Biological risk assessment of food containing recombinant DNA has exposed knowledge gaps related to the general fate of DNA in the gastrointestinal tract (GIT). Here, a series of experiments is presented that were designed to determine if genetic transformation of the naturally competent bacterium Acinetobacter baylyi BD413 occurs in the GIT of mice and rats, with feed-introduced bacterial DNA containing a kanamycin resistance gene (nptII). Strain BD413 was found in various gut locations in germ-free mice at 10 3 −10 5 CFU per gram GIT content 24-48 h after administration. However, subsequent DNA exposure of the colonized mice did not result in detectable bacterial transformants, with a detection limit of 1 transformant per 10 3 −10 5 bacteria. Further attempts to increase the likelihood of detection by introducing weak positive selection with kanamycin of putative transformants arising in vivo during a 4-week-long feeding experiment (where the mice received DNA and the recipient cells regularly) did not yield transformants either. Moreover, the in vitro exposure of actively growing A. baylyi cells to gut contents from the stomach, small intestine, cecum or colon contents of rats (with a normal microbiota) fed either purified DNA (50 µg) or bacterial cell lysates did not produce bacterial transformants. The presence of gut content of germfree mice was also highly inhibitory to transformation of A. baylyi, indicating that microbially-produced nucleases are not responsible for the sharp 500-to 1 000 000-fold reduction of transformation frequencies seen. Finally, a range of isolates from the genera Enterococcus, Streptococcus and Bifidobacterium spp. was examined for competence expression in vitro, without yielding any transformants. In conclusion, model choice and methodological constraints severely limit the sample size and, hence, transfer frequencies that can be measured experimentally in the GIT. Our observations suggest the contents of the GIT shield or adsorb DNA, preventing detectable exposure of feed-derived DNA fragments to competent bacteria.
Abstract. Stomatal regulation and whole plant hydraulic signaling affect water fluxes and stress in plants. Land surface models and crop models use a coupled photosynthesis–stomatal conductance modeling approach. Those models estimate the effect of soil water stress on stomatal conductance directly from soil water content or soil hydraulic potential without explicit representation of hydraulic signals between the soil and stomata. In order to explicitly represent stomatal regulation by soil water status as a function of the hydraulic signal and its relation to the whole plant hydraulic conductance, we coupled the crop model LINTULCC2 and the root growth model SLIMROOT with Couvreur's root water uptake model (RWU) and the HILLFLOW soil water balance model. Since plant hydraulic conductance depends on the plant development, this model coupling represents a two-way coupling between growth and plant hydraulics. To evaluate the advantage of considering plant hydraulic conductance and hydraulic signaling, we compared the performance of this newly coupled model with another commonly used approach that relates root water uptake and plant stress directly to the root zone water hydraulic potential (HILLFLOW with Feddes' RWU model). Simulations were compared with gas flux measurements and crop growth data from a wheat crop grown under three water supply regimes (sheltered, rainfed, and irrigated) and two soil types (stony and silty) in western Germany in 2016. The two models showed a relatively similar performance in the simulation of dry matter, leaf area index (LAI), root growth, RWU, gross assimilation rate, and soil water content. The Feddes model predicts more stress and less growth in the silty soil than in the stony soil, which is opposite to the observed growth. The Couvreur model better represents the difference in growth between the two soils and the different treatments. The newly coupled model (HILLFLOW–Couvreur's RWU–SLIMROOT–LINTULCC2) was also able to simulate the dynamics and magnitude of whole plant hydraulic conductance over the growing season. This demonstrates the importance of two-way feedbacks between growth and root water uptake for predicting the crop response to different soil water conditions in different soils. Our results suggest that a better representation of the effects of soil characteristics on root growth is needed for reliable estimations of root hydraulic conductance and gas fluxes, particularly in heterogeneous fields. The newly coupled soil–plant model marks a promising approach but requires further testing for other scenarios regarding crops, soil, and climate.
Leaf water pressure head (Ψleaf) and more specifically its critical thresholds (Ψthreshold) characterize stomatal control of transpiration, particularly for C4 plants, but this physiological process has rarely been integrated into dynamic crop models at the field scale. We further extended two coupled models with Feddes root water uptake (RWU) and Couvreur RWU models by adding the C4 photosynthesis model in order to be applicable to a maize (Zea mays L.) crop growing under field conditions. The Feddes RWU model relates RWU and plant stress directly to the root zone water hydraulic potential, whereas the Couvreur model explicitly represents hydraulic signals between soil and stomata. Model performance was evaluated with a comprehensive dataset including stomatal conductance, Ψleaf, sap flow, gross assimilation rate (GAR), soil water content (SWC), dry biomass, and leaf area index (LAI) from a two‐season maize experiment under contrasting environments and water regimes. For the Couvreur model, the RWU and dry biomass were more sensitive to the root hydraulic conductance parameters than to Ψthreshold and root growth parameters. The agreement index (I) for the Couvreur model after calibration was 0.91, 0.80, 0.81, and 0.69 for biomass, LAI, RWU, and GAR, respectively. The Feddes model performed similarly for the same metrics. The Feddes model simulated accurately the plant water stress in the first 45 d of the growing season, whereas the Couvreur model inaccurately predicted water stress, which resulted in lower agreement with observations (i.e., RMSEs of biomass simulated by Feddes and Couvreur model averaged from four validated plots were 0.171 and 0.214 kg m–2, respectively). The Feddes model showed the potential to be used for maize under water stress whereas the Couvreur model needs to be further evaluated and improved with an adequate estimation of root hydraulic conductance. A dynamic parameterization of normalized root system conductance and/or more accurate assimilate allocation to the roots, especially under drought stress, should be considered in order to apply this model in future studies to maize.
Proline accumulation is one of the major responses of plants to many abiotic stresses. However, the significance of proline accumulation for drought stress tolerance remains enigmatic in crop plants. First, we examined the natural variation of the pyrolline‐5‐carboxylate synthase (P5CS1) among 49 barley genotypes. Allele mining identified a previously unknown allelic series that showed polymorphisms at 42 cis‐elements across the P5CS1 promoter. Selected haplotypes had quantitative variation in P5CS1 gene expression and proline accumulation, putatively influenced by both abscisic acid‐dependent and independent pathways under drought stress. Next, we introgressed the P5CS1 allele from a high proline accumulating wild barley accession ISR42‐8 into cultivar Scarlett developing a near‐isogenic line (NIL‐143). NIL‐143 accumulated higher proline concentrations than Scarlett under drought stress at seedling and reproductive stages. Under drought stress, NIL‐143 showed less pigment damage, sustained photosynthetic health, and higher drought stress recovery compared to Scarlett. Further, the drought‐induced damage to yield‐related traits, mainly thousand‐grain weight, was lower in NIL‐143 compared with Scarlett in field conditions. Our data uncovered new variants of the P5CS1 promoter and the significance of the increased proline accumulation regulated by the P5CS1 allele of ISR42‐8 in drought stress tolerance and yield stability in barley.
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