Compositional and functional analysis of the bacterial community of Mediterranean Leptosols under livestock grazing

The composition and functioning of soil bacterial communities, as well as their responses to multiple perturbations, are not well understood in the terrestrial ecosystems. Our study focuses on the bacterial community of erosive and poorly developed soils (Haplic Leptosols) in Mediterranean rangelands of Extremadura (W Spain) with different grazing intensities. Leptosols from similar natural conditions were selected and sampled at two depths to determine the soil properties as well as the structure and activity of bacterial communities. As grazing intensified, the soil C and N content increased, as did the number and diversity of bacteria, mainly of fast-growing lineages. Aridibacter, Acidobacteria Gp6 and Gp10, Gemmatimonas, and Segetibacter increased their abundance along the grazing-intensity gradient. Firmicutes such as Romboutsia and Turicibacter from livestock microbiome also increased. In functional terms, the KEGG pathways enriched in the soils with moderate and high grazing intensity were ABC transporters, DNA repair and recombination proteins, the two-component system, and the degradation of xenobiotics. All of these proved to be related to stronger cell division and response mechanisms to environmental stressors such as drought, warming, toxic substances, and nutrient deprivation. Consequently, the bacterial community was affected by grazing, but appeared to adapt and counteract the effects of a high grazing intensity. Therefore, a clearly detrimental effect of grazing was not detected in the bacterial community of the soils studied.

Influence of 16S rRNA target region on the outcome of microbiome studies in soil and saliva samples

Next generation sequencing methods are widely used in evaluating the structure and functioning of microbial communities, especially those centered on 16S rRNA subunit. Since Illumina Miseq, the most used sequencing platform, does not allow the full sequencing of 16S rRNA gene, this study aims to evaluate whether the choice of different target regions might affect the outcome of microbiome studies regarding soil and saliva samples. V1V3, V3V4, V4V5 and V6V8 domains were studied, finding that while some regions showed differences in the detection of certain bacterial taxa and in the calculation of alpha diversity, especially in soil samples, the overall effect did not compromise the differentiation of any sample type in terms of taxonomic analysis at the genus level. 16S rRNA target regions did affect the detection of specific bacteria related to soil quality and development, and microbial genera used as health biomarkers in saliva. V1V3 region showed the closest similarity to internal sequencing control mock community B, suggesting it might be the most preferable choice regarding data reliability.

Biocrust cover and successional stages influence soil bacterial composition and diversity in semiarid ecosystems

Biocrusts are an important drylands landscape component, which enriches the upper millimeters of the soil with organic matter and initiates biogeochemical cycles. However, little is known about the influence of biocrusts on soil bacterial community structure and diversity. Different biocrust types representing a successional gradient were studied. This gradient, from the earliest to the latest successional stages, consisted of an incipient cyanobacterial biocrust < mature cyanobacterial biocrusts < biocrust dominated by the Squamarina lentigera and Diploschistes diacapsis lichens < Biocrust characterized by the Lepraria isidiata lichen. Moreover, in each biocrust type, four different percentages of biocrust cover were also selected. Soil diversity gradually increased with biocrust successional stage and percentage of biocrust cover. The biocrust cover had an important role in the total abundance of bacteria, generally increasing in soils colonized by the highest percentages of cover. Biocrust successional stage was the most important factor, significantly influencing 108 soil bacteria genera, whereas biocrust cover showed significant differences in only 10 genera. Principal Component Analysis showed contrasting microbial composition across the biocrust successional gradient. Some bacterial taxa were dominant in the soil colonized by different biocrust types. Thus, Leptolyngbya, Rubrobacter, Solirubrobacter, Geodermatophilus, etc., were more abundant in incipient cyanobacteria; Nostocales, Chroococcidiopsaceae, Coleofasciculaceae etc., under mature cyanobacterial biocrusts; Truepera, Sphingobacteriaceae, Actinophytocola, Kribella, etc., below the S. lentigera and D. diacapsis community, and Bryobacter, Ohtaekwangia, Opitutus, Pedosphaeraceae, etc., in soils colonized by L. isidiata. Several soil bacteria taxa showed significant correlations (p < 0.05) with chemical soil properties (pH, total nitrogen, total organic carbon, available phosphorous and electrical conductivity). We discuss the role of biocrusts influencing these chemical soil parameters, including the presence of certain metabolites secreted by biocrusts, and also their effects on soil moisture and several physical soil features, as well as their association with different microclimates, all of which could favor a more selective environment for certain bacteria.

Power functions improving the performance of color-difference formulas

Color-difference formulas modified by power functions provide results in better agreement with visually perceived color differences. Each of the modified color-difference formulas proposed here adds only one relevant parameter to the corresponding original color-difference formula. Results from 16 visual data sets and 11 color-difference formulas indicate that the modified formulas achieve an average decrease of 5.7 STRESS (Standardized Residual Sum of Squares) units with respect to the original formulas, signifying an improvement of 17.3%. In particular, for these 16 visual data sets, the average decrease for the current CIE/ISO recommended color-difference formula CIEDE2000 modified by an exponent 0.70 was 5.4 STRESS units (17.5%). The improvements of all modified color-difference formulas with respect to the original ones held for each of the 16 visual data sets and were statistically significant in most cases, particularly for all data sets with color differences close to the threshold. Results for 2 additional data sets with color pairs in the blue and black regions of the color space confirmed the usefulness of the proposed power functions. The main reason of the improvements found for the modified color-difference formulas with respect to the original color-difference formulas seems to be the compression provided by power functions.