Culturable Streptomyces spp. from high-altitude, oligotrophic North Western Himalaya: a comprehensive study on the diversity, bioactivity and insights into the proteome of potential species

Abstract The increasing global concern of antimicrobial resistance and shortage of new antimicrobials necessitates exploring untapped terrestrial environments for new bioactive microbiome diversity. The low-temperature and oligotrophic North Western Himalaya (NWH) region has a vast diversity of Streptomyces with potential antimicrobial properties that remain largely unexplored. This study evaluates the diversity of culturable Streptomyces from high-altitude NWH and their potential as a source of new antimicrobials through genus-specific isolation and identification. The results demonstrate a distinct phylogenetic clustering of Streptomyces from different sampling regions of NWH, site-specific variation in culturable β-diversity and species commonness with varying intersite bioactivity among different sites. Further, the study optimized the media selection for large-scale culture cultivation in antibiotic production processes and demonstrated the antimicrobial efficacy of Streptomyces against a range of pathogens through in vitro bioassays using minimum inhibitory concentration determination and antibiofilm activity. Untargeted label-free proteomic profiling also revealed variable expression of stress-response proteins and antibiotic regulators as a competitive survival strategy for selective antagonistic Streptomyces. The findings highlight the potential of NWH in augmenting antimicrobial discovery and combating antimicrobial resistance through the isolation and study of novel bioactive Streptomyces.


Introduction
Actinobacteria are known to be the potential reserves for different molecules including antibiotics in clinical use .T he genus Streptom yces has tr emendous bioactiv e ca pacity to pr oduce ne w types of antimicrobials (Schatz et al. 1944 , Kardos andDemain 2011 ).The increase in the r ediscov ery r ate of known antimicr obials fr om con ventional en vironments ("la w of diminishing returns") has already dried up the antibiotic pipeline and stagnated antibiotic natur al pr oducts (NPs) drug discov ery efforts (Baltz 2006 ).Nov el biosynthetic producers with novel antimicrobial chemical scaffolds are needed to combat resistance and the search for new antimicr obials ov er thr ee decades has met with very limited success (Newman and Cragg 2016 ).The call for "new drugs for bad bugs" shifted the focus on NPs drug discovery to extreme soil and aquatic environments (Udwary et al. 2007, Subramani and Aalbersberg 2013, Shah et al. 2017, Hassan et al. 2019, Sivalingam et al. 2019 ).The genus Streptomyces remains an attractive and exciting field in antibiotic drug discovery research and produces a r emarkable and div erse arr a y of secondary metabolites , including many antibiotics and anticancer drugs, as well as immune suppr essants and antipar asitic a gents (Br aña et al. 2015 ).Metagenomic anal ysis r e v ealed the number of Streptom yces r eads per Megabase (rpM) to be 129.32, 47.49 and 24.65 r pM fr om soil, fr eshwater and marine sources, suggesting that among all three habitats most Streptomyces are soil associated (Chevrette et al. 2019 ).North Western Himalaya (NWH) is the potential growing habitat for different genera of the phylum Actinobacteria, and the genus Streptomyces is exciting in its production of different pharmacologicall y activ e secondary metabolites (Hussain et al. 2017, Rather et al. 2017, Shah et al. 2017, Singh et al. 2019 ).Streptomyces puniceus AS-13 isolated from Sonamarg Mountain of NWH produces dinactin, a bioactive macrotetrolide compound exhibiting str ong antimicr obial (Hussain et al. 2018 ), antituberculosis (Hussain et al. 2019a ) and antitumor activity (Hussain et al. 2019b ).Streptomyces scabrisporus IIIM55 from NWH produces alborixin, a pharmacologically potential bioactive secondary metabolite that displays significant antipr olifer ativ e activity a gainst a panel of cancer cell lines (Shah et al. 2016 ) and also induces autophagy (Wani et al. 2019 ).The high altitudes of NWH ar e str essful envir onments c har acterized by cold temper atur es, limited v egeta-Table 1. Numeric detail of four selected sampling sites (S1-S4), their regional location and soil c har acteristics.Two labor atory Streptom yces cultur es wer e isolated eac h fr om soil samples collected pr e viousl y by our r esearc h gr oup fr om Nar ana g (L1) and Daksum (L2), r espectiv el y. tion and low-nutrient oligotr ophic conditions.Streptom yces gr owing in these str essed envir onments r espond both by antimicr obial production for their competiti ve survi val and regulation of differ ent c ha per one systems for pr oper pr otein folding and integrity (Bhat et al. 2022 ).Investigation into the bioactive potential and differential protein expression will provide deeper insights into the Streptomyces protein response coupled with antibiotic production.

No. of samples
We selected the genus Streptomyces because (i) it is an evolutionaril y ric h source of most United States Food and Drug Administr ation-a ppr ov ed and clinically used antimicrobials (Hopwood 2007 ); (ii) the majority of NP antimicrobials from actinobacteria are produced by Streptomyces cultured from the soil (Lewin et al. 2016 , Newman andCragg 2016 ); and (iii) Biosynthetic Gene Clusters (BGCs) diversity analysis of Streptomyces reveals that the genus can produce ∼100 000 antimicrobials, ho w ever only a small percentage of these have been identified and characterized (Watve et al. 2001 , Newman andCragg 2016 ).The aim of the current study was (1) to isolate and identify the Streptomyces of temper atur econstr ained and oligotr ophic sub-surface soils fr om NWH; (2) to draw a comparative pattern distribution across different sampling locations; (3) to search for the antibiotic production potential of the identified isolates; and (4) to look for the pr oteomic div ersity of selecti ve bioacti ve isolates with an emphasis on proteins as stress and antibiotic regulators.

Sampling
Four oligotrophic soil sampling sites, S1-S4, fr om r ar e (under explored) and high-altitude NWH were targeted and, using a soil probe, a total of 47 soil samples of different textures were collected from June to September 2016 and 2017 (Table 1 and Fig. 1 A).At each sampling site, the surface soil was removed and samples obtained beneath depths of 5-20 cm were sealed in previously labeled sterile pol yethylene ba gs, tr ansported asepticall y to the laboratory at an ambient temperature and stored at 4 • C. Before processing, all subsamples from different locations of each site were mixed pr oportionall y to form composite samples and labeled accordingly as S1, S2, S3 and S4 to r epr esent four differ ent sampling sites.Streptom yces micr obes wer e selectiv el y isolated fr om these composite samples.Further, we included two Streptomyces laboratory cultur es alr eady collected and isolated by our r esearc h gr oup fr om Nar ana g (L1) and Daksum (L2).The details of regional location, DMS coordinates and soil c har acteristics of sampling sites (S1-S4) and the sites from which laboratory isolates were taken (L1 and L2) are shown in Table 1 and Fig

Isolation of Actinobacteria
All the composite samples were dried using combined methods of dry heating (120 • C, 1 h) (Ha yaka wa et al. 1991 ) and drying in a laminar flow hood for 24 h.Actinobacteria were isolated by a standard spread plate method; 1 g of dried soil from each of the composite samples was taken and dilutions of 10 −1 were prepared using a sterile saline solution.Each of the resultant 10 −1 dilutions was given a thermal shock at 50 • C for 6 min.The preparations wer e seriall y diluted down to 10 −6 .Briefly, 200 μl fr om eac h dilution was spread over selective isolation media plates of eight types (M1 to M8) in triplicate (Table 2 ) (Williams et al. 1983 ).All media were supplemented with the antifungals cycloheximide and n ystatin (eac h at 50 μg/ml) and gr am-negativ e antibiotic nalidixic acid (50 μg/ml).Also, one set of plates was supplemented with  novobiocin (25 μg/ml), a gr am-positiv e antibiotic.The inoculated plates were incubated at 28 • C for 14 days and examined after every 2 days for the colonies .T he putative Actinobacteria colonies tak en from selecti ve isolation plates were subcultured and purified at 28 • C.

Selection of genus Streptomyces
All the isolates were examined for their morphologies, recognized and accordingly selected as putative Streptomyces members by their transition from substrate to aerial mycelial morphology patterns, sporulation c har acteristics, colour pigmentation and also by microscopic observation on Gram staining using binocular Leica microscope model DM 5500.The selective isolates of Streptom yces wer e pr eserv ed in 20% gl ycer ol/PBS (v/v) at -80 • C.

DN A isola tion
Streptom yces cultur es wer e gr o wn in star c h casein (SC) br oths for 3-4 days and 1.5 ml of cell suspension culture was taken in 2ml micro centrifuge tubes (or cell mass from bacterial colony was taken and uniformly suspended in 1.5 ml of TE buffer).Cells were harvested by spinning micro-centrifuge tubes for 5 min or until a compact pellet was formed.The pellet was re-suspended in 567-μl TE buffer; 10 μl of 100 mg/ml lysozyme (Thermo Fisher Scientific) was then added and incubated at 37 • C for 1-3 h.Next, 50 μl of 10% SDS and 10 μl of 20 mg/ml Proteinase K (Promega) were added befor e l ysis by incubation at 55 • C for 1 h.Then 100 μl of 5 M NaCl and 80 μl of CTAB/NaCl were added, the tubes were mixed thoroughly and incubated at 65 • C for 20 min.The tubes were cooled to 28 • C and an equal volume of c hlor oform: isoamyl alcohol (24:1 ratio) was added and the tubes were gently shaken until uniformly white and spun at 10 000 r/m for 10 min.After centrifugation, the top aqueous lay er w as tr ansferr ed to a ne w micr o-centrifuge tube and extracted again with an equal volume of phenol: chloroform: isoamyl alcohol (25:24:1 ratio).The top layer was again transferred to another tube and precipitated with 0.6 volume of isopropanol.
The precipitate was centrifuged at 10,000 rpm for 10-20 min and the pellet was washed and spun twice in 500 μl of 70% ethanol at 10 000 r/m for 5 min and resuspended in 100-μl TE buffer.DNA was quantified (NanoDrop Spectrophotometer ND-1000, Thermo Scientific), run on 0.8% gel to c hec k for purity and verify high molecular weight.

Identifica tion b y 16S rDN A sequencing and phylogenetic affiliations
After genomic DNA extraction and quantification, nearly complete 16S rRNA gene was amplified using a set of universal primers: 27F (5 -A GA GTTTGATCCTGGCTCA G-3 ) and 1492R (5 -GGTT ACCTTGTT ACGACT T-3 ) of hyper-variable regions V1-V9.PCR was performed in a 96-well Thermal cycler (Applied Biosystems) in a standard 25-μL reaction with 1-μL DNA template ( < 50 ng μL −1 ), 2.5-μL Taq pol ymer ase assay buffer, 1 μL each of the 10-μM primers , 2 μL of dNTPs , 1.5 μL of MgCl, 0.25 μL of Taq DNA Pol ymer ase (QIAGEN) and 15.75 μL of nuclease free water.Amplification profile with initial denaturation at 94 • C (3 min) was follo w ed b y 30 c ycles of denaturation at 94 • C (30 s), annealing at 55 • C (30 s), extension at 72 • C (90 s) and a final extension at 72 • C (5 min), follo w ed b y infinite hold at 10 • C. Amplicons w ere confirmed on 1% a gar ose electr ophor esis gel prior to cleanup using the in-house PEG/NaCl purification system.The 16S rRNA gene was sequenced by ABI 3730xl Genetic Analyzer (Applied Biosystems) using the sequencing primers 27F , 536F , 946F , 907R, 518R and 1492R.The sequence c hr omatogr ams of 16S rRNA gene of each strain were c hec ked and assembled by SeqMan Pro assembler.The resultant sequences ( ∼1350 nt) were blasted with EzBioCloud Database and the top 50 or maximum number of hits (whichever was possible) were taken.16S rRNA gene query sequence alignment with blast hits was performed using MEGA 11-based MUSCLE Alignment explorer.The evolutionary history was deduced using the Neighbor-Joining method and the percentage bootstrap consensus tree using 1000 replicates was generated to represent the evolutionary history of the analyzed taxa (Felsenstein 1985 , Saitou andNei 1987 ).The Maximum Composite Likelihood method was used to compute evolutionary distances and the final evolution-ary analysis was conducted in MEGA 11 v. 11.0.11 (Tam ur a et al. 2004, Tam ur a et al. 2021 ).The tree was visualized, manipulated and annotated in The Inter activ e Tr ee Of Life (iTOL v. 6.6) (Letunic and Bork 2021 ).

Media optimization of highly bioacti v e strains
Following the preliminary screening by the Agar Well Diffusion method against all the isolates, the 12 highly bioactive strains were selected and inoculated in triplicate in four different production media: SC (Starch Casein), KMM (Kenknight & Munaier's Medium), ISP2 (International Stre ptom yces Project 2) and CYPS (Casein, Yeast extract, Peptone and soluble Starch) (Table 2 ) (each containing 250 ml of medium in 1000-ml Erlenmeyer flasks) and incubated at 28 • C for 14 days at 180 r/m.The fermented broths were centrifuged (Eppenforf Centrifuge 5810 R) at 4000 r/m for 12 min, follo w ed b y filtr ation.The filtr ates wer e mixed with ethyl acetate solvent (2X), vigorously shaken and extracted exhaustiv el y.The supernatant organic layers wer e concentr ated on Rotav a por (R-215, B UCHI).The concentr ated extr acts wer e dried and quantified.

Prepar a tion of extracts of highly bioacti v e strains in optimized media
The Streptomyces isolates were grown as culture broths (300 ml in 1000-ml Erlenmeyer flasks) in different optimized media selected a gainst eac h str ain and incubated at 28 • C for 8-10 days in an orbital shaker (Forma) with 180 r/m.The fermented broths were centrifuged at 7000 r/m for 8 min to pellet down the mycelial cell mass .T he cell-fr ee supernatants wer e solv ent extr acted by ethyl acetate (2X).After exhaustiv e extr action, the or ganic layers were concentrated on a rotary evaporator (Rotavapor, R-215; B UCHI, Switzerland).The extr acted concentr ates wer e quantified and e v aluated for antimicr obial activity.

Test microorganisms
The

Minimum inhibitory concentr a tion measurements
The minimum inhibitory concentrations (MICs) of extracts a gainst test str ains of micr oor ganisms wer e determined by the br oth micr odilution method (Wiegand et al. 2008 ), pr escribed under the guidelines of Clinical and Laboratory Standards Institute (CLSI) pr ocedur es, M07, 11th edition (2018-9) (Humphries et al. 2018 ).Briefly, the stock solutions (50 mg ml −1 ) of extracts were pr epar ed in DMSO and the r efer ence drug, cipr ofloxacin (Sigma-Aldric h), was dissolv ed in 0.1 N HCl at 25 mg/ml.Aliquots of both the extracts and reference drug were further diluted with Muller Hinton broth (MHB) to form working concentrations.Starting with the first well, 2-fold serial dilution in 200-μl volumes and bacterial inoculum (50 μl) was added into each well of a 96-well plate with the final cell density of 1 × 10 5 CFUs/ml.Media containing microbial cells only and ciprofloxacin served as negative and positive contr ols, r espectiv el y.The plates wer e incubated at 37 • C for 24 h and visualized to determine the MICs .T he MIC was defined as the lo w est concentration that prevented the visible microbial growth.
Each MIC (in μg/ml) test was performed twice in triplicate.

Biofilm assay
Micr o titr e plate biofilm assay was used to visualize the attachment pattern of microbial cells to an abiotic surface.Briefly, cultur es of differ ent pathogenic micr oor ganisms wer e gr own overnight in MHB then diluted to 1:100 in fresh Mueller Hinton medium and 50 μL of diluted culture was added into each well in 96-well plates.DMSO-dissolved ethyl acetate extracts of bioactiv e pr epar ations wer e added into eac h well to make the final concentration up to 100 μg ml −1 , except for culture control (negative control) and media control wells.Ciprofloxacin served as the positiv e contr ol.The plates wer e incubated at 37 • C for 48 h.Then the plates were briskly shaken in an overturned position to remove planktonic bacteria from each well then submerged three times in three separate wash trays containing 2-3 in of tap water.The plates were then vigorously shaken to remove any liquid.Next, 125 μL of 0.1% crystal violet solution was added to each well and stained for 10 min at r oom temper atur e (RT).The plates were then a gain vigor ousl y shaken in wash tr ays to r emov e excess stain, inv erted and ta pped on pa per to w els to r emov e excess liquid and allo w ed to air dry.After drying, 250 μL of 30% acetic acid solvent was added to each well to solubilize the dye by incubating at 10-15 min at RT.The contents in each well were briefly mixed by pipetting and 125 μL of dye-solvent solution from each w ell w as transferred to separate flat bottom 96-well plates .T he optical density (OD) of each well was measured at 600 nm.The measurements for each well wer e r eplicated thrice and the mean absorbance values were calculated.Biofilm inhibition was calculated using the formula: P er centage inhibition = OD Negativ e contr ol − OD Experimental OD Negativ e contr ol × 100

Proteomics and systems biology
Next, 100 μL of each selected Streptomyces culture grown to stationary phase in optimized media at 28 • C for 6-8 days was taken and 4% of SDS was added and kept for 15 min at 95 • C. Total proteins in each sample were then precipitated by adding ice cold 6X acetone and centrifuged for 10 min at 13 000 r/m.The proteins pr ecipitated wer e then r ediscov er ed in ammonium bicarbonate buffer of pH 7 and subjected to Liquid Chr omatogr a phy with tandem Mass Spectr ometry (LC-MS/MS) pr oteomic e v aluation.Then 100-μL equivalent of protein from each sample was subjected to reduction and alkylation followed by trypsin digestion at 37 • C for 16-20 h using a sequencing grade modified trypsin: proteins ratio of 1 μg: 20 μg w/w.The cleaved peptides were cleaned by desalting and subjected to downstr eam LC-MS/MS anal ysis using the following parameters: peptide elution from 3 to 95% gradient at a flow rate of 300 μL/ml with buffer B (aqueous 80% acetonitrile in 0.1% formic acid).The elution gradient was carried for ∼60 min on a 25-cm analytical C18 column (C18, 3 mm, 100 A ˚).
The peptide ionization was performed by nano-electr ospr ay follo w ed b y tandem MS/MS on a Q-ExactiveTM Plus (Thermo Fisher Scientific , San J ose , C A, USA).T he ionized peptides were then analyzed using collision-induced dissociation mode in a mass spectrometer with the electrospray voltage of 2.3 kV.Using orbitrap the complete scan analysis of MS spectra was performed with a resolution of 70 000 from m/z 350 to 1800 and further analysis on MS/MS data was performed in Proteome Discoverer (version 2.0, Thermo Fisher Scientific, Waltham, MA, USA) using the UniProt database.Significant proteins at a threshold P < 0.05 were identified and subjected to statistical analysis using MetaboAnalyst version 5.0.  1 ).The five non-Streptomyces isolates sho w ed a physical and micr oscopic a ppear ance that was similar to Streptomyces , but upon molecular identification were found to be members of three different genera.T hus , the a verage hit rate for rediscovery of Streptomyces from these four sampling sites was 51/254 = 20%.Becasue we focused our studies only on Streptomyces , the follo wing w ere the significant observations made from the phylogenetic affiliations of identified isolates.

16S rRNA lacks Str e ptom yces taxonomic r esolution below genus level
Taxonomic classification of each taxon was deduced based on the results of three analytical approaches: (1) maximum percentage similarity of query sequence to top blast hit/s; (2) individual phylogenetic affiliations of query sequence; and (3) concatenation of all the query sequences with their hits and drawing the combined phylogeny.The final conclusion about the proper taxonomic identification of each taxon was reached after analyzing the results of all three approaches ( Supplementary Fig. S1 , Supplementary Table 2 and Supplementary  S2 and Supplementary Table 2 show the similarity percentages along with their amplified base pairs sequences .T hus , most of these species sho w ed a per centa ge similarity with their top hits abov e 99%; ho w e v er, they could not be taxonomically assigned to species le v el, highlighting that 16S rRNA alone is insufficient for proper Streptomyces identification and majorly cannot resolve species le v el delineation in such bacteria.NWH has the potential to pr oduce nov el (bioactiv e) Streptom yces .Streptom yces sp .ASQP 6 (98.64% identity to Streptomyces pseudovenezuelae ), ASQP 94 (98.96% identity to Streptomyces fagopyri ) and a bioactive strain, ASQP 123a (98.71% identity to Streptomyces pseudovenezuelae ), displayed sequence homology similarity well below the cut-off limit of 99%, suggestive of potential for isolation of nov el Streptom yces taxa fr om NWH.Ther efor e, the taxonomic status of Streptomyces spp .strains whose taxonomic identification could not be r esolv ed to species le v el and in which each query taxon sho w ed a per centage sequence similarity to two or more close species, thus warrant further taxonomic resolution to delineate some of these Streptomyces as a new species, suggestive of the importance of NWH as a region of potentially novel Streptom yces pr oducers ( Supplementary Fig. S2 ).

Site-specific phylogenetic clustering
Moder ate le v els of site-specific phylogenetic clustering wer e observed among different sampling locations and Streptomyces isolated fr om differ ent sites tend to cluster in different clades (e.g.Streptomyces spp. with the strain IDs ASQP 13, ASQP 123a, ASQP_98, ASQP 15, ASQP 57 and ASQP 19 clustered in a single phylogenetic clade and were all isolated from the S4 site).Likewise, site-specific phylogenetic clustering was observed in ASQP_29, ASQP 79, ASQP 65, ASQP 213 and ASQP 220, whic h wer e all isolated fr om the S1 site.With the one exception of ASQP 97 isolated from S3, phylogenetic clustering was also observed in ASQP 192, ASQP 177 and ASQP 67 isolated from S2 (Fig. 2 B).

Cultur able β-diversity v ariation among different sampling locations
With some exceptions of those Streptomyces common to two or more sampling locations (see the section below), Streptomyces cultur able beta div ersity ( β-div ersity) v aries moder atel y with r espect to biogeogr a phicall y distant places.Of the 15 Streptom yces isolated from S1, four taxa with the strain IDs ASQP 65, ASQP 79, ASQP 213 and ASQP 220 wer e onl y found fr om S1 and not fr om any other sampling site .Likewise , of the 11, 10 and 13 Streptomyces isolated from S2, S3 and S4, respectively, three taxa with the strain IDs ASQP 89, ASQP 177 and ASQP 192, two taxa with the strain IDs ASQP 5 and ASQP 37, and one taxon with the strain ID ASQP 77, wer e onl y found from S2, S3 and S4, r espectiv el y ( Supplementary Table 3 and Fig. 2 A).
T he abo v e anal ysis of phylogenetic clustering pattern, βdiv ersity and intr aspecies commonness numbers may c hange, ho w e v er, because of c hanges in species delineation and proper identification of isolates not assigned with species-le v el identification.

Bioacti v e Streptomyces displa y ed optimized growth in different media for metabolite production
The quantification of concentrated ethyl acetate extracts of 12 bioactive isolates sho w ed different bacterial growths in four production media, as sho wn b y the dry cell mass (Fig. 3 A).Among the four selected media, isolates with the strain IDs ASQP 19, ASQP 41, ASQP 79 and ASQP 123a sho w ed optim um gr owth in ISP2; ASQP_29, ASQP 77, ASQP_78 and ASQP_80 in SC; ASQP 37 and ASQP 57 in KMM and the growth optimum for ASQP_92 and ASQP_98 w as sho wn in CYPS (Fig. 3 B).Dry cell mass production was highest in ASQP_80 and lo w est in ASQP_92.Although the dry cell mass content for each isolate cultured in 250 ml of all four production media seems not so different, this difference in the fermentation perspective can be huge where hundreds and thousands of liters of production media are emplo y ed for large-scale industrial cultur e cultiv ation and bioactiv e antimicr obial secr etion.

In vitro antimicrobial activity of potential Str e ptomyces
Next, we e v aluated the antimicr obial potential of all Streptomyces spp.using well diffusion assays and then determined MICs (in μg/ml) of 12 bioactiv e Streptom yces species with 10 repetitions of 2-fold serial dilution concentration ranges set between 0.49 and 500 μg ml −1 .All isolates sho w ed broad spectrum antimicrobial activity against both gram-positive and gram-negative pathogens, with MIC values ranging from 500 μg ml −1 to as low as 0.98 μg ml −1 (Fig. 4 A).Two Streptomyces strains, S. sp .ASQP_29 and S. sp .ASQP_80, displayed strong antimicrobial activity and were maximall y anta gonistic a gainst the gr am-positiv e pathogens Staphylococcus aureus and Micrococcus luteus.The lowest MICs reported in these two strains were 3.9 μg ml −1 for S. sp .ASQP_29 and 0.98 μg ml −1 for S. sp .ASQP_80.The MIC values of the rest of the isolates wer e compar ativ el y higher than the abov e two str ains; ho w e v er, all the bioactive isolates were comparatively more antagonistic a gainst gr am-positiv e pathogens than gr am-negativ e pathogens .

Antibiofilm activity of bioactive Str e ptomyces
We subsequently performed antibiofilm assay and evaluated the ability of 12 bioactive Streptomyces isolates to prevent or inhibit biofilm formation against a r epr esentativ e gr am-positiv e ( Staphylococcus aureus ) and a gr am-negativ e ( Pseudomonas aeruginosa ) pathogen.The 12 bioactive isolates varied in respect of the pr e v ention of biofilm formation, ho w e v er all displayed positiv e r esults suggest biofilm inhibition (Fig. 4 B).The top six isolates str ongl y anta gonistic a gainst the biofilm formation by Pseu-domonas aeruginosa were ASQP_29, ASQP 57, ASQP 77, ASQP_80, ASQP_92 and ASQP_98, and also the six isolates that displayed str ong activity a gainst the biofilm formation by Staphylococcus aureus were ASQP_29, ASQP 57, ASQP 77, ASQP_78, ASQP_80 and ASQP_98 with percentage inhibition values ≥50%; ho w ever, the antibiofilm activity of the remaining six extracts against both pathogens was compar ativ el y < 50%.Ki Gali (S4), four isolates, ASQP 19, ASQP_98, ASQP 57 and ASQP 123a, ar e cluster ed into a single clade.Further, both the bioactive isolates ASQP_29 and ASQP 79 from Sinthan top (S1) are also grouped into a single separate clade (Fig. 5 ).

Proteomic phenotype of bioacti v e Streptomyces is predicti v e of both clustering and strain-specific variability in expression of some antibiotic response regulators and stress-responsi v e proteins
Out of 12 bioactive isolates, we selected only six isolates based on the higher bioactivity (MIC and biofilm assays) (ASQP_29, ASQP_77 and ASQP_80), possible novel phylogenetic nature of a bioactive strain (ASQP_92, ASQP_98) and the absence or limited genome submissions in GenBank databases of a bioactive strain or its nearest possible phylogenetic ancestor (ASQP_78).Untargeted Label fr ee quantitativ e pr oteomics was performed on these six selected bioactiv e Streptom yces isolates with the strain IDs ASQP_29, ASQP 77, ASQP_78, ASQP_80, ASQP_92 and ASQP_98.A total of 470 proteins were isolated from these bioactive isolates, run in triplicate.
Using non-parametric one-way ANOVA with an adjusted P value cut-off of 0.05 and post-hoc tests, 122 proteins were identified as significant.Multivariate analytical approaches were applied to these significant proteins, yielding the following results.Unsupervised principal component anal ysis (PCA) gener ated 2D and 3D scores plots, showing a total segregation of ASQP_29 from the rest of the isolates .T he fiv e r emaining isolates displayed mostl y ov erlapping distribution of proteomic datapoints with some variability between the samples .T he ellipse r epr esenting the confidence interval of 95% was largest in ASQP_92, indicating that this Streptom yces gener ated mor e v ariability in the proteome (Fig. 6 A and Supplementary Fig. S3a ).
Partial least square discriminant analysis (PLS-DA) was used to model differences more specifically between the isolates and to select specific features in the data (Fig. 6 B and Supplementary Fig. S3b ).2D scores plots for PLS-DA sho w ed more clear representation where ASQP_29 was clustered separately and distantly fr om other Streptom yces isolates.Gr eater v ariability was seen in ASQP_92 follo w ed b y ASQP_29, while compar ativ el y less v ariability was seen in ASQP_80 and ASQP_98 (Fig. 6 B).Hier arc hical clustering analysis using a heatmap of the top 60 proteins ( P < 0.05) Color gradient from green to red denotes lo w er to higher antimicrobial inhibition.Ciprofloxacin taken as a positive control displayed MIC v alues a gainst differ ent pathogens as Esc heric hia coli : 0.08 μg ml −1 , Pseudomonas aeruginosa : 0.015 μg ml −1 , Klebsiella pneumonia : 0.02 μg ml −1 , Staphylococcus aureus : 0.6 μg ml −1 , Enterococcus faecalis : 0.7 μg ml −1 and Micrococcus luteus : 0.075 μg ml −1 .(B) In vitro biofilm inhibition (as percentage units) by antagonistic Streptomyces isolates against a gram-positive ( Staphylococcus aureus ) and a gram-negative ( Pseudomonas aeruginosa ) pathogen.Color gradient from green to red denotes lo w er to higher percentage biofilm inhibition.As per established criterion, percentage values ≥50% suggest good biofilm inhibition.sho w ed clear segregation of ASQP_29 from ASQP_80 (Fig. 6C ).Most of the proteins upregulated in ASQP_29 were downregulated in ASQP_80, and proteins downregulated in ASQP_29 were upregulated in ASQP_80.The expr ession pr ofile of ASQP_77 was pr obabl y differ ent fr om the other samples, as almost all the proteins under study were downregulated.The expression of ASQP_78, ASQP_92 and ASQP_98 were somewhat similar, with little differential expression profiling of few proteins .Furthermore , ASQP_78, ASQP_92 and ASQP_98 wer e mor e similar to ASQP_77 than to ASQP_29 and ASQP_80.A Variable Importance in Projection (VIP) plot was drawn to project important features identified among differ entiall y expr essed pr oteins (DEPs) by PLS-DA (Fig. 6 D).The gr a ph shows the r elativ e contribution of proteins to the vari-ance between different Streptomyces isolates.Proteins with high VIP scor es, suc h as atpE, SCO1213 and STRIP9103_0627, indicated a greater contribution to the group separation.Many of these featur es involv ed in gr oup separ ation between the selected isolates contribute to Streptom yces antibiotic r esponse and stress tolerance.
We emplo y ed a systems biology a ppr oac h to anal yze the pr oteomes of two highly bioactive Streptomyces isolates with the strain IDs ASQP_29 (MIC 3.9 μg ml -1 ) and ASQP_80 (MIC 0.98 μg ml -1 ) (Fig. 7 ).A compar ativ e expr ession anal ysis of the two isolates r evealed 165 DEPs, with 125 upregulated and 40 downregulated in ASQP_29 compared with ASQP_80.PLS-DA analysis using a 2D plot sho w ed a clear separation between the two samples, with more Figure 5. Phylogenetic affiliations using 16S rDNA nucleotide sequences of 12 bioactive culturable Streptomyces .The evolutionary history was deduced using the Neighbor-Joining method and the percentage bootstr a p consensus tree using 1000 replicates was generated to r epr esent the evolutionary history of the analyzed taxa.The Maximum Composite Likelihood method was used to compute evolutionary distances and the final evolutionary analysis was conducted in MEGA 11.The tree was visualized, manipulated and annotated in The Inter activ e Tr ee Of Life (iTOL).Eac h taxon is shown with or ganism nomenclatur e, str ain ID, number of base pairs amplified and the sampling site from which the taxon is isolated.Different font colors r epr esent taxa isolated from different sampling sites: black for S1 (Sinthan top), red for S2 (Thajiwas glacier), green from S3 (Apharwat peak) and blue from S4 (Peer Ki Gali).
pr oteome v ariability in ASQP_29 (Fig. 7 A).Heatmap clustering analysis of the expression profiles of the top 65 proteins sho w ed contr asting expr ession le v els betw een the tw o bioactive samples (Fig. 7 B).Pr oteins fr om statusactiv e5 to statusactiv e15 wer e found to have increased expression in ASQP_80 but decreased expression in ASQP_29, while proteins listed after statusactive15 to the end (r pIE) wer e upr egulated in ASQP_29 and downregulated in ASQP_80.This was consistent with the PCA and PLS-DA plots of all six samples, where ASQP_29 was clustered separately from ASQP_80 (Fig. 6 C and Fig. 7 B).Furthermor e, featur e identification using a VIP plot of the top 15 pr oteins, suc h as DnaK-1 (c ha per one), gr oS (c ha per onin), infB (Tr anslation initiation factor IF-2) and rpsJ (30S ribosomal pr otein S10), r e v ealed significant shifts in their expression potential and largely contributed to the group separ ation, with VIP featur es showing differ ential concentr ation gradients between the two samples (Fig. 7 C).Volcano plot analysis ( P < 0.05, FC > 1.5) sho w ed that top significant pr oteins, suc h as DnaK-1 and rpsJ, among others, w ere do wnregulated, while proteins like groS and infB were upregulated in ASQP_29 compared with ASQP_80 (Fig. 7 D).Finally, using the UniProt search engine, the gene ontology annotation terms of these proteins supported their involvement in biological processes related to response to cold and c ha per one-mediated pr otein folding.

Discussion
Our study on Streptomyces growth characteristics from highaltitude NWH sho w ed that these microbes w er e maximall y isolated using four different media types , that is , ISP2 (M3), SCA (Starch Casein Agar) (M6), CYPS (M7) and KMM (M8).Looking into the composition of these media types, soluble starch and dextrose can best serve as the primary source of glucose; yeast extr act, malt extr act and salt supplements in lo w er concentrations can serve as the source of amino acids , vitamins , minerals and other nutrients that support the microbial growth of diverse Streptom yces fr om these high-altitude r egions .T hus , the optimum media composition of yeast and malt extracts in specific proportion with other ingredients such as peptones, limited salts and sug-ars (soluble starch and dextrose) can serve as the suitable culture medium for isolation of Streptomyces from high-altitude NWH regions.Ho w e v er, the specific concentr ations of eac h component in the media, as well as any additional supplements or variations, might be adjusted based on the particular strains of Streptomyces or the environmental conditions of the high-altitude regions from which they are isolated.Experimental optimization and fine tuning may be necessary to ac hie v e the best growth conditions for these bacteria.
Our Streptomyces species diversity assessment and application of inhibitory bioassays sho w ed that the NWH microbiome is a promising source of bioactive Streptomyces and has the potential to isolate novel cultures.When compared, although the culturable biodiversity of these Streptomyces is less as expected, the potential for inhibition and isolation of novel taxa by these highaltitude ranges signifies the importance of exploration to yield further species diversity and novelty and tap the untapped biochemical potential to produce novel biochemical scaffolds.Low Streptom yces cultur able species div ersity fr om these Himalayan r anges may be attributed to the low temper atur es, oligotr ophy, dispersal limitation and glaciated soils of these sampling sites .T he microclimate ice cold temper atur es and historical patterns of glaciations in Himalaya and adjacent mountains might have limited the time for Streptomyces speciation, decreased the phylogenetic diversity and increased the phylogenetic clustering of this genus (Hewitt 1996 ).Phylogenetic clustering of NWH and species commonness among different sites may be attributed to their equitable ecological and climate conditions, with almost all the sites bearing a similar climate and v egetation patterns.Further, ther e is negativ e corr elation between Streptom yces phylogenetic div ersity and altitude/latitude (Andam et al. 2016 ).Also, varied Streptom yces cultur able β-div ersity and bioc hemical potential was observ ed among differ ent sampling sites and may be because of the combination of dispersal limitation shaping Streptomyces diversity, bioacti vity and selecti v e envir onmental pr essur e particular to specific sampling sites (Eisenlord et al. 2012 ).The habitat filtering better known to microbiologists as the Baas Becking hypothesis-"Everything is everywhere, but, the environment selects"-applies well to Streptom yces fr om NWH habitats (van der Gast 2015 ).The high altitudes, cold temper atur es and nutrient constr aints limit the diversity and increase the selective and competitive pressures for the production of biochemically active scaffolds and nov el bioactiv es.Further 16S rRNA lac ks taxonomic r esolution below the genus le v el and is an incomplete phylogenetic marker for pr oper Streptom yces identification.Use of a combination of phylogenetic markers (subunit B of DNA gyrase-gyrB, heat shock protein-hsp70 or DnaK, β subunit of bacterial RNA polymeraser poB, beta c hain of tryptophan synthase-trpB and ATP-dependent DNA helicase-r ecG) along with univ ersal 16S rRNA gene, or e v en mor e adv anced although costl y in silico-based phylogenomic a ppr oac hes (Av er a ge Nucleotide Identity, DN A-DN A Hybridization), will help in proper species identification and pattern distribution of Streptomyces from NWH.Based on the dry cell mass quantification, media optimization of potential Streptomyces spp.displayed their v arying gr owths and highlights the use of specific media for lar ge-scale cultur e cultiv ation in the drug pr oduction pr ocess.
The proteomic analysis of two highly bioactive isolates of Streptom yces fr om high-altitude NWH, namel y, ASQP_29 and ASQP_80, has shed light on their potential as a rich source of bioactive natur al pr oducts .T he use of a systems biology a ppr oac h in the pr oteomic anal ysis r e v ealed 165 DEPs betw een the tw o isolates, with more proteome variability observed in ASQP_29.These DEPs  ar e involv ed in r esponse to cold and c ha per one-mediated pr otein folding, highlighting the unique adaptations of these Streptom yces to extr eme envir onmental conditions.Furthermor e, feature identification using a VIP plot of the top 15 proteins revealed significant shifts in their expression potential and lar gel y contributed to the group separation with VIP features showing differential concentr ation gr adients betw een the tw o samples .T hese results suggest that the two isolates have different protein expr ession pr ofiles that may contribute to their r espectiv e bioactivity.The identification of specific proteins that are differentially expressed between the two isolates provides a valuable insight into the biological processes involved in their bioactivity.Further studies can focus on investigating the functional roles of these proteins and their potential applications in drug discovery and de v elopment.
In gener al, NWH r eflects tr emendous potential for bioactiv e exploration of Streptomyces .In our study w e sho w ed the div ersity anal ysis, bioactivity and distribution pattern of culturable Streptom yces acr oss differ ent NWH r egions.We also studied the proteomic expression profile of selecti ve bioacti ve Streptomyces and the significance of some proteins in stress response and antibiotic regulation.The results encourage that further exploration of the NWH region with a larger sample size ma y pro vide more insights into Streptomyces diversification and proper pattern distribution.The exploration of such habitats may pr ov e to be a v aluable str ategy in the search of more Streptomyces species for new natural molecules with antimicrobial properties.

Figure 1 .
Figure 1.(A) Sampling map drawn using ArcGIS and depicting the latitudinal and longitudinal positioning of different experimental sites.(B) Site-specific details of culturable isolates of majorly Streptomyces and a few non-Streptomyces from four different sampling sites (S1, S2, S3 and S4).One cultur e eac h fr om Nar ana g (L1) and Daksun (L2) alr eady isolated by our r esearc h gr oup wer e also taken for 16S-based taxonomic identification.

Figure 2 .
Figure 2. (A) Phylogenetic affiliations using 16S rDNA nucleotide sequences of culturable 56 isolates .T he evolutionary history was deduced using the Neighbor-Joining method and the percentage bootstrap consensus tree using 1000 replicates was generated to represent the evolutionary history of the analyzed taxa.The Maximum Composite Likelihood method was used to compute evolutionary distances and the final evolutionary analysis was conducted in MEGA 11.The tree was visualized, manipulated and annotated in The Inter activ e Tr ee Of Life (iTOL).Eac h taxon is shown with or ganism nomenclatur e, str ain ID, number of base pairs amplified and the sampling site from which the taxon is isolated.Bioactive isolates are marked with an asterisk ( * ) and non-Streptomyces isolates are shown with a gray background color and are marked with #.Different font colors represent taxa isolated fr om differ ent sampling sites: blac k for S1 (Sinthan top), r ed for S2 (Thajiwas glacier), gr een fr om S3 (Apharwat peak), blue fr om S4 (Peer Ki Gali) and gray for both L1 (Naranag) and L2 (Daksun).The capital "C" letter represents common species from different sampling regions.(B) Site-specific phylogenetic clustering among different sampling locations.
Site-specific phylogenetic clustering was also noticed by e v aluating the phylogenetic affiliations of only 12 bioactive Streptomyces species.Of the se v en bioactiv e Streptom yces collected fr om Peer F igure 3. (A) Gro wth optima calculated as dry cell mass in 250 ml of br oth cultur e of 12 bioactiv e Streptom yces gr own in four differ ent media: starc h casein medium (SC), Kenknight & Munaier's Medium (KMM), Yeast Malt medium (ISP2) and Casein Yeast Peptone Starch medium (CYPS).The error bars r epr esent the standard err or of mean (SEM).(B) Optimized gr owth of Streptom yces isolates a gainst a particular medium.

Figure 4 .
Figure 4. Antimicrobial inhibition and antibiofilm activity of anta gonistic Streptom yces a gainst a panel of pathogens.(A) In vitr o antimicr obial potential measured as minimum inhibitory concentration (MIC) in μg/ml of 12 bioactive isolates against three gram-positive and three gram-negative test pathogens.Color gradient from green to red denotes lo w er to higher antimicrobial inhibition.Ciprofloxacin taken as a positive control displayed MIC v alues a gainst differ ent pathogens as Esc heric hia coli : 0.08 μg ml −1 , Pseudomonas aeruginosa : 0.015 μg ml −1 , Klebsiella pneumonia : 0.02 μg ml −1 , Staphylococcus aureus : 0.6 μg ml −1 , Enterococcus faecalis : 0.7 μg ml −1 and Micrococcus luteus : 0.075 μg ml −1 .(B) In vitro biofilm inhibition (as percentage units) by antagonistic Streptomyces isolates against a gram-positive ( Staphylococcus aureus ) and a gram-negative ( Pseudomonas aeruginosa ) pathogen.Color gradient from green to red denotes lo w er to higher percentage biofilm inhibition.As per established criterion, percentage values ≥50% suggest good biofilm inhibition.

Figure 6 .
Figure 6.Proteomic phenotype of six bioactive Streptomyces (ASQP_29, ASQP_77, ASQP_78, ASQP_80, ASQP_92 and ASQP_98).(A) Scores plot for 2D Principal Component Analysis displaying segregation and overlapping variability among six bioactive Streptomyces spp.The plot shows 32.4% of total v ariance.Variance pr oportion for PC1 along the x-axis is 17.6% and for PC2 along the y-axis is 14.8%.(B) 2D scor es plot for partial least squar e discriminant analysis (PLS-DA) using MetaboAnalyst 5.0, displaying clear segregation of six bioactive Streptomyces .A five-component model was performed by PLS-DA.The plot shows six different samples in different colors.Ovals display 95% confidence intervals for all six samples .T he diagram shows a scatterplot for two components of the greatest variation.Similar observations will fall close to each other and display a cluster-like pattern.Component 1 (x-axis) contains 13.8 of total variation and Component 2 contains 8.3%.(C) Hierarchical clustering (heatmap) analysis was performed for six different Streptomyces , comparing 60 Benjamini-Hochberg FDR correction t-test P value ( < 0.05) passing proteins.For clustering, MetaboAnalyst 5.0 was used.The horizontal axis r epr esents all the samples analyzed in the study and the vertical axis is UniProt accessions for 60 proteins.On top of the heatmap are six different Streptomyces samples, each represented by a different color.A dendrogram for different Streptomyces , each in triplicate, is shown on top of the heatmap and the protein dendrogram is on the left-hand side of the heatmap.Color gradient from dark blue to dark red denotes lo w er to higher expression.(D) Variable Importance in Projection (VIP) plot displays the top 15 most important proteins identified by PLS-DA.Colored boxes on the right indicate the r elativ e concentr ation (fr om low to high) of corr esponding pr oteins a gainst eac h gr oup under study.

Figure 7 .
Figure 7. Proteomic phenotype of two highly bioactive Streptomyces ( Streptomyces sp .ASQP_29 and Streptomyces sp .ASQP_80).(A) 2D scores plot for partial least square discriminant analysis (PLS-DA) using MetaboAnalyst 5.0.A five-component model was performed by PLS-DA.The plot shows two different samples in different colors.Ovals display 95% confidence intervals for both the samples .T he diagram shows a scatterplot for two components of the greatest variation.Similar observations will fall close to each other and display a cluster-like pattern.Component 1 (x-axis) contains 43.6% of total variation and Component 2 contains 18.8%; 62.4% of total variance is observed by the first two components.(B) Hier arc hical clustering heatmap of 65 Streptomyces proteins; hierarchical clustering was performed for two different Streptomyces , comparing 65 Benjamini-Hoc hber g FDR corr ection t-test P v alue ( < 0.05) passing proteins.For clustering, MetaboAnalyst 5.0 was used.The horizontal axis r epr esents two samples analyzed in the study and the vertical axis is UniProt accessions for 65 proteins.On top of the heatmap are two different Streptomyces samples, eac h r epr esented in a differ ent color.A dendr ogr am for two differ ent Streptom yces , eac h in triplicate, is shown on top of the heatma p and the pr otein dendr ogr am is on the left-hand side of the heatma p. Color gr adient fr om dark gr een to dark r ed denotes lo w er to higher expression.(C) Variable Importance in Projection (VIP) plot displays the top 15 most important proteins identified by PLS-DA.Colored boxes on the right indicate the r elativ e concentr ation (fr om low to high) of corr esponding pr oteins a gainst eac h gr oup under study.(D) In this Volcano plot, the x-axis is the Log2 of linear fold change and the y-axis is the negative Log10 of the Benjamini-Hochberg-corrected t-test P value .T he horizontal black dashed line designates a cut-off of 0.05 for the FDR-corrected P value .T he plot displays the proteins that fall to the left and right of vertical black dashed lines and above the horizontal black dashed line ( P < 0.05) as significant (proteins in colored dots), upregulated to w ar ds the right and downregulated to w ar ds the left in ASQP_29 versus ASQP_80.The top significant proteins are label + ed as shown in the plot.

Table 2 .
Composition of different media used for the isolation and growth of Actinobacteria cultures