The Golden Goal of Soil Management: Disease-Suppressive Soils.

Disease-suppressive soils encompass specific plant-pathogen-microbial interactions and represent a rare example of an agroecosystem where soil conditions and microbiome together prevent the pathogen from causing disease. Such soils have the potential to serve as a model for characterizing soil pathogen-related aspects of soil health, but the mechanisms driving the establishment of suppressive soils vary and are often poorly characterized. Yet, they can serve as a resource for identifying markers for beneficial activities of soil microorganisms concerning pathogen prevention. Many recent studies have focused on the nature of disease-suppressive soils, but it has remained difficult to predict where and when they will occur. This review outlines current knowledge on the distribution of these soils, soil manipulations leading to pathogen suppression, and markers including bacterial and fungal diversity, enzymes, and secondary metabolites. The importance to consider soil legacy in research on the principles that define suppressive soils is also highlighted. The goal is to extend the context in which we understand, study, and use disease-suppressive soils by evaluating the relationships in which they occur and function. Finally, we suggest that disease-suppressive soils are critical not only for the development of indicators of soil health, but also for the exploration of general ecological principles about the surrounding landscape, effects of deeper layers of the soil profile, little studied soil organisms, and their interactions for future use in modern agriculture.

Multi-level stratification of territories for waste composition analysis.

The fundamental knowledge at all levels of decision-making related to waste management is the quantity and composition of waste. Many articles deal with methods for estimating the composition of municipal waste, but most details are given as to how many categories should be chosen and what technical procedure should be followed. In order to obtain a broader view and a reasonable evaluation of the results, it is necessary to select the areas where the analyzes will be performed effectively. Current approaches have insufficiently addressed this issue at the regional and national levels. This paper presents a method that uses multi-level stratification to divide municipalities into similar groups to reduce the number of observations needed to obtain an estimate of the composition of waste in a selected area (region or state level). The method combines expert knowledge with statistical considerations and makes use of cluster analysis. Socio-economic and waste-related parameters are used within the individual steps. Regarding the available financial resources and the required accuracy of the results, the municipalities in which the analyzes should take place are selected. These representative municipalities represent other municipalities in the created groups, and thanks to them, it is possible to estimate the composition of waste in any municipality, region, or larger territory. Waste analysis planning is an essential procedure for waste management, but the respective costs represent a crucial factor at the national level and even more for individual municipalities. Estimating waste composition impacts the transition to sustainable waste management and is thus a key element for further development in this sector. The presented method demonstrates the selection of 10 representative municipalities from the Czech Republic, but an arbitrary number can be set respecting the financial resources. Estimating the composition of the mixed municipal waste for the Czech Republic should cost around 72,000 euros for ten representatives with different distribution of dwelling types. The method is described in general and can be applied to any territory/country in the world, considering local conditions and possibilities.

Multivariate Tail Coefficients: Properties and Estimation.

Multivariate tail coefficients are an important tool when investigating dependencies between extreme events for different components of a random vector. Although bivariate tail coefficients are well-studied, this is, to a lesser extent, the case for multivariate tail coefficients. This paper contributes to this research area by (i) providing a thorough study of properties of existing multivariate tail coefficients in the light of a set of desirable properties; (ii) proposing some new multivariate tail measurements; (iii) dealing with estimation of the discussed coefficients and establishing asymptotic consistency; and, (iv) studying the behavior of tail measurements with increasing dimension of the random vector. A set of illustrative examples is given, and practical use of the tail measurements is demonstrated in a data analysis with a focus on dependencies between stocks that are part of the EURO STOXX 50 market index.

Phylogenetic relatedness determined between antibiotic resistance and 16S rRNA genes in actinobacteria.

BACKGROUND: Distribution and evolutionary history of resistance genes in environmental actinobacteria provide information on intensity of antibiosis and evolution of specific secondary metabolic pathways at a given site. To this day, actinobacteria producing biologically active compounds were isolated mostly from soil but only a limited range of soil environments were commonly sampled. Consequently, soil remains an unexplored environment in search for novel producers and related evolutionary questions. RESULTS: Ninety actinobacteria strains isolated at contrasting soil sites were characterized phylogenetically by 16S rRNA gene, for presence of erm and ABC transporter resistance genes and antibiotic production. An analogous analysis was performed in silico with 246 and 31 strains from Integrated Microbial Genomes (JGI_IMG) database selected by the presence of ABC transporter genes and erm genes, respectively. In the isolates, distances of erm gene sequences were significantly correlated to phylogenetic distances based on 16S rRNA genes, while ABC transporter gene distances were not. The phylogenetic distance of isolates was significantly correlated to soil pH and organic matter content of isolation sites. In the analysis of JGI_IMG datasets the correlation between phylogeny of resistance genes and the strain phylogeny based on 16S rRNA genes or five housekeeping genes was observed for both the erm genes and ABC transporter genes in both actinobacteria and streptomycetes. However, in the analysis of sequences from genomes where both resistance genes occurred together the correlation was observed for both ABC transporter and erm genes in actinobacteria but in streptomycetes only in the erm gene. CONCLUSIONS: The type of erm resistance gene sequences was influenced by linkage to 16S rRNA gene sequences and site characteristics. The phylogeny of ABC transporter gene was correlated to 16S rRNA genes mainly above the genus level. The results support the concept of new specific secondary metabolite scaffolds occurring more likely in taxonomically distant producers but suggest that the antibiotic selection of gene pools is also influenced by site conditions.

Testing for homogeneity of multivariate dispersions using dissimilarity measures.

Testing homogeneity of dispersions may be of its own scientific interest as well as an important auxiliary step verifying assumptions of a main analysis. The problem is that many biological and ecological data are highly skewed and zero-inflated. Also the number of variables often exceeds the sample size. Thus data analysts often do not rely on parametric assumptions, but use a particular dissimilarity measure to calculate a matrix of pairwise differences. This matrix is then the basis for further statistical inference. Anderson (2006) proposed a distance-based test of homogeneity of multivariate dispersions for a one-way ANOVA design, for which a matrix of pairwise dissimilarities can be taken as an input. The key idea, like in Levene's test, is to replace each observation with its distance to an estimated group center. In this paper we suggest an alternative approach that is based on the means of within-group distances and does not require group centre calculations to obtain the test statistic. We show that this approach can have theoretical as well as practical advantages. A permutation procedure that gives type I error close to the prescribed value even in small samples is described.

Phylogenetically related soil actinomycetes distinguish isolation sites by their metabolic activities.

Soil environments are inhabited by microorganisms adapted to its diversified microhabitats. The metabolic activity of individual strains/populations reflects resources available at a particular spot, quality of which may not comply with broad soil characteristics. To explore the potential of individual strains to adapt to particular micro-niches of carbon sources, a set of 331 Actinomycetia strains were collected at ten sites differing in vegetation, soil pH, organic matter content and quality. The strains were isolated on the same complex medium with neutral pH and their metabolites analyzed by UHPLC and LC-MS/MS in spent cultivation medium (metabolic profiles). For all strains, their metabolic profiles correlated with soil pH and organic matter content of the original sites. In comparison, strains phylogeny based on either 16S rRNA or the beta-subunit of DNA-dependent RNA polymerase (rpoB) genes was partially correlated with soil organic matter content but not soil pH at the sites. Antimicrobial activities of strains against Kocuria rhizophila, Escherichia coli, and Saccharomyces cerevisiae were both site- and phylogeny-dependent. The precise adaptation of metabolic profiles to overall sites characteristics was further supported by the production of locally specific bioactive metabolites and suggested that carbon resources represent a significant selection pressure connected to specific antibiotic activities.

Microbial communities show parallels at sites with distinct litter and soil characteristics.

Plant and microbial community composition in connection with soil chemistry determines soil nutrient cycling. The study aimed at demonstrating links between plant and microbial communities and soil chemistry occurring among and within four sites: two pine forests with contrasting soil pH and two grasslands of dissimilar soil chemistry and vegetation. Soil was characterized by C and N content, particle size, and profiles of low-molecular-weight compounds determined by high-performance liquid chromatography (HPLC) of soil extracts. Bacterial and actinobacterial community composition was assessed by terminal restriction fragment length polymorphism (T-RFLP) and cloning followed by sequencing. Abundances of bacteria, fungi, and actinobacteria were determined by quantitative PCR. In addition, a pool of secondary metabolites was estimated by erm resistance genes coding for rRNA methyltransferases. The sites were characterized by a stable proportion of C/N within each site, while on a larger scale, the grasslands had a significantly lower C/N ratio than the forests. A Spearman's test showed that soil pH was correlated with bacterial community composition not only among sites but also within each site. Bacterial, actinobacterial, and fungal abundances were related to carbon sources while T-RFLP-assessed microbial community composition was correlated with the chemical environment represented by HPLC profiles. Actinobacteria community composition was the only studied microbial characteristic correlated to all measured factors. It was concluded that the microbial communities of our sites were influenced primarily not only by soil abiotic characteristics but also by dominant litter quality, particularly, by percentage of recalcitrant compounds.

Detection of residual B precursor lymphoblastic leukemia by uniform gating flow cytometry.

BACKGROUND: Residual disease (RD) is an important prognostic factor in acute lymphoblastic leukemia (ALL). Flow cytometry (FC)-based RD detection is easy to perform, but interpretation requires expert analysis due to individual differences among patients. PROCEDURE: We focused at the design of standardized and reproducible RD monitoring in ALL. RD was investigated by a uniform gating strategy, which was designed internationally and tested in one center by Ig/TCR rearrangements. RESULTS: For each gate, positivity cutoff value was assigned using quantification of non-leukemic background. Comparing to Ig/TCR at 0.1% level, 80 of 103 specimens were correctly diagnosed by FC. The predictive value of FC RD at day 15 was then analyzed. In B lineage ALL, day 15 FC significantly correlated with Ig/TCR results at day 33 and/or week 12 (P < 0.01). No significant correlation was found in T lineage ALL. CONCLUSIONS: Thus, FC with preset uniform gating at day 15 predicts PCR-detectable MRD in B precursor ALL. Presented data may be used to define new polychromatic cytometric diagnostics of MRD including semiautomatic assessment. Pediatr Blood Cancer 2010; 54:62-70. (c) 2009 Wiley-Liss, Inc.

DNA conformations and their sequence preferences.

The geometry of the phosphodiester backbone was analyzed for 7739 dinucleotides from 447 selected crystal structures of naked and complexed DNA. Ten torsion angles of a near-dinucleotide unit have been studied by combining Fourier averaging and clustering. Besides the known variants of the A-, B- and Z-DNA forms, we have also identified combined A + B backbone-deformed conformers, e.g. with alpha/gamma switches, and a few conformers with a syn orientation of bases occurring e.g. in G-quadruplex structures. A plethora of A- and B-like conformers show a close relationship between the A- and B-form double helices. A comparison of the populations of the conformers occurring in naked and complexed DNA has revealed a significant broadening of the DNA conformational space in the complexes, but the conformers still remain within the limits defined by the A- and B- forms. Possible sequence preferences, important for sequence-dependent recognition, have been assessed for the main A and B conformers by means of statistical goodness-of-fit tests. The structural properties of the backbone in quadruplexes, junctions and histone-core particles are discussed in further detail.

Bacterial, archaeal and micro-eukaryotic communities characterize a disease-suppressive or conducive soil and a cultivar resistant or susceptible to common scab.

Control of common scab disease can be reached by resistant cultivars or suppressive soils. Both mechanisms are likely to translate into particular potato microbiome profiles, but the relative importance of each is not known. Here, microbiomes of bulk and tuberosphere soil and of potato periderm were studied in one resistant and one susceptible cultivar grown in a conducive and a suppressive field. Disease severity was suppressed similarly by both means yet, the copy numbers of txtB gene (coding for a pathogenicity determinant) were similar in both soils but higher in periderms of the susceptible cultivar from conducive soil. Illumina sequencing of 16S rRNA genes for bacteria (completed by 16S rRNA microarray approach) and archaea, and of 18S rRNA genes for micro-eukarytes showed that in bacteria, the more important was the effect of cultivar and diversity decreased from resistant cultivar to bulk soil to susceptible cultivar. The major changes occurred in proportions of Actinobacteria, Chloroflexi, and Proteobacteria. In archaea and micro-eukaryotes, differences were primarily due to the suppressive and conducive soil. The effect of soil suppressiveness × cultivar resistance depended on the microbial community considered, but differed also with respect to soil and plant nutrient contents particularly in N, S and Fe.

A Short-Term Response of Soil Microbial Communities to Cadmium and Organic Substrate Amendment in Long-Term Contaminated Soil by Toxic Elements.

Two long-term contaminated soils differing in contents of Pb, Zn, As, Cd were compared in a microcosm experiment for changes in microbial community structure and respiration after various treatments. We observed that the extent of long-term contamination (over 200 years) by toxic elements did not change the total numbers and diversity of bacteria but influenced their community composition. Namely, numbers of Actinobacteria determined by phylum specific qPCR increased and also the proportion of Actinobacteria and Chloroflexi increased in Illumina sequence libraries in the more contaminated soil. In the experiment, secondary disturbance by supplemented cadmium (doses from double to 100-fold the concentration in the original soil) and organic substrates (cellobiose or straw) increased bacterial diversity in the less contaminated soil and decreased it in the more contaminated soil. Respiration in the experiment was higher in the more contaminated soil in all treatments and correlated with bacterial numbers. Considering the most significant changes in bacterial community, it seemed that particularly Actinobacteria withstand contamination by toxic elements. The results proved higher resistance to secondary disturbance in terms of both, respiration and bacterial community structure in the less contaminated soil.

The effect of peat and iron supplements on the severity of potato common scab and bacterial community in tuberosphere soil.

The control of common scab (CS) of potatoes includes resistant cultivars, specific fertilization, increase of soil moisture and chemical treatments. Yet, these management practices do not have common or reproducible results at differing sites. In order to determine the effects of soil organic matter, iron and pH on CS development, peat and DTPA-chelated iron were supplemented to pots filled with soil conducive for CS. All results were compared with the same data obtained for a suppressive soil, which has naturally low severity of CS and occurs nearby. Bacteria, Actinobacteria and the txtB genes from the biosynthetic cluster of thaxtomin, which is responsible for the disease development, were quantified by qPCR in tuberosphere soil and potato periderm. Illumina amplicon sequencing of bacterial 16S rRNA genes was performed for tuberosphere soils. Both peat and iron supplements controlled potato scab, and the combination of the two supplements reduced CS most effectively. The bacterial community was modified by all treatments but the highest number of operational taxonomic units (OTUs) changed towards the suppressive soil after the combined peat and iron treatment. It seemed that iron supplement supported plant defense while both iron and peat additions changed the bacterial community in favor of CS suppression.

Determination of factors associated with natural soil suppressivity to potato common scab.

Common scab of potatoes is a disease, which is difficult to manage due to complex interactions of the pathogenic bacteria (Streptomyces spp.) with soil, microbial community and potato plants. In Bohemian-Moravian Highlands in the Czech Republic two sites (Vyklantice and Zdirec) were selected for a study of common scab disease suppressivity. At both sites, a field with low disease severity occurs next to one with high severity and the situation was regularly observed over four decades although all four fields undergo a crop rotation. In the four fields, quantities of bacteria, actinobacteria and the gene txtB from the biosynthetic gene cluster of thaxtomin, the main pathogenicity factor of common scab, were analyzed by real-time PCR. Microbial community structure was compared by terminal fragment length polymorphism analysis. Soil and potato periderm were characterized by contents of carbon, nitrogen, phosphorus, sulphur, calcium, magnesium, and iron. Quality of organic matter was assessed by high performance liquid chromatography of soil extracts. The study demonstrated that the suppressive character of the fields is locally specific. At Zdirec, the suppressivity was associated with low txtB gene copies in bulk soil, while at Vyklantice site it was associated with low txtB gene copies in the tuberosphere. The differences were discussed with respect to the effect of abiotic conditions at Zdirec and interaction between potato plant and soil microbial community at Vyklantice. Soil pH, Ca soil content or cation concentrations, although different were not in the range to predict the disease severity. Low severity of common scab was associated with low content of soil C, N, C/N, Ca and Fe suggesting that oligotrophic conditions may be favorable to common scab suppression.

Development of methods for cross-sectional HIV incidence estimation in a large, community randomized trial.

BACKGROUND: Accurate methods of HIV incidence determination are critically needed to monitor the epidemic and determine the population level impact of prevention trials. One such trial, Project Accept, a Phase III, community-randomized trial, evaluated the impact of enhanced, community-based voluntary counseling and testing on population-level HIV incidence. The primary endpoint of the trial was based on a single, cross-sectional, post-intervention HIV incidence assessment. METHODS AND FINDINGS: Test performance of HIV incidence determination was evaluated for 403 multi-assay algorithms [MAAs] that included the BED capture immunoassay [BED-CEIA] alone, an avidity assay alone, and combinations of these assays at different cutoff values with and without CD4 and viral load testing on samples from seven African cohorts (5,325 samples from 3,436 individuals with known duration of HIV infection [1 month to >10 years]). The mean window period (average time individuals appear positive for a given algorithm) and performance in estimating an incidence estimate (in terms of bias and variance) of these MAAs were evaluated in three simulated epidemic scenarios (stable, emerging and waning). The power of different test methods to detect a 35% reduction in incidence in the matched communities of Project Accept was also assessed. A MAA was identified that included BED-CEIA, the avidity assay, CD4 cell count, and viral load that had a window period of 259 days, accurately estimated HIV incidence in all three epidemic settings and provided sufficient power to detect an intervention effect in Project Accept. CONCLUSIONS: In a Southern African setting, HIV incidence estimates and intervention effects can be accurately estimated from cross-sectional surveys using a MAA. The improved accuracy in cross-sectional incidence testing that a MAA provides is a powerful tool for HIV surveillance and program evaluation.

Actinobacterial community dominated by a distinct clade in acidic soil of a waterlogged deciduous forest.

Members of the Actinobacteria are among the most important litter decomposers in soil. The site of a waterlogged deciduous forest with acidic soil was explored for actinobacteria because seasonality of litter inputs, temperature, and precipitation provided contrasting environmental conditions, particularly variation of organic matter quantity and quality. We hypothesized that these factors, which are known to influence decomposition, were also likely to affect actinobacterial community composition. The relationship between the actinobacterial community, soil moisture and organic matter content was assessed in two soil horizons in the summer and winter seasons using a 16S rRNA taxonomic microarray and cloning-sequencing of 16S rRNA genes. Both approaches showed that the community differed significantly between horizons and seasons, paralleling the changes in soil moisture and organic matter content. The microarray analysis further indicated that the actinobacterial community of the upper horizon was characterized by high incidence of the genus Mycobacterium. In both horizons and seasons, the actinobacterial clone libraries were dominated (by 80%) by sequences of a separate clade sharing an ancestral node with Streptosporangineae. This relatedness is supported also by some common adaptations, for example, to soil acidity and periodic oxygen deprivation or dryness.

Development of a 16S rRNA gene-based prototype microarray for the detection of selected actinomycetes genera.

Actinomycetes are known for their secondary metabolites, which have been successfully used as drugs in human and veterinary medicines. However, information on the distribution of this group of Gram-positive bacteria in diverse ecosystems and a comprehension of their activities in ecosystem processes are still scarce. We have developed a 16S rRNA-based taxonomic microarray that targets key actinomycetes at the genus level. In total, 113 actinomycete 16S rRNA probes, corresponding to 55 of the 202 described genera, were designed. The microarray accuracy was evaluated by comparing signal intensities with probe/target-weighted mismatch values and the Gibbs energy of the probe/target duplex formation by hybridizing 17 non-actinomycete and 29 actinomycete strains/clones with the probe set. The validation proved that the probe set was specific, with only 1.3% of false results. The incomplete coverage of actinomycetes by a genus-specific probe was caused by the limited number of 16S rRNA gene sequences in databases or insufficient 16S rRNA gene polymorphism. The microarray enabled discrimination between actinomycete communities from three forest soil samples collected at one site. Cloning and sequencing of 16S rRNA genes from one of the soil samples confirmed the microarray results. We propose that this newly constructed microarray will be a valuable tool for genus-level comparisons of actinomycete communities in various ecological conditions.