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

peer-reviewedThe 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 the 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-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 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

Revisiting soil fungal biomarkers and conversion factors: Interspecific variability in phospholipid fatty acids, ergosterol and rDNA copy numbers

- Refined conversion factors for soil fungal biomarkers are proposed. - High interspecific variability is present in all fungal biomarkers. - A modeling approach supports the validity of biomarker estimates in diverse soils. - ITS1 copies vary strongly, but are fungal-specific with least phylogenetic bias. - A combination of fungal biomarkers will reveal soil fungal physiology and activity. The abundances of fungi and bacteria in soil are used as simple predictors for carbon dynamics, and represent widely available microbial traits. Soil biomarkers serve as quantitative estimates of these microbial groups, though not quantifying microbial biomass per se. The accurate conversion to microbial carbon pools, and an understanding of its comparability among soils is therefore needed. We refined conversion factors for classical fungal biomarkers, and evaluated the application of quantitative PCR (qPCR, rDNA copies) as a biomarker for soil fungi. Based on biomarker contents in pure fungal cultures of 30 isolates tested here, combined with comparable published datasets, we propose average conversion factors of 95.3 g fungal C g−1 ergosterol, 32.0 mg fungal C µmol−1 PLFA 18:2ω6,9 and 0.264 pg fungal C ITS1 DNA copy−1. As expected, interspecific variability was most pronounced in rDNA copies, though qPCR results showed the least phylogenetic bias. A modeling approach based on exemplary agricultural soils further supported the hypothesis that high diversity in soil buffers against biomarker variability, whereas also phylogenetic biases impact the accuracy of comparisons in biomarker estimates. Our analyses suggest that qPCR results cover the fungal community in soil best, though with a variability only partly offset in highly diverse soils. PLFA 18:2ω6,9 and ergosterol represent accurate biomarkers to quantify Ascomycota and Basidiomycota. To conclude, the ecological interpretation and coverage of biomarker data prior to their application in global models is important, where the combination of different biomarkers may be most insightful

Revisiting soil fungal biomarkers and conversion factors: Interspecific variability in phospholipid fatty acids, ergosterol and rDNA copy numbers

- Refined conversion factors for soil fungal biomarkers are proposed. - High interspecific variability is present in all fungal biomarkers. - A modeling approach supports the validity of biomarker estimates in diverse soils. - ITS1 copies vary strongly, but are fungal-specific with least phylogenetic bias. - A combination of fungal biomarkers will reveal soil fungal physiology and activity. The abundances of fungi and bacteria in soil are used as simple predictors for carbon dynamics, and represent widely available microbial traits. Soil biomarkers serve as quantitative estimates of these microbial groups, though not quantifying microbial biomass per se. The accurate conversion to microbial carbon pools, and an understanding of its comparability among soils is therefore needed. We refined conversion factors for classical fungal biomarkers, and evaluated the application of quantitative PCR (qPCR, rDNA copies) as a biomarker for soil fungi. Based on biomarker contents in pure fungal cultures of 30 isolates tested here, combined with comparable published datasets, we propose average conversion factors of 95.3 g fungal C g−1 ergosterol, 32.0 mg fungal C µmol−1 PLFA 18:2ω6,9 and 0.264 pg fungal C ITS1 DNA copy−1. As expected, interspecific variability was most pronounced in rDNA copies, though qPCR results showed the least phylogenetic bias. A modeling approach based on exemplary agricultural soils further supported the hypothesis that high diversity in soil buffers against biomarker variability, whereas also phylogenetic biases impact the accuracy of comparisons in biomarker estimates. Our analyses suggest that qPCR results cover the fungal community in soil best, though with a variability only partly offset in highly diverse soils. PLFA 18:2ω6,9 and ergosterol represent accurate biomarkers to quantify Ascomycota and Basidiomycota. To conclude, the ecological interpretation and coverage of biomarker data prior to their application in global models is important, where the combination of different biomarkers may be most insightful

Reconstructing genomes of carbon monoxide oxidisers in volcanic deposits including members of the class Ktedonobacteria

Microorganisms can potentially colonise volcanic rocks using the chemical energy in reduced gases such as methane, hydrogen (H2) and carbon monoxide (CO). In this study, we analysed soil metagenomes from Chilean volcanic soils, representing three different successional stages with ages of 380, 269 and 63 years, respectively. A total of 19 metagenome-assembled genomes (MAGs) were retrieved from all stages with a higher number observed in the youngest soil (1640: 2 MAGs, 1751: 1 MAG, 1957: 16 MAGs). Genomic similarity indices showed that several MAGs had amino-acid identity (AAI) values >50% to the phyla Actinobacteria, Acidobacteria, Gemmatimonadetes, Proteobacteria and Chloroflexi. Three MAGs from the youngest site (1957) belonged to the class Ktedonobacteria (Chloroflexi). Complete cellular functions of all the MAGs were characterised, including carbon fixation, terpenoid backbone biosynthesis, formate oxidation and CO oxidation. All 19 environmental genomes contained at least one gene encoding a putative carbon monoxide dehydrogenase (CODH). Three MAGs had form I coxL operon (encoding the large subunit CO-dehydrogenase). One of these MAGs (MAG-1957-2.1, Ktedonobacterales) was highly abundant in the youngest soil. MAG-1957-2.1 also contained genes encoding a [NiFe]-hydrogenase and hyp genes encoding accessory enzymes and proteins. Little is known about the Ktedonobacterales through cultivated isolates, but some species can utilise H2 and CO for growth. Our results strongly suggest that the remote volcanic sites in Chile represent a natural habitat for Ktedonobacteria and they may use reduced gases for growth

Estimating the effects of Cry1F Bt-maize pollen on non-target Lepidoptera using a mathematical model of exposure

In farmland biodiversity, a potential risk to the larvae of non-target Lepidoptera from genetically modified (GM) Bt-maize expressing insecticidal Cry1 proteins is the ingestion of harmful amounts of pollen deposited on their host plants. A previous mathematical model of exposure quantified this risk for Cry1Ab protein. We extend this model to quantify the risk for sensitive species exposed to pollen containing Cry1F protein from maize event 1507 and to provide recommendations for management to mitigate this risk.A 14-parameter mathematical model integrating small- and large-scale exposure was used to estimate the larval mortality of hypothetical species with a range of sensitivities, and under a range of simulated mitigation measures consisting of non-Bt maize strips of different widths placed around the field edge.The greatest source of variability in estimated mortality was species sensitivity. Before allowance for effects of large-scale exposure, with moderate within-crop host-plant density and with no mitigation, estimated mortality locally was <10% for species of average sensitivity. For the worst-case extreme sensitivity considered, estimated mortality locally was 99·6% with no mitigation, although this estimate was reduced to below 40% with mitigation of 24-m-wide strips of non-Bt maize. For highly sensitive species, a 12-m-wide strip reduced estimated local mortality under 1·5%, when within-crop host-plant density was zero. Allowance for large-scale exposure effects would reduce these estimates of local mortality by a highly variable amount, but typically of the order of 50-fold.Mitigation efficacy depended critically on assumed within-crop host-plant density; if this could be assumed negligible, then the estimated effect of mitigation would reduce local mortality below 1% even for very highly sensitive species.Synthesis and applications. Mitigation measures of risks of Bt-maize to sensitive larvae of non-target lepidopteran species can be effective, but depend on host-plant densities which are in turn affected by weed-management regimes. We discuss the relevance for management of maize events where cry1F is combined (stacked) with a herbicide-tolerance trait. This exemplifies how interactions between biota may occur when different traits are stacked irrespective of interactions between the proteins themselves and highlights the importance of accounting for crop management in the assessment of the ecological impact of GM plants

Salinity induces specific metabolic changes in sugarcane shoot explants in temporary immersion bioreactors

There is a great demand of salt-tolerant sugarcane planting material in Cuba. Temporary immersion bioreactors (TIB) are effective to significantly increase sugarcane in vitro shoot proliferation rate from 1:4 in conventional containers to about 1:35. Sugarcane micropropagation in TIBs under NaCl stress may help screen mutants with salinity tolerance. We developed the experiment shown here to identify a NaCl concentration able to stress shoot in TIBs. At 30 days of culture initiation with different NaCl levels (0 - 200 mM), explant multiplication rate, shoot cluster fresh mass, and levels of aldehydes, chlorophylls, carotenoids and phenolics were determined in the plant material. Content of soluble phenolics in the culture medium was also evaluated. Addition of NaCl decreased shoot multiplication rate and fresh mass. Other statistically significant differences were recorded but the most important were noted in the increased contents of carotenoids, malondialdehyde, other aldehydes and soluble phenolics in the plants, and in the soluble phenolics in the culture medium. This research may be useful for future experiments of in vitro selection of new sugarcane genetic materials with NaCl tolerance. Fifty percent of multiplication rate was reduced with 89 mM NaCl which can be used to stress shoots during micropropagation in TIBs and eventually detect mutants with salt tolerance

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JN was funded by a fellowship from the French MENESR.Peer reviewedPeer Reviewe

Integrated genomics and proteomics define huntingtin CAG length-dependent networks in mice.

To gain insight into how mutant huntingtin (mHtt) CAG repeat length modifies Huntington's disease (HD) pathogenesis, we profiled mRNA in over 600 brain and peripheral tissue samples from HD knock-in mice with increasing CAG repeat lengths. We found repeat length-dependent transcriptional signatures to be prominent in the striatum, less so in cortex, and minimal in the liver. Coexpression network analyses revealed 13 striatal and 5 cortical modules that correlated highly with CAG length and age, and that were preserved in HD models and sometimes in patients. Top striatal modules implicated mHtt CAG length and age in graded impairment in the expression of identity genes for striatal medium spiny neurons and in dysregulation of cyclic AMP signaling, cell death and protocadherin genes. We used proteomics to confirm 790 genes and 5 striatal modules with CAG length-dependent dysregulation at the protein level, and validated 22 striatal module genes as modifiers of mHtt toxicities in vivo

Inter-laboratory testing of the effect of DNA blocking reagent G2 on DNA extraction from low-biomass clay samples

Here we show that a commercial blocking reagent (G2) based on modifed eukaryotic DNA signifcantly improved DNA extraction efciency. We subjected G2 to an inter-laboratory testing, where DNA was extracted from the same clay subsoil using the same batch of kits. The inter-laboratory extraction campaign revealed large variation among the participating laboratories, but the reagent increased the number of PCR-amplifed16S rRNA genes recovered from biomass naturally present in the soils by one log unit. An extensive sequencing approach demonstrated that the blocking reagent was free of contaminating DNA, and may therefore also be used in metagenomics studies that require direct sequencing