Bacterial competition systems share a domain required for inner membrane transport of the nuclease bacteriocin pyocin G

Bacteria exploit a variety of attack strategies to gain dominance within ecological niches. Prominent amongst these are contact-dependent inhibition (CDI), type VI secretion (T6SS) and bacteriocins. The cytotoxic endpoint of these systems is often the delivery of a nuclease to the cytosol. How such nucleases translocate across the cytoplasmic membrane of Gram-negative bacteria is unknown. Here, we identify a small, conserved, 15-kDa domain, which we refer to as the inner membrane translocation (IMT) domain that is common to T6SS and bacteriocins and linked to nuclease effector domains. Through fluorescence microscopy assays using intact and spheroplasted cells, we demonstrate that the IMT domain of the Pseudomonas aeruginosa specific bacteriocin pyocin G (PyoG) is required for import of the toxin nuclease domain to the cytoplasm. We also show that translocation of PyoG into the cytosol is dependent on inner membrane proteins FtsH, a AAA+ATPase/protease, and TonB1, the latter more typically associated with transport of bacteriocins across the outer membrane. Our study reveals that the IMT domain directs the cytotoxic nuclease of PyoG to cross the cytoplasmic membrane and, more broadly, has been adapted for the transport of other toxic nucleases delivered into Gram-negative bacteria by both contact dependent- and contact-independent means.

Pattern recognition receptors in health and diseases

Pattern recognition receptors (PRRs) are a class of receptors that can directly recognize the specific molecular structures on the surface of pathogens, apoptotic host cells, and damaged senescent cells. PRRs bridge nonspecific immunity and specific immunity. Through the recognition and binding of ligands, PRRs can produce nonspecific anti-infection, antitumor, and other immunoprotective effects. Most PRRs in the innate immune system of vertebrates can be classified into the following five types based on protein domain homology: Toll-like receptors (TLRs), nucleotide oligomerization domain (NOD)-like receptors (NLRs), retinoic acid-inducible gene-I (RIG-I)-like receptors (RLRs), C-type lectin receptors (CLRs), and absent in melanoma-2 (AIM2)-like receptors (ALRs). PRRs are basically composed of ligand recognition domains, intermediate domains, and effector domains. PRRs recognize and bind their respective ligands and recruit adaptor molecules with the same structure through their effector domains, initiating downstream signaling pathways to exert effects. In recent years, the increased researches on the recognition and binding of PRRs and their ligands have greatly promoted the understanding of different PRRs signaling pathways and provided ideas for the treatment of immune-related diseases and even tumors. This review describes in detail the history, the structural characteristics, ligand recognition mechanism, the signaling pathway, the related disease, new drugs in clinical trials and clinical therapy of different types of PRRs, and discusses the significance of the research on pattern recognition mechanism for the treatment of PRR-related diseases.

Histone H3 N-terminal mimicry drives a novel network of methyl-effector interactions

The reader ability of PHD fingers is largely limited to the recognition of the histone H3 N-terminal tail. Distinct subsets of PHDs bind either H3K4me3 (a transcriptional activator mark) or H3K4me0 (a transcriptional repressor state). Structural studies have identified common features among the different H3K4me3 effector PHDs, including 1) removal of the initiator methionine residue of H3 to prevent steric interference, 2) a groove where arginine-2 binds, and 3) an aromatic cage that engages methylated lysine-4. We hypothesize that PHDs have the ability to engage with non-histone ligands, as long as they adhere to these three rules. A search of the human proteome revealed an enrichment of chromatin-binding proteins that met these criteria, which we termed H3 N-terminal mimicry proteins (H3TMs). Seven H3TMs were selected, and used to screen a protein domain microarray for potential effector domains, and they all had the ability to bind H3K4me3-interacting effector domains. Furthermore, the binding affinity between the VRK1 peptide and the PHD domain of PHF2 is ~3-fold stronger than that of PHF2 and H3K4me3 interaction. The crystal structure of PHF2 PHD finger bound with VRK1 K4me3 peptide provides a molecular basis for stronger binding of VRK1 peptide. In addition, a number of the H3TMs peptides, in their unmethylated form, interact with NuRD transcriptional repressor complex. Our findings provide in vitro evidence that methylation of H3TMs can promote interactions with PHD and Tudor domain-containing proteins and potentially block interactions with the NuRD complex. We propose that these interactions can occur in vivo as well.

The CRISPR ancillary effector Can2 is a dual-specificity nuclease potentiating type III CRISPR defence

Cells and organisms have a wide range of mechanisms to defend against infection by viruses and other mobile genetic elements (MGE). Type III CRISPR systems detect foreign RNA and typically generate cyclic oligoadenylate (cOA) second messengers that bind to ancillary proteins with CARF (CRISPR associated Rossman fold) domains. This results in the activation of fused effector domains for antiviral defence. The best characterised CARF family effectors are the Csm6/Csx1 ribonucleases and DNA nickase Can1. Here we investigate a widely distributed CARF family effector with a nuclease domain, which we name Can2 (CRISPR ancillary nuclease 2). Can2 is activated by cyclic tetra-adenylate (cA4) and displays both DNase and RNase activity, providing effective immunity against plasmid transformation and bacteriophage infection in Escherichia coli. The structure of Can2 in complex with cA4 suggests a mechanism for the cA4-mediated activation of the enzyme, whereby an active site cleft is exposed on binding the activator. These findings extend our understanding of type III CRISPR cOA signalling and effector function.

Nanobody: a promising toolkit for molecular imaging and disease therapy

Nanobodies are the recombinant variable domains of heavy-chain-only antibodies, with many unique properties such as small size, excellent solubility, superior stability, quick clearance from blood, and deep tissue penetration. As a result, nanobodies have become a promising tool for the diagnosis and therapy of diseases. As imaging tracers, nanobodies allow an early acquisition of high-quality images, provide a comprehensive evaluation of the disease, and subsequently enable a personalized precision therapy. As therapeutic agents, nanobodies enable a targeted therapy by lesion-specific delivery of drugs and effector domains, thereby improving the specificity and efficacy of the therapy. Up to date, a wide variety of nanobodies have been developed for a broad range of molecular targets and have played a significant role in patients with a broad spectrum of diseases. In this review, we aim to outline the current state-of-the-art research on the nanobodies for medical applications and then discuss the challenges and strategies for their further clinical translation.

An immunotoxin targeting Ebola virus glycoprotein inhibits Ebola virus production from infected cells

Ebola virus (EBOV), a member of the mononegaviral family Filoviridae, causes severe disease associated with high lethality in humans. Despite enormous progress in development of EBOV medical countermeasures, no anti-EBOV treatment has been approved. We designed an immunotoxin in which a single-chain variable region fragment of the EBOV glycoprotein-specific monoclonal antibody 6D8 was fused to the effector domains of Pseudomonas aeruginosa exotoxin A (PE38). This immunotoxin, 6D8-PE38, bound specifically to cells expressing EBOV glycoproteins. Importantly, 6D8-PE38 targeted EBOV-infected cells, as evidenced by inhibition of infectious EBOV production from infected cells, including primary human macrophages. The data presented here provide a proof of concept for immunotoxin-based targeted killing of infected cells as a potential antiviral intervention for Ebola virus disease.

HGG-41. STRUCTURAL VARIANT DRIVERS IN PEDIATRIC HIGH-GRADE GLIOMA

BACKGROUND Driver single nucleotide variants (SNV) and somatic copy number aberrations (SCNA) of pediatric high-grade glioma (pHGGs), including Diffuse Midline Gliomas (DMGs) are characterized. However, structural variants (SVs) in pHGGs and the mechanisms through which they contribute to glioma formation have not been systematically analyzed genome-wide. METHODS Using SvABA for SVs as well as the latest pipelines for SCNAs and SNVs we analyzed whole-genome sequencing from 174 patients. This includes 60 previously unpublished samples, 43 of which are DMGs. Signature analysis allowed us to define pHGG groups with shared SV characteristics. Significantly recurring SV breakpoints and juxtapositions were identified with algorithms we recently developed and the findings were correlated with RNAseq and H3K27ac ChIPseq. RESULTS The SV characteristics in pHGG showed three groups defined by either complex, intermediate or simple signature activities. These associated with distinct combinations of known driver oncogenes. Our statistical analysis revealed recurring SVs in the topologically associating domains of MYCN, MYC, EGFR, PDGFRA & MET. These correlated with increased mRNA expression and amplification of H3K27ac peaks. Complex recurring amplifications showed characteristics of extrachromosomal amplicons and were enriched in coding SVs splitting protein regulatory from effector domains. Integrative analysis of all SCNAs, SNVs & SVs revealed patterns of characteristic combinations between potential drivers and signatures. This included two distinct groups of H3K27M DMGs with either complex or simple signatures and different combinations of associated variants. CONCLUSION Recurrent SVs associate with signatures shaped by an underlying process, which can lead to distinct mechanisms to activate the same oncogene.

T3SEpp: an Integrated Prediction Pipeline for Bacterial Type III Secreted Effectors

ABSTRACT Many Gram-negative bacteria infect hosts and cause diseases by translocating a variety of type III secreted effectors (T3SEs) into the host cell cytoplasm. However, despite a dramatic increase in the number of available whole-genome sequences, it remains challenging for accurate prediction of T3SEs. Traditional prediction models have focused on atypical sequence features buried in the N-terminal peptides of T3SEs, but unfortunately, these models have had high false-positive rates. In this research, we integrated promoter information along with characteristic protein features for signal regions, chaperone-binding domains, and effector domains for T3SE prediction. Machine learning algorithms, including deep learning, were adopted to predict the atypical features mainly buried in signal sequences of T3SEs, followed by development of a voting-based ensemble model integrating the individual prediction results. We assembled this into a unified T3SE prediction pipeline, T3SEpp, which integrated the results of individual modules, resulting in high accuracy (i.e., ∼0.94) and >1-fold reduction in the false-positive rate compared to that of state-of-the-art software tools. The T3SEpp pipeline and sequence features observed here will facilitate the accurate identification of new T3SEs, with numerous benefits for future studies on host-pathogen interactions. IMPORTANCE Type III secreted effector (T3SE) prediction remains a big computational challenge. In practical applications, current software tools often suffer problems of high false-positive rates. One of the causal factors could be the relatively unitary type of biological features used for the design and training of the models. In this research, we made a comprehensive survey on the sequence-based features of T3SEs, including signal sequences, chaperone-binding domains, effector domains, and transcription factor binding promoter sites, and assembled a unified prediction pipeline integrating multi-aspect biological features within homology-based and multiple machine learning models. To our knowledge, we have compiled the most comprehensive biological sequence feature analysis for T3SEs in this research. The T3SEpp pipeline integrating the variety of features and assembling different models showed high accuracy, which should facilitate more accurate identification of T3SEs in new and existing bacterial whole-genome sequences.

Evolutionary and functional classification of the CARF domain superfamily, key sensors in prokaryotic antivirus defense

CRISPR-associated Rossmann Fold (CARF) and SMODS-associated and fused to various effector domains (SAVED) are key components of cyclic oligonucleotide-based antiphage signaling systems (CBASS) that sense cyclic oligonucleotides and transmit the signal to an effector inducing cell dormancy or death. Most of the CARFs are components of a CBASS built into type III CRISPR–Cas systems, where the CARF domain binds cyclic oligoA (cOA) synthesized by Cas10 polymerase-cyclase and allosterically activates the effector, typically a promiscuous ribonuclease. Additionally, this signaling pathway includes a ring nuclease, often also a CARF domain (either the sensor itself or a specialized enzyme) that cleaves cOA and mitigates dormancy or death induction. We present a comprehensive census of CARF and SAVED domains in bacteria and archaea, and their sequence- and structure-based classification. There are 10 major families of CARF domains and multiple smaller groups that differ in structural features, association with distinct effectors, and presence or absence of the ring nuclease activity. By comparative genome analysis, we predict specific functions of CARF and SAVED domains and partition the CARF domains into those with both sensor and ring nuclease functions, and sensor-only ones. Several families of ring nucleases functionally associated with sensor-only CARF domains are also predicted.