Soil microbial traits and functions play a central role in soil organic carbon (SOC) dynamics. However, at the macroscale (regional to global) it is still unresolved whether (i) specific environmental attributes (e.g., climate, geology, soil types) or (ii) microbial community composition drive key microbial traits and functions directly. To address this knowledge gap, we used 33 grassland topsoils (0-10 cm) from a geoclimatic gradient in Chile. First, we incubated the soils for 1 week in favorable standardized conditions and quantified a wide range of soil microbial traits and functions such as microbial biomass carbon (MBC), enzyme kinetics, microbial respiration, growth rates as well as carbon use efficiency (CUE). Second, we characterized climatic and physicochemical properties as well as bacterial and fungal community composition of the soils. We then applied regression analysis to investigate how strongly the measured microbial traits and functions were linked with the environmental setting versus microbial community composition. We show that environmental attributes (predominantly the amount of soil organic matter) determined patterns of MBC along the gradient, which in turn explained microbial respiration and growth rates. However, respiration and growth normalized for MBC (i.e., specific respiration and growth) were more linked to microbial community composition than environmental attributes. Notably, both specific respiration and growth followed distinct trends and were related to different parts of the microbial community, which in turn resulted in strong effects on microbial CUE. We conclude that even at the macroscale, CUE is the result of physiologically decoupled aspects of microbial metabolism, which in turn is partially determined by microbial community composition. The environmental setting and microbial community composition affect different microbial traits and functions, and therefore both factors need to be considered in the context of macroscale SOC dynamics.

Soil microorganisms play a crucial role in the plant invasion process, acting as both drivers of and responders to plant invasion. However, the effects of plant invasion on the complexity and stability of co-occurrence networks of soil microbial communities remain unclear. Here, we investigated how the invasion of Spartina alterniflora affected the diversity, composition, and co-occurrence networks of soil bacterial and fungal communities in the Yellow River Delta, China. Compared to the native plant (Suaeda salsa), S. alterniflora invasion decreased the α-diversity of soil bacterial communities but did not affect that of fungal communities. The β-diversity of soil bacterial and fungal communities under S. salsa and S. alterniflora habitats also differed dramatically. S. alterniflora invasion increased the relative abundance of the copiotrophic phylum Bacteroidota, whereas decreased the relative abundances of the oligotrophic phyla Acidobacteriota and Gemmatimonadota. Additionally, the relative abundance of Chytridiomycota, known for its role in degrading recalcitrant organic matter, increased substantially within the soil fungal community. Functional predictions revealed that S. alterniflora invasion increased the relative abundance of certain soil bacteria involved in carbon and nitrogen cycling, including aerobic chemoheterotrophy, nitrate reduction, and nitrate respiration. More importantly, S. alterniflora invasion reduced the complexity and stability of both soil bacterial and fungal community networks. The shifts in soil microbial community structure and diversity were mainly induced by soil available nutrients and soil salinity. Overall, our study highlights the profound impacts of S. alterniflora invasion on soil microbial communities, which could further indicate the modification of ecosystem functioning by invasive species.

Biochar (BC) has been proven effective in promoting the production of safety food in cadmium (Cd)-polluted soil and the impact can be further enhanced through interaction with compost (CM). However, there existed unclear impacts of biochar with varying particle sizes in conjunction with compost on microbiome composition, rhizosphere functions, and soil health. Hence, in this study, two bulk-biochar derived from wood chips and pig manure were fabricated into nano-biochar using a ball-milling method. Subsequently, in a field experiment, the root-associated bacterial community and microbial functions of lettuce were evaluated in respond to Cd-contaminated soil remediated with nano/bulk-BCCM. The results showed that compared to bulk-BCCM, nano-BCCM significantly reduced the Cd concentration in the edible part of lettuce and the available Cd in the soil. Both nano-BCCM and bulk-BCCM strongly influenced the composition of bacterial communities in the four root-associated niches, and enhanced rhizosphere functions involved in nitrogen, phosphorus, and carbon cycling, as well as the relative abundance and biodiversity of keystone modules in rhizosphere soil. Furthermore, soil quality index analysis indicated that nano-BCCM exhibited greater potential than bulk-BCCM in maintaining soil health. The data revealed that nano-BCCM could regulate the Cd concentration in lettuce shoot by promoting microbial biodiversity of keystone modules in soil-root continuum and rhizosphere bacterial functions. These findings suggest that nano-biochar compost associations can be a superior strategy for enhancing microbial functions, maintaining soil health, and ensuring crop production safety in the Cd-contaminated soil compared to the mix of bulk-biochar and compost.

Despite the increased research efforts aimed at understanding iron-based conductive materials (CMs) for facilitating chain elongation (CE) to produce medium chain fatty acids (MCFAs), the impact of these materials on microbial community functions and the adaptation mechanisms to their biotoxicity remain unclear. This study found that the supply of zero-valent iron (ZVI) and magnetite enhanced the MCFAs carbon-flow distribution by 26 % and 52 %, respectively. Metagenomic analysis revealed the upregulation of fatty acid metabolism, pyruvate metabolism and ABC transporters with ZVI and magnetite. The predominant functional microorganisms were Massilibacterium and Tidjanibacter with ZVI, and were Petrimonas and Candidatus_Microthrix with magnetite. Furthermore, it was demonstrated that CE microorganisms respond and adapt to the biotoxicity of iron-based CMs by adjusting Two-component system and Quorum sensing for the first time. In summary, this study provided a new deep-insight on the feedback mechanisms of CE microorganisms on iron-based CMs.

Taxonomic marker gene analysis allows uncovering taxonomic profiles of microbial communities at low cost, making it omnipresent in microbiome research. There is an ever-expanding set of tools to extract further biological information from this kind of data. In this perspective, we enunciate several concerns regarding the biological validity of predicting functional potential from taxonomic profiles, especially when they are generated by short-read sequencing. The taxonomic resolution of marker genes, intragenomic variability of marker genes, and the compositional nature of microbiome data are discussed. Combining actual measurements of microbiome functions with predicted functional potentials is proposed as a powerful approach to better understand microbiome functioning. In this context, the significance of predicted functional potentials for generating and testing hypotheses is highlighted. We argue that functions of microbiomes predicted from microbiome DNA read count data generated by short-read amplicon sequencing should not serve as the only basis to draw biological inferences.

In a 120-day microcosm incubation experiment, we investigated the impact of arsenic contamination on soil microbial nutrient metabolism, focusing on carbon cycling processes. Our study encompassed soil basal respiration, key enzyme activities (particularly, β-1,4-N-acetylglucosaminidase and phosphatases), microbial biomass, and community structure. Results revealed a substantial increase (1.21-2.81 times) in β-1,4-N-acetylglucosaminidase activities under arsenic stress, accompanied by a significant decrease (9.86%-45.20%) in phosphatase activities (sum of acid and alkaline phosphatases). Enzymatic stoichiometry analysis demonstrated the mitigation of microbial C and P requirements in response to arsenic stress. The addition of C-sources alleviated microbial C requirements but exacerbated P requirements, with the interference amplitude increasing with the complexity of the C-source. Network analysis unveiled altered microbial nutrient requirements and an increased resistance process of microbes under arsenic stress. Microbial carbon use efficiency (CUE) and basal respiration significantly increased (1.17-1.59 and 1.18-3.56 times, respectively) under heavy arsenic stress (500 mg kg-1). Arsenic stress influenced the relative abundances of microbial taxa, with Gemmatimonadota increasing (5.5-50.5%) and Bacteroidota/ Nitrospirota decreasing (31.4-47.9% and 31.2-63.7%). Application of C-sources enhanced microbial resistance to arsenic, promoting cohesion among microorganisms. These findings deepen our understanding of microbial nutrient dynamics in arsenic-contaminated areas, which is crucial for developing enzyme-based toxicity assessment systems for soil arsenic contamination.

Natural ecosystems harbor a huge reservoir of taxonomically diverse microbes that are important for plant growth and health. The vast diversity of soil microorganisms and their complex interactions make it challenging to pinpoint the main players important for the life support functions microbes can provide to plants, including enhanced tolerance to (a)biotic stress factors. Designing simplified microbial synthetic communities (SynComs) helps reduce this complexity to unravel the molecular and chemical basis and interplay of specific microbiome functions. While SynComs have been successfully employed to dissect microbial interactions or reproduce microbiome-associated phenotypes, the assembly and reconstitution of these communities have often been based on generic abundance patterns or taxonomic identities and co-occurrences but have only rarely been informed by functional traits. Here, we review recent studies on designing functional SynComs to reveal common principles and discuss multidimensional approaches for community design. We propose a strategy for tailoring the design of functional SynComs based on integration of high-throughput experimental assays with microbial strains and computational genomic analyses of their functional capabilities.

The resource quantity and elemental stoichiometry play pivotal roles in shaping belowground biodiversity. However, a significant knowledge gap remains regarding the influence of different plant communities established through monoculture plantations on soil fungi and bacteria\'s taxonomic and functional dynamics. This study aimed to elucidate the mechanisms underlying the regulation and adaptation of microbial communities at the taxonomic and functional levels in response to communities formed over 34 years through monoculture plantations of coniferous species (Japanese larch, Armand pine, and Chinese pine), deciduous forest species (Katsura), and natural shrubland species (Asian hazel and Liaotung oak) in the temperate climate. The taxonomic and functional classifications of fungi and bacteria were examined for the mineral topsoil (0-10 cm) using MiSeq-sequencing and annotation tools of microorganisms (FAPROTAX and Funguild). Soil bacterial (6.52 ± 0.15) and fungal (4.46 ± 0.12) OTUs\' diversity and richness (5.83*103±100 and 1.12*103±46.4, respectively) were higher in the Katsura plantation compared to Armand pine and Chinese pine. This difference was attributed to low soil DOC/OP (24) and DON/OP (11) ratios in the Katsura, indicating that phosphorus availability increased microbial community diversity. The Chinese pine plantation exhibited low functional diversity (3.34 ± 0.04) and richness (45.2 ± 0.41) in bacterial and fungal communities (diversity 3.16 ± 0.15 and richness 56.8 ± 3.13), which could be attributed to the high C/N ratio (25) of litter. These findings suggested that ecological stoichiometry, such as of enzyme, litter C/N, soil DOC/DOP, and DON/DOP ratios, was a sign of the decoupling of soil microorganisms at the genetic and functional levels to land restoration by plantations. It was found that the stoichiometric ratios of plant biomass served as indicators of microbial functions, whereas the stoichiometric ratios of available nutrients in soil regulated microbial genetic diversity. Therefore, nutrient stoichiometry could serve as a strong predictor of microbial diversity and composition during forest restoration.

Molecular profiling techniques such as metagenomics, metatranscriptomics or metabolomics offer important insights into the functional diversity of the microbiome. In contrast, 16S rRNA gene sequencing, a widespread and cost-effective technique to measure microbial diversity, only allows for indirect estimation of microbial function. To mitigate this, tools such as PICRUSt2, Tax4Fun2, PanFP and MetGEM infer functional profiles from 16S rRNA gene sequencing data using different algorithms. Prior studies have cast doubts on the quality of these predictions, motivating us to systematically evaluate these tools using matched 16S rRNA gene sequencing, metagenomic datasets, and simulated data. Our contribution is threefold: (i) using simulated data, we investigate if technical biases could explain the discordance between inferred and expected results; (ii) considering human cohorts for type two diabetes, colorectal cancer and obesity, we test if health-related differential abundance measures of functional categories are concordant between 16S rRNA gene-inferred and metagenome-derived profiles and; (iii) since 16S rRNA gene copy number is an important confounder in functional profiles inference, we investigate if a customised copy number normalisation with the rrnDB database could improve the results. Our results show that 16S rRNA gene-based functional inference tools generally do not have the necessary sensitivity to delineate health-related functional changes in the microbiome and should thus be used with care. Furthermore, we outline important differences in the individual tools tested and offer recommendations for tool selection.

The changes of soil moisture, salinity, and nutrients by halophyte colonization in high-salinity environment profoundly affect the assembly and structure of microbial communities. However, salt marshes in arid region have received little attention. This study was conducted in Lianhuachi Lake, a typical inland salt marsh wetland in China, to determine the physicochemical characteristics of salt crusts in [Kalidium cuspidatum (Ung.-Sternb.) Grub.] colonization areas and bulk soil, respectively, and to analyze the microbial community structure of salt crusts by high-throughput sequencing. Kalidium cuspidatum colonization significantly decreased total salinity, soil water content, and water-soluble ions of salt crusts and increased total carbon, total nitrogen, and total phosphorus content. At the same time, changes in physicochemical properties caused by Kalidium cuspidatum colonization affect the ecological processes of bacterial, fungal, and archaeal community assemblies in salt crusts. In addition, cross-kingdom network analysis showed that Kalidium cuspidatum colonization increased the complexity and stability of microbial networks in salt crust soils. Functional projections further showed that bacterial diversity had a potential driving effect on the nitrogen cycle function of salt crust. Our study further demonstrated the different ecological strategies of microorganisms for halophyte colonization in extreme environments and contributed to the understanding of restoration and management of salt marsh wetlands in arid region.