Biology subjects

Mutalik, V. K.

Publications and source records attributed to Mutalik, V. K..

At least 19 recordsLinked to original sources

bioRxiv2026

Genome-wide CRISPRi mapping of mycobacteriophage interaction determinants in Mycobacterium smegmatis mc2155

Bacteriophages are highly specific predators of bacterial hosts, but the molecular mechanisms governing their entry across the structurally complex mycobacterial cell envelope remain poorly defined. Utilizing a genome-wide CRISPR interference library in the model organism Mycobacterium smegmatis against a phylogenetically representative collection of 70 mycobacteriophages, we mapped the functional architecture of host susceptibility determinants. This parallelized genetic screen revealed a spatial continuum of infection requirements spanning from outer leaflet surface structures down to deep cytoplasmic machinery. The four major outer membrane Mycobacterium smegmatis porins (Msp) emerged as the dominant candidate receptor family for 46 diverse phages, representing the first protein receptors identified within this group. Interrogating the asymmetric outer bilayer also implicated cell envelope glycolipids as candidate receptors for 14 phages, resolving into glycopeptidolipid sub-lineages. Beneath the mycomembrane, arabinogalactan functions as a candidate secondary receptor for 5 phages, while the inner membrane lipid transporter MmpL11 and the global nucleoid-associated protein Lsr2 represent determinant factors for 14 and 31 phages respectively. While physical deletions of major porins trigger spontaneous regulatory pathways that upregulate silent backup paralogues, acute transcriptional knockdowns circumvent suppressor accumulation, revealing unmasked single-gene dependencies. Structural analysis demonstrated that host determinant usage decouples entirely from whole-genome viral phylogeny, indicating that standard phylogenetic groupings fail to predict surface recognition profiles. Ultimately, mapping this host interactome reveals an evolutionary strategy where phages target highly redundant or abundant host machinery to exploit fixed physiological liabilities, presenting a robust molecular blueprint for the rational engineering of escape-resistant therapeutic phage cocktails.

microbiology↗

bioRxiv2026

Genome-wide characterization of host factors involved in single-stranded RNA and DNA phage infection pathways

Single stranded RNA (ssRNA) and single stranded DNA (ssDNA) bacteriophages represent a key component of the global virome, yet the host genetic networks supporting their infection cycles remain poorly understood. Here, we present a comprehensive, genome-wide mapping of the genetic landscape regulating infection cycles for F pilus-dependent ssRNA and ssDNA phages in Escherichia coli. Genetic screens across ssRNA phages spanning all four genogroups of the Leviviricetes revealed a highly conserved network of host dependencies, with the notable exception of the F plasmid gene traD. While primary structural receptor components and dsbA mediated disulfide bond formation are universally required across all lineages to ensure F pilus integrity, traD exhibits a strict genogroup-specific requirement during entry, showing variable essentiality across different viral groups despite sharing an identical primary receptor. Our gene dosage screens revealed that an elevated copy number of the hslU protease or the RNA chaperone stpA restricts infection, identifying clear genetic barriers that can perturb the viral life cycle. Parallel assays with filamentous ssDNA phages produced host factor profiles consistent with published literature, while revealing additional variations in host dependency. These screens confirmed that ssDNA phages strictly rely on the host TolQRA complex for entry downstream of pilus engagement. The assays tracked prominent negative fitness signatures across homeostatic clusters, highlighting how the physiological burden of continuous, non-lytic virion extrusion strains the host envelope. Finally, this comparative approach traced the selectivity of our isolation host (E. coli HSF) to a horizontally acquired capsule architecture from Klebsiella. This surface shield excludes a large panel of double stranded DNA phages isolated on diverse E. coli strains, while allowing virions from ssDNA and ssRNA phages to engage the extended F pilus and bypass the barrier via native pilus retraction. Together, this work provides a systematic, class-wide map of single stranded phage-host interactions, bridging classical genetics with modern viral discovery while establishing a robust host platform to access uncultured viral diversity and a functional blueprint to design next generation diagnostics, protein antibiotics, and biocontrol tools to halt horizontal gene transfer.

microbiology↗

bioRxiv2026

Chemical stressors differentially induce prophage replication in Acinetobacter baumannii strains

Prophages are prevalent genomic elements that profoundly shape microbial communities by controlling host bacterial populations through lysis or enabling genetic recombination via transduction. Standard induction protocols rely heavily on DNA-damaging agents like mitomycin C, failing to capture the complex chemical landscapes bacteria encounter in natural and clinical settings where diverse environmental insults trigger excision. Furthermore, the regulatory variations governing polylysogenic hosts containing multiple co-habiting prophages under identical stressors remain largely uncharacterized. In this study, we surveyed a panel of five clinical Acinetobacter baumannii strains containing zero to four resident prophages against a library of 57 diverse chemical stressors. We demonstrate that chemical treatments, including distinct classes of antibiotics, drive differential prophage induction patterns across different host backgrounds. This could lead to a greater understanding of the importance of prophages in antibiotic treatment regimes.

microbiology↗

bioRxiv2026

PhageTAILor leverages machine learning for phage tail-like elements detection and classification in plant-associated bacteria

Phage tail-like elements (PTEs) -- tailocins, bacterial type VI secretion systems (T6SS), and extracellular contractile injection systems (eCIS) -- are contractile nanomachines that bacteria use to kill their neighbors and compete within their micro-ecosystems. PTEs help shape microbial community composition. Most PTE detection tools only detect a single PTE class. Moreover, most tailocin detection methods are largely restricted to Pseudomonas, leaving a key part of tailocin diversity uncharacterized. In this work, we present PhageTAILor (https://github.com/hjcho-bio/PhageTAILor), an integrative and fully automated pipeline that detects and classifies prophages and 3 PTE classes from bacterial genomes. PhageTAILor combines a 6-detector homology-based candidate search (geNomad, tail-gene, PHROGs-tail, SecReT6, eCIStem, and a divergence-tolerant tail-HMM detector) with a LightGBM classifier comprising 1 multiclass and 3 binary heads, trained on 6,501 bacterial genomes carrying 13,082 prophages and PTEs. A phylogeny-free feature matrix used in our model keeps predictions reproducible between model construction and user inference. PhageTAILor performs strongly at the genome level and generalizes beyond its Pseudomonas-rich training set. On a 76-strain cross-clade benchmark, PhageTAILor detected tailocins at F1 = 0.955. Furthermore, it identified 12 of 13 experimentally validated tailocins spanning five genera versus 2 of 13 for a Pseudomonas-restricted tool TattleTail. PhageTAILor also demonstrated sensitivity equivalent to viral detection tool geNomad while avoiding its higher false-positive rate. Applied to 7,925 plant- and soil-associated bacterial isolates, PhageTAILor showed that prophages in the phyllosphere and tailocins in plant-associated bacteria, whereas eCIS are enriched in soil. PhageTAILor is distributed as an open-source, modular pipeline with a command-line interface.

microbiology↗

bioRxiv2026

A comprehensive phage-bacteria interaction atlas links phage lineage and capsule serotype to genome-guided machine learning prediction in Klebsiella pneumoniae

Klebsiella pneumoniae is a WHO critical-priority pathogen for which strain-specific bacteriophages are being explored as precision antimicrobials, yet rapid phage-host matching remains a major barrier to therapeutic deployment. We constructed a comprehensive interaction atlas comprising 84 taxonomically diverse phages and 101 globally sourced, clinically representative K. pneumoniae strains, including multidrug-resistant isolates. Systematic pairwise profiling produced 8,484 interaction measurements, of which 2,656 (31.3%) scored positive for bacterial clearance. Genus was the dominant phage-side determinant of host range, while capsule K-serotype was the strongest host-side determinant of susceptibility; aggregate defense, prophage, plasmid, and antimicrobial-resistance features contributed comparatively little. A genome-guided machine learning model predicted interactions without curated host annotations (AUROC, 0.882; AUPR, 0.765), outperforming a model based only on phage genus and K-serotype and modestly exceeding a curated genomic baseline. The model recovered capsule- and lipopolysaccharide-biosynthesis genes, canonical receptors and defense-associated features as major predictors using SHAP analysis. Feasibility tests of expert- and model-selected cocktails exposed a translational constraint. Although all formulations suppressed growth in vitro, only the specific cocktail whose phages replicated robustly within the murine gut reduced colonization, suggesting in vivo amplification rather than predicted host range as the limiting factor for therapeutic efficacy. Together with the activity of a model-selected cocktail built for an isolate completely excluded from training, these results provide a species-wide resource for K. pneumoniae phage matching and support a hybrid workflow combining genome-based ranking with targeted phenotypic validation.

microbiology↗

bioRxiv2026

Surface architecture of the bacterial envelope determines phage adsorption route in pathogenic Escherichia coli O157:H7

The outermost surface layers of Gram-negative bacteria determine phage access to terminal receptors, yet their genetic basis has been mapped almost exclusively in laboratory strains that lack them. Here we apply genome-wide RB-TnSeq fitness profiling to four Escherichia coli O157:H7 strains from distinct phylogenetic clades sharing the O157 O-antigen, using 38 phages with terminal receptors previously mapped in E. coli K-12 strain. RB-TnSeq fitness landscapes across all four pathogenic backgrounds were mostly similar, and dominated by surface-associated loci, including the gfc-etk group 4 capsule operon, O-antigen biosynthesis genes, LPS core assembly genes and outer membrane proteins. Disruption of gfc-etk abolished infection in 11 genetically diverse myoviruses, establishing the O-antigen capsule as a widespread required primary recognition substrate. O-antigen loci generated two classes of fitness score patterns. For 10 phages, disruption increased infectivity, indicating it is a barrier to receptor access; for 3 others, disruption abolished infectivity, demonstrating it can also be a primary recognition substrate. Outer membrane protein receptor identity was conserved across laboratory and pathogenic backgrounds, with the same proteins recognized in both K-12 and O157:H7, while glycan layer state determines whether these receptors are reached. These results demonstrate that outer surface glycan layers can act as primary and optional recognition substrates for phage infection, or as physical barriers preventing terminal receptor access. Extending the ability to probe phage-targeted receptors beyond outer membrane proteins provides a framework for incorporating glycan layer state into predictive models of phage-host interactions.

microbiology↗

bioRxiv2026

Targeted DNA nicking enables efficient, single-step and counterselection-free editing of bacteriophage genomes

Genetic manipulation of bacteriophages is essential for interrogating phage biology and advancing antimicrobial therapies. However, current genome editing approaches can be inefficient, require multiple steps, or drastically reduce phage titers. Here, we show that targeted DNA nicking enables template-mediated editing of phage genomes in one step without reducing phage titers. Using T7 phage, we show that Cas9-mediated nicking achieved up to 100% recombination across multiple loci, including substitutions and deletions of up to 200 bp and insertions of up to 500 bp, all while preserving phage titers. Editing in T7 was RecA-independent and extended to other phages. Leveraging high titers, we engineered a T7 library of over 440,000 tail-fiber mutants, with isolated mutants restoring infection of two LPS-deficient Escherichia coli hosts by shifting recognition to core LPS components. Overall, DNA nicking is a simple and distinct editing strategy that can advance phage genome engineering, genetic interrogation, and antimicrobial development.

synthetic biology↗

bioRxiv2026

Comprehensive interaction profiling and machine learning prediction of bacteriophage infectivity across clinically diverse Pseudomonas aeruginosa

The rise of antibiotic-resistant bacterial infections has driven renewed interest in bacteriophage therapy, where viruses that specifically kill bacteria are used as targeted antimicrobials. Pseudomonas aeruginosa, a WHO critical-priority pathogen that causes severe infections in hospitalized and immunocompromised patients, presents a major challenge for phage therapy because of its extraordinary genetic diversity. Phages effective against one bacterial strain often fail against others, and existing cross-resistance-profiling approaches require iterative empirical testing of each new patient isolate. To establish a genome-based framework for rapid phage-isolate matching, we assembled a collection of 95 genomically diverse P. aeruginosa phages representing 20 genera and tested each against 99 genetically diverse clinical isolates, generating 9,405 infection outcome measurements. Bacterial O-antigen serotype emerged as the dominant determinant of strain susceptibility, while defense systems, anti-defense systems, and prophage burden contributed smaller strain-specific effects. The full curated multivariate model explained 47% of strain-susceptibility variance. Machine-learning models integrating these features and pangenome-derived gene clusters reached a per-strain AUROC of 0.86. In an in vivo proof-of-concept test against a single held-out strain, the ML-designed cocktail produced a [~]12-fold greater median CFU reduction than the expert-designed cocktail (q = 0.045), with both cocktails substantially reducing burden relative to the untreated control ([~]113-fold for ML, [~]9-fold for CG; both q < 10{square}3). SHAP analysis of the model identified bacterial surface-architecture genes (LPS biosynthesis, outer membrane proteins, type IV pili) as the dominant predictors, with defense-system content modulating which specific phages succeed against a strain rather than uniformly damping susceptibility. Together, these results establish a genome-based framework for predicting phage susceptibility in genetically diverse clinical isolates.

microbiology↗

bioRxiv2026

Enabling the prediction of phage receptor specificity from genome data

Predicting which receptor a phage binds to from genome sequence alone has remained an intractable challenge, principally because the experimental phenotypic data required to train and validate predictive models have not been available at sufficient scale. Here we address this by conducting 1,050 genome-wide genetic screens across 255 taxonomically diverse Escherichia coli dsDNA phages, assigning host receptors to 193 phages across 19 receptor classes. Comparative genomics and AlphaFold3 structural modelling resolved the sequence determinants of specificity to defined receptor-binding protein domains and individual residues. Machine learning models trained on this dataset predicted host receptor identity from phage genome sequence alone without prior annotation of receptor-binding genes, achieving perfect precision and greater than 80% recall on 49 independently validated phages, and yielding predictions for 1,060 of 1,875 E. coli phage genomes in NCBI. Domain swaps redirected receptor specificity as predicted, and a single amino acid substitution proved both necessary and sufficient to switch recognition between two distinct porins. These results demonstrate that systematic phenotyping at scale makes sequence-based prediction of molecular interaction specificity tractable, with direct implications for phage-based medicine, microbiome engineering and the broader challenge of inferring host-pathogen interaction outcomes from sequence.

microbiology↗

bioRxiv2026

Cross-family and phage-specific gene requirements for Klebsiella infection revealed by scalable RB-TnSeq genetic screens

Bacteriophages are being cataloged at an accelerating pace and are recognized as key players in nutrient and energy cycling across ecosystems. Yet the bacterial genetic determinants that govern phage-host specificity and infection success remain poorly understood, particularly in clinically and ecologically important genera such as Klebsiella where prior receptor characterization has been almost entirely limited to capsulated strains. Here we used a randomly barcoded, genome-wide, loss-of-function transposon mutant library (RB-TnSeq) of Klebsiella sp. M5al, a naturally acapsular, nitrogen-fixing rhizobacterium, to generate the first systematic, cross-family map of phage receptor gene dependencies in Klebsiella. Challenging the library against 25 double-stranded DNA phages spanning five families in 213 parallel assays, we identified 42 bacterial genes associated with phage infection, of which 15 had no prior association with phage infection in any bacterial system. Disruption of surface receptor biosynthesis genes conferred cross-resistance across multiple phage families, while intracellular gene disruptions had predominantly phage-specific effects. Clonal validation of eight genes confirmed LPS outer core biosynthesis genes as primary receptor determinants alongside additional host factors spanning outer membrane transport, cofactor biosynthesis, and two-component signaling. Comparative analysis across all 25 phages revealed that phage genus rather than family is the stronger predictor of host gene dependency profiles, a finding with direct implications for the functional annotation of uncharacterized phage isolates and rational phage cocktail design. Together, these findings provide a community resource for linking phage genomic diversity to functional host interaction space in this ecologically and clinically important genus. Author SummaryBacteriophages, or phages, are viruses that infect bacteria and play central roles in shaping microbial communities across ecosystems. Despite their ecological importance, the bacterial genes that determine infection outcomes remain poorly understood. Using a scalable barcoded transposon sequencing (RB-TnSeq) approach, we mapped host gene requirements for infection by 25 diverse phages of Klebsiella sp. M5al, a soil-associated plant-growth-promoting bacterium. We identified 42 bacterial genes associated with phage infection, spanning surface receptors, transcriptional regulators, and metabolic and protein-folding pathways. Infection strategies broadly clustered by phage genus and family, while phage-specific differences arose primarily in intracellular processes such as transcription and protein folding. These findings reveal both conserved and phage-specific host interactions that define infection strategies and establish a scalable framework for linking phage genomic diversity to function, with practical implications for predicting phage host range, designing phage cocktails for therapy, and understanding phage-driven dynamics in natural microbial communities.

microbiology↗

bioRxiv2026

Discovery, induction, and screening of prophages in clinical Acinetobacter baumannii isolates

BackgroundAcinetobacter baumannii is a common bacterial pathogen in nosocomial infections. It has become one of the greatest threats to human health for its growing resistance to last resort antibiotics, which has led to a revival of phage therapy as a potential treatment. However, conventional methods for isolating A. baumannii-infecting phages are labor-intensive and often unsuccessful. MethodsOur approach involves a computational pipeline to identify temperate phages (prophages) integrated into A. baumannii genomes, followed by mitomycin C (MMC) induction of those strains to screen for active prophages. ResultsHere we show a prophage analysis for nearly 900 A. baumannii genomes. We observed MMC-triggered excision of nine prophages from eight A. baumannii strains by PCR and sequencing. Further we show four prophage form virions detectable by transmission electron microscopy, and two which can plaque on other A. baumannii isolates. ConclusionThis work demonstrates the utility and diversity of prophages for further development as therapeutics for antibiotic resistant A. baumannii.

microbiology↗

bioRxiv2025

Phylogeny-agnostic strain-level prediction of phage-host interactions from genomes

Bacteriophages offer promising alternatives to antibiotics for treating drug-resistant infections and engineering microbiomes, but applications are limited by inability to select phages infecting specific bacterial strains. Selecting suitable phages requires either one-to-one experimental assays or strain-level predictions of phage-host interactions. Existing computational approaches either predict host taxonomy at broad ranks unsuitable for strain-level targeting or require species-specific mechanistic knowledge limiting generalizability. Here, we present a phylogenyagnostic machine learning framework predicting strain-level phage-host interactions across diverse bacterial genera from genome sequences alone. Systematically optimizing the workflow over 13.2 million training runs across six datasets (115,037 interactions, 949 bacterial strains, 518 phages), we achieved performance matching species-specific methods (AUROC 0.67-0.94) while eliminating phylogenetic constraints. Comprehensive feature engineering identifies biologically interpretable genetic determinants while minimizing overfitting in sparse, imbalanced datasets. Experimental validation through 1,240 novel interactions confirmed generalizability (AUROC 0.84), while genome-wide RB-TnSeq screens verified that 68.6% of experimentally identified infection mediators were captured computationally, including receptors and cell wall biosynthesis pathways. Model-guided cocktail design achieved up to 97.5% bacterial coverage with five phages, and up to a 3.1-fold improvement in single-phage selection over promiscuity-based selection. This platform enables rational phage therapy design and precision microbiome engineering with applications in combating antimicrobial resistance across clinical, agricultural, and industrial contexts.

microbiology↗

bioRxiv2025

Surviving phage attack dynamically regulates bacterial immunity to defeat counterdefenses

Transcriptional repressors with ligand-responsive WYL domains control diverse bacterial defense systems, yet the natural cues driving derepression and the physiological rationale for dynamic regulation in native host-phage contexts remain unknown. Here, we show that restricted phage infection, where defense clears a primary attack, serves as a natural cue for WYL-mediated derepression in Vibrio cholerae. Although not required to block the initial infection, this response increases defense protein abundance, shifting host-phage stoichiometry and priming surviving bacteria to overwhelm phage-encoded counterdefenses in subsequent attacks. We also find that restricted infection co-induces an unlinked anti-plasmid defense via its own WYL repressor, showing that parallel WYL sensors coordinate a broader immune response without regulatory crosstalk. In contrast, productive phage infection triggers horizontal transfer of the defense-encoding mobile element, ensuring its persistence in the population. Together, our work reveals that infection fate dictates divergent outcomes for the expression and dissemination of bacterial immunity.

microbiology↗

bioRxiv2025

Droplet-based Random Barcode Transposon-site Sequencing (Droplet RB-TnSeq) to characterize phage-host interactions

Bacteriophages (phages), the most abundant self-replicating entities on Earth, are central to microbial ecology and hold promise as therapies against antibiotic-resistant pathogens. However, the molecular determinants of phage adaptation to hosts remain poorly defined. While bulk genetic screens such as transposon sequencing are high throughput, running all mutants in mixed populations biases outcomes toward phage receptor discovery. Competition among resistant mutants and the escalating multiplicity of infection (MOI) from additional phages released from lysed cells often mask moderately acting host factors--such as inner-membrane and energy-transduction systems supporting DNA entry, surface modifiers, and regulators of host defense. To overcome these limitations, we developed droplet-based random barcode transposon-site sequencing (Droplet RB-TnSeq), which encapsulates single barcoded mutant cells with defined phage titers. Applying this method to Escherichia coli infected with phages T4 and N4, we reproducibly recovered known determinants (ompC for T4 and nfrA/B for N4) and identified additional contributors, including membrane proteins, polysaccharide modifiers, signaling modules, and several uncharacterized genes. Notably, mutations in chbR/C/F, ygaZ/H, and yfbO/L were found to confer resistance to N4, validated by plaque assays and complementation. Droplet RB-TnSeq thus enables genome-wide dissection of host factors beyond receptor-level interactions under well-controlled infection conditions.

microbiology↗

bioRxiv2025

Cross-species phenotypic profiling uncovers functional determinants of bacterial cold shock adaptation

Temperature shifts impose broad physiological stress, requiring precise and dynamic regulatory programs to restore cellular homeostasis. While the heat shock response is well characterized, the mechanisms underlying cold shock response (CSR) remain less understood. To identify genes critical for cold adaptation, we applied transposon sequencing (Tn-seq) to monitor mutant fitness across the full course of CSR and sustained low-temperature growth in two mesophilic bacteria, Escherichia coli and Bacillus subtilis. In B. subtilis, phenotypic profiling revealed a temporally structured program: membrane fluidity and cell wall remodeling were most critical in the early stage of CSR, whereas post-transcriptional regulation became essential during late-stage recovery to reprogram gene expression and restore growth. Cross-species comparison uncovered both conserved and species-specific mechanisms, with RNA metabolism and ribosome/translation regulators playing broad roles. Specifically, we identified a conserved synergy between two ribosomal RNA methyltransferases, RsmA and RsmH, in promoting cold adaptation. In B. subtilis, mutants lacking these enzymes exhibited significant delay in translation recovery following cold-induced global inhibition. Together, these findings provide a comparative, systems-level view of bacterial cold adaptation and establish a framework for exploring stress responses in pathogens and extremophiles.

microbiology↗

bioRxiv2025

Genome editing of phylogenetically distinct bacteria using portable retron-mediated recombineering

Advanced genome editing technologies have enabled rapid and flexible rewriting of the Escherichia coli genome, benefiting fundamental biology and biomanufacturing. Unfortunately, some of the most useful technologies to advance genome editing in E. coli have not yet been ported into other bacterial species. For instance, the addition of bacterial retrons to the genome editing toolbox has increased the efficiency of recombineering in E. coli by enabling sustained, abundant production of ssDNA recombineering donors by reverse transcription that install flexible, precise edits in the prokaryotic chromosome. To extend the utility of this technology beyond E. coli, we surveyed the portability and versatility of retron-mediated recombineering across three different bacterial phyla (Proteobacteria, Bacillota and Actinomycetota) and a total of 15 different species. We found that retron recombineering is functional in all species tested, reaching editing efficiencies above 20% in six of them, above 40% in three of them, and above 90% in two of them. We also tested the extension of the recombitron architecture optimizations and strain backgrounds in a subset of hosts to additionally increase editing rates. The broad recombitron survey carried out in this study forms the basis for widespread use of retron-derived technologies through the whole Bacteria domain.

bioengineering↗

bioRxiv2024

Insights into the role of root exudates in bacteriophage infection dynamics

Bacteriophages impact soil bacteria through lysis, altering the availability of organic carbon and plant nutrients. However, the magnitude of nutrient uptake by plants from lysed bacteria remains unknown, partly because this process is challenging to investigate in the field. In this study, we extend ecosystem fabrication (EcoFAB 2.0) approaches to study plant-bacteria-phage interactions by comparing the impact of phage-lysed and uninfected 15N-labeled bacterial necromass on plant nitrogen acquisition and rhizosphere exometabolites composition. We show that grass Brachypodium distachyon derives some nitrogen from amino acids in uninfected Pseudomonas putida necromass but not from virocell necromass. Additionally, the bacterial necromass elicits the formation of rhizosphere exometabolites, some of which (guanosine), alongside tested aromatic acids (p-coumaric and benzoic acid), show distinct effects on bacteriophage-induced lysis when tested in vitro. The study highlights the dynamic feedback between bacterial necromass and plants and suggests that root exudate metabolites can impact bacteriophage infection dynamics.

plant biology↗

bioRxiv2023

Genome-wide Characterization of Diverse Bacteriophages Enabled by RNA-Binding CRISPRi

Bacteriophages constitute one of the largest sources of unknown gene content in the biosphere. Even for well-studied model phages, robust experimental approaches to identify and study their essential genes remain elusive. We uncover and exploit the conserved vulnerability of the phage transcriptome to facilitate genome-wide protein expression knockdown via programmable RNA-binding protein dRfxCas13d (CRISPRi-ART) across diverse phages and their host. Establishing the first broad-spectrum phage functional genomics platform, we predict over 90 essential genes across four phage genomes, a third of which have no known function. These results highlight hidden infection strategies encoded in the most abundant biological entities on earth and provide a facile platform to study them.

microbiology↗