Direct Meta-Analyses Reveal Unexpected Microbial Life in the Highly Radioactive Water of an Operating Nuclear Reactor Core

Prokaryotic communities inhabiting a high-radon subterranean ecosystem (Castañar Cave, Spain): Environmental and substrate-driven controls

Castañar Cave (Caceres, Spain) is a unique show cave known for its high natural radiation levels. This study presents a comprehensive analysis of its prokaryotic diversity, specifically focusing on investigating the influence of environmental conditions and substrate characteristics on the prokaryotic community structure in the cave sediments. Additionally, the research aims to evaluate the potential impact of human activities on the cave ecosystem. The identification of distinct bioclimatic zones within the cave was made possible through a combination of environmental and microbial monitoring (ATP assays). The results reveal sediment texture as a significant factor, notably affecting the structure, diversity, and phylogenetic variability of the microbial community, including both Bacteria and Archaea. The proportion of clay minerals in sediments plays a crucial role in regulating moisture levels and nutrient availability. These substrate properties collectively exert a significant selective pressure on the structure of prokaryotic communities within cave sediments. The molecular approach shows that heterotrophic bacteria, including those with chitinolytic enzymes, primarily inhabit the cave. Furthermore, chemoautotrophic nitrifiers such as the archaea Nitrososphaeria and the genus Nitrospira, as well as methanotrophic bacteria from the phyla Methylomirabilota, Pseudomonadota, and Verrucomicrobiota, are also present. Remarkably, despite being a show cave, the cave microbiota displays minimal impacts from human activities and the surface ecosystem. Prokaryotic populations exhibit stability in the innermost areas, while the tourist trail area experiences slightly higher biomass increases due to visitor traffic. This suggests that conservation efforts have successfully limited the entry of external nutrients into the innermost cave areas. Additionally, the results suggest that integrating biomarkers like ATP into environmental monitoring can significantly enhance the methods used to study the negative impacts of tourism on cave ecosystems.

Label-Free Multiplex Proteotyping of Microbial Isolates

To meet clinical diagnostic needs and for general microbiological screening, it is essential to be able to accurately and rapidly identify any microorganisms from complex microbiota. To gain insight into the individual components of microbiota, culturomics has been proposed as a means to systematically test hundreds of possible cultivation conditions and generate numerous microbial isolates with very distinct characteristics. High-throughput identification methods must now be developed to quickly screen these isolates. Currently, most multiplexing methods involve labeling, which comes at a cost. In this paper, we present an innovative label-free multiplexing method for the identification of microorganisms using tandem mass spectrometry. The method is based on offline reversed-phase fractionation of individual peptidomes. Multiplexing is achieved by mixing fractions of staged hydrophobicity; thus, each sample is mapped to specific elution times. In this proof-of-concept study, multiplexed samples were analyzed by tandem mass spectrometry in a single run and microorganisms present in the mixture were resolved by phylopeptidomics proteotyping. Using this methodology, up to 21 microorganisms could be identified in a single 60 min run performed with a Q-Exactive HF high-resolution mass spectrometer, resulting in a rate of one microorganism identified per 3 min of mass spectrometry, without any need for the use of labeling reagents. This approach opens new perspectives for the application of high-throughput proteotyping of bacteria using tandem mass spectrometry in large culturomics projects.

First Isolation and Characterization of Bacteria from the Core's Cooling Pool of an Operating Nuclear Reactor

Microbial life can thrive in the most inhospitable places, such as nuclear facilities with high levels of ionizing radiation. Using direct meta-analyses, we have previously highlighted the presence of bacteria belonging to twenty-five different genera in the highly radioactive water of the cooling pool of an operating nuclear reactor core. In the present study, we further characterize this specific environment by isolating and identifying some of these microorganisms and assessing their radiotolerance and their ability to decontaminate uranium. This metal is one of the major radioactive contaminants of anthropogenic origin in the environment due to the nuclear and mining industries and agricultural practices. The microorganisms isolated when sampling was performed during the reactor operation consisted mainly of Actinobacteria and Firmicutes, whereas Proteobacteria were dominant when sampling was performed during the reactor shutdown. We investigated their tolerance to gamma radiation under different conditions. Most of the bacterial strains studied were able to survive 200 Gy irradiation. Some were even able to withstand 1 kGy, with four of them showing more than 10% survival at this dose. We also assessed their uranium uptake capacity. Seven strains were able to remove almost all the uranium from a 5 µM solution. Four strains displayed high efficiency in decontaminating a 50 µM uranium solution, demonstrating promising potential for use in bioremediation processes in environments contaminated by radionuclides.

Mix24X, a Lab-Assembled Reference to Evaluate Interpretation Procedures for Tandem Mass Spectrometry Proteotyping of Complex Samples

Correct identification of the microorganisms present in a complex sample is a crucial issue. Proteotyping based on tandem mass spectrometry can help establish an inventory of organisms present in a sample. Evaluation of bioinformatics strategies and tools for mining the recorded datasets is essential to establish confidence in the results obtained and to improve these pipelines in terms of sensitivity and accuracy. Here, we propose several tandem mass spectrometry datasets recorded on an artificial reference consortium comprising 24 bacterial species. This assemblage of environmental and pathogenic bacteria covers 20 different genera and 5 bacterial phyla. The dataset comprises difficult cases, such as the Shigella flexneri species, which is closely related to Escherichia coli, and several highly sequenced clades. Different acquisition strategies simulate real-life scenarios: from rapid survey sampling to exhaustive analysis. We provide access to individual proteomes of each bacterium separately to provide a rational basis for evaluating the assignment strategy of MS/MS spectra when recorded from complex mixtures. This resource should provide an interesting common reference for developers who wish to compare their proteotyping tools and for those interested in evaluating protein assignment when dealing with complex samples, such as microbiomes.

Taxonomical composition and functional analysis of biofilms sampled from a nuclear storage pool

Sampling small amounts of biofilm from harsh environments such as the biofilm present on the walls of a radioactive material storage pool offers few analytical options if taxonomic characterization and estimation of the different biomass contributions are the objectives. Although 16S/18S rRNA amplification on extracted DNA and sequencing is the most widely applied method, its reliability in terms of quantitation has been questioned as yields can be species-dependent. Here, we propose a tandem-mass spectrometry proteotyping approach consisting of acquiring peptide data and interpreting then against a generalist database without any a priori. The peptide sequence information is transformed into useful taxonomical information that allows to obtain the different biomass contributions at different taxonomical ranks. This new methodology is applied for the first time to analyze the composition of biofilms from minute quantities of material collected from a pool used to store radioactive sources in a nuclear facility. For these biofilms, we report the identification of three genera, namely Sphingomonas, Caulobacter, and Acidovorax, and their functional characterization by metaproteomics which shows that these organisms are metabolic active. Differential expression of Gene Ontology GOslim terms between the two main microorganisms highlights their metabolic specialization.

Characteristics of airborne bacterial communities and antibiotic resistance genes under different air quality levels

Pathogenic bacteria and antibiotic resistance genes (ARGs) in bioaerosols are major threats to human health. In this study, the microbial community structure and ARG distribution characteristics of airborne bacteria in total suspended particulates (TSP) and PM_2.5 were investigated under different air quality levels in Xinxiang, Central China. The results revealed that with the deterioration of air quality, the concentrations of airborne bacteria in both TSP and PM_2.5 decreased; however, the relative amounts of pathogenic bacteria increased. The predominant genera in pathogenic bacteria of Bacillus, Sphingomonas, Corynebacterium, Rhodococcus, and Staphylococcus were identified in both TSP and PM_2.5. Although the airborne bacteria concentrations and absolute abundances of ARGs in TSP were higher than those in PM_2.5 under identical air quality conditions, the bacterial community structure and relative amounts of pathogenic bacteria were similar. In addition, the relationship between environmental factors of ions, metal elements, and meteorological parameters and the community structures of airborne bacteria and pathogenic bacteria were also analyzed. The effects of soluble ions and metal elements on several dominant genera of total bacteria and pathogenic bacteria differed, probably due to the strong tolerance of pathogenic bacteria to harsh atmospheric environments Different subtypes of ARGs showed various distribution characteristics with variations in air quality. The deterioration of air quality can inhibit the dissemination of ARGs, as the minimum values of all ARGs and class 1 integrase intI1 were observed under Severely Polluted conditions. This study provides a comprehensive understanding of the effect of air pollution levels on the airborne bacteria community composition and ARG distribution.

Cyclical Patterns Affect Microbial Dynamics in the Water Basin of a Nuclear Research Reactor

The BR2 nuclear research reactor in Mol, Belgium, runs in successive phases of operation (cycles) and shutdown, whereby a water basin surrounding the reactor vessel undergoes periodic changes in physico-chemical parameters such as flow rate, temperature, and radiation. The aim of this study was to explore the microbial community in this unique environment and to investigate its long-term dynamics using a 16S rRNA amplicon sequencing approach. Results from two sampling campaigns spanning several months showed a clear shift in community profiles: cycles were mostly dominated by two Operational Taxonomic Units (OTUs) assigned to unclassified Gammaproteobacterium and Pelomonas, whereas shutdowns were dominated by an OTU assigned to Methylobacterium. Although 1 year apart, both campaigns showed similar results, indicating that the system remained stable over this 2-year period. The community shifts were linked with changes in physico-chemical parameters by Non-metric Multidimensional Scaling (NMDS) and correlation analyses. In addition, radiation was hypothesized to cause a decrease in cell number, whereas temperature had the opposite effect. Chemoautotrophic use of H₂ and dead cell recycling are proposed to be used as a strategies for nutrient retrieval in this extremely oligotrophic environment.