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FEMS Microbiology Ecology, 92, 2016, fiw160

doi: 10.1093/femsec/fiw160Advance Access Publication Date: 26 July 2016Research Article

RESEARCH ARTICLE

Diversity and succession of autotrophic microbialcommunity in high-elevation soils along deglaciationchronosequenceJinbo Liu1, Weidong Kong1,∗, Guoshuai Zhang2, Ajmal Khan1,Guangxia Guo1, Chunmao Zhu1, Xiaojie Wei1, Shichang Kang3,4

and Rachael M. Morgan-Kiss5

1Key Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research, Chinese Academy ofSciences, Building 3, Courtyard 16, Lincui Road, Chaoyang District, Beijing 100101, China, 2Key Laboratory ofTibetan Environmental Changes and Land Surface Processes, Institute of Tibetan Plateau Research, ChineseAcademy of Sciences, Building 3, Courtyard 16, Lincui Road, Chaoyang District, Beijing 100101, China, 3StateKey Laboratory of Cryospheric Sciences, Cold and Arid Regions Environmental and Engineering ResearchInstitute, Chinese Academy of Sciences, Lanzhou 730000, China, 4Center for Excellence in Tibetan PlateauEarth Sciences, CAS, Beijing 100101, China and 5Department of Microbiology, Miami University, Oxford,OH 45056, USA∗Corresponding author: Key Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Building3, Courtyard 16, Lincui Road, Chaoyang District, Beijing 100101, China. Tel: +8610-84097039; Fax: +8610-84097079; E-mail: [email protected] sentence summary: Autotrophic microorganisms rapidly colonized young deglaciated soils and their abundance positively correlated with totalorganic carbon and total nitrogen, suggesting that soil TOC and TN originated from autotrophs.Editor: Josef Elster

ABSTRACTGlobal warming has resulted in substantial glacier retreats in high-elevation areas, exposing deglaciated soils to harshenvironmental conditions. Autotrophic microbes are pioneering colonizers in the deglaciated soils and provide nutrients tothe extreme ecosystem devoid of vegetation. However, autotrophic communities remain less studied in deglaciated soils.We explored the diversity and succession of the cbbL gene encoding the large subunit of form I RubisCO, a key CO2-fixingenzyme, using molecular methods in deglaciated soils along a 10-year deglaciation chronosequence on the Tibetan Plateau.Our results demonstrated that the abundance of all types of form I cbbL (IA/B, IC and ID) rapidly increased in young soils(0–2.5 years old) and kept stable in old soils. Soil total organic carbon (TOC) and total nitrogen (TN) gradually increasedalong the chronosequence and both demonstrated positive correlations with the abundance of bacteria and autotrophs,indicating that soil TOC and TN originated from autotrophs. Form IA/B autotrophs, affiliated with cyanobacteria, exhibiteda substantially higher abundance than IC and ID. Cyanobacterial diversity and evenness increased in young soils (<6 yearsold) and then remained stable. Our findings suggest that cyabobacteria play an important role in accumulating TOC and TNin the deglaciated soils.

Keywords: autotrophic microbial community; deglaciated soil; Tibetan Plateau; cyanobacteria

Received: 30 October 2015; Accepted: 24 July 2016C⃝ FEMS 2016. All rights reserved. For permissions, please e-mail: [email protected]

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2 FEMS Microbiology Ecology, 2016, Vol. 92, No. 10

INTRODUCTIONGlobal warming has significantly accelerated glacier retreats inpolar and mountainous regions over the past 100 years. TibetanPlateau (TP), with an average elevation of over 4000 m above sealevel (a.s.l.) and an area of ∼2.5 × 106 km2, is the highest andthe most extensive highland in the world and is usually called‘the Third Pole’ (Qiu 2008). TP is one of the largest ice masseson Earth with more than 100 000 km2 of glaciers and accountsfor more than 80% of the total glacial mass in China (Kang et al.2010). The TP glaciers have been exhibiting rapid retreat due toclimate warming since 1980s (Su et al. 1999; Yao, Pu and Liu 2006;Yao et al. 2012).

Glacier retreat exposes new terrains to high levels of UV radi-ation and large-scale daily fluctuations in moisture and temper-ature. Deglaciated soils on the new terrains are typically domi-nated by sands with low nutrients and are particularly devoid oforganic carbon (Strauss, Ruhland and Day 2009; Eckmeier et al.2013). Deglaciated soils are rapidly colonized by functionallydiverse microbial communities (Tscherko et al. 2003; Philippotet al. 2011), and the soil biological, physical and chemical charac-teristics are highly dependent on deglaciation chronosequence(Bernasconi et al. 2011). The exposed terrains provide a natu-ral laboratory to study microbial community succession, func-tion and soil development (Schuette et al. 2010; Wu et al. 2013).Microbial succession in deglaciated soils is dynamic (Sigler,Crivii and Zeyer 2002), and is highly correlated or controlled byorganic carbon andnitrogen contents (Yoshitake et al. 2006, 2007;Zumsteg et al. 2012; Bajerski and Wagner 2013).

Autotrophic microorganisms, including photoautotrophsand chemoautotrophs, are pioneering colonizers in deglaciatedsoils (Kastovska et al. 2005). Establishment of pioneering mi-crobial communities is key determinant of deglaciated soil de-velopment and its ecosystem function and stability (Schmidtet al. 2008; Kabala and Zapart 2012), and facilitates to colo-nization of pioneering plants (Bradley, Singarayer and Anesio2014). Photosynthetic and nitrogen-fixing bacteria play impor-tant roles in the acquisition of nutrients and ecological suc-cession in high-elevation deglaciated soils (Schmidt et al. 2008,2011). Despite the importance of autotrophic microbial com-munities in deglaciated soils, their diversity, structure and suc-cession remain largely unexplored along deglaciation chronose-quence.

Autotrophic microorganisms fix atmospheric CO2 by sev-eral pathways. The Calvin–Benson–Bassham cycle (CBB) is themost widespread CO2-fixation pathway on Earth. The key en-zyme of the CBB cycle is Ribulose-1, 5-bisphosphate carboxy-lase/oxygenase (RubisCO), which catalyzes the first step in CO2

fixation into biosphere. The cbbL gene, encoding the large sub-unit of the RubisCO enzyme, is categorized into four forms (formI–IV), of which form I is the most prevalent (Tabita et al. 2008).Form I RubisCO could be further subdivided into IA, IB, IC andID. cbbL has been widely used as a phylogenetic biomarker tocharacterize the diversity and structure of autotrophic micro-bial communities in diverse habitats (Elsaied, Kimura and Na-ganuma 2007; John et al. 2007; Kong et al. 2012a,b; Yuan et al.2012).

Microbial community diversity and structure shift alongdeglaciated soil chronosequences (Bradley, Singarayer and Ane-sio 2014; Brown and Jumpponen 2014). We hypothesized that(i) autotrophic microbial communities could quickly colonizenewly deglaciated soils and their abundance and diversityshift along deglaciated soil chronosequence; (ii) the accu-mulation of organic carbon originated from autotrophic mi-

croorganisms. To test the hypothesis, we used primer setsspecifically designed to target forms IA/B, IC and ID cbbL geneto explore the abundance, diversity and succession of au-totrophic microbial communities in deglaciated soils along a10-year chronosequence on the plateau. A quantitative real-time PCR (qPCR) approach was applied to estimate the abun-dance of both total bacteria (16S rRNA gene) and autotrophicmicroorganisms. Clone library and sequencing of cbbL gene frag-ments were performed to determine the diversity and struc-ture of autotrophic communities across the deglaciated soilchronosequence.

MATERIALS AND METHODSStudy site and sample collection

The study site was in Zhadang (ZD) glacier termini (30◦28.540′ N,90◦38.362′ E) with an elevation of 5200 m a.s.l. on the southernTP (Zhou et al. 2010). Daily mean temperature markedly fluctu-ated with seasons with a range of −22.1◦C–5.8◦C in the region(Zhang et al. 2013). ZD deglaciation and its mass balance havebeen observed on a yearly basis since 2006 and the deglaciatedsoil chronosequence was 10 years old (Kang et al. 2007).

A total of 21 soil samples were collected along the deglacia-tion chronosequence in September 2012. The soils were sam-pled every 5 m starting from the ZD glacier terminus repre-senting the newly deglaciated soil to the far side representing10-year-old soils. The first sample (IT1) under the ZD glacier ter-minus was roughly estimated at zero year old and the far side(100m to the glacier terminus, IT21) was estimated to be 10 yearsold, based on the glacier retreat rate of 10 m yr−1 (Kang et al.2007). Surface soils were collected in sterile sampling bags (Lab-plas, Canada). Three surface soils were collected and mixed ateach distance, and only one replicate soil was collected for eachdistance because the local Tibetan religion rule allowsminimumsoil for sampling. Soil samples were transported to laboratory incoolers with ice bags and passed through a 2.0-mm sieve. Sub-samples for DNA extraction were stored at −80◦C and the re-maining samples were air-dried for physicochemical analysis.

Soil physicochemical analysis

Soil electrical conductivity (EC) and pH were measured by elec-trodemethodwith a soil towater ratio of 1:5 (Yan andMarschner2013). Soil total organic carbon (TOC) was measured by total or-ganic carbon analyzer (TOC-L, Shimadzu, Kyoto, Japan) and to-tal nitrogen (TN) was determined by elemental analyzer (varioMAX, Elementar, Hanau, Germany).

Soil DNA extraction and gene abundance quantification

Soil genomic DNA was extracted from 0.5 g of frozen soil us-ing a FastDNA spin kit for soil (MP Biomedicals, Solon, OH, USA)following the manufacturer’s protocol. The quantity of the DNAwas determined using a NanoDrop ND-1000 spectrophotometer(Thermo Scientific, Wilmington, DE, USA).

Gene abundance of bacterial 16S rRNA and cbbL (form IA/B, ICand ID) was determined by qPCR using primer sets from previ-ous publications (Paul, Alfreider andWawrik 2000; Corredor et al.2004; Alfreider et al. 2009; Philippot et al. 2011) (Table 1). qPCRwas conducted on a LightCycler R⃝ 480 system (Roche Diagnos-tics, Indianapolis, IN, USA) with the thermal program of 40 cy-cles of 30 s at 94◦C, 30 s at 54◦C for form IA/B cbbL gene, 30 s



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Table 1. Primer sets used in the study.

Primer name Sequence(5′-3′) Reference

16S rRNA-341F CCT ACG GGA GGC AGC AG Philippot et al. (2011)

16S RNA-534R ATT ACC GCG GCT GCT GGC A

FormIA/B-F TCI GCI TGR AAC TAY GGT CG Corredor et al. (2004)

FormIA/B-R GGC ATR TGC CAI ACR TGR AT

FormIC-F GAA CAT CAA YTC KCA GCC CTT Alfreider et al. (2009)

FormIC-R TGG TGC ATC TGV CCG GCR TG

FormID-F GAT GAT GAR AAY ATT AAC TC Paul, Alfreider and Wawrik (2000)

FormID-R ATT TGD CCA CAG TGD ATA CCA

at 52◦C for forms IC and ID cbbL genes and 53◦C for 16S rRNAgene and 30 s at 72◦C (Kong et al. 2012a,b). The total volume reac-tion was 20 µL, containing 10 µL SYBR Premix ExTaq GC (Takara,Dalian, China), 20–50 ng of genomic DNA and 0.6 µM of eachprimer. Standard curves were generated using a 10-fold dilutionseries from plasmids as previously described (Kong and Nakatsu2010). Briefly, plasmids were extracted from clones containingeach target gene fragment using PlasmidMiniprep Kit (Kangwei,Beijing, China) and quantified by spectrometry (Nanodrop-1000,Thermo Scientific,Wilmington, DE, USA). The gene copy numberwas calculated from the concentration of the extracted plasmidDNA assuming the nucleotide molecular weight of 1.096 × 10−12

g bp−1.

Clone library construction, sequencing andphylogenetic analysis of cbbL gene fragments

Clone libraries of cbbL gene fragments (form IA/B, IC and ID)wereconstructed for five soil samples: IT2 (0.5 year old), IT6 (2.5 yearsold), IT13 (6 years old), IT18 (8.5 years old) and IT21 (10 yearsold). A total of 15 DNA-based clone libraries were thus gener-ated. These samples were chosen because they represented across section of soil ages and exhibited differential levels of cbbLgene abundance along the deglaciated soil chronosequence. Thespecific PCR amplicons (623 bp for IA/B, 552 bp for IC and 557bp for ID) were amplified with triplicates for each sample us-ing Takara Master Mix (Takara), the same primer sets and 25 cy-cles of the thermal program as described above. Gel-purified PCRproducts were ligated into pGEM-T Easy vector (Promega, WI,USA), and the latter was chemically transferred into Escherichiacoli DH-5α cells. Randomly selected clones (40–50 per sample)were screened for positive inserts by PCR using the primer set ofM13F andM13R. The PCR products containing the correct insertswere then sequenced using an ABI model 3730xl DNA analyzer(Applied Biosystems, CA, USA).

Multiple sequence alignments were conducted usingCLUSTALW in MEGA6.0 (Tamura et al. 2013). Sequences with thenucleotide sequence similarity of >97%were defined as an oper-ational taxonomic unit (OTU) using the Mothur program v.1.33.3(Schloss et al. 2009). BLASTn (www.ncbi.nlm.nih.gov/BLAST/)was employed to search GenBank for the nearest related se-quences to each OTU. Phylogenetic trees were generated usingthe neighbor-joining method with the maximum compositelikelihood model in MEGA6.0 (Tamura et al. 2013). The reliabilityof phylogenetic trees was tested using bootstrap with 1000 iter-ations. Sequences generated in this study have been depositedin the National Center for Biotechnology Information GenBankdatabase under the accession numbers KJ700657–KJ700707

for form IA/B cbbL, KJ700708–KJ700766 for form IC cbbL andKJ700767–KJ700838 for form ID cbbL, respectively.

Data analysis

All figures and fitting curves were generated using SigmaPlot 10software (Systat Software, San Jose, CA, USA). For the fit curve,polynomial linear model was used for soil pH and EC, and loga-rithm model was used for gene abundance, TOC and TN. Shan-non’s diversity and evenness were calculated using the softwarePC-ORD 5.0. Pearson correlations were performed by SPSS 18(SPSS Inc., Chicago, IL, USA).

RESULTSSoil physicochemical characteristics along deglaciationchronosequence

Soil EC substantially decreased from 35 to 15 µs cm−1 within thefirst year of deglaciation and then gradually decreased along the10-year deglaciation chronosequence (Fig. 1A). The deglaciatedsoils were alkaline and their pH rapidly decreased from 9 to 6.7within the 10-year deglaciation (Fig. 1B). Soil TOC and TN weregenerally low, ranging from 0.03% to 0.11% and 0.05% to 0.016%,respectively (Fig. S1, Supporting Information). Soil TOC graduallyincreased in the first 6 years of deglaciation, and then exhibitedlarge fluctuations in old soils. The fitting curve showed that soilTOC gradually increased with the soil age (P = 0.03). In contrast,TN increased in the first 2 years of deglaciation, remained rela-tively stable to 6 years and then exhibited large fluctuations inolder soils.

Gene abundance of 16S rRNA and cbbL

The abundances of bacterial 16S rRNA and three forms ofcbbL (form IA/B, IC and ID) were quantified using qPCR acrossthe deglaciated soil chronosequence. Abundance of 16S rRNAgene increased rapidly during the first half year of deglaciation,and then gradually increased across the 10-year deglaciationchronosequence, ranging from 107 to 109 gene copies g−1 soil(Fig. 2). The cbbL abundance exhibited similar patterns as the16S rRNA gene along the chronosequence, and ranged from 104

to 108 gene copies g−1 soil. Form IA/B exhibited the highest abun-dance among the cbbL genes. The ratio of form IA/B cbbL geneto 16S rRNA gene ranged from 1.6% to 12.4%, and the highestoccurred in the new exposed soil (Fig. S2, Supporting Informa-tion). Curve fitting revealed that bacteria (indicated by 16S rRNAgene) and autotrophic microbes (forms IA/B, IC and ID cbbL)exponentially colonized deglaciated soils within a year of the



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Figure 1. Soil electrical conductivity (EC) and pH along deglaciation chronose-quence. Polynomial linear model was used for the curve fitting.

Figure 2. Abundance of 16S rRNA gene and cbbL genes in soils along deglaciationchronosequence. Logarithm model was used for the curve fitting.

deglaciation, followed by a slower increase and then graduallyincreased along the 10 years.

Correlations between the abundance of all genes and soilTOC or TNwere calculated by Pearson correlation analysis. Geneabundances of 16S rRNA and cbbL forms were positively corre-lated with both TOC and TN (Table 2). The abundances of 16SrRNA gene and all forms of cbbL gene were positively correlated

with each other, and the abundances of bacterial and cbbL geneswere negatively correlated with EC and pH.

Succession and diversity of autotrophic microbialcommunity

Clone libraries of all cbbL gene fragments (IA/B, IC and ID) wereconstructed for five deglaciated soil samples (0.5 year, 2.5 years,6 years, 8.5 years and 10 years old). cbbL gene sequences re-trieved from the five soils revealed that autotrophic microbialcommunity diversity and succession shifted along the 10-yeardeglaciation chronosequence.

Form IA/B autotrophs, which dominated the autotrophic mi-crobial communities, were only affiliated with cyanobacteria(Fig. 3), many of which shared high similarity (sequence similar-ity ranging from 91% to 97%) with those observed in Antarcticlakes (Kong et al. 2012b). The dominance of cyanobacteria wasfurther confirmed by a clone library of 0.5-year-old soil basedon 16S rRNA gene, which showed that the relative frequency ofcyanobacteria was 59.4% (Fig. S3, Supporting Information).

The form IA/B autotrophswere assigned to three orders, Nos-tocales, Oscillatoriales and Chroococcales, and the relative fre-quency of the three orders in all soils was 9.86%, 54.23% and35.92%, respectively. The relative frequency was herein definedas the number of clones assigned to a specific taxa in relation toall picked clones. Nostocales-like OTUs were not detected in rel-atively young deglaciated soils (0.5 and 2.5 years old), but abun-dantly occurred in older soils with a peak in 6-year-old soil sam-ple (28.0% in relative frequency). Oscillatoriales-like OTUs ex-hibited the highest relative frequency in 0.5-year-old soil (100%)and the least in 2.5-year-old soil (3.6%). The Chroococcales rela-tive frequency exhibited a substantially temporal variation witha peak in 2.5-year-old soil (96.4%) (Fig. S4A, Supporting Infor-mation). Pearson correlation analysis demonstrated that theChroococcales relative frequency negatively correlatedwith thatof Oscillatoriales (R = −0.954, P < 0.05).

Form IC cbbL sequences were affiliated with Proteobacteria,consisting of Actinomycetales of Actinobacteria and Proteobac-teria containing Burkholderiales, Rhodospirillales and Chroma-tiales (Fig. 4). The average relative frequency of the four ordersacross all the soils was 5.9%, 57.6%, 20.3% and 16.1%, respec-tively. All the Burkholderiales sequences were closely affiliated(similarity > 93%) with those retrieved from a supraglacial cry-oconite (Cameron, Hodson and Osborn 2012). Burkholderialesdominated all samples with the relative frequency ranging from50% to 80% across the five soil ages (Fig. S4B, Supporting Infor-mation). Rhodospirillales relative frequency gradually increasedand Chromatiales kept stable with soil age. The relative fre-quency of Rhodospirillales was negatively correlated with thatof Burkholderiales (R = −0.913, P < 0.05).

Form ID cbbL sequences were affiliated with Chroococcales,Nostocales, Oscillatoriales, Coscinodiscophyceae and Xantho-phyceae (Fig. 5). The first three orders belonged to cyanobacteria,and the last two were assigned to Stramenopiles. Oscillatorialesrarely occurred in young soils (0.5 and 2.5 years old), but dom-inated older soils (6–10 years old) (>60% in relative frequency).In contrast, Xanthophyceae dominated the young soils (0.5 and2.5 years old), and substantially decreased in older soils (6–10years old) (Fig. S4C, Supporting Information). A negative correla-tion between Oscillatoriales and Xanthophyceae in relative fre-quency was observed (R = −0.944, P < 0.05).

Autotrophic microbial diversity and evenness showed aclear temporal pattern along the deglaciated soil chronose-quence. Shannon’s diversity of form IA/B autotrophic microbial



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Table 2. Pearson correlations between gene abundance and soil physicochemical factors in deglaciated soils.

EC pH TOC TN 16S rRNA gene IA/B cbbL gene IC cbbL gene

16S rRNA gene −0.770a −0.747a 0.834a 0.709a

IA/B cbbL gene −0.606a −0.655a 0.778a 0.670a 0.937a

IC cbbL gene −0.700a −0.649a 0.895a 0.757a 0.944a 0.910a

ID cbbL gene −0.678a −0.643a 0.621a 0.461 0.928a 0.905a 0.856a

EC: electrical conductivity; TOC: total organic carbon; TN: total nitrogen.aSignificant level at 0.01 levels.

Figure 3. Neighbor-joining phylogenetic tree of form IA/B cbbL sequences (623 bp) retrieved from environmental DNA in deglaciated soils of ZD glacier. Bar, 0.02substitutions per nucleotide position. The GenBank accession number was listed in brackets after each sequence name.



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Figure 4. Neighbor-joining phylogenetic tree of form IC cbbL gene sequences (552 bp) retrieved from environmental DNA in deglaciated soils of ZD glacier. Bar, 0.02substitutions per nucleotide position. The GenBank accession number was listed in brackets after each sequence name.



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Figure 5. Neighbor-joining phylogenetic tree of form ID cbbL gene sequences (557 bp) retrieved from environmental DNA in deglaciated soils of ZD glacier. Bar, 0.05substitutions per nucleotide position. The GenBank accession number was listed in brackets after each sequence name.



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Figure 6. Shannon diversity (A) and evenness (B) of autotrophic microbial com-munities in soils along the 10-year deglaciation chronosequence.

community gradually increased with increasing soil age andthen showed a slight decrease in old soils (>6 years old) (Fig.6A). The diversity of form IC and ID followed a similar trend asIA/B along the deglaciated soil chronosequence. The maximumShannon’s diversity of all forms reached a similar level in oldersoils. Curve fitting revealed that the diversity of forms IA/B (R2 =0.99, P < 0.01) and IC (R2 = 0.97, P < 0.05) exponentially increasedalong the 10-year soil age. Similar to the Shannon’s diversity, theevenness of form IA/B autotrophic communities substantiallyincreased and then kept stable in old soils (>6 years old) (Fig.6B), while the evenness of IC and ID communities kept relativelyconstant along the 10-year soil age.

DISCUSSIONBacteria and cyanobacteria abundantly colonized the newlydeglaciated soils, increased substantially in 0.5–2.5-year-oldsoils and then remained a relatively stable trend in older soils(Fig. 2). Our finding is consistent with that 16S rRNA geneabundance increased with soil development after deglaciation(Kandeler et al. 2006). A similar trend was observed in Perudeglaciated soils, where phylotype abundance was lowest inthe youngest soils, increased in the intermediate aged soilsand plateaued in the oldest soils (20 years old) (Nemergut et al.2007). Our data showed that cyanobacteria dominated the au-totrophic microbial communities along the whole 10-year soilchronosequence. This is in the line with the increasing docu-ments that cyanobacteria widely habitat harsh environments.

They could soon colonize deglaciated soils after deglaciation ina high-elevation area (5000 m a.s.l.) (Schmidt et al. 2008). Recentstudies have shown that cyanobacteria dominated soil biocrustsacross all elevations in TP regions (Janatkova et al. 2013), andwere frequenty detected in glacier retreat barren soils in Sval-bard and southeastern Peru (Kastovska et al. 2005; Nemergutet al. 2007). Our data also demonstrated that Oscillatoriales dom-inantly occurred in the deglaciated soils, and Nostocales wasless in young soils. This is consistent with that Oscillatorialesdominated barren deglaciated soils and Nostocales dominatedsparely vegetated soils (Segawa and Takeuchi 2010). These stud-ies indicate that cyanobacteria are dominant primary colonizersin deglaciated soils (Rehakova et al. 2010), and Oscillatoriales arefrequently observed in barren soils.We have tomention that thelack of sampling replicates for the local Tibetan religion reasonmight lightly reduce the more general implications of our find-ings, although the data and findings were robust in the study.

The diversity and evenness of form IA/B and IC autotrophiccommunities dramatically increased in the first 5 years andthen kept relatively stable in the older soils (6–10 years old)(Fig. 6). This temporal trend is similar to the findings in a 20-year deglaciation chronosequence (Nemergut et al. 2007), whichshowed that bacterial diversity was lowest in youngest soils, in-creased in the intermediate aged soils and plateaued in the old-est soils. Our results suggested that autotrophic diversity andenvenness were mainly structured by deglaciated soil age.

The increase of both TOC and TN along the deglaciationchronosequence indicates that the nutrients have been accu-mulating by microbial autotrophs since the deglaciation. Thesignificant correlations of TOC and TN with abundances ofbacteria and autotrophs suggest that soil TOC and nutrientsmainly originated from soil autotrophs and bacteria, minimallyfrom ancient or external carbon sources. Studies have observedthat TOC positively correlated with soil age (Bradley, Singarayerand Anesio 2014), while our findings further extend that the TOCaccumulation results from autotroph abundance increase withsoil age, and highlight the autotrophicmicrobial role in accumu-lating nutrients and soil formation in young deglaciated soils.This is supportive of previous studies that turnover of themicro-bial community is the major source of dissolved nitrogen nutri-ents for plant uptake during the plant growing season (Schmidtet al. 2007). Among the three forms of autotrophs, cyanobacteriacarrying form IA/B cbbL gene exhibited the highest abundance,suggesting that photoautotrophs play a key role in accumulat-ing TOC and TN in the high-elevation deglaciated soils. This isin accordance with that photosynthetic bacteria play importantroles in acquiring nutrients and facilitate ecological successionin soils near some of the highest elevation receding glaciers(Schmidt et al. 2008, 2011). Our findings extend that photoau-totrophic microorganisms could play a key role in accumulatingorganic carbon and nutrients in young deglaciated soils (Stibalet al. 2008). It has to be mentioned that large fluctuations of TOCandTNoccurred in older soils. Thismight be caused by unevenlyscattered cyanobacterial mats. Findings showed that bacterialcommunities in Antarctic soils exhibited large variations at dif-ferent sampling sites, which was caused by large variations insoil physicochemical compositions (Kim et al. 2015). In our study,soil pH exhibited a large fluctuation in older soils, which is in ac-cordance with the TOC and TN, suggesting that pH variations atsampling sites might lead to the large fluctuations of TOC andTN. Therefore, enough sampling replicates may minimize thevariations in the future studies. Another shortage is that carbon-fixing capacity and activity were not experimentally determinedin the study, although there was a robust positive relationship



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between TOC and cbbL gene abundance. Stable isotope probingmethod andmRNA of cbbL gene could further elucidate the rolesof autotrophs in TOC accumulating in the future research.

The dominance of cyanobacteria and their quick coloniza-tion in deglaciated soils indicate that cyanobacteria are likelycapable of enduring extreme environmental conditions, includ-ing high UV, daily freeze-thaw cycles and low water availabil-ity and alkalinity. Cyanobacteria have been globally detected,particularly in extreme environments, including polar regions(Cameron, Hodson and Osborn 2012; Makhalanyane et al. 2015)and dry mountainous soils of Himalaya (Rehakova, Chlumskaand Dolezal 2011; Janatkova et al. 2013). The cyanobacterialcbbL gene sequences retrieved in the current study are sim-ilar to those observed in Swiss Alps deglaciated soils, Qilianglaciers (Segawa and Takeuchi 2010; Frey et al. 2013) and Antarc-tic quartz rocks (Khan et al. 2011). In addition, the cyanobac-terial sequences exhibited high similarity with those retrievedfrom Antarctic lake waters (Kong et al. 2012a,b) and Antarcticpillar mosses (Nakai et al. 2012). These findings collectively in-dicate that cyanobacteria are well adapted to extreme environ-ments in high elevations and high latitudes. Cyanobacteria cansurvive high UV exposure (Castenholz and Garcia-Pichel 2000;Sinha and Hader 2002), for they have developed photo protec-tive machinery to overcome solar UVR damage in extreme envi-ronments (Rastogi et al. 2014). Temperature and water availabil-ity are the most important environmental factors driving mi-crobial community in extreme environments (Cary et al. 2010).Cyanobacteria have evolved strategies to survive freezing anddesiccation, including lowmetabolic activity and producing spe-cific proteins andmolecules (e.g. anti-freezing proteins) (Makha-lanyane et al. 2015). Cyanobacteria were frequently dominant inalkaline environments (Uetake et al. 2010; Kovaleva et al. 2011;Rehakova, Chlumska and Dolezal 2011) for they could adjusttheir metabolism to maintain pH homeostasis under alkalineconditions (Summerfield and Sherman 2008).

Betaproteobacteria were dominant phylotypes of form ICcbbL in ZD deglaciated soils and exhibited high phylogeneticsimilaritywith those in supraglacial cryoconites (Cameron, Hod-son andOsborn 2012). These autotrophic bacteria have also beenobserved in cryoconite holes in Svalbard (Edwards et al. 2011),deglaciated soils of Tianshan No. 1 glacier (Wu et al. 2012) andon the glacier surface (Philippot et al. 2011). The occurrenceindicates that Betaproteobacteria could tolerate various envi-ronmental stressors, e.g. low temperature and low water avail-ability. Our results demonstrated that Betaproteobacteria weredominated by Burkholderiales in the high-elevation deglaciatedsoils (Fig. 4). Burkholderiales have been observed to dominatehigh-elevation airborne microbial communities and potentiallyact as atmospheric ice nuclei (Bowers et al. 2009). They couldinhabit debris-rich basal ice (Montross et al. 2014) and are themost efficient mineral-weathering bacteria (Ma et al. 2012) withhigh pH tolerance (Stopnisek et al. 2014). Our results were in linewith these findings and expand that abundant Burkholderialesin high-elevation deglaciated soils.

Soil physicochemical factors exhibited a clear temporal pat-tern along the deglaciation chronosequence. Soil EC and pHsubstantially decreased along the deglaciation chronosequence.Similar findings were observed in Antarctica glacier forefieldsoils, where pH decreased from 8.3 to 6.7 along deglaciationchronosequence (Bajerski and Wagner 2013). The higher levelsof EC and pH in the glacier terminus soils may result from snowand ice melting, for snow samples in this area were generallyalkaline with high concentrations of Ca2+ and HCO3

− (83%), andtheir pH values ranged from 7.24 to 8.39 with a mean value of

7.82 (Huang et al. 2012). It has been shown that snow and ice ECpositively correlated with alkalinity and land dust source Ca2+

ions (Xiao et al. 2001). It is reasonable to assume that snow andglacier melting waters in summer seasons induce higher valuesof pH and EC in new deglaciated soils adjacent to the glacierterminus, and they substantially decrease with increasing dis-tance to the glacier terminus. Additionally, biological weather-ing and yearly round strong winds could decrease the EC andpH of deglaciated soils with the soil-age increase.

CONCLUSIONEC and pH significantly decreased along deglaciation chronose-quence in deglaciated soils of ZD glacier on the TP. Soil TOC andTN increased in the first few years, and they positively correlatedwith bacterial and autotrophic microbial abundance, indicat-ing that barren soil nutrients were originated from autotrophicmicrobes. Bacteria and autotrophic microbes rapidly colonizeddeglaciated soils in a year of deglaciation. Cyanobacteria dom-inated the autotrophic microbial communities with a substan-tially higher abundance than their partners (IC and ID), and Os-cillatoriales were the dominant Cyanobacterial order. Most ofthe cyanobacteria had high similarity with those in Antarcticlake waters and supraglacial cryoconites. Shannon diversity andevenness of autotrophic microbial communities gradually in-creased in young soils (<5 years after glacial recession), and thenkept stable. The autotrophic microbial abundance and their di-versity were structured by deglaciated soil age, but not by an-cient nutrients.

SUPPLEMENTARY DATASupplementary data are available at FEMSEC online.

ACKNOWLEDGEMENTSWe thank Dr Cindy Nakatsu at Purdue University for thoughtfuldiscussions and suggestions.

FUNDINGThis project was financially supported by Chinese Academy ofSciences (KZZD-EW-TZ-14 and XDB15010203 to WK), NationalNatural Science Foundation of China (41471054 to WK) andChina Postdoctoral Science Foundation (2014M550849 to JL).

Conflict of interest. None declared.

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