DOI：10.31220/agriRxiv.2021.00066

Cryopreservation of a soil microbiome using a Stirling 1 cycle approach - a genomic assessment.

•  

  Abstract: Abstract Soil microbiomes are dynamic systems that respond to biotic and abiotic environmental factors such as those presented at seasonal scales or due to long-term anthropogenic regime shifts. These can affect the composition and function of microbiomes. Investigation of microbiomes can uncover hidden microbial roles in health and disease and discover microbiome-based interventions. Collections of soil samples are kept by various institutions in either a refrigerated or occasionally frozen state, but conditions are not optimised to ensure the integrity of soil microbiome. In this manuscript, we describe cryopreservation with a controlled rate cooler and estimate the genomic content of an exemplar soil sample before and after cryopreservation. The first hypothesis was to test the genomic integrity of the microbiome. We also enriched the soil sample with a liquid medium to estimate the growth of bacteria and compared their growth before and after cryopreservation. Sequence-based rRNA metabarcoding was used to demonstrate that the controlled rate cooler maintains intact the DNA content of the microbiome. Two methods of cryopreservation were applied and compared with control aliquots of soil. An optimised cryopreservation of soil samples is essential for the development of microbiome research in order to retain stable, functionally intact microbiomes. Our results showed that metabarcoding of 16S and ITS rRNA were useful methods to estimate successful cryopreservation. The soil microbiome after enrichment with liquid medium exhibited a similar response of cryopreserved soil and this was estimated with the comparison of the ten most abundant bacterial taxa. These findings support a successful process of cryopreservation and are promising for future use of this technology. To the best of our knowledge, this study is the first report of cryopreservation of soil using a Stirling cycle cooling approach.

  Key words: cryopreservation; microbiome; estimate; soil; soil microbiome; microbiome

  提交时间：2021-01-01

  版权声明：作者本人独立拥有该论文的版权，预印本系统仅拥有论文的永久保存权利。任何人未经允许不得重复使用。
• html

• 图表

• Elijah C. Mehlferber, Kent F. McCue, Jon Ferrel, Britt Koskella, Rajnish Khann. Temporally selective modification of the tomato rhizosphere and root microbiome by a dacitic tuff breccia (volcanic ash) containing minerals and trace elements.. 2021. doi: 10.31220/agriRxiv.2021.00105

  María‐Soledad Benítez, Patrick M. Ewing, Shannon L. Osborne, R. Michael Lehma. Rhizosphere microbial communities explain positive effects of diverse crop rotations on corn and soybean performance: microbiome explain benefits of diverse rotations.. 2020. doi: 10.31220/agriRxiv.2020.00023

  Prosper Kamusasa, Eddington Gororo, Fungayi Primrose Chatiz. Effect of whole and clarified egg yolk based extenders on post-thaw semen quality in bulls.. 2021. doi: 10.31220/agriRxiv.2021.00050

  Diego A. Delgadillo-Duran, César Augusto Vargas-García, Viviana Marcela Varón-Ramírez, Francisco Calderón, Andrea C. Montenegro, Paula H. Reyes‐Herrer. Using vis-NIRS and machine learning methods to diagnose sugarcane soil chemical properties.. 2021. doi: 10.31220/agriRxiv.2020.00028

  Muneta G. Manzeke-Kangara, Edward J.M. Joy, Florence Mtambanengwe, Prosper Chopera, Michael J. Watts, Martin R. Broadley, Paul Mapfum. Good soil management can reduce dietary zinc deficiency in Zimbabwe.. 2021. doi: 10.31220/agriRxiv.2021.00033

  Guoxian Liang, Lufeng Zhao, Junlong Ye, Zijun Ji, Jianjun Tang, Ke-yu Bai, Si-Jun Zheng, Liangliang Hu, Xin Che. Using aquatic animals as partners to increase yield and soil nitrogen in the paddy ecosystem.. 2021. doi: 10.31220/agriRxiv.2021.00086

  Beckley Ikhajiagbe, Matthew Chidozie Ogwu, Ivhuobe Izuapa Omoayen. Implications of soil nitrogen enhancement on the yield performance of soybean ( Glycine max ) in cadmium-polluted soil.. 2021. doi: 10.31220/agriRxiv.2021.00101

  Munir Zia, A. Lodhi, Muhammad Zahid Aziz, Aftab Naseem, Waqar Ahmad, R. Murray Lark, Michael J. Watts, Martin R. Broadley, E.L. Ande. Soil fertility mapping and agronomic advice at the regional scale using private sector data.. 2021. doi: 10.31220/agriRxiv.2021.00113

  Anna Rini, N. Hemalatha, Raji Sukuma. Decision tree classification of digital soil, weather, crop mapping and yield prediction using linear regression with region influences.. 2021. doi: 10.31220/agriRxiv.2021.00072

  K. V. Daniel, Mark A. Bradford, Emma Fuller, Emily E. Oldfield, Stephen A. Woo. Soil organic matter effects on US maize production and crop insurance payouts under drought.. 2020. doi: 10.31220/agriRxiv.2020.00018

• 序号	提交日期	编号	操作
  1	2021-01-01	10.31220/agriRxiv.2021.00066V1	下载

• 公开评论  匿名评论  仅发给作者 提交评论