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Reduced microbial diversity induces larger volatile organic compound emissions from soils | Scientific Reports


Sampling and site description

Samples were collected in the QualiAgro site, a field station taking part of the SOERE-PRO-network ( The QualiAgro agronomic set up which is described in this study started in September 1998. The QualiAgro site is located at Feucherolles in northwestern France (35 km west of Paris; 48°52′N, 1°57′E, alt 150 m) on a silt loam textured soil. The soil is classified as a hortic glossic Luvisol (IUSS Working Group WRB, 2014), representative of the Parisian Basin. The main characteristics of these soils are represented by the lack of clay, a silt-loam texture (15.0% clay, 78.3% slit) and an initial pH of 6.9 in the surface horizon (0–30 cm) and good drainage. Moreover, the QualiAgro field experiment is in a cropland dominated region, which leads to low organic carbon and low organic matter concentrations (initial content of 1.1%)57.

The experiment was a randomized block design with 4 replicates comparing 4 organic waste products: BIOW (bio-waste compost derived from the co-composting of green wastes and source-separated organic fractions of municipal solid wastes), GWS (compost derived from the co-composting of green wastes with sewage sludge), FYM (farmyard manure) and MSW (municipal solid waste compost derived from the composting of residual solid wastes after removing dry and clean packaging); plus a control without organic input (CN). Samples were collected in 5 blocks of the site amended with mineral N in order to reach optimal N application. Since 1998, the organic waste products (OWPs) have been applied at a rate of ~ 4 t C ha−1 every two years on the wheat stubbles in September after harvesting. In each plot, 5 soil cores were randomly sampled at 0–30 cm depth using a core drill and stored in a cold chamber at 4 °C prior to analysis. The sampling was performed in early September 2016, one year after the last amendment of OWPs.

Microcosms and experimental setup

Soil samples were sieved at 4 mm and homogenized before gamma-ray sterilization (35 kGy; Conservatome, Dagneux, France). The sterility of the irradiated soil was verified by spreading serial dilutions of the soil onto nutrient agar plates. After the sterilization process, soils were inoculated with a diluted soil suspension prepared with the same soil before sterilization58. The soil suspension was created by mixing 30 g of soil with 90 mL of sterilized water. From this soil suspension, we used a pure sample (100) D0, and two levels of dilution were prepared with a water ratio of 1:103 (D1) and 1:105 (D2). The second step was the re-inoculation of the sterilized soil with the three different soil suspensions (pure or 100, 10−3 and 10−5). In order to create the microcosms, 30 g of each sterilized soil sample were transferred to a flask, and we added 50% of the water necessary to reach 60% of the water holding capacity (WHC). We completed the microcosms by adding one of the three soil suspension until 60% of the WHC. Soil samples consisted of soils amended with 4 different OWPs and a control without organic input. Three replicates of each combination of soil and microbial diversity level were prepared, resulting in 45 microcosms in total (n = 45, replicates = 3). Microcosms were sealed hermetically and pre-incubated at 20 °C in the dark. Once a week during six weeks the microcosms have been aerated and the water content was adjusted to maintain constant soil moisture at 60% of the WHC.

One week before the measurement of VOC emissions with the PTR-QiTOF-MS, the silicone flask plugs were substituted with Teflon coated plugs. This was necessary in order to reduce the influence of the emissions of VOCs released from the silicone plugs. Teflon is an inert material reducing VOC emissions that would have been released from the silicone plug. After the six weeks incubation, the microcosms were connected to the PTR-QiTOF-MS in order to measure VOC emissions.

VOC emissions measurements with the PTR-QiTOF-MS

PTR-QiTOF-MS setup

The VOCs were analyzed with a PTR-QiTOF-MS (PTR-Quadrupole Ion guide-TOF, Ionicon, Analytik GmbH, AU). The analyzer setup is described in details by Abis et al.30 and is only briefly described here. In this study, ionization was carried out with H3O+ as proton donor. In the drift tube, the pressure was tuned to 4 mbar, the temperature to 80 °C, and the drift voltage to 1000 V. The E/N ratio (Electric field/density of natural particles) was 132 Td where 1 Td is 10−17 V cm2. The setup of the time of flight timing was: TOF extraction period 40000 ns, pulse width 2000 ns, trigger delay 100 ns. The number of channels was 240.000. This gave a mass spectrum measurement up to 510 m/z. The measurement period was set to 1 s, which means that each sample corresponded to 60 acquisitions of 25000 individual spectra. Raw PTR-ToF-MS data were recorded by TofDaq software (Tofwerk AG, Switzerland).

Flask sampling method and flux calculations

Each flask plug was equipped with two PEEK tubes, one allowing the connection with the PTR-QiTOF-MS and the other one was connected with a bottle of dry synthetic air (Alphagaz 1 Air: 80% nitrogen, 20% oxygen, 99.9999%, Air Liquide®). The flasks had a volume of 88 cm3. The detection of the VOC emissions from the microcosms was performed during 180 s for every sample. For each sample, an empty flask was used as a reference for zero emissions, using the same Teflon plug as the sample. An air flow (\({Q}_{air}\)) of 0.3 L min−1 (equivalent volumetric flow at 0 °C and 1 atm) of dry synthetic air was passed through a hydrocarbons and humidity filter (Filter for fuel gas, final purity = 99.999%, Restek®) and a Hydrocarbon Trap (Supelco, Supelpure® HC) prior to injection in the flask. A mass flowmeter (Bronkhorst® model F-201CV, accuracy: standard 0.5% Rd plus 0.1% FS, range: 0.2 L min−1 to 5 L min−1 air) was used to control the synthetic air flow rate. Air was sampled at the chamber outlet into a PTR-QiToF-MS with a 0.05 L min−1 flow rate with a 2 m long, 1 mm internal diameter PEEK tube, heated at 80 °C. A measurement cycle consisted in measuring the VOC mixing ratio at the outlet of the flask containing the microcosms (\({x}_{VOCmicro}\) in ppb) for 180 s. Then air was sampled for 180 s on the empty chamber with the same Teflon plug sealing to determine \({x}_{VOCempty}\) (ppb). Only the last 60 s of each measurement were kept to calculate averaged mixing ratios in order to ensure a stable VOCs mixing ratio. The VOC emission (\({E}_{VOC}\) in nmol g−1 s−1 dry soil) was calculated as:

$${E}_{VOC}=\frac{{Q}_{air}\times ({{\rm{\chi }}}_{VOCmicro}-{{\rm{\chi }}}_{VOCempty})}{{V}_{mol}^{air}\times {m}_{drysoil}}\,$$

where \({V}_{mol}^{air}\) is the air molar volume at standard temperature and pressure (22.4 L mol−1 at 0 °C and 1 atm), and \({{\boldsymbol{m}}}_{{\boldsymbol{dry}}{\boldsymbol{soil}}}\) 30 g. After each measurement, the flask was cleaned and the soil transferred in a −40 °C chamber before the DNA extraction.

VOCs data analysis

The analysis of the ion peaks in the mass spectra measured with the PTR-QiTOF-MS, the mass calibration, and the processing of the mass table with all the compounds detected were performed using the Spectra Analyser of the PTR viewer software (Ionicon, Analytik GmbH) following the protocol published in Abis et al.30. Likely isotopes and fragments were identified using a correlation coefficient of 0.99. Therefore, the ions having a time-correlation coefficient higher than 0.99 were considered as either isotopes or fragments depending on the m/z difference. Furthermore, correlated ion peaks that were closer than the resolution of the used PTR-QiTOF-MS were considered a single ion and only counted once.

Microbial analysis

DNA extraction

The DNA extraction has been performed for all microcosms following the protocol developed by GenoSol platform (INRA, Dijon, France, (Terrat et al., 2012) for application in large-scale soil survey (Terrat et al., n.d.). The protocol consist of mixing in a 15 mL Falcon tube 1 g of each soil sample with 2 g of 100 mm diameter silica beads, 2.5 g of 1.4 mm diameter ceramic beads and 4 glass bead of 4 mm diameter and 5 mL of a solution containing 100 mMTris (pH 8.0), 100 mMEDTA (pH 8.0), 100 mM NaCl, and 2% (wt/vol) sodium dodecyl sulfate. Then, we proceeded with homogenizing the samples in a FastPrep-24 (MP-Biomedicals, Santa Ana, CA, USA) during 90 s and incubated for 30 min at 70 °C before centrifugation at 7000 g for 5 min at 20 °C. The deproteination was performed by collecting 1 mL of the supernatant and incubating for 10 min on ice with 1/10 volume of 3 M potassium acetate (pH 5.5) and centrifuged at 14.000 g during 5 min. The precipitation of the proteins was performed with one volume of ice-cold isopropanol. The last step of the extraction consisted of washing the nucleic acid with 70% ethanol. DNA concentrations of crude extracts were determined by electrophoresis in 1% agarose gel stained with ethidium bromide using a calf thymus DNA standard curve, and used as estimates of microbial biomass (Dequiedt et al., 2011). After quantification, nucleic acids were separated from the residual impurities, particularly humic substances, by centrifuging through two types of minicolumn. After quantification, 100 µl of crude DNA extract were separated from the residual impurities, particularly humic substances, by using only the purification steps of Nucleospin Soil kit (Macherey-Nagel GmbH & Co. KG, Düren, Germany). Purified DNA concentrations were finally measured using the Quantifluor (Promega, Lyon, France) staining kit, according to the manufacturer’s instructions.

Quantitative PCR (qPCR)

Quantitative real-time PCR was performed on extracted DNA to quantify 16S and 18S rRNA gene sequences59,60, which led to the estimation of the F/P ratio. Prokaryotic and fungal quantitative PCR assays were performed using a StepONE (Applied Biosystems, Courtaboeuf, France) with a SYBRGreen® detection system. Purified DNA extract was amplified in a total reaction volume of 20 µl, containing 500 ng of T4 gene 32 protein (MP Biomedicals, France) and 10 µl of Takyon Rox Sybr 2X Mastermix dTTP blue (Eurogentec, Liège, Belgium).

For prokaryotic quantification, the reaction mixtures contained 1 µM of each primer (341 F: 5′ – CCT ACG GGA GGC AGC AG – 3′ and 515 R: 5′ – ATT ACC GCG GCT GCT GGC A – 3′) (López-Gutiérrez et al. 2004) and 2 ng of template DNA. The PCR conditions consisted of an initial step of 15 min at 95 °C then 35 cycles of 15 s at 95 °C, 30 s at 60 °C, 30 s at 72 °C and 20 s at 80 °C. The 16S rDNA gene from a pure culture of Pseudomonas aeruginosa PAO was used as a standard for the prokaryotic quantitative PCR assay.

Soil fungi were quantified using 1.25 µM of each primer (FR1: 5′-AIC CAT TCA ATC GGT AIT-3′, and FF390: 5′-CGA TAA CGA ACG AGA CCT-3′)61, and 2 ng of template DNA. The PCR conditions were: an initial step of 10 min at 95 °C for activation; followed by 35 cycles of 15 s at 95 °C, 30 s at 50 °C and 60 s at 70 °C. Amplified DNA from a pure culture of Fusarium oxysporum 47 was used as a fungal standard. These measures were used to estimate the prokaryotic and fungal densities in the samples.

High throughput sequencing of 16S and 18S rRNA gene sequences

Prokaryotic diversity was obtained by amplifying a 440-base 16S rRNA from each DNA samples. The corresponding primers were: F479 (5’-CAG CMG CYG CNG TAA NAC-3’) and R888 (5’-CCG YCA ATT CMT TTR AGT-3’) (Tardy et al., 2014). The amplification of the DNA was performed during a 25 µL PCR (with 5 ng of DNA for each sample) under the following set up conditions: 94 °C for 2 min, 35 cycles of 30 s at 94 °C, 52 °C for 30 s and 72 °C for 1 min, followed by 7 min at 72 °C.

For fungal diversity, a 350-base 18S rRNA fragment was amplified from each DNA sample (5 ng) with the corresponding primers: FF390 (5’-CGA TAA CGA ACG AGA CCT-3’) and FR1 (5’-ANC CAT TCA ATC GGT ANT-3’)61. For each sample, 5 ng of DNA were used for a 25 µL PCR conducted under the following conditions: 94 °C for 3 min, 35 cycles of 30 s at 94 °C, 52 °C for 1 min and 72 °C for 1 min, followed by 5 min at 72 °C.

The purification of the PCR products was performed using the Agencourt® AMPure® XP kit (Beckman Coulter, Italy, Milano) and quantified with the Quantifluor (Promega, Lyon, France) staining kit according to the manufacturer’s instructions. Purified PCR products (7.5 ng of DNA for prokaryotes and 5 ng of DNA for fungi) were amplified twice in order to integrate to the 5′ end of the primers a 10-bp multiplex identifiers allowing the specific identification of the samples and the prevention of PCR biases. For prokaryotes, the second PCR conditions were the same as previously described but with only seven cycles. For fungi, the second PCR conditions were optimized, with the number of cycles being reduced to seven and the denaturation step processed at 94 °C during 1 min. PCR products were purified with the MinElute PCR purification kit (Qiagen NV) and quantified with the Quantifluor (Promega, Lyon, France) staining kit according to the manufacturer’s instructions. Equal amounts of each sample were pooled and then cleaned with the SPRI (Solid Phase Reverse Immobilization Method) using the Agencourt® AMPure® XP kit (Beckman Coulter, Italy, Milano). The pool was finally sequenced with a MiSeq Illumina instrument (Illumina Inc, San Diego, CA) operating with V3 chemistry and producing 250 bp paired-reads.

Bioinformatic analysis of 16S and 18S rRNA gene sequences

The bioinformatics analyses were performed using the GnS-PIPE developed by the Genosol platform (INRA, Dijon, France) (Terrat et al., 2012). At first, all the 16S and 18S raw reads were organized according to the multiplex identifier sequences. All raw sequences were checked and discarded if: (i) they contained any ambiguous base (Ns), (ii) if their length was less than 350 nucleotides for 16S reads or 300 nucleotides for 18S reads, (iii) if the exact primer sequences were not found (for the distal primer, the sequence can be shorter than the complete primer sequence, but without ambiguities). A PERL program was then applied for rigorous dereplication (i.e. clustering of strictly identical sequences). The dereplicated reads were then aligned using Infernal alignment62, and clustered into operational taxonomic units (OTU) using a PERL program that groups rare reads to abundant ones, and does not count differences in homopolymer lengths with a threshold of 95% of sequence similarity. A filtering step was then carried out to check all single-singletons (reads detected only once and not clustered, which might be artifacts, such as PCR chimeras) based on the quality of their taxonomic assignments. Finally, in order to compare the datasets efficiently and avoid biased community comparisons, the reads retained were homogenized by random selection (23 700 and 11900 reads for 16S and 18S rRNA gene sequences, respectively). The retained high-quality reads were used for: (i) taxonomy-independent analyses, determining the Shannon index (ii) taxonomy-based analysis using similarity approaches against dedicated reference databases from SILVA63. The raw datasets are available in the EBI database system under project accession number PRJEB29286.

Statistical analysis

Microbial biomass, microbial diversity Index (Shannon) and the relative abundance of prokaryotes, and fungal phyla in the microbial composition were processed by the ANOVA test. With the ANOVA test, we also analyzed the effect of the organic waste product on the microbial community for the different dilution level The dataset before the statistical analysis was made of 754 variables (number of peaks detected) and 45 samples comprising the 3 replicate for each sample. In order to select the most representing variables of the dataset, several statistical tests have been performed using the R software (Version 1.0.153 – © 2009–2017 RStudio). At first, the normality test (Shapiro-Wilk test, W > 0.9) has been applied to verify that the mean mixing ratios were normally distributed for each VOC. Next, the homogeneity of the variances was verified for each treatment using the Levene test. Once the normality and the homogeneity of the variances were validated, a t-test was performed in order to see if the VOC flux was significantly higher than 0. Correlated masses that were closer than the resolution of the used PTR-QiTOF-MS were removed in order to not count twice the same peak. Finally, an ANOVA test was performed. The final selected dataset comprised of 45 samples and 239 variables meaning that only 32% of the dataset was kept for further analysis. The ANOVA tests were followed by the Tukey post hoc test.

A principal component analysis (PCA, Package Ade4 Version 1.0.153 – © 2009–2017 R Studio) was performed to see the different VOCs compounds differentiating the three dilution levels. The Shannon index of diversity (Figs. 1 and S4) was calculated with the diversity function of the vegan package (version 2.4-3) in the R software (version 3.2.3). The diversity index was calculated as \(H\,=\,\sum _{VOC}{E}_{VOC}\,\log ({E}_{VOC})\), where the sum is over all VOCs recorded in the mass table. The correlation matrix between VOCs and microorganisms has been created selecting the VOC having a R2 of the correlation microorganisms/VOC larger than 0.6, the final number of compounds displayed was 107.

Microbial biomass, microbial diversity Index (Shannon) and the relative abundance of prokaryotic, and fungal phyla in the microbial composition were processed by the ANOVA test. With the ANOVA test, we also analyzed the effect of the organic waste product on the microbial community for the different dilution levels. All significant effects were assessed by Tukey’s Honestly Significant Difference (HSD) post hoc test (P < 0.05).

The correlation between the summed VOC emissions and VOC diversity and the different microbiological factors has been calculated using the basic package STAT of R studio. We choose the Spearman correlation as a method since the distribution of the dataset was not normal.

To visualize the relationship between VOCs and soil physico-chemical and microbiological factors, redundancy analysis (RDA) and variance partitioning were carried out. All statistical analyses were performed with the Vegan package (v.2.0-8)64 in R software version 3.0.1. RDA was applied to VOCs variables (diversity and total emission rates) using soil physico-chemical (Corg, pH, C/N) and microbial community parameters (molecular microbial biomass, prokaryotic and fungal richness, prokaryotic and fungal diversity, F/P ratio) as explanatory variables. At first, a global variance partitioning was applied to quantify the respective effect of soil physico-chemistry and soil biology (rda followed by anova.cca function). Then, a detailed variance partitioning provided the pure effect of each exploratory variable was proceeded (ordiR2step followed by anova function)65. The interactions between all explanatory variables were also included in the model. The significance of the model and of each explanatory variable included in the model was tested using 10000 permutations.

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