppel, 2014). The
microbiota in its epi and endophytic niches, termed as plant-microbiome endophytic-microbiome is presumed to impact plant growth and
(Leach et al., 2017). The plant microbiome is considered to be the development more directly than epiphytic microbiomes due to their
“second genome” of plants, and the term “plant holobiont” is also sug intimate plant interactions. Presently, metagenomic NGS (mNGS) tools
gested for defining the broad role played by the microorganisms asso are frequently used to investigate plant endophytic-microbiomes which
ciated with plant (Zilber-Rosenberg and Rosenberg, 2008). The natural led to an enhanced understanding of microbiome profiles and functions.
* Corresponding author.
E-mail address: kumar@iari.res.in (A. Kumar).
https://doi.org/10.1016/j.micres.2021.126704
Received 10 October 2020; Received in revised form 20 November 2020; Accepted 6 January 2021
Available online 10 January 2021
0944-5013/© 2021 Elsevier GmbH. This article is made available under the Elsevier license (http://www.elsevier.com/open-access/userlicense/1.0/).
M. Kumar et al. Microbiological Research 246 (2021) 126704
Nevertheless, the taxonomic profiling of plant endophytic microbiomes Palampur, Himachal Pradesh; Almora, Uttarakhand (both represented
has been a challenge owing to plant DNA co-precipitation, and the mountain zone); and Hazaribagh, Jharkhand (plateau zone) were used
consequent nonspecific-amplifications which can obscure the limited in the analysis. While the total endophytic bacterial communities were
endophytic microbial-genomes. Low microbial genomic DNA yield is identified using high throughput mNGS method exploiting V3-V4 region
known to result in low-sequencing depth, and the eventual of ribosomal gene, the culturable bacterial communities were analyzed
poor-resolution of microbial composition. Target specific amplification by adopting microbiological methods on nutrient medium. The primary
primers (V5 -V7 of 16S rRNA genes) coupled with peptide nucleic acid objective of the investigation was to decipher the bacterial diversity and
(PNA) clamps to block nonspecific amplification of plant DNA are now composition of the endophytic microbiome of rice so as to uncover the
used for the metagenome studies (Lundberg et al., 2013; Beckers et al., core-endophytic microbiome of rice leaf.
2016). Besides determining endophytic microbial diversity, the func
tional capabilities are also elucidated using multi-omics tools like 2. Materials and methods
meta-genomics, meta-transcriptomics, meta-proteomics, and metab
olomics (Bäckhed et al., 2005; Ursell et al., 2012). 2.1. Rice genotypes, experimental site, and leaf sample collection
The plant-endophytic microbiomes are known to display both co-
operative and competitive interactive outcomes on plants. While coop 2.1.1. Rice genotypes and experimental site
erating endophytic microbiome shows synergistic effects on plant, the The rice cultivars, Pusa Basmati-1 (aromatic) and BPT-5204 (non-
competing microbiome causes detrimental impacts. Yet another micro aromatic) were grown at three locations in India namely Palampur
bial group, the commensal endophytic microbiomes, has a minimal ef (Himachal Pradesh), Almora (Uttarakhand), and Hazaribagh (Jhark
fect on plant growth (Rodriguez et al., 2009; Hardoim et al., 2015). The hand), which are endemic for rice blast disease. The genotype Pusa
cooperating plant endophytic microbiome is, now, considered as a new Basmati-1 is characterized by long slender, super fine, awned grains
source of bioinoculants to augment agricultural production. The endo with aroma that is a semi-dwarf (85− 95 cm), high yielding early
phytic microbes typically showed a well regulated-multiplication within maturing (130–135 days) basmati rice variety. The genotype BPT-5204
the plant niches modulated by the plant defense system (Sheoran et al., is characterized by medium slender awnless grains without character
2016; Ashajyothi et al., 2020). istic aroma that is a semi-dwarf (80− 90 cm), high yielding moderate
Culturable and unculturable microbiota colonizing endogenous maturing (140–145 days) (Supplementary Table 1). The location, Pal
niches of rice-plants are profiled by several workers (Mano and Mor ampur, is located in Himachal Pradesh, India [GPS coordinates:
isaki, 2008; Sun et al., 2008; Sessitsch et al., 2012; Bertani et al., 2016; 32◦ 05′ 59′′ N, 76◦ 32′ 38′′ E] which is characterized by an altitude of 1275
Sengupta et al., 2017). The role of host & co-host genotypes, macro & m above mean sea level (MSL) with a mean temperature of 22− 23 ◦ C;
micro environmental factors, geographical locations & their climatic 700− 1000 mm precipitation; 60–80 % RH and sunshine hours ranged
factors on rice endophytic microbiome assemblage is reported (Ikeda from 300− 350. The second location, Almora, is situated in Uttarakhand,
et al., 2014; Edwards et al., 2015; Bertani et al., 2016; Wang et al., 2016; India having GPS coordinates 29◦ 35′ 21′′ N, 79◦ 38′ 38′′ E that is charac
Santos-Medellín et al., 2017; Long and Yao, 2020). For instance, rice terized by an altitude of 1633 m above MSL; average temperature
shoot microbiome assembly is significantly influenced by the genotypes 18− 20 ◦ C; 900− 1100 mm precipitation; RH 85 %; 250–300 average
(either Indica or Japonica) as compared to agronomic practices; sunshine hours. The third location, Hazaribagh, is located in Jharkhand,
geographical zones played a key role in shaping the root-microbiome of India (GPS: 23◦ 57′ 32′′ N, 85◦ 22′ 17′′ E) is characterized by an altitude of
rice (Sasaki et al., 2013; Edwards et al., 2015). Plants are known to 607 m above MSL; an average temperature of 26− 28 ◦ C, 400− 600 mm
continuously acquire, assemble, and re-assemble their precipitation; RH of 75 %; and 225–250 average sunshine hours (Fig. 1).
microbial-partners during their growth and developmental transitions. Soil edaphic factors and agronomic practices adopted during the
Rice seeds are reported to contribute to endophytic microbiome of experimentation in three geographical locations are furnished in Sup
mature plants (Kaga et al., 2009; Raj et al., 2019). Furthermore, seeds plementary Table 2. No plant protection chemicals or fungicides of any
play role in the inter-generational and intra-generational transfer of kind were applied during the entire crop period as the three experi
microbiomes to other plant niches such as emerging plumule and mental sites are exclusively maintained for screening rice genotypes for
radicle. the National Blast Resistance Breeding program of India.
Previous microbiome studies have shown association of diverse
bacterial communities with rice endosphere. At the phylum level, 2.1.2. Preparation of leaves for microbiome analysis
abundance of Proteobacteria followed by Firmicutes, Bacteroidetes, and Two-months old leaves collected in pre-sterilized polyethylene bags
Actinobacteria in the rice-endosphere is reported (Walitang et al., 2017). were placed in 4 ◦ C, and transported to the laboratory for downstream
Other phyla such as Cyanobacteria, Verrucomicrobia, Acidobacteria, analysis. The leaf samples were, then, subjected to microbiome analysis
Gemmatimonadetes, and Planctomycetes were also frequently encoun by both mNGS method as well as microbiological approaches.
tered in endogenous tissues (Sessitsch et al., 2012; Bertani et al., 2016).
At lower taxonomic level, association of tissue specific bacterial species 2.2. Total endophytic microbiome
belong to Burkholderia, Herbaspirillum, Rhizobium, Methylobacterium, and
Bacillus in the root (Verma et al., 2004; Mano et al., 2006); Azospirillum 2.2.1. Extraction of the endophytic microbiome
and Herbaspirillum in the shoot (Koomnok et al., 2007; Mano and Mor Leaf (1.0 g each of three replications) excised from the plants were
isaki, 2008) and Pantoea, Bacillus, and Sphingomonas in the seed is re washed thoroughly, four times, in sterilized phosphate buffer saline (50
ported (Mano et al., 2006; Mano and Morisaki, 2008; Kaga et al., 2009). mL) [PBS, g L− 1 NaCl 8; KCl 0.2; Na2HPO4 1.44; KH2PO4 0.24; pH-7.4]
Bacterial communities belonging to Sphingomonas and Methylobacterium amended with 0.1 % tween-20 (PBS-T) to dislodge epiphytic microbes.
are reported as core-endophytic microbiota of rice seeds (Eyre et al., The washed leaf was surface-disinfected by vigorous shaking in 1.25 %
2019). sodium hypochlorite solution (NaOCl) for 2.0 min, and 70 % ethyl
Despite several microbiome-profiling efforts, the major drivers of the alcohol for 30 s followed by four serial washings in PBS-T for 30 s under
endophytic microbiome assemblage of rice are not clearly understood. aseptic condition. The 1.0 mL from the final wash was plated out on
In the present investigation, we have analyzed the endophytic micro nutrient agar medium for sterility check. The surface disinfected leaves
biome of rice-leaf by adopting mNGS and microbiological methods. In were subjected to endophytic microbiome extraction by macerating in
particular, two rice cultivars, non-aromatic BPT-5204, and aromatic pre-sterile pestle-mortar in laminar air flow cabinet. Macerated leaves
Pusa Basmati-1 were planted in three geographical locations repre were collected in 100 mL tubes, vortexed for two minutes, and allowed
senting two contrasting climatic zones of India; rice leaf sampled from for two minutes of gravitational sedimentation, followed by the
2
Fig. 1. Map showing three geographical locations of rice genotypes subjected to endophytic microbiome analysis.
collection of supernatant. Decimal dilutions were prepared using 1.0 mL spectrophotometrically (Nanodrop 2000, ThermoScientific, USA). Later
of clear supernatant for culturable microbiome analysis on bacterio on, the genomic DNA of all the samples was stored at − 20 ◦ C for further
logical medium. The remaining supernatant was centrifuged at 12,000- work.
rpm for one hour to pellet the total microbiome. Thus, obtained pellets
from all three biological replicates were resuspended in 10 mL of sterile 2.2.3. PCR amplification of V3-V4 region of 16S rRNA
deionized water separately for isolation of total genomic DNA. Total genomic DNA extracted by two methods from three biological
replicate per sample were used as a template in PCR amplification of the
2.2.2. Extraction of total genomic DNA of rice endophytic microbiome V3-V4 region of 16S rRNA (V3F:5’CCTACGGGNGGCWGCAG3′ and
The resuspended pellet was divided into two equals of 5.0 mL each for V4R5’ GACTACHVGGGTATCTAATCC3′ ). High fidelity and sensitive
isolation of total genomic DNA. Two different methods viz., Modified Takara PrimeSTAR® Max DNA Polymerase kit was used for the ampli
Cetyl Trimethyl Ammonium Bromide (CTAB) method (Moore et al., fication of the targeted region by following manufacturer’s instruction
1999) and Wizard® genomic DNA Purification Kit (Promega Corporation, (DSS Takara Bio India Pvt. Ltd, New Delhi). PCR amplification was
USA) was adopted for the isolation of genomic DNA. The genomic DNAs, performed in thermal cycler (VapoProtect S pro, Eppendorf India Pvt.
thus, obtained were quality assessed and quantified Ltd, Chennai, India) at initial denaturation at 98 ◦ C/2 min; 35 cycles of
3
denaturation at 98 ◦ C/10 s; annealing at 58 ◦ C/15 s and extension at 72 relative abundance. Bray-Curtis index was used for phylogenetic analysis
◦
C /40 s followed by a final extension at 72 ◦ C/7 min. Amplicons were using the Ward clustering algorithm at the genus level.
checked for integrity in agarose gel, and imaged using the QuantityOne
imaging system (Bio-Rad Laboratories Inc., USA). 2.4. Analysis of culturable microbiome
2.3. Metagenomic profiling of endophytic microbiome 2.4.1. Extraction and isolation of endophytic microbiome
Another portion of surface-disinfected leaf samples were analyzed
2.3.1. Preparation of libraries for sequencing for culturable endophytic microbiome by serial dilution plate technique.
The obtained amplicons were pooled, purified, quality assessed, and Briefly, macerated rice leaves (1.0 g in 100 mL of PBS-T) vortexed (2.0
quantified using Qubit Fluorimeter (V.3.0) according to manufactures min) were allowed to stand (2.0 min) for collection of clear-supernatant,
instructions (ThermoFisher, USA). The purified amplicons (5.0 ng) were and decimal dilutions up to 10− 5 were prepared in PBS-T. Aliquots (1.0
used for metagenome library preparation using the NEBNext Ultra DNA mL) from 10-2 10-3, 10-4, and 10-5 were pour plated in nutrient agar (NA)
Library preparation kit as per manufacturers’ instructions (New England and M9 minimal media supplemented with 2, 3, 5- tetrazolium chloride
Biolabs, USA). The library quantification and quality estimation were (50 mg L-1). The plates were incubated at 28 ◦ C+2 ◦ C for two days. The
performed in Agilent 2200 Tape Station (Agilent, USA). The prepared experiment was conducted with three biological and three technical
library was sequenced in Illumina HiSeq 2500 platform with 2 × 250 replications.
paired-end sequencing chemistry (Illumina, San Diego, CA).
2.4.2. Morphotyping and preservation
2.3.2. Bioinformatics analysis and species annotation The bacterial colonies that appeared on the media were counted
Paired-end reads were subjected to a series of bioinformatics analysis based on size, colour, and morphology. Later on, a single representative
and checks. Briefly, the demultiplexed sequences were quality analyzed colony of each-morphotype was transferred onto nutrient agar plates by
by FastQC v. 0.11.8 (https://www.bioinformatics.babraham.ac.uk/pro streaking for purification, isolation, and preservation. The single colony
jects/fastqc/), poor quality reads were removed before analysis using of all morphotypes was glycerol preserved (30 %) in -20 ◦ C and -80 ◦ C.
Trimmomatic v. 0.39 (http://www.usadellab.org/cms/?page=tr
immomatic). Merging and stitching of reads leading to consensus 2.4.3. Genomic DNA isolation
FASTA sequences (410–450 -bp) with an overlap of 10–240 -bp were Genomic DNA of the individual morphotype was extracted by the
obtained using the FLASH program. The Chimeric sequences were chelex method (Yang et al., 2008). Briefly, 200 μL of 5.0 % chelex was
removed using the de novo chimera removal tool, UCHIME. The curated added to the microcentrifuge tube containing bacterial pellet harvested
and pre-processed consensus sequences were subjected to Operational from overnight grown culture (1.0 mL of 1.0 ODA600nm). The tubes were,
Taxonomic Unit (OTU) picking, OTU clustering, and taxonomic classi then, incubated at 65 ◦ C for one hour. The temperature was raised to 80
fication using the UCLUST program (Similarity Cut-Off = 0.97) available ◦
C during the last five minutes, and then rapidly shifted to -20 ◦ C for five
in QIIME program (https://drive5.com/usearch/manual/uclust_algo. minutes before centrifugation (modification to Yang et al., 2008 pro
html). OTUs with < 5 sequence reads were discarded, and the others tocol) yielded significantly good results. The tubes were centrifuged at
were assigned taxonomic identity in the SILVA database using the 12,000 rpm for ten minutes, and the supernatant containing the DNA
PyNAST program (https://www.arb-silva.de/). Further, taxonomic was collected in the new sterilized microcentrifuge tubes and stored at
classification was performed using the RDP classifier by mapping each -20 ◦ C for further use.
representative sequence against the SILVA OTU database with a 97 %
identity threshold for genus delineation and 98–99 % for species 2.4.4. Genetic diversity and identification of endophytic bacterial
delineation. The bacterial community diversity metrics were calculated communities
and comparative metagenomic analysis was performed to decipher the To decipher the genetic diversity of endophytic bacteria, BOX-PCR
bacterial diversity composition, OTU distribution, abundance, and read based DNA fingerprinting was performed on each morphotype. Reac
counts in the rice leaf endophytic microbiome. tion mixture consisted of Gitschier buffer 1X: DMSO 10 %; BSA 4 μg/μl;
dNTPs 1.25 mM; Taq polymerase 1U; Box primer 10 pmol; Genomic DNA
2.3.3. Comparative endophytic microbiome analysis 100 ng; and mQ water to make up volume to 15 μL. Amplification were
Metagenome reads and the mapped OTUs representing endophytic performed in thermal cycler (ProS, Eppendorf Inc) at temperature con
bacterial genera of aromatic (Pusa Basmati-1) and non-aromatic (BPT- ditions consisted of an initial denaturation step at 95 ◦ C for 5 min; 94 ◦ C
5204) genotypes were compared across three locations (Palampur, for 3 s, followed by 35 cycles of 94 ◦ C for 1.0 min, 50 ◦ C for 1.0 min and 65
Almora, and Hazaribagh). The V3-V4 sequences mapped with known ◦
C for 8 min followed by one cycle of 65 ◦ C for 16 min, and the final
bacterial taxa were considered and any unknown, or unidentified, or cooling at 8 ◦ C (Kumar et al., 2004). Then PCR products were resolved in
unmapped reads and OTUs were ignored and discarded. Reads were 1.0 % agarose gel at 30 V for 12 h to visualize the amplicons. Isolates
processed and analyzed using scripts and programs from QIIME (Capor showing identical amplicon profiles were considered as duplicates, and a
aso et al., 2010) and Microbiome Analyst (Dhariwal et al., 2017). representative was, eventually, used in the further work. The prokaryotic
Microbiome Analyst is a comprehensive statistical, visual, and universal primers [27F:5’-AGAGTTTGATCCTGGCTCAG-3′ and
meta-analysis tool for microbiome data that utilizes the Microbiome 1492R:5’-GGTTACCTTGTTACGACTT-3′ ] were employed to amplify the
Analyst R package for statistical analysis and graphical outputs. QIIME 1465 bp region of 16S rRNA gene sequence. The reaction mixture for PCR
script, alpha_rarefaction.py, was used for making rarefaction curves along amplification was consisted of Promega PCR buffer 1X; MgCl2 1.5 mM;
with α-diversity indices. Microbiome Analyst was also utilized for the dNTPs 200 μM; Taq polymerase 1.5U; Forward primer 10 pmol; Reverse
determination of β-diversity, bacterial network, and core-microbiome primer 10 pmol; genomic DNA 100 ng; and mQ water to make up the
analysis (Dhariwal et al., 2017). Data processing including data integ volume to 50 μL. The amplification was performed in a thermal cycler
rity check, data filtering, and data normalization by total sum scaling with temperature conditions of an initial denaturation step at 95 ◦ C for 5
(TSS) method were performed before diversity estimation. PCoA was min followed by 35 cycles of 94 ◦ C for 1 min, annealing at 58 ◦ C for 1 min
performed using ANOSIM based on the Bray-Curtis method in Micro and extension at 72 ◦ C for 90 s followed by one cycle of 72 ◦ C for 10 min,
biome Analyst. Bacterial genera co-occurrence network was inferred and the final cooling at 4 ◦ C (Stackebrandt et al., 1993; Sheoran et al.,
using the SparCC method with a significance of P < 0.05 and correlation 2015; Munjal et al., 2016). Then, the PCR products were resolved in 1.0 %
coefficient R > 0.60 or <-0.6. Genotype and location-wise cor agarose gel at 80 V for 120 min, which was subsequently documented
e-microbiome were analyzed at 10 % sample prevalence and 0.01 % using image analysis system (QuantityOne, BioRad, USA).
4
2.4.5. Sequencing and analysis Table 1

16S rRNA gene amplicon (1465-bp) was eluted from agarose gel and α-diversity indices for endophytic microbiome of rice genotypes grown in three
purified using SV gel and PCR clean up system as per manufacturer’s locations
instructions (Promega Corporation, USA). The purified amplicons were Sample Filtered Total Chao1 Shannon Observed
sequenced bi-directionally by Sanger’s dideoxy chain termination Library filtered species
method to obtain maximum coverage of gene sequences. Thus obtained size OTUs
sequence reads were contigs assembled using DNA Baser (Version 1 PLM-Pusa 79,377 187 184.98 3.27 173
5.15.0), and end-trimmed in CLC Sequence Viewer (Version 8) and Basmati-1
2 PLM-BPT- 60,388 149 152.89 2.10 136
species identified by closest match in NCBI (https://www.ncbi.nlm.nih.
5204
gov/). 16S rRNA gene sequences of all isolates were assigned accession 3 ALM-Pusa 114,283 152 126.12 2.08 126
numbers, and published in GenBank database (https://www.ncbi.nlm. Basmati-1
nih.gov/https://www.ncbi.nlm.nih.gov/nucleotide/). 4 ALM-BPT- 79,072 119 109.05 2.42 101
5204
5 HZB-Pusa 53,815 82 81.9 2.45 79
2.5. Microbiological validation of mNGS mapped OTUs Basmati-1
6 HZB-BPT- 68,646 77 73.67 2.24 71
Cultured, isolated and purified endophytic bacterial isolates identi 5204
fied at genus level, and OTUs mapped from mNGS microbiome reads of α -diversity indices for endophytic microbiome of rice genotypes grown in three
two rice genotypes grown in three geographical locations were locations as measured by Chao1, Shannon and Observed species indices at p <
compared, and the frequency (%) of OTUs and isolates occurrence was 0.05.
estimated using the formula given below, and tabulated.
Samples positive for a bacterial genus Family level distribution of endophytic bacteria indicated the abun
Frequency(%) = × 100 dance of Enterobacteriaceae (68–73 %). Other over-represented families
Total number of samples
were Burkholderiaceae, Rhizobiaceae, Sphingobacteriaceae, Xantho
monadaceae, and Paenibacillaceae in both the genotypes. Genus level
3. Results
annotation reveals the high abundance and diversity of Enterobacter
(68–73 %) followed by Flavobacterium, Pantoea, Pseudomonas, Sphingo
3.1. Metagenomic profiling of endophytic microbiome of rice genotypes,
bacterium, and Stenotrophomonas in both the genotypes. Both the rice
and diversity
genotypes displayed nearly identical profiles of most of the bacterial
genus except for Aerococcus, Facklamia, Kineococcus, and Nocardioides
Endophytic microbiome profiles of two rice genotypes grown in
found associated only with BPT-5204. Lachnoclostridium, Leucobacter,
three locations such as Palampur -Pusa Basmati-1 (PLM-PB1), Palampur
Nubsella, Ochrobactrum Pleomorphomonas, Prosthecobacter, Saccha
-BPT-5204 (PLM-BPT-5204), Almora -Pusa Basmati-1 (ALM-PB1),
ribacillus, and Shinella were observed in Pusa Basmati-1 (Supplementary
Almora -BPT-5204 (ALM-BPT-5204), Hazaribagh -Pusa Basmati-1 (HZB-
Table 5).
PB1) and Hazaribagh -BPT-5204 (HZB-BPT-5204) was deciphered using
mNGS and microbiological tools (Fig. 1). The genomic DNAs isolated by
3.2.2. Almora, Uttarakhand
commercial-kit, and a lab-standardized CTAB protocol from three bio
A total of 152 and 119 endophytic bacterial operational taxonomic
logical replicate per sample were used to minimize biases arising from a
units (OTUs) were observed in rice genotypes with a nearly identical
single-method (Supplementary Table 3). PCR amplicons of conserved
α-diversity index (Table 1). OTUs belongs to Proteobacteria (52-56 %)
V3-V4 region (430 -bp) from all six genomic DNA per sample were
followed by Actinobacteria and Bacteroidetes were found dominant in
pooled, purified and sequenced followed by bioinformatic analysis for
aromatic and non-aromatic types (Supplementary Table 6). Bacterial
endophytic microbiome composition and diversity (Supplementary
classes α -proteobacteria (27–31 %), ɣ -proteobacteria (19–27 %), and
Fig. 1); metagenome sequencing of the V3-V4 region yielded 75.7–176.8
Actinobacteria (12–16 %) were predominant in both the genotypes.
Mb data (Supplementary Table 4). Mapping of high quality filtered reads
Rhizobiales (14–16 %), Sphingomonadales (10–12 %), Pseudomona
onto microbial databases culminated in the identification of operational
dales (6–8 %), and Enterobacteriales (4–9 %) were the major orders
taxonomic units (OTUs) in the range of 77–187 across the six endophytic
observed in rice genotypes; Family-wise distribution of endophytic
microbiome samples. The Shannon diversity index ranged from 2.08 to
bacteria in rice genotypes indicated the dominance of Sphingomona
3.27; and Chao1 from 73.67–184.98 while observed species is in the
daceae (11–12 %) followed by Enterobacteriaceae, Rhizobiaceae, Bei
range of 71–173 (Table 1; Supplementary Fig. 2).
jerinckiaceae, Burkholderiaceae, Moraxellaceae, and
Xanthomonadaceae. The abundance of major genera such as Acidovorax,
3.2. Diversity, abundance, and distribution of rice endophytic bacteria Acinetobacter, Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium,
Methylobacterium, Novosphingobium, Pantoea, Pseudomonas, Sphingomo
3.2.1. Palampur, Himachal Pradesh nas, and Xanthomonas was observed in both the genotypes. Whereas
A total of 187 and 149 endophytic bacterial operational taxonomic Chryseobacterium, Hymenobacter, Legionella, Mycobacterium, Quadri
units (OTUs) were observed in rice genotypes with high α -diversity sphaera, Ralstonia, and Rhizorhapis were uniquely found in Pusa Basmati-
indices in Pusa Basmati-1 (Table 1). OTUs belong Proteobacteria (68–69 1, Arsenophonus was found in BPT-5204.
%) were found over-represented and abundant (81–85 %) followed by
Bacteroidetes and Firmicutes among the endogenous bacterial phyla of 3.2.3. Hazaribagh, Jharkhand
rice genotypes. Class-level endophytic bacteria revealed the abundance A total of 82 and 77 endophytic bacterial operational taxonomic
of ɣ- proteobacteria over other classes of bacteria. Both the rice geno units (OTUs) were mapped from both the rice genotypes (Table 1).
types shared nearly similar bacterial class profiles; however, Verruco Phylum Proteobacteria was found abundant (10–70 %) and diverse
microbiae was not observed in non-aromatic from Palampur. For (62–67 %) followed by Firmicutes, Bacteroidetes, and Actinobacteria
bacterial order, Enterobacteriales (68–73 %) was found abundant over (Supplementary Table 7). Class level distribution revealed the pre
other bacterial communities. Flavobacteriales, Sphingobacteriales, dominance of class ɣ -proteobacteria (50–58 %) in both genotypes.
Pseudomonadales, β-proteobacteriales, and Xanthomonadales were also Pseudomonadales (28–31 %) and β -proteobacteriales (10 % in both)
found predominant in both the genotypes. While Kineosporiales was were the major orders of bacteria observed in both genotypes. The
found only in BPT-5204, Pusa Basmati-1 showed Verrucomicrobiales.
5
predominance of Moraxellaceae (16–20 %) followed by Burkholder revealed a consistent association of certain bacterial communities in all
iaceae, Pseudomonadaceae, and Enterobacteriaceae were observed in three geographical locations. Acidovorax, Acinetobacter, Aeromonas,
both genotypes. Genus level distribution of endophytic bacteria in rice Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium, Bradyrhizobium,
genotypes showed abundance of Acinetobacter, Pseudomonas, Sphingo Burkholderia-Caballeronia-Paraburkholderia, Pantoea, Pseudomonas,
monas, Acidovorax, Pantoea, and Sphingobacterium in both the genotypes. Sphingobacterium, Sphingomonas, and Stenotrophomonas were observed in
Both the rice genotypes displayed nearly identical profiles of the bac all locations in both the genotypes (Table 3). The data further revealed
terial genus except for Luteibacter found only in BPT-5204. location-specific genus such as Aureimonas, Bacillus, Corynebacterium,
Clostridium, Comamonas, Curvibacter, Enterococcus, Exiguobacterium,
3.3. Comparative analysis of endophytic microbiome Flavobacterium, Facklamia, Hafnia, Obesumbacterium, Herbaspirillum,
Kosakonia, Micrococcus, Mucilaginibacter, Nakamurella, Novosphingobium,
The principal coordinate analysis revealed no significant differences and Paenibacillus found in only one location.
for endophytic microbiome profiles between the aromatic and non-
aromatic genotypes grown in a particular geographical location as 3.4. Core microbiome and correlation network analysis
indicated by the ANOSIM indicator (R = -0.33333; p < 1) (Fig. 2A).
However, significant differences for the endophytic microbiome profile Core-bacterial genera analysis based on prevalence and relative
were observed for the three locations as revealed by the ANOSIM results abundance cut-off value at 10 % and 0.01 %, respectively revealed
(R: 1; p-value < 0.066667) (Fig. 2B). The endophytic microbiome pro consistent association of Acinetobacter, Delftia, Enterobacter, Fla
files of the rice genotypes grown in same agroclimatic zone appear to be vobacterium, Pantoea, Pseudomonas, Sphingobacterium, and Steno
shared but divergent from that of other agro-climatic zones (Fig. 3A). trophomonas in Pusa Basmati-1 genotype in all three locations. Similarly,
The analysis further showed that the endophytic microbiome of rice six-genera Acidovorax, Acinetobacter, Allorhizobium-Neorhizobium-
grown in mountain zone was found clustered in large group, and that of Pararhizobium-Rhizobium, Enterobacter, Pantoea, and Sphingomonas
plain zone formed a separate cluster (Fig. 3B). were found to be a part of the core microbiome of BPT-5204 (Fig. 4). The
geographical location specific core microbiome was also identified. The
3.3.1. Rice genotypes mountain zone core-microbiome showed association of Acidovorax,
Comparative analysis of the endophytic microbiome of both the ge Acinetobacter, Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium,
notypes revealed the occurrence of shared 11 bacterial genera in both Enterobacter, Delftia, Flavobacterium, Pantoea, Pseudomonas, Sphingo
the genotypes across all locations. Among them, Acinetobacter, Allo bacterium, Sphingomonas, and Stenotrophomonas; plain zone showed one
rhizobium-Neorhizobium-Pararhizobium-Rhizobium, Enterobacter, Pseudo genus Acinetobacter (Fig. 5). Microbial genera co-occurrence network
monas, Sphingomonas, and Stenotrophomonas were found at high inferred using the SparCC method with a significance level of P < 0.05
frequency and diversity in the Pusa Basmati-1 genotype (Table 2). and correlation coefficient R > 0.60 or < -0.6 revealed complex co-
Similarly, BPT-5204 harboured Acinetobacter, Methylobacterium, Pan operative and competing interaction among the bacterial communities
toea, Pseudomonas, and Sphingomonas in high numbers. The data further (Supplementary Fig. 3; Supplementary Table 8).
showed genotype-specific genera such as Brevundimonas, Chrys
eobacterium, Leucobacter, Paenibacillus, Shinella, and Sphingobacterium in 3.5. Culturable endophytic microbiome analysis of rice genotypes
Pusa Basmati-1, and Aerococcus, Devosia, Facklamia, Herbaspirillum,
Methylobacterium, and Xanthomonas in BPT-5204. 3.5.1. Enumeration, characterization, and identification of rice endophytic
microbiome
3.3.2. Geographical locations Endogenous bacterial population count ranged from 2.0 to 5.0 Log
Comparative endophytic microbiome analysis in three locations CFU g− 1 in aromatic and non-aromatic genotypes (Supplementary
Fig. 2. PCoA plot based on Bray Curtis analysis showing significant difference in bacterial community structure among A. rice genotypes (ANOSIM; R: -0.33333; p <
1) and B. diverse geographical locations (ANOSIM; R: 1; p-value < 0.066667).
6
Fig. 3. Clustering of rice endophytic microbiome by Bray-Curtis non-phylogenetic distance measure A: Genotype; B. Location.
Table 9; 10, 11; Supplementary Fig. 4). Shannon-Wiener score indicated (57) and Hazaribagh (50) were isolated, purified and preserved which
marginally high total endophytic bacterial diversity for Palampur as showed nearly identical Shannon-Wiener diversity index. The 162
compared to Almora and Hazaribagh (Supplementary Table 12). A total morphotypes were, further, grouped into distinct 92 isolates based on
of 162 distinct morphotypes of bacteria from Palampur (55), Almora BOX-PCR amplicon profiling (Supplementary Figs. 5a, 5b, 5c). Isolates
Table 2
Genus level abundance and distribution of genotype specific bacterial communities.
Aromatic rice Non-aromatic #Frequency (%)
Genus (OTUs) (Pusa Basmati-1) Total (BPT-5204) Total
PLM ALM HZB PLM ALM HZB
*Bacterial genera found in both Pusa Basmati-1 and BPT-5204

Acidovorax 2 2 2 6 3 1 2 6 100
Acinetobacter 6 5 15 26 4 5 11 20 100
Allorhizobium- Neorhizobium-Pararhizobium-Rhizobium 6 4 4 14 3 4 2 9 100
Aureimonas 2 2 1 5 2 1 1 4 100
Bradyrhizobium 2 2 2 6 2 2 2 6 100
Burkholderia-Caballeronia-Paraburkholderia 1 2 2 5 2 2 2 6 100
Enterobacter 12 2 2 16 3 2 1 6 100
Pantoea 3 3 2 8 7 6 2 15 100
Pseudomonas 5 3 5 13 3 4 6 13 100
Sphingomonas 5 7 2 14 5 5 4 14 100
Stenotrophomonas 6 6 4 16 3 2 2 7 100
**Bacterial genera found only in Pusa Basmati-1
Brevundimonas 2 2 2 6 – – – – 50
Chryseobacterium 5 2 2 9 – – – – 50
Leucobacter 2 2 1 5 – – – – 50
Paenibacillus 6 1 1 8 – – – – 50
Shinella 2 2 2 6 – – – – 50
Sphingobacterium 5 1 2 8 – – – 50
**Bacterial genera found only in BPT-5204
Aerococcus – – – – 2 2 1 5 50
Devosia – – – – 2 1 1 4 50
Facklamia – – – – 2 1 2 5 50
Herbaspirillum – – – – 4 2 1 7 50
Methylobacterium – – – – 4 4 2 10 50
Xanthomonas – – – – 2 2 1 5 50
*Bacterial genera found associated with both genotype in all three locations.
**Bacterial genera found associated only with either aromatic or non-aromatic rice in all three locations.
#Frequency (%) = (Samples positive for a bacterial genus / Total number of samples) ×100.
7
showed identical amplicon profiles were considered as duplicates, and aromatic cultivars. Interestingly, the aromatic cultivar showed pres
one representative isolate was used for further investigation. 16S rRNA ence of Achromobacter, Acinetobacter, Agrobacterium, Pseudacidovorax,
gene sequence-based species identification revealed the high-frequency and Rhodococcus, and the non-aromatic type harboured Bhargavaea,
occurrence of genera such a Acidovorax (6), Bacillus (5), Curtobacterium Massilia, Leucobacter, and Serratia.
(10), Microbacterium (8), Pantoea (7), Pseudomonas (12), Staphylococcus
(7), and Stenotrophomonas (5) in rice endosphere, and many other 3.7. Microbiological validation of mNGS mapped OTUs
genera (Table 4).
A total of 13 bacterial genera such as Acidovorax, Acinetobacter, Ba
cillus, Chryseobacterium, Comamonas, Delftia, Pantoea, Pseudomonas,
3.6. Comparative culturable endophytic microbiome analysis Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium, Serratia, Sphingo
bacterium, Stenotrophomonas, and Xanthomonas were the most repre
Geographical location wise comparative analysis indicated frequent sented among the cultured bacterial communities in the aromatic and
occurence of Curtobacterium, Pseudomonas, Staphylococcus, and Steno non-aromatic genotypes in all three experimental sites. Comparative
trophomonas across three locations (Fig. 6). Bacterial genera such as analysis of mNGS mapped OTUs with cultured microbiome showed
Acidovorax, Alcaligenes, Bacillus, Chryseobacterium, Comamonas, Curto consistence association of these 13 bacterial genera that validated our
bacterium, Delftia, Microbacterium, Ochrobactrum, Pantoea, Pseudomonas, mNGS microbiome analysis (Table 5; Figs. 7,8 )
Rhizobium, Rhodococcus, Sphingobacterium, Staphylococcus, Steno
trophomonas, and Xanthomonas were found in both aromatic and non-
Table 3
Genus level abundance and distribution of rice endophytic bacterial communities in three geographical locations.
Palampur Almora Hazaribagh
Genus (OTU) Total #Frequency
Pusa Basmati-1 BPT-5204 Pusa Basmati-1 BPT-5204 Pusa Basmati-1 BPT-5204
*Bacterial genera found in all three locations

Acidovorax 3 4 2 2 3 3 17 100
Acinetobacter 6 4 6 6 17 13 52 100
Aeromonas 1 2 2 1 1 1 5 100
Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium 5 4 4 4 2 2 21 100
Bradyrhizobium 2 2 2 2 2 2 12 100
Burkholderia-Caballeronia-Paraburkholderia 1 1 2 2 2 2 10 100
Pantoea 5 5 3 3 2 2 20 100
Pseudomonas 4 2 4 4 9 9 32 100
Sphingobacterium 5 3 1 1 2 2 14 100
Sphingomonas 4 6 7 5 2 4 28 100
Stenotrophomonas 7 6 2 2 2 2 21 100
**Bacterial genera found only two of three location
Aeromicrobium 1 1 2 2 – – 6 66.7
Brevundimonas 2 2 2 2 – – 8 66.7
Devosia 2 2 3 1 – – 8 66.7
Methylobacterium 1 4 7 6 – – 18 66.7
Xanthomonas 2 2 3 2 – – 9 66.7
Chryseobacterium 5 3 – – 2 2 12 66.7
Delftia 2 1 – – 2 1 6 66.7
Enterobacter 11 6 – – 1 1 19 66.7
**Bacterial genera found in only one location
Aureimonas 2 2 – – – – 4 33.3
Clostridium-sensu-stricto-1 2 2 – – – – 4 33.3
Comamonas 4 4 – – – – 8 33.3
Curvibacter 2 2 – – – – 4 33.3
Enterococcus 1 1 – – – – 2 33.3
Flavobacterium 3 1 – – – – 4 33.3
Hafnia-Obesumbacterium 2 2 – – – – 4 33.3
Herbaspirillum 3 4 – – – – 7 33.3
Kosakonia 3 2 – – – – 5 33.3
Paenibacillus 6 4 – – – – 10 33.3
Pedobacter 2 2 – – – – 4 33.3
Raoultella 1 1 – – – – 2 33.3
Schumannella 1 1 – – – – 2 33.3
Serratia 2 1 – – – – 3 33.3
Corynebacterium-1 – – 2 2 – – 4 33.3
Kineococcus – – 2 2 – – 4 33.3
Micrococcus – – 2 1 – – 3 33.3
Mucilaginibacter – – 2 2 – – 4 33.3
Nakamurella – – 2 1 – – 3 33.3
Novosphingobium – – 4 2 – – 6 33.3
Sphingobium – – 2 2 – – 4 33.3
Spirosoma – – 2 1 – – 3 33.3
Bacillus – – – – 3 2 5 33.3
Exiguobacterium – – – – 2 2 4 33.3
Facklamia – – – – 2 2 4 33.3
Subtotal 103 89 70 58 56 52
428
Grand total 192 128 108
*Bacterial genera found associated with all three locations ; **Bacterial genera found associated with one or two locations.
#Frequency (%) =(Samples positive for a bacterial genus / Total number of samples) × 100.
8
Fig. 4. Core-endophytic microbiome of rice genotypes as identified by MicrobiomeAnalyst using the parameters sample prevalence (10 %) and relative abundance
(0.1 %).
4. Discussion as root endosphere niche (Edwards et al., 2015; Eyre et al., 2019; Raj
et al., 2019; Roman-Reyna et al., 2020; Wang et al., 2020).
Endophytic microbiota including bacteria communities colonize Bray-Curtis principal coordinate analysis revealed no significant
plant interior without causing any visible harm to their host plant, and differences for endophytic microbiome profiles between the aromatic
are reported to play ecological role in plant growth, development, and non-aromatic genotypes grown in a particular geographical location
fitness, and protection against environmental stresses (Aravind et al., as indicated by the ANOSIM indicator. Conversely, significant differ
2009; Farrar et al., 2014; Truyens et al., 2015; Eke et al., 2019). The ences for the endophytic microbiome profile were observed among the
endophytic bacteria complete their life cycle, either in part or full, and three geographical locations representing two diverse agro-ecological
obtain essential growth factors from the plant intercellular spaces zones. Thus, the dissimilarity analysis confirmed the significant influ
(Bacon and Hinton, 2007). The endophytic microbiome of rice was ence of geographical location over genotype per se to shape endogenous
explored by the combinatorial approach involving mNGS and microbi microbiome profiles of rice. In other words, endophytic microbiome
ological approaches. To avoid inadvertent biases arising from a single composition of rice genotypes cultivated in an agroclimatic zone
DNA isolation method, we have deployed two-independent extraction appeared to be convergent but divergent from that of another agro
methods for nucleic acid isolation from the microbial communities climatic zone. The results are in agreement with the reports of Whitaker
residing in rice endogenous tissues. It is strongly recommended to use a et al. (2018) who concluded significant impact of the environment on
toolbox of technologies aimed at reducing bias resulting from each microbiome composition in plants. While the endophytic rice micro
technology and result in a more complete view on the biological system biome profiles from Mountain zones in Palampur and Almora were
as a whole (Berg et al., 2020). A combination of several methods is ex found clustered in one group, the endophytic rice microbiome of
pected to elucidate deeper-insights into microbial functioning and for Plateau-Zone, Hazaribagh was clustered separately. In the agricultural
possible exploitation in crop production systems. Conserved 16S rRNA system, both inter-seasonal long-term and intra-seasonal short-term
gene fragments generated using mNGS methods were annotated using cultivation practices are expected to play role in shaping endophytic
microbial databases, and microbial contents were determined and microbiome assembly and composition in plants (Zhang et al., 2013;
expressed as OTUs. Rice genotypes, Pusa Basmati-1 and BPT-5204 Long and Yao, 2020). It is now postulated that plant microbiome
grown in three-geographical locations showed different endophytic structure and composition are driven by complex interactions between
microbial diversity indices in the leaf tissues as revealed by Shannon and hosts, microbes, and associated environmental factors such as climate,
Chao1 diversity indices. The rice leaf samples from mountain zone, soil, cultivation practices (Dastogeer et al., 2020). Nevertheless, Whi
Palampur and Almora, showed marginally more OTUs than of plateau at taker et al. (2018) observed that the environmental factors, and not the
Hazaribagh. The rice leaf endosphere harbour either comparable or low- host genotype are the major drivers of the endophytic microbiome of
bacterial count as well as diversity compared to other plant niches such switchgrass. Among them, climate and geographical locations are the
9
Fig. 5. Core-endophytic microbiome at diverse geographical locations identified by MicrobiomeAnalyst using the parameters sample prevalence (10 %) and relative
abundance (0.1 %).
major drivers of plant microbiome assembly and composition with the and α-Proteobacteria classes, followed by Firmicutes, Bacteroidetes,
potential to alter the microbiome function on a temporal scale. Coupled Verrucomicrobia, and Actinobacteria are earlier reported in rice
with the existing reports, our data is suggestive of the major influence of endogenous niches (Ikenaga et al., 2003; Hernández et al., 2015; Wu
geographical-location over host-genotypes for endophytic microbiome et al., 2018; Eyre et al., 2019; Roman-Reyna et al., 2019; Jha et al.,
assemblage in the leaf endogenous niches of rice. 2020). However, Sun et al. (2008) reported diverse bacterial commu
Qualitatively, Proteobacteria followed by Bacteroidetes, Firmicutes, nities to belong to α, β, ɣ, δ, and ε -subclasses of the Proteobacteria,
and Actinobacteria were found predominant among the endophytic Cytophaga/Flexibacter/Bacteroides (CFB) phylum, and low G + C
bacterial communities of rice genotypes grown in all three geographical gram-positive bacteria, Deinococcus-Thermus, Acidobacteria, and
locations. The high-frequency occurrence of Proteobacteria especially γ- Archaea in rice endogenous tissues. At lower taxa-level, diverse bacterial
10
Table 4 Table 4 (continued )

16S rRNA gene sequences based identification of endophytic bacterial species Isolates *Species by closest Geographical Genotype **GenBank
isolated from basmati and non-basmati rice genotypes grown in three locations match origin origin Accession
in India.
OsEnb-
Isolates *Species by closest Geographical Genotype **GenBank PLM-
match origin origin Accession L30
OsEnb- Acidovorax facilis Palampur Basmati and MN889265 OsEnb- Microbacterium Almora Basmati Rice MN889313
PLM- Non Basmati ALM- laevaniformans
L27 Rice A19
OsEnb- Bacillus circulans Palampur Basmati and MN889256 OsEnb- Microbacterium sp. Almora Basmati Rice MN889310
PLM- Non Basmati ALM-
L14 Rice A12
OsEnb- Bacillus siamensis Palampur Basmati and MN889269 OsEnb- Microbacterium sp. Almora Basmati Rice MN889304
PLM- Non Basmati ALM-
L34 Rice A5
OsEnb- Curtobacterium Palampur Basmati and MN889264 OsEnb- Ochrobactrum Hazaribagh Basmati Rice MN889372
PLM- albidum Non Basmati HZB- pseudogrignonense
L25.1 Rice E1
OsEnb- Curtobacterium Palampur Basmati and MN889252 OsEnb- Pantoea agglomerans Almora Basmati Rice MN889303
PLM- citreum Non Basmati ALM-
L11 Rice A4
OsEnb- Curtobacterium Palampur Basmati and MN889268 OsEnb- Pantoea ananatis Almora Basmati Rice MN889312
PLM- citreum Non Basmati ALM-
L32 Rice A17
OsEnb- Pantoea ananatis Palampur Basmati and MN889260 OsEnb- Pantoea eucrina Palampur Basmati Rice MN889247
PLM- Non Basmati PLM-
L19 Rice L2
OsEnb- Rhizobium sp. Palampur Basmati and MN889262 OsEnb- Pantoea vagans Palampur Basmati Rice MN889270
PLM- Non Basmati PLM-
L22 Rice L36
OsEnb- Achromobacter Hazaribagh Basmati Rice MN889379 OsEnb- Pseudacidovorax Almora Basmati Rice MN889309
HZB- xylosoxidans ALM- intermedius
E20 A11
OsEnb- Acinetobacter Almora Basmati Rice MN889306 OsEnb- Pseudacidovorax Almora Basmati Rice MN889302
ALM- baumannii ALM- intermedius
A7 A3
OsEnb- Acinetobacter baylyi Almora Basmati Rice MN889307 OsEnb- Pseudomonas Hazaribagh Basmati Rice MN889376
ALM- HZB- geniculata
A8 E12
OsEnb- Agrobacterium Palampur Basmati Rice MN889248 OsEnb- Pseudomonas Almora Basmati Rice MN889311
PLM- larrymoorei ALM- parafulva
L5 A15
OsEnb- Alcaligenes faecalis Hazaribagh Basmati Rice MN889378 OsEnb- Pseudomonas Almora Basmati Rice MN889308
HZB- ALM- parafulva
E19 A9
OsEnb- Alcaligenes faecalis Hazaribagh Basmati Rice MN889375 OsEnb- Pseudomonas Almora Basmati Rice MN889314
HZB- ALM- psychrotolerans
E4 A21
OsEnb- Bacillus licheniformis Palampur Basmati Rice MN889250 OsEnb- Pseudomonas stutzeri Almora Basmati Rice MN889316
PLM- ALM-
L10 A30
OsEnb- Bacillus velezensis Palampur Basmati Rice MN889253 OsEnb- Pseudomonas stutzeri Almora Basmati Rice MN889317
PLM- ALM-
L12 A32
OsEnb- Chryseobacterium Almora Basmati Rice MN889305 OsEnb- Rhodococcus Palampur Basmati Rice MN889263
ALM- endophyticum PLM- yunnanensis
A6 L24
OsEnb- Chryseobacterium sp. Almora Basmati Rice MN889315 OsEnb- Sphingobacterium sp. Palampur Basmati Rice MN889272
ALM- PLM-
A22 L38
OsEnb- Comamonas koreensis Hazaribagh Basmati Rice MN889377 OsEnb- Staphylococcus Palampur Basmati Rice MN889246
HZB- PLM- arlettae
E17 L1
OsEnb- Curtobacterium Palampur Basmati Rice MN889258 OsEnb- Staphylococcus Palampur Basmati Rice MN889255
PLM- luteum PLM- arlettae
L16 L13
OsEnb- Curtobacterium Palampur Basmati Rice MN889259 OsEnb- Staphylococcus Palampur Basmati Rice MN889271
PLM- luteum PLM- arlettae
L18 L37
OsEnb- Curtobacterium Palampur Basmati Rice MN889249 OsEnb- Staphylococcus Hazaribagh Basmati Rice MN889374
PLM- luteum HZB- epidermidis
L7 E3
OsEnb- Delftia tsuruhatensis Hazaribagh Basmati Rice MN889373 OsEnb- Stenotrophomonas Palampur Basmati Rice MN889267
HZB- PLM- maltophilia
E2 L31
Microbacterium Palampur Basmati Rice MN889266 OsEnb- Xanthomonas Almora Basmati Rice MN889301
hydrothermale ALM- sacchari
A1
(continued on next page)
11
Table 4 (continued ) Table 4 (continued )

Isolates *Species by closest Geographical Genotype **GenBank Isolates *Species by closest Geographical Genotype **GenBank
match origin origin Accession match origin origin Accession
OsEnb- Acidovorax avenae Almora Non Basmati MN889350 OsEnb- Pseudomonas Almora Non Basmati MN889345
ALM- Rice ALM- parafulva Rice
C26 C17
OsEnb- Acidovorax avenae Almora Non Basmati MN889354 OsEnb- Pseudomonas Almora Non Basmati MN889344
ALM- Rice ALM- psychrotolerans Rice
C35 C15
OsEnb- Acidovorax cattleyae Palampur Non Basmati MN889286 OsEnb- Pseudomonas Almora Non Basmati MN889340
PLM- Rice ALM- psychrotolerans Rice
L69 C2
OsEnb- Acidovorax oryzae Palampur Non Basmati MN889281 OsEnb- Pseudomonas putida Hazaribagh Non Basmati MN889396
PLM- Rice HZB- Rice
L59 G20
OsEnb- Acidovorax wautersii Almora Non Basmati MN889355 OsEnb- Pseudomonas stutzeri Almora Non Basmati MN889349
ALM- Rice ALM- Rice
C36 C24
OsEnb- Alcaligenes faecalis Hazaribagh Non Basmati MN889387 OsEnb- Rhizobium pusense Palampur Non Basmati MN889294
HZB- Rice PLM- Rice
G1 L80
OsEnb- Bacillus altitudinis Palampur Non Basmati MN889296 OsEnb- Serratia marcescens Hazaribagh Non Basmati MN889394
PLM- Rice HZB- Rice
L88 G12
OsEnb- Bhargavaea Hazaribagh Non Basmati MN889398 OsEnb- Sphingobacterium Hazaribagh Non Basmati MN889397
HZB- cecembensis Rice HZB- multivorum Rice
G25 G23
OsEnb- Chryseobacterium Almora Non Basmati MN889348 OsEnb- Sphingobacterium Hazaribagh Non Basmati MN889391
ALM- culicis Rice HZB- multivorum Rice
C23 G9
OsEnb- Comamonas sediminis Hazaribagh Non Basmati MN889392 OsEnb- Staphylococcus Almora Non Basmati MN889346
HZB- Rice ALM- aureus Rice
G10 C18
OsEnb- Curtobacterium Palampur Non Basmati MN889279 OsEnb- Staphylococcus Almora Non Basmati MN889352
PLM- albidum Rice ALM- caprae Rice
L52 C28
OsEnb- Curtobacterium Palampur Non Basmati MN889283 OsEnb- Staphylococcus Almora Non Basmati MN889343
PLM- albidum Rice ALM- hominis Rice
L61 C9
OsEnb- Curtobacterium Palampur Non Basmati MN889288 OsEnb- Stenotrophomonas Hazaribagh Non Basmati MN889393
PLM- luteum Rice HZB- maltophilia Rice
L74 G11
OsEnb- Curtobacterium Palampur Non Basmati MN889291 OsEnb- Stenotrophomonas Hazaribagh Non Basmati MN889399
PLM- luteum Rice HZB- maltophilia Rice
L77 G27
OsEnb- Delftia tsuruhatensis Hazaribagh Non Basmati MN889395 OsEnb- Stenotrophomonas Hazaribagh Non Basmati MN889390
HZB- Rice HZB- maltophilia Rice
G18 G5
OsEnb- Leucobacter alluvii Hazaribagh Non Basmati MN889388 OsEnb- Stenotrophomonas Palampur Non Basmati MN889289
HZB- Rice PLM- pavanii Rice
G2 L75
OsEnb- Massilia consociata Almora Non Basmati MN889342 OsEnb- Xanthomonas Almora Non Basmati MN889347
ALM- Rice ALM- sacchari Rice
C6 C22
OsEnb- Microbacterium Palampur Non Basmati MN889287 OsEnb- Xanthomonas Palampur Non Basmati MN889285
PLM- arborescens Rice PLM- sacchari Rice
L71 L64
OsEnb- Microbacterium Palampur Non Basmati MN889293 OsEnb- Xanthomonas sp. Almora Non Basmati MN889353
PLM- azadirachtae Rice ALM- Rice
L79 C29
OsEnb- Microbacterium Palampur Non Basmati MN889295
PLM- proteolyticum Rice *Species identity was established by closest match for 1345-1430 bp sequence
L82 length at 97 % similarity coefficient with entries in GenBank database; **16S
OsEnb- Microbacterium sp. Palampur Non Basmati MN889292 rRNA gene sequences were end-trimmed, curated of poor quality basecalls and
PLM- Rice published in GenBank database.
L78
OsEnb- Ochrobactrum Hazaribagh Non Basmati MN889389
HZB- pseudogrignonense Rice
species belonging Azospirillum, Burkholderia, Herbaspirillum, Methyl
G4 obacterium, Pantoea, and Rhizobium has been frequently found inside rice
OsEnb- Pantoea ananatis Almora Non Basmati MN889351 plants as member of the endophytic microbiome (Mano and Morisaki,
ALM- Rice 2008). Whereas Acinetobacter, Delftia, Enterobacter, Flavobacterium,
C27
Pantoea, Pseudomonas, Sphingobacterium, and Stenotrophomonas were
OsEnb- Pantoea ananatis Almora Non Basmati MN889341
ALM- Rice consistently found in Pusa Basmati-1 (aromatic-type), Acidovorax, Aci
C3 netobacter, Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium,
OsEnb- Pseudomonas Almora Non Basmati MN889339 Enterobacter, Pantoea, and Sphingomonas were found in BPT-5204
ALM- oryzihabitans Rice
(non-aromatic type).
C1
Among hundreds of identified bacterial OTUs, bacterial genera such
12
Fig. 6. Relative population size of cultivated endophytic bacterial isolates from rice genotypes grown in three geographical zone of India.
as Acidovorax; Acinetobacter; Allorhizobium-Neorhizobium-Pararhizobium- shared among microbiome of similar habitat; here, the leaf
Rhizobium; Aureimonas; Bradyrhizobium; Burkholderia-Caballeronia- endogenous-niche of rice planted in contrasting agroclimatic zones.
Paraburkholderia;Enterobacter;Pantoea; Pseudomonas; Sphingomonas; and Typically, core-plant microbiomes are characterized by their ‘stable and
Stenotrophomonas was consistently found in both the rice genotypes consistent’ occurrence on plant niches representing contrasting
grown in all three experimental sites; these bacterial communities may geographical, climatic and ecological zones (Shade and Handelsman,
be the member of the core-endophytic microbiome of rice genotypes. 2012). One of the key questions is the perpetuation of core microbial
According to the recently accepted definition proposed by (Berg and communities in the spatio-temporal scales of the ecosystem. Vertical
Raaijmakers, 2018), the core microbiota is a suite of microbial members transmission of a core microbiota from across generations by seeds is
13
M. Kumar et al.
Table 5
Microbiological validation of mapped mNGS reads of rice leaf endophytic microbiome.
mNGS Microbiological tools
Palampur Almora Hazaribagh Total Frequency Palampur Almora Hazaribagh Total n Frequency
Genus
OTUs (%) Isolates (%)
Pusa BPT- Pusa BPT- Pusa BPT- Pusa BPT- Pusa BPT- Pusa BPT-
Basmati-1 5204 Basmati-1 5204 Basmati-1 5204 Basmati-1 5204 Basmati-1 5204 Basmati-1 5204
Observed in both Metagenome and Microbiological analysis

Acidovorax 3 4 2 2 3 3 17 100 1 2 – 3 – – 6 50.0
Acinetobacter 6 4 6 6 17 13 52 100 – – 2 – – – 2 16.7
Bacillus – – – – 3 2 5 33.3 3 2 – – – – 5 33.3
Chryseobacterium 5 3 – – 2 2 12 66.7 – – 2 1 – – 3 33.3
Comamonas 4 4 – – – – 8 33.3 – – – – 1 1 2 33.3
Delftia 2 1 – – 2 1 6 66.7 – – – – 1 1 2 33.3
Pantoea 5 5 3 3 2 2 20 100 2 1 2 2 – – 7 66.7
Pseudomonas 4 2 4 4 9 9 32 100 – – 5 5 1 1 12 66.7
Allorhizobium-Neorhizobium- 5 4 4 4 2 2 21 100 1 1 – – – – 2 33.3
Pararhizobium-Rhizobium
Serratia 2 1 – – – – 3 33.3 – – – – – 1 1 16.7
Sphingobacterium 5 3 1 1 2 2 14 100 1 – – – – 2 3 33.3
Stenotrophomonas 7 6 2 2 2 2 21 100 1 1 – – – 3 5 50.0
Xanthomonas 2 2 3 2 – – 9 66.7 1 1 2 – – 4 50.0
50 39 25 24 44 38 220 9 8 12 13 3 9 54
Observed only in Microbiological analysis
Achromobacter – – – – – – – – – – – 1 – 1 16.7
Agrobacterium – – – – – – – – 1 – – – – – 1 16.7
Alcaligenes – – – – – – – – – – – – 2 1 3 33.3
Bhargavaea – – – – – – – – – – – – – 1 1 16.7
14
Curtobacterium 5 5 – – 10 33.3
Ochrobactrum – – – – – – – – – – – 1 1 2 33.3
Janthinobacterium – – – 1 – 1 16.7
Leucobacter – – – – – – – – – – – – – 1 1 16.7
Microbacterium – – – – – – – – 1 4 3 – – 8 50.0
Pseudacidovorax – – – – – – – – – – 2 – – – 2 16.7
Rhodococcus – – – – – – – – 1 – – – – – 1 16.7
Staphylococcus – – – – – – – – 3 – – 3 1 – 7 50.0
11 9 5 4 5 4 38
Observed in only in Metagenome analysis
Aeromicrobium 1 1 2 2 – – 6 66.7 – – – – – – –
Aeromonas 1 2 2 1 1 1 8 100 – – – – – – –
Aureimonas 2 2 – – – – 4 33.3 – – – – – – –
Bradyrhizobium 2 2 2 2 2 2 12 100 – – – – – – –
Brevundimonas 2 2 2 2 – – 8 66.7 – – – – – – –
Burkholderia-Caballeronia- 1 1 2 2 2 2 10 100 – – – – – – –
Paraburkholderia
Microbiological Research 246 (2021) 126704

Corynebacterium-1 – – 2 2 – – 4 33.3 – – – – – –
Clostridium-sensu-stricto-1 2 2 – – – – 4 33.3 – – – – – – – –
Curvibacter 2 2 – – – – 4 33.3 – – – – –
Devosia 2 2 3 1 – – 8 66.7 – – – – – – – –
Enterobacter 11 6 – – 1 1 19 66.7 – – – – – – – –
Enterococcus 1 1 – – – – 2 33.3 – – – – – – – –
Exiguobacterium – – – – 2 2 4 33.3 – – – – – – – –
Flavobacterium 3 1 – – – – 4 33.3 – – – – – – – –
Facklamia – – – – 2 2 4 33.3 – – – – – – – –
Hafnia-Obesumbacterium 2 2 – – – – 4 33.3 – – – – – – – –
Herbaspirillum 3 4 – – – – 7 33.3 – – – – –
Kosakonia 3 2 – – – – 5 33.3 – – – – – – – –
(continued on next page)
also highlighted (Berg and Raaijmakers, 2018). While the

core-microbiome is likely to remain stable in spatio-temporal scales, the
Frequency
transient microbiome composition is highly unstable. The genotype and
changes in environmental factors are major drivers of the assembly of
33.3
(%)
–
–
–
–
–
–
–
–
–
–
–
–
–
transient microbial members. Our data showed the inconsistent pres
ence of eighteen bacterial genera in one or other rice genotypes or
Isolates
climate zones; they are Aeromicrobium; Aeromonas; Aureimonas; Bacillus;

Total n
Brevundimonas; Chryseobacterium; Clostridium-sensu-stricto-1; Comamo
92
–
–
–
–
–
–
–
–
–
–
nas; Corynebacterium-1; Curvibacter; Delftia; Devosia;Enterobacter;Entero
coccus; Exiguobacterium; Facklamia; Flavobacterium;
5204
BPT-
Hafnia-Obesumbacterium; Herbaspirillum; Kineococcus; Kosakonia; Meth
13
–
–
–
–
–
–
–
–
–
–
–
–
–
ylobacterium; Micrococcus; Mucilaginibacter; Nakamurella; Novos
Hazaribagh
phingobium; Paenibacillus; Pedobacter; Raoultella; Schumannella; Serratia;

Basmati-1
Sphingobium; Spirosoma; and Xanthomonas. The composition and occur

Pusa
rence of transient microbiota on plant niches are attributed to the
21
*Bacterial genera found associated with all three locations or both the genotypes; **Bacterial genera found associated with one or two location or either of the genotype.
8
–
–
–
–
–
–
–
–
–
–
–
–
– intra-seasonal vagaries of biotic and abiotic factors such as dynamic
weather factors, nutrient fluxes, physiology of plant, or even diurnal
5204
BPT-
rhythms of hosts (Kumar et al., 2019; Sivakumar et al., 2020).

17
–
–
–
–
–
–
–
–
–
–
–
–
–
Conversely, the core-microbiota appears to remain constant on a tem

poral scale. While the long-term cultivation practices along with natural
Basmati-1
Almora
climatic factors are likely to impact permanent microbial members, the

Pusa
short-term agronomic practices are expected to affect transient mi

17
34
–
–
–
–
–
–
–
–
–
–
–
–
–
crobes, including plant-pathogen colonization. The endophytic bacterial

Microbiological tools
communities such as Acinetobacter, Bacillus, Enterobacter, Kineococcus,

5204
BPT-
17
Methylobacterium, Pantoea, Pseudomonas, and Sphingomonas identified in

–
–
–
–
–
–
–
–
–
–
–
–
–
our investigation are frequently reported as epiphytic bacteria on the

Basmati-1
Palampur
phyllosphere or rhizosphere (Delmotte et al., 2009; Durand et al., 2018;

Kumar et al., 2019). Coupled with other published information, our
Pusa
20
37
endophytic microbial metagenome data suggest that phyllosphere

–
–
–
–
–
–
–
–
–
–
microbiota, in addition to primary soil-dark matter (microbiome), are

contributing to leaf endophytic microbiome composition.
Frequency
Culturable microbiome analysis by polyphasic taxonomic ap

33.3
66.7
33.3
33.3
33.3
33.3
33.3
33.3
33.3
33.3
33.3
33.3
55.5
100
(%)
proaches culminated in isolation of distinct bacterial isolates repre

senting diverse genera. mNGS approaches in conjunction with
microbiological method enabled us to validate the metagenomic OTUs.
OTUs
Total
The isolated and preserved bacterial communities are valuable micro

208
428
18
10
28
4
3
4
3
6
4
2
2
4
bial resource for future microbiome re-engineering for sustainable rice

cultivation. The microbiological investigation of culturable bacterial
5204
BPT-
#Frequency (%) =(Samples positive for a bacterial genus / Total number of samples) ×100.
diversity revealed nearly identical endophytic bacterial counts in the

14
52
4
–
–
–
–
–
–
–
–
–
–
–
range of 2–5 Log CFU g− 1 in aromatic and non-aromatic genotypes. The

Hazaribagh
endogenous bacterial counts obtained for rice agree with other pub
Basmati-1
lished reports (Aravind et al., 2009; Sheoran et al., 2016; Ashajyothi

Pusa
108
et al., 2020). Recent reports indicated endophytism plant Pseudomonas

12
56
2
–
–
–
–
–
–
–
–
–
–
–
putida BP25 and Bacillus megaterium BP17 is primarily attributed to the

regulation of bacterial multiplication by activated plant defense by the
5204
BPT-
endophyte itself (Sheoran et al., 2016; Ashajyothi et al., 2020). Hun

33
58
2
6
1
2
1
2
2
5
1
–
–
–
–
dreds of endophytic bacterial isolates obtained from the rice leaf were
morphotyped, DNA fingerprinted, and identified at the species level. A
Basmati-1
Almora
total of 92 distinct bacterial isolates representing mountain zones, Pal

Pusa
128
ampur and Almora as well as plateau zone Hazaribagh were isolated.

43
70
2
7
2
2
2
4
2
7
2
–
–
–
–
Spar CC analysis revealed complex intra-microbial interactions

among the endophytic microbial communities. We could observe both
5204
BPT-
50
89
positive and negative interactions among the bacterial members of

4
4
2
1
1
6
–
–
–
–
–
endophytic microbiome. Acidovorax, Alcaligenes, Bacillus, Chrys

Basmati-1
Palampur
eobacterium, Comamonas, Curtobacterium, Delftia, Microbacterium,

mNGS
Ochrobactrum, Pantoea, Pseudomonas, Rhizobium, Rhodococcus, Sphingo

Pusa
103
192
53
bacterium, Staphylococcus, Stenotrophomonas, and Xanthomonas were

1
6
2
1
1
4
–
–
–
–
–
isolated from both aromatic and non-aromatic rice genotypes. Majority

of the endophytic bacterial genera isolated from the rice leaf were also
found in the metagenomic OTUs that validated the mNGS based
Table 5 (continued )
microbiome data generated in the present investigation. mNGS provides

Methylobacterium
Novosphingobium
a comprehensive method by which nearly all microbes can be accurately

Mucilaginibacter
Sphingomonas
Schumannella
identified in a single assay (Tucker et al., 2012; Chiu, 2013; Simner

Paenibacillus
Nakamurella
Sphingobium
Micrococcus
Kineococcus
Grand total
Pedobacter
Spirosoma
Raoultella
et al., 2018; Gu et al., 2019). While mNGS can provide holistic identi
Subtotal
Genus
fication of microbiota, the functional exploitation of such metagenome

information necessitates laboratory-culturing, characterization and
15
Fig. 7. Comparaison of endophytic bacterial OTUs with cultivated genera associated with aromatic and non-aromatic rice genotypes.
activity screening for targeted applications. However, challenges are iv. SAMN16380689; v. SAMN16380690 ; vi. SAMN16380691. The data
aplenty while migrating mNGS into microbiology laboratory as over 98 sets were also uploaded in MG-RAST server with ALM-BPT-5204 (Proj
% of the microbial communities are yet to be isolated in pure culture. ect ID- mgp90495 ; Deposition Number- mgm4857417.3) ; ALM-PB1
Isolated bacterial genera found consistently in all six samples frequently (mgp90495 ; mgm4857418.3) ; PLM-PB1 (mgp90495 ;
reported as an endophyte in many crop plants or reported as plant mgm4857419.3) ; PLM-BPT-5204 (mgp90495 ; mgm4857420.3) ; HZB-
growth-promoting bacteria (Komagta and Suzuki, 1986; Kadota and BPT-5204 (mgp90495 ; mgm4857421.3) and HZB-PB1(mgp90495 ;
Nishiyama, 1998; Megías et al., 2017; Qin et al., 2020). Several bacterial mgm4857422.3).
genera were found uniquely associated only with either aromatic or
non-aromatic genotypes. Similarly, many location-specific bacterial CRediT authorship contribution statement
genera were also found in the investigation. Nevertheless, the precise
role and activities of bacterial endophytes remain unexplored and in Mukesh Kumar: Conceptualization, Data curation, Formal analysis,
sights into plant-endophytic microbe interaction are compounded by its Investigation, Methodology. Aundy Kumar: Conceptualization, Meth
complexity (Walitang et al., 2017). The investigation culminated in odology, Formal analysis, Resources, Data curation, Writing - original
isolation and identification core-endophytic microbial communities of draft, Visualization, Supervision, Project administration, Funding
rice for developing microbiome assisted crop management by endo acquisition. Kuleshwar Prasad Sahu: Validation, Writing - original
phytic microbiome reengineering in future. draft. Asharani Patel: Validation. Bhaskar Reddy: Formal analysis,
Data curation, Visualization. Neelam Sheoran: Methodology, Supervi
5. Metagenome data availability sion. Krishnappa Charishma: Validation. Hosahatti Rajashekara:
Investigation, Resources. Someshwar Bhagat: Investigation, Resources.
Data sets were submitted to GenBank with BioSample accessions Rajeev Rathour: Investigation, Resources.
numbers i. SAMN16380686; ii. SAMN16380687; iii. SAMN16380688 ;
16
Fig. 8. Comparaison of identified endophytic bacterial OTUs representing three locations with cultivated bacterial genera.
17
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Institute, New Delhi and Dean, PG School, ICAR-Indian Agricultural Watanabe, T., Murase, J., Asakawa, S., 2014. Low nitrogen fertilization adapts rice
Research Institute, New Delhi for encouragement and support. Mukesh root microbiome to low nutrient environment by changing biogeochemical
functions. Microbes Environ. ME13110.
Kumar is grateful to University Grant Commission and Ministry of Social Ikenaga, M., Asakawa, S., Muraoka, Y., Kimura, M., 2003. Bacterial communities
Justice & Empowerment, and Ministry of Tribal Affairs for granting associated with nodal roots of rice plants along with the growth stages: estimation by
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Deciphering Core-Microbiome Rice Leaf Endosphere Metagenomic Microbiological Analysis Aromatic and Nonaromatic Genotypes

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Microbiological Research 246 (2021) 126704

Contents lists available at ScienceDirect

Deciphering core-microbiome of rice leaf endosphere: Revelation by

1. Introduction ecological functions of the plant microbiome contributing to plant

2.4.5. Sequencing and analysis Table 1

*Bacterial genera found in both Pusa Basmati-1 and BPT-5204

*Bacterial genera found in all three locations

Table 4 Table 4 (continued )

Table 4 (continued ) Table 4 (continued )

Observed in both Metagenome and Microbiological analysis

Microbiological Research 246 (2021) 126704

also highlighted (Berg and Raaijmakers, 2018). While the

climate zones; they are Aeromicrobium; Aeromonas; Aureimonas; Bacillus;

Brevundimonas; Chryseobacterium; Clostridium-sensu-stricto-1; Comamo­

Hafnia-Obesumbacterium; Herbaspirillum; Kineococcus; Kosakonia; Meth­

phingobium; Paenibacillus; Pedobacter; Raoultella; Schumannella; Serratia;

Sphingobium; Spirosoma; and Xanthomonas. The composition and occur­

rence of transient microbiota on plant niches are attributed to the

rhythms of hosts (Kumar et al., 2019; Sivakumar et al., 2020).

Conversely, the core-microbiota appears to remain constant on a tem­

climatic factors are likely to impact permanent microbial members, the

short-term agronomic practices are expected to affect transient mi­

crobes, including plant-pathogen colonization. The endophytic bacterial

communities such as Acinetobacter, Bacillus, Enterobacter, Kineococcus,

Methylobacterium, Pantoea, Pseudomonas, and Sphingomonas identified in

our investigation are frequently reported as epiphytic bacteria on the

phyllosphere or rhizosphere (Delmotte et al., 2009; Durand et al., 2018;

endophytic microbial metagenome data suggest that phyllosphere

microbiota, in addition to primary soil-dark matter (microbiome), are

Culturable microbiome analysis by polyphasic taxonomic ap­

proaches culminated in isolation of distinct bacterial isolates repre­

The isolated and preserved bacterial communities are valuable micro­

bial resource for future microbiome re-engineering for sustainable rice

diversity revealed nearly identical endophytic bacterial counts in the

range of 2–5 Log CFU g− 1 in aromatic and non-aromatic genotypes. The

lished reports (Aravind et al., 2009; Sheoran et al., 2016; Ashajyothi

et al., 2020). Recent reports indicated endophytism plant Pseudomonas

putida BP25 and Bacillus megaterium BP17 is primarily attributed to the

endophyte itself (Sheoran et al., 2016; Ashajyothi et al., 2020). Hun­

total of 92 distinct bacterial isolates representing mountain zones, Pal­

ampur and Almora as well as plateau zone Hazaribagh were isolated.

Spar CC analysis revealed complex intra-microbial interactions

positive and negative interactions among the bacterial members of

endophytic microbiome. Acidovorax, Alcaligenes, Bacillus, Chrys­

eobacterium, Comamonas, Curtobacterium, Delftia, Microbacterium,

Ochrobactrum, Pantoea, Pseudomonas, Rhizobium, Rhodococcus, Sphingo­

bacterium, Staphylococcus, Stenotrophomonas, and Xanthomonas were

isolated from both aromatic and non-aromatic rice genotypes. Majority

microbiome data generated in the present investigation. mNGS provides

a comprehensive method by which nearly all microbes can be accurately

identified in a single assay (Tucker et al., 2012; Chiu, 2013; Simner

fication of microbiota, the functional exploitation of such metagenome

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Brevundimonas; Chryseobacterium; Clostridium-sensu-stricto-1; Comamo

Hafnia-Obesumbacterium; Herbaspirillum; Kineococcus; Kosakonia; Meth

Sphingobium; Spirosoma; and Xanthomonas. The composition and occur

Conversely, the core-microbiota appears to remain constant on a tem

short-term agronomic practices are expected to affect transient mi

Culturable microbiome analysis by polyphasic taxonomic ap

proaches culminated in isolation of distinct bacterial isolates repre

The isolated and preserved bacterial communities are valuable micro

endophyte itself (Sheoran et al., 2016; Ashajyothi et al., 2020). Hun

total of 92 distinct bacterial isolates representing mountain zones, Pal

endophytic microbiome. Acidovorax, Alcaligenes, Bacillus, Chrys

Ochrobactrum, Pantoea, Pseudomonas, Rhizobium, Rhodococcus, Sphingo