APOBEC3B is an enzymatic source of mutation in breast cancer.

Several mutations are required for cancer development, and genome sequencing has revealed that many cancers, including breast cancer, have somatic mutation spectra dominated by C-to-T transitions. Most of these mutations occur at hydrolytically disfavoured non-methylated cytosines throughout the genome, and are sometimes clustered. Here we show that the DNA cytosine deaminase APOBEC3B is a probable source of these mutations. APOBEC3B messenger RNA is upregulated in most primary breast tumours and breast cancer cell lines. Tumours that express high levels of APOBEC3B have twice as many mutations as those that express low levels and are more likely to have mutations in TP53. Endogenous APOBEC3B protein is predominantly nuclear and the only detectable source of DNA C-to-U editing activity in breast cancer cell-line extracts. Knockdown experiments show that endogenous APOBEC3B correlates with increased levels of genomic uracil, increased mutation frequencies, and C-to-T transitions. Furthermore, induced APOBEC3B overexpression causes cell cycle deviations, cell death, DNA fragmentation, γ-H2AX accumulation and C-to-T mutations. Our data suggest a model in which APOBEC3B-catalysed deamination provides a chronic source of DNA damage in breast cancers that could select TP53 inactivation and explain how some tumours evolve rapidly and manifest heterogeneity.

Guanine holes are prominent targets for mutation in cancer and inherited disease.

Single base substitutions constitute the most frequent type of human gene mutation and are a leading cause of cancer and inherited disease. These alterations occur non-randomly in DNA, being strongly influenced by the local nucleotide sequence context. However, the molecular mechanisms underlying such sequence context-dependent mutagenesis are not fully understood. Using bioinformatics, computational and molecular modeling analyses, we have determined the frequencies of mutation at G • C bp in the context of all 64 5'-NGNN-3' motifs that contain the mutation at the second position. Twenty-four datasets were employed, comprising >530,000 somatic single base substitutions from 21 cancer genomes, >77,000 germline single-base substitutions causing or associated with human inherited disease and 16.7 million benign germline single-nucleotide variants. In several cancer types, the number of mutated motifs correlated both with the free energies of base stacking and the energies required for abstracting an electron from the target guanines (ionization potentials). Similar correlations were also evident for the pathological missense and nonsense germline mutations, but only when the target guanines were located on the non-transcribed DNA strand. Likewise, pathogenic splicing mutations predominantly affected positions in which a purine was located on the non-transcribed DNA strand. Novel candidate driver mutations and tissue-specific mutational patterns were also identified in the cancer datasets. We conclude that electron transfer reactions within the DNA molecule contribute to sequence context-dependent mutagenesis, involving both somatic driver and passenger mutations in cancer, as well as germline alterations causing or associated with inherited disease.

The somatic autosomal mutation matrix in cancer genomes.

DNA damage in somatic cells originates from both environmental and endogenous sources, giving rise to mutations through multiple mechanisms. When these mutations affect the function of critical genes, cancer may ensue. Although identifying genomic subsets of mutated genes may inform therapeutic options, a systematic survey of tumor mutational spectra is required to improve our understanding of the underlying mechanisms of mutagenesis involved in cancer etiology. Recent studies have presented genome-wide sets of somatic mutations as a 96-element vector, a procedure that only captures the immediate neighbors of the mutated nucleotide. Herein, we present a 32 × 12 mutation matrix that captures the nucleotide pattern two nucleotides upstream and downstream of the mutation. A somatic autosomal mutation matrix (SAMM) was constructed from tumor-specific mutations derived from each of 909 individual cancer genomes harboring a total of 10,681,843 single-base substitutions. In addition, mechanistic template mutation matrices (MTMMs) representing oxidative DNA damage, ultraviolet-induced DNA damage, (5m)CpG deamination, and APOBEC-mediated cytosine mutation, are presented. MTMMs were mapped to the individual tumor SAMMs to determine the maximum contribution of each mutational mechanism to the overall mutation pattern. A Manhattan distance across all SAMM elements between any two tumor genomes was used to determine their relative distance. Employing this metric, 89.5% of all tumor genomes were found to have a nearest neighbor from the same tissue of origin. When a distance-dependent 6-nearest neighbor classifier was used, 10.4% of the SAMMs had an Undetermined tissue of origin, and 92.2% of the remaining SAMMs were assigned to the correct tissue of origin. [corrected]. Thus, although tumors from different tissues may have similar mutation patterns, their SAMMs often display signatures that are characteristic of specific tissues.

Non-B DB v2.0: a database of predicted non-B DNA-forming motifs and its associated tools.

The non-B DB, available at http://nonb.abcc.ncifcrf.gov, catalogs predicted non-B DNA-forming sequence motifs, including Z-DNA, G-quadruplex, A-phased repeats, inverted repeats, mirror repeats, direct repeats and their corresponding subsets: cruciforms, triplexes and slipped structures, in several genomes. Version 2.0 of the database revises and re-implements the motif discovery algorithms to better align with accepted definitions and thresholds for motifs, expands the non-B DNA-forming motifs coverage by including short tandem repeats and adds key visualization tools to compare motif locations relative to other genomic annotations. Non-B DB v2.0 extends the ability for comparative genomics by including re-annotation of the five organisms reported in non-B DB v1.0, human, chimpanzee, dog, macaque and mouse, and adds seven additional organisms: orangutan, rat, cow, pig, horse, platypus and Arabidopsis thaliana. Additionally, the non-B DB v2.0 provides an overall improved graphical user interface and faster query performance.

Dysregulation of Semaphorin7A/ß1-integrin signaling leads to defective GnRH-1 cell migration, abnormal gonadal development and altered fertility.

Reproduction in mammals is dependent on the function of specific neurons that secrete gonadotropin-releasing hormone-1 (GnRH-1). These neurons originate prenatally in the nasal placode and migrate into the forebrain along the olfactory-vomeronasal nerves. Alterations in this migratory process lead to defective GnRH-1 secretion, resulting in heterogeneous genetic disorders such as idiopathic hypogonadotropic hypogonadism (IHH), and other reproductive diseases characterized by the reduction or failure of sexual competence. Combining mouse genetics with in vitro models, we demonstrate that Semaphorin 7A (Sema7A) is essential for the development of the GnRH-1 neuronal system. Loss of Sema7A signaling alters the migration of GnRH-1 neurons, resulting in significantly reduced numbers of these neurons in the adult brain as well as in reduced gonadal size and subfertility. We also show that GnRH-1 cells differentially express the Sema7 receptors ß1-integrin and Plexin C1 as a function of their migratory stage, whereas the ligand is robustly expressed along developing olfactory/vomeronasal fibers. Disruption of Sema7A function in vitro inhibits ß1-integrin-mediated migration. Analysis of Plexin C1(-/-) mice did not reveal any difference in the migratory process of GnRH-1 neurons, indicating that Sema7A mainly signals through ß1-integrin to regulate GnRH-1 cell motility. In conclusion, we have identified Sema7A as a gene implicated in the normal development of the GnRH-1 system in mice and as a genetic marker for the elucidation of some forms of GnRH-1 deficiency in humans.

Bacterial Genotype, Carrier Risk Factors, and an Antimicrobial Stewardship Approach Relevant to Methicillin-resistant Staphylococcus aureus Prevalence in a Population of Macaques Housed in a Research Facility.

Methicillin-resistant Staphylococcus aureus (MRSA) remains a significant problem for human and animal health and can negatively affect the health status of macaques and other nonhuman primates (NHP) in research colonies. However, few publications provide guidance on the prevalence, genotype, or risk factors for macaques with MRSA and even fewer on how to effectively respond to MRSA once identified in a population. After having a clinical case of MRSA in a rhesus macaque, we sought to determine the MRSA carrier prevalence, risk factors, and genotypes of MRSA in a population of research NHPs. Over a 6-wk period in 2015, we collected nasal swabs from 298 NHPs. MRSA was isolated from 28% (n = 83). We then reviewed each macaque's medical record for a variety of variables including animal housing room, sex, age, number of antibiotic courses, number of surgical interventions, and SIV status. Analysis of these data suggests that MRSA carriage is associated with the room location, age of the animal, SIV status, and the number of antibiotic courses. We used multilocus sequence typing and spa typing on a subset of MRSA and MSSA isolates to determine whether the MRSA present in NHPs was comparable with common human strains. Two MRSA sequence types were predominant: ST188 and a novel MRSA genotype, neither of which is a common human isolate in the United States. We subsequently implemented antimicrobial stewardship practices (significantly reducing antimicrobial use) and then resampled the colony in 2018 and found that MRSA carriage had fallen to 9% (26/285). These data suggest that, as in humans, macaques may have a high carrier status of MRSA despite low clinically apparent disease. Implementing strategic antimicrobial stewardship practices resulted in a marked reduction in MRSA carriage in the NHP colony, highlighting the importance of limiting antimicrobial use when possible.

A comparative computer simulation of dendritic morphology.

Computational modeling of neuronal morphology is a powerful tool for understanding developmental processes and structure-function relationships. We present a multifaceted approach based on stochastic sampling of morphological measures from digital reconstructions of real cells. We examined how dendritic elongation, branching, and taper are controlled by three morphometric determinants: Branch Order, Radius, and Path Distance from the soma. Virtual dendrites were simulated starting from 3,715 neuronal trees reconstructed in 16 different laboratories, including morphological classes as diverse as spinal motoneurons and dentate granule cells. Several emergent morphometrics were used to compare real and virtual trees. Relating model parameters to Branch Order best constrained the number of terminations for most morphological classes, except pyramidal cell apical trees, which were better described by a dependence on Path Distance. In contrast, bifurcation asymmetry was best constrained by Radius for apical, but Path Distance for basal trees. All determinants showed similar performance in capturing total surface area, while surface area asymmetry was best determined by Path Distance. Grouping by other characteristics, such as size, asymmetry, arborizations, or animal species, showed smaller differences than observed between apical and basal, pointing to the biological importance of this separation. Hybrid models using combinations of the determinants confirmed these trends and allowed a detailed characterization of morphological relations. The differential findings between morphological groups suggest different underlying developmental mechanisms. By comparing the effects of several morphometric determinants on the simulation of different neuronal classes, this approach sheds light on possible growth mechanism variations responsible for the observed neuronal diversity.

Gene expression profiling of whole blood: A comparative assessment of RNA-stabilizing collection methods.

Peripheral Blood gene expression is widely used in the discovery of biomarkers and development of therapeutics. Recently, a spate of commercial blood collection and preservation systems have been introduced with proprietary variations that may differentially impact the transcriptomic profiles. Comparative analysis of these collection platforms will help optimize protocols to detect, identify, and reproducibly validate true biological variance among subjects. In the current study, we tested two recently introduced whole blood collection methods, RNAgard® and PAXgene® RNA, in addition to the traditional method of peripheral blood mononuclear cells (PBMCs) separated from whole blood and preserved in Trizol reagent. Study results revealed striking differences in the transcriptomic profiles from the three different methods that imply ex vivo changes in gene expression occurred during the blood collection, preservation, and mRNA extraction processes. When comparing the ability of the three preservation methods to accurately capture individuals' expression differences, RNAgard® outperformed PAXgene® RNA, and both showed better individual separation of transcriptomic profiles than PBMCs. Hence, our study recommends using a single blood collection platform, and strongly cautions against combining methods during the course of a defined study.

A cross-platform freeware tool for digital reconstruction of neuronal arborizations from image stacks.

Digital reconstruction of neuronal arborizations is an important step in the quantitative investigation of cellular neuroanatomy. In this process, neurites imaged by microscopy are semi-manually traced through the use of specialized computer software and represented as binary trees of branching cylinders (or truncated cones). Such form of the reconstruction files is efficient and parsimonious, and allows extensive morphometric analysis as well as the implementation of biophysical models of electrophysiology. Here, we describe Neuron_ Morpho, a plugin for the popular Java application ImageJ that mediates the digital reconstruction of neurons from image stacks. Both the executable and code of Neuron_ Morpho are freely distributed (www.maths. soton.ac.uk/staff/D'Alessandro/morpho or www.krasnow.gmu.edu/L-Neuron), and are compatible with all major computer platforms (including Windows, Mac, and Linux). We tested Neuron_Morpho by reconstructing two neurons from each of the two preparations representing different brain areas (hippocampus and cerebellum), neuritic type (pyramidal cell dendrites and olivar axonal projection terminals), and labeling method (rapid Golgi impregnation and anterograde dextran amine), and quantitatively comparing the resulting morphologies to those of the same cells reconstructed with the standard commercial system, Neurolucida. None of the numerous morphometric measures that were analyzed displayed any significant or systematic difference between the two reconstructing systems.

Acute and chronic plasma metabolomic and liver transcriptomic stress effects in a mouse model with features of post-traumatic stress disorder.

Acute responses to intense stressors can give rise to post-traumatic stress disorder (PTSD). PTSD diagnostic criteria include trauma exposure history and self-reported symptoms. Individuals who meet PTSD diagnostic criteria often meet criteria for additional psychiatric diagnoses. Biomarkers promise to contribute to reliable phenotypes of PTSD and comorbidities by linking biological system alterations to behavioral symptoms. Here we have analyzed unbiased plasma metabolomics and other stress effects in a mouse model with behavioral features of PTSD. In this model, C57BL/6 mice are repeatedly exposed to a trained aggressor mouse (albino SJL) using a modified, resident-intruder, social defeat paradigm. Our recent studies using this model found that aggressor-exposed mice exhibited acute stress effects including changed behaviors, body weight gain, increased body temperature, as well as inflammatory and fibrotic histopathologies and transcriptomic changes of heart tissue. Some of these acute stress effects persisted, reminiscent of PTSD. Here we report elevated proteins in plasma that function in inflammation and responses to oxidative stress and damaged tissue at 24 hrs post-stressor. Additionally at this acute time point, transcriptomic analysis indicated liver inflammation. The unbiased metabolomics analysis showed altered metabolites in plasma at 24 hrs that only partially normalized toward control levels after stress-withdrawal for 1.5 or 4 wks. In particular, gut-derived metabolites were altered at 24 hrs post-stressor and remained altered up to 4 wks after stress-withdrawal. Also at the 4 wk time point, hyperlipidemia and suppressed metabolites of amino acids and carbohydrates in plasma coincided with transcriptomic indicators of altered liver metabolism (activated xenobiotic and lipid metabolism). Collectively, these system-wide sequelae to repeated intense stress suggest that the simultaneous perturbed functioning of multiple organ systems (e.g., brain, heart, intestine and liver) can interact to produce injuries that lead to chronic metabolic changes and disorders that have been associated with PTSD.

The role of methylation in the intrinsic dynamics of B- and Z-DNA.

Methylation of cytosine at the 5-carbon position (5 mC) is observed in both prokaryotes and eukaryotes. In humans, DNA methylation at CpG sites plays an important role in gene regulation and has been implicated in development, gene silencing, and cancer. In addition, the CpG dinucleotide is a known hot spot for pathologic mutations genome-wide. CpG tracts may adopt left-handed Z-DNA conformations, which have also been implicated in gene regulation and genomic instability. Methylation facilitates this B-Z transition but the underlying mechanism remains unclear. Herein, four structural models of the dinucleotide d(GC)(5) repeat sequence in B-, methylated B-, Z-, and methylated Z-DNA forms were constructed and an aggregate 100 nanoseconds of molecular dynamics simulations in explicit solvent under physiological conditions was performed for each model. Both unmethylated and methylated B-DNA were found to be more flexible than Z-DNA. However, methylation significantly destabilized the BII, relative to the BI, state through the Gp5mC steps. In addition, methylation decreased the free energy difference between B- and Z-DNA. Comparisons of α/γ backbone torsional angles showed that torsional states changed marginally upon methylation for B-DNA, and Z-DNA. Methylation-induced conformational changes and lower energy differences may contribute to the transition to Z-DNA by methylated, over unmethylated, B-DNA and may be a contributing factor to biological function.

Automated reconstruction of neuronal morphology: an overview.

Digital reconstruction of neuronal morphology is a powerful technique for investigating the nervous system. This process consists of tracing the axonal and dendritic arbors of neurons imaged by optical microscopy into a geometrical format suitable for quantitative analysis and computational modeling. Algorithmic automation of neuronal tracing promises to increase the speed, accuracy, and reproducibility of morphological reconstructions. Together with recent breakthroughs in cellular imaging and accelerating progress in optical microscopy, automated reconstruction of neuronal morphology will play a central role in the development of high throughput screening and the acquisition of connectomic data. Yet, despite continuous advances in image processing algorithms, to date manual tracing remains the overwhelming choice for digitizing neuronal morphology. We summarize the issues involved in automated reconstruction, overview the available techniques, and provide a realistic assessment of future perspectives.

NeuroMorpho.Org implementation of digital neuroscience: dense coverage and integration with the NIF.

Neuronal morphology affects network connectivity, plasticity, and information processing. Uncovering the design principles and functional consequences of dendritic and axonal shape necessitates quantitative analysis and computational modeling of detailed experimental data. Digital reconstructions provide the required neuromorphological descriptions in a parsimonious, comprehensive, and reliable numerical format. NeuroMorpho.Org is the largest web-accessible repository service for digitally reconstructed neurons and one of the integrated resources in the Neuroscience Information Framework (NIF). Here we describe the NeuroMorpho.Org approach as an exemplary experience in designing, creating, populating, and curating a neuroscience digital resource. The simple three-tier architecture of NeuroMorpho.Org (web client, web server, and relational database) encompasses all necessary elements to support a large-scale, integrate-able repository. The data content, while heterogeneous in scientific scope and experimental origin, is unified in format and presentation by an in house standardization protocol. The server application (MRALD) is secure, customizable, and developer-friendly. Centralized processing and expert annotation yields a comprehensive set of metadata that enriches and complements the raw data. The thoroughly tested interface design allows for optimal and effective data search and retrieval. Availability of data in both original and standardized formats ensures compatibility with existing resources and fosters further tool development. Other key functions enable extensive exploration and discovery, including 3D and interactive visualization of branching, frequently measured morphometrics, and reciprocal links to the original PubMed publications. The integration of NeuroMorpho.Org with version-1 of the NIF (NIFv1) provides the opportunity to access morphological data in the context of other relevant resources and diverse subdomains of neuroscience, opening exciting new possibilities in data mining and knowledge discovery. The outcome of such coordination is the rapid and powerful advancement of neuroscience research at both the conceptual and technological level.

The neuroscience information framework: a data and knowledge environment for neuroscience.

With support from the Institutes and Centers forming the NIH Blueprint for Neuroscience Research, we have designed and implemented a new initiative for integrating access to and use of Web-based neuroscience resources: the Neuroscience Information Framework. The Framework arises from the expressed need of the neuroscience community for neuroinformatic tools and resources to aid scientific inquiry, builds upon prior development of neuroinformatics by the Human Brain Project and others, and directly derives from the Society for Neuroscience's Neuroscience Database Gateway. Partnered with the Society, its Neuroinformatics Committee, and volunteer consultant-collaborators, our multi-site consortium has developed: (1) a comprehensive, dynamic, inventory of Web-accessible neuroscience resources, (2) an extended and integrated terminology describing resources and contents, and (3) a framework accepting and aiding concept-based queries. Evolving instantiations of the Framework may be viewed at http://nif.nih.gov , http://neurogateway.org , and other sites as they come on line.

Local diameter fully constrains dendritic size in basal but not apical trees of CA1 pyramidal neurons.

Computational modeling of dendritic morphology is a powerful tool for quantitatively describing complex geometrical relationships, uncovering principles of dendritic development, and synthesizing virtual neurons to systematically investigate cellular biophysics and network dynamics. A feature common to many morphological models is a dependence of the branching probability on local diameter. Previous models of this type have been able to recreate a wide variety of dendritic morphologies. However, these diameter-dependent models have so far failed to properly constrain branching when applied to hippocampal CA1 pyramidal cells, leading to explosive growth. Here we present a simple modification of this basic approach, in which all parameter sampling, not just bifurcation probability, depends on branch diameter. This added constraint prevents explosive growth in both apical and basal trees of simulated CA1 neurons, yielding arborizations with average numbers and patterns of bifurcations extremely close to those observed in real cells. However, simulated apical trees are much more varied in size than the corresponding real dendrites. We show that, in this model, the excessive variability of simulated trees is a direct consequence of the natural variability of diameter changes at and between bifurcations observed in apical, but not basal, dendrites. Conversely, some aspects of branch distribution were better matched by virtual apical trees than by virtual basal trees. Dendritic morphometrics related to spatial position, such as path distance from the soma or branch order, may be necessary to fully constrain CA1 apical tree size and basal branching pattern.