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Multispecies microbial communities drive most ecosystems on Earth. Chemical and biological interactions within these communities can affect the survival of individual members and the entire community. However, the prohibitively high number of possible interactions within a microbial community has made the characterization of factors that influence community development challenging. Here, we report a Microbial Community Interaction (µCI) device to advance the systematic study of chemical and biological interactions within a microbial community. The µCI creates a combinatorial landscape made up of an array of triangular wells interconnected with circular wells, which each contains either a different chemical or microbial strain, generating chemical gradients and revealing biological interactions. Bacillus cereus UW85 containing green fluorescent protein provided the "target" readout in the triangular wells, and antibiotics or microorganisms in adjacent circular wells are designated the "variables." The µCI device revealed that gentamicin and vancomycin are antagonistic to each other in inhibiting the target B. cereus UW85, displaying weaker inhibitory activity when used in combination than alone. We identified three-member communities constructed with isolates from the plant rhizosphere that increased or decreased the growth of B. cereus . The µCI device enables both strain-level and community-level insight. The scalable geometric design of the µCI device enables experiments with high combinatorial efficiency, thereby providing a simple, scalable platform for systematic interrogation of three-factor interactions that influence microorganisms in solitary or community life., Competing Interests: Competing interests statement:D.J.B. holds equity in Bellbrook Labs LLC, Tasso Inc., Salus Discovery LLC, Lynx Biosciences Inc., Stacks to the Future LLC, Onexio Biosystems LLC, Navitro Biosciences LLC, and Flambeau Diagnostics LLC. J.H. holds equity in Wacasa Pharmaceuticals, Inc. A patent application (US011185860B2) was filed through the Wisconsin Alumni Research Foundation for the device described in this work.

Bacteriophages, viruses that infect bacteria, have great specificity for their bacterial hosts at the strain and species level. However, the relationship between the phageome and associated bacterial population dynamics is unclear. Here we generated a computational pipeline to identify sequences associated with bacteriophages and their bacterial hosts in cell-free DNA from plasma samples. Analysis of two independent cohorts, including a Stanford Cohort of 61 septic patients and 10 controls and the SeqStudy cohort of 224 septic patients and 167 controls, reveals a circulating phageome in the plasma of all sampled individuals. Moreover, infection is associated with overrepresentation of pathogen-specific phages, allowing for identification of bacterial pathogens. We find that information on phage diversity enables identification of the bacteria that produced these phages, including pathovariant strains of Escherichia coli. Phage sequences can likewise be used to distinguish between closely related bacterial species such as Staphylococcus aureus, a frequent pathogen, and coagulase-negative Staphylococcus, a frequent contaminant. Phage cell-free DNA may have utility in studying bacterial infections., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Ovarian cancer and triple-negative breast cancer are among the most lethal diseases affecting women, with few targeted therapies and high rates of metastasis. Cancer cells are capable of evading clearance by macrophages through the overexpression of anti-phagocytic surface proteins called 'don't eat me' signals-including CD47 1 , programmed cell death ligand 1 (PD-L1) 2 and the beta-2 microglobulin subunit of the major histocompatibility class I complex (B2M) 3 . Monoclonal antibodies that antagonize the interaction of 'don't eat me' signals with their macrophage-expressed receptors have demonstrated therapeutic potential in several cancers 4,5 . However, variability in the magnitude and durability of the response to these agents has suggested the presence of additional, as yet unknown 'don't eat me' signals. Here we show that CD24 can be the dominant innate immune checkpoint in ovarian cancer and breast cancer, and is a promising target for cancer immunotherapy. We demonstrate a role for tumour-expressed CD24 in promoting immune evasion through its interaction with the inhibitory receptor sialic-acid-binding Ig-like lectin 10 (Siglec-10), which is expressed by tumour-associated macrophages. We find that many tumours overexpress CD24 and that tumour-associated macrophages express high levels of Siglec-10. Genetic ablation of either CD24 or Siglec-10, as well as blockade of the CD24-Siglec-10 interaction using monoclonal antibodies, robustly augment the phagocytosis of all CD24-expressing human tumours that we tested. Genetic ablation and therapeutic blockade of CD24 resulted in a macrophage-dependent reduction of tumour growth in vivo and an increase in survival time. These data reveal CD24 as a highly expressed, anti-phagocytic signal in several cancers and demonstrate the therapeutic potential for CD24 blockade in cancer immunotherapy.

Exciting progress in the field of cancer immunotherapy has renewed the urgency of the need for basic studies of immunoregulation in both adaptive cell lineages and innate cell lineages. Here we found a central role for major histocompatibility complex (MHC) class I in controlling the phagocytic function of macrophages. Our results demonstrated that expression of the common MHC class I component β 2 -microglobulin (β2M) by cancer cells directly protected them from phagocytosis. We further showed that this protection was mediated by the inhibitory receptor LILRB1, whose expression was upregulated on the surface of macrophages, including tumor-associated macrophages. Disruption of either MHC class I or LILRB1 potentiated phagocytosis of tumor cells both in vitro and in vivo, which defines the MHC class I-LILRB1 signaling axis as an important regulator of the effector function of innate immune cells, a potential biomarker for therapeutic response to agents directed against the signal-regulatory protein CD47 and a potential target of anti-cancer immunotherapy.

We inhale respiratory pathogens continuously, and the subsequent signaling events between host and microbe are complex, ultimately resulting in clearance of the microbe, stable colonization of the host, or active disease. Traditional in vitro methods are ill-equipped to study these critical events in the context of the lung microenvironment. Here we introduce a microscale organotypic model of the human bronchiole for studying pulmonary infection. By leveraging microscale techniques, the model is designed to approximate the structure of the human bronchiole, containing airway, vascular, and extracellular matrix compartments. To complement direct infection of the organotypic bronchiole, we present a clickable extension that facilitates volatile compound communication between microbial populations and the host model. Using Aspergillus fumigatus, a respiratory pathogen, we characterize the inflammatory response of the organotypic bronchiole to infection. Finally, we demonstrate multikingdom, volatile-mediated communication between the organotypic bronchiole and cultures of Aspergillus fumigatus and Pseudomonas aeruginosa.

Germination of spores into actively growing cells is a process essential for survival and pathogenesis of many microbes. Molecular mechanisms governing germination, however, are poorly understood in part because few tools exist for evaluating and interrogating the process. Here, we introduce an assay that leverages developments in microfluidic technology and image processing to quantitatively measure germination with unprecedented resolution, assessing both individual cells and the population as a whole. Using spores from Cryptococcus neoformans, a leading cause of fatal fungal disease in humans, we developed a platform to evaluate spores as they undergo morphological changes during differentiation into vegetatively growing yeast. The assay uses pipet-accessible microdevices that can be arrayed for efficient testing of diverse microenvironmental variables, including temperature and nutrients. We discovered that temperature influences germination rate, a carbon source alone is sufficient to induce germination, and the addition of a nitrogen source sustains it. Using this information, we optimized the assay for use with fungal growth inhibitors to pinpoint stages of germination inhibition. Unexpectedly, the clinical antifungal drugs amphotericin B and fluconazole did not significantly alter the process or timing of the transition from spore to yeast, indicating that vegetative growth and germination are distinct processes in C. neoformans. Finally, we used the high temporal resolution of the assay to determine the precise defect in a slow-germination mutant. Combining advances in microfluidics with a robust fungal molecular genetic system allowed us to identify and alter key temporal, morphological, and molecular events that occur during fungal germination.

The microbial secondary metabolome encompasses great synthetic diversity, empowering microbes to tune their chemical responses to changing microenvironments. Traditional metabolomics methods are ill-equipped to probe a wide variety of environments or environmental dynamics. Here we introduce a class of microscale culture platforms to analyse chemical diversity of fungal and bacterial secondary metabolomes. By leveraging stable biphasic interfaces to integrate microculture with small molecule isolation via liquid-liquid extraction, we enable metabolomics-scale analysis using mass spectrometry. This platform facilitates exploration of culture microenvironments (including rare media typically inaccessible using established methods), unusual organic solvents for metabolite isolation and microbial mutants. Utilizing Aspergillus, a fungal genus known for its rich secondary metabolism, we characterize the effects of culture geometry and growth matrix on secondary metabolism, highlighting the potential use of microscale systems to unlock unknown or cryptic secondary metabolites for natural products discovery. Finally, we demonstrate the potential for this class of microfluidic systems to study interkingdom communication between fungi and bacteria.