The metro is one of the more representative urban transportation systems of Mexico City, and it transports approximately 4.5 million commuters every day. Large crowds promote the exchange of microbes between humans. In this study, we determined the bacterial diversity profile of the Mexico City metro by massive sequencing of the 16S rRNA gene. We identified a total of 50,174 operational taxonomic units (OTUs) and 1058 genera. The metro microbiome was dominated by the phylum Actinobacteria and by the genera Cutibacterium (15%) (C. acnes 13%), Corynebacterium (13%), Streptococcus (9%), and Staphylococcus (5%) (S. epidermidis; 4%), reflecting the microbe composition of healthy human skin. The metro likely microbial sources were skin, dust, saliva, and vaginal, with no fecal contribution detected. A total of 420 bacterial genera were universal to the twelve metro lines tested, and those genera contributed to 99.10% of the abundance. The annual 1.6 billion ridership makes this public transport a main hub for microbe-host-environment interactions. Finally, this study shows that the microbial composition of the Mexico City metro comes from a mixture of environmental and human sources and that commuters are exposed to healthy composition of the human microbiota.

The two-step model for plant root microbiomes considers soil as the primary microbial source. Active selection of the plant’s bacterial inhabitants results in a biodiversity decrease toward roots. We collected sixteen samples of in situ ruderal plant roots and their soils and used these soils as the main microbial input for single genotype tomatoes grown in a greenhouse. Our main goal was to test the soil influence in the structuring of rhizosphere microbiomes, minimizing environmental variability, while testing multiple plant species. We massively sequenced the 16S rRNA and shotgun metagenomes of the soils, in situ plants, and tomato roots. We identified a total of 271,940 bacterial operational taxonomic units (OTUs) within the soils, rhizosphere and endospheric microbiomes. We annotated by homology a total of 411,432 (13.07%) of the metagenome predicted proteins. Tomato roots did follow the two-step model with lower α-diversity than soil, while ruderal plants did not. Surprisingly, ruderal plants are probably working as a microenvironmental oasis providing moisture and plant-derived nutrients, supporting larger α-diversity. Ruderal plants and their soils are closer according to their microbiome community composition than tomato and its soil, based on OTUs and protein comparisons. We expected that tomato β-diversity clustered together with their soil, if it is the main rhizosphere microbiome structuring factor. However, tomato microbiome β-diversity was associated with plant genotype in most samples (81.2%), also supported by a larger set of enriched proteins in tomato rhizosphere than soil or ruderals. The most abundant bacteria found in soils was the Actinobacteria Solirubrobacter soli , ruderals were dominated by the Proteobacteria Sphingomonas sp. URGHD0057, and tomato mainly by the Bacteroidetes Ohtaekwangia koreensis , Flavobacterium terrae, Niastella vici , and Chryseolinea serpens. We calculated a metagenomic tomato root core of 51 bacterial genera and 2,762 proteins, which could be the basis for microbiome-oriented plant breeding programs. We attributed a larger diversity in ruderal plants roots exudates as an effect of the moisture and nutrient acting as a microbial harbor. The tomato and ruderal metagenomic differences are probably due to plant domestication trade-offs, impacting plant-bacteria interactions.

IntroductionRecent studies have revealed the presence of N-acyl-homoserine lactones (AHLs) quorum sensing (QS) signals in the oral environment. Yet, their role in oral biofilm development remains scarcely investigated. The use of quorum quenching (QQ) strategies targeting AHLs has been described as efficient for the control of pathogenic biofilms. Here, we evaluate the use of a highly active AHL-targeting QQ enzyme, Aii20J, to modulate oral biofilm formation in vitro.MethodsThe effect of the QQ enzyme was studied in in vitro multispecies biofilms generated from oral samples taken from healthy donors and patients with periodontal disease. Subgingival samples were used as inocula, aiming to select members of the microbiota of the periodontal pocket niche in the in vitro biofilms. Biofilm formation abilities and microbial composition were studied upon treating the biofilms with the QQ enzyme Aii20J.Results and DiscussionThe addition of the enzyme resulted in significant biofilm mass reductions in 30 – 60% of the subgingival-derived biofilms, although standard AHLs could not be found in the supernatants of the cultured biofilms. Changes in biofilm mass were not accompanied by significant alterations of bacterial relative abundance at the genus level. The investigation of 125 oral supragingival metagenomes and a synthetic subgingival metagenome revealed a surprisingly high abundance and broad distribution of homologous of the AHL synthase HdtS and several protein families of AHL receptors, as well as an enormous presence of QQ enzymes, pointing to the existence of an intricate signaling network in oral biofilms that has been so far unreported, and should be further investigated. Together, our findings support the use of Aii20J to modulate polymicrobial biofilm formation without changing the microbiome structure of the biofilm. Results in this study suggest that AHLs or AHL-like molecules affect oral biofilm formation, encouraging the application of QQ strategies for oral health improvement, and reinforcing the importance of personalized approaches to oral biofilm control.

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Subways are urban transport systems with high capacity. Every day around the world, there are more than 150 million subway passengers. Since 2013, thousands of microbiome samples from various subways worldwide have been sequenced. Skin bacteria and environmental organisms dominate the subway microbiomes. The literature has revealed common bacterial groups in subway systems; even so, it is possible to identify cities by their microbiome. Low frequency bacteria are responsible for specific bacterial fingerprints of each subway system. Furthermore, daily subway commuters leave their microbial clouds and interact with other passengers. Microbial exchange is quite fast; the hand microbiome changes within minutes, and after cleaning the handrails, the bacteria are re-established within minutes. To investigate new taxa and metabolic pathways of subway microbial communities, several high-quality metagenomic-assembled genomes (MAG) have been described. Subways are harsh environments unfavorable for microorganism growth. However, recent studies have observed a wide diversity of viable and metabolically active bacteria. Understanding which bacteria are living, dormant, or dead allows us to propose realistic ecological interactions. Questions regarding the relationship between humans and the subway microbiome, particularly the microbiome effects on personal and public health, remain unanswered. This review summarizes our knowledge of subway microbiomes and their relationship with passenger microbiomes.