Cystatin C is glucocorticoid responsive, directs recruitment of Trem2+ macrophages, and predicts failure of cancer immunotherapy

Cystatin C (CyC), a secreted cysteine protease inhibitor, has unclear biological functions. Many patients exhibit elevated plasma CyC levels, particularly during glucocorticoid (GC) treatment. This study links GCs with CyC’s systemic regulation by utilizing genome-wide association and structural equation modeling to determine CyC production genetics in the UK Biobank. Both CyC production and a polygenic score (PGS) capturing predisposition to CyC production were associated with increased all-cause and cancer-specific mortality. We found that the GC receptor directly targets CyC, leading to GC-responsive CyC secretion in macrophages and cancer cells. CyC-knockout tumors displayed significantly reduced growth and diminished recruitment of TREM2+ macrophages, which have been connected to cancer immunotherapy failure. Furthermore, the CyC-production PGS predicted checkpoint immunotherapy failure in 685 patients with metastatic cancer from combined clinical trial cohorts. In conclusion, CyC may act as a GC effector pathway via TREM2+ macrophage recruitment and may be a potential target for combination cancer immunotherapy.publishedVersio

A comparison of methods to assess the antimicrobial activity of nanoparticle combinations on bacterial cells

Copyright: © 2018 Bankier et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.BACKGROUND: Bacterial cell quantification after exposure to antimicrobial compounds varies widely throughout industry and healthcare. Numerous methods are employed to quantify these antimicrobial effects. With increasing demand for new preventative methods for disease control, we aimed to compare and assess common analytical methods used to determine antimicrobial effects of novel nanoparticle combinations on two different pathogens. METHODS: Plate counts of total viable cells, flow cytometry (LIVE/DEAD BacLight viability assay) and qPCR (viability qPCR) were used to assess the antimicrobial activity of engineered nanoparticle combinations (NPCs) on Gram-positive (Staphylococcus aureus) and Gram-negative (Pseudomonas aeruginosa) bacteria at different concentrations (0.05, 0.10 and 0.25 w/v%). Results were analysed using linear models to assess the effectiveness of different treatments. RESULTS: Strong antimicrobial effects of the three NPCs (AMNP0-2) on both pathogens could be quantified using the plate count method and flow cytometry. The plate count method showed a high log reduction (>8-log) for bacteria exposed to high NPC concentrations. We found similar antimicrobial results using the flow cytometry live/dead assay. Viability qPCR analysis of antimicrobial activity could not be quantified due to interference of NPCs with qPCR amplification. CONCLUSION: Flow cytometry was determined to be the best method to measure antimicrobial activity of the novel NPCs due to high-throughput, rapid and quantifiable results.Peer reviewe

Coevolutionary interactions between bacteria and phage in natural environments

Bacteria and their viruses (bacteriophage, phage) are the most abundant and diverse taxonomic groups, but ecological and evolutionary research on bacteria-phage interactions has largely focused on studies of simplified communities using a few model organisms. The goal of the thesis is to understand how bacteria and phage interact within natural environments, and how these interactions impact the patterns of phage infectivity and bacterial resistance. Here I investigate the effects of natural environments on the coevolutionary patterns of bacteria (Pseudomonas fluorescens) and phage (SBW25Φ2). In chapter 3 I investigate the effects of nineteen different communities on the coevolutionary interactions of SBW25 and phage, and the degree to which the infectivity of phage to its host, SBW25, changes depending on their local microbial community. Chapter 4 aimed to understand the effects of varying diversities of communities on coevolutionary interactions. In Chapter 5, I looked at how coevolutionary interactions were affected by different communities in different abiotic conditions (pH, temperature and nutrient concentration) and the effect communities had on the ability of SBW25 to adapt to the abiotic conditions. Understanding how biological and physical factors affect coevolutionary interactions in natural environments allows predictions of how phage and bacteria coevolve in natural and unnatural settings.Open Acces

Nanoparticle Lysis of Cryptosporidium Oocysts

The extraction of DNA from Cryptosporidium oocysts is challenging due to the robust oocyst wall. Nanoparticles have been applied to disinfect Cryptosporidium oocysts; here, we demonstrate the utilisation of nanoparticles to disrupt the oocyst wall to enable sporozoite lysis and detection via PCR. Both silver and zinc oxide nanoparticles are investigated under different conditions and compared to existing techniques. Zinc oxide nanoparticles are shown to be as effective as freeze–thaw methods, suggesting that a nanoparticle lysis approach offers a viable alternative to existing methods

Antiviral surfaces and coatings and their mechanisms of action

Viral infections are a serious health challenge, and the COVID-19 pandemic has increased the demand for antiviral measures and treatments for clean surfaces, especially in public places. Here, we review a range of natural and synthetic surface materials and coatings with antiviral properties, including metals, polymers and biopolymers, graphene and antimicrobial peptides, and their underpinning antiviral mechanisms. We also discuss the physico-chemical properties of surfaces which influence virus attachment and persistence on surfaces. Finally, an overview is given of the current practices and applications of antiviral and virucidal materials and coatings in consumer products, personal protective equipment, healthcare and public settings

Bar graph showing log reduction for a) <i>P</i>. <i>aeruginosa</i> and b) <i>S</i>. <i>aureus</i> for three AMNP nanoparticle composites (AMNP0, 1 and 2) at different NPC concentrations (0.05, 0.10 and 0.25 w/v%) with an antibody control (Ab control).

<p>A log reduction of >8-log shows complete inhibition of bacterial growth. Data is expressed as mean (<i>n</i> = 3)-/+ SD.</p

Primers and probes for sequence amplification and detection (qPCR).

<p>Primers and probes for sequence amplification and detection (qPCR).</p

Comparison to determine the effectiveness of qPCR-PMA and qPCR only to distinguish between live and dead cells.

<p><i>P</i>. <i>aeruginosa</i> (a) and <i>S</i>. <i>aureus</i> (b) were exposed to different concentrations of NPCs (0.05, 0.10 and 0.25 w/v %) for 24 hours and an Ab control. qPCR-only and qPCR-PMA was used to detect cell lysis via measurement of ΔCT. ΔCT values below 0 show a decrease in amplification (less DNA, dead cells) and ΔCT values above 0 show an increase in amplification (more DNA, live cells). Data expressed as mean (<i>n</i> = 3) -/+ SD.</p

Gating strategy used to determine ‘live’ populations of bacteria after exposure to NPCs (stained positive for SYTO9) and ‘dead’ populations of bacteria (stained positive for propidium iodide).

<p>Bacterial populations were gated using positive and negative controls alongside FMO controls. (Gated using FlowJo V10, TreeStar).</p

Bar graph showing log reduction for a) <i>P</i>. <i>aeruginosa</i> and b) <i>S</i>. <i>aureus</i> for three AMNP nanoparticle composites (AMNP0, 1 and 2) at different NPC concentrations (0.05, 0.10 and 0.25 w/v%) with an antibody control (Ab control).

<p>A log reduction of >8-log shows complete inhibition of bacterial growth. Data is expressed as mean (<i>n</i> = 3)-/+ SD.</p