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Environmental Factor, February 2014

Extramural papers of the month

By Nancy Lamontagne

Srp logo : Read the current Superfund Research Program "Research Brief". New issues are pulblished on the first Wednesday of each month.

Transcription factor influences codon choice and protein evolution

Research, partially supported by an NIEHS grant funded by the National Institutes of Health Common Fund, revealed that complex genomes simultaneously code for amino acids and regulatory information. The work adds a transcription factor binding code to the spectrum of other regulatory codes that are believed to influence protein evolution by influencing codon choice.

Genomes contain protein-coding regions, as well as regulatory code that influences gene expression by specifying recognition sequences for transcription factors. Scientists have assumed that the genetic code and regulatory codes were physically and operationally independent. To find out if these codes intersect, the researchers created a nucleotide-resolution map showing where protein-coding regions of the human genome were occupied by a transcription factor. They looked at 81 diverse cell types, and found that approximately 15 percent of human codons simultaneously specify both proteins and transcription factor recognition sites. These dual-use codons, or duons, are highly conserved, and constraint from the transcription factors appears to be a major driver of codon usage bias. The researchers found that more than 17 percent of single-nucleotide variants within duons directly altered transcription factor binding.

The researchers concluded that widespread dual encoding of amino acid and regulatory information appears to be a fundamental feature of genome evolution.

CitationStergachis AB, Haugen E, Shafer A, Fu W, Vernot B, Reynolds A, Raubitschek A, Ziegler S, LeProust EM, Akey JM, Stamatoyannopoulos JA. (http://www.ncbi.nlm.nih.gov/pubmed/24337295)  2013. Exonic transcription factor binding directs codon choice and affects protein evolution. Science 342(6164):1367-1372.

Compound from mold linked to symptoms of Parkinson’s disease

NIEHS grantees report that an organic compound emitted by mold might be linked to Parkinson's and other neurodegenerative diseases in humans. Studies have found evidence that several environmental agents, especially pesticides, are possible risk factors for Parkinson’s disease, but this is the first naturally occurring environmental agent identified as a potential risk factor.

Exposure to fungi has been linked to movement disorders, as well as loss of balance and coordination, but the mechanisms involved in these health effects are unknown. To find out more about the possible toxicological effects of fungal volatile organic compounds associated with indoor environments, the researchers screened a variety of fungal toxicants using fruit flies. The volatile fungal semiochemical 1-octen-3-ol emerged as one of the most potent agents they tested. 1-octen-3-ol is commonly emitted by molds and is responsible for much of the moldy odor associated with fungal colonization.

Parkinson’s disease is associated with the loss of neurons that produce the neurotransmitter dopamine. The researchers found that low levels of 1-octen-3-ol reduced dopamine levels and caused dopamine neuron degeneration in the fruit flies. Genetic and cell culture studies revealed that 1-octen-3-ol most likely exerts toxicity by disrupting dopamine handling. The agent also increased loss of dopaminergic neurons through interactions with genetic variants of the vesicular monoamine transporter, which is involved in dopamine biosynthesis.   

CitationInamdar AA, Hossain MM, Bernstein AI, Miller GW, Richardson JR, Bennett JW. (http://www.ncbi.nlm.nih.gov/pubmed/24218591)  2013. Fungal-derived semiochemical 1-octen-3-ol disrupts dopamine packaging and causes neurodegeneration. Proc Natl Acad Sci U S A 110(48):19561-19566.

New tool for assessing ovarian cancer

An NIEHS grantee and colleagues developed a new technique that may help predict ovarian treatment response, cancer recurrence, and disease-free survival earlier and more effectively than current methods.

For many types of cancer, counting the number of tumor-attacking immune cells (TILs) that have migrated into the tumor offers a way to predict a patient’s survival. The number of TILs indicate the body’s immune response to the cancer, but current methods for counting TILs are either technically challenging or exhibit too much variability to be used for clinical decisions. The new approach, which the researchers call QuanTILfy, uses droplet digital polymerase chain reaction technology to count TILs reliably, quickly, and cheaply.

The researchers tested QuanTILfy on tumor samples from 30 ovarian cancer patients who had survival times ranging from one to 22 months. The results showed an association between higher TIL counts and improved survival among women with ovarian cancer, which was consistent with other studies that had found that a person’s immune response against ovarian cancer can be used to estimate survival.

The ability to reproducibly compute TILs in tumors with sensitivity may allow doctors to stratify and more effectively treat patients based on tumor TIL counts.

CitationRobins HS, Ericson NG, Guenthoer J, O'Briant KC, Tewari M, Drescher CW, Bielas JH. (http://www.ncbi.nlm.nih.gov/pubmed/24307693)  2013. Digital genomic quantification of tumor-infiltrating lymphocytes. Sci Transl Med. 5(214):214ra169.

Partnership identifies chemical-gene-disease interactions for inclusion in database

Environmental health researchers and pharmaceutical drug developers share the common goal of improving the ability to predict chemical toxicity. With this goal in mind, Pfizer safety scientists and the biocuration staff at the Comparative Toxicogenomics Database (http://ctdbase.org/)  (CTD) collaborated in text mining and manually reviewing more than 88,000 scientific articles, to develop a dataset of adverse events from drugs. Funded in part by NIEHS, this partnership demonstrates the benefits of resource sharing and collaboration between public and private entities with complementary needs.

CTD is a public database that promotes understanding about how the molecular interactions between environmental chemicals and genes affect human health. CTD curators use text mining and manual curation to convert knowledge from scientific papers into data on chemical-gene, chemical-disease, and gene-disease interactions that can be more easily managed, queried, explored, and analyzed. The collaborating researchers text mined and manually reviewed 88,629 articles with information on the potential involvement of 1,200 pharmaceutical drugs in cardiovascular, neurological, renal, and hepatic toxicity. In one year, this process produced 254,173 toxicogenomic interactions, including 152,173 chemical-disease, 58,572 chemical-gene, 5,345 gene-disease, and 38,083 phenotype interactions. All of these interactions are fully integrated into the public CTD.

CitationDavis AP, Wiegers TC, Roberts PM, King BL, Lay JM, Lennon-Hopkins K, Sciaky D, Johnson R, Keating H, Greene N, Hernandez R, McConnell KJ, Enayetallah AE, Mattingly CJ. (http://www.ncbi.nlm.nih.gov/pubmed/24288140)  2013. A CTD-Pfizer collaboration: manual curation of 88,000 scientific articles text mined for drug-disease and drug-phenotype interactions. Database (Oxford) 2013:bat080. Story

(Nancy Lamontagne is a science writer with MDB Inc., a contractor for the NIEHS Division of Extramural Research and Training.)



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