Changes in nutrient availability substantially alter bacteria and extracellular enzymatic activities in Antarctic soils

Abstract In polar regions, global warming has accelerated the melting of glacial and buried ice, resulting in meltwater run-off and the mobilization of surface nutrients. Yet, the short-term effects of altered nutrient regimes on the diversity and function of soil microbiota in polyextreme environments such as Antarctica, remains poorly understood. We studied these effects by constructing soil microcosms simulating augmented carbon, nitrogen, and moisture. Addition of nitrogen significantly decreased the diversity of Antarctic soil microbial assemblages, compared with other treatments. Other treatments led to a shift in the relative abundances of these microbial assemblages although the distributional patterns were random. Only nitrogen treatment appeared to lead to distinct community structural patterns, with increases in abundance of Proteobacteria (Gammaproteobateria) and a decrease in Verrucomicrobiota (Chlamydiae and Verrucomicrobiae).The effects of extracellular enzyme activities and soil parameters on changes in microbial taxa were also significant following nitrogen addition. Structural equation modeling revealed that nutrient source and extracellular enzyme activities were positive predictors of microbial diversity. Our study highlights the effect of nitrogen addition on Antarctic soil microorganisms, supporting evidence of microbial resilience to nutrient increases. In contrast with studies suggesting that these communities may be resistant to change, Antarctic soil microbiota responded rapidly to augmented nutrient regimes.


Introduction
Soil micr oor ganisms pr ovide essential ecosystem services and are pivotal for the recycling of elemental carbon and nitrogen (Bardgett and Van Der Putten 2014, Bahram et al. 2018, Delgado-Baquerizo et al. 2018, Cavicchioli et al. 2019 ).Se v er al studies have pr ovided str ong e vidence r egarding the global, r egional, and local patterns of soil micr oor ganisms (Serna-Chav ez et al. 2013, Delgado-Baquerizo et al. 2021, Shaffer et al. 2022 ).Ho w e v er, for se v er al r easons including the logistics associated with studies in polar r egions, compar ativ el y less is known r egarding Antarctic micr obial comm unities (Makhalan yane et al. 2016 ).A r ecent global soil survey has provided strong evidence that colder high latitudinal are hotspots for soil nature conservation (Guerra et al. 2022 ).Yet, compared to more temperate soils, the effects of global warming induced climate change on the diversity and functional attributes of belowground soil microbial communities in the colder high latitudes remains largely unexplored.
Earlier studies report that nutrient rich soils harbor high micr obial div ersity (MD).These studies suggest that microbial communities play major roles in energy and nutrient flow (Miransari 2013 , Tecon andOr 2017 ).There is some evidence that nutrient limitation pr ofoundl y impacts micr obial food webs and soil formation (Krauze et al. 2021 ), biogeochemical cycling (Lysak et al. 2018 ), bior emediation (v an Dorst et al. 2021 ), and ecological succession (Krauze et al. 2021 ).Restrictions on the availability of k e y soil n utrients, including organic carbon, may limit bacterial growth and directly affect microbial biomass and related enzymatic activities (Su et al. 2022 ).Similarl y, nitr ogen and water imbalances could also affect the abundance and r espir ation r ates of soil micr oor ganisms (Li et al. 2011 ).Pr e vious studies show the importance of nitrogen and N-cycle on Antarctic soil bacterial comm unity structur e and r elated functions (Yer geau and Ko w alchuk 2008, Berthrong et al. 2014, Lav er gne et al. 2021 ).Reports from other polar habitats such as the Arctic have also seen shifts in diversity and functional attributes in permafrost soils as result of carbon fluctuations caused due to temper atur e c hanges (Monteux et al. 2018, Ricketts et al. 2020, Liu et al. 2021b ).Ne v ertheless, the broader impacts on soil micr oor ganisms r emain unclear especially in soils from understudied cold en vironments .Given the fact that soil micr oor ganisms in these environments underpin nutrient recycling, it is crucial to investigate the extent to which envir onmental stoc hasticity (e.g.nutrient availability fluctuations) impacts ecosystem services (Malard and Pearce 2018, Prather et al. 2019, Schmidt et al. 2022 ).
Perv asiv e melting of ice sheet in Antarctica due to climate c hange intr oduced b y global w arming has tr emendousl y impacted the surface hydrology of Antarctica resulting in percolation and ablation zones .T he increase in meltwater due to warming climate leads to runoff and mobilization of surface nutrients causing stoichiometric imbalances with impacts on microbialderived ecosystem services (Bell et al. 2018, Soong et al. 2020 ).These imbalances may be especially significant in oligotrophic desert ecosystems, such as the Antarctic McMurdo Dry Valley (MDVs) soils where microbes dominate and prime biogeochemical cycling (Niederberger et al. 2019, Zoumplis et al. 2023 ).De v eloping an understanding of microbial responses to climate change has been a major focus of r esearc h ov er the past decade (Glassman et al. 2018, Malik et al. 2020, Wahid et al. 2020, Bardgett and Caruso 2020a ).These studies suggest three types of responses to c hange including micr obial r esistance (r emain in original state), r esilience (c hange due to favor able ada ptation), and functional r edundancy (changes with unaltered ecosystem process rates) (Allison andMartiny 2008 , Shade et al. 2011 ).These categories provide a v alid fr ame work for testing the impact of global c hange pr ocesses on nutrient cycling.
Evidence suggests that climate c hange-r elated c hanges in soil microbial activities may induce positive feedbacks (Frey et al. 2013, Nie et al. 2013 ), exacerbating the effects of change (Bardgett et al. 2008, Shakoor et al. 2020, Bardgett and Caruso 2020b, Fanin et al. 2022 ).For example, the effects of changes in soil micr obial comm unities due to incr eases in nitr ogen and phosphorous highlights significant changes in biogeochemical recycling (Rinnan et al. 2008, Campbell et al. 2010, Ko y ama et al. 2014, Ma et al. 2021 ).In ad dition to this, a recent stud y by Adamczyk et al. ( 2020 ) has demonstrated the impact of carbon addition on the abundances of Arctic soil microbial communities, using a combination of experimental manipulations and field studies.Ho w e v er, we lack broader insights regarding the effects of moisture and incr eased nitr ogen and carbon inputs on the structure and function of microbial communities in oligotrophic Antarctic soils.
Here, we used soils from the MDVs to investigate the effects of nutrient supplementation.We predicted that the increased carbon, nitrogen, and soil moisture availability would substantially alter bacterial and archaeal communities, with direct impacts on the diversity and function.Using four treatments sets and one contr ol, we sim ulated the effects of alter ed nutrient r egimes and investigated the effects of nutrient augmentation on microbial comm unities ov er a period of 45 days via constructing soil microcosms in the laboratory.The treatments include supplementation with glucose (carbon source), ammonium chloride (nitrogen source), glycine (carbon and nitrogen source), and aerosolized filter sterilized water (moisture) to test the effects of higher carbon, nitrogen, and soil moisture, respectively.We used 16S rRNA gene amplicon sequencing to determine microbial community diversity dynamics in response to moisture and nutrient input.We also monitor ed extr acellular enzymatic activities to e v aluate micr obial comm unity-link ed n utrient acquisition.

Soil sampling and microcosm construction
Appr oximatel y 2 kg of bulk surface soils (0-5 cm) were collected during the austral summer of 2014, from a site near Spaulding Pond (77 • 39 S, 163 • 7 E), in the MDVs, Antarctica ( Fig. S1 ) as described pr e viousl y (Barnard et al.2020 ).The sampling site is situated in the MDV region of Eastern Antarctica, which is characterized by strong katabatic winds, minimal precipitation, and temper atur es as low as −60 • C during the austral winter (Sohm et al. 2020 ).The sampling was performed in a sterile manner from a 20 × 20 area by removing top 5 cm soil at an elevation of 68.7 cm and distance of ∼8.35 m from the shoreline of Spaulding Pond in the Taylor Valley ( Fig. S1 ).For the soil collection, all necessary permits wer e obtained fr om Antarctica Ne w Zealand and the New Zealand Ministry of Foreign Affairs and Trade .T hese samples were placed into sterile Whirl-Pak bags (Nasco, WI, USA) and stored on ice, until transportation to the laboratory at the University of Pretoria in South Africa, where they were maintained at −80 • C until further pr ocessing.The r equir ed amount of soil sample fr om se v er al r eplicates were taken from −80ºC and samples were thawed slowly at −20ºC and then at 4ºC and then sie v ed to r emov e stones using 2 mm sterile (autoclaved) metal mesh, just before constructing microcosms .T he methodology for microcosm construction was adopted from previously published w ork b y our group (De Scally et al. 2016 ).Roughly each microcosm was constructed from 30 g of soil sample by r andoml y assigning the soil to four treatment gr oups eac h supplemented with carbon, nitr ogen, carbon + nitrogen, and moisture in replicates of three .T he untreated group was assigned as control for which no replicate was taken, and the nutrient and moisture sources were added only once at the start of the experiment and sim ulations wer e maintained for a period of 45 days with sample r etrie v al for analysis at intervals of 15, 30, and 45 days ( Fig. S5 ).No sample was r etrie v ed at day 0 for treated sets except for the controls ( Table S1 ).

Experimental manipulation, nutrient amendments, and chemical analysis
A r andomized bloc k design was used, and individual soil microcosms were placed in a Memmert ICP temper atur e-contr olled incubator (Sc hwabac h, German y) at 15 • C, under daylight conditions of ≥ 300 lx with forced air circulation and 70% humidity for a 45-da y period.T he r elativ e humidity and temper atur e of the microcosms, and incubator, were monitored using iButton probes (Maxim Integrated, CA, USA), which were programmed to sample at 10-minute intervals.As opposed to untreated soils (contr ol), tr eated soils wer e supplemented with aer osolized solutions of 0.85 M glucose (carbon source), 2.85 M ammonium c hloride (NH4Cl; nitr ogen source), 2 M gl ycine (carbon and nitr ogen source), and filter-sterilized ultr a pur e water (0.15 g ml −1 w/v; moistur e source).The tr eatments wer e a pplied at the beginning of the experiment excluding controls and not at regular intervals and samples were retrieved at intervals of day 15, 30, and 45, respectiv el y ( Fig. S5 ).We included 3 replicates per treatment × 4 treatment sets (carbon, nitrogen, carbon + nitrogen, and moisture) × 3 time points (15, 30, and 45) + 4 controls totaling 40 samples ( Table S1 ).The supplements for nutrient sources (NSs) were selected based on their effectiveness in promoting growth and activity in soil micr oor ganisms.Glucose addition can lead to carbon fixation in C-poor soils influencing soil bacterial diversity and function (Zhou et al. 2021, Karhu et al. 2022, Qi et al. 2022 ).Ammonium chloride is the considered as a steady and best nitrogen source for improving soil fertility and micr obial gr owth outperforming other sources such as urea and ammonium nitrate (Wang et al. 2016, Shi et al. 2023 ).Glycine serves as a combined source of carbon and nitr ogen, widel y used in a gricultur al pr actices mitigating fertilizer r equir ement in soil and leads to impr ov ed utilization by soil micr oor ganisms (Yang et al. 2016, Xue et al. 2022 ).At each sampling point, soils were aseptically removed from the microcosms, weighed, and stored in 50-ml Falcon tubes at −20 • C until further analysis .T he Coleman method (NT, 1984 ) was used to determine pH as pr e viousl y described by Makhalan yane et al. ( 2013 ).The analysis of total organic carbon and nitrogen was performed by Bemlab laboratories (Somerset, South Africa) using a LECO Truspec ® Elemental Determinator according to the instructions of the manufacturer.

DNA extraction and 16S rRNA gene sequencing
DN A w as extracted from soil microcosms using the Po w erSoil ® DNA Isolation Kit as specified in the manufacturer's protocol (MO BIO Laboratories , C A, USA).For amplification, the V4-V5 region of the 16S rRNA gene was targeted, using primer pairs 515F (5 -GTGYCAGCMGCCGCGGRA-3 ) and 909R (5 -CCCCGYCAATTCMTTTRAG-3 ) (Tamaki et al. 2011 ).This amplification was followed by libr ary pr epar ation and sequencing at Molecular Research LP (MR DNA, Shallowater, TX, USA) using the Illumina MiSeq ® platform as detailed pr e viousl y (Ca por aso et al. 2012 ).Demultiplexed amplicon sequence raw data obtained from the sequencing provider were processed using the default parameters in the D AD A2 pipeline (version 1.22) as described by Callahan et al. ( 2016 ).Quality control and error rate determination was performed, for eac h pair ed-end sequencing run, to account for run-specific errors .T he quality control step involved trimming the low-quality sequences (Phred < 20) from the reads using filter and trim parameter resulting reads with minimum read length of 190 bp.The resultant data were merged, and chimeric sequences wer e r emov ed to obtain high quality sequences .T he amplicon sequence variants (ASVs) table was generated from these sequences using D AD A2 algorithm that employs the error model for generating ASVs, which were analogous but more improved than OTU table differing only in single nucleotide over the sequenced region (Callahan et al. 2017 ).Further, taxonomic assignments were done using a native implementation of the naive Bayesian classifier method emplo y ed in D AD A2 .A sequence similarity of 97% against the Silva reference database was selected for comparisons to the Silva 138.1 prokaryotic SSU taxonomic training dataset.Finally, the data were filtered to remove mitochondrial and chloroplast derived sequences and singletons .T hese data were then rarefied to 836 (lo w est library size) reads per sample to account for library size differences for downstream analysis .T he Illumina MiSeq sequencing data are available on the NCBI-SRA under the BioProject accession PRJNA827358.

Extracellular enzyme assays
The effects of nutrient addition on soil microbiome function were determined by measuring extracellular enzymatic activities implicated in carbon, nitrogen, and phosphorus acquisition assa ys .Assays were performed as detailed by RL Sinsabaugh, CL Lauber, MN Weintraub, B Ahmed, SD Allison, C Crenshaw, AR Contosta, D Cusac k, S Fr ey, and ME Gallo et al .(Sinsabaugh et al. 2008 ), with appr opriate nonenzymatic contr ols .T he dry mass of each soil sample was determined, after overnight incubation at 60 • C and specific enzyme activities were calculated in units of nmol h −1 g −1 dry mass and nmol h −1 g −1 soil organic matter.Briefly, 5 g of soil was suspended in 100 ml 0.1 M Tris buffer, pH 8.6 (for samples with a pH greater than 8) or 0.1 M sodium acetate buffer, pH 5.5 (for samples with pH below 8).The resultant slurry was homogenized, and 200 μl was aliquoted into flat bottom 96-well microplates (Greiner, Fric kenhausen, German y; Corning Incor por ated, Ne w York, USA).In total, 50 μl of each substrate was added per well and four replicate w ells w ere used per sample.For carbon acquisition, the activity of hydr ol ytic enzyme ß-1,4-glucosidase (BG) was mea-sured by adding substrate 4-methylumbelliferyl-ß-d -glucosidase, a gain substr ate 4-methylumbelliferyl-ß-d -xylosidase was added to detect ß-1,4-xylosidase (BX) enzyme .T he activity of oxidative enzymes phenol oxidase (PO) and phenol peroxidase (PP) w as measured b y ad ding l -3,4-dihydro xyphenylalanine ( l -DOPA) as substrate along with H 2 O 2 for pero xidase acti vity.For nitr ogen acquisition, substr ates 4-methylumbelliferyl -N -acetyl-ßglucosaminide l -leucine-7-amido-4-methylcoumarin were added to acquire the activity of ß-N -acetylglucosaminidase (NAG) and leucyl aminope ptidase (LAP), respecti vely.Further, alkaline phosphatase (AP) was used to test for phosphorus acquisition by adding 4-methylumbelliferyl-phospahte as a substrate .T he micr oplates wer e incubated for 2 h at 15 • C in the dark.Fluor escence was measured for hydrolytic enzyme activity (EA) using a Spectr amax ® P ar adigm Multi-Mode Micr oplate Reader (Molecular Devices , USA).T he hydr ol ytic enzymes PP and PO wer e e v aluated using colorimetry and absorbance was measured on a Thermo Scientific Multiskan GO spectrophotometer (ThermoScientific, USA) (Sinsabaugh et al. 2008, German et al. 2011, De Scally et al. 2016 ).

Sta tistical anal ysis
Statistical and exploratory data analyses were conducted using v arious pac ka ges in R v ersion 4.2.2 (R Cor e Team 2010 ) and R studio desktop version: 2023.03.1 + 446 (Team 2020 ).Alpha and betadiv ersity v alues wer e calculated fr om the r ar efied dataset, using pac ka ge "phyloseq " (v 1.38.0)(McMurdie and Holmes 2013 )and "microbiome R" pac ka ge (Leo and Shetty 2017 ).Significant differences were tested, using Wilcoxon rank-sum test, with P -value correction by FDR (Benjamini and Hoc hber g).P airwise Perm utational m ultiv ariate anal ysis of v ariance (PERMANOVA) was used to test for significant differences in microbial community abundance.The tests were conducted based on comparisons following nutrient addition between treatment groups, and the day of destructive sampling by using the adonis function at 999 random permutations with P -value correction (FDR) in R pac ka ge "vegan " v.2.5.7 (Oksanen 2010 ).The differential abundances of microbiota, in response to nutrient amendment, were calculated with ANCOMBC-II (Lin and Peddada 2020 ) using the "microeco" pac ka ge (v.0.19.0) in R (Liu et al. 2021a ).Significant differences in soil pH, nutrient source (NS), microbial diversity (MD), and extracellular enzymatic activities between the treatments were tested and used to generate canonical correspondence analysis (CCA) ordination plots with the envfit function using "microeco" pac ka ge (v 0.19.0).Soil parameters (pH, % of carbon, and % of nitrogen) and extracellular enzyme activities (LAP , AP , BX, BG, PO, and PP) were inspected for goodness of fit at a * P -value < .05cut off.To establish the relationship between MD and extracellular EA, significantly differing micr obial taxa wer e selected using RF (r andom for est + differ ential test) and correlation analysis (Karl Pearson) was performed for these differ entiall y abundant taxa associated with soil microcosms at genus le v el and plotted with P -value significance with FDR correction all this was achieved again using the "microeco " pac ka ge (v 0.19.0)(Liu et al. 2021a ).The latent variable modeling was used to quantitativ el y e v aluate the causal relationship between latent variables (MD, NS, and extracellular enzymatic activities) and their manifest variables via structural equation modeling using the lavaan package in R (Rosseel 2012 ).All plots were generated using the ggplot2 (Wickham et al. 2016 ) and ggpubr v.0.4.0 (Kassambara 2020 ) supported with these pac ka ges in the RStudio environment.

Nutrient augmentation affects chemical profile of soil microcosms
The pH was gener all y alkaline in most of the soil microcosm sets after nutrient and moisture amendment, with pH values as high as 13.73 (highly alkaline) in sample 4AZ and as low as 5.41 (acidic) in 1A W ( T able S1 ).The alkaline pH in the control microcosm was consistent with coastal MDV soils (Aislabie et al. 1998 ).In treated microcosms, the addition of carbon and nitr ogen substr ates led to a decrease in soil pH (i.e.> 1 unit decrease), while the addition of filter sterilized ultr a pur e water r esulted in an incr ease in pH (i.e.0.1-4 unit increase) when compared to the control ( Table S1 ).Significant differences in pH were found between treatment groups of water with carbon, carbon and nitrogen with water and nitrogen with water (ANOVA, all * * * P < .001).The soil pH may decrease due to ammonia oxidation or carbon dioxide release through microbial activity (Han et al. 2015 , Ayiti andBabalola 2022 ).These decr eases hav e also been shown to structur e bacterial div ersity and composition (Li et al. 2011 ).In gener al, high div ersity is pr e v alent in neutral soils and lo w er diversity is typically found in acidic or alkaline soils (Zhalnina et al. 2015 ).Nitr ogen le v els wer e lowest (0.03%) among untreated Antarctic soils (control), and highest (1.23%) in carbon and nitrogen supplemented soils.As expected, the le v els of nitr ogen detected wer e highest (0.51%) in nitrogen source supplemented soils, similarly carbon levels were higher in all soils supplemented with carbon source, with a maximum of 2.48% in 1CW.The carbon and nitrogen concentrations incr eased ov er time, in tr eated soils, with glucose and gl ycine treated soils showing the highest percentages of carbon (0.36%-2.48%) and nitrogen (0.21%-1.23%), respectively ( Table S1 ).These observations confirm the validity of nutrient amendments as the increased carbon and nitrogen values were directly proportional to the supplied treatments in comparison to the unamended control.

MD changes disproportiona tel y in response to carbon, nitrogen, and moisture addition
The addition of moistur e, carbon, nitr ogen, and carbon with nitr ogen containing substr ates to soils r esulted in a significant difference (Wilcox, * P < .05;* * P < .01) in the diversity of microbiota among the treatment sets (Fig. 1 A).Alpha-diversity measurements (Shannon and inverse Simpson index) were high in soils supplemented with carbon and nitrogen combined, as opposed to nitrogen addition where a substantial reduction in MD was observed ( Table S2 ).This shows that the combined addition of carbon and nitrogen favors the Antarctic Dry Valley soil microbial comm unities in contr ast to addition of nitr ogen with decr eased effects in a contr olled envir onmental setup (micr ocosm).Earlier report on the effects of glycine (carbon and nitrogen combined) addition on Antarctic soil microbial communities has shown varied responses in two different sampling sites wherein glycine addition led to increase in Gram positive bacteria indicated by high concentrations of ester-linked fatty acids (ELFAs) in one sampling site compared to the control (Dennis et al. 2013a ).Following this using ELFAs, another study carried out specifically on Antarctic Dry Valley soil microbial communities sho w ed that high nitrogen amendment reduced the total ELFA concentration.Contrastingly, the ELFA-linked Shannon and Simpson div ersity wer e r eported to decr ease onl y with high carbon and high carbon combined with low nitr ogen tr eatments compar ed to the other tr eatment sets (Dennis et al. 2013b ).While a pr e vious study befor e this carried out in Antarctic Dry Valley soil has reported no evident changes in micr obial comm unity structur e after nutrient supplementation and concluded that the microbial community is unresponsive to treatment (Hopkins et al. 2008 ).A newer study on Antarctic soil micr obial comm unities using 16S rRNA gene sequencing also reported no direct effect of nutrient application supplied in the form of tryptic soy broth on bacterial community composition or diversity (Newsham et al. 2019 ).Considering these discrepancies from the earlier observations on the response of Antarctic soil microbial communities to nutrient treatments, we presume that nutrient treatments induce considerable shifts in the microbial comm unity structur e and stability of the micr obial comm unity depends on se v er al other factors influencing the nutrient availability and its uptake in the Antarctic soil ecosystem.Ar guabl y, as opposed to these earlier studies that are carried out in the field ( in situ ) ours is a closed system ( ex situ ) wherein microorganisms are neither added nor r emov ed and maintained in a controlled manner.Hence, we predict that these reductions or improvements may be because of specific responses of some microbial taxa to nutrient input which needs further understanding.Principal coordinate analysis (PCoA), based on Bray-Curtis dissimilarity matrix, suggests a significant variation (Wilcox, * * * P < .01;* P < .05)among the micr obial comm unities following n utrient-ad dition.The microbial communities treated with moisture, carbon, and carbon along with nitrogen were broadly similar compared to the nitr ogen tr eatment (Fig. 2 A).Further a significant difference in the community composition as a response to nutrient and moisture addition was also tested using pairwise permanova that sho w ed significance (PERMANOVA, * P < .05;* * P < .01)among all tested pairs except for none (control) vs carbon and nitrogen ( Table S3 ).We did not find significant differences based on samples collected at different time points (da ys).T hese findings suggest that nutrient amendments may dispr oportionatel y affect Antarctic soil micr obial comm unities.

Addition of nutrients may favour copiotrophic microbial communities over oligotrophic
The analysis of ASV relative abundance sho w ed that ASVs belonging to bacterial taxa were the most dominant in Antarctic soil microcosms (99%) compared to archaea, which constituted minor fractions of these ASVs ( Fig. S2b ).The r esults ar e consistent with pr e vious r eports (Makhalan yane et al. 2013, Lambr ec hts et al. 2019, Barnard et al. 2020, Malc he v a et al. 2020, Ortiz et al. 2021 ) that show pol yextr eme soils harbor sur prisingl y fe w arc haea, whic h might be a reason to observe this result in our dataset apart from several others.Crenarchaeota , now Thermoproteota , wer e the onl y pr ominent arc haea r ecov er ed in our samples.Members of the phylum Thermoproteota are thermostable anaerobic Arc haea, typicall y found in the Antarctic soils (Hatzenpic hler et al. 2008, Lewis et al. 2021, Koc hetk ov a et al. 2022 ).Archaea from this acidophilic phylum require elemental sulphur (S • ) for r espir ation, although their ca pacity to use carbon and nitr ogen sources remains unclear (Florentino et al. 2016 ).These archaea ( Nitrososphaeria ) decreased significantly ( * P < .05,ANCOMBC-II) in r elativ e abundance following moisture addition ( Fig. S3 a), compar ed to contr ol.These arc haeal linea ges might be better ada pted to survive in low moisture conditions, as the soil was collected from Antarctic Dry Valley, which receives very low precipitation (Vishnivetskaya et al. 2018, Greenfield et al. 2020 ) .
Bacterial ASVs associated with Antarctic soil micr ocosms, wer e br oadl y affiliated with 20 dominant class including Gammaproteobacteria , Actinobacteria , Thermoliophilia , Bacilli , Longimicrobia , Alphaproteobacteria , Deinococci , Acidimicrobiia , Chloroflexia , Bacteroidia , and se v er al others (Fig. 1 B).Our analysis confirmed that nutrient augmentation resulted in significant changes ( * * * P < .001,ANCOMBC-II) in the r elativ e abundances of these dominant members of bacterial class (Table 1 ).Proteobacteria ( Gammaproteobacteria ) a ppear ed to r espond positiv el y to nitr ogen input compar ed to other treatments (Table 1 ) and poorly to carbon input among the carbon and control group as confirmed by the significant decrease in their r elativ e abundance pattern ( Fig. S3 b).Further, addition of moisture led to decrease in r elativ e abundance of Actinobacteriota ( Thermoliophilia and Acidimicrobiia ), Chloroflexi ( Chloroflexia , KD4-96 , and Gitt-GS-136 ), Armatimonadota ( Armatimonadia ), and Patescibacteria | ( Saccharimonadia ) in moisture vs control microcosm ( Fig. S3 a).Nitrogen addition also favoured Acidobacteriota ( Acidobacteriae ) when compared to control microcosm ( Fig. S3 c), and Firmicutes ( Bacilli and Clostridia ) but negativ el y impacted Verrucomicrobiota ( Chlamydiae and Verrucomicrobiae ) in all treatment comparisons (Table 1 ).We also found significant increases in the abundance of Acidobacteriota ( Holophagae , Blastocatellia , and Acidobacteriae ), Bacteroidota ( Kapabacteria ) and Gemmatimonadota ( S0134 terrestrial group ) after combined addition of carbon and nitrogen in comparison to control (Table 1 , Fig. S3 d).Nonmetric multidimensional scaling (NMDS) ordination analyses, based on Bray-Curtis distances of bacterial community data ( Fig. S2 a), sho w ed that the differ ent nutrient tr eatments r esulted in significant ( * * * P < .001,PERMANOVA) structur al differ ences among micr ocosm comm unities.We observ ed differ ences in the structur al patterns of bacterial communities following the sole addition of nitrogen.Compared to other treatments which resulted in random distribution patterns, nitrogen addition appears to be the only treatment leading to clear community structural patterns ( Fig. S2 ) and having contrasting effects on the relative abundances of Proteobacteria and Verrucomicrobiota (Table 1 ).Proteobacteria typically grow and r epr oduce r a pidl y in high nitr ogen envir onments, due to their eutr ophic physiology (Fier er et al. 2012, Ma et al. 2021 ), which may explain their positive responses to nitrogen addition.The significant increase in Actinobacteriota ( Thermoliophilia and Acidimicrobiia ) abundance ( Fig. S3 a) with respect to moisture addition, may be explained by their well-known capacity to r a pidl y r espond to pr ecipitation (Ko y ama et al. 2018 ).Based on these findings, it appears that nutrient augmentation leads to significant shifts in bacterial comm unity composition, whic h ar e r andom and not specific to members of bacterial class.Ho w e v er, sole effects of nitrogen treatment suggest that copiotrophic lineages might be more supported, in contrast to oligotrophic lineages, which are found ubiquitous in these Antarctic soils (Fierer et al. 2007, Ko y ama et al. 2014, Ho et al. 2017, Ma et al. 2021 ).

Antarctic soil microbial communities show positi v e and negati v e correlations with soil parameters and extracellular enzymes under different treatment regimes
The extracellular enzyme activities sho w ed differ ent v alues under different treatment regimens with no distinct pattern ( Fig. S4 ).
The LAP activity declined after addition of carbon compared to other treatments ( Fig. S4 a), which was completely opposite to EA of AP ( Fig. S4 b).The NAG activity was seen higher with moisture, nitrogen, and carbon and nitrogen input in relation to control and carbon ( Fig. S4 c).The activity of PO ( Fig. S4 f) and PP ( Fig. S4 g) were observ ed onl y high with carbon and contr ol sets, wher eas it was low in other treatment sets.Addition of nitrogen and moisture positiv el y influenced the activity of BG when compared to carbon and carbon and nitrogen together ( Fig. S4 d), while in BX all treatments had positive effect with respect to control ( Fig. S4 e).
Table 1.Differ entiall y abundant bacterial taxa in Antarctic soil microcosms with response to nutrient and moisture amendment.

Comparison Taxa P .adj Sig Group
Carbon-NONE Proteobacteria (Gammaproteobacteria) 0.000615 Further, the relationship between extracellular enzymatic activities and soil parameters on microbial community structure in the different soil microcosms, was studied.We used constrained ordination, through CCA, to assess the factors (soil parameters and extracellular enzymatic activities) and test their correlations using r elativ e abundance of micr obial comm unities in differ ent micr ocosms.Onl y those factors that sho w ed strong significant correlations ( * P < .05)were used to visualize the CCA by plotting gr a ph.Ov er all, Antarctic soil micr obial comm unity abundances wer e positiv el y influenced by se v er al factors including pH, nitr ogen availability and metabolic activity of extracellular enzymes such as LAP , AP , BX, PO, and PP .In contrast, we found that these soil comm unities wer e negativ el y impacted by carbon input and activity of extracellular enzyme BG (Fig. 2 B).Correlation coefficient analysis (Pearson), conducted at genus le v el on individual tr eatment sets, further corr obor ated the extent to whic h soil parameters and extracellular enzymatic activities influenced microbial abundances (Fig. 3 ).The corr elations wer e onl y significant for soils amended with nitrogen.Within the group amended with nitr ogen, extr acellular enzymatic activities of LAP and BX were significantl y corr elated ( * * * P < .001)with members of the genus Sphingomonas .Positi ve and negati ve correlations, observed with other micr ocosm tr eatment sets supplemented with nitr ogen, carbon, both nitrogen and carbon combined, water were not significant (Fig. 3 ).Extracellular enzymatic activities are k e y indicators of microbial function and provide some reflection on microbial contributions to nutrient cycling.While some recent studies have criticized the use of these enzymes (Mori et al. 2023 ), there is strong evidence that these enzymes provide valid data for determining the shifts in micr obial comm unities (Xiao et al. 2018, Yang et al. 2020, Gao et al. 2021, Ma et al. 2021 ).Assessing extracellular enzymatic activities may provide some indication of the efficiency of nutrient utilization in these oligotrophic environments (Robertson 1999, Rovira and Vallejo 2002, Veres et al. 2015, Huang et al. 2020 ).
The positive correlation ( * * * P < .001)found for LAP and genus Sphingomonas suggests a direct link between nitrogen use efficiency in soils supplemented with nitr ogen (Fig. 3 ).Our anal yses suggest that se v er al other factors had corr elations (both positiv e and negati ve) with n utrient and moisture supplementation in Antarctic soil microcosms.Ho w ever, these correlations w ere not significant enough to explain nutrient utilization capacity in these Antarctic soil microcosms.In summary, it appears that only bacterial genus Sphingomonas present in the Antarctic soil microbial community had the capacity to use the nutrient substrates and demonstrated significant nutrient utilization efficiency that r equir es further r esearc h for full y understanding the mec hanism and implications, while changes in the abundance pattern Sphingomonas have been shown to have a direct link with nitrogen addition in agricultural soils (Galindo et al. 2021 ).They are also known to promote plant gro wth b y their ability of fix atmospher e nitr ogen and impr ov e nitr ogen suppl y indicating their nitr ogen use efficiency (Luo et al. 2019, Zhang et al. 2023 ).The analysis revealed the effects of extracellular enzymatic activities and soil parameters to changes in microbial taxa, following nutrient addition and the results sho w ed significance impacts of nitrogen addition in these oligotrophic soils.

Structur al equa tion modeling re vealed significant relationship among NS, extracellular enzymatic activity, and MD
Structural equation modeling (SEM) was used to predict the causal relationships among microbial communities and their primary drivers in Antarctic soil microcosms, in response to nutrient addition (Mamet et al. 2019 ).SEM predicted significant relationships among NS, extracellular EA , and MD.Both EA and NS were positiv e pr edictors of MD in Antarctic soil microcosms with enzymatic activities having a stronger effect (0.38) compared to NS (0.13), Ho w e v er the effect of the NS, on EA, was r elativ el y weak ( −1.28).SEM suggests that the measured environmental parameters had a positive effect on the latent variables except for observ ed div ersity, nitr ogen source, BG, and AP, whic h had a negativ e relationship with the predictive components (Fig. 4 ).Extracellular enzymatic activities, ascribed chiefly to LAP and BG, were a positiv e pr edictor of MD in Antarctic soil microcosms .T his is consistent with pr e vious r eports whic h sho w ed positiv e r elationships between soil extracellular enzymatic activities and MD (Van Horn et al. 2014 , Geyer andBarrett 2019 ) In contrast to the effects of other extracellular enzymes including BG, BX, AP, NAG, PO, and PP, LAP activity provides insights regarding the acquisition of nitrogen in these Antarctic soils (Sinsabaugh et al. 2008, Br a gazza et al. 2019 ).NS, marked by nitrogen and carbon, positiv el y pr edicted MD.Ho w e v er, the r elationship betw een NS and EA w as less strong (Fig. 4 ).The extent to which nitrogen addition drives MD in soil remains unclear.This is because we could not corroborate the relationship between microbial communities and nitrogen addition due to the degree of variability (Williams et al. 2013, Zhao et al. 2014 ).Ho w e v er, ther e ar e some insights fr om compar able systems suggesting a str ong r elationship between nitrogen supplementation and micr obial comm unities .For instance , a recent study reported that nitrogen addition substantially altered MD, with significant increases in the abundances of soil bacteria and archaea in permafrost peatlands (Ma et al. 2021 ).A se parate stud y also used SEM analysis to demonstrate a negative influence of nutrient addition on enzymatic activities showing that LAP was dir ectl y affected by nitrogen addition (Schnecker et al. 2014 ).

Conclusion
Ther e is str ong e vidence that the melting of buried, and surface ice has led to the mobilization of soil nutrients due to run-off.
Ho w e v er, ther e effects of nutrient mobilization on microbial diversity and functionality remains unclear.Given the centrality of micr obial comm unities as driv ers of Antar ctic food w ebs, nutrient mobilization may substantially influence ecosystem services.In this study, we used an experimental manipulation to investigate the effect of changes in Antarctic soil micr oor ganisms and their potential functionality by ad ding n utrient and moisture supple- ments in a microcosm.The addition of nitrogen, carbon, both carbon and nitrogen and water, over a 45-day period, had pronounced effects on microbial diversity.The results from our studies suggest that increases in the availability of nitrogen and carbon may result in substantial changes in micr obial comm unity structur e and div ersity.The alter ed nutrient r egimes, due to the mobilization of nutrients , ma y result in significant changes in dominant bacterial taxa, including Proteobacteria ( Gammaproteobacteria ), Firmicutes ( Bacilli and Clostridia ), Actinobacteriota ( Thermoliophilia and Acidimicrobiia ), Chloroflexi ( Chloroflexia , KD4-96 , and Gitt-GS-136 ), Acidobacteriota ( Holophagae , Blastocatellia , and Acidobacteriae ), and Verrucomicrobiota ( Chlamydiae and Verrucomicrobiae ).The results from SEM analysis suggest a positive correlation between nutrient addition and extracellular enzymatic activities on the diversity of Antarctic soil micr obial comm unity.Taken together, the significant c hanges in microbial diversity and the related extracellular enzymatic activities indicate that certain taxa may r espond mor e r a pidl y to shifts in nutrient regimes in climate-sensitiv e r egion of Antarctica.This finding is in contrast with earlier studies that report Antarctic micr oor ganisms may be resistant to suc h c hanges (Hopkins et al. 2008, Sparrow et al. 2011, Dennis et al. 2013a, Newsham et al. 2019 ).Significant shifts in the composition and function of Antarctic soil microbes suggest that these communities may be r esilient, and not r esistant to ecosystem c hanges whic h is critical to understanding ecosystem stability with respect to climate driv en c hanges.Futur e studies may ho w e v er pr ovide insights r egarding the implications of this micr obial r esilience on ecosystems services, and Antarctic food webs.

Figure 1 .
Figure 1.(A) Violin plots depict the Shannon and inverse Simpson diversity of the Antarctic soil microcosms upon moisture and nutrient supplementation.The significance was tested using Wilcoxon rank-sum test with P -value correction using FDR (Benjamini and Hochberg).Significant differ ences ar e marked by asterix ( * * P < .01;* P < .05),ns stands for nonsignificant.(B) Relative abundance of top 20 bacterial class in Antarctic soil microcosms upon moisture and nutrient supplementation."Others" represent the proportion of less abundant class.

Figure 2 .
Figure 2. (A) PCoA plot (Bray-Curtis distance) showing abundance and distribution of ASVs upon nutrient and moisture amendment (Wilcox, * * * P < .01;* P < .05).(B) CCA plot based on Bray-Curtis distance showing the effect of extracellular enzymatic activity and soil parameters on Antarctic soil micr obial comm unities under differ ent tr eatment r egimes.

Figure 3 .
Figure 3. Correlation plot showing the correlation between extracellular EA, soil parameters, and microbial genera for different treatment sets in the Antarctic soil microcosm.The significance of Pearson correlation is marked by asterisks in the plot ( * * * P < .001).g_: denotes genus.