@unpublished{15016, abstract = {The development, evolution, and function of the vertebrate central nervous system (CNS) can be best studied using diverse model organisms. Amphibians, with their unique phylogenetic position at the transition between aquatic and terrestrial lifestyles, are valuable for understanding the origin and evolution of the tetrapod brain and spinal cord. Their metamorphic developmental transitions and unique regenerative abilities also facilitate the discovery of mechanisms for neural circuit remodeling and replacement. The genetic toolkit for amphibians, however, remains limited, with only a few species having sequenced genomes and a small number of transgenic lines available. In mammals, recombinant adeno-associated viral vectors (AAVs) have become a powerful alternative to genome modification for visualizing and perturbing the nervous system. AAVs are DNA viruses that enable neuronal transduction in both developing and adult animals with low toxicity and spatial, temporal, and cell-type specificity. However, AAVs have never been shown to transduce amphibian cells efficiently. To bridge this gap, we established a simple, scalable, and robust strategy to screen AAV serotypes in three distantly-related amphibian species: the frogs Xenopus laevis and Pelophylax bedriagae, and the salamander Pleurodeles waltl, in both developing larval tadpoles and post-metamorphic animals. For each species, we successfully identified at least two AAV serotypes capable of infecting the CNS; however, no pan-amphibian serotype was identified, indicating rapid evolution of AAV tropism. In addition, we developed an AAV-based strategy that targets isochronic cohorts of developing neurons – a critical tool for parsing neural circuit assembly. Finally, to enable visualization and manipulation of neural circuits, we identified AAV variants for retrograde tracing of neuronal projections in adult animals. Our findings expand the toolkit for amphibians to include AAVs, establish a generalizable workflow for AAV screening in non-canonical research organisms, generate testable hypotheses for the evolution of AAV tropism, and lay the foundation for modern cross-species comparisons of vertebrate CNS development, function, and evolution. }, author = {Jaeger, Eliza C.B. and Vijatovic, David and Deryckere, Astrid and Zorin, Nikol and Nguyen, Akemi L. and Ivanian, Georgiy and Woych, Jamie and Arnold, Rebecca C and Ortega Gurrola, Alonso and Shvartsman, Arik and Barbieri, Francesca and Toma, Florina-Alexandra and Gorbsky, Gary J. and Horb, Marko E. and Cline, Hollis T. and Shay, Timothy F. and Kelley, Darcy B. and Yamaguchi, Ayako and Shein-Idelson, Mark and Tosches, Maria Antonietta and Sweeney, Lora Beatrice Jaeger}, booktitle = {bioRxiv}, title = {{Adeno-associated viral tools to trace neural development and connectivity across amphibians}}, doi = {10.1101/2024.02.15.580289}, year = {2024}, } @article{14443, abstract = {Importance Climate change, pollution, urbanization, socioeconomic inequality, and psychosocial effects of the COVID-19 pandemic have caused massive changes in environmental conditions that affect brain health during the life span, both on a population level as well as on the level of the individual. How these environmental factors influence the brain, behavior, and mental illness is not well known. Observations A research strategy enabling population neuroscience to contribute to identify brain mechanisms underlying environment-related mental illness by leveraging innovative enrichment tools for data federation, geospatial observation, climate and pollution measures, digital health, and novel data integration techniques is described. This strategy can inform innovative treatments that target causal cognitive and molecular mechanisms of mental illness related to the environment. An example is presented of the environMENTAL Project that is leveraging federated cohort data of over 1.5 million European citizens and patients enriched with deep phenotyping data from large-scale behavioral neuroimaging cohorts to identify brain mechanisms related to environmental adversity underlying symptoms of depression, anxiety, stress, and substance misuse. Conclusions and Relevance This research will lead to the development of objective biomarkers and evidence-based interventions that will significantly improve outcomes of environment-related mental illness.}, author = {Schumann, Gunter and Andreassen, Ole A. and Banaschewski, Tobias and Calhoun, Vince D. and Clinton, Nicholas and Desrivieres, Sylvane and Brandlistuen, Ragnhild Eek and Feng, Jianfeng and Hese, Soeren and Hitchen, Esther and Hoffmann, Per and Jia, Tianye and Jirsa, Viktor and Marquand, Andre F. and Nees, Frauke and Nöthen, Markus M. and Novarino, Gaia and Polemiti, Elli and Ralser, Markus and Rapp, Michael and Schepanski, Kerstin and Schikowski, Tamara and Slater, Mel and Sommer, Peter and Stahl, Bernd Carsten and Thompson, Paul M. and Twardziok, Sven and Van Der Meer, Dennis and Walter, Henrik and Westlye, Lars}, issn = {2168-6238}, journal = {JAMA Psychiatry}, number = {10}, pages = {1066--1074}, publisher = {American Medical Association}, title = {{Addressing global environmental challenges to mental health using population neuroscience: A review}}, doi = {10.1001/jamapsychiatry.2023.2996}, volume = {80}, year = {2023}, } @article{13168, abstract = {Urban-living individuals are exposed to many environmental factors that may combine and interact to influence mental health. While individual factors of an urban environment have been investigated in isolation, no attempt has been made to model how complex, real-life exposure to living in the city relates to brain and mental health, and how this is moderated by genetic factors. Using the data of 156,075 participants from the UK Biobank, we carried out sparse canonical correlation analyses to investigate the relationships between urban environments and psychiatric symptoms. We found an environmental profile of social deprivation, air pollution, street network and urban land-use density that was positively correlated with an affective symptom group (r = 0.22, Pperm < 0.001), mediated by brain volume differences consistent with reward processing, and moderated by genes enriched for stress response, including CRHR1, explaining 2.01% of the variance in brain volume differences. Protective factors such as greenness and generous destination accessibility were negatively correlated with an anxiety symptom group (r = 0.10, Pperm < 0.001), mediated by brain regions necessary for emotion regulation and moderated by EXD3, explaining 1.65% of the variance. The third urban environmental profile was correlated with an emotional instability symptom group (r = 0.03, Pperm < 0.001). Our findings suggest that different environmental profiles of urban living may influence specific psychiatric symptom groups through distinct neurobiological pathways.}, author = {Xu, Jiayuan and Liu, Nana and Polemiti, Elli and Garcia-Mondragon, Liliana and Tang, Jie and Liu, Xiaoxuan and Lett, Tristram and Yu, Le and Nöthen, Markus M. and Feng, Jianfeng and Yu, Chunshui and Marquand, Andre and Schumann, Gunter and Walter, Henrik and Heinz, Andreas and Ralser, Markus and Twardziok, Sven and Vaidya, Nilakshi and Serin, Emin and Jentsch, Marcel and Hitchen, Esther and Eils, Roland and Taron, Ulrike Helene and Schütz, Tatjana and Schepanski, Kerstin and Banks, Jamie and Banaschewski, Tobias and Jansone, Karina and Christmann, Nina and Meyer-Lindenberg, Andreas and Tost, Heike and Holz, Nathalie and Schwarz, Emanuel and Stringaris, Argyris and Neidhart, Maja and Nees, Frauke and Siehl, Sebastian and A. Andreassen, Ole and T. Westlye, Lars and Van Der Meer, Dennis and Fernandez, Sara and Kjelkenes, Rikka and Ask, Helga and Rapp, Michael and Tschorn, Mira and Böttger, Sarah Jane and Novarino, Gaia and Marr, Lena and Slater, Mel and Viapiana, Guillem Feixas and Orosa, Francisco Eiroa and Gallego, Jaime and Pastor, Alvaro and Forstner, Andreas and Hoffmann, Per and M. Nöthen, Markus and J. Forstner, Andreas and Claus, Isabelle and Miller, Abbi and Heilmann-Heimbach, Stefanie and Sommer, Peter and Boye, Mona and Wilbertz, Johannes and Schmitt, Karen and Jirsa, Viktor and Petkoski, Spase and Pitel, Séverine and Otten, Lisa and Athanasiadis, Anastasios Polykarpos and Pearmund, Charlie and Spanlang, Bernhard and Alvarez, Elena and Sanchez, Mavi and Giner, Arantxa and Hese, Sören and Renner, Paul and Jia, Tianye and Gong, Yanting and Xia, Yunman and Chang, Xiao and Calhoun, Vince and Liu, Jingyu and Thompson, Paul and Clinton, Nicholas and Desrivieres, Sylvane and H. Young, Allan and Stahl, Bernd and Ogoh, George}, issn = {1546-170X}, journal = {Nature Medicine}, pages = {1456--1467}, publisher = {Springer Nature}, title = {{Effects of urban living environments on mental health in adults}}, doi = {10.1038/s41591-023-02365-w}, volume = {29}, year = {2023}, } @article{14455, author = {Narzisi, Antonio and Halladay, Alycia and Masi, Gabriele and Novarino, Gaia and Lord, Catherine}, issn = {1664-0640}, journal = {Frontiers in Psychiatry}, publisher = {Frontiers}, title = {{Tempering expectations: Considerations on the current state of stem cells therapy for autism treatment}}, doi = {10.3389/fpsyt.2023.1287879}, volume = {14}, year = {2023}, } @article{13267, abstract = {Three-dimensional (3D) reconstruction of living brain tissue down to an individual synapse level would create opportunities for decoding the dynamics and structure–function relationships of the brain’s complex and dense information processing network; however, this has been hindered by insufficient 3D resolution, inadequate signal-to-noise ratio and prohibitive light burden in optical imaging, whereas electron microscopy is inherently static. Here we solved these challenges by developing an integrated optical/machine-learning technology, LIONESS (live information-optimized nanoscopy enabling saturated segmentation). This leverages optical modifications to stimulated emission depletion microscopy in comprehensively, extracellularly labeled tissue and previous information on sample structure via machine learning to simultaneously achieve isotropic super-resolution, high signal-to-noise ratio and compatibility with living tissue. This allows dense deep-learning-based instance segmentation and 3D reconstruction at a synapse level, incorporating molecular, activity and morphodynamic information. LIONESS opens up avenues for studying the dynamic functional (nano-)architecture of living brain tissue.}, author = {Velicky, Philipp and Miguel Villalba, Eder and Michalska, Julia M and Lyudchik, Julia and Wei, Donglai and Lin, Zudi and Watson, Jake and Troidl, Jakob and Beyer, Johanna and Ben Simon, Yoav and Sommer, Christoph M and Jahr, Wiebke and Cenameri, Alban and Broichhagen, Johannes and Grant, Seth G.N. and Jonas, Peter M and Novarino, Gaia and Pfister, Hanspeter and Bickel, Bernd and Danzl, Johann G}, issn = {1548-7105}, journal = {Nature Methods}, pages = {1256--1265}, publisher = {Springer Nature}, title = {{Dense 4D nanoscale reconstruction of living brain tissue}}, doi = {10.1038/s41592-023-01936-6}, volume = {20}, year = {2023}, }