Low-molecular weight branched polyethylenimine reduces cytokine secretion from human immune system monocytes stimulated with bacterial and fungal PAMPs.

Adaptive immunity recruits T-cells and specific antibodies against antigens, innate immune cells express pathogen recognition receptors (PRRs) that can detect various pathogen-associated molecular patterns (PAMPs) released by invading pathogens. Microbial molecular patterns, such as lipopolysaccharide (LPS) from Gram-negative bacteria, trigger signaling cascades in the host that result in the production of pro-inflammatory cytokines. LPS stimulation produces a strong immune response and excessive LPS signaling leads to dysregulation of the immune response. However, dysregulated inflammatory response during wound healing often results in chronic non-healing wounds that are difficult to control. In this work, we present data demonstrating partial neutralization of anionic LPS molecules using cationic branched polyethylenimine (BPEI). The anionic sites on the LPS molecules from Escherichia coli (E. coli) and Klebsiella pneumoniae (K. pneumoniae) are the lipid A moiety and BPEI binding create steric factors that hinder the binding of PRR signaling co-factors. This reduces the production of pro-inflammatory TNF-α cytokines. However, the anionic sites of Pseudomonas aeruginosa (P. aeruginosa) LPS are in the O-antigen region and subsequent BPEI binding slightly reduces TNF-α cytokine production. Fortunately, BPEI can reduce TNF-α cytokine expression in response to stimulation by intact P. aeruginosa bacterial cells and fungal zymosan PAMPs.

Neutralizing Staphylococcus aureus PAMPs that Trigger Cytokine Release from THP-1 Monocytes.

Innate immunity has considerable specificity and can discriminate between individual species of microbes. In this regard, pathogens are "seen" as dangerous to the host and elicit an inflammatory response capable of destroying the microbes. This immune discrimination is achieved by toll-like receptors on host cells recognizing pathogens, such as Staphylococcus aureus, and microbe-specific pathogen-associated molecular pattern (PAMP) molecules, such as lipoteichoic acid (LTA). PAMPs impede wound healing by lengthening the inflammatory phase of healing and contributing to the development of chronic wounds. Preventing PAMPs from triggering the release of inflammatory cytokines will counteract the dysregulation of inflammation. Here, we use ELISA to evaluate the use of cationic molecules branched polyethylenimine (BPEI), PEGylated BPEI (PEG-BPEI), and polymyxin-B to neutralize anionic LTA and lower levels of TNF-α cytokine release from human THP-1 monocytes in a concentration-dependent manner. Additional data collected with qPCR shows that BPEI and PEG-BPEI reduce the expression profile of the TNF-α gene. Similar effects are observed for the neutralization of whole-cell S. aureus bacteria. In vitro cytotoxicity data demonstrate that PEGylation lowers the toxicity of PEG-BPEI (IC50 = 2661 µm) compared to BPEI (IC50 = 853 µM) and that both compounds are orders of magnitude less toxic than the cationic antibiotic polymyxin-B (IC50 = 79 µM). Additionally, the LTA neutralization ability of polymyxin-B is less effective than BPEI or PEG-BPEI. These properties of BPEI and PEG-BPEI expand their utility beyond disabling antibiotic resistance mechanisms and disrupting S. aureus biofilms, providing additional justification for developing these agents as wound healing therapeutics. The multiple mechanisms of action for BPEI and PEG-BPEI are superior to current wound treatment strategies that have a single modality.

Quantifying Cell Heterogeneity and Subpopulations Using Single Cell Metabolomics.

Mass spectrometry (MS) has become an indispensable tool for metabolomics studies. However, due to the lack of applicable experimental platforms, suitable algorithm, software, and quantitative analyses of cell heterogeneity and subpopulations, investigating global metabolomics profiling at the single cell level remains challenging. We combined the Single-probe single cell MS (SCMS) experimental technique with a bioinformatics software package, SinCHet-MS (Single Cell Heterogeneity for Mass Spectrometry), to characterize changes of tumor heterogeneity, quantify cell subpopulations, and prioritize the metabolite biomarkers of each subpopulation. As proof of principle studies, two melanoma cancer cell lines, the primary (WM115; with a lower drug resistance) and the metastatic (WM266-4; with a higher drug resistance), were used as models. Our results indicate that after the treatment of the anticancer drug vemurafenib, a new subpopulation emerged in WM115 cells, while the proportion of the existing subpopulations was changed in the WM266-4 cells. In addition, metabolites for each subpopulation can be prioritized. Combining the SCMS experimental technique with a bioinformatics tool, our label-free approach can be applied to quantitatively study cell heterogeneity, prioritize markers for further investigation, and improve the understanding of cell metabolism in human diseases and response to therapy.

Single-Cell Mass Spectrometry Enables Insight into Heterogeneity in Infectious Disease.

Cellular heterogeneity is generally overlooked in infectious diseases. In this study, we investigated host cell heterogeneity during infection with Trypanosoma cruzi (T. cruzi) parasites, causative agents of Chagas disease (CD). In chronic-stage CD, only a few host cells are infected with a large load of parasites and symptoms may appear at sites distal to parasite colonization. Furthermore, recent work has revealed T. cruzi heterogeneity with regard to replication rates and drug susceptibility. However, the role of cellular-level metabolic heterogeneity in these processes has yet to be assessed. To fill this knowledge gap, we developed a Single-probe SCMS (single-cell mass spectrometry) method compatible with biosafety protocols, to acquire metabolomics data from individual cells during T. cruzi infection. This study revealed heterogeneity in the metabolic response of the host cells to T. cruzi infection in vitro. Our results showed that parasite-infected cells possessed divergent metabolism compared to control cells. Strikingly, some uninfected cells adjacent to infected cells showed metabolic impacts as well. Specific metabolic changes include increases in glycerophospholipids with infection. These results provide novel insight into the pathogenesis of CD. Furthermore, they represent the first application of bioanalytical SCMS to the study of mammalian-infectious agents, with the potential for broad applications to study infectious diseases.

Local Phenomena Shape Backyard Soil Metabolite Composition.

Soil covers most of Earth's continental surface and is fundamental to life-sustaining processes such as agriculture. Given its rich biodiversity, soil is also a major source for natural product drug discovery from soil microorganisms. However, the study of the soil small molecule profile has been challenging due to the complexity and heterogeneity of this matrix. In this study, we implemented high-resolution liquid chromatography-tandem mass spectrometry and large-scale data analysis tools such as molecular networking to characterize the relative contributions of city, state and regional processes on backyard soil metabolite composition, in 188 soil samples collected from 14 USA States, representing five USA climate regions. We observed that region, state and city of collection all influence the overall soil metabolite profile. However, many metabolites were only detected in unique sites, indicating that uniquely local phenomena also influence the backyard soil environment, with both human-derived and naturally-produced (plant-derived, microbially-derived) metabolites identified. Overall, these findings are helping to define the processes that shape the backyard soil metabolite composition, while also highlighting the need for expanded metabolomic studies of this complex environment.