The Structure and Function of Serum Opacity Factor: A Unique Streptococcal Virulence Determinant That Targets High-Density Lipoproteins

Serum opacity factor (SOF) is a virulence determinant expressed by a variety of streptococcal and staphylococcal species including both human and animal pathogens. SOF derives its name from its ability to opacify serum where it targets and disrupts the structure of high-density lipoproteins resulting in formation of large lipid vesicles that cause the serum to become cloudy. SOF is a multifunctional protein and in addition to its opacification activity, it binds to a number of host proteins that mediate adhesion of streptococci to host cells, and it plays a role in resistance to phagocytosis in human blood. This article will provide an overview of the structure and function of SOF, its role in the pathogenesis of streptococcal infections, its vaccine potential, its prevalence and distribution in bacteria, and the molecular mechanism whereby SOF opacifies serum and how an understanding of this mechanism may lead to therapies for reducing high-cholesterol concentrations in blood, a major risk factor for cardiovascular disease

Profiling lung adenocarcinoma by liquid biopsy: can one size fit all?

BACKGROUND: Cancer is first and foremost a disease of the genome. Specific genetic signatures within a tumour are prognostic of disease outcome, reflect subclonal architecture and intratumour heterogeneity, inform treatment choices and predict the emergence of resistance to targeted therapies. Minimally invasive liquid biopsies can give temporal resolution to a tumour's genetic profile and allow the monitoring of treatment response through levels of circulating tumour DNA (ctDNA). However, the detection of ctDNA in repeated liquid biopsies is currently limited by economic and time constraints associated with targeted sequencing. METHODS: Here we bioinformatically profile the mutational and copy number spectrum of The Cancer Genome Network's lung adenocarcinoma dataset to uncover recurrently mutated genomic loci. RESULTS: We build a panel of 400 hotspot mutations and show that the coverage extends to more than 80% of the dataset at a median depth of 8 mutations per patient. Additionally, we uncover several novel single-nucleotide variants present in more than 5% of patients, often in genes not commonly associated with lung adenocarcinoma. CONCLUSION: With further optimisation, this hotspot panel could allow molecular diagnostics laboratories to build curated primer banks for 'off-the-shelf' monitoring of ctDNA by droplet-based digital PCR or similar techniques, in a time- and cost-effective manner

Relationship between Expression of the Family of M Proteins and Lipoteichoic Acid to Hydrophobicity and Biofilm Formation in Streptococcus pyogenes

Background: Hydrophobicity is an important attribute of bacteria that contributes to adhesion and biofilm formation. Hydrophobicity of Streptococcus pyogenes is primarily due to lipoteichoic acid (LTA) on the streptococcal surface but the mechanism(s) whereby LTA is retained on the surface is poorly understood. In this study, we sought to determine whether members of the M protein family consisting of Emm (M protein), Mrp (M-related protein), Enn (an M-like protein), and the streptococcal protective antigen (Spa) are involved in anchoring LTA in a manner that contributes to hydrophobicity of the streptococci and its ability to form biofilms. Methodology/Principal Findings: Isogenic mutants defective in expression of emm, mrp, enn, and/or spa genes of eight different serotypes and their parental strains were tested for differences in LTA bound to surface proteins, LTA released into the culture media, and membrane-bound LTA. The effect of these mutations on the ability of streptococci to form a hydrophobic surface and to generate biofilms was also investigated. A recombinant strain overexpressing Emm1 was also engineered and similarly tested. The serotypes tested ranged from those that express only a single M protein gene to those that express two or three members of the M protein family. Overexpression of Emm1 led to enhanced hydrophobicity an

Preclinical and clinical biomarker studies of CT1812:A novel approach to Alzheimer's disease modification

INTRODUCTION: Amyloid beta (Aβ) oligomers are one of the most toxic structural forms of the Aβ protein and are hypothesized to cause synaptotoxicity and memory failure as they build up in Alzheimer’s disease (AD) patients’ brain tissue. We previously demonstrated that antagonists of the sigma-2 receptor complex effectively block Aβ oligomer toxicity. CT1812 is an orally bioavailable, brain penetrant small molecule antagonist of the sigma-2 receptor complex that appears safe and well tolerated in healthy elderly volunteers. We tested CT1812’s effect on Aβ oligomer pathobiology in preclinical AD models and evaluated CT1812’s impact on cerebrospinal fluid (CSF) protein biomarkers in mild to moderate AD patients in a clinical trial (ClinicalTrials.gov NCT02907567). METHODS: Experiments were performed to measure the impact of CT1812 versus vehicle on Aβ oligomer binding to synapses in vitro, to human AD patient post mortem brain tissue ex vivo, and in living APP(Swe)/PS1dE9 transgenic mice in vivo. Additional experiments were performed to measure the impact of CT1812 versus vehicle on Aβ oligomer-induced deficits in membrane trafficking rate, synapse number, and protein expression in mature hippocampal/cortical neurons in vitro. The impact of CT1812 on cognitive function was measured in transgenic Thy1 huAPP(Swe/Lnd+) and wild-type littermates. A multicenter, double-blind, placebo-controlled parallel group trial was performed to evaluate the safety, tolerability, and impact on protein biomarker expression of CT1812 or placebo given once daily for 28 days to AD patients (Mini-Mental State Examination 18–26). CSF protein expression was measured by liquid chromatography with tandem mass spectrometry or enzyme-linked immunosorbent assay in samples drawn prior to dosing (Day 0) and at end of dosing (Day 28) and compared within each patient and between pooled treated versus placebo-treated dosing groups. RESULTS: CT1812 significantly and dose-dependently displaced Aβ oligomers bound to synaptic receptors in three independent preclinical models of AD, facilitated oligomer clearance into the CSF, increased synaptic number and protein expression in neurons, and improved cognitive performance in transgenic mice. CT1812 significantly increased CSF concentrations of Aβ oligomers in AD patient CSF, reduced concentrations of synaptic proteins and phosphorylated tau fragments, and reversed expression of many AD-related proteins dysregulated in CSF. DISCUSSION: These preclinical studies demonstrate the novel disease-modifying mechanism of action of CT1812 against AD and Aβ oligomers. The clinical results are consistent with preclinical data and provide evidence of target engagement and impact on fundamental disease-related signaling pathways in AD patients, supporting further development of CT1812

Inactivation of DltA Modulates Virulence Factor Expression in Streptococcus pyogenes

D-alanylated lipoteichoic acid is a virtually ubiquitous component of gram-positive cell walls. Mutations in the dltABCD operon of numerous species exhibit pleiotropic effects, including reduced virulence, which has been attributed to increased binding of cationic antimicrobial peptides to the more negatively charged cell surface. In this study, we have further investigated the effects that mutating dltA has on virulence factor expression in Streptococcus pyogenes.Isogenic Delta dltA mutants had previously been created in two distinct M1T1 isolates of S. pyogenes. Immunoblots, flow cytometry, and immunofluorescence were used to quantitate M protein levels in these strains, as well as to assess their ability to bind complement. Bacteria were tested for their ability to interact with human PMN and to grow in whole human blood. Message levels for emm, sic, and various regulatory elements were assessed by quantitative RT-PCR. Cell walls of Delta dltA mutants contained much less M protein than cell walls of parent strains and this correlated with reduced levels of emm transcripts, increased deposition of complement, increased association of bacteria with polymorphonuclear leukocytes, and reduced bacterial growth in whole human blood. Transcription of at least one other gene of the mga regulon, sic, which encodes a protein that inactivates antimicrobial peptides, was also dramatically reduced in Delta dltA mutants. Concomitantly, ccpA and rofA were unaffected, while rgg and arcA were up-regulated.This study has identified a novel mechanism for the reduced virulence of dltA mutants of Streptococcus pyogenes in which gene regulatory networks somehow sense and respond to the loss of DltA and lack of D-alanine esterification of lipoteichoic acid. The mechanism remains to be determined, but the data indicate that the status of D-alanine-lipoteichoic acid can significantly influence the expression of at least some streptococcal virulence factors and provide further impetus to targeting the dlt operon of gram-positive pathogens in the search for novel antimicrobial compounds

Exploiting antitumor immunity to overcome relapse and improve remission duration

Cancer survivors often relapse due to evolving drug-resistant clones and repopulating tumor stem cells. Our preclinical study demonstrated that terminal cancer patient’s lymphocytes can be converted from tolerant bystanders in vivo into effective cytotoxic T-lymphocytes in vitro killing patient’s own tumor cells containing drug-resistant clones and tumor stem cells. We designed a clinical trial combining peginterferon α-2b with imatinib for treatment of stage III/IV gastrointestinal stromal tumor (GIST) with the rational that peginterferon α-2b serves as danger signals to promote antitumor immunity while imatinib’s effective tumor killing undermines tumor-induced tolerance and supply tumor-specific antigens in vivo without leukopenia, thus allowing for proper dendritic cell and cytotoxic T-lymphocyte differentiation toward Th1 response. Interim analysis of eight patients demonstrated significant induction of IFN-γ-producing-CD8+, -CD4+, -NK cell, and IFN-γ-producing-tumor-infiltrating-lymphocytes, signifying significant Th1 response and NK cell activation. After a median follow-up of 3.6 years, complete response (CR) + partial response (PR) = 100%, overall survival = 100%, one patient died of unrelated illness while in remission, six of seven evaluable patients are either in continuing PR/CR (5 patients) or have progression-free survival (PFS, 1 patient) exceeding the upper limit of the 95% confidence level of the genotype-specific-PFS of the phase III imatinib-monotherapy (CALGB150105/SWOGS0033), demonstrating highly promising clinical outcomes. The current trial is closed in preparation for a larger future trial. We conclude that combination of targeted therapy and immunotherapy is safe and induced significant Th1 response and NK cell activation and demonstrated highly promising clinical efficacy in GIST, thus warranting development in other tumor types

Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies

Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., Random Forests) to 1) quantify the extent to which relationship quality is predictable and 2) identify which constructs reliably predict relationship quality. Across 43 dyadic longitudinal datasets from 29 laboratories, the top relationship-specific predictors of relationship quality were perceived-partner commitment, appreciation, sexual satisfaction, perceived-partner satisfaction, and conflict. The top individual-difference predictors were life satisfaction, negative affect, depression, attachment avoidance, and attachment anxiety. Overall, relationship-specific variables predicted up to 45% of variance at baseline, and up to 18% of variance at the end of each study. Individual differences also performed well (21% and 12%, respectively). Actor-reported variables (i.e., own relationship-specific and individual-difference variables) predicted two to four times more variance than partner-reported variables (i.e., the partner’s ratings on those variables). Importantly, individual differences and partner reports had no predictive effects beyond actor-reported relationship-specific variables alone. These findings imply that the sum of all individual differences and partner experiences exert their influence on relationship quality via a person’s own relationship-specific experiences, and effects due to moderation by individual differences and moderation by partner-reports may be quite small. Finally, relationship-quality change (i.e., increases or decreases in relationship quality over the course of a study) was largely unpredictable from any combination of self-report variables. This collective effort should guide future models of relationships

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives