High and Low Molecular Weight Hyaluronic Acid Differentially Regulate Human Fibrocyte Differentiation

Following tissue injury, monocytes can enter the tissue and differentiate into fibroblast-like cells called fibrocytes, but little is known about what regulates this differentiation. Extracellular matrix contains high molecular weight hyaluronic acid (HMWHA; ∼2×10(6) Da). During injury, HMWHA breaks down to low molecular weight hyaluronic acid (LMWHA; ∼0.8-8×10(5) Da).In this report, we show that HMWHA potentiates the differentiation of human monocytes into fibrocytes, while LMWHA inhibits fibrocyte differentiation. Digestion of HMWHA with hyaluronidase produces small hyaluronic acid fragments, and these fragments inhibit fibrocyte differentiation. Monocytes internalize HMWHA and LMWHA equally well, suggesting that the opposing effects on fibrocyte differentiation are not due to differential internalization of HMWHA or LMWHA. Adding HMWHA to PBMC does not appear to affect the levels of the hyaluronic acid receptor CD44, whereas adding LMWHA decreases CD44 levels. The addition of anti-CD44 antibodies potentiates fibrocyte differentiation, suggesting that CD44 mediates at least some of the effect of hyaluronic acid on fibrocyte differentiation. The fibrocyte differentiation-inhibiting factor serum amyloid P (SAP) inhibits HMWHA-induced fibrocyte differentiation and potentiates LMWHA-induced inhibition. Conversely, LMWHA inhibits the ability of HMWHA, interleukin-4 (IL-4), or interleukin-13 (IL-13) to promote fibrocyte differentiation.We hypothesize that hyaluronic acid signals at least in part through CD44 to regulate fibrocyte differentiation, with a dominance hierarchy of SAP>LMWHA≥HMWHA>IL-4 or IL-13

Stability of Metabolic Correlations under Changing Environmental Conditions in Escherichia coli – A Systems Approach

Background: Biological systems adapt to changing environments by reorganizing their cellular and physiological program with metabolites representing one important response level. Different stresses lead to both conserved and specific responses on the metabolite level which should be reflected in the underlying metabolic network. Methodology/Principal Findings: Starting from experimental data obtained by a GC-MS based high-throughput metabolic profiling technology we here develop an approach that: (1) extracts network representations from metabolic condition-dependent data by using pairwise correlations, (2) determines the sets of stable and condition-dependent correlations based on a combination of statistical significance and homogeneity tests, and (3) can identify metabolites related to the stress response, which goes beyond simple observations about the changes of metabolic concentrations. The approach was tested with Escherichia coli as a model organism observed under four different environmental stress conditions (cold stress, heat stress, oxidative stress, lactose diauxie) and control unperturbed conditions. By constructing the stable network component, which displays a scale free topology and small-world characteristics, we demonstrated that: (1) metabolite hubs in this reconstructed correlation networks are significantly enriched for those contained in biochemical networks such as EcoCyc, (2) particular components of the stable network are enriched for functionally related biochemical pathways, and (3) independently of the response scale, based on their importance in the reorganization of the correlation network a set of metabolites can be identified which represent hypothetical candidates for adjusting to a stress-specific response. Conclusions/Significance: Network-based tools allowed the identification of stress-dependent and general metabolic correlation networks. This correlation-network-based approach does not rely on major changes in concentration to identify metabolites important for stress adaptation, but rather on the changes in network properties with respect to metabolites. This should represent a useful complementary technique in addition to more classical approaches

Molecular and Evolutionary Bases of Within-Patient Genotypic and Phenotypic Diversity in Escherichia coli Extraintestinal Infections

Although polymicrobial infections, caused by combinations of viruses, bacteria, fungi and parasites, are being recognised with increasing frequency, little is known about the occurrence of within-species diversity in bacterial infections and the molecular and evolutionary bases of this diversity. We used multiple approaches to study the genomic and phenotypic diversity among 226 Escherichia coli isolates from deep and closed visceral infections occurring in 19 patients. We observed genomic variability among isolates from the same site within 11 patients. This diversity was of two types, as patients were infected either by several distinct E. coli clones (4 patients) or by members of a single clone that exhibit micro-heterogeneity (11 patients); both types of diversity were present in 4 patients. A surprisingly wide continuum of antibiotic resistance, outer membrane permeability, growth rate, stress resistance, red dry and rough morphotype characteristics and virulence properties were present within the isolates of single clones in 8 of the 11 patients showing genomic micro-heterogeneity. Many of the observed phenotypic differences within clones affected the trade-off between self-preservation and nutritional competence (SPANC). We showed in 3 patients that this phenotypic variability was associated with distinct levels of RpoS in co-existing isolates. Genome mutational analysis and global proteomic comparisons in isolates from a patient revealed a star-like relationship of changes amongst clonally diverging isolates. A mathematical model demonstrated that multiple genotypes with distinct RpoS levels can co-exist as a result of the SPANC trade-off. In the cases involving infection by a single clone, we present several lines of evidence to suggest diversification during the infectious process rather than an infection by multiple isolates exhibiting a micro-heterogeneity. Our results suggest that bacteria are subject to trade-offs during an infectious process and that the observed diversity resembled results obtained in experimental evolution studies. Whatever the mechanisms leading to diversity, our results have strong medical implications in terms of the need for more extensive isolate testing before deciding on antibiotic therapies

The Long Pentraxin PTX3 Promotes Fibrocyte Differentiation

Monocyte-derived, fibroblast-like cells called fibrocytes are associated with fibrotic lesions. The plasma protein serum amyloid P component (SAP; also known as pentraxin-2, PTX2) inhibits fibrocyte differentiation in vitro, and injections of SAP inhibit fibrosis in vivo. SAP is a member of the pentraxin family of proteins that includes C-reactive protein (CRP; PTX1) and pentraxin-3 (PTX3). All three pentraxins are associated with fibrosis, but only SAP and CRP have been studied for their effects on fibrocyte differentiation. We find that compared to SAP and CRP, PTX3 promotes human and murine fibrocyte differentiation. The effect of PTX3 is dependent on FcγRI. In competition studies, the fibrocyte-inhibitory activity of SAP is dominant over PTX3. Binding competition studies indicate that SAP and PTX3 bind human FcγRI at different sites. In murine models of lung fibrosis, PTX3 is present in fibrotic areas, and the PTX3 distribution is associated with collagen deposition. In lung tissue from pulmonary fibrosis patients, PTX3 has a widespread distribution, both in unaffected tissue and in fibrotic lesions, whereas SAP is restricted to areas adjacent to vessels, and absent from fibrotic areas. These data suggest that the relative levels of SAP and PTX3 present at sites of fibrosis may have a significant effect on the ability of monocytes to differentiate into fibrocytes

The prevalence and clinical relevance of 2R/2R TYMS genotype in patients with gastrointestinal malignancies treated with fluoropyrimidine-based chemotherapy regimens

INTRODUCTION: The prevalence of 2R/2R TYMS genotype is variable but estimated to be around 20–30% in Caucasians. The clinical relevance of TYMS 2R/2R genotype in predicting severe fluoropyrimidine-related adverse events (FrAE) is controversial. Here, we explored the prevalence and clinical relevance of 2R/2R TYMS genotype. METHODS: Between 2011 and 2018, 126 patients were genotyped for TYMS. FrAEs were graded according to CTCAE version 5.0. Fisher’s exact test was used for statistical analysis. RESULTS: The prevalence of TYMS 2R/2R genotype was 24.6%. Among patients with TYMS genotypes (N = 71) that predict decreased TS expression, 2R/2R TYMS genotype was the most common TYMS genotype seen in female (57%) and African American (60%) patients. Among patients with genotypes that predict increased TS expression (N = 55), 12 patients had grade 3–4 FrAEs (22%), while among patients with genotypes that predict decreased TS expression (N = 71), 30 patients had grade 3–4 FrAEs (42%) (p = 0.0219). Compared to patients with genotypes predicting increased TS expression, 17 out of 31 patients (55%) with TYMS 2R/2R genotype had grade 3–4 FrAEs (p = 0.0039) and 15 out 40 patients (38%) with TYMS 2R/3RC and TYMS 3RC/3RC genotype had grade 3–4 FrAEs (p = 0.1108). CONCLUSION: The prevalence of TYMS 2R/2R genotype was 24.6%, and it had a unique sex and ethnic distribution. Polymorphism in the promoter region of TYMS gene that predicts decreased TS expression due to 2R/2R variant was associated with grade 3–4 FrAEs. These data suggest that genotyping patients who are not DPD deficient for TYMS might identify patients at risk of severe FrAEs