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Ma, Lanying

Publications and source records attributed to Ma, Lanying.

Response of Total (DNA) and Metabolically Active (RNA) Microbial Communities in Miscanthus × Giganteus Cultivated Soil to Different Nitrogen Fertilization Rates

Miscanthus × giganteus is a promising high-yielding perennial plant to meet growing bioenergy demands; however, the degree to which the soil microbiome affects its nitrogen cycling and subsequently, biomass yield remains unclear. In this study, we hypothesize that contributions of metabolically active soil microbial membership may be underestimated with DNA-based approaches. We assessed the response of the soil microbiome to nitrogen availability in terms of both DNA and RNA soil microbial communities from the Long-term Assessment of Miscanthus Productivity and Sustainability (LAMPS) field trial. DNA and RNA were extracted from 271 samples, and 16S small subunit (SSU) rRNA amplicon sequencing was performed to characterize microbial community structure. Significant differences were observed in the resulting soil microbiomes and were best explained by the sequencing library of origin, either DNA or RNA. Similar numbers of membership were detected in DNA and RNA microbial communities, with more than 90% of membership shared. However, the profile of dominant membership within DNA and RNA differed, with varying proportions of Actinobacteria and Proteobacteria and Firmicutes and Proteobacteria. Only RNA microbial communities showed seasonal responses to nitrogen fertilization, and these differences were associated with nitrogen-cycling bacteria. The relative abundance of bacteria associated with nitrogen cycling was 7-fold higher in RNA than in DNA, and genes associated with denitrifying bacteria were significantly enriched in RNA, suggesting that these bacteria may be underestimated with DNA-only approaches. Our findings indicate that RNA-based SSU characterization can be a significant and complementing resource for understanding the role of soil microbiomes in bioenergy crop production.

59 BASIC BIOLOGICAL SCIENCES↗

The Impact of Stand Age and Fertilization on the Soil Microbiome of Miscanthus × giganteus

Yield of the perennial grass Miscanthus × giganteus has shown an inconsistent and unpredictable response to nitrogen (N) fertilizer, yet fertilization underpins the crop’s environmental and economic sustainability. The interactions among soil microbial communities, N availability, and Miscanthus × giganteus and management may explain changes in plant productivity. In this study, soil samples from different stand ages of Miscanthus × giganteus in a replicated chronosequence field trial were used to investigate the effects of stand age and N fertilizer rates on microbial community structure. We hypothesized that there is a definable Miscanthus × giganteus soil microbiome and that this community varies significantly with stand age and fertilization. Our results showed that the main phyla in soil microbial communities, regardless of plant age, are similar but microbial community structures are significantly different. The variation in observed microbial communities generally decreases with older stand ages. The amount of N fertilizer applied also affected the microbial community structure associated with different aged Miscanthus × giganteus. Specifically, the relative abundance of Proteobacteria (Alphaproteobacteria and Gammaproteobacteria) and Acidobacteria (subgroup Gp1) increased shortly after fertilization and was more associated with younger Miscanthus × giganteus. Furthermore, our results show a significant relationship between bacterial α diversity and fertilization rates and that this response is also affected by stand age. Overall, our results emphasize linkages between microbial community structure, plant age, and fertilization in Miscanthus × giganteus.

59 BASIC BIOLOGICAL SCIENCES↗

germs-lab/LAMPS-miscanthus-microbiome

Data and analysis to accompany our submitted paper characterizing the LAMPS Miscanthus Microbiome comparing 16S rRNA gene DNA sequencing of Miscanthus in a staggered-start experiment. Authors for this analysis include Fernando Igne Rocha, Lanying Ma, and Adina Howe.

Igne Rocha, Fernando↗