Soil depth and geographic distance modulate bacterial ß-diversity in deep soil profiles throughout the U.S. Corn Belt.

Understanding how microbial communities are shaped across spatial dimensions is of fundamental importance in microbial ecology. However, most studies on soil biogeography have focused on the topsoil microbiome, while the factors driving the subsoil microbiome distribution are largely unknown. Here we used 16S rRNA amplicon sequencing to analyse the factors underlying the bacterial ß-diversity along vertical (0-240 cm of soil depth) and horizontal spatial dimensions (~500,000 km2 ) in the U.S. Corn Belt. With these data we tested whether the horizontal or vertical spatial variation had stronger impacts on the taxonomic (Bray-Curtis) and phylogenetic (weighted Unifrac) ß-diversity. Additionally, we assessed whether the distance-decay (horizontal dimension) was greater in the topsoil (0-30 cm) or subsoil (in each 30 cm layer from 30-240 cm) using Mantel tests. The influence of geographic distance versus edaphic variables on the bacterial communities from the different soil layers was also compared. Results indicated that the phylogenetic ß-diversity was impacted more by soil depth, while the taxonomic ß-diversity changed more between geographic locations. The distance-decay was lower in the topsoil than in all subsoil layers analysed. Moreover, some subsoil layers were influenced more by geographic distance than any edaphic variable, including pH. Although different factors affected the topsoil and subsoil biogeography, niche-based models explained the community assembly of all soil layers. This comprehensive study contributed to elucidating important aspects of soil bacterial biogeography including the major impact of soil depth on the phylogenetic ß-diversity, and the greater influence of geographic distance on subsoil than on topsoil bacterial communities in agroecosystems.

Sugars and Jasmonic Acid Concentration in Root Exudates Affect Maize Rhizosphere Bacterial Communities.

Root exudates contribute to shaping the root-associated microbiomes, but it is unclear which of the many exudate compounds are important in this process. Here, we focused on understanding the influence of sugars and jasmonic acid (JA) concentrations in maize root exudates on the rhizobacterial communities. Twelve maize genotypes were identified with variable concentrations of sugars and JA based on a screening of 240 maize genotypes grown in a semihydroponic system. These twelve maize genotypes were grown in a replicated field experiment in which samples were collected at three maize developmental stages. The 16S rRNA gene (V4 region) was amplified and sequenced. Sugars and JA concentrations from rhizosphere soils were also quantified. The results indicated that the maize genotypic variability in sugars and JA concentration in root exudates, measured in the semihydroponic system, significantly affected the rhizosphere bacterial community composition at multiple stages plant development. In contrast, the root endosphere and bulk soil bacterial communities were only affected at specific growth stages. Sugars and JA concentration as quantified in rhizosphere soil samples confirmed that these two compounds affected the rhizobacterial communities at all developmental stages analyzed. The effects of specific sugars on the composition of the rhizobacterial communities were also measured, with larger effects of sucrose at earlier developmental stages and trehalose at later developmental stages. Our results indicate that JA and sugars are important root exudate compounds that influence the composition of the maize rhizobacterial communities. IMPORTANCE Roots secrete exudates that are important in interactions with soil microbes that promote plant growth and health. However, the exact chemical compounds in root exudates that participate in these interactions are not fully known. Here, we investigated whether sugars and the phytohormone jasmonic acid influence the composition of the rhizobacterial communities of maize, which is an important crop for food, feed, and energy. Our results revealed that both compounds contribute to the assemblage of rhizobacterial communities at different maize developmental stages. Knowledge about the specific compounds in root exudates that contribute to shape the rhizobiome will be important for future strategies to develop sustainable agricultural practices that are less dependent on agrochemicals.

Root exudate concentrations of indole-3-acetic acid (IAA) and abscisic acid (ABA) affect maize rhizobacterial communities at specific developmental stages.

Root exudates shape the rhizosphere microbiome, but little is known about the specific compounds in root exudates that are important. Here, we investigated the impacts of the plant-synthesized phytohormones indole-3-acetic acid (IAA) and abscisic acid (ABA) exuded by roots on the maize rhizobacterial communities. To identify maize genotypes that differed in the root exudate concentrations of IAA and ABA, we screened hundreds of inbred lines using a semi-hydroponic system. Twelve genotypes with variable exudate concentrations of IAA and ABA were selected for a replicated field experiment. Bulk soil, rhizosphere, and root endosphere samples were collected at two vegetative and one reproductive maize developmental stage. IAA and ABA concentrations in rhizosphere samples were quantified by liquid chromatography-mass spectrometry. The bacterial communities were analyzed by V4 16S rRNA amplicon sequencing. Results indicated that IAA and ABA concentrations in root exudates significantly affected the rhizobacterial communities at specific developmental stages. ABA impacted the rhizosphere bacterial communities at later developmental stages, whereas IAA affected the rhizobacterial communities at the vegetative stages. This study contributed to our knowledge about the influence that specific root exudate compounds have on the rhizobiome composition, showing that the phytohormones IAA and ABA exuded by roots have a role in the plant-microbiome interactions.

Assessment of Bacterial Inoculant Delivery Methods for Cereal Crops.

Despite growing evidence that plant growth-promoting bacteria can be used to improve crop vigor, a comparison of the different methods of delivery to determine which is optimal has not been published. An optimal inoculation method ensures that the inoculant colonizes the host plant so that its potential for plant growth-promotion is fully evaluated. The objective of this study was to compare the efficacy of three seed coating methods, seedling priming, and soil drench for delivering three bacterial inoculants to the sorghum rhizosphere and root endosphere. The methods were compared across multiple time points under axenic conditions and colonization efficiency was determined by quantitative polymerase chain reaction (qPCR). Two seed coating methods were also assessed in the field to test the reproducibility of the greenhouse results under non-sterile conditions. In the greenhouse seed coating methods were more successful in delivering the Gram-positive inoculant (Terrabacter sp.) while better colonization from the Gram-negative bacteria (Chitinophaga pinensis and Caulobacter rhizosphaerae) was observed with seedling priming and soil drench. This suggested that Gram-positive bacteria may be more suitable for the seed coating methods possibly because of their thick peptidoglycan cell wall. We also demonstrated that prolonged seed coating for 12 h could effectively enhance the colonization of C. pinensis, an endophytic bacterium, but not the rhizosphere colonizing C. rhizosphaerae. In the field only a small amount of inoculant was detected in the rhizosphere. This comparison demonstrates the importance of using the appropriate inoculation method for testing different types of bacteria for their plant growth-promotion potential.

Sequencing-Based Bin Map Construction of a Tomato Mapping Population, Facilitating High-Resolution Quantitative Trait Loci Detection.

Genotyping-by-sequencing (GBS) was employed to construct a highly saturated genetic linkage map of a tomato ( L.) recombinant inbred line (RIL) population, derived from a cross between cultivar NC EBR-1 and the wild tomato L. accession LA2093. A pipeline was developed to convert single nucleotide polymorphism (SNP) data into genomic bins, which could be used for fine mapping of quantitative trait loci (QTL) and identification of candidate genes. The pipeline, implemented in a python script named SNPbinner, adopts a hidden Markov model approach for calculation of recombination breakpoints followed by genomic bins construction. The total length of the newly developed high-resolution genetic map was 1.2-fold larger than previously estimated based on restriction fragment length polymorphism (RFLP) and polymerase chain reaction (PCR)-based markers. The map was used to verify and refine QTL previously identified for two fruit quality traits in the RIL population, fruit weight (FW) and fruit lycopene content (LYC). Two well-described FW QTL ( and ) were localized precisely at their known underlying causative genes, and the QTL intervals were decreased by two- to tenfold. A major QTL for LYC content () was verified at high resolution and its underlying causative gene was determined to be ζ (). The RIL population, the high resolution genetic map, and the easy-to-use genotyping pipeline, SNPbinner, are made publicly available.