Targeting Repeat Sequences with DNA-Binding Small Molecules

Recognition of repeat sequences in DNA would have applications in molecular biology. One of the most biologically interesting repeat sequences is the telomeric repeat which composes the ends of eukaryotic chromosomes; in vertebrates 5'-TTAGGG-3'. This sequence has been used as a model to study how DNA-binding polyamide molecules composed of pyrrole (Py) and imidazole (Im) residues bind to repeating sequences. DNase I footprinting shows that the polyamide-fluorophore conjugate IrnImImPy-γ-PyPy((CH_2)_3N,N',N''trimethylbis hexamethylene)triamineOregonGreen488) PyPy-β-Me can bind the sequence 5'-AGGGTT-3' K_a = 1.8x10^8 M^(-1). Quantitative fluorescence titrations with varying patterns of telomeric repeat suggest that the molecule can tolerate another polyamide binding contiguously, but not two. Truncation of the tail of the conjugate to yield the molecule ImImImPy-γ-Py Py((CH_2)_3N,N',N''trimethylbis (hexamethylene)triamine-OregonGreen488) PyPy-Me allows the compound to bind three contiguous sites, suggesting that steric polyamide-polyamide interactions control binding in this manner

Identification and characterization of small-molecule inhibitors of hepsin.

Hepsin is a type II transmembrane serine protease overexpressed in the majority of human prostate cancers. We recently demonstrated that hepsin promotes prostate cancer progression and metastasis and thus represents a potential therapeutic target. Here we report the identification of novel small-molecule inhibitors of hepsin catalytic activity. We utilized purified human hepsin for high-throughput screening of established drug and chemical diversity libraries and identified sixteen inhibitory compounds with IC(50) values against hepsin ranging from 0.23-2.31 microM and relative selectivity of up to 86-fold or greater. Two compounds are orally administered drugs established for human use. Four compounds attenuated hepsin-dependent pericellular serine protease activity in a dose dependent manner with limited or no cytotoxicity to a range of cell types. These compounds may be used as leads to develop even more potent and specific inhibitors of hepsin to prevent prostate cancer progression and metastasis

An Automated Images-to-Graphs Framework for High Resolution Connectomics

Reconstructing a map of neuronal connectivity is a critical challenge in contemporary neuroscience. Recent advances in high-throughput serial section electron microscopy (EM) have produced massive 3D image volumes of nanoscale brain tissue for the first time. The resolution of EM allows for individual neurons and their synaptic connections to be directly observed. Recovering neuronal networks by manually tracing each neuronal process at this scale is unmanageable, and therefore researchers are developing automated image processing modules. Thus far, state-of-the-art algorithms focus only on the solution to a particular task (e.g., neuron segmentation or synapse identification). In this manuscript we present the first fully automated images-to-graphs pipeline (i.e., a pipeline that begins with an imaged volume of neural tissue and produces a brain graph without any human interaction). To evaluate overall performance and select the best parameters and methods, we also develop a metric to assess the quality of the output graphs. We evaluate a set of algorithms and parameters, searching possible operating points to identify the best available brain graph for our assessment metric. Finally, we deploy a reference end-to-end version of the pipeline on a large, publicly available data set. This provides a baseline result and framework for community analysis and future algorithm development and testing. All code and data derivatives have been made publicly available toward eventually unlocking new biofidelic computational primitives and understanding of neuropathologies.Comment: 13 pages, first two authors contributed equally V2: Added additional experiments and clarifications; added information on infrastructure and pipeline environmen

Microguards and micromessengers of the genome

The regulation of gene expression is of fundamental importance to maintain organismal function and integrity and requires a multifaceted and highly ordered sequence of events. The cyclic nature of gene expression is known as ‘transcription dynamics’. Disruption or perturbation of these dynamics can result in significant fitness costs arising from genome instability, accelerated ageing and disease. We review recent research that supports the idea that an important new role for small RNAs, particularly microRNAs (miRNAs), is in protecting the genome against short-term transcriptional fluctuations, in a process we term ‘microguarding’. An additional emerging role for miRNAs is as ‘micromessengers’—through alteration of gene expression in target cells to which they are trafficked within microvesicles. We describe the scant but emerging evidence that miRNAs can be moved between different cells, individuals and even species, to exert biologically significant responses. With these two new roles, miRNAs have the potential to protect against deleterious gene expression variation from perturbation and to themselves perturb the expression of genes in target cells. These interactions between cells will frequently be subject to conflicts of interest when they occur between unrelated cells that lack a coincidence of fitness interests. Hence, there is the potential for miRNAs to represent both a means to resolve conflicts of interest, as well as instigate them. We conclude by exploring this conflict hypothesis, by describing some of the initial evidence consistent with it and proposing new ideas for future research into this exciting topic

Neural Reconstruction Integrity: A Metric for Assessing the Connectivity Accuracy of Reconstructed Neural Networks

Neuroscientists are actively pursuing high-precision maps, or graphs consisting of networks of neurons and connecting synapses in mammalian and non-mammalian brains. Such graphs, when coupled with physiological and behavioral data, are likely to facilitate greater understanding of how circuits in these networks give rise to complex information processing capabilities. Given that the automated or semi-automated methods required to achieve the acquisition of these graphs are still evolving, we developed a metric for measuring the performance of such methods by comparing their output with those generated by human annotators (“ground truth” data). Whereas classic metrics for comparing annotated neural tissue reconstructions generally do so at the voxel level, the metric proposed here measures the “integrity” of neurons based on the degree to which a collection of synaptic terminals belonging to a single neuron of the reconstruction can be matched to those of a single neuron in the ground truth data. The metric is largely insensitive to small errors in segmentation and more directly measures accuracy of the generated brain graph. It is our hope that use of the metric will facilitate the broader community's efforts to improve upon existing methods for acquiring brain graphs. Herein we describe the metric in detail, provide demonstrative examples of the intuitive scores it generates, and apply it to a synthesized neural network with simulated reconstruction errors. Demonstration code is available

Neural Reconstruction Integrity: A Metric for Assessing the Connectivity Accuracy of Reconstructed Neural Networks

Neuroscientists are actively pursuing high-precision maps, or graphs consisting of networks of neurons and connecting synapses in mammalian and non-mammalian brains. Such graphs, when coupled with physiological and behavioral data, are likely to facilitate greater understanding of how circuits in these networks give rise to complex information processing capabilities. Given that the automated or semi-automated methods required to achieve the acquisition of these graphs are still evolving, we developed a metric for measuring the performance of such methods by comparing their output with those generated by human annotators (“ground truth” data). Whereas classic metrics for comparing annotated neural tissue reconstructions generally do so at the voxel level, the metric proposed here measures the “integrity” of neurons based on the degree to which a collection of synaptic terminals belonging to a single neuron of the reconstruction can be matched to those of a single neuron in the ground truth data. The metric is largely insensitive to small errors in segmentation and more directly measures accuracy of the generated brain graph. It is our hope that use of the metric will facilitate the broader community's efforts to improve upon existing methods for acquiring brain graphs. Herein we describe the metric in detail, provide demonstrative examples of the intuitive scores it generates, and apply it to a synthesized neural network with simulated reconstruction errors. Demonstration code is available

Mismatch Negativity (MMN) reveals inefficient auditory ventral stream function in chronic auditory comprehension impairments

Background: Auditory discrimination is significantly impaired in Wernicke’s aphasia (WA) and thought to be causatively related to the language comprehension impairment which characterises the condition. This study used mismatch negativity (MMN) to investigate the neural responses corresponding to successful and impaired auditory discrimination in WA. Methods: Behavioural auditory discrimination thresholds of CVC syllables and pure tones were measured in WA (n=7) and control (n=7) participants. Threshold results were used to develop multiple-deviant mismatch negativity (MMN) oddball paradigms containing deviants which were either perceptibly or non-perceptibly different from the standard stimuli. MMN analysis investigated differences associated with group, condition and perceptibility as well as the relationship between MMN responses and comprehension (within which behavioural auditory discrimination profiles were examined). Results: MMN waveforms were observable to both perceptible and non-perceptible auditory changes. Perceptibility was only distinguished by MMN amplitude in the PT condition. The WA group could be distinguished from controls by an increase in MMN response latency to CVC stimuli change. Correlation analyses displayed relationship between behavioural CVC discrimination and MMN amplitude in the control group, where greater amplitude corresponded to better discrimination. The WA group displayed the inverse effect; both discrimination accuracy and auditory comprehension scores were reduced with increased MMN amplitude. In the WA group, a further correlation was observed between the lateralisation of MMN response and CVC discrimination accuracy; the greater the bilateral involvement the better the discrimination accuracy. Conclusions: The results from this study provide further evidence for the nature of auditory comprehension impairment in WA and indicate that the auditory discrimination deficit is grounded in a reduced ability to engage in efficient hierarchical processing and the construction of invariant auditory objects. Correlation results suggest that people with chronic WA may rely on an inefficient, noisy right hemisphere auditory stream when attempting to process speech stimuli