Leveraging interindividual variability in threat conditioning of inbred mice to model trait anxiety.

Trait anxiety is a major risk factor for stress-induced and anxiety disorders in humans. However, animal models accounting for the interindividual variability in stress vulnerability are largely lacking. Moreover, the pervasive bias of using mostly male animals in preclinical studies poorly reflects the increased prevalence of psychiatric disorders in women. Using the threat imminence continuum theory, we designed and validated an auditory aversive conditioning-based pipeline in both female and male mice. We operationalised trait anxiety by harnessing the naturally occurring variability of defensive freezing responses combined with a model-based clustering strategy. While sustained freezing during prolonged retrieval sessions was identified as an anxiety-endophenotype behavioral marker in both sexes, females were consistently associated with an increased freezing response. RNA-sequencing of CeA, BLA, ACC, and BNST revealed massive differences in phasic and sustained responders' transcriptomes, correlating with transcriptomic signatures of psychiatric disorders, particularly post-traumatic stress disorder (PTSD). Moreover, we detected significant alterations in the excitation/inhibition balance of principal neurons in the lateral amygdala. These findings provide compelling evidence that trait anxiety in inbred mice can be leveraged to develop translationally relevant preclinical models to investigate mechanisms of stress susceptibility in a sex-specific manner.

ViNe-Seg: deep-learning-assisted segmentation of visible neurons and subsequent analysis embedded in a graphical user interface.

SUMMARY: Segmentation of neural somata is a crucial and usually the most time-consuming step in the analysis of optical functional imaging of neuronal microcircuits. In recent years, multiple auto-segmentation tools have been developed to improve the speed and consistency of the segmentation process, mostly, using deep learning approaches. Current segmentation tools, while advanced, still encounter challenges in producing accurate segmentation results, especially in datasets with a low signal-to-noise ratio. This has led to a reliance on manual segmentation techniques. However, manual methods, while customized to specific laboratory protocols, can introduce variability due to individual differences in interpretation, potentially affecting dataset consistency across studies. In response to this challenge, we present ViNe-Seg: a deep-learning-based semi-automatic segmentation tool that offers (i) detection of visible neurons, irrespective of their activity status; (ii) the ability to perform segmentation during an ongoing experiment; (iii) a user-friendly graphical interface that facilitates expert supervision, ensuring precise identification of Regions of Interest; (iv) an array of segmentation models with the option of training custom models and sharing them with the community; and (v) seamless integration of subsequent analysis steps. AVAILABILITY AND IMPLEMENTATION: ViNe-Seg code and documentation are publicly available at https://github.com/NiRuff/ViNe-Seg and can be installed from https://pypi.org/project/ViNeSeg/.

NanopoReaTA: a user-friendly tool for nanopore-seq real-time transcriptional analysis.

SUMMARY: Oxford Nanopore Technologies' (ONT) sequencing platform offers an excellent opportunity to perform real-time analysis during sequencing. This feature allows for early insights into experimental data and accelerates a potential decision-making process for further analysis, which can be particularly relevant in the clinical context. Although some tools for the real-time analysis of DNA-sequencing data already exist, there is currently no application available for differential transcriptome data analysis designed for scientists or physicians with limited bioinformatics knowledge. Here, we introduce NanopoReaTA, a user-friendly real-time analysis toolbox for RNA-sequencing data from ONT. Sequencing results from a running or finished experiment are processed through an R Shiny-based graphical user interface with an integrated Nextflow pipeline for whole transcriptome or gene-specific analyses. NanopoReaTA provides visual snapshots of a sequencing run in progress, thus enabling interactive sequencing and rapid decision making that could also be applied to clinical cases. AVAILABILITY AND IMPLEMENTATION: Github https://github.com/AnWiercze/NanopoReaTA; Zenodo https://doi.org/10.5281/zenodo.8099825.

A Call for Gene Expression Analysis in Whole Blood of Patients With Rheumatoid Arthritis (RA) as a Biomarker for RA-Associated Interstitial Lung Disease.

OBJECTIVE: Rheumatoid arthritis (RA)-associated interstitial lung disease (ILD) is one of the most common and prognostic organ manifestations of RA. Therefore, to allow effective treatment, it is of crucial importance to diagnose RA-ILD at the earliest possible stage. So far, the gold standard of early detection has been high-resolution computed tomography (HRCT) of the lungs. This procedure involves considerable radiation exposure for the patient and is therefore unsuitable as a routine screening measure for ethical reasons. Here, we propose the analysis of characteristic gene expression patterns as a biomarker to aid in the early detection and initiation of appropriate, possibly antifibrotic, therapy. METHODS: To investigate unique molecular patterns of RA-ILD, whole blood samples were taken from 12 female patients with RA-ILD (n = 7) or RA (n = 5). The RNA was extracted, sequenced by RNA-Seq, and analyzed for characteristic differences in the gene expression patterns between patients with RA-ILD and those with RA without ILD. RESULTS: The differential gene expression analysis revealed 9 significantly upregulated genes in RA-ILD compared to RA without ILD: arginase 1 (ARG1), thymidylate synthetase (TYMS), sortilin 1 (SORT1), marker of proliferation Ki-67 (MKI67), olfactomedin 4 (OLFM4), baculoviral inhibitor of apoptosis repeat containing 5 (BIRC5), membrane spanning 4-domains A4A (MS4A4A), C-type lectin domain family 12 member A (CLEC12A), and the long intergenic nonprotein coding RNA (LINC02967). CONCLUSION: All gene products of these genes (except for LINC02967) are known from the literature to be involved in the pathogenesis of fibrosis. Further, for some, a contribution to the development of pulmonary fibrosis has even been demonstrated in experimental studies. Therefore, the results presented here provide an encouraging perspective for using specific gene expression patterns as biomarkers for the early detection and differential diagnosis of RA-ILD as a routine screening test.

Dichotomic Hippocampal Transcriptome After Glutamatergic vs. GABAergic Deletion of the Cannabinoid CB1 Receptor.

Brain homeostasis is the dynamic equilibrium whereby physiological parameters are kept actively within a specific range. The homeostatic range is not fixed and may change throughout the individual's lifespan, or may be transiently modified in the presence of severe perturbations. The endocannabinoid system has emerged as a safeguard of homeostasis, e.g., it modulates neurotransmission and protects neurons from prolonged or excessively strong activation. We used genetically engineered mouse lines that lack the cannabinoid type-1 receptor (CB1) either in dorsal telencephalic glutamatergic or in forebrain GABAergic neurons to create new allostatic states, resulting from alterations in the excitatory/inhibitory (E/I) balance. Previous studies with these two mouse lines have shown dichotomic results in the context of behavior, neuronal morphology, and electrophysiology. Thus, we aimed at analyzing the transcriptomic profile of the hippocampal CA region from these mice in the basal condition and after a mild behavioral stimulation (open field). Our results provide insights into the gene networks that compensate chronic E/I imbalances. Among these, there are differentially expressed genes involved in neuronal and synaptic functions, synaptic plasticity, and the regulation of behavior. Interestingly, some of these genes, e.g., Rab3b, Crhbp, and Kcnn2, and related pathways showed a dichotomic expression, i.e., they are up-regulated in one mutant line and down-regulated in the other one. Subsequent interrogation on the source of the alterations at transcript level were applied using exon-intron split analysis. However, no strong directions toward transcriptional or post-transcriptional regulation comparing both mouse lines were observed. Altogether, the dichotomic gene expression observed and their involved signaling pathways are of interest because they may act as "switches" to modulate the directionality of neural homeostasis, which then is relevant for pathologies, such as stress-related disorders and epilepsy.

Voluntary Wheel Running Did Not Alter Gene Expression in 5xfad Mice, but in Wild-Type Animals Exclusively after One-Day of Physical Activity.

Physical activity is considered a promising preventive intervention to reduce the risk of developing Alzheimer's disease (AD). However, the positive effect of therapeutic administration of physical activity has not been proven conclusively yet, likely due to confounding factors such as varying activity regimens and life or disease stages. To examine the impact of different routines of physical activity in the early disease stages, we subjected young 5xFAD and wild-type mice to 1-day (acute) and 30-day (chronic) voluntary wheel running and compared them with age-matched sedentary controls. We observed a significant increase in brain lactate levels in acutely trained 5xFAD mice relative to all other experimental groups. Subsequent brain RNA-seq analysis did not reveal major differences in transcriptomic regulation between training durations in 5xFAD mice. In contrast, acute training yielded substantial gene expression changes in wild-type animals relative to their chronically trained and sedentary counterparts. The comparison of 5xFAD and wild-type mice showed the highest transcriptional differences in the chronic and sedentary groups, whereas acute training was associated with much fewer differentially expressed genes. In conclusion, our results suggest that different training durations did not affect the global transcriptome of 3-month-old 5xFAD mice, whereas acute running seemed to induce a similar transcriptional stress state in wild-type animals as already known for 5xFAD mice.

Acitretin reverses early functional network degradation in a mouse model of familial Alzheimer's disease.

Aberrant activity of local functional networks underlies memory and cognition deficits in Alzheimer's disease (AD). Hyperactivity was observed in microcircuits of mice AD-models showing plaques, and also recently in early stage AD mutants prior to amyloid deposition. However, early functional effects of AD on cortical microcircuits remain unresolved. Using two-photon calcium imaging, we found altered temporal distributions (burstiness) in the spontaneous activity of layer II/III visual cortex neurons, in a mouse model of familial Alzheimer's disease (5xFAD), before plaque formation. Graph theory (GT) measures revealed a distinct network topology of 5xFAD microcircuits, as compared to healthy controls, suggesting degradation of parameters related to network robustness. After treatment with acitretin, we observed a re-balancing of those network measures in 5xFAD mice; particularly in the mean degree distribution, related to network development and resilience, and post-treatment values resembled those of age-matched controls. Further, behavioral deficits, and the increase of excitatory synapse numbers in layer II/III were reversed after treatment. GT is widely applied for whole-brain network analysis in human neuroimaging, we here demonstrate the translational value of GT as a multi-level tool, to probe networks at different levels in order to assess treatments, explore mechanisms, and contribute to early diagnosis.

Common miRNA Patterns of Alzheimer's Disease and Parkinson's Disease and Their Putative Impact on Commensal Gut Microbiota.

With the rise of Next-Generation-Sequencing (NGS) methods, Micro-RNAs (miRNAs) have achieved an important position in the research landscape and have been found to present valuable diagnostic tools in various diseases such as multiple sclerosis or lung cancer. There is also emerging evidence that miRNAs play an important role in the pathogenesis of neurodegenerative diseases such as Alzheimer's disease (AD) or Parkinson's disease (PD). Apparently, these diseases come along with changes in miRNA expression patterns which led to attempts from researchers to use these small RNA species from several body fluids for a better diagnosis and in order to observe disease progression. Additionally, it became evident that microbial commensals might play an important role for pathology development and were shown to have a significantly different composition in patients suffering from neurodegeneration compared with healthy controls. As it could recently be shown that secreted miRNAs are able to enter microbial organisms, it is conceivable that the host's miRNA might affect the gut microbial ecosystem. As such, miRNAs may inherit a central role in shaping the "diseased microbiome" and thereby mutually act on the characteristics of these neurodegenerative diseases. We have therefore (1) compiled a list of miRNAs known to be associated with AD and/or PD, (2) performed an in silico target screen for binding sites of these miRNA on human gut metagenome sequences and (3) evaluated the hit list for interesting matches potentially relevant to the etiology of AD and or PD. The examination of protein identifiers connected to bacterial secretion system, lipopolysaccharide biosynthesis and biofilm formation revealed an overlap of 37 bacterial proteins that were targeted by human miRNAs. The identified links of miRNAs to the biological processes of bacteria connected to AD and PD have yet to be validated via in vivo experiments. However, our results show a promising new approach for understanding aspects of these neurodegenerative diseases in light of the regulation of the microbiome.