Prevalence and impacts of genetically engineered feedstuffs on livestock populations.

A new review study finds there is no evidence in earlier scientific studies indicating that genetically engineered feed crops harmed the health or productivity of livestock and poultry, and that food products from animals consuming such feeds were nutritionally the same as products from animals that ate non-GMO feeds. Globally, food-producing animals consume 70 to 90% of genetically engineered (GE) crop biomass. This review briefly summarizes the scientific literature on performance and health of animals consuming feed containing GE ingredients and composition of products derived from them. It also discusses the field experience of feeding GE feed sources to commercial livestock populations and summarizes the suppliers of GE and non-GE animal feed in global trade. Numerous experimental studies have consistently revealed that the performance and health of GE-fed animals are comparable with those fed isogenic non-GE crop lines. United States animal agriculture produces over 9 billion food-producing animals annually, and more than 95% of these animals consume feed containing GE ingredients.

Green soybean plants, mixed organic and GMO

Data on livestock productivity and health were collated from publicly available sources from 1983, before the introduction of GE crops in 1996, and subsequently through 2011, a period with high levels of predominately GE animal feed. These field data sets, representing over 100 billion animals following the introduction of GE crops, did not reveal unfavorable or perturbed trends in livestock health and productivity. No study has revealed any differences in the nutritional profile of animal products derived from GE-fed animals. Because DNA and protein are normal components of the diet that are digested, there are no detectable or reliably quantifiable traces of GE components in milk, meat, and eggs following consumption of GE feed. Globally, countries that are cultivating GE corn and soy are the major livestock feed exporters. Asynchronous regulatory approvals (i.e., cultivation approvals of GE varieties in exporting countries occurring before food and feed approvals in importing countries) have resulted in trade disruptions. This is likely to be increasingly problematic in the future as there are a large number of "second generation" GE crops with altered output traits for improved livestock feed in the developmental and regulatory pipelines. Additionally, advanced techniques to affect targeted genome modifications are emerging, and it is not clear whether these will be encompassed by the current GE process-based trigger for regulatory oversight. There is a pressing need for international harmonization of both regulatory frameworks for GE crops and governance of advanced breeding techniques to prevent widespread disruptions in international trade of livestock feed stuffs in the future.

Posted By:-

Biotechnology Department

Bioinformatics approach helps Researchers find new use for Old drug

Developing and testing a new anti-cancer drug can cost billions of dollars and take many years of research. Finding an effective anti-cancer medication from the pool of drugs already approved for the treatment of other medical conditions could cut a considerable amount of time and money from the process. Now, using a novel bioinformatics approach, a team led by investigators at Beth Israel Deaconess Medical Center (BIDMC) has found that the approved antimicrobial drug pentamidine may help in the treatment of patients with advanced kidney cancer. Described online in the journal Molecular Cancer Therapeutics, the discovery reveals how linking cancer gene expression patterns with drug activity might help advance cancer care.

"The strategy of repurposing drugs that are currently being used for other indications is of significant interest to the medical community as well as the pharmaceutical and biotech industries," says senior author Towia Libermann, PhD, Director of the Genomics, Proteomics, Bioinformatics and Systems Biology Center at BIDMC and Associate Professor of Medicine at Harvard Medical School. "Our results demonstrate that bioinformatics approaches involving the analysis and matching of cancer and drug gene signatures can indeed help us identify new candidate cancer therapeutics."

Renal cell cancer consists of multiple subtypes that are likely caused by different genetic mutations. Over the years, Libermann has been working to identify new disease markers and therapeutic targets through gene expression signatures of renal cell cancer that distinguish these different cancer subtypes from each other, as well as from healthy individuals. In this paper, he and his colleagues were looking for drugs that might be effective against clear cell renal cancer, the most common and highly malignant subtype of kidney cancer. Although patients with early stage disease can often be successfully treated through surgery, up to 30 percent of patients with renal cell cancer present with advanced stages of disease at the time of their diagnosis.

To pursue this search, they made use of the Connectivity Map (C-MAP) database (http://www.broadinstitute.org/cmap), a collection of gene expression data from human cancer cells treated with hundreds of small molecule drugs.

"C-MAP uses pattern-matching algorithms to enable investigators to make connections between drugs, genes and diseases through common, but inverse, changes in gene expression," says Libermann. "It provided us with an exciting opportunity to use our renal cell cancer gene signatures and a new bioinformatics strategy to match kidney cancer gene expression profiles from individual patients with gene expression changes inducted by various commonly used drugs."

After identifying drugs that may reverse the gene expression changes associated with renal cell cancer, the investigators used assays to measure the effect of the selected drugs on cells. This led to the identification of a small number of FDA-approved drugs that induced cell death in multiple kidney cancer cell lines. The investigators then tested three of these drugs in an animal model of renal cell cancer and demonstrated that the antimicrobial agent pentamidine (primarily used for the treatment of pneumonia) reduced tumor growth and enhanced survival. Gene expression experiments using microarrays also identified the genes in renal cell cancer that were counteracted by pentamidine.

Posted By:-

Bioinformatics Department