Fig 2: Cpt1a genetic knockdown modulates the metabolism of 12-HETE and its metabolites by RAW cells, etomoxir reduces the metabolism of tetranor triene in vivo, and prevents LPS stimulation of RANTES/TNFa generation, oxylipins regulate leukocyte responses, and transcriptomics of human neonatal sepsis proposes multiple genes that support a mitochondrial oxylipin ß-oxidation pathway.a–c Knockdown of Cpt1a alters 12-HETE metabolism. RAW cells were incubated ± LPS (100 ng/ml, for 4 h) with 12-HETE (2.34 µg/ml) added after the first hour (thus added for 3 h). Supernatants were harvested, then lipids were extracted and analyzed for 12-HETE and metabolites using LC/MS/MS as described in Methods (n = 4 (basal nonsil), 5 (basal Cpt1aKD), or 6 (other groups), separate wells of cells, mean ± SEM). d Tetranor triene 12-HETE is increased in vivo during inflammation with CPT1 inhibition. Wild-type mice (female, 7–9 weeks) were injected i.p. with vehicle (PBS), etomoxir (100 µg), and/or LPS (1 µg). After 6 h, lavage was harvested and lipids extracted and analyzed using LC/MS/MS as outlined in Methods (n = 10, individual mice). Outliers are shown as red, or with values. e, f Etomoxir dampens the generation of RANTES and TNF by peritoneal macrophages. Supernatants from macrophages cultured in vitro for 24 h with LPS (100 ng/ml)/etomoxir (25 µM) were tested for RANTES/CCL5 or TNF using ELISAs as described in Methods (n = 3 per group, separate wells of cells, mean ± SEM). a–f *p < 0.05, **p < 0.01, ***p < 0.005 with/without etomoxir, one-way ANOVA with Tukey post hoc test was used. g, h Oxylipin levels detected in vivo promote neutrophil ROS generation. Whole blood was incubated with oxylipin mixtures (Supplementary Table 1) , and then ROS generation in response to stimulation using opsonized S. epidermidis was determined by APF fluorescence as indicated in Methods. Three individual donor samples were separately tested. Monocytes and neutrophils were analyzed using the gating strategy as outlined in Methods. Response to high or low oxylipin doses was expressed either as %APF + cells or % of the vehicle (ethanol) response. Each donor is shown separately. Data were analyzed by repeated-measures two-way ANOVA (g—pairing p < 0.0001, cell type p = 0.018, lipid p = 0.0002, and interaction p = 0.0005; h—pairing p = 0.0008, cell type p = 0.0094, lipid p = 0.0082, and interaction p = 0.0024), Sidak’s post hoc tests are indicated—g Neutrophils ethanol vs low lipid p = 0.0001, neutrophils ethanol vs high lipid p < 0.0001, neutrophils low lipid vs high lipid p = 0.0350, monocytes ethanol vs low lipid p = 0.7020, monocytes ethanol vs high lipid p = 0.8075, monocytes low lipid vs high lipid p = 0.8075—h neutrophils low lipid vs high lipid p = 0.0023, monocytes low lipid vs high lipid p = 0.2363). i Oxylipin levels detected in vivo modulate CD4+ and CD8+ T-cell activation. Whole blood was incubated with oxylipin mixtures (Supplementary Table 1), and then generation of TNF was determined in response to activation using CD3/CD28 beads as indicated in Methods. CD8+ and CD4+ T cells were analyzed using the gating strategy outlined in Methods. Data from individual donors is shown. Two-way ANOVA (repeated measures) was used, pairing p = 0.0039, interaction p = 0.1690, cell type p = 0.0007, effect of lipid p = 0.0253, Sidak’s post hoc tests are indicated—CD4: no lipid vs low lipid p = 0.0461, CD4: no lipid vs high lipid p = 0.7115, CD4: low lipid vs high lipid p = 0.9989, CD8: no lipid vs low lipid p = 0.3742, CD8: no lipid vs high lipid p = 0.0449, CD8: low lipid vs high lipid p = 0.9952). j Human transcriptomics data show significant upregulation of several genes including ACSL and CPT isoforms. Gene expression (log2 expression data) from 35 controls and 26 bacterial confirmed sepsis cases published in57 were compared for expression of 32 genes putatively involved in mitochondrial import and ß-oxidation of oxylipins, based on known metabolic pathways for long-chain native FA. *p < 0.05, ***p < 0.005, Student’s t-test, two-tailed, then adjusted using Benjamini–Hochberg test.

Fig 3: PMNs inhibit HIV-1 replication in HLACs and HLH(A) Schematic of the experimental setup. HLACs and HLH were prepared from human tonsils, infected with HIV-1, and cultured in the presence (red) or absence (black) of 1 × 106 PMNs for 12–14 days. Cell culture supernatant was harvested every 2–3 days, and viral load was analyzed by SG-PERT.(B) Representative replication curves of HIV-1-infected HLACs ± T20 in the presence or absence of PMNs. Data points are mean values + SD of triplicate infections of cells from the same donor.(C) Representative flow cytometry dot plots of the cells analyzed in (B), stained for CD3 and CD8 at 14 dpi, followed by analysis of CD4 T cell depletion. Numbers indicate the percentage of cells of the total living cell population in the respective gate.(D) CD4 T cell depletion of the experiment shown in (C). The ratio of CD4 (CD3+CD8−) and CD8 (CD3+CD8+) T cells was calculated, and CD4 T cell depletion was determined relative to the respective mock samples, which were arbitrarily set to 0.(E) HIV-1 replication, depicted as the area under the curve (AUC) of 23 independent experiments performed in triplicates (mean + SD).(F) CD4 T cell depletion in HLACs from 14 donors, analyzed at 12–14 days post infection (dpi) as shown in (D). Shown are mean values of experiments performed in triplicates + SD.(G) Representative replication curves of HIV-1-infected HLHs ± T20 in the presence or absence of PMNs. Data points are mean values + SD of duplicates from one well containing four HLH blocks of the same donor.(H and I) HLACs from one donor (H) or activated PBMCs from two donors (I) were infected with X4 HIV-1 and cultured in the presence of 1 × 106 autologous (orange) or heterologous (red) PMNs or in the absence (black) of PMNs for additional 13 (HLACs) or 14 (PBMCs) days.Gray bars with errors in (E) and (F) indicate the median + interquartile range of all experiments and the fold reduction, respectively. Data points are mean values + SD of triplicate infections of cells from the same donor. Statistical significance was assessed by Mann-Whitney U test (∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.0001). See also Figure S1.

Fig 4: Early Antibody Responses to RV in the Nose Are Cross-Reactive, Limited to IgG, and Coincide with Infiltrating Dual-Specific B Cells(A) Immunohistochemistry analysis of nasal tissue analyzed for CD19 (green), CD3 (white), RV (red), and DNA (blue). Panels on the right show tissue from an uninfected subject (top) and from an infected subject at inferior turbinate (IT), middle turbinate (MT), and nasopharyngeal (NP) sites. Left panels show corresponding negative controls (Ctrl) prepared without primary antibodies. Data are representative of five subjects infected with RV-A16.(B) Cell counts in nasal biopsies from infected subjects after RV-A16 challenge and in uninfected (Un) controls (five per group). Specimens from uninfected subjects were available for a single nasal site only. Averages for each subject were calculated from four image locations within each biopsy.(C) Scatter plots of B cells isolated from nasal tissue (inferior turbinate) from a subject infected with RV-A16 at day 4. Memory B cells (CD19+IgD-) in the nose (black) are overlaid on memory B cells (gray) from the blood of a healthy control for comparison. Representative of three infected subjects.(D) Longitudinal analysis of antibody isotypes specific for homotypic or heterotypic virus (depending on infecting strain) in nasal washes during RV infection (subjects infected with RV-A16 and RV-A39 = 13 and 12, respectively; n = 25 for all time points).Significance was determined by Mann Whitney ranked-sum test (B) or Wilcoxon matched pairs signed-rank test (D). Geometric mean ± geometric SD (B and D).*p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001 versus uninfected tissue (B) or day 0 (D).See also Figures S4, S5, and S6.

Fig 5: Immune cell populations in colonic tissue from HSCR and control patients and in vitro T-cell conversion assay. (A) Flow cytometric analysis of mononuclear cells isolated from different aganglionic and ganglionic colonic segments of HSCR and control patients. Frequencies of total cells are shown. IL17+ Th17 T cells were gated in viable CD3+ CD4+ lymphocytes restimulated with PMA/ionomycin. Treg cells were defined as CD127- Foxp3+ cells in unstimulated viable CD3+ CD4+ lymphocytes. Fiber-low (n = 30); fiber-high (n = 13); AG DC (n = 10); G DC (n = 10); control DC (n = 5). CD14+ MF were gated in viable HLA+ CD64+ cells. Fiber-low (n = 26); fiber-high (n = 13); AG DC (n = 10); muscle (n = 10); G DC (n = 10); control DC (n = 5). Exact P values indicated in Table 10. (B) Frequencies of NCR+ (Nkp44+) and NCR- (Nkp44-) ILC3 (CD117+) subsets. Fiber-low (n = 17); fiber-high (n = 9); AG DC (n = 6); G DC (n = 6); control DC (n = 3). Figure 15 shows flow cytometric gating strategy. Scatter plots with bar show means ± standard error of the mean. Significance was determined by multiple comparison using one-way analysis of variance (*P = .05; **P = .01, ***P = .001, ****P = .0001); exact P values indicated in Table 10. (C) Quantitative RT-PCR analysis of full-thickness colonic tissue or isolated muscle tissue from different aganglionic and ganglionic colonic segments of HSCR and control patients (CX3CR1, circles and CCR2, squares). Significance was determined by using Wilcoxon matched-pairs signed-rank test. Fiber-low (n = 31); fiber-high (n = 13); AG DC (n = 12); G DC (n = 11); control DC (n = 5). (D and E) Representative brightfield microscopic images (original magnification, ×10) of M2 (D) and M1 (E) after 10 days of differentiation. Scale bar: 20 µm. (F and G) Flow cytometric analysis of blood-derived M1 and M2 macrophages from adult healthy donors. Histograms show CD14 (F) and CX3CR1 (G) expression in M1 (green) and M2 (blue) macrophages as well as in unstained controls (filled histograms). Representative analysis out of 3 independent experiments is shown. (H) Th17 and Treg conversion assay using blood-derived M1 and M2 macrophages. Frequencies of Th17 and Treg cells were determined, and Th17/Treg ratio was calculated. One out of 3 independent experiments is shown. Significance was determined using unpaired t test. Figure 15 indicates FACS gating strategy.