Understanding the molecular diversity of synapses
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GluN2B-mediated regulation of silent synapses for receptor specification and addiction memory
Psychostimulants, including cocaine, elicit stereotyped, addictive behaviors. The reemergence of silent synapses containing only NMDA-type glutamate receptors is a critical mediator of addiction memory and seeking behaviors. Despite the predominant abundance of GluN2B-containing NMDA-type glutamate receptors in silent synapses, their operational mechanisms are not fully understood. Here, using conditional depletion/deletion of GluN2B in D1-expressing accumbal medium spiny neurons, we examined the synaptic and behavioral actions that silent synapses incur after repeated exposure to cocaine. GluN2B ablation reduces the proportion of silent synapses, but some of them can persist by substitution with GluN2C, which drives the aberrantly facilitated synaptic incorporation of calcium-impermeable AMPA-type glutamate receptors (AMPARs). The resulting precocious maturation of silent synapses impairs addiction memory but increases locomotor activity, both of which can be normalized by the blockade of calcium-impermeable AMPAR trafficking. Collectively, GluN2B supports the competence of cocaine-induced silent synapses to specify the subunit composition of AMPARs and thereby the expression of addiction memory and related behaviors.
Coding principles and mechanisms of serotonergic transmission modes
Serotonin-mediated intercellular communication has been implicated in myriad human behaviors and diseases, yet how serotonin communicates and how the communication is regulated remain unclear due to limitations of available monitoring tools. Here, we report a method multiplexing genetically encoded sensor-based imaging and fast-scan cyclic voltammetry, enabling simultaneous recordings of synaptic, perisynaptic, proximate and distal extrasynaptic serotonergic transmission. Employing this method alongside a genetically encoded sensor-based image analysis program (GESIAP), we discovered that heterogeneous firing patterns of serotonergic neurons create various transmission modes in the mouse raphe nucleus and amygdala, encoding information of firing pulse frequency, number, and synchrony using neurotransmitter quantity, releasing synapse count, and synaptic and/or volume transmission. During tonic and low-frequency phasic activities, serotonin is confined within synaptic clefts due to efficient retrieval by perisynaptic transporters, mediating synaptic transmission modes. Conversely, during high-frequency, especially synchronized phasic activities, or when transporter inhibition, serotonin may surpass transporter capacity, and escape synaptic clefts through 1‒3 outlet channels, leading to volume transmission modes. Our results elucidate a mechanism of how channeled synaptic enclosures, synaptic properties, and transporters collaborate to define the coding principles of activity pattern-dependent serotonergic transmission modes.
An integrative data-driven model simulating C. elegans brain, body and environment interactions
The behavior of an organism is influenced by the complex interplay between its brain, body and environment. Existing data-driven models focus on either the brain or the body–environment. Here we present BAAIWorm, an integrative data-driven model of Caenorhabditis elegans, which consists of two submodels: the brain model and the body–environment model. The brain model was built by multicompartment models with realistic morphology, connectome and neural population dynamics based on experimental data. Simultaneously, the body–environment model used a lifelike body and a three-dimensional physical environment. Through the closed-loop interaction between the two submodels, BAAIWorm reproduced the realistic zigzag movement toward attractors observed in C. elegans. Leveraging this model, we investigated the impact of neural system structure on both neural activities and behaviors. Consequently, BAAIWorm can enhance our understanding of how the brain controls the body to interact with its surrounding environment.
Baseline gut microbiome alpha diversity predicts chemotherapy-induced gastrointestinal symptoms in patients with breast cancer
Chemotherapy frequently causes debilitating gastrointestinal symptoms, which are inadequately managed by current treatments. Recent research indicates the gut microbiome plays a role in the pathogenesis of these symptoms. The current study aimed to identify pre-chemotherapy microbiome markers that predict gastrointestinal symptom severity after breast cancer chemotherapy. Fecal samples, blood, and gastrointestinal symptom scores were collected from 59 breast cancer patients before, during, and after chemotherapy. Lower pre-chemotherapy microbiome alpha diversity and abundance of specific microbes (e.g., Faecalibacterium) predicted greater chemotherapy-induced gastrointestinal symptoms. Notably, tumor and diet characteristics were associated with lower pre-chemotherapy alpha diversity. Lower baseline alpha diversity also predicted higher chemotherapy-induced microbiome disruption, which was positively associated with diarrhea symptoms. The results indicate certain cancer patients have lower microbiome diversity before chemotherapy, which is predictive of greater chemotherapy-induced gastrointestinal symptoms and a less resilient microbiome. These patients may be strong candidates for pre-chemotherapy microbiome-directed preventative interventions (e.g., diet change).
Modelling the alpha and beta diversity of copepods across tropical and subtropical Atlantic ecoregions
Copepods, the most abundant individuals of the mesozooplankton, play a pivotal role in marine food webs and carbon cycling. However, few studies have focused on their diversity and the environmental factors influencing it. The objective of the present study is to model the alpha and beta diversity of copepods across the tropical and subtropical ecoregions of Atlantic Ocean using both taxonomic and functional approaches. The study used a dataset of 226 copepod species collected by stratified plankton hauls (0–800 m depth) across the tropical and equatorial Atlantic, from oligotrophic waters close to the Brazilian coast to more productive waters close to the Mauritanian Upwelling. To perform the functional analysis, six traits related to the behaviour, growth, and reproduction of copepods were selected. Several alpha diversities were estimated using taxonomic metrics (SR, Δ+, and Λ+) and functional metrics (FDis, FEve, FDiv, FOri, FSpe), and modelized with GAM model across spatial and environmental gradients, and day/night. The overall and two components of β-diversity (turnover and nestedness) were shared between depth and stations. The surface layers of stations from oligotrophic, equatorial, and Cape Verde ecoregions displayed higher values of taxonomic α-diversity. More unpredictable were the facets of functional α-diversity, although they showed a tendency to be positive with depth during the daytime. The GAM analysis revealed spatial gradients as the key factors modelling the taxonomic α-diversity, whereas depth was the most relevant for functional α-diversity. The turnover component drove taxonomic β-diversity in depth and station, whereas the nestedness component acquired relevance for the functional β-diversity. The taxonomic structure of the copepod community varied spatially across depths and ecoregions, but this was not linked to functional changes of the same magnitude.
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