Development of novel Classical and Quantum Information Theory Based Methods for the Detection of Compensatory Mutations in MSAs

Multiple Sequenzalignments (MSAs) von homologen Proteinen sind nützliche Werkzeuge, um kompensatorische Mutationen zwischen nicht-konservierten Residuen zu charakterisieren. Die Identifizierung dieser Residuen in MSAs ist eine wichtige Aufgabe um die strukturellen Grundlagen und molekularen Mechanismen von Proteinfunktionen besser zu verstehen. Trotz der vielen Anzahl an Literatur über kompensatorische Mutationen sowie über die Sequenzkonservierungsanalyse für die Erkennung von wichtigen Residuen, haben vorherige Methoden meistens die biochemischen Eigenschaften von Aminosäuren nicht mit in Betracht gezogen, welche allerdings entscheidend für die Erkennung von kompensatorischen Mutationssignalen sein können. Jedoch werden kompensatorische Mutationssignale in MSAs oft durch das Rauschen verfälscht. Aus diesem Grund besteht ein weiteres Problem der Bioinformatik in der Trennung signifikanter Signale vom phylogenetischen Rauschen und beziehungslosen Paarsignalen. Das Ziel dieser Arbeit besteht darin Methoden zu entwickeln, welche biochemische Eigenschaften wie Ähnlichkeiten und Unähnlichkeiten von Aminosäuren in der Identifizierung von kompensatorischen Mutationen integriert und sich mit dem Rauschen auseinandersetzt. Deshalb entwickeln wir unterschiedliche Methoden basierend auf klassischer- und quantum Informationstheorie sowie multiple Testverfahren. Unsere erste Methode basiert auf der klassischen Informationstheorie. Diese Methode betrachtet hauptsächlich BLOSUM62-unähnliche Paare von Aminosäuren als ein Modell von kompensatorischen Mutationen und integriert sie in die Identifizierung von wichtigen Residuen. Um diese Methode zu ergänzen, entwickeln wir unsere zweite Methode unter Verwendung der Grundlagen von quantum Informationstheorie. Diese neue Methode unterscheidet sich von der ersten Methode durch gleichzeitige Modellierung ähnlicher und unähnlicher Signale in der kompensatorischen Mutationsanalyse. Des Weiteren, um signifikante Signale vom Rauschen zu trennen, entwickeln wir ein MSA-spezifisch statistisches Modell in Bezug auf multiple Testverfahren. Wir wenden unsere Methode für zwei menschliche Proteine an, nämlich epidermal growth factor receptor (EGFR) und glucokinase (GCK). Die Ergebnisse zeigen, dass das MSA-spezifisch statistische Modell die signifikanten Signale vom phylogenetischen Rauschen und von beziehungslosen Paarsignalen trennen kann. Nur unter Berücksichtigung BLOSUM62-unähnlicher Paare von Aminosäuren identifiziert die erste Methode erfolgreich die krankheits-assoziierten wichtigen Residuen der beiden Proteine. Im Gegensatz dazu, durch die gleichzeitige Modellierung ähnlicher und unähnlicher Signale von Aminosäurepaare ist die zweite Methode sensibler für die Identifizierung von katalytischen und allosterischen Residuen

Coupled mutation finder: A new entropy-based method quantifying phylogenetic noise for the detection of compensatory mutations

Background: The detection of significant compensatory mutation signals in multiple sequence alignments (MSAs) is often complicated by noise. A challenging problem in bioinformatics is remains the separation of significant signals between two or more non-conserved residue sites from the phylogenetic noise and unrelated pair signals. Determination of these non-conserved residue sites is as important as the recognition of strictly conserved positions for understanding of the structural basis of protein functions and identification of functionally important residue regions. In this study, we developed a new method, the Coupled Mutation Finder (CMF) quantifying the phylogenetic noise for the detection of compensatory mutations.Results: To demonstrate the effectiveness of this method, we analyzed essential sites of two human proteins: epidermal growth factor receptor (EGFR) and glucokinase (GCK). Our results suggest that the CMF is able to separate significant compensatory mutation signals from the phylogenetic noise and unrelated pair signals. The vast majority of compensatory mutation sites found by the CMF are related to essential sites of both proteins and they are likely to affect protein stability or functionality.Conclusions: The CMF is a new method, which includes an MSA-specific statistical model based on multiple testing procedures that quantify the error made in terms of the false discovery rate and a novel entropy-based metric to upscale BLOSUM62 dissimilar compensatory mutations. Therefore, it is a helpful tool to predict and investigate compensatory mutation sites of structural or functional importance in proteins. We suggest that the CMF could be used as a novel automated function prediction tool that is required for a better understanding of the structural basis of proteins. The CMF server is freely accessible at http://cmf.bioinf.med.uni-goettingen.de

Optogenetics and electron tomography for structure-function analysis of cochlear ribbon synapses

Ribbon synapses of cochlear inner hair cells (IHCs) are specialized to indefatigably transmit sound information at high rates. To understand the underlying mechanisms, structure-function analysis of the active zone (AZ) of these synapses is essential. Previous electron microscopy studies of synaptic vesicle (SV) dynamics at the IHC AZ used potassium stimulation, which limited the temporal resolution to minutes. Here, we established optogenetic IHC stimulation followed by quick freezing within milliseconds and electron tomography to study the ultrastructure of functional synapse states with good temporal resolution in mice. We characterized optogenetic IHC stimulation by patch-clamp recordings from IHCs and postsynaptic boutons revealing robust IHC depolarization and neurotransmitter release. Ultrastructurally, the number of docked SVs increased upon short (17–25 ms) and long (48–76 ms) light stimulation paradigms. We did not observe enlarged SVs or other morphological correlates of homotypic fusion events. Our results indicate a rapid recruitment of SVs to the docked state upon stimulation and suggest that univesicular release prevails as the quantal mechanism of exocytosis at IHC ribbon synapses

Removing Background Co-occurrences of Transcription Factor Binding Sites Greatly Improves the Prediction of Specific Transcription Factor Cooperations

Today, it is well-known that in eukaryotic cells the complex interplay of transcription factors (TFs) bound to the DNA of promoters and enhancers is the basis for precise and specific control of transcription. Computational methods have been developed for the identification of potentially cooperating TFs through the co-occurrence of their binding sites (TFBSs). One challenge of these methods is the differentiation of TFBS pairs that are specific for a given sequence set from those that are ubiquitously appearing, rendering the results highly dependent on the choice of a proper background set. Here, we present an extension of our previous PC-TraFF approach that estimates the background co-occurrence of any TF pair by preserving the (oligo-) nucleotide composition and, thus, the core of TFBSs in the sequences of interest. Applying our approach to a simulated data set with implanted TFBS pairs, we could successfully identify them as sequence-set specific under a variety of conditions. When we analyzed the gene expression data sets of five breast cancer associated subtypes, the number of overlapping pairs could be dramatically reduced in comparison to our previous approach. As a result, we could identify potentially cooperating transcriptional regulators that are characteristic for each of the five breast cancer subtypes. This indicates that our approach is able to discriminate specific potential TF cooperations against ubiquitously occurring combinations. The results obtained with our method may help to understand the genetic programs governing specific biological processes such as the development of different tumor types

Computational Identification of Master Regulators Influencing Trypanotolerance in Cattle

African Animal Trypanosomiasis (AAT) is transmitted by the tsetse fly which carries pathogenic trypanosomes in its saliva, thus causing debilitating infection to livestock health. As the disease advances, a multistage progression process is observed based on the progressive clinical signs displayed in the host’s body. Investigation of genes expressed with regular monotonic patterns (known as Monotonically Expressed Genes (MEGs)) and of their master regulators can provide important clue for the understanding of the molecular mechanisms underlying the AAT disease. For this purpose, we analysed MEGs for three tissues (liver, spleen and lymph node) of two cattle breeds, namely trypanosusceptible Boran and trypanotolerant N’Dama. Our analysis revealed cattle breed-specific master regulators which are highly related to distinguish the genetic programs in both cattle breeds. Especially the master regulators MYC and DBP found in this study, seem to influence the immune responses strongly, thereby susceptibility and trypanotolerance of Boran and N’Dama respectively. Furthermore, our pathway analysis also bolsters the crucial roles of these master regulators. Taken together, our findings provide novel insights into breed-specific master regulators which orchestrate the regulatory cascades influencing the level of trypanotolerance in cattle breeds and thus could be promising drug targets for future therapeutic interventions

agReg-SNPdb: A Database of Regulatory SNPs for Agricultural Animal Species

Transcription factors (TFs) govern transcriptional gene regulation by specifically binding to short DNA motifs, known as transcription factor binding sites (TFBSs), in regulatory regions, such as promoters. Today, it is well known that single nucleotide polymorphisms (SNPs) in TFBSs can dramatically affect the level of gene expression, since they can cause a change in the binding affinity of TFs. Such SNPs, referred to as regulatory SNPs (rSNPs), have gained attention in the life sciences due to their causality for specific traits or diseases. In this study, we present agReg-SNPdb, a database comprising rSNP data of seven agricultural and domestic animal species: cattle, pig, chicken, sheep, horse, goat, and dog. To identify the rSNPs, we constructed a bioinformatics pipeline and identified a total of 10,623,512 rSNPs, which are located within TFBSs and affect the binding affinity of putative TFs. Altogether, we implemented the first systematic analysis of SNPs in promoter regions and their impact on the binding affinity of TFs for livestock and made it usable via a web interface

Genotyping by Sequencing Reads of 20 Vicia faba Lines with High and Low Vicine and Convicine Content

The grain faba bean (Vicia faba) which belongs to the family of the Leguminosae, is a crop that is grown worldwide for consumption by humans and livestock. Despite being a rich source of plant-based protein and various agro-ecological advantages its usage is limited due to its anti-nutrients in the form of the seed-compounds vicine and convicine (V+C). While markers for a low V+C content exist the underlying pathway and the responsible genes have remained unknown for a long time and only recently a possible pathway and enzyme were found. Genetic research into Vicia faba is difficult due to the lack of a reference genome and the near exclusivity of V+C to the species. Here, we present sequence reads obtained through genotyping-by-sequencing of 20 Vicia faba lines with varying V+C contents. For each line, ∼3 million 150 bp paired end reads are available. This data can be useful in the genomic research of Vicia faba in general and its V+C content in particular

Identifying Cattle Breed-Specific Partner Choice of Transcription Factors during the African Trypanosomiasis Disease Progression Using Bioinformatics Analysis

African Animal Trypanosomiasis (AAT) is a disease caused by pathogenic trypanosomes which affects millions of livestock every year causing huge economic losses in agricultural production especially in sub-Saharan Africa. The disease is spread by the tsetse fly which carries the parasite in its saliva. During the disease progression, the cattle are prominently subjected to anaemia, weight loss, intermittent fever, chills, neuronal degeneration, congestive heart failure, and finally death. According to their different genetic programs governing the level of tolerance to AAT, cattle breeds are classified as either resistant or susceptible. In this study, we focus on the cattle breeds N’Dama and Boran which are known to be resistant and susceptible to trypanosomiasis, respectively. Despite the rich literature on both breeds, the gene regulatory mechanisms of the underlying biological processes for their resistance and susceptibility have not been extensively studied. To address the limited knowledge about the tissue-specific transcription factor (TF) cooperations associated with trypanosomiasis, we investigated gene expression data from these cattle breeds computationally. Consequently, we identified significant cooperative TF pairs (especially D B P − P P A R A and D B P − T H A P 1 in N’Dama and D B P − P A X 8 in Boran liver tissue) which could help understand the underlying AAT tolerance/susceptibility mechanism in both cattle breeds