Decoding the microbiome and metabolome of the <i>Panchagavya</i>—An indigenous fermented bio‐formulation

Abstract

For the first time, updated molecular techniques were used to validate and elucidate the effect of the Panchagavya. Metagenomics was used to decipher the bacterial microbiome structure, which showed promising results for their existence and abundance in the Panchagavya. The word “Panchagavya” is derived from Sanskrit, meaning “five ingredients from a cow,” which includes dung, milk, urine, curd, and clarified butter (ghee) [1]. The “Panchagavya” application has been reported to enhance plant growth and nutrient uptake, reducing the biotic and abiotic stresses in crop plants. Preparation of the Panchagavya formulation involves several fermentation processes with a consortium of beneficial bacteria [2]. In such bio-formulations, cow dung is an important constituent that acts as a source of bacterial inoculum [3]. The Panchagavya formulations can be applied to crop plants using many methods, among which foliar spray is widely used. The bio-formulation can be suspended or dissolved in water and, therefore, can be used along with irrigation water. In organic farming, it is used as a foliar spray at a concentration of 3% to supplement plant nutrient requirements and suppress pests and diseases [4]. The Panchagavya is also used as a biofertilizer at 1:100 (Panchagavya: soil; v/wt) to promote plant growth [5]. It was reported previously that the Panchagavya formulation contains numerous plant growth-regulatory molecules, such as gibberellins (GAs) and indole acetic acid (IAA) [3, 6]. In addition, the beneficial microorganism, namely, the Plant Growth-Promoting Rhizobacteria (PGPR), synthesizes many amino acids and other essential enzymes. It is evident from the previous reports that the foliar application of the Panchagavya enhances the yield and quality of cereals and vegetables [7]. Several studies on the biodynamics of bacterial species in the Panchagavya exists that are linked to the solubilization of various carbon compounds and minerals using a polyphasic approach resulting in the most reported bacterial species to produce IAA and ammonia [3]. Despite its wide use in crop production, especially in organic agriculture, the metabolic profiles (hormones, proteins, nutrients, etc.) and microbial profiles have not been explored completely. Moreover, the profile and dynamics of the entire microbial community associated with the Panchagavya are unavailable due to limitations in culturing several genera/species using conventional microbiological techniques. Also, the complete enzymatic profile of the Panchagavya is still unknown. Not many efforts have been made to explore the complete biology involved in the plant-growth-promoting and ISR activity of the Panchagavya. It is possible to understand the fundamental aspect of a complex system only if different omics approaches are combined [8]. Therefore, we have used different omics approaches to decode the microbial community (metagenomics) and metabolite profile (metabolomics) in the Panchagavya. These approaches can reveal the microbial composition and their abundance, the functional annotation of genes and important protein compounds, hormones, and so forth, in the Panchagavya formulation. With the recent advancement in metagenomic sequencing, construction of the whole microbiome is easier and more comprehensive than the conventional 16S rRNA sequencing of culturable bacteria [9, 10]. However, metagenomics reveals only the microbial populations; therefore, metabolomics is required to study the in situ microbial metabolic activity and its capabilities [11]. Therefore, with the help of metabolomics, we can identify the plant growth-promoting compounds, including hormones, which can be further screened with high-throughput metabolite identification technologies such as liquid chromatography mass spectrometry (LCMS) [12]. In this study, through an integrated approach, we report the microbial population assemblages of the Panchagavya by metagenomics and identify its potential plant-growth-promoting molecules through LCMS attached to the “metlin” library. Furthermore, by combining different omics technologies, we have revealed the overall function of these microbes in the Panchagavya. This is the first comprehensive report of the microbial and metabolome profiles of the Panchagavya. Metagenomic DNA from the Panchagavya formulation was used to decode its microbiome structure. The total sequence data size obtained was 135.6 Mb with 160,945 assembled contigs (Supporting Information: Table S1A). The operational taxonomic unit (OTU) picking through Eukaryotic and prokaryotic diversity was estimated using CCMetagen v1.2.5, which revealed that the domain bacteria were the most abundant OTUs (99.58%), with a high abundance of species belonging to the phylum Proteobacteria (40.40%), Firmicutes (26.90%), and Bacteroidetes (14.20%). Rhodospirillales (24%), Lactobacillales (22.40%), Bacteroidales (11.30%), Enterobacteriales (6.60%), Pseudomonadales (2.40%), Eubacterials, and Burkholderiales (1.00%) were the most prevalent orders. Among the class, Alphaproteobacteria was highly abundant (24.30%), followed by Bacilli (23.00%), Bacteroidia (11.30%), Gammaproteobacteria (11.20%), and Betaproteobacteria (3.40%). The proportions of bacterial families such as Acetobacteraceae, Streptococcaceae Prevotellaceae, Enterobacteriaceae, Bacteroidaceae, and Pseudomonadaceae were 23.70%, 21.30%, 6.8%, 6.60%, 3.7%, and 2.40%, respectively, in the Panchagavya bio-formulation. The most predominant genera in the decreasing order of their abundance were Streptococcus (20.80%), Acetobacter (14.60%), Prevotella (5.60%), Bacteroides (3.50%), Gluconobacter (3.00%), Klebsiella (2.60), Enterobacter (2.30%), Azospira (2.10%), Azotobacter (1.70%), Gluconoacetobacter (1.60%), Acinetobacter (1.40%), Selenomonas (0.90%), and Pseudomonas (0.40%). The Panchagavya bio-formulation was rich in S. lutetiensis (9.90%), A. peroxydans (8.20%), S. equinus (5.00%), S. infantarius (3.30%), G. oxydans (3.00%), B. fragilis (2.70%), uncultured B. bacterium (2.50%), and A. chroococcum (1.20%) species. The relative distributions of bacteria belonging to the different phyla, classes, order, families, and genera are summarized in Figure 1A and Supporting Information: Table S2. Based on previous reports, the different genera/species of bacteria identified in the Panchagavya formulation were grouped into different functional groups. Several bacteria that promote plant growth were identified in the Panchagavya bio-formulation. Among them, Accumulibacter phosphatis, Achromobacter spp. Root565, Acidobacteria bacterium, Acinetobacter lactucae, A. kooki, Aquitalea magnusonii, Bacillus cereus, Candidatus Accumulibacter spp. 66-26, Citrobacter amalonaticus, Clostridium pasteurianum BC1, Enterobacter cloacae, E. asburiae, E. cancerogenus, E. kobei, E. xiangfangensis, Gluconacetobacter diazotrophicus, Rhizobium leguminosarum, Pseudomanas putida, Acinetobacter kooki, Azospirillium brasilense, A. lipoferum, P. fluorescens, Azotobacter beijerinckii, B. subtilis Lactobacillus mucosae, and L. harbinensis were found to be predominant (Figure 1B,C and Supporting Information: Table S2). Several bacteria reported as an ISR activators in plants against biotic stress were found in the Panchagavya bio-formulation. The unclassified Burkholderiales showed the highest reads (79 reads), followed by Pseudomonas fluorescens (12 reads), Bacillus cereus (12 reads), and Pseudomonas chlororaphis (3 reads), which are involved in imparting ISR in the crop plants (Figure 1 and Supporting Information: Table S2). Various bacterial genera such as Butyrivibrio spp. Caloramator spp. Cellulosilyticum lentocellum. Chloroflexi bacterium, Clostridium clariflavum, C. cellulosi, C. disporicum, C. homopropionicum, C. innocuum, C. kluyveri, C. leptum, C. magnum, C. neopropionicum, Herbinix hemicellulosilytica, Leclercia sp. Marvinbryantia formatexigens, Dyella jiangningensis, Pseudobacteroides cellulosolvens, Ruminococcus spp., Selenomonas spp., and so forth, which decompose cellulose, hemicellulose, and other fibers, were found in the Panchagavya formulation (Figure 1 and Supporting Information: Table S2). Several bacteria (Acidovorax ebreus, Acinetobacter tandoii, A. venetianus, Alicycliphilus spp., Alkaliphilus metalliredigens, Chloroflexi sp., Dechloromonas spp., Desulfovibrio spp., Lysinibacillus spp., Paenirhodobacter enshiensis, Pandoraea thiooxydans, Propionispora spp., Pseudomonas aeruginosa, P. mendocina, P. alcaligenes, P. balearica, P. knackmussii, etc.) reported to be associated with soil bioremediation by degrading hydrocarbons, polyesters, phenols, and so forth, were predominantly present in the Panchagavya formulation (Figure 1 and Supporting Information: Table S2). Nutrient recyclers such as Accumulibacter phosphatis, Acidobacteria bacterium, Acidovorax caeni, Candidatus Accumulibacter sp. Citrobacter amalonaticus, Dechlorosoma suillum, Denitrobacterium detoxificans, Desulfosporosinus orientis, Desulfovibrio spp. Gallionella sp. Hylemonella gracilis, Mitsuokella jalaludinii, Novosphingobium nitrogenifigens, Pandoraea thiooxydans, Pseudoxanthomonas spp., Sebaldella termitidis, Thiobacillus sp., and so forth, were also part of the Panchagavya microbiome (Figure 1 and Supporting Information: Table S2). As auxin transporters, Azotobacter chroococcum, Arcobacter butzleri, uncultured Ruminococcus sp., Sutterella sp., Bifidobacterium bohemicum, Prevotella sp. CAG:891 and Pedobacter sp. V48 play a pivotal role. Paenirhodobacter enshiensis, Dialister sp. CAG:357, Acidovorax sp. 202149, Comamonas aquatica, Lactobacillus mucosae, Streptococcus equinus, Enterobacter asburiae, and Lactobacillus harbinensis aid cytokinin transportation. In addition, several bacterial genera were identified. However, their function in the soil and plant system is unknown (Figure 1 and Supporting Information: Table S2). The genes involved in promoting plant growth, metabolism, nutrition recycling, and so forth, were predicted. The number of genes predicted by Prodigal was 122,976. Of these, 87.9% (n = 108,096) of the genes were annotated (without filtering). When genes were filtered with 50% sequence identity and 30% query coverage, 76.6% (n = 94,359) of the genes were annotated. Similarly, genes with 70% identity and 50% query showed 49.7% (n = 61,175) annotated genes. The predicted genes matched Uniprot protein sequences of bacteria, fungi, archaea, and viruses. The sequence annotations, gene names, and organisms with other details of alignments are listed in Supporting Information: Table S3. The data also revealed the presence of important regulatory proteins involved in the biosynthesis and transport of auxin (in Arcobacter butzleri and six other bacteria) and cytokinin (in Paenirhodobacter enshiensis and also in other 35 genera) (Supporting Information: Table S4). The gene ontology classification revealed that all predicted gene sets were involved in molecular functions (79522 enriched genes onto logs), biological processes (70463 enriched genes onto logs), and cellular components (43,369 enriched genes onto logs). The GO analysis revealed that the percentages of genes involved in cellular components, viz., the cell part, the cell, and the membrane were 40.20%, 40.20%, and 17.90%, respectively. In the molecular function component, gene ontology responsible for catalytic activity (67.30%), binding (52.30%), and transporter activity (6.00%) was abundant. Higher gene percentages of GO terms in the biological process were the cellular process (62.30%), the metabolic process (60.20%), localization (10.70%), and response to stimuli (9.70%) (Figure 1D and Supporting Information: Table S5). The Clusters of Orthologous Groups of proteins (COGs) analysis distributed the annotated proteins into three major functional sections, that is, (a) metabolism, (b) cellular process and signaling, and (c) information storage and processing. Further subsystem analysis predicted the proteins related to carbohydrate metabolism (12.44%), amino acid metabolism (8.90%), protein metabolism (7.40%), RNA metabolism (6.09%), DNA metabolism (3.89%), membrane transport (2.52%), and stress response (2.44%) (Figure 1D). The associated annotated genes of different pathways were predicted using the DAVID program. Some of the significant pathways obtained were Amino Acid Biosynthesis (AAB), Amino Acid Degradation (AAD), Amine and Polyamine Biosynthesis (APAB), amino–sugar metabolism (ASM), Bacterial Outer Membrane Biogenesis (BOMB), Cell Wall Biogenesis (CWB), Co-Factor Biogenesis (CFB), Glycan Degradation (GD), Glycan Metabolism (GM) and Metabolic Intermediate Biosynthesis (MIB), Nitrogen metabolism (NM), one-carbon metabolism (OCM), Protein modification (PM), Pyrimidine metabolism (PYM), Sulfur metabolism (SM) pathways, and so forth (Figure 1 and Supporting Information: Table S6). The microbial community composition of the Panchagavya formulation assessed using CCMetagen revealed the reads of eukaryotic (17.50%) and prokaryotic (57.10%) origins (Supporting Information: Figure S1). The assembled metagenome by MEGAHIT was found to have 189,455 contigs, out of which 188,989 contigs were revealed to be of prokaryotic origin by EukRep, which was retained for downstream analysis. Read coverage and the relative abundance-based binning of the prokaryotic contigs using MetaBAT2 resulted in 54 genome bins. De-replication of the genome bins with with of and resulted in genome bins. analysis revealed that of the bins and were to the bins and were to the and bins and were to order (Supporting Information: Table S1). was to these bins using against the as in Supporting Information: Table The bins were annotated using and the annotated in were used as for to total of were predicted from bins by genes and associated genes were identified and are in Supporting Information: Table The was used to decipher the of the Panchagavya formulation. total of were identified in metabolite analysis in the and in the of which were identified in the and of and methods, (Supporting Information: Table plant was used to the from and The essential plant hormones, and its other such as and were In addition, several compounds such as and so forth, belonging to different that are associated with plant-growth-promoting functions and biotic stress were also in the Panchagavya formulation (Supporting Information: Table has been more due to the of on and the In organic farming, made organic from the organic of the is the such important of is the It has been reported that several the Panchagavya made from and cow and have plant-growth-promoting functions and to several The Panchagavya is a of cow obtained from an cow that dung, urine, milk, curd, and However, the microbial and metabolic profiles of the which are responsible for its have not been completely. Moreover, the of the Panchagavya microbiome and their in metabolism in soil have still not been bio-formulation and its microbiome and plant-growth-promoting metabolite profile in this The metagenome sequencing approach was used in this study to understand the diversity and function of microbial which not be using conventional have used a Metagenomic sequencing approach for all the associated of the Panchagavya. The analysis revealed that the Panchagavya a wide of bacterial genera with the domain bacteria as the most abundant OTUs of with a of species belonging to the phylum and functional classification of identified bacterial genera revealed the many bacteria involved in of plant nutrient in and plant Among the Enterobacter cloacae, E. asburiae, Rhizobium leguminosarum, Pseudomanas putida, Acinetobacter kooki, Azospirillium brasilense, A. lipoferum, P. fluorescens, Azotobacter B. and Lactobacillus were found to be L. was found in abundance in the bio-formulation. The Pseudomonas fluorescens and Bacillus cereus were involved in imparting ISR in the crop reads the time, the unclassified Burkholderiales showed the highest reads of The of from cow for plant growth bacteria, enzymatic bacteria, and bacteria, and plant is reported in the Panchagavya play an important in by the minerals for plant This study microbiological for plant growth the Panchagavya to the crop as reported previously [5]. Various other bacterial genera were found in the Panchagavya which decompose and Several bacteria associated with soil bioremediation by degrading hydrocarbons, polyesters, phenols, and so forth, were predominantly present in the Panchagavya formulation. associated with nutrient in soil were and bacteria responsible for the plant IAA and cytokinin were also study also identified several bacterial genera associated with ISR in crop plants. In addition, several bacterial genera that can complex such as cellulose, hemicellulose, and were the of the Panchagavya in organic carbon in the soil with several has been a especially in due to use of and water for crop The by the has an due to the of technologies for and biological that are not essential for plant growth also in various of the plant Higher of these to growth and can be to and have identified several bacteria (Acidovorax ebreus, A. venetianus, Alicycliphilus Alkaliphilus metalliredigens, Chloroflexi bacterium, suillum, P. enshiensis, etc.) in the Panchagavya formulation that can the of soil and bioremediation of Therefore, use of the Panchagavya a potential for to produce Plant are among the most important growth have a major on plant metabolism and play a in plant response against stresses In the study, the Acinetobacter spp. were found to be more abundant in the bio-formulation. Several species of this genera are to the in the soil more and suppress the In addition, Acinetobacter spp. are to produce several and their metabolome analysis revealed that many plant growth-promoting were the major components, and the IAA have been by Acinetobacter sp. important plant identified in bio-formulation through metabolomics was acid and its acid and its are essential for plant The bacteria genera such as and Bacillus were abundant in the Panchagavya. are the species of bacteria reported to produce acid and its and reported that bacteria such as and Streptococcus are present in cow dung, a for the Panchagavya. cytokinin was by organisms in the this cytokinin into the by It is involved in an important growth-promoting have reported that acid high as was by the bacteria present in the cow urine, a constituent of the Panchagavya. In study, from metagenomic we identified several species of Rhizobium which are to produce acid and its In to the hormones, we also identified several essential proteins and in the bio-formulation many metabolic pathways in the to the overall soil and crop The predominant genes involved in the molecular cellular and biological process were the most abundant in gene ontology analysis. that the catalytic cellular and metabolic and cell genes in the Panchagavya These genes play a in the of DNA and of genes in the cell, which play a significant in the overall growth of the plants. Metagenomic analysis the functional diversity that microbial can amino acids cell and the cell organic and microbial to play an essential in the carbon by reducing of functional genes were related to This is with previous which with bacteria, such as This is a study the microbes and responsible for the beneficial of the Panchagavya formulation applied to crop plants and to the abundance of beneficial microbes and which can be to to enhance crop In addition, study has identified several bacterial genera in the Panchagavya which have not been so for in the soil and plant which a study to such potential For the first time, updated molecular techniques were used to validate and elucidate the effect of the Panchagavya. Metagenomics was used to decipher the bacterial microbiome structure, which showed promising results for their existence and abundance in the Panchagavya of reads of the gene and functional were the other the metabolome predicted the of numerous plant growth and other compounds and by these to these the Panchagavya is a promising that contains and plant As a the Panchagavya is a bio-formulation that is and in soil and crop Figure The Panchagavya was the previously The ingredients for the bio-formulation were obtained from the cow at the of was used to the Panchagavya formulation. a of cow dung and cow was to for the the cow urine, cow milk, and cow curd, were and for The was to promote microbial activity for the bio-formulation was used for analysis. and of the Panchagavya was used for DNA using the Plant the The quality and of DNA were assessed using the and for metagenome The sequencing was at a using of DNA concentration was used to the for size was and with the the was enriched with of was the and their quality was using the sequencing in of reads were obtained as and their quality was using the The quality of the reads was for the and of The reads were assembled using a of for whole metagenome studies The contigs of were from the analysis to gene and The filtered sequences with an of were used for the operational taxonomic unit (OTU) in The metagenome was used for gene using The of predicted was to the abundance of a taxonomic of eukaryotic and prokaryotic in metagenomic reads was using CCMetagen The MEGAHIT in the was used to the metagenomic of prokaryotic from eukaryotic contigs was using Read coverage and relative abundance were estimated using which was as to MetaBAT2 for binning the prokaryotic contigs to genome bins. was used to the genome bins by of highly and the genome for genome was used to the genome and the of of the genome bins. was to the genome bins using The bins were further annotated using was used to the gene that have the potential to produce The functional annotation was by sequences against the protein using the The genes for predicted proteins were identified using The annotated gene was used for as bacteria involved in production, and the ISR in plants were identified [5]. was using the the various species. the and was used to proteins into a of functional The protein sequences of the genome were to against the and the was annotated using The annotation was in annotation and the proteins GO annotation were The filtered annotated was to for GO The gene were obtained from the results for and analysis was for the genes. Several pathways were identified using DAVID the is to and as The of from the Panchagavya was out using and In the and water were used in the of as the of the Panchagavya was with of for 1 and for the was at for at The was and at analysis. However, in the water was used as the of the Panchagavya was for 1 with of and for the was at for at The was filtered using a the was and at analysis. analysis was out using followed by analysis using a mass with an system with a was used for data and the for the for the analysis. The used were acid in water as and acid in as the was The was for with the for 30% for for for and for The was out for the mass spectrometry data which was using to The from the were used for analysis in the using The metabolite data was out in and at and respectively, at a of The were of potential and of the were out in The was against the metabolite to metabolite The for the analysis were in their that is, and The was out using the with a size of 1 For the of the of and 1 for the and in a were The matched was for the with an of of of and a of For and and were with and against the Plant The used were and for the and for the the study, the and the the the and the the and the the the results and the the the the and the have the of the are to for their metagenomic and was by the The of The of the Panchagavya is in the with the the and The is in the with an Supporting The is not responsible for the or of information by the than be to the for the

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