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Defining Microbial and Host Pathways Driving Asymptomatic C. difficile Colonization Associated with Aging and High-Sugar Diets
SUMMARY Clostridioides difficile infection (CDI) is a leading cause of healthcare-associated diarrhea, with rising incidence in community settings and a growing burden of asymptomatic colonization. Asymptomatic car- riers, particularly among the elderly and individuals consuming high-sugar diets, represent a critical but underexplored reservoir for transmission and disease progression. This proposal introduces novel, anti- biotic-independent mouse models demonstrating that both dietary sugar and aging independently pro- mote asymptomatic C. difficile colonization. We hypothesize that these factors disrupt colonization re- sistance (CR) through distinct but overlapping microbial, metabolic, and immune pathways. In Aim 1, we will define how traditional and emerging dietary sugars alter the gut environment to permit C. difficile colonization using in vitro bioreactors and in vivo models. Aim 2 will identify age-associated changes in microbiota and mucosal immunity that impair CR, using longitudinal studies and fecal micro- biota transfer. Aim 3 will functionally validate C. difficile genes upregulated during asymptomatic carriage using CRISPR-Cas9 mutants in both sugar- and age-induced models. This integrative, multi-omics approach will uncover the mechanisms enabling asymptomatic colonization and identify microbial and host targets for intervention. The findings will inform microbiome-based strat- egies to prevent CDI in vulnerable populations and shift current paradigms in CDI risk assessment and prevention.
TAR RNA binding to INI1/SMARCB1 and its role in HIV-1 transcription and latency reactivation
Abstract The goal of this application is to study the role of interplay between the components of chromatin remodeling SWI/SNF (BAF complex) and HIV-1 transcription machinery, focusing on the interaction of a BAF component, INI1 (Integrase Interactor 1) with TAR RNA. HIV-1 reservoirs are a mixture of latent cells harboring proviruses silenced at transcriptional level. Cure strategies need a deeper understanding of HIV-1 transcriptional regulation. HIV-1 transcription, initiated by RNA Pol II, pauses producing short TAR transcripts. pTEFb recruitment to TAR by Tat overcomes this transcriptional pause, facilitating elongation. Beyond Tat, the action of chromatin remodeling complexes (CRCs) is required to facilitate elongation. The BAF complexes CBAF and PBAF play distinct roles. While CBAF represses proviral transcription by maintaining nucleosomes in an unfavorable state, PBAF remodels nucleosomes to facilitate elongation. INI1 is a component of both CBAF and PBAF, and its role in transcription is not fully understood. INI1 was identified as a binding partner for HIV-1 integrase (IN) and exerts multifacted roles in virus assembly, production and morphogenesis. INI1 has multiple functional domains. IN binding Rpt1 domain structurally mimics TAR RNA & is necessary for late events. We have made a novel observation that another domain of INI1, the N-terminal Winged Helix DNA binding domain (WHD) specifically binds to TAR RNA and that this interaction is necessary for mediating HIV-1 transcriptional elongation. These exciting results suggest that different functional domains of INI1(Rpt1 and WHD) involved in “TAR RNA mimicry” or “TAR RNA binding” regulate distinct stages of replication. We hypothesize that INI1 WHD domain-TAR interaction is necessary for recruitment of PBAF to HIV-1 LTR for transcriptional elongation and latency reactivation. Disrupting this interaction results in transcriptional repression. We will investigate the role of this novel INI1:TAR RNA interaction in HIV-1 transcription and latency reactivation. This is a multi-PI application involving Drs. Kalpana (HIV-1 virologist), Heng (NMR biophysicist) and Zou (computational biologist/protein-RNA structure). In Aim 1, we will characterize INI1-WHD:TAR interaction in vitro and in vivo via molecular/genetic analyses (Kalpana/Heng). We will employ alanine scanning mutagenesis based on WHD NMR structure to test WHD:TAR interaction. We will use biophysical & biochemical approaches to probe TAR structural elements required for this interaction. In Aim 2, we will employ computational modeling and NMR to determine the structure of INI1- WHD:TAR RNA complex (Zou/Heng). In Aim 3, we will determine the role of INI1:TAR interactions in HIV-1 transcription, latency reactivation and mechanism of action (Kalpana). We will analyze the effect of TAR- Interaction-Defective (TID) INI1 mutants on transcription of LTR-reporters and full-length HIV in INI1-/- cells. Latent cells in which TID-INI1 mutants are knocked in (KI) will be used to assess effect on reactivation via RNA-FISH and qRT-PCR assays. Our studies will establish INI1:TAR interaction as a drug target. Inhibiting this interaction could block latency reactivation promoting deep latency and advancing cure strategies.
ATPase Chromatin Remodeling Complexes as Modulators of HIV-1 Latency and Therapeutic Targets
Abstract Significance: HIV persists in long-lived CD4⁺ T cell reservoirs despite suppressive ART, as integrated proviruses remain poised for reactivation. Chromatin remodeling is a central barrier to durable silencing, yet most studies have focused on SWI/SNF family members. The roles of non- SWI/SNF remodelers remain poorly defined, limiting our ability to rationally design host-directed “block-and-lock” cure strategies. Our unbiased shRNA screen of all 16 human remodeler ATPases identified EP400, CHD1, and CHD9 as repressors and INO80A, SMARCA5, and CHD2 as activators, establishing chromatin remodeling as a key determinant of HIV latency. Innovation: Our prior studies revealed that the p400 complex regulates HIV transcription through dual mechanisms: directly, by engaging Tat via the DMAP1 subunit to block Tat-TAR RNA interactions and restrict p-TEFb recruitment; and indirectly, by altering host transcriptional programs that control T cell activation states. Building on this mechanistic precedent and methodological platform, we now focus on INO80A, SMARCA5, CHD1, and CHD2, remodelers from distinct ATPase families that govern Tat-independent checkpoints at initiation, pause release, and elongation. Methodologically, we will apply TurboID-ChAP-MS (locus-specific proteomics), BEM-seq (single-nucleosome mapping), and degron-mediated acute depletion with ATPase-dead rescue to interrogate remodeler function with unprecedented resolution. Approach: Aim 1 will define the ATPase requirement and transcriptional checkpoints regulated by INO80A, SMARCA5, CHD1, and CHD2 using degron/CRISPR perturbations, ChIP-seq, nascent RNA profiling, and nucleosome mapping. Aim 2 will characterize remodeler-specific complexes and Tat dependence at the HIV promoter via TurboID proximity labeling integrated with chromatin affinity purification-mass spectrometry. Aim 3 will test combinatorial perturbations in Jurkat and primary CD4⁺ T cell latency models, including ART-suppressed donor cells, to identify synergistic “block-and-lock” strategies that enforce durable proviral silencing. Impact: By defining remodeler-specific mechanisms at discrete transcriptional checkpoints and leveraging their enzymatic, druggable activities, this work will establish chromatin remodeling as a therapeutic axis for durable HIV suppression and functional cure.
Neutralizing persistent IFN-I to improve HIV-specific CAR T cell therapy
PROJECT SUMMARY A critical hurdle to further improving the quality of life for people living with HIV (PLWH) is the need to resolve the residual immune activation and inflammation that persists even in those taking effective antiretroviral therapy (ART), which suppresses HIV replication. This unresolved and persistent immune activation is associated with increased type-I interferon (IFN-I) signaling, and increased incidence of comorbidities. Encouragingly, reports demonstrate that blocking IFN-I signaling in animal models of HIV infection can reduce HIV reservoirs and restore T cell immune function. We hypothesize that blocking IFN-I would likewise augment engineered T cell-based therapies against HIV, such as chimeric antigen receptor (CAR) T cells. Our prior work has demonstrated that when engineered to express both the 4-1BB and CD28 costimulatory domains and protected from HIV infection, HIV-specific CD4 ectodomain CAR T cells can reduce acute viremia, prevent CD4+ T cell loss, and reduce viral burden in the tissues of HIV-infected humanized mice. However, the reduction of plasma viral loads was ultimately transient, suggesting that the potency of HIV-specific CAR T cells should be further optimized for clinical translation. Our preliminary data highlights interferon-beta (IFNb) as a key immunosuppressive IFN-I negatively regulating CAR T cell proliferation, and we demonstrate that neutralizing IFNb in vivo enhanced the engraftment and persistence of HIV-specific CAR T cells adoptively transferred into HIV-infected ART- suppressed humanized mice. This proposal will interrogate whether IFNb neutralization augments CAR T cell therapy through 1) identifying the mechanism(s) by which chronic IFNb exposure mediates HIV-specific CAR T cell dysfunction, and 2) determining the effect of neutralizing IFNb on CAR T cell function and persistence in HIV infection in vivo. The proposed aims seek to develop the neutralization of IFNb as a novel immunotherapy approach to maximize the potency of HIV-specific CAR T cells aimed at achieving a functional HIV cure.
Neurobiological constraints on learning: bug or feature?
Understanding how brains learn requires bridging evidence across scales—from behaviour and neural circuits to cells, synapses, and molecules. In our work, we use computational modelling and data analysis to explore how the physical properties of neurons and neural circuits constrain learning. These include limits imposed by brain wiring, energy availability, molecular noise, and the 3D structure of dendritic spines. In this talk I will describe one such project testing if wiring motifs from fly brain connectomes can improve performance of reservoir computers, a type of recurrent neural network. The hope is that these insights into brain learning will lead to improved learning algorithms for artificial systems.
Heterogeneity and non-random connectivity in reservoir computing
Reservoir computing is a promising framework to study cortical computation, as it is based on continuous, online processing and the requirements and operating principles are compatible with cortical circuit dynamics. However, the framework has issues that limit its scope as a generic model for cortical processing. The most obvious of these is that, in traditional models, learning is restricted to the output projections and takes place in a fully supervised manner. If such an output layer is interpreted at face value as downstream computation, this is biologically questionable. If it is interpreted merely as a demonstration that the network can accurately represent the information, this immediately raises the question of what would be biologically plausible mechanisms for transmitting the information represented by a reservoir and incorporating it in downstream computations. Another major issue is that we have as yet only modest insight into how the structural and dynamical features of a network influence its computational capacity, which is necessary not only for gaining an understanding of those features in biological brains, but also for exploiting reservoir computing as a neuromorphic application. In this talk, I will first demonstrate a method for quantifying the representational capacity of reservoirs without training them on tasks. Based on this technique, which allows systematic comparison of systems, I then present our recent work towards understanding the roles of heterogeneity and connectivity patterns in enhancing both the computational properties of a network and its ability to reliably transmit to downstream networks. Finally, I will give a brief taster of our current efforts to apply the reservoir computing framework to magnetic systems as an approach to neuromorphic computing.
Ask SAC: Be Neurocurious with Our Mentors!
Through Ask SAC sessions we aim to bridge the gap between our Scientific Advisory Committe and our budding neuroscientists! After completing her Masters in Neuroscience from the University of Manchester, UK and a professional stint at Pfizer, Ritwika joined Reservoir to make a difference in neurology. She develops creative strategies to assist the neurodiverse community and facilitate better healt support functions. Join us, to ask her anything and everything related to a career in neuroscience!
The emergence and modulation of time in neural circuits and behavior
Spontaneous behavior in animals and humans shows a striking amount of variability both in the spatial domain (which actions to choose) and temporal domain (when to act). Concatenating actions into sequences and behavioral plans reveals the existence of a hierarchy of timescales ranging from hundreds of milliseconds to minutes. How do multiple timescales emerge from neural circuit dynamics? How do circuits modulate temporal responses to flexibly adapt to changing demands? In this talk, we will present recent results from experiments and theory suggesting a new computational mechanism generating the temporal variability underlying naturalistic behavior and cortical activity. We will show how neural activity from premotor areas unfolds through temporal sequences of attractors, which predict the intention to act. These sequences naturally emerge from recurrent cortical networks, where correlated neural variability plays a crucial role in explaining the observed variability in action timing. We will then discuss how reaction times can be accelerated or slowed down via gain modulation, flexibly induced by neuromodulation or perturbations; and how gain modulation may control response timing in the visual cortex. Finally, we will present a new biologically plausible way to generate a reservoir of multiple timescales in cortical circuits.
The emergence and modulation of time in neural circuits and behavior
Spontaneous behavior in animals and humans shows a striking amount of variability both in the spatial domain (which actions to choose) and temporal domain (when to act). Concatenating actions into sequences and behavioral plans reveals the existence of a hierarchy of timescales ranging from hundreds of milliseconds to minutes. How do multiple timescales emerge from neural circuit dynamics? How do circuits modulate temporal responses to flexibly adapt to changing demands? In this talk, we will present recent results from experiments and theory suggesting a new computational mechanism generating the temporal variability underlying naturalistic behavior. We will show how neural activity from premotor areas unfolds through temporal sequences of attractors, which predict the intention to act. These sequences naturally emerge from recurrent cortical networks, where correlated neural variability plays a crucial role in explaining the observed variability in action timing. We will then discuss how reaction times in these recurrent circuits can be accelerated or slowed down via gain modulation, induced by neuromodulation or perturbations. Finally, we will present a general mechanism producing a reservoir of multiple timescales in recurrent networks.
One-shot learning of paired associations by a reservoir computing model with Hebbian plasticity
COSYNE 2022
One-shot learning of paired associations by a reservoir computing model with Hebbian plasticity
COSYNE 2022
A reservoir of timescales in random neural networks
COSYNE 2022
A reservoir of timescales in random neural networks
COSYNE 2022
Slow transition to chaos and robust reservoir computing in recurrent neural networks with heavy-tailed distributed synaptic weights
COSYNE 2025
Sparse neural engagement in connectome-based reservoir computing networks
COSYNE 2025
Reservoir computing using cultured neuronal networks with modular topology
FENS Forum 2024
A Reservoir Model of Explicit Human Intelligence
Neuromatch 5
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