Biodiversity and Bioactive Potential of Actinomycetes from Unexplored High Altitude Regions of Kargil, India

Abstract

The effectiveness of currently available antimicrobials and anticancer medications is steadily declining due to the emergence of drug resistance. Since actinobacteria are important producers of bioactive substances, we have isolated them from the soil samples of exotic North-Western Himalayan terrains. Out of 128 isolates, 39 strains were prioritized based on their bioactive potential. The diversity analysis revealed higher abundance distribution of actinomycetes in the soil of an open field (68.7%), followed by the mountainside (34.9%), from which most of the bioactive strains were obtained. The extract of the strain S26-11 was found to be highly active against Gram-positive Staphylococcus aureus and Bacillus subtilis with a MIC of 0.5 μg/mL and 1 μg/mL respectively. A cytotoxicity assay (sulforhodamine B) was performed on a series of cancer cell lines (PC-3, MCF-7, A-549, and HCT-116). The extract of the strain S26-11 showed cytotoxic activity against all cancer cell lines with an IC₅₀ of 2 µg/mL against PC-3, 1.9 µg/mL against MCF-7, 0.52 µg/mL against A-549, and 0.83 µg/mL against HCT-116. Moreover, the antioxidant activity was assessed using a DPPH-based assay and the results revealed that the S17-8 isolate showed the highest antioxidant activity with IC₅₀ of 114.136 μg/mL. The Response Surface Methodology (RSM) had helped to optimize the physical parameters for scaling up of the bioactive strain S26-11. The unexplored soil niches of Kargil (UT, Ladakh), India, is rich in actinomycetes which are having potential bioactivities, would be worth to explore for the discovery of bioactive compounds.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12088-023-01133-1.

Introduction

Actinomycetes are gram-positive bacteria that possess a high G + C content of over 55% in their DNA and are known as the largest genus for the production of natural molecules of pharmacological importance [1–4]. The unique sets of enzymes in actinomycetes make them a potentially useful resource for antibiotics by allowing them to produce novel compounds [5]. The activity of these novel compounds depends on their chemical structure, which makes their affinity for specific biological targets [6].

From a chemical point of view, actinomycetes produce different classes of antibiotics like aminoglycosides [7, 8], peptides [5, 9], ansamycins [10, 11], β-lactams [12, 13], tetracyclines [14], macrolides [15–17], lincosamides, epoxides, and aminocoumarins. Some of the examples which can be considered an achievement in the pharmacology and pharmaceutical industries are penicillin, cephalosporin, tetracyclines, and costomicins [6, 18–20].

Secondary metabolites act as a reservoir for novel drug discovery with potential therapeutic applications for the pharmaceutical industries [2, 5]. The production of bioactive molecules depends upon the growth curve and the availability of nutrients in the growth medium. It is initiated at the end of vegetative growth at the stationary phase which is accompanied by a variety of gene expressions [21]. During scale-up processes, the optimization of physical and chemical parameters is crucial for specific antibiotic production and also for the enhancement of the targeted yield [22]. Some metabolites are important organic molecules that originated from natural sources having a wide range of chemical structures with bio-specific activities. antimicrobial, antitumor, antioxidant, anti-inflammatory, and antiviral [23–28]. Actinobacteria has also the ability to produce diverse cold-active hydrolytic enzymes with various industrial applications (pharmaceutical, food, detergents etc.) which can be determined by various biochemical tests (cellulase, protease, amylase etc.) [29].

Soil microbes are essential for maintaining soil health, fertility and plant protection. The north-west Himalayas have a rich diversity of microorganism due to diverse soil microorganisms. Previous studies focused on snow and glacier samples, but recent focus has shifted to assessing soil bacterial diversity in the north-western part of Himalayas, which features diverse climatic zones, alpine glaciers, and varied soil textures. Only few have focused on the soil bacterial diversity and no study has been conducted on the diversity of actinomycetes [30, 31]. Yadav et al. [32] studied diverse group of microbial communities in cold deserts of northwestern Himalayas. The group of microbes, including actinomycetes, bacteria and fungi, screened for plant growth promoting (PGP) attributes. It also revealed the presence of cold-adapted microorganisms like Arthrobacter nicotianae, Brevundimonas terrae, Paenibacillus tylopili, and Pseudomonas cedrina in cold deserts, exhibiting multifunctional PGP attributes at low temperatures [32].

Since the pathogenic microorganisms are developing resistance at a rapid pace and decline in the discovery of novel antimicrobials, it is now more important than ever for research to look into previously undiscovered habitats in order to find novel actinobacteria and bioactive compounds [33–35]. There is an increasing interest in researching the unexplored regions of the Himalayas, more notably the North Western Himalayas, for the exploration and utilization of rare and novel actinobacteria. Hence, in order to get novelty, we had decided to explore the extreme untouched area i.e., Kargil of North West Himalayan region. The Kargil region in Ladakh (Union Territory), also known as the cold desert is situated at an average elevation of 2676 m above the sea level. This region experiences harsh climatic conditions varying from extreme warmth to cold temperatures, i.e., 35 to − 40 °C. Due to the extreme environmental conditions, the chances of getting diverse actinomycetes with bioactive potential are high [36].

Our research group is working with the mandate of drug discovery and had already reported natural bioactive molecules from different fungi [37–43]. In this study, the exploration of actinomycetes for bioactivities had made us hopeful to get novel molecules of therapeutic potential.

Materials and Methods

Soil Sample Collection

Nine soil samples were collected from three different habitats i.e. river-side, mountain-side and open field of the Kargil region (Fig. 1). The soil samples were visually different in nature because of the variation in the topography, and vegetation of the habitats.

Fig. 1.

A map showing the sampling sites in Kargil. S1 Parkachik; S7 Minjee; S10 Akchamal; S15 umbulong; S17 Darkhet; S19 Shargole; S26 Sankoo; S38 Pandrass; S39 Matayen

Soil samples were collected within the depth of 10 cm in the month of September when the weather conditions were cool and dry, and further pretreated by sun-drying. Later, samples were stored in ziplock bags at 4 °C till further use [44].

Isolation of Actinomycetes

The soil samples were processed for the isolation of actinomycetes by using the serial dilution technique [45]. 1 g of selected soil sample was taken and suspended in 9 mL of normal saline solution (NSS) (0.9% NaCl solution), and vortexed. The suspension was serially diluted up to 10^–6 dilutions. Later, 100 µL of each dilution was taken and spread plated on five different media plates, i.e., Tryptone Soya Agar (TSA), Luria Bertani agar (LBA), Water Yeast Extract agar (WYEA), Kenknight Munaier Media agar (KMM) and Actinomycete Isolation Agar (AIA) supplemented with amphotericin B (20 μg/mL); an anti-fungal antibiotic [46]. The media components and antibiotics used in the study were procured from HiMedia Laboratories, Mumbai, India. Later, plates were incubated for 3–15 days at 28 °C. Henceforth, growth of actinomycetes colonies was observed, picked and inoculated on selective media plates to obtain the pure cultures.

Morphological Identification of Actinomycetes

The preliminary identification of actinomycetes was done by observing the colony characteristics on KMM and AIA medium. The parameters like powdery, dry colonies embedded in the agar medium with their intracellular pigmentation and mycelial sporulation were observed [47].

Biochemical Characteristics of Actinomycetes

The bacterial isolates were subjected to biochemical tests and segregated on the basis of different substrates utilization for the synthesis of various enzymes. The hydrolytic activities of the strains were tested on Actinomycete isolation agar medium supplemented with different substrates such as starch (0.25% w/v), carboxymethyl cellulose (0.5% w/v), and skimmed milk (10% w/v) to study the production of amylase, cellulase, and protease, respectively. Actinomycetes strains were smeared into the media and incubated at 28 °C for 4–5 days. A clear zone appeared when stained with iodine, showing amylolytic activity [48, 49]. For the cellulose hydrolysis test; plates were exposed to 1% Congo red solution for 10 min at room temperature. Later, 1 M NaCl was added for 5 min. The positive cultures showed a clear zone around the smear [50]. However, the proteolytic activity was tested on skim milk agar medium, and culture plates were incubated for 3–4 days at 28 °C and the formation of a clear zone was observed around the colonies [51].

To check the ability of citrate utilization as an energy source, actinomycetes isolates were streaked on Simmons citrate agar plates and incubated for 7 days at 28 °C. The positive result showed the change in media colour, i.e., from green to intense prussian blue due to the break-down of ammonium salt into ammonia and resulted in an alkaline pH [52].

Catalase activity was analysed on the glass slides using sterilised conditions. The Actinomycetes were smeared and 3% of H₂O₂ was added to them. Here, the formation of bubbles was observed immediately due to the decomposition of hydrogen peroxide into water and oxygen, indicating the presence of catalase [53].

actinomycetes also have the ability to produce hydrogen sulfide (H₂S), commonly used for taxonomic purposes [54]. Actinomycetes were grown on triple sugar iron (TSI) agar containing a pH-sensitive dye (phenol red) along with 1% of the three sugars (lactose, glucose, and sucrose). H₂S-producing actinomycetes turned black in colour due to the formation of ferrous sulphide by reacting H₂S with ferrous ammonium sulphate after 3–4 days of incubation at 28 °C [55].

Genomic DNA Extraction, Amplification of 16S rDNA, and Sequencing

Genomic DNA of the bioactive actinomycetes was extracted according to the manufacturer’s protocol using a ZR Fungal/bacterial Miniprep Kit (Zymo Research, Cat. No. D6005 USA). The quantitative and qualitative analysis was done using Plate Nanoquant (Tecan Infinite 200 pro, Austria). The 16S ribosomal RNA (rRNA) gene was amplified by actino-specific primers ACT283F (5′-CTGATCTGCGATTACTAGCGACTCC-3′) and ACT1360R (5′-GGGTAGCCGGCCTGAGAGGG-3′) (Integrated DNA Technologies, Skokie, IL, USA) in a thermal cycler (Eppendorf, Stevenage, UK, Mastercycler pro). The PCR reaction was performed at 94 °C initial denaturation temperature for 5 min, then denaturation at 94 °C for 1 min, followed by 62 °C annealing temperature for 45 s, then extension at 72 °C for 1 min 30 s. Later, the final extension was performed at 72 °C for 5 min. The denaturation, annealing, and extension were repeated for 30 cycles. PCR amplification was performed in a 40 μL reaction mixture comprising 20 μL of Taq PCR master mix, 2 μL of both forward and reverse primers (12 μmol/L), 2 μL of the DNA template and 14 μL of nuclease-free water (Promega Corporation, New Delhi, India) [28, 56]. The PCR product was purified using an HiPurA™ PCR product purification kit (HiMedia Laboratories, Mumbai, India) according to the manufacturer’s protocol. The amplified product was outsourced for sequencing to SciGenom Labs Pvt.Ltd, India [38].

Taxonomical Identification of the Bioactive Actinomycetes

The taxonomic identification of the isolated actinomycetes was done on the basis of morphological characteristics and 16S rRNA gene amplification. The 16S rRNA gene was amplified, subjected to homology search and aligned with other sequences in GenBank using the BLASTN program. The alignment of 16S rRNA with the reference sequence was done using MEGA-7 software to construct the phylogenetic tree using the neighbour-joining algorithm with 1000 bootstrap analyses [57]. All the identified bioactive actinomycetes were deposited in Col. Sir R.N Chopra, Microbial Resource Center Jammu, India (Table S5).

Cultivation of Actinomycetes and Extracts Preparation

To obtain the extracts the isolated actinomycetes were grown in 200 mL of Tryptone Soya broth medium in an Erlenmeyer flask (500 mL) and were incubated in an orbital shaker (Lab Companion IS-971) at 150 rpm for 10 days at 28 °C. For termination purposes, 10% methanol (HiMedia Laboratories, Mumbai, India) was added and homogenized. The extraction was performed by adding an equal volume of ethyl acetate (HiMedia, Laboratories, Mumbai, India) using a separating funnel, and the organic solvent layer was collected. Further, rotavapor was used to dry the organic layer at 40 °C to collect the crude extract.

Biological Activity-Based Screening of Actinomycetes

Antimicrobial Activity

The antibacterial and antifungal activities of crude extract of each actinomycetes was determined by the microdilution method as per CLSI (Clinical and Laboratory Standards Institute) guidelines against a panel of standard strains, namely Escherichia coli ATCC 25922 and Pseudomonas aeruginosa ATCC 27853 (Gram-negative bacterial strains), Staphylococcus aureus ATCC 6538 and Bacillus subtilis ATCC 6633 (Gram-positive bacterial strains), Aspergillus niger ATCC 16404 (filamentous fungus) and Candida albicans ATCC 24433 (yeast). Mueller–Hinton broth (MHB) and Sabouraud Dextrose broth (SDB) were used for testing antibacterial and antifungal properties, respectively. The stock solution of extracts (10 mg/mL) was prepared in DMSO (Dimethyl Sulfoxide) (HiMedia Laboratories, Mumbai, India). The minimum inhibitory concentration (MIC) of the extracts was determined by two-fold serial dilution within a range of 0.0125–128 μg/mL in a 96-well U-bottom microtiter plate. Ciprofloxacin and Amphotericin-B (Sigma-Aldrich, New Delhi, India) within a range of 0.01–32 μg/mL were used as positive controls for antibacterial and antifungal studies, respectively. The overnight culture of bacteria and fungi was used to prepare their respective suspensions in NSS by adjusting the density to 0.5 Mcfarland. The final bacterial inoculum of 1 × 10⁵ CFU/mL and 1 × 10³ CFU/mL of fungal culture was used, and the plates were incubated at 37 °C for 24 h (bacteria) and 28 °C for 48 h (fungi). Based on visual observation, minimum inhibitory concentration (MIC), minimum bactericidal concentration (MBC), and minimal fungicidal concentration (MFC) were analyzed in comparison to the control [39].

Antioxidant Activity Using DPPH (1,1 Diphenyl 2 Picrylhydrazyl)

The antioxidant activity of the crude extracts was performed using DPPH-based scavenging activity assay. The 0.53 mg DPPH (Sigma-Aldrich, New Delhi, India) was added to 10 mL of methanol (HiMedia Laboratories, Mumbai, India) to measure the activity of the (200 μg/mL) extracts in flat-bottom 96-well plates. The plate was incubated for 30–45 min in the dark, and the absorbance was measured at 517 nm in a multimode microplate reader (Tecan Infinite 200 pro, Austria). The scavenging activity of the antioxidants is based on the reduction of DPPH (a stable free radical) with strong absorbance at 517 nm, giving a deep violet colour. The absorption decreases as the free radical gets a hydrogen donor and DPPH is reduced to DPPH-H, which leads to decolourization (yellow colour). Ascorbic acid was used as a positive control. The percentage of DPPH radical scavenging activity was expressed as the decrease in absorbance percentage of the samples compared to the control (DMSO + DPPH) as shown below.

$$\%DPPHinhibition=\frac{Absorbanceofcontrol-Absorbanceofsample}{Absorbanceofcontrol}\times 100$$

Acetylcholinesterase (AChE) Activity

The AChE inhibition potential of the extracts was assessed by an optimized version of the Ellman method using acetylcholinesterase activity assay kit (Sigma-Aldrich, St. Louis, MO, USA) as per the manufacturer’s protocol in 96 well plate [58, 59]. The components of the kit include assay buffer, calibrator and reagent. Working reagent was freshly prepared in assay buffer (0.01 mg/µL). The activity was done by adding 10 µL of extract to the working reagent (190 µL). DMSO was used as a blank and 200 µL of calibrator was added in separate well. The plate was incubated at 37 °C. Initial absorbance was measured after 2 min (A₄₁₂)_initial and the final absorbance was taken after 10 min of incubation (A₄₁₂)_final. The AChE activity (units/L) was calculated as:

$$AChEactivity=\frac{\left(\text{A}412\right)\text{final}-\left(\text{A}412\right)\text{initial}}{\left(\text{A}412\right)\text{calibrator}-\left(\text{A}412\right)\text{blank}}\times 200$$

where 200 = equivalent activity (units/L) of the calibrator when absorbance is measured at 2 min and 10 min.

Cytotoxicity Assay

Cell Culture and Treatment

The cancer cell lines representing prostate (PC-3), breast (MCF-7 and MDA-MB-231), lung (A-549), and colon (HCT-116) were procured from the National Cancer Institute (NCI). The cell lines of the cancer-screening panel were sustained in RPMI-1640 medium containing 10% fetal bovine serum (FBS), penicillin (100 units/mL), and streptomycin (100 μg/mL). The cell cultures were grown in a CO₂ incubator (NewBrunswick, Galaxy 170 R, Eppendorf) at 37 °C under 98% humidity, 95% air, 100% relative humidity, and a 5% CO₂ environment.

Sulphorhodamine B (SRB) Assay

The cell suspension (100 μL) was seeded in 96-well flat-bottom plates, with the density ranging from 7000 to 12,000 cells/well depending on the doubling time of particular cell lines. The plates were incubated at 37 °C (5% CO₂, 95% air, and 100% relative humidity) for 24 h. After 24 h, the cells were exposed to different concentrations of the extracts along with paclitaxel and 5-fluorouracil (5-FU) as a positive control for 48 h under the same condition. After 48 h, cells were fixed in situ with cold TCA (trichloroacetic acid) for 60 min at 4 °C. Then, plates were rinsed three times with water and air-dried. The SRB solution (0.4% of SRB in1% acetic acid) was added to each well and incubated for 30 min at room temperature. After staining, the plates were washed (three times) with 1% acetic acid and air-dried. A 10 mmol tris-base buffer solution was used for solubilizing the protein-bound dye. The absorbance was read at a wavelength of 540 nm on a microplate reader, followed by the calculation of percentage cell viability by applying the following formula.

$$\text{Percentage}Cytotoxicity=\frac{Absorbanceoftreatedcells}{Absorbanceofcontrol}\times 100$$

The percentage growth inhibition was calculated by using the formula, 100% cell viability and IC₅₀ values were calculated using Prism GraphPad, version 5 [40, 60].

Preliminary Study for Response Surface Methodology (RSM) Modelling

RSM is an effective statistical technique for the optimization of various parameters like media, pH, temperature, incubation time, etc. [61, 62]. It is a less time and labor-intensive approach that reduces the number of experimental trials needed to evaluate multiple parameters and their interactions. A preliminary experiment was carried out to determine the maximum yield of the extract. In this study, (A) temperature in °C, (B) pH, and (C) incubation time in days were selected as the independent variables for optimization of yield of extract from the strain S26-11. These variables were the key physical factors that would influence the production of secondary metabolites [63–65].

Experimental Design and Statistical Analysis

In designing the experiment, Design Expert trial software 8.0.7.1 (Stat-Ease, Inc., Minneapolis, MN) was used for RSM optimization, statistical analysis, and regression model [66]. A central composite design (CCD) with a quadratic model was employed [67]. The selected independent variables include (A) temperature, (B) pH, and (C) incubation time with three levels: − 1, 0, and + 1. The complete design was executed in random order (comprising 17 combinations with three replicates at a central point) according to CCD configuration for three factors [61]. The levels of independent parameters and their coded values are illustrated in Table 1. The response (Y) of the actinomycetes’s extract yield was measured. Using the equation below, these values were related to the coded variables (Xi, i = 1, 2, and 3) by a second-degree polynomial.

$$\text{Y}=\alpha \text{o}+\text{AX1}+\text{BX2}+\text{CX3}+\text{ABX1X2}+\text{ACX1X3}+\text{BCX2X3}+{\text{A}}^2\text{X12}+{\text{B}}^2\text{X22}+{\text{C}}^2\text{X32}$$ 1

Y is the predicted response and the coefficients of the polynomial were represented byαo (intercept), A, B, and C (linear effects), AB, AC, and BC (interaction effects), and A², B², and C² (quadratic effects), respectively.

Table 1.

Levels of independent variables for the experimental design for maximum extract yield

Independent variable	Symbol	Coded level
		− α	− 1	0	+ 1	+ α
Temperature (°C)	A	15	20	28.38	37	40
pH	B	4.98	6	7.50	9	10.02
Incubation time (days)	C	7	8	10.06	12	14

Statistical Analysis

The similarity analysis at the species level was based on the similarity measures: the Bray–Curtis dissimilarity (standardized, square-root transformed) [68] based on the relative abundances of actinomycetes species. Differences between the habitats were visualized by means of non-metric multi-dimensional scaling (nMDS) plot.

We have applied the pearson correlation and one-way analysis of variance (ANOVA) to detect the statistical significance between and within the habitats [69]. Diversity was expressed in term of the expected number of species in a sample, ES (51). The other diversity indices were calculated by means of Margalef’s index for species richness (d) [70], Pielou’s index for species evenness (J′) [71], and the Shannon–Wiener index for species diversity (H′) [72].

Results and Discussion

Collection of Soil Samples

A total of nine soil samples were collected from three untouched extreme habitats (river-side, mountain-side and open field) of the Kargil region of Ladakh, India (Fig. 1). From these soil samples, 128 pure cultures of actinomycetes were obtained by using five different isolating media. The scale of elevation of the soil sampling sites was 2770–4394 m, and pH of the soil samples ranged from 5.91 to 6.82 (Table 2).

Table 2.

Description of collected soil samples alongside the number of isolates

Sample code	Geographical coordinates	Elevation (m)	Location	Soil characteristics			No. of isolates
				Texture	Colour	pH
S1	34° 36′ 12.14″ N 76° 12′ 46.29″ E	4300	Parkachik	Sandy	Light Brown	6.06	15
S7	34° 28′ 08.90″ N 76° 04′ 25.65″ E	2770	Minjee	Sandy	Brown	5.91	10
S10	34° 34′ 07.57″ N 76° 07′ 45.56″ E	2815	Akchamal	Dark Brown	Sandy	6.20	19
S15	34° 34′ 04.60″ N 76° 06′ 49.48″ E	2900	Umbulung	Brown	Clay	6.82	11
S17	34° 23′ 23.85″ N 76° 19′ 45.70″ E	3230	Darkhet	Light Brown	Sandy	6.46	10
S19	34° 34′ 44.55″ N 76° 06′ 37.95″ E	3169	Shargole	Light Brown	Sandy	6.43	20
S26	34° 17′ 44.03″ N 75° 57′ 45.78″ E	2959	Sankoo	Greenish Grey	Sandy	6.62	12
S38	34° 24′ 46.06″ N 75° 37′ 54.17″ E	3247	Pandrass	Dark Brown	Loamy	6.60	16
S39	34° 36′ 22.92″ N 75° 12′ 49.17″ E	4394	Matayen	Grey	Sandy	6.20	15

Morphological Characterization of the Isolates

Actinomycetes strains were characterized based on phenotypic characteristics varying in their spore formations, colour (white, yellow, green, black, and creamy), and release of pigments, i.e., from pale yellow to dark brown, both in agar plates and broth media (Fig. S2, S3, and Table S1).

Biochemical Tests

The biochemical tests viz. catalase, cellulase, protease, triple sugar iron test, and citrate utilization test were performed. 28 isolates were found to be catalase positive, 24 isolates hydrolyzed starch and protease, and 16 isolates resulted in hydrolysis of cellulose (Table S6).

Molecular Identification and Phylogenetic Analysis

The homology search via BLASTn in GenBank lead to the identification of the 39 actinomycete strains with > 98% identity to the known strains (Table S5). The 16S rRNA gene sequence of the actinomycetes strains has been deposited in the Genbank under the accession numbers OM478593-OM478631. The resultant topology of the maximum likelihood tree was evaluated using MEGA version 7 software by bootstrap analysis based on 1000 replicates (Fig. 3).

Fig. 3.

Evolutionary tree was inferred by using the maximum likelihood method based on the sequence of 16S rRNA gene. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site

Antimicrobial and Antioxidant Activity of the Extracts

The antimicrobial activity of the extracts reveals that the isolates S26-11 and S15-1 have potent antibacterial activity against S. aureus and B. subtilis (Gram-positive) with 0.5 μg/mL, 1 μg/mL and 1 μg/mL, 4 μg/mL MIC, respectively. Similarly, S26-11 was also active against E. coli (Gram-negative) with 64 μg/mL MIC. The extracts of the two isolates, S26-11 and S19-20 exhibited activity against Candida albicans (yeast) with MIC values of 128 μg/mL respectively (Table 3). Shah et al. [73] also reported similar results for gram-positive bacteria from soil samples of the Kashmir Himalayan region. The minimal inhibitory concentration (MIC) of the extracts and positive control are shown in supplementary data (Table S2).

Table 3.

Antimicrobial activity of actinomycetes extracts

S. no	Pathogens	S26-11 (µg/mL)		S17-3 (µg/mL)		S15-1 (µg/mL)		Ciprofloxacin/Nystatin* (µg/mL)
		MIC	MBC	MIC	MBC	MIC	MBC	MIC
1	S. aureus	0.5	2	0.5	1	1	> 2	0.6
2	B. subtilis	1	4	1	1	4	8	0.15
3	E. coli	64	> 128	64	64	128	> 128	0.6
4	C. albicans	128	256	64	128	256	> 256	0.54

*Ciprofloxacin was used against the bacteria, whereas, nystatin was used against C. albicans

Furthermore, antioxidant activity was analyzed for all the extracts. The results revealed that only one extract, i.e., S17-8, showed effective antioxidant activity in scavenging the DPPH free radical with EC₅₀ of 114.136 μg/mL (Table S3) [39].

Acetylcholinesterase (AChE) Activity

We have screened the extracts to check the inhibition of AChE activity and found that extract S17-3 and S26-11 showed acetylcholine inhibitory activity with IC₅₀ values of ≤ 250 and ≤ 500 μg/mL respectively (Fig. S4).

In Vitro Cytotoxicity of Extracts Against Different Cancer Cell Lines

The effect of the extracts on various cancer cell proliferation was determined by performing the SRB assay on different human cancer cell lines. The preliminary screening results shows that the extract S26-11 showed better growth inhibition in various cancer cell lines (Table S4). This extract was further taken up for IC₅₀ value determination, in which cells were treated with different concentrations (1, 2.5, 5, and 10 μg/mL) for 48 h. The cell proliferation was markedly reduced at different concentration against PC-3 (IC₅₀value of 2 μg/mL), MCF-7 (IC₅₀value of 1.9 μg/mL), A-549 (IC₅₀value of 0.52 μg/mL), and HCT-116 (IC₅₀value of 0.83 μg/mL) cancer cell lines. Where as in normal human embryonic kidney cells (HEK-293), proliferation was high (IC₅₀value of 13.2 μg/mL). Additionally, several in-vitro studies for S26-11 extract have been carried out because it showed potent effect on A-549 cancer cell lines (Fig. 2, Table S4).

Fig. 2.

In-vitro assay of S216-11 extract against lung cancer cell line (A-549). A S26-11 extract suppresses the colony forming ability of A-549; B DAPI staining showing nuclear morphology of S26-11 extract treated A-549 cell line. The extract induces cell shrinkage, chromatin condensation and nuclear fragmentation; C Detection of mitochondrial membrane potential by rhodamine-123 staining. The S26-11 extract showed a decrease in cell fluorescence with increase in concentration; D ROS detection by DCFDA assay. The increasing in fluorescence intensity indicates the enhancement of ROS in A-549 treated with S26-11 extract

Response Surface Methodology (RSM)

The extract yield of the actinomycetes strain S2611 is shown in Table 4, along with the experimental, predicted, and residual values by the RSM. Analysis of variance (ANOVA), regression coefficients, R² values, and lack of fit are presented in Table 5, which shows the linear, interaction, and quadratic effects of each independent parameter. Two linear variables (B, C) and two quadratic variables (A² and C²) are significant (p > 0.1). The independent variable for extract yield was quadratic with a good regression coefficient (R² = 0.7906). After neglecting the insignificant term in Eq. (1), the final predictive equation for extract is simplified as follows:

$$\text{Extract}\text{yield}=-151.71986+8.90\text{897B}+12.81720\text{C}-0.0{\text{56244 A}}^2-0.4570{\text{2 C}}^2$$ 2

Table 4.

Central composite design for extract yield with predicted, experimental and residual value

Run	Independent variables			Response values
				Extract yield (mg/L)
	T (A, °C)	pH (B)	I.T (C, Days)	Experimental	Predicted	Residual
1	15.00	7.50	10.00	59.43	59.20	0.23
2	28.50	7.50	7.00	107.81	105.99	1.82
3	28.50	4.98	10.00	402.65	400.53	2.12
4	28.50	7.50	14.00	335.15	334.19	0.96
5	37.00	9.00	8.00	99.06	100.73	− 1.33
6	40.00	7.50	10.00	229.65	231.35	− 1.70
7	37.00	6.00	8.00	273.2	272.47	0.73
8	28.50	7.50	10.00	361.34	363.10	− 1.76
9	28.50	7.50	10.00	472.51	473.62	− 1.11
10	20.00	9.00	12.00	266.7	263.86	2.84
11	37.00	9.00	12.00	117.15	118.25	− 1.10
12	20.00	6.00	8.00	92.9	95.63	− 2.73
13	20.00	9.00	8.00	123.75	125.52	− 1.77
14	20.00	6.00	12.00	292.15	290.56	1.59
15	28.50	7.50	10.00	405.42	404.02	1.40
16	28.50	10.02	10.00	184.3	181.3	3.00
17	37.00	6.00	12.00	189.65	189.38	0.27

T (A, °C), temperature; I.T (C, Days), incubation time

Table 5.

Regression coefficients values for maximum extract yield by using RSM

Variable	Extract yield (mg/L)
	Regression coefficients	p value
Model	20.13	0.0134*
A-Temperature (α1)	0.30	0.6518
B-pH (α2)	− 1.44	0.0454*
C-Incubation time (α3)	2.12	0.0128*
A2 (α11)	− 4.06	0.0013*
B2 (α22)	− 1.14	0.1206
C2 (α33)	− 1.83	0.0166*
AB (α12)	− 1.28	0.1428
AC (α13)	− 1.82	0.0516
BC (α23)	0.17	0.8304
R2	0.8863
Adj. R2	0.7402
Lack of fit	0.2558NS

NS represent non-significant, * represent significant (p < 0.05)

The optimal levels of independent variables on theextract yield of actinomycetes were determined by three-dimensional (3D) response surface plots (Fig. 3), which were constructed according to Eq. (2).

Effect of Independent Variables on Extract Yield

The3D plot of extract yield as affected by incubation time and temperature is presented in Fig. 4A, which shows an increase in incubation time (8–11 days) and temperature (20–28.5 °C), giving a maximum yield of 446.824 mg/L. The incubation period for secondary metabolites production in actinomycetes is thus agreed with the previous findings of Naik and co-workers (Naik et al. 2015). The temperature and pH graph plotted with constant incubation time shows a maximum extract yield at 28.5 °C with a pH of 6.6 in the culture media (Fig. 4B). The optimized conditions with the experimental and predicted values of the response are summarized in Table 6. Temperature (28.5 °C), pH 6.6, and incubation time (11 Days) with the maximum extract yield (446.824 mg/L) are the process variables for the best combination of response functions.

Fig. 4.

Response surface plot of the extract yield affected by independent variables A Effect of temperature and incubation time on extract yield B Effect of temperature and pH

Table 6.

Optimum condition, experimental and predicted value of response at optimized conditions

Optimum conditions	Coded levels	Actual levels
Temperature (°C)	0.0035	28.5
pH	− 0.03	6.6
Incubation time (days)	0.97	11.00

Response	Predicted values	Experimental values
Extract yield (mg/L)	446.824	438.7794

Statistical Analysis

Non-metric multi-dimensional scaling (nMDS) based on actinomycetes species abundance (Bray–Curtis) data illustrates clearly the extent to which the three zones differ (Fig. 5). The nMDS plot based on the Bray–Curtis similarity measure indicated three groups of soil sample (Fig. 6) and the ANOVA community results indicated non-significant differences between the three zones (p = 0.046) (Table7).

Fig. 5.

nMDS coordination based on actinomycetes species abundance according to the Bray–Curtis similarity index

Fig. 6.

nMDS coordination based on actinomycetes habitats according to the Bray–Curtis similarity index

Table 7.

Diversity indices mean and standard deviation of the actinomycetes communities at species level

	River-side	Open field	Mountain-side
Taxa S	9	9	12
Dominance D	0.1531	0.12	0.09333
Simpson 1-D	0.8469	0.88	0.9067
Shannon H	2.045	2.164	2.431
Equitability J	0.9307	0.9849	0.9782

	S1	S26	S39	S10	S15	S17	S7	S19	S38
Taxa S	7	1	2	3	6	1	1	8	6
Dominance D	0.1605	1	0.5	0.3333	0.1837	1	1	0.125	0.1667
Simpson 1-D	0.8395	0	0.5	0.6667	0.8163	0	0	0.875	0.8333
Shannon H	1.889	0	0.6931	1.099	1.748	0	0	2.079	1.792
Equitability J	0.9708	0	1	1	0.9755	0	0	1	1

Margalef’s index for species richness (d), Pielou’s index for species eveness (J′), log2 Shannon–Wiener index for species diversity (H′), ES (51) = estimated total number of species

The three habitat zones did not differ significantly in the diversity indices (Margalef’s index: d, Pielou;s index: J′, evenness; expected total number of species: ES (51); and log 2 Shannon–Wiener index for species diversity: H′) of actinomycetes assemblages. However, the diversity of actinomycetes within the habitat is highly significant (p < 0.05) on the basis of t-test. The average values of diversity indices in each zone are given in Table 7. The species accumulation curve did not reach asymptote (Fig. 7).

Fig. 7.

Species accumulation plot

Conclusion and Future Perspective

The study of actinomycetes diversity in the soil of unexplored areas of Kargil (Ladakh, Indian Trans-Himalaya) is an important task for their products in various biological activities of industrial applications. The earlier studies were limited to cold-active hydrolytic enzymes from psychotropic bacteria [74–76].

In this study, the diversity of actinomycetes was found to be rich in the soil of open fields (Darkhet, S17) and mountain-side (Pandrass, S38) compared to the soil of river-side. According to the t-test, the habitat's actinomycete diversity is highly significant. Based on their morphological characteristics, these diverse actinomycetes were isolated. The growth of aerial and substrate mycelium showed a distinct variation in growth on different culture media. Growth on TSA was excellent, which may be due to sufficient amount of nutrients, and early sporulation was seen on KMM agar, which may reflect nutrient deficiency. 52.34% (67 out of 128) showed pigmentation, while 47.65% (61 isolates) had no pigmentation.

Among the 128 actinomycete isolates, 39 showed antimicrobial activity. The most potent strain (S26-11) showed activity against both gram-positive (S. aureus and B. subtilis with MIC values 0.5 and 1 μg/mL, respectively) and gram-negative bacteria (E. coli with MIC-64 μg/mL). Further, the crude extracts of the isolates were also screened for AChE activity and antioxidant potential. The S17-3 and S26-11 extracts showed acetylcholine inhibitory activity with IC₅₀ values of ≤ 250 and ≤ 500 µg/mL respectively. The antioxidant activity was highest in S17-8 extract with an EC₅₀ of 114.136 μg/mL. Furthermore, the majority of the isolates were active for various hydrolytic enzymes. All the extracts were tested for cytotoxicity on five cancer cell lines, among which S26-11 showed potent activity against all the cancer cell lines.

To obtain the optimum yield of extract from bioactive strain (S26-11), the physical parameters (temperature, pH, and incubation time) were optimized using RSM approach. The S26-11 strain produced maximum yield of extract (446.824 mg/L) under the optimized conditions (temperature 28.41 °C, pH 7.45 and 11 days incubation). Since the extract of S26-11 showed potent antibacterial and anticancer properties, it would be interesting to explore the strain further to obtain the bioactive pure compounds.

Using the RSM technique, the physical parameters (temperature, pH, and incubation time) were tuned to produce the highest yield of extract from the bioactive strain (S26-11). Under the ideal circumstances (temperature 28.41 °C, pH 7.45 and 11-days incubation), the S26-11 strain provided the highest yield of extract (446.824 mg/L). It would be intriguing to investigate S26-11 further in order to obtain the bioactive pure chemicals because the extract of the strain shown strong antibacterial and anticancer capabilities.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

MM did the experimental work, writing-original draft of the manuscript, VA executed methodology, writing and editing of the original draft, PC did experimental work, EN did pharmacological analysis, SKS did the formal analysis, supervision and review of the analysis, and SJ contributed for the funding acquisition, conceptualization, supervision, validation, writing-review and final editing of the manuscript.

Declarations

Conflict of interest

The authors declare no conflict of interest.