Genomic Instability in Liver Cells Caused by an LPS-Induced Bystander-Like Effect

<div><p>Bacterial infection has been linked to carcinogenesis, however, there is lack of knowledge of molecular mechanisms that associate infection with the development of cancer. We analyzed possible effects of the consumption of heat-killed <i>E. coli</i> O157:H7 cells or its cellular components, DNA, RNA, protein or lipopolysaccharides (LPS) on gene expression in naïve liver cells. Four week old mice were provided water supplemented with whole heat-killed bacteria or bacterial components for a two week period. One group of animals was sacrificed immediately, whereas another group was allowed to consume uncontaminated tap water for an additional two weeks, and liver samples were collected, post mortem. Liver cells responded to exposure of whole heat-killed bacteria and LPS with alteration in <i>γ</i>H2AX levels and levels of proteins involved in proliferation, DNA methylation (MeCP2, DNMT1, DNMT3A and 3B) or DNA repair (APE1 and KU70) as well as with changes in the expression of genes involved in stress response, cell cycle control and bile acid biosynthesis. Other bacterial components analysed in this study did not lead to any significant changes in the tested molecular parameters. This study suggests that lipopolysaccharides are a major component of Gram-negative bacteria that induce molecular changes within naïve cells of the host.</p></div

Western blot analysis of DNMT1 (A), DNMT3A (B), DNMT3B (C) and MeCP2 (D) protein levels in liver tissue of mice exposed to whole heat-killed <i>E. coli</i> O157:H7 bacteria and DNA, RNA, protein, and LPS extracted from heat-killed bacteria.

<p>Bars show the average protein levels (with SD) as compared to the control set at 100%. Asterisks and bars show significant increase from non-exposed controls through the analysis of data using one way ANOVA test (p<0.05). Lower panel shows representative Western blots in 2 and 4 weeks groups.</p

Exposure to LPS and Bacteria alters mRNA levels in mouse livers.

<p>A. Clustering of differential expression of genes with the use of control as a standard. Red denotes high expression levels, whereas green denotes low expression levels. RTPCR gene expression analysis of <i>Dusp1</i> (B), <i>Alas1</i> (C), <i>Tff3</i> (D), <i>Esm1</i> (E), <i>Mmd2</i> (F), <i>Gsta1</i> (G), <i>Cyp7A1</i> (H), <i>Gadd45g</i> (I). Bars show normalized expression levels (average from three reactions, with SD) of aforementioned genes in control and two groups exposed for 2 weeks, whole heat-killed bacteria and LPS groups. Normalization was conducted with Actin transcription levels. Asterisks indicate significant difference (p<0.05).</p

Immunohistochemical analysis of liver tissue samples stained with DAPI staining and Green Fluorescent antibody for PCNA.

<p><b>A</b>. Images of liver samples taken from individual animals within 2 week and 4 week test groups. B. Quantification of PCNA-positive cells. Bars represent the average (with SD) number of PCNA cells. Asterisks show significant differences from control (p<0.05).</p

Immunohistochemical analysis of liver tissue samples stained with DAPI staining and Green Fluorescent antibody for γH2AX.

<p>A. Images taken from animals in the group exposed to tap water (control), DNA, RNA, protein, LPS and whole heat-killed bacteria. B. Bars show the average (with SD) fold difference in number of γH2AX-positive cells between treated and control groups. Asterisks show significant difference from control (p<0.05).</p

Western blot analysis of KU70 (A), APE1 (B) and PCNA (C) protein levels in liver tissue of mice exposed to whole heat-killed <i>E. coli</i> O157:H7 bacteria and DNA, RNA, protein, and LPS extracted from heat-killed bacteria.

<p>Bars show the average protein levels (with SD) as compared to the control set at 100%. Asterisks and bars show significant increase from non-exposed controls through the analysis of data using one way ANOVA test (p<0.05). Lower panel shows representative Western blots in 2 and 4 weeks groups.</p

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<p>While the refinement of existing and the development of new chemotherapeutic regimens has significantly improved cancer treatment outcomes and patient survival, chemotherapy still causes many persistent side effects. Central nervous system (CNS) toxicity is of particular concern, as cancer patients experience significant deficits in memory, learning, cognition, and decision-making. These chemotherapy-induced cognitive changes are termed chemo brain, and manifest in more than half of cancer survivors. Moreover, recent studies have emerged suggesting that neurocognitive deficits manifest prior to cancer diagnosis and treatment, and thus may be associated with tumor presence, a phenomenon recently termed “tumor brain.” To dissect the molecular mechanisms of tumor brain, we used TumorGraft^TM models, wherein part of a patient's tumor is grafted into immune-deficient mice. Here, we analyzed molecular changes in the hippocampal tissues of mice carrying triple negative (TNBC) or progesterone receptor positive (PR+BC) xenografts. TNBC growth led to increased oxidative damage, as detected by elevated levels of 4-hydroxy-2-nonenal, a product of lipid peroxidation. Furthermore, the growth of TNBC and PR+BC tumors altered global gene expression in the murine hippocampus and affected multiple pathways implicated in PI3K-Akt and MAPK signaling, as well as other pathways crucial for the proper functioning of hippocampal neurons. TNBC and PR+BC tumor growth also led to a significant decrease in the levels of neuronal transcription factor NPAS4, a regulator that governs the expression of brain-derived neurotrophic factor (BDNF), and several other key brain neurotrophic factors and pro-survival molecules. The decreased expression of ERK1/2, NPAS4, and BDNF are also seen in neurodegenerative conditions and aging, and may constitute an important tumor brain mechanism.</p

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<p>Cancer survivors experience numerous treatment side effects that negatively affect their quality of life. Cognitive side effects are especially insidious, as they affect memory, cognition, and learning. Neurocognitive deficits occur prior to cancer treatment, arising even before cancer diagnosis, and we refer to them as “tumor brain.” Metabolomics is a new area of research that focuses on metabolome profiles and provides important mechanistic insights into various human diseases, including cancer, neurodegenerative diseases, and aging. Many neurological diseases and conditions affect metabolic processes in the brain. However, the tumor brain metabolome has never been analyzed. In our study we used direct flow injection/mass spectrometry (DI-MS) analysis to establish the effects of the growth of lung cancer, pancreatic cancer, and sarcoma on the brain metabolome of TumorGraft™ mice. We found that the growth of malignant non-CNS tumors impacted metabolic processes in the brain, affecting protein biosynthesis, and amino acid and sphingolipid metabolism. The observed metabolic changes were similar to those reported for neurodegenerative diseases and brain aging, and may have potential mechanistic value for future analysis of the tumor brain phenomenon.</p

Tactile stimulation restored forelimb function after ischemic lesion.

<p><b>A,</b> Success rate in the single pellet reaching task; <b>B,</b> Number of pellets obtained; <b>C,</b> Sequence of video frames depicting grasp, supination 1 and 2, and release components; <b>D,</b> Qualitative assessment of reaching components. Note that the ischemic lesion reduced quantitative (success, pellets obtained) and qualitative aspects of skilled reaching. Cumulative effects of prenatal and adult stress further reduced skilled reaching ability. TS promoted reaching success and movement ability. *p<0.05, **p<0.01.</p

Global gene expression analysis by microarrays was validated by RT-PCR analysis of selected genes.

<p><b>A, </b><i>Lgals3</i>; <b>B, </b><i>S100a4</i>; <b>C, </b><i>Vim</i>; <b>D, </b><i>B2m</i>; <b>E, </b><i>Egr1</i>; <b>F, </b><i>F2r</i>; <b>G, </b><i>Fabp7</i>; <b>H, </b><i>Gfap</i>; <b>I, </b><i>Hmgn.</i> All measurements were compared to naïve controls values. <i>Gadph</i> was used as a reference control for calculation of gene expression ratio. PCR-product amplification was confirmed by agarose electrophoresis gels (photographs).</p