Local Phenomena Shape Backyard Soil Metabolite Composition

Improved Characterization of Soil Organic Matter by Integrating FT-ICR MS, Liquid Chromatography Tandem Mass Spectrometry, and Molecular Networking: A Case Study of Root Litter Decay under Drought Conditions

Understanding of how soil organic matter (SOM) chemistry is altered in a changing climate has advanced considerably; however, most SOM components remain unidentified, impeding the ability to characterize a major fraction of organic matter and predict what types of molecules, and from which sources, will persist in soil. We present a novel approach to better characterize SOM extracts by integrating information from three types of analyses, and we deploy this method to characterize decaying root-detritus soil microcosms subjected to either drought or normal conditions. To observe broad differences in composition, we employed direct infusion Fourier-transform ion cyclotron resonance mass spectrometry (DI-FT-ICR MS). We complemented this with liquid chromatography tandem mass spectrometry (LC-MS/MS) to identify components by library matching. Since libraries contain only a small fraction of SOM components, we also used fragment spectral cosine similarity scores to relate unknowns and library matches through molecular networks. This integrated approach allowed us to corroborate DI-FT-ICR MS molecular formulas using library matches, which included fungal metabolites and related polyphenolic compounds. We also inferred structures of unknowns from molecular networks and improved LC-MS/MS annotation rates from ∼5 to 35% by considering DI-FT-ICR MS molecular formula assignments. Under drought conditions, we found greater relative amounts of lignin-like vs condensed aromatic polyphenol formulas and lower average nominal oxidation state of carbon, suggesting reduced decomposition of SOM and/or microbes under stress. Our integrated approach provides a framework for enhanced annotation of SOM components that is more comprehensive than performing individual data analyses in parallel.

Soil metabolomics: Deciphering underground metabolic webs in terrestrial ecosystems

Soil metabolomics is an emerging approach for profiling diverse small molecule metabolites, i.e., metabolomes, in the soil. Soil metabolites, including fatty acids, amino acids, lipids, organic acids, sugars, and volatile organic compounds, often contain essential nutrients such as nitrogen, phosphorus, and sulfur and are directly linked to soil biogeochemical cycles driven by soil microorganisms. This paper presents an overview of methods for analyzing soil metabolites and the state-of-the-art of soil metabolomics in relation to soil nutrient cycling. We describe important applications of metabolomics in studying soil carbon cycling and sequestration, and the response of soil organic pools to changing environmental conditions. This includes using metabolomics to provide new insights into the close relationships between soil microbiome and metabolome, as well as responses of soil metabolome to plant and environmental stresses such as soil contamination. We also highlight the advantage of using soil metabolomics to study the biogeochemical cycles of elements and suggest that future research needs to better understand factors driving soil function and health.

Environmental pseudotargeted metabolomics: A high throughput and wide coverage method for metabolic profiling of 1000-year paddy soil chronosequences

Pseudotargeted metabolomics is achieved by introducing an algorithm designed to choose ions for selected ion monitoring from identified metabolites. This method integrates the advantages of both untargeted and targeted metabolomics. In this study, environmental pseudotargeted metabolomics was established to analyze the soil metabolites, based on microwave assisted derivatization followed by gas chromatography-mass spectrometry analysis. The method development included the optimization of extraction factors and derivatization conditions, evaluation of silylation reagent types and matrix-dependent behaviors. Under the optimal conditions, the microwave oximation and silylation were completed in 5 min and 9 min. A total of 184 metabolites from 26 chemical classifications were identified in soil matrices. The method validation demonstrated excellent performance in terms of linearity (correlation coefficient > 0.99), repeatability (relative standard deviation (RSD) < 20 %), reproducibility (RSD < 25 %), stability (relative difference < 10 % within 18 h), and sensitivity (16-110 times higher signal-to-noise ratio). This developed method was applied to characterize the metabolite compositions and metabolic profiling in a 1000-year paddy soil chronosequence. The relative abundance of trehalose was highest in 6-(40.3 %), 60-(55.8 %), 300-(67.7 %)and 1000-(61.7 %)years paddy soil, respectively, but long-chain fatty acids were most abundant in marine sediment (57.4 %). Forty-two characteristic metabolites were considered as primarily responsible for discriminating and characterizing the paddy soil chronosequences development and seven major metabolic pathways were altered. In addition, GC-MS metabolite profile presented better discriminating power in paddy soil ecosystem changes than phospholipid fatty acids (PLFAs). Overall, environmental pseudotargeted metabolomics can provide a high throughout and wide coverage approach for performing metabolic profiling in the soil research.

Factors driving the halophyte rhizosphere bacterial communities in coastal salt marshes

Introduction

Root-associated microorganisms promote plant growth and provide protection from stresses. Halophytes are the fundamental components maintaining ecosystem functions of coastal salt marshes; however, it is not clear how their microbiome are structured across large spatial scales. Here, we investigated the rhizosphere bacterial communities of typical coastal halophyte species (Phragmites australis and Suaeda salsa) in temperate and subtropical salt marshes across 1,100 km in eastern China.

Methods

The sampling sites were located from 30.33 to 40.90°N and 119.24 to 121.79°E across east China. A total of 36 plots were investigated in the Liaohe River Estuary, the Yellow River Estuary, Yancheng, and Hangzhou Bay in August 2020. We collected shoot, root, and rhizosphere soil samples. the number of pakchoi leaves, total fresh and dry weight of the seedlings was counted. The soil properties, plant functional traits, the genome sequencing, and metabolomics assay were detected.

Results

The results showed that soil nutrients (total organic carbon, dissolved organic carbon, total nitrogen, soluble sugars, and organic acids) are high in the temperate marsh, while root exudates (measured by metabolite expressions) are significantly higher in the subtropical marsh. We observed higher bacterial alpha diversity, more complex network structure, and more negative connections in the temperate salt marsh, which suggested intense competition among bacterial groups. Variation partitioning analysis showed that climatic, edaphic, and root exudates had the greatest effects on the bacteria in the salt marsh, especially for abundant and moderate subcommunities. Random forest modeling further confirmed this but showed that plant species had a limited effect.

Conclutions

Taken together, the results of this study revealed soil properties (chemical properties) and root exudates (metabolites) had the greatest influence on the bacterial community of salt marsh, especially for abundant and moderate taxa. Our results provided novel insights into the biogeography of halophyte microbiome in coastal wetlands and can be beneficial for policymakers in decision-making on the management of coastal wetlands.

Untargeted Fecal Metabolomic Analyses across an Industrialization Gradient Reveal Shared Metabolites and Impact of Industrialization on Fecal Microbiome-Metabolome Interactions

The metabolome is a central determinant of human phenotypes and includes the plethora of small molecules produced by host and microbiome or taken up from exogenous sources. However, studies of the metabolome have so far focused predominantly on urban, industrialized populations. Through an untargeted metabolomic analysis of 90 fecal samples from human individuals from Africa and the Americas-the birthplace and the last continental expansion of our species, respectively-we characterized a shared human fecal metabolome. The majority of detected metabolite features were ubiquitous across populations, despite any geographic, dietary, or behavioral differences. Such shared metabolite features included hyocholic acid and cholesterol. However, any characterization of the shared human fecal metabolome is insufficient without exploring the influence of industrialization. Here, we show chemical differences along an industrialization gradient, where the degree of industrialization correlates with metabolomic changes. We identified differential metabolite features such as amino acid-conjugated bile acids and urobilin as major metabolic correlates of these behavioral shifts. Additionally, coanalyses with over 5,000 publicly available human fecal samples and cooccurrence probability analyses with the gut microbiome highlight connections between the human fecal metabolome and gut microbiome. Our results indicate that industrialization significantly influences the human fecal metabolome, but diverse human lifestyles and behavior still maintain a shared human fecal metabolome. This study represents the first characterization of the shared human fecal metabolome through untargeted analyses of populations along an industrialization gradient. IMPORTANCE As the world becomes increasingly industrialized, understanding the biological consequences of these lifestyle shifts and what it means for past, present, and future human health is critical. Indeed, industrialization is associated with rises in allergic and autoimmune health conditions and reduced microbial diversity. Exploring these health effects on a chemical level requires consideration of human lifestyle diversity, but understanding the significance of any differences also requires knowledge of what molecular components are shared between human groups. Our study reveals the key chemistry of the human gut as defined by varied industrialization-based differences and ubiquitous shared features. Ultimately, these novel findings extend our knowledge of human molecular biology, especially as it is influenced by lifestyle and behavior, and provide steps toward understanding how human biology has changed over our species' history.

Integrated microbiology and metabolomics analysis reveal responses of soil microorganisms and metabolic functions to phosphorus fertilizer on semiarid farm

Localized fertilization of phosphorus has potential benefits in achieving higher crop productivity and nutrient use efficiency, but the underlying biological mechanisms of interactions between soil microorganisms and related metabolic cycle remain largely to be recognized. Here, we combined microbiology with non-target metabolomics to explore how P fertilizer levels and fertilization patterns affect wheat soil microbial communities and metabolic functions based on high-throughput sequencing and UPLC-MS/MS platforms. The results showed P fertilizer decreased the diversity of bacterial 16S rRNA genes and fungal ITS genes, and it did significantly change both soil bacterial and fungal overall community structures and compositions. The P levels and patterns also interfered with complexity of soil bacterial and fungal symbiosis networks. Moreover, metabolomics analysis showed that P fertilizer significantly changed soil metabolite spectrum, and the differential metabolites were significantly enriched to 7 main metabolic pathways, such as arginine and proline metabolism, biosynthesis of plant hormones, amino acids, plant secondary metabolites, and alkaloids derived from ornithine. Additionally, microbes also were closely related to the accumulation of metabolites through correlation analysis. Our results indicated that localized appropriate phosphorus fertilizer plays an important role in regulating soil microbial metabolism, and their interactions in soil providing valuable information for understanding how the changed phosphorus management practices affect the complex biological processes and the adaption capacity of plants to environments.

Advancements in capturing and mining mass spectrometry data are transforming natural products research

Covering: 2016 up to 2021Mass spectrometry (MS) is an essential technology in natural products research with MS fragmentation (MS/MS) approaches becoming a key tool. Recent advancements in MS yield dense metabolomics datasets which have been, conventionally, used by individual labs for individual projects; however, a shift is brewing. The movement towards open MS data (and other structural characterization data) and accessible data mining tools is emerging in natural products research. Over the past 5 years, this movement has rapidly expanded and evolved with no slowdown in sight; the capabilities of today vastly exceed those of 5 years ago. Herein, we address the analysis of individual datasets, a situation we are calling the '2021 status quo', and the emergent framework to systematically capture sample information (metadata) and perform repository-scale analyses. We evaluate public data deposition, discuss the challenges of working in the repository scale, highlight the challenges of metadata capture and provide illustrative examples of the power of utilizing repository data and the tools that enable it. We conclude that the advancements in MS data collection must be met with advancements in how we utilize data; therefore, we argue that open data and data mining is the next evolution in obtaining the maximum potential in natural products research.

Identification and characterization of proteins, lipids, and metabolites in two organic fertilizer products derived from different nutrient sources

The biochemical composition of organic fertilizers largely determines their nutrient supply characteristics following soil application as well as their potential impact on soil microbial communities. Yet, limited information is available regarding the biochemical composition of organic fertilizers derived from different nutrient sources. Here, we qualitatively analyzed the presence and abundance of proteins, lipids, and metabolites in a liquid fish fertilizer (LFF) product and a type of granular organic fertilizer (GOF) commonly used in organic vegetable production, using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Our results suggest that the presence and abundance of proteins, lipids, and metabolites differ greatly between GOF and LFF. The qualitative analysis shows LFF as a rich source of metabolites, while complex proteins and long-chain saturated fatty acids are dominant in GOF. The degree of biochemical composition complexity may help explain the varying impacts of different types of organic fertilizers on nutrient availability, soil health, and environmental quality.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1186/s13765-021-00625-2.

An Integrated Strategy for the Detection, Dereplication, and Identification of DNA-Binding Biomolecules from Complex Natural Product Mixtures

A fundamental factor in natural product drug discovery programs is the necessity to identify the active component(s) from complex chemical mixtures. Whereas this has traditionally been accomplished using bioassay-guided fractionation, we questioned whether alternative techniques could supplement and, in some cases, even supplant this approach. We speculated that a combination of ligand-fishing methods and modern analytical tools (e.g., LC-MS and online natural product databases) offered a route to enhance natural product drug discovery. Herein, a candidate solution referred to as the lickety-split ligand-affinity-based molecular angling system (LLAMAS) is described. This approach utilizes an ultrafiltration-based LC-PDA-MS/MS-guided DNA-binding assay in combination with the (i) Global Natural Products Social Molecular Networking, (ii) Dictionary of Natural Products, and (iii) SciFinder platforms to identify DNA binders in complex chemical mixtures. LLAMAS was initially vetted in tests using known small-molecule DNA binders and then optimized to a 96-well plate-based format. A set of 332 plant samples used in traditional Chinese medicine was screened for DNA-binding activity with LLAMAS, resulting in the identification of seven DNA-binding molecules, including berberine (12), palmatine (13), coptisine (14), fangchinoline (15), tetrandrine (16), daurisoline (17), and dauricine (18). These results demonstrate that LLAMAS is an effective natural product discovery platform for the efficient identification and dereplication of DNA-binding molecules from complex mixtures.

Beyond Plant Microbiome Composition: Exploiting Microbial Functions and Plant Traits via Integrated Approaches

Plants recruit specific microorganisms to live inside and outside their roots that provide essential functions for plant growth and health. The study of the microbial communities living in close association with plants helps in understanding the mechanisms involved in these beneficial interactions. Currently, most of the research in this field has been focusing on the description of the taxonomic composition of the microbiome. Therefore, a focus on the plant-associated microbiome functions is pivotal for the development of novel agricultural practices which, in turn, will increase plant fitness. Recent advances in microbiome research using model plant species started to shed light on the functions of specific microorganisms and the underlying mechanisms of plant–microbial interaction. Here, we review (1) microbiome-mediated functions associated with plant growth and protection, (2) insights from native and agricultural habitats that can be used to improve soil health and crop productivity, (3) current -omics and new approaches for studying the plant microbiome, and (4) challenges and future perspectives for exploiting the plant microbiome for beneficial outcomes. We posit that integrated approaches will help in translating fundamental knowledge into agricultural practices.