Researchers at the Georgia Institute of Technology have developed a computer program that trains itself to predict genes in the DNA sequences of fungi.

Fungi – which range from yeast to mushrooms – are important for industry and human health, so understanding the recently sequenced fungal genomes can help in developing and producing critical pharmaceuticals. Gene prediction can also help to identify potential targets for therapeutic intervention and vaccination against pathogenic fungi.

"While we previously showed that our unsupervised training program worked well to predict genes in many eukaryotes, it didn't work as well for various fungal genomes that carry a significant part of the information that facilitates accurate gene prediction in locations called branch point sites," said Mark Borodovsky, director of Georgia Tech's Center for Bioinformatics and Computational Genomics.

Branch point sites are located inside introns, which are non-coding regions of DNA located between genetic-code carrying regions called exons.

"Previously during the process of predicting the exon-intron structure of eukaryotic genes, we didn't search for branch point sites, but doing so in the new program helps to better delineate intron regions inside fungal genes," added Borodovsky, who is also a Regents' Professor in the Coulter Department of Biomedical Engineering and the Computational Science and Engineering Division of the College of Computing.

Borodovsky and his colleagues expanded the eukaryotic genome self-training software program they developed in 2005 to address the issue that fungal genes are more complex than other eukaryotes. The research team included graduate student Vardges Ter-Hovhannisyan, Wallace H. Coulter Department of Biomedical Engineering research scientist Alexandre Lomsadze and School of Biology professor Yury Chernoff.

Details of the new program, called GeneMark.hmm-ES (BP), are available online in the journal Genome Research and will be included in the journal's December print edition. The software will also be freely available for academic researchers.

Borodovsky developed the first version of GeneMark in 1993. In 1995, this program was used to find genes in the first completely sequenced genomes of bacteria and archea. The research team then developed self-training versions of the gene finding program for prokaryotic (organisms that lack a cell nucleus) and eukaryotic (organisms that contain a cell nucleus) genomes in 2001 and 2005, respectively. Development of these programs has been supported by the National Institutes of Health.

Unlike other programs that require a pre-determined training set along with the genome sequence, GeneMark.hmm-ES (BP) only requires the genome sequence. The program is able to iteratively identify the correct algorithm parameters from the anonymous sequence. The program uses a probabilistic mathematical model called the Hidden Markov Model to pinpoint the boundaries between coding sequences (exons) and non-coding sequences (introns and intergenic regions).

Most introns start from the dinucleotide guanine-thymine (abbreviated GT) and end with the dinucleotide adenine-guanine (abbreviated AG). However, finding these dinucleotides is not sufficient to signal the presence of an intron. Several nucleotides that surround GT and AG are also important, but the similarity of the pattern is not deterministic. Locating the branch site – which is nine nucleotides in length, almost always contains an adenine and is located 20-50 bases upstream of the acceptor site – helps to accurately identify an intron.

An initial run of the program with a reduced model containing heuristically defined parameters breaks the sequence into coding and non-coding regions. With this information, the researchers apply machine-learning techniques to refine the parameters of the recognition algorithm with respect to the specific patterns found in the newly identified protein-coding and non-coding sequences as well as the border sites.

The prediction and training steps are repeated, each time detecting a larger set of true coding and non-coding sequences that are used to further improve the model employed in statistical pattern recognition. When the new sequence breakdown coincides with the previous one, the researchers record their final set of predicted genes.

To test the algorithm, the researchers selected 16 fungal species from the phyla Ascomycota, Basidiomycota and Zygomycota and compiled sets of genome sequences containing previously validated genes. The species spanned large evolutional distances and exhibited significant variability in genome size, gene number and average number of introns per gene. The results showed that by including branch site information in the model, the researchers could more accurately predict exon-intron structures of fungal genes.

"The enhanced program predicted fungal genes with higher accuracy than either the original self-training algorithm or known algorithms with supervised training," noted Borodovsky. "And because we didn't need any additional training information for our program, the sequencing teams could immediately proceed with gene annotation right after the genomic sequence was in hand without spending time and effort to extract a set of validated genes necessary for estimating parameters of traditional algorithms."

Researchers at the U.S. Department of Energy Joint Genome Institute and the Broad Institute of the Massachusetts Institute of Technology and Harvard University have already realized the advantages of the new algorithm. They have already used the new program to annotate about 20 novel fungal genomes. In addition, hundreds of fungal genome sequencing projects currently in progress should benefit from the new method as well, according to Borodovsky.

With the fungal software completed, Borodovsky and his team are already looking to expand their gene prediction algorithms to accurately interpret even more complex eukaryotic genomes.

"There are genome sequencing projects where large repeat populations, a significant number of pseudogenes or substantial sequence inhomogeneity hamper ab initio gene prediction and we're ready to tackle them next," added Borodovsky.

Thought processes made visible: An international team of scientists headed by Mazahir Hasan of the Max Planck Institute for Medical Research in Heidelberg has succeeded in optically detecting individual action potentials in the brains of living animals. The scientists introduced fluorescent indicator proteins into the brain cells of mice via viral gene vectors: the illumination of the fluorescent proteins indicates both when and which neurons are communicating with each other.

This new method enables the observation of brain activity over a period of many months and provides new ways of identifying, for example, the early onset of dysfunction in neurological disorders such as Alzheimer’s and Parkinson’s. The fluorescent proteins could also provide scientists with information about the ways in which normal aging processes affect nerve cell communication.

A nerve cell is a major hub for the exchange of valuable information. The nose, eyes, ears, and other sense organs perceive our environment through various antennae known as receptors. The numerous stimuli are then passed on to the neurons.

All of this information is collected, processed, and finally transferred to specific brain centers at these hubs - the human brain consists of almost 100 billion nerve cells. The nerve cell uses a special means of transport for this purpose: the action potential which codes the information, thus enabling communication between the nerve cells.

Calcium as the starting gun

An action potential of this kind is an electrical excitation and arises when our nerve cells receive the information via a stimulus: the voltage across the cell membrane of the neuron changes and various ion channels open and close in a very specialized manner. Shortly before the nerve cell forwards the information via the stimulus, calcium ions pour into the nerve cell, acting as the starting gun for the flow of data from one neuron to the next.

In the past, action potential was measured and rendered visible using microelectrodes. However, this method only enabled the monitoring of a limited number of cells engaged in the process of communication. Moreover, scientists were unable to record neuronal communication in a clearly identifiable way over a longer period or in freely moving animals using this method.

Yellow and blue fluorescent proteins

This situation could be set to change. As part of an intensive international cooperation project, Mazahir Hasan has made nerve cells, which release a single action potential, optically visible in mice. This means that the communication of entire groups of neurons can be observed over an extended period of time. Mazahir Hasan also attracted attention in 2004 when he demonstrated for the first time that fluorescent proteins are suitable for making activity in the brains of mice visible (Hasan et al., 2004 PLoS Biology 2:e163).

For this new recent development, Hasan used a sensor protein called D3cpv, which was generated by Amy Palmer at the Roger Tsien Laboratory of the University of California in San Diego, as a complex of numerous interconnected protein subunits. Two of these subunits react to the binding of calcium ions to the complex: the yellow-fluorescent protein (YFP) lights up and the illuminating power of cyan-fluorescent protein (CFP) declines - a coincidence that would later prove crucial to the success of the study.

The Max Planck scientists introduced the corresponding genetic material - that is the construction manual for this protein complex - into the genetic material of viruses. Hasan and his team then used these viruses as a genetic "ferry" for introducing the genetic material into the brains of mice. The protein complex was actually produced in the nerve cells of the "infected" mice and functions there as an calcium indicator: if the calcium level within a cell increases - which is the case with every action potential - the D3cpv changes form when it binds to calcium. As a result, the two fluorescent proteins, CFP and YFP, move closer to each other and the transmission of energy between the CFP and YFP changes.

"To observe this change, we use a two-photon microscope developed by Winfried Denk", explains Hasan. Each individual action potential that arises due to a stimulus makes itself directly perceivable in the brain through yellow illumination and the simultaneous reduction in the emission of blue light. The two-photon microscope pinpoints the coincidence between the two fluorescent signals very accurately and clearly reveals which nerve cells are communicating and exchanging information with each other and when.

Damian Wallace and Jason Kerr from the Max Planck Institute for Biological Cybernetics in Tübingen were able to confirm this finding: targeted electrical recordings of neuronal activity after the triggering of stimulus showed that the colour change actually coincides with the firing of the action potentials. Hasan’s method sheds light on which nerve cells will talk to each other and in which time period. However, it is only applicable if the neurons fire action potentials with a frequency of less than one hertz.

Insight into complex thought processes

The researchers were thus able to demonstrate for the first time that genetic calcium indicators provide optical proof of the perceptions of the sensory system in higher organisms. "With this method we can understand, in greater detail, how the human brain regulates complex thought processes and, for example, how it transforms the numerous sensory impressions into long-term memories", says Hasan. Developments resulting from the aging of the nerve cells can also be understood better as a result - "as we now have a way of observing the neurons over longer periods of time," concludes Hasan. Moreover, the sensor proteins could prove very useful in helping researchers to reach a better understanding at the cellular level of neurological diseases including Alzheimer’s, Parkinson’s, and Huntington’s chorea.

The 2008 ozone hole – a thinning in the ozone layer over Antarctica – is larger both in size and ozone loss than 2007 but is not as large as 2006.

Ozone is a protective atmospheric layer found in about 25 kilometres altitude that acts as a sunlight filter shielding life on Earth from harmful ultraviolet rays, which can increase the risk of skin cancer and cataracts and harm marine life.

This year the area of the thinned ozone layer over the South Pole reached about 27 million square kilometres, compared to 25 million square kilometres in 2007 and a record ozone hole extension of 29 million square kilometres in 2006, which is about the size of the North American continent.

The depletion of ozone is caused by extreme cold temperatures at high altitude and the presence of ozone-destructing gases in the atmosphere such as chlorine and bromine, originating from man-made products like chlorofluorocarbons (CFCs), which were phased out under the 1987 Montreal Protocol but continue to linger in the atmosphere.

Depending on the weather conditions, the size the Antarctic ozone hole varies every year. During the southern hemisphere winter, the atmosphere above the Antarctic continent is kept cut off from exchanges with mid-latitude air by prevailing winds known as the polar vortex – the area in which the main chemical ozone destruction occurs. The polar vortex is characterized by very low temperatures leading to the presence of so-called stratospheric clouds (PSCs).

As the polar spring arrives in September or October, the combination of returning sunlight and the presence of PSCs leads to a release of highly ozone-reactive chlorine radicals that break ozone down into individual oxygen molecules. A single molecule of chlorine has the potential to break down thousands of molecules of ozone.

Julian Meyer-Arnek of the German Aerospace Centre (DLR), which monitors the hole annually, explained the impact of regional meteorological conditions on the time and range of the ozone hole by comparing 2007 with 2008.

"In 2007 a weaker meridional heat transport was responsible for colder temperatures in the stratosphere over the Antarctic, leading to an intensified formation of PSCs in the stratosphere," Meyer-Arnek said. "Therefore, we saw a fast ozone hole formation in the beginning of September 2007."

"In 2008 a stronger-than-usual meridional heat transport caused warmer temperatures in the Antarctic stratosphere than usual, reducing the formation of PSCs. Consequently, the conversion of chemically inactive halogens into ozone-destroying substances was reduced. As a result in the beginning of September 2008, the ozone hole area was slightly smaller than average," he continued.

"Since the polar vortex remained undisturbed for a long period, the 2008 ozone hole became one of the largest ever observed."

Minimum values of the ozone layer of about 120 Dobson Units are observed this year compared to around 100 Dobson Units in 2006. A Dobson Unit is a unit of measurement that describes the thickness of the ozone layer in a column directly above the location of measurement.

DLR’s analysis is based upon the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) atmospheric sensor onboard ESA’s Envisat, the Global Ozone Monitoring Experiment (GOME) aboard ESA’s ERS-2 and its follow-on instrument GOME-2 aboard EUMETSAT’s MetOp.

Scientists say that since the size and precise time of the ozone hole is dependent on the year-to-year variability in temperature and atmospheric dynamics, the detection of signs of ozone recovery is difficult.

"In order to detect these signs of recovery, a continuous monitoring of the global ozone layer and in particular of the Antarctic ozone hole is crucial," Meyer-Arnek said.

In order to train the next generation of atmospheric scientists to continue the monitoring, students at ESA’s Advanced Atmospheric Training Course, held 15–20 September at University of Oxford, UK, were given the task of analysing this year’s ozone hole with Envisat sensors.

Studying the Envisat data, the students’ findings were in line with atmospheric scientists that the south polar vortex was more concentric in 2008 than in 2007, leading to a relatively late onset of ozone depletion, and that the size of this year’s hole is similar to previous years.

"This exercise led us to realise that although many questions have been answered and much has been learned about the stratospheric chemistry and atmospheric dynamics driving ozone hole behaviour, many new questions must be raised especially concerning ozone hole recovery," said Deborah C Stein Zweers, a post-doc satellite researcher from the Royal Netherlands Meteorological Institute (KNMI) who attended the course.

"We want to know when the ozone hole will recover, how its recovery will be complicated by an environment with increasing greenhouse gases and how atmospheric dynamics will shape future ozone holes. These and many other questions will attract the attention of our generation of scientists for the next several decades."