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In the normal murine mucosal plexus, blood flow is generally smooth and continuous. In inflammatory conditions, such as chemically-induced murine colitis, the mucosal plexus demonstrates markedly abnormal flow patterns. The inflamed mucosal plexus is associated with widely variable blood flow velocity as well as discontinuous and even bidirectional flow. To investigate the mechanisms responsible for these blood flow patterns, we used intravital microscopic examination of blood flow within the murine mucosal plexus during dextran sodium sulphate-and trinitrobenzenesulfonic acid-induced colitis. The blood flow patterns within the mucosal plexus demonstrated flow exclusion in 18% of the vessel segments (p<.01). Associated with these segmental exclusions was significant variation in neighboring flow velocities. Intravascular injection of fluorescent platelets demonstrated platelet incorporation into both fixed and rolling platelet aggregates. Rolling platelet aggregates (mean velocity 113um/sec; range 14 to 186um/sec) were associated with reversible occlusions and flow variations within the mucosal plexus. Gene expression profiles of microdissected mucosal plexus demonstrated enhanced expression of genes for CCL3, CXCL1, CCL2, CXCL5, CCL7, CCL8 and Il-1b (p<.01), and decreased expression of CCL6 (p<.01). These results suggest that platelet aggregation, activated by the inflammatory mileau, contributes to the complex flow dynamics observed in acute murine colitis.
In the normal murine mucosal plexus, blood flow is generally smooth and continuous. In inflammatory conditions, such as chemically-induced murine colitis, the mucosal plexus demonstrates markedly abnormal flow patterns. The inflamed mucosal plexus is associated with not only widely variable changes in blood flow velocity (Ravnic et al., 2007b), but discontinuous and even bidirectional flow (Turhan et al., 2007; Tsuda et al., 2008). These flow patterns in colitis are relevant to understanding not only metabolic supply and demand, but also flow-induced alterations in gene expression (Zhao et al., 2002; Chien, 2007).
Attempts to explain the vascular events in inflammatory bowel disease have focused on small vessel thrombosis. In regional enteritis, mucosal vascular changes—ranging from fibrin deposition to complete thrombotic occlusions—occurs early in the disease evolution and precedes mucosal ulceration (Wakefield et al., 1989). Platelets have been implicated in the capillary occlusion by immunostaining for the platelet glycoprotein IIIa (Hudson et al., 1993). Similarly, platelet-associated thrombotic changes have been implicated in the pathogenesis of colitis. Biopsies of patients with ulcerative colitis have identified intravascular platelet aggregates (Donnellan, 1966) and intracapillary thrombus (Dhillon et al., 1992). Murine models of chemically-induced colitis have demonstrated increased platelet adhesions in the inflammatory mucosal vessels (Mori et al., 2005a; Anthoni et al., 2006). Platelet adhesions to vessel walls have been correlated with both disease activity and vascular permeability (Mori et al., 2005b) and appear to be mediated, at least in part, by the platelet adhesion molecule P-selectin (Anthoni et al., 2006; Rivera-Nieves et al., 2006; Rijcken et al., 2007; Vowinkel et al., 2007b). Finally, the relevance of platelet activation is supported by studies of the CD40-CD40L signaling pathway in both patients (Danese et al., 2003) and murine models of coltis (Vowinkel et al., 2007a) Despite the growing evidence of platelet activation in the mucosal plexus, the effect of platelet aggregation on intramucosal blood flow patterns is unknown.
In this report, we investigated the blood flow patterns within the inflammatory colon microcirculation. Blood flow dynamics in the mucosal plexus were spatially associated with platelet aggregates and functionally implicated in both fixed and reversible flow exclusion. The mechanism of platelet activation was explored using RT-PCR arrays that demonstrated the expression of multiple platelet agonists within the inflamed mucosal plexus.
C57B/6 and BALB/c mice (Jackson Laboratory, Bar Harbor, ME), 25–33g, were used in all experiments. The care of the animals was consistent with guidelines of the American Association for Accreditation of Laboratory Animal Care (Bethesda, MD) and approved by the Institutional Animal Care and Use Committee (IACUC).
The dextran sodium sulfate (DSS) (TdB Consultancy AB, Uppsala, Sweden) model of colitis was similar to that described previously (Okayasu et al., 1990). Briefly, DSS was freshly prepared and added daily to the BALB/c mice drinking water at a final concentration of 5%. The mice were assessed daily for clinical signs and total body weight. The DSS treatment was continued for 7 days. The mice were studied on days 7 to 65. Acute colitis was defined as 7 to 10 days after DSS exposure.
The 2,4,6-Trinitrobenzenesulfonic acid (TNBS) (Sigma, St. Louis, MO) model of colitis was similar to that described previously (Ravnic et al., 2007a). After the mouse abdomen was sheared and cleansed with water, 36ul of a 2.5% 2,4,6-Trinitrochlorobenzene (TNCB)(ChemArt, Egling, Germany) in a 4:1 acetone:olive oil solution was sprayed onto a 1.5cm diameter circular PhastTansfer Filter Paper (Pharmacia, Upsala, Sweden). The TNCB soaked filter paper was applied to the sheared abdomen and secured with Tegaderm (3M, St. Paul, MN) and Durapore Surgical Tape (3M, St. Paul, MN). The TNCB patch was removed 24 hours after application. On post-sensitization day six, 125ul of 1.75% TNBS in a 50% ethanol solution was instilled into the rectum. Control mice had only the 50% ethanol solution instilled intrarectally. Acute colitis was defined as 5 to 7 days after TNBS exposure.
After systemic heparinization, PBS perfusion and intravascular fixation with 2.5% buffered glutaraldehyde, the systemic circulation was perfused with 10–20ml of Mercox (SPI, West Chester, PA) diluted with 20% methyl methacrylate monomers (Aldrich Chemical, Milwaukee, WI) as described previously (Konerding et al., 2001; Ravnic et al., 2005). After complete polymerization, the tissues were harvested and macerated in 5% potassium hydroxide followed by drying and mounting for scanning electron microscopy. The microvascular corrosion casts were imaged after coating with gold in an argon atmosphere with a Philips ESEM XL30 scanning electron microscope (Eindhoven, Netherlands)(Konerding et al., 1998).
The colon was exteriorized through a midline laparotomy incision and imaged using a Nikon Eclipse TE2000 inverted epifluorescence microscope using Nikon water dipping Fluor 10x, 20x, and 40x objectives. The intravital microscopy was performed by using a custom-machined immersion stage. The tissue contact area consisted of vacuum galleries that provided tissue apposition to the lens surface without tissue compression. An X-Cite (Exfo; Vanier, Canada) 120 watt metal halide light source and a liquid light guide was used to illuminate the tissue samples. Excitation and emission filters (Chroma, Rockingham, VT) in separate LEP motorized filter wheels were controlled by a MAC 5000 controller (Ludl, Hawthorne, NY) and MetaMorph Imaging System 7.5 software (MDS Analytical Technologies, Brandywine, PA). The intravital videomicroscopy 14-bit fluorescent images were digitally recorded with an electron multiplier CCD (EMCCD) camera (C9100-02, Hamamatsu, Japan). Images with 1000 × 1000 pixel resolution were routinely obtained at frame rates exceeding 60 fps with 2×2 binning or subarray acquisition. The images were recorded in image stacks comprising 30 second to 10 minute video sequences on a Dell Precision workstation (3.06Ghz Xeon processors, 15,000rpm ultra-SCSI hard drive, 4gb RAM and an Nvidia Quadro 3450 graphics card with 512mb memory). The image stacks were processed with standard MetaMorph filters.
Images were processesed with the MetaMorph 7.5 software (MDS Analytical Technologies). The 14-bit grayscale images were thresholded and standard distance calibration was performed. The MetaMorph’s region measurements and caliper applications were used to measure platelet aggregates. Routine distance calibration and thresholding was applied to the “stacked” image sequences (Ravnic et al., 2006b). The data was logged into Microsoft Excel 2003 (Redmond WA) by dynamic data exchange.
Platelet procedures were designed to avoid temperature variation or platelet agitation. After general anesthesia, 900ul of donor blood was obtained in a syringe filled with 0.1ml of citate-dextrose solution (Sigma, St Louis). The blood was sequentially centrifuged at 200×g, 500×g and 1000×g for 10 minutes followed by removal of the platelet rich plasma layer. The pooled platelet fractions were resuspended in 750ul of phosphate buffered saline. A 5-(and-6)-carboxyfluorescein diacetate succinimidyl ester (CFSE) (Invitrogen, Eugene, OR) fluorochrome solution was added to platelets at a final concentration of 125uM and incubated for 10 minutes at 25°C. The platelets were washed in a 10% citrate-dextrose solution and resuspended in 0.5ml of phosphate buffered saline. Typical platelet concentrations were 4.0–6.5×108/ml. The CFSE-labeled platelets (310ul) were injected into the mouse tail vein.
In vivo fluorescence labeling of circulating blood elements was performed with CFSE. CFSE (Invitrogen, Eugene, OR) labeling solution was prepared in DMSO as described (Becker et al., 2004; Ravnic et al., 2006a). The freshly prepared CFSE (400ul) was injected into the mouse tail vein over 2–3 minutes. The CFSE tracer (ex 480nm, em 520nm) was imaged with 25nm band pass filters (Omega).
The previously described 500nm polystyrene spheres were used to visualize flow fields by intravital microscopy (Ravnic et al., 2006a; Ravnic et al., 2006b). The particles were labeled with derivatives of the BODIPDY fluorochrome using organic solvents (Invitrogen; Eugene OR). The nanoparticles used in this study were typically green (ex 488; em 510); however, orange (ex 545nm; em 570nm) and infra-red (ex 655nm; em 710nm) tracers were also used.
Systematic and random sampling of tracer flow paths in the mucosal plexus was performed using isotropic line probes. A digital grid consisting of 4 parallel flow paths was overlaid on each on each intravital microscopy recording. The lines were shifted a random fraction of the spacing between lines, then rotated to an angle given by a random number between 0 and 180. The flow path most closely corresponding to the line probe was recorded. Optical resolution suitability of each segment of the flow path was assessed prior to data collection; segments without sufficient optical resolution were excluded from the data collection.
A space-time plot was drawn in each vessel segment through each random flow path using the MetaMorph 7.5 (MDS Analytical Technologies) kymograph application. Flux was calculated for each vessel segment as the number of tracers per unit time; thus, flux was independent of flow direction. Flux graphically represented on a stepcurve with each step reflecting a successive vessel segment. Variability of the flux was quantified using analysis of variance.
Tracking of the intravascular tracers was performed on digitally recorded and distance calibrated multi-image “stacks” (Ravnic et al., 2006a). The image stacks produced a sequential time history of velocity and direction as the acquired images were time stamped based on the 100mhz system bus clock of the Xeon processor (Intel, Santa Clara, CA). The movement of individual particles was tracked using the MetaMorph 7.5 (MDS Analytical Technologies) object tracking application. For displacement reference, the algorithm used the location of the particle at its first position in the stack. Each particle was imaged as a high contrast fluorescent disk and its position was determined with sub pixel accuracy. The image of the particle was tracked using a cross correlation centroid-finding algorithm to determine the best match of the particle/cell position in successive images. With routine distance calibration, the overlay of the image stack provided a quantitative assessment of the particle/cell path.
After routine distance calibration, the recorded image stack was processed using a custom MatLab (MathWorks, Natick, MA) algorithm. The speckles are identified as high contrast regions with speckle position determined with subpixel accuracy. The speckle displacement was identified using a cross correlation algorithm to determine the best match of the speckle pattern displacement in successive images. Instantaneous velocity was calculated and plotted based on the time intervals based on the 100mhz system bus clock of the Xeon processor (Intel, Santa Clara, CA).
The stream acquired images were stacked to create a time-series of 500 or 1000 consecutive frames. The stacks were systematically analyzed to ensure the absence of motion artifact. The stack “maximum” operation selected the highest intensity value for each pixel location throughout the time-series. The resultant image, reflecting a time-series reconstruction of particle locations during the time interval of the image stack, was segmented by particle density and pseudocolored into “high flow” and “low flow” regions. The pseudocolored image was overlaid on the original video series to facilitate the analysis of flow distribution.
After euthanasia, subtotal colectomy (cecum to sigmoid) was performed. The lumen was flushed and opened along the mesenteric border (McDonald and Newberry, 2007). The mucosa was copiously irrigated with cold PBS (4°C) until all debris was removed as determined by stereomicroscopy. The colon wall was immobilized on a standard microscope slide and the mucosa, superficial to the lamina propria, was removed using gentle dissection with a second microscope slide. Limited dissection of the superficial (approximately 50um thick) mucosa was confirmed by light microscopy. The microdissected mucosa was used for all subsequent mRNA analyses.
Total RNA was isolated using Qiagen RNeasy Midi Kit (Qiagen, Valencia, CA). Briefly, the fresh tissue was homogenized using a rotor-stator homogenizer for 60s until uniformly homogeneous. The tissue lysate was centrifuged at 3000×g for 10minutes and the supernatant (lysate) was removed by pipetting. An equal volume of 70% ethanol was added to lysate and gently mixed. The sample was placed in a RNeasy midi column, centrifuged for 5m at 3000×g and the flow-trough was discarded. After additional RPE buffer was added to the column, the tube was again centrifuged for 5m at 3000×g to dry the RNeasy silica-gel membrane. The RNeasy column was transferred to a collection tube and elution was performed using RNase-free water and centrifugation for 3m at 3000×g. Generally, a second elution step was not performed. Genomic DNA contamination was eliminated by RNase-Free DNase Set (Qiagen). Briefly, 1–2ug of potentially contaminated RNA was treated with DNase buffer, RNase inhibitor and DNase I. In all RNA isolations, the total RNA quality was assessed by using an Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA). RNA integrity numbers (RIN) (Schroeder et al., 2006) of the RNA samples were uniformally greater than 7.3 (mean 8.5; range 7.3 to 9.8).
First Strand cDNA Synthesis used RT2 First Strand Kit from SuperArray Bioscience Corporation. Mouse Angiogenesis RT2 Profiler PCR Array and RT2 Real-Timer SyBR Green/ROX PCR Mix were purchased from SuperArray Bioscience Corporation (Frederick, MD). The genes of interest in this study are shown in Table 1.
Real-time PCR was performed with SYBR green qPCR master mixes that include a chemically-modified hot start Taq DNA polymerase (SABioscience). PCR was performed on ABI 7300 Real-Time PCR System (Applied Biosystems). All reactions were 50 cycles using standard ABI cycling conditions (initial 2 minutes at 50°C, 10 minutes at 95°C and 1 minute annealing and extension at 60°C).
Gene expression was calculated using the comparative cycle threshold (Ct) method (Livak and Schmittgen, 2001). Although the data was monitored for nonideal efficiencies, comparable amplification of the target genes and reference genes was assumed. Every effort to optimize the reaction efficiency was made. Validation assays using serial dilutions of the target and reference genes were not routinely performed. The DSS-induced colitis and control data were plotted as a scattergram and a linear regression was calculated with 95% prediction bands after the data was imported into Origin 8.0 (OriginLab, North Hampton, MA). Linear regression was uniformly p<.0001. In nanoparticle velocity analyses, the unpaired Student’s t test for samples of unequal variances was used to calculate statistical significance. The data was expressed as mean ± one standard deviation. The significance level for the sample distribution was defined as P<.01. Volcano plots of the RT-PCR data were constructed with log fold change on the X-axis (reflecting biologic impact) and the p value on the Y-axis (statistical significance). The p values, representing the t-test comparison of inflamed and control microdissected mucosa, were plotted on a negative log scale to facilitate presentation.
The anatomy of the mucosal plexus, a quasi-polygonal network surrounding the mucosal crypts, was confirmed by corrosion casting and scanning electron microscopy (Figure 1A-B) as well as epi-illumination intravital microscopy (Figure 1C). In acute chemically-induced colitis, videomicroscopy of intravascular fluorescent tracers demonstrated flow velocities with wide dispersion (Figure 1D). Despite a lower mean velocity in colitis mice, the variability in blood flow velocity was higher than in control mice. To provide a more quantitative assessment of flow changes, systematic and random sampling of the mucosal plexus flow paths was performed. Tracer flux, reflecting volumetric blood flow, confirmed the flow variation in the colitis mice (Figure 2A–B). Analysis of variance demonstrated a highly significant difference between control and colitis animals (Figure 2C). The tracer flux variability appeared to be spatially associated with areas of zero flow; that is, vessel segments in which tracer flow was excluded. The number of excluded segments was significantly higher in colitis animals (p<.01; Figure 2D).
Microvessel segments excluded from mucosal plexus blood flow suggested a potential role for platelets in producing the observed blood flow patterns. After the intravascular injection of fluorescently labeled platelets, regions of tracer exclusion were spatially associated with the stable accumulation of platelets within the mucosal plexus. Within one hour of injection, stable or fixed platelet aggregates were present in 15% of excluded segments (N=6; range 12–23%)(Figure 3). The remaining excluded segments, not demonstrating platelet fluorescence, likely represented pre-existing thrombus (inaccessible to fluorescently labeled platelets) or alternative mechanisms of flow exclusion.
In contrast to platelet-associated occlusion of microvessels within the mucosal plexus, platelet aggregates were frequently observed at the bifurcations of collecting veins. The platelet aggregates demonstrated stable adherence to the endothelium, but dynamic extensions into the vessel lumen (Figure 4A). The blood flow velocity in the collecting veins, generally higher than in the mucosal plexus, suggested that the fluctuating luminal aggregates were responding to flow variation (Figure 4B). Regardless of the causal relationship, the apparent size of the aggregates varied over seconds (Figure 4C) and was associated with platelet microaggregates in the flow stream (Figure 4A, arrow).
In many capillaries and collecting veins, platelets were observed rolling on the endothelium. Although occasional platelet microaggregates were seen in the collecting veins of control mice, larger aggregates were frequent in both the mucosal plexus and collecting veins of colitis mice. In 6 colitis mice (TNBS N=3; DSS N=3), the rolling velocity of platelet aggregates ranged from 14 to 186 um/sec (mean=113um/sec). Because the mucosal plexus is an interconnected network of microvessels, rolling platelet aggregates were associated with transient occlusion of the collecting veins. Transient occlusions were followed by redistribution of blood flow and bidirectional movement of the aggregates. This pattern of reversible flow exclusion is illustrated in Figure 5A. As the platelet aggregate rolled “upstream,” connecting segments (Figure 5A, b1 and b2) of the mucosal plexus were initially excluded from the flow stream. With sufficient upstream displacement of the aggregate, the tracers in segments b1 and b2 subsequently passed into the draining vein. The velocity of the tracers, reflected in the b1 and b2 flow paths, was temporally linked to platelet displacement (Figure 5B). Of note, the rolling velocity of the platelet aggregate (50–100um/sec; Figure 5C) was typical of both large and small platelet aggregates.
The numerous platelet aggregates in the mucosal plexus suggested the importance of the local inflammatory milleau in platelet activation and subequent blood flow dynamics. To investigate the expression of platelet-associated factors associated with platelet activation, mRNA was harvested by microdissection of the mucosal plexus. Because of the more homogeneous and reproducible response to DSS, the longitudinal study of platelet-associated gene expression was limited to DSS-induced colitis. RT-PCR array analysis of gene expression was studied at 7, 14, 31 and 65 days after the start of DSS exposure. The peak of chemokine expression occurred 14 days after the start of DSS (Figure 6A). Consistent with intense inflammation, expression of genes for CCL3, CXCL1, CCL2, CXCL5, CCL7, CCL8 and Il-1b were significantly increased (p<.01), whereas the expression of CCL6 was significantly decreased (p<.01) 14 days after the onset of inflammation (Figure 6B).
In this report, we quantitatively assessed mucosal blood flow dynamics in chemically-induced murine colitis. The blood flow patterns within the mucosal plexus demonstrated 1) wide dispersion of flow velocity, 2) microvessel segments excluded from blood flow, 3) platelet aggregates spatially associated with blood flow perturbations, and 4) enhanced expression of platelet agonists within the mucosal plexus. These results suggest that platelet aggregation, activated by the inflammatory mileau, is a primary mechanism responsible for the complex flow dynamics observed in acute murine colitis.
Our in vivo observations suggest that the variability in mucosal plexus blood flow is a reflection of both platelet aggregation and the underlying structural anatomy of the plexus. The mucosal microcirculation is a non-parallel arteriovenous system fed by one or two central feeding arteries and draining marginal veins defining approximately 6500um2 of the mucosal plexus (Turhan et al., 2007). Within these flow regions, the mucosal plexus is a densely interconnected quasi-polygonal network without evidence of precapillary sphincter-like activity (Turhan et al., 2007). As result of the network structure, the isolated occlusion of a plexus vessel segment results in little risk to tissue viability. Blood flow can rapidly adapt and redistribute to meet tissue demands. In the present study, these adaptive flow changes were observed in the vessels adjacent to the occluded segment. In most instances, there was a sharp increase in blood flow in the segments connected to areas of presumed platelet-associated occlusion. The rapid adaptive changes in blood flow were even more apparent as a result of rolling platelet aggregates. Reversible occlusions were associated with rapid changes in mucosal plexus flow velocity and the redistribution of blood flow.
The variability in blood flow was spatially associated with microvascular segments that excluded intravascular tracers. In this report, we identified two mechanisms of flow exclusion. First, stable or fixed aggregates were identified within mucosal plexus capillaries. Second, rolling platelet aggregates in the collecting veins of the mucosal plexus resulted in reversible obstruction of segments of the mucosal plexus. Although platelets were spatially associated with perturbed blood flow patterns, it is likely that leukocytes and the coagulation cascade participated as well. Patients with inflammatory bowel disease have been shown to have more platelet-leukocyte aggregates (PLA) than healthy or inflammatory control subjects (Irving et al., 2008). It is possible that the microaggregates observed in the draining veins represented both platelet aggregates as well as PLA. Similarly, several studies have indicated subclinical activation of the coagulatory cascade (Chamouard et al., 1995; Souto et al., 1995). The vascular segments that excluded blood flow tracers likely reflected activation of both the coagulation cascade and circulating platelets.
Dynamic changes in blood patterns have adaptive consequences beyond sustaining organ viability and maintaining tissue function. Growing evidence indicates that endothelial cells respond to mechanical factors such as fluid shear stress (Davies, 1995; Gimbrone et al., 2000; Chien, 2007). Wall shear stress, reflecting both flow velocity and vessel geometry, activates a variety of mechanosensors (Labrador et al., 2003; Chien, 2007). Membrane molecules include receptor tyrosine kinases (Chen et al., 1999; Wang et al., 2002), integrins (Jalali et al., 2001; Schwartz, 2001), ion channels (Olesen et al., 1988; Yamamoto et al., 2006), G protein receptors (Kuchan et al., 1994) and even lipids (Haidekker et al., 2000). In turn, these membrane mechanoreceptors trigger signaling pathways that activate multiple genes that can be both homeostatic and proinflammatory (Chien, 2007). Here, we show that platelet aggregates in acute colitis produce abrupt changes in mucosal plexus blood flow. Additional work will be needed to determine if these changes in blood flow trigger the gene transcription associated with the structural adaptations and proinflammatory consequences observed in chronic colitis.
Whereas the presence of stable platelet aggregates within the mucosal plexus was consistent with the presence of strong agonists such as collagen and thrombin, the prevalence of dynamic or metastable aggregates suggested the presence of so-called weak agonists. Weak agonists have recently been shown to include a variety of chemokines including CCL5, CCL17 and CXCL12 (Clemetson et al., 2000; Abi-Younes et al., 2001; Shenkman et al., 2004). In our colitis model, we investigated the presence of these weak agonists by characterizing gene expression within the microdissected mucosal plexus. We analyzed platelet gene pathways of both blood vessels and infiltrating inflammatory cells. The enhanced expression of multiple platelet agonists, including CCL3, CCL5, CCL7, CXCL1 and CXCL5 indicates the prominent expression of multiple platelet agonists within the inflammatory microenvironment.
An intriguing observation is the significant elevation in CXCL1 gene expression in our model of murine colitis. Originally identified by subtractive hybridization of tumorigenic cells (Anisowicz et al., 1987), the chemokine CXCL1 is a high affinity ligand of the CXCR2 receptor and structurally related to CXCL5 and IL-8. CXCL1 is a potent mediator of tumor-associated angiogenesis (Strieter et al., 1995; Wang et al., 2006) and leukocyte chemoattraction. CXCL1 is found in platelet alpha-granules along with a number of other chemokines capable of attracting leukocytes and further activating other platelets (Gear and Camerini, 2003). Several findings have linked CXCL1 to colonic disease. Enhanced CXCL1 expression in the colon has been demonstrated in a variety of neoplastic conditions (Rubie et al., 2008) as well as in response to injury and/or inflammatory cytokines (Yang et al., 1997; Song et al., 1999; Thorpe et al., 2001). In addition to other studies demonstrating enhanced mRNA expression (Qualls et al., 2006; Wu and Chakravarti, 2007), increased levels of the CXCL1 chemokine have been demonstrated in the plasma of mice with chemically-induced colitis (Karlsson et al., 2008) as well as in the bowel lumen of human patients with colitis (Egesten et al., 2007). Finally, mice with a genetically engineered deficiency of CXCL1 have a markedly dysregulated response to DSS (Shea-Donohue et al., 2008). Although these results suggest an important role for CXCL1 in both human and murine colitis, the co-expression of multiple other platelet agonists suggest that single variable manipulations—such as treatment with a single chemokine antagonist—are unlikely to be revealing. The complexity of the inflammatory mileau will require an integrated experimental approach that assesses both extravascular inflammation and intravascular blood flow.
Finally, this study illustrates the challenges of characterizing the complex adaptive responses of the inflammatory microcirculation. In the mucosal plexus, segmental vascular occlusions were associated with not only variation in blood flow velocity, but also changes in blood flow direction. The complex blood flow patterns were not easily characterized by studying isolated components of the system. Future studies will benefit from 1) the development of spatial statistics capable of characterizing the variable velocity profiles across than network; 2) mosaicized video recordings that provide a near real-time assessment of blood flow patterns within entire flow regions of the mucosal plexus; and 3) network computational models that can accurately simulate perturbations in system components. These developments would provide useful insights into not only murine colitis, but similar biological processes characterized by adaptive change and feedback control.
Supported in part by NIH Grants HL47078, HL75426, HL054885, HL074022 and HL070542