Phenotypic polarization of macrophages is regulated by a milieu of cues in the local tissue microenvironment. Although much is known about how soluble factors influence macrophage polarization, relatively little is known about how physical cues present in the extracellular environment might modulate proinflammatory (M1) vs. prohealing (M2) activation. Specifically, the role of cell shape has not been explored, even though it has been observed that macrophages adopt different geometries in vivo. We and others observed that macrophages polarized toward different phenotypes in vitro exhibit dramatic changes in cell shape: M2 cells exhibit an elongated shape compared with M1 cells. Using a micropatterning approach to control macrophage cell shape directly, we demonstrate here that elongation itself, without exogenous cytokines, leads to the expression of M2 phenotype markers and reduces the secretion of inflammatory cytokines. Moreover, elongation enhances the effects of M2-inducing cytokines IL-4 and IL-13 and protects cells from M1-inducing stimuli LPS and IFN-γ. In addition shape-but not cytokine-induced polarization is abrogated when actin and actin/myosin contractility are inhibited by pharmacological agents, suggesting a role for the cytoskeleton in the control of macrophage polarization by cell geometry. Our studies demonstrate that alterations in cell shape associated with changes in ECM architecture may provide integral cues to modulate macrophage phenotype polarization. Macrophages play an essential role in innate immunity and are involved in a variety of immune functions, including host defense and wound healing. In addition, these cells participate in the progression of many chronic inflammatory diseases. To fulfill their functionally distinct roles, macrophages are capable of polarizing toward a spectrum of phenotypes, which include classical (proinflammatory, M1) and alternative (anti-inflammatory, prohealing, M2) activation states, as well as a regulatory phenotype and subtypes of these broad classifications (1). In the presence of inflammatory stimuli and danger signals, macrophages polarize toward the M1 state and release reactive species and inflammatory cytokines to fight pathogens. In contrast, a wound healing environment promotes polarization toward an M2 phenotype and leads to cellular processes that facilitate tissue repair. Although distinct macrophage subpopulations are clearly observed at different phases of the immune response to infection and injury (2), regulation of phenotypic polarization of these remarkably plastic cells still remains poorly defined.Activated macrophages are derived from circulating monocytes or resident tissue macrophages and migrate through the extracellular space in response to chemotactic agents to reach the target wound or infection site. Although it is thought that cytokines and chemokines are the primary regulators of macrophage behavior (3), some recent studies suggest that tissue structure and physical cues in the extracellular environment also contribute to ...

Despite a long-suspected role in the development of human colorectal cancer (CRC), the composition of gut microbiota in CRC patients has not been adequately described. In this study, fecal bacterial diversity in CRC patients (n=46) and healthy volunteers (n=56) were profiled by 454 pyrosequencing of the V3 region of the 16S ribosomal RNA gene. Both principal component analysis and UniFrac analysis showed structural segregation between the two populations. Forty-eight operational taxonomic units (OTUs) were identified by redundancy analysis as key variables significantly associated with the structural difference. One OTU closely related to Bacteroides fragilis was enriched in the gut microbiota of CRC patients, whereas three OTUs related to Bacteroides vulgatus and Bacteroides uniformis were enriched in that of healthy volunteers. A total of 11 OTUs belonging to the genera Enterococcus, Escherichia/Shigella, Klebsiella, Streptococcus and Peptostreptococcus were significantly more abundant in the gut microbiota of CRC patients, and 5 OTUs belonging to the genus Roseburia and other butyrate-producing bacteria of the family Lachnospiraceae were less abundant. Real-time quantitative PCR further validated the significant reduction of butyrate-producing bacteria in the gut microbiota of CRC patients by measuring the copy numbers of butyryl-coenzyme A CoA transferase genes (Mann-Whitney test, P<0.01). Reduction of butyrate producers and increase of opportunistic pathogens may constitute a major structural imbalance of gut microbiota in CRC patients.

BackgroundCoronary artery disease (CAD) has substantial heritability and a polygenic architecture. However, the potential of genomic risk scores to help predict CAD outcomes has not been evaluated comprehensively, because available studies have involved limited genomic scope and limited sample sizes.ObjectivesThis study sought to construct a genomic risk score for CAD and to estimate its potential as a screening tool for primary prevention.MethodsUsing a meta-analytic approach to combine large-scale, genome-wide, and targeted genetic association data, we developed a new genomic risk score for CAD (metaGRS) consisting of 1.7 million genetic variants. We externally tested metaGRS, both by itself and in combination with available data on conventional risk factors, in 22,242 CAD cases and 460,387 noncases from the UK Biobank.ResultsThe hazard ratio (HR) for CAD was 1.71 (95% confidence interval [CI]: 1.68 to 1.73) per SD increase in metaGRS, an association larger than any other externally tested genetic risk score previously published. The metaGRS stratified individuals into significantly different life course trajectories of CAD risk, with those in the top 20% of metaGRS distribution having an HR of 4.17 (95% CI: 3.97 to 4.38) compared with those in the bottom 20%. The corresponding HR was 2.83 (95% CI: 2.61 to 3.07) among individuals on lipid-lowering or antihypertensive medications. The metaGRS had a higher C-index (C = 0.623; 95% CI: 0.615 to 0.631) for incident CAD than any of 6 conventional factors (smoking, diabetes, hypertension, body mass index, self-reported high cholesterol, and family history). For men in the top 20% of metaGRS with >2 conventional factors, 10% cumulative risk of CAD was reached by 48 years of age.ConclusionsThe genomic score developed and evaluated here substantially advances the concept of using genomic information to stratify individuals with different trajectories of CAD risk and highlights the potential for genomic screening in early life to complement conventional risk prediction.