Microscale Spatial Dysbiosis in Oral biofilms Associated with Disease.

Microbiome dysbiosis has largely been defined using compositional analysis of metagenomic sequencing data; however, differences in the spatial arrangement of bacteria between healthy and diseased microbiomes remain largely unexplored. In this study, we measured the spatial arrangement of bacteria in dental implant biofilms from patients with healthy implants, peri-implant mucositis, or peri-implantitis, an oral microbiome-associated inflammatory disease. We discovered that peri-implant biofilms from patients with mild forms of the disease were characterized by large single-genus patches of bacteria, while biofilms from healthy sites were more complex, mixed structures.

Spatial mapping of mobile genetic elements and their bacterial hosts in complex microbiomes.

The exchange of mobile genetic elements (MGEs) facilitates the spread of functional traits including antimicrobial resistance within bacterial communities. Tools to spatially map MGEs and identify their bacterial hosts in complex microbial communities are currently lacking, limiting our understanding of this process. Here we combined single-molecule DNA fluorescence in situ hybridization (FISH) with multiplexed ribosomal RNA-FISH to enable simultaneous visualization of both MGEs and bacterial taxa.

Spatial Mapping of Mobile Genetic Elements and their Cognate Hosts in Complex Microbiomes.

The frequent exchange of mobile genetic elements (MGEs) between bacteria accelerates the spread of functional traits, including antimicrobial resistance, within the human microbiome. Yet, progress in understanding these intricate processes has been hindered by the lack of tools to map the spatial spread of MGEs in complex microbial communities, and to associate MGEs to their bacterial hosts. To overcome this challenge, we present an imaging approach that pairs single molecule DNA Fluorescence In Situ Hybridization (FISH) with multiplexed ribosomal RNA FISH, thereby enabling the simultaneous visualization of both MGEs and host bacterial taxa.

Chickensplash! Exploring the health concerns of washing raw chicken.

The Food and Drug Administration recommends against washing raw chicken due to the risk of transferring dangerous food-borne pathogens through splashed drops of water. Many cooks continue to wash raw chicken despite this warning, however, and there is a lack of scientific research assessing the extent of microbial transmission in splashed droplets. Here, we use large agar plates to confirm that bacteria can be transferred from the surface of raw chicken through splashing.

Recent advances in tools to map the microbiome.

Microbes thrive in diverse habitats. They often form ecological niches with rich species diversity and complex spatial structure. These communities drive biogeochemical cycles in the environment and modulate host health in the human body.

Spatiotemporal single-cell RNA sequencing of developing chicken hearts identifies interplay between cellular differentiation and morphogenesis.

Single-cell RNA sequencing is a powerful tool to study developmental biology but does not preserve spatial information about tissue morphology and cellular interactions. Here, we combine single-cell and spatial transcriptomics with algorithms for data integration to study the development of the chicken heart from the early to late four-chambered heart stage. We create a census of the diverse cellular lineages in developing hearts, their spatial organization, and their interactions during development.

Highly multiplexed spatial mapping of microbial communities.

Mapping the complex biogeography of microbial communities in situ with high taxonomic and spatial resolution poses a major challenge because of the high density and rich diversity of species in environmental microbiomes and the limitations of optical imaging technology. Here we introduce high-phylogenetic-resolution microbiome mapping by fluorescence in situ hybridization (HiPR-FISH), a versatile technology that uses binary encoding, spectral imaging and decoding based on machine learning to create micrometre-scale maps of the locations and identities of hundreds of microbial species in complex communities. We show that 10-bit HiPR-FISH can distinguish between 1,023 isolates of Escherichia coli, each fluorescently labelled with a unique binary barcode.