Novel approach of adaptive laboratory evolution: triggers defense molecules in Streptomyces sp. against targeted pathogen

Abstract

The adaptation and evolution of microorganisms under selective pressure is the major cause of the development of antibiotic resistance. However, our present study presents adaptive laboratory evolution as an efficient tool to mine for and develop targeted bioactive molecules. Cryptococcal meningitis is an emerging neurological disease with limited therapeutic options. In the present study, a new marine anticryptococcal strain of Streptomyces variabilis AFP2 was co-cultured with C. neoformans with periodic transfer for 30 days. AFP2 displayed improved anticryptococcal activity post co-culture versus the parental type. The metabolomes of the parental and evolved strains were analyzed by HPLC-UV and GC-MS. The changes in phenotype and chemotype between the parental and the evolved strain were analyzed to determine the evolution of new traits. About 21 new metabolites alien to the parent strain were seen to be produced by the evolved strain. Among these, a few of the induced molecules such as DL-alanyl-L-leucine, dihydro-3,3-dimethyl-2(3H)-furanone, enanthamide, 1,3,5-cycloheptatriene and 1-aziridineethanol were not reported to have antifungal activity. In addition, these molecules were not reported in S. variabilis. Evolutionary fitness analysis revealed a 64-fold or 98% reduction in the growth of C. neoformans for the evolved strain S3, with an overexpression of compounds of ∼52%. Hence, the present study confirms that an integrated approach using adaptive laboratory techniques and co-culturing techniques is useful to discover potential molecules active against targeted pathogens.

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Introduction

Invasive fungal infections have emerged as a great challenge in medicine. Their incidence and mortality rates have dramatically increased in the last few decades.¹ Although patients with weak immunity are highly susceptible and prone to these infections, reports of healthy individuals being affected are also on the rise. The most common causes of invasive fungal infections in healthy individuals are surgery and long-term antibiotic treatment.^2–4 Cryptococcus neoformans is an emerging opportunistic fungal pathogen that causes meningitis, a neurological infection, in immunocompromised patients and is particularly predominant in patients with HIV.^5,6 C. neoformans has unique virulence properties such as capsule production and melanization during infection. Although the availability of antiretroviral therapy has helped patients to become less prone to cryptococcal infection, it is still a major problem under resource-limited conditions where HIV is still prevalent.⁷ Recently, the Centers for Disease Control estimated that there are approximately one million new cases of cryptococcal meningitis each year, which result in the death of 625 000 people worldwide.^8,9 Therapeutic options for the management of cryptococcal infections are limited. The current therapy consists of a cocktail of amphotericin B and flucytosine (5-FC), but 5-FC remains largely unavailable in Asia and Africa where cryptococcal meningitis is common.¹⁰ However, fluconazole intake for a prolonged period of time can lead to other yeast infections such as fluconazole-resistant candidiasis, whereas in the case of highly efficient lipid-based amphotericin B its cost and inability to pass through the blood–brain barrier are major setbacks. Thus, the need for research into novel, effective and safe drugs to treat cryptococcal meningitis has become a relevant question in the scientific community.^11,12

The majority of antimicrobial agents in clinical use are natural products obtained from microorganisms.¹³ The ocean constitutes one source for developing antimicrobial agents owing primarily to its rich biodiversity. Marine organisms, especially plants and invertebrates, have received a lot of attention owing to their ability to produce antimicrobial agents. Along with marine plants and animals, marine microbes, which are found to be distributed in every niche of the ocean ecosystem, form a poorly investigated source of antimicrobial agents.¹⁴ Although new antimicrobial agents from Actinomycetes are being identified, they are nevertheless mostly related compounds or derivatives. To search for more diversified antibiotics, we have co-cultivated Streptomyces sp. with a pathogen, thereby helping to trigger defense and the related production of metabolites. It has been shown that co-cultivation is an efficient method for identifying and employing new secondary metabolites that are not detected in axenic cultures of the producing strain.¹⁵ For example, during co-cultivation fungally derived enniatin derivatives displayed an increase in antagonistic alterations against MRSA.¹⁶ Co-cultivation has been identified as a powerful emerging tool for enhancing chemical diversity in microbes. Although this technique has been found to be promising in biomedical research, it is still in its infancy.

There are various methods of elicitation that are being used by various research groups to induce secondary metabolites that were not actually expressed in monocultures such as elicitation by microbial co-cultivation,^17–19 microbial lysates,²⁰ and cellular components,^21,22 chemical elicitation,²³ and molecular elicitation.²⁴ Adaptive laboratory evolution (ALE) has also been reported as a method of acceleration to induce the production of secondary metabolites.^25–27

ALE is an important scientific approach in the analysis of evolutionary phenomena.²⁸ ALE is a well-known method for generating new improved phenotypes of industrial importance. In addition, ALE is used as a laboratory technique to investigate ethanol tolerance, osmotic stress, and antibiotic resistance, and to increase the production of antibiotics.^26,28–31

In the present study, we developed a novel approach to trigger and improve the activity of bioactive molecules by a combined approach using ALE and co-culture. A new strain of Streptomyces variabilis AFP2 displaying anticryptococcal activity was co-cultivated with C. neoformans. The technique was carried out for a period of 30 days, which comprised 3 serial passages of S. variabilis AFP2. The metabolomes of the wild-type and evolved strains were compared by HPLC-UV and GC-MS methods.

Methodology

Isolation of marine Actinomycetes spp.

Samples of marine sediment were collected from the sea at Rameswaram, Tamil Nadu, India (latitude: 9.145105 to 9.06412677; longitude: 79.453812 to 79.31699753) at different depths ranging from the surface to 250 cm. The sediment samples were mixed together and preserved at 4 °C until further processing. A simple pretreatment method was employed to promote the isolation of Actinomycetes spp. The soil samples were incubated at 60 °C for 40 min and resuspended in 0.9% saline water. The resuspended mixture was diluted with 100 mL saline containing 1.5% (v/v) phenol and shaken for 30 min at 28 °C.³² The pretreated samples were plated on various media such as Zobell marine agar,³³ Actinomycetes isolation agar,³⁴ starch agar,³⁵ yeast extract–malt extract agar²¹ and starch–casein–nitrate agar.³⁵ The media were supplemented with gentamycin (1 μg mL⁻¹) and fluconazole (50 μg mL⁻¹) after sterilization to inhibit the growth of bacteria and fungi, respectively.^36,37 The plates were incubated for 21 days at 37 °C. The isolates obtained from each medium were stored in 15% glycerol at −80 °C.

Antagonism assay against C. neoformans

Test strain. The test strain C. neoformans 14116 was purchased from the Microbial Culture Collection Centre, Chandigarh. The strain was maintained in PDA slants at 4 °C and 15% glycerol stocks at −80 °C.

Antifungal assay. The anticryptococcal activity of 60 marine Actinomycetes isolates was assayed to select a potential strain according to Ramakrishnan et al. Spore suspensions of individual isolates were spot-inoculated (10 μL per spot) on Mueller–Hinton agar plates and incubated at 30 °C for 3 days. The cells were then killed with chloroform vapor and were subsequently overlaid with agar with 15 mL of a medium containing 1% (w/v) agar, 0.5% (w/v) peptone, and 0.5% (w/v) yeast extract and swabbed with 100 μL of a test isolate of C. neoformans on the agar surface. The resulting clear zone of inhibition (ZOI) was measured after incubation for 2 days. The experiment was repeated three times. The mean diameter of the ZOI and the standard deviations were calculated. The AFP2 strain, which exhibited the maximum antagonistic activity against C. neoformans, was selected for taxonomical investigation.^38,39

Taxonomical investigation of AFP2. Genomic DNA from AFP2 was isolated using the procedure described by Kimura.⁴⁰ Gene fragments were amplified using a PCR kit (GENEI Pvt. Ltd, India) and the 16S rRNA gene was amplified using an Eppendorf Mastercycler pro thermal cycler with the following procedure: initial denaturation at 95 °C for 4 min, 30 amplification cycles of 95 °C for 1 min, an annealing temperature of 50 °C for 60 s, and 72 °C for 1 min, and a final extension step at 72 °C for 4 min. The PCR product was electrophoresed and purified from 1.5% agarose gel using a QIAquick PCR purification kit (QIAGEN) and sequenced using the 8F and U1492R primers.^41,42 Sequencing was performed at Chromous Biotech, Bangalore, India using an ABI 3100 sequencer (Applied Biosystems). The sequence was edited using FinchTV (Geospiza Inc.) and BioEdit (Ibis Biosciences, Abbott Labs). A sequence similarity search was conducted using the 16S rRNA gene and a taxid-specific BLAST tool.³⁹

Adaptive laboratory evolution by competition-based co-culture

Adaptive laboratory evolution by competition-based co-culture was begun by growing AFP2 and C. neoformans separately in 50 mL starch broth at 37 °C for 48 h and 24 h, respectively, in an orbital shaker at 120 rpm (step 1). Following the logarithmic growth period, competitive co-culture was initiated by transferring 10% of AFP2 (48 h-old culture) and a 5% inoculum of C. neoformans (24 h-old culture) into 500 mL starch broth in a 1000 mL conical flask and growing them together at 37 °C over a 10 day period (step 2). The culture was serially passed every 10 days for 30 days. Whichever isolate displayed increased anticryptococcal activity in comparison with the parental strain was selected for each serial passage. AFP2 was then cultured alone using the quadrant streak technique on Actinomycetes isolation agar medium at 37 °C for 72 h. Different colonies with distinct morphologies were checked for anticryptococcal activity. The isolate that produced the largest ZOI (hereafter referred to as S1) was selected for a second round of adaptive competitive co-culture (step 3). The serial passages of AFP2 (S1) were continued until the third cycle of the adaptive co-culture experiment (steps 4–7). The best evolved strain from the third serial passage of the adaptive phase was selected that displayed higher antagonistic activity against C. neoformans than the parental and other evolved strains. However, we did not proceed to further serial passages as S3 exhibited suboptimal growth in comparison to the parental strain and it was also presumed that over time AFP2 would reach its maximum defense level against C. neoformans. During this study of selective pressure, we selected 3 potential evolved strains from each cycle of adaptive evolution, whichever displayed improved activity in comparison with the parental strain (Fig. 1). The evolved isolates S1, S2, and S3 were selected for further analysis of the production of secondary metabolites (step 8). The evolved strains were stored in 20% glycerol at −80 °C.^26,28,43

Fig. 1 Adaptive laboratory evolution by competition-based co-culture: step 1: monoculturing of AFP2 and C. neoformans for 48 h and 24 h, respectively; step 2: co-culturing of 10% AFP2 and 5% C. neoformans for 10 days; step 3: isolation of discrete colonies of AFP2 from co-culture broth and selection of phenotype with improved antifungal activity (evolved strain designated as S1); step 4: co-culturing of S1 and C. neoformans for a second round of ALE; step 5: isolation of discrete colonies of S1 from co-culture broth and selection of phenotype with improved antifungal activity (strain designated as S2); steps 6 and 7: the above procedure repeated for a third round of ALE; step 8: selection of potential evolved strain for monitoring the induction and overproduction of antifungal molecules in comparison with the parental strain.

Production and extraction of antifungal metabolites

A loopful of spores of parental-type S. variabilis AFP2, S1, S2, S3, and C. neoformans as a control were cultivated in 25 mL starch broth. The seed media were incubated at 37 °C for 48 h for the parental strain, S1 and S2, 72 h for S3 and 24 h for C. neoformans for the logarithmic growth period. Then, 10% (v/v) of each seed inoculum was used to seed 2.5 L production medium composed of yeast extract (0.1%), peptone (0.5%), glucose (1%), KH₂PO₄ (0.1%), and MgSO₄ (0.05%) at 30 °C with a shaking speed of 180 rpm for an incubation period of 10 days. Each fermented broth was centrifuged at 8000g for 10 minutes. The culture filtrates were extracted twice with equal volumes of ethyl acetate using the cross-current method. Residual ethyl acetate was concentrated in vacuo to dryness. Finally, the extracts were dissolved in phosphate buffer (pH 7). The yield of each crude extract was observed and then the extracts were tested for antifungal activity by the well diffusion method, with a volume of 100 μL of the compound in each well.

Differential production of secondary metabolites by HPLC-UV-PDA

To monitor the differential production of secondary metabolites by the parental and evolved strains, ethyl acetate extracts of the parental strain, S1, S2 and S3 were analyzed using semi-preparatory HPLC (1260 Infinity, Agilent). A reverse-phase analytical C18 column (4.6 mm × 250 mm) was used with a linear gradient from 1% to 60% MeOH and 99% to 40% water over 30 minutes at a flow rate of 1 mL min⁻¹ at 25 °C. For the first 4 minutes the MeOH concentration was increased linearly to 20%. At the twentieth minute, the MeOH concentration was increased linearly to 50%. Finally, the MeOH concentration was increased to 60% at 30 min. Chromatograms were obtained at different wavelengths (200 nm, 225 nm, 250 nm, and 300 nm) to study the possible metabolite profiles at various wavelengths.¹⁸

Antifungal activity of parental and S3 HPLC fractions

The HPLC fractions of the parental and S3 strains were collected using a peak-based method. The fractions were dried in an oven at 50 °C, dissolved in 50 μL PBS and tested for anticryptococcal activity (10⁵ cells in each well) using a 96-well plate. Triplicates were measured for each fraction. The 96-well plate was incubated at 37 °C for 48 h in humid conditions to reduce evaporation of the media. The optical density of each well was recorded using an ELISA reader (Sunrise, Tecan) at 620 nm.¹⁵

Evaluation of evolution in Streptomyces variabilis AFP2

In general, morphological variants are evident in Streptomyces mutants.⁴³ Hence, phenotypic changes in the parental and evolved strains were monitored by observing changes in colony and spore morphology. The spore morphology of 14 day-old culture samples of the parental strain and S3 strain was examined using light and scanning electron microscopy. The spore morphology was studied by examining gold-coated dehydrated specimens using a field emission scanning electron microscope (JSM-6701F, JEOL, Japan).

In addition, increases in the antagonistic activity of S3 were analyzed by culturing in the following conditions: (i) monoculture of the parental strain; (ii) monoculture of the S3 strain; (iii) monoculture of C. neoformans; (iv) co-culture of the parental strain and C. neoformans; and (v) co-culture of S3 and C. neoformans. The experiments were carried out for 14 days at 37 °C. Each day, 100 μL co-culture broth was withdrawn at time intervals of 24 h for 14 consecutive days and cell counts of C. neoformans were performed using a hemocytometer. In addition, changes in capsule size and the polysaccharide matrix that surrounded C. neoformans were assessed.

Measurement of capsule thickness by staining with India ink

A drop of India ink was mixed with an aliquot of C. neoformans on a glass slide. The samples were examined using a Nikon Eclipse Ci-L microscope and images were recorded with an SLR camera (Canon D5100). To calculate the relative size of the capsule, the diameter of the whole cell including the capsule (D_wc) and the diameter of the cell body limited by the cell wall (D_cb) were measured using ImageJ 1.48v software (National Institutes of Health, Washington, D.C.). The size of the capsule relative to that of the whole cell was defined as a percentage {[(D_wc − D_cb)/D_wc] × 100}. Eight cells were measured for each determination and the average was calculated.^44–46

GC-MS analysis

A crude extract of the S3 strain was subjected to comparative analysis against an extract from the parental strain using gas chromatography and mass spectrometry (GC-MS) with the help of the National Institute of Standards and Technology spectral library.⁴⁷ The analyses were performed using a PerkinElmer Clarus 500 GC-MS system. The program was set at a temperature of 50 °C for a duration of 1 min and the temperature was then raised at 10 °C min⁻¹ to 150 °C (1 min hold), at 8 °C min⁻¹ to 250 °C (1 min hold), and at 15 °C min⁻¹ to 300 °C (3 min hold). Helium (1 mL min⁻¹) was used as the carrier gas. The injector temperature was maintained at 280 °C and the mass range was 40–450 amu. A sample of 1 μL dissolved in ethanol was injected into the system. Compounds were identified by comparing their mass spectra with spectra from the database.

Results

Isolation of S. variabilis AFP2

During this study, 60 morphologically different Actinomycetes spp. from marine sediments were isolated using various agar media recommended for the isolation of Actinomycetes. However, only two isolates were shown to exhibit anticryptococcal activity, among which the AFP2 strain isolated from starch agar displayed a maximum ZOI of 12 mm. Thus, the AFP2 strain was selected for sequencing of 16S rRNA. A sequence similarity search using the BLAST tool revealed that AFP2 (KJ716228) belongs to a distinct phyletic line of S. variabilis. The isolate was closely related to the type strains of S. variabilis strain NRRL B-3984, S. labedae strain CSSP735, S. lateritius strain CSSP722 and S. griseoincarnatus strain CSSP407, sharing a homology of 99%.

Adaptive laboratory evolution by competition-based co-culture

ALE by competition-based co-culture was carried out to trigger the expression of anticryptococcal metabolites by AFP2. After serial passage for 30 days (∼180 generations) of AFP2 in competition-based co-culture with C. neoformans, three isolates, namely, S1, S2 and S3 were derived from a single evolved population in three adaptive cycles. During adaptive evolution, certain changes in the characteristics of S. variabilis are expected to occur. Hence, to confirm the putative effect, the evolved isolate from each adaptive phase was tested for anticryptococcal activity because the best phenotype is not necessarily the one with the highest ability to survive in competitive conditions, but the one that displays increased activity.²⁸ The ZOIs of the evolved strains were comparatively larger than that of the parental strain, which suggests that antagonistic activity was higher in the evolved strains than in the parental strain. A similar kind of adaptive evolution was used by Charusanti et al. to increase the activity of S. clavuligerus against S. aureus; however, the experimental design was different from that in the present study.^26,48,49

Increase in antifungal activity in evolved strains

The parental-type, S1, S2, and S3 strains were cultivated in production medium for 10 days at 37 °C. The culture supernatants were then centrifuged and extracted with ethyl acetate. A variation in yield between the strains was observed (parental-type: 11.8 mg; S1 and S2: 12.6 mg; S3: 8.6 mg; and C. neoformans: 3 mg, for 100 mL production medium). A significant increase in antifungal activity for the crude extracts of the adapted strains is shown in Fig. 2: ZOI of parental strain: 12 mm; S1 and S2: 15 mm; and S3: 26 mm. Interestingly, the yield of compounds and the antagonistic activity were not directly proportional, which probably suggests that adaptation could most probably promote the synthesis of more specific inhibitory molecules than in the wild-type strain.

Fig. 2 Antagonism assay of EtOAc extracts of parental and evolved strains of AFP2 (A–D): ZOIs of parental, S1, S2, and S3 strains of AFP2.

Profiles of secondary metabolites by HPLC-UV-PDA

The profiles of secondary metabolites of the parental-type, S1, S2, and S3 strains were monitored by HPLC-UV-PDA. The maximum absorbance was observed at 225 nm for all the strains. The metabolomes of the evolved strains displayed a different chemotype than that of the parental-type strain (Fig. 3). A comparison of all the chromatograms implies that some new peaks were observed for S1, S2 and S3 between retention times of 4 and 8 minutes. In addition, the increase in peak area in the S3 chromatogram confirms that the triggered molecules and existing molecules were overexpressed. A comparison of the HPLC chromatograms of the parental and evolved strains suggests that progressive adaptation of strains over several passages is useful to trigger and promote the expression of metabolites. Many reports have demonstrated chemotypic differences in axenic and mixed cultures using HPLC-UV analysis;^15,18,50 however, this is a presumptive test to confirm variations in the metabolome. Although the samples were analyzed at different wavelengths to screen the maximum number of peaks, it is mandatory to identify the chemotype of the parental and evolved strains.

Fig. 3 Comparative study of HPLC profiles of EtOAc extracts of parental and evolved strains of AFP2. HPLC chromatograms of parental, S1, S2, and S3 strains of AFP2 and C. neoformans at 225 nm. In the S3 chromatogram (*) represents newly expressed peaks and (^) overexpressed peaks.

Antifungal activity of parental and S3 HPLC fractions

HPLC fractionation of the crude extracts of the wild-type and S3 strains yielded 22 and 32 fractions, respectively. Fig. 4 shows that nearly 12 molecules were newly expressed by the evolved strain. Among these, 3 fractions were shown to display antagonistic activities of 35–45% in terms of reduction in the growth of C. neoformans in comparison with the positive control. However, the 22^nd fraction, which was found to be expressed by both parental-type and S3 strains, exhibited a 65% reduction in the growth of C. neoformans. Hence, the induction and overexpression of antifungal molecules were evident in the evolved S3 strain.

Fig. 4 Antifungal activity of HPLC fractions of parental and evolved S3 strains of AFP2. (−)ve represents negative control (media without culture); (+)ve represents positive control (media with culture).

Evaluation of evolution in AFP2

A notable phenotypic change in terms of colony morphology was observed in the S3 strain (Fig. 5I). Scanning electron microscopy analysis of 14 day-old spores of the parental strain showed the presence of wart-like projections and spines on spore surfaces. However, the S3 strain was characterized by tightly coiled spiral chains of spores, with spores having large numbers of long projections (Fig. 5II), unlike the somewhat straighter and loosely coiled chains of spores with fewer projections over the spore surface of the parent type.

Fig. 5 (I) Variation between parental strain (A) and evolved strain (B) in colony morphology on AIA agar; (II) SEM micrographs of parental (C) and S3 (D) strains of AFP2.

Changes in growth profile were also observed between the evolved and parental strains. The evolved strain displayed suboptimal growth when compared with the parental strain (Fig. 6I). The suboptimal growth of the S3 strain revealed that it underwent a competition for nutrients during co-cultivation. However, a high growth rate of a microbe is not a common criterion for determining evolutionary fitness.^28,51 Nevertheless, biomass yield and an ability to survive in a competitive environment are always correlated with the production of secondary metabolites.⁵² Interestingly, increased activity was observed even for suboptimal growth of S3. Fig. 6II shows the reduction in the growth of C. neoformans during mixed culture with the parental strain. However, a remarkable reduction in fungal growth was observed for co-cultivation of S3 with C. neoformans. Moreover, a notable change in capsule thickness in the evolved strain is clearly evident in Fig. 7, with a reduction of 25% in capsule thickness.

Fig. 6 (I) Growth profiles of monocultures (control): (A) C. neoformans; (B) AFP2 parental strain; (C) S3 evolved strain; (II) antagonistic effects of parental and evolved strains during co-culturing: (D) parental strain vs. C. neoformans; (E) S3 evolved strain vs. C. neoformans.

Fig. 7 Comparison of capsule growth of C. neoformans during co-cultivation with parental and S3 evolved strains: (A) the percentage capsule thickness for ≥8 cells per group is shown. The bars represent standard errors; (B–D) light microscopy views (100×) of C. neoformans capsules.

GC-MS analysis

About 21 new metabolites alien to the parent strain were seen to be produced by S3 (Fig. 8). The list of compounds that are commonly expressed by the parental and S3 evolved strains is given in Table 1. The molecules triggered in S3 and those that are absent in the wild-type strain are listed in Table 2. In addition to interpreting the chemical diversity, the data for percentage peak area represents the yield of compounds. The increase in the yield of compounds is a notable result that proves that the integrated approach using ALE and co-cultivation is a suitable method for increasing the production of metabolite. For instance, increases in the yield of 2-methylpropanamide (56%), butanamide (54%), 3-methylbutanamide (53%) and hexahydro-3-(2-methylpropyl)-pyrrolo[1,2-a]pyrazine-1,4-dione (41%) were recorded in comparison with parental-type S. variabilis. Overproduction was clearly evident, as shown in Fig. 8 and Table 1. Few of the induced compounds and their derivatives were previously reported to have antifungal activity (Table 2). Nevertheless, molecules such as DL-alanyl-L-leucine (yield, % peak area: 3.1%), dihydro-3,3-dimethyl-2(3H)-furanone (2.7%), enanthamide (2.7%), 1,3,5-cycloheptatriene (1.6%) and 1-aziridineethanol (1.6%) were not reported to have antifungal activity. In addition, these molecules were not reported in S. variabilis. Hence, this confirms that our approach enables the triggering of silent gene cluster(s), resulting in the synthesis of novel molecules.

Fig. 8 GC-MS profiles of AFP2 parental and S3 evolved strains: in the S3 chromatogram (*) represents induced molecules and (^) represents overproduced molecules. (1) Dihydro-3,3-dimethyl-2(3H)-furanone; (2) enanthamide; (3) 1,3,5-cycloheptatriene; (4) DL-alanyl-L-leucine.

Table 1 Common compounds present in both wild-type strain and S3 strain determined by GC-MS

S. no.	Name	Formula	MW	Wild-type			S3			Overproduction of compound in S3 (% increase)
				Retention time	Peak area	% peak area	Retention time	Peak area	% peak area
1	2-Methylpropanamide	C4H9NO	87	4.74	39 873 944	3.7718	4.82	1.39 × 10^8	8.6307	56.29787
2	Butanamide	C4H9NO	87	5.42	13 945 809	1.3192	5.48	46 590 024	2.8877	54.31658
3	N-Hydroxymethylacetamide	C3H7NO2	89	7.87	4 336 799	0.4102	6.29	4 697 297	0.2911	—
4	3-Methylbutanamide	C5H11NO	101	6.48	25 926 508	2.4525	6.61	85 550 336	5.3025	53.74823
5	Pentanamide	C5H11NO	101	9.12	43 524 428	4.1171	9.26	91 229 608	5.6545	27.18896
6	Octanamide	C8H17NO	143	13.64	8 076 171	0.7639	11.66	17 206 876	1.0665	28.37318
7	Octanamide	C8H17NO	143	—	—	—	13.70	6 632 707	0.4111	—
8	[(Methoxymethoxy)methyl]benzene	C9H12O2	152	14.24	3 329 908	0.315	14.25	4 154 936	0.2575	—
9	Tridecane	C13H28	184	14.92	1 007 684	0.0953	14.92	696 186	0.0432	—
10	Benzeneacetamide	C8H9NO	135	15.76	2.85 × 10^8	26.9762	16.10	4.72 × 10^8	29.244	7.754753
11	2,4-Bis(1,1-dimethylethyl)phenol	C14H22O	206	18.38	24 139 044	2.2834	18.40	2 209 378	0.1369	—
12	Tridecane	C13H28	184	14.92	1 007 684	0.0953	14.92	696 186	0.0432	—
13	Tridecane	C13H28	184	—	—	—	20.19	608 988	0.0377	—
14	Hexahydro-3-(2-methylpropyl)-pyrrolo[1,2-a]pyrazine-1,4-dione	C11H18N2O2	210	27.05	35 255 676	3.3349	27.16	67 217 472	4.1662	19.95343
15	4-Methylbenzoic acid 1-methylethyl ester	C11H14O2	178	28.23	24 750 376	2.3412	28.33	51 245 500	3.1762	26.28928
16	Hexahydro-3-(2-methylpropyl)-pyrrolo[1,2-a]pyrazine-1,4-dione	C11H18N2O2	210	29.41	21 280 488	2.013	29.52	55 535 760	3.4422	41.51996
17	Hexahydro-3-(2-methylpropyl)-pyrrolo[1,2-a]pyrazine-1,4-dione	C11H18N2O2	210	30.05	79 494 712	7.5196	30.17	1.29 × 10^8	7.9727	5.683144
18	Hexahydro-3-(2-methylpropyl)-pyrrolo[1,2-a]pyrazine-1,4-dione	C11H18N2O2	210	30.36	28 916 384	2.7353	30.48	67 372 280	4.1758	34.49638
19	Dodecanamide	C12H25NO	199	31.83	94 955 744	8.9821	34.00	2 033 383	0.126	—
20	Hexahydro-3-(phenylmethyl)-pyrrolo[1,2-a]pyrazine-1,4-dione	C14H16N2O2	244	40.47	72 263 544	6.8356	41.06	80 100 008	4.9647	—

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Table 2 Compounds present in S3 strain determined by GC-MS

S. no.	Name	Formula	MW	Retention time	Peak area	% peak area
1	1,3-Dimethylbenzene	C8H10	106	3.86	4 746 478	0.2942
2	1-Aziridineethanol	C4H9NO	87	7.08	26 188 024	1.6232
3	1,1′-[Ethylidenebis(oxy)]bis[2-methylbutane]	C12H26O2	202	7.39	1 686 723	0.1045
4	2-Methyl-3-butenoic acid methyl ester	C6H10O2	114	7.6	3 654 044	0.2265
5	Butanedioic acid	C4H6O4	118	13.12	1 403 604	0.087
6	4-Methylene-5-hexenal	C7H10O	110	7.79	2 322 845	0.144
7	Dihydro-3,3-dimethyl-2(3H)-furanone	C6H10O2	114	8.32	44 006 676	2.7276
8	4-Acetylbutyric acid	C6H10O3	130	10.49	2 265 020	0.1404
9	6-Methyl-6-azabicyclo[3.2.1]octane	C8H15N	125	10.69	196 201	0.0122
10	Enanthamide	C7H15NO	129	11.45	44 932 220	2.7849
11	1,3,5-Cycloheptatriene	C7H8	92	12.76	26 539 802	1.645
12	Dihydro-4,4-dimethyl-2(3H)-furanone	C6H10O2	114	13.91	1 851 129	0.1147
13	Benzamide	C7H7NO	121	14.38	2 886 997	0.1789
14	2-Methyl-(4H)-3,1-benzoxazin-4-one	C9H7NO2	161	15.43	698 960	0.0433
15	Phenylpropanamide	C9H11NO	149	18.91	1 882 071	0.1167
16	4-Methylpentanamide	C6H13NO	115	21.04	3 508 549	0.2175
17	4-Hydroxybenzeneacetic acid	C8H8O3	152	22.21	6 275 494	0.389
18	3-(1-Aziridinyl)-3-dimethylamino-2-propenal	C7H12N2O	140	24.37	14 641 184	0.9075
19	DL-Alanyl-L-leucine	C9H18N2O3	202	25.78	51 295 148	3.1793
20	4-Hydroxyphenylacetamide	C8H9NO2	151	26.4	8 670 816	0.5374
21	4-Ethyl-5-methylheptanamide	C10H21NO	171	26.68	14 915 393	0.9245
22	2,6,10,15-Tetramethylheptadecane	C21H44	296	33.79	582 825	0.0361

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Evolutionary fitness analysis revealed that a 64-fold or 98% reduction in the growth of C. neoformans was observed for the evolved S3 strain. In addition, remarkable differences in the induction and overproduction of antifungal molecules were also evident for the S3 strain, with an increase of ∼52% in compounds and 21 new triggered compounds. Hence, the present study confirms that an integrated approach using adaptive laboratory techniques and co-culturing techniques is useful to discover potential molecules against targeted pathogens.

Discussion

Natural products from Actinomycetes spp. are considered to be an important source of novel antimicrobial compounds owing to their diversified secondary metabolites.^53,54 Recently, the rate of discovery of new compounds from terrestrial Actinomycetes spp. has been decreasing, whereas the rate of rediscovery of known compounds has increased.^55,56 As marine environmental conditions are extremely different from terrestrial conditions, it is surmised that marine Actinomycetes spp. have different characteristics from those of their terrestrial counterparts and therefore might produce different types of bioactive compounds. They form a stable, persistent population in various marine ecosystems.⁵⁷ There have been some recent discoveries of new antifungal molecules, namely, the polyene-polyol-macrolides bahamaolide A and B,⁵⁸ ikarugamycin derivatives from marine S. variabilis^59–61 and a new tetramic acid glycoside, aurantoside K, obtained from a marine sponge.^62,63 In addition, more information was provided by Xu et al. in a recent review, which reports 116 new antifungal and antibacterial compounds from marine fungi during 2010-15.⁶⁴ Many studies propose the existence of undiscovered antifungal compounds from marine Actinomycetes spp. The present study exploited marine sediments for Actinomycetes spp. exhibiting anticryptococcal activity. During the course of this study, we found a new strain of S. variabilis AFP2 that has an inhibitory effect against C. neoformans, which suggests the production of possible new antifungal metabolites. However, the chances of rediscovering the tens of thousands of known molecules are high. The main challenges behind this are the inability to cultivate potential microbes and finding a suitable trigger that enables the expression of silent biosynthetic gene clusters under normal laboratory conditions. Novel approaches are being implemented by various researchers to search for antimicrobial agents such as genome mining and soil metagenomics.^43,48,65 Until now various co-culture strategies have been employed to mimic natural conditions to facilitate the discovery of novel secondary metabolites.^66,67 The mixed cultivation of microbes has drawn the attention of most investigators, as the interspecies communication and defense mechanisms are found to trigger the expression of silent biosynthetic gene clusters.^68,69 However, mixed fermentation is still in its infancy, which is probably due to lack of reproducibility.⁷⁰ More recently, two new butyrolactone derivatives were isolated during the co-cultivation of A. terreus with the bacteria Bacillus subtilis and Bacillus cereus.⁷¹ Similarly, a new molecule, rhodostreptomycin, was expressed during the co-cultivation of Rhodococcus fascians and S. padanus,⁷² which was not detected in axenic cultures. However, co-culture may not always be suitable for discovering novel molecules. For example, levorin (an existing molecule) was isolated during co-cultivation of Candida tropicalis and Actinomyces levoris.^73,74 Similarly, 6-methylsalicylic acid and cyclo-(phe–phe) dipeptides were isolated during the co-cultivation of two unknown marine endophytic fungi.⁷⁵ Also, in a recent study, co-cultivation of Aspergillus fumigatus and S. bullii was reported to produce seven metabolites belonging to the diketopiperazine alkaloid family with antimicrobial and antiprotozoan activity.²¹ However, significant numbers of known compounds were reported and thus mixed fermentation is not always likely to yield novel molecules.⁷⁶ Hence, until now various co-culture strategies have been employed to mimic natural conditions to facilitate the discovery of novel secondary metabolites.⁶⁷ In the present study, we followed a different approach by combining adaptive laboratory evolution and mixed fermentation. Our idea was to evolve improved phenotypes that provide an efficient defense mechanism against the targeted pathogen by the overexpression and induction of novel molecules. In general, ALE involves the cultivation of microbes in controlled conditions for prolonged periods in the range of weeks to years, which enables the selection of improved phenotypes. Evolutionary engineering has been proven to be an efficient method for the improvement of industrial strains. This technique has been successfully established to generate strains with improved activity such as tolerance to thermal stress, nutrient stress, osmotic stress, ethanol stress, and acid stress and also for enhanced substrate utilization.^77–79 The primary motive of the present study was to apply the evolutionary principle to generate improved antagonistic properties via possible methods for activating silent gene clusters by co-cultivation. During our study, by adaptive evolution and the competitive co-culture of S. variabilis AFP2 and C. neoformans for periods of 30 days, we have selected 3 improved phenotypes with higher anticryptococcal activity and their metabolomes were analysed.

In general, the common analytical techniques for the analysis of metabolomes include LC-MS, GC-MS and NMR. GC-MS is recognized to be one of the most versatile analytical methods in metabolomics studies of biological samples, because of its reliable and reproducible results.^80,81 However, reports on microbial metabolomics using GC-MS are limited.⁸² Cevallos-Cevallos et al. demonstrated the suitability of GC-MS for microbial metabolomics of E. coli, Bacillus sp. and Pseudomonas sp. More frequently, researchers have used HPLC/LC-MS followed by NMR to determine the structural details of triggered molecules.^21,71,83 However, as our intention was to compare the metabolic profiles of the parental and evolved strains, a GC-MS platform was used. GC-MS analysis showed clear comparisons between the metabolomes of the parental and S3 strains with respect to peak identification, peak relative area, retention time and mass spectroscopic data (Fig. 8). Structural determination using NMR is a future direction of our lab. Although GC-MS analysis determines the overexpression and induction of compounds, we believe that biological assays are also mandatory. Therefore, we tested the extracts of the parental, S1, S2 and S3 strains against C. neoformans and its capsule growth. The capsule is the most prominent and well-studied antiphagocytic factor in C. neoformans.^84,85 The efficiency of phagocytosis is regulated by the capsule size. An increase in capsule size is found to decrease complement-mediated phagocytosis.^86,87 Hence, the determination of the in vitro activity of the extracts of the parental and evolved strains and its influence on the capsule size of C. neoformans was considered to be another significant result of the present study, which is clearly depicted in Fig. 7. The evolved strain displayed a 64-fold or 98% reduction in the growth of C. neoformans in comparison with the parental strain. The increased antifungal activity was possibly due to the induction of new molecules and overexpression of compounds in the S3 strain. GC-MS analysis revealed an increase of ∼52% in the production of metabolites. Hence, the present study concludes with evidence that adaptive laboratory evolution by competition-based co-culture is a novel and suitable method of strain engineering to induce and overproduce specific molecules against a targeted pathogen.

Conclusion

The main challenge behind the discovery of novel anti-infective agents from microbial sources is to find a suitable trigger that enables the expression of silent biosynthetic gene clusters under normal laboratory conditions. Novel approaches are being implemented by various researchers to discover novel antimicrobial agents such as genome mining, soil metagenomics and co-culture techniques employed to mimic natural conditions to facilitate the discovery of novel secondary metabolites. However, co-culture may not always be suitable for discovering novel molecules. Our results suggests that the proposed integrated approach using adaptive laboratory evolution and competition-based co-culture is a novel and suitable method of strain engineering to induce and overproduce specific molecules against a targeted pathogen.

Conflict of interest

The authors declare no conflict of interests.

Funding

Department of Science & Technology (DST), New Delhi, under the Fast Track Young Scientist Scheme (No. SB/FT/LS-249/2012) and EMR scheme SR/S0/HS-0073/2012.

Acknowledgements

This study was financially supported by the Science and Engineering Research Board (SERB), Department of Science & Technology, New Delhi, under the Fast Track Young Scientist Scheme (No. SB/FT/LS-249/2012) and HPLC facility EMR scheme SR/S0/HS-0073/2012 to JP. We thank SASTRA University for providing us with the infrastructure to carry out our research work.

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Footnote

† All authors have equal contribution.

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