Spatial metatranscriptomics resolves host-bacteria-fungi interactomes

Dual spatial host-bacterial gene expression in Mycobacterium abscessus respiratory infections

Co-localization of spatial transcriptome information of host and pathogen can revolutionize our understanding of microbial pathogenesis. Here, we aimed to demonstrate that customized bacterial probes can be successfully used to identify host-pathogen interactions in formalin-fixed-paraffin-embedded (FFPE) tissues by probe-based spatial transcriptomics technology. We analyzed the spatial gene expression of bacterial transcripts with the host transcriptomic profile in murine lung tissue chronically infected with Mycobacterium abscessus embedded in agar beads. Customized mycobacterial probes were designed for the constitutively expressed rpoB gene (an RNA polymerase β subunit) and the virulence factor precursor lsr2, modulated by oxidative stress. We found a correlation between the rpoB expression, bacterial abundance in the airways, and an increased expression of lsr2 virulence factor in lung tissue with high oxidative stress. Overall, we demonstrate the potential of dual bacterial and host gene expression assay in FFPE tissues, paving the way for the simultaneous detection of host and bacterial transcriptomes in pathological tissues.

Quantitative and spatially resolved detection of multiplexed microRNA from plant tissue via hybridization to hydrogel-bound DNA probes in nanoliter well arrays

Understanding complex regulatory networks in plant systems requires elucidating the roles of various gene regulators under a spatial landscape. MicroRNA are key regulators that impart high information value through their tissue specificity and stability when using expression patterns for evaluating network outcomes. However, current techniques that utilize spatial multiplexing and quantitation of microRNA are limited to primarily mammalian systems. Here, we present a method to spatially resolve and quantify multiple endogenous microRNA in situ using ethanol fixed, paraffin embedded model plant species. This method utilizes target-specific microRNA capture along with universal ligating and labelling, all within functionalized hydrogel posts containing DNA probes in nanoliter well arrays. We demonstrate the platform's multiplexing capabilities through analyzing three endogenous microRNA in Arabidopsis thaliana rosettes which provide useful answers to fundamental plant growth and development from the unique expression patterns. The spatial tissue technique is also validated using non-spatial small RNA assays to demonstrate the versatility of the well array platform. Our new platform expands the toolkit of spatial omics technologies for plants.

An approach to analyze spatiotemporal patterns of gene expression at single-cell resolution in Candida albicans-infected mouse tongues

Microbial gene expression measurements derived from infected organs are invaluable to understand pathogenesis. However, current methods are limited to "bulk" analyses that neglect microbial cell heterogeneity and the lesion's spatial architecture. Here, we report the use of hybridization chain reaction RNA fluorescence in situ hybridization (HCR RNA-FISH) to visualize and quantify Candida albicans transcripts at single-cell resolution in tongues of infected mice. The method is compatible with fixed-frozen and formalin-fixed paraffin-embedded tissues. We document cell-to-cell variation and intriguing spatiotemporal expression patterns for C. albicans mRNAs that encode products implicated in oral candidiasis. The approach provides a spatial dimension to gene expression analyses of host-Candida interactions.

IMPORTANCE

Candida albicans is a fungal pathobiont inhabiting multiple mucosal surfaces of the human body. Immunosuppression, antibiotic-induced microbial dysbiosis, or implanted medical devices can impair mucosal integrity enabling C. albicans to overgrow and disseminate, causing either mucosal diseases such as oropharyngeal candidiasis or life-threatening systemic infections. Profiling fungal genes that are expressed in the infected mucosa or in any other infected organ is paramount to understand pathogenesis. Ideally, these transcript profiling measurements should reveal the expression of any gene at the single-cell level. The resolution typically achieved with current approaches, however, limits most gene expression measurements to cell population averages. The approach described in this report provides a means to dissect fungal gene expression in infected tissues at single-cell resolution.

Single-cell transcriptomics reveals heterogeneity in plant responses to the environment: a focus on biotic and abiotic interactions

Biotic and abiotic environmental cues are major factors influencing plant growth and productivity. Interactions with biotic (e.g. symbionts and pathogens) and abiotic (e.g. changes in temperature, water, or nutrient availability) factors trigger signaling and downstream transcriptome adjustments in plants. While bulk RNA-sequencing technologies have traditionally been used to profile these transcriptional changes, tissue homogenization may mask heterogeneity of responses resulting from the cellular complexity of organs. Thus, whether different cell types respond equally to environmental fluctuations, or whether subsets of the responses are cell-type specific, are long-lasting questions in plant biology. The recent breakthrough of single-cell transcriptomics in plant research offers an unprecedented view of cellular responses under changing environmental conditions. In this review, we discuss the contribution of single-cell transcriptomics to the understanding of cell-type-specific plant responses to biotic and abiotic environmental interactions. Besides major biological findings, we present some technical challenges coupled to single-cell studies of plant-environment interactions, proposing possible solutions and exciting paths for future research.

Comparative Cross-Kingdom DDA- and DIA-PASEF Proteomic Profiling Reveals Novel Determinants of Fungal Virulence and a Putative Druggable Target

Accurate and reliable detection of fungal pathogens presents an important hurdle to manage infections, especially considering that fungal pathogens, including the globally important human pathogen, Cryptococcus neoformans, have adapted diverse mechanisms to survive the hostile host environment and moderate virulence determinant production during coinfections. These pathogen adaptations present an opportunity for improvements (e.g., technological and computational) to better understand the interplay between a host and a pathogen during disease to uncover new strategies to overcome infection. In this study, we performed comparative proteomic profiling of an in vitro coinfection model across a range of fungal and bacterial burden loads in macrophages. Comparing data-dependent acquisition and data-independent acquisition enabled with parallel accumulation serial fragmentation technology, we quantified changes in dual-perspective proteome remodeling. We report enhanced and novel detection of pathogen proteins with data-independent acquisition-parallel accumulation serial fragmentation (DIA-PASEF), especially for fungal proteins during single and dual infection of macrophages. Further characterization of a fungal protein detected only with DIA-PASEF uncovered a novel determinant of fungal virulence, including altered capsule and melanin production, thermotolerance, and macrophage infectivity, supporting proteomics advances for the discovery of a novel putative druggable target to suppress C. neoformans pathogenicity.

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. We spatially mapped bacteriophage and antimicrobial resistance (AMR) plasmids and identified their host taxa in human oral biofilms. This revealed distinct clusters of AMR plasmids and prophage, coinciding with densely packed regions of host bacteria. Our data suggest spatial heterogeneity in bacterial taxa results in heterogeneous MGE distribution within the community, with MGE clusters resulting from horizontal gene transfer hotspots or expansion of MGE-carrying strains. Our approach can help advance the study of AMR and phage ecology in biofilms.

LIANA+ provides an all-in-one framework for cell-cell communication inference

The growing availability of single-cell and spatially resolved transcriptomics has led to the development of many approaches to infer cell-cell communication, each capturing only a partial view of the complex landscape of intercellular signalling. Here we present LIANA+, a scalable framework built around a rich knowledge base to decode coordinated inter- and intracellular signalling events from single- and multi-condition datasets in both single-cell and spatially resolved data. By extending and unifying established methodologies, LIANA+ provides a comprehensive set of synergistic components to study cell-cell communication via diverse molecular mediators, including those measured in multi-omics data. LIANA+ is accessible at https://github.com/saezlab/liana-py with extensive vignettes ( https://liana-py.readthedocs.io/ ) and provides an all-in-one solution to intercellular communication inference.

RiboSnake - a user-friendly, robust, reproducible, multipurpose and documentation-extensive pipeline for 16S rRNA gene microbiome analysis

Background

Next-generation sequencing for microbial communities has become a standard technique. However, the computational analysis remains resource-intensive. With declining costs and growing adoption of sequencing-based methods in many fields, validated, fully automated, reproducible and flexible pipelines are increasingly essential in various scientific fields.

Results

We present RiboSnake, a validated, automated, reproducible QIIME2-based pipeline implemented in Snakemake for analysing 16S rRNA gene amplicon sequencing data. RiboSnake includes pre-packaged validated parameter sets optimized for different sample types, from environmental samples to patient data. The configuration packages can be easily adapted and shared, requiring minimal user input.

Conclusion

RiboSnake is a new alternative for researchers employing 16S rRNA gene amplicon sequencing and looking for a customizable and user-friendly pipeline for microbiome analyses with in vitro validated settings. By automating the analysis with validated parameters for diverse sample types, RiboSnake enhances existing methods significantly. The workflow repository can be found on GitHub (https://github.com/IKIM-Essen/RiboSnake).

Spatiotemporal omics for biology and medicine

The completion of the Human Genome Project has provided a foundational blueprint for understanding human life. Nonetheless, understanding the intricate mechanisms through which our genetic blueprint is involved in disease or orchestrates development across temporal and spatial dimensions remains a profound scientific challenge. Recent breakthroughs in cellular omics technologies have paved new pathways for understanding the regulation of genomic elements and the relationship between gene expression, cellular functions, and cell fate determination. The advent of spatial omics technologies, encompassing both imaging and sequencing-based methodologies, has enabled a comprehensive understanding of biological processes from a cellular ecosystem perspective. This review offers an updated overview of how spatial omics has advanced our understanding of the translation of genetic information into cellular heterogeneity and tissue structural organization and their dynamic changes over time. It emphasizes the discovery of various biological phenomena, related to organ functionality, embryogenesis, species evolution, and the pathogenesis of diseases.

Breaking barriers: improving time and space resolution of arbuscular mycorrhizal symbiosis with single-cell sequencing approaches

The cell and molecular bases of arbuscular mycorrhizal (AM) symbiosis, a crucial plant-fungal interaction for nutrient acquisition, have been extensively investigated by coupling traditional RNA sequencing techniques of roots sampled in bulk, with methods to capture subsets of cells such as laser microdissection. These approaches have revealed central regulators of this complex relationship, yet the requisite level of detail to effectively untangle the intricacies of temporal and spatial development remains elusive.The recent adoption of single-cell RNA sequencing (scRNA-seq) techniques in plant research is revolutionizing our ability to dissect the intricate transcriptional profiles of plant-microbe interactions, offering unparalleled insights into the diversity and dynamics of individual cells during symbiosis. The isolation of plant cells is particularly challenging due to the presence of cell walls, leading plant researchers to widely adopt nuclei isolation methods. Despite the increased resolution that single-cell analyses offer, it also comes at the cost of spatial perspective, hence, it is necessary the integration of these approaches with spatial transcriptomics to obtain a comprehensive overview.To date, few single-cell studies on plant-microbe interactions have been published, most of which provide high-resolution cell atlases that will become crucial for fully deciphering symbiotic interactions and addressing future questions. In AM symbiosis research, key processes such as the mutual recognition of partners during arbuscule development within cortical cells, or arbuscule senescence and degeneration, remain poorly understood, and these advancements are expected to shed light on these processes and contribute to a deeper understanding of this plant-fungal interaction.

Unraveling plant-microbe symbioses using single-cell and spatial transcriptomics

Plant-microbe symbioses require intense interaction and genetic coordination to successfully establish in specific cell types of the host and symbiont. Traditional RNA-seq methodologies lack the cellular resolution to fully capture these complexities, but single-cell and spatial transcriptomics (ST) are now allowing scientists to probe symbiotic interactions at an unprecedented level of detail. Here, we discuss the advantages that novel spatial and single-cell transcriptomic technologies provide in studying plant-microbe endosymbioses and highlight key recent studies. Finally, we consider the remaining limitations of applying these approaches to symbiosis research, which are mainly related to the simultaneous capture of both plant and microbial transcripts within the same cells.

Getting to the root of root-microbe interactions

Microbial relationships with roots influence many ecosystem functions and nutrient fluxes, including their sometimes-profound effects on plant health and productivity. Fine roots were often classified with a diameter less than 2 mm, but fine roots under that size perform distinct functional roles in the environment. Importantly, two broad functional categories of fine roots are absorptive and transportive, with absorptive fine roots acting as metabolic hotspots for root activity. In two of our recent studies, we have shown that several microbial community characteristics differ between absorptive and transportive fine roots, including composition, abundance, and function, as well as the root metabolome. This highlights a growing recognition within microbial ecology that we must consider fine-scale environmental variability, such as root physiology and morphology, when interpreting microbial patterns. In this commentary, we summarize the findings of our latest article, further speculate on some of these patterns, and suggest future studies for examining decomposition and applying cutting-edge single-cell sequencing techniques.

A practical guide to spatial transcriptomics

Spatial transcriptomics is revolutionizing modern biology, offering researchers an unprecedented ability to unravel intricate gene expression patterns within tissues. From pioneering techniques to newly commercialized platforms, the field of spatial transcriptomics has evolved rapidly, ushering in a new era of understanding across various disciplines, from developmental biology to disease research. This dynamic expansion is reflected in the rapidly growing number of technologies and data analysis techniques developed and introduced. However, the expanding landscape presents a considerable challenge for researchers, especially newcomers to the field, as staying informed about these advancements becomes increasingly complex. To address this challenge, we have prepared an updated review with a particular focus on technologies that have reached commercialization and are, therefore, accessible to a broad spectrum of potential new users. In this review, we present the fundamental principles of spatial transcriptomic methods, discuss the challenges in data analysis, provide insights into experimental considerations, offer information about available resources for spatial transcriptomics, and conclude with a guide for method selection and a forward-looking perspective. Our aim is to serve as a guiding resource for both experienced users and newcomers navigating the complex realm of spatial transcriptomics in this era of rapid development. We intend to equip researchers with the necessary knowledge to make informed decisions and contribute to the cutting-edge research that spatial transcriptomics offers.

Omics approaches in understanding the benefits of plant-microbe interactions

Plant-microbe interactions are pivotal for ecosystem dynamics and sustainable agriculture, and are influenced by various factors, such as host characteristics, environmental conditions, and human activities. Omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, have revolutionized our understanding of these interactions. Genomics elucidates key genes, transcriptomics reveals gene expression dynamics, proteomics identifies essential proteins, and metabolomics profiles small molecules, thereby offering a holistic perspective. This review synthesizes diverse microbial-plant interactions, showcasing the application of omics in understanding mechanisms, such as nitrogen fixation, systemic resistance induction, mycorrhizal association, and pathogen-host interactions. Despite the challenges of data integration and ethical considerations, omics approaches promise advancements in precision intervention and resilient agricultural practices. Future research should address data integration challenges, enhance omics technology resolution, explore epigenomics, and understand plant-microbe dynamics under diverse conditions. In conclusion, omics technologies hold immense promise for optimizing agricultural strategies and fortifying resilient plant-microbe alliances, paving the way for sustainable agriculture and environmental stewardship.

Next-Generation Sequencing-Based Spatial Transcriptomics: A Perspective from Barcoding Chemistry

Gene expression profiling of tissue cells with spatial context is in high demand to reveal cell types, locations, and intercellular or molecular interactions for physiological and pathological studies. With rapid advances in barcoding chemistry and sequencing chemistry, spatially resolved transcriptome (SRT) techniques have emerged to quantify spatial gene expression in tissue samples by correlating transcripts with their spatial locations using diverse strategies. These techniques provide both physical tissue structure and molecular characteristics and are poised to revolutionize many fields, such as developmental biology, neuroscience, oncology, and histopathology. In this context, this Perspective focuses on next-generation sequencing-based SRT methods, particularly highlighting spatial barcoding chemistry. It delves into optically manipulated spatial indexing methods and DNA array-barcoded spatial indexing methods by exploring current advances, challenges, and future development directions in this nascent field.

A Spatial Multi-Modal Dissection of Host-Microbiome Interactions within the Colitis Tissue Microenvironment

The intricate and dynamic interactions between the host immune system and its microbiome constituents undergo dynamic shifts in response to perturbations to the intestinal tissue environment. Our ability to study these events on the systems level is significantly limited by in situ approaches capable of generating simultaneous insights from both host and microbial communities. Here, we introduce Microbiome Cartography (MicroCart), a framework for simultaneous in situ probing of host features and its microbiome across multiple spatial modalities. We demonstrate MicroCart by comprehensively investigating the alterations in both gut host and microbiome components in a murine model of colitis by coupling MicroCart with spatial proteomics, transcriptomics, and glycomics platforms. Our findings reveal a global but systematic transformation in tissue immune responses, encompassing tissue-level remodeling in response to host immune and epithelial cell state perturbations, and bacterial population shifts, localized inflammatory responses, and metabolic process alterations during colitis. MicroCart enables a deep investigation of the intricate interplay between the host tissue and its microbiome with spatial multiomics.

Life at the borderlands: microbiomes of interfaces critical to One Health

Microbiomes are foundational components of the environment that provide essential services relating to food security, carbon sequestration, human health, and the overall well-being of ecosystems. Microbiota exert their effects primarily through complex interactions at interfaces with their plant, animal, and human hosts, as well as within the soil environment. This review aims to explore the ecological, evolutionary, and molecular processes governing the establishment and function of microbiome-host relationships, specifically at interfaces critical to One Health-a transdisciplinary framework that recognizes that the health outcomes of people, animals, plants, and the environment are tightly interconnected. Within the context of One Health, the core principles underpinning microbiome assembly will be discussed in detail, including biofilm formation, microbial recruitment strategies, mechanisms of microbial attachment, community succession, and the effect these processes have on host function and health. Finally, this review will catalogue recent advances in microbiology and microbial ecology methods that can be used to profile microbial interfaces, with particular attention to multi-omic, advanced imaging, and modelling approaches. These technologies are essential for delineating the general and specific principles governing microbiome assembly and functions, mapping microbial interconnectivity across varying spatial and temporal scales, and for the establishment of predictive frameworks that will guide the development of targeted microbiome-interventions to deliver One Health outcomes.

Latex - a potential plant defense against microbes

Laticifers - among the most common defensive reservoirs in plants - are hypothesized to benefit plant fitness by preventing microbes from entering wounds. I argue that while latex seals wounds, and can suppress microbial growth, direct evidence that these processes benefit plant fitness is scarce. I outline a roadmap for filling this knowledge gap.

Integrating single-cell multi-omics and prior biological knowledge for a functional characterization of the immune system

The immune system comprises diverse specialized cell types that cooperate to defend the host against a wide range of pathogenic threats. Recent advancements in single-cell and spatial multi-omics technologies provide rich information about the molecular state of immune cells. Here, we review how the integration of single-cell and spatial multi-omics data with prior knowledge-gathered from decades of detailed biochemical studies-allows us to obtain functional insights, focusing on gene regulatory processes and cell-cell interactions. We present diverse applications in immunology and critically assess underlying assumptions and limitations. Finally, we offer a perspective on the ongoing technological and algorithmic developments that promise to get us closer to a systemic mechanistic understanding of the immune system.