Mitochondrial proteins essential for viability mediate protein import into yeast mitochondria

Only five mitochondrial proteins are known to be essential for viability of the yeast Saccharomyces cerevisiae; all of them are key components of the mitochondrial protein import system. Other components of this system are not essential for life; they include functionally redundant import receptors on the mitochondrial surface and enzymes acting upon only a few precursor proteins.     

Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations

It is well established that autism spectrum disorders (ASD) have a strong genetic component; however, for at least 70% of cases, the underlying genetic cause is unknown. Under the hypothesis that de novo mutations underlie a substantial fraction of the risk for developing ASD in families with no previous history of ASD or related phenotypes--so-called sporadic or simplex families--we sequenced all coding regions of the genome (the exome) for parent-child trios exhibiting sporadic ASD, including 189 new trios and 20 that were previously reported. Additionally, we also sequenced the exomes of 50 unaffected siblings corresponding to these new (n = 31) and previously reported trios (n = 19), for a total of 677 individual exomes from 209 families. Here we show that de novo point mutations are overwhelmingly paternal in origin (4:1 bias) and positively correlated with paternal age, consistent with the modest increased risk for children of older fathers to develop ASD. Moreover, 39% (49 of 126) of the most severe or disruptive de novo mutations map to a highly interconnected β-catenin/chromatin remodelling protein network ranked significantly for autism candidate genes. In proband exomes, recurrent protein-altering mutations were observed in two genes: CHD8 and NTNG1. Mutation screening of six candidate genes in 1,703 ASD probands identified additional de novo, protein-altering mutations in GRIN2B, LAMC3 and SCN1A. Combined with copy number variant (CNV) data, these results indicate extreme locus heterogeneity but also provide a target for future discovery, diagnostics and therapeutics.     

Atomic model of the type III secretion system needle

Pathogenic bacteria using a type III secretion system (T3SS) to manipulate host cells cause many different infections including Shigella dysentery, typhoid fever, enterohaemorrhagic colitis and bubonic plague. An essential part of the T3SS is a hollow needle-like protein filament through which effector proteins are injected into eukaryotic host cells. Currently, the three-dimensional structure of the needle is unknown because it is not amenable to X-ray crystallography and solution NMR, as a result of its inherent non-crystallinity and insolubility. Cryo-electron microscopy combined with crystal or solution NMR subunit structures has recently provided a powerful hybrid approach for studying supramolecular assemblies, resulting in low-resolution and medium-resolution models. However, such approaches cannot deliver atomic details, especially of the crucial subunit-subunit interfaces, because of the limited cryo-electron microscopic resolution obtained in these studies. Here we report an alternative approach combining recombinant wild-type needle production, solid-state NMR, electron microscopy and Rosetta modelling to reveal the supramolecular interfaces and ultimately the complete atomic structure of the Salmonella typhimurium T3SS needle. We show that the 80-residue subunits form a right-handed helical assembly with roughly 11 subunits per two turns, similar to that of the flagellar filament of S. typhimurium. In contrast to established models of the needle in which the amino terminus of the protein subunit was assumed to be α-helical and positioned inside the needle, our model reveals an extended amino-terminal domain that is positioned on the surface of the needle, while the highly conserved carboxy terminus points towards the lumen.     

Pharmaco-metabonomic phenotyping and personalized drug treatment

There is a clear case for drug treatments to be selected according to the characteristics of an individual patient, in order to improve efficacy and reduce the number and severity of adverse drug reactions. However, such personalization of drug treatments requires the ability to predict how different individuals will respond to a particular drug/dose combination. After initial optimism, there is increasing recognition of the limitations of the pharmacogenomic approach, which does not take account of important environmental influences on drug absorption, distribution, metabolism and excretion. For instance, a major factor underlying inter-individual variation in drug effects is variation in metabolic phenotype, which is influenced not only by genotype but also by environmental factors such as nutritional status, the gut microbiota, age, disease and the co- or pre-administration of other drugs. Thus, although genetic variation is clearly important, it seems unlikely that personalized drug therapy will be enabled for a wide range of major diseases using genomic knowledge alone. Here we describe an alternative and conceptually new 'pharmaco-metabonomic' approach to personalizing drug treatment, which uses a combination of pre-dose metabolite profiling and chemometrics to model and predict the responses of individual subjects. We provide proof-of-principle for this new approach, which is sensitive to both genetic and environmental influences, with a study of paracetamol (acetaminophen) administered to rats. We show pre-dose prediction of an aspect of the urinary drug metabolite profile and an association between pre-dose urinary composition and the extent of liver damage sustained after paracetamol administration.     

Computational redesign of endonuclease DNA binding and cleavage specificity

The reprogramming of DNA-binding specificity is an important challenge for computational protein design that tests current understanding of protein-DNA recognition, and has considerable practical relevance for biotechnology and medicine. Here we describe the computational redesign of the cleavage specificity of the intron-encoded homing endonuclease I-MsoI using a physically realistic atomic-level forcefield. Using an in silico screen, we identified single base-pair substitutions predicted to disrupt binding by the wild-type enzyme, and then optimized the identities and conformations of clusters of amino acids around each of these unfavourable substitutions using Monte Carlo sampling. A redesigned enzyme that was predicted to display altered target site specificity, while maintaining wild-type binding affinity, was experimentally characterized. The redesigned enzyme binds and cleaves the redesigned recognition site approximately 10,000 times more effectively than does the wild-type enzyme, with a level of target discrimination comparable to the original endonuclease. Determination of the structure of the redesigned nuclease-recognition site complex by X-ray crystallography confirms the accuracy of the computationally predicted interface. These results suggest that computational protein design methods can have an important role in the creation of novel highly specific endonucleases for gene therapy and other applications.