Caitlin M. Daimon

VennPlex–A Novel Venn Diagram Program for Comparing and Visualizing Datasets with Differentially Regulated Datapoints

With the development of increasingly large and complex genomic and proteomic data sets, an enhancement in the complexity of available Venn diagram analytical programs is becoming increasingly important. Current freely available Venn diagram programs often fail to represent extra complexity among datasets, such as regulation pattern differences between different groups. Here we describe the development of VennPlex, a program that illustrates the often diverse numerical interactions among multiple, high-complexity datasets, using up to four data sets. VennPlex includes versatile output features, where grouped data points in specific regions can be easily exported into a spreadsheet. This program is able to facilitate the analysis of two to four gene sets and their corresponding expression values in a user-friendly manner. To demonstrate its unique experimental utility we applied VennPlex to a complex paradigm, i.e. a comparison of the effect of multiple oxygen tension environments (1–20% ambient oxygen) upon gene transcription of primary rat astrocytes. VennPlex accurately dissects complex data sets reliably into easily identifiable groups for straightforward analysis and data output. This program, which is an improvement over currently available Venn diagram programs, is able to rapidly extract important datasets that represent the variety of expression patterns available within the data sets, showing potential applications in fields like genomics, proteomics, and bioinformatics.

Metabolic and hormonal signatures in pre-manifest and manifest Huntington's disease patients

Huntingtons disease (HD) is an inherited neurodegenerative disorder typified by involuntary body movements, and psychiatric and cognitive abnormalities. Many HD patients also exhibit metabolic changes including progressive weight loss and appetite dysfunction. Here we have investigated metabolic function in pre-manifest and manifest HD subjects to establish an HD subject metabolic hormonal plasma signature. Individuals at risk for HD who have had predictive genetic testing showing the cytosine-adenine-guanine (CAG) expansion causative of HD, but who do not yet present signs and symptoms sufficient for the diagnosis of manifest HD are said to be “pre-manifest.” Pre-manifest and manifest HD patients, as well as both familial and non-familial controls, were evaluated for multiple peripheral metabolism signals including circulating levels of hormones, growth factors, lipids, and cytokines. Both pre-manifest and manifest HD subjects exhibited significantly reduced levels of circulating growth factors, including growth hormone and prolactin. HD-related changes in the levels of metabolic hormones such as ghrelin, glucagon, and amylin were also observed. Total cholesterol, HDL-C, and LDL-C were significantly decreased in HD subjects. C-reactive protein was significantly elevated in pre-manifest HD subjects. The observation of metabolic alterations, even in subjects considered to be in the pre-manifest stage of HD, suggests that in addition, and prior, to overt neuronal damage, HD affects metabolic hormone secretion and energy regulation, which may shed light on pathogenesis, and provide opportunities for biomarker development.

Altered lipid and salt taste responsivity in ghrelin and GOAT null mice.

Taste perception plays an important role in regulating food preference, eating behavior and energy homeostasis. Taste perception is modulated by a variety of factors, including gastric hormones such as ghrelin. Ghrelin can regulate growth hormone release, food intake, adiposity, and energy metabolism. Octanoylation of ghrelin by ghrelin O-acyltransferase (GOAT) is a specific post-translational modification which is essential for many biological activities of ghrelin. Ghrelin and GOAT are both widely expressed in many organs including the gustatory system. In the current study, overall metabolic profiles were assessed in wild-type (WT), ghrelin knockout (ghrelin−/−), and GOAT knockout (GOAT−/−) mice. Ghrelin−/− mice exhibited decreased food intake, increased plasma triglycerides and increased ketone bodies compared to WT mice while demonstrating WT-like body weight, fat composition and glucose control. In contrast GOAT−/− mice exhibited reduced body weight, adiposity, resting glucose and insulin levels compared to WT mice. Brief access taste behavioral tests were performed to determine taste responsivity in WT, ghrelin−/− and GOAT−/− mice. Ghrelin and GOAT null mice possessed reduced lipid taste responsivity. Furthermore, we found that salty taste responsivity was attenuated in ghrelin−/− mice, yet potentiated in GOAT−/− mice compared to WT mice. Expression of the potential lipid taste regulators Cd36 and Gpr120 were reduced in the taste buds of ghrelin and GOAT null mice, while the salt-sensitive ENaC subunit was increased in GOAT−/− mice compared with WT mice. The altered expression of Cd36, Gpr120 and ENaC may be responsible for the altered lipid and salt taste perception in ghrelin−/− and GOAT−/− mice. The data presented in the current study potentially implicates ghrelin signaling activity in the modulation of both lipid and salt taste modalities.

Long-Term Artificial Sweetener Acesulfame Potassium Treatment Alters Neurometabolic Functions in C57BL/6J Mice

With the prevalence of obesity, artificial, non-nutritive sweeteners have been widely used as dietary supplements that provide sweet taste without excessive caloric load. In order to better understand the overall actions of artificial sweeteners, especially when they are chronically used, we investigated the peripheral and central nervous system effects of protracted exposure to a widely used artificial sweetener, acesulfame K (ACK). We found that extended ACK exposure (40 weeks) in normal C57BL/6J mice demonstrated a moderate and limited influence on metabolic homeostasis, including altering fasting insulin and leptin levels, pancreatic islet size and lipid levels, without affecting insulin sensitivity and bodyweight. Interestingly, impaired cognitive memory functions (evaluated by Morris Water Maze and Novel Objective Preference tests) were found in ACK-treated C57BL/6J mice, while no differences in motor function and anxiety levels were detected. The generation of an ACK-induced neurological phenotype was associated with metabolic dysregulation (glycolysis inhibition and functional ATP depletion) and neurosynaptic abnormalities (dysregulation of TrkB-mediated BDNF and Akt/Erk-mediated cell growth/survival pathway) in hippocampal neurons. Our data suggest that chronic use of ACK could affect cognitive functions, potentially via altering neuro-metabolic functions in male C57BL/6J mice.

Euglycemic Agent-mediated Hypothalamic Transcriptomic Manipulation in the N171–82Q Model of Huntington Disease Is Related to Their Physiological Efficacy

Background: Huntington disease (HD) involves neurological and metabolic pathologies. Results: Euglycemic therapeutics that affect hypothalamic transcription ameliorate multiple aspects of HD pathology. Conclusion: Hypothalamic targeting in HD may yield enhanced HD drug efficacy. Significance: Wider consideration of the metabolic aspects of neurological disorders may be important for drug design. Our aim was to employ novel analytical methods to investigate the therapeutic treatment of the energy regulation dysfunction occurring in a Huntington disease (HD) mouse model. HD is a neurodegenerative disorder that is characterized by progressive motor impairment and cognitive alterations. Changes in neuroendocrine function, body weight, energy metabolism, euglycemia, appetite function, and gut function can also occur. It is likely that the locus of these alterations is the hypothalamus. We determined the effects of three different euglycemic agents on HD progression using standard physiological and transcriptomic signature analyses. N171–82Q HD mice were treated with insulin, Exendin-4, and the newly developed GLP-1-Tf to determine whether these agents could improve energy regulation and delay disease progression. Blood glucose, insulin, metabolic hormone levels, and pancreatic morphology were assessed. Hypothalamic gene transcription, motor coordination, and life span were also determined. The N171–82Q mice exhibited significant alterations in hypothalamic gene transcription signatures and energy metabolism that were ameliorated, to varying degrees, by the different euglycemic agents. Exendin-4 or GLP-1-Tf (but not insulin) treatment also improved pancreatic morphology, motor coordination, and increased life span. Using hypothalamic transcription signature analyses, we found that the physiological efficacy variation of the drugs was evident in the degree of reversal of the hypothalamic HD pathological signature. Euglycemic agents targeting hypothalamic and energy regulation dysfunction in HD could potentially alter disease progression and improve quality of life in HD.

Altered hypothalamic protein expression in a rat model of Huntington's disease.

Huntingtons disease (HD) is a neurodegenerative disorder, which is characterized by progressive motor impairment and cognitive alterations. Changes in energy metabolism, neuroendocrine function, body weight, euglycemia, appetite function, and circadian rhythm can also occur. It is likely that the locus of these alterations is the hypothalamus. We used the HD transgenic (tg) rat model bearing 51 CAG repeats, which exhibits similar HD symptomology as HD patients to investigate hypothalamic function. We conducted detailed hypothalamic proteome analyses and also measured circulating levels of various metabolic hormones and lipids in pre-symptomatic and symptomatic animals. Our results demonstrate that there are significant alterations in HD rat hypothalamic protein expression such as glial fibrillary acidic protein (GFAP), heat shock protein-70, the oxidative damage protein glutathione peroxidase (Gpx4), glycogen synthase1 (Gys1) and the lipid synthesis enzyme acylglycerol-3-phosphate O-acyltransferase 1 (Agpat1). In addition, there are significant alterations in various circulating metabolic hormones and lipids in pre-symptomatic animals including, insulin, leptin, triglycerides and HDL, before any motor or cognitive alterations are apparent. These early metabolic and lipid alterations are likely prodromal signs of hypothalamic dysfunction. Gaining a greater understanding of the hypothalamic and metabolic alterations that occur in HD, could lead to the development of novel therapeutics for early interventional treatment of HD.

Aging and Bone Health in Individuals with Developmental Disabilities

Low bone mass density (BMD), a classical age-related health issue and a known health concern for fair skinned, thin, postmenopausal Caucasian women, is found to be common among individuals with developmental/intellectual disabilities (D/IDs). It is the consensus that BMD is decreased in both men and women with D/ID. Maintaining good bone health is important for this population as fractures could potentially go undetected in nonverbal individuals, leading to increased morbidity and a further loss of independence. This paper provides a comprehensive overview of bone health of adults with D/ID, their risk of fractures, and how this compares to the general aging population. We will specifically focus on the bone health of two common developmental disabilities, Down syndrome (DS) and cerebral palsy (CP), and will discuss BMD and fracture rates in these complex populations. Gaining a greater understanding of how bone health is affected in individuals with D/ID could lead to better customized treatments for these specific populations.

Textrous!: Extracting Semantic Textual Meaning from Gene Sets

The un-biased and reproducible interpretation of high-content gene sets from large-scale genomic experiments is crucial to the understanding of biological themes, validation of experimental data, and the eventual development of plans for future experimentation. To derive biomedically-relevant information from simple gene lists, a mathematical association to scientific language and meaningful words or sentences is crucial. Unfortunately, existing software for deriving meaningful and easily-appreciable scientific textual ‘tokens’ from large gene sets either rely on controlled vocabularies (Medical Subject Headings, Gene Ontology, BioCarta) or employ Boolean text searching and co-occurrence models that are incapable of detecting indirect links in the literature. As an improvement to existing web-based informatic tools, we have developed Textrous!, a web-based framework for the extraction of biomedical semantic meaning from a given input gene set of arbitrary length. Textrous! employs natural language processing techniques, including latent semantic indexing (LSI), sentence splitting, word tokenization, parts-of-speech tagging, and noun-phrase chunking, to mine MEDLINE abstracts, PubMed Central articles, articles from the Online Mendelian Inheritance in Man (OMIM), and Mammalian Phenotype annotation obtained from Jackson Laboratories. Textrous! has the ability to generate meaningful output data with even very small input datasets, using two different text extraction methodologies (collective and individual) for the selecting, ranking, clustering, and visualization of English words obtained from the user data. Textrous!, therefore, is able to facilitate the output of quantitatively significant and easily appreciable semantic words and phrases linked to both individual gene and batch genomic data.

Effective use of latent semantic indexing and computational linguistics in biological and biomedical applications

Text mining is rapidly becoming an essential technique for the annotation and analysis of large biological data sets. Biomedical literature currently increases at a rate of several thousand papers per week, making automated information retrieval methods the only feasible method of managing this expanding corpus. With the increasing prevalence of open-access journals and constant growth of publicly-available repositories of biomedical literature, literature mining has become much more effective with respect to the extraction of biomedically-relevant data. In recent years, text mining of popular databases such as MEDLINE has evolved from basic term-searches to more sophisticated natural language processing techniques, indexing and retrieval methods, structural analysis and integration of literature with associated metadata. In this review, we will focus on Latent Semantic Indexing (LSI), a computational linguistics technique increasingly used for a variety of biological purposes. It is noted for its ability to consistently outperform benchmark Boolean text searches and co-occurrence models at information retrieval and its power to extract indirect relationships within a data set. LSI has been used successfully to formulate new hypotheses, generate novel connections from existing data, and validate empirical data.

The effects of aging on the BTBR mouse model of autism spectrum disorder.

Autism spectrum disorder (ASD) is a complex heterogeneous neurodevelopmental disorder characterized by alterations in social functioning, communicative abilities, and engagement in repetitive or restrictive behaviors. The process of aging in individuals with autism and related neurodevelopmental disorders is not well understood, despite the fact that the number of individuals with ASD aged 65 and older is projected to increase by over half a million individuals in the next 20 years. To elucidate the effects of aging in the context of a modified central nervous system, we investigated the effects of age on the BTBR T + tf/j mouse, a well characterized and widely used mouse model that displays an ASD-like phenotype. We found that a reduction in social behavior persists into old age in male BTBR T + tf/j mice. We employed quantitative proteomics to discover potential alterations in signaling systems that could regulate aging in the BTBR mice. Unbiased proteomic analysis of hippocampal and cortical tissue of BTBR mice compared to age-matched wild-type controls revealed a significant decrease in brain derived neurotrophic factor and significant increases in multiple synaptic markers (spinophilin, Synapsin I, PSD 95, NeuN), as well as distinct changes in functional pathways related to these proteins, including “Neural synaptic plasticity regulation” and “Neurotransmitter secretion regulation.” Taken together, these results contribute to our understanding of the effects of aging on an ASD-like mouse model in regards to both behavior and protein alterations, though additional studies are needed to fully understand the complex interplay underlying aging in mouse models displaying an ASD-like phenotype.