Identifying a predictive gene signature and signaling networks/pathways associated with acute kidney injury

Poster presented in SOT 2016<div><br></div><div>Understanding the molecular mechanisms and signaling networks of acute kidney injury (AKI) will aid in biomarker development. In this study, we carried out co-expression-based analyses of DrugMatrix, a toxicogenomics database with kidney gene expression data from rats after exposure to diverse chemicals. We used the iterative signature algorithm and exhaustively generated modules using 50 different parameter combinations. We clustered the modules using gene and condition overlap scores and obtained 16 module clusters. Two of the module clusters showed activation in chemical exposures causing kidney injury and mapped well-known AKI marker genes such as <i>Havcr1</i>, <i>Tff3,</i> and <i>Clu</i>. We used the genes in these AKI-relevant module clusters to develop a signature of 30 genes that could assess the potential of a chemical to cause kidney injury well before injury actually occurs. We integrated AKI-relevant module cluster genes with protein-protein interaction networks and identified the involvement of immunoproteasomes in AKI. To identify biological networks and processes linked to <em>Havcr1</em>, we determined genes within the modules that frequently co-express with <em>Havcr1</em>, including <em>Cd44</em>, <em>Plk2</em>, <em>Mdm2</em>, <em>Hnmt</em>, <em>Macrod1</em>, and <em>Gtpbp4</em>. In this gene set, CD44 is a potential non-invasive biomarker candidate as it is up-regulated during AKI, undergoes cleavage of its ectodomain, and is secreted in urine. Overall, our analysis shows data mining of toxicological big data and identification of new insights/biomarker candidates for acute kidney injury.</div

Detection of Dichlorvos Adducts in a Hepatocyte Cell Line

The toxicity of dichlorvos (DDVP), an organophosphate (OP) pesticide, classically results from modification of the serine in the active sites of cholinesterases. However, DDVP also forms adducts on unrelated targets such as transferrin and albumin, suggesting that DDVP could cause perturbations in cellular processes by modifying noncholinesterase targets. Here we identify novel DDVP-modified targets in lysed human hepatocyte-like cells (HepaRG) using a direct liquid chromatography–mass spectrometry (LC–MS) assay of cell lysates incubated with DDVP or using a competitive pull-down experiments with a biotin-linked organophosphorus compound (10-fluoroethoxyphosphinyl-<i>N</i>-biotinamidopentyldecanamide; FP-biotin), which competes with DDVP for similar binding sites. We show that DDVP forms adducts to several proteins important for the cellular metabolic pathways and differentiation, including glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and actin. We validated the results using purified proteins and enzymatic assays. The study not only identified novel DDVP-modified targets but also suggested that the modification directly inhibits the enzymes. The current approach provides information for future hypothesis-based studies to understand the underlying mechanism of toxicity of DDVP in non-neuronal tissues. The MS data have been deposited to the ProteomeXchange with identifier PXD001107

Comparisons of blood plasma and urine biomarkers (mean ± standard deviation) between time points (post kidney ischemia-reperfusion) in different treatment groups.^*

<p>*Creatinine and BUN (Blood Urea Nitrogen) were measured in blood plasma</p><p>Albumin, Lipocalin-2, Osteopontin, and KIM-1 (Kidney Injury Molecule-1) were measured in urine. <b>Normal/Naive,</b> plasma or urine drawn from naïve uninjured/untreated Wister rats served as base line. <b>VPA</b> (Valproic Acid), <b>Dex</b> (Dexamethasone) and <b>Vehicle</b> (saline control) treated groups at 3, 24 and 120 hour (h) reperfusion. Means with at least one common superscript (a, b or c) between 3, 24 or 120 h within each group (Vehicle, VPA or Dex) did not vary significantly (P>0.05).</p><p>Comparisons of blood plasma and urine biomarkers (mean ± standard deviation) between time points (post kidney ischemia-reperfusion) in different treatment groups.^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0126622#t001fn001" target="_blank">*</a>}</p

Effects of Valproic Acid and Dexamethasone Administration on Early Bio-Markers and Gene Expression Profile in Acute Kidney Ischemia-Reperfusion Injury in the Rat

<div><p>Renal ischemia-reperfusion (IR) causes acute kidney injury (AKI) with high mortality and morbidity. The objective of this investigation was to ameliorate kidney IR injury and identify novel biomarkers for kidney injury and repair. Under general anesthesia, left renal ischemia was induced in Wister rats by occluding renal artery for 45 minutes, followed by reperfusion and right nephrectomy. Thirty minutes prior to ischemia, rats (n = 8/group) received Valproic Acid (150 mg/kg; VPA), Dexamethasone (3 mg/kg; Dex) or Vehicle (saline) intraperitoneally. Animals were sacrificed at 3, 24 or 120 h post-IR. Plasma creatinine (mg/dL) at 24 h was reduced (P<0.05) in VPA (2.7±1.8) and Dex (2.3±1.2) compared to Vehicle (3.8±0.5) group. At 3 h, urine albumin (mg/mL) was higher in Vehicle (1.47±0.10), VPA (0.84±0.62) and Dex (1.04±0.73) compared to naïve (uninjured/untreated control) (0.14±0.26) group. At 24 h post-IR urine lipocalin-2 (μg/mL) was higher (P<0.05) in VPA, Dex and Vehicle groups (9.61–11.36) compared to naïve group (0.67±0.29); also, kidney injury molecule-1 (KIM-1; ng/mL) was higher (P<0.05) in VPA, Dex and Vehicle groups (13.7–18.7) compared to naïve group (1.7±1.9). Histopathology demonstrated reduced (P<0.05) ischemic injury in the renal cortex in VPA (Grade 1.6±1.5) compared to Vehicle (Grade 2.9±1.1). Inflammatory cytokines IL1β and IL6 were downregulated and anti-apoptotic molecule BCL2 was upregulated in VPA group. Furthermore, kidney DNA microarray demonstrated reduced injury, stress, and apoptosis related gene expression in the VPA administered rats. VPA appears to ameliorate kidney IR injury via reduced inflammatory cytokine, apoptosis/stress related gene expression, and improved regeneration. KIM-1, lipocalin-2 and albumin appear to be promising early urine biomarkers for the diagnosis of AKI.</p></div

Histopathology of hematoxylin and eosin stained kidney sections.

<p>A, B, C = Renal cortex at 3 hours (h) post ischemia-reperfusion (IR); D, E, F = Renal outer medulla at 24 h post-IR; A, D = Vehicle (saline control); B, E = Valproic acid (VPA); C, F = Dexamethasone (Dex) treated animals. Three high power fields (400x) representing approximately 50 tubules from cortex and outer medulla of each kidney were evaluated for ischemic changes (injury), tubular necrosis and regenerative changes. Collectively kidney injury and regeneration were graded (0–4) based on the mean percentage of tubules affected: 0, None; 1, <25%; 2, ≥25 but <50%; 3, ≥50 but <75%; 4, >75–100%. Ischemic changes included nuclear condensation <b>(nc)</b>, cytoplasmic eosinophilia, individual cell necrosis and tubular dilation <b>(td)</b>; tubular necrosis <b>(tn)</b> included confluent cell necrosis or sloughing of the tubular epithelium; and regenerative changes included tubular dilation, cytoplasmic basophilia and contraction of the cytoplasm, as well as vesicular chromatin with nucleoli. Hemorrhage <b>(hg)</b> was predominant in the vehicle control group. G, H, I = represent Histopathology quantification: renal cortex (black bars ■) and renal outer medulla (white bars □). The histologic injury score was significantly (P<0.05) lower in the VPA treated group compared to the Vehicle control at 3 h post-IR (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0126622#pone.0126622.t003" target="_blank">Table 3</a>).</p

Exposure to Cobalt Causes Transcriptomic and Proteomic Changes in Two Rat Liver Derived Cell Lines

<div><p>Cobalt is a transition group metal present in trace amounts in the human diet, but in larger doses it can be acutely toxic or cause adverse health effects in chronic exposures. Its use in many industrial processes and alloys worldwide presents opportunities for occupational exposures, including military personnel. While the toxic effects of cobalt have been widely studied, the exact mechanisms of toxicity remain unclear. In order to further elucidate these mechanisms and identify potential biomarkers of exposure or effect, we exposed two rat liver-derived cell lines, H4-II-E-C3 and MH1C1, to two concentrations of cobalt chloride. We examined changes in gene expression using DNA microarrays in both cell lines and examined changes in cytoplasmic protein abundance in MH1C1 cells using mass spectrometry. We chose to closely examine differentially expressed genes and proteins changing in abundance in both cell lines in order to remove cell line specific effects. We identified enriched pathways, networks, and biological functions using commercial bioinformatic tools and manual annotation. Many of the genes, proteins, and pathways modulated by exposure to cobalt appear to be due to an induction of a hypoxic-like response and oxidative stress. Genes that may be differentially expressed due to a hypoxic-like response are involved in Hif-1α signaling, glycolysis, gluconeogenesis, and other energy metabolism related processes. Gene expression changes linked to oxidative stress are also known to be involved in the NRF2-mediated response, protein degradation, and glutathione production. Using microarray and mass spectrometry analysis, we were able to identify modulated genes and proteins, further elucidate the mechanisms of toxicity of cobalt, and identify biomarkers of exposure and effect <i>in vitro</i>, thus providing targets for focused <i>in vivo</i> studies.</p></div

Modulated Extracellular Transcripts and Proteins.

<p>We identified 26 extracellular proteins and/or genes which encode extracellular protein whose expression was modulated in response to cobalt exposure. We propose them as candidate biomarkers of exposure or effect. We focused on extracellular proteins as they have the best potential to be identified through non-invasive methods.</p

Enriched Pathways.

<p>Enriched IPA canonical pathways are listed for the transcriptomic, proteomic, and combined data. We considered a pathway to be enriched at a p<.05 and contain more than 2 changing molecules.</p

Experimental design.

<p>Lewis rats were pre-medicated with Valproic acid (VPA; 150 mg/kg body weight) or Dexamethasone (Dex; 3 mg/kg/body weight) or saline (Vehicle control) intraperitoneally 30 minutes (min) prior to cross clamping left renal artery and inducing left renal ischemia. The cross clamp was removed after 45 min allowing kidney reperfusion, and at the same time a right nephrectomy was performed. Animals were sacrificed at 3, 24 and 120 hours post ischemia-reperfusion. Left kidney, blood and urine were collected for cellular and molecular analyses.</p

Oral Toxicity Database.

<p>An extensive database was created to access and prioritize the oral hazard of industrial chemicals based on the toxicity, stability, and usage of the chemical. This prioritization was limited to only pure elements and metal compounds.</p