Quantification of Ammonia Oxidizing Bacterial Abundances in Environmental Samples by Quantitative-PCR

Effect of Ammonia-Oxidizing Bacterial Strains That Coexist in Rhizosphere Soil on Italian Ryegrass Regrowth

Potted Italian ryegrasses (Lolium multiflorum L.) were used to investigate the effect of ammonia-oxidizing bacterial (AOB) strain that coexisted in rhizosphere soil on Italian ryegrass regrowth. The results showed that the isolated and screened AOB strain (S2_8_1) had 100% similarity to Ensifer sesbaniae. The inoculation of S2_8_1 on day 44 before defoliation caused its copy number in rhizosphere soils to increase by 83-157% from day 34 before defoliation to day 14 after defoliation compared with that in Italian ryegrass without S2_8_1 inoculation, indicating that S2_8_1 coexisted permanently with Italian ryegrass. The coexistence promoted the delivery of root-derived cytokinin to leaves and to increase its cytokinin concentrations; thus, the Italian ryegrass regrowth accelerated. During the 14-day regrowth period, the S2_8_1 coexistence with Italian ryegrass caused its leaf and xylem sap cytokinin concentrations, rhizosphere soil nitrification rates, net photosynthetic rates, and total biomass to increase by 38%, 58%, 105%, 18%, and 39% on day 14 after defoliation, respectively. The inoculation of S2_8_1 on day 2 before defoliation also increased the regrowth of Italian ryegrass. Thus, the coexistence of AOB with Italian ryegrass increased its regrowth by regulating the delivery of cytokinins from roots to leaves.

Effect of ammonia-oxidizing bacterial strain that survives drought stress on corn compensatory growth upon post-drought rewatering

A pot experiment was performed under rain-shelter conditions to explore the effects of drought stress and post-drought rewatering on the abundance of an ammonia-oxidizing bacteria (AOB) strain in corn (Zea mays L.) rhizosphere soils and the relationship between the AOB strain and corn (Zea mays L.) compensatory growth after drought stress rewatering. Corn seedlings were used as test materials, and one AOB strain was isolated and screened from the soil. The experimental design included six treatments: (1) wet (WT), (2) wet with AOB strain inoculation during wetness (WI), (3) wet with AOB strain inoculation during rewatering (WR), (4) post-drought rewatering (DT), (5) post-drought rewatering with AOB strain inoculation during wetness (DI), and (6) post-drought rewatering with AOB strain inoculation during rewatering (DR). Wetness and drought stress were obtained by keeping the soil water content at 75-80% and 50-55% of the field capacities, respectively. The results showed that the isolated and screened AOB strain (S2_8_1) had 100% similarity to Ensifer sesbaniae. The inoculation of S2_8_1 during the wet period in the DI treatment caused it to colonize the rhizosphere soil. Drought stress decreased its abundance, but rewatering resulted in a great increase. The S2_8_1 in the DI treatment increased the total biomass, water use efficiencies, net photosynthetic rates, rhizosphere soil nitrification rates, leaf cytokinin concentrations, xylem sap cytokinin concentrations, copy number of S2_8_1 in rhizosphere soils, and organic carbon contents in rhizosphere soils by 23, 104, 35, 30, 18, 29, 104, and 23% on day 10 after rewatering compared with WT treatment. In the DI treatment, the increase in rhizosphere soil nitrification rates caused by S2_8_1 during wetness was closely related to the cytokinin delivery from roots to leaves and increased leaf cytokinin concentrations. The increase in leaf cytokinin concentrations improved rewatering corn growth, which caused compensatory growth and increased water use. Compensatory and over-compensatory growths occurred in DT and DR treatments, respectively. Therefore, the coexistence of the strain of AOB with corn in rhizosphere soil increased the corn compensatory growth by regulating soil nitrification and root-induced leaf cytokinin.

Current Applications of Absolute Bacterial Quantification in Microbiome Studies and Decision-Making Regarding Different Biological Questions

High throughput sequencing has emerged as one of the most important techniques for characterizing microbial dynamics and revealing bacteria and host interactions. However, data interpretation using this technique is mainly based on relative abundance and ignores total bacteria load. In certain cases, absolute abundance is more important than compositional relative data, and interpretation of microbiota data based solely on relative abundance can be misleading. The available approaches for absolute quantification are highly diverse and challenging, especially for quantification in differing biological situations, such as distinguishing between live and dead cells, quantification of specific taxa, enumeration of low biomass samples, large sample size feasibility, and the detection of various other cellular features. In this review, we first illustrate the importance of integrating absolute abundance into microbiome data interpretation. Second, we briefly discuss the most widely used cell-based and molecular-based bacterial load quantification methods, including fluorescence spectroscopy, flow cytometry, 16S qPCR, 16S qRT-PCR, ddPCR, and reference spike-in. Last, we present a specific decision-making scheme for absolute quantification methods based on different biological questions and some of the latest quantitative methods and procedure modifications.