mLife

Bacteriophages exhibit staggering genomic diversity, yet phenotypic characterization remains bottlenecked by assays that generally yield simple binary infection outcomes. Quantitative traits can be extracted from standard liquid cultures, but many phages fail to produce a measurable effect in these settings, necessitating an improved quantitative approach on semi-solid media. While end-point plaque size is commonly used for quantitative phenotyping, it only provides a static snapshot that fails to disentangle phage performance across changing bacterial growth phases. Here, we report a cost-effective, scalable method to quantify the bacterial killing rates of diverse phages by continuously tracking plaque development using a consumer-grade flatbed scanner and custom open-source computer vision software. By fitting a minimal, five-parameter phenomenological model to the diverse BASEL collection of Escherichia coli phages, we accurately captured plaque expansion dynamics across all bacterial growth phases. We discovered that plaque expansion parameters vary significantly across individual phages and taxonomic families, with the initial expansion rate demonstrating an inverse correlation with viral genome size. Notably, these plaque expansion dynamics did not correlate with bacterial collapse times in liquid culture, indicating that they represent distinct physiological and kinetic processes. Finally, we demonstrated that phage taxonomic family can be predicted with 72.1% accuracy solely from dynamic plaque parameters using a random forest classifier, whereas conventional endpoint plaque sizes held no predictive power. This time-lapse phenotyping approach yields robust kinetic data superior to end-point measurements, establishing a scalable platform to accelerate phage discovery and genotype-phenotype mapping.

Photosynthetic hydrogen (photoH2) production by the cyanobacterium Synechocystis sp. PCC 6803 is an attractive means for storing solar energy. However, photoH2 yields remain limited by competing electron flux pathways. Recent in vitro characterization suggests that photoH2 production requires electrons from both carbohydrate oxidation and photosynthesis. Engineered fusions between photosystem I (PSI) and hydrogenase (PSI-H2ase) aim to divert electrons toward H2 production and rely exclusively on photosynthesis. Thus, photoH2 production differs fundamentally between wildtype (WT) and PSI-H2ase fusion mutants. Here, we show that photoH2 production in WT is enhanced by supplemented glucose, consistent with the recently reported confurcating nature of HoxEFUYH H2ases. PhotoH2 production was further studied in the new psaE-hoxUYH mutant by simultaneously monitoring electron flux through PSI alongside with turnover rates of O2, CO2 and H2. PsaE-hoxUYH achieved the highest photoH2 yield and longest production period among the currently available PSI-H2ase mutants in Synechocystis, prolonged by removing O2. Upon illumination, psaE-hoxUYH exhibited high initial photoH2 production rates, which decreased in parallel with CO2 fixation and ceased immediately in the presence of O2. In absence of O2, photoH2 production still declined slowly. Therefore, in addition to CO2 fixation and O2, other yet unknown factors might limit photoH2 production under these conditions. Moreover, we traced a previously observed high H2 production phase of unclear origin in psaD-hoxYH cultures to contaminating [FeFe]-H2ases from Clostridium intestinale rather than genuine photoH2 production by the mutant. Together, these findings indicate a complex metabolic interplay tuning photoH2 production in Synechocystis WT and PSI-H2ase fusion mutants.

Plaque assays remain the gold standard for bacteriophage quantification, but routine plaque counting is labor-intensive, time-consuming, and poorly suited to large experiments or automated workflows. Conventional plaque images also often provide insufficient contrast for simple software-based counting, especially when plaques are small, faint, or heterogeneous. Here we show that a membrane-impermeant nucleic acid dye can convert standard bacteriophage plaque assays into a high-contrast, machine-readable format compatible with simple automated counting. In a soft-agar overlay workflow, fluorescent labeling enabled plaque detection and automated enumeration using an open-source ImageJ pipeline based on Find Maxima, without phage engineering, machine learning, or custom software. Because the method improves the image contrast of the assay itself, it may also provide improved input for future machine-learning or other advanced automated counting workflows. The method was evaluated across diverse phage-host systems spanning dsDNA, ssRNA, filamentous, and enveloped phages, including T7, MS2, M13, and phi6. In lytic systems, fluorescent signal emerged prior to or alongside conventional plaque visibility and yielded automated counts that agreed closely with manual counting. M13 exhibited delayed fluorescence consistent with its chronic, nonlytic lifestyle, yet remained machine-countable at the conventional next-day endpoint. A Gram-positive Leo2-Bacillus safensis system revealed an important compatibility limit: dye incorporation at plating inhibited plaque formation, but a post-labeling workflow restored detectability and automated counting. Together, these results show that membrane-impermeant dye labeling can make plaque assays more computationally tractable while preserving the accessibility of standard phage methods. This approach provides a practical path toward higher-throughput, statistically rigorous phage biology in both low-resource and automation-oriented laboratories.

The filamentous cyanobacterium Nostoc punctiforme is a key model organism used to study several aspects of cyanobacterial biology, including development, nitrogen-fixing symbioses with plants, and secondary metabolites, among others. While N. punctiforme is amenable to genetic manipulation, traditional approaches for the generation of mutant strains using homologous recombination are slow, requiring prolonged outgrowth under antibiotic selection to ensure isogenic mutant populations. CRISPR-based genome editing using Cpf1 (Cas12a) was recently shown to be an effective means of rapid generation of isogenic mutants in several cyanobacteria. In this study, Cpf1-based genome editing tools were developed for N. punctiforme. A total of 19 unmarked, in-frame deletion mutants were successfully constructed using Cpf1-targeted cleavage along with homology directed repair (HDR). The length of the homology arms (HAs) on the homologous repair template (HRT) used for HDR was found to be a critical factor for successful deletion of target genes, with some requiring up to 4 kb HAs to acquire mutant exconjugants. A strategy for allelic replacement was also developed by introducing an exogenous target site in place of the deleted genes, which could subsequently be targeted for cleavage and repaired with an HRT containing altered alleles of the genes of interest. Additionally, a single-step cloning strategy was devised, allowing for rapid assembly of editing plasmids, and improved conjugation protocols for genetic transfer from E. coli to N. punctiforme were implemented. Collectively, these tools and protocols should enhance the pace and ease of conducting genetic studies in this important model cyanobacterium.

Recent work has established septation as a critical process for virulence in A. fumigatus, as strains lacking septa are avirulent. While our work has focused on the well-studied Septation Initiation Network (SIN), understanding of septation machinery upstream and downstream of SIN remains limited in filamentous fungi. Proximity labeling techniques are powerful tools to study pathway interactions, especially those that are transient. Recent advances have seen TurboID used to study pathways and processes important for fungal pathogenesis. In this study, we adapt TurboID for use in Aspergillus fumigatus and use overlapping datasets of two SIN components, the terminal NDR kinase SidB and its binding partner MobA, to identify putative septation effectors. Many known septation effectors, including septins and cell wall synthesis proteins, were enriched in our datasets, validating the approach. Phenotypic characterization of hits identified by LC-MS/MS revealed several previously uncharacterized gene products involved in septum formation and cell wall stress tolerance. These included the PP2A regulatory subunit PabA and IQGAP SepG, which have been shown to regulate septation in Aspergillus nidulans. Thus, TurboID is a useful tool to study fungal signaling and physiology in A. fumigatus and may be used to improve understanding of pathogenic processes.

Environmental biosurveillance requires technologies that can rapidly translate genomic information into sensitive, specific, and deployable detection tools. Here, we present the first proof-of-concept application of SENTINEL (Smart Environmental Nucleic-acid Tracking using Inference from Neural-networks for Early-warning Localization), integrating artificial-intelligence-guided target discovery, isothermal amplification, CRISPR-based detection, and environmental DNA. Using Rattus exulans, R. norvegicus, and R. rattus as a challenging model of closely related invasive vertebrates, SENTINEL achieved species-specific discrimination without detectable cross-reactivity and sensitivities of 10 aM for plasmid DNA and 10 fg/uL for genomic DNA. Selected assays also showed reproducible semi-quantitative performance and successful eDNA validation. This first application of CRISPR-based environmental biosurveillance to terrestrial invasive vertebrates demonstrates a transferable framework for converting sequence data into field-deployable assays, with potential applications across biosecurity, conservation, agriculture, and environmental monitoring.

Bacteria experience diverse mechanical forces throughout their natural environments, yet quantitative measurements of bacterial biomechanics remain challenging because most existing techniques require specialized instrumentation, such as atomic force microscopy (AFM) or microfluidic devices. Here, we introduce mechanofiltration, a simple, high-throughput assay that estimates whole-cell mechanics using standard laboratory equipment. In mechanofiltration, bacterial suspensions are centrifuged through porous membranes in multiwell plates. Pressure generated during centrifugation drives cells toward pores that are smaller than cell width, requiring cells to deform to transit through the membrane. By combining recovery on the opposite side of the filter with measurements of cell size, the assay estimates maximum cell deformation, a size-corrected proxy for whole-cell stiffness. We show that mechanofiltration detects established reductions in Escherichia coli cell stiffness caused by genetic disruption of load-bearing cell envelope components, treatment with outer membrane-destabilizing agents, and sublethal exposure to antibiotics. Fold changes in maximum deformation closely agree with published measurements obtained using AFM, cell-bending assays, and osmotic shock experiments. Mechanofiltration also reproduces previously reported mechanical differences among bacterial species with distinct morphologies and envelope architectures. Together, these results establish mechanofiltration as an accessible, inexpensive, and scalable approach for identifying genetic and environmental determinants of bacterial mechanics and for high-throughput screening of bacterial biomechanical phenotypes.

Streptococcus pneumoniae asymptomatically colonizes the nasopharynx but can invade the lower respiratory tract to cause life-threatening disease, particularly in older adults. However, whether the initial site of bacterial deposition following intranasal inoculation determines disease progression has not been directly examined. Here, we developed a near-infrared (NIR) fluorescence imaging approach using indocyanine green (ICG)-labeled S. pneumoniae TIGR4 to visualize early bacterial distribution in real time. ICG labeling by simple mixing, without genetic or chemical modification, neither impaired bacterial growth at 33 or 37{degrees}C, nor altered acid tolerance. Continuous video imaging during the first 10 min of infection resolved two distinct patterns: bacteria confined to the nasopharynx (colonization) and those aspirated into the lower respiratory tract (aspiration). Kaplan-Meier analysis revealed markedly higher mortality in the aspiration group in both young (hazard ratio = 7.9) and aged (hazard ratio = 8.4) mice, despite a 10-fold lower inoculum used for aged animals, with deaths beginning on day 3. Systemic profiling of blood at 24 h by RNA sequencing and plasma proteomics revealed that early aspiration in aged mice was associated with the activation of inflammatory and hematopoietic programs, enrichment of complement and coagulation cascades, and phagocytic pathways. Together, these findings establish aspiration into the lower respiratory tract as a trigger of severe pneumococcal disease and introduce real-time NIR imaging as a technique for linking early infection dynamics to systemic host responses.

The rise of antimicrobial resistance has intensified interest in antimicrobial photodynamic inactivation (aPDI) and antimicrobial blue light (aBL) as alternatives or adjuvants to conventional antibiotics. However, whether chemically distinct photodynamic treatments elicit a shared bacterial response remains unclear. Here, we integrated transcriptomic profiles of Escherichia coli BW25113 exposed to five short-term, sub-lethal photodynamic treatments: antimicrobial blue light (aBL), aBL combined with 5-aminolevulinic acid (aBL+ALA), rose bengal (RB), new methylene blue (NMB), and the cationic porphyrin TMPyP. Intersection analysis identified 891 conserved core genes differentially expressed across all treatments, of which approximately 98% changed in a consistent direction despite differences in photosensitizer chemistry and activating wavelength. Random-effects meta-analysis and robust rank aggregation prioritized 88 high-confidence genes, revealing induction of envelope stress and cytoplasmic protein quality control pathways alongside repression of acid resistance, hydrogen metabolism, molybdate transport, and biofilm formation. Regulon enrichment indicated that heat-shock sigma factor {sigma}32/RpoH and the envelope-stress regulators CpxR, BaeR, {sigma}24/RpoE, and PspF were enriched among induced genes, whereas GadW/GadX/GadE, Fur, and {sigma}38/RpoS were enriched among repressed genes. Functional validation using selected single-gene Keio knockouts confirmed that deletion of conserved-core genes sensitized E. coli to photodynamic treatment and delayed post-treatment recovery in a modality-dependent manner. Moreover, RT-qPCR analysis of selected transcriptional responses confirmed the direction and overall pattern of RNA-seq-derived expression changes. Together, these findings define a unified conserved early survival program in E. coli after chemically distinct photodynamic treatments and identify stress-response modules that may serve as targets for potentiating aPDI. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=126 SRC="FIGDIR/small/744726v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@dbbadaorg.highwire.dtl.DTLVardef@1c85538org.highwire.dtl.DTLVardef@152d699org.highwire.dtl.DTLVardef@18705a6_HPS_FORMAT_FIGEXP M_FIG C_FIG

Foodborne pathogens including Salmonella spp., Escherichia coli and Listeria monocytogenes cause an estimated 600 million illnesses annually. Yet conventional detection methods remain slow, costly, or insufficiently specific for routine food safety surveillance. Phage receptor-binding proteins (RBPs) are attractive recognition elements for biosensors, but their extensive sequence diversity limits reliable computational identification. Here, we present a systematic open-source computational pipeline for identifying and structurally characterising high-confidence RBP candidates from phage genomes targeting these three priority pathogens. The pipeline integrates four stages: deep learning-based RBP prediction, protein structure prediction, structural homology validation, and exploratory molecular docking. Applied to a quality-controlled dataset of 247 complete phage genomes retrieved from the National Center for Biotechnology Information Nucleotide database (31,752 total protein sequences), PhageRBPdetect, built on the ESM-2 protein language model, identified 653 high-confidence RBP candidates. Foldseek structural homology validation against PDB100 confirmed 13 candidates with a structural match probability of 1.0 to known phage adsorption proteins, spanning four structural archetypes. ESMFold-predicted structures showed strong confidence, with a mean model confidence score of 0.89 and a 90.2% prediction success rate. Exploratory rigid-body docking identified YDV08491.1, an E. coli-targeting candidate, as having the most energetically favourable predicted interaction, with a predicted binding energy of -132.3 kcal/mol against OmpF, supporting experimental prioritisation. These candidates structural diversity and predicted host specificity support their future development as phage-based biosensors and biocontrol tools, and this reproducible, accessible pipeline offers a transferable strategy for prioritising RBP candidates in downstream functional studies, pending experimental validation. Author SummaryFoodborne bacterial infections cause an estimated 600 million illnesses every year worldwide, with Salmonella, Escherichia coli, and Listeria monocytogenes among the most significant contributors. Detecting these pathogens quickly and specifically in food supply chains remains a major challenge for global food safety. Bacteriophages viruses that infect bacteria use surface proteins called receptor-binding proteins (RBPs) to recognize their bacterial hosts with remarkable precision, making RBPs promising building blocks for pathogen-specific biosensors. However, the huge sequence diversity of RBPs across phage genomes has made it difficult to reliably identify good candidates computationally. We built an open-source pipeline that combines deep learning, protein structure prediction, and molecular docking to screen phage genomes for high-confidence RBP candidates. Applied to 247 phage genomes targeting the three pathogens above, our pipeline flagged 653 candidate RBPs, of which 13 showed strong structural similarity to known phage adsorption proteins. One candidate, targeting E. coli, showed a particularly strong predicted binding interaction with a bacterial surface protein, making it a priority target for experimental testing. This pipeline gives researchers a reproducible, publicly available strategy for prioritizing phage proteins toward the development of biosensors and biocontrol tools for food safety.

Phage cocktails are promising biocontrol agents against bacterial plant diseases by broadening host range and limiting the emergence of resistant mutants. To date, nine lytic phages with properties suitable for biocontrol have been isolated against Xanthomonas hortorum pv. vitians, the causal agent of bacterial leaf spot of lettuce. Here, a six-phage cocktail was rationally designed based on complementary host ranges, covering 91% of tested vitians strains while maintaining strict phage specificity toward the pathovar. To design a robust biocontrol, three distinct phage infection strategies, identified by transposon insertion sequencing, were combined in a cocktail. The susceptibility determinants were involved in LPS biosynthesis, a modified O-antigen structure, and an outer membrane protein putatively linked to the type I secretion system. As these structures contribute to plant colonization and virulence, phage resistance is expected to impose substantial fitness costs. In growth-chamber experiments, the phage cocktail provided dose-dependent protection, with significant symptom reduction observed across all tested concentrations, from 17% at 106 PFU.mL-1, to 34.7% at 107 PFU.mL-1 (two applications), and up to 66% at 108 PFU.mL-1. In two independent field trials conducted across contrasting growing seasons, weekly applications consistently reduced disease severity by 30%, decreased the proportion of non-marketable lettuce heads by more than 84%, and reduced post-harvest trimming losses from 20.7% to 18.1% in summer and from 17.8% to 14.0% in autumn. These findings provide the first demonstration of a reproducible and effective phage-based biocontrol strategy against Xanthomonas hortorum pv. vitians under field conditions.

During phage infection, phages reprogram their host to secure energy, building blocks for their genome, and proteins, as well as the transcription and translation machinery required to replicate their genome and produce phage particles. This also includes reprogramming the host transcriptome to modify host gene expression and align it with the needs of the phage during infection. In this study, we present a putative early-expressed protein, Gp204 of Mosigvirus AV110, renamed Host transcription modulator (Htm), that has a broad impact on the extended-spectrum beta-lactamase (ESBL)- associated E. coli transcriptome. Overexpression of Htm decreased the growth rate of ESBL-E. coli and caused DNA condensation. Htm is structurally similar to bacterial enhancer-binding proteins, binds ssDNA, and alters the expression levels of over 700 E. coli genes when expressed. The majority of these genes were upregulated and are involved in multiple pathways, such as galactose metabolism and pentose and glucuronate interconversions, which may promote the synthesis of purines, pyrimidines, and histidine, all of which are required for the replication, transcription, and translation of the phage genome. Furthermore, energy production is likely to be upregulated by increased availability of acetyl-CoA, resulting from, among other factors, fatty acid degradation. Htm also downregulated the expression of the structural genes involved in flagellar assembly and multiple two-component systems. In conclusion, Htm could promote phage progeny production by increasing the availability of nucleotides, amino acids, and energy, while inhibiting non-essential processes, such as flagella formation.

The global spread of antimicrobial-resistant (AMR) bacteria represents one of the greatest threats to modern medicine, making the development of novel therapeutic strategies increasingly urgent. Phage therapy, which exploits bacteriophages (phages, viruses that specifically infect and kill bacteria) has regained attention as a therapeutic approach for multidrug-resistant infections. One critical determinant of treatment outcome is the capacity of phages to sustain bacterial growth suppression; however, no metric has previously existed to directly quantify the duration of effective lytic activity. Here, we propose the Sustainability Index (SusI), a novel metric that quantifies both the duration and extent of phage-mediated bacterial growth suppression, which is restricted to the primary lysis period from lysis initiation to resistance emergence. Evaluation of individual phages and two-phage cocktails against both laboratory and clinical isolates of Escherichia coli demonstrated that SusI provides information independent of the Virulence Index, which primarily reflects bactericidal activity during the initial phase of infection, and serves as a complementary metric to the Suppression Index, which may incorporate behavior beyond primary lysis. Cocktails composed of phages targeting different receptors specificities consistently exhibited higher SusI values, consistent with the notion that multifaceted selective pressure delays resistance emergence. Furthermore, in a mouse model of systemic infection established by intraperitoneal administration, cocktails with higher SusI values demonstrated superior therapeutic efficacy. These results confirm SusI as a practical metric for rational phage cocktail design. As phage therapy advances toward clinical implementation, standardized quantitative metrics such as SusI are expected to facilitate evidence-based selection of therapeutic phages across diverse pathogens and infection conditions. ImportanceThe global spread of antimicrobial-resistant bacteria is making bacterial infections increasingly difficult to treat. Phage therapy, which uses bacteriophages (viruses that specifically infect bacteria), has re-emerged as a therapeutic alternative; however, reliable methods to determine in advance which phages will be therapeutically effective remain limited. Current evaluation metrics are well-suited for quantifying how rapidly phages kill bacteria but were not designed to directly measure how long lytic activity is sustained before resistant bacteria emerge. Here, we developed the Sustainability Index (SusI), a novel metric that specifically quantifies the duration of effective bacterial growth suppression. Evaluation of multiple phages and their combinations (cocktails) against both laboratory and clinical bacterial isolates demonstrated that SusI can distinguish phage combinations that existing metrics fail to differentiate. Moreover, in a mouse model of lethal bacterial infection, higher SusI values correlated with improved therapeutic outcomes. SusI has potential as a practical tool for selecting phages with greater likelihood of therapeutic success.

The emerging neonatal bacterial pathogen Paenibacillus thiaminolyticus causes sepsis and postinfectious hydrocephalus, yet few tools are available to study or specifically detect it. We developed fluorescent probes based on cell wall-binding domains (CBDs) from bacteriophage-derived cell-wall hydrolases. CBDs can target structurally conserved cell-wall glycans, making them attractive affinity reagents for bacterial detection. None of the 11 probes we designed labeled intact cells under standard conditions, and we identified a surface layer (S-layer) that prevented access to their cell-wall targets. Brief acidic treatment (pH 2.0) released abundant high-molecular-mass proteins from the cell surface and enabled labeling by five distinct CBD probes, each containing a single C-terminal S-layer homology domain. Mass spectrometry identified the main released protein as an ortholog of the P. alvei SpaA S-layer protein, which we designate SlsA. Across 26 surveyed P. thiaminolyticus genomes, we identified four distinct SlsA variants with 58-79% pairwise amino acid identity, encoded within a conserved cluster homologous to the P. alvei S-layer-associated locus. After either the acidic treatment or a quick flame fixation, the lead probe mGL-BDPt9 labeled six P. thiaminolyticus strains, including three Ugandan clinical isolates, as well as a P. dendritiformis clinical isolate from a US infant, and three additional Paenibacillus species. mGL-BDPt9 also distinguished P. thiaminolyticus from five gram-positive sepsis pathogens in pairwise mixtures and detected it in a five-species suspension. Together, these findings establish the presence of an S-layer in P. thiaminolyticus and provide a rapid fluorescent labeling strategy for multiple Paenibacillus pathogens associated with neonatal paenibacilliosis.

Multispectral imaging is a cornerstone of chemical imaging, with bioluminescence, fluorescence, and phosphorescence imaging underpin much of preclinical and analytical chemical measurements. However, conventional implementations are typically proprietary, costly, and resolve spectral content from the reflectance of a broadband source, without control over the excitation spectrum. This architecture cannot isolate excitation-dependent photophysical processes. Spectral discrimination through sequentially resolved narrowband excitation, detected on a single broadband-sensitive camera, instead enables excitation-dependent fluorescence, phosphorescence, and reflectance measurements not available to such broadband approaches. We describe AURORA-MSI, an open-source multispectral platform that inverts this arrangement with fourteen narrowband LEDs spanning 367-940 nm, a 120-element annular illumination ring with eight independently addressable azimuthal sectors, and a thermoelectrically cooled monochrome CMOS camera. Radiometric calibration, spatial uniformity mapping, and camera noise characterization establish the quantitative measurement foundation. In bioluminescence imaging, AURORA-MSI localized sources in a calibrated tissue-mimicking mouse phantom comparably to a commercial Revvity IVIS Spectrum, detected luciferase-expressing HSJD-GBM1-001 glioblastoma cells across a dilution series, with reduced replicate consistency at the lowest densities, and mapped substrate-free fungal-pathway emission in an intact bioluminescent Petunia hybrida, none requiring photon-counting instrumentation. Time-resolved phosphorescence decay imaging of six inorganic phosphors over 33 minutes found tri-exponential models adequate at early times, while distributed-lifetime models were preferred at extended timescales. Multispectral image-texture features extracted across all fourteen excitation bands discriminated ten pharmaceutical and household powders spanning distinct chemical compositions and, in two cases, distinct formulations of the same compound. Generality beyond these regimes was established through dual-excitation fluorescence fingerprinting of fifteen mineral specimens and wavelength-selective plant-tissue imaging exploiting UV and NIR penetration-depth differences. Excitation-side spectral encoding enables photophysical measurements that detection-side systems with uncontrolled broadband illumination cannot isolate, and the cooled-camera architecture supports weak-signal modalities without photon-counting instrumentation.

Quantitative microscopy of microorganisms increasingly produces large, multidimensional datasets, yet their analysis often depends on fragmented workflows spanning file conversion, segmentation, quality control, fluorescence quantification, tracking, and visualization. Here, we present BactoMate, an open-source, cross-platform graphical user interface that integrates these steps into a unified workflow for microbial image analysis. BactoMate incorporates established segmentation methods and supports both single-file and batch processing. Its modules enable image preprocessing, cell segmentation, morphology-based quality control, fluorescence and foci quantification, single-cell tracking, lineage reconstruction, structured data export, and generation of quality-control and visualization outputs. We demonstrate the applicability of BactoMate across multichannel fluorescence imaging, bacterial swimming assays, microcolony lineage analysis, phage infection assay and a microfluidic time series. All user-configurable parameters are exposed through the interface, are recorded alongside structured outputs and can be loaded for reproducible image analyses across experiments to reduce introduction of bias. By reducing workflow handoffs while preserving parameter control and exportable results, BactoMate enables accessible, reproducible, and scalable quantitative analysis of microbial microscopy data.

BackgroundThe quantification of fungal spores constitutes a fundamental metric in phytopathology, serving as the primary variable for inoculum standardization and being used as a proxy for disease severity. Historically, spore quantification has relied on manual hemocytometry, which remains the most precise counting process to date, where chambers such as the Malassez slide are used to count a subsample of the inoculum. However, this method applied manually is highly labor-intensive, time-consuming, and can be prone to operator-dependent variability. To overcome these limitations, we introduce MIRA (Microscopy Image Recognition & Analysis), a novel open-source software integrating You Only Look Once (YOLO) deep learning algorithms. Featuring a user-friendly graphical interface, MIRA is adaptable to multiple camera systems and supports advanced object detection models, including YOLOv11 and YOLOv26. ResultsWe demonstrate that MIRA can be used to accurately detect and count spores from several phytopathogenic fungi, automatically measure spore surface area, and to differentiate spores across different genera. In an exhaustive comparative analysis using Pyricularia oryzae spores as an example, MIRA was benchmarked against manual gold-standard counting slides (Malassez and Kova) and indirect spectrophotometric methods (SPARK). The P. oryzae model loaded via MIRA achieved a strong correlation (R = 0.96) with manual gold standards while reducing processing time by over 90% for high-concentration samples (10 spores/mL). Beyond this benchmark, we also successfully tested specific YOLO models designed to recognize macro- and microconidia of Fusarium oxysporum f. sp. cubense, a model for Pseudocercospora fijiensis, and a single multiclass model capable of identifying six different rice pathogenic fungi. We provide comprehensive tutorials for operating the software and training custom detection models for free using Roboflow and Google Colab. MIRA is available both as open-source Python code and as standalone executables for Windows and Linux. ConclusionsMIRA provides a rapid, accurate, and highly reproducible alternative to manual spore counting, effectively removing a major bottleneck in phytopathology workflows. By combining advanced YOLO-based deep learning with an accessible interface and comprehensive training resources, MIRA makes accessible automated image analysis for researchers without programming expertise. Moreover, MIRA drastically improves the efficiency of high-throughput disease phenotyping and can be adapted for a wide range of microscopic quantification tasks across various biological disciplines.

BackgroundDetection of rare mycobacterial genotypes, including those associated with antibiotic resistance or population heterogeneity is important for diagnostic, therapeutic and research applications. This depends on efficient recovery of genomic DNA (gDNA) from sampled populations, a challenging requirement in paucibacillary clinical materials. Mycobacteria have uniquely lipid-rich, structurally robust cell envelopes which resists cell lysis by conventional methods. Here, we characterize mycobacteriophage D29-mediated lysis at the single-cell level, evaluating its utility as a biological lysis strategy for mycobacterial DNA isolation, benchmarked against the standard cetyltrimethylammonium bromide (CTAB) extraction method. MethodsConditions for mycobacteriophage D29 infection of Mycobacterium smegmatis (Msm) were established, and single-cell phage adsorption and phage-mediated lysis visualized through live-cell time-lapse fluorescence microscopy (FM). A mycobacteriophage D29-based lysis method was applied to both Msm and M. tuberculosis (Mtb), and extraction efficiencies compared with the standard CTAB method. Cell lysis efficiency was quantified by colony forming units (CFU), flow cytometry (FC) and FM; DNA yield was determined by quantitative polymerase chain reaction (qPCR) and droplet digital PCR (ddPCR). ResultsMycobacteriophage D29 adsorption was observed at the poles and septa of individual mycobacterial cells. Phage infection was associated with loss of cytoplasmic green fluorescence protein (GFP) reporter protein, with uptake of a cell death marker propidium iodide (PI). Mycobacteriophage D29 infection resulted in a marked loss of cell viability, with >6log10 reduction in CFU, and cell lysis efficiencies calculated as 93.3% (FC) and 96.8% (FM). Molecular quantification (qPCR and ddPCR) indicated that the mycobacteriophage-based lysis achieved between 4- to 7-fold greater gDNA yields in Msm and between 3- to 12-fold greater gDNA yields in Mtb H37Ra compared with the CTAB method. Notably, gDNA extraction efficiencies in both mycobacterial species exceeded 92% in low-biomass samples containing approximately 100, 175 and 320 bacilli. ConclusionThese results demonstrate the utility of the mycobacteriophage D29-based method for improved DNA extraction yields from mycobacteria through direct lysis of individual bacilli, with performance suited to low-biomass samples. SummaryRecovering genomic DNA (gDNA) from low numbers of mycobacteria is a persistent bottleneck for diagnostics and genomic studies, because the lipid-rich mycobacterial envelope resists conventional lysis. Here we show that mycobacteriophage D29 provides an efficient, biologically selective route to mycobacterial DNA. Leveraging single-cell live imaging, we reveal that phage D29 adsorbs preferentially at the poles and septa of individual cells, and that infection is heterogeneous and asynchronous, progressing from envelope permeabilization to loss of viability. Applied as an extraction method and benchmarked against the standard cetyltrimethylammonium bromide (CTAB) protocol, phage D29-mediated lysis recovered 4- to 7-fold more gDNA in Mycobacterium smegmatis (Msm) and 3- to 12-fold more in Mycobacterium tuberculosis (Mtb). Critically, extraction efficiency exceeded 92% in both species in low-biomass samples of approximately 100, 175 and 320 bacilli, where CTAB performed poorly (<20% efficiency). These findings support phage-mediated lysis as a quantitative, near-complete DNA-recovery method that outperforms conventional extraction precisely in the paucibacillary regime of greatest clinical relevance and demonstrate the value of single-cell interrogations in building towards precision tools to engage the mycobacterial cell.

O_LIDrought and warming can disrupt soil microbial processes and ecosystem functioning. Although soil microorganisms can exhibit physiological adjustments to drought, it remains unclear how they allocate resources between extracellular resource acquisition, potential oxidative metabolism, and carbon storage during drought and recovery, particularly under constant warming and/or heat waves. C_LIO_LIHere, we tested the effects of drought on microbial resource allocation strategies across warming regimes during the resistance and recovery phases. We performed a full-factorial outdoor mesocosm experiment combining drought with constant warming and periodic heat waves, applied individually and in combination. We measured the potential activities of extracellular enzymes as proxy for the acquisition of microbial resources, the activity of dehydrogenase as a proxy for the potential active oxidative metabolism, and microbial glycogen pools as a proxy for carbon storage. We also quantified drought legacy effects by measuring microbial functioning before the new drought treatments, capturing the influence of the drought imposed in the previous year. C_LIO_LIDuring the resistance phase, dehydrogenase activity and glycogen pools remained stable, despite reduced extracellular enzyme production, while enzyme allocation shifted towards oxidative enzymes associated with acquisition of recalcitrant C in warming regimes. One month after rewetting, all microbial proxies no longer differed from the control soil moisture conditions. Drought legacy effects were observed in extracellular enzymes, dehydrogenase activity, and glycogen pools, with glycogen exhibiting the strongest legacy effect. C_LIO_LIWe conclude that the asymmetrical responses of extracellular resource acquisition and internal C storage to drought and warming may function as strategies for microbial survival in increasingly variable climates. C_LI

Bacteriophage genomes contain large fractions of uncharacterized genes, motivating high-throughput functional screens to illuminate their roles in host interaction and cytotoxicity. Here, we performed a genome wide overexpression assay for a Pseudomonas putida KT2440 infecting phage, Emajogi, and identified eight cytotoxic genes that reduce host growth under both basal and induced expression. We show that these proteins are conserved across phages that infect a diverse set of hosts. The most cytotoxic gene identified was a hypothetical protein (gp18) with no predicted functional domains. Transcriptomic profiling revealed that overexpression of gp18 caused a pronounced metabolic remodeling of the cell, likely shifting cell resources to phage production. Overall, this genome wide screen provides information about phage genes that were previously unannotated that can support biotechnology and novel antimicrobial development.