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Antibody-guided design of a human astrovirus vaccine
PROJECT SUMMARY Viral diarrheal diseases cause substantial global morbidity and mortality. Diarrheal disease is the second leading cause of childhood mortality in the world, accounting for over 10% of all deaths of children under 5 years old. Gobally, over 1 billion cases of diarrheal diseases occur every year, making prevention of these diseases a public health concern of the highest priority. Human astrovirus (HAstV) infection is a leading cause of viral diarrhea in children and has been shown to cause chronic gastrointestinal disease and fatal neurological disease in immunocompromised patients. There are nearly 4 million cases of HAstV infection each year in the United States alone, and there are no clinically approved HAstV-specific vaccines or therapeutics. Antibody-guided vaccine development leverages a deep understanding of productive antiviral antibody responses in order to design vaccine immunogens that deliberately focus the induced response toward highly conserved epitopes with the goal of reliably inducing broad, durable immunity. Using a cutting-edge monoclonal antibody (mAb) discovery approach based on next-generation antigen barcoding, single cell multi-omics, and sophisticated bioinformatics, we will exhaustively screen the HAstV- specific antibody repertoires of geographically distinct donor cohorts to uncover the structural and immunogenetic features that differentiate broad and potently neutralizing HAstV mAbs. A more complete understanding of these exceptional – and potentially very rare – mAbs will accelerate the development of HAstV vaccines and therapeutics. We have assembled a collaborative, multidisciplinary group of investigators with a long history of productive collaboration and with highly complementary areas of expertise. We expect our work will result in the discovery of thousands of novel anti-HAstV mAbs from cohorts of healthy adult and pediatric participants. Detailed genetic, functional, and structural characterization of these mAbs will reveal conserved sites of viral vulnerability, uncover the precise molecular mechanisms of viral neutralization, and inform our development of a broadly protective HAstV vaccine.
HIV-1 Matrix and Envelope Protein Interactions
It is important to characterize how HIV-1 proteins fulfill their functions in order to develop new approaches for curtailing the AIDS epidemic. One of the remaining frontiers of HIV-1 research concerns the mechanisms by which the HIV-1 matrix (MA) and envelope (Env) proteins collaborate with each other to ensure the assembly of infectious viruses. The HIV-1 MA protein directs the delivery of precursor Gag (PrGag) proteins to the plasma membranes (PMs) of infected cells, and drives the formation of lipid raft-like, liquid ordered (Lo) membrane domains. This membrane reorganization attracts a number of proteins that favor lipid raft-type microdomains. Such proteins appear to assemble into virus particles as innocent bystanders, and this appears to be how Env proteins that carry cytoplasmic tail deletions (CT) can be incorporated into virions. In contrast, wild type (WT) Env proteins additionally require an interaction with MA proteins to assemble into viruses. This is most easily understood in the context of the lattice that MA proteins construct at the PMs of infected cells. In particular, multiple lines of evidence imply that the CTs of WT Env proteins are trapped by MA lattices in immature, assembling virus particles, and then are released after assembled viruses are processed into their mature forms. Despite a seeming consensus on the MA-Env interaction steps, there are a number of very significant unknowns. Using our recent and preliminary results as a foundation, and taking advantage of the unique expertise of our collaborators, we propose the characterization of WT and mutant MA lattices, and of interactions of MA and Env with each other, and with membrane lipids. Our results will help clarify how MA and Env cooperate; they will illuminate aspects of host cell protein-membrane interactions; and they will foster the development of new approaches to intefere with HIV-1 replication.
Weak Cell Adhesion is a Prognostic Signature of Invasive Cancer
Project Summary Despite early detection, low-grade and localized breast cancers such as ductal carcinoma in situ (DCIS) can relapse in up to 20% of cases despite standard of care. For DCIS, relapse affects over 12,000 U.S. women annually and has increased 60% in the last 40 years. Current diagnostic assessments including histopathological markers often miss early disseminating cells, lack specificity, or cannot distinguish cancer from non-cancer cells in the stroma. Hence there is an unmet need for cancer diagnostic technologies that employ radically different characterization methods. For example, significant physical differences exist between metastasizing and benign breast cancer cells, owing to metastasizing cells detaching from the primary tumor, migrating through the surrounding stroma, intravasating and extravasating, and ultimately engrafting in distant tissues. We recently demonstrated that cancer cells with weaker adhesion migrate faster and metastasize more frequently in murine breast cancer models than strongly adherent cells. In a small pilot study of human breast tumors, we also observed that the abundance of weakly adherent (WA) cells scales with disease severity; subpopulations from invasive carcinomas were the least adherent. However, a subset of DCIS cases displayed much less adhesion, suggesting that these patients may have a tumor subpopulation that progresses to metastatic disease despite standard-of-care treatment. Weak adhesion is a defining physical characteristic of tumors, but to establish their role in initiation, metastasis, and patient outcomes, we will leverage model systems and our newly patented adhesion technology to answer these fundamental questions of cancer biology and clinical translation. To understand the impact of adhesion on cancer progression, we will evaluate the tumor-initiating potential of WA versus strongly adherent (SA) tumor cells in a murine breast cancer model before confirming how weak adhesion advantages cells to cause secondary disease using bioengineered in vitro models. In dissecting the stages of metastasis where WA cells exhibit advantages, e.g., recapitulating stromal niche, transendothelial migration, and tissue-specific colonization, we will identify mechanisms that enable WA cells to thrive and evaluate therapeutic targets that disrupt these pathways. Finally, we will analyze the adhesion profiles of resected tumors and stroma from 80 breast cancer patients with DCIS or invasive disease. Adhesion data will be correlated with conventional assessment methods and ultimately with patient outcomes, e.g., disease-free and progression-free intervals. We anticipate that the DCIS subpopulation that aligns with the adhesion signature of invasive carcinomas will have shorter intervals and survival time. This integrated study design bridges mouse models, mechanistic bioengineering assays, and human samples to clarify the metastatic potential and prognostic value of WA breast cancer cells. Our use of mouse models in this grant is required to study the interactions among tumor cells, immune cells, vasculature, and stromal tissues that drive tumor formation in vivo. Bioengineered in vitro systems lack the complexity to ask such questions and using injected tumor cells is not possible in humans.
Mentoring investigators in patient-oriented research on HIV and public health
PROJECT SUMMARY/ABSTRACT Despite marked progress in treatment and prevention, HIV remains a significant public health threat in the US and globally. Innovative strategies are needed to effectively deploy interventions and reduce HIV incidence, which requires a sustained and committed workforce. Dr. Dennis is an infectious disease physician and researcher at the University of North Carolina (UNC) at Chapel Hill, Division of Infectious Diseases. She seeks the protected time of the K24 award to ensure adequate time and effort to provide mentorship in patient- oriented HIV research focused on applied public health strategies. Dr. Dennis has a track record of performing high-quality patient-oriented research supported by independent funding. Her research bridges basic, clinical, and epidemiologic science by using HIV-1 molecular epidemiology and phylogenetics to understand HIV transmission at the population level and to use this information to direct prevention. She has expanded this work to optimize strategies to detect and respond to HIV networks using mixed-methods approaches. The overall goal of this work is to uncover the links between these sub-epidemics - which are overlapping sub- epidemics defined by risk groups, geography, social interaction - to facilitate the design of timely, effective interventions. The research specific aims are 1) Investigate HIV transmission networks using molecular epidemiology and phylodynamics (R01AI135970), 2) Evaluate uptake of HIV treatment and prevention services in public health with social network approaches (supported by R01AI169602), and 3) Pilot a network-based characterization of early syphilis infections to inform strategies to increase the uptake of injectable antiretrovirals for HIV treatment and prevention (supported by K24). With the support of the K24, she will leverage resources at UNC to support mentorship and professional development to strengthen new directions (implementation science, community-engaged research). Dr. Dennis is deeply committed to expanding her mentorship and dedicated to fostering diverse mentees with lived experiences that are critical for sustaining the HIV workforce. Dr. Dennis is Co-Director of the UNC Center for AIDS Research (CFAR) Scientific Working Group which focuses on Ending the HIV Epidemic efforts in North and South Carolina. She has strong institutional support and a multidisciplinary team of advisors, including the UNC CFAR, and is an advisor on the UNC T32 HIV/STI institutional training program. She has collaborated for the past 10 years with NC Division of Public Health and with multiple investigators and trainees at the UNC Gillings School of Public Health. She is active in the UNC Infectious Diseases Fellowship program, providing clinical and research mentorship to numerous ID fellows. Her clinical activity provides practical grounding and relevance in patient-oriented research. The K24 will provide 50% of Dr. Dennis’ salary and additional funds to support mentees’ research. The proposed research is timely and aligned with the National HIV/AIDS Strategy and will support the protected time needed to mentor the next-generation of investigators in HIV patient-oriented research.
Structural and functional characterization of autoimmune antibodies against NMDAR
Project Summary. The goal of this project is to understand the origins and molecular mechanisms underlying the anti-cancer autoimmune response against the N-methyl-D-aspartate receptor (NMDAR) and its correlation with anti-N-methyl-D-aspartate receptor autoimmune encephalitis (NMDARAE). While anti-cancer immune responses can promote tumor elimination, they may also lead to the production of self-reactive antibodies that trigger autoimmune diseases. NMDARAE is the most common form of immune-mediated encephalitis, which results in prominent neuropsychiatric symptoms, including seizures, psychosis, and memory deficits. NMDARs belong to a family of ligand-gated ion channels expressed exclusively in the central nervous system. They are involved in various aspects of brain development and function, including learning and memory. They respond to the neurotransmitter glutamate and a co-agonist, glycine or D-serine, to mediate excitatory neurotransmission, which plays a central role in synaptic plasticity. NMDARAE is associated with ovarian teratomas, where aberrant NMDAR expression is believed to trigger an autoimmune response. In NMDARAE, anti-NMDAR antibodies, as well as B cells and antibody-secreting cells, cross the blood-brain barrier via unknown mechanisms, resulting in the presence of anti-NMDAR antibodies at high titers within the brain and cerebrospinal fluid (CSF). These antibodies target NMDARs, modulating their function and contributing to disease pathology. Emerging evidence, supported by our preliminary data, suggests that NMDARs are also expressed in triple-negative breast cancer (TNBC), extending the relevance of anti-NMDAR autoimmunity beyond ovarian teratomas. In our TNBC mouse model, which ectopically expresses NMDARs (TNBC-NMDAR), we observed the onset of anti-NMDAR autoimmunity, where the produced antibodies cause both anti-tumor activity and symptoms such as lowered seizure threshold, mirroring key features of NMDARAE. Here, we will establish this TNBC mouse model as we develop molecular methods to characterize it. Aim 1 will focus on establishing and characterizing the TNBC- NMDAR mouse model. We will develop a detection method utilizing the intact tetrameric NMDAR channel proteins and a method to isolate B cells expressing B cell receptors against NMDAR from biological samples by using fluorescently labeled intact NMDAR proteins, followed by single-cell RNA sequencing. Aim 2 will utilize single-particle cryo-electron microscopy (cryo-EM) to investigate the interactions between NMDAR and the cloned antibodies, providing insights into epitope recognition, NMDAR subtype specificity, and conformational changes induced by antibody binding. Aim 3 will assess the impact of the cloned antibodies on NMDAR channel activity using electrophysiology. We will also assess anti-tumor activity and NMDARAE onset by each antibody clone. Together, the proposed research will gain insights into the link between anti-cancer anti-NMDAR autoimmunity and NMDARAE. It will also elucidate which functional properties of the cloned antibodies promote anti-tumor activity while contributing to NMDARAE, thereby informing potential therapeutic strategies.
Characterization and functional impact of somatic numtogenesis in the human cortex
Project Summary This project focuses on studying nuclear mitochondrial insertions (numts), which are fragments of mitochondrial DNA that get integrated into the nuclear DNA of human cells. While this process, called numtogenesis, occurs naturally and can be passed down to future generations, it has also been observed to occur somatically in our bodies. Historically the function of numts has been difficult to study because they are repetitive and difficult to map with short read sequencing technologies, but there is emerging evidence that they can influence cell function and play a role in diseases, aging, and even complicate genetic studies. Our recent research discovered numts in the human brain’s cortex, and their presence appeared to be linked with earlier death, suggesting they may play a role in aging. However, due to limitations in the data we used, we could not fully explore the extent or impact of these insertions across different tissues or individuals. This project aims to map and study numts in more detail, especially in the human cortex, to further explore this ongoing transfer of DNA from the mitochondria to the nuclear genome and their potential to impact aging and brain function. We will accomplish this by 1) improving sequencing methods to detect numts, 2) comparing their presence across different tissues, and 3) investigating how they affect gene expression and DNA structure. By the end of the project, we aim to provide a model for how such somatic variation may occur and impact cellular function at the tissue level.
Response and defense mechanisms of extraintestinal Escherichia coli to reactive oxygen and chlorine species
Members of the Escherichia coli species are remarkably diverse and comprise commensal, probiotic and pathogenic strains. While some pathogenic E. coli cause intestinal diseases, extraintestinal E. coli (ExPEC) can colonize and infect environments outside the gut. For instance, members of this pathotype can inhabit the urinary tract where they are confronted with a multitude of bactericidal host defense strategies, which requires specialized genetic adaption for survival. ExPEC must defend highly toxic antimicrobials such as hypochlorous acid (HOCl), a potent reactive oxygen and chlorine species (RO/CS) generated during neutrophil-mediated phagocytosis and by enzymes in uroepithelial cells to control bacterial colonization. The increasing rate of ExPEC infections in humans due to changing infection dynamics demonstrate the critical need for a better understanding of ExPEC pathogenesis, which is desperately needed to improve approaches for infection prevention and treatment given the rise in antibiotic resistance spreading among E. coli. Our lab has reported that members of the ExPEC pathotype are more resistant to RCS in vitro and to neutrophil-mediated phagocytosis when compared to non-pathogenic and enteropathogenic E. coli. We identified the defense system responsible for these phenotypes and characterized its regulation during RCS stress: the RcrR regulon consisting of the rcrARB genes is controlled by the RCS-sensing transcriptional repressor RcrR, which reversibly loses its repressor activity upon oxidation by RCS, resulting in de-repression of its downstream targets. Induced expression of rcrB contributes significantly to ExPEC’s increased RCS resistance, however, the precise mechanism of RcrB and the role of RcrA (and potentially other defense players) during RCS stress remain enigmatic. Our long-term goal is to increase the efficacy of existing antimicrobial therapies by purposefully and selectively sensitizing ExPEC to clearance by innate immune cells. The overall objective of this application is a comprehensive analysis of ExPEC’s RCS defense with particular focus on the mechanism of the RcrR regulon. We hypothesize that RcrB directly protects cells from HOCl, while RcrA, another member of the RcrR regulon, mediates evasion from HOCl and invasion into host cells. In Aim 1, we will use phenotypic, biochemical, and imaging approaches to investigate the mechanism by which RcrB contributes to ExPEC’s increased RCS resistance. In Aim 2, we will study the role of RcrA for ExPEC motility, biofilm formation, and host cell invasion. In Aim 3, we will use independent unbiased and targeted approaches, including phenotypic characterization of transposon mutants, to fully comprehend ExPEC-specific responses to and defenses against RCS. Identifying, characterizing and targeting ExPEC-specific defense systems has the potential to increase the body’s own capacity to fight UTIs. Overall, we will involve at least four undergraduate students in our research projects, which we believe will provide an excellent training opportunity for the next generation of scientists.
Temporomandibular Joint Disc Replacement: Biomechanical Characterization and Novel Implant Assessment
Project Summary/Abstract Temporomandibular joint (TMJ) disorders inflict approximately 5% to 12% of the population. For advanced disorders of the articular TMJ disc, which typically do not respond to conservative treatments, disc resection is the most common surgical intervention. However, the TMJ disc plays a critical role in distributing mechanical stress and preventing wear to the articular surfaces of the joint. Thus, removing the disc can further disrupt joint homeostasis, driving degeneration and the development of osteoarthritis, which can lead to highly invasive and challenging surgical interventions such as joint reconstructions and total joint replacement. Therefore, there is a critical need for disc replacements that can restore the homeostasis of the joint when disc resection is required. Prior attempts at replacing the disc with alloplastic implants have led to deleterious pathological changes related to wear debris, implant fragmentation, and adverse inflammatory responses. Therefore, it is crucial to consider wear, mechanical strength, and biocompatibility of disc replacement materials in the context of long-term cyclic loading in the TMJ. Accordingly, the objective of this proposal is to create an artificial TMJ disc that replaces the mechanical function of the native disc and prevents subsequent degeneration of the joint. Towards this goal, the proposed research will characterize the mechanical loading environment of the TMJ in order to determine the mechanical criteria of a TMJ disc replacement needed to minimize internal stress in the joint (Specific Aim 1). Further, non-resorbable composite hydrogels will be fabricated using biocompatible materials, refined to exhibit biomimetic properties, and molded into a TMJ disc implant. Rigorous mechanical evaluations will determine material durability and suitability as a TMJ disc replacement (Specific Aim 2). Finally, a large animal study will be utilized to evaluate the safety and efficacy of the developed TMJ disc replacement (Specific Aim 3). Successful completion of the proposed work would represent a paradigm shift in the treatment of TMJ disc disorders that can mitigate further joint degeneration and prevent more invasive and complicated surgeries.
I3-BC: Image-Based Infiltrating Immune Cell Detection and Outcomes in Breast Cancer Clinical Trials
PROJECT SUMMARY Tumor infiltrating lymphocytes (TILs) represent an accessible biomarker of the tumor-immune microenvironment (TIME) in breast cancer, demonstrating consistent association with response to neoadjuvant chemotherapy and outcomes in HER2-positive and triple-negative breast cancer. Despite efforts to standardize TIL enumeration from hematoxylin and eosin stained tumor slides, TILs have not gained widespread adoption due to inter- observer variability, and time limitations in pathologic assessment, among others. Further, other key elements of the microenvironment, such as tumor-associated macrophages (TAMs), do not yet have standardized approaches for quantification or characterization. As a result, there is no assessment of the TIME for the vast majority of breast cancers diagnosed in the US and around the world. However, the rapid growth of digital pathology offers the potential to leverage computational approaches to overcome these limitations and democratize access to TIL and TAM enumeration. The overall goal of this project is to determine if computational approaches to TILs (existing) and TAMs (to be developed within this grant) are comparable to pathologist- enumerated TILs and TAMs and, further, associated with relevant patient outcomes from two phase III breast cancer clinical trials. Prior to project initiation, we have developed both a compute-intensive artificial intelligence- based TILs approach, an open source software (QuPath)-based TILs approach, and expertise in RNAseq-based immune quantification. We will first focus on TILs - benchmarking the two computational and RNAseq immune approaches against pathologist TIL counts (‘gold standard’) then evaluating association of each with event-free survival in two completed clinical trials (Aim 1). In parallel, we will develop a novel computational approache to enumerate and phenotype TAMs by using immunohistochemical staining for macrophage markers on the same slide with standard H&E, then apply in the same two clinical trials (Aim 2). Our approach is innovative because we will benchmark diverse approaches at scale in relevant clinical studies. The study is significant because we will determine if computational approaches to TILs/TAMs align with pathologist estimates and clinical outcomes, then ensure these algorithms are available to the community. Our long-term goal is to democratize computational TIL and TAM enumeration as pathology decision-support to facilitate integration of accessible tumor-immune microenvironment into clinical trials and care.
Characterization of biofilm formation in shigellosis
Abstract The intestinal pathogen Shigella flexneri is the causative agent of bacillary dysentery and is responsible for more than 250 million cases of dysentery annually, resulting in more than 200,000 deaths. S. flexneri is an intracellular pathogen that invade epithelial cells in the colon and spread from cell to cell. The dissemination process relies on a bacterial adaptor termed IcsA that recruits key components of the actin cytoskeleton and supports actin-based motility. We have recently discovered that in addition of its intracellular role in dissemination, IcsA also support bile salt-dependent biofilm formation. Here, we propose to characterize the structural determinants that support IcsA-mediated bile salts-dependent biofilm formation (Aim1) and the role of IcsA in extracellular and intracellular colonization in an infant rabbit model of shigellosis (Aim2). The characterization of the dual functions of IcsA will provide novel insights into the mechanisms supporting bacillary dysentery in humans.
The quest for brain identification
In the 17th century, physician Marcello Malpighi observed the existence of distinctive patterns of ridges and sweat glands on fingertips. This was a major breakthrough, and originated a long and continuing quest for ways to uniquely identify individuals based on fingerprints, a technique massively used until today. It is only in the past few years that technologies and methodologies have achieved high-quality measures of an individual’s brain to the extent that personality traits and behavior can be characterized. The concept of “fingerprints of the brain” is very novel and has been boosted thanks to a seminal publication by Finn et al. in 2015. They were among the firsts to show that an individual’s functional brain connectivity profile is both unique and reliable, similarly to a fingerprint, and that it is possible to identify an individual among a large group of subjects solely on the basis of her or his connectivity profile. Yet, the discovery of brain fingerprints opened up a plethora of new questions. In particular, what exactly is the information encoded in brain connectivity patterns that ultimately leads to correctly differentiating someone’s connectome from anybody else’s? In other words, what makes our brains unique? In this talk I am going to partially address these open questions while keeping a personal viewpoint on the subject. I will outline the main findings, discuss potential issues, and propose future directions in the quest for identifiability of human brain networks.
Molecular Characterization of Retinal Cell Types: Insights into Evolutionary Origins and Regional Specializations
Epigenetic rewiring in Schinzel-Giedion syndrome
During life, a variety of specialized cells arise to grant the right and timely corrected functions of tissues and organs. Regulation of chromatin in defining specialized genomic regions (e.g. enhancers) plays a key role in developmental transitions from progenitors into cell lineages. These enhancers, properly topologically positioned in 3D space, ultimately guide the transcriptional programs. It is becoming clear that several pathologies converge in differential enhancer usage with respect to physiological situations. However, why some regulatory regions are physiologically preferred, while some others can emerge in certain conditions, including other fate decisions or diseases, remains obscure. Schinzel-Giedion syndrome (SGS) is a rare disease with symptoms such as severe developmental delay, congenital malformations, progressive brain atrophy, intractable seizures, and infantile death. SGS is caused by mutations in the SETBP1 gene that results in its accumulation further leading to the downstream accumulation of SET. The oncoprotein SET has been found as part of the histone chaperone complex INHAT that blocks the activity of histone acetyltransferases suggesting that SGS may (i) represent a natural model of alternative chromatin regulation and (ii) offer chances to study downstream (mal)adaptive mechanisms. I will present our work on the characterization of SGS in appropriate experimental models including iPSC-derived cultures and mouse.
Convex neural codes in recurrent networks and sensory systems
Neural activity in many sensory systems is organized on low-dimensional manifolds by means of convex receptive fields. Neural codes in these areas are constrained by this organization, as not every neural code is compatible with convex receptive fields. The same codes are also constrained by the structure of the underlying neural network. In my talk I will attempt to provide answers to the following natural questions: (i) How do recurrent circuits generate codes that are compatible with the convexity of receptive fields? (ii) How can we utilize the constraints imposed by the convex receptive field to understand the underlying stimulus space. To answer question (i), we describe the combinatorics of the steady states and fixed points of recurrent networks that satisfy the Dale’s law. It turns out the combinatorics of the fixed points are completely determined by two distinct conditions: (a) the connectivity graph of the network and (b) a spectral condition on the synaptic matrix. We give a characterization of exactly which features of connectivity determine the combinatorics of the fixed points. We also find that a generic recurrent network that satisfies Dale's law outputs convex combinatorial codes. To address question (ii), I will describe methods based on ideas from topology and geometry that take advantage of the convex receptive field properties to infer the dimension of (non-linear) neural representations. I will illustrate the first method by inferring basic features of the neural representations in the mouse olfactory bulb.
A draft connectome for ganglion cell types of the mouse retina
The visual system of the brain is highly parallel in its architecture. This is clearly evident in the outputs of the retina, which arise from neurons called ganglion cells. Work in our lab has shown that mammalian retinas contain more than a dozen distinct types of ganglion cells. Each type appears to filter the retinal image in a unique way and to relay this processed signal to a specific set of targets in the brain. My students and I are working to understand the meaning of this parallel organization through electrophysiological and anatomical studies. We record from light-responsive ganglion cells in vitro using the whole-cell patch method. This allows us to correlate directly the visual response properties, intrinsic electrical behavior, synaptic pharmacology, dendritic morphology and axonal projections of single neurons. Other methods used in the lab include neuroanatomical tracing techniques, single-unit recording and immunohistochemistry. We seek to specify the total number of ganglion cell types, the distinguishing characteristics of each type, and the intraretinal mechanisms (structural, electrical, and synaptic) that shape their stimulus selectivities. Recent work in the lab has identified a bizarre new ganglion cell type that is also a photoreceptor, capable of responding to light even when it is synaptically uncoupled from conventional (rod and cone) photoreceptors. These ganglion cells appear to play a key role in resetting the biological clock. It is just this sort of link, between a specific cell type and a well-defined behavioral or perceptual function, that we seek to establish for the full range of ganglion cell types. My research concerns the structural and functional organization of retinal ganglion cells, the output cells of the retina whose axons make up the optic nerve. Ganglion cells exhibit great diversity both in their morphology and in their responses to light stimuli. On this basis, they are divisible into a large number of types (>15). Each ganglion-cell type appears to send its outputs to a specific set of central visual nuclei. This suggests that ganglion cell heterogeneity has evolved to provide each visual center in the brain with pre-processed representations of the visual scene tailored to its specific functional requirements. Though the outline of this story has been appreciated for some time, it has received little systematic exploration. My laboratory is addressing in parallel three sets of related questions: 1) How many types of ganglion cells are there in a typical mammalian retina and what are their structural and functional characteristics? 2) What combination of synaptic networks and intrinsic membrane properties are responsible for the characteristic light responses of individual types? 3) What do the functional specializations of individual classes contribute to perceptual function or to visually mediated behavior? To pursue these questions, we label retinal ganglion cells by retrograde transport from the brain; analyze in vitro their light responses, intrinsic membrane properties and synaptic pharmacology using the whole-cell patch clamp method; and reveal their morphology with intracellular dyes. Recently, we have discovered a novel ganglion cell in rat retina that is intrinsically photosensitive. These ganglion cells exhibit robust light responses even when all influences from classical photoreceptors (rods and cones) are blocked, either by applying pharmacological agents or by dissociating the ganglion cell from the retina. These photosensitive ganglion cells seem likely to serve as photoreceptors for the photic synchronization of circadian rhythms, the mechanism that allows us to overcome jet lag. They project to the circadian pacemaker of the brain, the suprachiasmatic nucleus of the hypothalamus. Their temporal kinetics, threshold, dynamic range, and spectral tuning all match known properties of the synchronization or "entrainment" mechanism. These photosensitive ganglion cells innervate various other brain targets, such as the midbrain pupillary control center, and apparently contribute to a host of behavioral responses to ambient lighting conditions. These findings help to explain why circadian and pupillary light responses persist in mammals, including humans, with profound disruption of rod and cone function. Ongoing experiments are designed to elucidate the phototransduction mechanism, including the identity of the photopigment and the nature of downstream signaling pathways. In other studies, we seek to provide a more detailed characterization of the photic responsiveness and both morphological and functional evidence concerning possible interactions with conventional rod- and cone-driven retinal circuits. These studies are of potential value in understanding and designing appropriate therapies for jet lag, the negative consequences of shift work, and seasonal affective disorder.
Homeostatic Plasticity in Health and Disease
Dr. Davis will present a summary regarding the identification and characterization of mechanisms of homeostatic plasticity as they relate to the control of synaptic transmission. He will then provide evidence of translation to the mammalian neuromuscular junction and central synapses, and provide tangible links to the etiology of neurological disease.
Towards a More Authentic Vision of the (multi)Coding Potential of RNA
Ten of thousands of open reading frames (ORFs) are hidden within transcripts. They have eluded annotations because they are either small or within unsuspected locations. These are named alternative ORFs (altORFs) or small ORFs and have recently been highlighted by innovative proteogenomic approaches, such as our OpenProt resource, revealing their existence and implications in biological functions. Due to the absence of altORFs from annotations, pathogenic mutations within these are being ignored. I will discuss our latest progress on the re-analysis of large-scale proteomics datasets to improve our knowledge of proteomic diversity, and the functional characterization of a second protein coded by the FUS gene. Finally, I will explain the need to map the coding potential of the transcriptome using artificial intelligence rather than with conventional annotations that do not capture the full translational activity of ribosomes.
NMC4 Short Talk: Maggot brain, mirror image? A statistical analysis of bilateral symmetry in an insect brain connectome
Neuroscientists have many questions about connectomes that revolve around the ability to compare networks. For example, comparing connectomes could help explain how neural wiring is related to individual differences, genetics, disease, development, or learning. One such question is that of bilateral symmetry: are the left and right sides of a connectome the same? Here, we investigate the bilateral symmetry of a recently presented connectome of an insect brain, the Drosophila larva. We approach this question from the perspective of two-sample testing for networks. First, we show how this question of “sameness” can be framed as a variety of different statistical hypotheses, each with different assumptions. Then, we describe test procedures for each of these hypotheses. We show how these different test procedures perform on both the observed connectome as well as a suite of synthetic perturbations to the connectome. We also point out that these tests require careful attention to parameter alignment and differences in network density in order to provide biologically meaningful results. Taken together, these results provide the first statistical characterization of bilateral symmetry for an entire brain at the single-neuron level, while also giving practical recommendations for future comparisons of connectome networks.
NMC4 Short Talk: Synchronization in the Connectome: Metastable oscillatory modes emerge from interactions in the brain spacetime network
The brain exhibits a rich repertoire of oscillatory patterns organized in space, time and frequency. However, despite ever more-detailed characterizations of spectrally-resolved network patterns, the principles governing oscillatory activity at the system-level remain unclear. Here, we propose that the transient emergence of spatially organized brain rhythms are signatures of weakly stable synchronization between subsets of brain areas, naturally occurring at reduced collective frequencies due to the presence of time delays. To test this mechanism, we build a reduced network model representing interactions between local neuronal populations (with damped oscillatory response at 40Hz) coupled in the human neuroanatomical network. Following theoretical predictions, weakly stable cluster synchronization drives a rich repertoire of short-lived (or metastable) oscillatory modes, whose frequency inversely depends on the number of units, the strength of coupling and the propagation times. Despite the significant degree of reduction, we find a range of model parameters where the frequencies of collective oscillations fall in the range of typical brain rhythms, leading to an optimal fit of the power spectra of magnetoencephalographic signals from 89 heathy individuals. These findings provide a mechanistic scenario for the spontaneous emergence of frequency-specific long-range phase-coupling observed in magneto- and electroencephalographic signals as signatures of resonant modes emerging in the space-time structure of the Connectome, reinforcing the importance of incorporating realistic time delays in network models of oscillatory brain activity.
Anatomical and functional characterization of the neuronal circuits underlying ejaculation
During sexual behavior, copulation related sensory information and modulatory signals from the brain must be integrated and converted into the motor and secretory outputs that characterize ejaculation (Lenschow and Lima, Current Opinion in Neurobiology, 2020). Studies in humans and rats suggest the existence of interneurons in the lumbar spinal cord that mediates that step: the spinal ejaculation generator (SEG). My work aimed at gaining mechanistic insights about the neuronal circuits controlling ejaculation thereby applying cutting-edge techniques. More specifically, we mapped anatomically and functionally the spinal circuit for ejaculation starting from the main muscle being involved in sperm expulsion: the bulbospongiosus muscle (BSM). Combining viral tracing strategies with electrophysiology, we specifically show that the BSM motoneurons receive direct synaptic input from a group of interneurons located in between lumbar segment 2 and 3 and expressing the peptide galanin. Electrically and optogenetically activating the galanin positive cells (the SEG) lead to the activation of the motoneurons innervating the BSM and the muscle itself. Finally, inhibition of SEG cells using DREADDs (Designer Receptors Exclusively Activated by Designer Drugs) in sexual behaving animals is currently conducted to reveal whether ejaculation can be prevented.
From genetics to neurobiology through transcriptomic data analysis
Over the past years, genetic studies have uncovered hundreds of genetic variants to be associated with complex brain disorders. While this really represents a big step forward in understanding the genetic etiology of brain disorders, the functional interpretation of these variants remains challenging. We aim to help with the functional characterization of variants through transcriptomic data analysis. For instance, we rely on brain transcriptome atlases, such as Allen Brain Atlases, to infer functional relations between genes. One example of this is the identification of signaling mechanisms of steroid receptors. Further, by integrating brain transcriptome atlases with neuropathology and neuroimaging data, we identify key genes and pathways associated with brain disorders (e.g. Parkinson's disease). With technological advances, we can now profile gene expression in single-cells at large scale. These developments have presented significant computational developments. Our lab focuses on developing scalable methods to identify cells in single-cell data through interactive visualization, scalable clustering, classification, and interpretable trajectory modelling. We also work on methods to integrate single-cell data across studies and technologies.
A geometric framework to predict structure from function in neural networks
The structural connectivity matrix of synaptic weights between neurons is a critical determinant of overall network function. However, quantitative links between neural network structure and function are complex and subtle. For example, many networks can give rise to similar functional responses, and the same network can function differently depending on context. Whether certain patterns of synaptic connectivity are required to generate specific network-level computations is largely unknown. Here we introduce a geometric framework for identifying synaptic connections required by steady-state responses in recurrent networks of rectified-linear neurons. Assuming that the number of specified response patterns does not exceed the number of input synapses, we analytically calculate all feedforward and recurrent connectivity matrices that can generate the specified responses from the network inputs. We then use this analytical characterization to rigorously analyze the solution space geometry and derive certainty conditions guaranteeing a non-zero synapse between neurons.
Deciphering the Dynamics of the Unconscious Brain Under General Anesthesia
General anesthesia is a drug-induced, reversible condition comprised of five behavioral states: unconsciousness, amnesia (loss of memory), antinociception (loss of pain sensation), akinesia (immobility), and hemodynamic stability with control of the stress response. Our work shows that a primary mechanism through which anesthetics create these altered states of arousal is by initiating and maintaining highly structured oscillations. These oscillations impair communication among brain regions. We illustrate this effect by presenting findings from our human studies of general anesthesia using high-density EEG recordings and intracranial recordings. These studies have allowed us to give a detailed characterization of the neurophysiology of loss and recovery of consciousness due to propofol. We show how these dynamics change systematically with different anesthetic classes and with age. As a consequence, we have developed a principled, neuroscience-based paradigm for using the EEG to monitor the brain states of patients receiving general anesthesia. We demonstrate that the state of general anesthesia can be rapidly reversed by activating specific brain circuits. Finally, we demonstrate that the state of general anesthesia can be controlled using closed loop feedback control systems. The success of our research has depended critically on tight coupling of experiments, signal processing research and mathematical modeling.
Defining new multimodal neuroimaging marker for grey matter characterization
The human cortical ribbon varies during the lifespan, from childhood to senescence. To study the effects of genetic and environmental factors on these dynamics, one needs to measure specific phenotypes (cortical volume, surface area, thickness, new neuroimaging phenotypes such as intracortical myelination or multimodal ones based on their combination, or their asymmetries) that characterize the cerebral grey matter accurately
Functional characterization and therapeutic targeting of gene regulatory elements
Residual population dynamics as a window into neural computation
Neural activity in frontal and motor cortices can be considered to be the manifestation of a dynamical system implemented by large neural populations in recurrently connected networks. The computations emerging from such population-level dynamics reflect the interaction between external inputs into a network and its internal, recurrent dynamics. Isolating these two contributions in experimentally recorded neural activity, however, is challenging, limiting the resulting insights into neural computations. I will present an approach to addressing this challenge based on response residuals, i.e. variability in the population trajectory across repetitions of the same task condition. A complete characterization of residual dynamics is well-suited to systematically compare computations across brain areas and tasks, and leads to quantitative predictions about the consequences of small, arbitrary causal perturbations.
Biomedical Image and Genetic Data Analysis with machine learning; applications in neurology and oncology
In this presentation I will show the opportunities and challenges of big data analytics with AI techniques in medical imaging, also in combination with genetic and clinical data. Both conventional machine learning techniques, such as radiomics for tumor characterization, and deep learning techniques for studying brain ageing and prognosis in dementia, will be addressed. Also the concept of deep imaging, a full integration of medical imaging and machine learning, will be discussed. Finally, I will address the challenges of how to successfully integrate these technologies in daily clinical workflow.
K+ Channel Gain of Function in Epilepsy, from Currents to Networks
Recent human gene discovery efforts show that gain-of-function (GOF) variants in the KCNT1gene, which encodes a Na+-activated K+ channel subunit, cause severe epilepsies and other neurodevelopmental disorders. Although the impact of these variants on the biophysical properties of the channels is well characterized, the mechanisms that link channel dysfunction to cellular and network hyperexcitability and human disease are unknown. Furthermore, precision therapies that correct channel biophysics in non-neuronal cells have had limited success in treating human disease, highlighting the need for a deeper understanding of how these variants affect neurons and networks. To address this gap, we developed a new mouse model with a pathogenic human variant knocked into the mouse Kcnt1gene. I will discuss our findings on the in vivo phenotypes of this mouse, focusing on our characterization of epileptiform neural activity using electrophysiology and widefield Ca++imaging. I will also talk about our investigations at the synaptic, cellular, and circuit levels, including the main finding that cortical inhibitory neurons in this model show a reduction in intrinsic excitability and action potential generation. Finally, I will discuss future directions to better understand the mechanisms underlying the cell-type specific effects, as well as the link between the cellular and network level effects of KCNT1 GOF.
Human reconstruction of local image structure from natural scenes
Retinal projections often poorly represent the structure of the physical world: well-defined boundaries within the eye may correspond to irrelevant features of the physical world, while critical features of the physical world may be nearly invisible at the retinal projection. Visual cortex is equipped with specialized mechanisms for sorting these two types of features according to their utility in interpreting the scene, however we know little or nothing about their perceptual computations. I will present novel paradigms for the characterization of these processes in human vision, alongside examples of how the associated empirical results can be combined with targeted models to shape our understanding of the underlying perceptual mechanisms. Although the emerging view is far from complete, it challenges compartmentalized notions of bottom-up/top-down object segmentation, and suggests instead that these two modes are best viewed as an integrated perceptual mechanism.
Functional characterization of human iPSC-derived neurons at single-cell resolution
Recent developments in induced pluripotent stem cell (iPSC) technology have enabled easier access to human cells in vitro. With increasing availability of human iPSC-derived neurons, both healthy and disease cell lines, screening compounds for neurodegenerative diseases on human cells can potentially be performed in the earlier stages of drug discovery. To accelerate the functional characterization of iPSC-derived neurons and the effect of compounds, reproducible and relevant results are necessary. In this webinar, the speakers will: Introduce high-resolution functional imaging of human iPSC-derived neurons Showcase how to extract functional features of hundreds of cells in a cell culture sample label-free Discuss electrophysiological parameters for characterizing the differences among several human neuronal cell lines
IMMUNOHISTOCHEMICAL CHARACTERIZATION OF THE RETINA–OPTIC NERVE–BRAIN VISUAL PATHWAY IN THE AFRICAN TREE SQUIRREL
FENS Forum 2026
Anatomical characterization of the Frontal Voice Areas based on the individual sulcal anatomy
Characterization of the antiapoptotic and neuroprotective effect of dapsone in a model of status epilepticus induced with kainic acid in rats
Analysis of the intraamygdalar connectivity and morphological characterization of principal neurons in the basolateral amygdala
Behind sporadic ALS: a biophysical characterization of motor neurons in health and disease
Anatomical and Electrophysiological Characterization of Hypothalamic Neurons Involved in Female Sexual Behavior
Anatomical and functional characterization of Amygdala-Striatal circuits
Behavioral and electrophysiological characterization of different functional regions of the subthalamic nucleus in healthy non-human primates
Behavioral and Molecular Characterization of a Novel Mouse Model of HERV-W Envelope Protein Expression
Behavioural and neuropathological characterization of a rat model of resilience in the field of Alzheimer’s Disease
Characterization of disease-associated microglia in social deficits linked to early life adversity
Beyond retigabine: design, synthesis, and pharmacological characterization of a potent and chemically-stable neuronal Kv7 channels activator with anticonvulsant activity
Cell-type specific and molecular characterization of DEPDC5-mediated epilepsy
Characterization of anatomical and functional vestibulospinal pathways in larval Xenopus laevis
Alzheimer disease: functional characterization of KLVFF activity on native nicotinic receptors
Characterization of astrocyte reactivity in a model of encephalopathy of prematurity
Characterization of axo-axonic interneurons targeted with the Nkx2.1Cre-ER mouse line
Characterization of brain networks using functional ultrasound imaging
Characterization of circuitry functions involving the paraventricular nucleus of the thalamus (PVT) in social behaviors
Characterization of conditional bistable neurons, the putative substrate underlying parametric working memory in the prefrontal cortex
Characterization of conscious and unconscious brain patterns in rats
Characterization of directionally tuned signals in mouse pre- and postsubiculum during passive rotation using high-density probes
Characterization of neuronal resonance and inter-areal transfer using optogenetics
COSYNE 2022
Characterization of dysfunctional oligodendrocytes at single-cell resolution
Characterization of the earliest thalamocortical interactions in the human fetal brain
Characterization of the expression of Transcription factor 4 mRNA and protein isoforms in the developing and adult rodent and human brain and peripheral tissues
Characterization of extracellular vesicles released from spinal cord astrocytes of late symptomatic SOD1G93A mouse model of amyotrophic lateral sclerosis
Characterization of a habenula-driven serotonergic recurrent inhibitory network in dorsal raphe nucleus
Characterization of hippocampal neuronal activity during the first postnatal week in-vivo
Characterization of hiPSC-derived endothelial cells role in the formation of cerebral amyloid angiopathy related to Alzheimer’s disease
Characterization of human induced pluripotent stem cell-derived microglia from a familial amyotrophic lateral sclerosis patient
Characterization of human Tau protein in yeast cells under normal and stress conditions
Characterization of impaired motor movements in a mouse model of freezing of gait
Characterization of a KCNA2 loss-of-function mouse model
Characterization of long projecting propriospinal neurons in the mouse spinal cord
Characterization of Long-range Monoaminergic Neuromodulatory Projections in Focal Cortical Dysplasia
Characterization of memory recall-associated transcriptional programs in wildtype and Angelman syndrome model mice
Characterization of microglial cells in a model of selective neuronal loss: the Purkinje Cell Degeneration mouse
Characterization of the molecular mechanisms underlying neuromuscular junction defects and cell death in FUS and sporadic ALS
Bayesian active learning for closed-loop synaptic characterization
COSYNE 2022
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