Post-monsoon seasonal variation of prokaryotic diversity in solfataric soil from the North Sikkim hot spring

The solfataric soil sediments of the hot springs of Sikkim located at Yume Samdung and Lachen valley were studied for deciphering the bacterial diversity. The main aim here is to present a comparative study and generate a baseline data on the post-monsoon seasonal variation for the months of October and December, analyzed through 16S rRNA V3-V4 amplicon sequencing. The results have shown that there is not much variation at phylum level in the month of October in all the three hot springs such as New Yume Samdung (NYS), Old Yume Samdung (OYS), and Tarum (TAR) hot spring. The abundant phyla mainly present were Firmicutes, followed by Proteobacteria, Actinobacteria, and Bacteroidetes. Similarly, in the month of December, Firmicutes, Proteobacteria, Actinobacteria, and Bacteroidetes were prevalent; however, the percent relative abundance of these phyla in the month of December is relatively less. Besides this decrease in percent abundance, it was interestingly seen that relatively more phyla were found contributing towards the bacterial diversity in the month of December. Similar to phylum level, at genus level, there was not much variation seen among various prevalent genera of the three studied hot springs in both months. The major genera prevalent in both months among all the three hot springs were followed by Bacillus, Desulfotomaculum, Lactobacillus, and Paenibacillus. A similar trend was also seen at gene level that relative abundance of various genera was higher in the month of October but more genera were found to be contributing towards bacterial diversity in the month of December. Few distinct genera were found to be more abundant in the month of December such as Rhodopirellula and Blastopirellula. The results may conclude that there is not much variation in the abundance and type of bacterial communities during the post-monsoon season in the month of October and December. However, this may be assumed that there is the accumulation or increase in the bacterial communities during the winter (relatively higher temperature among hot springs) and may favor few mesophilic and more thermophilic communities as well.


Introduction
The most prodigious gift of nature if anyone has to consider then undoubtedly has to be the extreme environmental conditions. The word "extreme" has been concocted by mankind as the abiotic parameters governing these niches or ecosystem are beyond human adaptive physiological capabilities. Our cognitive functioning and metabolomics cannot explain or survive the ruthlessness of nature's extreme ecosystems be it on the basis of temperature or pH or salinity or atmospheric pressure among other factors. The countenance of hot springs is their invaluable microbial communities which has gained impetus in recent decades (Pedron et al. 2019). The hot spring microbiology is regarded as the hotspot of research in the arena of microbial ecology as study of life at extremes has challenged the scientific world to retrospect the adaptability and limitations of life (Schmid et al. 2020). Encountering the limitations from culture-dependent methods, new molecular strategies such as amplicon/shotgun sequencing, nanopore chip assay, and omics tools gave a leapfrog advantage for better understanding of the microbial diversity throughout the world (Rawat and Joshi 2019).

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Aiming the geomicrobiological features, microbial community structure of different geothermal springs has been determined worldwide such as in China (Guo et al. 2020), Japan (Martinez et al. 2019), South Africa, Colombia, solfataric fields of Iceland, Great Basin hot springs, and Yellowstone National Park (USA) (López-López et al. 2013;Urbieta et al. 2015). The Indian sub-continent supposedly houses 400 hot springs distributed across seven geothermal provinces, and among them, only about 30 hot springs have been explored with respect to microbiological aspects (Poddar and Das 2018). Out of these 30 hot springs, the hot spring soil ecology and their bacterial diversity analyzed through high-throughput sequencing (HTS) have been limited and cover only the hot springs of Manikarnan (Himachal Pradesh), Tapovan (Uttarakhand), Jakrem (Meghalaya), and Taptopani and Atri (Orissa). Most of the researches have been on the hot spring water only, and so far, there are no studies on the seasonal variation of the microbial diversity in these geothermal systems. Hence, the bacterial diversity analysis of the hot spring encompassing both the soil and water components is of great significance, as these hot springs have been traditionally used for various balneotherapeutic purposes and recreational activities (Das et al. 2012).
On the context of the soil microbial diversity studies of the hot springs of Sikkim, there is a dearth in the knowledge of its ecology and diversity. Here, we have tried to examine the hot spring soil bacterial ecology to understand its community structure through culture-independent approach. An attempt was done to generate a first-ever report on the monthly variation in these diversity profiles during the postmonsoon season at Sikkim Himalayas.

Sampling sites and sample collection
The geographical position of the coordinates and elevation (above mean sea level) of the hot springs were measured with the help of GPSMAP 78S (Garmin, India). The hot springs located at the North Sikkim district were selected for the current study (Fig. 1). Three hot spring soil samples were chosen for the present study-NYS, OYS, and TAR. The samples were taken in the month of October and December 2019.
The solfataric soil sediments (1000 g) were aseptically pooled in triplicates from different sections encompassing the whole perimeter of the NYS, OYS, and TAR hot springs of North Sikkim district in sterile sample containers (Wang et al. 2013). The samples were preserved in situ by storing in the thermally insulated sampling box packed with ice gel bags and were then transported (temperature maintained at 4 °C) for DNA extraction analysis.

Environmental DNA isolation and quantitative analysis
The environmental DNA (eDNA) was extracted using NucleoSpin Soil Kit (MACHEREY-NAGEL GmbH and Co. KG, Duren, Germany) in accordance with the manufacturer's protocol. The eDNA extraction and the amplicon sequencing were done at Eurofins Pvt. Ltd., Bangalore. Quality of the DNA was checked on 0.8% agarose gel and quantified using a Qubit Fluorometer (Thermo Fisher Scientific, USA), with a detection limit of 10-100 ng·μL −1 .

16S rRNA amplicon sequencing library preparation
Amplifications of the V3 and V4 regions of bacterial 16S rRNA gene were done using two primers 16S rRNA-F-5′GCC TAC GGGNGGC WGC AG3′ and 16S rRNA-R-5′ACTACHVGGG TAT CTA ATC C3′ (Klindworth et al. 2013). The amplicon libraries were prepared using the Nextera XT Index Kit (Illumina Inc.), in accordance with the 16S metagenomic sequencing library preparation protocol (Faircloth et al. 2012). The amplicon library was purified with AMPure XP beads. The amplified libraries were analyzed on 4200 Tape Station system (Agilent Technologies) using D1000 Screen tape as per manufacturer instructions, and the concentration was quantified by the Qubit Fluorometer. Based on the data obtained from the Qubit Fluorometer and the Bioanalyzer, 500 μL of the 10 pM library was loaded into MiSeq cartridge for cluster generation and sequencing. Paired-end sequencing method (read length 2 × 300 bp) was used. After the sequencing, high-quality metagenome reads were trimmed to remove the barcode and adaptor sequences.

Data and statistical analysis
Samples (NYS_MUD_OCT, NYS_MUD_DEC, OYS_ MUD_OCT, OYS_MUD_DEC, TAR_MUD_OCT, and TAR_MUD_DEC) were subjected to pre-processing of reads, de-replication, singleton removal, ASV clustering, chimera filtering, and each ASV annotation till species level, with QIIME2 release 2020.6 (Kuczynski et al. 2011). For quality control of the sequences, the DADA2 plugin in QIIME 2 was used to associate erroneous sequence reads with the true biological sequence from which they were derived, thus producing high-quality sequence variant data. Using DADA2, all reads were trimmed to 260 bp, based on the median quality score. In addition, chimeric sequences were detected and excluded from analyses. 16S rRNA ASVs were picked using a closed-reference ASV picking protocol against the Greengenes database (https:// data. qiime2. org/ 2020.6/ common/ gg-13-8-99-515-806-nbclass ifier. qza) In the next step, taxonomy assignments were associated with ASVs based on the taxonomy associated with the SILVA reference sequence defining each ASV (Edgar 2013). The taxonomic abundance at several levels was classified-kingdom, phylum, class, order, family, genus, and species. Sequences without homologous pair were classified as unknown. Statistical analysis based on PERMANOVA in ASV composition between the six samples was done. Taking them as unity factor, EdgeR and DESEQ2 were performed for calculating the differential abundance analysis. Many low abundance classes or ranks get omitted during computation. Thus, these statistical tools were used to eliminate this discrimination. Venn diagram and correlation matrix were used to depict the variation among the ASVs.

Description of sampling sites
Three hot spring soil samples were chosen for the present study-NYS, OYS, and TAR. NYS (New Yume Samdung) hot spring is situated at an altitude of Fig. 1 Geographical locations of the sampling site from where hot spring mud sediments were collected. The geographical position of the coordinates and elevation (above mean sea level) of the hot springs were measured with the help of GPSMAP 78S (Garmin, India) 4685.8 m above the mean sea level at 27.917302° N and 88.694308° E coordinates. OYS (Old Yume Samdung) hot spring lies just beside the NYS within few meters away. It is situated at an altitude of 4687.9 m above the mean sea level at 27.918242° N and 88.694935° E coordinates. Both hot springs are situated at the Yume Samdung valley. The third hot spring, Tarum/Takrum Tsha Chuu (TAR), is located at Tarum valley, Lachen, and is also known as Lha Bha Tarum Tsha Chuu. It is located at 2893 m above the mean sea level at 27.703888° N and 88.575277° E coordinates. In local dialect, hot springs are referred to as the "Tsha Chuu/Tatopani" (Das et al. 2012). The temperature of NYS, OYS, and TAR hot spring soil during the month of October was around 57 °C, 45 °C, and 44 °C that increased to 61 °C, 57 °C, and 49 °C during the month of December, respectively. Similarly, in the case of pH, at NYS, OYS, and TAR, they were moderately alkaline in the month of October, ranging from 8.5 to 9.2, whereas during the month of December, with decrease in the groundwater aquifer discharges, it got reduced to 7.8-9 (Table 1). Thus, it can be said that there were variations in temperature and pH observed in these hot spring soil components. The elemental analysis was done and published already in paper .

Metagenomic data analysis
The high-throughput sequencing assembly (Table 2) obtained gave 234,612 reads for NYS (October), 209,837 reads for NYS (December), 219,384 reads for OYS (October), 238,388 reads for OYS (December), 231,568 reads for TAR (October), and 254,002 reads for TAR (December). A total of 3803 ASVs were obtained from the six soil samples, with the minimum length of an ASV being 291 bp and maximum being 492 bp. The mean ASV length obtained was 450.3 bp. Statistical analysis based on PERMANOVA revealed significant differences in ASV composition between the six locations (F value = 3.534, r 2 = 0.469, p < 0.1).

Diversity indices and rarefaction curves
The diversity indices were calculated using MG RAST and PAST software. Alpha diversity denotes the species variedness, and Chao value depicts the species richness among the environmental samples. The alpha diversity was found to be the highest in the hot spring TAR (143.3) in the month of December and TAR (139.1) in the month of October as per Fisher alpha diversity indices. The beta diversities were more in the month of October (0.28) than in the month of December (0.22) as per the Whittaker concept of beta diversity. In the month of October, the Shannon and Chao-1 diversity indices were also higher, 4.68 and 822.3, respectively, for Tarum hot spring. However, the Shannon and Chao-1 diversity indices were relatively higher, 4.66 and 855.2, respectively, in Old Yume Samdung hot spring in the month of December. However, alpha diversity for NYS in the month of December (131.6) and October (138) was relatively lower compared to TAR hot spring samples. Similarly, the Chao-1 diversity indices in the month of December  ST1). Rarefaction curve plots the number of species as a function of the number of samples. Calculated rarefaction is represented by a line graph. The rarefaction curve not only deals with the sample coverage but also depicts whether the sampling depth was sufficient or not to estimate the diversity. The results in curve have shown the initial rapid rise as most common species are found. However, in both graphs, Tarum hot spring has shown the highest peak representing the accumulation of the rarest species. This result was in line with the results shown by diversity indices (Fig. 2a, b).

Phylum level bacterial diversity
Firmicutes, Proteobacteria, Bacteroidetes, Actinobacteria, Cyanobacteria, and Planctomycetes were the major abundant phyla present in all the solfataric soil sediments of the studied hot spring ecosystem of Sikkim (Fig. 3a, b). There was a considerable amount of variation in their abundance percentages when observed individually.
The results have shown that the NYS hot spring possess the Firmicutes as the most dominant phyla in both months of October (23.2%) and December (29.9%) in the postmonsoon season. The major phyla found to be present in NYS were Firmicutes, Proteobacteria, Bacteroidetes, and Actinobacteria. The results have shown that the variation of phylum's during the two months October and December remains more or less constant. However, interestingly, it was shown that the relative abundance of various phyla decreases from October to December. The percent abundance of Firmicutes (Oct-23.2%; Dec-29.9%), Proteobacteria (Oct-21.0%; Dec-20.7%), Bacteroidetes (Oct-12.2%; Dec-5.8%), and Actinobacteria (Oct-5.4%; Dec-6.5%) was found in this study. However, more interestingly besides being less abundance, more phyla were found contributing towards the bacterial diversity in the month of December.
In the case of OYS hot spring, the percent abundance of Firmicutes (Oct-24.3%; Dec-22.5%) was higher followed by Proteobacteria (Oct-21.5%; Dec-20.3%) and Bacteroidetes (Oct-8.2%; Dec-5.6%). However, the abundance of various phyla such as Actinobacteria (Oct-5.2%; Dec-7.3%), Cyanobacteria (Oct-3.4%; Dec-4.4%), and Planctomycetes (Oct-2.0%; Dec-4.4%) has increased from the month of October to December. The OYS hot spring analysis shows that more phyla were found contributing towards the bacterial diversity in the month of December likewise NYS. Thus, this can be hypothesized that the winter climate favored the ecological growth of microorganisms.
In the case of TAR hot spring, the percent abundance was found to be variable than that of the other two hot springs discussed above. Proteobacteria (Oct-19.1%) was the abundant phylum in the month of December; however, during the month of October, the relative abundance of Proteobacteria (Dec-20.8%) was higher than the month December. Firmicutes were abundant in the month of October (Oct-22.1%; Dec-16.4%) followed by Bacteroidetes (Oct-9.7%; Dec-7.4%). The abundance of phyla Actinobacteria (Oct-6.9%; Dec-7.4%) and Planctomycetes (Oct-4.4%; Dec-8.4%) was found to be increased from the month of October to December. Similar to the other two hot springs, it has shown that more phyla were found contributing towards the bacterial diversity in the month of December. Thus, the bacterial diversity is favored by winter climate. Overall, it can also be said that at the phylum level, TAR hot spring had more variation and diversity compared to the other studied hot springs. Besides these characterized phyla discussed above, unclassified phyla were abundant in both months among all the hot springs. All the data are tabulated in Supplementary ST2a, b.

Genus level bacterial diversity
The genus level diversity showed more unclassified genera similar to phylum level classification which suggests the possibility of discovering novel genera from these hot spring solfataric soil sediments. Proteobacteria, Firmicutes, Bacteroidetes, and Verrucomicrobia were some of the common phyla among which unclassified genera were present. There was higher variation among all the individual samples observed during both the months (Fig. 4a, b).
The relative abundance of similar genera was found in both months. The results have shown that the genera such as Clostridium, Bacillus, Paenibacillus, and Desulfotomaculum were prevalent in all the hot springs in both Genus level diversity of December month hot spring (mud) samples months; however, their relative abundance varies considerably. In the case of NYS hot spring, it was shown that the abundance of Clostridium (Oct-12.0%; Dec-18.9%) was higher in both months followed by Bacillus (Oct-2.9%; Dec-4.5%), Desulfotomaculum (Oct-2.7%; Dec-2.2%), and Paenibacillus (Oct-1.5%; Dec-2.2%). However, Planctomyces and Terrimonas were having similar abundance. The results have also shown that Lactobacillus which has the property of probiotics was also present in the both the months and a nitrogen fixing bacteria; Azospirillum was also found in both months with moderate abundance. The relative abundance was found to be higher among discussed genera in the month of December. Similar to phylum-wise distribution, it has been shown that more genera were contributing towards the bacterial diversity in the month of December.
Venn diagram analysis was done to understand the distribution of shared ASVs at phylum and genus level of the hot spring soil bacterial diversity (Fig. 5a, b). Less proportions of ASV were shared between the six hot springs. 13 phyla are common among all the samples or hot springs, 19 are common in December samples and 15 in October samples. 10 genera were common in all the hot springs, 8 were common in October month and 20 we common in December as per revealed by Venn diagram. The distribution of shared ASVs across the sediments revealed less overlap among each other. Thus, it showed higher variation and diversity among the samples.

Discussion
In India, the geothermal exploration began in early 1973 by Geological Survey of India and they reported more than 350 hot springs having temperature range varying above 40 °C-100 °C throughout the entire sub-continent region (Narsing Rao et al. 2021). Based on the tectonic movements, the hot springs of India were categorized into orogenic and non-orogenic. Sikkim naturally hosts many hot springs. It is a major tourist attractive state of India where nature is in its juvenile form and a refreshing season greets its visitors. Previous studies through culture-independent studies done on the water samples from some hot springs of Sikkim located at Polok, Borong, Reshi, and Yumthang showed bacterial diversity at both the phylum and genus levels. Those hot spring water samples were abundant in Proteobacteria (Polok-47%; Borong-63%; Reshi-76%) and Yumthang hot spring was predominant with Actinomycetes (98%). The most abundant genera in the hot spring water of Sikkim were Acidovorax, Acinetobacter, Exiguobacterium, Flavobacterium, Ignavibacterium, Paenisporosarcina, Paracoccus, Pseudomonas, Rhodococcus, Serratia, Sulfuritalea, Thermodesulfovibrio, Thermus, andThiobacillus (Najar et al. 2018, 2020;Panda et al. 2016;Sharma et al. 2020). Similarly, in the present metagenomic study, we have found microbes belonging to thermophiles, alkaliphiles, and mesophiles mainly.
Hot spring soil ecology is usually governed by complex uncultured bacteriomes. The hot spring soil ecology of the Sikkim Himalayas had higher percentages of Gram-negative bacterial phylum such as Proteobacteria and Bacteroidetes as compared to Gram-positive bacterial phylum of Firmicutes and Actinobacteria. Interestingly, in the hot spring water samples of the present study, it has been found that Gram-positive bacteria such as Firmicutes were abundant (Najar et al. 2018Sharma et al. 2020). In the various other hot spring soil sediments also, a similar observation was found. The hot spring soil of Tatapani, Bor Khleung, NYS, and Eritrea all had similar range of temperature varying from 50 °C to 70 °C. The Tatapani hot spring soil of Orissa and Solfatara Crater, Italy, as studied by Sahoo et al. (2015) and Crognale et al. (2018) had the highest abundance of Proteobacteria (45%) and Bacteroidetes (23.4%); they lied within the same temperature ranging from 45 °C to 65 °C (Sahoo et al. 2015;Crognale et al. 2018). Globally, the hot spring soils are rich in Proteobacteria which seems a common characteristic feature in soil ecology. Bacteroidetes was also relevantly abundant in Taptapani, Bor Khleung, NYS, OYS, and TAR. The resident signature soil flora such as Planctomycetes and Chlorobi which are commonly found in sulfur-rich hot springs were also found here. However, the abundance of Chlorobi was less. Temperature plays a  (Sharp et al. 2014). During the month of December, there were drastic changes in the abundance percentage for majority of the phylum and genera as compared to that from the month of October. At phylum level, the abundance of majority of the phyla such as Firmicutes, Proteobacteria, Bacteroidetes, and Actinobacteria decreased during the month of December except Planctomycetes which showed higher abundance, and at genus level, more or less similar trend was found.
Firmicutes and Proteobacteria were the most abundant phyla obtained in various studies in India and around the hot springs of world. Similar to our study, Firmicutes and Proteobacteria are found to be abundant in Jakrem, Bakreshwar, hot springs of Odisha such as Taptapani, Athamallik, and Tapovan (Sahoo et al. 2015;Panda et al. 2015;Chaudhuri et al. 2017). At the genus level, our results are distinct from those of other studies on hot springs of India. Chloroflexus, Roseiflexus, Anaerolinea, and Caldilinea were found major genera in the hot springs of Odisha (Sahoo et al. 2015). In the other study, the hot spring soil sediments of Manikarnan (Himachal Pradesh, India), as reported by Mahato et al. (2019), was abundant in Acidothermus, Alishewanella, Arthrobacter, Bifidobacterium, Brevundimonas, Burkholderia, Chloroflexus, Frankia, Meiothermus, Nocardia, Rhodothermus, Thermobaculum, and Thermosynechococcus (Mahato et al. 2019). These findings are in contrast to our study where we found the abundance of Clostridium, Bacillus, Lactobacillus, and Desulfotomaculum. Similarly, other studies from the hot springs of Northeast India, i.e., from Sikkim, showed distinct results shown by the present studied hot springs of Yume Samdung and Tarum. Our previous studies on the hot springs of Sikkim such as Polok, Borong, and Yumthang have shown the abundance of Acinetobacter (7.69%), Flavobacterium (3.85%), Vogesella (3.85%), Ignavibacterium (2.88%), Sediminibacterium (2.88%), Thermodesulfovibrio (2.88%), and Acidovorax (1.92%) which are totally distinct from our present study (Najar et al. 2018). However, similar to our results, Clostridium has been found abundant in Jakrem and Bakreshwar hot springs (Panda et al. 2015;Chaudhuri et al. 2017). Global comparisons with our findings show that Firmicutes and Proteobacteria are the dominant taxa. A study on Malaysian hot springs shows the abundance of Firmicutes (38.5%) and Proteobacteria (16.3%) (Chan et al. 2017). Similar results were found by Ghilamicael et al. (2018) while studying five hot springs in Eritrea (Ghilamicael et al. 2018). At global level, the genus Clostridium has been found to be abundant in various hot springs such as hot springs of Yunnan-Tibet, Eritrea, Argentina, and Sri Lanka (Liu et al. 2020;Rupasinghe et al. 2022).
According to the literature review, variation of the genera and phylum depends on various abiotic parameters such as pH, temperature, dissolved oxygen, and other physicochemical components present in the hot springs (Li et al. 2015;Podar et al. 2020). Thiobacillus, Planctomyces, and Arthronema and phylum Cyanobacteria, Acidobacteria, and Armatimonadetes had the highest variation/fluctuations in their relative abundance percentage in NYS, OYS, and TAR, throughout both the months (Fig. 6). This may be due to the change in temperature (Wang et al. 2013;Sharp et al. 2014;Badhai et al. 2015) as well as the variability of ground aquifer discharge with the onset of winter during the postmonsoon season. Many researchers have shown the correlation of temperature with the dominance of various phyla and interpreted by many researchers as a function of temperature. Subudhi et al. (2017) have shown the predominant shifting of thermophilic cyanobacteria as a function of temperature and also have shown the abundant growth of different strains at different temperatures (Subudhi et al. 2017). Similarly, Sahoo et al. (2015) have correlated and linked the dominant nature of Proteobacteria in the hot springs of Odisha, India, as a function of temperature (Sahoo et al. 2015). Firmicutes and Bacteroidetes could easily withstand these climatic variations and did not have much effect on their relative abundance percentage. This might be due to their physiological and cellular adaptation to the geothermal environment. There was a temperature change from mesophilic (45 °C and 44 °C) to thermophilic (57 °C and 49 °C) from October to December. As the monsoon season is from the month of June to September, at the Sikkim Himalayas, hence during the first month of the post-monsoon season, i.e., in October, there is higher abundance of the species in the hot spring soil ecosystem. This might be due to the fact that during rain in these high altitudes, frequent geomorphological changes occur that enhances the bacterial diversity. Also, with heavy rainfall, the aquifer discharge is substantially high and hence more enrichment of the bacterial ecology occurs. With the recede in rainfall, during the later stages of post-monsoon, i.e., from November onwards, these high altitudes start experiencing snowfall and winter onsets. Thus, with less groundwater aquifer discharge and also drastic change in the atmospheric conditions, the bacterial diversity at the month of December changes. Besides, it was shown that the percent relative abundance of these phyla in the month of December is relatively less and relatively more phyla were found contributing towards the bacterial diversity in the month of December. This may be also correlated with the temperature change. One of the reasons may be the less water dilution due to reducing rainfall and thus free flow of hot water through plumbing systems and making conditions favorable for the growth of many mesophilic and thermophilic microorganisms. It may be hypothesized that as temperature changes from mesophilic to thermophilic, the psychrophilic and mesophilic bacteria start diminishing so we are getting lower abundances. However, as temperature rises, many specific bacteria with optimum thermophilic temperature start growing and contributing towards the bacterial diversity. In our study, we have seen the accumulation and additional contribution of bacterial genus from lower temperature (October) to higher temperature (December) such as Isosphaera, Acidimicrobium, Ruminococcus, Gemmata, and Rhodopirellula. It has been shown that the particular bacteria accumulate at different temperatures such as at higher temperature only a few genera (e.g., bacterial Caldisericum, Thermotoga, and Thermoanaerobacter and archaeal Vulcanisaeta and Hyperthermus) often dominated in high-temperature environments (Li et al. 2015). Similarly, in another study, it was shown that there is a higher diversity at lower temperatures such as at the lowest temperature (38℃) the water and microbial mats of the Hverahólmi lagoon were dominated by a large diversity of mesophilic and mildly thermophilic heterotrophic as well as photosynthetic bacteria, including Alpha and Betaproteobacteria (Roseomonas, Rhodobacter, and Tepidimonas), Bacteroidetes (Chitinophaga, Saprospira), and Cyanobacteria (Cyanobium, Leptolyngbya). However, when temperature increases, a certain portion of bacteria were contributing to microbial diversity and few specific microbes started accumulating such as Pyrobaculum, Aquificae, and Thermi (Podar et al. 2020).
Correlation matrix represented through heat map analysis ( Fig. 7) was done to compare the unculturable bacterial diversity present in soil among the nine different hot springs of the world-Atri (55 °C-58 °C) and Taptani ). The phyla Proteobacteria, Planctomycetes, Bacteroidetes, Chloroflexi, Actinobacteria, and Verrucomicrobia were positively correlated and had similar abundance percentages in these hot spring soil sediments as reported by various researchers (Panda et al. 2016;Sharma et al. 2020;Sahoo et al. 2015;Crognale et al. 2018;Ghilamicael et al. 2017;Kanokratana et al. 2004). These phyla are commonly associated with the soil flora and are an important contributor of bacterial diversity in the hot springs worldwide.
Another important aspect was the discovery of many unclassified genera, which suggests that novel flora might be habituating these hot springs. The present study was able to get valuable insights into the microbial diversity of thermal springs in Sikkim Himalayas, and the results of this study would be valuable in designing future studies on target species found in these springs. There is other future research prospective that needs to be conducted on industrially important thermophiles identified in this study.

Conclusion
In this first ever report on the two-month comparative study of the bacterial diversity from hot spring soil of Sikkim Himalayas during the post-monsoon season, there were not much remarkable changes in the bacterial diversity both at 1 3 the phylum and genus levels. Although only very few studies have been done on the seasonal variation of hot spring soil bacteriomes, a general trend was found common between the available reports globally. Proteobacteria and Bacteroidetes were the worldwide abundant phyla. In the case of genera, the Himalayan Geothermal Belt had comparably similar profile, with the abundance of Thiobacillus, Chloroflexus, and Meiothermus which was very much distinct from our present study. Moreover, other hot springs of Europe and Africa had varied genera owing to their geological difference. Also, it is evident that temperature difference plays a very crucial role in determining the bacterial diversity. With the drop-in temperature about 5 °C-7 °C on an average, from the month of October to December, a huge variation of species occurs in the studied Sikkim Himalayan hot spring soil niches. In the present study, winter season favors the bacterial diversity Fig. 7 Heat map showing the comparison of bacterial diversity in the hot spring mud samples globally as many psychrophilic and psychrotolerant or mesophilic microbes. Thus, this may be the reason we are getting more taxa during the month of December; however, the abundance of these taxa is less. Future studies on the pre-monsoon seasonal variation of the bacterial diversity will complete this initiative and present us with a prismatic view of the complete annual uncultured bacteriome profile. These types of comparative analysis are the result of high-throughput sequencing, and it helps in understanding these extreme ecologies where the habitats are fragile and are at risk from geomorphological hazards.