Biology subjects

Pool, A.-H.

Publications and source records attributed to Pool, A.-H..

3 recordsLinked to original sources

bioRxiv2025

A novel interoceptive subfornical organ to infralimbic cortex circuit relays airway inflammation effects on fear extinction

There is growing interest in the impact of internal body states on the brain and behavior. The detrimental effects of chronic lung inflammation on mental health are well recognized, however, underlying mechanisms are not known. Here, using a murine model of allergic asthma we report compromised fear extinction in mice with severe but not mild airway inflammation (AI); an effect abolished by anti-interleukin-17A (IL-17A) antibodies. Investigation of innate immune cells, microglia as-well-as transcriptomic signatures in the subfornical organ (SFO), a brain interoceptive node lacking a traditional blood-brain-barrier, revealed significant alterations in severe AI mice. IL-17 Receptor A (IL-17RA) was expressed in SFO microglia and upregulated in severe AI mice. Notably, ablation of microglial IL-17RA improved fear extinction in severe AI mice. Furthermore, we identified direct SFO projections to the infralimbic (IL) cortex, a key area regulating extinction. Importantly, chemogenetic inhibition of the SFO-IL circuit led to improved fear extinction in severe AI mice. Collectively, we report a unique body-to-brain interoceptive mechanism engaging the SFO and an SFO-to-IL circuit, through which airway inflammatory mediators compromise fear extinction. Beyond asthma, our findings are relevant to other pulmonary pathologies (e.g. bacterial pneumonia, ARDS, COVID-19) highlighting a risk for cortical dysfunction and fear pathologies such as PTSD.

neuroscience↗

bioRxiv2025

Unbiased Quantification of Persistent Postural and Motor Deficits Following Spinal Cord Injury in Mice

Spinal cord injury (SCI) causes multifaceted postural and motor impairments that are challenging to quantify. Conventional behavioral tests, such as the Basso mouse scale (BMS), rely on qualitative observations, which do not detect subtle yet significant functional deficits. To perform unbiased and quantitative evaluation of motor function and posture after SCI, we employed high-speed video tracking with machine learning-based whole body pose estimation and weight-bearing analyses using the Blackbox system in freely moving mice. We found enduring alterations in posture induced by SCI not captured by conventional metrics. Postural deficits included reduced hindpaw spacing with concomitant increased forepaw spacing, narrowed femur width, and altered hind paw angles, which remained evident beyond 42 days post-injury (dpi). Furthermore, sustained deficits in locomotor activity were identified as decreased distance traveled, decreased exploratory behavior, and disrupted fore-to-hindpaw speed ratio. Additionally, we analyzed behavioral motifs using Keypoint MoSeq software and found frequency changes in unique motor syllables correlating with forward acceleration and turning after SCI. Interestingly, while motor deficits persisted, sensory deficits, such as thermal and mechanical sensitivity, returned to baseline levels by 21 days after injury in C57Bl/6J mice, with no subsequent hypersensitivity. Lastly, we developed a web-based application to assist in visualization and analyses of Blackbox-based kinematic data. Altogether, our study identifies distinct postural and motor deficits pre- and post-SCI using accurate, unbiased, and quantitative behavioral assessments. By tracking the unique features of motor recovery trajectories, researchers can more accurately assess the effectiveness of SCI therapeutic strategies.

neuroscience↗

bioRxiv2022

Enhanced recovery of single-cell RNA-sequencing reads for missing gene expression data

Droplet-based 3 single-cell RNA-sequencing (scRNA-seq) methods have proved transformational in characterizing cellular diversity and generating valuable hypotheses throughout biology1,2. Here we outline a common problem with 3 scRNA-seq datasets where genes that have been documented to be expressed with other methods, are either completely missing or are dramatically under-represented thereby compromising the discovery of cell types, states, and genetic mechanisms. We show that this problem stems from three main sources of sequencing read loss: (1) reads mapping immediately 3 to known gene boundaries due to poor 3 UTR annotation; (2) intronic reads stemming from unannotated exons or pre-mRNA; (3) discarded reads due to gene overlaps3. Each of these issues impacts the detection of thousands of genes even in well-characterized mouse and human genomes rendering downstream analysis either partially or fully blind to their expression. We outline a simple three-step solution to recover the missing gene expression data that entails compiling a hybrid pre-mRNA reference to retrieve intronic reads4, resolving gene collision derived read loss through removal of readthrough and premature start transcripts, and redefining 3 gene boundaries to capture false intergenic reads. We demonstrate with mouse brain and human peripheral blood datasets that this approach dramatically increases the amount of sequencing data included in downstream analysis revealing 20 - 50% more genes per cell and incorporates 15-20% more sequencing reads than with standard solutions5. These improvements reveal previously missing biologically relevant cell types, states, and marker genes in the mouse brain and human blood profiling data. Finally, we provide scRNA-seq optimized transcriptomic references for human and mouse data as well as simple algorithmic implementation of these solutions that can be deployed to both thoroughly as well as poorly annotated genomes. Our results demonstrate that optimizing the sequencing read mapping step can significantly improve the analysis resolution as well as biological insight from scRNA-seq. Moreover, this approach warrants a fresh look at preceding analyses of this popular and scalable cellular profiling technology.

genomics↗