Mismatch repair protein MLH1 suppresses replicative stress in BRCA2-deficient breast tumors

Loss of BRCA2 (breast cancer 2) is lethal for normal cells. Yet it remains poorly understood how, in BRCA2 mutation carriers, cells undergoing loss of heterozygosity overcome the lethality and undergo tissue-specific neoplastic transformation. Here, we identified mismatch repair gene mutL homolog 1 (MLH1) as a genetic interactor of BRCA2 whose overexpression supports the viability of Brca2-null cells. Mechanistically, we showed that MLH1 interacts with Flap endonuclease 1 (FEN1) and competes to process the RNA flaps of Okazaki fragments. Together, they restrained the DNA2 nuclease activity on the reversed forks of lagging strands, leading to replication fork (RF) stability in BRCA2-deficient cells. In these cells, MLH1 also attenuated R-loops, allowing the progression of stable RFs, which suppressed genomic instability and supported cell viability. We demonstrated the significance of their genetic interaction by the lethality of Brca2-mutant mice and inhibition of Brca2-deficient tumor growth in mice by Mlh1 loss. Furthermore, we described estrogen as inducing MLH1 expression through estrogen receptor α (ERα), which might explain why the majority of BRCA2 mutation carriers develop ER-positive breast cancer. Taken together, our findings reveal a role of MLH1 in relieving replicative stress and show how it may contribute to the establishment of BRCA2-deficient breast tumors.

Sequencing-based functional assays for classification of BRCA2 variants in mouse ESCs

Sequencing of genes, such as BRCA1 and BRCA2, is recommended for individuals with a personal or family history of early onset and/or bilateral breast and/or ovarian cancer or a history of male breast cancer. Such sequencing efforts have resulted in the identification of more than 17,000 BRCA2 variants. The functional significance of most variants remains unknown; consequently, they are called variants of uncertain clinical significance (VUSs). We have previously developed mouse embryonic stem cell (mESC)-based assays for functional classification of BRCA2 variants. We now developed a next-generation sequencing (NGS)-based approach for functional evaluation of BRCA2 variants using pools of mESCs expressing 10-25 BRCA2 variants from a given exon. We use this approach for functional evaluation of 223 variants listed in ClinVar. Our functional classification of BRCA2 variants is concordant with the classification reported in ClinVar or those reported by other orthogonal assays.

PKM2 dictates the poised chromatin state of PFKFB3 promoter to enhance breast cancer progression

The hypoxic milieu is a critical modulator of aerobic glycolysis, yet the regulatory mechanisms between the key glycolytic enzymes in hypoxic cancer cells are largely unchartered. In particular, the M2 isoform of pyruvate kinase (PKM2), the rate-limiting enzyme of glycolysis, is known to confer adaptive advantages under hypoxia. Herein, we report that non-canonical PKM2 mediates HIF-1α and p300 enrichment at PFKFB3 hypoxia-responsive elements (HREs), causing its upregulation. Consequently, the absence of PKM2 activates an opportunistic occupancy of HIF-2α, along with acquisition of a poised state by PFKFB3 HREs-associated chromatin. This poised nature restricts HIF-2α from inducing PFKFB3 while permitting the maintenance of its basal-level expression by harboring multiple histone modifications. In addition, the clinical relevance of the study has been investigated by demonstrating that Shikonin blocks the nuclear translocation of PKM2 to suppress PFKFB3 expression. Furthermore, TNBC patient-derived organoids and MCF7 cells-derived xenograft tumors in mice exhibited substantial growth inhibition upon shikonin treatment, highlighting the vitality of targeting PKM2. Conclusively, this work provides novel insights into the contributions of PKM2 in modulating hypoxic transcriptome and a previously unreported poised epigenetic strategy exhibited by the hypoxic breast cancer cells for ensuring the maintenance of PFKFB3 expression.

Saturation genome editing of 11 codons and exon 13 of BRCA2 coupled with chemotherapeutic drug response accurately determines pathogenicity of variants

The unknown pathogenicity of a significant number of variants found in cancer-related genes is attributed to limited epidemiological data, resulting in their classification as variant of uncertain significance (VUS). To date, Breast Cancer gene-2 (BRCA2) has the highest number of VUSs, which has necessitated the development of several robust functional assays to determine their functional significance. Here we report the use of a humanized-mouse embryonic stem cell (mESC) line expressing a single copy of the human BRCA2 for a CRISPR-Cas9-based high-throughput functional assay. As a proof-of-principle, we have saturated 11 codons encoded by BRCA2 exons 3, 18, 19 and all possible single-nucleotide variants in exon 13 and multiplexed these variants for their functional categorization. Specifically, we used a pool of 180-mer single-stranded donor DNA to generate all possible combination of variants. Using a high throughput sequencing-based approach, we show a significant drop in the frequency of non-functional variants, whereas functional variants are enriched in the pool of the cells. We further demonstrate the response of these variants to the DNA-damaging agents, cisplatin and olaparib, allowing us to use cellular survival and drug response as parameters for variant classification. Using this approach, we have categorized 599 BRCA2 variants including 93-single nucleotide variants (SNVs) across the 11 codons, of which 28 are reported in ClinVar. We also functionally categorized 252 SNVs from exon 13 into 188 functional and 60 non-functional variants, demonstrating that saturation genome editing (SGE) coupled with drug sensitivity assays can enhance functional annotation of BRCA2 VUS.

Injury measurements improve interpretation of thrombus formation data in the cremaster arteriole laser-induced injury model of thrombosis

Background

The cremaster arteriole laser-induced injury model is a powerful technique with which to investigate the molecular mechanisms that drive thrombus formation. This model is capable of direct visualization and quantification of accumulation of thrombus constituents, including both platelets and fibrin. However, a large degree of variability in platelet accumulation and fibrin formation is observed between thrombi. Strategies to understand this variability will enhance performance and standardization of the model. We determined whether ablation injury size contributes to variation in platelet accumulation and fibrin formation and, if so, whether incorporating ablation injury size into measurements reduces variation.

Methods

Thrombus formation was initiated by laser-induced injury of cremaster arterioles of mice (n=59 injuries). Ablation injuries within the vessel wall were consistently identified and quantified by measuring the length of vessel wall injury observed immediately following laser-induced disruption. Platelet accumulation and fibrin formation as detected by fluorescently-labeled antibodies were captured by digital intra-vital microscopy.

Results

Laser-induced disruption of the vessel wall resulted in ablation injuries of variable length (18-95 μm) enabling interrogation of the relationship between injury severity and thrombus dynamics. Strong positive correlations were observed between vessel injury length and both platelet and fibrin when the data are transformed as area under the curve (Spearman r = 0.80 and 0.76 respectively). Normalization of area under the curve measurements by injury length reduced intraclass coefficients of variation among thrombi and improved hypothesis testing when comparing different data sets.

Conclusions

Measurement of vessel wall injury length provides a reliable and robust marker of injury severity. Injury length can effectively normalize measurements of platelet accumulation and fibrin formation improving data interpretation and standardization.

Injury Length and Arteriole Constriction Shape Clot Growth and Blood-Flow Acceleration in a Mouse Model of Thrombosis

OBJECTIVE

Quantitative relationships between the extent of injury and thrombus formation in vivo are not well understood. Moreover, it has not been investigated how increased injury severity translates to blood-flow modulation. Here, we investigated interconnections between injury length, clot growth, and blood flow in a mouse model of laser-induced thrombosis. Approach and Results: Using intravital microscopy, we analyzed 59 clotting events collected from the cremaster arteriole of 14 adult mice. We regarded injury length as a measure of injury severity. The injury caused transient constriction upstream and downstream of the injury site resulting in a 50% reduction in arteriole diameter. The amount of platelet accumulation and fibrin formation did not depend on arteriole diameter or deformation but displayed an exponentially increasing dependence on injury length. The height of the platelet clot depended linearly on injury length and the arteriole diameter. Upstream arteriolar constriction correlated with delayed upstream velocity increase, which, in turn, determined downstream velocity. Before clot formation, flow velocity positively correlated with the arteriole diameter. After the onset of thrombus growth, flow velocity at the injury site negatively correlated with the arteriole diameter and with the size of the above-clot lumen.

CONCLUSIONS

Injury severity increased platelet accumulation and fibrin formation in a persistently steep fashion and, together with arteriole diameter, defined clot height. Arterial constriction and clot formation were characterized by a dynamic change in the blood flow, associated with increased flow velocity.

Controlled Multifactorial Coagulopathy: Effects of Dilution, Hypothermia, and Acidosis on Thrombin Generation In Vitro

BACKGROUND

Coagulopathy and hemostatic abnormalities remain a challenge in patients following trauma and major surgery. Coagulopathy in this setting has a multifactorial nature due to tissue injury, hemodilution, hypothermia, and acidosis, the severity of which may vary. In this study, we combined computational kinetic modeling and in vitro experimentation to investigate the effects of multifactorial coagulopathy on thrombin, the central enzyme in the coagulation system.

METHODS

We measured thrombin generation in platelet-poor plasma from 10 healthy volunteers using the calibrated automated thrombogram assay (CAT). We considered 3 temperature levels (31°C, 34°C, and 37°C), 3 pH levels (6.9, 7.1, and 7.4), and 3 degrees of dilution with normal saline (no dilution, 3-fold dilution, and 5-fold dilution). We measured thrombin-generation time courses for all possible combinations of these conditions. For each combination, we analyzed 2 scenarios: without and with (15 nM) supplementation of thrombomodulin, a key natural regulator of thrombin generation. For each measured thrombin time course, we recorded 5 quantitative parameters and analyzed them using multivariable regression. Moreover, for multiple combinations of coagulopathic conditions, we performed routine coagulation tests: prothrombin time (PT) and activated partial thromboplastin time (aPTT). We compared the experimental results with simulations using a newly developed version of our computational kinetic model of blood coagulation.

RESULTS

Regression analysis allowed us to identify trends in our data (P < 10). In both model simulations and experiments, dilution progressively reduced the peak of thrombin generation. However, we did not experimentally detect the model-predicted delay in the onset of thrombin generation. In accord with the model predictions, hypothermia delayed the onset of thrombin generation; it also increased the thrombin peak time (up to 1.30-fold). Moreover, as predicted by the kinetic model, the experiments showed that hypothermia increased the area under the thrombin curve (up to 1.97-fold); it also increased the height of the thrombin peak (up to 1.48-fold). Progressive acidosis reduced the velocity index by up to 24%; acidosis-induced changes in other thrombin generation parameters were much smaller or none. Acidosis increased PT by 14% but did not influence aPTT. In contrast, dilution markedly prolonged both PT and aPTT. In our experiments, thrombomodulin affected thrombin-generation parameters mainly in undiluted plasma.

CONCLUSIONS

Dilution with normal saline reduced the amount of generated thrombin, whereas hypothermia increased it and delayed the time of thrombin accumulation. In contrast, acidosis in vitro had little effect on thrombin generation.

Predictive Approach Identifies Molecular Targets and Interventions to Restore Angiogenesis in Wounds With Delayed Healing

Impaired angiogenesis is a hallmark of wounds with delayed healing, and currently used therapies to restore angiogenesis have limited efficacy. Here, we employ a computational simulation-based approach to identify influential molecular and cellular processes, as well as protein targets, whose modulation may stimulate angiogenesis in wounds. We developed a mathematical model that captures the time courses for platelets, 9 cell types, 29 proteins, and oxygen, which are involved in inflammation, proliferation, and angiogenesis during wound healing. We validated our model using previously published experimental data. By performing global sensitivity analysis on thousands of simulated wound-healing scenarios, we identified six processes (among the 133 modeled in total) whose modulation may improve angiogenesis in wounds. By simulating knockouts of 25 modeled proteins and by simulating different wound-oxygenation levels, we identified four proteins [namely, transforming growth factor (TGF)-β, vascular endothelial growth factor (VEGF), fibroblast growth factor-2 (FGF-2), and angiopoietin-2 (ANG-2)], as well as oxygen, as therapeutic targets for stimulating angiogenesis in wounds. Our modeling results indicated that simultaneous inhibition of TGF-β and supplementation of either FGF-2 or ANG-2 could be more effective in stimulating wound angiogenesis than the modulation of either protein alone. Our findings suggest experimentally testable intervention strategies to restore angiogenesis in wounds with delayed healing.

Impact of Tissue Factor Localization on Blood Clot Structure and Resistance under Venous Shear

The structure and growth of a blood clot depend on the localization of tissue factor (TF), which can trigger clotting during the hemostatic process or promote thrombosis when exposed to blood under pathological conditions. We sought to understand how the growth, structure, and mechanical properties of clots under flow are shaped by the simultaneously varying TF surface density and its exposure area. We used an eight-channel microfluidic device equipped with a 20- or 100-μm-long collagen surface patterned with lipidated TF of surface densities ∼0.1 and ∼2 molecules/μm². Human whole blood was perfused at venous shear, and clot growth was continually measured. Using our recently developed computational model of clot formation, we performed simulations to gain insights into the clot’s structure and its resistance to blood flow. An increase in TF exposure area resulted not only in accelerated bulk platelet, thrombin, and fibrin accumulation, but also in increased height of the platelet mass and increased clot resistance to flow. Moreover, increasing the TF surface density or exposure area enhanced platelet deposition by approximately twofold, and thrombin and fibrin generation by greater than threefold, thereby increasing both clot size and its viscous resistance. Finally, TF effects on blood flow occlusion were more pronounced for the longer thrombogenic surface than for the shorter one. Our results suggest that TF surface density and its exposure area can independently enhance both the clot’s occlusivity and its resistance to blood flow. These findings provide, to our knowledge, new insights into how TF affects thrombus growth in time and space under flow.

LPS-stimulated NF-κB p65 dynamic response marks the initiation of TNF expression and transition to IL-10 expression in RAW 264.7 macrophages

During injury and infection, inflammation is a response by macrophages to effect healing and repair. The kinetics of the responses of proinflammatory TNFα, anti-inflammatory IL-10, and inflammatory master regulator NF-κB elicited by lipopolysaccharide (LPS) may be critical determinants of the inflammatory response by macrophages; however, there is a lack of homogeneous kinetic data in this pathway. To address this gap, we used the RAW 264.7 macrophage cell line to define intracellular signaling kinetics and cytokine expression in cells treated with LPS for 15 min to 72 h. The abundance of IκBα was maximally reduced 45-min following LPS treatment, but expression increased at 10-h, reaching a maximum at 16 h. NF-κB phosphorylation was significantly increased 45-min following LPS treatment, maximal at 2-h, and decreased to basal levels by 6-h. Nuclear NF-κB expression was elevated 30-min following LPS treatment, maximal by 45-min, and returned to basal levels by 24-h. Binding of nuclear NF-κB to consensus oligonucleotide sequences followed a similar pattern to that observed for p-NF-κB, but lasted slightly longer. Following LPS treatment, TNFα mRNA expression began at 1-h, was maximal at 6-h, and decreased starting at 10-h. TNFα protein secretion in conditioned growth medium began at 4-h and was maximal by 16-h. IL-10 mRNA expression was induced by LPS at 10-h, and was maximal at 16-h. IL-10 protein secretion was induced at 16-h and was maximal at 24-h. Our data reveal the temporal kinetics of pro- and anti-inflammatory signaling events that may be important therapeutic targets for inflammatory diseases.

Computational Study of Thrombus Formation and Clotting Factor Effects under Venous Flow Conditions

A comprehensive understanding of thrombus formation as a physicochemical process that has evolved to protect the integrity of the human vasculature is critical to our ability to predict and control pathological states caused by a malfunctioning blood coagulation system. Despite numerous investigations, the spatial and temporal details of thrombus growth as a multicomponent process are not fully understood. Here, we used computational modeling to investigate the temporal changes in the spatial distributions of the key enzymatic (i.e., thrombin) and structural (i.e., platelets and fibrin) components within a growing thrombus. Moreover, we investigated the interplay between clot structure and its mechanical properties, such as hydraulic resistance to flow. Our model relied on the coupling of computational fluid dynamics and biochemical kinetics, and was validated using flow-chamber data from a previous experimental study. The model allowed us to identify the distinct patterns characterizing the spatial distributions of thrombin, platelets, and fibrin accumulating within a thrombus. Our modeling results suggested that under the simulated conditions, thrombin kinetics was determined predominantly by prothrombinase. Furthermore, our simulations showed that thrombus resistance imparted by fibrin was ∼30-fold higher than that imparted by platelets. Yet, thrombus-mediated bloodflow occlusion was driven primarily by the platelet deposition process, because the height of the platelet accumulation domain was approximately twice that of the fibrin accumulation domain. Fibrinogen supplementation in normal blood resulted in a nonlinear increase in thrombus resistance, and for a supplemented fibrinogen level of 48%, the thrombus resistance increased by ∼2.7-fold. Finally, our model predicted that restoring the normal levels of clotting factors II, IX, and X while simultaneously restoring fibrinogen (to 88% of its normal level) in diluted blood can restore fibrin generation to ∼78% of its normal level and hence improve clot formation under dilution.

Wound healing in Mac-1 deficient mice

Mac-1 (CD11b/CD18) is a macrophage receptor that plays several critical roles in macrophage recruitment and activation. Because macrophages are essential for proper wound healing, the impact of Mac-1 deficiency on wound healing is of significant interest. Prior studies have shown that Mac-1^-/- mice exhibit deficits in healing, including delayed wound closure in scalp and ear wounds. This study examined whether Mac-1 deficiency influences wound healing in small excisional and incisional skin wounds. Three millimeter diameter full thickness excisional wounds and incisional wounds were prepared on the dorsal skin of Mac-1 deficient (Mac-1^-/- ) and wild type (WT) mice, and wound healing outcomes were examined. Mac-1 deficient mice exhibited a normal rate of wound closure, generally normal levels of total collagen, and nearly normal synthesis and distribution of collagens I and III. In incisional wounds, wound breaking strength was similar for Mac-1^-/- and WT mice. Wounds of Mac-1 deficient mice displayed normal total macrophage content, although macrophage phenotype markers were skewed as compared to WT. Interestingly, amounts of TGF-β1 and its downstream signaling molecules, SMAD2 and SMAD3, were significantly decreased in the wounds of Mac-1 deficient mice compared to WT. The results suggest that Mac-1 deficiency has little impact on the healing of small excisional and incisional wounds. Moreover, the findings demonstrate that the effect of single genetic deficiencies on wound healing may markedly differ among wound models. These conclusions have implications for the interpretation of the many prior studies that utilize a single model system to examine wound healing outcomes in genetically deficient mice.

Computational identification and analysis of signaling subnetworks with distinct functional roles in the regulation of TNF production

Inflammation is a complex process driven by the coordinated action of a vast number of pro- and anti-inflammatory molecular mediators. While experimental studies have provided an abundance of information about the properties and mechanisms of action of individual mediators, essential system-level regulatory patterns that determine the time-course of inflammation are not sufficiently understood. In particular, it is not known how the contributions from distinct signaling pathways involved in cytokine regulation combine to shape the overall inflammatory response over different time scales. We investigated the kinetics of the intra- and extracellular signaling network controlling the production of the essential pro-inflammatory cytokine, tumor necrosis factor (TNF), and its anti-inflammatory counterpart, interleukin 10 (IL-10), in a macrophage culture. To tackle the intrinsic complexity of the network, we employed a computational modeling approach using the available literature data about specific molecular interactions. Our computational model successfully captured experimentally observed short- and long-term kinetics of key inflammatory mediators. Subsequent model analysis showed that distinct subnetworks regulate IL-10 production by impacting different temporal phases of the cAMP response element-binding protein (CREB) phosphorylation. Moreover, the model revealed that functionally similar inhibitory control circuits regulate the early and late activation phases of nuclear factor κB and CREB. Finally, we identified and investigated distinct signaling subnetworks that independently control the peak height and tail height of the TNF temporal trajectories. The knowledge of such subnetwork-specific regulatory effects may facilitate therapeutic interventions aimed at precise modulation of the inflammatory response.

Computational Identification of Mechanistic Factors That Determine the Timing and Intensity of the Inflammatory Response

Timely resolution of inflammation is critical for the restoration of homeostasis in injured or infected tissue. Chronic inflammation is often characterized by a persistent increase in the concentrations of inflammatory cells and molecular mediators, whose distinct amount and timing characteristics offer an opportunity to identify effective therapeutic regulatory targets. Here, we used our recently developed computational model of local inflammation to identify potential targets for molecular interventions and to investigate the effects of individual and combined inhibition of such targets. This was accomplished via the development and application of computational strategies involving the simulation and analysis of thousands of inflammatory scenarios. We found that modulation of macrophage influx and efflux is an effective potential strategy to regulate the amount of inflammatory cells and molecular mediators in both normal and chronic inflammatory scenarios. We identified three molecular mediators − tumor necrosis factor-α (TNF-α), transforming growth factor-β (TGF-β), and the chemokine CXCL8 − as potential molecular targets whose individual or combined inhibition may robustly regulate both the amount and timing properties of the kinetic trajectories for neutrophils and macrophages in chronic inflammation. Modulation of macrophage flux, as well as of the abundance of TNF-α, TGF-β, and CXCL8, may improve the resolution of chronic inflammation.

A recent approach to quantitatively characterize the timing and intensity of the inflammatory response relies on the use of four quantities termed inflammation indices. The values of the inflammation indices may reflect the differences between normal and pathological inflammation, and may be used to gauge the effects of therapeutic interventions aimed to control inflammation. Yet, the specific inflammatory mechanisms that can be targeted to selectively control these indices remain unknown. Here, we developed and applied a computational strategy to identify potential target mechanisms to regulate such indices. We used our recently developed model of local inflammation to simulate thousands of inflammatory scenarios. We then subjected the corresponding inflammation index values to sensitivity and correlation analysis. We found that the inflammation indices may be significantly influenced by the macrophage influx and efflux rates, as well as by the degradation rates of three specific molecular mediators. These results suggested that the indices can be effectively regulated by individual or combined inhibition of those molecular mediators, which we confirmed by computational experiments. Taken together, our results highlight possible targets of therapeutic intervention that can be used to control both the timing and the intensity of the inflammatory response.

Mechanistic Modeling of the Effects of Acidosis on Thrombin Generation

Supplemental Digital Content is available in the text.

Published ahead of print April 2, 2015

BACKGROUND:

Acidosis, a frequent complication of trauma and complex surgery, results from tissue hypoperfusion and IV resuscitation with acidic fluids. While acidosis is known to inhibit the function of distinct enzymatic reactions, its cumulative effect on the blood coagulation system is not fully understood. Here, we use computational modeling to test the hypothesis that acidosis delays and reduces the amount of thrombin generation in human blood plasma. Moreover, we investigate the sensitivity of different thrombin generation parameters to acidosis, both at the individual and population level.

METHODS:

We used a kinetic model to simulate and analyze the generation of thrombin and thrombin–antithrombin complexes (TAT), which were the end points of this study. Large groups of temporal thrombin and TAT trajectories were simulated and used to calculate quantitative parameters, such as clotting time (CT), thrombin peak time, maximum slope of the thrombin curve, thrombin peak height, area under the thrombin trajectory (AUC), and prothrombin time. The resulting samples of parameter values at different pH levels were compared to assess the acidosis-induced effects. To investigate intersubject variability, we parameterized the computational model using the data on clotting factor composition for 472 subjects from the Leiden Thrombophilia Study. To compare acidosis-induced relative parameter changes in individual (“virtual”) subjects, we estimated the probabilities of relative change patterns by counting the pattern occurrences in our virtual subjects. Distribution overlaps for thrombin generation parameters at distinct pH levels were quantified using the Bhattacharyya coefficient.

RESULTS:

Acidosis in the range of pH 6.9 to 7.3 progressively increased CT, thrombin peak time, AUC, and prothrombin time, while decreasing maximum slope of the thrombin curve and thrombin peak height (P < 10^–5). Acidosis delayed the onset and decreased the amount of TAT generation (P < 10^–5). As a measure of intrasubject variability, maximum slope of the thrombin curve and CT displayed the largest and second-largest acidosis-induced relative changes, and AUC displayed the smallest relative changes among all thrombin generation parameters in our virtual subject group (1-sided 95% lower confidence limit on the fraction of subjects displaying the patterns, 0.99). As a measure of intersubject variability, the overlaps between the maximum slope of the thrombin curve distributions at acidotic pH levels with the maximum slope of the thrombin curve distribution at physiological pH level systematically exceeded analogous distribution overlaps for CT, thrombin peak time, and prothrombin time.

CONCLUSIONS:

Acidosis affected all quantitative parameters of thrombin and TAT generation. While maximum slope of the thrombin curve showed the highest sensitivity to acidosis at the individual-subject level, it may be outperformed by CT, thrombin peak time, and prothrombin time as an indicator of acidosis at the subject-group level.

Kinetic model facilitates analysis of fibrin generation and its modulation by clotting factors: implications for hemostasis-enhancing therapies

Current mechanistic knowledge of protein interactions driving blood coagulation has come largely from experiments with simple synthetic systems, which only partially represent the molecular composition of human blood plasma. Here, we investigate the ability of the suggested molecular mechanisms to account for fibrin generation and degradation kinetics in diverse, physiologically relevant in vitro systems. We represented the protein interaction network responsible for thrombin generation, fibrin formation, and fibrinolysis as a computational kinetic model and benchmarked it against published and newly generated data reflecting diverse experimental conditions. We then applied the model to investigate the ability of fibrinogen and a recently proposed prothrombin complex concentrate composition, PCC-AT (a combination of the clotting factors II, IX, X, and antithrombin), to restore normal thrombin and fibrin generation in diluted plasma. The kinetic model captured essential features of empirically detected effects of prothrombin, fibrinogen, and thrombin-activatable fibrinolysis inhibitor titrations on fibrin formation and degradation kinetics. Moreover, the model qualitatively predicted the impact of tissue factor and tPA/tenecteplase level variations on the fibrin output. In the majority of considered cases, PCC-AT combined with fibrinogen accurately approximated both normal thrombin and fibrin generation in diluted plasma, which could not be accomplished by fibrinogen or PCC-AT acting alone. We conclude that a common network of protein interactions can account for key kinetic features characterizing fibrin accumulation and degradation in human blood plasma under diverse experimental conditions. Combined PCC-AT/fibrinogen supplementation is a promising strategy to reverse the deleterious effects of dilution-induced coagulopathy associated with traumatic bleeding.

Computational approach to characterize causative factors and molecular indicators of chronic wound inflammation

Chronic inflammation is rapidly becoming recognized as a key contributor to numerous pathologies. Despite detailed investigations, understanding of the molecular mechanisms regulating inflammation is incomplete. Knowledge of such critical regulatory processes and informative indicators of chronic inflammation is necessary for efficacious therapeutic interventions and diagnostic support to clinicians. We used a computational modeling approach to elucidate the critical factors responsible for chronic inflammation and to identify robust molecular indicators of chronic inflammatory conditions. Our kinetic model successfully captured experimentally observed cell and cytokine dynamics for both acute and chronic inflammatory responses. Using sensitivity analysis, we identified macrophage influx and efflux rate modulation as the strongest inducing factor of chronic inflammation for a wide range of scenarios. Moreover, our model predicted that, among all major inflammatory mediators, IL-6, TGF-β, and PDGF may generally be considered the most sensitive and robust indicators of chronic inflammation, which is supported by existing, but limited, experimental evidence.

Computational analysis of intersubject variability and thrombin generation in dilutional coagulopathy

BACKGROUND

Blood dilution is a frequent complication of massive transfusion during trauma and surgery. This article investigates the quantitative effects of blood plasma dilution on thrombin generation in the context of intersubject variability.

STUDY DESIGN AND METHODS

A thoroughly validated computational model was used to simulate thrombin generation curves for 472 healthy subjects in the Leiden Thrombophilia Study. Individual thrombin curves were calculated for undiluted blood and for different dilution scenarios. For every such curve, five standard quantitative parameters of thrombin generation were calculated and analyzed.

RESULTS

Thrombin generation parameters in diluted blood plasma displayed significant intersubject variability (with a coefficient of variation up to approx. 28%). Nevertheless, dilutional effects in the majority (or all) of the subjects in the study group were characterized by persistent patterns. In particular, the largest dilution-induced change typically occurred in the maximum slope (MS) of the thrombin curve, followed by a change in thrombin peak height (PH), whereas the smallest change often occurred in the area under the curve. The identified patterns demonstrated considerable robustness to variations in dilution scenario and tissue factor concentration.

CONCLUSION

Dilutional effects on thrombin generation in a human population can be predicted from trends identified for the "average" subject and then refined by performing an analysis of actual subjects in the study group. The MS and PH are dilution indicators that are both sensitive and reliable across a large subject group and could potentially be used as disease markers in the diagnosis of coagulopathic conditions.

Positive autoregulation shapes response timing and intensity in two-component signal transduction systems

Positive feedback loops are regulatory elements that can modulate expression output, kinetics and noise in genetic circuits. Transcriptional regulators participating in such loops are often expressed from two promoters, one constitutive and one autoregulated. Here, we investigate the interplay of promoter strengths and the intensity of the stimulus activating the transcriptional regulator in defining the output of a positively autoregulated genetic circuit. Using a mathematical model of two-component regulatory systems, which are present in all domains of life, we establish that positive feedback strongly affects the steady-state output levels at both low and high levels of stimulus if the constitutive promoter of the regulator is weak. By contrast, the effect of positive feedback is negligible when the constitutive promoter is sufficiently strong, unless the stimulus intensity is very high. Furthermore, we determine that positive feedback can affect both transient and steady state output levels even in the simplest genetic regulatory systems. We tested our modeling predictions by abolishing the positive feedback loop in the two-component regulatory system PhoP/PhoQ of Salmonella enterica, which resulted in diminished induction of PhoP-activated genes.

Response acceleration in post-translationally regulated genetic circuits

Transcription factors must often be chemically modified to perform their functions. Yet, it is not known whether the mechanisms that bring about such modifications impact the quantitative or kinetic properties of gene expression. Phosphorylation controls the activity of regulatory proteins of the two-component system family, which constitutes a prevalent form of bacterial signal transduction. These proteins are phosphorylated/dephosphorylated by cognate sensor proteins in response to specific signals. The phosphorylation level of the regulatory proteins is also modulated by small proteins-termed connectors-that are produced when a cell experiences signals other than those detected directly by the sensors. Here, we explore how differences in the targets (i.e., sensor or regulator) and the mechanisms used by connectors to generate phosphorylated regulatory proteins affect the output of two-component systems. Our mathematical modeling demonstrates that sensor-targeting mechanisms exhibit stronger response acceleration than those where the connector targets the regulator. These differences are robust to perturbations in kinetic parameters but dependent upon the specific sensor-to-regulator ratio and how the ratio is controlled in living cells. In contrast, the steady-state output levels of the circuits are determined primarily by the circuit parameters, and can be adjusted without affecting response acceleration. Likewise, the analyzed connector-mediated circuits exhibit similar noise generation properties. Our results highlight the relationship between the architecture of genetic regulatory circuits and their dynamic properties.

Signal integration in bacterial two-component regulatory systems

Two-component systems (TCSs) and phosphorelays are key mediators of bacterial signal transduction. The signals activating these systems promote the phosphorylated state of a response regulator, which is generally the form that carries out specific functions such as binding to DNA and catalysis of biochemical reactions. An emerging class of proteins-termed TCS connectors-modulate the output of TCSs by affecting the phosphorylation state of response regulators. TCS connectors use different mechanisms of action for signal integration, as well as in the coordination and fine-tuning of cellular processes. Present in both Gram-positive and Gram-negative bacteria, TCS connectors are critical for a variety of physiological functions including sporulation, competence, antibiotic resistance, and the transition to stationary phase.

Evolution and dynamics of regulatory architectures controlling polymyxin B resistance in enteric bacteria

Complex genetic networks consist of structural modules that determine the levels and timing of a cellular response. While the functional properties of the regulatory architectures that make up these modules have been extensively studied, the evolutionary history of regulatory architectures has remained largely unexplored. Here, we investigate the transition between direct and indirect regulatory pathways governing inducible resistance to the antibiotic polymyxin B in enteric bacteria. We identify a novel regulatory architecture—designated feedforward connector loop—that relies on a regulatory protein that connects signal transduction systems post-translationally, allowing one system to respond to a signal activating another system. The feedforward connector loop is characterized by rapid activation, slow deactivation, and elevated mRNA expression levels in comparison with the direct regulation circuit. Our results suggest that, both functionally and evolutionarily, the feedforward connector loop is the transitional stage between direct transcriptional control and indirect regulation.

A regulatory protein can activate the expression of a target gene either directly, i.e., by binding to the gene's promoter, or indirectly, i.e., by altering the expression of regulators, which, in turn, bind to the target gene's promoter and induce or inhibit its transcription. Indirect regulatory circuits can contain multiple components and functional elements, such as feedforward and feedback loops. The complex structure of indirect regulation raises the question of its evolutionary origins. Here, we study the dynamic and evolutionary properties of regulatory architectures that involve members of the recently emerged class of bacterial proteins termed connectors. Such proteins post-translationally modulate the activity of two-component systems and phosphorelays, which constitute the prevalent form of bacterial signal transduction. We describe a novel connector-mediated regulatory circuit that combines the structural and functional properties of direct and indirect regulation. Our results indicate that this architecture is the evolutionary link between direct and connector-dependent regulatory designs.

Positive feedback in cellular control systems

Feedback loops have been identified in a variety of regulatory systems and organisms. While feedback loops of the same type (negative or positive) tend to have properties in common, they can play distinctively diverse roles in different regulatory systems, where they can affect virulence in a pathogenic bacterium, maturation patterns of vertebrate oocytes and transitions through cell cycle phases in eukaryotic cells. This review focuses on the properties and functions of positive feedback in biological systems, including bistability, hysteresis and activation surges.

A connector of two-component regulatory systems promotes signal amplification and persistence of expression

Organisms rely on a variety of regulatory architectures to control gene transcription. Whereas the functional characteristics of particular architectures are well understood, the properties of newly discovered regulatory designs cannot be easily predicted. One emerging design depends on small proteins that connect two-component regulatory systems, which constitute the dominant form of bacterial signal transduction. These connectors enable one system to respond to the signal perceived by a different system. To understand the functional properties of such connector-mediated architectures, we investigated the pathway controlled by the PhoP-dependent connector protein PmrD of Salmonella enterica and contrasted it to the circuit in which genes are regulated directly by the transcription factor PhoP. The PmrD-mediated pathway displayed both signal amplification and persistence of expression when compared with the direct pathway. Mathematical modeling of the two pathways allowed us to identify critical factors responsible for signal amplification.

Convergence rate estimation for the TKF91 model of biological sequence length evolution

The TKF91 model of biological sequence evolution describes changes in the sequence length via an infinite state-space birth-death process, which we term the TKF91-BD process. The TKF91 model assumes that, for any pair of modern sequences, the ancestral sequence has equilibrium length distribution, an assumption whose validity has not been rigorously investigated. We obtain explicit upper and lower bounds on the rate of convergence to equilibrium for the distribution of the TKF91-BD process. We show that the rate of convergence of the TKF91-BD process for protein sequences with parameter values inferred from sequence data on alpha and beta globins is too low to guarantee convergence to equilibrium on a reasonable timescale. For the analyzed nucleotide sequences, the convergence is faster, but the equilibrium sequence length is unrealistically small. The Jukes-Cantor model of nucleotide substitutions can converge considerably faster than the length evolution model for both amino acid and nucleotide sequences, while the speed of convergence for the Kimura model is close to that for the TKF91-BD process describing nucleotide sequences.

Control of Streptococcus pyogenes virulence: modeling of the CovR/S signal transduction system

The CovR/S system in Streptococcus pyogenes (Group A Streptococcus, or GAS), a two-component signal transduction/transcription regulation system, controls the expression of major virulence factors. The presence of a negative feedback loop distinguishes the CovR/S system from the majority of bacterial two-component systems. We developed a deterministic model of the CovR/S system consisting of eight delay differential equations. Computational experiments showed that the system possessed a unique stable steady state. The dynamical behavior of the system showed a tendency for oscillations becoming more pronounced for longer but still biochemically realistic delays resulting from reductions in the rates of translation elongation. We have devised an efficient procedure for computing the system's steady state. Further, we have shown that the signal-response curves are hyperbolic for the default parameter values. However, in experiments with randomized parameters we demonstrated that sigmoidality of signal-response curves, implying a response threshold, is not only possible, but seems to be rather typical for CovR/S-like systems even when binding of the CovR response regulator protein to a promoter is non-cooperative. We used sensitivity analysis to simplify the model in order to make it analytically tractable. The existence and uniqueness of the steady state and hyperbolicity of signal-response curves for the majority of the variables was proved for the simplified model. Also, we found that provided CovS was active, the system was insensitive to changes in the concentration of any other phosphoryl donor such as acetyl phosphate.