Microbial carbon use efficiency promotes global soil carbon storage

Soils store more carbon than other terrestrial ecosystems$^{1,2}$. How soil organic carbon (SOC) forms and persists remains uncertain$^{1,3}$, which makes it challenging to understand how it will respond to climatic change$^{3,4}$. It has been suggested that soil microorganisms play an important role in SOC formation, preservation and loss$^{5–7}$. Although microorganisms affect the accumulation and loss of soil organic matter through many pathways$^{4,6,8–11}$, microbial carbon use efficiency (CUE) is an integrative metric that can capture the balance of these processes$^{12,13}$. Although CUE has the potential to act as a predictor of variation in SOC storage, the role of CUE in SOC persistence remains unresolved$^{7,14,15}$. Here we examine the relationship between CUE and the preservation of SOC, and interactions with climate, vegetation and edaphic properties, using a combination of global-scale datasets, a microbial-process explicit model, data assimilation, deep learning and meta-analysis. We find that CUE is at least four times as important as other evaluated factors, such as carbon input, decomposition or vertical transport, in determining SOC storage and its spatial variation across the globe. In addition, CUE shows a positive correlation with SOC content. Our findings point to microbial CUE as a major determinant of global SOC storage. Understanding the microbial processes underlying CUE and their environmental dependence may help the prediction of SOC feedback to a changing climate

Microbial carbon use efficiency promotes global soil carbon storage

Funding Information: We thank H. Yang, M. Schrumpf, T. Wutzler, R. Zheng and H. Ma for their comments and suggestions on this study. This work was supported by the National Natural Science Foundation of China (42125503) and the National Key Research and Development Program of China (2020YFA0608000, 2020YFA0607900 and 2021YFC3101600). F.T. was financially supported by China Scholarship Council during his visit at Food and Agricultural Organization of the United Nations (201906210489) and the Max-Planck Institute for Biogeochemistry (202006210289). The contributions of Y.L. were supported through US National Science Foundation DEB 1655499 and 2242034, subcontract CW39470 from Oak Ridge National Laboratory (ORNL) to Cornell University, DOE De-SC0023514, and the USDA National Institute of Food and Agriculture. S.M. has received funding from the ERC under the European Union’s H2020 Research and Innovation Programme (101001608). The contributions of U.M. were supported through a US Department of Energy grant to the Sandia National Laboratories, which is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International, Inc., for the US Department of Energy’s National Nuclear Security Administration under contract DE-NA-0003525. We thank the WoSIS database ( https://www.isric.org/explore/wosis ) for providing the publicly available global-scale SOC database used in this study. Publisher Copyright: © 2023, The Author(s).Peer reviewedPublisher PD

Biocontrol of Fusarium graminearum Growth and Deoxynivalenol Production in Wheat Kernels with Bacterial Antagonists

Fusarium graminearum is the main causal pathogen affecting small-grain cereals, and it produces deoxynivalenol, a kind of mycotoxin, which displays a wide range of toxic effects in human and animals. Bacterial strains isolated from peanut shells were investigated for their activities against F. graminearum by dual-culture plate and tip-culture assays. Among them, twenty strains exhibited potent inhibition to the growth of F. graminearum, and the inhibition rates ranged from 41.41% to 54.55% in dual-culture plate assay and 92.70% to 100% in tip-culture assay. Furthermore, eighteen strains reduced the production of deoxynivalenol by 16.69% to 90.30% in the wheat kernels assay. Finally, the strains with the strongest inhibitory activity were identified by morphological, physiological, biochemical methods and also 16S rDNA and gyrA gene analysis as Bacillus amyloliquefaciens. The current study highlights the potential application of antagonistic microorganisms and their metabolites in the prevention of fungal growth and mycotoxin production in wheat kernels. As a biological strategy, it might avoid safety problems and nutrition loss which always caused by physical and chemical strategies

Establishment of chromium detecting kit and its application in sea water and seafood

Chromium is one of main pollution in sea water, and the establishment of detecting kit is the research hot topic. In this study, immunized mice were obtained by immunogen Cr3+-EDTA-BSA, and hybridoma strains that secrete Cr3+-EDTA monoclonal antibody were selected. Cr3+-EDTA mAb were prepared with in vivo method. Then, Cr-kit for measurement of chromium was developed, and its application was executed in sea water and seafood. Two hybridoma strains of A321 and A424 were screened. The Cr-kit standard curve of the linear range was 1.0—512 μg/L, and limit of detection was 1.0 μg/L. The average recovery rates Cr spiked in samples of sea water, clam and shrimp were 102.62%, 94.69% and 96.29%, which were accordance with the results of ICP-AES. Totally, Cr-kit was successfully developed and behaved broad application potential in sea water and seafood

Biochemical and Metabolomic Responses of Antarctic Bacterium <i>Planococcus</i> sp. O5 Induced by Copper Ion

Heavy metal pollution in the Antarctic has gone beyond our imagination. Copper toxicity is a selective pressure on Planococcus sp. O5. We observed relatively broad tolerance in the polar bacterium. The heavy metal resistance pattern is Pb2+ > Cu2+ > Cd2+ > Hg2+ > Zn2+. In the study, we combined biochemical and metabolomics approaches to investigate the Cu2+ adaptation mechanisms of the Antarctic bacterium. Biochemical analysis revealed that copper treatment elevated the activity of antioxidants and enzymes, maintaining the bacterial redox state balance and normal cell division and growth. Metabolomics analysis demonstrated that fatty acids, amino acids, and carbohydrates played dominant roles in copper stress adaptation. The findings suggested that the adaptive mechanisms of strain O5 to copper stress included protein synthesis and repair, accumulation of organic permeable substances, up-regulation of energy metabolism, and the formation of fatty acids

Peripheral T cell receptor beta immune repertoire is promptly reconstituted after acute myocardial infarction

Abstract Background Acute myocardial infarction (AMI) is characterized by an inflammatory process in which T cell plays a key role. However, the profile of immune microenvironment in AMI is still uncertain. High-throughput sequencing of T cell receptor (TCR) provides deep insight into monitoring the immune microenvironment. Methods 30 patients with AMI were enrolled and 30 healthy individuals were recruited as controls. Flow cytometer were used to analyze the distribution of αβ T cells and their CD69 expression from peripheral leukomonocytes. TCRβ repertoire library was amplified by two-round multiplex PCR and detected by next-generation sequencing (NGS). Results The percentage of αβ T cells in AMI patients were significantly restricted than those in healthy controls, while the highly activated αβ T cells along with distinguishing usage of variable (V), diversity (D) and joining (J) gene segments were also found in AMI patients. In addition, AMI induced a significantly restricted CDR3 amino acid (AA) diversity and remarkably reconstituted TCR immune repertoires. Finally, we identified several AMI-associated tendency of CDR3 AAs expression after AMI. Conclusions Our work suggests that the aberrant αβ T cells distribution and activation may associated with the pathogenesis of AMI and demonstrates a reconstitution of TCRβ immune repertoire after AMI

Biocontrol of Fusarium graminearum Growth and Deoxynivalenol Production in Wheat Kernels with Bacterial Antagonists

Fusarium graminearum is the main causal pathogen affecting small-grain cereals, and it produces deoxynivalenol, a kind of mycotoxin, which displays a wide range of toxic effects in human and animals. Bacterial strains isolated from peanut shells were investigated for their activities against F. graminearum by dual-culture plate and tip-culture assays. Among them, twenty strains exhibited potent inhibition to the growth of F. graminearum, and the inhibition rates ranged from 41.41% to 54.55% in dual-culture plate assay and 92.70% to 100% in tip-culture assay. Furthermore, eighteen strains reduced the production of deoxynivalenol by 16.69% to 90.30% in the wheat kernels assay. Finally, the strains with the strongest inhibitory activity were identified by morphological, physiological, biochemical methods and also 16S rDNA and gyrA gene analysis as Bacillus amyloliquefaciens. The current study highlights the potential application of antagonistic microorganisms and their metabolites in the prevention of fungal growth and mycotoxin production in wheat kernels. As a biological strategy, it might avoid safety problems and nutrition loss which always caused by physical and chemical strategies

Matrix Approach to Land Carbon Cycle Modeling

Land ecosystems contribute to climate change mitigation by taking up approximately 30% of anthropogenically emitted carbon. However, estimates of the amount and distribution of carbon uptake across the world's ecosystems or biomes display great uncertainty. The latter hinders a full understanding of the mechanisms and drivers of land carbon uptake, and predictions of the future fate of the land carbon sink. The latter is needed as evidence to inform climate mitigation strategies such as afforestation schemes. To advance land carbon cycle modeling, we have developed a matrix approach. Land carbon cycle models use carbon balance equations to represent carbon exchanges among pools. Our approach organizes this set of equations into a single matrix equation without altering any processes of the original model. The matrix equation enables the development of a theoretical framework for understanding the general, transient behavior of the land carbon cycle. While carbon input and residence time are used to quantify carbon storage capacity at steady state, a third quantity, carbon storage potential, integrates fluxes with time to define dynamic disequilibrium of the carbon cycle under global change. The matrix approach can help address critical contemporary issues in modeling, including pinpointing sources of model uncertainty and accelerating spin-up of land carbon cycle models by tens of times. The accelerated spin-up liberates models from the computational burden that hinders comprehensive parameter sensitivity analysis and assimilation of observational data to improve model accuracy. Such computational efficiency offered by the matrix approach enables substantial improvement of model predictions using ever-increasing data availability. Overall, the matrix approach offers a step change forward for understanding and modeling the land carbon cycle

Matrix Approach to Land Carbon Cycle Modeling

Land ecosystems contribute to climate change mitigation by taking up approximately 30% of anthropogenically emitted carbon. However, estimates of the amount and distribution of carbon uptake across the world's ecosystems or biomes display great uncertainty. The latter hinders a full understanding of the mechanisms and drivers of land carbon uptake, and predictions of the future fate of the land carbon sink. The latter is needed as evidence to inform climate mitigation strategies such as afforestation schemes. To advance land carbon cycle modeling, we have developed a matrix approach. Land carbon cycle models use carbon balance equations to represent carbon exchanges among pools. Our approach organizes this set of equations into a single matrix equation without altering any processes of the original model. The matrix equation enables the development of a theoretical framework for understanding the general, transient behavior of the land carbon cycle. While carbon input and residence time are used to quantify carbon storage capacity at steady state, a third quantity, carbon storage potential, integrates fluxes with time to define dynamic disequilibrium of the carbon cycle under global change. The matrix approach can help address critical contemporary issues in modeling, including pinpointing sources of model uncertainty and accelerating spin-up of land carbon cycle models by tens of times. The accelerated spin-up liberates models from the computational burden that hinders comprehensive parameter sensitivity analysis and assimilation of observational data to improve model accuracy. Such computational efficiency offered by the matrix approach enables substantial improvement of model predictions using ever-increasing data availability. Overall, the matrix approach offers a step change forward for understanding and modeling the land carbon cycle