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. 2020 Oct 6;15(10):e0239594. doi: 10.1371/journal.pone.0239594

Metagenome analysis from the sediment of river Ganga and Yamuna: In search of beneficial microbiome

Bijay Kumar Behera 1,*, Biswanath Patra 1, Hirak Jyoti Chakraborty 1, Parameswar Sahu 1, Ajaya Kumar Rout 1, Dhruba Jyoti Sarkar 1, Pranaya Kumar Parida 1, Rohan Kumar Raman 1, Atmakuri Ramakrishna Rao 2, Anil Rai 3, Basanta Kumar Das 1,*, Joykrushna Jena 2, Trilochan Mohapatra 2
Editor: Manas Ranjan Dikhit4
PMCID: PMC7537857  PMID: 33021988

Abstract

Beneficial microbes are all around us and it remains to be seen, whether all diseases and disorders can be prevented or treated with beneficial microbes. In this study, the presence of various beneficial bacteria were identified from the sediments of Indian major Rivers Ganga and Yamuna from nine different sites using a metagenomic approach. The metagenome sequence analysis using the Kaiju Web server revealed the presence of 69 beneficial bacteria. Phylogenetic analysis among these bacterial species revealed that they were highly diverse. Relative abundance analysis of these bacterial species is highly correlated with different pollution levels among the sampling sites. The PCA analysis revealed that Lactobacillus spp. group of beneficial bacteria are more associated with sediment sampling sites, KAN-2 and ND-3; whereas Bacillus spp. are more associated with sites, FAR-2 and ND-2. This is the first report revealing the richness of beneficial bacteria in the Indian rivers, Ganga and Yamuna. The study might be useful in isolating different important beneficial microorganisms from these river sediments, for possible industrial applications.

Introduction

Rivers are known to be important for the development of human civilization, culture, and welfare. They are one of the crucial components of freshwater ecosystems, maintaining large biodiversity which is vital for sustenance of the terrestrial biome. Since rivers are significant reservoirs of the microbiome, they are relentlessly being explored for the search of de novo microbiota. These bacteria are of greater importance due to their different benefits to humans as well as all other strata of organisms present in the trophic pyramid [1]. It provides its rewarding effects generally through four main mechanisms i.e. enhancement of barrier function, intervention with host pathogens, immunomodulation, and assembly of neurotransmitters [2]. These organisms are gaining increasing importance as functional foods as well as prophylactic, therapeutic, and growth supplements for humans [3–5]. Some of the most common human gut probiotics viz. Lactobacillus and Enterococcus are reported to counteract diabetes, obesity, autoimmune disorder, and cancer through the production of metabolites like short-chain fatty acids [6]. Not only for humans, nowadays, the important microbiome is also being used in agriculture, including veterinary and fisheries, to benefit the animal physiology by improving their internal and external environment [5, 7, 8]. However, in fisheries, the scope of microbial treatment is enormous and the use of the same is gaining day by day. The latest study on Labeo rohita established that dietary administration of a probiotic bacterium, Bacillus aerophilus KADR3, improves the disease resistance and enhances the immunity against Aeromonas hydrophila infection [9]. Similarly, the dietary application of B. amyloliquefaciens CCF7, in L. rohita, challenged with a fish pathogenic bacteria, A. hydrophila MTCC 1739, showed beneficial effects [10]. Though many reports are present on discovering microbiome from natural streams of other countries, there is very insufficient literature available on the same in context to the Indian subcontinent especially in the large riverine ecosystems like Ganga and Yamuna. Therefore, in the present study, the abundance of different beneficial microbiota in the selected stretches of the river Ganga and Yamuna have been identified through the metagenomics approach. The metagenomics study has overcome the problem of culture-oriented microbiological studies associated with different environmental samples and came out as a potential search tool for detailed screening of supportive microbiome species present in an ecosystem [11]. Since the total DNA extracted from an environmental sample is a snapshot of the entire microbial community, metagenomics analysis makes it easier for a comprehensive evaluation of the native microbial ecology [12]. The recent computational advancement and evolution of next-generation sequencing, which can generate millions of sequences at improved cost and speed, make it possible to detect microbial biodiversity easily and their abundance directly from the environmental samples [13–14]. As per our knowledge, this is the first report, presenting an analysis of a large sediment metagenome dataset from these rivers in search of beneficial bacteria.

Materials and methods

Sample collection

A total of nine sediment samples were collected from the river Ganga and Yamuna. From the Ganga river, six sediment samples were collected from different sites viz. Ganga Barrage (N 26030.858//E 80019.114//) (KAN-1), Jajmau (N 26025.301//E 80025.282//) (KAN-2), Jana Village (N 26024.495//E 80026.904//) (KAN-3) near Kanpur, Uttar Pradesh, Farakka Barrage (N 24047.804//E 87055.417//) (FAR-1), Dhulian (N 24047.804//E 87055.417//) (FAR-2), Lalbagh (N 29011.087//E 88016.079//) (FAR-3) near Farakka, West Bengal. From the river Yamuna, sediment samples were collected from three different sites viz. Wazaribad (N 28042.39//E 77013.57//) (ND-1), Okhla barrage (N 28032.51//E 77018.30//) (ND-2), Faizupur Khaddar (N 28018.43//E 77027.52//) (ND-3) near New Delhi, India (Fig 1).

Fig 1. Map showing the sediment sampling sites.

Fig 1

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Sediments were collected from the river Ganga at six locations namely, Kanpur (KAN-1, KAN-2 and KAN-3) and Farakka, (FAR-1, FAR-2 and FAR-3) whereas, three locations from the river Yamuna, at New Delhi (ND-1, ND-2 and ND-3). The map of sediment collection sites was prepared using ArcGIS 10.2.1 platform.

DNA extraction

The obtained samples from different locations from river Ganga and Yamuna were kept in sterile plastic bags, sealed and transported on ice (4°C), and afterward stored at -80°C until further processing. Metagenomic DNA from these sediment samples were extracted using a soil gDNA isolation kit (Nucleospin Soil). After the isolation of metagenomic DNA, the quality was checked in Nanodrop 2000 and Qubit® 3.0 Fluorometer. The metagenomic library was prepared using sufficient amounts of extracted good quality DNA.

Metagenomic library preparation

The paired-end sequencing libraries were arranged using Illumina Trueseq Nano DNA Library Prep Kit. Approximately 200ng of eDNA was fragmented by Covaris M220 to produce a mean fragment allocation of 350bp. Covaris shearing produced dsDNA fragments with 3' or 5' overhangs. The fragments were then subjected to end-repair. As per the description in the kit, the products were PCR amplified with the index primer. The D1000 Screen tape was used to investigate the PCR enriched libraries in the 4200 Tape Station system (Agilent Technologies).

Whole metagenome sequencing and quality assessment

After obtaining the mean peak size from Agilent Tape Station profile and Qubit concentration for the libraries, PE Illumina libraries were loaded into NextSeq 500 for cluster generation and sequencing. After trimming, a minimum length of 100 nt was applied. The CLC Genomics Workbench version 8.5.1 (CLC bio; https://www.qiagenbioinformatics.com/products/clc-genomics-workbench) was used to assemble the filtered high-quality reads of each sample into scaffolds.

Metagenomic sequences accession numbers

The Metagenomic sequences used in this study have been submitted to the NCBI-SRA database under Accession Nos: SRP190174, SRP190175, SRP189880, SRP191076, SRP191079, SRP191075, SRP191073, SRP191080, and SRP191499 for three Kanpur samples (KAN-1, KAN-2, KAN-3), three Farakka samples (FAR-1, FAR-2, FAR-3) and three New Delhi samples (ND-1, ND-2, ND-3) respectively.

Sequence annotation and bioinformatics analysis

For the detection of the beneficial microbiome in the sediment metagenome, filtered metagenomic reads were used for taxonomical binning by the Kaiju web interface. Classifier-Kaiju used Burrows-Wheeler transform algorithm for taxonomic classification on the protein-level [15]. On the other hand, to highlight the phylogenetic relationship among the beneficial microbiome species found in the sediment metagenome, multiple sequence analysis was carried out using MEGA 6 software. The Neighbor-Joining method was used to infer evolutionary history [16]. The Maximum Composite Likelihood method [17] was used to compute evolutionary distances. To understand the evolutionary relationship among the 69 identified beneficial microbial species, derived from the sediments of the rivers, Ganga and Yamuna, a multiple sequence analysis (MSA) was carried out using MEGA 6 software [18]. Relative abundance of beneficial bacteria was calculated using Kaiju Web Server. Comparison was done based on standard student t-test [19]. Heat map presentation was arranged using multiple experiment viewer (MeV), a standalone tool for visualizing the clustering of multivariate data [20]. The Principal Component Analysis (PCA) biplot and Scatterplot matrix along with correlation values between sampling sites and relative abundance of helpful bacteria were developed in JMP Pro 10 after the standardization of the estimated data.

Results

Sequence generation

Sediment samples from nine sites (Fig 1) of river Ganga (KAN-1, KAN-2, and KAN-3; FAR-1, FAR-2, and FAR-3) and river Yamuna (ND-1, ND-2, and ND-3) were analyzed using high throughput next-generation sequencing to identify the microbial biodiversity. The total number of high quality reads with their consequent data volume of each sediment samples are presented in Table 1. All the high quality reads obtained from the sediments of different sites were considered for sensitive taxonomic classification analysis. However, the taxonomic classification study could not classify all the reads. Only 41.58%, 49.35%, and 54.79% of the total reads were classified form Kanpur sediment samples (KAN-1, KAN-2, and KAN-3) of river Ganga, respectively. In Farakka sediment samples (FAR-1, FAR-2, and FAR-3) of river Ganga, only 50.82%, 52.08%, and 35.68% of the total reads were classified. Similarly, in New Delhi sediment samples (ND-1, ND-2, and ND-3) of river Yamuna, 53.37%, 38.95%, and 44.82% of the total reads were classified, respectively.

Table 1. Data details of nine sediment metagenome of river Ganga and Yamuna.

Location Description High quality reads (bp)
KAN-1 28,718,955
Kanpur KAN-2 33,703,138
KAN-3 33,887,572
FAR-1 24,929,338
Farakka FAR-2 29,128,182
FAR-3 54,496,302
ND-1 64,876,611
New Delhi ND-2 64,749,798
ND-3 62,670,420
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Taxonomical classification of sediment metagenome

Based on the taxonomical classification, a large number of beneficial bacterial species (Table 2) were identified from the sediment samples of the rivers, Ganga, and Yamuna. Four Vibrio (V. mediterranei, V. fluvialis, V. gazogenes, and V. alginolyticus), nine Bacillus (B. clausii, B. circulans, B. subtilis, B. coagulans, B. cereus, B. megaterium, B. mycoides, B. pumilus, and B. licheniformis), sixteen Lactobacillus (L. curvatus, L. brevis, L. casei, L. acidophilus, L. buchneri, L. crispatus, L. delbrueckii, L. fermentum, L. gasseri, L. helveticus, L. johnsonii, L. paracasei, L. plantarum, L. reuteri, L. rhamnosus and L. salivarius), five Bifidobacterium (B. animalis, B. bifidum, B. longum, B. breve, and B. adolescentis), three Shewanella (S. colwelliana, S. putrefaciens and S. xiamenensis), three Pediococcus (P. pentosaceus, P. Acidilactici and P. ethanolidurans), six Enterococcus (E. durans, E. faecium, E. faecalis E. raffinosus E. hirae and E. mundtii), four Pseudomonas (P. fluorescens, P. chlororaphis, P. stutzeri and P. synxantha), four Roseobacter (R. litoralis, R. denitrificans, R. litoralis and R. denitrificans), four Oenococcus (O. oeni, O. kitaharae, O. alcoholitolerans and O. oeni AWRIB429), two Carnobacterium (C. divergens and C. maltaromaticum), two Streptococcus (S. salivarius and S. thermophilus), two Vagococcus (V. fluvialis bH819 and V. teuberi) along with one each for, Aeromonas veronii, Leuconostocme senteroides, Micrococcus luteus, Paenibacillus polymyxa, and Lactococcus lactis were identified from the metagenome.

Table 2. Relative abundance of beneficial bacteria species identified from the nine sediment metagenome of river Ganga and Yamuna.

Name of the Genus Name of the species KAN-1 KAN-2 KAN-3 Average SD FAR-1 FAR-2 FAR-3 Average SD ND-1 ND-2 ND-3 Average SD
L. curvatus 0.00008 0.0002 0.00002 1.0E-04 9.17E-05 0.0001 0.0001 0.00009 9.7E-05 5.77E-06 0.0001 0.0001 0.0002 1.3E-04 5.77E-05
L. brevis 0.0001 0.0003 0.0002 2.0E-04 1.00E-04 0.0005 0.0003 0.0006 4.7E-04 1.5E-04 0.0003 0.0003 0.0003 3.0E-04 0
L. casei 0.0004 0.0006 0.0002 4E-04 2.00E-04 0.0008 0.0005 0.0004 5.7E-04* 2.1E-04 0.0001 0.0001 0.0001 1.0E-04* 0
L. acidophilus 0.00003 0.00004 0.00002 3E-05 1.00E-05 0.00009 0.00003 0.00004 5.33E-05 3.21E-05 0.00005 0.00004 0.00007 5.33E-05 1.52E-05
L. buchneri 0.00004 0.00009 0.00003 5.3E-05 3.2E-05 0.00009 0.00004 0.00008 7.0E-05 2.65E-05 0.00006 0.00008 0.00009 7.67E-05 1.52E-05
L. crispatus 0.0002 0.0004 0.0002 2.7E-04 1.2E-04 0.0003 0.0003 0.0002 2.7E-04 5.7E-05 0.0003 0.0002 0.0004 3.0E-04 1.0E-04
L. delbrueckii 0.0001 0.0003 0.0001 1.7E-04 1.2E-04 0.0003 0.0001 0.0001 1.7E-04 1.1E-04 0.0003 0.0003 0.0006 04.0E-04 1.7E-04
L. fermentum 0.0002 0.0003 0.00007 1.9E-04 1.2E-04 0.0003 0.0002 0.0002 2.3E-04 5.77E-05 0.0002 0.0003 0.0004 3.0E-04 1.0E-04
L. gasseri 0.0001 0.0003 0.0001 1.7E-04 1.2E-04 0.0002 0.0001 0.00006 1.2E-04 7.21E-05 0.0002 0.0001 0.0003 2.0E-04 1.0E-04
L. helveticus 0.00005 0.0001 0.00005 6.67E-05 2.88E-05 0.0001 0.00008 0.00006 8.0E-05 2.0E-05 0.0001 0.00008 0.0002 1.3E-04 6.4E-05
Lactobacillus L. johnsonii 0.00007 0.0001 0.00003 6.67E-05 3.5E-05 0.0001 0.0001 0.00007 9.0E-05 1.73E-05 0.0001 0.0001 0.0001 1.0E-04 0
L. paracasei 0.0001 0.0002 0.00008 1.3E-04 6.43E-05 0.0002 0.0001 0.0001 1.3E-04 5.77E-05 0.0001 0.0001 0.0002 1.3E-04 5.7E-05
L. plantarum 0.0003 0.0005 0.0003 3.7E-04 1.2E-04 0.0004 0.0003 0.0003 3.3E-04 5.77E-05 0.0006 0.0004 0.0007 5.7E-04 1.5E-04
L. reuteri 0.0003 0.0006 0.0002 3.7E-04 2.1E-04 0.0004 0.0003 0.0002 3.0E-04 1.0E-04 0.0006 0.0004 0.0007 5.7E-04 1.5E-04
L. rhamnosus 0.0002 0.0004 0.0001 2.3E-04 1.5E-04 0.0004 0.0002 0.0001 2.3E-04 1.5E-04 0.0002 0.0002 0.0003 2.3E-04 5.7E-05
L. salivarius 0.0003 0.0006 0.0002 3.7E-04 2.1E-04 0.0005 0.0003 0.0002 3.3E-04 1.5E-04 0.001 0.0005 0.001 8.3E-04 2.9E-04
B. clausii 0.001 0.001 0.0005 8.3E-04 2.89E-04 0.002 0.001 0.001 1.3E-03* 5.7E-04 0.0002 0.0004 0.0004 3.3E-04* 1.2E-04
B. circulans 0.0003 0.0006 0.0002 3.7E-04 2.08E-04 0.0005 0.0004 0.0003 4.0E-04 1.0E-04 0.0002 0.0004 0.0003 3.0E-04 1.0E-04
Bacillus B. subtilis 0.0006 0.0008 0.0004 6.0E-04 2.00E-04 0.001 0.0007 0.0006 7.7E-04 2.0E-04 0.0003 0.0008 0.0007 6.0E-04 2.6E-04
B. coagulans 0.001 0.002 0.0006 1.2E-03 7.21E-04 0.002 0.001 0.001 1.3E-03 5.7E-04 0.001 0.001 0.001 1.0E-03 0
B. cereus 0.003 0.004 0.002 3.0E-03 1.00E-03 0.006 0.003 0.007 5.3E-03 2.1E-03 0.003 0.004 0.004 3.7E-03 5.8E-04
B. megaterium 0.0006 0.001 0.0003 6.3E-04 3.51E-04 0.0009 0.0009 0.001 9.3E-04 5.77E-05 0.0005 0.001 0.0008 7.7E-04 2.5E-04
B. mycoides 0.0005 0.0006 0.0007 6.0E-04* 1.00E-04 0.0006 0.0005 0.0004 5.0E-04 1.0E-04 0.0002 0.0004 0.0004 3.3E-04* 1.2E-04
B. pumilus 0.0004 0.0006 0.0002 4.0E-04 2.00E-04 0.0008 0.0006 0.0004 6.0E-04 2.0E-04 0.0003 0.0008 0.0007 6.0E-04 2.6E-04
B. licheniformis 0.0002 0.0002 0.0001 1.07E-04 5.77E-05 0.0003 0.0002 0.0001 2.0E-04 1.0E-04 0.0001 0.0002 0.0002 1.7E-04 5.77E-05
P. pentosaceus 0.00007 0.0002 0.00006 1.1E-04 7.81E-05 0.0002 0.0002 0.0001 1.7E-04 5.77E-05 0.0003 0.0001 0.0002 2.0E-04 1.0E-04
Pediococcus P. acidilactici 0.008 0.008 0.1 3.9E-02 5.31E-02 0.0003 0.0003 0.0002 2.7E-04 5.77E-05 0.0003 0.0002 0.0003 2.7E-04 5.77E-05
P. ethanolidurans 0.00007 0.00008 0.00005 6.67E-05 1.53E-05 0.00007 0.00007 0.00004 6.0E-05 1.73E-05 0.00006 0.00006 0.00009 7.0E-05 1.73E-05
V. mediterranei 0.00005 0.00004 0.00005 4.67E-05 5.77E-06 0.0001 0.00004 0.00005 6.3E-05 3.2E-05 0.00003 0.00005 0.00005 4.3E-05 1.15E-05
Vibrio V. fluvialis 0.0002 0.0002 0.0003 2.3E-04 5.77E-05 0.0002 0.0002 0.0002 2.0E-04 0 0.0004 0.0001 0.0002 2.3E-04 1.5E-04
V. gazogenes 0 0 0 0.00 0 0 0 0 0.00 0.00 0.0003 0.0002 0.0003 2.7E-04** 5.77E-05
V. alginolyticus 0.0007 0.0008 0.0009 8.0E-04 1.00E-04 0.0009 0.0008 0.0005 7.3E-04 2.1E-04 0.001 0.0006 0.001 8.7E-04 2.3E-04
R. litoralis 0.001 0.001 0.003 1.6E-03 1.18E-03 0.0009 0.0006 0.0007 7.3E-04 1.5E-04 0.0020 0.0004 0.0005 9.7E-04 8.9E-04
Roseobacter R. denitrificans 0.001 0.0009 0.003 1.6E-03 1.18E-03 0.0007 0.0006 0.0006 6.3E-04 5.77E-05 0.0020 0.0004 0.0004 9.3E-04 9.2E-04
R. litoralis 149 0.00002 0.00003 0.00009 4.67E-05 3.79E-05 0.00002 0.00001 0.00001 1.3E-05 5.77E-06 0.000008 0.00001 0.000005 7.7E-06 2.5E-06
R. denitrificans 114 0.00006 0.00006 0.0002 1.1E-04 8.08E-05 0.00003 0.00003 0.00002 2.7E-05 5.77E-06 0.00008 0.00002 0.00003 4.3E-05 3.2E-05
Vagococcus V. fluvialis bH819 0 0 0 0* 0.00E+00 0 0 0.000002 6.7E-07* 1.15E-06 0.0003 0.0004 0.0006 4.3E-04** 1.5E-04
V. teuberi 0.0002 0.0005 0.0001 2.7E-04 2.08E-04 0 0.0003 0.0002 1.7E-04 1.5E-04 0.00006 0.00005 0.0001 7.0E-05 2.6E-05
O. oeni 0.0003 0.0004 0.0002 3.0E-04 1.00E-04 0.0004 0.0003 0.0002 3.0E-04 1.0E-04 0.0003 0.0003 0.0004 3.3E-04 5.77E-05
Oenococcus O. kitaharae 0.0002 0.0003 0.0001 2.0E-04 1.00E-04 0.0004 0.0002 0.0002 2.7E-04 1.1E-04 0.0001 0.0002 0.0002 1.7E-04 5.77E-05
O. alcoholitolerans 0.0001 0.0001 0.00006 8.67E-05 2.31E-05 0.0002 0.0001 0.00009 1.3E-04 6.1E-05 0.00008 0.0001 0.0002 1.3E-04 6.4E-05
O. oeni AWRIB429 0.00001 0.000006 0.000003 6.33E-06 3.51E-06 0.00002 0.00001 0.000004 1.1E-05 8.1E-06 0 0.000003 0.000002 1.67E-06 1.5E-06
P. fluorescens 0.04 0.01 0.02 2.3E-02 1.53E-02 0.01 0.008 0.008 8.7E-03 1.2E-03 0.01 0.005 0.007 7.3E-03 2.5E-03
Pseudomonas P. chlororaphis 0.002 0.002 0.003 2.3E-03 5.77E-04 0.002 0.002 0.001 1.7E-03 5.7E-04 0.002 0.001 0.001 1.3E-03 5.8E-04
P. stutzeri 0.008 0.02 0.02 1.6E-02 6.93E-03 0.008 0.006 0.006 6.7E-03 1.2E-03 0.02 0.005 0.009 1.13E-02 7.8E-03
P. synxantha 0.0002 0.0002 0.0003 2.3E-04 5.77E-05 0.0002 0.0001 0.0001 1.3E-04 5.7E-05 0.0003 0.0001 0.0001 1.7E-04 1.2E-04
S. colwelliana 0.0008 0.0006 0.0009 7.7E-04* 1.53E-04 0.0007 0.0005 0.0005 5.7E-04 1.2E-04 0.0005 0.0004 0.0005 4.7E-04* 5.77E-05
Shewanella S. putrefaciens 0.0003 0.0007 0.006 2.3E-03 3.18E-03 0.0003 0.0002 0.0002 2.3E-04 5.77E-05 0.0004 0.0002 0.0003 3.0E-04 1.0E-04
S. xiamenensis 0.0001 0.0003 0.0004 2.6-E04 1.53E-04 0.0002 0.0001 0.0001 1.3E-04 5.77E-05 0.0004 0.0001 0.0002 2.3E-04 1.5E-04
E. durans 0.00009 0.0002 0.00005 1.1E-04 7.77E-05 0.0001 0.0001 0.0001 1.0E-04 0 0.0001 0.0002 0.0003 2.0E-04 1.0E-04
E. faecium 0.0003 0.001 0.0002 5.0E-04 4.36E-04 0.0006 0.0003 0.0004 4.3E-04* 1.5E-04 0.001 0.0006 0.001 8.7E-04* 2.3E-04
Enterococcus E. faecalis 0.0006 0.002 0.0005 1.0E-03 8.39E-04 0.0008 0.0006 0.0005 6.3E-04 1.5E-04 0.001 0.0009 0.002 1.3E-03 6.1E-04
E. raffinosus 0.00001 0.00006 0.00001 2.67E-05 2.89E-05 0.00002 0.00001 0.00002 1.7E-05 5.77E-06 0.00004 0.00002 0.00005 3.67E-05 1.5E-05
E. hirae 0.00002 0.00009 0.00001 4.0E-05 4.36E-05 0.00007 0.00003 0.00003 4.3E-05 2.3E-05 0.0006 0.00007 0.0001 2.7E-04 3.0E-04
E. mundtii 0.0001 0.0003 0.00009 1.6E-04 1.18E-04 0.0002 0.0001 0.0001 1.3E-04 5.77E-05 0.0002 0.0002 0.0002 2.0E-04 0
B. animalis 0.0003 0.0004 0.0002 3.0E-04 1.00E-04 0.0004 0.0003 0.0002 3.0E-04 1.0E-04 0.0005 0.0002 0.0003 3.3E-04 1.5E-04
Bifidobacterium B. bifidum 0.0002 0.0004 0.0001 2.3E-04 1.53E-04 0.0003 0.0002 0.0002 2.3E-04 5.7E-05 0.003 0.0003 0.0008 1.4E-03 1.4E-03
B. longum 0.0004 0.002 0.0004 9.3E-04 9.24E-04 0.0004 0.0004 0.0004 4.0E-04 0 0.01 0.001 0.003 4.7E-03 4.7E-03
B. breve 0.0002 0.0005 0.0002 3.0E-04 1.73E-04 0.0004 0.0002 0.0002 2.7E-04 1.2E-04 0.002 0.0003 0.0008 1.0E-03 8.7E-04
B. adolescentis 0.0004 0.004 0.0007 2.0E-03 2.0E-03 0.0004 0.0003 0.0003 3.0E-04 1.0E-04 0.03 0.002 0.009 1.4E-02 1.5E-02
Carnobacterium C. divergens 0.0003 0.0006 0.0002 3.7E-04 2.1E-04 0.0003 0.0003 0.0002 2.7E-04 5.77E-05 0.0002 0.0003 0.0004 3.0E-04 1.0E-04
C. maltaromaticum 0.0004 0.001 0.0003 5.7E-04 3.8E-04 0.0006 0.0004 0.0004 4.7E-04 1.2E-04 0.0005 0.0004 0.0007 5.0E-04 1.5E-04
Lactococcus L. lactis 0.0007 0.002 0.0004 1.03E-03 8.5E-04 0.001 0.0008 0.0006 8.0E-04 2.0E-04 0.001 0.0009 0.002 1.3E-03 6.0E-04
Leuconostock L. mesenteroides 0.0002 0.0005 0.002 9.0E-04 9.6E-04 0.0003 0.0002 0.0002 2.3E-04 5.77E-05 0.0007 0.0003 0.001 6.7E-04 3.5E-04
Micrococcus M. luteus 0.0007 0.003 0.0009 1.5E-03 1.3E-03 0.002 0.001 0.0008 1.3E-03 6.4E-04 0.001 0.0004 0.0006 6.7E-04 3.0E-04
Streptococcus S. salivarius 0.00007 0.0003 0.00002 1.3E-04 1.5E-04 0.00009 0.00004 0.00005 6.0E-05 2.64E-05 0.0004 0.0001 0.0004 3.0E-04 1.7E-04
S. thermophilus 0.00009 0.0003 0.00005 1.5E-04 1.3E-04 0.0001 0.00008 0.00007 8.3E-05** 1.5E-05 0.0003 0.0003 0.0004 3.0E-04** 5.77E-05
Paenibacillus P. polymyxa 0.0009 0.001 0.0005 8E-04 2.6E-04 0.001 0.001 0.0008 9.0E-04 1.2E-04 0.0008 0.001 0.001 9.3E-04 1.2E-04
Aeromonas A. veronii 0.001 0.002 0.004 2.3E-03 1.5E-03 0.0008 0.0006 0.0006 6.7E-04 1.2E-04 0.002 0.0006 0.0009 1.2E-03 7.3E-04
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p≤0.05 * p≤0.01** denote the level significance in Student t-test among average value in the respective row.

Phylogenetic analysis

MSA revealed that the majority of the species showed diversity. Phylogenetic tree analysis delineated that, all the species shaped five different clusters (Fig 2). In the first CLUSTER, S. thermophilus and L. brevis derived from Yamuna and Farakka sediment samples respectively were found phylogenetically very close to each other with the bootstrap value of 34. In CLUSTER-2, E. faecium and L. johnsonii, derived from Yamuna and Farakka sediment samples respectively, were found very close to each other with a bootstrap value of 14. Similarly, in CLUSTER-3, L. fermentum and L. helveticus derived from Kanpur and Yamuna sediment samples respectively, were found phylogenetically related with a high bootstrap value of 71. In CLUSTER-4, P. pentosaceus and B. adolescentis both derived from Yamuna sediment samples were found close to each other with the bootstrap value of 19. The highest numbers of evolutionary closed beneficial microbiome species were found in CLUSTER-5. L. gasser and B. mycoides derived from Kanpur and Yamuna sediment samples were found close to each other with a bootstrap value of 54.

Fig 2. Phylogenetic tree of 69 identified genome of helpful bacterial species derived from the sediments metagenome of the river Ganga and Yamuna.

Fig 2

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Relative abundance at different sites

In the classified metagenomics data, a total of 69 species of the bacteria from 18 different genera were considered for analysis. Heat map analysis showed a clear distinction in the relative abundance of different bacteria between Kanpur and Farakka sediment samples of river Ganga. Similarly, the prevalence of beneficial bacterial species in the sediment samples of river Yamuna was also different from Kanpur and Farakka stretches of river Ganga (Fig 3).

Fig 3. Heat map of relative species abundance of identified beneficial bacteria from nine different sediment metagenome.

Fig 3

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Heat map showing 69 species of beneficial bacteria with significant differences of relative abundances among the nine sampling sites of river Ganga and Yamuna.

Relative abundance analysis revealed that the species L. curvetus and L. brevis were present in similar proportion in sediment samples of all the nine sampling sites of the two rivers; however, L. casei was present in relatively high proportion at Farakka stretch of river Ganga with statistical significance (p-value of 0.02). B. clausii was found in a high proportion (p≤0.05) at Farakka stretch whereas, B. mycoides found in a high proportion (p≤0.05) at Kanpur stretch of river Ganga. Our metagenomic data showed that, one species of Vibrio (V. harveyi) which showed differential relative abundance between three locations (Kanpur, Farakka and New Delhi) and was found relatively lower (p≤0.05) proportion at New Delhi stretch of river Yamuna as compared to Kanpur stretch of river Ganga. Similarly, S. colwelliana was found in a higher proportion (p≤0.05) at Kanpur stretch of river Ganga. E. faecium was found in high proportion at New Delhi stretch of river Yamuna as compared to other locations (p≤0.05) (Table 2).

Based on the taxonomical hierarchy, it was revealed that, in all the three locations (Kanpur, Farakka, and New Delhi), L. curvatus had similar relative abundances. The species, L. brevis also showed a similar trend, however, its relative abundance was comparatively higher in the sediment samples of Farakka stretch of river Ganga. The L. casei showed lower abundance in sediment samples at New Delhi stretch of river Yamuna as compared to the other two sites of river Ganga (Fig 4A). Among the Pediococcus population, it is interesting to note that, in the sediment metagenome of Kanpur site of river Ganga, the P. acidilactici was (Student’s t-test, p ≤0.05) dominant over the all taxonomical profile; however, P. pentosaceus and P. ethanolidurans showed equal distribution among the sediment metagenomes at Farakka of river Ganga and New Delhi of river Yamuna (Fig 4B). Likewise, Pseudomonas population showed an equal distribution of relative abundance in all the nine sites. However, P. fluorescens, P. chlororaphis showed (Student’s t-test, p ≤0.05) relative abundance value at Kanpur (Fig 4C). Among the Enterococcus spp., E. durans, E. malodoratus, E. raffinosus, E. hirae, and E. mundtii showed non-significant differences among the nine sampling sites. E. faecium and E. faecalis showed higher abundance (Student’s t-test, p ≤0.05) in sediment metagenomes of river Yamuna compared to Kanpur and Farakka stretch of river Ganga (Fig 4D).

Fig 4. Relative abundance of beneficial microbes on the basis of their taxonomical profile, where A, B, C, and D represent Lactobacillus, Prediococcus, Pseudomonas and Enterococcus groups of different beneficial microbes respectively.

Fig 4

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(A) L. casei showed significantly (Student’s t-test, p ≤0.05) lower abundance in New Delhi as compared to rest two locations. (B) Prediococcus pentosaceus and Prediococcus ethanolidurans showed equal abundance among the Farakka and New Delhi locations. Prediococcus acidilacticiis significantly dominant over the all taxonomical profile at Kanpur (Student’s t-test, p ≤0.05). (C) Found significant difference (Student’s t-test, p ≤0.05) for Pseudomonas fluorescens, Pseudomonas chlororaphis. (D) Enterococcus faecium and Enterococcus faecalis showed higher abundance (Student’s t-test, p ≤0.05) in Kanpur and Farakka, respectively.

The biplot of principal component analysis (PCA), the PC1, and PC2 altogether could explain 64% variability in the data which showed that the sites at Farraka are closely associated and sites at Kanpur and New Delhi are diverse about the relative abundance of beneficial bacteria (Fig 5A). The relative abundance of beneficial bacteria is found to be closely associated at site FAR-1, KAN-2, KAN-3, ND-1, ND-2, and ND-3. Further, PCA showed that Lactobacillus spp. group of beneficial bacteria are more associated with sites KAN-2 and ND-3; whereas Bacillus spp. are more associated with FAR-2 and ND-2. The Scatter plot matrix showed the correlation between the sites about the relative abundance of beneficial bacteria (Fig 5B). Highest positive correlation was found between ND-2 and ND-3 (r = 0.48) followed by FAR-1 and FAR-2 (r = 0.36) and KAN-1 and KAN-3 (r = 0.33).

Fig 5. Biplot of identified helpful bacterial species using Principal Component Analysis (PCA) between two principal component PC1 and PC2 of the river Ganga and Yamuna.

Fig 5

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Discussion

The study found that, the river Ganga and Yamuna host several beneficial bacterial genera with enormous taxonomical diversities. Altogether the study could identify 69 beneficial species belonging to 18 genera (Table 2). All the identified beneficial bacteria with their proposed mechanism of action are represented in S1 and S2 Tables. The bacterial communities and their functional genomics in sediments and water of the Apies River, South Africa were analyzed using Metagenomic data. Higher diversity in the microbial species associated with the different land uses in the water and sediments of the Apies River was revealed in this study [21]. The taxonomic classification was also previously used to classify microbe strains with consistent categorization at the species level with appropriate safety evaluation, quality assurance, and non-fraudulent labeling [15, 22–26]. In the present study, the beneficial bacterial species under genus Lactobacillus (L. curvatus, L. brevis, L. helveticus, L. gasseri, L. crisptus and L. casei, etc.) were identified. These Lactobacillus species were reported to exert their beneficial effects by reducing soreness in inflammatory bowel disease (IBD) by producing anti-inflammatory cytokine [27], antibiotic and bacteriostatic activity by the production of bacteriocins [28], and anti-stress activity by the production of β-galactosidase enzymes [29]. L. curvatus, was reported to lower the cholesterol level through enhancement of esterase, lipase, cysteine arylamidase, and β-galactosidase activities in the host organisms [30]. Vibrio spp. were reported to cause health benefits to the host organism by improving disease resistance through the production of bacteriocin-like substance [31], alteration in the hepatosomatic index, and haemocytes number [32]. Bacillus spp. found in the present study were reported to enhance growth, survivability and disease resistance of Labeo rohita, and Macrobrachium rosenbergii etc. through increased alkaline phosphatase activity, globulin content and lysozyme level [33], enhancement of serum lysozyme activity and serum IgM level [34], increased LYZ gene expression [35], etc. The identified Bifidobacterium spp., (B. animalis, B. bifidum, B. longum, B. breve and B. adolescentis, etc.) were reported to attenuate autoimmune encephalomyelitis by inhibiting mononuclear infiltration into the central nervous system [36], diminish gastrointestinal distress by stimulating the production of gastric mucin and other gastrointestinal or neuropeptide hormones [37], anti-obese activities by inhibition of lipid deposit in the liver and adipose tissues [38], alleviate of high-fat diet-induced colitis by inhibition of NF-κB activation and lipopolysaccharide production by gut microbiota [39]. Similarly, Pediococcus spp. was reported to cause many health benefits viz. P. acidilactici was reported to advance reproductive performance [40], P. pentosaceus has anti-inflammation and anti-cancer effects through mitigation of azoxymethane-induced toxicity [41], P. ethanol idurans enhances health through the production of high levels of cellular antioxidant and amplified bile salt hydrolase activities [42]. The identified Enterococcus faecalis, was reported to enhance anti-oxidative activity and anti-tumor activity by NK cells and TNF-α [42]. E. raffinosus which was reported to prevent bacterial infection in Labeo rohita and Labeo catla from E. coli, A. hydrophilla, S. aerous, S. typhimurium [43]. The identified E. hirae, reported producing lipase and bile salt hydrolase enzyme with antioxidant properties, and E. mundtii reported with antimicrobial activity [44]. Four Roseobacter spp., identified from the sediment metagenomes, were reported with therapeutic value for commercial aquaculture. Earlier, several Roseobacter sp. were also reported to reduce fish pathogenic bacteria V. anguillarum by R. clade [45].

The phylogenetic tree analysis showed that the majority of the species are evolutionary diverse. The phylogenetic tree of all the identified beneficial bacteria species was shaped in five different clusters. In CLUSTER-3, L. fermentum and L. helveticus derived from Kanpur and Yamuna sediment samples respectively were found phylogenetically related with a high bootstrap value of 71. A similar observation was reported from Lactobacillus spp. isolated from animal faeces and it was found that, L. salivarius phylogenetic group was closely related to L. animalis, L. apodemi, and L. Murinus [46]. The present finding could be corroborated with a previous report where Lactococcus and Streptococcus appeared to be closely related and Lactobacillus was found to be phylogenetically diverse [27]. The intermixing of phylogenetic distribution, as observed from our study, was also reported previously where Lactobacillus and Pediococcus were phylogenetically intermixed with 5 species of Pediococcus [47]. The Lactobacillus chromosomes also expressed the high heterogeneity at phylogenetic, phenotypic, and ecological levels amid the different members of this genus [48]. The present study also found heterogeneity of clustering in Lactobacillus species and other beneficial bacteria.

Relative abundance study showed that beneficial bacteria species of different genera were variedly distributed among the three locations; few species are highly dominant in one location over others, viz. Pediococcus acidilactici was highly abundant in Kanpur location of river Ganga as compared to other locations. The PCA analysis also showed that the sites at Farraka are closely associated and sites at Kanpur and New Delhi are diverse about the relative abundance of beneficial bacteria. This location-specific change of microbial diversity in the river sediments might be due to differential physiochemical properties and pollution level of the collected sediments. The primary reason for this difference might be due to the release of heavy organic loads and toxic substances (heavy metals, hazardous chemicals, etc.) in some of the selected locations (Kanpur and New Delhi) of these riverine ecosystems through the release of untreated sewage and industrial wastes. It was reported that Kanpur stretch of river Ganga is highly polluted by the untreated effluents from hundreds of tannery industries present in the river bank [49–50]. Very high quantities of diverse heavy metals like Cr, Cu, Pb, Ni, Zn, etc. were found extensively in the water and in the sediments of river Ganga in Kanpur, where pesticide residue like α-HCH, γ-HCH, Dieldrin and Malathion were also reported with a concentration range from 0.190±0.02 to 2.61±0.05 μg/L2 [51]. However, the Farakka stretch of the river Ganga was reported to be less polluted [52]. Like Kanpur stretch of river Ganga, the New Delhi stretch of the river Yamuna was also reported to be severely polluted by heavy metal pollutions due to the release of untreated metropolitan swages, factory effluents, etc. [53, 54]. Therefore, we presume it might be the reason for differences in the relative abundance of beneficial bacteria species among different locations in the river Ganga and Yamuna. Our results could be supported by the previous finding, where the proportion of beneficial microbes in the gastrointestinal microbiota of Bufo raddei was altered due to heavy-metal pollution [55]. This is the first report on the identification of beneficial bacteria in the sediments of the river Ganga and Yamuna, using a metagenomic approach. This study revealed extensive insights on the abundance of native important beneficial microorganisms in these rivers and their functional properties.

Conclusion

Our research indicates that the sediment metagenome of the river Ganga and Yamuna manifests the enriched microbial distribution of beneficial bacteria. The phylogenetic study of identified useful microbial species revealed that the majority of the species are evolutionarily diverse. This study also refers to the clear distinction in the relative abundance of different beneficial bacteria across the sampling sites. Isolation of different beneficial bacteria from these riverine ecosystems would be highly useful for industrial applications in the future.

Supporting information

S1 Table. Health benefit of identified bacteria and their proposed mechanism of action.

(DOCX)

Click here for additional data file. (38KB, docx)
S2 Table. Relative abundance of beneficial bacteria species identified from the nine sediment metagenome of river Ganga and Yamuna.

(DOCX)

Click here for additional data file. (46KB, docx)

Acknowledgments

Authors are thankful to Mr. Asim Kumar Jana, Senior Technical Assistant, ICAR-CIFRI, Barrackpore, Kolkata, India for sampling and technical assistance. This work has been carried under CABin Scheme.

Data Availability

The metagenomic sequences used in this study have been submitted to the NCBI-SRA database under Accession Nos: SRP190174, SRP190175, SRP189880, SRP191076, SRP191079, SRP191075, SRP191073, SRP191080, and SRP191499.

Funding Statement

The authors received no specific funding for this work.

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Decision Letter 0

Manas Ranjan Dikhit

9 Jun 2020

PONE-D-20-11686

Metagenome analysis from the sediment of river Ganga and Yamuna: In search of health beneficial microbiome

PLOS ONE

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Comments to the Author

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Reviewer #1: No

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #2: Yes

**********

5. Review Comments to the Author

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Reviewer #1: This manuscript by Behera BK et al describes distribution of various beneficial bacterial species in the sediments of two Indian rivers (Ganga and Yamuna) using shutgun metagenomic approach. In this study the authors generated sequencing reads for nine sampling sites; with three sites from three geographically distant regions along the river banks makes the experimental design well thoughtful. They primarily analyzed the sequencing reads using bioinformatics tools and compared average number of species in these three regions. Through system biology based approaches they tried to elucidate the functional relevance of some selected bacteria to aquatic environment.

The study seems to be interesting and well relevant. Although the manuscript depicts to address the problem, it lacks clarity in many aspects and should be addressed before acceptance.

My major concerns are :

1. The criteria used for construction of the beneficial bacteria list is incomprehensible. It looks very strange that beneficial effects of each of these 69 bacteria (Supplementary Table 1) were evidenced by only one study. A simple pubmed search indicates that several of them have pathogenic effect to aquatic organisms. For example, Vibrio mediterranei is associated to major mortality in Pinna nobilis (https://www.sciencedirect.com/science/article/abs/pii/S0044848619324494). Some have role in serious human health hazards. For example consumption of fish infected with V. fluvialis has been reported to cause mild to moderate dehydration, vomiting, fever, abdominal pain and diarrhoea (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2996184/). There are many more such bacteria from this list which has been reported to be associated with serious illness in human and other aquatic organisms. So authors need to define a clear criteria for this classification and provide more than one evidence supporting their health benefit.

2. The abstract describes that a total of 242 health beneficial bacteria were identified. However, rest of the manuscript discusses only 69 (Heatmap figure legend says 67 species). While Kaiju web server performs taxonomic classification of sequencing reads, it is unclear from the manuscript whether the list of beneficial bacteria was created before performing the all data analysis or bacteria names (form Kaiju results) were selected later after a manual literature search?

3. The method section is ambiguous and insufficient to reproduce the results independently. Important analyses such as relative abundance calculation and statistical methods used for significance tests have not been described sufficiently.

4. In many cases the input data are not clear. For example, the inputs for multiple sequence analysis (or multiple sequence alignment???), species Phylogeny construction and PCA are not clear form the text.

5. The purpose of Phylogenetic analysis should be discussed appropriately. The authors conclude that "some of the microbial species are highly conserved throughout the evolution". How come a species can be conserved? Genes/proteins are conserved during evolution of a lineage.

- Bootstrap is a score to show confidence of relatedness or similarily in a clade and does not refer to species closeness.

- Pg 15: What is "evolutionary closed supportive microbiome"??

- Pg 20: What is the difference between "Circular Cladogram" and "Cladogram"?

6. The Relative abundance calculation is totally unclear. In biodiversity studies usually it refers to the number of individuals from i-th speceis divided by total number of individuals from a sample (10.1590/S1516-89132012000200014). It would be useful if the authors provide a concise definition of this index at species level.

7. The GO enrichment and pathway enrichment does not show any relation with heavy metal re-mediation. Mere presence of HMA domain in one protein from one species should not be concluded as "potential heavy metal remediating property". This result should be reported in a subtle way.

8. The rationale behind the STRING protein-protein interaction is not clear.

9. In introduction, the manuscript describes that there are many studies on discovering microbiome from natural streams of other countries. However, in the discussion the results obtained from present study were not compared enough with results from past metagenomic studies. The discussion should put the results in a more broader context.

10. The conclusion that "sediment metagenome of the river Ganga and Yamuna manifests the enriched microbial distribution of health beneficiary microbes" seems biased. Since the study analyses pre-selected list of 69 species, whether the samples are enriched in beneficial bacteria or not is difficult to conclude.

## Minor Comments

1. Lack of page and line numbers in the manuscript makes it hard to review. I have tried to write the exact phrase so that the authors can find the concerned lines.

2. Reference-1 seems bit out of context. Also the list of authors seems incomplete (Compare with this https://www.scienceopen.com/document?vid=b20de2d9-e8dd-478e-8e2b-5fb9d967b6ea)

3. Pg -12 "of health beneficialmicrobiome" should be "beneficial microbiome"

4. Substitution models and number of bootstrap replicate number should be mentioned in a phylogenetic analysis.

5. For all software tools please provide appropriate citation. Citations help the labs to receive funding and maintain the tool.

6. Pg-12: "each sample were then assembled into scaffolds using CLC". Please provide the number of scaffolds and their average length. There is no information about these scaffolds in the results.

7. Pg 14: Please fix the scientific names: Bacillus Clausii, Enterococcus Hirae, Leuconostocme senteroides, Pediococcus Acidilactici,

Pseudomonas Stutzeri, Roseobacter Litoralis

8. Pg-14: "four Roseobacter (R. litoralis, R. denitrificans, R. Litoralis and R. denitrificans)"- R. litoralis and R. Litoralis are similar or diffenent. It makes the list fof species to 68.

9. Multiple species has Similar genus abbreviation. Consider using two letter abbreviation; for example Vi. mediterranei and Va. fluvialis bH819.

10. "Lactococcuslactis " should be Lactococcus lactis ???

11. "Leuconostocme senteroides" should be Leuconostoc mesenteroides ???

12. "boot strap" or bootstrap ???

13. Pg 15: Heatmap is a way of data representation. What is Heatmap analysis??

14. Pg 15: "beneficialspecies in the" should be "beneficial species in the" ??

15. The term "significantly" should be used more cautiously. It should be used only for statistical tests and the alpha (p-value) must be specified.

16. The term "a large number of" seems very vague. Rather, shuch numbers should be descried in a quantitative manner (in terms of percentage).

17. Pg 35: I would suggest to replace Table 2 with a box-plot. It would reduce the number of pages while making the results more informative and attractive.

18. The bootstrap values should be displayed on the tree in appropriate way.

My intention behind extensive comments should be taken in a constructive manner to improve the manuscript.

Thank you.

Reviewer #2: In the manuscript PONE-D-20-11686 authors have performed metagenome analysis to identify microbes with favorable health outcome to humans as well as all other strata of organisms present in the trophic pyramid. Through contemporary high throughput method authors have reported presence of Lactobacillus, at Farakka stretch of river Ganga and at New Delhi stretches of river Yamuna, whereas Roseobacter spp. was found to be highly enriched at Kanpur sites of river Ganga. Such finding would definitely helpful in isolating beneficial microbes from river sediments for future industrial application. The article meets scientific standard for publication.

However, authors may carry out minor revision to improve quality of the manuscript.

1. In method logic behind setting up string analysis parameter could be mentioned.

2. Authors could mention limitations and future direction of the study in the conclusion.

**********

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Reviewer #1: Yes: Kanhu Charan Moharana

Reviewer #2: Yes: Dr. Dibyabhaba Pradhan

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PLoS One. 2020 Oct 6;15(10):e0239594. doi: 10.1371/journal.pone.0239594.r002

Author response to Decision Letter 0

7 Sep 2020

Response to reviewers

Comment

We note that Figure 1 in your submission contain map/satellite images which may be copyrighted. All PLOS content is published under the Creative Commons Attribution License (CC BY 4.0), which means that the manuscript, images, and Supporting Information files will be freely available online, and any third party is permitted to access, download, copy, distribute, and use these materials in any way, even commercially, with proper attribution. For these reasons, we cannot publish previously copyrighted maps or satellite images created using proprietary data, such as Google software (Google Maps, Street View, and Earth). For more information, see our copyright guidelines:

http://journals.plos.org/plosone/s/licenses-and-copyright.

Thank you for letting us know the Map in Figure 1 was created used ArcGIS 10.2.1 platform.

Before we proceed, please also clarify where the data used in the map is from. If the authors used their own data for the map, please let us know.

Response

Thanks for suggestion.

As per the suggestion, the Figure 1 has been modified using ArcGIS 10.2.1 platform.

The data used in preparation of the map was own data of the authors.

Reviewer # 1

Comment 1

The criteria used for construction of the beneficial bacteria list are incomprehensible. It looks very strange that beneficial effects of each of these 69 bacteria (Supplementary Table 1) were evidenced by only one study. A simple pubmed search indicates that several of them have pathogenic effect to aquatic organisms. For example, Vibrio mediterranei is associated to major mortality in Pinna nobilis(https://www.sciencedirect.com/science/article/abs/pii/S0044848619324494). Some have role in serious human health hazards. For example consumption of fish infected with V. fluvialis has been reported to cause mild to moderate dehydration, vomiting, fever, abdominal pain and diarrhoea(https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2996184/). There are many more such bacteria from this list which has been reported to be associated with serious illness in human and other aquatic organisms. So authors need to define clear criteria for this classification and provide more than one evidence supporting their health benefit.

Response

The beneficial effects of the identified bacteria from the metagenome sequence data were verified again with more literatures to confirm. Study revealed that, few strains of the identified bacterial species are beneficial in nature; however same bacterial species are also pathogenic which may be due to different strains of same species. The pathogenic activities of the same bacterial species may be due to the variations in genome. They may be representing different ecotype or biotype. The details have been provided as Supplementary Table S1 and S2.

Comment 2

The abstract describes that a total of 242 health beneficial bacteria were identified. However, rest of the manuscript discusses only 69 (Heatmap figure legend says 67 species). While Kaiju web server performs taxonomic classification of sequencing reads, it is unclear from the manuscript whether the list of beneficial bacteria was created before performing the all data analysis or bacteria names (form Kaiju results) were selected later after a manual literature search?

Response

The MS has been modified. The 69 helpful bacteria have been reported in this MS instead of 242. Heat map figure legend has been changed accordingly. The list of bacteria names (form Kaiju results) were selected after a manual literature search.

Comment 3

The method section is ambiguous and insufficient to reproduce the results independently. Important analyses such as relative abundance calculation and statistical methods used for significance tests have not been described sufficiently.

Response

Thanks for suggestion.

The identified beneficial bacteria found in our metagenomic data were manually checked with NCBI references for conformation. Relative abundance of beneficial bacteria was calculated using Kaiju Web Server. Comparison was done based on standard student t-test following the Reference Imchen et al., 2018. They did similar kind of metagenomic research.

Comment 4

In many cases the input data are not clear. For example, the inputs for multiple sequence analysis (or multiple Sequence alignment???), species Phylogeny construction and PCA are not clear from the text.

Response

The Phylogenetic tree has been reconstructed and PCA analysis has been revised.

Comment 5

The purpose of Phylogenetic analysis should be discussed appropriately. The authors conclude that "some of the microbial species are highly conserved throughout the evolution". How come a species can be conserved? Genes/proteins are conserved during evolution of a lineage.

- Bootstrap is a score to show confidence of relatedness or similarity in a clade and does not refer to species closeness.

- Pg 15: What is "evolutionary closed supportive microbiome”??

- Pg 20: What is the difference between "Circular Cladogram" and "Cladogram"?

Response

The Phylogenetic tree has been reconstructed considering 69 identified helpful bacteria with the Bootstrap values. The phylogenetics description part in the MS has been modified accordingly.

Comment 6

The Relative abundance calculation is totally unclear. In biodiversity studies usually it refers to the number of individuals from i-th pecies divided by total number of individuals from a sample (10.1590/S1516-89132012000200014). It would be useful if the authors provide a concise definition of this index at species level.

Response

Thanks for suggestion.

Relative abundance was calculated from total number of bacterial population generated from metagenomic sequences. The MS has been modified as suggested by the Reviewer.

Comment 7

The GO enrichment and pathway enrichment does not show any relation with heavy metal re-mediation. Mere presence of HMA domain in one protein from one species should not be concluded as "potential heavy metal remediating property".

This result should be reported in a subtle way.

Response

The Functional metagenomics analysis in the Result section of the MS has been removed. The same in the Methods and Discussion part of the MS has also been removed.

Comment 8

The rationale behind the STRING protein-protein interaction is not clear.

Response

STRING protein-protein interaction part has been removed from the MS.

Comment 9

In introduction, the manuscript describes that, there are many studies on discovering microbiome from natural streams of other countries. However, in the discussion the results obtained from present study were not compared enough with results from past metagenomic studies. The discussion should put the results in a more broader context.

Response

As suggested by the reviewer, the results obtained from present study has been compared with results from past metagenomic studies in the discussion.

Comment 10

The conclusion that "sediment metagenome of the river Ganga and Yamuna manifests the enriched microbial distribution of health beneficiary microbes" seems biased. Since the study analyses pre-selected list of 69 species, whether the samples are enriched in beneficial bacteria or not is difficult to conclude.

Response

The 69 species of helpful bacteria were identified from our Metagenome data and confirmed with published literatures about their benefits. The detail information has been provided in the Supplementary Table S1 and S2.

Minor Comments

Comment 1

Lack of page and line numbers in the manuscript makes it hard to review. I have tried to write the exact phrase so that the authors can find the concerned lines.

Response

Modified the MS as suggested

Comment 2

Reference-1 seems bit out of context. Also the list of authors seems incomplete (Compare with this

https://www.scienceopen.com/document?vid=b20de2d9-e8dd-478e-8e2b-5fb9d967b6ea)

Response

Reference-1 has been removed from the MS

Comment 3

Pg -12 "of health beneficial microbiome" should be "beneficial microbiome"

Response

Modified the MS as suggested

Comment 4

Substitution models and number of bootstrap replicate number should be mentioned in a phylogenetic analysis.

Response

The bootstrap replicate number have been mentioned in the phylogenetic tree

Comment 5

For all software tools please provide appropriate citation. Citations help the labs to receive funding and maintain the tool.

Response

Modified the MS as suggested

Comment 6

Pg-12: "each sample was then assembled into scaffolds using CLC". Please provide the number of scaffolds and their Average length. There is no information about these scaffolds in the results.

Response

Modified the MS as suggested

Comment 7

Pg 14: Please fix the scientific names: Bacillus Clausii, Enterococcus Hirae, Leuconostocme senteroides, Pediococcus Acidilactici, Pseudomonas Stutzeri, Roseobacter Litoralis

Response

Corrected the MS as suggested

Comment 8

Pg-14: "four Roseobacter (R. litoralis, R. denitrificans, R. Litoralis and R. denitrificans)"- R. litoralis and R. Litoralis are similar or different. It makes the list of species to 68.

Response

Corrected the MS as suggested

Comment 9

Multiple species has Similar genus abbreviation. Consider using two letter abbreviation; for example Vi. Mediterranei and Va. fluvialis bH819.

Response

Corrected the MS as suggested

Comment 10

"Lactococcuslactis " should be Lactococcus lactis ???

Response

Corrected the MS as suggested

Comment 11

"Leuconostocme senteroides" should be Leuconostoc mesenteroides ???

Response

Corrected the MS as suggested

Comment 12

"boot strap" or bootstrap ???

Response

Corrected the MS as suggested

Comment 13

Pg 15: Heatmap is a way of data representation. What is Heatmap analysis??

Response

Corrected the MS as suggested

Comment 14

Pg 15: "beneficial species in the" should be "beneficial species in the”??

Response

Corrected the MS as suggested

Comment 15

The term "significantly" should be used more cautiously. It should be used only for statistical tests and the alpha (pvalue) must be specified.

Response

Modified the MS as suggested

Comment 16

The term "a large number of" seems very vague. Rather, such numbers should be described in a quantitative manner (in terms of percentage).

Response

Modified the MS as suggested

Comment 17

Pg 35: I would suggest replacing Table 2 with a box-plot. It would reduce the number of pages while making the results more informative and attractive.

Response

Thanks for suggestion

Tabular form in the MS would be more useful

Comment 18

The bootstrap values should be displayed on the tree in appropriate way.

Response

The bootstrap values have been displayed on the tree in appropriate way

Reviewer # 2

Comment 1

In method logic behind setting up string analysis parameter could be mentioned.

Response

The string analysis part has been removed from the MS.

Comment 2

Authors could mention limitations and future direction of the study in the conclusion.

Response

The MS has been modified as suggested

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file. (23KB, docx)

Decision Letter 1

Manas Ranjan Dikhit

10 Sep 2020

Metagenome analysis from the sediment of river Ganga and Yamuna: In search of beneficial microbiome

PONE-D-20-11686R1

Dear Dr. Behera,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Manas Ranjan Dikhit

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Manas Ranjan Dikhit

25 Sep 2020

PONE-D-20-11686R1

Metagenome analysis from the sediment of river Ganga and Yamuna: In search of beneficial microbiome

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Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Table. Health benefit of identified bacteria and their proposed mechanism of action.

    (DOCX)

    Click here for additional data file. (38KB, docx)
    S2 Table. Relative abundance of beneficial bacteria species identified from the nine sediment metagenome of river Ganga and Yamuna.

    (DOCX)

    Click here for additional data file. (46KB, docx)
    Attachment

    Submitted filename: Response to Reviewers.docx

    Click here for additional data file. (23KB, docx)

    Data Availability Statement

    The metagenomic sequences used in this study have been submitted to the NCBI-SRA database under Accession Nos: SRP190174, SRP190175, SRP189880, SRP191076, SRP191079, SRP191075, SRP191073, SRP191080, and SRP191499.

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