Sequence of Plasmodium falciparum chromosomes 2, 10, 11 and 14

The mosquito-borne malaria parasite Plasmodium falciparum kills an estimated 0.7-2.7 million people every year, primarily children in sub-Saharan Africa. Without effective interventions, a variety of factors-including the spread of parasites resistant to antimalarial drugs and the increasing insecticide resistance of mosquitoes-may cause the number of malaria cases to double over the next two decades. To stimulate basic research and facilitate the development of new drugs and vaccines, the genome of Plasmodium falciparum clone 3D7 has been sequenced using a chromosome-by-chromosome shotgun strategy. We report here the nucleotide sequences of chromosomes 10, 11 and 14, and a re-analysis of the chromosome 2 sequence. These chromosomes represent about 35% of the 23-megabase P. falciparum genome.     

Fine-scale phylogenetic architecture of a complex bacterial community

Although molecular data have revealed the vast scope of microbial diversity, two fundamental questions remain unanswered even for well-defined natural microbial communities: how many bacterial types co-exist, and are such types naturally organized into phylogenetically discrete units of potential ecological significance? It has been argued that without such information, the environmental function, population biology and biogeography of microorganisms cannot be rigorously explored. Here we address these questions by comprehensive sampling of two large 16S ribosomal RNA clone libraries from a coastal bacterioplankton community. We show that compensation for artefacts generated by common library construction techniques reveals fine-scale patterns of community composition. At least 516 ribotypes (unique rRNA sequences) were detected in the sample and, by statistical extrapolation, at least 1,633 co-existing ribotypes in the sampled population. More than 50% of the ribotypes fall into discrete clusters containing less than 1% sequence divergence. This pattern cannot be accounted for by interoperon variation, indicating a large predominance of closely related taxa in this community. We propose that such microdiverse clusters arise by selective sweeps and persist because competitive mechanisms are too weak to purge diversity from within them.     

Direct integration of Hox and segmentation gene inputs during Drosophila development

During Drosophila embryogenesis, segments, each with an anterior and posterior compartment, are generated by the segmentation genes while the Hox genes provide each segment with a unique identity. These two processes have been thought to occur independently. Here we show that abdominal Hox proteins work directly with two different segmentation proteins, Sloppy paired and Engrailed, to repress the Hox target gene Distalless in anterior and posterior compartments, respectively. These results suggest that segmentation proteins can function as Hox cofactors and reveal a previously unanticipated use of compartments for gene regulation by Hox proteins. Our results suggest that these two classes of proteins may collaborate to directly control gene expression at many downstream target genes.     

Suppression of anoikis and induction of metastasis by the neurotrophic receptor TrkB

Metastasis is a major factor in the malignancy of cancers, and is often responsible for the failure of cancer treatment. Anoikis (apoptosis resulting from loss of cell-matrix interactions) has been suggested to act as a physiological barrier to metastasis; resistance to anoikis may allow survival of cancer cells during systemic circulation, thereby facilitating secondary tumour formation in distant organs. In an attempt to identify metastasis-associated oncogenes, we designed an unbiased, genome-wide functional screen solely on the basis of anoikis suppression. Here, we report the identification of TrkB, a neurotrophic tyrosine kinase receptor, as a potent and specific suppressor of caspase-associated anoikis of non-malignant epithelial cells. By activating the phosphatidylinositol-3-OH kinase/protein kinase B pathway, TrkB induced the formation of large cellular aggregates that survive and proliferate in suspension. In mice, these cells formed rapidly growing tumours that infiltrated lymphatics and blood vessels to colonize distant organs. Consistent with the ability of TrkB to suppress anoikis, metastases--whether small vessel infiltrates or large tumour nodules--contained very few apoptotic cells. These observations demonstrate the potent oncogenic effects of TrkB and uncover a specific pro-survival function that may contribute to its metastatic capacity, providing a possible explanation for the aggressive nature of human tumours that overexpress TrkB.     

Bayesian integration in sensorimotor learning

When we learn a new motor skill, such as playing an approaching tennis ball, both our sensors and the task possess variability. Our sensors provide imperfect information about the ball's velocity, so we can only estimate it. Combining information from multiple modalities can reduce the error in this estimate. On a longer time scale, not all velocities are a priori equally probable, and over the course of a match there will be a probability distribution of velocities. According to bayesian theory, an optimal estimate results from combining information about the distribution of velocities-the prior-with evidence from sensory feedback. As uncertainty increases, when playing in fog or at dusk, the system should increasingly rely on prior knowledge. To use a bayesian strategy, the brain would need to represent the prior distribution and the level of uncertainty in the sensory feedback. Here we control the statistical variations of a new sensorimotor task and manipulate the uncertainty of the sensory feedback. We show that subjects internally represent both the statistical distribution of the task and their sensory uncertainty, combining them in a manner consistent with a performance-optimizing bayesian process. The central nervous system therefore employs probabilistic models during sensorimotor learning.     

Regulatory evolution across the protein interaction network

Protein-protein interactions may impose constraints on both structural and regulatory evolution. Here we show that protein-protein interactions are negatively associated with evolutionary variation in gene expression. Moreover, interacting proteins have similar levels of variation in expression, and their expression levels are positively correlated across strains. Our results suggest that interacting proteins undergo similar evolutionary dynamics, and that their expression levels are evolutionarily coupled. These patterns hold for organisms as diverse as budding yeast and fruit flies.