Protein Tyrosine and Serine/Threonine Phosphorylation in Oral Bacterial Dysbiosis and Bacteria-Host Interaction

The human oral cavity harbors approximately 1,000 microbial species, and dysbiosis of the microflora and imbalanced microbiota-host interactions drive many oral diseases, such as dental caries and periodontal disease. Oral microbiota homeostasis is critical for systemic health. Over the last two decades, bacterial protein phosphorylation systems have been extensively studied, providing mounting evidence of the pivotal role of tyrosine and serine/threonine phosphorylation in oral bacterial dysbiosis and bacteria-host interactions. Ongoing investigations aim to discover novel kinases and phosphatases and to understand the mechanism by which these phosphorylation events regulate the pathogenicity of oral bacteria. Here, we summarize the structures of bacterial tyrosine and serine/threonine kinases and phosphatases and discuss the roles of tyrosine and serine/threonine phosphorylation systems in Porphyromonas gingivalis and Streptococcus mutans, emphasizing their involvement in bacterial metabolism and virulence, community development, and bacteria-host interactions.

T-DNA integration in plants requires MRE11- or TDP2-mediated removal of the 5’ bound Agrobacterium protein VirD2

Agrobacterium tumefaciens, a pathogenic bacterium capable of transforming plants through horizontal gene transfer, is nowadays the preferred vector for plant genetic engineering. The vehicle for transfer is the T-strand, a single-stranded DNA molecule bound by the bacterial protein VirD2, which guides T-DNA into the plants nucleus where it integrates. How VirD2 is removed from T-DNA, and which mechanism acts to attach the liberated end to the plant genome is currently unknown. Here, using newly developed technology that yields hundreds of T-DNA integrations in somatic tissue of Arabidopsis thaliana, we uncover two redundant mechanisms for the genomic capture of the T-DNA’s 5’ end. Different from capture of the 3’ end of the T-DNA, which is the exclusive action of polymerase theta-mediated end joining (TMEJ), 5’ attachment is accomplished either by TMEJ or by canonical non-homologous end joining (cNHEJ). We further find that TMEJ needs MRE11, whereas cNHEJ requires TDP2 to remove the 5’-end blocking protein VirD2. As a consequence, T-DNA integration is severely impaired in plants deficient for both MRE11 and TDP2 (or other cNHEJ factors). In support of MRE11 and cNHEJ specifically acting on the 5’ end, we demonstrate rescue of the integration defect of double-deficient plants by using T-DNAs that are capable of forming telomeres upon 3’ capture. Our study provides a mechanistic model for how Agrobacterium exploits the plant’s own DNA repair machineries to transform them.

1370. Role of Clindamycin Versus Linezolid for Serious Group A Streptococcal Infections

Background Streptococcus pyogenes can cause severe illnesses such as toxic-shock syndrome and necrotizing fasciitis due to pyrogenic exotoxins. Clindamycin is added to penicillin for treatment of severe S. pyogenes infections as it is a bacterial protein synthesis inhibitor which reduces toxin production. However, clindamycin is associated with several adverse effects including C. difficile infection. Linezolid is a bacterial protein synthesis inhibitor that has been shown to provide excellent coverage of S. pyogenes including toxin inhibition in vitro, but clinical evidence is lacking. We compared outcomes of patients treated with linezolid versus clindamycin for serious S. pyogenes infections. Methods This was a retrospective study of patients with necrotizing fasciitis or toxic shock syndrome caused by S. pyogenes admitted to the Shock Trauma Center at University of Maryland Medical Center treated with at least 48 hours of either clindamycin or linezolid. Data collected included Sequential Organ Failure Assessment (SOFA) and Laboratory Risk Indicator for Necrotizing Fasciitis (LRINEC) severity scores, time to resolution of infection, number of surgeries, C. difficile infection, other antibiotic associated adverse effects, and mortality. Associations between patient characteristics, antibiotic groups, and outcomes were analyzed using the chi-square test, Fisher’s exact test and t-test or Wilcoxon rank-sum test as appropriate (SAS v 9.4). Results 52 patients were included, 26 treated with clindamycin and 26 with linezolid. Most patients (85% clindamycin and 96.2% linezolid) were treated for necrotizing fasciitis. Baseline characteristics, including SOFA and LRINEC scores, were similar between the groups. There was no difference in mortality between patients treated with clindamycin versus linezolid (11.5% vs. 7.7%, p = 0.22), and resolution of infection was similar between the groups (92.3% vs. 88.5%, p = 1.0). There was no difference in adverse effects between the clindamycin and linezolid groups, including C. difficile infection (3.9% vs. 0% p = 1.0) and thrombocytopenia (30.8% vs. 42.3%, p = 0.4). Conclusion Linezolid could be an alternate to clindamycin for the treatment of serious toxin producing S. pyogenes infections. Further prospective studies are needed. Disclosures Emily Heil, PharmD, MS, BCIDP, Nothing to disclose

Improved prediction of protein-protein interactions using AlphaFold2

Predicting the structure of interacting protein chains is fundamental for understanding the function of proteins. Here, we examine the use of AlphaFold2 (AF2) for predicting the structure of heterodimeric protein complexes. We find that using the default AF2 protocol, 44% of the models in a test set can be predicted accurately. However, by optimising the multiple sequence alignment, we can increase the accuracy to 59%. In comparison, the alternative fold-and-dock method RoseTTAFold is only successful in 10% of the cases on this set, template-based docking 35% and traditional docking methods 22%. We can distinguish acceptable (DockQ>0.23) from incorrect models with an AUC of 0.85 on the test set by analysing the predicted interfaces. The success is higher for bacterial protein pairs, pairs with large interaction areas consisting of helices or sheets, and many homologous sequences. Further, we test the possibility to distinguish interacting from non-interacting proteins and find that by analysing the predicted interfaces, we can separate truly interacting from non-interacting proteins with an AUC of 0.82 in the ROC curve, compared to 0.76 with a recently published method. In addition, when using a more realistic negative set, including mammalian proteins, the identification rate remains (AUC=0.83), resulting in that 27% of interactions can be identified at a 1% FPR. All scripts and tools to run our protocol are freely available at: https://gitlab.com/ElofssonLab/FoldDock.

Analysing structural data to explore the function of an essential bacterial protein foldase

Structural biology, or the study of how protein structures dictate their function, is a fundamental part of life science research, allowing the mechanisms underpinning life to be unravelled at the molecular level. Due to the complexity of 3D data, researchers often use special visualization methods to extract useful information from protein structures. This article uses the most common of these visualisation methods to examine different structures of the β-barrel assembly machinery complex (BAM), an essential protein that folds other proteins into the outer-membranes of Gram-negative bacteria. By exploring how BAM’s 3D shape changes as it interacts with its substrates throughout the folding process, it is possible to reconstruct a potential mechanism for this molecular machine that can be used to drive further research.