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Article

Bacterial Communities in Alkaline Saline Soils Amended with Young Maize Plants or Its (Hemi)Cellulose Fraction

by
Valentín Pérez-Hernández
1,2,
Mario Hernández-Guzmán
2,
Marco Luna-Guido
2,
Yendi E. Navarro-Noya
3,
Elda M. Romero-Tepal
2 and
Luc Dendooven
2,*
1
Laboratory of Soil Ecology, Department of Chemistry and Biochemistry, Instituto Tecnológico de Tuxtla-Gutiérrez, Tecnológico Nacional de México, Tuxtla Gutiérrez, Chiapas 29050, Mexico
2
Laboratory of Soil Ecology, Cinvestav, Mexico City 07360, Mexico
3
Centro de Investigación en Ciencias Biológicas, Universidad Autónoma de Tlaxcala, Tlaxcala 90070, Mexico
*
Author to whom correspondence should be addressed.
Microorganisms 2021, 9(6), 1297; https://doi.org/10.3390/microorganisms9061297
Submission received: 17 April 2021 / Revised: 11 May 2021 / Accepted: 12 May 2021 / Published: 15 June 2021
(This article belongs to the Collection Microbial Life in Extreme Environments)
Browse Figures
Versions Notes

Abstract

:
We studied three soils of the former lake Texcoco with different electrolytic conductivity (1.9 dS m−1, 17.3 dS m−1, and 33.4 dS m−1) and pH (9.3, 10.4, and 10.3) amended with young maize plants and their neutral detergent fibre (NDF) fraction and aerobically incubated in the laboratory for 14 days while the soil bacterial community structure was monitored by means of 454-pyrosequencing of their 16S rRNA marker gene. We identified specific bacterial groups that showed adaptability to soil salinity, i.e., Prauseria in soil amended with young maize plants and Marinobacter in soil amended with NDF. An increase in soil salinity (17.3 dS m−1, 33.4 dS m−1) showed more bacterial genera enriched than soil with low salinity (1.9 dS m−1). Functional prediction showed that members of Alfa-, Gamma-, and Deltaproteobacteria, which are known to adapt to extreme conditions, such as salinity and low nutrient soil content, were involved in the lignocellulose degradation, e.g., Marinimicrobium and Pseudomonas as cellulose degraders, and Halomonas and Methylobacterium as lignin degraders. This research showed that the taxonomic annotation and their functional prediction both highlighted keystone bacterial groups with the ability to degrade complex C-compounds, such as lignin and (hemi)cellulose, in the extreme saline-alkaline soil of the former Lake of Texcoco.

1. Introduction

High salinity is one of the major limitations for using soil for agriculture practices, and it is estimated that, in the world, approximately 351.2 million ha are saline and 581 million ha sodic [1]. Salinity has a profound effect on the structure [2], nutrient content [3], and water movement in soils [2], but it also affects the microbial [4] and plant diversity [5]. In Mexico and central America, approximately two million ha are saline. They are natural saline (e.g., Solonchak) or as the result of anthropogenic activity (e.g., soil irrigation) [1]. Lake Texcoco, which originally surrounded the Aztec city of Tenochtitlan (currently Mexico City), was drained mostly leaving a soil with little or no vegetation exposed to wind erosion. Soil in some parts of the former lake Texcoco are extremely alkaline saline with pH reaching 10.5 and an electrolytic conductivity (EC) of 200 dS m−1 [6]. The high soil pH and EC are the result of brackish groundwater that reaches the soil surface and then evaporates. The former lakebed has been drained for different periods, so, in certain areas, the EC (<2 dS m−1) and pH (<10) has dropped, i.e., but, in other parts, the pH remains >10 and the EC > 100 dS m−1. The variation in salinity and alkalinity allows to study how changes in EC and pH affects different soil processes, such as mineralization of organic material [7] or denitrification [8], and the microbial community, i.e., Bacteria and Archaea [9].
The degradation of organic material occurs in the Texcoco soil, although high salinity is known to inhibit mineralization and cellulose degradation. A study with 14C labelled young maize plants showed that the plants and neutral detergent fibre (NDF) fraction (mostly (hemi)cellulose) were mineralized in a soil with EC 32.7 dS m−1 and pH 9.8 [7]. However, it remained unclear as to which organisms were involved in the degradation of the organic material in the extreme alkaline saline soil. Under these conditions, isolation techniques proved the presence of specialized bacterial cellulose degraders, e.g., Cellulomonas bogoriensis and Nocardiopsis dassonvillei [10]. Nevertheless, the limitations in isolation techniques used, i.e., only a small number of microorganisms can be cultured, gives only a glimpse of the diversity and functionality of the microorganisms in the soil environment. In a previous study, one soil of the former lake Texcoco was flooded and the reduction in soil EC did not affect the bacterial capacity to mineralize organic material applied, but it did affect specific bacterial groups [11].
The aim of this study was to determine the effect of salinity and alkalinity on the bacterial community structure and their functionality when young maize plants or their NDF fraction was applied to three different soils from Texcoco with varying alkalinity and salinity. Soil was taken from the former Texcoco lakebed and then amended with young maize plants or their NDF fraction, mostly (hemi)cellulose, and aerobically incubated for 14 days while changes in the bacterial community structure were monitored by means of 454 pyrosequencing of the 16S rRNA marker gene.

2. Materials and Methods

2.1. Cultivation of the Maize and Neutral Detergent Extraction

Details of how the maize (Zea mays L.) was cultivated and its characteristics can be found in the study conducted by Ramírez-Villanueva et al. [12]. Briefly, maize seeds were surface sterilized and germinated on 0.8% agar. Maize seedlings that had formed 2 cm roots were placed on sterilized and C-free vermiculite in the growth chamber and watered regularly with a nutritive Steiner solution [13]. Twenty-five days after planting, the maize plants were harvested, air-dried, and characterised.
The maize plants were characterised and fractionated [14,15] to obtain the neutral detergent fibre (NDF) fraction, as described in Ramírez-Villanueva et al. [12] (Table S1). The NDF fraction is obtained after hot extraction with a neutral detergent solution that removes the “soluble” part of the maize plants, leaving most of the cell wall constituents, i.e., (hemi)cellulose plus some lignin. The young maize plants contained 599 ± 6.5 g kg−1 soluble fraction, 311 ± 8.0 g kg−1 (hemi)cellulose, 25 ± 1.1 g kg−1 lignin, and the rest ash, while the NDF fraction contained 776 ± 15.4 g kg−1 (hemi)cellulose, 63 ± 2.8 g kg−1 lignin, and 155 ± 2.9 g kg−1 ash.

2.2. Soil Sampling

The soil was sampled from the lakebed of the former lake Texcoco at three locations (Figure S1). At the three locations, three 400-m2 areas were defined. In each area, the soil was sampled 20 times by augering the 0–20 cm layer. The 20 soil samples of each area were pooled separately. As such, nine soil samples were obtained, i.e., from three locations (n = 3) in triplicate (n = 3). The soil samples were taken on ice to the laboratory, 5-mm sieved separately, and then characterised (Table 1). This field-based replication was maintained in the laboratory experiment to avoid pseudoreplication [16].
The particle size distribution was determined by the hydrometer method [17], total organic carbon was measured with a carbon analyzer TOC-VCSN (Shimadzu, Canby, OR, USA), inorganic C, as described by Bundy and Bremner [18], and total nitrogen by the method outlined by Kjeldahl [19]. The water holding capacity was determined by the gravimetric method, EC, as reported by Rhoades et al. [20], and the pH was measured in a suspension sediment-H2O using a glass electrode [21].

2.3. Experimental Design and Microcosms Setup

The aerobic incubation was done, as developed at the soil science department in Rothamsted, e.g., Inubushi et al. [22]. The soil was incubated for 14 days, as previous research with soil of Texcoco [7] had found that the mineralization of 14C-labelled maize residue and its NDF fraction was most accentuated in the first days of an aerobic incubation.
The soil was separately pre-incubated in drums containing 1-L jar with 1 M NaOH to trap evolved CO2 and 1-L jar with distilled water to avoid soil desiccation for a week. After seven days, 15 sub-samples of 25 g from each soil (n = 9) were added separately to 120-mL glass flasks. Five samples were amended with young maize plants, five with the NDF fraction of the young maize plants and five were left unamended. The amount of organic material applied was such that 2 g C kg−1 was applied to soil. The soil of each treatment was mixed, and the glass flasks were placed separately in 1-L glass jars with 10 mL distilled water to avoid desiccation and containing a 25-mL flask with 20 mL 1 M NaOH to trap the evolved CO2. The glass jars were closed airtight and stored in the dark at 22 ± 2 °C (the mean annual temperature of the studied sites) for 14 days. Additionally, 15 flasks without soil, i.e., only containing NaOH solution and water, were incubated also for 14 days. These flasks were used to account for the CO2 trapped from the environment. After one, three, seven, and 14 days, a jar from each soil (n = 3), replicate (n = 3), and treatment (n = 3) were selected at random, opened and the flasks with 1M NaOH removed, and the soil was stored at −20 °C pending DNA extraction. The 25-mL flasks with 1M NaOH were removed from the flasks, closed airtight, and stored until analysed for the CO2 trapped in the 1M NaOH. Additionally, three flasks without soil, but with a 25-mL flask with NaOH and water were opened, and the 25-mL flasks removed, closed airtight and stored. At day 7, all of the remaining flasks with soil or without soil were opened and then aired to avoid anaerobic conditions. After 10 min., all flasks were closed air-tight and then incubated for another seven days.

2.4. DNA Extraction and PCR Amplification of Bacterial 16S rRNA Genes

Metagenomic DNA was extracted with three different techniques twice from 0.5 g soil and pooled. As such, a total of 3 g soil was extracted for DNA per plot (n = 3). Each soil sample was washed with 0.15 M sodium pyrophosphate and 0.15 M phosphate buffer pH 8 to remove the fulvic and humic acids [23]. Three different techniques were then used to extract the DNA from the washed soil. The first method was developed by Valenzuela-Encinas et al. [24] and it consisted in a chemical and thermal shock for cell lysis. The second method, in which cells were lysed enzymatically, was developed by Sambrook and Rusell [25], while the third method used a detergent solution for cell lysis (chemical method), as described by Hoffman and Winston [26].
The V1-V6 region of the 16S rRNA bacterial genes was amplified with 10-pb barcoded primers 8-F (5′-AGA GTT TGA TCI TGG CTC A-3′) and 949-R (5′-CCG TCW ATT KCT TTG AGT T-3′) and containing the A and B 454 FLX adapters [27]. The PCR reactions were done, as previously described by Navarro-Noya et al. [27]. The product of five reactions of each metagenomic DNA sample was pooled to minimise the PCR bias and constituted a single library [28]. All of the pyrosequencing libraries were purified using the DNA Clean & Concentrator purification kit, as recommended by the manufacturer (Zymo Research, Irvine, CA, USA), and quantified using the PicoGreen® dsDNA assay (Invitrogen, Carlsbad, USA) and the NanoDropTM 3300 Fluorospectrometer (Thermo Fisher Scientific Inc., Suwanee, CA, USA). Sequencing was done by Macrogen Inc. (DNA Sequencing Service, Seoul, Korea) using a Roche 454 GS-FLX Plus System (Roche, Mannheim, Germany).

2.5. Analysis of Pyrosequencing Data

The QIIME version 1.9.0 software was used to analyse the pyrosequencing data [29]. The low-quality reads were eliminated from the data sets, i.e., quality score < 25, containing homopolymers > 6, length < 400 nt, and containing errors in primers and barcodes. Operational taxonomic units (OTUs) were determined at 97% similarity level with the UCLUST algorithm [30]. Chimeras were identified and removed from the data sets using Chimera Slayer [31]. The sequence alignments were done against the GreenGenes core set and using representative sequences of each OTU using PyNAST and filtered at a threshold of 75% [32]. Rarefaction was done using the alpha_rarefaction.py command within QIIME v1.9.0 using default settings.
The functional potential of bacterial communities in soil samples were predicted using the phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt v1.1.2) pipeline [33]. The functional profile was conducted using the “Kyoto Encyclopedia of genes and genomes” (KEGG) and genes that were related to the degradation of cellulose, lignin, hemicellulose, and cello-oligosaccharides were analysed [34] (Table S2) using metagenome_contribution.py command. In addition, the functional annotation of prokaryotic taxa v1.2.4 (FAPROTAX) [35] was used to investigate functional pathways in the environment, e.g., C and N cycles.
The bacterial diversity was determined using the equivalent Hill numbers at different q orders (at q = 0, 1, and 2) and they were calculated using the raw count dataset at the genus taxonomic level, as described in Ma and Li [36].

2.6. Statistical Analysis

Statistical analyses were done within the R software v4.0.2. [37]. A one-way ANOVA with Tukey post hoc analysis was used to determine significant differences in soil physicochemical characteristics (p < 0.05). Heatmaps of the relative abundance of the bacterial groups were constructed with the pheatmap package [38]. The ALDEx2 package v1.21.1. was used to transform the sequence counts data using the centered log-ratio (clr) transform test returned by the aldex.clr argument [39] prior to ordination analysis. Principal component analysis (PCA) was used to explore the effect of treatment on the bacterial groups using FactoMineR package v2.3 [40]. The permutational multivariate analyses of variance (perMANOVA) test was used to determine the effect of treatments (unamended soil or soil amended with young maize plants or its NDF fraction), soil electrolytic conductivity value (1.9 dS m−1, 17.3 dS m−1 and 33.4 dS m−1), and incubation time (one, three, seven, 14 days) using Vegan v2.5 [41]. The non-parametric Kruskal–Wallis test with Benjamini–Hochberg corrected p value (aldex.kw argument within ALDEx2 package) was used to determine the effect of electrolytic conductivity (EC) value and soil treatment on the bacterial groups using clr-transformed data. The differential abundance analysis between treatments (soil amended with young maize plants or its NDF) when compared to the unamended control soil was done with DESeq2 v1.28.1 package [42]. Only bacterial groups with assigned reads counts >10 were considered for differential abundance analysis with DESeq2.

3. Results

3.1. Carbon Mineralization

The application of young maize plants increased the emitted CO2 in each soil, but not when the NDF fraction was added (Figure S2). After 14 days, the CO2 that was emitted in the young maize plants-amended soil was significantly higher in soil with EC 1.9 dS m−1 than in the other two soils (p < 0.05).

3.2. Sequencing Results and Bacterial Diversity

Overall, 369,016 good quality sequences were retrieved from the soil representing 8478 OTUs. The number of sequences retrieved was sufficient, as the rarefication curves were asymptotic (Figure S3). As such, an increase in the number of sequences analysed would only yield a limited number of OTUs more. The soil of the former lakebed was characterised by a large variation in the number of bacterial groups at different taxonomical levels. Overall, 31 different phyla, 93 classes, 142 orders, and 194 genera were detected in the soil.
At the onset of the experiment and after 14 days, the effective numbers of bacterial genera q = 0 (species richness, 0D) and q = 1 (typical genera, 1D) in unamended soil decreased with increased EC (Figure S4). The application of young maize plants or the NDF fraction decreased the 0D and 1D value with the lowest values being found in the NDF fraction amended soil. The soil with the highest EC had the highest 2D in the unamended soil and 2D decreased in all treatments over time.

3.3. Bacterial Community Structure in the Unamended Soil

At the onset of the experiment, the unamended soil with EC 1.9 dS m−1 was dominated by the bacterial phyla Proteobacteria (55.44 ± 1.49% relative abundance), Actinobacteria (12.61 ± 1.87%), and the genera Halomonas (15.41 ± 13.22) and Bacillus (1.95 ± 0.73) (Figure 1 and Figure 2). In the unamended soil with EC 17.3 dS m−1, Proteobacteria (32.04 ± 22.04%), Firmicutes (15.21 ± 12.35%), Halomonas (9.27 ± 8.59%), and Alkaliphilus (9.24 ± 9.13%) were dominant phyla and genera. The unamended soil with EC 33.4 dS m−1 was dominated by Proteobacteria (40.95 ± 20.00%) and Actinobacteria (15.76 ± 8.12%), and the genera Halomonas (5.92 ± 1.81) and KSA1 (4.29 ± 4.29%).
The PCA clearly separated the different unamended soils and clustered soil samples by EC (Figure 3a–c). The perMANOVA analysis confirmed that soil had a significant effect on the bacterial community structure, but not incubation time or the interaction between incubation time and soil (p < 0.05) (Table 2). The differential abundance analysis with aldex.kw showed that a large number of bacterial genera were significantly affected by soil, e.g., Prauseria, Halomonas, and KSA1 (Table S3).

3.4. Bacterial Community Structure in the Organic Material Amended Soil

The application of young maize plants and their NDF fraction altered the soil bacterial community structure (Figure 4). The PCA clearly separated the maize that was amended from the unamended soil was the most accentuated when considering all OTUs (Figure 4g–i). The perMANOVA analysis showed that the application of organic material had a significant effect on the bacterial community structure, irrespective of soil or taxonomic level considered (Table 3). Time only affected the bacterial community structure when all bacterial groups assigned up to the taxonomic level of genus were considered. The differential abundance analysis with aldex.kw showed that a large number of bacterial genera were significantly affected by organic material application with the largest number in soil with highest EC and the least in soil with the lowest EC (Table 4).
A sequence of bacterial genera was significantly enriched by the application of young maize plants and the NDF fraction when compared to the unamended soil (p < 0.05) (Figure 5 and Figure 6). Members of Bacillus were enriched in the maize amended soil with high EC at day 1 and Prauseria on day 3, while phylotypes to Glycomyces in soil with low and medium EC on day 7 and Streptomyces on day 14 (Figure 7a). In the NDF amended soil, members of Marinobacter were enriched on day 1, Variovorax on day 3, and Nesternkonia and Halomonas on day 7 (Figure 7b).
The PCA separated the soils with different EC when amended with young maize plants and its NDF fraction. The bacterial community in the NDF-amended soil with EC 1.9 dS m−1 was different from the one in soil with EC 33.4 dS m−1 when considering all of the bacterial groups assigned up to the taxonomic level of genus and when all the OTUs were considered (Figure S5a–c). Consequently, the perMANOVA analysis showed that soil had a significant effect on the bacterial community structure at the OTUs level when amended with NDF, but not incubation time (p < 0.05) (Table S4). The application of NDF to soil significantly affected members within Xylanimicrobium (p < 0.05) (Table S3).
The application of young maize plants clearly separated the different soils, as visualized by the PCA while considering all bacterial groups that were assigned up to the taxonomic level of genus and OTUs, but not considering all phyla (Figure S5d–f). As such, the perMANOVA analysis (Table S4) showed that soil had a strong significant effect on the bacterial community structure (p < 0.001). The analysis with ALDEx.kw showed that the relative abundance of a wide range of bacterial genera was significantly different between the soils that were amended with young maize plants, e.g., KSA1, Bacillus, Alkaliphilus, and Halomonas (Table S3).
The PCA considering all soils and treatments clearly separated the soils, while the effect of organic material on the bacterial community structure was smaller (Figure S6a,b). The aldex.kw analysis showed that soil had a highly significant effect on a larger number of bacterial groups than the application of young maize plants and its NDF fraction (p < 0.05) (Table S5).

3.5. Bacterial Functional Prediction Analysis

Proteobacteria showed the highest potential gene contribution to cellulose degradation (e.g., K01188, K01179), lignin degradation (e.g., K00428, K00432, K03863), hemicellulose degradation (e.g., K01181, K01198, K01206), and cello-oligosaccharides degradation (e.g., K01194, K11200) (Figure S7a). Actinobacteria and Firmicutes were the second most important gene contributors, being mainly related to cellulose, hemicellulose, and cello-oligosaccharides degradation. Prauseria and Marinimicrobium contained potential functions that were related to cellulose (K01225 and K01199) and hemicellulose degradation (K01218 and K01224) (Figure S7b). The largest number of potential genes was detected in soil with low EC and the least in soil with medium EC. The FAPROTAX analysis indicated that the number of potential metabolic functions related to the carbon and nitrogen cycles was larger in soil with low EC than in the other soils (Figure S8). Functions that were related to cellulose and lignin degradation were found in the three soils, i.e., cellulolysis, xylanolysis, and chitinolysis.

4. Discussion

Salinity affects the soil microbial communities due to osmotic pressure [43], low nutrient content [44], poor soil structure [45], and/or high pH [46]. The application of organic matter improves soil physical properties and increases the availability of nutrients [47]. Different types of organic material have been applied to saline soil to study how they might affect soil characteristics [48]. The application of organic material generally increased N, P, and K availability [49], while pH [50] and EC decreased [51]. Soil Bacteria play an important role in the degradation of organic material, so their involvement in the degradation of young maize plants and NDF fraction were studied in three soils from the former lake of Texcoco with a gradient of salinity and alkalinity. The NDF fraction of the maize plants was included in this study, as it might indicate which bacteria can degrade cellulose in alkaline saline soils.

4.1. Bacterial Community in Unamended Soil with Varying pH and EC

The bacterial community structure was clearly different in the three different soils of the former lake Texcoco. It can be assumed that soil characteristics, such as pH, particle size distribution, organic matter content, and EC, affect the relative abundance of the different bacterial groups. Although the soil bacterial community in Texcoco was different due to pH and EC, Proteobacteria and Actinobacteria both dominated this extreme environment. Keshri et al. [52] reported that Proteobacteria and Actinobacteria were also dominant in a soil with EC 23.7 dS m−1 and pH 9.1. Some members of the Proteobacteria are dominant in saline bare land, sewage-impacted, and lacustrine soil, as they thrive in high salinity and high pH environments [53,54]. In this study, Halomonas (Gammaproteobacteria) was the dominant genus in unamended alkaline saline soil. Phylotypes belonging to this genus have been found in a hypersaline lakebed [55], solonchak [56], and saline desert soils [57]. Previously, Oueriaghli et al. [58] studied the diversity and distribution of Halomonas in Rambla Salada, a hypersaline environment in Spain, and found higher diversity in soil with higher salinity.
Members of Actinobacteria, the second dominant phylum, have been reported to tolerate salinity, high and low temperatures, and low nutrient content [59]. For instance, Prauseria comprise various haloterant members [11,60]. In this study, the relative abundance of Prauseria increased from 0.07 ± 0.15% in soil with low EC (1.9 dS m−1) to 1.20 ± 0.47% in the soil with high EC (33.4 dS m−1). The members of KSA1 (Bacteroidetes) were also enriched in soil with high salinity when compared to the soil with a low EC. Members of KSA1 have been identified in a maar lakebed high pH and extreme salinity, which indicate a tolerance to these extreme conditions [61]. In contrast, members of Acidobacteria were negatively affected by soil salinity. The negative effect of salinity on members of Acidobacteria has been observed in a saline semi-arid soil [4].
It has to be remembered that not only were salinity and pH different between the soils, but soil organic matter content and particle size distribution also varied, which is known to affect the bacterial community. Soil with high sand content is characterised by its limited capacity to retain water and nutrients, while a soil with high clay content retains them [62]. Additionally, the bacteria are affected differently by the particle size distribution and soil water content [63]. Organic matter affects soil aggregation, aeration, and water movement, but also provides a C substrate and nutrients for microorganisms and plants [64]. Large amounts of easy decomposable organic material in soil favours copiotrophs, while nutrient limited environments enrich oligotrophs [65].

4.2. Bacterial Community Structure in Organic Material Amended Soil

The application of young maize plants or the NDF fraction profoundly changed the soil bacterial community structure. The NDF fraction, mainly (hemi)cellulose and lignin, is more resistant to degradation than the rest of the young maize plants, e.g., easy decomposable carbohydrates and proteins, and promotes lignocellulolytic bacterial groups [66]. In addition, the Texcoco soil is characterised by a low mineral N content [6]. The addition of NDF with a large amount of (hemi)cellulose and lignin and the limited availability of mineral N hindered the rapid assimilation of carbon, which, in turn, favoured some bacterial phylotypes, i.e., Bacillus (Firmicutes), Prauseria (Actinobacteria), Glycomyces (Actinobacteria), and Streptomyces (Actinobacteria).
Members of Actinobacteria, the second most abundant phylum, are involved in the degradation of lignin, cellulose, chitin and starch [67]. The functional prediction with PICRUSt showed that members of Actinobacteria, e.g., Prauseria and Gordonia, were the second most important contributors to cellulose and hemicellulose degradation. Little is known regarding the genus Prauseria. It was previously found to be enriched when young maize plants or its NDF fraction were applied to soil from the former lake Texcoco and might suggest participation in the degradation of lignocellulose [11]. Phylotypes that belong to Gordonia can degrade xenobiotics, environmental pollutants, and natural polymers [68]. Members of Bacilli, i.e., Bacillus, Paenibacillus, and Anaerobacillus were important contributors in the cellulose, hemicellulose, and cello-oligosaccharides degradation process [69,70,71]. Strains of Bacillus produce enzymes, such as cellulases, hemicellulases, and β-glucanases [69,72], whereas some members of Paenibacillus produce glucanases, chitinases, and cellulases that are involved in the degradation of organic material [70]. The enzymatic machinery of these bacterial groups suggests a metabolic specialization and an active participation in the degradation of high complexity C-compounds in the Texcoco soil. Members of Anaerobacillus were identified in hypersaline lakes [71], which indicated that they can thrive in saline environments, such as soil of the former lake Texcoco.
The addition of young maize plants to soil altered the bacterial community differently than when NDF was applied as the “soluble fraction”, i.e., the main component of young maize plants, was removed from the latter. The soluble fraction of plant residue comprises non-polymeric carbohydrates and proteins, and are more rapidly degraded by soil microorganisms [66]. The young maize plants that were applied to soil contained nearly 50% of easily decomposable organic material and had a higher N content than the NDF fraction. As such, young maize plants should enrich more members of bacteria with a copiotroph lifestyle than the NDF fraction, e.g., Marinobacter (Gammaproteobacteria), Variovorax (Betaproteobacteria), Nesterenkonia (Actinobacteria), and Halomonas (Gammaproteobacteria). Interestingly, these three bacterial groups also possess the ability to enhance plant growth [73,74,75].
Although the lignin content in the organic material applied to soil was low (<63 g kg−1 dry plant material), the functional prediction analysis showed that members of Alphaproteobacteria, Gammaproteobacteria, and Deltaproteobacteria were the primary gene contributors of the degradation of lignin, i.e., Halomonas, Methylobacterium and Corallococcus. Whilst Marinimicrobium, Pseudomonas, and Phenylobacterium were involved in the cellulose degradation in the Texcoco amended soils. Members of Halomonas can degrade lignocellulose (e.g., wheat straw) [76], and it is a source of lignocellulolytic haloenzymes [77]; it has also been found in alkaline-saline environments, including the Texcoco soil [78,79]. Methylobacterium is a methylotroph group participating in methane and methanol oxidation [80], as well as in the lignin degradation [81] and Corallococcus member has previously been found in saline-alkaline soils [82]. The members of Marinimicrobium, Phenylobacterium, and Pseudomonas are halotolerant and they possess the enzymatic machinery to degrade cellulose and lignin [83,84]. As such, members of Alphaproteobacteria, Gammaproteobacteria and Betaproteobacteria could be playing a major role in complex organic compounds degradation in alkaline-saline environments, such as the Texcoco soil.
Our results indicated that application of young maize plants or its NDF fraction enriched various groups. However, the extent of their enrichment might depend on other factors than just the application of organic material, e.g., soil edaphic variables. For instance, salinity changed the bacterial community structure in soil, and extreme salinity strongly reduced their diversity [85,86]. Bacterial groups with a known tolerance to soil salinity were enriched when young maize plants and the NDF fraction were applied, e.g., Marinobacter and Prauseria. Bacterial groups, such as Mesorhizobium, Alkalibacterium, Microbacterium, and Hyphomicronium were enriched when young maize plants were applied to soil, which indicates their participation in the degradation of lignocellulolytic material. These genera belong to the three phyla, i.e., Proteobacteria, Actinobacteria, and Firmicutes, often being dominant in saline soils [86].
Furthermore, it must be remembered that other microorganisms actively participate in the degradation of organic material in soil, e.g., fungi. Fungi are capable of metabolizing complex organic molecules, as reported extensively so they play an important role in the degradation of organic material in soil [87]. Further research might include a more comprehensive investigation of soil microbial community, i.e., including fungi, bacterial, protists, and viral community structure, using shotgun metagenomics. The assembly, as well as functional and taxonomical annotation, may increase our knowledge on how the soil microbial community in an extreme alkaline-saline soil responds to organic material input.

5. Conclusions

The soil bacterial community structure was profoundly altered by the application of both young maize plants and its NDF fraction. The application of easily decomposable organic material increased the relative abundance of members within Proteobacteria (mainly Gammaproteobacteria, e.g., Acinetobacter and Pseudomonas), Firmicutes (e.g., Alkaliphilus and Paenibacillus), and Actinobacteria (mainly Prauseria) when compared to the unamended soil. Young maize plants induced larger changes in soil bacterial community than the application of the NDF fraction, as the young maize plants contained easily decomposable organic material in the “soluble fraction”, which was absent in the NDF fractions. The NDF fraction mostly contained (hemi)cellulose and lignin, which are more difficult to mineralize. The soil bacterial functional prediction confirmed that, irrespective of the high salinity and pH in soil of the former lake Texcoco, the application of organic material increased the relative abundance of bacterial groups with the capacity to mineralize high and complex C compounds, e.g., lignin and (hemi)cellulose.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/microorganisms9061297/s1, Figure S1: Schematic overview of the soil sampling procedure, Figure S2: Cumulative emission of CO2 (mg C kg−1 dry soil) from unamended soil with EC 1.9 dS m−1 (□), unamended soil with EC 17.3 dS m−1 (Δ), unamended soil with EC 33.4 dS m−1 (○), neutral detergent fibre fraction amended soil with EC 1.9 dS m−1 (■), neutral detergent fibre fraction amended soil with EC 17.3 dS m−1 (▲), neutral detergent fibre fraction amended soil with EC 33.4 dS m−1 (●), young maize plants amended soil with EC 1.9 dS m−1 (■), young maize plants amended soil with EC 33.4 dS m−1 (▲), young maize plants amended soil with EC 33.4 dS m−1 (●) incubated aerobically at 22 ± 2 °C for 14 days, Figure S3: Rarefaction curve or the relation between the number of sequences analysed and operational taxonomic units (OTUs) obtained. Unamended soil with EC 1.9 dS m−1 (□), unamended soil with EC 17.3 dS m−1 (Δ), unamended soil with EC 33.4 dS m−1 (○), neutral detergent fibre fraction amended soil with EC 1.9 dS m−1 (■), neutral detergent fibre fraction amended soil with EC 17.3 dS m−1 (▲), neutral detergent fibre fraction amended soil with EC 33.4 dS m−1 (●), young maize plants amended soil with EC 1.9 dS m−1 (■), young maize plants amended soil with EC 33.4 dS m−1 (▲), young maize plants amended soil with EC 33.4 dS m−1 (●), Figure S4: (a) Boxplot of the alfa diversity of the bacterial communities based on the equivalent Hill numbers at different q orders (at q = 0, 1 and 2) in the unamended soil with electrolytic conductivity (EC) 1.9 dS m−1 (low), EC 17.3 dS m−1 (medium) and EC 33.4 dS m−1 (high) at the onset of the experiment, and (b) changes in alfa diversity in the unamended soil with EC 1.9 dS m−1 (□), unamended soil with EC 17.3 dS m−1 (Δ), unamended soil with EC 33.4 dS m−1 (○), neutral detergent fibre fraction amended soil with EC 1.9 dS m−1 (■), neutral detergent fibre fraction amended soil with EC 17.3 dS m−1 (▲), neutral detergent fibre fraction amended soil with EC 33.4 dS m−1 (●), young maize plants amended soil with EC 1.9 dS m−1 (■), young maize plants amended soil with EC 33.4 dS m−1 (▲), young maize plants amended soil with EC 33.4 dS m−1 (●) incubated aerobically at 22 ± 2 °C for 14 days, Figure S5: Principal component analysis (PCA) with the centered log-ratio transformed counts of bacterial groups in soil with electrolytic conductivity (EC) 1.9 dS m−1 (■), EC 17.3 dS m−1 (■) and EC 33.4 dS m−1 (■) amended with the neutral detergent fibre (NDF) fraction at the taxonomic level of (a) all bacterial phyla, (b) all bacterial genera and (c) all bacterial OTUs, and PCA with the centered log-ratio transformed counts of bacterial groups in soil with electrolytic conductivity (EC) 1.9 dS m−1 (■), EC 17.3 dS m−1 (■) and EC 33.4 dS m−1 (■) amended with young maize plants at the taxonomic level of (d) all bacterial phyla, (e) all bacterial genera, and (f) all bacterial OTUs, incubated aerobically at 22 ± 2 °C for 14 days, Figure S6: (a) Principal component analysis (PCA) with clr-transformed count numbers of all phyla, all bacterial groups assigned up to the taxonomic level of genus and all operational taxonomic units (OTUs) in unamended soil with EC 1.9 dS m−1 (■), unamended soil with EC 17.3 dS m−1 (■), unamended soil with EC 33.4 dS m−1 (■), neutral detergent fibre fraction amended soil with EC 1.9 dS m−1 (●), neutral detergent fibre fraction amended soil with EC 17.3 dS m−1 (●), neutral detergent fibre fraction amended soil with EC 33.4 dS m−1 (●), young maize plants amended soil with EC 1.9 dS m−1 (▲), young maize plants amended soil with EC 17.3 dS m−1 (▲), young maize plants amended soil with EC 33.4 dS m−1 (▲) incubated aerobically at 22 ± 2 °C for 14 days and (b) the effect of treatment (left unamended, application of young maize plants or their NDF fraction), time and their interaction on the bacterial community structure with the permutational multivariate analyses of variance (perMANOVA) test, Figure S7: Functional prediction analysis with PICRUSt of genes involved in the cellulose, hemicellulose, lignin and cello-oligosaccharides degradation of bacterial groups assigned up to the taxonomic level of (a) phylum and (b) genus in soil of the former Lake of Texcoco aerobically incubated for 14 days. UN: unamended soil, YMR: young maize plants amended soil, NDF: neutral detergent fibre amended soil. Low: soil EC 1.9 dS m−1, medium: soil EC 17.3 dS m−1 and high: soil EC 33.4 dS m−1. Bacterial groups with gene contribution (relative abundance) > 0.5% are shown, Figure S8: Functional annotation of prokaryotic taxa (FAPROTAX) analysis showing functions that are related to (a) carbon and (b) nitrogen cycle in soil of the former lake of Texcoco. Shapes contrast different treatment: unamended soil (○), soil amended with neutral detergent fibre (NDF) (■) and soil amended with young maize plants (▲), Table S1. Characteristics of organic material used in the aerobic incubation experiment, Table S2. List of KOs used for the analysis of genes involved in cellulose, lignin, hemicellulose, and cello-oligosaccharides degradation, Table S3. Effect of soil (EC: 1.9 dS−1 (low), 17.3 dS−1 (medium), 33.4 dS−1 (high)) on bacterial phyla and genera in the unamended soil, soil amended with NDF and soil amended with young maize plants using a compositional approach, i.e., analysis of differential abundance taking sample variation into account ALDEx2 package [39], Table S4. Effect of soil (EC 1.9 dS m−1, EC 17.3 dS m−1, 33.4 dS m−1), time (one, three, seven, and 14 days of aerobic incubation) and their interaction on the soil bacterial community in the young maize plants and neutral detergent fibre (NDF) amended soil using a perMANOVA analysis with the sequence counts converted to centeredlog-ratio transformation with ALDEx2 package [39], Table S5. Effect of treatment (unamended soil, amended soil with young maize plants or its NDF) and effect of soil (EC: 1.9 dS m−1, 17.3 dS m−1, 33.4 dS m−1) on bacterial phyla or genera using a compositional approach, i.e., analysis of differential abundance taking sample variation into account (ALDEx2 package [39]).

Author Contributions

Conceptualization, V.P.-H.; Data curation, M.H.-G. and Y.E.N.-N.; Formal analysis, V.P.-H., M.H.-G., Y.E.N.-N. and L.D.; Investigation, V.P.-H., M.H.-G., E.M.R.-T. and L.D.; Methodology, Y.E.N.-N., E.M.R.-T. and L.D.; Project administration, M.L.-G. and L.D.; Resources, L.D.; Supervision, M.L.-G.; Visualization, V.P.-H. and M.H.-G.; Writing—original draft, V.P.-H., E.M.R.-T. and L.D.; Writing—review & editing, V.P.-H., M.H.-G., M.L.-G., Y.E.N.-N., E.M.R.-T. and L.D. All authors have read and agreed to the published version of the manuscript.

Funding

V.P.-H. and M.H.-G. received grant-aided support from “Consejo Nacional de Ciencia y Tecnología” (CONACyT, México) with grant number [304568] and [306905], respectively.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Sequence data have been deposited in the NCBI Sequence Read Archive (SRA) under accession refence PRJNA722365.

Acknowledgments

The authors thank Comisión Nacional del Agua (CNA) for access to the former Lake Texcoco.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Shahid, S.A.; Zaman, M.; Heng, L. Soil salinity: Historical perspectives and a world overview of the problem. In Guideline for Salinity Assessment, Mitigation and Adaptation Using Nuclear and Related Techniques; Zaman, M., Shahid, S.A., Heng, L., Eds.; Springer International Publishing: Cham, Switzerland, 2018; pp. 43–53. ISBN 978-3-319-96190-3. [Google Scholar]
  2. Edelstein, M.; Plaut, Z.; Ben-Hur, M. Water salinity and sodicity effects on soil structure and hydraulic properties. Adv. Hortic. Sci. 2010, 24, 154–160. [Google Scholar]
  3. Bidalia, A.; Vikram, K.; Yamal, G.; Rao, K.S. Effect of salinity on soil nutrients and plant health. In Salt Stress, Microbes, and Plant Interactions: Causes and Solution; Akhtar, M.S., Ed.; Springer: Singapore, 2019; pp. 273–297. ISBN 978-981-13-8801-9. [Google Scholar]
  4. Canfora, L.; Bacci, G.; Pinzari, F.; Lo Papa, G.; Dazzi, C.; Benedetti, A. Salinity and bacterial diversity: To what extent does the concentration of salt affect the bacterial community in a saline soil? PLoS ONE 2014, 9, e106662. [Google Scholar] [CrossRef] [Green Version]
  5. Bui, E.N. Soil salinity: A neglected factor in plant ecology and biogeography. J. Arid Environ. 2013, 92, 14–25. [Google Scholar] [CrossRef]
  6. Dendooven, L.; Alcántara-Hernández, R.J.; Valenzuela-Encinas, C.; Luna-Guido, M.; Perez-Guevara, F.; Marsch, R. Dynamics of carbon and nitrogen in an extreme alkaline saline soil: A review. Soil Biol. Biochem. 2010, 42, 865–877. [Google Scholar] [CrossRef]
  7. Luna-Guido, M.L.; Vega-Estrada, J.; Ponce-Mendoza, A.; Hernandez-Hernandez, H.; Montes-Horcasitas, M.-C.; Vaca-Mier, M.; Dendooven, L. Mineralization of 14C-labelled maize in alkaline saline soils. Plant Soil 2003, 250, 29–38. [Google Scholar] [CrossRef]
  8. Ruiz-Romero, E.; Alcántara-Hernández, R.; Cruz-Mondragon, C.; Marsch, R.; Luna-Guido, M.L.; Dendooven, L. Denitrification in extreme alkaline saline soils of the former lake Texcoco. Plant Soil 2009, 319, 247–257. [Google Scholar] [CrossRef]
  9. Martínez-Olivas, M.A.; Jiménez-Bueno, N.G.; Hernández-García, J.A.; Fusaro, C.; Luna-Guido, M.; Navarro-Noya, Y.E.; Dendooven, L. Bacterial and archaeal spatial distribution and its environmental drivers in an extremely haloalkaline soil at the landscape scale. PeerJ 2019, 7, e6127. [Google Scholar] [CrossRef]
  10. Lopez-Ramirez, M.P.; Sanchez-Lopez, K.B.; Sarria-Guzman, Y.; Bello-Lopez, J.M.; Cano-Garcia, V.L.; Ruiz-Valdiviezo, V.M.; Dendooven, L. Haloalkalophilic cellulose-degrading bacteria isolated from an alkaline saline soil. J. Pure Appl. Microbiol. 2015, 9, 2879–2886. [Google Scholar]
  11. De León-Lorenzana, A.S.; Delgado-Balbuena, L.; Domínguez-Mendoza, C.A.; Navarro-Noya, Y.E.; Luna-Guido, M.; Dendooven, L. Soil salinity controls relative abundance of specific bacterial groups involved in the decomposition of maize plant residues. Front. Ecol. Evol. 2018, 6, 51. [Google Scholar] [CrossRef] [Green Version]
  12. Ramirez-Villanueva, D.A.; Bello-López, J.M.; Navarro-Noya, Y.E.; Luna-Guido, M.; Verhulst, N.; Govaerts, B.; Dendooven, L. Bacterial community structure in maize residue amended soil with contrasting management practices. Appl. Soil Ecol. 2015, 90, 49–59. [Google Scholar] [CrossRef]
  13. Steiner, A.A. A universal method for preparing nutrient solutions of a certain desired composition. Plant Soil 1961, 15, 134–154. [Google Scholar] [CrossRef] [Green Version]
  14. Van Soest, P.J. Use of detergents in the analysis of fibrous feeds. II. A rapid method for the determination of fiber and lignin. J. Assoc. Off. Agric. Chem. 1963, 46, 829–835. [Google Scholar]
  15. Van Soest, P.J.; Wine, R.H. Use of detergents in the analysis of fibrous feeds. IV. Determination of plant cell-wall constituents. J. AOAC Int. 1967, 50, 50–55. [Google Scholar] [CrossRef]
  16. Heffner, R.A.; Butler, M.J.; Reilly, C.K. Pseudoreplication revisited. Ecology 1996, 77, 2558–2562. [Google Scholar] [CrossRef]
  17. Gee, G.W.; Bauder, J.W. Particle-size Analysis. In Methods of Soil Analysis: Part 1—Physical and Mineralogical Methods; Klute, A., Ed.; SSSA Book Series SV—5.1; Soil Science Society of America: Madison, WI, USA; American Society of Agronomy: Madison, WI, USA, 1972; pp. 383–411. ISBN 978-0-89118-864-3. [Google Scholar]
  18. Bundy, L.G.; Bremner, J.M. A simple titrimetric method for determination of inorganic carbon in soils. Soil Sci. Soc. Am. J. 1972, 36, 273–275. [Google Scholar] [CrossRef]
  19. Bremner, J.M. Nitrogen-Total. In Methods of Soil Analysis Part 3—Chemical Methods; Sparks, D.L., Page, A.L., Helmke, P.A., Loeppert, R.H., Soltanpour, P.N., Tabatabai, M.A., Johnston, C.T., Sumner, M.E., Eds.; SSSA Book Series SV—5.3; Soil Science Society of America: Madison, WI, USA; American Society of Agronomy: Madison, WI, USA, 1996; pp. 1085–1121. ISBN 978-0-89118-866-7. [Google Scholar]
  20. Rhoades, J.D. Salinity: Electrical Conductivity and Total Dissolved Solids. In Methods of Soil Analysis Part 3—Chemical Methods; Sparks, D.L., Page, A.L., Helmke, P.A., Loeppert, R.H., Soltanpour, P.N., Tabatabai, M.A., Johnston, C.T., Sumner, M.E., Eds.; SSSA Book Series SV—5.3; Soil Science Society of America: Madison, WI, USA; American Society of Agronomy: Madison, WI, USA, 1996; pp. 417–435. ISBN 978-0-89118-866-7. [Google Scholar]
  21. Thomas, G.W. Soil pH and Soil Acidity. In Methods of Soil Analysis Part 3—Chemical Methods; Sparks, D.L., Page, A.L., Helmke, P.A., Loeppert, R.H., Soltanpour, P.N., Tabatabai, M.A., Johnston, C.T., Sumner, M.E., Eds.; SSSA Book Series SV—5.3; Soil Science Society of America: Madison, WI, USA; American Society of Agronomy: Madison, WI, USA, 1996; pp. 475–490. ISBN 978-0-89118-866-7. [Google Scholar]
  22. Inubushi, K.; Brookes, P.C.; Jenkinson, D.S. Soil microbial biomass C, N and ninhydrin-N in aerobic and anaerobic soils measured by the fumigation-extraction method. Soil Biol. Biochem. 1991, 23, 737–741. [Google Scholar] [CrossRef]
  23. Ceja-Navarro, J.A.; Rivera, F.N.; Patiño-Zúñiga, L.; Govaerts, B.; Marsch, R.; Vila-Sanjurjo, A.; Dendooven, L. Molecular characterization of soil bacterial communities in contrasting zero tillage systems. Plant Soil 2010, 329, 127–137. [Google Scholar] [CrossRef]
  24. Valenzuela-Encinas, C.; Neria-González, I.; Alcántara-Hernández, R.J.; Enríquez-Aragón, J.A.; Estrada-Alvarado, I.; Hernández-Rodríguez, C.; Dendooven, L.; Marsch, R. Phylogenetic analysis of the archaeal community in an alkaline-saline soil of the former lake Texcoco (Mexico). Extremophiles 2008, 12, 247–254. [Google Scholar] [CrossRef] [PubMed]
  25. Sambrook, J.; Russell, D. Plasmid and their usefulness in molecular cloning. In Molecular Cloning, a Laboratory Manual; Cold Spring Harbor Laboratory: New York, NY, USA, 2001; Volume 1, pp. 1–31. ISBN 978-0879695774. [Google Scholar]
  26. Hoffman, C.S.; Winston, F. A ten-minute DNA preparation from yeast efficiently releases autonomous plasmids for transformaion of Escherichia coli. Gene 1987, 57, 267–272. [Google Scholar] [CrossRef]
  27. Navarro-Noya, Y.E.; Suárez-Arriaga, M.C.; Rojas-Valdes, A.; Montoya-Ciriaco, N.M.; Gómez-Acata, S.; Fernández-Luqueño, F.; Dendooven, L. Pyrosequencing analysis of the bacterial community in drinking water wells. Microb. Ecol. 2013, 66, 19–29. [Google Scholar] [CrossRef]
  28. Acinas, S.G.; Klepac-Ceraj, V.; Hunt, D.E.; Pharino, C.; Ceraj, I.; Distel, D.L.; Polz, M.F. Fine-scale phylogenetic architecture of a complex bacterial community. Nature 2004, 430, 551–554. [Google Scholar] [CrossRef] [PubMed]
  29. Caporaso, J.G.; Kuczynski, J.; Stombaugh, J.; Bittinger, K.; Bushman, F.D.; Costello, E.K.; Fierer, N.; Peña, A.G.; Goodrich, J.K.; Gordon, J.I.; et al. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 2010, 7, 335–336. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  30. Edgar, R.C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 2010, 26, 2460–2461. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  31. Haas, B.J.; Gevers, D.; Earl, A.M.; Feldgarden, M.; Ward, D.V.; Giannoukos, G.; Ciulla, D.; Tabbaa, D.; Highlander, S.K.; Sodergren, E.; et al. Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons. Genome Res. 2011, 21, 494–504. [Google Scholar] [CrossRef] [Green Version]
  32. Caporaso, J.G.; Bittinger, K.; Bushman, F.D.; DeSantis, T.Z.; Andersen, G.L.; Knight, R. PyNAST: A flexible tool for aligning sequences to a template alignment. Bioinformatics 2010, 26, 266–267. [Google Scholar] [CrossRef] [Green Version]
  33. Langille, M.G.I.; Zaneveld, J.; Caporaso, J.G.; McDonald, D.; Knights, D.; Reyes, J.A.; Clemente, J.C.; Burkepile, D.E.; Vega Thurber, R.L.; Knight, R.; et al. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat. Biotechnol. 2013, 31, 814–821. [Google Scholar] [CrossRef] [PubMed]
  34. Ceballos, S.J.; Yu, C.; Claypool, J.T.; Singer, S.W.; Simmons, B.A.; Thelen, M.P.; Simmons, C.W.; VanderGheynst, J.S. Development and characterization of a thermophilic, lignin degrading microbiota. Process Biochem. 2017, 63, 193–203. [Google Scholar] [CrossRef]
  35. Louca, S.; Parfrey, L.W.; Doebeli, M. Decoupling function and taxonomy in the global ocean microbiome. Science 2016, 353, 1272–1277. [Google Scholar] [CrossRef]
  36. Ma, Z.; Li, L. Measuring metagenome diversity and similarity with Hill numbers. Mol. Ecol. Resour. 2018, 18, 1339–1355. [Google Scholar] [CrossRef]
  37. R Core Team. R: A Language and Environment for Statistical Computing (Versión 4.0.2); R Foundation for Statistical Computing: Vienna, Austria, 2000; Available online: https//www.R-project.org (accessed on 30 July 2020).
  38. Kolde, R. Pheatmap: Pretty Heatmaps. 2018. Available online: https//CRAN.R-project.org/package=pheatmap (accessed on 30 July 2020).
  39. Gloor, G.; Fernandes, A.; Macklaim, J.; Albert, A.; Links, M.; Quinn, T.; Wu, J.R.; Wong, R.G.; Lieng, B. ALDEx2: Analysis of Differential Abundance Taking Sample Variation into Account; Bioconductor: Seattle, WA, USA, 2020. [Google Scholar]
  40. Husson, F.; Josse, J.; Le, S.; Mazet, J.; Husson, M.F. Package ‘FactoMineR’. 2020. Available online: https://CRAN.R-project.org/package=FactoMineR (accessed on 30 July 2020).
  41. Oksanen, J.; Blanchet, F.G.; Kindt, R.; Legendre, P.; Minchin, P.R.; O’Hara, R.B.; Simpson, G.L.; Solymos, P.; Stevens, M.H.H.; Wagner, H. Package ‘Vegan.’ Community Ecol. Package. Version 2.5; 2020; pp. 1–295. [Google Scholar]
  42. Love, M.I.; Huber, W.; Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014, 15, 550. [Google Scholar] [CrossRef] [Green Version]
  43. Yan, N.; Marschner, P.; Cao, W.; Zuo, C.; Qin, W. Influence of salinity and water content on soil microorganisms. Int. Soil Water Conserv. Res. 2015, 3, 316–323. [Google Scholar] [CrossRef] [Green Version]
  44. Rengasamy, P. Transient salinity and subsoil constraints to dryland farming in Australian sodic soils: An overview. Aust. J. Exp. Agric. 2002, 42, 351–361. [Google Scholar] [CrossRef]
  45. Sparks, D.L. (Ed.) The chemistry of saline and sodic soils. In Environmental Soil Chemistry, 2nd ed.; Academic Press: Burlington, VT, USA, 2003; pp. 285–300. ISBN 978-0-12-656446-4. [Google Scholar]
  46. Rengasamy, P. Soil processes affecting crop production in salt-affected soils. Funct. Plant Biol. 2010, 37, 613–620. [Google Scholar] [CrossRef]
  47. Fageria, N.K. Role of soil organic matter in maintaining sustainability of cropping systems. Commun. Soil Sci. Plant Anal. 2012, 43, 2063–2113. [Google Scholar] [CrossRef]
  48. Leogrande, R.; Vitti, C. Use of organic amendments to reclaim saline and sodic soils: A review. Arid Land Res. Manag. 2019, 33, 1–21. [Google Scholar] [CrossRef]
  49. Wang, L.; Sun, X.; Li, S.; Zhang, T.; Zhang, W.; Zhai, P. Application of organic amendments to a coastal saline soil in North China: Effects on soil physical and chemical properties and tree growth. PLoS ONE 2014, 9, e89185. [Google Scholar]
  50. Lakhdar, A.; Rabhi, M.; Ghnaya, T.; Montemurro, F.; Jedidi, N.; Abdelly, C. Effectiveness of compost use in salt-affected soil. J. Hazard. Mater. 2009, 171, 29–37. [Google Scholar] [CrossRef]
  51. Zhang, T.; Wang, T.; Liu, K.S.; Wang, L.; Wang, K.; Zhou, Y. Effects of different amendments for the reclamation of coastal saline soil on soil nutrient dynamics and electrical conductivity responses. Agric. Water Manag. 2015, 159, 115–122. [Google Scholar] [CrossRef]
  52. Keshri, J.; Mishra, A.; Jha, B. Microbial population index and community structure in saline–alkaline soil using gene targeted metagenomics. Microbiol. Res. 2013, 168, 165–173. [Google Scholar] [CrossRef]
  53. Mhete, M.; Eze, P.N.; Rahube, T.O.; Akinyemi, F.O. Soil properties influence bacterial abundance and diversity under different land-use regimes in semi-arid environments. Sci. Afr. 2020, 7, e00246. [Google Scholar] [CrossRef]
  54. Rath, K.M.; Fierer, N.; Murphy, D.V.; Rousk, J. Linking bacterial community composition to soil salinity along environmental gradients. ISME J. 2019, 13, 836–846. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  55. Zhao, S.; Liu, J.-J.; Banerjee, S.; Zhou, N.; Zhao, Z.-Y.; Zhang, K.; Tian, C.-Y. Soil pH is equally important as salinity in shaping bacterial communities in saline soils under halophytic vegetation. Sci. Rep. 2018, 8, 4550. [Google Scholar] [CrossRef] [PubMed]
  56. Begmatov, S.A.; Selitskaya, O.V.; Vasileva, L.V.; Berestovskaja, Y.Y.; Manucharova, N.A.; Drenova, N. V Morphophysiological features of some cultivable bacteria from saline soils of the aral sea region. Eurasian Soil Sci. 2020, 53, 90–96. [Google Scholar] [CrossRef]
  57. Kearl, J.; McNary, C.; Lowman, J.S.; Mei, C.; Aanderud, Z.T.; Smith, S.T.; West, J.; Colton, E.; Hamson, M.; Nielsen, B.L. Salt-tolerant halophyte rhizosphere bacteria stimulate growth of alfalfa in salty soil. Front. Microbiol. 2019, 10, 1849. [Google Scholar] [CrossRef] [Green Version]
  58. Oueriaghli, N.; González-Domenech, C.M.; Martínez-Checa, F.; Muyzer, G.; Ventosa, A.; Quesada, E.; Béjar, V. Diversity and distribution of Halomonas in Rambla Salada, a hypersaline environment in the southeast of Spain. FEMS Microbiol. Ecol. 2014, 87, 460–474. [Google Scholar] [CrossRef] [Green Version]
  59. Bull, A.T. Extremophiles Handbook; Horikoshi, K., Ed.; Springer: Tokyo, Japan, 2011; pp. 1203–1240. ISBN 978-4-431-53898-1. [Google Scholar]
  60. Gohel, S.D.; Singh, S.P. Molecular Phylogeny and diversity of the salt-tolerant alkaliphilic Actinobacteria inhabiting coastal Gujarat, India. Geomicrobiol. J. 2018, 35, 775–789. [Google Scholar] [CrossRef]
  61. Ibarra-Sánchez, C.L.; Prince, L.; Aguirre-Noyola, J.L.; Sánchez-Cerda, K.E.; Navaro-Noya, Y.E.; Luna-Guido, M.; Conde-Barajas, E.; Dendooven, L.; Gomez-Acata, E.S. The microbial community in an alkaline saline sediment of a former maar lake bed. J. Soils Sediments 2020, 20, 542–555. [Google Scholar] [CrossRef]
  62. Osman, K.T. Physical Properties of Soil. In Soils Principles, Properties and Management; Osman, K.T., Ed.; Springer: Dordrecht, The Netherlands, 2013; pp. 49–65. ISBN 978-94-007-5663-2. [Google Scholar]
  63. Wolf, A.B.; Vos, M.; de Boer, W.; Kowalchuk, G.A. Impact of matric potential and pore size distribution on growth dynamics of filamentous and non-filamentous soil Bacteria. PLoS ONE 2014, 8, e83661. [Google Scholar] [CrossRef] [Green Version]
  64. Osman, K.T. Soil Organic Matter. In Soils Principles, Properties and Management; Osman, K.T., Ed.; Springer: Dordrecht, The Netherlands, 2013; pp. 89–96. ISBN 978-94-007-5663-2. [Google Scholar]
  65. Schostag, M.; Priemé, A.; Jacquiod, S.; Russel, J.; Ekelund, F.; Jacobsen, C.S. Bacterial and protozoan dynamics upon thawing and freezing of an active layer permafrost soil. ISME J. 2019, 13, 1345–1359. [Google Scholar] [CrossRef]
  66. Vanlauwe, B.; Dendooven, L.; Merckx, R. Residue fractionation and decomposition: The significance of the active fraction. Plant Soil 1994, 158, 263–274. [Google Scholar] [CrossRef]
  67. Silva, M.S.; Sales, A.N.; Magalhães-Guedes, K.T.; Dias, D.R.; Schwan, R.F. Brazilian Cerrado soil Actinobacteria ecology. Biomed Res. Int. 2013, 2013, 503805. [Google Scholar] [CrossRef]
  68. Drzyzga, O. The strengths and weaknesses of Gordonia: A review of an emerging genus with increasing biotechnological potential. Crit. Rev. Microbiol. 2012, 38, 300–316. [Google Scholar] [CrossRef] [PubMed]
  69. Rastogi, G.; Bhalla, A.; Adhikari, A.; Bischoff, K.M.; Hughes, S.R.; Christopher, L.P.; Sani, R.K. Characterization of thermostable cellulases produced by Bacillus and Geobacillus strains. Bioresour. Technol. 2010, 101, 8798–8806. [Google Scholar] [CrossRef] [PubMed]
  70. Grady, E.N.; MacDonald, J.; Liu, L.; Richman, A.; Yuan, Z.-C. Current knowledge and perspectives of Paenibacillus: A review. Microb. Cell Fact. 2016, 15, 203. [Google Scholar] [CrossRef] [Green Version]
  71. Guan, T.-W.; Lin, Y.-J.; Ou, M.-Y.; Chen, K.-B. Isolation and diversity of sediment bacteria in the hypersaline aiding lake, China. PLoS ONE 2020, 15, e0236006. [Google Scholar]
  72. Wongwilaiwalin, S.; Rattanachomsri, U.; Laothanachareon, T.; Eurwilaichitr, L.; Igarashi, Y.; Champreda, V. Analysis of a thermophilic lignocellulose degrading microbial consortium and multi-species lignocellulolytic enzyme system. Enzyme Microb. Technol. 2010, 47, 283–290. [Google Scholar] [CrossRef]
  73. Albdaiwi, R.N.; Khyami-Horani, H.; Ayad, J.Y.; Alananbeh, K.M.; Al-Sayaydeh, R. Isolation and characterization of halotolerant plant growth promoting rhizobacteria from durum wheat (Triticum turgidum subsp. durum) cultivated in saline areas of the Dead Sea region. Front. Microbiol. 2019, 10, 1639. [Google Scholar] [CrossRef] [Green Version]
  74. Han, J.-I.; Choi, H.-K.; Lee, S.-W.; Orwin, P.M.; Kim, J.; LaRoe, S.L.; Kim, T.-G.; O’Neil, J.; Leadbetter, J.R.; Hur, C.-G.; et al. Complete genome sequence of the metabolically versatile plant growth-promoting endophyte Variovorax paradoxus S110. J. Bacteriol. 2011, 193, 1183–1190. [Google Scholar] [CrossRef] [Green Version]
  75. Orhan, F.; Demirci, A. salt stress mitigating potential of halotolerant/halophilic plant growth promoting. Geomicrobiol. J. 2020, 37, 663–669. [Google Scholar] [CrossRef]
  76. Cortes-Tolalpa, L.; Norder, J.; van Elsas, J.D.; Falcao Salles, J. Halotolerant microbial consortia able to degrade highly recalcitrant plant biomass substrate. Appl. Microbiol. Biotechnol. 2018, 102, 2913–2927. [Google Scholar] [CrossRef] [Green Version]
  77. Shivanand, P.; Mugeraya, G.; Kumar, A. Utilization of renewable agricultural residues for the production of extracellular halostable cellulase from newly isolated Halomonas sp. strain PS47. Ann. Microbiol. 2013, 63, 1257–1263. [Google Scholar] [CrossRef]
  78. De León-Lorenzana, A.S.; Delgado-Balbuena, L.; Domínguez-Mendoza, C.; Navarro-Noya, Y.E.; Luna-Guido, M.; Dendooven, L. Reducing salinity by flooding an extremely alkaline and saline soil changes the Bacterial community but its effect on the Archaeal community is limited. Front. Microbiol. 2017, 8, 466. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  79. Soto-Padilla, M.Y.; Valenzuela-Encinas, C.; Dendooven, L.; Marsch, R.; Gortáres-Moroyoqui, P.; Estrada-Alvarado, M.I. Isolation and phylogenic identification of soil haloalkaliphilic strains in the former Texcoco Lake. Int. J. Environ. Health Res. 2014, 24, 82–90. [Google Scholar] [CrossRef]
  80. Green, P.N. Methylobacterium. In The Prokaryotes; Dworkin, M., Falkow, S., Rosenberg, E., Schleifer, K.-H., Stackebrandt, E., Eds.; Springer: New York, NY, USA, 2006; pp. 257–265. ISBN 978-0-387-30745-9. [Google Scholar]
  81. Wang, L.; Nie, Y.; Tang, Y.-Q.; Song, X.-M.; Cao, K.; Sun, L.-Z.; Wang, Z.-J.; Wu, X.-L. Diverse bacteria with lignin degrading potentials isolated from two ranks of coal. Front. Microbiol. 2016, 7, 1428. [Google Scholar] [CrossRef]
  82. Zhang, X.; Yao, Q.; Cai, Z.; Xie, X.; Zhu, H. Isolation and identification of myxobacteria from saline-alkaline soils in Xinjiang, China. PLoS ONE 2013, 8, e70466. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  83. Lima, R.N.; Porto, A.L.M. Chapter eight—Recent advances in marine enzymes for biotechnological processes. In Marine Enzymes Biotechnology: Production and Industrial Applications, Part I—Production of Enzymes; Kim, S.-K., Toldrá, F.B.T.-A., Eds.; Academic Press: Cambridge, MA, USA, 2016; Volume 78, pp. 153–192. ISBN 1043-4526. [Google Scholar]
  84. Puentes-Téllez, P.E.; Salles, J.F. Dynamics of abundant and rare bacteria during degradation of lignocellulose from sugarcane biomass. Microb. Ecol. 2020, 79, 312–325. [Google Scholar] [CrossRef] [Green Version]
  85. Valenzuela-Encinas, C.; Neria-González, I.; Alcántara-Hernández, R.J.; Estrada-Alvarado, I.; Zavala-Díaz de la Serna, F.J.; Dendooven, L.; Marsch, R. Changes in the bacterial populations of the highly alkaline saline soil of the former lake Texcoco (Mexico) following flooding. Extremophiles 2009, 13, 609–621. [Google Scholar] [CrossRef]
  86. Ma, B.; Gong, J. A meta-analysis of the publicly available bacterial and archaeal sequence diversity in saline soils. World J. Microbiol. Biotechnol. 2013, 29, 2325–2334. [Google Scholar] [CrossRef]
  87. Andlar, M.; Rezić, T.; Marđetko, N.; Kracher, D.; Ludwig, R.; Šantek, B. Lignocellulose degradation: An overview of fungi and fungal enzymes involved in lignocellulose degradation. Eng. Life Sci. 2018, 18, 768–778. [Google Scholar] [CrossRef]
Microorganisms 09 01297 g001a 550Microorganisms 09 01297 g001b 550
Figure 1. Changes in the relative abundance (%) of bacterial phyla in the three soils from the former lake Texcoco with different electrolytic conductivity (EC) left unamended or amended with young maize plants or their neutral detergent fiber (NDF) fraction at the onset of the experiment (0) and incubated aerobically at 22 ± 2 °C for one (1), three (3), seven (7), or 14 days (14).
Figure 1. Changes in the relative abundance (%) of bacterial phyla in the three soils from the former lake Texcoco with different electrolytic conductivity (EC) left unamended or amended with young maize plants or their neutral detergent fiber (NDF) fraction at the onset of the experiment (0) and incubated aerobically at 22 ± 2 °C for one (1), three (3), seven (7), or 14 days (14).
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Figure 2. Heatmap with the relative abundance (%) of the 50 most abundant genera in the three soils from the former lake Texcoco with different electrolytic conductivity (EC) left unamended or amended with young maize plants and their neutral detergent fiber (NDF) fraction at the onset of the experiment (day 0) and incubated aerobically at 22 ± 2 °C for one (day 1), three (day 3), seven (day 7), or 14 days (day 14).
Figure 2. Heatmap with the relative abundance (%) of the 50 most abundant genera in the three soils from the former lake Texcoco with different electrolytic conductivity (EC) left unamended or amended with young maize plants and their neutral detergent fiber (NDF) fraction at the onset of the experiment (day 0) and incubated aerobically at 22 ± 2 °C for one (day 1), three (day 3), seven (day 7), or 14 days (day 14).
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Microorganisms 09 01297 g003 550
Figure 3. Principal component analysis (PCA) with centered log-ratio transformed count numbers of (a) all bacterial phyla, (b) all bacterial groups assigned up to the taxonomic level of genus and (c) all operational taxonomic units (OTUs) in unamended soil with electrolytic conductivity (EC) 1.9 dS m−1 (■) EC 17.3 dS m−1 (■), and EC 33.4 dS m−1 (■).
Figure 3. Principal component analysis (PCA) with centered log-ratio transformed count numbers of (a) all bacterial phyla, (b) all bacterial groups assigned up to the taxonomic level of genus and (c) all operational taxonomic units (OTUs) in unamended soil with electrolytic conductivity (EC) 1.9 dS m−1 (■) EC 17.3 dS m−1 (■), and EC 33.4 dS m−1 (■).
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Microorganisms 09 01297 g004 550
Figure 4. Principal component analysis (PCA) with the centered log-ratio transformed counts of bacterial groups in soil left unamended (■), or amended with NDF fraction (■) or young maize plants (■) at the phylum taxonomic level in soil with (a) electrolytic conductivity (EC) 1.9 dS m−1, (b) EC 17.3 dS m−1, and (c) EC 33.4 dS m−1, at the genus taxonomic level in soil with (d) EC 1.9 dS m−1, (e) EC 17.3 dS m−1, and (f) EC 33.4 dS m−1, and at the OTU level in soil with (g) EC 1.9 dS m−1, (h) EC 17.3 dS m−1, and (i) EC 33.4 dS m−1, incubated aerobically at 22 ± 2 °C for 14 days.
Figure 4. Principal component analysis (PCA) with the centered log-ratio transformed counts of bacterial groups in soil left unamended (■), or amended with NDF fraction (■) or young maize plants (■) at the phylum taxonomic level in soil with (a) electrolytic conductivity (EC) 1.9 dS m−1, (b) EC 17.3 dS m−1, and (c) EC 33.4 dS m−1, at the genus taxonomic level in soil with (d) EC 1.9 dS m−1, (e) EC 17.3 dS m−1, and (f) EC 33.4 dS m−1, and at the OTU level in soil with (g) EC 1.9 dS m−1, (h) EC 17.3 dS m−1, and (i) EC 33.4 dS m−1, incubated aerobically at 22 ± 2 °C for 14 days.
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Figure 5. Differential abundance analysis with DESEq2 package [42]. A positive Log2FoldChange value (red bar) indicates a phylum that was significantly enriched by the application of young maize plants or its neutral detergent fibre (NDF) fraction, whereas a negative one (blue bar) indicates that the relative abundance of the phylum was significantly higher in unamended control soil. Only significantly affected bacterial groups at the taxonomic level of phylum are shown based on the Wald’s test (p < 0.05).
Figure 5. Differential abundance analysis with DESEq2 package [42]. A positive Log2FoldChange value (red bar) indicates a phylum that was significantly enriched by the application of young maize plants or its neutral detergent fibre (NDF) fraction, whereas a negative one (blue bar) indicates that the relative abundance of the phylum was significantly higher in unamended control soil. Only significantly affected bacterial groups at the taxonomic level of phylum are shown based on the Wald’s test (p < 0.05).
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Microorganisms 09 01297 g006 550
Figure 6. Differential abundance analysis with DESEq2 package [42]. A positive Log2FoldChange value (red bar) indicates a bacterial genus that was significantly enriched by the application of young maize plants or its NDF fraction, whereas a negative one (blue bar) indicates a bacterial genus that was significantly enriched in unamended control soil. Only significantly affected bacterial groups at the taxonomic level of genus are shown based on the Wald’s test (p < 0.05).
Figure 6. Differential abundance analysis with DESEq2 package [42]. A positive Log2FoldChange value (red bar) indicates a bacterial genus that was significantly enriched by the application of young maize plants or its NDF fraction, whereas a negative one (blue bar) indicates a bacterial genus that was significantly enriched in unamended control soil. Only significantly affected bacterial groups at the taxonomic level of genus are shown based on the Wald’s test (p < 0.05).
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Figure 7. (a) Changes in the relative abundance (%) of bacterial genera with higher relative abundance in NDF amended soil than in the unamended soil incubated aerobically at 22 ± 2 °C for 14 days. Unamended soil with EC 1.9 dS m−1 (□), unamended soil with EC 17.3 dS m−1 (Δ), unamended soil with EC 33.4 dS m−1 (○), neutral detergent fibre fraction amended soil with EC 1.9 dS m−1 (■), neutral detergent fibre fraction amended soil with EC 17.3 dS m−1 (▲), neutral detergent fibre fraction amended soil with EC 33.4 dS m−1 (●), young maize plants amended soil with EC 1.9 dS m−1 (■), young maize plants amended soil with EC 33.4 dS m−1 (▲), young maize plants amended soil with EC 33.4 dS m−1 (●), and (b) changes in the relative abundance (%) of bacterial genera with higher relative abundance in the young maize plants amended soil than in the control soil that was incubated aerobically at 22 ± 2 °C for 14 days. Same legend as the subsection (a).
Figure 7. (a) Changes in the relative abundance (%) of bacterial genera with higher relative abundance in NDF amended soil than in the unamended soil incubated aerobically at 22 ± 2 °C for 14 days. Unamended soil with EC 1.9 dS m−1 (□), unamended soil with EC 17.3 dS m−1 (Δ), unamended soil with EC 33.4 dS m−1 (○), neutral detergent fibre fraction amended soil with EC 1.9 dS m−1 (■), neutral detergent fibre fraction amended soil with EC 17.3 dS m−1 (▲), neutral detergent fibre fraction amended soil with EC 33.4 dS m−1 (●), young maize plants amended soil with EC 1.9 dS m−1 (■), young maize plants amended soil with EC 33.4 dS m−1 (▲), young maize plants amended soil with EC 33.4 dS m−1 (●), and (b) changes in the relative abundance (%) of bacterial genera with higher relative abundance in the young maize plants amended soil than in the control soil that was incubated aerobically at 22 ± 2 °C for 14 days. Same legend as the subsection (a).
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Table
Table 1. Characteristics of the three locations used in this study.
Table 1. Characteristics of the three locations used in this study.
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a EC: Electrolytic conductivity, b WHC: Water holding capacity.
Table
Table 2. The effect of soil (EC 1.9 dS m−1, EC 17.3 dS m−1 and EC 33.4 dS m−1), time (0, 1, 3, 7 and 14 days of aerobic incubation) and their interaction on the soil bacterial community using a perMANOVA analysis with the sequence counts converted to centered log-ratio transformation with ALDEx2 package [39].
Table 2. The effect of soil (EC 1.9 dS m−1, EC 17.3 dS m−1 and EC 33.4 dS m−1), time (0, 1, 3, 7 and 14 days of aerobic incubation) and their interaction on the soil bacterial community using a perMANOVA analysis with the sequence counts converted to centered log-ratio transformation with ALDEx2 package [39].
ComparisonF Valuep Value a
Phylum
Soil4.071<0.001
Time1.5030.080
Interaction1.1430.273
All taxonomic groups assigned to the taxonomic level of genus
Soil3.865<0.001
Time0.9960.396
Interaction1.0590.284
All operational taxonomic units (OTUs)
Soil1.577<0.001
Time1.0030.364
Interaction0.9920.579
ap-values were determined using 999 permutations. Bold p-values indicate a significant effect.
Table
Table 3. The effect of treatment (unamended, young maize plants amended soil or neutral detergent fibre amended soil), time (one, three, seven, and 14 days of aerobic incubation) and their interaction on the soil bacterial community, as determined with a perMANOVA analysis with the sequence counts converted to centeredlog-ratio transformation with ALDEx2 package [39].
Table 3. The effect of treatment (unamended, young maize plants amended soil or neutral detergent fibre amended soil), time (one, three, seven, and 14 days of aerobic incubation) and their interaction on the soil bacterial community, as determined with a perMANOVA analysis with the sequence counts converted to centeredlog-ratio transformation with ALDEx2 package [39].
Soil EC 1.9 dS m−1Soil EC 17.2 dS m−1Soil EC 33.4 dS m−1
ComparisonF Valuep Value aF Valuep ValueF Valuep Value
Phyla
Treatment2.070<0.0011.551<0.0191.848<0.001
Time1.0030.4341.2610.1971.2420.174
Interaction1.0280.4121.4460.0651.0620.341
All Taxonomic Groups Assigned up to the Level of Genus
Treatment1.829<0.0011.560<0.0011.556<0.001
Time1.148<0.0181.185<0.0041.191<0.004
Interaction1.101<0.0311.135<0.0040.9680.723
All Operational Taxonomic Units (OTUs)
Treatment1.179<0.0011.184<0.0011.196<0.001
Time1.0210.1711.0250.1460.9890.621
Interaction0.9950.5681.0230.1021.0150.219
ap-values are based on 999 permutations. Bold p-values indicate a significant effect.
Table
Table 4. The effect of treatment (unamended soil or soil amended with NDF or soil amended with young maize plants) on the soil bacterial community structure at the phyla and genus taxonomic level in soil with EC 1.9 dS m−1 (low), EC 17.3 dS m−1 (medium), and EC 33.4 dS m−1 (high) using a compositional approach, i.e., the analysis of differential abundance taking sample variation into account with the ALDEx2 package [39].
Table 4. The effect of treatment (unamended soil or soil amended with NDF or soil amended with young maize plants) on the soil bacterial community structure at the phyla and genus taxonomic level in soil with EC 1.9 dS m−1 (low), EC 17.3 dS m−1 (medium), and EC 33.4 dS m−1 (high) using a compositional approach, i.e., the analysis of differential abundance taking sample variation into account with the ALDEx2 package [39].
Soil EC 1.9 dS m−1Soil EC 17.3 dS m−1Soil EC 33.4 dS m−1
Phyla
Taxonomic groupp Value aTaxonomic groupp ValueTaxonomic groupp Value
Acidobacteria0.0076Verrucomicrobia0.0062Actinobacteria0.0365
Chloroflexi0.0105Gemmatimonadetes0.0039
Nitrospirae0.0140Proteobacteria0.0073
Proteobacteria0.0199Bacteroidetes0.0089
NC100.0424Planctomycetes0.0190
Genera
Pseudomonas0.0025Prauseria0.0006Marinobacter0.0133
Azorhizophilus0.0026KSA10.0059Acinetobacter0.0154
Rhodoplanes0.0037Streptomyces0.0200Marinimicrobium0.0195
Nitrospira0.0063Bacillus0.0279Bacillus0.0303
Opitutus0.0099B-420.0299Alkalimonas0.0317
Steroidobacter0.0102 Cobetia0.0351
Acinetobacter0.0125 Variovorax0.0405
Glycomyces0.0132
Streptomyces0.0136
Prauseria0.0196
Devosia0.0367
Nocardioides0.0400
a Significance was measured using ALDEx2 argument within ALDEx2 package [39] and using the Benjamini-Hochberg correction procedure of the Kruskal-Wallis test (significance threshold, p < 0.05).
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Pérez-Hernández, V.; Hernández-Guzmán, M.; Luna-Guido, M.; Navarro-Noya, Y.E.; Romero-Tepal, E.M.; Dendooven, L. Bacterial Communities in Alkaline Saline Soils Amended with Young Maize Plants or Its (Hemi)Cellulose Fraction. Microorganisms 2021, 9, 1297. https://doi.org/10.3390/microorganisms9061297

AMA Style

Pérez-Hernández V, Hernández-Guzmán M, Luna-Guido M, Navarro-Noya YE, Romero-Tepal EM, Dendooven L. Bacterial Communities in Alkaline Saline Soils Amended with Young Maize Plants or Its (Hemi)Cellulose Fraction. Microorganisms. 2021; 9(6):1297. https://doi.org/10.3390/microorganisms9061297

Chicago/Turabian Style

Pérez-Hernández, Valentín, Mario Hernández-Guzmán, Marco Luna-Guido, Yendi E. Navarro-Noya, Elda M. Romero-Tepal, and Luc Dendooven. 2021. "Bacterial Communities in Alkaline Saline Soils Amended with Young Maize Plants or Its (Hemi)Cellulose Fraction" Microorganisms 9, no. 6: 1297. https://doi.org/10.3390/microorganisms9061297

APA Style

Pérez-Hernández, V., Hernández-Guzmán, M., Luna-Guido, M., Navarro-Noya, Y. E., Romero-Tepal, E. M., & Dendooven, L. (2021). Bacterial Communities in Alkaline Saline Soils Amended with Young Maize Plants or Its (Hemi)Cellulose Fraction. Microorganisms, 9(6), 1297. https://doi.org/10.3390/microorganisms9061297

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