Using unsupervised metabolomics, we defined the complex metabolic conditions in the cortex of a mouse model of Rett syndrome (RTT). RTT, which represents a cause of mental and cognitive disabilities in females, results in profound cognitive impairment with autistic features, motor disabilities, seizures, gastrointestinal problems, and cardiorespiratory irregularities. Typical RTT originates from mutations in the X-chromosomal methyl-CpG-binding-protein-2 (Mecp2) gene, which encodes a transcriptional modulator. It then causes a deregulation of several target genes and metabolic alterations in the nervous system and peripheral organs. We identified 101 significantly deregulated metabolites in the Mecp2-deficient cortex of adult male mice; 68 were increased and 33 were decreased compared to wildtypes. Pathway analysis identified 31 mostly upregulated metabolic pathways, in particular carbohydrate and amino acid metabolism, key metabolic mitochondrial/extramitochondrial pathways, and lipid metabolism. In contrast, neurotransmitter-signaling is dampened. This metabolic fingerprint of the Mecp2-deficient cortex of severely symptomatic mice provides further mechanistic insights into the complex RTT pathogenesis. The deregulated pathways that were identified—in particular the markedly affected amino acid and carbohydrate metabolism—confirm a complex and multifaceted metabolic component in RTT, which in turn signifies putative therapeutic targets. Furthermore, the deregulated key metabolites provide a choice of potential biomarkers for a more detailed rating of disease severity and disease progression.

Rett syndrome (RTT) is a genetic neurodevelopmental disorder with mutations in the X-chromosomal MECP2 (methyl-CpG-binding protein 2) gene. Most patients are young girls. For 7–18 months after birth, they hardly present any symptoms; later they develop mental problems, a lack of communication, irregular sleep and breathing, motor dysfunction, hand stereotypies, and seizures. The complex pathology involves mitochondrial structure and function. Mecp2^−/y hippocampal astrocytes show increased mitochondrial contents. Neurons and glia suffer from oxidative stress, a lack of ATP, and increased hypoxia vulnerability. This spectrum of changes demands comprehensive molecular studies of mitochondria to further define their pathogenic role in RTT. Therefore, we applied a comparative proteomic approach for the first time to study the entity of mitochondrial proteins in a mouse model of RTT. In the neocortex and hippocampus of symptomatic male mice, two-dimensional gel electrophoresis and subsequent mass-spectrometry identified various differentially expressed mitochondrial proteins, including components of respiratory chain complexes I and III and the ATP-synthase FoF1 complex. The NADH-ubiquinone oxidoreductase 75 kDa subunit, NADH dehydrogenase [ubiquinone] iron-sulfur protein 8, NADH dehydrogenase [ubiquinone] flavoprotein 2, cytochrome b-c1 complex subunit 1, and ATP synthase subunit d are upregulated either in the hippocampus alone or both the hippocampus and neocortex of Mecp2^−/y mice. Furthermore, the regulatory mitochondrial proteins mitofusin-1, HSP60, and 14-3-3 protein theta are decreased in the Mecp2^−/y neocortex. The expressional changes identified provide further details of the altered mitochondrial function and morphology in RTT. They emphasize brain-region-specific alterations of the mitochondrial proteome and support the notion of a metabolic component of this devastating disorder.

Ticks serve as vectors for numerous pathogens, making their ecological characterization essential for disease control measures. Within the country of Georgia, multiple medically-relevant tick species are prevalent, yet comprehensive studies on tick community composition and biogeographic patterns remain limited. We analyzed 720 tick occurrence records representing 21 species collected across Georgia from 2013-2023, integrating these data with environmental covariates. Species distribution models were developed using boosted regression trees, while bioregions were constructed using spatially constrained hierarchical clustering. Co-occurrence networks were constructed to identify co-occurring species. Biodiversity metrics were calculated to characterize community structure. Tick diversity was high across Georgia (Shannon's H' = 2.40, Gini-Simpson = 0.89) with moderate evenness (Pielou = 0.79) and low dominance (Berger-Parker = 0.17). The species with the most presence records were Ixodes ricinus (17.2% of records), Haemaphysalis punctata (16.4%), and Dermacentor marginatus (14.6%). Three distinct bioregions were identified, with temperature being the most influential feature driving tick distribution and bioregionalization. Nine significant positive co-occurrence relationships were detected between species pairs, with no negative associations observed. Species distribution models revealed high niche overlap across all seven modeled species (mean Schoener's D = 0.91, Warren's I = 0.74), with southeastern Georgia showing the highest predicted suitability for most species. Our findings highlight strong biodiversity, overlapping distributions, and the importance of temperature in influencing tick ecology in Georgia. These results underscore the need for integrated multi-species vector control and the value of ecological frameworks for guiding vector-borne disease prevention in the region.