Annual replication is essential in evaluating the response of the soil microbiome to the genetic modification of maize in different biogeographical regions

Abstract

The importance of geographic location and annual variation on the detection of differences in the rhizomicrobiome caused by the genetic modification of maize (Bt-maize, event MON810) was evaluated at experimental field sites across Europe including Sweden, Denmark, Slovakia and Spain. DNA of the rhizomicrobiome was collected at the maize flowering stage in three consecutive years and analyzed for 20the abundance and diversity of PCR-amplified structural genes of Bacteria, Archaea and Fungi, and functional genes for bacterial nitrite reductases (nirS, nirK). The nirK genes were always more abundant than nirS. Maize MON810 did not significantly alter the abundance of any microbial genetic marker, except for sporadically detected differences at individual sites and years. In contrast, annual variation between sites was often significant and variable depending on the targeted markers. Distinct, site-25 specific microbial communities were detected but the sites in Denmark and Sweden were similar to each other. A significant effect of the genetic modification of the plant on the community structure in the rhizosphere was detected among the nirK denitrifiers at the Slovakian site in only one year. However, most nirK sequences with opposite response were from the same or related source organisms suggesting that the transient differences in community structure did not translate to the functional level. Our 30 results show a lack of effect of the genetic modification of maize on the rhizosphere microbiome that would be stable and consistent over multiple years. This demonstrates the importance of considering annual variability in assessing environmental effects of genetically modified crops.

The host niches of soybean rather than genetic modification or glyphosate application drive the assembly of root‐associated microbial communities

“…According to some previous studies, denitrification may sometimes accelerate under Bt crops by promoting nitrite reductase activities along with an increase in denitrifying bacteria (Li et al, 2019;Wu et al, 2004). However, other studies claimed that Bt crops had little to no impact on bacterial nitrite reductases (Szoboszlay et al, 2019). These results were inconsistent with our findings, and the possible explanation can be that we applied glyphosate in the planting of GM soybean in the real scenario, which was not completely consistent with the treatments in the previous studies.…”

Diverse recruitment to a globally structured atmospheric microbiome

“…Calculation of geographic distances were performed using R package geosphere 89 function distGeo with WGS84 ellipsoid. Source tracking was conducted by fast expectation-maximization using FEAST 44 with data from other studies (processed using dada2 following the same parameters as this study) as additional sources/sinks [90][91][92][93][94][95][96] and NCBI BioProject PRJEB42801. For correlation analysis between abiotic and biotic variables the Pearson correlation coefficient for multiple pairwise combinations were calculated using the R package corrplot 97 , with P-value cut-off of 0.05 corrected for multiple tests using Bonferroni correction.…”

Diverse recruitment to a globally structured atmospheric microbiome

“…Calculation of geographic distances were performed using R package geosphere 35 function distGeo with WGS84 ellipsoid. Source tracking was conducted using FEAST 36 with data from other studies (processed using dada2 following the same parameters as this study) as additional sources/sinks [37][38][39][40][41][42][43] and NCBI BioProject PRJEB42801. For correlation analysis between abiotic and biotic variables the Pearson correlation coefficient for multiple pairwise combinations were calculated using the R package Corrplot 44 .…”

“…UV repair and desiccation tolerance 41 . The ability to become aerosolized may vary between taxa in marine 34 and terrestrial 42 systems and so deterministic biotic drivers may also be relevant to recruitment from sources, as well as selective deposition during transit 43 . Overall, the source tracking demonstrated that atmospheric diversity is driven by a complex recruitment process involving local soils plus globally distributed inputs from drylands and the phyllosphere.…”