Non-negative matrix factorization for learning alignment-specific models of protein evolution

Models of protein evolution currently come in two flavors: generalist and specialist. Generalist models (e.g. PAM, JTT, WAG) adopt a one-size-fits-all approach, where a single model is estimated from a number of different protein alignments. Specialist models (e.g. mtREV, rtREV, HIVbetween) can be estimated when a large quantity of data are available for a single organism or gene, and are intended for use on that organism or gene only. Unsurprisingly, specialist models outperform generalist models, but in most instances there simply are not enough data available to estimate them. We propose a method for estimating alignment-specific models of protein evolution in which the complexity of the model is adapted to suit the richness of the data. Our method uses non-negative matrix factorization (NNMF) to learn a set of basis matrices from a general dataset containing a large number of alignments of different proteins, thus capturing the dimensions of important variation. It then learns a set of weights that are specific to the organism or gene of interest and for which only a smaller dataset is available. Thus the alignment-specific model is obtained as a weighted sum of the basis matrices. Having been constrained to vary along only as many dimensions as the data justify, the model has far fewer parameters than would be required to estimate a specialist model. We show that our NNMF procedure produces models that outperform existing methods on all but one of 50 test alignments. The basis matrices we obtain confirm the expectation that amino acid properties tend to be conserved, and allow us to quantify, on specific alignments, how the strength of conservation varies across different properties. We also apply our new models to phylogeny inference and show that the resulting phylogenies are different from, and have improved likelihood over, those inferred under standard models.     

Greenhouse gas emissions and extracellular enzyme activity variability during decomposition of native versus invasive riparian tree litter

Plant Ecology - Invasive plants alter riparian vegetation communities and shift biogeochemical processes by changing decomposition rates and the soil chemical environment created by leaf litter. It...     

In vitro and in vivo aggregation of a fragment of huntingtin protein directly causes free radical production

Neurodegenerative diseases are characterized by intra- and/or extracellular protein aggregation and oxidative stress. Intense attention has been paid to whether protein aggregation itself contributes to abnormal production of free radicals and ensuing cellular oxidative damage. Although this question has been investigated in the context of extracellular protein aggregation, it remains unclear whether protein aggregation inside cells alters the redox homeostasis. To address this, we have used in vitro and in vivo (cellular) models of Huntington disease, one of nine polyglutamine (poly(Q)) disorders, and examined the causal relationship among intracellular protein aggregation, reactive oxygen species (ROS) production, and toxicity. Live imaging of cells expressing a fragment of huntingtin (httExon1) with a poly(Q) expansion shows increased ROS production preceding cell death. ROS production is poly(Q) length-dependent and not due to the httExon 1 flanking sequence. Aggregation inhibition by the MW7 intrabody and Pgl-135 treatment abolishes ROS production, showing that increased ROS is caused by poly(Q) aggregation itself. To examine this hypothesis further, we determined whether aggregation of poly(Q) peptides in vitro generated free radicals. Monitoring poly(Q) protein aggregation using atomic force microscopy and hydrogen peroxide (H(2)O(2)) production over time in parallel we show that oligomerization of httEx1Q53 results in early generation of H(2)O(2). Inhibition of poly(Q) oligomerization by the single chain antibody MW7 abrogates H(2)O(2) formation. These results demonstrate that intracellular protein aggregation directly causes free radical production, and targeting potentially toxic poly(Q) oligomers may constitute a therapeutic target to counteract oxidative stress in poly(Q) diseases.     

Disruption of Arterial Perivascular Drainage of Amyloid-β from the Brains of Mice Expressing the Human APOE ε4 Allele

Failure of elimination of amyloid-β (Aβ) from the brain and vasculature appears to be a key factor in the etiology of sporadic Alzheimer's disease (AD) and cerebral amyloid angiopathy (CAA). In addition to age, possession of an apolipoprotein E (APOE) ε4 allele is a strong risk factor for the development of sporadic AD. The present study tested the hypothesis that possession of the APOE ε4 allele is associated with disruption of perivascular drainage of Aβ from the brain and with changes in cerebrovascular basement membrane protein levels. Targeted replacement (TR) mice expressing the human APOE3 (TRE3) or APOE4 (TRE4) genes and wildtype mice received intracerebral injections of human Aβ(40). Aβ(40) aggregated in peri-arterial drainage pathways in TRE4 mice, but not in TRE3 or wildtype mice. The number of Aβ deposits was significantly higher in the hippocampi of TRE4 mice than in the TRE3 mice, at both 3- and 16-months of age, suggesting that clearance of Aβ was disrupted in the brains of TRE4 mice. Immunocytochemical and Western blot analysis of vascular basement membrane proteins demonstrated significantly raised levels of collagen IV in 3-month-old TRE4 mice compared with TRE3 and wild type mice. In 16-month-old mice, collagen IV and laminin levels were unchanged between wild type and TRE3 mice, but were lower in TRE4 mice. The results of this study suggest that APOE4 may increase the risk for AD through disruption and impedance of perivascular drainage of soluble Aβ from the brain. This effect may be mediated, in part, by changes in age-related expression of basement membrane proteins in the cerebral vasculature.     

OMERO: flexible, model-driven data management for experimental biology

Data-intensive research depends on tools that manage multidimensional, heterogeneous datasets. We built OME Remote Objects (OMERO), a software platform that enables access to and use of a wide range of biological data. OMERO uses a server-based middleware application to provide a unified interface for images, matrices and tables. OMERO's design and flexibility have enabled its use for light-microscopy, high-content-screening, electron-microscopy and even non-image-genotype data. OMERO is open-source software, available at http://openmicroscopy.org/.