The structural substrate of brain function: analysis of brain structural networks based on diffusion-weighted imaging

The brain is a complex neural network with a hierarchical organization and the mapping of its elements and connections is an important step towards the understanding of its function. Recent developments in diffusion-weighted imaging have provided the opportunity to reconstruct the whole-brain structural network in-vivo at a large scale level and to study the brain structural substrate in a framework that is close to the current understanding of brain function. However, methods to construct the connectome are still under development and they should be carefully evaluated. To this end, the first two studies included in my thesis aimed at improving the analytical tools specific to the methodology of brain structural networks. The first of these papers assessed the repeatability of the most common global and local network metrics used in literature to characterize the connectome, while in the second paper the validity of further metrics based on the concept of communicability was evaluated. Communicability is a broader measure of connectivity which accounts also for parallel and indirect connections. These additional paths may be important for reorganizational mechanisms in the presence of lesions as well as to enhance integration in the network. These studies showed good to excellent repeatability of global network metrics when the same methodological pipeline was applied, but more variability was detected when considering local network metrics or when using different thresholding strategies. In addition, communicability metrics have been found to add some insight into the integration properties of the network by detecting subsets of nodes that were highly interconnected or vulnerable to lesions. The other two studies used methods based on diffusion-weighted imaging to obtain knowledge concerning the relationship between functional and structural connectivity and about the etiology of schizophrenia. The third study integrated functional oscillations measured using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) as well as diffusion-weighted imaging data. The multimodal approach that was applied revealed a positive relationship between individual fluctuations of the EEG alpha-frequency and diffusion properties of specific connections of two resting-state networks. Finally, in the fourth study diffusion-weighted imaging was used to probe for a relationship between the underlying white matter tissue structure and season of birth in schizophrenia patients. The results are in line with the neurodevelopmental hypothesis of early pathological mechanisms as the origin of schizophrenia. The different analytical approaches selected in these studies also provide arguments for discussion of the current limitations in the analysis of brain structural networks. To sum up, the first studies presented in this thesis illustrated the potential of brain structural network analysis to provide useful information on features of brain functional segregation and integration using reliable network metrics. In the other two studies alternative approaches were presented. The common discussion of the four studies enabled us to highlight the benefits and possibilities for the analysis of the connectome as well as some current limitations.

Cascading climate effects and related ecological consequences during past centuries

The interface between climate and ecosystem structure and function is incompletely understood, partly because few ecological records start before the recent warming phase. Here, we analyse an exceptional 100-yr long record of the great tit (Parus major) population in Switzerland in relation to climate and habitat phenology. Using structural equation analysis, we demonstrate an uninterrupted cascade of significant influences of the large-scale atmospheric circulation (North-Atlantic Oscillation, NAO, and North-sea – Caspian Pattern, NCP) on habitat and breeding phenology, and further on fitness-relevant life history traits within great tit populations. We then apply the relationships of this analysis to reconstruct the circulation-driven component of fluctuations in great tit breeding phenology and productivity on the basis of new seasonal NAO and NCP indices back to 1500 AD. According to the structural equation model, the multi-decadal oscillation of the atmospheric circulation likely led to substantial variation in habitat phenology, productivity and consequently, tit population fluctuations with minima during the "Maunder Minimum" (∼ 1650–1720) and the Little Ice Age Type Event I (1810–1850). The warming since 1975 was not only related with a quick shift towards earlier breeding, but also with the highest productivity since 1500, and thus, the impact of the NAO and NCP has contributed to an unprecedented increase of the population. A verification of the structural equation model against two independent data series (1970–2000 and 1750–1900) corroborates that the retrospective model reliably depicts the major long-term NAO/NCP impact on ecosystem parameters. The results suggest a complex cascade of climate effects beginning at a global scale and ending at the level of individual life histories. This sheds light on how large-scale climate conditions substantially affect major life history parameters within a population, and thus influence key ecosystem parameters at the scale of centuries.

Structural analysis of Heschl's gyrus in schizophrenia patients with auditory hallucinations

Heschl's gyrus (HG) is functionally involved in the genesis of auditory verbal hallucinations (AVH). This dysfunction seems to be structurally facilitated. The aim of the study was to analyze macrostructural features of HG in a group of patients reporting AVH who demonstrated white matter diffusion tensor imaging abnormalities reported previously.

Structural differences between the bladder dome and trigone revealed by mRNA expression analysis of cold-cut biopsies

To establish the mRNA expression profiles of selected genes involved in bladder contractility and epithelial permeability in the bladder dome and trigone in order to evaluate the use of cold-cut biopsies for comparative quantitative studies into the anatomical differences between these two bladder regions.

Fic domain-catalyzed adenylylation: insight provided by the structural analysis of the type IV secretion system effector BepA

Numerous bacterial pathogens subvert cellular functions of eukaryotic host cells by the injection of effector proteins via dedicated secretion systems. The type IV secretion system (T4SS) effector protein BepA from Bartonella henselae is composed of an N-terminal Fic domain and a C-terminal Bartonella intracellular delivery domain, the latter being responsible for T4SS-mediated translocation into host cells. A proteolysis resistant fragment (residues 10-302) that includes the Fic domain shows autoadenylylation activity and adenylyl transfer onto Hela cell extract proteins as demonstrated by autoradiography on incubation with α-[(32)P]-ATP. Its crystal structure, determined to 2.9-Å resolution by the SeMet-SAD method, exhibits the canonical Fic fold including the HPFxxGNGRxxR signature motif with several elaborations in loop regions and an additional β-rich domain at the C-terminus. On crystal soaking with ATP/Mg(2+), additional electron density indicated the presence of a PP(i) /Mg(2+) moiety, the side product of the adenylylation reaction, in the anion binding nest of the signature motif. On the basis of this information and that of the recent structure of IbpA(Fic2) in complex with the eukaryotic target protein Cdc42, we present a detailed model for the ternary complex of Fic with the two substrates, ATP/Mg(2+) and target tyrosine. The model is consistent with an in-line nucleophilic attack of the deprotonated side-chain hydroxyl group onto the α-phosphorus of the nucleotide to accomplish AMP transfer. Furthermore, a general, sequence-independent mechanism of target positioning through antiparallel β-strand interactions between enzyme and target is suggested.

Reconstitution of mitochondrial ATP synthase into lipid bilayers for structural analysis

Mitochondrial F(1)F(o)-ATP synthase is a molecular motor that couples the energy generated by oxidative metabolism to the synthesis of ATP. Direct visualization of the rotary action of the bacterial ATP synthase has been well characterized. However, direct observation of rotation of the mitochondrial enzyme has not been reported yet. Here, we describe two methods to reconstitute mitochondrial F(1)F(o)-ATP synthase into lipid bilayers suitable for structure analysis by electron and atomic force microscopy (AFM). Proteoliposomes densely packed with bovine heart mitochondria F(1)F(o)-ATP synthase were obtained upon detergent removal from ternary mixtures (lipid, detergent and protein). Two-dimensional crystals of recombinant hexahistidine-tagged yeast F(1)F(o)-ATP synthase were grown using the supported monolayer technique. Because the hexahistidine-tag is located at the F(1) catalytic subcomplex, ATP synthases were oriented unidirectionally in such two-dimensional crystals, exposing F(1) to the lipid monolayer and the F(o) membrane region to the bulk solution. This configuration opens a new avenue for the determination of the c-ring stoichiometry of unknown hexahistidine-tagged ATP synthases and the organization of the membrane intrinsic subunits within F(o) by electron microscopy and AFM.

GH mutant (R77C) in a pedigree presenting with the delay of growth and pubertal development: structural analysis of the mutant and evaluation of the biological activity

A heterozygous missense mutation in the GH-1 gene converting codon 77 from arginine (R) to cysteine (C), which was previously reported to have some GH antagonistic effect, was identified in a Syrian family. The index patient, a boy, was referred for assessment of his short stature (-2.5 SDS) at the age of 6 years. His mother and grandfather were also carrying the same mutation, but did not differ in adult height from the other unaffected family members. Hormonal examination in all affected subjects revealed increased basal GH, low IGF-I concentrations, and subnormal IGF-I response in generation test leading to the diagnosis of partial GH insensitivity. However, GH receptor gene (GHR) sequencing demonstrated no abnormalities. As other family members carrying the GH-R77C form showed similar alterations at the hormonal level, but presented with normal final height, no GH therapy was given to the boy, but he was followed through his pubertal development which was delayed. At the age of 20 years he reached his final height, which was normal within his parental target height. Functional characterization of the GH-R77C, assessed through activation of Jak2/Stat5 pathway, revealed no differences in the bioactivity between wild-type-GH (wt-GH) and GH-R77C. Detailed structural analysis indicated that the structure of GH-R77C, in terms of disulfide bond formation, is almost identical to that of the wt-GH despite the introduced mutation (Cys77). Previous studies from our group demonstrated a reduced capability of GH-R77C to induce GHR/GH-binding protein (GHBP) gene transcription rate when compared with wt-GH. Therefore, reduced GHR/GHBP expression might well be the possible cause for the partial GH insensitivity found in our patients. In addition, this group of patients deserve further attention because they could represent a distinct clinical entity underlining that an altered GH peptide may also have a direct impact on GHR/GHBP gene expression causing partial GH insensitivity. This might be responsible for the delay of growth and pubertal development. Finally, we clearly demonstrate that GH-R77C is not invariably associated with short stature, but that great care needs to be taken in ascribing growth failure to various heterozygous mutations affecting the GH-IGF axis and that careful functional studies are mandatory.

Structural analysis of B-Box 2 from MuRF1: identification of a novel self-association pattern in a RING-like fold

The B-box motif is the defining feature of the TRIM family of proteins, characterized by a RING finger-B-box-coiled coil tripartite fold. We have elucidated the crystal structure of B-box 2 (B2) from MuRF1, a TRIM protein that supports a wide variety of protein interactions in the sarcomere and regulates the trophic state of striated muscle tissue. MuRF1 B2 coordinates two zinc ions through a cross-brace alpha/beta-topology typical of members of the RING finger superfamily. However, it self-associates into dimers with high affinity. The dimerization pattern is mediated by the helical component of this fold and is unique among RING-like folds. This B2 reveals a long shallow groove that encircles the C-terminal metal binding site ZnII and appears as the defining protein-protein interaction feature of this domain. A cluster of conserved hydrophobic residues in this groove and, in particular, a highly conserved aromatic residue (Y133 in MuRF1 B2) is likely to be central to this role. We expect these findings to aid the future exploration of the cellular function and therapeutic potential of MuRF1.

A new approach to detect structural differences in lung parenchyma using digital image analysis

Morphometric investigations using a point and intersection counting strategy in the lung often are not able to reveal the full set of morphologic changes. This happens particularly when structural modifications are not expressed in terms of volume density changes and when rough and fine surface density alterations cancel each other at different magnifications. Making use of digital image processing, we present a methodological approach that allows to easily and quickly quantify changes of the geometrical properties of the parenchymal lung structure and reflects closely the visual appreciation of the changes. Randomly sampled digital images from light microscopic sections of lung parenchyma are filtered, binarized, and skeletonized. The lung septa are thus represented as a single-pixel wide line network with nodal points and end points and the corresponding internodal and end segments. By automatically counting the number of points and measuring the lengths of the skeletal segments, the lung architecture can be characterized and very subtle structural changes can be detected. This new methodological approach to lung structure analysis is highly sensitive to morphological changes in the parenchyma: it detected highly significant quantitative alterations in the structure of lungs of rats treated with a glucocorticoid hormone, where the classical morphometry had partly failed.

Repeatability analysis of global and local metrics of brain structural networks

Computational network analysis provides new methods to analyze the human connectome. Brain structural networks can be characterized by global and local metrics that recently gave promising insights for diagnosis and further understanding of neurological, psychiatric and neurodegenerative disorders. In order to ensure the validity of results in clinical settings the precision and repeatability of the networks and the associated metrics must be evaluated. In the present study, nineteen healthy subjects underwent two consecutive measurements enabling us to test reproducibility of the brain network and its global and local metrics. As it is known that the network topology depends on the network density, the effects of setting a common density threshold for all networks were also assessed. Results showed good to excellent repeatability for global metrics, while for local metrics it was more variable and some metrics were found to have locally poor repeatability. Moreover, between subjects differences were slightly inflated when the density was not fixed. At the global level, these findings confirm previous results on the validity of global network metrics as clinical biomarkers. However, the new results in our work indicate that the remaining variability at the local level as well as the effect of methodological characteristics on the network topology should be considered in the analysis of brain structural networks and especially in networks comparisons.

Validation of network communicability metrics for the analysis of brain structural networks.

Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.