Pareto-Optimal Methods for Gene Ranking

The massive scale and variability of microarray gene data creates new and challenging problems of signal extraction, gene clustering, and data mining, especially for temporal gene profiles. Many data mining methods for finding interesting gene expression patterns are based on thresholding single discriminants, e.g. the ratio of between-class to within-class variation or correlation to a template. Here a different approach is introduced for extracting information from gene microarrays. The approach is based on multiple objective optimization and we call it Pareto front analysis (PFA). This method establishes a ranking of genes according to estimated probabilities that each gene is Pareto-optimal, i.e., that it lies on the Pareto front of the multiple objective scattergram. Both a model-driven Bayesian Pareto method and a data-driven non-parametric Pareto method, based on rank-order statistics, are presented. The methods are illustrated for two gene microarray experiments.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41339/1/11265_2005_Article_5273219.pd

A statistical framework for consolidating "sibling" probe sets for Affymetrix GeneChip data

<p>Abstract</p> <p>Background</p> <p>Affymetrix GeneChip typically contains multiple probe sets per gene, defined as sibling probe sets in this study. These probe sets may or may not behave similar across treatments. The most appropriate way of consolidating sibling probe sets suitable for analysis is an open problem. We propose the Analysis of Variance (ANOVA) framework to decide which sibling probe sets can be consolidated.</p> <p>Results</p> <p>The ANOVA model allows us to separate the sibling probe sets into two types: those behave similarly across treatments and those behave differently across treatments. We found that consolidation of sibling probe sets of the former type results in large increase in the number of differentially expressed genes under various statistical criteria. The approach to selecting sibling probe sets suitable for consolidating is implemented in R language and freely available from <url>http://research.stowers-institute.org/hul/affy/</url>.</p> <p>Conclusion</p> <p>Our ANOVA analysis of sibling probe sets provides a statistical framework for selecting sibling probe sets for consolidation. Consolidating sibling probe sets by pooling data from each greatly improves the estimates of a gene expression level and results in identification of more biologically relevant genes. Sibling probe sets that do not qualify for consolidation may represent annotation errors or other artifacts, or may correspond to differentially processed transcripts of the same gene that require further analysis.</p

Identification of the molecular signatures integral to regenerating photoreceptors in the retina of the zebra fish

Investigating neuronal and photoreceptor regeneration in the retina of zebra fish has begun to yield insights into both the cellular and molecular means by which this lower vertebrate is able to repair its central nervous system. However, knowledge about the signaling molecules in the local microenvironment of a retinal injury and the transcriptional events they activate during neuronal death and regeneration is still lacking. To identify genes involved in photoreceptor regeneration, we combined light-induced photoreceptor lesions, laser-capture microdissection of the outer nuclear layer (ONL) and analysis of gene expression to characterize transcriptional changes for cells in the ONL as photoreceptors die and are regenerated. Using this approach, we were able to characterize aspects of the molecular signature of injured and dying photoreceptors, cone photoreceptor progenitors, and microglia within the ONL. We validated changes in gene expression and characterized the cellular expression for three novel, extracellular signaling molecules that we hypothesize are involved in regulating regenerative events in the retina

Transcriptomic Signatures in Alcohol Use Disorder - A Translational Approach

To date, there are only limited pharmacological treatments to cure AUD and the success rate is very low. Therefore, new therapeutic routes are warranted. This thesis aims to contribute to this need by identifying molecular mechanisms that are altered in AUD, considering the patient aspect through the use of human post-mortem brain samples, and compare the findings to a frequently used animal model of alcohol dependence. By combining multiple cutting-edge techniques, this study provides high evidence for further follow-up studies, where it will be possible to validate the findings in pre-clinical approaches and predict the relevance for the patient more precisely than previous studies. In addition, biomarkers for AUD, that are defined by this study, contribute substantially to the diagnosis of AUD on a molecular basis. The meta-analysis of three brain regions (study 2) –prefrontal cortex (PFC), nucleus accumbens (NAc) and amygdala (AMY)– identified common signatures comparing rodent, monkey, and human post-mortem brain tissue. In the PFC, we found commonly enriched pathways for cancerogenesis, pro-inflammatory processes, and oxidative stress. The analysis of the NAc resulted in no differentially expressed genes (DEGs) in the rodent model and less than 10 DEGs in humans, suggesting that this brain region is not significantly vulnerable to long-term alcohol abuse with prolonged abstinence. Further evidence was also found in the bulk sequencing approach (Study 1), where both methylome- and transcriptome-wide data of prefrontal and striatal regions were conducted, and the ventral striatum (VS) showed a limited number of DEGs and no overlapping genes in the data integration of methylation and transcription data. However, on the level of differentially methylated positions and regions, the VS was one of most affected regions observed. When comparing the results of all three brain regions in humans, SERPINA3 appears to be up-regulated independently of the region, suggesting this gene as a new biomarker for AUD. First preliminary snRNA-Seq data from the dorsomedial striatum of PD rats (Study 3) – the brain region that was also found in the human post-mortem brain to be most significantly altered on the multiomics level (Study 1) – suggests a pronounced relevance for oligodendrocytes and microglia in regard to altered transcripts that persist after long-term abstinence. These cell types have been previously found to be relevant in AUD patients and the post-dependent rats on several brain regions. III As indicated by studies 1-3, the immune system is strongly dysregulated in AUD. Therefore, in study 4, chronic alcohol consumption and alcohol dependence as potential risk factors for COVID-19 infection and severity was observed across multiple rat models of alcohol intake. Especially, the consistent up-regulation of ACE2 in lung tissue detected in all models as well as the reduction of Mas expression in the olfactory bulb led to the conclusion that alcohol intake – especially in a sub-chronic to chronic manner – might increase the propensity to develop a SARS-CoV2 infection and potentially, suffer from severe long-term consequences, such as anosmia

Biosensors for Environmental Monitoring

Real-time and reliable detection of molecular compounds and bacteria is essential in modern environmental monitoring. For rapid analyses, biosensing devices combining high selectivity of biomolecular recognition and sensitivity of modern signal-detection technologies offer a promising platform. Biosensors allow rapid on-site detection of pollutants and provide potential for better understanding of the environmental processes, including the fate and transport of contaminants.This book, including 12 chapters from 37 authors, introduces different biosensor-based technologies applied for environmental analyses

Lab-on-a-Chip Fabrication and Application

The necessity of on-site, fast, sensitive, and cheap complex laboratory analysis, associated with the advances in the microfabrication technologies and the microfluidics, made it possible for the creation of the innovative device lab-on-a-chip (LOC), by which we would be able to scale a single or multiple laboratory processes down to a chip format. The present book is dedicated to the LOC devices from two points of view: LOC fabrication and LOC application

An integrative polyomics investigation of bovine mastitis

Bovine mastitis, inflammation of the mammary gland, is one of the most costly and prevalent diseases in the dairy industry. It is commonly caused by bacteria, and Streptococcus uberis is one of the most prevalent causative agents. With advancements in omics technologies, the analysis of system-wide changes in the expression of proteins and metabolites in milk has become possible, and such analyses have broadened the knowledge of molecular changes in bovine mastitis. The work presented in this thesis aims to understand the dynamics of molecular changes in bovine mastitis caused by Streptococcus uberis through system-wide profiling and integrated analysis of milk proteins and metabolites. To this end, archived milk samples collected at specific intervals during the course of an experimentally induced model of Streptococcus uberis mastitis were used. Label-free quantitative proteomics and untargeted metabolomics data were generated from the archived milk samples obtained from six cows at six time-points (0, 36, 42, 57, 81 & 312 hours post-challenge). A total of 570 bovine proteins and 690 putative metabolites were quantified. Hierarchical cluster analysis and principal component analysis showed clustering of samples by the stage of infection, with similarities between pre-infection and resolution stages (0 and 312 hours post-challenge), early infection stages (36 and 42 hours post-challenge) and late infection stages (57 and 81 hours post-challenge). The proteomics and metabolomics data were analysed at both individual omics-layer level and combined inter-layer-level. At individual omics layer-level, the temporal changes identified include changes in the expression of proteins in acute-phase response signalling, FXR/RXR activation, complement system, IL-6 and IL-10 pathways, and changes in the expression of metabolites related to amino acid, carbohydrate, lipid and nucleotide metabolisms. The combined inter-layer-level analyses revealed functional relevance of proteins and metabolites enriched in the co-expression modules. For example, possible immunomodulatory role of bile acids via the FXR/RXR activation pathways could be inferred. Similarly, the actin-binding proteins could be linked to endocytic trafficking of signalling receptors. Overall, the work presented in this thesis provides deeper understanding of molecular changes in mastitis. On a secondary note, it also serves as a case study in the use of integrative polyomics analysis methods in the investigation of host-pathogen interactions