The Toxicologist - Society of Toxicology

PAHs, such as dioxins, are prevalent contaminates that are produced by both natural
and man-made activities. 2,3,7,8 tetrachloro-dibenzo-p-dioxin (TCDD), is the
prototypical dioxin and a group I carcinogen. TCDD-induced toxicity has species
and tissue specificity, indicating the complex nature of AHR-mediated signaling
and biology. To date, a complete understanding of the AHR’s role on cellular
processes and how these are influenced in TCDD exposure remain incomplete. To
explore the potential influences of protein-protein interactions in AHR-mediated
signaling and toxicity, tandem affinity purification (TAP) and mass spectrometry
strategy was utilized to isolate and identify proteins that co-purify with the AHR.
This methodology was validated by the identification of the known protein interactions
between the AHR, Hsp90, and ARA9 and the ligand dependant association
with ARNT. Furthermore, using this technology, novel interactions for the AHR
have been indentified that connect the receptor to cellular energetics, cell cycle regulation,
cell death, mitochondrial function, and development. Here we present the
identification of the AHR-PIN and characterization of TCDD-induced changes in
the network.
128 SEQUENCE TAGGING REVEALS UNEXPECTED
MODIFICATIONS IN TOXICOPROTEOMICS.
S. Dasari 1 , M. C. Chambers 1 , D. C. Liebler 2 , F. P. Guengerich 2 and D. L. Tabb 1,
2 . 1 Biomedical Informatics, School of Medicine, Vanderbilt University, Nashville, TN
and 2 Biochemistry, School of Medicine, Vanderbilt University, Nashville, TN.
Rationale: Improved bioinformatics for detecting unexpected chemical and posttranslational
modifications in toxicoproteomic datasets.Toxicoproteomics produces
tandem mass spectra (MS/MS) that contain all the information needed to identify
modified peptides. Identifying these variant peptides, however, is intractable with
traditional database search engines. We have developed new software (TagRecon)
that leverages inferred sequence tags for detecting known and unknown modifications
present in toxicoproteomic datasets. TagRecon is integrated into a bioinformatics
pipeline containing a protein assembler and a user-friendly modification results
reviewer. The pipeline produces HTML reports of proteins, peptides, and
modifications. Processing a diverse collection of toxicoproteomic datasets with the
pipeline revealed a surprisingly wide palette of unanticipated modifications, none
of which were apparent via standard database search. We tested TagRecon with a
total of 1.5 million MS/MS produced from three complex toxicoproteomic experiments:
liver lysates of rats administered with five potentially hepatotoxic drugs;
THP1 cell lines treated with alkynylhydroxynonenal (alk-HNE); DNA/histone
complexes treated with 1,2-dibromoethane (EDB) and diepoxybutane (BDE).
TagRecon improved peptide identification rates by 50%-70% vs. the state-of-theart
InsPecT software. TagRecon revealed 25 proteins in rat liver samples (including
microsomal glutathione s-transferase 1, a known drug metabolite) that were targets
of drug-induced oxidative stress. In the DNA/histones sample, we detected unintended
cross-reactions between EDB and dimethylated histone lysines. Proteins in
the THP1 cell lines dataset contained unanticipated alk-HNE adducts. These experiments
demonstrate that toxicoproteomic datasets contain important additional
information that can be revealed through improved bioinformatics. The complete
set of tools is freely available from http://fenchurch.mc.vanderbilt.edu.
129 PROTEOMIC PROFILING OF DYNAMIC CELLULAR
RESPONSES TO SILICA NANOPARTICLES USING
STABLE ISOTOPE AMINO ACID LABELING.
B. Thrall 1 , B. Webb-Robertson 2 , K. Burnham 3 , M. H. Littke 1 , N. J. Karin 3 , J.
Jacobs 3 and K. M. Waters 2 . 1 Cell Biology & Biochemistry, PNNL, Richland, WA,
2 Computational Biology & Bioinformatics, PNNL, Richland, WA and 3 Biological
Separations & Mass Spectrometry Groups, Pacific Northwest National Laboratory,
Richland, WA.
In addition to transcriptional events, selective alterations in protein synthesis, stability
and degradation underlie many key cellular processes linked to pathological
outcomes. Motivated by the hypothesis that cellular responses to engineered
nanoparticles (ENPs) may be manifested by dynamic post-transcriptional events,
we conducted a proteomic analysis of the effects of SiO2 ENP exposure on mouse
lung epithelial cells. Our strategy involved mass spectrometry analysis of the metabolic
incorporation of a stable isotope labeled amino acid (+8 Da lysine) into proteins
over time to quantify the impacts of ENP treatment on levels of newly translated
proteins in mouse C10 cells during exposure to a threshold cytotoxic dose of
50 nm SiO2 ENPs for 1, 3, 5, 8 or 14 hrs. Among 457 proteins (777 peptides)
identified with sufficient data across time point for statistical analysis, over 200 proteins
showed significantly different (p