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Gordeeva, J.

Publications and source records attributed to Gordeeva, J..

3 recordsLinked to original sources

Intracellular barriers and receptor masking limit success of a Pseudomonas aeruginosa clinical phage family

Bacteriophage therapy is needed to treat antibiotic resistant infections; however, when a clinical isolate resists a given phage, it is often unclear why. It is therefore currently unknown how to rationally fortify phage therapies to circumvent a priori resistance. Using a family of broad host range therapeutic Pseudomonas aeruginosa phages (Pbunaviruses), we show that cell surface receptor masking and intracellular defenses are both common barriers in distinct clinical isolates. In some cases these barriers can be bypassed by intrafamily phage engineering. Using unbiased genome-wide CRISPRi screens, we reveal that the broadly conserved L-Rhamnose in the core polysaccharide is the receptor for Pbunavirus family. This molecule is often masked by diverse O-antigen structures. In other isolates with the L-Rha receptor accessible, internal defense mechanisms commonly prevent Pbunavirus DNA replication. A single anti-defense locus often encoding 8-11 different genes within the Pbunavirus family is required for optimal host range, providing anti-defense genes that enable replication of both Pbunavirus phages and phages of other families. Our work demonstrates the importance of both internal and surface defense mechanisms in clinical isolates causally antagonizing a commonly used phage therapeutic and presents phage engineering strategies to circumvent a priori resistance.

microbiology↗

A virion protein of an archaeal virus inhibits a Type V BREX defense system in Haloarcula hispanica

Bacteriophage Exclusion (BREX) systems are a diverse family of bacterial and archaeal defense mechanisms defined by two conserved genes encoding a putative alkaline phosphatase BrxZ (PglZ) and an ATPase BrxC (PglY). Here, we characterize a Type V BREX system from the archaeon Haloarcula hispanica. Similar to bacterial Type I BREX systems, host-virus discrimination relies on methylation of specific non-palindromic DNA motifs. Notably, the H. hispanica BREX locus encodes two methyltransferases, BrxX1 and BrxX2, which independently target distinct motifs (GTAYCCG and GACCCC). The system protects H. hispanica against three of seven tested archaeal viruses. However, two related viruses, SH1 and HHIV-2, despite encoding multiple BREX target sites, escape BREX-mediated defense. We demonstrate that a large virion protein, VP1, encoded by these viruses inhibits the BREX system, as mutant viruses carrying partial deletions of VP1 lose resistance to the host defense. Together, these findings provide the first characterization of a Type V BREX system and demonstrate that archaeal viruses can counteract BREX through virion-associated anti-defense proteins.

molecular biology↗

FMAGJ: Fluorescence Microscopic Astrocyte Gap Junction Images Dataset

This work introduces a novel and specialized dataset of high-resolution fluorescence microscopic images focused on astrocytic gap junctions, aiming to get insights into intercellular communication in both healthy and pathological brain conditions. The dataset includes 20 z-stack image series--10 from human glioblastoma tissue and 10 from healthy rat brain tissue--each containing between 22 and 104 optical slices. These images were acquired using standardized protocols following immunofluorescence labeling with antibodies against connexin 43 (Cx43), enabling visualization of gap junction localization at the subcellular level. The dataset is tailored to support detailed morphological and quantitative analyses of gap junction networks, featuring metadata including species and localization of possible gap junctions in images provided by bounding boxes and image masks. Its structure facilitates comparative studies across physiological states and species, enhancing translational and evolutionary perspectives on astrocytic connectivity. Given the labor-intensive nature of manual gap junction quantification, this dataset serves as a resource for the development of machine learning tools capable of automating the detection and analysis of Cx43-positive signals. CCS CONCEPTSComputing methologies[~]Computer vision problems[~]Object detection * Applied computing[~]Life and medical sciences[~]Computational biology/Molecular structural biology * Software and its engineering[~]Software notations and tools[~]Software libraries and repositories

cancer biology↗