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Bacterial Community in Soils Following Century-Long Application of Organic Or Inorganic Fertilizers Under Continuous Winter Wheat Cultivation

Bacterial Community in Soils Following Century-Long Application of Organic Or Inorganic Fertilizers Under Continuous Winter Wheat Cultivation

agronomy

Article Bacterial Community in Following Century-Long Application of Organic or Inorganic Fertilizers under Continuous Winter Wheat Cultivation

Xiufen Li 1,2 , Shiping Deng 1,*, William R. Raun 1, Yan Wang 1 and Ying Teng 3

1 Department of and Sciences, Oklahoma State University, Stillwater, OK 74078, USA; [email protected] (X.L.); [email protected] (W.R.R.); [email protected] (Y.W.) 2 Texas A&M AgriLife Research Center at Beaumont, Texas A&M University System, Beaumont, TX 77713, USA 3 Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China; [email protected] * Correspondence: [email protected]; Tel.: +1-405-744-9591

 Received: 30 July 2020; Accepted: 29 September 2020; Published: 1 October 2020 

Abstract: Fertilization is one of the most common agricultural practices to achieve high yield. Although microbes play a critical role in nutrient cycling and , knowledge of the long-term responses of the soil bacterial community to organic and inorganic fertilizers is still limited. This study was conducted to evaluate the effects of century-long organic (manure), inorganic (NPK), and no fertilization (control) treatments on soil bacterial community structure under continuous winter wheat (Triticum aestivum L.) cultivation. Fertilization treatments altered the richness, diversity and composition of the soil bacterial community. Compared with the control, manure significantly increased the operational taxonomic units (OTUs), Chao 1 and Shannon indices, and taxonomic groups, while NPK significantly decreased these parameters. Fertilization treatments did not alter the types of dominant phyla but did significantly affect their relative abundances. and were the most dominant phyla in all treatments. Manure led to enrichment of most phyla, with a diazotrophic group, , being an exception; NPK reduced most phyla, but enriched Chloroflexi; control led to promotion of Cyanobacteria. Soil pH and NO3− were two dominant parameters influencing the bacterial community structure. Soil pH positively correlated with the relative abundances of Proteobacteria and but negatively correlated with those of Acidobacteria and Chloroflexi; NO3− negatively correlated with the relative abundance of Cyanobacteria, which was 14–52 times higher in control than the fertilized soils. Cyanobacteria, especially M. paludosus and L. appalachiana, could be the key players in maintaining wheat productivity in the century-long unfertilized control.

Keywords: soil bacterial community; 16S rRNA; organic fertilizer; inorganic fertilizer; manure; NPK

1. Introduction Understanding the soil microbial community structure presents understated challenges, largely due to the complex nature of the system and the enormous abundance and diversity of the community residing within [1]. comprise over 70% of the total soil [1–3]. With as many as one billion bacterial cells and an estimated 8.3 million species in each gram of soil [4], the challenges in revealing and understanding the richness, diversity and composition of soil microbial community are thought-provoking. Nevertheless, the importance of the soil microbial community in nutrient acquisition, cycling, and availability is amply evidenced [5–8].

Agronomy 2020, 10, 1497; doi:10.3390/agronomy10101497 www.mdpi.com/journal/agronomy Agronomy 2020, 10, 1497 2 of 15

Numerous studies have demonstrated that healthy soil harbors abundant and diverse microbes, while environmental perturbation and management practices could lead to changes in microbial community structure that impact soil health and productivity [5–9]. Although long-term manure application resulted in enrichment of soil organic matter and microbial abundance [5,10–13], it did not always translate into higher crop yield than soils supplemented with inorganic fertilizers [5,14]. Long-term inorganic fertilizer addition, on the other hand, may lead to soil acidification and decreases in microbial abundance and diversity [5,11,13,15]. Based on an analysis of 22 soils from a liming experiment spanning > 60 years, Rousk et al. [10] found that both relative abundance and diversity of bacteria were positively correlated with soil pH in the range from 4.0 to 8.3. In contrast, Lauber et al. [16] found that bacterial richness peaked in the near-neutral pH range based on analysis of 132,088 16S rRNA sequences from 88 soils. The observed inconsistency could, in part, be due to gradual system-level changes that make their detection challenging [7,8,17]. Although the dominant in soil are reported to be Proteobacteria, Acidobacteria, , , and [18], their relative abundances varied considerably in pristine , grassland, winter wheat fields, and rice paddies [13,19–22]. Of soil properties, carbon and N availabilities and pH are recognized as key factors governing changes in the soil bacterial community composition. However, the relative importance of these factors in driving changes in specific bacterial groups that impact function and soil productivity is still not clear. A century-long continuous winter wheat (Triticumaestivum L.) experiment provided an opportunity for extending our understanding of the effect of long-term organic and inorganic fertilizations on the bacterial community structure. We hypothesized that different fertilization practices would differentially affect soil properties and bacterial communities over century-long wheat cultivation. Insights gained from long-term studies are crucial to support sustainable wheat production. The specific objectives were to (1) evaluate richness, diversity, and composition of the soil bacterial community in response to century-long organic, inorganic, and no fertilization regimes under continuous winter wheat cultivation; and (2) identify drivers in these soils that govern the richness, diversity and composition of the bacterial community.

2. Materials and Methods

2.1. Site Description and Soil Sampling This study was conducted in a century-long continuous winter wheat (Triticum aestivum L.) experimental field established in 1892 in central Oklahoma, USA (36◦7011” N, 97◦5019” W). The soil is a Kirkland silt loam (fine, mixed, thermic Udertic Paleustolls) with 37.5% sand, 40% silt, and 22.5% clay. Annual precipitation in this region (CD5 Central Oklahoma, OK, USA) ranged from 483 to 1448 mm (average 874 mm) and annual air temperature ranged from 14.4 to 17.7 ◦C (average 15.8 ◦C) based on data from 1895 to 2019 (https://climate.ok.gov). The field was conventionally tilled before planting every year. Comprehensive descriptions of this experimental site, soil properties, and winter wheat yield from 1892–2014 have been reported by Omara et al. [14], Girma et al. [23], and Aula et al. [24]. In this study, soil treatments were: no fertilizer added (Control), organic fertilizer applied in the form of cattle manure (Manure), and inorganic nitrogen, phosphorus, and potassium fertilizers (NPK). The manure treatment was initiated in 1899 and NPK treatment was added in 1929. Cattle manure 1 from a feedlot was applied every four years at 269 kg N ha− and inorganic NPK fertilizers were 1 1 1 applied annually in October before planting at 67 kg N ha− , 14.6 kg P ha− , and 28 kg K ha− in the forms of NH4NO3, Ca(H2PO4)2, and KCl, respectively. When the field experiment was initiated in 1892, the application of statistics to research was not yet firmly established. To compensate for the limited degrees of freedom from replication restrictions, we used an adapted sampling design to obtain three replicated samples from each fertilization treatment and repeated the study in two consecutive years (2012 and 2013). In each year, each treatment plot (30.5 6.1 m) was divided into three subplots (10.2 6.1 m) after wheat harvest. Five soil cores × × Agronomy 2020, 10, 1497 3 of 15

(0–15 cm) were collected from each subplot and composited as one soil sample. A total of 18 composite soil samples were collected for the three treatments in two years. Following sample collection, soils were placed in a cooler with dry ice and transported to the laboratory. Each field-moist sample was then passed through a 2 mm sieve, mixed thoroughly, and divided into two portions. One portion was air-dried and stored at room temperature for chemical analyses, and the other was freeze-dried and stored at 80 C for subsequent biological and genetic analyses. − ◦ Soil pH was determined using a soil: water ratio of 1:2.5 (v/v) and a combination glass electrode (Mettler-Toledo International Inc., Columbus, OH, USA). Soil organic carbon (SOC) and total nitrogen + (TN) were determined using a Carlo-Erba NA 1500 nitrogen/carbon/sulfur analyzer [25]. Soil NH4 and NO3− were extracted using 2 M KCl and analyzed with a BioTek Epoch 2 microplate reader (BioTek Instruments, Inc., Winooski, VT, USA) at OD660 and OD550, respectively. Microbial biomass carbon (MBC) was determined using the chloroform-fumigation incubation method with a Kc factor of 0.45 [26,27].

2.2. Soil DNA Extraction, PCR Amplification and Sequencing Soil DNA was extracted from 0.5 g soil using an Ultra Clean Soil DNA Isolation Kit (MO BIO Laboratories, Inc., Carlsbad, CA, USA) according to the manufacturer’s instructions. The quality and quantity of DNA was evaluated utilizing agarose gel electrophoresis and a NanoDrop-1000 spectrophotometer (NanoDrop Technologies, Inc., Wilmington, DE, USA). All extracted DNA had an A260/A280 > 1.8 and was of sufficient purity to be used in a polymerase chain reaction (PCR) following a 10-fold dilution with nuclease-free water. PCR primers were 27F (50-AGA GTT TGA TCC TGG CTC AG-30) and 1492R (50-GGT TAC CTT GTT ACG ACT T-30)[28,29]. Each 25 µL PCR reaction mixture contained 1 µL of template DNA at 1 0.25 ng µL− , 1 µL each of the forward and reverse primers at 10 µM, 12.5 µL of Taq 2X Master Mix (New England Biolabs Inc., Ipswich, MA, USA), and 9.5 µL of H2O. After an initial denaturation for 2 min at 94 ◦C, amplification was carried out in 35 cycles with each cycle consisting of denaturation (40 s, 94 ◦C), annealing (40 s, 49 ◦C), and extension (40 s, 72 ◦C). The extension in the final cycle was 2 min. The expected amplicons were about 1465 base pairs (bp). All PCR products were evaluated to confirm the expected size, quantified using a NanoDrop-1000 spectrophotometer, and purified using a Gel/PCR DNA Fragments Extraction Kit (IBI Scientific, Peosta, IA, USA) prior to being sequenced. Sequencing was done using a Roche 454 FLX/FLX+ platform at the Research and Testing Laboratory (RTL), Lubbock, TX (https://www.medicalbiofilm.org/index.html). PCR amplicons in the region 939F to 1492R targeting the V6-V9 hypervariable regions of the 16S rRNA gene were sequenced [30,31].

2.3. Bioinformatics and Statistical Analyses Prior to downstream analyses, de-noising and chimera checking were performed on the sequences using USEARCH [32] and UCHIME [33] to remove low quality sequences and error reads. Sequences with less than 250 bp, sequences with quality scores less than 25, and all chimeric sequences were removed [32–35]. The remaining 16S rRNA sequences were clustered into operational taxonomic units (OTUs) at 97% similarity using UPARSE [36]. Clusters with <2 members (singleton clusters) were removed. The filtered high-quality sequences were analyzed to reveal the richness, diversity, and composition of soil bacterial communities under different fertilization treatments. Microbial α-diversity analyses were conducted using MOTHUR 1.44.1 and the Schloss standard procedure (http://www.mothur.org/) with modifications [37,38]. The 16S rRNA RDP reference database (Trainset9_032012.rdp) [39] was used to support analyses in MOTHUR. The evaluated α-diversity indices included two richness indices, Chao 1 [40] and abundance-based coverage estimator (ACE) [41], and two diversity indices, Shannon [42] and reverse Simpson (Invsimpson) [43]. Taxonomic assignment was conducted using the USEARCH global alignment algorithm against a database of high-quality 16S rRNA sequences derived from NCBI [32]. Three-way Venn diagrams (Venny 2.0, http://bioinfogp.cnb.csic.es/tools/venny/index.html) Agronomy 2020, 10, 1497 4 of 15 were used to reveal taxonomic groups that were shared by two or three treatments and taxonomic groups that were specific to one of the treatments. One-way multivariate analysis of variance (MANOVA) was conducted in R 3.6.3 (https://www. r-project.org/;[44]) to determine whether soil properties, number of OTUs, α-diversity indices, and the relative abundance of bacterial phyla differ among treatments. Mean separation was carried out according to the Tukey’s honestly significant difference post hoc test (HSD, p 0.05). Pearson’s ≤ correlations between soil properties and the relative abundance of each bacterial and their significances (p) were assessed with the “corr” function at p 0.05. ≤ The variations in bacterial community structure among different treatments (β-diversity) were evaluated by non-metric multi-dimensional scaling (NMDS) analysis using the “vegan” package in R. Bray–Curtis distance matrix and the “ordiellipse” function were used to generate the NMDS plot. Permutational multivariate analysis of variance (PERMANOVA) was performed to test effects of different fertilizers on β-diversity using the “adonis” function (999 permutations) at a p value of 0.05. The multi-response permutation procedure (MRPP) was used to compare the within-groups dissimilarities (WD) and between-groups dissimilarities (BD) at p 0.05. Pearson’s correlation ≤ coefficients (r) between the NMDS scores and tested soil properties were calculated with the “cor” function. Significant treatment differences (p 0.05) were tested with the post hoc permutation tests ≤ with 999 permutations. Vectors of Pearson’s correlations between the NMDS scores and tested soil properties were added to the NMDS plot using the “envfit” function.

3. Results

3.1. Bacterial Richness and Diversity A total of 42,087 high-quality 16S rRNA gene sequences were used for the microbial community structure analyses. Bacterial rarefaction curves of the observed OTUs numbers approached plateaus in all treatments (Figure1), indicating that the number of 16S rRNA sequences obtained in each treatment was sufficient to reveal detectable genotypes in the community. Bacterial richness and diversity were evaluated based on the number of OTUs observed in each soil, richness indices, diversity indices, and taxonomic groups specific to each treatment (Tables1 and2, Figures1 and2). The sequences were clustered into 1463, 1580, and 834 OTUs at 97% similarity in control, manure, and NPK treatments, respectively (Table1). Bacterial richness and diversity indices, including Chao 1, Shannon, and Invsimpson, were significantly higher in manure and control treatments, and lower in NPK treatment (Table1). The number of bacterial groups’ at all taxonomic levels from phylum to species were consistently and significantly lower in NPK than control or manure treatments. Manure had 1–1.3 times the bacterial groups compared with the control, while NPK had 72-84% of the number of bacterial groups detected in the control (Table2).

Table 1. Richness and diversity of bacterial communities in soils tested.

Richness and Diversity Control Manure NPK Number of OTUs Observed 1463 b 1580 a 834 c Richness Index Chao 1 1860 b 2480 a 1235 b ACE 2571 a 3355 a 1897 a Diversity Index Shannon 6.33 b 6.42 a 5.45 c Invsimpson 246.2 a 237.5 b 84.6 c Note: Control, century-long continuous wheat cultivation without fertilization; Manure, century-long continuous 1 wheat cultivation received organic fertilizer cattle manure every four years at 269 kg N ha− ; NPK, century-long 1 1 continuous wheat cultivation received inorganic fertilizer NPK annually at 67 kg N ha− , 14.6 kg P ha− , and 1 28 kg K ha− . Different lower case letters indicate significantly different means according to Tukey’s honestly significant difference (HSD) post hoc test at p 0.05. ≤ Agronomy 20202020, 10, x 1497 FOR PEER REVIEW 55 of of 15 15

Table 2. Bacteria belonging to major taxonomic ranks of the hierarchy of biological classification in theTable tested 2. Bacteria soils based belonging on 16S to rRNA major ge taxonomicne sequences. ranks of the hierarchy of biological classification in the tested soils based on 16S rRNA gene sequences. Number Detected in Soils Specified Taxonomic Rank Control NumberManure Detected in SoilsNPK Specified All soils Taxonomic Rank Phylum 18 a Control Manure18 a NPK13 b All soils 20 a b Phylum35 18 a 1836a 13 b 28 20 40 Order Class64 a 35 a 6536 28 b 50 b 40 79 Family Order99 b 64 a 11065 50 b 83 c 79 133 Genus Family 168 a 99 b 205110 a 83 c127 b 133 268 a a b Species Genus211 a 168 272205 a 127 160 b 268 399 Species 211 a 272 a 160 b 399 Note: Control, century-long continuous wheat cultivation without fertilization; Manure, century-long Note: Control, century-long continuous wheat cultivation without fertilization; Manure, century-long continuous continuous wheat cultivation received organic fertilizer cattle manure every four1 years at 269 kg N wheat cultivation received organic fertilizer cattle manure every four years at 269 kg N ha− ; NPK, century-long –1 1 1 hacontinuous; NPK, wheatcentury cultivation-long continuous received inorganicwheat cultivation fertilizer NPK received annually inorganic at 67 kg fertilizer N ha− , 14.6NPK kg annually P ha− , and at 1 6728 kg N K ha−–1,. 14.6 Diff erentkg P ha lower–1, and case 28 letters kg K ha indicate–1. Different significantly lower di casefferent letters means indicate according significantly to Tukey’s different honestly significant difference (HSD) post hoc test at p 0.05. means according to Tukey’s honestly significant≤ difference (HSD) post hoc test at p ≤ 0.05.

Figure 1. Rarefaction curves of 16S rRNA sequences obtained from soils tested. Curves were constructed Figure 1. Rarefaction curves of 16S rRNA sequences obtained from soils tested. Curves were based on the number of OTUs observed at 97% similarity per 100 sequences analyzed. Control, constructed based on the number of OTUs observed at 97% similarity per 100 sequences analyzed. century-long continuous wheat cultivation without fertilization; Manure, century-long continuous Control, century-long continuous wheat cultivation without fertilization; Manure, century1 -long wheat cultivation received organic fertilizer cattle manure every four years at 269 kg N ha− ; NPK, continuous wheat cultivation received organic fertilizer cattle manure every four years at 269 kg N century-long continuous wheat cultivation received inorganic fertilizer NPK annually at 67 kg N ha 1, –1 − ha ; NPK, century1 -long continuous1 wheat cultivation received inorganic fertilizer NPK annually at 14.6 kg P ha− , and 28 kg K ha− . 67 kg N ha–1, 14.6 kg P ha–1, and 28 kg K ha–1. The number of bacterial groups that were shared by two or three treatments and the number of bacterialThe number groups thatof bacterial were specific groups to that one were treatment shared are by illustrated two or three in treatments the three-way and Venn the number diagrams of bacterial(Figure2 ).groups Higher that grouping were specific resolutions to one yielded treatment higher are illustrated percentages in ofthe bacterial three-way groups Venn thatdiagrams were (Figurespecific 2). to Higherone treatment. grouping At resolutions the phylum yielded level, higher bacterial percentages groups specific of bacterial to control groups and that manure were specifictreatments to one accounted treatment. for 7.7%At the and phylum 10.3% of level, total bacterial phyla, respectively; groups specific bacterial to control groups and specific manure to treatmentsthe NPK treatment accounted were for not7.7% detected and 10.3% at thisof total taxonomic phyla, respectively; level. At the bacterial species level, groups bacterial specific groups to the NPKspecific treatment to control, were manure, not detectedand NPK at treatments this taxonomic comprised level. 16.1%, At 31.4%,the species and 10.4% level, of bacterial the total groupsspecies, specificrespectively. to control, About manure, 64% of the and detected NPK treatments phyla were comprised shared among 16.1%, the 31.4% three, and treatments; 10.4% of while the total only species,19% of therespectively. species were About shared 64% of among the detected the three phyl soils.a were Of shared the soils among tested, the the three number treatments; of bacterial while onlygroups 19% specific of the tospecies one treatment were shared was among generally the highestthree soils. in manure, Of the soils followed tested, by the control, number and of lowestbacterial in groupsNPK. Of specific the 399 to species one treatment detected, was 125 generally were specific highest to manure, in manure, 64 were followed specific by tocontrol, the control, and lowest while 42in NPKspecies. Of were the 399 unique species to the detected, NPK treatment. 125 were Compared specific to tomanure, manure, 64 NPK were had specific a greater to the degree control, of impact while 42on species soil bacterial were unique richness to and the diversity.NPK treatment. Phyla orCompared classes specific to manure, to NPK NPK were had not a greater detected. degree At the of impact on soil bacterial richness and diversity. Phyla or classes specific to NPK were not detected. At

Agronomy 2020, 10, 1497 6 of 15 Agronomy 2020, 10, x FOR PEER REVIEW 6 of 15 thespecies species level, level, about about 10.4% 10.4% were were specific specific to NPK, to NP whichK, which was was significantly significantly lower lower than than the 16.1%the 16.1% and and31.4% 31.4% specific specific to control to control and and manure, manure, respectively. respectively.

FigureFigure 2. Average 2. Average number number and percentage and percentage of taxonomic of taxonomic grou groupsps specific specific to each to each microbial microbial community community or sharedor by shared communities by communities in three-wa in three-wayy Venn diagrams Venn diagrams (Venny 2.0, (Venny http: 2.0,// bioinfogp.cnb.csic.es/tools/venny/ http://bioinfogp.cnb.csic.es/tools/ index.venny html)./index ND, .not html). detected. ND, notControl, detected. century-long Control, century-longcontinuous wheat continuous cultivation wheat without cultivation fertilization; without Manure,fertilization; century-long Manure, continuous century-long wheat cultivation continuous received wheat cultivation organic fertilizer received cattle organic manure fertilizer every cattlefour –1 1 years manureat 269 kg every N ha four; NPK, years century-long at 269 kg N continuous ha− ; NPK, wheat century-long cultivation continuous received wheat inorganic cultivation fertilizer received NPK 1 1 1 annuallyinorganic at 67 kg fertilizer N ha–1, NPK14.6 kg annually P ha–1, atand 67 28 kg kg N K ha ha− –1,. 14.6 kg P ha− , and 28 kg K ha− .

3.2.3.2. Bacterial Bacterial Community Community Composition Composition TheThe non-metric non-metric multi-dimensional multi-dimensional scaling scaling (NMDS) (NMDS) analysis analysis based based on on the the relative relative abundance abundance of of bacterial groups indicated significant (p 0.01) differences in the composition of soil bacterial bacterial groups indicated significant (p ≤ ≤0.01) differences in the composition of soil bacterial communitiescommunities under under different different fertili fertilizationzation regimes regimes (Figure (Figure 3).3 ).The The result result was was further further supported supported by the by the significantly (p 0.01) larger between-groups distance (dissimilarity) than within-group distance significantly (p ≤ 0.01)≤ larger between-groups distance (dissimilarity) than within-group distance basedbased on on the the MRPP MRPP analysis analysis (Figure (Figure 3). 3To). further To further evaluate evaluate the effects the eofff differentects of di fertilizationfferent fertilization regimes onregimes the composition on the composition of the soil of bacterial the soil community, bacterial community, we compared we compared the relative the abundance relative abundance of bacterial of phylabacterial among phyla the among treatments the treatments (Figure 4). (Figure Of the4). 14 Of ph theyla 14 detected phyla detected in one or in more one or soils more in soils both in years, both Acidobacteriayears, Acidobacteria and Proteobacteriaand Proteobacteria were weremost most dominant, dominant, averaging averaging 45.8% 45.8% and and 22.0%, 22.0%, respectively. respectively. AdditionalAdditional phyla phyla included Actinobacteria (8.6%),(8.6%), ChloroflexiChloroflexi (6.2%),(6.2%), (4.9%),(4.9%), Bacteroidetes (4.4%),(4.4%), VerrucomicrobiaVerrucomicrobia (2.7%),(2.7%), NitrospiraeNitrospirae (2.4%),(2.4%), GemmatimonadetesGemmatimonadetes (1.3%),(1.3%), CyanobacteriaCyanobacteria (0.94%),(0.94%), and and TM7TM7 (0.40%). (0.40%). Although Although the the relative relative abundance abundance of of FirmicutesFirmicutes waswas not not significantly significantly different different among among soilsoil treatments, treatments, the the relative relative abundance abundance of of some some bacterial bacterial groups groups varied varied considerably. considerably. For For example, example, thethe relative relative abundance abundance of of ActinobacteriaActinobacteria waswas highest highest in in control, control, followed followed by by manure, manure, and and lowest lowest in in NPK.NPK. The The relative relative abundance abundance of of ChloroflexiChloroflexi,, on on the the other other hand, hand, was was highest highest in in NPK, NPK, followed followed by by control,control, andand lowest lowest in manure.in manure. The abundanceThe abundance of Cyanobacteria of Cyanobacteria, a diazotrophic, a diazotrophic group, was group, significantly was significantlyhigher in the higher unfertilized in the control unfertilized (2.59%), control compared (2.59%), with manurecompared (0.19%) with ormanure NPK (0.05%) (0.19%) treatments. or NPK (0.05%)Focusing treatments. on Cyanobacteria Focusing, Microcoleus on Cyanobacteria paludosus, Microcoleusand Leptolyngbya paludosus appalachiana and Leptolyngbyawere the appalachiana two most were the two most dominant species, with the control population reaching 39 and 55 times of those in manure and NPK treatments, respectively (Figure 5). Compared to the control, manure application

Agronomy 2020, 10, x FOR PEER REVIEW 7 of 15 Agronomy 2020, 10, 1497 7 of 15 generally led to enrichment of Proteobacteria, , Bacteroidetes, and Gemmatimonadetes, and declinesdominant in Acidobacteria, species, with theChloroflex controli, populationVerrucomicrobia, reaching and 39 Cyanobacteria and 55 times; ofNPK those application in manure resulted and in higherNPK relative treatments, abundances respectively of Acidobacteria, (Figure5). Compared , to the Nitrospirae, control, manure Bacteroidetes application, and generallyTM7, but lower relativeled to abundances enrichment ofof Proteobacteria,Actinobacteria Nitrospirae,, Verrucomicrobia, Bacteroidetes Cyanobacteria,, and Gemmatimonadetes, and Gemmatimonadetes.and declines in Acidobacteria, Chloroflexi, Verrucomicrobia, and Cyanobacteria; NPK application resulted in higher relative abundances of Acidobacteria, Chloroflexi, Nitrospirae, Bacteroidetes, and TM7, but lower relative abundances of Actinobacteria, Verrucomicrobia, Cyanobacteria, and Gemmatimonadetes.

- ** NO3 (r = 0.933, p ≤ 0.01 ) TN + MBC SOC NH4

Within-groups Distance = 0.114 Between-groups Distance = 0.183 pH p ≤ 0.01** (r = 0.786, p ≤ 0.05*)

2 Stress = 0.026, R = 0.999, p ≤ 0.01**

Figure 3. Non-metric multidimensional scaling (NMDS) ordination of soil bacterial community Figurestructure 3. Non in diff-metricerent fertilization multidimensional regimes. Control, scaling century-long (NMDS) ordinationcontinuous wheat of soil cultivation bacterial without community fertilization; Manure, century-long continuous wheat cultivation received organic fertilizer cattle structure in different fertilization regimes.1 Control, century-long continuous wheat cultivation manure every four years at 269 kg N ha− ; NPK, century-long continuous wheat cultivation received without fertilization; Manure, century-long continuous1 wheat1 cultivation received1 organic fertilizer inorganic fertilizer NPK annually at 67 kg N ha− , 14.6 kg P ha− , and 28 kg K ha− . The degree of –1 cattleseparation manure between every groupsfour years ranges at from269 kg1 N to ha 1, where; NPK, 0 means century not-long different, continuous 1 means wheat completely cultivation − –1 –1 –1 receiveddifferent. inorganic Ellipses fertilizer represent NPK the 95% annually confidence at 67 intervalkg N ha for, 14.6 the standardkg P ha error, and of28 thekg K distances ha . The of degree of samplesseparation in each between microbial groups community. ranges Withfrom increasing−1 to 1, where distance 0 means between not two different, ellipses the1 means community completely different.structure Ellipses becomes represent more dissimilar; the 95% ** confidencep 0.01 means interval that there for the was standard a significant error diff oference the indistances the of ≤ samplesstructure in betweeneach microbial two microbial community. communities With increasing based on thedistance permutational between multivariate two ellipses analysis the community of structurevariance becomes (PERMANOVA). more dissimilar; WD stands * for p within-groups≤ 0.05 means distance that there and was BDstands a significant for between-groups difference in the distance; * p 0.05 means that there was a significant difference between WD and BD based on the structure between≤ two microbial communities based on the permutational multivariate analysis of MRPP analysis. Vectors show Spearman’s correlations of variation in bacterial community composition variance (PERMANOVA). WD stands for within-groups distance and BD stands for between-groups and soil properties tested. Soil pH and NO3− had significantly strong correlations to the first axis distance; * p ≤ 0.05 means that there was a significant difference between WD and BD based on the (NMDS1) or second axis (NMDS2) of NMDS ordination. MRPP analysis. Vectors show Spearman’s correlations of variation in bacterial community composition and soil properties tested. Soil pH and NO3− had significantly strong correlations to the first axis (NMDS1) or second axis (NMDS2) of NMDS ordination.

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Figure 4. Soil bacterial community composition at the phylum level under different fertilization FigureFigure 4. 4. Soil bacterial community composition composition at at the the phylum phylum level level under under different different fertilization fertilization treatments. Control, century-long continuous wheat cultivation without fertilization; Manure, treatments.treatments. Control, Control, century century-long-long continuous continuous wheat wheat cultivation cultivation without without fertilization; fertilization; Manure, Manure, century-long continuous wheat cultivation received organic fertilizer cattle manure every four years century-longcentury-long continuouscontinuous wheat cultivation received organic fertilizer cattle cattle manure manure every every four four years years at 269 kg N ha–11; NPK, century-long continuous wheat cultivation received inorganic fertilizer NPK atat 269269 kgkg NN haha−–1;; NPK, century century-long-long continuous continuous wheat wheat cultivation cultivation receiv receiveded inorganic inorganic fertilizer fertilizer NPK NPK annually at 67 kg N ha–11, 14.6 kg P ha–1,1 and 28 kg K ha–1. 1 annuallyannually atat 6767 kgkg NN haha−–1,, 14.6 14.6 kg kg P P ha ha–−1, and, and 28 28 kg kg K K ha ha–1.− .

Dominant Average 16S rRNA reads CyanobacterialDominant Average 16S rRNA reads CyanobacterialSpecies Control Manure NPK Species Control Manure NPK M. paludosus 191 6 2 M. paludosus 191 6 2 L. appalachiana 82 1 3 L. appalachiana 82 1 3 Figure 5. Cyanobacterial species detected in soils under different fertilization treatments. Control, Figure 5. Cyanobacterial species detected in soils under different fertilization treatments. Control, Figurecentury 5.-longCyanobacterial continuous specieswheat cultivation detected in without soils under fertilization; different Manure, fertilization century treatments.-long continuous Control, century-long continuous wheat cultivation without fertilization; Manure, century-long continuous–1 century-longwheat cultivation continuous received wheat organic cultivation fertilizer without cattle manure fertilization; every four Manure, years century-long at 269 kg N h continuousa ; NPK, –1 wheat cultivation received organic fertilizer cattle manure every four years at 269 kg N ha ; NPK,– wheatcentury cultivation-long continuous received wheat organic cultivation fertilizer received cattle manure inorganic every fertilizer four yearsNPK annually at 269 kg at N 67 ha kg1 ;N NPK, ha − – century1 -long continuous–1 wheat –cultivation1 received inorganic fertilizer NPK annually at 67 kg N ha century-long, 14.6 kg P ha continuous, and 28 kg wheat K ha cultivation. received inorganic fertilizer NPK annually at 67 kg N ha 1, 1 –1 –1 − , 14.6 kg P ha1 , and 28 kg K ha1 . 14.6 kg P ha− , and 28 kg K ha− . -, and were less dominant bacterial phyla detectedDeinococcus in control-Thermus and manure, Fibrobacteres treatments, and Thermodesulfobacteria but not in NPK. Deinococcus were less-Thermus dominant populations bacterial phylawere detectednear the detectionin control limit and inmanure the control treatments, but averaged but not 0.02% in NPK. of the Deinococcus community-Thermus in manure populations-treated soils.were near the detection limit in the control but averaged 0.02% of the community in manure-treated soils.

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Deinococcus-Thermus, Fibrobacteres and Thermodesulfobacteria were less dominant bacterial phyla detected in control and manure treatments, but not in NPK. Deinococcus-Thermus populations were near the detection limit in the control but averaged 0.02% of the community in manure-treated soils. Application of manure also promoted Fibrobacteres, averaging 0.22% of the community compared to 0.04% in the control. The impact of manure treatment on Thermodesulfobacteria was limited, and these bacteria were not detected in NPK-treated soils.

3.3. Soil Parameters and Their Relationships with Bacterial Community Structure Century-long research plots with different fertilization regimes had significantly different soil pH, ranging from 4.6 (NPK) to 6.6 (manure) (Table3). The trends observed for soil organic C (SOC), total N (TN), and microbial biomass C (MBC) were similar, being significantly higher in the two fertilized soils compared to the unfertilized control. Differences between manure and NPK treatments were not significant.

Table 3. Properties of the soils used.

+ SOC TN NH4 NO3− MBC Treatment pH 1 1 g kg− mg kg− Control 5.4 b 6.67 b 0.66 b 22.1 c 5.2 c 68 b Manure 6.6 a 8.56 a 0.82 a 39.9 a 10.0 b 124 a NPK 4.6 c 7.97 a 0.82 a 31.0 b 13.9 a 126 a Note: SOC, soil organic carbon; TN, total nitrogen; MBC, soil microbial biomass carbon. Control, century-long continuous wheat cultivation without fertilization; Manure, century-long continuous wheat cultivation received 1 organic fertilizer cattle manure every four years at 269 kg N ha− ; NPK, century-long continuous wheat cultivation 1 1 1 received inorganic fertilizer NPK annually at 67 kg N ha− , 14.6 kg P ha− , and 28 kg K ha− . Different lower case letters indicate significantly different means according to Tukey’s honestly significant difference (HSD) post hoc test at p 0.05. ≤

+ Focusing on the plant-available forms of N, NH4 was significantly higher in manure than NPK, but NO3− was significantly higher in NPK compared to the manure treatment. NMDS analysis and Pearson’s correlation further showed the interrelationships between soil properties and the bacterial community composition (Table4, Figure2). Of the evaluated soil properties, soil bacterial community structure was significantly correlated to pH (r = 0.786, p 0.05) and NO (r = 0.933, p 0.01). Of ≤ 3− ≤ the 20 dominant phyla detected, pH had significant positive correlations to Proteobacteria (r = 0.703, p 0.05) and Gemmatimonadetes (r = 0.700, p 0.05), and significant negative correlations to Acidobacteria ≤ ≤ (r = 0.744, p 0.05) and Chloroflexi (r = 0.766, p 0.05). Similarly, NO had a significant positive − ≤ − ≤ 3− correlation to Acidobacteria (r = 0.750, p 0.05), but significant negative correlations to Actinobacteria ≤ (r = 0.773, p 0.05), Verrucomicrobia (r = 0.924, p 0.0001), and Cyanobacteria (r = 0.911, p 0.0001) − ≤ − ≤ − ≤ (Table5).

Table 4. Pearson’s correlation coefficients (r) and p values between nonmetric multidimensional scaling (NMDS) ordination scores of the bacterial community and soil properties.

Parameter NMDS1 NMDS2 p Value pH 0.786 0.305 0.030 * − SOC 0.276 0.548 0.269 TN 0.100 0.764 0.090 + NH4 0.508 0.526 0.091 NO 0.223 0.933 0.002 ** 3− − MBC 0.235 0.499 0.335 − Note: Pearson’s correlations between the NMDS scores and tested soil properties were assessed with the “cor” function and “envfit” function and post hoc permutation tests (999 permutations). Correlations with p 0.05 * and p 0.01 ** were considered as significant. NMDS1 is the first axis of the NMDS plot, NMDS2 is the second≤ axis of the≤ NMDS plot. SOC, soil organic carbon; TN, total nitrogen; MBC, soil microbial biomass carbon. Agronomy 2020, 10, 1497 10 of 15

Table 5. Pearson’s correlation coefficients (r) between soil parameters and the relative abundance of bacterial phyla.

+ Bacterial Phyla pH SOC TN NH4 NO3− MBC Acidobacteria 0.744 * 0.124 ns 0.396 ns 0.019 ns 0.750 * 0.489 ns − − Actinobacteria 0.211 ns 0.457 ns 0.607 ns 0.472 ns 0.773 * 0.270 ns − − − − − Proteobacteria 0.703 * 0.339 ns 0.191 ns 0.552 ns 0.084 ns 0.214 ns − − Chloroflexi 0.766 * 0.190 ns 0.027 ns 0.414 ns 0.313 ns 0.155 ns − − − − Firmicutes 0.186 ns 0.083 ns 0.016 ns 0.130 ns 0.037 ns 0.201 ns − − − − Verrucomicrobia 0.502 ns 0.365 ns 0.647 ns 0.341 ns 0.924 *** 0.615 ns − − − − − Cyanobacteria 0.068 ns 0.692 * 0.867 ** 0.836 ** 0.911 *** 0.687 * − − − − − − Nitrospirae 0.403 ns 0.455 ns 0.522 ns 0.658 ns 0.355 ns 0.838 ** Bacteroidetes 0.476 ns 0.488 ns 0.450 ns 0.684 * 0.308 ns 0.062 ns − Gemmatimonadetes 0.700 * 0.061 ns 0.142 ns 0.240 ns 0.447 ns 0.514 ns − − − TM7 0.401 ns 0.078 ns 0.244 ns 0.032 ns 0.451 ns 0.077 ns − − Others 0.419 ns 0.039 ns 0.075 ns 0.141 ns 0.266 ns 0.061 ns − − Note: ns, not significant; * p 0.05, ** p 0.01, *** p 0.001; SOC, soil organic carbon; TN, total nitrogen; MBC, soil microbial biomass carbon. ≤ ≤ ≤

4. Discussion

4.1. Soil Parameters and Their Relationships with Bacterial Community Structure All soils used in this study were of the same soil series under long-term continuous winter wheat cultivation. The detected differences in the richness, diversity, and structure of bacterial community would likely reflect impact induced by different long-term soil fertilization regimes, evidenced by the consistent trends in results from samples in both years. Clear separation of the tested treatments in NMDS plot suggested significant effect of soil fertilization regimes on the bacterial community structure (Figure3). The richness and diversity of the bacterial community in manure treatment were higher or similar to those of control, and both were significantly higher than NPK treatment, which was evidenced by the number of OTUs observed, richness indices, diversity indices, and the number of bacterial groups at each taxonomic level (Tables1 and2; Figures1 and2). Compared to manure, NPK had a greater impact on soil bacterial community structure, which was evidenced by the lower percentage of bacterial groups shared between NPK and control than the percentage of bacterial groups shared between manure and control at all taxonomic levels (Figure2), as well as the larger distance (dissimilarity) in microbial community structure between NPK and control than the distance between manure and control in the NMDS plot (Figure3). Promotion of bacterial richness and diversity by long-term application of manure could be due to multifaceted changes in soil, including enrichment of organic C and reduction of acidity. Previous studies using these soils showed significantly higher microbial biomass and enzyme activities in manure treatment than control or NPK treatment [5,7]. Application of manure led to a 16-20% increase in microbial activity [22,45], a marked increase in the abundance of gram-negative bacteria [21], and proliferation of selected microbial groups and changes in community composition [46,47]. A loss of richness and diversity by long-term application of NPK was clearly demonstrated in this study. It is well established that long-term application of inorganic fertilizer often leads to soil acidification [13,15,48]. Addition of available N, P, and K could shift the microbial community in favor of those that are less competitive in acquiring these nutrients but have higher tolerance to acidity. Therefore, the NPK treatment may have exerted selective pressures that led to reduced diversity and development of a less evenly distributed bacterial community. The relatively low number of bacterial groups and diversity indices observed among the treatments (Tables1 and2; Figure2) were consistent with shifts in the microbial communities. Century-long wheat production without fertilization led to marked depletion of soil nutrition and productivity [5]. The average grain yield in the control between 1890 and 2015 was about 52% and 46% of manure and NPK treatments, respectively [14,23]. Nevertheless, control continuously produced Agronomy 2020, 10, 1497 11 of 15

1 an average of >1100 kg ha− of wheat grain every year for over a century [14]. Aside from limited nutrients added by rainfall, microbes with the capability to fix atmospheric N2 may have played an important role in maintaining soil productivity.

4.2. Soil Bacterial Groups under Century-Long Fertilization Regimes and Their Ecological Implications Nutrient availability, especially C and N, may markedly impact the predominant microbial groups found in soils [49,50]. High nutrient availability promoted fast-growing copiotrophs while nutrient-limited soils favored slow-growing [49,51]. In the present study, Acidobacteria and Proteobacteria were the two most dominant phyla in soils under all three fertilization regimes, comprising 43-52% and 18-27% of the bacterial community within each soil, respectively (Table5). This finding is consistent with a number of reports showing that Acidobacteria and Proteobacteria were the two most dominant bacterial groups, with their relative abundance varying considerably across different soil environments [3,13,18,52]. The abundance ratio of Proteobacteria:Acidobacteria can serve as a broad indicator of trophic status across a range of terrestrial soils [53]. In this study, the ratio was highest in manure (0.64), followed by control (0.47), and lowest in NPK (0.35) treatment (Figure4). Of the three fertilization treatments, manure generally led to enrichment of all phyla except Cyanobacteria, NPK resulted in shrinking of most phyla but thriving of Chloroflexi, the control led to promotion of Cyanobacteria but detraction of Nitrospirae (Table5). The lowest relative abundance of Chloroflexi was found in the manure treatment, while the highest abundance was in NPK (Figure4). The results suggested that Chloroflexi might be less competitive in a diverse community but thrive in disturbed, high-stress environments, consistent with previous reports [19,20,54]. Suleiman et al. [20] reported that Chloroflexi, the most dominant rare (with 1% abundance) phylum detected, constituted ≤ a higher abundance in deforested grassland (0.6%) than pristine forest (0.4%). In agroecosystems, its abundance was higher, especially in soils under long-term cultivation. Sheng et al. [19] reported that Chloroflexi was significant higher in a century-long rice paddy (15.1%) than soils associated with 30 years of vegetable cultivation (1.1-4.3%). In the wheat field of this study, Chloroflexi accounted ≤ for 1.7-10.4% of the bacterial community, and was the third dominant phyla. Assuming pristine forest is a non-disturbed system, deforested grassland and agricultural fields would be systems with higher disturbance and stress. The higher occurrence of Chloroflexi in stressed environments has been reported previously, including at subzero temperatures [54], CO2-rich hypoxic soil [55], and PCB-contaminated soils [56]. Thus, the thriving of Chloroflexi in NPK could be related to acid stress resilience. In the century-long unfertilized control plot, microbes with the capability to fix atmospheric N2 may have played an important role in maintaining soil nutrient availability and wheat productivity. Cyanobacteria were most abundant in the control, with relative abundance values 13.6–51.8 times those in the two fertilized soils (Table2). Another phylum that was promoted in the unfertilized control was Actinobacteria. Interestingly, Actinobacteria also contains strains capable of nitrogen fixation [57]. The dominance of Actinobacteria in soil environments is often reported [58,59], which was also the third most dominant groups in the tested soils. Actinobacteria contribute to biological buffering of soils and organic matter decomposition, as well as producing many bioactive metabolites (antibacterials, antifungals, and growth promoting substances for and ) [60,61].

4.3. Soil Parameters Drive Soil Bacterial Community Structure Soil properties play key roles in shaping microbial community structure [50]. In this study, soil pH and NO3− content were the two most-dominant factors influencing soil bacterial community structure under different fertilization regimes (Tables4 and5; Figure3). The results were in agreement with previous studies [12,13,50] indicating nutrient availability (especially C and N) and soil pH are main factors for shifts in soil microbial communities under different fertilization regimes. Soil acidity, as a crucial factor governing bacterial richness and diversity, could serve as a selective pressure to promote or suppress the growth of specific bacterial groups. In this study, soil pH was lowest Agronomy 2020, 10, 1497 12 of 15 in NPK, followed by control, and highest in manure (Table3), following the trends in bacterial richness and diversity in the three treatments (Tables1 and2; Figures1 and2). Furthermore, a significant correlation between pH and NMDS scores suggested an association with bacterial community structure. Fierer and Jackson [62] found that bacterial richness and diversity differed by ecosystem type, and these differences could largely be explained by soil pH (richness r2 = 0.70, p 0.0001; diversity r2 = 0.58, ≤ p 0.0001). Rousk et al. [10] also reported positive relationships between bacterial richness and soil pH ≤ (r2 = 0.75, p 0.001), with the number of OTUs doubling between pH 4.0 and 8.3. Fierer and Jackson [62] ≤ and Zhang et al. [48] reported that most bacteria require a pH of 6.0–8.0, which is suitable for most to function [63]. Of the bacterial phyla detected, pH had significant positive correlations with Proteobacteria and Gemmatimonadetes but significant negative correlations with Acidobacteria and Chloroflexi (Table5), suggesting that the variations in bacterial richness and diversity in three treatments could be primarily due to the promotion or suppression of microorganisms within these four phyla. With increasing pH from 4.0 to 7.0, Zhang et al. [48] also reported that Acidobacteria and Chloroflexi decreased, while Proteobacteria and Gemmatimonadetes increased. Nitrogen availability was another determining factor regulating the richness, diversity, and composition of the soil bacterial community. Cyanobacteria was one of the phyla most affected by N content, evidenced by the significant negative correlations between the relative abundance of Cyanobacteria and soil total N (r = 0.867, p 0.01), NH + (r = 0.836, p 0.01), and NO (r = 0.911, − ≤ 4 − ≤ 3− − p 0.01) contents (Table5). Ramirez et al. [ 17] also reported that the abundance of Cyanobacteria in soil ≤ was negatively correlated with N levels (r= 0.50 to 0.64, p 0.05) during 0–800 kg N ha 1 yr 1. − − ≤ − − 5. Conclusions Century-long organic or inorganic fertilization significantly altered the richness, diversity, and composition of the soil bacterial community compared to the unfertilized control. Bacterial richness and diversity were enhanced by manure addition but reduced by NPK application. Different fertilization regimes did not change the types of dominant phyla, but did affect the relative abundance of bacterial phyla in a community. Of the bacterial phyla detected, Acidobacteria and Proteobacteria were the most abundant phyla in all three communities. Of the three fertilization treatments, manure generally led to enrichment of all phyla except Cyanobacteria, NPK resulted in shrinking of most phyla but thriving of Chloroflexi, while century-long wheat cultivation without fertilization promoted the diazotrophic group Cyanobacteria. Soil pH and NO3− availability were the two most dominant parameters governing the richness, diversity, and composition of the soil bacterial community. Soil pH significantly correlated with Acidobacteria, Proteobacteria, Chloroflexi, and Gemmatimonadetes and was major contributors to variations in bacterial richness and diversity among the three treatments. Soil N contents were significantly correlated to Cyanobacteria, whose relative abundance in control was 13.6–51.8 times than those in the fertilized soils. Cyanobacteria, especially Microcoleus paludosus and Leptolyngbya appalachiana, could play an important role in maintaining wheat productivity in the century-long unfertilized control. This study extends our understanding of soil bacterial community structure under long-term organic, inorganic, or no fertilization regimes and provides insight for making improved fertilization strategies.

Author Contributions: All authors contributed significantly to the intellectual inputs for this study and manuscript preparation. X.L. performed the research, analyzed the data, and prepared the initial manuscript. S.D. provided oversight on project design, execution, and analysis. W.R.R. managed the experimental site and provided guidance on manuscript preparation. Y.W. provided technical assistance, and Y.T. helped develop the reviewed manuscript. All authors have read and agreed to the published version of the manuscript. Funding: This work was partially supported by the Oklahoma Agricultural Experiment Station (OAES) under projects h-OKLO2394 and h-OKLO2953. Acknowledgments: The authors gratefully acknowledge the soil fertility program and high performance computing center at Oklahoma State University for the use of facilities. Special thanks go to Jeremiah Mullock and Dhital Sulochana for their assistance during field sampling. Conflicts of Interest: The authors declare no conflict of interest. Agronomy 2020, 10, 1497 13 of 15

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