Tag: Hippocampus

Unveiling the brain mechanism behind memory consolidation in sleep

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Neuroscientists have established in recent decades the idea that some of each day’s experiences are converted by the brain into permanent memories during sleep the same night. Now, a new study proposes a mechanism that determines which memories are tagged as important enough to linger in the brain until sleep makes them permanent.

Led by researchers at NYU Grossman School of Medicine, the new study revolves around brain cells called neurons that “fire”—bring about swings in the balance of their positive and negative charges—to transmit electrical signals that encode memories. Large groups of neurons in a brain region called the hippocampus fire together in rhythmic cycles, creating sequences of signals within milliseconds of each other that can encode complex information.

Called “sharp wave-ripples,” these “shouts” to the rest of the brain represent the near-simultaneous firing of 15 percent of hippocampal neurons, and are named for the shape they take when their activity is captured by electrodes and recorded on a graph.

While past studies had linked ripples with memory formation during sleep, the new study, published online March 28 in the journal Science, found that daytime events followed immediately by 5 to 20 sharp wave-ripples are replayed more during sleep and so consolidated into permanent memories. Events followed by very few or no sharp wave-ripples failed to form lasting memories.

Our study finds that sharp wave-ripples are the physiological mechanism used by the brain to ‘decide’ what to keep and what to discard.”

György Buzsáki, MD, PhD, senior study author, the Biggs Professor of Neuroscience in the Department of Neuroscience and Physiology at NYU Langone Health

Walk and pause

The new study is based on a known pattern: humans and other mammals experience the world for a few moments, then pause, then experience a little more, then pause again. After we pay attention to something, say the study authors, brain computation often switches into an “idle” reassessment mode. Such momentary pauses occur throughout the day, but the longest idling periods occur during sleep.

Dr. Buzsáki and colleagues had previously established that no sharp wave-ripples occur as we actively explore sensory information or move, but only during the idle pauses before or after. The current study found that sharp wave-ripples represent the natural tagging mechanism during such pauses after waking experiences, with the tagged neuronal patterns reactivated during post-task sleep.

Importantly, sharp wave-ripples are known to be made up of the firing of hippocampal “place cells” in a specific order that encodes, for instance, every room we enter and every section of a maze entered by a mouse. For memories that are remembered, those same cells fire at high speed, as we sleep, “playing back the recorded event thousands of times per night,” as the study authors put it. The process strengthens the connections between the cells involved.

For the current study, successive maze runs by study mice were tracked via electrodes by populations of hippocampal cells that constantly changed over time, despite recording very similar experiences. This revealed for the first time the maze runs during which ripples occurred during waking pauses and then were replayed during sleep.

Sharp wave-ripples were typically recorded when a mouse paused to enjoy a sugary treat after each maze run. The consumption of the reward, say the authors, prepared the brain to switch from an exploratory to an idle pattern, so that sharp wave-ripples could occur.

Using dual-sided silicon probes, the research team was able to record up to 500 neurons simultaneously in the hippocampi of animals during maze runs. This in turn created a challenge, because data becomes exceedingly complex the more neurons are independently recorded. To gain an intuitive understanding of the data, visualize neuronal activity, and form hypotheses, the team successfully reduced the number of dimensions in the data, which is in some ways like converting a 3D into a flat one, without losing the data’s integrity.

“We worked to take the external world out of the equation, and looked at the mechanisms by which the mammalian brain innately and subconsciously tags some memories to become permanent,” said first author Wannan (Winnie) Yang, PhD, a graduate student in the Buzsáki Lab. “Why such a system evolved is still a mystery, but future research may reveal devices or therapies that can adjust sharp wave-ripples to improve memory, or even lessen recall of traumatic events.”

Along with Dr. Buzsáki and Dr. Yang, study authors from NYU Langone’s Neuroscience Institute were Roman Huszár and Thomas Hainmueller. Kirill Kiselev, of NYU’s Center for Neural Science, was also an author, as was Chen Sun of Mila, the Quebec Artificial Intelligence Institute, in Montréal. The work was supported by National Institutes of Health grants R01MH122391 and U19NS107616.

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Journal reference:

Yang, W., et al. (2024) Selection of experience for memory by hippocampal sharp wave ripples. Science. doi.org/10.1126/science.adk8261.

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March 29, 2024
Formation of memory assemblies through the DNA-sensing TLR9 pathway

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Animal husbandry

Eight-week-old male and female C57BL/6 N mice were obtained from Envigo. Tlr9^fl/fl (C57BL/6J-Tlr9^em1Ldm/J) mice with loxP sites flanking exon 1 of the Tlr9, Ifnar1^fl/fl (B6(Cg)-Ifnar1^tm1.1Ees/J) mice with loxP sites flanking exon 3 of the type-1 interferon α/β receptor gene, Rela^fl/fl (B6.129S1-Rela^tm1Ukl/J) mice with loxP sites flanking exon 1 of the Rela gene, and Sting1-knockout mice C57BL/6J-Sting1gt/J; Goldenticket (Tmem173gt) mice were obtained from Jackson Laboratory and bred in institutional facilities. All mice were eight weeks of age at the beginning of experiments, unless otherwise specified. All mice were group housed (12 h:12 h light:dark cycle with lights on at 07:00, temperature 20–22 °C, humidity 30–60%) with ad libitum access to food and water (mice were switched to single housing one week before experiments). All experimental groups were mixed sex, consisting of approximately equal numbers of males and females. All procedures were approved by Northwestern University’s Animal Care and Use Committee (protocols IS00002463 and IS00003359) and Albert Einstein’s Animal Care and Use Committee (protocols 00001289 and 00001268) in compliance with US National Institutes of Health standards, and at Aarhus University in compliance with the Danish National Animal Experiment Committee (protocol 2021-15-0201-00801).

Tissue collection

For all analyses, mice were euthanized by cervical dislocation, dorsal hippocampi immediately dissected and frozen in liquid nitrogen. Frozen tissue was stored at −80 °C until protein or RNA extractions were performed.

Bulk RNA-seq

Read quality was assessed using FastQC⁴⁶ (v0.10.1) to identify sequencing cycles with low average quality, adapter contamination, or repetitive sequences from PCR amplification. Alignment quality was analysed using SAMtools flagstat with default parameters. Data quality was visually inspected as described previously⁵⁵. Furthermore, we assessed whether samples were sequenced deep enough by analysing the average per base coverage and the saturation correlation for all samples using the MEDIPS R package⁵⁶. The saturation function splits each library in fractions of the initial number of reads (ten subsets of equal size) and plots the convergence. The correlation between biological replicates was evaluated using Pearson correlation (function MEDIPS.correlation). Only data passing all quality standards were used for further analyses. Data were aligned to the genome using gapped alignment as RNA transcripts are subject to splicing and reads might therefore span two distant exons. Reads were aligned to the whole Mus musculus mm10 genome using STAR aligner58 (2.3.0e_r291) with default options, generating mapping files (BAM format). Reads were aligned to mouse genome M. musculus mm10 and counted using FeaturesCount as described previously⁵⁵. Genes with significantly different fold change (false discovery rate-corrected P < 0.05) were classified as up-regulated or down-regulated.

Isolation of nuclei and FACS

Fresh dorsal hippocampal tissue was collected from mice 96 h after CFC. Nuclei were isolated following an established protocol⁵⁷. RNase inhibitor was added to the 6× homogenization buffer stable master mix at a final concentration of 1.2 U μl⁻¹. Tissue was homogenized using a Polytron homogenizer for 1.5 min. Samples were resuspended with the 50% iodixanol solution (50% iodixanol in 1× homogenization buffer) via gentle pipetting to make a final concentration of 25% iodixanol. Three millilitres of a 35% iodixanol solution (35% iodixanol in 1× homogenization containing 480 mM sucrose) was added to a new 15 ml Falcon tube. Three millilitres of a 29% iodixanol solution (29% iodixanol in 1× homogenization buffer containing 480 mM sucrose) was layered above the 35% iodixanol mixture. A 4 ml 25% iodixanol solution was layered on the 29% solution. In a swinging-bucket centrifuge, nuclei were centrifuged for 20 min at 3,000g. After centrifugation, the nuclei were present at the interface of the 29% and 35% iodixanol solutions. This band with the nuclei was collected in a 300 μl volume and transferred to a pre-chilled tube. Following isolation, nuclei were counted and resuspended in fluorescence-activated cell sorting (FACS) buffer (1% BSA, 1 mM EDTA, and 0.2 U μl⁻¹ RNase inhibitor in PBS) at 2 × 10⁶ nuclei per ml. A subset of nuclei was sorted by GFP expression on a high-speed cell sorter flow cytometer (Beckman Coulter MoFlowXDP cell sorter). See Supplementary Fig. 1 for the detailed gating strategy.

snRNA-seq

snRNA-seq libraries were generated from up to 10,000 individual cells captured in an oil emulsion on a Chromium Controller (10x Genomics). cDNA was generated in the individual cell–gel bead emulsion micro-reactors while adding barcodes at the cellular and molecular level using the Chromium Next GEM Single Cell 3′ Kit v3.1(10x Genomics kit 1000268). The barcoded cDNAs from the individual cells were combined for the remaining library process. The unique molecular barcodes (UMIs) prevented amplification artefacts from skewing the analysis. The libraries were analysed on a Fragment Analyzer 5200 (Agilent Technologies) to ensure a normal size distribution with an average size of 450 bp and sequenced on an llumina Sequencer with the following read lengths: 28 bp for read 1, 10 bp for i7 index, 10 bp for i5 index and 90 bp for read 2 at a read depth of 20,000 reads per cell. Five libraries were generated and analysed (Supplementary Table 6).

snRNA-seq analysis

The sequencing files in FASTQ format of each sample were aligned against mouse mm10 genome v4.0.0 and converted to gene count matrices using Cellranger software v7.0.1. Quality control and downstream analysis was performed using Seurat R package v4.3.0. Doublets were detected and removed using R package scDblFinder v1.13.13. Ambient RNA was detected and corrected using R package SoupX v1.6.2. Cells with less than 1000 detected genes, more than 4,000 detected genes, or more than 5% mitochondrial genes were excluded from further analysis. Samples were normalized using Seurat SCTransform function and then integrated and clustered using Seurat functions. Differential gene expression analysis was performed to compare cells from different samples in each cluster. Genes with more than 1.5-fold change and an adjusted P value of less than 0.01 were defined as significant. Co-expression of two genes was assessed by comparing the cosine similarity of the target two genes and random chosen pair of genes. Gene set enrichment analysis was run on each cluster comparing samples with different condition against the Gene Ontology database using R package fgsea v1.20.0. Pathways with less than 0.05 adjusted P value are considered significantly enriched. The pathway analysis was performed using the Reactome Patway database (version 86)⁵⁸. Well-established markers for brain and blood-derived cell populations were used to define individual clusters^59,60.

Gene ontology and interaction network analyses of bulk RNA-seq data

Functional protein association network analysis was performed using Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database (version 11.0)⁶¹ for up-regulated genes. The network was processed applying kmeans clustering, setting cluster number to 4. Inflammatory response-associated genes were identified using Mouse Genome Database (MGI) Batch Query Genome Analysis Tool (v6.23). Selection criteria was classification within the GO term ‘Inflammatory response’ (ID: GO:0006954) using IMP (Inferred from mutant phenotype), IEA (Inferred from electronic annotation) and IBA (Inferred from biological aspect of ancestor) evidence codes. Functional classification of up-regulated genes was performed using PANTHER Classification System engine, version 17.0. Genes were analysed through PANTHER Overrepresentation (test type: Fisher; correction: FDR; functional classification: PANTHER GO-Slim Biological Process, Mus musculus – REFLIST (21997)).

RT² array

Differential expression of inflammatory response-associated genes between recent and remote memory was analysed using The Mouse Innate and Adaptive Immune Responses RT² Profiler PCR Array (Qiagen, 330231 PAMM-052ZA), according to manufacturer’s instructions. Total RNA was extracted from dorsal hippocampi using PureLink RNA Mini Kit (ThermoFisher, 12183018 A). Tissue was dissected either 96 h (n = 5, pooled) or 21 days (n = 5, pooled) after CFC, resuspended in lysis buffer, flash frozen in liquid nitrogen and stored at −80 °C. RNA was extracted following manufacturer’s instructions. cDNA was synthetized using the RT² First Strand Kit (Qiagen, 330401). For each experimental group, 500 µg of total RNA was used for the cDNA synthesis. Genomic DNA elimination reaction was prepared by mixing RNA with 2 µl of buffer GE in 10 µl total reaction volume. Real-time PCR reaction was performed using RT² SYBR Green qPCR Mastermix in duplicates for each sample (recent, remote). The PCR reaction was performed in an Applied Biosystems 7300 Real-Time PCR System with the following cycling conditions: 95 °C, 10 min; then 40 cycles of 95 °C, 15 s; 60 °C, 1 min. ΔC_t values for each gene were calculated by subtracting the average C_t value of 6 housekeeping genes from the C_t value of each target gene. Differential expression between recent and remote memory was calculated from ΔΔC_t value.

Quantitative PCR analysis

Total RNA was extracted using RNeasy Plus Mini Kit (Qiagen, 74136). Reverse transcription was performed on 100 ng of total RNA PrimeScript RT Reagent Kit (Takara RR037A). Real-time PCR analysis was performed on a QuantStudio 6 Flex instrument (ThermoFisher) using SYBR green detection system (Applied Biosystems, 4367659) and primers specific for Tlr9 (330001/PPM04221A-200), Tlr7 (330001/PPM04208A-200) and Tlr13 (330001/PPM41490A-200) (all from Qiagen). Housekeeping genes Gapdh and Hprt were used for normalization. ΔC_t for target genes was calculated using average C_t of the two housekeeping genes. mRNA amount for each experimental group was expressed relative to naive group and calculated as \({2}^{\Delta {C}_{{\rm{t}}}-\Delta {C}_{{{\rm{t}}}_{naive}}}\).

Cytosolic DNA extraction and analysis

Cytosolic DNA extraction was performed as previously described⁶². DNA was extracted using Mitochondria/Cytosol Fractionation Kit (Abcam, ab65320) from fresh tissue (dorsal hippocampus) and cleared extracts were treated with 1 mg ml⁻¹ proteinase K for 1 h at 55 °C, extracted with phenol:chloroform, treated with RNase A (1 mg ml⁻¹) for 1.5 h at 37 °C, and sequentially extracted with phenol:chloroform and chloroform. Purified cytosolic DNA was tested for nuclear DNA contamination by performing a 40-cycle PCR reaction using primers for vGlut1 (also known as Slc17a7) (forward: GTGGAAGTCCTGGAAACTGC, reverse: ATGAGCGAGGAGAATGTGG). For cloning of dsDNA, samples were treated with DNA polymerase I, large (Klenow) fragment (1 U µg⁻¹ DNA; NEB), supplemented with 33 µM of each dNTP, for 15 min. DNA was precipitated with sodium acetate/ethanol as described above, and dissolved in water. DNA samples were treated with Taq polymerase (NEB) for 20 min, and immediately cloned into pCR4-TOPO vector (Invitrogen), according to manufacturer’s instructions. One Shot competent cells were transformed by adding 2 μl of the TOPO Cloning reaction into a vial of One Shot chemically competent Escherichia coli. Cells were incubated on ice for 30 min, heat-shocked for 30 s at 42 °C without shaking, and immediately transferred to ice. After 5 min, 250 μl of room temperature SOC medium was added, and tubes were placed horizontally in a shaker (200 rpm) at 37 °C for 1 h. Cells were pelleted at 6,000 rpm for 10 min, resuspended in 50 µl of SOC medium, and spread on a pre-warmed selective plate. Plates were incubated at 37 °C overnight. All colonies from each plate were picked and placed into individual wells of a 96-well plate containing 50 µl of PBS. The sequence of cloned DNA fragments was determined by direct colony sequencing (ACGT).

Primary cultures, treatment and live imaging

The hippocampi from post-natal day 0 (P1) C57BL/6 N male and female mice were isolated, and dissociated, as described previously⁶³. Cells were plated in a 14-mm-diameter glass dish (MatTek, P35G-1.5-14-C) coated with poly-d-lysine (Sigma-Aldrich) at a density of 50,000 cells per cm² and grown in neuronal medium (Neurobasal Medium containing 1 mM GlutaMax, and 2% B27, all from ThermoFisher). Neurons were cultured for 14 days in vitro before treatments. Cells were treated with 25 μM N-methyl-d-aspartate (NMDA) for 10 min in fresh neuronal medium, washed twice, and incubated for 1 h with PicoGreen (dsDNA dye, 1:20,000), CellMAsk (cell membrane dye, 1:1,000), and MitoTracker (mitochondria dye, 1:20,000) diluted in neuronal medium. Cells were imaged on Nikon W1 spinning disc confocal microscope (Center for Advanced Microscopy, Northwestern University), 1 frame per 10 s at 100× magnification.

Immunohistochemistry

Mice were anaesthetized with an intraperitoneal injection of 240 mg kg⁻¹ Avertin and transcardially perfused with ice-cold 4% paraformaldehyde in phosphate buffer (pH 7.4, 150 ml per mouse). Brains were removed and post-fixed for 24 h in the same fixative and then immersed for 24 h each in 20% and 30% sucrose in phosphate buffer. Brains were frozen and 50-μm sections were cut for use in free-floating immunohistochemistry¹⁷ with the primary and secondary antibodies listed in Supplementary Tables 7 and 8, respectively. In addition to manufacturers’ validation, all primary antibodies were validated by comparison to no primary control samples.

PNN imaging

PNNs were visualized using Wisteria floribunda lectin (WFA) staining, a widely used approach for PNN visualization⁴⁰. WFA staining was performed according to the manufacturer’s instructions. In brief, endogenous peroxidase was inactivated with hydrogen peroxide. Following streptavidin/biotin and Carbo-Free blocking, sections were incubated with biotinylated WFA (Vector Biolaboratories), Vectastain ABC system, and fluorescein, coumarin or rhodamine isothiocyanate (Akoya Biosciences). Sections were mounted using FluorSave (Millipore-Sigma).

Microscopy, image analysis and quantification

Low-magnification images (up to 60× magnification) were captured with a Leica microscope with a Leica DFC450 C digital camera whereas high-magnification images and z-stacks (60–100× magnification) were captured using a confocal laser-scanning microscope (Olympus Fluoview FV10i). All quantifications were performed with ImageJ. Clusters of γH2AX-positive neurons were first identified, and analyses were performed in the surrounding (~100 µm × 100 µm) area. Thus, the numbers are representative of regions of interest rather than average of the CA1 subfield. For time-course analyses, we counted γH2AX neurons in 180 neurons per mouse (3 consecutive slices of 60 neurons). With 6 mice per group, this amounted to 1,000 neurons per time point. In most of the other molecular targets we counted 60 neurons per mouse using a 60–100× objective. All images were converted to binary format, and for each cell showing γH2AX we determined the background and applied a threshold twice above the background signal. We thus obtained similar results across different antibodies and conditions. All analyses were performed with Fiji/ImageJ. The JACoP Plugin for object-based co-localization was used to determine co-localization by comparing the position of the centroids of the nuclei of the colour channels. Their respective coordinates were then used to define structures separated by distances equal to or below the optical resolution⁴⁵. Volume and 3D viewer Plugins were used for 3D reconstruction of z-stacks, whereas plot profile and surface plot functions were used for analyses of clusters at lower (40×) magnification. Coloc2 was used to determine correlation of expression levels of different fluorophore signals. The analyse particles, plot profile and measure functions were used to determine the number, size, distribution and distance between indicated signals.

Fluorescent multiplex v2 RNAscope

Naive mice (n = 4) or mice subjected to CFC (n = 4) were perfused 96 h later with ice-cold 0.1 M PBS and 4% paraformaldehyde in PBS and processed as described above. RNAscope was performed according to the manufacturer instructions. To visualize Hsp90b1 and Dcx mRNA and NeuN protein RNAscope Multiplex Fluorescent Reagent Kit v2 (ACD Biotechne, 323100) and RNA–Protein Co-Detection Ancillary kit (ACD Biotechne, 323180) were used. In brief, slides were dried at 60 °C in an oven for 30 min, dehydrated in ethanol, treated with hydrogen peroxide for 10 min at room temperature, washed in water and boiled in co-detection target retrieval reagent (around 98 °C) for 5 min. The sections were incubated with anti-Neun antibody (1:500, Sigma, ABN78), fixed with 10% Neutral Buffered Formalin (VWR, GEN0786-1056), protease plus, and rinsed with sterile water. The hybridization step was performed by incubating the sections with the following probes: Mm-Hsp90b1-C1 (ACD Biotechne, 556051), Mm-DCX-C2 (ACD Biotechne, 478671-C2), Mm-PPIB (positive control probe, ACD Biotechne, 320881) and dabB (negative control probe, ACD Biotechne, 320871) for 2 h at 40 °C and stored overnight in 5× saline sodium citrate. The hybridization was amplified with AMP 1 and AMP 2. All amplification and development were performed at 40 °C, and 2 × 2 min of washes in ACD wash buffer was performed after each step. For C1 probe TSA Vivid Fluorophore Kit 520 (Biotechne, 7523) was used, for C2 and C3, positive and negative probes TSA Vivid Fluorophore Kit 650 (7527) was used. Sections were incubated with goat anti-rabbit Alexa-568 secondary antibody (1:300, Invitrogen, A11036) and DAPI solution (ACD bio), and mounted with Prolong Gold Antifade Mountant (ThermoFisher Scientific, 33342). Images were acquired with an Andor BC43 spinning disk confocal microscope (Oxford Instruments) controlled by the Fusion software from Andor, using a 10× air 0.45 NA objective, a 60× oil immersion 1.42 NA objective, a CMOS camera (6.5 μm pixel; 2,048 × 2,000 pixels generating 16-bit, monochrome images) with no binning. Samples were illuminated with 4 fixed wavelengths of 405 nm, 488 nm, 561 nm and 638 nm. Dorsal hippocampus overview was obtained with 3 × 3 stitching (10% overlap) using the 10× objective and the region of interest (CA1 pyramidal layer, closest to the midline) was afterward imaged at higher magnification using the 60× objective. Image analysis was performed after thresholding using the analyse particle function in ImageJ using four slices per mouse. The number of particles was analysed per 60 neurons per slice (240 neurons per mouse).

Fear conditioning

CFC was performed in an automated system (TSE Systems) as previously described²⁹. In brief, mice were exposed for 3 min to a novel context, followed by a foot shock (2 s, 0.7 mA, constant current). TFC was performed by exposing the mice to for 3 min to a novel context, followed by a 30 s tone (75 dB SPL, 10 kHz, 200 ms pulse), a 15 s trace, and a foot shock (2 s, 0.7 mA, constant current)⁶³. DFC was performed as described for TFC, except that trace was omitted so that shock immediately followed the end of the tone. At indicated time points, mice were tested for memory retrieval by re-exposing them to the same context (context test), or to a tone presented over 30 s in a different context (tone test after TFC or DFC). Testing consisted of 3 min in the conditioning context, during which freezing was measured every 10 s. Freezing was expressed as a percentage of the total number of observations during which the mice were motionless. Activity was recorded automatically by an infrared beam system and expressed in cm s⁻¹. The individual experiments with wild-type mice were not performed on littermates, so we did not apply randomization procedures, but with all genetic lines bred in our facility, littermates were randomly assigned to different experimental groups to minimize litter effects. The behavioural tests were performed blindly, either by experimentalists who were unaware of the treatments because the solutions were coded or by experimenters unaware of the experimental design. The experimenter performing the tests was not aware of the numbering code.

Surgery and cannulation

Double-guided cannulas (Plastic One) were implanted in the dorsal hippocampus as described previously¹⁷. Mice were anesthetized with 1.2% tribromoethanol (vol/vol, Avertin) and implanted with bilateral 26-gauge cannulas using a stereotaxic apparatus (Kopf, model 1900). Stereotaxic coordinates for the dorsal hippocampus were 1.8 mm posterior, ±1.0 mm lateral and 2.0 mm ventral to bregma.

Pharmacological treatments

All oligonucleotides and drugs were injected into the dorsal hippocampus at a volume of 0.25 μl per side, at a rate of 0.15 μl min⁻¹ using microinfusion pumps (Model UMP3T-1 UltraMicroPump 3 with SMARTouch Controller). ODN2088 was injected at doses of 125 and 300 ng per mouse corresponding to 4 and 8 nmol, respectively. Based on pilot experiments, the cGAS and STING antagonists were injected at doses of 10 and 50 ng in 250 nl per mouse.

DNase I (Sigma-Aldrich D4513, lot SLCQ3662, diluted in water) was injected intraperitoneally with 50 U DNase I in 200 µl saline, 24 h and 12 h before and 1 h after CFC, or intrahippocampally with 50 U DNase I per mouse at volume of 0.5 μl per side, at a rate of 1 μl min⁻¹ 24 h before and 1 h after test. DNase I and S1 nuclease (Thermo Scientific, EN0321) treatment were injected into the dorsal hippocampus at dosage 5 U DNase I + 10U S1 in 20% glycerol/artificial cerebrospinal fluid, vehicle: 20% glycerol/artificial cerebrospinal fluid 4 h before the memory test. Treatment schedules and doses were designed based on published data⁶⁴ and including both high and low doses as well as pre-CFC and pre-test injections.

For depletion of microglia, Pexidartinib (PLX-3397, HY-16749 lot: 212013 MedChemExpress) was formulated into 5053 PicoLab Rodent Diet 20 at the concentration of 290 ppm (W.F. Fisher and Son). The mice were fed for four weeks before the test. LabDiet 5053 served as a control diet. At the end of experiments, all brains were collected for histological determination of cannula placements or immunohistochemistry.

Virus injections

All viruses (listed in Supplementary Table 9) were injected at a volume of 0.5 μl per side, 1.8 mm posterior, ±1.0 mm lateral and 2.0 mm ventral to bregma, at a rate of 0.15 μl min⁻¹. At the time of virus infusion, mice were eight weeks old. CFC and memory tests were performed from weeks 13 to 17. One day after the completion of behavioural testing, mice were intracardially perfused, and all brains were collected, and virus spread was confirmed by immunohistochemical analysis of GFP or mCherry.

Labelling CFC-activated CA1 neurons using robust activity marking

We labelled the CA1 neurons in the dorsal hippocampus activated during CFC using doxycycline-off (off-Dox) activity-dependent cell tagging with the Robust Activity RAM system³¹ coupled to the human Fos minimal promoter with four tandem repeats of an enhancer module (PRAM) as recently described in detail¹¹. In brief, we put two groups of wild-type mice on a doxycycline diet one day before injecting AAV2/9-PRAM:d2tTA-TRE:NLS-mKate2 and took them off the diet after 9 days, followed by CFC the day after. Mice were left undisturbed in our testing facility without doxycycline for additional two days. Following two days, mice were put back on the doxycycline diet and 96 h after CFC, one group was subjected to memory reactivation (context test) and euthanized 1 h later. An additional, non-reactivated group served as control. This later group was only used internally to ensure that there was no Fos response without memory reactivation.

Statistics and reproducibility

Statistical power to detect anticipated effect sizes was determined using power analysis (calculator at http://www.stat.ubc.ca/~rollin/stats/ssize/n2.html) conducted on representative samples of previous work and pilot experiments. For all proposed experiments, minimum power is set at 0.90 to detect an α = 0.05 (two-sided test) for a difference in means from 20% to 40%, with a 15% common standard deviation. To prevent litter effects, mice from the same litter were assigned to different experimental groups. Viruses were injected by experimenters aware of the construct but the mice were then assigned coded numbers by the laboratory technician. The code was available after quantification and before analyses. Statistical analyses were performed using GraphPad Prism. Mice with misplaced virus infusion or cannulas, and mice with less than 70% viral expression in the CA1 were excluded. One-way ANOVA followed by Tukey’s test was used for post hoc comparisons of three or more experimental groups (only when ANOVA was significant) whereas Student’s t-test was used for comparison of two experimental groups. Homogeneity of variance was confirmed with Levene’s test for equality of variances. On indicated data, we performed correlation analyses and report Pearson’s r coefficients. Significant changes of co-localization or activation (%) were determined using the Chi-square test. A priori determined post hoc analyses following Chi-square tests were performed using Bonferroni-corrected alpha levels as the original overall alpha level (α = 0.05) was divided by the number of tests being conducted. These adjusted alpha levels were used as the new significance threshold for each individual test. All comparisons were conducted using two-tailed tests and the P value for all cases was set to <0.05 for significant differences. Data are expressed as mean ± s.e.m. Statistically significant differences are indicated as *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001 and *****P < 0.00001. All cellular and molecular effects were shown in a minimum of six biological replicates (Figs. 1e and 2e and Extended Data Figs. 3f and 9). Two experimental replicates were performed for all time-course, Tlr9-KO, Rela-KO, Ifnar1-KO and WT–cre experiments (Figs. 1c,d, 2a–d and 5a,c and Extended Data Figs. 2–4, 11 and 12). All significant behavioural effects were replicated at least three times using wild-type, virus-specific and cell-specific control groups. All main gene expression effects were replicated with four different approaches (bulk RNA-seq, quantitative PCR arrays, quantitative PCR and snRNA-seq). Replicates produced similar results relative to initial or representative experiments.

Figures

Figures were created and edited using Adobe Illustrator CS6 (Adobe, v27.5, RRID: SCR_010279). Figs. 1a, 1b, 2a, 2e, 3a, 3c, 3d, 4a, and 5a, as well as Extended Data Figs. 4c, 4d, 5a, 5b, 5c, 5d and Supplementary Fig. 1 were created using BioRender.com.

Ethics declaration

All animal procedures used in this study were approved by the Northwestern University IACUC, Albert Einstein Medical College IACUC and Danish National Animal Experiment Committee, and complied with federal regulations set forth by the National Institutes of Health.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

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March 27, 2024
Novel treatment approach to halt epilepsy progression identified

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Only a very small percentage of neurons show changes after an epileptic seizure in mice, but these alterations can be permanent and trigger future seizures that can affect the whole brain and lead to impaired cognition, like memory and learning, according to new research from the Perelman School of Medicine at the University of Pennsylvania. The researchers identified an experimental treatment that, if provided within the first 48 hours after the first seizure, can prevent these long-term changes. The findings, which were published recently in The Journal of Clinical Investigation, suggest a promising target for developing treatments for epilepsy and preventing downstream effects of seizures.

Epilepsy is characterized by excessive activity of brain cells – neurons – which generate seizures. Research is increasingly showing that the development of epilepsy involves changes of synapses, which are structures that connect one neuron to another. While an estimated 3.4 million people in the United States live with some form of epilepsy, it is still unknown what causes it, and there is no cure. Further, half of individuals with epilepsy experience cognitive impairment, such as problems with memory, or with emotional regulation, but it remains unclear why or how epilepsy changes brain cells to cause this. What’s more, epilepsy is common in children with autism and individuals with dementia.

It is clear that there is some connection between an epileptic brain, impaired memory and trouble controlling emotions and how we act on those feelings, but we don’t understand the underlying mechanisms. Existing treatments for epilepsy only help manage seizures. This research gives us a promising starting point for developing therapies that prevent them from happening.”

Frances E. Jensen, MD, chair of the Department of Neurology, and senior author of the study

In this study, the researchers used a method that “tagged” neurons in the hippocampus-;an area commonly affected by epilepsy, and critical for memory-;of mice that were activated by epileptic activity. The researchers were able to monitor those activated neurons over time and observe how they responded to subsequent seizures. They found that only about twenty percent of neurons in the hippocampus were activated by seizures. Over time, the overactivity of these neurons diminished their ability to make connections with other neurons, called synapses, which is necessary for learning.

“The overactive neurons lose their ability to build the strong synapses necessary for learning, which may explain why some people with epilepsy have trouble with learning and with memory,” said Jensen. “If we can stop these neurons from undergoing changes after being activated by seizures, our hope is that we can also prevent not only the progression of epilepsy, but also avoid these cognitive deficits individuals experience long-term.”

To see if they could prevent neurons from becoming permanently epileptic, the researchers used an experimental glutamate receptor-blocker, called IEM-1460, which has been shown to reduce neuron hyperexcitability in models of mice with epilepsy. They found when they treated mice with this blocker in the first 48 hours after their very first seizure the neurons did not become permanently activated, and the subjects did not experience future seizures or the associated effects, like impaired cognition and trouble learning.

“Now that we have identified the subgroup of neurons that are impacted by epilepsy, we can investigate what makes these cells vulnerable to becoming epileptic, and whether that is something we can develop a therapy to stop,” said Jensen. “We are also eager to determine whether there is a glutamate receptor-blocker that works similarly to IEM-1460 in humans, which could be given to people after their first seizure, and prevent the lifelong struggles associated with epilepsy.”

Source:

University of Pennsylvania School of Medicine

Journal reference:

Xing, B., et al. (2024). Reversible synaptic adaptations in a subpopulation of murine hippocampal neurons following early-life seizures. The Journal of Clinical Investigation. doi.org/10.1172/JCI175167.

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March 23, 2024
Eating fatty food before surgery may affect memory-related cognitive function in older adults

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Eating fatty food in the days leading up to surgery may prompt a heightened inflammatory response in the brain that interferes for weeks with memory-related cognitive function in older adults – and, new research in animals suggests, even in young adults.

The study, building upon previous research from the same lab at The Ohio State University, also showed that taking a DHA omega-3 fatty acid supplement for a month before the unhealthy eating and surgical procedure prevented the effects on memory linked to both the high-fat diet and the surgery in aged and young adult rats.

Three days on a high-fat diet alone was detrimental to a specific type of fear-related memory in aged rats for as long as two weeks later – the same type of impairment seen in younger rats that ate fatty food and had a surgical procedure. The team has traced the brain inflammation behind these effects to a protein that activates the immune response.

“These data suggest that these multiple insults have a compounding effect,” said senior author Ruth Barrientos, an investigator in Ohio State’s Institute for Behavioral Medicine Research and associate professor of psychiatry and behavioral health and neuroscience in the College of Medicine.

We’ve shown that an unhealthy diet, even in the short term, especially when it’s consumed so close to a surgery, which in and of itself will cause an inflammatory response, can have damaging results. The high-fat diet alone might increase inflammation in the brain just a little bit, but then you have surgery that does the same thing, and when put together in a short amount of time you get a synergistic response that can set things in motion toward a longer-term memory issue.”

Ruth Barrientos, investigator in Ohio State’s Institute for Behavioral Medicine Research

The study was published recently in the journal Brain, Behavior, and Immunity.

Barrientos’ lab studies how everyday life events might trigger inflammation in the aging brain as the nervous system responds to signals from the immune system reacting to a threat. Decades of research has suggested that with aging comes long-term “priming” of the brain’s inflammatory profile and a loss of brain-cell reserve to bounce back.

Researchers fed young adult and aged rats a diet high in saturated fat for three days before a procedure resembling exploratory abdominal surgery – an event already known to cause about a week of cognitive issues in an older brain. Control rats ate regular food and were anesthetized, but had no surgery. (Barrientos’ lab has determined anesthesia alone does not cause memory problems in rats.)

In this study, as in previous research on aged rats treated with morphine after surgery, the team showed that an immune system receptor called TLR4 was the culprit behind the brain inflammation and related memory problems generated by both surgery and the high-fat diet, said first author Stephanie Muscat, assistant clinical professor of neuroscience at Ohio State.

“Blocking the TLR4 signaling pathway prior to the diet and surgery completely prevented that neuroimmune response and memory impairments, which confirmed this specific mechanism,” Muscat said. “And as we had found before in another model of an unhealthy diet, we showed that DHA supplementation did mitigate those inflammatory effects and prevent memory deficits after surgery.”

There were some surprising memory findings in the new work. Different behavioral tasks are used to test two types of memory: contextual memory based in the hippocampus and cued-fear memory based in the amygdala. In contextual memory tests, rats with normal memory freeze when they re-enter a room in which they had an unpleasant experience. Cued-fear memory is evident when rats freeze in a new environment when they hear a sound connected to that previous bad experience.

For aged rats in this study, as expected, the combination of a high-fat diet and surgery led to problems with both contextual and cued-fear memory that persisted for at least two weeks – a longer-lasting effect than the researchers had seen before.

The high-fat diet alone also impaired the aging rats’ cued-fear memory. And in young adult rats, the combination of the high-fat diet and surgery led to only cued-fear memory deficits, but no problems with memory governed by the hippocampus.

“What this is telling us in aged animals, along with the fact we’re seeing this same impairment in young animals after the high-fat diet and surgery, is that cued-fear memory is uniquely vulnerable to the effects of diet. And we don’t know why,” Barrientos said. “One of the things we’re hoping to understand in the future is the vulnerability of the amygdala to these unhealthy diet challenges.”

With increasing evidence suggesting that fatty and highly processed foods can trigger inflammation-related memory problems in brains of all ages, the consistent findings that DHA – one of two omega-3 fatty acids in fish and other seafood and available in supplement form – has a protective effect are compelling, Barrientos said.

“DHA was really effective at preventing these changes,” she said. “And that’s amazing – it really suggests that this could be a potential pretreatment, especially if people know they’re going to have surgery and their diet is unhealthy.”

This work was supported by grants from the National Institute on Aging and the National Institute of Neurological Disorders and Stroke.

Co-authors included Michael Butler, Menaz Bettes, James DeMarsh, Emmanuel Scaria and Nicholas Deems, all of Ohio State.

Source:

Journal reference:

Muscat, S. M., et al. (2024). Post-operative cognitive dysfunction is exacerbated by high-fat diet via TLR4 and prevented by dietary DHA supplementation. Brain, Behavior, and Immunity. doi.org/10.1016/j.bbi.2023.12.028.

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March 15, 2024
Diabetes drug dulaglutide may reduce symptoms of depression
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A recent Brain and Behavior study investigated the antidepressant effect of dulaglutide and the mechanism that underlies this effect.

Study: Dulaglutide treatment reverses depression-like behavior and hippocampal metabolomic homeostasis in mice exposed to chronic mild stress. Image Credit: luchschenF/Shutterstock.com

Background

Depression is a chronic mood disorder that is associated with low mood, insomnia, weight loss, a state of unhappiness, aversion to activity, fatigue, and low self-esteem. According to the World Health Organization, depression has become one of the major health burdens across the world.

This mental health condition is commonly treated with an antidepressant that takes around a month to alleviate the symptoms. However, several side effects are associated with the use of antidepressant drugs and could be toxic at high doses.

A combination of psychological, genetic, and neurological factors contributes to the manifestations of depression. Even though the exact etiology of this mental health issue is not fully understood, research has shown chronic stress to be an inducer of depression.

The hippocampus is a region of the brain that is associated with depression and modifies functionally and morphologically in response to stress. Animal model studies have shown that a decrease in neuronal and glial size, reduction in synaptic markers, loss of dendrites, and increase in apoptosis in the hippocampus leads to depression.

Many studies have uncovered the metabolic aspects of depression. For instance, diabetes and obesity are two common metabolic disorders that increase the risk of depression. Considering its high prevalence, novel therapies with high efficacy and fewer side effects are required to combat depression. The chronic mild stress (CMS) model has been recognized as a reliable rodent model to study depression.

Glucagon-like peptide-1 (GLP-1) and its receptor agonists are involved with anti-inflammatory effects and neuroprotective activities and can improve mental disorders, particularly depression and cognition. GLP-1 is a peptide hormone that stimulates the secretion of insulin and restricts the synthesis of glucagon in the pancreas in a glucose-dependent manner. Liraglutide is a GLP-1 analog that exhibited a positive effect in reducing anxiety and depression symptoms.

Dulaglutide is a novel long-acting GLP-1 receptor agonist that improves cognitive dysfunction and neuronal damage in rats with vascular dementia. Although many studies highlighted the efficacy of dulaglutide in preventing depression-like behavior triggered by chronic social defeat stress (CSDS), the underlying mechanism of this effect is not clearly understood.

About the study

The current study used a metabolomics strategy to evaluate the effect of dulaglutide in a CMS model. Furthermore, the underlying mechanism of this effect was also assessed. Adult male ICR mice, which is a strain of albino mice, were selected for this study. All test mice were around seven weeks old.

After one week of acclimatization, 60 mice were randomly assigned in four groups, namely, control (CON), the CMS and Vehicle group (CMS+Veh), the CMS and 0.3 mg/kg dulaglutide group (Low Dula), and the CMS and 0.6 mg/kg dulaglutide group (High Dula). Except for the CON group, all other groups were exposed to stressors.

To establish the CMS model of depression, selected mice were exposed to two or three different stressors for 28 days continuously. For stress induction, mice were deprived of water and food for 12 hours, kept in wet bedding for 24 hours, kept in a tilted cage for 24 hours, pintail for 1 minute, and cold water treatment for five minutes. The body weight of each test mouse was measured weekly, and behavioral tests, such as the tail suspension test (TST), open field test (OFT), and forced swimming test (FST), were performed.

Study findings

The mice subjected to CMS for four weeks exhibited depressive- and anxiety-like symptoms. An LC-MS/MS metabolomics study was performed to understand the potential pathophysiological mechanisms and investigate the efficacy of drugs to alleviate depression-like symptoms.

A distinct difference between the CON group, CMS+Veh group, and High Dula group was observed in accordance with the metabolic disorders induced by chronic stress, which was altered through dulaglutide treatment. Many potential biomarkers were identified that are associated with purine metabolism, arginine and proline metabolism, glycerophospholipid metabolism, glutamate metabolism, sphingolipid metabolism, and bile secretion.

Lipid metabolism pathways could be potential targets through which dulaglutide alleviates depression. Lysophosphatidylcholine (LPC), phosphatidylethanolamine (PE), lysophosphatidylethanolamine (LPE), phosphatidylinositol (PI), sphingolipids, and phosphatidylcholine (PC), are involved with the therapeutic effect of dulaglutide in alleviating depression. Consistent with previous studies findings, this study highlighted the association between lipid metabolism and the antidepressant effect of dulaglutide.

The current study indicated the downregulation of N-acetyl-L-aspartic acid (NAA) in the CMS model group. NAA, which is one of the most important metabolites of the vertebrate nervous system, was found in decreased levels in rats with chronic, unpredictable, mild stress. However, the current study indicated that dulaglutide therapy increased the levels of NAA through its upregulation in the hippocampus.

In the CMS model group, an upregulation in L-glutamic acid and L-arginine was observed. Dulaglutide treatment caused a decrease in arginine and proline, thereby indirectly exhibiting a neuroprotective effect.

Conclusions

The current study highlighted the antidepressant effects of dulaglutide using the CMS depression model. Notably, the potential metabolisms that underlie the antidepressant effect of dulaglutide have been elucidated in this study.
Journal reference:

Jin, M., Zhang, S., Huang, B., Li, L., Liang, H., Ni, A., Han, L., Liang, P., Liu, J., Shi, H. and Lv, P. (2024) Brain and Behavior, 14(3). doi: 10.1002/brb3.3448. https://onlinelibrary.wiley.com/doi/10.1002/brb3.3448?utm_medium=email
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March 8, 2024
UC Riverside professor receives NIH grant for neurodevelopmental disorder study

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Iryna Ethell, a professor of biomedical sciences in the School of Medicine at the University of California, Riverside, has been awarded a five-year grant of $2.4 million from the National Institutes of Health to study mechanisms of hyperexcitability and seizures in neurodevelopmental disorders such as such as attention-deficit/hyperactivity disorder and autism.

In this project we will address critical gaps in our knowledge, such as what role do astrocytes play in inhibitory synapse development in the hippocampus. We expect our work will lead to the development of novel therapeutic targets to treat neurodevelopmental disorders, including autism spectrum disorder, schizophrenia, and epilepsy.”

Iryna Ethell, professor of biomedical sciences, School of Medicine, University of California, Riverside

Astrocytes are star-shaped cells in the brain that are actively involved in brain function. They regulate synaptic connections between neurons. Each neuron in the brain receives numerous excitatory and inhibitory synaptic inputs. The balance between excitation and inhibition in neuronal circuits can play a role in causing many neurological disorders.

Ethell’s lab has studied a protein called ephrin-B1, which spans the membrane surrounding the cell and plays a role in maintaining the nervous system. Preliminary findings from her lab show that loss of astrocytic ephrin-B1 increases susceptibility to seizures and reduces sociability in mice.

EphB receptor signaling is a cellular pathway that regulates many developmental processes and is necessary for distributing and organizing synapses. Ethell explained that ephrin-B/EphB receptor signaling in the brain controls the development of inhibitory networks, that control brain excitability in a timely and special manner to ensure orderly brain functions and preventing seizures.

“If you compare the brain to driving a car, your excitatory network is a gas pedal that initiates the brain responses, but inhibitory networks are the brakes to ensure it does not crash,” Ethell said.

The research will use mouse models as well as state-of-art analysis and imaging approaches.

“We think this project will further our understanding of the mechanisms which lead to neurodevelopmental disorders and will allow us to discover novel interventions for treating these disorders by fixing abnormal inhibitory networks,” Ethell said.

Source:

University of California – Riverside

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March 1, 2024
How cell types and location influence Parkinson’s disease

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In a recent study published in Cell Reports, researchers conducted a single-cell spatial transcriptome analysis on murine brain expression in age and disease using a Parkinson’s disease (PD) transgenic model, focusing on dopaminergic neurons (DA) spanning 29 cell types.

Study: Single-cell spatial transcriptomic and translatomic profiling of dopaminergic neurons in health, aging, and disease. Image Credit: solarseven/Shutterstock.com

Background

The spatially structured brain contains various cells, each with a distinct purpose. PD is a neurodegenerative condition characterized by DA loss and alpha-synuclein buildup due to overexpression via locus multiplication.

Single-cell ribonucleic acid sequencing (RNS-seq) has improved the knowledge of cell-based expression in organs such as the brain, but current methods fail to attain high-throughput resolution. Fluorescent in situ hybridization (FISH) technologies provide higher sensitivity at an individual level.

About the study

In the present study, researchers performed single-cell spatial transcriptomic and translatomic profiling of DA to find markers for healthy and aged cells.

The researchers crossed Rosa26fsTRAP::DATIREScre (DAT-TRAP) mice with SNCA-OVX mice to enable DA messenger RNA (mRNA) capture in a PD model.

The mice were aged to 18 months to assess the influence of human ⍺-synuclein overexpression and aging on dopaminergic neuron genetic expression and study the effect of healthy and Parkinsonian aging.

The researchers created a single-cell-level spatial transcriptomic map of gene expression in the adult mouse brain and a high-fidelity translatome-level profile of DA neuron expression.

They analyzed stereo-seq arrays with special transcript maps. They converted the transcript expression maps to segmented individual cells, identifying 29 types of cells, including astrocytes and inhibitory cortical neurons, in 18 brain slices.

The team filtered the segmented cells by transcriptome size and complexity and analyzed spatially distinct cortex, hippocampus, and thalamus populations. They also examined the ventral midbrain and striatum to enrich transcripts confined to the cell body and putative axon.

They used data from gene enrichment and genome-wide association studies (GWAS) to identify potential disease-causing genes.

They evaluated each cell’s location and compared DA neuronal gene expression in various cells.

The researchers examined enhanced green fluorescent protein (eGFP)-tagged ribosomes in DAT-expressing cells and confirmed eGFP colocalization with tyrosine hydroxylase (TH), a DA neuronal marker.

They split cells from stereo-seq brain slices, filtering them based on detected genes, and performed Uniform Manifold Approximation and Projection (UMAP) analysis.

They also performed short- and long-read RNA sequencing of the translating mRNA collected by TRAP and used stereo-sequencing and TRAP data to rank prospective genes for inquiry into sporadic PD.

The researchers demonstrated specific enrichment of DA marker genes and depletion of marker genes of other neighboring cell types in DAT-TRAP mRNA.

They confirmed specific calcium-sensing receptor (CASR) protein expression in mouse ventral midbrain neurons and investigated CASR expression in human-induced pluripotent stem cell-derived DA neurons. They also examined age-related gene variations in cells revealed by stereo-seq.

Results

The team studied PD in young and aged brains to identify genes having spatially varying expression in dopaminergic neurons of the ventral tegmental area (VTA) and substantia nigra (SN) and particular markers such as copine-7 (Cpne7) and Solute carrier family 10 member 4 (Slc10a4) genes.

They also detected splice variants unique to DA. They demonstrated ways of using TRAP and stereo-sequencing expression specificity measurements to identify potentially relevant genes from GWAS areas, indicating that CASR regulates intracellular DA neuronal calcium.

The findings demonstrated substantia nigra-specific DA neuronal loss and increased microglial activation with age. They highlighted aging- and disease-associated genetic alterations in various cells, including dopaminergic neurons, across many PD-related pathways.

Stereo-seq detected expression alterations caused by aging and illness across different cell types, loss of nigral DA neurons, and the neuroinflammatory expansion of microglia.

Pathway enrichment research revealed that various biological processes were altered, including axon ensheathment, synaptic transmission modulation, intracellular calcium ion homeostasis, and catecholamine secretion control.

The team extracted 355,307 transcriptomes of high quality with spatial coordinate details from 18 murine brains, identifying a total of 14,494 genes.

They observed synaptosomal-associated protein, 25kDa (Snap25) expression, and structured localization in places like the thalamus or hippocampus differentiated neurons from glia.

They also examined neuronal cells in the CA1 region, CA3 region, subiculum, and dentate gyrus in the hippocampus region or gamma-aminobutyric acid (GABA)-releasing nuclei in the midbrain.

Marker expression enabled oligodendrocyte, astrocyte, microglia, and erythrocyte identification. In DAT-TRAP samples, classical markers of dopaminergic neurons showed significant enrichment, whereas those of other cell types decreased in the ventral midbrain.

Conclusion

Overall, the study identified 29 unique brain cell types by examining variations in spatial gene expression linked to aging and illness. The stereo-seq data indicated differences in transcript use across more than a thousand genes.

There were 817 occurrences of alternative splicing, suggesting that more genes were being translated than gene-level count data showed. The study also discovered an age-dependent drop in SN DA neuron cell number, which supports earlier findings.

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February 27, 2024
Maternal happiness in pregnancy boosts child brain development, study finds
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A new study in the journal Nature Mental Health explores how a mother’s positive state of mind during pregnancy affects the structure and function of the developing fetal brain by measuring these parameters by 7.5 years of age.

Study: Maternal positive mental health during pregnancy impacts the hippocampus and functional brain networks in children. Image Credit: Dean Drobot / Shutterstock.com

How does the maternal emotional state affect fetal development?

During pregnancy, which is a time of significant physical, mental, and social change, anxiety, depression, and other stress-related mental health disorders are frequently reported. These mental health issues have been associated with a durable and adverse effect on fetal brain development.

For example, previous research has shown that these mental disorders can lead to changes in the growth rate of the fetal hippocampus and a lower density of gray matter in the prefrontal and medial temporal lobes in early childhood. These children may also exhibit altered structure and function of emotion-regulating cortico-limbic networks, which are important for stress management.

At certain stages, these changes appear to be more significant in girls than boys. Notably, it is not necessary that the mother be clinically anxious or depressed for these alterations to manifest.

As a key component of mental health, positive maternal emotions like happiness can affect multiple outcomes, including maternal-infant bonding, parenting approaches, and child development. Furthermore, maternal happiness during pregnancy also impacts the long-term health of both the mother and child; however, it remains unclear how positive maternal emotions affect prenatal development.

About the study

The current study used data from the Growing Up in Singapore Towards Health Outcomes (GUSTO) cohort. Both structural and functional magnetic resonance imaging (MRI) were performed on children to explore the association of maternal happiness during pregnancy with brain development.

The researchers developed their own tool to measure positive maternal mental health during pregnancy. This was based on a mental health questionnaire given to pregnant women at 26-28 weeks.

What did the study show?

At 7.5 years of age, children are experiencing a vital phase of development during which the brain shifts towards different patterns of activity and cognitive processes develop in new ways. As a result, this period was chosen as the focus of the study.

Brain areas involved in perceiving and regulating emotions include the hippocampus and amygdala, as well as various functional networks like the visual networks, default mode network (DMN), and functional network. These regions of the brain have also been directly correlated with how the mother cares for the child.

A composite measure from multiple mental health scales was used for assessing positive maternal emotions during pregnancy. Other potential contributing factors such as socioeconomic status, stress levels, family and friend relationships, and death of close relatives in the two years before and after pregnancy were also recorded to determine a socio-environmental adversity factor. Maternal parenting stress was also assessed when the child was six years of age.

Interestingly, girls born to mothers who reported feeling happy during pregnancy had larger hippocampus volumes, whereas both boys and girls born to happy mothers exhibited altered functional connectivity of multiple networks.

When categorized by task-negative and task-positive networks, reduced connectivity between task-negative networks was observed among girls born to mothers with increased positive emotions during pregnancy. Conversely, increased connectivity between task-positive networks was associated with greater maternal happiness during pregnancy.

Since these findings were absent when explored in relation to depression or anxiety in the mother during pregnancy, the observed changes in functional connectivity may occur specifically with greater maternal positive emotion in pregnancy. This may indicate that maternal happiness transmits to the developing child’s brain through neural changes.

What are the implications?

The study findings suggest that feeling happy during pregnancy not only reduces the risk of psychiatric illness in the mother but also potentially acts as a protective factor for fetal brain development.

Previous studies have shown that anxious and stressed mothers are more likely to have children with hippocampal changes, which may affect the developing brain and lead to impaired stress responses in the future. By encouraging mothers to have positive emotions during pregnancy, hippocampal development in the offspring may be promoted, with better structure and functional networks during the time when children typically begin to attend school.

Importantly, better hippocampal development is associated with greater childhood resilience, thus serving as an early marker for psychological vulnerability and greater potential for behavioral and emotional problems when encountering stressful circumstances. However, the period of fetal development at which maternal positive emotions occur may modify the impact.

Future studies are needed to establish and extend these findings, especially to understand the neural basis of prenatal-maternal interactions during psychoneurological development. These studies could support the development of preventive strategies to help mothers feel happy during pregnancy and ultimately promote the mental health of their children.
Journal reference:

Qiu, A., Shen, C., Lopez-Vicente, M., et al. (2024). Maternal positive mental health during pregnancy impacts the hippocampus and functional brain networks in children. Nature Mental Health. doi:10.1038/s44220-024-00202-8.
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February 5, 2024
Maternal happiness during pregnancy linked to child’s brain development
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In a recent study published in the journal Nature Mental Health, researchers explored the relationship between maternal mental health and children’s brain development. Their results contribute to the medical understanding of the importance of the intrauterine environment and suggest that in addition to positive outcomes for the mother, emotional well-being during pregnancy can be an important protective factor for brain development in children.

Study: Maternal positive mental health during pregnancy impacts the hippocampus and functional brain networks in children. Image Credit: Prostock-studio / Shutterstock

Background

Research suggests that depression, anxiety, and stress during pregnancy can have enduring adverse effects on the child’s brain development. Maternal anxiety and depression have been found to affect gray matter density in the medial temporal and prefrontal cortex as well as hippocampal growth.

Maternal health factors can also modify the cortico-limbic system, which helps regulate stress responses and emotional states. These widespread effects have been observed to be more prominent in female children between birth and early childhood. These findings highlight the need to address prenatal mental health to promote brain development in children.

However, emotional well-being is not merely the absence of mental illness but also includes the experience of positive emotions and mental affect. While the effect of positive maternal emotions on parenting behavior, mother-infant bonding, long-term mental health, and child development has been studied, its impacts on brain development have not been explored.

About the study

The study followed a longitudinal prospective birth cohort design to investigate the relationship between maternal well-being and brain development in 7.5-year-old children using magnetic resonance imaging (MRI). This age was chosen because it is a key neurodevelopmental period when significant cognitive processes and brain changes occur.

Participants in the study included pregnant Asian (Malay, Indian, or Chinese) women in their first trimester who were recruited while they antenatal care at an ultrasound scan clinic in Singapore. For the MRI, children were included if they had a gestational age of more than 30 weeks and a birth weight of more than 2 kg to avoid the confounding effects of birth complications.

The authors hypothesized that positive emotions during pregnancy would be associated with significant differences in brain structures, such as the amygdala and hippocampus as well as functional networks, such as the default mode and visual networks. The mental health of the mothers was assessed using the Beck Depression Inventory, the Edinburgh Postnatal Depression Scale, and the State-Trait Anxiety Inventory.

Additionally, the survey included questions on socioeconomic status, relationships with friends and family, life stress, and other topics related to prenatal health and well-being. This information was used to construct an overall socio-environmental adversity factor and scores for four risk domains – personal, interpersonal, socioeconomic, and life stress.

Findings

The sample of participants who underwent the structural MRI included 381 children, of whom 369 also underwent the functional MRI procedure. After controlling for the overall socio-environmental adversity factor and the child’s age during the MRI, researchers found that more positive maternal emotions during the prenatal period were associated with a larger bilateral hippocampal volume in female children but not males. However, maternal positive emotions were not seen to be associated with cortical thickness or volumes of the thalamus, amygdala, lateral ventricles, or basal ganglia.

In terms of functional networks, more maternal positive emotions were associated with higher functional connectivity between the right frontoparietal and visual association networks, salience and thalamo-hippocampal networks, and posterior default mode and attention networks. Notably, these results were significant after controlling for child sex and age as well as postnatal parenting stress and other risk factors. These outcomes were not, however, associated with anxiety or depressive symptoms during pregnancy.

Conclusions

These findings indicate that there may be a neural basis through which positive emotions during pregnancy are transmitted from the mother to her offspring during the early development of the brain. Of the significantly associated outcomes, only the change in the bilateral hippocampi differed between male and female children. This research implies that ensuring mothers’ mental health could lead to sustained benefits for offspring in terms of neural development.

While the study has several strengths and offers novel insights, the authors acknowledged some limitations. While brain development was assessed through neuroimaging, data on maternal mood and well-being were collected through subjective reports and may, therefore, be subject to biases related to recall and social desirability. Self-reports of positive emotions may not be an adequate proxy for psychological well-being, a complex and multifaceted issue. The study participants were all Asian, leading to a lack of generalizability to other populations.

Future studies can build on these findings by including individuals of other races and factoring in positive emotions during other stages (such as during the postnatal period). This work adds to a growing body of literature showing the transgenerational nature of mental health outcomes and the importance of ensuring that mothers and children are not just healthy but happy, too.
Journal reference:

Maternal positive mental health during pregnancy impacts the hippocampus and functional brain networks in children. Qui, A., Shen, C., López-Vicente, M., Szekely, E., Chong, Y., White, T., Wazana, A. Nature Mental Health (2024). DOI: 10.1038/s44220-024-00202-8, https://www.nature.com/articles/s44220-024-00202-8
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January 31, 2024