Biology subjects

Wei, W.

Publications and source records attributed to Wei, W..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

Pathogenicity and transmissibility of bovine-derived HPAI H5N1 B3.13 virus in pigs

Since the first emergence of highly pathogenic avian influenza (HPAI) H5N1 viruses in dairy cattle, the virus has continued to spread, reaching at least 17 states and at least 970 dairy herds in the United States. Subsequently, spillovers of the virus from dairy cattle to humans have been reported. Pigs are an important reservoir in influenza ecology because they serve as a mixing vessel in which novel reassortant viruses with pandemic potential can be generated. Here, we show that oro-respiratory infection of pigs resulted in productive replication of a bovine-derived HPAI H5N1 B3.13 virus. Infectious virus was mainly identified in the lower respiratory tract of principal infected pigs, and sero-conversion was observed in most of the principal pigs at later time points. In one animal, we detected the emergence of a mutation in hemagglutinin (HA) previously associated with increased affinity for "mammalian-type" 2,6-linked sialic acid receptors, but this mutation did not reach consensus levels. Sentinel contact pigs remained sero-negative throughout the study, indicating lack of transmission. The results support that pigs are susceptible to a bovine-derived HPAI H5N1 B3.13 virus, but this virus did not replicate as robustly in pigs as mink-derived HPAI H5N1 and swine-adapted influenza viruses.

microbiology↗

bioRxiv2025

Insights From Protein Frustration Analysis Of BRD4-Cereblon Degrader Ternary Complexes Show Separation of Strong from Weak Degraders

PROteolysis TArgeting Chimeras (PROTACs), also known as Ligand-Directed Degraders (LDDs), are an innovative class of small molecules that leverage the ubiquitin-proteasome system to induce the degradation of target proteins. Structure based design methods are not readily applicable for designing LDDs due to the dynamic nature of the ternary complexes. This study investigates the dynamic properties of five LDD-mediated BRD4-Cereblon complexes, focusing on the challenges of evaluating linker efficiency due to the difficulty in identifying suitable computational metrics that correlate well with the cooperativity or degradation propensity of LDDs. We uncovered that protein frustration, a concept originally developed to understand protein folding, calculated for the residues in the protein-protein interface of the LDD-mediated ternary complexes recapitulate the strength of degradation of the LDDs. Our findings indicated that hydrophobic residues in the interface are among the highly frustrated residues pairs, and they are crucial in distinguishing strong degraders from weak ones. By analyzing frustration patterns, we identified key residues and interactions critical to the effectiveness of the ternary complex. These insights provide practical guidelines for designing and prioritizing more efficient degraders, paving the way for the development of next-generation LDDs with improved therapeutic potential.

biophysics↗

bioRxiv2025

The role of cortico-thalamic feedback for visual information processing

In the early visual system, neurons in the dorsal lateral geniculate nucleus (dLGN) not only relay visual inputs from the retina to the primary visual cortex (V1), but also receive cortico-thalamic (CT) feedback inputs, which anatomically outnumber feedforward inputs. Most experimental and theoretical work so far has focused on the modulatory influence of CT feedback on relay cells in the dLGN. However, the role of feedback for the activity of V1 neurons, which are mainly driven by visual input meditated by dLGN neurons, is still unclear. To address this question, we devised a spiking neural network model of the thalamo-cortical and cortico-thalamic loop, where the CT feedback can be turned on and off to study its effect. We identified three main phenomena of the effect of CT feedback on V1 neurons: (i) orientation selectivity of cortical responses is increased for all contrasts, (ii) preferred orientations of input and output are better aligned with each other, (iii) neuronal population activity represents the stimulus orientation with higher confidence. Our analysis showed that CT feedback generally improves the signal-to-noise ratio (SNR) of the responses of dLGN neurons and therefore also increases the SNR of thalamic inputs to V1 neurons. Moreover, we found that the modulatory effects on visual processing depend on the geometry of the CT feedback projections. We conclude that CT feedback increases the selectivity of V1 neurons particularly at low contrasts by modulating the activity of dLGN neurons. Author summaryExtensive experimental and theoretical studies have been conducted to understand the functional role of cortico-thalamic (CT) feedback on relay cells in the dorsal lateral geniculate nucleus (dLGN) during visual processing. However, it remains unclear how CT feedback affects the neuronal responses of V1 neurons. To address this question, we developed a computational model of the thalamo-cortico-thalamic loop circuit based on biophysical parameters. Our results indicate that CT feedback modulates the orientation preference of V1 neurons in a contrast-dependent manner: The increase of orientation selectivity (OS) is stronger and the input preferred orientation (PO) is better preserved at lower contrasts. Our analysis suggests a mechanistic explanation: The CT feedback attenuates the untuned part of the thalamic input, while it amplifies the tuned part. This effectively increases the signal-to-noise ratio (SNR) in particular for weak contrasts. Our network model for the first time allows us to study the effect of feedback on cortical neurons and understand the impact of the number and the geometry of feedback connections.

neuroscience↗

bioRxiv2025

Unbiased co-occurring mutational landscapes in tumorigenesis

Mutations with a synergistic effect on tumorigenesis were positively selected during tumor evolution, showing a tendency to co-occur in cancer genomes. To systematically gain insight of tumorigenic crosstalk at the mutation level, we utilized the FP-Growth algorithm in frequent pattern mining to create an unbiased map of co-occurring mutations from clinical genome sequencing data. We identified 100,933 frequent co-occurring mutation pairs across 22 cancer types. The co-mutation pairs involving cancer driver genes highlighted potential mechanisms for collaborative tumor formation, suggesting promising targets to disrupt tumorigenesis. Additionally, the large number of intra-gene co-mutations with strong dependencies indicated possible combinational effects on the oncogenic properties of specific proteins, which might be overlooked when individual mutations are not hotspots. Furthermore, our whole-genome mining strategy revealed a significant number of co-mutations in non-coding regions, with an enrichment of regulatory elements suggesting their potential role in modulating the co-expression of related genes. Finally, we demonstrated that our pipeline could systematically identify high-order co-mutations. In summary, our study provides the most extensive co-occurring mutations in tumor development, offering valuable insights into mechanisms and potential therapeutic targets.

bioinformatics↗

bioRxiv2024

Individual uniqueness of connectivity gradients is driven by the complexity of the embedded networks and their dispersion

Connectivity gradients are widely used to characterize meaningful principles of functional brain organization in health and disease. However, the degree of individual uniqueness and shared common principles is not yet fully understood. Here, we leveraged the Hangzhou test-retest dataset, comprising repeated resting-state fMRI scans over the span of one month, to investigate the balance between individual variation and shared patterns of brain organization. We quantified the short- and long-term stability for the first three connectivity gradients and used connectome fingerprinting to establish the associated individual identification rate. We found that all three connectivity gradients are highly correlated over both short and long time intervals, demonstrating connectome fingerprinting utility. Individual uniqueness was dictated by the complexity of the networks such that heteromodal networks had higher connectome fingerprinting rates than unimodal networks. Importantly, the dispersion of the gradient coefficients associated with canonical functional networks was correlated with identification rates, irrespective of the position along the gradients. Beyond individual uniqueness, between subject similarity was high along the first connectivity gradient, which captures the dissociation between unimodal and heteromodal cortices, and the second connectivity gradient, which differentiates sensory cortices. Our results support the usage of connectivity gradients for the purposes of both group comparisons and prediction of individual behaviours. Our work adds to existing knowledge on the shared versus unique organizational principles and offers insights into the importance of network dispersion to the individual uniqueness it carries.

neuroscience↗

bioRxiv2024

Engineered mitochondrial A-to-G editors with enhanced efficiency and targeting scope

Mitochondrial base editing is a powerful technology, but the current A-to-G mitochondrial DNA (mtDNA) base editors are reluctant to achieve high efficiency, which is critical for mtDNA engineering. Through laboratory evolution, TadA-8e variants were discovered with substantially increased activity and expanded targeting compatibility, especially for previously unfavorite sequence contexts, when applied to both nuclear and mitochondrial ABEs. Further engineering of the mtDNA editors (eTd-mtABEs) dramatically reduced both DNA and RNA off-targeting effects and enhanced strand-selective A-to-G editing with substitution of DddA to DNA nickases. Moreover, the eTd-mtABEs induced up to 145-fold editing frequencies compared to previous mtDNA adenine base editors in rat cells, and installed targeted mutations in all injected rat embryos with up to 74% efficiency in founders, resulting generation of SNHL and Leigh syndrome models with severe defects. It suggests that eTd-mtABEs are promising mtDNA engineering technology for basic research and for translational studies. HighlightsO_LIEngineered TadA variants enhance nuclear and mitochondrial ABE activity in all sequence contexts. C_LIO_LIAdditional mutations in eTd-mtABEs further minimize both DNA and RNA off-targeting effects. C_LIO_LIEngineered TadA variants are compatible to DNA nickase assisted strand-selective mtDNA editing. C_LIO_LIeTd-mtABEs enable highly efficient generation of rat mtDNA disease models with severe phenotypes. C_LI

bioengineering↗

bioRxiv2024

Individual brain activity patterns during task are predicted by distinct resting-state networks that may reflect local neurobiological features

Understanding how individual cortical features shape functional brain organization offers a promising framework for examining the principles of cognitive specialization in the human brain. This study explores the relationship between various cortical characteristics--i.e resting-state functional connectivity, structural connectivity, microstructure, morphology, and geometry--and the layout of task-specific functional activations. We employ linear models to predict the functional layout of the cortex at the individual level from each of these feature modalities. Our findings demonstrate that resting-state component loadings predict individual task activations, consistently across hemispheres and independent datasets. Whereas the first few components provide a common space for functional activations across tasks, predictive higher-order component loadings demonstrated task-specificity. Cortical microstructure/morphology was notably predictive of activation strength in the occipital cortex, highlighting its relevance for cortical functional specialization. By relating resting state components to a set of reference maps of cortical organization, we identify associations that suggest possible neurobiological underpinnings of specific cognitive functions. The remaining feature modalities were only predictive of group-level functional activations. These results advance our understanding of how distinct cortical features may contribute to functional specialization, guiding future inquiry into the organization of cognitive functions on the cortex.

neuroscience↗

bioRxiv2024

BaNDyT: Bayesian Network modeling of molecular Dynamics Trajectories

Bayesian network modeling (BN modeling, or BNM) is an interpretable machine learning method for constructing probabilistic graphical models from the data. In recent years, it has been extensively applied to diverse types of biomedical datasets. Concurrently, our ability to perform long-timescale molecular dynamics (MD) simulations on proteins and other materials has increased exponentially. However, the analysis of MD simulation trajectories has not been data-driven but rather dependent on the users prior knowledge of the systems, thus limiting the scope and utility of the MD simulations. Recently, we pioneered using BNM for analyzing the MD trajectories of protein complexes. The resulting BN models yield novel fully data-driven insights into the functional importance of the amino acid residues that modulate proteins function. In this report, we describe the BaNDyT software package that implements the BNM specifically attuned to the MD simulation trajectories data. We believe that BaNDyT is the first software package to include specialized and advanced features for analyzing MD simulation trajectories using a probabilistic graphical network model. We describe here the softwares uses, the methods associated with it, and a comprehensive Python interface to the underlying generalist BNM code. This provides a powerful and versatile mechanism for users to control the workflow. As an application example, we have utilized this methodology and associated software to study how membrane proteins, specifically the G protein-coupled receptors, selectively couple to G proteins. The software can be used for analyzing MD trajectories of any protein as well as polymeric materials.

bioinformatics↗

bioRxiv2024

Disease-linked mutations dysregulate neuronal condensate physical properties, composition, and RNA translation

Local RNA translation is essential for development. In neurons, deficient local translation linked with mutations in scaffold proteins results in dysregulated dendrite and dendritic spine growth. However, mechanisms by which these proteins control translation and how disease-linked mutations induce aberrant translation were unclear. We use biochemical reconstitution and neuronal assays to show that mutations to the neuronal condensate scaffold shank2 cause physical hardening and altered composition of condensates; a key RNA translation-modulator FMRP is excluded from mutant condensates. Functionally, shank2 condensates repress translation while condensates composed of shank2 with intrinsically disordered region-localized missense mutations promote translation. These results demonstrate that disease-linked dysregulation of condensate physical properties and composition is an underlying mechanism of aberrant RNA translation often observed in disease. One Sentence SummaryDisease-linked missense mutations in the postsynaptic density scaffold protein shank2 dysregulate phase separated biomolecular condensate physical properties and composition resulting in aberrant RNA translation.

biophysics↗

bioRxiv2024

An mTOR-Tfeb-Fabp7a signaling axis can be harnessed to ameliorate bag3 cardiomyopathy in adult zebrafish

Dysregulated proteostasis in cardiomyocytes is an important pathological event in BAG3 cardiomyopathy, which can be repaired by inhibiting mechanistic target of rapamycin (mTOR) for cardioprotective effects. Here, we aimed to uncover additional pathological events and therapeutic target genes via leveraging zebrafish genetics. We first assessed transcription factor EB (tfeb), a candidate gene that encodes a direct downstream phosphorylation target of mTOR signaling. We found that cardiomyocyte-specific transgenic overexpression of tfeb (Tg[cmlc2:tfeb]) is sufficient to repair defective proteostasis, attenuate accelerated cardiac senescence, a previously unrecognized phenotype in the bag3 cardiomyopathy model, and rescue cardiac dysfunction. Next, we compared cardiac transcriptomes between the Tg(cmlc2:tfeb) transgenic fish and the mtorxu015/+ mutant, and tested 4 commonly downregulated lipodystrophy genes using an F0-based genetic assay. We found that inhibition of the fatty acid binding protein a (fabp7a) gene, but not the other 3 genes, exerts therapeutic effects on bag3 cardiomyopathy. Conversely, fabp7a expression is elevated in bag3 cardiomyopathy model and cardiomyocyte-specific overexpression of fabp7a resulted in dysregulated proteostasis, accelerated cardiac senescence, as well as cardiac dysfunction. Together, these genetic studies in zebrafish uncovered Fabp7a activation and accelerated cardiac senescence as important pathological events in bag3 cardiomyopathy. The mTOR-Tfeb-Fabp7a signaling axis can be harnessed to repair these pathological changes and exert cardioprotective effects.

genetics↗

bioRxiv2024

Engineering a Cell-Based Orthogonal Ubiquitin Transfer Cascade for Profiling the Substrates of RBR E3 Parkin

The E3 ubiquitin (UB) ligase Parkin utilizes a Ring-Between-Ring (RBR) domain to mediate the transfer of UB to its substrates to regulate diverse cellular functions, including mitochondrial quality control, cell cycle progression, metabolism programming, and the establishment of synaptic functions. Mutations affecting the E3 ligase activity of Parkin are associated with cancer and Parkinsons disease (PD). An essential role of Parkin is to synthesize UB chains on the surface of damaged mitochondria to initiate mitophagy. Still, it is not clear how Parkin carries out other biological functions through the ubiquitination of its downstream targets in the cell. We hypothesized that a comprehensive substrate profile of Parkin would facilitate the discovery of ubiquitination pathways underpinning its multifaceted roles in cell regulation and reveal mechanistic linkages between Parkin malfunction and disease development. Here, we used phage display to assemble an orthogonal ubiquitin transfer (OUT) cascade of Parkin that can exclusively deliver an engineered UB mutant (xUB) to Parkin and its substrates in living cells. We then generated a substrate profile of Parkin by purifying xUB-conjugated proteins from cells and identifying them by proteomics. The OUT screen identified Parkin substrates involved in DNA replication, protein translation, intracellular protein transport, and rhythmic regulation. Based on previous literature implicating alterations in membrane vesicle trafficking in PD, we verified Parkin-catalyzed ubiquitination of Rab GTPases (Rab1a, Rab5a, Rab5c, Rab7a, Rab8a, Rab10, an Rab13) as well as CDK5, with reconstituted ubiquitination reactions in vitro and in cells. We also found chemical-induced stimulation of mitophagy enhanced Parkin-mediated ubiquitination of Rab proteins. These findings demonstrate that the OUT cascade of Parkin can serve as an empowering tool for identifying Parkin substrates to elucidate its cellular functions.

biochemistry↗

bioRxiv2024

High-coverage, massively parallel sequencing of single-cell genomes with CAP-seq

Microbial communities are extraordinarily diverse and play crucial roles in health and disease, yet current methods lack the resolution and scalability needed to dissect their genomic and ecological complexity at the single-cell level. Here, we present CAP-seq, a high-throughput single-microbe genomics platform that combines hydrogel-based semi-permeable encapsulation with minimal microfluidics to recover thousands of single-amplified genomes (SAGs) with long reads and high completeness at low sequencing depth. We benchmarked CAP-seq using defined microbial communities, demonstrating strain-level resolution, accurate detection of rare taxa, and genome recovery exceeding 50% at [~]10x coverage. Applying CAP-seq to pediatric Clostridioides difficile infection microbiomes, we generated a high-resolution single-cell atlas comprising tens of thousands of SAGs across hundreds of species. Host-resolved profiling of the cryptic plasmid pBI143 revealed previously hidden low-abundance host associations, six new plasmid versions, and their coexistence within individuals, indicating complex plasmid evolution in situ. Longitudinal analysis during fecal microbiota transplantation and vancomycin treatment uncovered dynamic remodeling of microbial hosts, antimicrobial resistance genes, and plasmids at single-cell resolution. CAP-seq enables scalable, high-performance single-cell genomics and provides a practical, widely accessible platform for microbiome analysis, paving the way for large-scale exploration of microbial dark matter and host-microbe interactions across diverse ecosystems.

genomics↗

bioRxiv2024

A secondary β-hydroxybutyrate metabolic pathway linked to energy balance

{beta}-hydroxybutyrate (BHB) is an abundant ketone body. To date, all known pathways of BHB metabolism involve interconversion of BHB and primary energy intermediates. Here we show that CNDP2 controls a previously undescribed secondary BHB metabolic pathway via enzymatic conjugation of BHB and free amino acids. This BHB-ylation reaction produces a family of endogenous ketone metabolites, the BHB-amino acids. Genetic ablation of CNDP2 in mice eliminates tissue amino acid BHB-ylation activity and reduces BHB-amino acid levels. Administration of BHB-Phe, the most abundant BHB-amino acid, to obese mice activates neural populations in the hypothalamus and brainstem and suppresses feeding and body weight. Conversely, CNDP2-KO mice exhibit increased food intake and body weight upon ketosis stimuli. CNDP2-dependent amino acid BHB-ylation and BHB-amino acid metabolites are also conserved in humans. Therefore, the metabolic pathways of BHB extend beyond primary metabolism and include secondary ketone metabolites linked to energy balance.

biochemistry↗

bioRxiv2024

Engineering pathogen-inducible promoters for conferring disease resistance in tomato

Many disease resistance genes utilized in crop breeding encode nucleotide-binding leucine-rich repeat receptors (NLRs), which are frequently race-specific and fail to provide durable protection in the field. Consequently, engineering broad-spectrum resistance has become a primary goal. While autoactive NLRs can provide broad-spectrum immunity by bypassing specific pathogen recognition, they often impose severe fitness costs. Here, we hypothesized that precise transcriptional control could mitigate these penalties and developed a synthetic strategy coupling pathogen-inducible (PI) promoters with autoactive NLRs. Through a transcriptomic meta-analysis, we identified and validated native tomato PI promoters that respond to diverse pathogens while remaining insensitive to abiotic stress. We established a tunable system by pairing these promoters varying in basal and inducible expression with NLRs exhibiting different degrees of autoactivity. Systematic characterization revealed that balancing these components is critical to prevent leaky immune activation in the absence of pathogens. Transgenic tomatoes expressing a weakly autoactive NLR under a PI phenylalanine ammonia-lyase promoter exhibited enhanced resistance to two taxonomically distinct pathogens without growth impairment. Disruption of the PI sequence largely abolished this resistance, confirming the necessity of pathogen-mediated transcriptional induction. Finally, we added an additional layer of tunability by engineering the copy number of inducible elements and the core promoter to fine-tune promoter strength while preserving inducibility. Together, our results showcase a versatile framework for engineering multi-pathogen resistance and provide new insights into using transcriptional control in overcoming the fitness costs associated with autoactive NLRs.

synthetic biology↗

bioRxiv2024

The role of TRPV4 in acute sleep deprivation-induced fear memory impairment

Acute sleep deprivation (ASD) negatively impacts fear memory, but the underlying mechanisms are not fully understood. Transient receptor potential vanilloid 4 (TRPV4), a cation channel which is closely correlated with the concentration of Ca2+, and neuronal Ca2+ overloading is a crucial inducement of learning and memory impairment. This study utilized an acute sleep-deprived mouse model combined with fear conditioning to investigate these mechanisms. mRNA sequencing revealed increased expression of TRPV4 in mice with ASD-induced fear memory impairment. Notably, knockdown of TRPV4 reversed ASD-induced fear memory impairment. ASD leads to the increased concentration of Ca2+. Additionally, we observed a reduction in spine density and a significant decrease in postsynaptic density protein 95 (PSD95), which is associated with synaptic plasticity, in sleep-deprived fear memory impairment mice. This indicates that ASD may cause overloaded Ca2+, disrupting synaptic plasticity and impairing fear memory. Moreover, TRPV4 knockdown significantly decreased Ca2+ concentration, mitigated the loss of dendritic spines and reduction of PSD95, contributing to the restoration of fear memory. These findings indicate a potential protective role of TRPV4 knockdown in counteracting ASD-induced fear memory deficits. Collectively, our results highlight that TRPV4 may be a potential therapeutic target in mediating fear memory impairment due to ASD and underscore the importance of sleep management for conditions like PTSD.

neuroscience↗

bioRxiv2024

Engineering the plant intracellular immune receptor Sr50 to restore recognition of the AvrSr50 escape mutant

Pathogen-driven plant diseases cause significant crop losses worldwide. The introgression of intracellular nucleotide-binding leucine-rich repeat receptor (NLR) genes into elite crop cultivars is a common strategy for disease control, yet pathogens rapidly evolve to evade NLR-mediated immunity. The NLR gene Sr50 protects wheat against stem rust, a devastating disease caused by the fungal pathogen Puccinia graminis f. sp. tritici (Pgt). However, mutations in AvrSr50 allowed Pgt to evade Sr50 recognition, leading to resistance breakdown. Advances in protein structure modeling can enable targeted NLR engineering to restore recognition of escaped effectors. Here, we combined iterative computational structural analyses and site-directed mutagenesis to engineer Sr50 recognition of AvrSr50QCMJC, a Pgt effector variant that evades wild-type Sr50 detection. Derived by molecular docking, our initial structural model identified the K711D substitution in Sr50, which partially restored AvrSr50QCMJC recognition. Enhancing Sr50K711D expression via strong promoters compensated for weak recognition and restored robust immune responses. Further structural refinements led to the generation of five double and two triple receptor mutants. These engineered mutants, absent in nature, showed robust dual recognition for AvrSr50 and AvrSr50QCMJC in both Nicotiana benthamiana and wheat protoplasts. Notably, the K711D substitution was essential and synergistic with the additional substitutions for AvrSr50QCMJC recognition, demonstrating protein epistasis. Furthermore, this single substitution altered AlphaFold 2 predictions, enabling accurate modeling of the Sr50K711D-AvrSr50 complex structure, consistent with our final structural hypothesis. Collectively, this study outlines a framework for NLR engineering to counteract pathogen adaptation and provides novel Sr50 variants with potential for stem rust resistance.

plant biology↗

bioRxiv2024

Ophthalmic acid is a bloodborne metabolite that contributes to age-induced cardiomyocyte hypertrophy

Cardiac aging involves the development of left ventricular hypertrophy alongside a decline in functional capacity. Here, we use neutral blood exchange to demonstrate that the acute removal of age-accumulated blood factors significantly regresses cardiac hypertrophy in aged mice. The reversal of hypertrophy was not attributed to age-associated hemodynamic effects, implicating a role of blood-derived factors. In addition, the overarching paradigm of systemic aging maintains that the age-related overabundance of plasma proteins are largely responsible for causing pathological phenotypes in tissues. Our results suggest that blood metabolites, not proteins, drive cardiac hypertrophy instead. Upon analyzing serum metabolomics data sets, we identified ophthalmic acid as a circulating metabolite whose levels increase with advanced age. Treatment of adult mouse and neonatal rat cardiomyocytes in culture with ophthalmic acid increased their relative surface areas. This study uncovers a non-protein metabolite that may contribute to cardiomyocyte hypertrophy during aging. Identifying a method to counteract ophthalmic acids hypertrophic effects may reveal novel therapeutic opportunities for cardiac rejuvenation.

physiology↗

bioRxiv2024

Transmission of Mixed Convergent Signals at the Mouse Retinogeniculate Synapse

There are two broad modes of information transfer in the brain: the labeled line model, where neurons relay inputs they receive, and the mixed tuning model, where neurons transform and integrate different inputs. In the visual pathway, information transfer between retinal ganglion cells (RGCs) and the dorsal lateral geniculate nucleus (dLGN) neurons is primarily viewed as a labeled line. However, recent work in mice has demonstrated that different RGC types, encoding distinct visual features, can converge onto a dLGN neuron, raising the fundamental question of whether the dLGN transforms visual information. Using optogenetics we activated distinct RGC populations and assessed spiking output of dLGN neurons by in vivo recordings. We found that visual response properties of dLGN neurons driven by a specific RGC population largely matched properties of the activated RGCs. Furthermore, in vitro dual-opsin experiments demonstrate that strong functional convergence from distinct RGC types rarely occurs. Thus, retinogeniculate information transfer in mice largely adheres to a labeled line model.

neuroscience↗