Environmental biology

Iron-bearing minerals in sediments naturally reduce contaminant levelsApril 8, 2014

The release of wastes associated with nuclear reprocessing from storage facilities into the underlying sediments and groundwater is an important environmental concern. Scientists working with two national laboratories have found evidence that iron-bearing minerals naturally abundant in some sediments can react with and immobilize contaminants such as technetium.

Argonne partners with Metropolitan Water Reclamation District to study Chicago River microbe populationDecember 2, 2013

Scientists from the U.S. Department of Energy’s Argonne National Laboratory are partnering with the Metropolitan Water Reclamation District of Greater Chicago to find out the typical sources and distribution of microbial communities in Chicago area waterways.

Membrane protein kit may lead to better targeted drugsAugust 29, 2013

Argonne biologists Deborah Hanson and Phil Laible developed a method to produce large quantities of membrane proteins, which may lead to better targeted and more effective pharmaceuticals.

Methane-eating microbes found in Illinois aquiferJuly 24, 2013

A survey finds unusual methane-eating archaea in an Illinois aquifer.

X-ray analysis could boost legumes, thus reducing fertilizer pollutionApril 19, 2013

The overuse of nitrogen fertilizers in agriculture can wreak havoc on waterways, health and the environment. An international team of scientists aims to lessen the reliance on these fertilizers by helping beans and similar plants boost their nitrogen production, even in areas with traditionally poor soil quality.

Predicting the microbial “weather”April 16, 2012

Environmental microbiologist Jack Gilbert heads the Earth Microbiome Project, an initiative to sample and analyze DNA from bacteria, viruses, algae and fungi across the world. Our environment is full of microbes that affect everything from human health to climate change, and these microbes are constantly in flux. One of the project’s goals is to develop models that can predict fluctuations in advance.