Since its first experimental implementation in 2005, single-molecule localization microscopy (SMLM) emerged as a versatile and powerful imaging tool for biological structures with nanometer resolution. By now, SMLM has compiled an extensive track-record of novel insights in sub- and inter- cellular organization.\\ Moreover, since all SMLM techniques rely on the analysis of emission patterns from isolated fluorophores, they inherently allocate molecular information $per$ $definitionem$.\\ Consequently, SMLM transitioned from its origin as pure high-resolution imaging instrument towards quantitative microscopy, where the key information medium is no longer the highly resolved image itself, but the raw localization data set.\\ The work presented in this thesis is part of the ongoing effort to translate those $per$ $se$ molecular information gained by SMLM imaging to insights into the structural organization of the targeted protein or even beyond. Although largely consistent in their objectives, the general distinction between global or segmentation clustering approaches on one side and particle averaging or meta-analyses techniques on the other is usually made.\\ During the course of my thesis, I designed, implemented and employed numerous quantitative approaches with varying degrees of complexity and fields of application.\\ \\ In my first major project, I analyzed the localization distribution of the integral protein gp210 of the nuclear pore complex (NPC) with an iterative \textit{k}-means algorithm. Relating the distinct localization statistics of separated gp210 domains to isolated fluorescent signals led, among others, to the conclusion that the anchoring ring of the NPC consists of 8 homo-dimers of gp210.\\ This is of particular significance, both because it answered a decades long standing question about the nature of the gp210 ring and it showcased the possibility to gain structural information well beyond the resolution capabilities of SMLM by crafty quantification approaches.\\ \\ The second major project reported comprises an extensive study of the synaptonemal complex (SNC) and linked cohesin complexes. Here, I employed a multi-level meta-analysis of the localization sets of various SNC proteins to facilitate the compilation of a novel model of the molecular organization of the major SNC components with so far unmatched extend and detail with isotropic three-dimensional resolution.\\ In a second venture, the two murine cohesin components SMC3 and STAG3 connected to the SNC were analyzed. Applying an adapted algorithm, considering the disperse nature of cohesins, led to the realization that there is an apparent polarization of those cohesin complexes in the SNC, as well as a possible sub-structure of STAG3 beyond the resolution capabilities of SMLM.\\ \\ Other minor projects connected to localization quantification included the study of plasma membrane glycans regarding their overall localization distribution and particular homogeneity as well as the investigation of two flotillin proteins in the membrane of bacteria, forming clusters of distinct shapes and sizes.\\ \\ Finally, a novel approach to three-dimensional SMLM is presented, employing the precise quantification of single molecule emitter intensities. This method, named TRABI, relies on the principles of aperture photometry which were improved for SMLM.\\ With TRABI it was shown, that widely used Gaussian fitting based localization software underestimates photon counts significantly. This mismatch was utilized as a $z$-dependent parameter, enabling the conversion of 2D SMLM data to a virtual 3D space. Furthermore it was demonstrated, that TRABI can be combined beneficially with a multi-plane detection scheme, resulting in superior performance regarding axial localization precision and resolution.\\ Additionally, TRABI has been subsequently employed to photometrically characterize a novel dye for SMLM, revealing superior photo-physical properties at the single-molecule level.\\ Following the conclusion of this thesis, the TRABI method and its applications remains subject of diverse ongoing research.

Lipid rafts are membrane microdomains specialized in the regulation of numerous cellular processes related to membrane organization, as diverse as signal transduction, protein sorting, membrane trafficking or pathogen invasion. It has been proposed that this functional diversity would require a heterogeneous population of raft domains with varying compositions. However, a mechanism for such diversification is not known. We recently discovered that bacterial membranes organize their signal transduction pathways in functional membrane microdomains (FMMs) that are structurally and functionally similar to the eukaryotic lipid rafts. In this report, we took advantage of the tractability of the prokaryotic model Bacillus subtilis to provide evidence for the coexistence of two distinct families of FMMs in bacterial membranes, displaying a distinctive distribution of proteins specialized in different biological processes. One family of microdomains harbors the scaffolding flotillin protein FloA that selectively tethers proteins specialized in regulating cell envelope turnover and primary metabolism. A second population of microdomains containing the two scaffolding flotillins, FloA and FloT, arises exclusively at later stages of cell growth and specializes in adaptation of cells to stationary phase. Importantly, the diversification of membrane microdomains does not occur arbitrarily. We discovered that bacterial cells control the spatio-temporal remodeling of microdomains by restricting the activation of FloT expression to stationary phase. This regulation ensures a sequential assembly of functionally specialized membrane microdomains to strategically organize signaling networks at the right time during the lifespan of a bacterium.

Aims Various studies have reported that young European women are more likely to develop early‐onset periodontitis compared to men. A potential explanation for the observed variations in sex and age of disease onset is the natural genetic variation within the autosomal genomes. We hypothesized that genotype‐by‐sex (G × S) interactions contribute to the increased prevalence and severity. Materials and methods Using the case‐only design, we tested for differences in genetic effects between men and women in 896 North‐West European early‐onset cases, using imputed genotypes from the OmniExpress genotyping array. Population‐representative 6823 controls were used to verify that the interacting variables G and S were uncorrelated in the general population. Results In total, 20 loci indicated G × S associations (P < 0.0005), 3 of which were previously suggested as risk genes for periodontitis (ABLIM2, CDH13, and NELL1). We also found independent G × S interactions of the related gene paralogs MACROD1/FLRT1 (chr11) and MACROD2/FLRT3 (chr20). G × S‐associated SNPs at CPEB4, CDH13, MACROD1, and MECOM were genome‐wide‐associated with heel bone mineral density (CPEB4, MECOM), waist‐to‐hip ratio (CPEB4, MACROD1), and blood pressure (CPEB4, CDH13). Conclusions Our results indicate that natural genetic variation affects the different heritability of periodontitis among sexes and suggest genes that contribute to inter‐sex phenotypic variation in early‐onset periodontitis.

Aggressiveness is a behavioral trait that has the potential to be harmful to individuals and society. With an estimated heritability of about 40%, genetics is important in its development. We performed an exploratory genome-wide association (GWA) analysis of childhood aggressiveness in attention deficit hyperactivity disorder (ADHD) to gain insight into the underlying biological processes associated with this trait. Our primary sample consisted of 1,060 adult ADHD patients (aADHD). To further explore the genetic architecture of childhood aggressiveness, we performed enrichment analyses of suggestive genome-wide associations observed in aADHD among GWA signals of dimensions of oppositionality (defiant/vindictive and irritable dimensions) in childhood ADHD (cADHD). No single polymorphism reached genome-wide significance (P<5.00E-08). The strongest signal in aADHD was observed at rs10826548, within a long noncoding RNA gene (beta = -1.66, standard error (SE) = 0.34, P = 1.07E-06), closely followed by rs35974940 in the neurotrimin gene (beta = 3.23, SE = 0.67, P = 1.26E-06). The top GWA SNPs observed in aADHD showed significant enrichment of signals from both the defiant/vindictive dimension (Fisher's P-value = 2.28E-06) and the irritable dimension in cADHD (Fisher's P-value = 0.0061). In sum, our results identify a number of biologically interesting markers possibly underlying childhood aggressiveness and provide targets for further genetic exploration of aggressiveness across psychiatric disorders.

Evidence for a shared genetic basis of association between coronary artery disease (CAD) and periodontitis (PD) exists. To explore the joint genetic basis, we performed a GWAS meta-analysis. In the discovery stage, we used a German aggressive periodontitis sample (AgP-Ger; 680 cases vs 3,973 controls) and the CARDIoGRAMplusC4D CAD meta-analysis dataset (60,801 cases vs 123,504 controls). Two SNPs at the known CAD risk loci ADAMTS7 (rs11634042) and VAMP8 (rs1561198) passed the pre-assigned selection criteria (PAgP-Ger < 0.05; PCAD < 5 × 10−8; concordant effect direction) and were replicated in an independent GWAS meta-analysis dataset of PD (4,415 cases vs 5,935 controls). SNP rs1561198 showed significant association (PD[Replication]: P = 0.008 OR = 1.09, 95% CI = [1.02–1.16]; PD [Discovery + Replication]: P = 0.0002, OR = 1.11, 95% CI = [1.05–1.17]). For the associated haplotype block, allele specific cis-effects on VAMP8 expression were reported. Our data adds to the shared genetic basis of CAD and PD and indicate that the observed association of the two disease conditions cannot be solely explained by shared environmental risk factors. We conclude that the molecular pathway shared by CAD and PD involves VAMP8 function, which has a role in membrane vesicular trafficking, and is manipulated by pathogens to corrupt host immune defense.