Effect of endogenous microbiota on the molecular composition of cloud water: a study by Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS)

Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Applications for Metabolomics

Metabolomics is an interdisciplinary field that aims to study all metabolites < 1500 Da that are ubiquitously found within all organisms. Metabolomics is experiencing exponential growth and commonly relies on high-resolution mass spectrometry (HRMS). Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is a form of HRMS that is particularly well suited for metabolomics research due to its exceptionally high resolution (105-106) and sensitivity with a mass accuracy in parts per billion (ppb). In this regard, FT-ICR-MS can provide valuable insights into the metabolomics analysis of complex biological systems due to unique capabilities such as the easy separation of isobaric and isomeric species, isotopic fine structure analysis, spatial resolution of metabolites in cells and tissues, and a high confidence (<1 ppm mass error) in metabolite identification. Alternatively, the large and complex data sets, long acquisition times, high cost, and limited access mainly through national mass spectrometry facilities may impede the routine adoption of FT-ICR-MS by metabolomics researchers. This review examines recent applications of FT-ICR-MS metabolomics in the search for clinical and non-human biomarkers; for the analysis of food, beverage, and environmental samples; and for the high-resolution imaging of tissues and other biological samples. We provide recent examples of metabolomics studies that highlight the advantages of FT-ICR-MS for the detailed and reliable characterization of the metabolome. Additionally, we offer some practical considerations for implementing FT-ICR-MS into a research program by providing a list of FT-ICR-MS facilities and by identifying different high-throughput interfaces, varieties of sample types, analysis methods (e.g., van Krevelen diagrams, Kendrick mass defect plot, etc.), and sample preparation and handling protocols used in FT-ICR-MS experiments. Overall, FT-ICR-MS holds great promise as a vital research tool for advancing metabolomics investigations.

Effect of Land Use Change on Molecular Composition and Concentration of Organic Matter in an Oxisol

Land use change from native vegetation to cropping can significantly affect the quantity and quality of soil organic matter (SOM). However, it remains unclear how the chemical composition of SOM is affected by such changes. This study employed a sequential chemical extraction to partition SOM from an Oxisol into several distinct fractions: water-soluble fractions (ultrapure water (W)), organometal complexes (sodium pyrophosphate (PP)), short-range ordered (SRO) oxides (hydroxylamine-HCl (HH)), and well-crystalline oxides (dithionite-HCl (DH)). Coupled with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS), the impact of land use change on the molecular composition of different OM fractions was investigated. Greater amounts of OM were observed in the PP and HH fractions compared to other fractions, highlighting their importance in SOM stabilization. The composition of different OM fractions varied based on extracted phases, with lignin-like and tannin-like compounds being prevalent in the PP and HH fractions, while aliphatic-like compounds dominated in the DH fraction. Despite changes in the concentration of each OM fraction from native vegetation to cropping, there was little influence of land use change on the molecular composition of OM associated with different mineral phases. No significant selective loss or preservation of organic carbon compounds was observed, indicating the composition of SOM remained unchanged.

Emerging investigator series: aqueous photooxidation of live bacteria with hydroxyl radicals under cloud-like conditions: insights into the production and transformation of biological and organic matter originating from bioaerosols

Live bacteria in clouds are exposed to free radicals such as the hydroxyl radical (˙OH), which is the main driver of many photochemical processes. While the ˙OH photooxidation of organic matter in clouds has been widely studied, equivalent investigations on the ˙OH photooxidation of bioaerosols are limited. Little is known about the daytime encounters between ˙OH and live bacteria in clouds. Here we investigated the aqueous ˙OH photooxidation of four bacterial strains, B. subtilis, P. putida, E. hormaechei B0910, and E. hormaechei pf0910, in microcosms composed of artificial cloud water that mimicked the chemical composition of cloud water in Hong Kong. The survival rates for the four bacterial strains decreased to zero within 6 hours during exposure to 1 × 10-16 M of ˙OH under artificial sunlight. Bacterial cell damage and lysis released biological and organic compounds, which were subsequently oxidized by ˙OH. The molecular weights of some of these biological and organic compounds were >50 kDa. The O/C, H/C, and N/C ratios increased at the initial onset of photooxidation. As the photooxidation progressed, there were few changes in the H/C and N/C, whereas the O/C continued to increase for hours after all the bacterial cells had died. The increase in the O/C was due to functionalization and fragmentation reactions, which increased the O content and decreased the C content, respectively. In particular, fragmentation reactions played key roles in transforming biological and organic compounds. Fragmentation reactions cleaved the C-C bonds of carbon backbones of higher molecular weight proteinaceous-like matter to form a variety of lower molecular weight compounds, including HULIS of molecular weight <3 kDa and highly oxygenated organic compounds of molecular weight <1.2 kDa. Overall, our results provided new insights at the process level into how daytime reactive interactions between live bacteria and ˙OH in clouds contribute to the formation and transformation of organic matter.

The aeromicrobiome: the selective and dynamic outer-layer of the Earth's microbiome

The atmosphere is an integral component of the Earth's microbiome. Abundance, viability, and diversity of microorganisms circulating in the air are determined by various factors including environmental physical variables and intrinsic and biological properties of microbes, all ranging over large scales. The aeromicrobiome is thus poorly understood and difficult to predict due to the high heterogeneity of the airborne microorganisms and their properties, spatially and temporally. The atmosphere acts as a highly selective dispersion means on large scales for microbial cells, exposing them to a multitude of physical and chemical atmospheric processes. We provide here a brief critical review of the current knowledge and propose future research directions aiming at improving our comprehension of the atmosphere as a biome.

How Well Do We Handle the Sample Preparation, FT-ICR Mass Spectrometry Analysis, and Data Treatment of Atmospheric Waters?

FT-ICR MS (Fourier-transform ion cyclotron resonance mass spectrometry) analysis has shown great potential to aid in the understanding of the extremely high molecular diversity of cloud water samples. The main goal of this work was to determine the differences in terms of formula assignment for analytical (i.e., measurement replicates) and experimental replicates of a given cloud water sample. The experimental replicates, obtained by solid phase extraction, were also compared to the results obtained for freeze-dried samples to evaluate whether the presence of salts interferes with the analysis. Two S/N ratios, generally adopted for atmospheric samples, were evaluated, and three different algorithms were used for assignment: DataAnalysis 5.3 (Bruker), Composer (Sierra Analytics), and MFAssignR (Chemical Advanced Resolution Methods Lab). In contrast to other works, we wanted to treat this comparison from the point of view of users, who usually must deal with a simple list of m/z ratios and intensity with limited access to the mass spectrum characteristics. The aim of this study was to establish a methodology for the treatment of atmospheric aqueous samples in light of the comparison of three different software programs, to enhance the possibility of data comparison within samples.

OUP accepted manuscript

The atmosphere connects habitats across multiple spatial scales via airborne dispersal of microbial cells, propagules and biomolecules. Atmospheric microorganisms have been implicated in a variety of biochemical and biophysical transformations. Here, we review ecological aspects of airborne microorganisms with respect to their dispersal, activity and contribution to climatic processes. Latest studies utilizing metagenomic approaches demonstrate that airborne microbial communities exhibit pronounced biogeography, driven by a combination of biotic and abiotic factors. We quantify distributions and fluxes of microbial cells between surface habitats and the atmosphere and place special emphasis on long-range pathogen dispersal. Recent advances have established that these processes may be relevant for macroecological outcomes in terrestrial and marine habitats. We evaluate the potential biological transformation of atmospheric volatile organic compounds and other substrates by airborne microorganisms and discuss clouds as hotspots of microbial metabolic activity in the atmosphere. Furthermore, we emphasize the role of microorganisms as ice nucleating particles and their relevance for the water cycle via formation of clouds and precipitation. Finally, potential impacts of anthropogenic forcing on the natural atmospheric microbiota via emission of particulate matter, greenhouse gases and microorganisms are discussed.

Classification of Clouds Sampled at the Puy de Dôme Station (France) Based on Chemical Measurements and Air Mass History Matrices

A statistical analysis of 295 cloud samples collected at the Puy de Dôme station in France (PUY), covering the period 2001–2018, was conducted using principal component analysis (PCA), agglomerative hierarchical clustering (AHC), and partial least squares (PLS) regression. Our model classified the cloud water samples on the basis of their chemical concentrations and of the dynamical history of their air masses estimated with back-trajectory calculations. The statistical analysis split our dataset into two sets, i.e., the first set characterized by westerly air masses and marine characteristics, with high concentrations of sea salts and the second set having air masses originating from the northeastern sector and the “continental” zone, with high concentrations of potentially anthropogenic ions. It appears from our dataset that the influence of cloud microphysics remains minor at PUY as compared with the impact of the air mass history, i.e., physicochemical processes, such as multiphase reactivity.