Biology subjects

Cai, L.

Publications and source records attributed to Cai, L..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

The forkhead transcription factor FKH-7/FOXP acts in chemosensory neurons to regulate developmental decision-making

Autism is a complex neurodevelopmental disorder with many associated genetic factors, including the forkhead transcription factor FOXP1. Although FOXP1s neuronal role is well-studied, the specific molecular consequences of different FOXP1 pathogenic variants in physiologically-relevant contexts are unknown. Here we ascribe the first function to Caenorhabditis elegans FKH-7/FOXP, which acts in two chemosensory neuron classes to promote the larval decision to enter the alternative, developmentally-arrested dauer life stage. We demonstrate that human FOXP1 can functionally substitute for C. elegans FKH-7 in these neurons and that engineering analogous FOXP1 hypomorphic missense mutations in the endogenous fkh-7 locus also impairs developmental decision-making. In a fkh-7/FOXP1 missense variant, single-cell transcriptomics identifies downregulated expression of autism-associated kcnl-2/KCNN2 calcium-activated potassium channel in a serotonergic sensory neuron. Our findings establish a novel framework linking two evolutionarily-conserved autism-associated genes for deeper characterization of variant-specific molecular pathology at single neuron resolution in the context of a developmental decision-making paradigm.

neuroscience↗

bioRxiv2025

Recombination and retroprocessing in broomrapes reveal a universal roadmap for mitochondrial evolution in heterotrophic plants

The altered life history strategies of heterotrophic organisms often leave a profound genetic footprint on energy metabolism related functions. In parasitic plants, the reliance on host-derived nutrients and loss of photosynthesis in holoparasites have led to highly degraded to absent plastid genomes, but its impact on mitochondrial genome (mitogenome) evolution has remained controversial. By examining mitogenomes from 45 Orobanchaceae species including three independent transitions to holoparasitism and key evolutionary intermediates, we identified measurable and predictable genetic alterations in genomic shuffling, RNA editing, and intracellular (IGT) and horizontal gene transfer (HGT) en route to a nonphotosynthetic lifestyle. In-depth comparative analyses revealed DNA recombination and repair processes, especially RNA-mediated retroprocessing, as significant drivers for genome structure evolution. In particular, we identified a novel RNA-mediated IGT and HGT mechanism, which has not been demonstrated in cross-species and inter-organelle transfers. Based on this, we propose a generalized dosage effect mechanism to explain the biased transferability of plastid DNA to mitochondria across green plants, especially in heterotrophic lineages like parasites and mycoheterotrophs. Evolutionary rates scaled with these genomic changes, but the direction and strength of selection varied substantially among genes and clades, resulting in high contingency in mitochondrial genome evolution. Finally, we describe a universal roadmap for mitochondrial evolution in heterotrophic plants where increased recombination and repair activities, rather than relaxed selection alone, lead to differentiated genome structure compared to free-living species.

evolutionary biology↗

bioRxiv2025

Altered mitochondrial respiration is associated with loss of nuclear-encoded OXPHOS genes in parasitic broomrapes

Parasitic plants, characterized by their dependency on host organisms for nutrients, have displayed far-reaching alterations in physiology and genetics. While significant gene losses and relaxed selection have been documented in the nuclear and plastid genomes, how parasitism impacts the molecular evolution and function of mitochondria has remained controversial. One of the main culprits hindering our understanding in this area is the lack of knowledge on nuclear-encoded mitochondrial-targeted genes (N-mt), which encode most mitochondrial oxidative phosphorylation (OXPHOS) proteins. By conducting a comprehensive survey of N-mt genes across angiosperms, we demonstrated significant gene losses and horizontal transfers associated with relaxed selection unique to holoparasitic Orobanchaceae. These putative losses and transfers have the potential to affect mitochondrial function directly and cause mitonuclear incompatibility because of breakdown between co-evolved protein complexes from mitochondrial and nuclear genomes. Our physiological assessments using high-resolution respirometry revealed that despite genetic alterations, holoparasitic Orobanchaceae maintained robust OXPHOS function but relied more on the fully nuclear-encoded succinate dehydrogenase (complex II). Our results document the first example of significant and biased gene loss in nuclear-encoded mitochondrial OXPHOS genes in parasitic plants, expanding on previous studies focused on mitochondrial-encoded genes and elucidating the mechanisms underlying the preservation of OXPHOS function despite genomic reduction.

evolutionary biology↗

bioRxiv2024

A Spatiotemporal Atlas of Mouse Gastrulation and Early Organogenesis to Explore Axial Patterning and Project In Vitro Models onto In Vivo Space

At the onset of murine gastrulation, pluripotent epiblast cells migrate through the primitive streak, generating mesodermal and endodermal precursors, while the ectoderm arises from the remaining epiblast. Together, these germ layers establish the body plan, defining major body axes and initiating organogenesis. Although comprehensive single cell transcriptional atlases of dissociated mouse embryos across embryonic stages have provided valuable insights during gastrulation, the spatial context for cell differentiation and tissue patterning remain underexplored. In this study, we employed spatial transcriptomics to measure gene expression in mouse embryos at E6.5 and E7.5 and integrated these datasets with previously published E8.5 spatial transcriptomics1 and a scRNA-seq2 atlas spanning E6.5 to E9.5. This approach resulted in a comprehensive spatiotemporal atlas, comprising over 150,000 cells with 88 refined cell type annotations as well as genome-wide transcriptional imputation during mouse gastrulation and early organogenesis. The atlas facilitates exploration of gene expression dynamics along anterior-posterior and dorsal-ventral axes at cell type, tissue, and organismal scales, revealing insights into mesodermal fate decisions within the primitive streak. Moreover, we developed a bioinformatics pipeline to project additional scRNA-seq datasets into a spatiotemporal framework and demonstrate its utility by analysing cardiovascular models of gastrulation3. To maximise impact, the atlas is publicly accessible via a user-friendly web portal empowering the wider developmental and stem cell biology communities to explore mechanisms of early mouse development in a spatiotemporal context.

developmental biology↗

bioRxiv2024

STEP: Deciphering Spatial Atlas at Single-Cell Level with Whole-Transcriptome Coverage

Recent advances in spatial transcriptomics have revolutionized our understanding of tissue spatial architecture and biological processes. However, many of these technologies face significant challenges in achieving either single-cell resolution or comprehensive whole-transcriptome profiling, hindering their capacity to fully elucidate intercellular interactions and the tissue microenvironment. To address these limitations, we present STEP, a hybrid framework that synergistically integrates probabilistic models with deep learning techniques for spatial transcriptome analysis. Through innovations in model and algorithm design, STEP not only enhances sequencing-based spatial transcriptome data to single-cell resolution but accurately infers transcriptome-wide expression levels for image-based spatial transcriptomic. By leveraging the nuclear features extracted from histological images, STEP achieves precise predictions of cell type and gene expression and effectively diffuses the discriminative ability to serial sections for modeling solid tissue landscapes. The capability is particularly advantageous for analyzing cells with distinctive characteristics, such as cancer cells, enabling cross-sample inference. In addition, STEP simulates intercellular communication through a spatially resolved cell-cell interaction network, uncovering intrinsic biological processes. Overall, STEP equips researchers with a powerful tool for understanding biological functions and unveiling spatial gene expression patterns, paving the way for advancements in spatial transcriptomics research. Code is available at https://github.com/childishHU/STEP.

bioinformatics↗

bioRxiv2024

Machine learning engineered PoLixNano nanoparticles overcome delivery barriers for nebulized mRNA therapeutics

There continues to be a dearth of competent inhalable mRNA delivery although it holds great potential for addressing a wide variety of refractory diseases. The huge advances seen with parenteral-administered lipid nanoparticle (LNP) have not been translated into nebulized mRNA delivery due to the aggressive nebulization process and insurmountable barriers inherent to respiratory mucosa. Here, we show amphiphilic block copolymers revealed by machine learning (ML) can spontaneously form stabilized nanoparticles (PoLixNano) with the lipids components of LNP and simultaneously impart the PoLixNano with "shield" (shear force-resistant) and "spear" (pulmonary barriers-penetrating abilities) capabilities. We present a ML approach that leverages physicochemical properties and inhaled mRNA transfection profiles of a chemically diverse library of polymeric components to validate the integration of "shield" and "spear" properties as highly predictive indicators of transfection efficiency. This quantitative structure-mRNA transfection prediction (QSMTP) model identifies top-performing amphiphilic-copolymers from more than 10000 candidates and suggests their mucus-penetrating ability outweights the shear force-resistant property in contributing to efficient mRNA transfection. The optimized PoLixNano substantially outperforms the LNP counterpart and mediates up to 1114-times higher levels of mRNA transfection in animal models with negligible toxicities. The PoLixNano promotes overwhelming SARS-CoV-2 antigen-specific sIgA antibody secretion and expansion of TRM cells which collectively confers 100% protection in mice against lethal SARS-CoV-2 challenges and blocks the transmission of Omicron variant between hamsters. PoLixNano also displays versatile therapeutic potential in lung carcinoma and cystic fibrosis models. Our study provides new insights for designing delivery platforms of aerosol-inhaled mRNA therapeutics with clinical translation potential.

synthetic biology↗

bioRxiv2024

Spatial Transcriptomics Reveals the Temporal Architecture of the Seminiferous Epithelial Cycle and Precise Sertoli-Germ Synchronization

Spermatogenesis is characterized by the seminiferous epithelial cycle, a periodic pattern of germ cell differentiation with a wave-like progression along the length of seminiferous tubules. While key signaling and metabolic components of the cycle are known, the transcriptional changes across the cycle and the correlations between germ cell and somatic lineages remain undefined. Here, we use spatial transcriptomics via RNA SeqFISH+ to profile 2,638 genes in 216,090 cells in mouse testis and identify a periodic transcriptional pattern across tubules that precisely recapitulates the seminiferous epithelial cycle, enabling us to map cells to specific timepoints along the developmental cycle. Analyzing gene expression in somatic cells reveals that Sertoli cells exhibit a cyclic transcriptional profile closely synchronized with germ cell development while other somatic cells do not demonstrate such synchronization. Remarkably, in mouse testis with drug-induced ablation of germ cells, Sertoli cells independently maintain their cyclic transcriptional dynamics. By analyzing expression data, we identify an innate retinoic acid cycle, a network of transcription factors with cyclic activation, and signaling from germ cells that could interact with this network. Together, this work leverages spatial geometries for mapping the temporal dynamics and reveals a regulatory mechanism in spermatogenesis where Sertoli cells oscillate and coordinate with the cyclical progression of germ cell development. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/620681v2_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@10a78c7org.highwire.dtl.DTLVardef@7f5a95org.highwire.dtl.DTLVardef@113f6b6org.highwire.dtl.DTLVardef@1aa41f3_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2024

Well-resolved phylogeny reveals multiple origins of keel flowers during the diversification of papilionoid legumes

O_LIThe butterfly-shaped keel flower is a highly successful floral form in angiosperms. These flowers steer the mechanical interaction with bees and thus are hypothesized to accelerate pollinator-driven diversification. The exceptionally labile evolution of keel flowers in Papilionoideae (Fabaceae) provides a suitable system to test this hypothesis. C_LIO_LIUsing 1,456 low-copy nuclear loci, we confidently resolve the early divergence history of Papilionoideae. Constrained by this backbone phylogeny, we generated a time tree for 3,326 Fabales to evaluate the tempo and mode of diversification within a state-dependent evolutionary framework. C_LIO_LIThe first keel flowers emerged around 59.0 Ma in Papilionoideae, predating the earliest fossil by 3-4 million years. The Miocene diversification of Papilionoideae coincided with rapid evolution of keel flowers. At least six independent origins and thirty-two losses of keel flowers were identified in Papilionoideae, Cercidoideae, and Polygalaceae. However, the state-dependent diversification model was not favored. C_LIO_LILack of radiation associated with keel flowers suggests that diversification within Papilionoideae was not solely driven by pollinator-mediated selection, but instead an outcome of the synergistic effects of multiple innovations including nitrogen fixation and chemical defense as well as dispersal into subtropical and temperate regions. C_LI

evolutionary biology↗

bioRxiv2024

PointTree: Automatic and accurate reconstruction of long-range axonal projections of single-neuron

Single-neuron axonal projections reveal the route map of neuron output and provide a key cue for understanding how information flows across the brain. Reconstruction of single-neuron axonal projections requires intensive manual operations in tens of terabytes of brain imaging data, and is highly time-consuming and labor-intensive. The main issue lies in the need for precise reconstruction algorithms to avoid reconstruction errors, yet current methods struggle with densely distributed axons, focusing mainly on skeleton extraction. To overcome this, we introduce a point assignment-based method that uses cylindrical point sets to accurately represent axons and a minimal information flow tree model to suppress the snowball effect of reconstruction errors. Our method successfully reconstructs single-neuron axonal projections across hundreds of GBs (Gigabytes) images with an average of 80% F1-score, while current methods only provide less than 40% F1-score reconstructions from a few hundred MBs (Megabytes) images. This huge improvement is helpful for high-throughput mapping of neuron projections.

neuroscience↗

bioRxiv2024

The danger zone: the joint trap of incomplete lineage sorting and long-branch attraction in placing Rafflesiaceae

Two key factors have been implicated as major impediments to phylogenomic inference: incomplete lineage sorting (ILS)--especially in cases where clades are in the so-called anomaly zone--and erroneous gene tree estimation--commonly manifested by long- branch attraction in the Felsenstein zone. Rafflesiaceae (Malpighiales) is an iconic parasitic plant clade whose species occur west of Wallaces line in tropical Southeast Asia. This clade has been notoriously difficult to place phylogenetically and is nested within an explosive ancient radiation, rendering the Malpighiales one of the thorniest nodes across the angiosperm Tree of Life. The parasitic family Apodanthaceae has recently been positioned as sister to Rafflesiaceae, offering the hope to stabilize their placements. Here, using a dataset of 2,135 genes and complex species tree inference methods, the monophyletic Rafflesiaceae+Apodanthaceae clade is variously placed with Euphorbiaceae, Peraceae, Putranjivaceae, and Pandaceae. Such unstable placements appear to be the result of excessive levels of rate heterogeneity and ILS, which contribute to a phylogenetic "danger zone" where simulation suggests that current methods and genomic data will never provide a tidy phylogenetic resolution for species trees alike. Despite the topological uncertainty, however, our divergence time estimation identifies a mid-Cretaceous origin of stem group Rafflesiaceae and Apodanthaceae, not only making them the oldest parasitic plant lineage reported to date, but also suggests a likely Gondwana vicariance scenario to explain their disjunct distribution in South America, Africa, Australia, and Northern India.

evolutionary biology↗

bioRxiv2024

micronuclAI: Automated quantification of micronuclei for assessment of chromosomal instability.

Chromosomal instability (CIN) is a hallmark of cancer that drives metastasis, immune evasion and treatment resistance. CIN results from chromosome mis-segregation events during anaphase, as excessive chromatin is packaged in micronuclei (MN), that can be enumerated to quantify CIN. Despite recent advancements in automation through computer vision and machine learning, the assessment of CIN remains a predominantly manual and time-consuming task, thus hampering important work in the field. Here, we present micronuclAI, a novel pipeline for automated and reliable quantification of MN of varying size, morphology and location from DNA-only stained images. In micronucleAI, single-cell crops are extracted from high-resolution microscopy images with the help of segmentation masks, which are then used to train a convolutional neural network (CNN) to output the number of MN associated with each cell. The pipeline was evaluated against manual single-cell level counts by experts and against routinely used MN ratio within the complete image. The classifier was able to achieve a weighted F1 score of 0.937 on the test dataset and the complete pipeline can achieve close to human-level performance on various datasets derived from multiple human and murine cancer cell lines. The pipeline achieved a root-mean-square deviation (RMSE) value of 0.0041, an R2 of 0.87 and a Pearsons correlation of 0.938 on images obtained at 10X magnification. We tested the approach in otherwise isogenic cell lines in which we genetically dialed up or down CIN rates, and also on a publicly available image data set (obtained at 100X) and achieved an RMSE value of 0.0159, an R2 of 0.90, and a Pearsons correlation of 0.951. Given the increasing interest in developing therapies for CIN-driven cancers, this method provides an important, scalable, and rapid approach to quantifying CIN on routinely obtained images. We release a GUI-implementation for easy access and utilization of the pipeline.

systems biology↗

bioRxiv2024

Glycosaminoglycan-mediated lipoprotein uptake protects cancer cells from ferroptosis

Lipids are essential for tumours because of their structural, energetic, and signaling roles. While many cancer cells upregulate lipid synthesis, growing evidence suggests that tumours simultaneously intensify the uptake of circulating lipids carried by lipoproteins. Which mechanisms promote the uptake of extracellular lipids, and how this pool of lipids contributes to cancer progression, are poorly understood. Here, using functional genetic screens, we find that lipoprotein uptake confers resistance to lipid peroxidation and ferroptotic cell death. Lipoprotein supplementation robustly inhibits ferroptosis across numerous cancer types. Mechanistically, cancer cells take up lipoproteins through a pathway dependent on sulfated glycosaminoglycans (GAGs) linked to cell-surface proteoglycans. Tumour GAGs are a major determinant of the uptake of both low and high density lipoproteins. Impairment of glycosaminoglycan synthesis or acute degradation of surface GAGs decreases the uptake of lipoproteins, sensitizes cells to ferroptosis and reduces tumour growth in mice. We also find that human clear cell renal cell carcinomas, a distinctively lipid-rich tumour type, display elevated levels of lipoprotein-derived antioxidants and the GAG chondroitin sulfate than non-malignant human kidney. Altogether, our work identifies lipoprotein uptake as an essential anti-ferroptotic mechanism for cancer cells to overcome lipid oxidative stress in vivo, and reveals GAG biosynthesis as an unexpected mediator of this process.

cancer biology↗

bioRxiv2024

Functional reorganization of brain regions supporting non-adjacent dependency learning across the first half year of life

Pre-babbling infants can track nonadjacent dependencies (NADs) in the auditory domain. While this forms a crucial prerequisite for language acquisition, the neurodevelopmental origins of this ability remain unknown. We applied functional near- infrared spectroscopy in neonates and 6-7-month-old infants to investigate the neural substrate supporting NAD learning using tone sequences in an artificial grammar learning paradigm. Detection of NADs was indicated by left prefrontal activation in neonates while by left supramarginal gyrus (SMG), superior temporal gyrus (STG), and inferior frontal gyrus activation in 6-7-month-olds. Functional connectivity analyses further indicated that the neonate activation pattern during the test phase benefited from a brain network consisting of prefrontal regions, left SMG and STG during the rest and learning phases. These findings suggest a left-hemispheric learning-related functional brain network may emerge at birth and be strengthened by complex auditory input across the first half year of life, providing a neural basis for language acquisition.

neuroscience↗

bioRxiv2024

An EEG Signature of MCH Neuron Activities Predicts Cocaine Seeking

BackgroundIdentifying biomarkers that predict substance use disorder (SUD) propensity may better strategize anti-addiction treatment. The melanin-concentrating hormone (MCH) neurons in the lateral hypothalamus (LH) critically mediates interactions between sleep and substance use; however, their activities are largely obscured in surface electroencephalogram (EEG) measures, hindering the development of biomarkers. MethodsSurface EEG signals and real-time Ca2+ activities of LH MCH neurons (Ca2+MCH) were simultaneously recorded in male and female adult rats. Mathematical modeling and machine learning were then applied to predict Ca2+MCH using EEG derivatives. The robustness of the predictions was tested across sex and treatment conditions. Finally, features extracted from the EEG-predicted Ca2+MCH either before or after cocaine experience were used to predict future drug-seeking behaviors. ResultsAn EEG waveform derivative - a modified theta-to-delta ratio (EEG Ratio) - accurately tracks real-time Ca2+MCH in rats. The prediction was robust during rapid eye movement sleep (REMS), persisted through REMS manipulations, wakefulness, circadian phases, and was consistent across sex. Moreover, cocaine self-administration and long-term withdrawal altered EEG Ratio suggesting shortening and circadian redistribution of synchronous MCH neuron activities. In addition, features of EEG Ratio indicative of prolonged synchronous MCH neuron activities predicted lower subsequent cocaine seeking. EEG Ratio also exhibited advantages over conventional REMS measures for the predictions. ConclusionsThe identified EEG Ratio may serve as a non-invasive measure for assessing MCH neuron activities in vivo and evaluating REMS; it may also serve as a potential biomarker predicting drug use propensity.

neuroscience↗

bioRxiv2024

A Lung Cancer Mouse Model Database

Lung cancer, the leading cause of cancer mortality, exhibits diverse histological subtypes and genetic complexities. Numerous preclinical mouse models have been developed to study lung cancer, but data from these models are disparate, siloed, and difficult to compare in a centralized fashion. Here we established the Lung Cancer Mouse Model Database (LCMMDB), an extensive repository of 1,354 samples from 77 transcriptomic datasets covering 974 samples from genetically engineered mouse models (GEMMs), 368 samples from carcinogen-induced models, and 12 samples from a spontaneous model. Meticulous curation and collaboration with data depositors have produced a robust and comprehensive database, enhancing the fidelity of the genetic landscape it depicts. The LCMMDB aligns 859 tumors from GEMMs with human lung cancer mutations, enabling comparative analysis and revealing a pressing need to broaden the diversity of genetic aberrations modeled in GEMMs. Accompanying this resource, we developed a web application that offers researchers intuitive tools for in-depth gene expression analysis. With standardized reprocessing of gene expression data, the LCMMDB serves as a powerful platform for cross-study comparison and lays the groundwork for future research, aiming to bridge the gap between mouse models and human lung cancer for improved translational relevance.

cancer biology↗

bioRxiv2024

Bottlebrush polyethylene glycol nanocarriers translocate across human airway epithelium via molecular architecture enhanced endocytosis

Pulmonary drug delivery is critical to the treatment of respiratory diseases. However, the human airway surface presents multiscale barriers to efficient drug delivery. Here we report a bottlebrush polyethylene glycol (PEG-BB) nanocarrier that can translocate across all barriers within the human airway surface. Guided by the molecular theory, we design a PEG-BB molecule consisting of a linear backbone densely grafted by many ([~]1,000) low molecular weight ([~]1000 g/mol) PEG chains; this results in a highly anisotropic, wormlike nanocarrier featuring a contour length of [~]250 nm, a cross-section of [~]20 nm, and a hydrodynamic diameter of [~]40 nm. Using the classic air-liquid-interface culture system to recapitulate essential biological features of the human airway surface, we show that PEG-BB rapidly penetrates through endogenous airway mucus and periciliary brush layer (mesh size of 20-40 nm) to be internalized by cells across the whole epithelium. By quantifying the cellular uptake of polymeric carriers of various molecular architectures and manipulating cell proliferation and endocytosis pathways, we show that the translocation of PEG-BB across the epithelium is driven by bottlebrush architecture enhanced endocytosis. Our results demonstrate that large, wormlike bottlebrush PEG polymers, if properly designed, can be used as a novel carrier for pulmonary and mucosal drug delivery. Table of Contents O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=99 SRC="FIGDIR/small/580508v1_ufig1.gif" ALT="Figure 1"> View larger version (59K): org.highwire.dtl.DTLVardef@191f141org.highwire.dtl.DTLVardef@7600f4org.highwire.dtl.DTLVardef@138c9c6org.highwire.dtl.DTLVardef@1471c22_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2024

Progressive engagement of SST+ interneurons via Elfn1 regulates the barrel-septa response identity in the somatosensory cortex of mice

Just as separated digits and repeated sampling enhance somatosensation in humans, mice sense objects through multiple segregated whiskers through successive contacts. Individual whisker identity is maintained through the somatotopic organization of the Whisker[->]Brainstem[->]Thalamus[->]Cortex axis, culminating in distinct cortical domains: barrels and the surrounding septa. By performing simultaneous recordings using in-vivo electrophysiology in wild-type (WT) mice, we identify a progressive divergence in spiking activity between these domains upon repeated behaviorally relevant (10Hz) single- and multi-whisker stimulation. While the spiking activity ratio of multi- to single-whisker stimulation remains stable in barrels, it increases progressively in septa, suggesting inhibitory cell recruitment. Using genetic fate-mapping and tissue clearing, we indeed reveal that SST+ and VIP+ interneurons exhibit distinct laminar and regional distributions in barrel and septa domains. Further, calcium imaging of SST+ and VIP+ interneurons shows that while both neuron types respond to single-whisker stimulus, SST+ interneurons preferentially engage more in 10Hz multi-whisker stimulation, indicating their critical role in progressive stimulus preference. Genetic removal of Elfn1, which regulates the incoming excitatory synaptic dynamics onto SST+ interneurons, leads to the loss of the progressive increase in septal spiking ratio (MWS/SWS) upon stimulation. The importance of the loss of functional segregation of barrels, versus septa is revealed by cumulative temporal decoding analysis, supporting the notion that SST+ interneuron-mediated inhibition contributes to temporal encoding and stimulus integration. Finally, viral tracing combined with whole brain clearing and imaging reveals that barrel and septa domains project differentially to secondary somatosensory (S2) and motor (M1) cortices. These distinct projection patterns suggest that differential inhibitory processing in barrels and septa may contribute to functionally specialized downstream signaling. Together, our findings indicate that the progressive engagement of SST+ interneurons, mediated by Elfn1-dependent synaptic facilitation, underlies the preferential integration of multi-whisker stimuli in septa. This local inhibitory mechanism likely contributes to the functional segregation of barrel and septa domains and their distinct cortical projections, shaping how sensory information is processed and relayed to higher-order brain regions.

neuroscience↗

bioRxiv2024

Reconstructing cell histories in space with image-readable base editor recording

Knowing the ancestral states and lineage relationships of individual cells could unravel the dynamic programs underlying development. Engineering cells to actively record information within their own genomic DNA could reveal these histories, but existing recording systems have limited information capacity or disrupt spatial context. Here, we introduce baseMEMOIR, which combines base editing, sequential hybridization imaging, and Bayesian inference to allow reconstruction of high-resolution cell lineage trees and cell state dynamics while preserving spatial organization. BaseMEMOIR stochastically and irreversibly edits engineered dinucleotides to one of three alternative image-readable states. By genomically integrating arrays of editable dinucleotides, we constructed an embryonic stem cell line with 792 bits of recordable, image-readable memory, a 50-fold increase over the state of the art. Simulations showed that this memory size was sufficient for accurate reconstruction of deep lineage trees. Experimentally, baseMEMOIR allowed precise reconstruction of lineage trees 6 or more generations deep in embryonic stem cell colonies. Further, it also allowed inference of ancestral cell states and their quantitative cell state transition rates, all from endpoint images. baseMEMOIR thus provides a scalable framework for reconstructing single cell histories in spatially organized multicellular systems.

synthetic biology↗