IL-17A influences essential functions of the monocyte/macrophage lineage and is involved in advanced murine and human atherosclerosis.

Atherosclerosis is a chronic inflammatory disease. Lesion progression is primarily mediated by cells of the monocyte/macrophage lineage. IL-17A is a proinflammatory cytokine, which modulates immune cell trafficking and is involved inflammation in (auto)immune and infectious diseases. But the role of IL-17A still remains controversial. In the current study, we investigated effects of IL-17A on advanced murine and human atherosclerosis, the common disease phenotype in clinical care. The 26-wk-old apolipoprotein E-deficient mice were fed a standard chow diet and treated either with IL-17A mAb (n = 15) or irrelevant Ig (n = 10) for 16 wk. Furthermore, essential mechanisms of IL-17A in atherogenesis were studied in vitro. Inhibition of IL-17A markedly prevented atherosclerotic lesion progression (p = 0.001) by reducing inflammatory burden and cellular infiltration (p = 0.01) and improved lesion stability (p = 0.01). In vitro experiments showed that IL-17A plays a role in chemoattractance, monocyte adhesion, and sensitization of APCs toward pathogen-derived TLR4 ligands. Also, IL-17A induced a unique transcriptome pattern in monocyte-derived macrophages distinct from known macrophage types. Stimulation of human carotid plaque tissue ex vivo with IL-17A induced a proinflammatory milieu and upregulation of molecules expressed by the IL-17A-induced macrophage subtype. In this study, we show that functional blockade of IL-17A prevents atherosclerotic lesion progression and induces plaque stabilization in advanced lesions in apolipoprotein E-deficient mice. The underlying mechanisms involve reduced inflammation and distinct effects of IL-17A on monocyte/macrophage lineage. In addition, translational experiments underline the relevance for the human system.

Isaac: ultra-fast whole-genome secondary analysis on Illumina sequencing platforms.

SUMMARY: An ultrafast DNA sequence aligner (Isaac Genome Alignment Software) that takes advantage of high-memory hardware (>48 GB) and variant caller (Isaac Variant Caller) have been developed. We demonstrate that our combined pipeline (Isaac) is four to five times faster than BWA + GATK on equivalent hardware, with comparable accuracy as measured by trio conflict rates and sensitivity. We further show that Isaac is effective in the detection of disease-causing variants and can easily/economically be run on commodity hardware. AVAILABILITY: Isaac has an open source license and can be obtained at https://github.com/sequencing.

A comparison of medical and pharmacy student perspectives of a clinical interprofessional home-visit versus a virtual interprofessional workshop.

Background: No Place Like Home is a clinical interprofessional education (IPE) activity whereby pharmacy and medical students conduct home visits under the guidance and supervision of a clinical preceptor to homebound patients. Purpose: We examined pharmacy and medical student perceptions of mastery of interprofessional competencies during an in-person clinical home visit pre-COVID-19 pandemic versus a virtual IPE learning activity consisting of didactic and case discussions in response to the global COVID-19 pandemic. Methods: We administered the same modified Interprofessional Collaborative Competency Attainment Survey (ICCAS) instrument, which uses a five-point Likert scale, to both the in-person and the virtual IPE students following their learning activity.   Results: We received a total of 459 completed survey responses with an overall response rate of 84%. For both groups of students, the in-person format was preferred, however, to our surprise, the results indicated that students in the virtual group reported greater perceived gain in interprofessional skills than students in the in-person group. In addition, pharmacy students perceived greater gain from the interprofessional activity and offered more thoughtful reflections about their experience. Conclusions: Even though both groups of students preferred the in-person visit, the IPE objectives were equally (for medical students) or better (for pharmacy students) absorbed in the virtual environment than the in-person clinical home visit.

CXC chemokine ligand 4 induces a unique transcriptome in monocyte-derived macrophages.

In atherosclerotic arteries, blood monocytes differentiate to macrophages in the presence of growth factors, such as macrophage colony-stimulation factor (M-CSF), and chemokines, such as platelet factor 4 (CXCL4). To compare the gene expression signature of CXCL4-induced macrophages with M-CSF-induced macrophages or macrophages polarized with IFN-gamma/LPS (M1) or IL-4 (M2), we cultured primary human peripheral blood monocytes for 6 d. mRNA expression was measured by Affymetrix gene chips, and differences were analyzed by local pooled error test, profile of complex functionality, and gene set enrichment analysis. Three hundred seventy-five genes were differentially expressed between M-CSF- and CXCL4-induced macrophages; 206 of them overexpressed in CXCL4 macrophages coding for genes implicated in the inflammatory/immune response, Ag processing and presentation, and lipid metabolism. CXCL4-induced macrophages overexpressed some M1 and M2 genes and the corresponding cytokines at the protein level; however, their transcriptome clustered with neither M1 nor M2 transcriptomes. They almost completely lost the ability to phagocytose zymosan beads. Genes linked to atherosclerosis were not consistently upregulated or downregulated. Scavenger receptors showed lower and cholesterol efflux transporters showed higher expression in CXCL4- than M-CSF-induced macrophages, resulting in lower low-density lipoprotein content. We conclude that CXCL4 induces a unique macrophage transcriptome distinct from known macrophage types, defining a new macrophage differentiation that we propose to call M4.

ReSASC: a resampling-based algorithm to determine differential protein expression from spectral count data.

Label-free methods for MS/MS quantification of protein expression are becoming more prevalent as instrument sensitivity increases. Spectral counts (SCs) are commonly used, readily obtained, and increase linearly with protein abundance; however, a statistical framework has been lacking. To accommodate the highly non-normal distribution of SCs, we developed ReSASC (resampling-based significance analysis for spectral counts), which evaluates differential expression between two conditions by pooling similarly expressed proteins and sampling from this pool to create permutation-based synthetic sets of SCs for each protein. At a set confidence level and corresponding p-value cutoff, ReSASC defines a new p-value, p', as the number of synthetic SC sets with p>p(cutoff) divided by the total number of sets. We have applied ReSASC to two published SC data sets and found that ReSASC compares favorably with existing methods while being easy to operate and requiring only standard computing resources.

The plasma microparticle proteome.

All cell types shed ectosomes and exosomes, collectively known as microparticles (MP; 0.1 to 1.5 µm in diameter), when activated or stressed; normal human plasma contains ~2 µg MP protein/mL. The cellular composition of plasma MP is altered in many diseases, including acute coronary syndrome, diabetes mellitus, sepsis, and sickle cell disease. We measured the plasma MP protein composition of 42 patients (median age 69.5 years, most with cardiovascular disease) by label-free liquid chromatography coupled to tandem mass spectrometry. Among 458 proteins detected with high confidence (identified by at least two unique peptides with SEQUEST XCor (Thermo Electron Corp., San Jose, CA) ≥ 2.0, 2.2, and 3.3 for charge states +1, +2, and +3, respectively), 130 were present in most patients, representing a "core" set of plasma MP proteins. This core is enriched in cytoskeletal, integrin complex, and hemostasis proteins, and spectral counts of several proteins correlate with patient age and gender. We conclude that the MP proteome may be a useful and reliable source of biologically relevant disease biomarkers.