The metabolome of typical chernozems under different land uses

Cover Page

Cite item

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription Access

Abstract

The effect of land use on the formation of the metabolome of typical Chernozem is studied. Typical Chernozems (Haplic Chernozems) of four land uses—55-year-old permanent bare fallow, the plot untilled for 21 years after permanent bare fallow, and 4-year field experiments with zero tillage and traditional tillage–from the long-term field experiments at the Kursk Federal Agricultural Research Center (Cheremushki, Kursk oblast, Russia) are analyzed. To study the soil metabolome, the water extracts of both fumigated and nonfumigated soil samples are assayed for the contents of dissolved organic (DOC) and microbial biomass (Cmic) carbon species using high-temperature catalytic oxidation; the soil metabolites are analyzed using gas chromatography–mass spectrometry. The effect of postagrogenic Chernozem transformation on the accumulation of labile soil carbon species is demonstrated by the case study of the plot untilled for 21 years. Plowing of Chernozems in the absence of plant litter decreases the content of labile carbon. A positive effect of no-till practice on the content of labile carbon species is observable at the level of a trend. According to metabolomic analysis, 21 compounds involved in the metabolism of carbohydrates, lipids, and nitrogenous substances are identified in Chernozems. The Shannon diversity index shows that tillage has a negative effect on the complexity of metabolic profiles in Chernozems. Untilled Chernozems and those under permanent fallow conditions display the most contrasting metabolic compositions with the prevalence of metabolites having plant and microbial origin, respectively. The metabolites of a plant origin tend to accumulate in the chernozem under no-till conditions. The components of the carbohydrate metabolism are prevalent in the metabolomic profile of arable chernozemic soils and the components of nitrogen and lipid metabolism predominate in the untilled soils.

About the authors

Y. R. Farkhodov

Dokuchaev Soil Science Institute

Author for correspondence.
Email: yulian.farkhodov@yandex.ru
ORCID iD: 0000-0002-0210-380X
Russian Federation, Moscow, 119017

N. A. Kulikova

Lomonosov Moscow State University

Email: yulian.farkhodov@yandex.ru
Russian Federation, Moscow, 119991

N. N. Danchenko

Dokuchaev Soil Science Institute

Email: yulian.farkhodov@yandex.ru
Russian Federation, Moscow, 119017

V. P. Belobrov

Dokuchaev Soil Science Institute

Email: yulian.farkhodov@yandex.ru
Russian Federation, Moscow, 119017

N. V. Yaroslavtseva

Dokuchaev Soil Science Institute

Email: yulian.farkhodov@yandex.ru
Russian Federation, Moscow, 119017

V. I. Lazarev

Federal Agricultural Kursk Research Center

Email: yulian.farkhodov@yandex.ru
Russian Federation, Kursk, 305021

S. A. Krysanov

Lomonosov Northern (Arctic) Federal University

Email: yulian.farkhodov@yandex.ru
Russian Federation, Arkhangelsk, 163002

V. A. Kholodov

Dokuchaev Soil Science Institute

Email: yulian.farkhodov@yandex.ru
Russian Federation, Moscow, 119017

References

  1. Воробьева Л.А. Теория и практика химического анализа почв. М.: ГЕОС, 2006. 400 с.
  2. Гончаров Н.В., Уколов А.И., Орлова Т.И., Мигаловская Е.Д., Войтенко Н.Г. Метаболомика: на пути интеграции биохимии, аналитической химии, информатики // Успехи современной биологии. 2015. Т. 135. № 1. С. 3–17.
  3. Евдокимов И.В. Методы определения биомассы почвенных микроорганизмов // Russian Journal of Ecosystem Ecology. 2018. № 3. С. 1–20. https://doi.org/10.21685/2500-0578-2018-3-5
  4. Классификация и диагностика почв России. Смоленск: Ойкумена, 2004. 342 с.
  5. Корчагин А.А., Мазиров М.А., Щукин И.М. Общее земледелие: учебное пособие. Владимир: Изд-во ВлГУ, 2021. 193 с.
  6. Никитин Д.А., Иванова Е.А., Железова А.Д., Семенов М.В., Гаджиумаров Р.Г., Тхакахова А.К., и др. Оценка влияния технологии no-till и вспашки на микробиом южных агрочерноземов // Почвоведение. 2020. № 12. С. 1508–1520.
  7. Полянская Л.М., Суханова Н.И., Чакмазян К.В., Звягинцев Д.Г. Особенности изменения структуры микробной биомассы почв в условиях залежи // Почвоведение. 2012. № 7. С. 792–792.
  8. Фрунзе Н.И. Разнообразие аминокислот чернозема типичного (Молдавия) // Почвоведение. 2014. № 12. С. 1483–1489.
  9. Холодов В.А., Фарходов Ю.Р., Ярославцева Н.В., Айдиев А.Ю., Лазарев В.И., Ильин Б.С., и др.. Термолабильное и термостабильное органическое вещество черноземов разного землепользования // Почвоведение. 2020. № 8. С. 970–982. https://doi.org/10.31857/S0032180X20080080
  10. Холодов В.А., Ярославцева Н.В. Агрегаты и органическое вещество почв восстанавливающихся ценозов. М.: ГЕОС, 2021. 119 с.
  11. Холодов В.А., Фарходов Ю.Р., Ярославцева Н.В., Данченко Н.Н., Ильин Б.С., Лазарев В.И. Водоэкстрагируемый и микробный углерод черноземов разного вида использования // Бюл. Почв. ин-та им В.В. Докучаева. 2022. № 112. С. 122–133. https://doi.org/10.19047/0136-1694-2022-112-122-133
  12. Aksenov A.A., Laponogov I., Zhang Z., Doran S.L.F., Belluomo I., Veselkov D., et al. Auto-deconvolution and molecular networking of gas chromatography–mass spectrometry data // Nature Biotechnology. 2021. V. 39. № 2. P. 169–173. https://doi.org/10.1038/s41587-020-0700-3
  13. Chantigny M.H. Dissolved and water-extractable organic matter in soils: a review on the influence of land use and management practices // Geoderma. 2003. V. 113. № 3. P. 357–380. https://doi.org/10.1016/S0016-7061(02)00370-1
  14. Cheng H., Yuan M., Tang L., Shen Y., Yu Q., Li S. Integrated microbiology and metabolomics analysis reveal responses of soil microorganisms and metabolic functions to phosphorus fertilizer on semiarid farm // Sci. Total Environ. 2022. V. 817. P. 152878. https://doi.org/10.1016/j.scitotenv.2021.152878
  15. Chinou I. Primary and secondary metabolites and their biological activity // Chromatographic Sci. Series. 2008. V. 99. P. 59.
  16. Domingues R., Bondar M., Palolo I., Queirós O., de Almeida C.D., Cesário M.T. Xylose Metabolism in Bacteria–Opportunities and Challenges towards Efficient Lignocellulosic Biomass-Based Biorefineries // Appl. Sci. 2021. V. 11. № 17. P. 8112. https://doi.org/10.3390/app11178112
  17. Elbein A.D., Pan Y.T., Pastuszak I., Carroll D. New insights on trehalose: a multifunctional molecule // Glycobiology. 2003. V. 13. № 4. P. 17R–27R. https://doi.org/10.1093/glycob/cwg047
  18. Fischer H., Meyer A., Fischer K., Kuzyakov Y. Carbohydrate and amino acid composition of dissolved organic matter leached from soil // Soil Biol. Biochem. 2007. V. 39. № 11. P. 2926–2935. https://doi.org/10.1016/j.soilbio.2007.06.014
  19. Gancedo C. Energy-yielding metabolism // The yeasts. 1989. V. 3. P. 205–259.
  20. Gunina A., Kuzyakov Y. Sugars in soil and sweets for microorganisms: Review of origin, content, composition and fate // Soil Biol. Biochem. 2015. V. 90. P. 87–100. https://doi.org/10.1016/j.soilbio.2015.07.021
  21. Helgason B.L., Walley F.L., Germida J.J. Fungal and Bacterial Abundance in Long-Term No-Till and Intensive-Till Soils of the Northern Great Plains // Soil Sci. Soc. Am. J. 2009. V. 73. № 1. P. 120–127. https://doi.org/10.2136/sssaj2007.0392
  22. Hollywood K., Brison D.R., Goodacre R. Metabolomics: Current technologies and future trends // PROTEOMICS. 2006. V. 6. № 17. P. 4716–4723. https://doi.org/10.1002/pmic.200600106
  23. ISO 8245. Water quality–guidelines for the determination of total organic carbon (TOC) and dissolved organic carbon (DOC). 1999.
  24. ISO 10694:1995 – Soil quality – Determination of organic and total carbon after dry combustion (elementary analysis). 1995.
  25. Iturriaga G., Suárez R., Nova-Franco B. Trehalose Metabolism: From Osmoprotection to Signaling // Int. J. Molecular Sci. 2009. V. 10. № 9. P. 3793–3810. https://doi.org/10.3390/ijms10093793
  26. Jones O.A.H., Maguire M.L., Griffin J.L., Dias D.A., Spurgeon D.J., Svendsen C. Metabolomics and its use in ecology // Austral Ecology. 2013. V. 38. № 6. P. 713–720. https://doi.org/10.1111/aec.12019
  27. Kind T., Wohlgemuth G., Lee D.Y., Lu Y., Palazoglu M., Shahbaz S., et al. FiehnLib: Mass Spectral and Retention Index Libraries for Metabolomics Based on Quadrupole and Time-of-Flight Gas Chromatography/Mass Spectrometry // Anal. Chem. 2009. V. 81. № 24. P. 10038–10048. https://doi.org/10.1021/ac9019522
  28. Li M., He P., Guo X.-L., Zhang X., Li L.-J. Fifteen-year no tillage of a Mollisol with residue retention indirectly affects topsoil bacterial community by altering soil properties // Soil Till. Res. 2021. V. 205. P. 104804. https://doi.org/10.1016/j.still.2020.104804
  29. Liu K., Ding X., Wang J. Soil metabolome correlates with bacterial diversity and co-occurrence patterns in root-associated soils on the Tibetan Plateau // Sci. Total Environ. 2020. V. 735. P. 139572. https://doi.org/10.1016/j.scitotenv.2020.139572
  30. Misra B.B. Data normalization strategies in metabolomics: Current challenges, approaches, and tools // Eur. J. Mass Spectrometry. 2020. V. 26. № 3. P. 165–174. https://doi.org/ 10.1177/1469066720918446
  31. Miura M., Hill P.W., Jones D.L. Impact of a single freeze-thaw and dry-wet event on soil solutes and microbial metabolites // Appl.Soil Ecology. 2020. V. 153. P. 103636. https://doi.org/10.1016/j.apsoil.2020.103636
  32. Oades J.M. Soil organic matter and structural stability: mechanisms and implications for management // Plant and Soil. 1984. V. 76. № 1. P. 319–337. https://doi.org/10.1007/BF02205590
  33. Patel A., Patel N., Ali A., Alim H. Chapter 4 – Metabolic engineering of plant primary–secondary metabolism interface // Genomics, Transcriptomics, Proteomics and Metabolomics of Crop Plants. Academic Press, 2023. P. 69–87. https://doi.org/10.1016/B978-0-323-95989-6.00015-2
  34. R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2022. https://www.R-project.org/
  35. Reina-Bueno M., Argandoña M., Nieto J.J., Hidalgo-García A., Iglesias-Guerra F., Delgado M.J., et al. Role of trehalose in heat and desiccation tolerance in the soil bacterium Rhizobium etli // BMC Microbiology. 2012. V. 12. № 1. P. 207. https://doi.org/10.1186/1471-2180-12-207
  36. Rochfort S., Ezernieks V., Mele P., Kitching M. NMR metabolomics for soil analysis provide complementary, orthogonal data to MIR and traditional soil chemistry approaches – a land use study // Magnetic Resonance in Chemistry. 2015. V. 53. № 9. P. 719–725. https://doi.org/10.1002/mrc.4187
  37. Romero C.M., Engel R.E., D’Andrilli J., Chen C., Zabinski C., Miller P.R., et al. Bulk optical characterization of dissolved organic matter from semiarid wheat-based cropping systems // Geoderma. 2017. V. 306. P. 40–49. https://doi.org/10.1016/j.geoderma.2017.06.029
  38. Samson M.-E., Chantigny M.H., Vanasse A., Menasseri-Aubry S., Royer I., Angers D.A. Management practices differently affect particulate and mineral-associated organic matter and their precursors in arable soils // Soil Biol. Biochem. 2020. V. 148. P. 107867. https://doi.org/10.1016/j.soilbio.2020.107867
  39. Song Y., Yao S., Li X., Wang T., Jiang X., Bolan N. et al. Soil metabolomics: Deciphering underground metabolic webs in terrestrial ecosystems // Eco-Environment Health. 2024. V. 3. № 2. P. 227–237. https://doi.org/10.1016/j.eehl.2024.03.001
  40. Swenson T.L., Jenkins S., Bowen B.P., Northen T.R. Untargeted soil metabolomics methods for analysis of extractable organic matter // Soil Biol. Biochem. 2015. V. 80. P. 189–198. https://doi.org/10.1016/j.soilbio.2014.10.007
  41. Toosi E.R., Castellano M.J., Singer J.W., Mitchell D.C. Differences in Soluble Organic Matter After 23 Years of Contrasting Soil Management // Soil Sci. Soc. Am. J. 2012. V. 76. № 2. P. 628–637. https://doi.org/10.2136/sssaj2011.0280
  42. Vance E.D., Brookes P.C., Jenkinson D.S. An extraction method for measuring soil microbial biomass C // Soil Biol. Biochem. 1987. V. 19. № 6. P. 703–707. https://doi.org/10.1016/0038-0717(87)90052-6
  43. Warren C.R. Response of osmolytes in soil to drying and rewetting // Soil Biol. Biochem. 2014. V. 70. P. 22–32. https://doi.org/10.1016/j.soilbio.2013.12.008
  44. Warren C.R., Manzoni S. When dry soil is re-wet, trehalose is respired instead of supporting microbial growth // Soil Biol. Biochem. 2023. V. 184. P. 109121. https://doi.org/10.1016/j.soilbio.2023.109121
  45. World Reference Base for Soil Resources 2014, International soil classification system for naming soils and creating legends for soil maps Rome: FAO, 2015. 203 p.
  46. Xu L., Jin S., Su Y., Lyu X., Yan S., Wang C., et al. Combined metagenomics and metabolomic analysis of microbial community structure and metabolic function in continuous soybean cropping soils of Songnen Plain, China // Chemical and Biological Technologies in Agriculture. 2024. V. 11. № 1. P. 46. https://doi.org/10.1186/s40538-024-00569-x
  47. Yao S., Bian Y., Jiang X., Song Y. Characterization of dissolved organic matter distribution in forestland and farmland of mollisol based on untargeted metabolomics // Soil Ecology Lett. 2023. V. 5. № 4. P. 230179. https://doi.org/10.1007/s42832-023-0179-1
  48. Zhang A., Sun H., Xu H., Qiu S., Wang X. Cell metabolomics // Omics. 2013. V. 17. № 10. P. 495-501. https://doi.org/10.1089/omi.2012.0090
  49. Zhang J., Zhou D., Yuan X., Xu Y., Chen C., Zhao L. Soil microbiome and metabolome analysis reveals beneficial effects of ginseng–celandine rotation on the rhizosphere soil of ginseng-used fields // Rhizosphere. 2022. V. 23. P. 100559. https://doi.org/10.1016/j.rhisph.2022.100559
  50. Zhao Y., Yao Y., Xu H., Xie Z., Guo J., Qi Z., et al. Soil metabolomics and bacterial functional traits revealed the responses of rhizosphere soil bacterial community to long-term continuous cropping of Tibetan barley // PeerJ. 2022. V. 10. P. e13254. https://doi.org/10.7717/peerj.13254
  51. Zheng F., Wu X., Zhang M., Liu X., Song X., Lu J., et al. Linking soil microbial community traits and organic carbon accumulation rate under long-term conservation tillage practices // Soil Till. Res. 2022. V. 220. P. 105360.https://doi.org/10.1016/j.still.2022.105360
  52. Zuber S.M., Villamil M.B. Meta-analysis approach to assess effect of tillage on microbial biomass and enzyme activities // Soil Biol. Biochem. 2016. V. 97. P. 176–187. https://doi.org/10.1016/j.soilbio.2016.03.011

Supplementary files

Supplementary Files
Action
1. JATS XML
Download
2. Appendix
Download (18KB)
Indexing metadata
3. Fig. 1. Clusterogram of the relative content of metabolites of typical chernozems of different types of use.

Download (687KB)
Indexing metadata
4. Fig. 2. Diversity of the metabolite composition of typical chernozems according to the Shannon index.

Download (391KB)
Indexing metadata
5. Fig. 3. Group metabolite composition of typical chernozems.

Download (649KB)
Indexing metadata

Copyright (c) 2025 Russian Academy of Sciences