Linking alkaline phosphatase activity with bacterial phoD gene abundance in soil from a long-term management trial

Changes in land management practices may have significant implications for soil microbial communities important in organic P turnover. Soil bacteria can increase plant P availability by excreting phosphatase enzymes which catalyze the hydrolysis of ester-phosphate bonds. Examining the diversity and abundance of alkaline phosphatase gene harboring bacteria may provide valuable insight into alkaline phosphatase production in soils. This study examined the effect of 20 years of no input organic (ORG), organic with composted manure (ORG + M), conventional (CONV) and restored prairie (PRA) management on soil P bioavailability, alkaline phosphatase activity (ALP), and abundance and diversity of ALP gene (phoD) harboring bacteria in soils from the northern Great Plains of Canada. Management system influenced bioavailable P (P < 0.001), but not total P, with the lowest concentrations in the ORG systems and the highest in PRA. Higher rates of ALP were observed in the ORG and ORG + M treatments with a significant negative correlation between bioavailable P and ALP in 2011 (r2 = 0.71; P = 0.03) and 2012 (r2 = 0.51; P = 0.02), suggesting that ALP activity increased under P limiting conditions. The phoD gene abundance was also highest in ORG and ORG + M resulting in a significant positive relationship between bacterial phoD abundance and ALP activity (r2 = 0.71; P = 0.009). Analysis of phoD bacterial community fingerprints showed a higher number of species in CONV compared to ORG and ORG + M, contrary to what was expected considering greater ALP activity under ORG management. In 2012, banding profiles of ORG + M showed fewer phoD bacterial species following the second manure application, although ALP activity is higher than in 2011. This indicates that a few species may be producing more ALP and that quantitative gene analysis was a better indicator of activity than the number of species present.

Soil bacterial phoD gene abundance and expression in response to applied phosphorus and long-term management

Bacterial transformation of phosphorus (P) compounds in soil is largely dependent on soil microbial community function, and is therefore sensitive to anthropogenic disturbances such as fertilization or cropping systems. However, the effect of soil management on the transcription of bacterial genes that encode phosphatases, such as phoD, is largely unknown. This greenhouse study examined the effect of long-term management and P amendment on potential alkaline phosphatase (ALP) activity and phoD gene (DNA) and transcript (RNA) abundance. Soil samples (0–15 cm) were collected from the Glenlea Long-term Rotation near Winnipeg, Manitoba, to compare organic, conventional and prairie management systems. In the greenhouse, pots of soil from each management system were amended with P as either soluble mineral fertilizer or cattle manure and then planted with Italian ryegrass (Lolium multiforum). Soils from each pot were sampled for analysis immediately and after 30 and 106 days. Significant differences among the soil/P treatments were detected for inorganic P, but not the organic P in NaHCO3-extracts. At day 0, ALP activity was similar among the soil/P treatments, but was higher after 30 days for all P amendments in soil from organically managed plots. In contrast, ALP activity in soils under conventional and prairie management responded to increasing rates of manure only, with significant effects from medium and high manure application rates at 30 and 106 days. Differences in ALP activity at 30 days corresponded to the abundance of bacterial phoD genes, which were also significantly higher in soils under organic management. However, this correlation was not significant for transcript abundance. Next-generation sequencing allowed the identification of 199 unique phoD operational taxonomic units (OTUs) from the metagenome (soil DNA) and 35 unique OTUs from the metatranscriptome (soil RNA), indicating that a subset of phoD genes was being transcribed in all soils.

Wheat seed embryo excision enables the creation of axenic seedlings and Koch’s postulates testing of putative bacterial endophytes

Early establishment of endophytes can play a role in pathogen suppression and improve seedling development. One route for establishment of endophytes in seedlings is transmission of bacteria from the parent plant to the seedling via the seed. In wheat seeds, it is not clear whether this transmission route exists, and the identities and location of bacteria within wheat seeds are unknown. We identified bacteria in the wheat (Triticum aestivum) cv. Hereward seed environment using embryo excision to determine the location of the bacterial load. Axenic wheat seedlings obtained with this method were subsequently used to screen a putative endophyte bacterial isolate library for endophytic competency. This absence of bacteria recovered from seeds indicated low bacterial abundance and/or the presence of inhibitors. Diversity of readily culturable bacteria in seeds was low with 8 genera identified, dominated by Erwinia and Paenibacillus. We propose that anatomical restrictions in wheat limit embryo associated vertical transmission, and that bacterial load is carried in the seed coat, crease tissue and endosperm. This finding facilitates the creation of axenic wheat plants to test competency of putative endophytes and also provides a platform for endophyte competition, plant growth, and gene expression studies without an indigenous bacterial background.

A constrained recursive least squares algorithm for adaptive combination of multiple models

In this paper, we develop a novel constrained recursive least squares algorithm for adaptively combining a set of given multiple models. With data available in an online fashion, the linear combination coefficients of submodels are adapted via the proposed algorithm.We propose to minimize the mean square error with a forgetting factor, and apply the sum to one constraint to the combination parameters. Moreover an l1-norm constraint to the combination parameters is also applied with the aim to achieve sparsity of multiple models so that only a subset of models may be selected into the final model. Then a weighted l2-norm is applied as an approximation to the l1-norm term. As such at each time step, a closed solution of the model combination parameters is available. The contribution of this paper is to derive the proposed constrained recursive least squares algorithm that is computational efficient by exploiting matrix theory. The effectiveness of the approach has been demonstrated using both simulated and real time series examples.

A generalised background correction algorithm for a Halo Doppler lidar and its application to data from Finland

Current commercially available Doppler lidars provide an economical and robust solution for measuring vertical and horizontal wind velocities, together with the ability to provide co- and cross-polarised backscatter profiles. The high temporal resolution of these instruments allows turbulent properties to be obtained from studying the variation in radial velocities. However, the instrument specifications mean that certain characteristics, especially the background noise behaviour, become a limiting factor for the instrument sensitivity in regions where the aerosol load is low. Turbulent calculations require an accurate estimate of the contribution from velocity uncertainty estimates, which are directly related to the signal-to-noise ratio. Any bias in the signal-to-noise ratio will propagate through as a bias in turbulent properties. In this paper we present a method to correct for artefacts in the background noise behaviour of commercially available Doppler lidars and reduce the signal-to-noise ratio threshold used to discriminate between noise, and cloud or aerosol signals. We show that, for Doppler lidars operating continuously at a number of locations in Finland, the data availability can be increased by as much as 50 % after performing this background correction and subsequent reduction in the threshold. The reduction in bias also greatly improves subsequent calculations of turbulent properties in weak signal regimes.