Conventional fluorescence-activated cell sorting (FACS) systems are usually expensive and require large sample volumes. In this study, we present a compact microfluidic system based on gradient dielectrophoresis (gDEP-μFACS). The device integrates inertial self-ordering, laser-induced fluorescence detection, and programmable cell deflection on a single chip. It uses asymmetric curved microchannels to achieve uniform single-cell distribution and curved gradient electrodes to generate precise electric fields for cell sorting. Intermittent sinusoidal signals help prevent cells from sticking to the electrodes. The system can efficiently screen fluorescent microspheres and isolate human cancer cells expressing green fluorescent protein (GFP) with high viability. Its portable design enables gentle, accurate sorting of small samples, making it suitable for on-chip cytometry and point-of-care testing.

Polyethylene terephthalate (PET) is one of the most widely produced synthetic plastics globally, posing serious environmental challenges due to its resistance to natural degradation. Enzymatic degradation offers a sustainable solution for PET recycling. However, natural PET hydrolases often suffer from limited catalytic efficiency, and existing screening methods are labor-intensive with low throughput. To overcome the limitations of conventional methods in throughput and efficiency, this study developed a fluorescent nanoprobe technology combining substrate authenticity with high detection sensitivity, which was integrated into an ultra-high-throughput fluorescence-activated droplet sorting (FADS) platform for the single-cell screening and directed evolution of PET hydrolases. Fluorescein dilaurate (FDL)-loaded PET nanoparticles (PET-FDL NPs) were synthesized as specific fluorogenic probes. By combining Escherichia coli surface display of mScarletI-leaf-branch compost cutinase (LCC) fusion proteins with a dual-fluorescence ratiometric assay (fluorescein/mScarletI), we achieved precise normalization of enzymatic activity against expression variations. An LCC mutant library generated by error-prone PCR (epPCR) was screened by FADS at a throughput of 107 droplets per day. The results showed that FADS enrichment significantly increased the proportion of positive droplets. Subsequent microplate rescreening revealed that this strategy improved the positive hit rate from ~5% (plate screening) to 44%, establishing a robust and scalable workflow for directed evolution of PET hydrolases.

The clinical translation of phage therapy for multidrug-resistant (MDR) infections is constrained by the lack of rapid, standardized susceptibility testing methods. Here, we present digital Phage Susceptibility Testing (dPST), an automated droplet digital PCR (ddPCR)-based workflow that directly quantifies phage-induced bacterial DNA release as a universal molecular signature of lysis. By targeting conserved 16 S rRNA gene regions, dPST enables standardized, species-independent detection of cell lysis across most ESKAPE pathogens within approximately 3 hours, representing a significant increase in efficiency compared to conventional plaque assays. Validation against a panel of 13 clinical MDR isolates across 104 phage–host combinations demonstrated > 95% concordance with conventional spot tests, while uniquely resolving weak or heterogeneous lytic activities. Importantly, ddPCR also exhibits strong robustness to low-level phage cross-contamination: unlike plaque or spot tests that are highly susceptible to trace contaminating phages, ddPCR signals remain stable until contamination exceeds high thresholds, ensuring reliable readouts in high-throughput PST workflows. Furthermore, the assay provides molecular quantification of infection outcomes across a range of multiplicities of infection, revealing defense-mediated interactions in systems such as CRISPR–Cas and Sir2–HerA that are obscured by conventional plaque-based phenotypic readouts. With sensitivity far exceeding that of optical density or plaque-based assays, dPST establishes a robust and mechanically insightful framework for personalized phage screening and host–phage interaction profiling.

The clinical translation of phage therapy for multidrug-resistant infections is constrained by the lack of rapid, standardized therapeutic phage selection. Here, we introduce digital phage susceptibility testing (dPhaST), an automated droplet digital PCR workflow that quantifies phage-induced DNA release as a molecular signature of lysis. By targeting conserved 16S rRNA regions, dPhaST measures lytic activity across diverse bacterial pathogens within 3 h. Across 122 phage-host combinations involving 19 bacterial strains from six species, dPhaST shows 95.9% concordance with spot tests while resolving weak and heterogeneous lytic activities that are not readily distinguished phenotypically. It remains robust during the early infection window despite phage-encoded nuclease activity and tolerates phage cross-contamination better than spot tests. The method captures defense-mediated interactions involving CRISPR-Cas and Sir2-HerA systems. In this work, we show that automated digital quantification enables rapid and mechanistically informative profiling of early phage lytic efficacy across Gram-positive and Gram-negative pathogens.

Abstract Rapid and accurate pathogen identification is crucial for the clinical management of infectious diseases, particularly sepsis and severe respiratory infections, yet standard clinical workflows remain slow and resource-intensive. Here, we developed an automated, high-throughput imaging platform built on standard, clinically accessible bright-field microscopy, and generated a large dataset comprising 24.9 million label-free bacterial cells across six focal pathogens. Leveraging this resource, we trained a neural network (ESKAPe-ResNet) to identify ESKAPe species at the single-bacterium level. The model achieved >92% accuracy in species-level classification and >82% accuracy in quantifying ESKAPe abundance in mock mixtures, with high specificity against non-ESKAPe bacteria. In clinical validation using sputum, bronchoalveolar lavage fluid and blood samples from patients with respiratory infections and sepsis, the approach correctly identified the dominant ESKAPe pathogen in >78% of samples after minimum broth culture enrichment. The imaging-to-identification pipeline was completed in under 10 minutes, and coupled with brief cultivation, the median time to accurate identification was reduced to 5–6 hours, compared with days for conventional blood culture-based workflows. This work establishes the proof-of-principle for label-free, hardware-minimal rapid pathogen identification, providing a clinically deployable workflow to expedite diagnosis and reduce mortality in severe bacterial infections.

The rare biosphere harbors immense microbial diversity, yet most low-abundance taxa remain uncultured and functionally enigmatic. Here, we isolated strain D14T from deep-sea water, and propose to classify it as a novel species, Metabolovarius oceani sp. nov., within the novel family Metabolovariaceae fam. nov. M. oceani represents the first cultivated member of the candidate family NORP267, a globally distributed but elusive alphaproteobacterial lineage known only from metagenome-assembled genomes. It possesses broad metabolic capabilities, including CO2 fixation, polyhydroxyalkanoate biosynthesis, complete denitrification and thiosulfate oxidation, and is capable of aerobic growth under both heterotrophic and autotrophic conditions and of anaerobic autotrophic denitrification via thiosulfate oxidation. Despite its versatile metabolic repertoire and global distribution, Metabolovariaceae remains consistently low in abundance across diverse habitats. The isolation of M. oceani permits direct experimental insights into the evolutionary adaptations, physiological resilience, and potential ecosystem roles of rare but metabolically versatile microorganisms within the microbial dark matter.

The translation of 3D multicellular systems into clinical applications has been constrained by the need to balance physiological relevance and scalability. Current biofabrication methods primarily depend on passive cell aggregation or capillary- and viscosity-limited segmentation, resulting in stochastic heterogeneity that limits high-throughput screening (HTS). Here, we present OsciSphere, a chip-free droplet microfluidic platform that utilizes Weber-number-driven inertial forces to enable deterministic bioassembly of uniform 3D multicellular systems. Through programmable oscillatory acceleration, OsciSphere achieves precise, high-frequency droplet generation in standard well plates, eliminating the requirement for complex microfabrication. We demonstrate the versatility of this platform by generating miniaturized multicellular tumor spheroids (µMCTs) for drug screening, tissue-derived organoids (µTDOs) for pharmacological studies, and patient-derived organoids (µPDOs) that support tumor-immune co-cultures. In comparison to conventional Matrigel domes, OsciSphere-assembled 3D multicellular systems display improved uniformity, viability, and chemosensitivity. The platform’s scalability enabled the screening of 49 commensal gut bacterial secretomes, leading to the identification of Eubacterium species that modulate cancer apoptotic pathways. Furthermore, µPDOs generated with OsciSphere support efficient infiltration of autologous PBMCs, enabling quantitative assessment of PD-1 blockade. This platform provides a robust, accessible approach to bridging the gap between complex tissue modeling and large-scale functional screening in precision oncology.

Deep-sea microorganisms comprise the Earth's largest and least explored microbiome, yet the vast majority remain uncultivated due to challenges of preserving in situ high hydrostatic pressure and preventing loss of viability and diversity during recovery, which limits our ability to explore their ecological functions and adaptive strategies. Here, we introduce DeepDrop, a microfluidics platform that enables high-throughput single-cell cultivation under pressures spanning the full ocean depth directly aboard research vessels, following direct colony formation via pipette-generated double emulsions. Applying to hadal samples, DeepDrop recovered >50% more microbial diversity than conventional high-pressure bulk cultivation, including rare taxa with streamlined genomes and distinctive genetic features associated with pressure adaptation. Combined metagenomic and transcriptomic analyses revealed that DeepDrop enriched pressure-adapted taxa carrying key stress-related genes and induced coordinated transcriptional reprogramming, characterized by upregulation of stress pathways and repression of motility. By integrating shipboard deployment, pressure-stable droplet cultivation, and efficient recovery, DeepDrop offers a powerful platform for accessing deep-sea microbial dark matter and illuminating microbial life strategies under extreme environmental constraints.

Antibiotic misuse is a key driver of antimicrobial resistance, but extensive use and prolonged environmental persistance of disinfectants like quaternary ammonium compounds (QACs), poses an urgent and underappreciated threat. Conventional QACs accumulate at sub-inhibitory concentrations (sub-MICs), accelerating multidrug resistance (MDR) in bacteria via sustained selection pressure. We introduce R-substituted silaketal-bridged QACs (RSBQs), which feature acid-cleavable linkages that enable controllable hydrolysis from bactericidal to non-toxic states. By modulating the R-substituents and environmental conditions, degradation half-lives range from 12 h to 6 days, reducing selection pressure before resistance establishes. Even at sub-MICs, partially degraded RSBQs such as ethyl-substituted SBQ (Et-SBQ) and n-propyl-substituted SBQ (nPr-SBQ), exhibit dual resistance-suppression, including downregulation of resistance gene expression and inhibition of efflux pump activity. By resensitizing multidrug-resistant bacteria to antibiotics, Et-SBQ synergized with ciprofloxacin to accelerate wound healing in mice. This strategy combines potent antibacterial activity, environmental degradability, and resistance suppression, offering a promising MDR solution.

Neonatal pneumonia is a leading cause of infant mortality worldwide; however, a lack of microbial profiling, especially of low-abundance species, makes accurate diagnosis challenging. Traditional methods can fail to capture the complexity of the neonatal respiratory microbiota, thereby obscuring its role in disease progression. Here, we describe a novel approach that combines high-throughput sequencing with droplet-based microfluidic cultivation to investigate microbiome shifts in neonates with pneumonia. Using 16S ribosomal RNA (rRNA) gene sequencing of 71 pneumonia cases and 49 controls, we identified 1009 genera, including 930 low-abundance taxa, which showed significant compositional differences between groups. Linear discriminant analysis effect size identified key pneumonia-associated genera, such as Streptococcus, Rothia, and Corynebacterium. Droplet-based cultivation recovered 299 strains from 94 taxa, including rare species and ESKAPE pathogens, thereby supporting targeted antimicrobial management. Host-pathogen interaction assays showed that Rothia and Corynebacterium induced inflammation in lung epithelial cells, likely via dysregulation of the PI3K-Akt pathway. Integrating these marker taxa with clinical factors, such as gestational age and delivery type, offers the potential for precise diagnosis and treatment. The recovery of diverse species can support the construction of a biobank of neonatal respiratory microbiota to advance mechanistic studies and therapeutic strategies.

We report a high-quality metagenome-assembled genome (MAG) of a novel Pseudoalteromonas species recovered from deep-sea water of the South Mid-Atlantic Ridge. This MAG encodes key chitinase-related genes, suggesting potential involvement in chitin degradation and organic matter remineralization in the deep sea.

The differences in microbiota between periodontitis and health have been extensively studied; however, knowledge about how the microbiota shifts from shallow to deep periodontal pockets remains limited despite its clinical importance in disease progres-sion and management. Patients diagnosed with stage III periodontitis commonly pre-sent varied probing depths (PD) within the same oral cavity, reflecting localized disease severity. This study aims to analyze the microbiome of subgingival plaques at various PDs in periodontitis patients. Subgingival plaques were collected from sixteen healthy subjects (health group) and periodontal pockets of sixteen stage III periodontitis pa-tients (PD 0–3 mm, PD 4–5 mm and PD 6–9 mm groups). A total of 64 subgingival plaque samples underwent 16S rRNA gene sequencing. The PD 6–9 mm group exhib-ited significantly higher alpha diversity than the health group, and distinct subgingival microbial community structures were observed in periodontitis patients, regardless of probing depth. The relative abundance of specific genera differed notably between health and periodontitis states; Corynebacterium and Cardiobacterium decreased, whereas Schaalia increased in shallow pockets (PD 0–3 mm) of periodontitis relative to the health group. Co-occurrence network analysis on the species level revealed that the PD 4–5 mm group had the most complex interspecies interactions, followed by the PD 6–9 mm and PD 0–3 mm groups. These findings indicate significant variations in mi-crobial diversity, composition, and interspecies interactions associated with periodon-tal health and periodontitis severity, highlighting their potential relevance for clinical diagnosis and targeted therapeutic strategies.

Anaerobic methanotrophic (ANME) microbes play a crucial role in the bioprocess of anaerobic oxidation of methane (AOM). However, due to their unculturable status, their diversity is poorly understood. In this study, we established a microfluidics-based epicPCR (Emulsion, Paired Isolation, and Concatenation PCR) to fuse the 16S rRNA gene and mcrA gene to reveal the diversity of ANME microbes (mcrA gene hosts) in three sampling push-cores from the marine cold seep. A total of 3725 16S amplicon sequence variants (ASVs) of the mcrA gene hosts were detected, and classified into 78 genera across 23 phyla. Across all samples, the dominant phyla with high relative abundance (>10%) were the well-known Euryarchaeota, and some bacterial phyla such as Campylobacterota, Proteobacteria, and Chloroflexi; however, the specificity of these associations was not verified. In addition, the compositions of the mcrA gene hosts were significantly different in different layers, where the archaeal hosts increased with the depths of sediments, indicating the carriers of AOM were divergent in depth. Furthermore, the consensus phylogenetic trees of the mcrA gene and the 16S rRNA gene showed congruence in archaea not in bacteria, suggesting the horizontal transfer of the mcrA gene may occur among host members. Finally, some bacterial metagenomes were found to contain the mcrA gene as well as other genes that encode enzymes in the AOM pathway, which prospectively propose the existence of ANME bacteria. This study describes improvements for a potential method for studying the diversity of uncultured functional microbes and broadens our understanding of the diversity of ANMEs.

The human body harbors diverse microbial communities essential for maintaining health and influencing disease processes. Droplet microfluidics, a precise and high-throughput platform for manipulating microscale droplets, has become vital in advancing microbiome research. This review introduces the foundational principles of droplet microfluidics, its operational capabilities, and wide-ranging applications. We emphasize its role in enhancing single-cell sequencing technologies, particularly genome and RNA sequencing, transforming our understanding of microbial diversity, gene expression, and community dynamics. We explore its critical function in isolating and cultivating traditionally unculturable microbes and investigating microbial activity and interactions, facilitating deeper insight into community behavior and metabolic functions. Lastly, we highlight its broader applications in microbial analysis and its potential to revolutionize human health research by driving innovations in diagnostics, therapeutic development, and personalized medicine. This review provides a comprehensive overview of droplet microfluidics' impact on microbiome research, underscoring its potential to transform our understanding of microbial dynamics and their relevance to health and disease.

Heterogeneous vancomycin-intermediate Staphylococcus aureus (hVISA) is associated with suboptimal glycopeptide treatment outcomes. However, conventional antimicrobial susceptibility testing fails to distinguish hVISA from vancomycin-susceptible Staphylococcus aureus (VSSA), potentially delaying effective therapy. The gold standard population analysis profiling with area under the curve (PAP-AUC) method is labor-intensive and time-consuming, necessitating rapid detection alternatives. This study introduces a microfluidic platform based on fluorescence-activated droplet sorting (FADS) for the rapid detection and isolation of hVISA. Through systematic optimization of key parameters such as droplet generation conditions, bacterial suspension concentration, fluorescence probe selection, fluorescence duration, and vancomycin screening concentration, we established a rapid hVISA screening system. The efficacy of this system was evaluated using the hVISA standard strain Mu3, followed by validation with 15 clinical hVISA isolates. Genomic analysis further elucidated the genetic basis of drug resistance in hVISA strains. We developed a high-throughput detection platform for hVISA by integrating a microfluidic system with FADS. Based on a Poisson distribution theoretical model, the bacterial suspension concentration was optimized to 106 CFU/mL, achieving a single-bacterium droplet encapsulation rate of approximately 30

This work describes μMET, a novel microfluidic device for precise microbial enumeration tests (MET), essential in pharmaceutical, cosmetic, and food industries for ensuring microbiological safety standards. The μMET chip, comprising two hydrophobic glass plates, features a 15-μm deep μMET chamber enhanced by nanopillars and air supply units, facilitating both immediate and growth-dependent MET. Experimental results, with E. coli as a model bacterium, demonstrate that μMET provides counting linearity that outperforms traditional hemocytometers. The chip's design mitigates challenges like evaporation and ensures high-resolution imaging, making it a cost-effective and reusable alternative to conventional methods. Notably, bright-field μMET eliminates the need for fluorescent staining, streamlining operations with deep-learning algorithms for bacterial counts. Furthermore, we have developed a high-parallel μMET chip featuring 16 counting chambers, enhancing throughput and accommodating immediate and growth-dependent MET approaches. Its innovative design and adaptability render the μMET chip as a valuable tool for microbiology, medicine, and industry applications.

BACKGROUND:Children affected by severe early childhood caries (S-ECC) usually need comprehensive caries treatment due to the extensive of caries. How the oral microbiome changes after caries therapy within the short-term warrant further study. AIM:This study aimed to investigate the short-term impact of comprehensive caries treatment on the supragingival plaque microbiome of S-ECC children. DESIGN:Thirty-three children aged 2-4 years with severe caries (dt > 7) were recruited. Comprehensive caries treatment was performed under general anesthesia in one session and included restoration, pulp treatment, extraction, and fluoride application. Supragingival plaque was sampled pre- and 1-month posttreatment. The genomic DNA of the supragingival plaque was extracted, and bacterial 16S ribosomal RNA gene sequencing was performed. RESULTS:Our data showed that the microbial community evenness significantly decreased posttreatment. Furthermore, comprehensive caries treatment led to more diverse microbial structures among the subjects. The interbacterial interactions reflected by the microbial community's co-occurrence network tended to be less complex posttreatment. Caries treatment increased the relative abundance of Corynebacterium matruchotii, Corynebacterium durum, Actinomyces naeslundii, and Saccharibacteria HMT-347, as well as Aggregatibacter HMT-458 and Haemophilus influenzae. Meanwhile, the relative abundance of Streptococcus mutans, three species from Leptotrichia, Neisseria bacilliformis, and Provotella pallens significantly decreased posttreatment. CONCLUSION:Our results suggested that comprehensive caries treatment may contribute to the reconstruction of a healthier supragingival microbiome.

Summary: Background: The pathology of keloid and especially the roles of bacteria on it were not well understood. Methods: In this study, multi-omics analyses including microbiome, metaproteomics, metabolomic, single-cell transcriptome and cell-derived xenograft (CDX) mice model were used to explore the roles of bacteria on keloid disease. Findings: We found that the types of bacteria are significantly different between keloid and healthy skin. The 16S rRNA sequencing and metaproteomics showed that more catalase (CAT) negative bacteria, Clostridium and Roseburia existed in keloid compared with the adjacent healthy skin. In addition, protein mass spectrometry shows that CAT is one of the differentially expressed proteins (DEPs). Overexpression of CAT inhibited the proliferation, migration and invasion of keloid fibroblasts, and these characteristics were opposite when CAT was knocked down. Furthermore, the CDX model showed that Clostridium butyricum promote the growth of patient's keloid fibroblasts in BALB/c female nude mice, while CAT positive bacteria Bacillus subtilis inhibited it. Single-cell RNA sequencing verified that oxidative stress was up-regulated and CAT was down-regulated in mesenchymal-like fibroblasts of keloid. Interpretation: In conclusion, our findings suggest that bacteria and CAT contribute to keloid disease. Funding: A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

Digital PCR (dPCR) holds immense potential for precisely detecting nucleic acid markers essential for personalized medicine. However, its broader application is hindered by high consumable costs, complex procedures, and restricted multiplexing capabilities. To address these challenges, an all-in-one dPCR system is introduced that eliminates the need for microfabricated chips, offering fully automated operations and enhanced multiplexing capabilities. Using this innovative oscillation-induced droplet generation technique, OsciDrop, this system supports a comprehensive dPCR workflow, including precise liquid handling, pipette-based droplet printing, in situ thermocycling, multicolor fluorescence imaging, and machine learning-driven analysis. The system's reliability is demonstrated by quantifying reference materials and evaluating HER2 copy number variation in breast cancer. Its multiplexing capability is showcased with a quadruplex dPCR assay that detects key EGFR mutations, including 19Del, L858R, and T790M in lung cancer. Moreover, the digital stepwise melting analysis (dSMA) technique is introduced, enabling high-multiplex profiling of seven major EGFR variants spanning 35 subtypes. This innovative dPCR system presents a cost-effective and versatile alternative, overcoming existing limitations and paving the way for transformative advances in precision diagnostics.

Within the supergroup Rotosphaeromycetes, or "Holomycota"/"Nucletmycea", there are several well-recognised unicellular clades in the earliest diverging fungi (EDF). However, we know little about their occurrence. Here, we investigated EDF in the rhizosphere and bulk soils from cropland, forest, orchard, and wetland ecosystems around the Beijing-Hebei area, China, to illustrate their niche and ecosystem preference. More than 500 new operational taxonomic units (OTUs) of EDF were detected based on the 18S rRNA genes. Microsporida and Aphelida constitute dominant groups, whereas Rozellosporida was quite rare. Although the EDF community was site-specific, the soil chemical characteristics, vegetation, and other eukaryotic microorganisms were the key factors driving the occurrence of EDF. Moreover, the stochastic process consisted the most of the EDF community assembly.