Spatial transcriptomics of planktonic and sessile bacterial populations at single-cell resolution

Pharmacological strategies for targeting biofilms in otorhinolaryngologic infections and overcoming antimicrobial resistance (Review)

Biofilm formation is a key factor in the persistence and recurrence of otorhinolaryngology (ORL) infections, driving antimicrobial resistance and treatment failure. Chronic conditions, such as rhinosinusitis, otitis media and tonsillitis, are linked to biofilm-producing pathogens, forming protective extracellular matrices that shield bacteria from immune defenses and antibiotics. The present review explores emerging pharmacological strategies to disrupt biofilm integrity and improve treatment outcomes. Strategies such as quorum sensing inhibitors, antibiofilm peptides, enzymatic dispersal agents, and drug repurposing can potentially disrupt biofilms and counter-resistance mechanisms. Furthermore, novel therapies (including nanotechnology-based drug delivery systems, phage therapy and immunomodulation) offer innovative alternatives for managing biofilm-associated infections. However, clinical implementation remains challenging. Future research should prioritize optimizing drug formulations, refining delivery techniques, and exploring synergistic combinations to enhance biofilm eradication. Implementing these innovative strategies can improve the management of chronic ORL infections, reducing recurrence rates and enhancing patient outcomes.

Single-cell and spatial omics: exploring hypothalamic heterogeneity

Elucidating the complex dynamic cellular organization in the hypothalamus is critical for understanding its role in coordinating fundamental body functions. Over the past decade, single-cell and spatial omics technologies have significantly evolved, overcoming initial technical challenges in capturing and analyzing individual cells. These high-throughput omics technologies now offer a remarkable opportunity to comprehend the complex spatiotemporal patterns of transcriptional diversity and cell-type characteristics across the entire hypothalamus. Current single-cell and single-nucleus RNA sequencing methods comprehensively quantify gene expression by exploring distinct phenotypes across various subregions of the hypothalamus. However, single-cell/single-nucleus RNA sequencing requires isolating the cell/nuclei from the tissue, potentially resulting in the loss of spatial information concerning neuronal networks. Spatial transcriptomics methods, by bypassing the cell dissociation, can elucidate the intricate spatial organization of neural networks through their imaging and sequencing technologies. In this review, we highlight the applicative value of single-cell and spatial transcriptomics in exploring the complex molecular-genetic diversity of hypothalamic cell types, driven by recent high-throughput achievements.

Pseudomonas syringae subpopulations cooperate by coordinating flagellar and type III secretion spatiotemporal dynamics to facilitate plant infection

Isogenic bacterial populations can display probabilistic cell-to-cell variation in response to challenges. This phenotypic heterogeneity can affect virulence in animals, but its impact on plant pathogens is unknown. Previously, we showed that expression of the type III secretion system (T3SS) of the plant pathogen Pseudomonas syringae displays phenotypic variation in planta. Here we use flow cytometry and microscopy to investigate single-cell flagellar expression in relation to T3SS expression, showing that both systems undergo phenotypic heterogeneity in vitro in apoplast-mimicking medium and within apoplastic microcolonies throughout colonization of Phaseolus vulgaris. Stochastic, spatial and time factors shape the dynamics of a phenotypically diverse pathogen population that displays division of labour during colonization: effectors produced by T3SS-expressing bacteria act as 'common goods' to suppress immunity, allowing motile flagella-expressing bacteria to increase and leave infected tissue before necrosis. These results showcase the mechanisms of bacterial specialization during plant colonization in an environmentally and agriculturally relevant system.

Resolving spatiotemporal dynamics in bacterial multicellular populations: approaches and challenges

SUMMARYThe development of multicellularity represents a key evolutionary transition that is crucial for the emergence of complex life forms. Although multicellularity has traditionally been studied in eukaryotes, it originates in prokaryotes. Coordinated aggregation of individual cells within the confines of a colony results in emerging, higher-level functions that benefit the population as a whole. During colony differentiation, an almost infinite number of ecological and physiological population-forming forces are at work, creating complex, intricate colony structures with divergent functions. Understanding the assembly and dynamics of such populations requires resolving individual cells or cell groups within such macroscopic structures. Addressing how each cell contributes to the collective action requires pushing the resolution boundaries of key technologies that will be presented in this review. In particular, single-cell techniques provide powerful tools for studying bacterial multicellularity with unprecedented spatial and temporal resolution. These advancements include novel microscopic techniques, mass spectrometry imaging, flow cytometry, spatial transcriptomics, single-bacteria RNA sequencing, and the integration of spatiotemporal transcriptomics with microscopy, alongside advanced microfluidic cultivation systems. This review encourages exploring the synergistic potential of the new technologies in the study of bacterial multicellularity, with a particular focus on individuals in differentiated bacterial biofilms (colonies). It highlights how resolving population structures at the single-cell level and understanding their respective functions can elucidate the overarching functions of bacterial multicellular populations.

High-throughput single-microbe RNA sequencing reveals adaptive state heterogeneity and host-phage activity associations in human gut microbiome

Microbial communities such as those residing in the human gut are highly diverse and complex, and many with important implications for health and diseases. The effects and functions of these microbial communities are determined not only by their species compositions and diversities but also by the dynamic intra- and inter-cellular states at the transcriptional level. Powerful and scalable technologies capable of acquiring single-microbe-resolution RNA sequencing information in order to achieve a comprehensive understanding of complex microbial communities together with their hosts are therefore utterly needed. Here we report the development and utilization of a droplet-based smRNA-seq (single-microbe RNA sequencing) method capable of identifying large species varieties in human samples, which we name smRandom-seq2. Together with a triple-module computational pipeline designed for the bacteria and bacteriophage sequencing data by smRandom-seq2 in four human gut samples, we established a single-cell level bacterial transcriptional landscape of human gut microbiome, which included 29,742 single microbes and 329 unique species. Distinct adaptive response states among species in Prevotella and Roseburia genera and intrinsic adaptive strategy heterogeneity in Phascolarctobacterium succinatutens were uncovered. Additionally, we identified hundreds of novel host-phage transcriptional activity associations in the human gut microbiome. Our results indicated that smRandom-seq2 is a high-throughput and high-resolution smRNA-seq technique that is highly adaptable to complex microbial communities in real-world situations and promises new perspectives in the understanding of human microbiomes.

Uncovering dynamic transcriptional regulation of methanogenesis via single-cell imaging of archaeal gene expression

Archaeal methanogenesis is a dynamic process regulated by various cellular and environmental signals. However, understanding this regulation is technically challenging due to the difficulty of measuring gene expression dynamics in individual archaeal cells. Here, we develop a multi-round hybridization chain reaction (HCR)-assisted single-molecule fluorescence in situ hybridization (FISH) method to quantify the transcriptional dynamics of 12 genes involved in methanogenesis in individual cells of Methanococcoides orientis. Under optimal growth condition, most of these genes appear to be expressed in a temporal order matching metabolic reaction order. Interestingly, an important environmental factor, Fe(III), stimulates cellular methane production without upregulating methanogenic gene expression, likely through a Fenton-reaction-triggered mechanism. Through single-cell clustering and kinetic analyses, we associate these gene expression patterns to a dynamic mixture of distinct cellular states, potentially regulated by a set of shared factors. Our work provides a quantitative framework for uncovering the mechanisms of metabolic regulation in archaea.

Chemical dissection of bacterial virulence

The emergence of antibiotic-resistant bacteria has intensified the need for novel therapeutic strategies targeting bacterial virulence rather than growth or survival. Bacterial virulence involves complex processes that enable pathogens to invade and survive within host cells. Chemical biology has become a powerful tool for dissecting these virulence mechanisms at the molecular level. This review highlights key chemical biology approaches for studying bacterial virulence, focusing on four areas: 1) regulation of virulence, where chemoproteomics has identified small molecule-protein interactions that modulate virulence gene expression; 2) identification of virulence proteins, using techniques like unnatural amino acid incorporation and activity-based protein profiling (ABPP) to uncover proteins involved in infection; 3) post-translational modifications of host proteins, where chemical probes have revealed how bacterial effectors alter host cell processes; and 4) effector-host protein interactions, with methods such as bifunctional unnatural amino acid incorporation facilitating the discovery of key host targets manipulated by bacterial effectors. Collectively, these chemical tools are providing new insights into pathogen-host interactions, offering potential therapeutic avenues that aim to disarm pathogens and combat antibiotic resistance.

Morphogenesis of confined biofilms: how mechanical interactions determine cellular patterning and global geometry

Biofilms are surface-attached bacterial communities encased within extracellular matrices that play significant roles in health and society and serve as prototypical examples of proliferating active nematics. Recent advances in fluorescence microscopy have facilitated an unprecedented view of biofilm development at the single-cell level, thus providing the opportunity to develop a mechanistic understanding of how biofilm development is influenced by mechanical interactions with the environment. Here, we review recent studies that examined the morphogenesis of Vibrio cholerae biofilms under confinement at both single-cell and continuum levels. We describe how biofilms under different confinement modes-embedded and interstitial-can acquire various global geometries and forms of cell orientational ordering different from those in unconfined biofilms, and we demonstrate how these properties arise from the mechanical interplay between the biofilm and its confining medium. We also discuss how this interplay is fundamentally governed by the extracellular matrix, which facilitates the transmission of mechanical stress from the medium into the biofilm via adhesion and friction, and serves as the key feature that distinguishes biofilms from classical bacterial colonies. These studies lay the groundwork for many potential future directions, all of which will contribute to the establishment of a new "developmental biology" of biofilms.

The 2025 motile active matter roadmap

Activity and autonomous motion are fundamental aspects of many living and engineering systems. Here, the scale of biological agents covers a wide range, from nanomotors, cytoskeleton, and cells, to insects, fish, birds, and people. Inspired by biological active systems, various types of autonomous synthetic nano- and micromachines have been designed, which provide the basis for multifunctional, highly responsive, intelligent active materials. A major challenge for understanding and designing active matter is their inherent non-equilibrium nature due to persistent energy consumption, which invalidates equilibrium concepts such as free energy, detailed balance, and time-reversal symmetry. Furthermore, interactions in ensembles of active agents are often non-additive and non-reciprocal. An important aspect of biological agents is their ability to sense the environment, process this information, and adjust their motion accordingly. It is an important goal for the engineering of micro-robotic systems to achieve similar functionality. Many fundamental properties of motile active matter are by now reasonably well understood and under control. Thus, the ground is now prepared for the study of physical aspects and mechanisms of motion in complex environments, the behavior of systems with new physical features like chirality, the development of novel micromachines and microbots, the emergent collective behavior and swarming of intelligent self-propelled particles, and particular features of microbial systems. The vast complexity of phenomena and mechanisms involved in the self-organization and dynamics of motile active matter poses major challenges, which can only be addressed by a truly interdisciplinary effort involving scientists from biology, chemistry, ecology, engineering, mathematics, and physics. The 2025 motile active matter roadmap of Journal of Physics: Condensed Matter reviews the current state of the art of the field and provides guidance for further progress in this fascinating research area.

CellSAM: A Foundation Model for Cell Segmentation

Cells are a fundamental unit of biological organization, and identifying them in imaging data - cell segmentation - is a critical task for various cellular imaging experiments. While deep learning methods have led to substantial progress on this problem, most models are specialist models that work well for specific domains but cannot be applied across domains or scale well with large amounts of data. In this work, we present CellSAM, a universal model for cell segmentation that generalizes across diverse cellular imaging data. CellSAM builds on top of the Segment Anything Model (SAM) by developing a prompt engineering approach for mask generation. We train an object detector, CellFinder, to automatically detect cells and prompt SAM to generate segmentations. We show that this approach allows a single model to achieve human-level performance for segmenting images of mammalian cells, yeast, and bacteria collected across various imaging modalities. We show that CellSAM has strong zero-shot performance and can be improved with a few examples via few-shot learning. Additionally, we demonstrate how CellSAM can be applied across diverse bioimage analysis workflows. A deployed version of CellSAM is available at https://cellsam.deepcell.org/.

Building Spatiotemporal Understanding of Mycobacterium tuberculosis-Host Interactions

Heterogeneity during Mycobacterium tuberculosis (Mtb) infection greatly impacts disease outcome and complicates treatment. This heterogeneity encompasses many facets, spanning local differences in the host immune response to Mtb and the environment experienced by the bacterium, to nonuniformity in Mtb replication state. All of these facets are interlinked and each can affect Mtb susceptibility to antibiotic treatment. In-depth spatiotemporal understanding of Mtb-host interactions is thus critical to both fundamental comprehension of Mtb infection biology and for the development of effective therapeutic regimens. Such spatiotemporal understanding dictates the need for analysis at the single bacterium/cell level in the context of intact tissue architecture, which has been a significant technical challenge. Excitingly, innovations in spatial single cell methodology have opened the door to such studies, beginning to illuminate aspects ranging from intergranuloma differences in cellular composition and phenotype, to sublocation differences in Mtb physiology and replication state. In this perspective, we discuss recent studies that demonstrate the potential of these methodological advancements to reveal critical spatiotemporal insight into Mtb-host interactions, and highlight future avenues of research made possible by these advances.

Spatial propagation of temperate phages within and among biofilms

Bacteria form groups composed of cells and a secreted polymeric matrix that controls their spatial organization. These groups-termed biofilms-can act as refuges from environmental disturbances and from biotic threats, including phages. Despite the ubiquity of temperate phages and bacterial biofilms, live propagation of temperate phages within biofilms has not been characterized on cellular spatial scales. Here, we leverage several approaches to track temperate phages and distinguish between lytic and lysogenic host infections. We determine that lysogeny within Escherichia coli biofilms initially occurs within a predictable region of cell group packing architecture on the biofilm periphery. Because lysogens are generally found on the periphery of large cell groups, where lytic viral infections also reduce local biofilm structural integrity, lysogens are predisposed to disperse into the passing liquid and are overrepresented in downstream biofilms formed from the dispersal pool of the original biofilm-phage system. Comparing our results with those for virulent phages reveals that temperate phages have unique advantages in propagating over long spatial and time scales within and among bacterial biofilms.

Highly multiplexed spatial transcriptomics in bacteria

Single-cell decisions made in complex environments underlie many bacterial phenomena. Image-based transcriptomics approaches offer an avenue to study such behaviors, yet these approaches have been hindered by the massive density of bacterial messenger RNA. To overcome this challenge, we combined 1000-fold volumetric expansion with multiplexed error-robust fluorescence in situ hybridization (MERFISH) to create bacterial-MERFISH. This method enables high-throughput, spatially resolved profiling of thousands of operons within individual bacteria. Using bacterial-MERFISH, we dissected the response of Escherichia coli to carbon starvation, systematically mapped subcellular RNA organization, and charted the adaptation of a gut commensal Bacteroides thetaiotaomicron to micrometer-scale niches in the mammalian colon. We envision that bacterial-MERFISH will be broadly applicable to the study of bacterial single-cell heterogeneity in diverse, spatially structured, and native environments.

Dual RNA sequencing of a co-culture model of Pseudomonas aeruginosa and human 2D upper airway organoids

Pseudomonas aeruginosa is a Gram-negative bacterium that is notorious for airway infections in cystic fibrosis (CF) subjects. Bacterial quorum sensing (QS) coordinates virulence factor expression and biofilm formation at population level. Better understanding of QS in the bacterium-host interaction is required. Here, we set up a new P. aeruginosa infection model, using 2D upper airway nasal organoids that were derived from 3D organoids. Using dual RNA-sequencing, we dissected the interaction between organoid epithelial cells and WT or QS-mutant P. aeruginosa strains. Since only a single healthy individual and a single CF subject were used as donors for the organoids, conclusions about CF-specific effects could not be deduced. However, P. aeruginosa induced epithelial inflammation, whereas QS signaling did not affect the epithelial airway cells. Conversely, the epithelium influenced infection-related processes of P. aeruginosa, including QS-mediated regulation. Comparison of our model with samples from the airways of CF subjects indicated that our model recapitulates important aspects of infection in vivo. Hence, the 2D airway organoid infection model is relevant and may help to reduce the future burden of P. aeruginosa infections in CF.

Cell-scale gene-expression measurements in Vibrio cholerae biofilms reveal spatiotemporal patterns underlying development

Bacteria commonly exist in multicellular, surface-attached communities called biofilms. Biofilms are central to ecology, medicine, and industry. The Vibrio cholerae pathogen forms biofilms from single founder cells that, via cell division, mature into three-dimensional structures with distinct, yet reproducible, regional architectures. To define mechanisms underlying biofilm developmental transitions, we establish a single-molecule fluorescence in situ hybridization (smFISH) approach that enables accurate quantitation of spatiotemporal gene-expression patterns in biofilms at cell-scale resolution. smFISH analyses of V. cholerae biofilm regulatory and structural genes demonstrate that, as biofilms mature, overall matrix gene expression decreases, and simultaneously, a pattern emerges in which matrix gene expression becomes largely confined to peripheral biofilm cells. Both quorum sensing and c-di-GMP-signaling are required to generate the proper temporal pattern of matrix gene expression. Quorum sensing autoinducer levels are uniform across the biofilm, and thus, c-di-GMP-signaling alone sets the regional matrix gene expression pattern. The smFISH strategy provides insight into mechanisms conferring particular fates to individual biofilm cells.

Environmental community transcriptomics: strategies and struggles

Transcriptomics is the study of RNA transcripts, the portion of the genome that is transcribed, in a specific cell, tissue, or organism. Transcriptomics provides insight into gene expression patterns, regulation, and the underlying mechanisms of cellular processes. Community transcriptomics takes this a step further by studying the RNA transcripts from environmental assemblies of organisms, with the intention of better understanding the interactions between members of the community. Community transcriptomics requires successful extraction of RNA from a diverse set of organisms and subsequent analysis via mapping those reads to a reference genome or de novo assembly of the reads. Both, extraction protocols and the analysis steps can pose hurdles for community transcriptomics. This review covers advances in transcriptomic techniques and assesses the viability of applying them to community transcriptomics.

Chloramphenicol-mobilized Bacillus subtilis transiently expresses resistance to multiple antibiotics, including the glycopeptides phleomycin and bleomycin

Antibiotic resistance is a global crisis that stems from the use of antibiotics as an essential part of modern medicine. Understanding how antibiotic resistance is controlled among cells in bacterial populations will provide insights into how antibiotics shape microbial communities. Here, we describe patterns of B. subtilis gene expression that arise from growth on a surface either in isolation or under subinhibitory chloramphenicol exposure. We identified elevated expression of genes encoding five different antibiotic resistance functions. The expression of four of the five resistance functions is controlled by a combination of terminator attenuation and transcriptional regulation. Two of these, vmlR and tlrB provide resistance to lincosamides and tylosin, respectively. We found that bmrCD promotes resistance to glycopeptides, including phleomycin and bleomycin. Promoter fusions to luciferase were used to follow expression of bmrCD, vmlR, and tlrB. Subinhibitory chloramphenicol exposure induces sliding motility of B. subtilis, wherein the three antibiotic resistance functions are expressed heterogeneously in spatiotemporally segregated pattern. We found that their expression is transiently elevated even in the absence of antibiotic exposure. The data suggest that for some antibiotics, intrinsic resistance genes are entrained to changes in growth and metabolism. Antibiotic exposure amplifies their expression, potentially providing a subpopulation of cells elevated protection to multiple classes of antibiotic.

Advances and applications in single-cell and spatial genomics

The applications of single-cell and spatial technologies in recent times have revolutionized the present understanding of cellular states and the cellular heterogeneity inherent in complex biological systems. These advancements offer unprecedented resolution in the examination of the functional genomics of individual cells and their spatial context within tissues. In this review, we have comprehensively discussed the historical development and recent progress in the field of single-cell and spatial genomics. We have reviewed the breakthroughs in single-cell multi-omics technologies, spatial genomics methods, and the computational strategies employed toward the analyses of single-cell atlas data. Furthermore, we have highlighted the advances made in constructing cellular atlases and their clinical applications, particularly in the context of disease. Finally, we have discussed the emerging trends, challenges, and opportunities in this rapidly evolving field.

Biofilms as more than the sum of their parts: lessons from developmental biology

Although our understanding of both bacterial cell physiology and the complex behaviors exhibited by bacterial biofilms is expanding rapidly, we cannot yet sum the behaviors of individual cells to understand or predict biofilm behavior. This is both because cell physiology in biofilms is different from planktonic growth and because cell behavior in biofilms is spatiotemporally patterned. We use developmental biology as a guide to examine this phenotypic patterning, discussing candidate cues that may encode spatiotemporal information and possible roles for phenotypic patterning in biofilms. We consider other questions that arise from the comparison between biofilm and eukaryotic development, including what defines normal biofilm development and the nature of biofilm cell types and fates. We conclude by discussing what biofilm development can tell us about developmental processes, emphasizing the additional challenges faced by bacteria in biofilm development compared with their eukaryotic counterparts.

Sequencing-based analysis of microbiomes

Microbiomes occupy a range of niches and, in addition to having diverse compositions, they have varied functional roles that have an impact on agriculture, environmental sciences, and human health and disease. The study of microbiomes has been facilitated by recent technological and analytical advances, such as cheaper and higher-throughput DNA and RNA sequencing, improved long-read sequencing and innovative computational analysis methods. These advances are providing a deeper understanding of microbiomes at the genomic, transcriptional and translational level, generating insights into their function and composition at resolutions beyond the species level.

Bioenergetic suppression by redox-active metabolites promotes antibiotic tolerance in Pseudomonas aeruginosa

The proton-motive force (PMF), consisting of a pH gradient and a membrane potential (ΔΨ) underpins many processes essential to bacterial growth and/or survival. Yet bacteria often enter a bioenergetically diminished state characterized by a low PMF. Consequently, they have increased tolerance for diverse stressors, including clinical antibiotics. Despite the ubiquity of low metabolic rates in the environment, the extent to which bacteria have agency over entry into such a low-bioenergetic state has received relatively little attention. Here, we tested the hypothesis that production of redox-active metabolites (RAMs) could drive such a physiological transition. Pseudomonas aeruginosa is an opportunistic pathogen that produces phenazines, model RAMs that are highly toxic in the presence of molecular oxygen (O2). Under oxic conditions, the phenazines pyocyanin and phenazine-1-carboximide, as well as toxoflavin-a RAM produced by Burkholderia species-suppress the ΔΨ in distinct ways across distributions of single cells, reduce the efficiency of proton pumping, and lower cellular adenosine-triphosphate (ATP) levels. In planktonic culture, the degree and rate by which each RAM lowers the ΔΨ correlates with the protection it confers against antibiotics that strongly impact cellular energy flux. This bioenergetic suppression requires the RAM's presence and corresponds to its cellular reduction rate and abiotic oxidation rate by O2; it can be reversed by increasing the ΔΨ with nigericin. RAMs similarly impact the bioenergetic state of cells in (hyp)oxic biofilm aggregates. Collectively, these findings demonstrate that bacteria can suppress their bioenergetic state by the production of endogenous toxins in a manner that bolsters stress resilience.

Community standards and future opportunities for synthetic communities in plant-microbiota research

Harnessing beneficial microorganisms is seen as a promising approach to enhance sustainable agriculture production. Synthetic communities (SynComs) are increasingly being used to study relevant microbial activities and interactions with the plant host. Yet, the lack of community standards limits the efficiency and progress in this important area of research. To address this gap, we recommend three actions: (1) defining reference SynComs; (2) establishing community standards, protocols and benchmark data for constructing and using SynComs; and (3) creating an infrastructure for sharing strains and data. We also outline opportunities to develop SynCom research through technical advances, linking to field studies, and filling taxonomic blind spots to move towards fully representative SynComs.

Artificial intelligence with mass spectrometry-based multimodal molecular profiling methods for advancing therapeutic discovery of infectious diseases

Infectious diseases, driven by a diverse array of pathogens, can swiftly undermine public health systems. Accurate diagnosis and treatment of infectious diseases-centered around the identification of biomarkers and the elucidation of disease mechanisms-are in dire need of more versatile and practical analytical approaches. Mass spectrometry (MS)-based molecular profiling methods can deliver a wealth of information on a range of functional molecules, including nucleic acids, proteins, and metabolites. While MS-driven omics analyses can yield vast datasets, the sheer complexity and multi-dimensionality of MS data can significantly hinder the identification and characterization of functional molecules within specific biological processes and events. Artificial intelligence (AI) emerges as a potent complementary tool that can substantially enhance the processing and interpretation of MS data. AI applications in this context lead to the reduction of spurious signals, the improvement of precision, the creation of standardized analytical frameworks, and the increase of data integration efficiency. This critical review emphasizes the pivotal roles of MS based omics strategies in the discovery of biomarkers and the clarification of infectious diseases. Additionally, the review underscores the transformative ability of AI techniques to enhance the utility of MS-based molecular profiling in the field of infectious diseases by refining the quality and practicality of data produced from omics analyses. In conclusion, we advocate for a forward-looking strategy that integrates AI with MS-based molecular profiling. This integration aims to transform the analytical landscape and the performance of biological molecule characterization, potentially down to the single-cell level. Such advancements are anticipated to propel the development of AI-driven predictive models, thus improving the monitoring of diagnostics and therapeutic discovery for the ongoing challenge related to infectious diseases.

Real-time high-resolution microscopy reveals how single-cell lysis shapes biofilm matrix morphogenesis

During development, multiscale patterning requires that cells organize their behavior in space and time. Bacteria in biofilms must similarly dynamically pattern their behavior with a simpler toolkit. Like in eukaryotes, morphogenesis of the extracellular matrix is essential for biofilm development, but how it is patterned has remained unclear. Here, we explain how the architecture of eDNA, a key matrix component, is controlled by single cell lysis events during Pseudomonas aeruginosa biofilm development. We extend single-cell imaging methods to capture complete biofilm development, characterizing the stages of biofilm development and visualizing eDNA matrix morphogenesis. Mapping the spatiotemporal distribution of single cell lysis events reveals that cell lysis is restricted to a specific biofilm zone. Simulations indicate that this patterning couples cell lysis to growth, more uniformly distributing eDNA throughout the biofilm. Finally, we find that patterning of cell lysis is organized by nutrient gradients that act as positioning cues.

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.

Specialized Listeria monocytogenes produce tailocins to provide a population-level competitive growth advantage

Tailocins are phage tail-like bacteriocins produced by various bacterial species to kill kin competitors. Given that tailocin release is dependent upon cell lysis, regulation of tailocin production at the single-cell and population level remains unclear. Here we used flow cytometry, competition assays and structural characterization of tailocin production in a human bacterial pathogen, Listeria monocytogenes. We revealed that a specialized subpopulation, constituting less than 1% of the total bacterial population, differentiates to produce, assemble and store thousands of tailocin particles. Tailocins are packed in a highly ordered manner, clustered in a liquid crystalline phase that occupies a substantial volume of the cell. Tailocin production confers a competitive growth advantage for the rest of the population. This study provides molecular insights into tailocin production as a form of altruism, showing how cell specialization within bacterial populations can confer competitive advantages at the population level.

ProBac-seq, a bacterial single-cell RNA sequencing methodology using droplet microfluidics and large oligonucleotide probe sets

Methods that measure the transcriptomic state of thousands of individual cells have transformed our understanding of cellular heterogeneity in eukaryotic cells since their introduction in the past decade. While simple and accessible protocols and commercial products are now available for the processing of mammalian cells, these existing technologies are incompatible with use in bacterial samples for several fundamental reasons including the absence of polyadenylation on bacterial messenger RNA, the instability of bacterial transcripts and the incompatibility of bacterial cell morphology with existing methodologies. Recently, we developed ProBac sequencing (ProBac-seq), a method that overcomes these technical difficulties and provides high-quality single-cell gene expression data from thousands of bacterial cells by using messenger RNA-specific probes. Here we provide details for designing large oligonucleotide probe sets for an organism of choice, amplifying probe sets to produce sufficient quantities for repeated experiments, adding unique molecular indexes and poly-A tails to produce finalized probes, in situ probe hybridization and single-cell encapsulation and library preparation. This protocol, from the probe amplification to the library preparation, requires ~7 d to complete. ProBac-seq offers several advantages over other methods by capturing only the desired target sequences and avoiding nondesired transcripts, such as highly abundant ribosomal RNA, thus enriching for signal that better informs on cellular state. The use of multiple probes per gene can detect meaningful single-cell signals from cells expressing transcripts to a lesser degree or those grown in minimal media and other environmentally relevant conditions in which cells are less active. ProBac-seq is also compatible with other organisms that can be profiled by in situ hybridization techniques.

High-throughput single-cell transcriptomics of bacteria using combinatorial barcoding

Microbial split-pool ligation transcriptomics (microSPLiT) is a high-throughput single-cell RNA sequencing method for bacteria. With four combinatorial barcoding rounds, microSPLiT can profile transcriptional states in hundreds of thousands of Gram-negative and Gram-positive bacteria in a single experiment without specialized equipment. As bacterial samples are fixed and permeabilized before barcoding, they can be collected and stored ahead of time. During the first barcoding round, the fixed and permeabilized bacteria are distributed into a 96-well plate, where their transcripts are reverse transcribed into cDNA and labeled with the first well-specific barcode inside the cells. The cells are mixed and redistributed two more times into new 96-well plates, where the second and third barcodes are appended to the cDNA via in-cell ligation reactions. Finally, the cells are mixed and divided into aliquot sub-libraries, which can be stored until future use or prepared for sequencing with the addition of a fourth barcode. It takes 4 days to generate sequencing-ready libraries, including 1 day for collection and overnight fixation of samples. The standard plate setup enables single-cell transcriptional profiling of up to 1 million bacterial cells and up to 96 samples in a single barcoding experiment, with the possibility of expansion by adding barcoding rounds. The protocol requires experience in basic molecular biology techniques, handling of bacterial samples and preparation of DNA libraries for next-generation sequencing. It can be performed by experienced undergraduate or graduate students. Data analysis requires access to computing resources, familiarity with Unix command line and basic experience with Python or R.

Modern microbiology: Embracing complexity through integration across scales

Microbes were the only form of life on Earth for most of its history, and they still account for the vast majority of life's diversity. They convert rocks to soil, produce much of the oxygen we breathe, remediate our sewage, and sustain agriculture. Microbes are vital to planetary health as they maintain biogeochemical cycles that produce and consume major greenhouse gases and support large food webs. Modern microbiologists analyze nucleic acids, proteins, and metabolites; leverage sophisticated genetic tools, software, and bioinformatic algorithms; and process and integrate complex and heterogeneous datasets so that microbial systems may be harnessed to address contemporary challenges in health, the environment, and basic science. Here, we consider an inevitably incomplete list of emergent themes in our discipline and highlight those that we recognize as the archetypes of its modern era that aim to address the most pressing problems of the 21st century.

Yersinia pseudotuberculosis growth arrest during type-III secretion system expression is associated with altered ribosomal protein expression and decreased gentamicin susceptibility

It has been long appreciated that expression of the Yersinia type-III secretion system (T3SS) in culture is associated with growth arrest. Here we sought to understand whether this impacts expression of ribosomal protein genes, which were among the most highly abundant transcripts in exponential phase Yersinia pseudotuberculosis based on RNA-seq analysis. To visualize changes in ribosomal protein expression, we generated a fluorescent transcriptional reporter with the promoter upstream of rpsJ/S10 fused to a destabilized gfp variant. We confirmed reporter expression significantly increases in exponential phase and decreases as cells transition to stationary phase. We then utilized a mouse model of systemic Y. pseudotuberculosis infection to compare T3SS and S10 reporter expression during clustered bacterial growth in the spleen, and found that cells expressing high levels of the T3SS had decreased S10 levels, while cells with lower T3SS expression retained higher S10 expression. In bacteriological media, growth inhibition with T3SS induction and a reduction in S10 expression were observed in subsets of cells, while cells with high expression of both T3SS and S10 were also observed. Loss of T3SS genes resulted in rescued growth and heightened S10 expression. To understand if clustered growth impacted bacterial gene expression, we utilized droplet-based microfluidics to encapsulate bacteria in spherical agarose droplets, and also observed growth inhibition with high expression of T3SS and reduced S10 levels that better mirrored phenotypes observed in the mouse spleen. Finally, we show that T3SS expression is sufficient to promote tolerance to the ribosome-targeting antibiotic, gentamicin. Collectively, these data indicate that the growth arrest associated with T3SS induction leads to decreased expression of ribosomal protein genes, and this results in reduced antibiotic susceptibility.

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.

Spatial metatranscriptomics resolves host-bacteria-fungi interactomes

The interactions of microorganisms among themselves and with their multicellular host take place at the microscale, forming complex networks and spatial patterns. Existing technology does not allow the simultaneous investigation of spatial interactions between a host and the multitude of its colonizing microorganisms, which limits our understanding of host-microorganism interactions within a plant or animal tissue. Here we present spatial metatranscriptomics (SmT), a sequencing-based approach that leverages 16S/18S/ITS/poly-d(T) multimodal arrays for simultaneous host transcriptome- and microbiome-wide characterization of tissues at 55-µm resolution. We showcase SmT in outdoor-grown Arabidopsis thaliana leaves as a model system, and find tissue-scale bacterial and fungal hotspots. By network analysis, we study inter- and intrakingdom spatial interactions among microorganisms, as well as the host response to microbial hotspots. SmT provides an approach for answering fundamental questions on host-microbiome interplay.

Hosts manipulate lifestyle switch and pathogenicity heterogeneity of opportunistic pathogens in the single-cell resolution

Host-microbe interactions are virtually bidirectional, but how the host affects their microbiome is poorly understood. Here, we report that the host is a critical modulator to regulate the lifestyle switch and pathogenicity heterogeneity of the opportunistic pathogens Serratia marcescens utilizing the Drosophila and bacterium model system. First, we find that Drosophila larvae efficiently outcompete S. marcescens and typically drive a bacterial switch from pathogenicity to commensalism toward the fly. Furthermore, Drosophila larvae reshape the transcriptomic and metabolic profiles of S. marcescens characterized by a lifestyle switch. More importantly, the host alters pathogenicity and heterogeneity of S. marcescens in the single-cell resolution. Finally, we find that larvae-derived AMPs are required to recapitulate the response of S. marcescens to larvae. Altogether, our findings provide an insight into the pivotal roles of the host in harnessing the life history and heterogeneity of symbiotic bacterial cells, advancing knowledge of the reciprocal relationships between the host and pathogen.

The wound microbiota: microbial mechanisms of impaired wound healing and infection

The skin barrier protects the human body from invasion by exogenous and pathogenic microorganisms. A breach in this barrier exposes the underlying tissue to microbial contamination, which can lead to infection, delayed healing, and further loss of tissue and organ integrity. Delayed wound healing and chronic wounds are associated with comorbidities, including diabetes, advanced age, immunosuppression and autoimmune disease. The wound microbiota can influence each stage of the multi-factorial repair process and influence the likelihood of an infection. Pathogens that commonly infect wounds, such as Staphylococcus aureus and Pseudomonas aeruginosa, express specialized virulence factors that facilitate adherence and invasion. Biofilm formation and other polymicrobial interactions contribute to host immunity evasion and resistance to antimicrobial therapies. Anaerobic organisms, fungal and viral pathogens, and emerging drug-resistant microorganisms present unique challenges for diagnosis and therapy. In this Review, we explore the current understanding of how microorganisms present in wounds impact the process of skin repair and lead to infection through their actions on the host and the other microbial wound inhabitants.

Perspectives on the future of host-microbe biology from the Council on Microbial Sciences of the American Society for Microbiology

Host-microbe biology (HMB) stands on the cusp of redefinition, challenging conventional paradigms to instead embrace a more holistic understanding of the microbial sciences. The American Society for Microbiology (ASM) Council on Microbial Sciences hosted a virtual retreat in 2023 to identify the future of the HMB field and innovations needed to advance the microbial sciences. The retreat presentations and discussions collectively emphasized the interconnectedness of microbes and their profound influence on humans, animals, and environmental health, as well as the need to broaden perspectives to fully embrace the complexity of these interactions. To advance HMB research, microbial scientists would benefit from enhancing interdisciplinary and transdisciplinary research to utilize expertise in diverse fields, integrate different disciplines, and promote equity and accessibility within HMB. Data integration will be pivotal in shaping the future of HMB research by bringing together varied scientific perspectives, new and innovative techniques, and 'omics approaches. ASM can empower under-resourced groups with the goal of ensuring that the benefits of cutting-edge research reach every corner of the scientific community. Thus, ASM will be poised to steer HMB toward a future that champions inclusivity, innovation, and accessible scientific progress.

Transcriptome analysis: a powerful tool to understand individual microbial behaviors and interactions in ecosystems

Transcriptome analysis is a powerful tool for studying microbial ecology, especially individual microbial functions in an ecosystem and their interactions. With the development of high-throughput sequencing technology, great progress has been made in analytical methods for microbial communities in natural environments. 16S rRNA gene amplicon sequencing (ie microbial community structure analysis) and shotgun metagenome analysis have been widely used to determine the composition and potential metabolic capability of microorganisms in target environments without requiring culture. However, even if the types of microorganisms present and their genes are known, it is difficult to determine what they are doing in an ecosystem. Gene expression analysis (transcriptome analysis; RNA-seq) is a powerful tool to address these issues. The history and basic information of gene expression analysis, as well as examples of studies using this method to analyze microbial ecosystems, are presented.

Deciphering the Temporal-Spatial Interactive Heterogeneity of Long Non-Coding RNAs and RNA-Binding Proteins in Living Cells at Single-Cell Resolution

The investigation of long noncoding RNAs (lncRNAs) and RNA binding proteins (RBPs) interactions in living cell holds great significance for elucidating their critical roles in a variety of biological activities, but limited techniques are available to profile the temporal-spatial dynamic heterogeneity. Here, we introduced a molecular beacon-functionalized nanoneedle array designed for spatially resolved profiling of lncRNA-RBP interactions (Nano-SpatiaLR). A nanoneedle array modified with a molecular beacon is employed to selectively isolate specific intracellular lncRNAs and their associated RBPs without affecting cell viability. The RBPs are then in situ analyzed with a fluorescent labeled antibody and colocalized with lncRNA signals to get a quantitative measurement of their dynamic interactions. Additionally, leveraging the spatial distribution and nanoscale modality of the nanoneedle array, this technique provides the spatial heterogeneity information on cellular lncRNA-RBPs interaction at single cell resolution. In this study, we tracked the temporal-spatial interactive heterogeneity dynamics of lncRNA-RBPs interaction within living cells across different biological progresses. Our findings demonstrated that the interactions between lncRNA HOTAIR and RBPs EZH2 and LSD1 undergo significant changes in response to drug treatments, particularly in tumor cells. Moreover, these interactions become more intensified as tumor cells aggregate during the proliferation process.

Spatial recovery of the murine gut microbiota after antibiotics perturbation

Bacterial communities are highly complex, with interaction networks dictating ecosystem function. Bacterial interactions are constrained by the spatial organization of these microbial communities, yet studying the spatial organization of microbial communities at the single-cell level has been technically challenging. Here, we use the recently developed high-phylogenetic-resolution microbiota mapping by fluorescence in situ hybridization technology to image the gut microbiota at the species and single-cell level. We simultaneously image 63 different bacterial species to spatially characterize the perturbation and recovery of the gut microbiota to ampicillin and vancomycin in the cecum and distal colon of mice. To decipher the biology in this complex imaging data, we developed an analytical framework to characterize the spatial changes of the gut microbiota to a perturbation. The three-tiered analytical approach includes image-level diversity, pairwise colocalization analysis, and hypothesis-driven neighborhood analysis. Through this workflow, we identify biogeographic and antibiotic-based differences in the spatial organization of the gut microbiota. We demonstrate that the cecal microbiota has increased micrometer-scale diversity than the colon at baseline and recovers better from perturbation. Also, we identify potential foundation and keystone species that have high baseline neighborhood richness and that are associated with recovery from antibiotics. Through this workflow, we add a spatial layer to the characterization of bacterial communities and progress toward a better understanding of bacterial interactions leading to improved microbiome modulation strategies.

IMPORTANCE

Antibiotics have broad off-target effects on the gut microbiome. When the microbial community is unable to recover from antibiotics, it can lead to increased susceptibility to gastrointestinal infections and increased risk of immunological and metabolic diseases. In this study, we work to better understand how the gut microbiota recovers from antibiotics by employing a recent technology to image the entire bacterial community at once. Through this approach, we characterize the spatial changes in the gut microbiota after treatment with model antibiotics in both the cecum and colon of mice. We find antibiotic- and biogeographic-dependent spatial changes between bacterial species and that many of these spatial colocalizations do not recover to baseline levels even 35 days after antibiotic administration.

Single-cell RNA sequencing reveals plasmid constrains bacterial population heterogeneity and identifies a non-conjugating subpopulation

Transcriptional heterogeneity in isogenic bacterial populations can play various roles in bacterial evolution, but its detection remains technically challenging. Here, we use microbial split-pool ligation transcriptomics to study the relationship between bacterial subpopulation formation and plasmid-host interactions at the single-cell level. We find that single-cell transcript abundances are influenced by bacterial growth state and plasmid carriage. Moreover, plasmid carriage constrains the formation of bacterial subpopulations. Plasmid genes, including those with core functions such as replication and maintenance, exhibit transcriptional heterogeneity associated with cell activity. Notably, we identify a cell subpopulation that does not transcribe conjugal plasmid transfer genes, which may help reduce plasmid burden on a subset of cells. Our study advances the understanding of plasmid-mediated subpopulation dynamics and provides insights into the plasmid-bacteria interplay.

Unveiling the Intricate Connection: Cell Volume as a Key Regulator of Mechanotransduction

The volumes of living cells undergo dynamic changes to maintain the cells' structural and functional integrity in many physiological processes. Minor fluctuations in cell volume can serve as intrinsic signals that play a crucial role in cell fate determination during mechanotransduction. In this review, we discuss the variability of cell volume and its role in vivo, along with an overview of the mechanisms governing cell volume regulation. Additionally, we provide insights into the current approaches used to control cell volume in vitro. Furthermore, we summarize the biological implications of cell volume regulation and discuss recent advances in understanding the fundamental relationship between cell volume and mechanotransduction. Finally, we delve into the potential underlying mechanisms, including intracellular macromolecular crowding and cellular mechanics, that govern the global regulation of cell fate in response to changes in cell volume. By exploring the intricate interplay between cell volume and mechanotransduction, we underscore the importance of considering cell volume as a fundamental signaling cue to unravel the basic principles of mechanotransduction. Additionally, we propose future research directions that can extend our current understanding of cell volume in mechanotransduction. Overall, this review highlights the significance of considering cell volume as a fundamental signal in understanding the basic principles in mechanotransduction and points out the possibility of controlling cell volume to control cell fate, mitigate disease-related damage, and facilitate the healing of damaged tissues.

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.

Highly Multiplexed Spatial Transcriptomics in Bacteria

Single-cell decisions made in complex environments underlie many bacterial phenomena. Image-based transcriptomics approaches offer an avenue to study such behaviors, yet these approaches have been hindered by the massive density of bacterial mRNA. To overcome this challenge, we combine 1000-fold volumetric expansion with multiplexed error robust fluorescence in situ hybridization (MERFISH) to create bacterial-MERFISH. This method enables high-throughput, spatially resolved profiling of thousands of operons within individual bacteria. Using bacterial-MERFISH, we dissect the response of E. coli to carbon starvation, systematically map subcellular RNA organization, and chart the adaptation of a gut commensal B. thetaiotaomicron to micron-scale niches in the mammalian colon. We envision bacterial-MERFISH will be broadly applicable to the study of bacterial single-cell heterogeneity in diverse, spatially structured, and native environments.

Interplay of two small RNAs fine-tunes hierarchical flagella gene expression in Campylobacter jejuni

Like for many bacteria, flagella are crucial for Campylobacter jejuni motility and virulence. Biogenesis of the flagellar machinery requires hierarchical transcription of early, middle (RpoN-dependent), and late (FliA-dependent) genes. However, little is known about post-transcriptional regulation of flagellar biogenesis by small RNAs (sRNAs). Here, we characterized two sRNAs with opposing effects on C. jejuni filament assembly and motility. We demonstrate that CJnc230 sRNA (FlmE), encoded downstream of the flagellar hook protein, is processed from the RpoN-dependent flgE mRNA by RNase III, RNase Y, and PNPase. We identify mRNAs encoding a flagella-interaction regulator and the anti-sigma factor FlgM as direct targets of CJnc230 repression. CJnc230 overexpression upregulates late genes, including the flagellin flaA, culminating in longer flagella and increased motility. In contrast, overexpression of the FliA-dependent sRNA CJnc170 (FlmR) reduces flagellar length and motility. Overall, our study demonstrates how the interplay of two sRNAs post-transcriptionally fine-tunes flagellar biogenesis through balancing of the hierarchically-expressed components.

Ecology of Legionella pneumophila biofilms: The link between transcriptional activity and the biphasic cycle

There has been considerable discussion regarding the environmental life cycle of Legionella pneumophila and its virulence potential in natural and man-made water systems. On the other hand, the bacterium's morphogenetic mechanisms within host cells (amoeba and macrophages) have been well documented and are linked to its ability to transition from a non-virulent, replicative state to an infectious, transmissive state. Although the morphogenetic mechanisms associated with the formation and detachment of the L. pneumophila biofilm have also been described, the capacity of the bacteria to multiply extracellularly is not generally accepted. However, several studies have shown genetic pathways within the biofilm that resemble intracellular mechanisms. Understanding the functionality of L. pneumophila cells within a biofilm is fundamental for assessing the ecology and evaluating how the biofilm architecture influences L. pneumophila survival and persistence in water systems. This manuscript provides an overview of the biphasic cycle of L. pneumophila and its implications in associated intracellular mechanisms in amoeba. It also examines the molecular pathways and gene regulation involved in L. pneumophila biofilm formation and dissemination. A holistic analysis of the transcriptional activities in L. pneumophila biofilms is provided, combining the information of intracellular mechanisms in a comprehensive outline. Furthermore, this review discusses the techniques that can be used to study the morphogenetic states of the bacteria within biofilms, at the single cell and population levels.

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.

The past, present and future of polymicrobial infection research: Modelling, eavesdropping, terraforming and other stories

Over the last two centuries, great advances have been made in microbiology as a discipline. Much of this progress has come about as a consequence of studying the growth and physiology of individual microbial species in well-defined laboratory media; so-called "axenic growth". However, in the real world, microbes rarely live in such "splendid isolation" (to paraphrase Foster) and more often-than-not, share the niche with a plethora of co-habitants. The resulting interactions between species (and even between kingdoms) are only very poorly understood, both on a theoretical and experimental level. Nevertheless, the last few years have seen significant progress, and in this review, we assess the importance of polymicrobial infections, and show how improved experimental traction is advancing our understanding of these. A particular focus is on developments that are allowing us to capture the key features of polymicrobial infection scenarios, especially as those associated with the human airways (both healthy and diseased).

Enhancing Specific Fluorescence In Situ Hybridization with Quantum Dots for Single-Molecule RNA Imaging in Formalin-Fixed Paraffin-Embedded Tumor Tissues

Single-molecule fluorescence in situ hybridization (smFISH) represents a promising approach for the quantitative analysis of nucleic acid biomarkers in clinical tissue samples. However, low signal intensity and high background noise are complications that arise from diagnostic pathology when performed with smFISH-based RNA imaging in formalin-fixed paraffin-embedded (FFPE) tissue specimens. Moreover, the associated complex procedures can produce uncertain results and poor image quality. Herein, by combining the high specificity of split DNA probes with the high signal readout of ZnCdSe/ZnS quantum dot (QD) labeling, we introduce QD split-FISH, a high-brightness smFISH technology, to quantify the expression of mRNA in both cell lines and clinical FFPE tissue samples of breast cancer and lung squamous carcinoma. Owing to its high signal-to-noise ratio, QD split-FISH is a fast, inexpensive, and sensitive method for quantifying mRNA expression in FFPE tumor tissues, making it suitable for biomarker imaging and diagnostic pathology.

Applications of single‑cell omics and spatial transcriptomics technologies in gastric cancer (Review)

Gastric cancer (GC) is a prominent contributor to global cancer-related mortalities, and a deeper understanding of its molecular characteristics and tumor heterogeneity is required. Single-cell omics and spatial transcriptomics (ST) technologies have revolutionized cancer research by enabling the exploration of cellular heterogeneity and molecular landscapes at the single-cell level. In the present review, an overview of the advancements in single-cell omics and ST technologies and their applications in GC research is provided. Firstly, multiple single-cell omics and ST methods are discussed, highlighting their ability to offer unique insights into gene expression, genetic alterations, epigenomic modifications, protein expression patterns and cellular location in tissues. Furthermore, a summary is provided of key findings from previous research on single-cell omics and ST methods used in GC, which have provided valuable insights into genetic alterations, tumor diagnosis and prognosis, tumor microenvironment analysis, and treatment response. In summary, the application of single-cell omics and ST technologies has revealed the levels of cellular heterogeneity and the molecular characteristics of GC, and holds promise for improving diagnostics, personalized treatments and patient outcomes in GC.

Adaptation of the Mycobacterium tuberculosis transcriptome to biofilm growth

Mycobacterium tuberculosis (M. tb), the causative agent of tuberculosis (TB), is a leading global cause of death from infectious disease. Biofilms are increasingly recognized as a relevant growth form during M. tb infection and may impede treatment by enabling bacterial drug and immune tolerance. M. tb has a complicated regulatory network that has been well-characterized for many relevant disease states, including dormancy and hypoxia. However, despite its importance, our knowledge of the genes and pathways involved in biofilm formation is limited. Here we characterize the biofilm transcriptomes of fully virulent clinical isolates and find that the regulatory systems underlying biofilm growth vary widely between strains and are also distinct from regulatory programs associated with other environmental cues. We used experimental evolution to investigate changes to the transcriptome during adaptation to biofilm growth and found that the application of a uniform selection pressure resulted in loss of strain-to-strain variation in gene expression, resulting in a more uniform biofilm transcriptome. The adaptive trajectories of transcriptomes were shaped by the genetic background of the M. tb population leading to convergence on a sub-lineage specific transcriptome. We identified widespread upregulation of non-coding RNA (ncRNA) as a common feature of the biofilm transcriptome and hypothesize that ncRNA function in genome-wide modulation of gene expression, thereby facilitating rapid regulatory responses to new environments. These results reveal a new facet of the M. tb regulatory system and provide valuable insight into how M. tb adapts to new environments.