Network analysis of differential Ras isoform mutation effects on intestinal epithelial responses to TNF-α

Tumor necrosis factor alpha (TNF-α) is an inflammatory cytokine that can elicit distinct cellular behaviors under different molecular contexts. Mitogen activated protein kinase (MAPK) pathways, especially the extracellular signal-regulated kinase (Erk) pathway, help to integrate influences from the environmental context, and therefore modulate the phenotypic effect of TNF-α exposure. To test how variations in flux through the Erk pathway modulate TNF-α-elicited phenotypes in a complex physiological environment, we exposed mice with different Ras mutations (K-Ras activation, N-Ras activation, and N-Ras ablation) to TNF-α and observed phenotypic and signaling changes in the intestinal epithelium. Hyperactivation of Mek1, an Erk kinase, was observed in the intestine of mice with K-Ras activation and, surprisingly, in N-Ras null mice. Nevertheless, these similar Mek1 outputs did not give rise to the same phenotype, as N-Ras null intestine was hypersensitive to TNF-α-induced intestinal cell death while K-Ras mutant intestine was not. A systems biology approach applied to sample the network state revealed that the signaling contexts presented by these two Ras isoform mutations were different. Consistent with our experimental data, N-Ras ablation induced a signaling network state that was mathematically predicted to be pro-death, while K-Ras activation did not. Further modeling by constrained Fuzzy Logic (cFL) revealed that N-Ras and K-Ras activate the signaling network with different downstream distributions and dynamics, with N-Ras effects being more transient and diverted more towards PI3K-Akt signaling and K-Ras effects being more sustained and broadly activating many pathways. Our study highlights the necessity to consider both environmental and genomic contexts of signaling pathway activation in dictating phenotypic responses, and demonstrates how modeling can provide insight into complex in vivo biological mechanisms, such as the complex interplay between K-Ras and N-Ras in their downstream effects.National Institute of General Medical Sciences (U.S.) (Grant R01-GM088827)National Cancer Institute (U.S.) (U54-CA112967)United States. Army Research Office (Institute for Collaborative Biotechnologies Grant W911NF-09-D-000

In Vivo Systems Analysis Identifies Spatial and Temporal Aspects of the Modulation of TNF-α-Induced Apoptosis and Proliferation by MAPKs

Cellular responses to external stimuli depend on dynamic features of multipathway network signaling; thus, cell behavior is influenced in a complex manner by the environment and by intrinsic properties. Methods of multivariate systems analysis have provided an understanding of these convoluted effects, but only for relatively simplified examples in vitro. To determine whether such approaches could be successfully used in vivo, we analyzed the signaling network that determines the response of intestinal epithelial cells to tumor necrosis factor–α (TNF-α). We built data-driven, partial least-squares discriminant analysis (PLSDA) models based on signaling, apoptotic, and proliferative responses in the mouse small intestinal epithelium after systemic exposure to TNF-α. The extracellular signal–regulated kinase (ERK) signaling axis was a critical modulator of the temporal variation in apoptosis at different doses of TNF-α and of the spatial variation in proliferation in distinct intestinal regions. Inhibition of MEK, a mitogen-activated protein kinase kinase upstream of ERK, altered the signaling network and changed the temporal and spatial phenotypes consistent with model predictions. Our results demonstrate the dynamic, adaptive nature of in vivo signaling networks and identify natural, tissue-level variation in responses that can be deconvoluted only with quantitative, multivariate computational modeling. This study lays a foundation for the use of systems-based approaches to understand how dysregulation of the cellular network state underlies complex diseases.National Institute of General Medical Sciences (U.S.) (Grant R01-GM088827)National Cancer Institute (U.S.) (Grant U54-CA112967

Multi-Scale In Vivo Systems Analysis Reveals the Influence of Immune Cells on TNF-α-Induced Apoptosis in the Intestinal Epithelium

Intestinal epithelial cells exist within a complex environment that affects how they interpret and respond to stimuli. We have applied a multi-scale in vivo systems approach to understand how intestinal immune cells communicate with epithelial cells to regulate responses to inflammatory signals. Multivariate modeling analysis of a large dataset composed of phospho-signals, cytokines, and immune cell populations within the intestine revealed an intimate relationship between immune cells and the epithelial response to TNF-α. Ablation of lymphocytes in the intestine prompted a decrease in the expression of MCP-1, which in turn increased the steady state number of intestinal plasmacytoid dendritic cells (pDCs). This change in the immune compartment affected the intestinal cytokine milieu and subsequent epithelial cell signaling network, with cells becoming hypersensitive to TNF-α-induced apoptosis in a way that could be predicted by mathematical modeling. In summary, we have uncovered a novel cellular network that regulates the response of intestinal epithelial cells to inflammatory stimuli in an in vivo setting

Feasibility of Universal Anomaly Detection without Knowing the Abnormality in Medical Images

Many anomaly detection approaches, especially deep learning methods, have been recently developed to identify abnormal image morphology by only employing normal images during training. Unfortunately, many prior anomaly detection methods were optimized for a specific "known" abnormality (e.g., brain tumor, bone fraction, cell types). Moreover, even though only the normal images were used in the training process, the abnormal images were often employed during the validation process (e.g., epoch selection, hyper-parameter tuning), which might leak the supposed ``unknown" abnormality unintentionally. In this study, we investigated these two essential aspects regarding universal anomaly detection in medical images by (1) comparing various anomaly detection methods across four medical datasets, (2) investigating the inevitable but often neglected issues on how to unbiasedly select the optimal anomaly detection model during the validation phase using only normal images, and (3) proposing a simple decision-level ensemble method to leverage the advantage of different kinds of anomaly detection without knowing the abnormality. The results of our experiments indicate that none of the evaluated methods consistently achieved the best performance across all datasets. Our proposed method enhanced the robustness of performance in general (average AUC 0.956)

Childhood loneliness as a predictor of adolescent depressive symptoms: an 8-year longitudinal study

Childhood loneliness is characterised by children’s perceived dissatisfaction with aspects of their social relationships. This 8-year prospective study investigates whether loneliness in childhood predicts depressive symptoms in adolescence, controlling for early childhood indicators of emotional problems and a sociometric measure of peer social preference. 296 children were tested in the infant years of primary school (T1 5 years of age), in the upper primary school (T2 9 years of age) and in secondary school (T3 13 years of age). At T1, children completed the loneliness assessment and sociometric interview. Their teachers completed externalisation and internalisation rating scales for each child. At T2, children completed a loneliness assessment, a measure of depressive symptoms, and the sociometric interview. At T3, children completed the depressive symptom assessment. An SEM analysis showed that depressive symptoms in early adolescence (age 13) were predicted by reports of depressive symptoms at age 8, which were themselves predicted by internalisation in the infant school (5 years). The interactive effect of loneliness at 5 and 9, indicative of prolonged loneliness in childhood, also predicted depressive symptoms at age 13. Parent and peer-related loneliness at age 5 and 9, peer acceptance variables, and duration of parent loneliness did not predict depression. Our results suggest that enduring peer-related loneliness during childhood constitutes an interpersonal stressor that predisposes children to adolescent depressive symptoms. Possible mediators are discussed

BAY61-3606 Affects the Viability of Colon Cancer Cells in a Genotype-Directed Manner

Background: K-RAS mutation poses a particularly difficult problem for cancer therapy. Activating mutations in K-RAS are common in cancers of the lung, pancreas, and colon and are associated with poor response to therapy. As such, targeted therapies that abrogate K-RAS-induced oncogenicity would be of tremendous value. Methods: We searched for small molecule kinase inhibitors that preferentially affect the growth of colorectal cancer cells expressing mutant K-RAS. The mechanism of action of one inhibitor was explored using chemical and genetic approaches. Results: We identified BAY61-3606 as an inhibitor of proliferation in colorectal cancer cells expressing mutant forms of K-RAS, but not in isogenic cells expressing wild-type K-RAS. In addition to its anti-proliferative effects in mutant cells, BAY61-3606 exhibited a distinct biological property in wild-type cells in that it conferred sensitivity to inhibition of RAF. In this context, BAY61-3606 acted by inhibiting MAP4K2 (GCK), which normally activates NFκβ signaling in wild-type cells in response to inhibition of RAF. As a result of MAP4K2 inhibition, wild-type cells became sensitive to AZ-628, a RAF inhibitor, when also treated with BAY61-3606. Conclusions: These studies indicate that BAY61-3606 exerts distinct biological activities in different genetic contexts

Molecular network analysis of phosphotyrosine and lipid metabolism in hepatic PTP1b deletion mice

Metabolic syndrome describes a set of obesity-related disorders that increase diabetes, cardiovascular, and mortality risk. Studies of liver-specific protein-tyrosine phosphatase 1b (PTP1b) deletion mice (L-PTP1b[superscript −/−]) suggest that hepatic PTP1b inhibition would mitigate metabolic-syndrome through amelioration of hepatic insulin resistance, endoplasmic-reticulum stress, and whole-body lipid metabolism. However, the altered molecular-network states underlying these phenotypes are poorly understood. We used mass spectrometry to quantify protein-phosphotyrosine network changes in L-PTP1b[superscript −/−] mouse livers relative to control mice on normal and high-fat diets. We applied a phosphosite-set-enrichment analysis to identify known and novel pathways exhibiting PTP1b- and diet-dependent phosphotyrosine regulation. Detection of a PTP1b-dependent, but functionally uncharacterized, set of phosphosites on lipid-metabolic proteins motivated global lipidomic analyses that revealed altered polyunsaturated-fatty-acid (PUFA) and triglyceride metabolism in L-PTP1b[superscript −/−] mice. To connect phosphosites and lipid measurements in a unified model, we developed a multivariate-regression framework, which accounts for measurement noise and systematically missing proteomics data. This analysis resulted in quantitative models that predict roles for phosphoproteins involved in oxidation–reduction in altered PUFA and triglyceride metabolism.Pfizer Inc. (grant)National Institutes of Health (U.S.) (grant 5R24DK090963)National Institutes of Health (U.S.) (grant U54-CA112967)National Institutes of Health (U.S.) (grant CA49152 R37)National Institutes of Health (U.S.) (grant R01-DK080756)National Mouse Metabolic Phenotyping Center at UMASS (Grant (U24-DK093000))National Science Foundation (U.S.) (Graduate Research Fellowship

Cell Spatial Analysis in Crohn's Disease: Unveiling Local Cell Arrangement Pattern with Graph-based Signatures

Crohn's disease (CD) is a chronic and relapsing inflammatory condition that affects segments of the gastrointestinal tract. CD activity is determined by histological findings, particularly the density of neutrophils observed on Hematoxylin and Eosin stains (H&E) imaging. However, understanding the broader morphometry and local cell arrangement beyond cell counting and tissue morphology remains challenging. To address this, we characterize six distinct cell types from H&E images and develop a novel approach for the local spatial signature of each cell. Specifically, we create a 10-cell neighborhood matrix, representing neighboring cell arrangements for each individual cell. Utilizing t-SNE for non-linear spatial projection in scatter-plot and Kernel Density Estimation contour-plot formats, our study examines patterns of differences in the cellular environment associated with the odds ratio of spatial patterns between active CD and control groups. This analysis is based on data collected at the two research institutes. The findings reveal heterogeneous nearest-neighbor patterns, signifying distinct tendencies of cell clustering, with a particular focus on the rectum region. These variations underscore the impact of data heterogeneity on cell spatial arrangements in CD patients. Moreover, the spatial distribution disparities between the two research sites highlight the significance of collaborative efforts among healthcare organizations. All research analysis pipeline tools are available at https://github.com/MASILab/cellNN.Comment: Submitted to SPIE Medical Imaging. San Diego, CA. February 202

mPGES-1-Mediated Production of PGE2 and EP4 Receptor Sensing Regulate T Cell Colonic Inflammation

PGE2 is a lipid mediator of the initiation and resolution phases of inflammation, as well as a regulator of immune system responses to inflammatory events. PGE2 is produced and sensed by T cells, and autocrine or paracrine PGE2 can affect T cell phenotype and function. In this study, we use a T cell-dependent model of colitis to evaluate the role of PGE2 on pathological outcome and T-cell phenotypes. CD4+ T effector cells either deficient in mPGES-1 or the PGE2 receptor EP4 are less colitogenic. Absence of T cell autocrine mPGES1-dependent PGE2 reduces colitogenicity in association with an increase in CD4+RORγt+ cells in the lamina propria. In contrast, recipient mice deficient in mPGES-1 exhibit more severe colitis that corresponds with a reduced capacity to generate FoxP3+ T cells, especially in mesenteric lymph nodes. Thus, our research defines how mPGES-1-driven production of PGE2 by different cell types in distinct intestinal locations impacts T cell function during colitis. We conclude that PGE2 has profound effects on T cell phenotype that are dependent on the microenvironment

MTG16 regulates colonic epithelial differentiation, colitis, and tumorigenesis by repressing E protein transcription factors

Aberrant epithelial differentiation and regeneration contribute to colon pathologies, including inflammatory bowel disease (iBD) and colitis-associated cancer (CAC). Myeloid translocation gene 16 (MTG16, also known as CBFA2T3) is a transcriptional corepressor expressed in the colonic epithelium. MTG16 deficiency in mice exacerbates colitis and increases tumor burden in CAC, though the underlying mechanisms remain unclear. Here, we identified MTG16 as a central mediator of epithelial differentiation, promoting goblet and restraining enteroendocrine cell development in homeostasis and enabling regeneration following dextran sulfate sodium-induced (DSS-induced) colitis. Transcriptomic analyses implicated increased Ephrussi box-binding transcription factor (E protein) activity in MTG16-deficient colon crypts. Using a mouse model with a point mutation that attenuates MTG16:E protein interactions (Mtg16(P20ST)), we showed that MTG16 exerts control over colonic epithelial differentiation and regeneration by repressing E protein-mediated transcription. Mimicking murine colitis, MTG16 expression was increased in biopsies from patients with active IBD compared with unaffected controls. Finally, uncoupling MTG16:E protein interactions partially phenocopied the enhanced tumorigenicity of Mtg16(-/)(-) colon in the azoxymethane/DSS-induced model of CAC, indicating that MTG16 protects from tumorigenesis through additional mechanisms. Collectively, our results demonstrate that MTG16, via its repression of E protein targets. is a key regulator of cell fate decisions during colon homeostasis, colitis, and cancer.Peer reviewe