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.

Quantification of antibiotic resistance genes (ARGs) in clouds at a mountain site (puy de Dôme, central France).

Antibiotic resistance in bacteria is becoming a major sanitary concern worldwide. The extensive use of large quantities of antibiotics to sustain human activity has led to the rapid acquisition and maintenance of antibiotic resistant genes (ARGs) in bacteria and to their spread into the environment. Eventually, these can be disseminated over long distances by atmospheric transport. Here, we assessed the presence of ARGs in clouds as an indicator of long-distance travel potential of antibiotic resistance in the atmosphere. We hypothesized that a variety of ARGs can reach the altitude of clouds mainly located within the free troposphere. Once incorporated in the atmosphere, they are efficiently transported and their respective concentrations should differ depending on the sources and the geographical origin of the air masses. We deployed high-flow rate impingers and collected twelve clouds between September 2019 and October 2021 at the meteorological station of the puy de Dôme summit (1465 m a.s.l., France). Total airborne bacteria concentration was assessed by flow cytometry, and ARGs subtypes of the main families of antibiotic resistance (quinolone, sulfonamide, tetracycline; glycopeptide, aminoglycoside, ß-lactamase, macrolide) including one mobile genetic element (transposase) were quantified by qPCR. Our results indicate the presence of 29 different ARGs' subtypes at concentrations ranging from 1.01 × 103 to 1.61 × 104 copies m-3 of air. Clear distinctions could be observed between clouds in air masses transported over marine areas (Atlantic Ocean) and clouds influenced by continental surfaces. Specifically, quinolones (mostly qepA) resistance genes were prevalent in marine clouds (54 % of the total ARGs on average), whereas higher contributions of sulfonamide, tetracycline; glycopeptide, ß-lactamase and macrolide were found in continental clouds. This study constitutes the first evidence for the presence of microbial ARGs in clouds at concentrations comparable to other natural environments. This highlights the atmosphere as routes for the dissemination of ARGs at large scale.

Rainfalls sprinkle cloud bacterial diversity while scavenging biomass.

Bacteria circulate in the atmosphere, through clouds and precipitation to surface ecosystems. Here, we conducted a coordinated study of bacteria assemblages in clouds and precipitation at two sites distant of ∼800 m in elevation in a rural vegetated area around puy de Dôme Mountain, France, and analysed them in regard to meteorological, chemical and air masses' history data. In both clouds and precipitation, bacteria generally associated with vegetation or soil dominated. Elevated ATP-to-cell ratio in clouds compared with precipitation suggested a higher proportion of viable cells and/or specific biological processes. The increase of bacterial cell concentration from clouds to precipitation indicated strong below-cloud scavenging. Using ions as tracers, we derive that 0.2 to 25.5% of the 1.1 × 107 to 6.6 × 108 bacteria cell/m2/h1 deposited with precipitation originated from the source clouds. Yet, the relative species richness decreased with the proportion of inputs from clouds, pointing them as sources of distant microbial diversity. Biodiversity profiles, thus, differed between clouds and precipitation in relation with distant/local influencing sources, and potentially with bacterial phenotypic traits. Notably Undibacterium, Bacillus and Staphylococcus were more represented in clouds, while epiphytic bacteria such as Massilia, Sphingomonas, Rhodococcus and Pseudomonas were enriched in precipitation.

Deciphering intra-species bacterial diversity of meat and seafood spoilage microbiota using gyrB amplicon sequencing: A comparative analysis with 16S rDNA V3-V4 amplicon sequencing.

Meat and seafood spoilage ecosystems harbor extensive bacterial genomic diversity that is mainly found within a small number of species but within a large number of strains with different spoilage metabolic potential. To decipher the intraspecies diversity of such microbiota, traditional metagenetic analysis using the 16S rRNA gene is inadequate. We therefore assessed the potential benefit of an alternative genetic marker, gyrB, which encodes the subunit B of DNA gyrase, a type II DNA topoisomerase. A comparison between 16S rDNA-based (V3-V4) amplicon sequencing and gyrB-based amplicon sequencing was carried out in five types of meat and seafood products, with five mock communities serving as quality controls. Our results revealed that bacterial richness in these mock communities and food samples was estimated with higher accuracy using gyrB than using16S rDNA. However, for Firmicutes species, 35% of putative gyrB reads were actually identified as sequences of a gyrB paralog, parE, which encodes subunit B of topoisomerase IV; we therefore constructed a reference database of published sequences of both gyrB and pare for use in all subsequent analyses. Despite this co-amplification, the deviation between relative sequencing quantification and absolute qPCR quantification was comparable to that observed for 16S rDNA for all the tested species. This confirms that gyrB can be used successfully alongside 16S rDNA to determine the species composition (richness and evenness) of food microbiota. The major benefit of gyrB sequencing is its potential for improving taxonomic assignment and for further investigating OTU richness at the subspecies level, thus allowing more accurate discrimination of samples. Indeed, 80% of the reads of the 16S rDNA dataset were represented by thirteen 16S rDNA-based OTUs that could not be assigned at the species-level. Instead, these same clades corresponded to 44 gyrB-based OTUs, which differentiated various lineages down to the subspecies level. The increased ability of gyrB-based analyses to track and trace phylogenetically different groups of strains will generate improved resolution and more reliable results for studies of the strains implicated in food processes.