Harvard University

NIH Research Projects · FY 2026 · 2021-08

ABSTRACT Our research approach is to uncover receptors and signaling mechanisms in specialized cell types as a means to understand mechanistic underpinnings of various physiological systems. We then compare discovered mechanisms across cells, organs and organisms to reveal fundamental principles in signal transduction. As an example of this approach, this MIRA proposal leverages two uniquely-suited model systems to broadly ask how cells detect and integrate signals to mediate specific functions: 1) Octopuses possess uniquely hyperactive adenosine-to-inosine (A-to-I) mRNA editing that enables a single gene to produce numerous distinct proteins. The physiological stimuli that trigger editing and the organismal outcomes of editing are not well understood. Here, we will exploit state-dependent RNA editing of recently discovered “taste by touch” chemotactile receptors (CRs) to ask how signal detection and transduction in single cells is regulated by distinct organismal states. We will use amplicon sequencing to profile RNA editing of CRs in hungry animals and those mothering eggs. A combination of electrophysiology, cryo-EM structural biology, and unique autonomous arm behavior will then be used to test if RNA editing generates receptor variants with different functional properties to facilitate state- dependent predation or egg care. This study will exploit a unique biological system to broadly understand how organisms use adaptive protein synthesis to synergistically alter single protein, cellular, and organismal activity. 2) Animals use multicellular systems to detect stimuli, transmit information among functionally distinct cells, and carry out coordinated behaviors. Yet animals evolved from unicellular eukaryotes, in which a single cell can detect diverse stimuli to mediate specific behaviors without need for multicellularity. The closest living relatives of animals are choanoflagellates (choanos), unicellular organisms that also have simple multicellular forms. Here, we propose to exploit choanos as a model to investigate how unicellular organisms elicit specific responses to a range of environmental cues, and how these signaling systems evolve in conjunction with the innovation of multicellularity. We first used gene family evolution analyses to discover of a novel receptor class in choanos that we will characterize using ecologically relevant natural products coupled with structural and functional methods. We will then exploit these proteins to explore how receptor families diversify in response to divergent environments to mediate new cellular behaviors. This strategy will allow us to ask how distinct receptors control unicellular behavior in diverse organisms in response to specific bacterial prey cues, using electrophysiology, genetically encoded Ca2+ indicator strains, and single cell tracking. Finally, we will explore how choanos integrate simultaneous stimuli in both unicellular and multicellular forms to understand how the evolution of multicellularity drives the innovation of integrative signaling essential to the origin of organ systems in animals. Together, these integrative studies span multiple specialized cell types, tissues, and organisms to increase our understanding of the basic cell biology underlying signal transduction.

NIH Research Projects · FY 2025 · 2021-06

The overarching goal of this research is to develop predictive multiscale biophysical models of adaptive evolutionary dynamics. The new concept of Biophysical Fitness Landscape (BFL) is a map of protein/nucleic acid molecular properties to fitness. We demonstrated the conceptual validity of BFL by discovering a simple and accurate quantitative relationship between fitness of E. coli and molecular properties of important core metabolic enzymes. This finding transforms the concept of fitness landscape from an artful metaphor into a quantitative tractable tool to predict the genotype-phenotype relationship (GPR). Here we take these findings as a foundation to further extend our understanding of interplay between biophysical and population factors that determine the dynamics and outcome of adaptive evolution. We will apply biophysical analysis, automated robotics setup along with protein engineering and genomic editing tools to explore evolutionary dynamics in laboratory experiments under conditions that allow tight control on all scales – from molecules to populations. As a key model we carry out a set of evolution experiments with adapting populations of E. coli escaping from antibiotic stress and structural instability of the essential protein Dihydrofolate Reductase. We characterize on all scales – genotyping, molecular traits, systems proteomics and metabolomics and population - multiple evolutionary paths to resistance and adaption of emerging bacterial strains and determine at which level of description (genotype, biophysical properties, systems responses) evolution becomes reproducible – and by implication predictable. We model the evolutionary dynamics using multiscale models where cytoplasm of model cells is presented in a biophysically realistic manner, and fitness of model organisms is predicted from its molecular traits using experimentally derived BFL. Comprehensive molecular mapping of possible escape routes will provide an opportunity to rationally design new class of compounds – “evolution drugs” - that comprehensively block pathogen’s resistance. In a related effort we will explore the biophysical underpinnings of codon adaptation to discern their effects on mRNA and cotranslational protein folding. A tight integration between theory and experiment will provide an opportunity to develop predictive evolutionary models of ever increasing accuracy and realism. Progress along these lines will transform our approaches to study evolutionary dynamics from descriptive into predictive and quantitative, which will be instrumental to the development of novel approaches to fight antibiotic resistance and, potentially, viral escape from stressors such as drugs and immune response.

NIH Research Projects · FY 2025 · 2021-04

PROJECT SUMMARY/ABSTRACT The U.S. service sector employs 27 million workers, 20% of the U.S. workforce. Abetted by new technologies, employers in the service sector have embraced surveillance and sanctioning, which affect time and pace of tasks on the job, unpredictable and constrained scheduling practices, which affect the organization of time on and off work, and automation, which shapes longer-term expectations for the future and job insecurity. We refer to these working conditions, collectively, as temporal dimensions of job quality to draw a contrast with purely economic dimensions of job quality. Although prior research has established a robust relationship between other aspects of job conditions and health, there is a gap in knowledge about how these new and increasingly prevalent workplace practices affect worker health and healthy aging. One important reason for this gap is a lack of suitable existing data containing information on both these emergent workplace practices and workers’ health outcomes, yet policy makers have already begun to take action to regulate these practices. There is thus a critical need to collect new data that will allow researchers to estimate the health effects of exposure to these temporal dimensions of job quality for workers across the life course. The proposed research expands upon an innovative method for collecting survey data at scale, at low-cost, and with speed from a target population of service-sector workers. We use the Facebook advertising platform to purchase and place survey recruitment advertisements in the mobile and desktop newsfeeds of Facebook and Instagram users, targeting those who work in retail and fast food. This approach allows us to target users with particular employers and/or in specific localities. We propose to collect repeated cross-sectional and longitudinal survey data from 90,000 workers across the country. The proposed research uses these data and methods to accomplish three aims. First, we estimate the relationship between emergent temporal dimensions of job quality and worker health and healthy aging. The data collection is designed to capitalize on natural experiments to provide rigorous evidence on the health effects of temporally precarious work. One set of analyses will exploit city and company policy changes to use rigorous difference-in-differences and instrumental variable methods to estimate causal effects of job quality on health. Second, we assess whether the health consequences of surveillance and sanctioning, schedule unpredictability and constraint, and automation vary across the life course. Finally, we will assess the social and public supports that may buffer and mitigate the harmful health effects of these temporal dimensions of job quality. In sum, we deploy an innovative data collection approach combined with rigorous estimation to take advantage of natural experiments implemented when labor laws or company practices change. The significant contributions of our project entail testing how new dimensions of job quality affect health, estimating differential vulnerabilities across the life course, and gauging the importance of protective supports and policies. Collectively, this research provides key missing evidence on health impacts of job quality.

NIH Research Projects · FY 2025 · 2021-04

PROJECT SUMMARY Assisted Reproduction Technology (ART) is a clinical treatment for infertile couples who want to achieve a pregnancy. In ART, embryologists fertilize eggs retrieved from the patient or a donor, culture the resulting embryos in vitro, and then transfer the selected embryo(s) to the mother's uterus. While ART is responsible for 1.9% of babies born in the United States as of 2018, selecting which embryo to transfer is a significant challenge. The difficulty comes from the complexity of confounding factors and the lack of understanding of human pre-implantation embryo development. Because of this difficulty, multiple embryos are often transferred to increases the potential of success, resulting in multiple pregnancy rates of nearly 20%, which can lead to significant morbidity and medical expenses to patients. The ideal is to transfer only a single embryo, but this necessitates the ability to select the best embryo from a cohort. Here, we propose to create a clinical decision support system to improve embryo selection in ART. To this end, we will develop novel deep learning models for robust embryo feature extraction and interactive data visualization methods for human-in-the-loop analysis. We will first extract and analyze visual features from routinely collected images of embryos. We will then combine these visual features with patients' electronic health record (EHR) data to develop interpretable computation models that score embryos on their viability. We plan to integrate our machine learning solutions into an easily accessible cloud service platform that will be adaptable across clinics to improve ART embryo selection and clinical data analysis. Our research goals will be achieved by novel machine learning-based models for morphological feature extrac- tion and importance estimation of each confounding factor and a clinical decision support system for ART. For morphological feature extraction, we plan to conduct semi-supervised learning of convolutional neural networks to minimize manual labeling that requires extensive human effort. Our feature extraction model will be the first comprehensive classification and segmentation method for ART. To aid in embryo selection, we will develop novel deep learning-based models to predict probabilities of achieving pregnancy by accepting visual features and EHR data as the input. We will also develop visual analytic tools that allow analysts to better understand and steer these deep learning models. We will estimate the importance of each input interpretable factor in embryo selection to explain the prediction to embryologists. Finally, we will develop EmbryoProfiler, a clinical decision support system for ART, that combines our machine learning-based models with a user-facing suite of visual analytic tools to support user guidance and clinical decision making. EmbryoProfiler will help facilitate daily operation in clinics, foster human-guided decision making, enrich data-driven embryo analysis, and enhance the ability to select the developmentally most competent embryo for transfer to improve ART success rates. Our project will create state-of-the-art analysis approaches for ART clinicians.

NIH Research Projects · FY 2025 · 2021-04

7. PROJECT SUMMARY/ABSTRACT Children and adolescents (herein “youths”) treated in outpatient mental health care span a broad range of problems and disorders, with substantial comorbidity, and their most pressing problems and treatment needs may shift during treatment. These challenges may be addressed by treatment that is flexible and transdiagnostic (i.e., applicable to multiple mental health problems and disorders). A recent transdiagnostic treatment, FIRST, created in collaboration with community practitioners and intervention scientists, uses a principle-based approach to support efficient learning and implementation by clinicians. FIRST is built upon five empirically supported principles of change (e.g., calming, problem solving), each applicable to treatment of depression, anxiety/OCD, trauma, and misconduct. Three open benchmarking trials of FIRST, using low-cost clinician training and group consultation, have shown steep slopes of clinical improvement in youths treated in outpatient clinics. The proposed randomized controlled effectiveness trial will provide a more definitive test of FIRST, an initial investigation of a candidate mechanism of change, and tests of therapist characteristics that may predict and moderate implementation of evidence-based practices. The sample will be ethnically and economically diverse youths, aged 8-15, from four community clinics—two in greater Boston MA, two in greater Austin TX—all referred by their families and all showing elevated depression, anxiety/OCD, post-traumatic stress, or conduct problems. Clinicians within each clinic will be randomly assigned to learn and use FIRST or to employ Usual Care (UC), and youths will be randomized to treatment by FIRST or UC clinicians. Clinical outcomes will include change on standardized measures of mental health and on severity of the specific problems identified as most important by each youth and each caregiver at baseline. Study measures will include a proposed mechanism—regulation of negative emotions— thought to be responsive to treatment and responsible for changes in mental health. Analyses will assess whether treatment with FIRST impacts regulation, and whether improved regulation accounts for outcomes of FIRST treatment relative to UC. Finally, the study will investigate whether clinicians’ baseline knowledge of, attitudes toward, and motivation to use evidence-based practices predicts or moderates their implementation of such practices in psychotherapy. The study will thus provide the first randomized trial of this new practice- adapted transdiagnostic treatment, plus an inquiry into the process through which it may work and therapist factors that may strengthen or weaken implementation.

NIH Research Projects · FY 2024 · 2020-09

Late onset neurodegenerative diseases together affect more than 7 million Americans with associated healthcare costs currently reach hundreds of billions of dollars per year. Cognitive decline is a common feature of many of these diseases, especially Alzheimer’s disease, Parkinson’s disease, and vascular dementia. In spite of exciting progress being made in studying those disorders, currently, there are no available therapeutics capable of improving cognition. Therefore, it came as a surprise when a set of observations from a few labs, including ours, supported the notion that recovery of brain function after damage to the CNS might be achievable. Much of the data was obtained from studies of heterochronic parabiotic mice – young and old mice whose circulatory systems had been surgically joined. Our additional studies were equally exciting in that they demonstrated that injection of a single factor, GDF11, a normal serum protein, into aged mice was also able to improve important properties of the CNS. Specifically, GDF11 stimulated neurogenesis, increased neural activity and improved vascular structure. Surprisingly, we found that GDF11 does not cross the blood- brain barrier and instead may exert its effects by acting directly on aging brain vasculature. This proposal focuses on understanding in much greater detail how GDF11 exerts these ameliorative effects on the CNS. First, we will use a combination of histological, molecular and transcriptomic methods to investigate the effects of GDF11 on the cells of the brain more broadly. We will employ several measures including markers of neural activity, neurogenesis, angiogenesis, as well as changes in gene expression of the different cell types, and we will determine the sequence of GDF11’s actions (testing the hypothesis that GDF11’s neural effects are indirect and follow direct effects on brain vasculature). Next, we will compare GDF11’s effects on cells of the CNS with effects of other TGFβ-family ligands such as GDF8, TGFβ2 and modified forms of GDF11. Identifying the most effective ligand will help us understand the molecular changes these ligands produce, as well as position us to develop effective therapeutics in the future. Finally, our unpublished findings show that GDF11 and the components of its signaling pathway are expressed by multiple brain cell types well into adulthood. We will compare and contrast the functions of systemically injected GDF11 with those of GDF11 acting from within the brain. We will use a combination of histology and genetic perturbation to quantify the expression of GDF11 and its receptors across various regions the brain and how they are altered by aging. We will then measure the consequences of reducing brain GDF11 on neurogenesis and neural function. This will provide a better understanding of what might happen if systemic GDF11 gained direct access to neural cells in diseases in which the blood-brain barrier becomes compromised. From this work, we hope to gain a comprehensive understanding of the effects of GDF11, how they relate to those of other TGFβ-family ligands, and what benefits to brain function may be achieved by administering these factors.

NIH Research Projects · FY 2025 · 2020-09

Alzheimer’s disease and related dementias (ADRD) represent a growing health concern as the global population ages. While many promising treatments for ADRD have been developed and tested, they have largely failed to prevent disease onset or slow disease progression in older adults. However, research has found that subtle signs of ADRD pathology are detectable decades before disease onset. To develop treatments that can slow the progression of ADRD before intractable deterioration of the brain has taken place, we will need to better understand the lifespan trajectory of cognitive, biological and brain aging and develop biomarkers that can connect subtle signs of individual differences in midlife aging to ADRD in late life. In the F99 phase of the proposed research, the candidate will characterize signatures of midlife brain aging and investigate potential surrogate biomarkers using a multi-faceted approach in the Dunedin Study, a population representative birth cohort now in midlife. Specifically, the candidate will investigate the ability of widely used measures of risk for ADRD in older adults, including white matter hyperintensities and brain age, to measure accelerated cognitive and biological aging in midlife. The candidate will then develop a longitudinal measure from 20 years of biological aging across 19 biomarkers to investigate the consequences of accelerated pace of biological aging on individual differences in the structural integrity of the brain in midlife. Then the candidate will use childhood exposure to the neurotoxin lead, a known risk factor for ADRD, to further examine the utility of these candidate surrogate biomarkers to capture risk-related features of midlife brain aging. In the K00 phase of the proposed research, the candidate will utilize statistical techniques, developed when creating the pace of biological aging in midlife, to measure correlated decline in brain biomarkers in healthy aging and ADRD in older adults. The proposed research will yield techniques to measure accelerated biological aging in midlife and in older adults, as well as insights into ADRD through application of these measures. Critically, the proposed project will provide a deeper understanding of connections between midlife and late life accelerated aging that will contribute to growing efforts to target ADRD intervention earlier in life.

NIH Research Projects · FY 2024 · 2020-09

PROJECT SUMMARY In the U.S. alone, up to 26 million people have chronic kidney disease, over 460,000 people are on dialysis, and 100,000 people await kidney transplants with 3,000 new patients added monthly. Given the growing lack of transplantable organs, patients typically require renal replacement therapies that themselves lead to substantial morbidity and mortality. We posit that biomanufactured kidney tissues, and ultimately, organs may offer an important solution to this growing problem. Indeed, recent protocols in developmental biology are unlocking the potential for stem cells to undergo differentiation and self-assembly to form “mini-organs”, known as organoids. Kidney organoids exhibit remarkable tissue microarchitectures with high cellular density and heterogeneity akin to their in vivo counterparts. To bridge the gap from these kidney organoid building blocks (OBBs) to therapeutic organs, integrative approaches that combine bottom-up organoid assembly with top-down bioprinting are needed. While it is difficult, if not impossible, to imagine how either organoids or bioprinting alone would fully replicate the complex multiscale features required for kidney function – their combination could provide an enabling foundation for de novo organ manufacturing. To generate 3D functional kidney tissues ex vivo for potential transplantation, our highly collaborative research team will undertake two primary aims. In Specific Aim 1, we will create kidney organoids enhanced by multilineage induction that display functional differentiation of nephrons. We will produce iPSC-derived kidney organoids and subject them to fluid flow during their differentiation and maturation on an adherent extracellular matrix (ECM). Through multilineage induction, we will also induce collecting duct cells that self-assemble and structurally bridge other tubular nephron segments. We will evaluate the effects of mimicking kidney organogenesis on kidney organoid structure and function using microperfusion and micropuncture methods. In Specific Aim 2, we will create 3D functional kidney tissues composed of these optimized kidney OBBs with embedded macrochannels produced by bioprinting that serve as both vascular and urinary output conduits. We will first produce a densely cellular, tissue matrix composed of kidney OBBs that facilitates bioprinting of embedded macrochannels. We will then establish connections between the printed macrochannels embedded in this OBB-laden matrix and the self-assembled microvascular and collecting duct networks within individual OBBs. Finally, we will assess the glomerular filtration, tubular maturation, and primitive urinary production of these 3D kidney tissues. If successful, our proposed project will provide a foundational advance in kidney organ engineering for potential renal therapeutic applications.

NIH Research Projects · FY 2024 · 2020-09

Late onset neurodegenerative diseases, such as Alzheimer’s disease (AD), affect more than 7 million Americans, with the associated healthcare costs currently reaching hundreds of billions of dollars per year (and constantly rising). It is known that the pathology of AD involves many more cell types than the neurons of the hippocampus and cortex. The cells that comprise the brain vasculature, including the endothelial cells, pericytes, astrocytes and smooth muscle cells are critically important in maintaining the balance of health and disease in the brain. In particular, many properties of the endothelial cells, including their roles in establishing the blood-brain barrier (BBB), delivering nutrients to the brain, and regulating the proliferation of neural stem cells, are essential to proper brain function. Studies from our lab and others have demonstrated that brain vasculature can be restored even after it has been damaged, suggesting new strategies for treating neurodegenerative disorders via improving the integrity of brain vasculature. In experiments detailed in this application, we propose to both identify and correct processes within the cells of the brain vasculature that are known to be affected in Alzheimer’s disease and other dementias. Some of our work is based on the acknowledgement that aging is the major risk factor for dementia and is also characterized by declining vasculature. As a step toward obtaining a comprehensive understanding of aging-associated changes in the brain, our lab recently published a large single-cell RNAseq study comparing young and old mouse brains. Here, we propose to exploit our knowledge of the gene expression changes that define the aging process to identify cellular and molecular factors critical to brain blood vessel function and the maintenance of the BBB in a mouse model of AD. First, we will test several different hypotheses concerning the cellular and molecular bases for the vascular defects in the AD brain. Surprisingly, recent literature suggests that some of these changes are mediated by soluble factors and may be reversible. To explore this possibility in greater detail, we will use our knowledge of the CNS network of cell-cell interactions mediated by secreted factors to identify potentially correctable changes that occur in AD vasculature. Finally, we will use our lab’s expertise in human induced pluripotent stem cells (iPSCs) to employ an in vitro model of the BBB. This in vitro platform will serve as an important complementary approach to the in vivo mechanistic evaluation of putative aging or rejuvenation factors in human brain vascular cells. At the same time, we propose modifications of the current in vitro system that should improve its ability to recapitulate properties of the in vivo BBB. Together, our proposed studies seek to identify and validate new modulators of brain vasculature and to elucidate how the functions of these modulators play a role in the maintenance or degradation of the BBB in dementia.

NIH Research Projects · FY 2024 · 2020-08

Project Summary The ability to engineer living cells as intelligent therapeutic agents is poised to transform current cancer treatment paradigms. Based on the inherent growth specificity of some natural and exogenous bacteria to solid tumors, microbes have been explored as programmed vehicles to deliver therapeutics to tumor environments. However, a universal challenge for developing this next-generation living therapy is the lack of tools to study the dynami- cally interacting population of bacteria and cancer cells. Consequently, the vast majority of the past studies have relied on animal models that only test a handful of therapeutic candidates and provide limited spatiotemporal information. To address this challenge, I have recently developed a 3D multicellular coculture platform that ena- bles high-throughput characterization of bacteria in tumor spheroids, assessing dynamics of multicellular inter- actions and predicting therapeutic efficacy in vivo. In this proposal, I will leverage the 3D coculture technologies and synthetic biology tools to construct novel bacterial systems that sense and express therapeutics specifically in tumors. In the F99 phase, I will engineer tumor-homing bacteria to dynamically regulate production of cytotoxic molecules in response to tumor shrinkage. Specifically, as the cancer cell death increases the level of oxygen in the tumor core, I will engineer a bacterial biosensor circuit to monitor this change in the tumor microenvironment. By detecting rises in oxygen levels, which indicate extensive therapeutic progression, this gene circuit will reduce the therapeutic level produced, minimizing off-target toxicity. In the K00 phase, I will repurpose tumor-homing bacteria to target and eradicate oncogenic F. nucleatum in colorectal cancer. I will apply the 3D coculture platform to screen anti-F. nucleatum peptides delivered by bacteria to tumor spheroids. Orthotropic mouse cancer models will be used to assess the F. nucleatum elimination, effect on commensal microbiota, and cancer progression. Collectively, the proposed work will utilize a novel engineering framework to develop effective bacterial cancer therapies towards clinical translation.

NIH Research Projects · FY 2024 · 2020-07

PROJECT SUMMARY Exposure to stressful life events (SLEs) is involved in the etiology of most forms of psychopathology, and SLEs occurring early in development are particularly strong predictors of mental health problems. Most adolescent disorder onsets are temporally preceded by a major SLE. Yet, the mechanisms linking SLEs to the onset of adolescent psychopathology remain poorly understood. Prior research on mechanisms linking SLEs with youth mental disorders has focused largely on severe forms of adversity like abuse, neglect, and institutionalization. It is unknown whether similar mechanisms are involved in the link between less severe SLEs and psychopathology. Perhaps more critically, existing work has relied largely on cross-sectional between-subjects designs that compare children with exposure to some type of SLE to children without that experience. There is a dearth of longitudinal studies examining how SLEs influence emotion, cognition, behavior, and neural circuits within-individuals over time in ways that predict the emergence of psychopathology. The proposed research addresses this gap, using a novel methodological approach that permits examination of dynamic changes in emotion, cognition, social behavior, and neural function and connectivity following SLEs at a sufficiently fine grained level of temporal specificity to identify mechanisms underlying the link between SLEs and adolescent psychopathology as they unfold in real time. Specifically, the project will examine how monthly fluctuations in exposure to SLEs within-individuals predict subsequent changes in emotional processing in the Negative and Positive Valence Systems, Cognitive Control, Social Processes, and neural function and connectivity over a 12-month period. In addition to monthly assessments of SLEs, psychopathology, and potential mechanisms, passive monitoring of activity, sleep, and social behavior (e.g., interaction with peers through text and social media) through smartphones and wearable devices will allow additional mechanisms to be assessed passively and without subject burden. The study will investigate whether monthly variation in these emotional, cognitive, social, and neural processes predicts later increases in internalizing and externalizing problems in an accelerated cohort design with monthly assessments spanning age 11-18 years, producing 1,680 monthly observations over the study period. The longitudinal design and high-frequency assessments are innovative in allowing the identification of mechanisms that are altered by SLEs and prospectively predict psychopathology with high temporal specificity during a developmental period associated with increases in SLE exposure, stress vulnerability, and risk for psychopathology. Study findings will provide critical information regarding the specific domains of emotion, cognition, social behavior, and neural function that are altered by exposure to SLEs and increase vulnerability to psychopathology. These mechanisms represent modifiable targets for interventions to prevent the onset of stress-related psychopathology in children and adolescents.

NIH Research Projects · FY 2026 · 2020-05

Enter the text here that is the new abstract information for your application. ABSTRACT We consider chromosomes to be "living, breathing objects" whose fluctuations in time and space underlie their basic functions. We compare meiotic and mitotic chromosomes and E. coli nucleoids to identify commonalities. Meiosis underlies sexual reproduction. Unique hallmarks are (i) pairing and (ii) recombination between maternal and paternal chromosomes, including "crossover interference" in which crossover sites are evenly spaced along chromosomes. Both processes depend critically on association of recombination complexes with chromosome axial structures. Pairing. Using our 4D low SNR tracking of locus-specific "spots" in budding yeast, we have provided a new understanding of recombination-mediated pairing. Key features will now be explored. We also analyze global pairing topology by tracking chromosome paths, recombination complex status and chromatin status in Sordaria macrospora in living cells and by Expansion Microscopy. Patterning. Yeast crossover interference, including our recent discovery that crossovers occur in short "runs", will be dissected using new assays provided by pairing studies. We have proposed that crossover patterning is mediated by mechanical forces along chromosome axes. In support, we find that Sordaria meiotic chromosomes exhibit axis deformations ("perversions"), diagnostic of mechanical axis stress, with periodicities related to those of recombination complexes. We will ask whether perversions are altered in mutants with altered interference. In C. elegans, we are analyzing a early chromosome axis "notch" that reflects patterning. We find that yeast crossoverinterference requires phosphatase PP2A, whose HEAT repeat we showed to sense/transduce mechanical stress. We will ask whether interference is affected by PP2A mutations predicted to alter stress transduction. Our mitotic chromosome studies have recently defined a new morphogenetic pathway involving stress-diagnostic axis perversions (presaging meiotic findings). We are developing nanoscale tools for fluorescence sensing of stress patterns in vivo. These will first be applied to mitotic chromosomes, with concomitant investigation of whether chromatin status influences perversion morphology (as expected). We are alsoinvesting in a unique live mouse ex vivo oocyte system, thus enabling eventual application of stress sensors to meiotic chromosomes, but with immediate applicability to analysis of prophase chromosome dynamics. In E. coli, we analyze nucleoid dynamics by 4D imaging of walled cells and membrane-enclosed L- forms. We will validate our recent discovery that sister chromosome segregation is rate-limiting for cell division and investigate our new hypothesis that tension at the nucleoid/membrane interface coordinates chromosome and cell division cycles as driven by our discovered periodic nucleoid length/width fluctuations.

NIH Research Projects · FY 2026 · 2019-03

The olfactory tubercle (OT) is a ventral striatal brain region implicated in reward processing and motivated behaviors including addiction. It receives olfactory sensory input, as well as strong dopaminergic innervation from the ventral tegmental area (VTA). Learning-induced changes in neural activity can occur rapidly and differentially in distinct types of neurons on the OT, but it is not clear how stable these changes in representations are. Recent studies in many brain regions have revealed a surprising instability in sensory representations, even when the animal’s behavior is stable. Unstable representations are hypothesized to potentially arise from ongoing synaptic plasticity, as might occur with ongoing activity or further learning. Whether such “representational drift” is present in striatal areas including the OT is unknown and will be a subject of inquiry in this proposal. The PIs will ask whether OT neural representation of previously learned associations is stable when new associations are learned, and whether the representations are altered when old associations are unlearned or degraded. The PIs will use deep brain multiphoton imaging at subcellular resolution to monitor activity in identified subtypes of OT neurons over weeks as mice learn and maintain odor-outcome associations. Using our collective expertise in behavior, physiology, and imaging, the PIs will tackle the following Aims. Aim 1: To determine whether neural representations of cue-outcome associations in the OT are stable over several days. The PIs will train mice to learn the arbitrarily assigned valence of several odors and track the activity of two cardinal types of neurons in the OT in behaving mice during and after task learning over multiple weeks. The PIs hypothesize that continuous experience and reinforcement will stabilize representations in the OT, which can degrade with pauses in experience. Aim 2: To determine whether and how existing representations in the OT change when new cue-outcome associations are learned. After mice have stably associated several odors with specific outcomes, the PIs will introduce new odors to be learned, reverse or extinguish familiar associations, as specific OT neural populations are tracked. The PIs hypothesize that new learning will lead to greater representational drift for older, familiar associations. Aim 3: To determine the role of dopaminergic signaling in maintaining stability and flexibility of representations in the OT. Whether continued dopamine signaling in the OT helps maintain stable representations through repetition or perturbs stability by promoting additional synaptic plasticity is unknown. The PIs will perturb dopaminergic signaling to the OT in mice that have learned cue-outcome associations and investigate how neural representations in the OT evolve. The PIs hypothesize that perturbing dopamine signaling will degrade representational stability even with continued experience. Our studies, in addition to answering questions about the function of the OT, will also shed light more broadly on exciting new ideas about continual learning.

NIH Research Projects · FY 2025 · 2019-01

Abstract The long-term goal of this project is to understand how cells sense and process signals to make fate decisions and pattern into complex tissues, both during normal human development and in developmental diseases. How tissues of the embryo pattern and undergo morphogenesis is a fundamental question in developmental biology. This application will address the question in the context of the axial elongation of the human embryo during development, during which it breaks anterior-posterior (A-P) symmetry, forms a tailbud posteriorly, and elongates along the A-P axis. The progenitors in the tail bud proliferate to drive this extension and further differentiate to give rise to neural and mesodermal cell types. This proposal aims to understand how axial elongation is driven and how the progenitor cells in the tailbud maintain a self-sustaining pool, even as they differentiate into neural and mesodermal cells. Since the mechanisms underlying human axial elongation and patterning are not shared between other vertebrates, the generalizability of results from model organisms to humans remains unknown. While ethical reasons necessitate the use of in vitro models of human development, the large variability in such organoid systems has been a critical barrier. Preliminary work overcame this barrier to strikingly and reproducibly model human axial morphogenesis and patterning by developing an organoid system that elongates to generate the posterior neural tube and flanking paraxial mesoderm. Using this powerful system, the proposal seeks to answer two fundamental questions associated with this process: first, how morphogen signals break A-P symmetry and stably drive self-sustaining axial extension along a single axis. The goal is to uncover the underlying dynamical system that is activated to drive self-sustaining axial elongation and to understand how this system buffers against noise so as not to be susceptible to dynamical instabilities, for example, leading to branched or multiple axes. The second is to determine the dynamical system governing the maintenance of a proliferating pool of progenitors in the tailbud throughout axial elongation, even as they are driven to differentiate into neural and mesodermal tissues. The proposal brings together methods to infer and measure spatiotemporal profiles of gene expression; compare these profiles with other model organisms to determine similarities and differences in gene expression patterns driving axial elongation, and Bayesian ensemble modeling to build predictive models of the GRN driving axial elongation and experimental tools to test model predictions. The proposal will allow us to achieve a quantitative understanding of the dynamics across scales, from intracellular signaling and transcriptional regulation to cellular rearrangement to tissue-level axial extension made possible by new human stem cell lines, imaging, image processing, statistical inference, mathematical modeling, and bioengineering tools, to provide insights into principles governing human axial elongation. The ability to build and test quantitative predictive models of human axial extension will open novel avenues to understanding the mechanisms underlying human diseases.

NIH Research Projects · FY 2025 · 2018-04

Abstract My lab currently has two main areas of interest: 1) a new chaperone system (eFOLD) that enables biogenesis of eukaryotic translation elongation factor 1 alpha (eEF1A); 2) endoplasmic reticulum (ER) and peroxisome degradation by selective autophagy. Errors in eEF1A biogenesis result in rapid degradation by the ubiquitin-proteasome system (UPS) thus making protein degradation a natural link between the two areas. Both eFOLD and selective autophagy are controlled by distinct stress responses (e.g. heat shock vs. amino acid starvation) but jointly serve as effectors of protein homeostasis (proteostasis). Both areas raise similar questions regarding substrate selectivity: How does a specific eFOLD chaperone co-translationally recognize an aggregation-prone region of eEF1A nascent chains? How is terminally misfolded eEF1A recognized for degradation by the UPS? What signals on damaged or unwanted organelles are detected by specific autophagy receptors to orchestrate encapsulation of organelle targets into autophagosomes? To answer these questions, we are dissecting biogenesis and degradation mechanisms that select substrates of grossly different sizes, respond to distinct physiological cues, and have widely different temporal dynamics. Using yeast and human cell culture in parallel, we are exploring conserved aspects of eFOLD and selective autophagy mechanisms shared by each species, as well as species-specific adaptations. Broadly speaking, our projects spawn from identification of missing factors by genetic screening or biochemical purification but all seek a deep mechanistic understanding of mutant phenotypes through biochemical reconstitution with purified components and protein structure-function analysis. Along this path, we iteratively test our hypotheses by genomics, quantitative cell microscopy, and theoretical modeling approaches.

NIH Research Projects · FY 2025 · 2018-02

Project summary / Abstract Autism spectrum disorder (ASD) is a neurodevelopmental disorder whose underlying mechanisms have been proposed to include abnormal excitatory-inhibitory balance in brain regions including the cerebral cortex. The ATP-dependent chromatin-remodeling factor chromodomain helicase binding protein 8 (CHD8) is one of the most commonly-mutated genes in sporadic ASD, producing an ASD subtype associated with a high prevalence of macrocephaly (Barnard et al., Front Neurosci., 2015). In prior work supported by the original grant, we optimized a human cortical organoid model we developed (Velasco et al., Nature, 2019; Uzquiano et al., Cell, 2022) and applied it to show that CHD8 and other ASD risk genes converge on an early developmental defect in the GABAergic neuron lineage, leading to asynchronous development of target neurons relative to the other cell types developing in the organoids (Paulsen et al., Nature, 2022). From this data, we hypothesized that asynchronous development of GABAergic neurons relative to the excitatory neurons they wire with could lead to later abnormalities in the activity and function of the cortical local circuit. In support of this hypothesis, we showed that mutation in another ASD risk gene, SUV420H1, also associated with accelerated development of GABAergic neurons, leads to abnormal activity of mutant circuits in organoids (Paulsen et al., Nature, 2022). Building on this data, in this renewal we will leverage our expertise in organoid biology and cortical development together with co-Investigator Mark Harnett's expertise in human cortical physiology to investigate the effect of heterozygous loss-of-function of CHD8 on neuronal development and circuit activity using newly-developed organoid models. Firstly, we will apply a chimeric organoid (“chimeroid”) model (Antón Bolaños and Faravelli et al., preprint at bioRxiv 2023, and in revision at Nature) to understand whether the genetic context of ASD patients is permissive for expressivity of the previously-identified CHD8+/- phenotypes (Aim 1). In parallel, we will apply a new human organoid model of the ventral telencephalon, which we validated to be able to produce GABAergic neurons of the caudal, medial, and lateral ganglionic eminences (Sartore et al., manuscript in preparation), to understand whether specific classes of GABAergic interneurons are preferentially affected by CHD8 mutation (Aim 2). Finally, with the aim of promoting circuits that reflect the endogenous neuronal composition, we will apply a new “dorsal-ventral chimeroid” organoid model that allows us to control development of the correct proportions of both excitatory and inhibitory cortical neurons, to investigate cell identity and circuit activity in the CHD8 heterozygous mutant in a more physiologically-relevant system, using calcium imaging, extracellular recording, and pharmacological manipulations (Aim 3). Taken together, this work will provide mechanistic understanding of the roles of a major ASD risk gene in the formation of GABAergic neuron populations of the cerebral cortex and in the biology of cortical circuits.

NIH Research Projects · FY 2025 · 2017-09

Our current U19 has focused primarily on Exteroception, which can be defined as the accumulated sensory experience originating from events in the outside world. However, all neural computation takes place in the context of the body, which is subject to the dynamics of hunger, fatigue, motivation and diurnal cycles. The information that reaches the brain from the organs and receptors inside of the body, summarized under the umbrella term of Interoception, is therefore overlaid onto exteroceptive computations. This adds behavioral variability to any animal task, from changing vigor to altering valence of rewards to vetoing responses altogether. To better understand such embodied computation, we will first incorporate cardiac and respiratory variables that dynamically report basic internal states to our standard behavioral classification methods, and we will include detailed characterization and modeling of the autonomic and intracardiac nervous system in our functional imaging studies. Finally, as a critical resource for the description and validation of the generated neural circuit models, we will create a complete body-and-brain connectome of the larval zebrafish. This research plan is aligned with the three levels of understanding articulated by David Marr more than thirty years ago, who emphasized the importance of considering Evolutionary Principles, Algorithmic Representation and Hardware Implementation as a unified and interconnected approach for understanding the brain. Following this framework, we first try to isolate aspects of fish behavior that are adapted to their native environment and context. We next use a variety of controlled behavioral assays to extract the algorithmic rules that govern the dynamics of modular sensorimotor transformations, and that are augmented by knowledge about internal state changes as reflected by observed modulation of cardiac and respiratory activity. To characterize the hardware implementation of these explicit and latent behavioral algorithms, we propose to first measure cellular activity using brain-wide functional light imaging of the central, the autonomic and the intracardiac nervous systems (CNS, ANS and ICNS). We next will use these comprehensive datasets to generate realistic circuit models of the observed dynamics. These models will then guide a series of circuit dissection experiments, such as optogenetic perturbations of specific cell types, targeted patch-clamp physiology and sparse connectomics tracing, allowing us to validate, extend, and constrain our models. We note that this approach also affords us the opportunity to discover new circuit elements and circuit motifs, and novel ways to implement computational algorithms by the brain. Another extension of our current U19 is the addition of a dynamical modeling framework for these behaviors, where animals can interact flexibly with the environment, and where we consider multiple time scales of interaction. We believe that this constitutes a different and perhaps ethologically more relevant approach when compared to the highly constrained, simplified and repetitive challenges we used before. Further, this framework is well suited in characterizing the continuous process of cardiac control and its interaction with behavioral modulation.

NIH Research Projects · FY 2025 · 2016-09

Project Summary/Abstract Genome sequence data is now available for hundreds of thousands of species. Our ability to exploit this vast trove of information about the molecular basis and evolution of life depends on sophisticated computational analysis tools. One important class of tools is profile analysis software, for making consensus statistical models of multiple alignments of biological sequence families, and for using those models to sensitively detect homologs and make deep multiple alignments. Profile analysis derives its power from the fact that despite the unbounded growth of sequence data, the majority of functional sequences can be condensed into a manageably small number of conserved families. Profile software underlies numerous protein, RNA, and DNA sequence family databases. The systematic availability of deep multiple alignments (of many thousands of sequences) is enabling revolutionary advances in predicting molecular function and 3D structure by comparative sequence analysis. The HMMER and Infernal software packages from our laboratory are some of the most widely used tools for profile analysis. HMMER implements profile hidden Markov models (profile HMMs) of primary sequence consensus, typically for protein domains and conserved DNA elements. Infernal implements profile stochastic context-free grammars (profile SCFGs) of RNA secondary structure and sequence consensus. In the context of the continued development of these packages, this proposal has three specific aims for new lines of research that we expect to lead to major improvements in the accuracy, utility, and computational efficiency of profile anal- ysis. The first aim proposes to develop a discontinuous Markov model of nonhomologous sequences, to improve the ability to distinguish homologs from nonhomologs and reduce the false positive rate of database searches. The second aim proposes to develop sketching methods for efficiently representing the voluminous results of a database homology search with a subset of the most phylogenetically informative hits. The third aim proposes to develop adaptive computation methods to flexibly harness the complex mix of CPU/GPU processors, mem- ory, and storage in modern hardware architectures, enabling efficient scalable computation and near-interactive database search times.

NIH Research Projects · FY 2025 · 2016-09

Neural circuits underlying the acquisition and control of motor skills Much of our behavioral repertoire consists of learned motor skills, yet little is known about the neural circuits underlying their acquisition and control. The overarching goals of our research program is to identify these circuits, delineate their respective functions, and explain the logic by which they work together to implement motor skill learning and execution. To work towards this goal, we developed cutting-edge experimental infrastructure designed to enable high-throughout and rigorous studies of complex learned behaviors in rodents. To facilitate the study of learned motor skills, we developed a task that train rats to produce task-specific movement patterns with complex learned movement kinematics. In previous work, we showed that motor cortex is necessary for learning these skills, but not for executing them once acquired. These surprising results suggest that, while motor cortex has a function in learning, the acquired skills are stored and generated subcortically. We further showed that the sensorimotor input region of the basal ganglia, the dorsolateral striatum, encodes the kinematic details of the learned motor skills and is essential for generating them. Here, we build on these results to examine the logic and mechanisms by which subcortical circuits, specifically the striatum and thalamus, contribute to acquiring, storing, and generating these skills. To get at this, we will use our innovative experimental platform to monitor neural activity and behavior continuously over weeks of training, while also perturbing neural activity and observe the effects of these manipulations on behavior. We will describe how striatal encoding of task-related movement patterns changes with learning and how these changes relate to a striatum’s putative control function (Aim 1). We will further parse the pathways from thalamus to striatum that are relevant for motor skill execution (Aim 2) and describe task-related activity patterns in the thalamus and how they are transformed in the striatum (Aim 3). Precise measurement of the rats’ movements using video-based motion tracking will relate our neural recordings and circuit manipulations to behavior in exact ways, allowing us to infer how subcortical circuits implement the acquisition and execution of learned skills. Addressing these aims will clarify the logic of how the mammalian motor system enables motor skill learning and execution and delineate the roles of the basal ganglia and thalamus in these important processes, thus addressing fundamental questions in neuroscience with far-reaching implications for clinical practice and neurorehabilitation.

NIH Research Projects · FY 2025 · 2016-07

PROJECT SUMMARY Colorectal cancer (CRC) is the third most prevalent form of cancer in the US and the second leading cause of cancer deaths. Studies over the last several decades have revealed that the gut microbiota influences CRC, and recent work has implicated gut bacterial genotoxins as key effectors in cancer development and progression. One of the bacterial genotoxins most strongly connected to cancer is colibactin, a metabolite produced by human gut commensal bacteria, including certain E. coli strains, that possess a biosynthetic gene cluster termed the pks island. The increased prevalence of pks+ E. coli in CRC patients and the ability of pks+ strains to potentiate tumorigenesis in mouse models of CRC suggest colibactin may play a causal role in cancer progression. However, achieving a mechanistic understanding of colibactin's genotoxicity and contribution to CRC has been impeded by an inability to isolate and structurally characterize the active genotoxic metabolite(s). During the previous funding period of this grant, we gained critical information about colibactin's structure and mode of action by studying the enzymes involved in its biosynthesis. Most notably, we established that colibactin is a DNA alkylating agent and proposed a potential structure for the active genotoxin. The overall objective of this renewal application is to elucidate additional molecular mechanisms underlying colibactin's activity and role in CRC carcinogenesis. Building off of the central hypothesis that the genotoxic activity of colibactin derives from the formation of DNA interstrand cross-links (ICLs), our three specific aims will: 1) characterize the specificity and structure of colibactin-DNA ICLs; 2) develop small molecules that inhibit colibactin biosynthesis in microbial communities; 3) elucidate the physiological location and timing of colibactin-mediated DNA damage in CRC development. These advances will be enabled by our multidisciplinary approach, which merges knowledge and techniques from chemical biology, structural biology, microbiology, toxicology, and cancer biology. Overall, this effort will fill critical gaps in fundamental knowledge needed to elucidate the role of colibactin-producing gut bacteria in CRC carcinogenesis and ultimately impact cancer prevention, diagnosis, and treatment. Additionally, by successfully demonstrating that studying and manipulating individual disease-associated microbial pathways can provide key mechanistic insights, this work will also support and validate future efforts to understand how other gut microbial activities influence CRC initiation and development.

NIH Research Projects · FY 2024 · 2015-08

Project Summary/Abstract Many severe mental disorders with considerable disease burden such Autism Spectrum Disorders, Schizophrenia, and Major Depressive Disorder are characterized by profound social impairments. At present, there is little understanding of the origin of these social deficits, and efficient diagnosis and therapeutic options are lacking. Advanced molecular and genetic techniques make the discovery of specific neural circuits involved in social behavior possible, facilitating the development of diagnostics and novel therapeutic approaches specific to disorders with social deficits. We have taken advantage of newly developed molecular, genetic and systems- levels tools to uncover how specific neural populations and circuits involved in parental care, a social behavior essential for the survival and well-being of the offspring are regulated according to the animal sex and physiological status. Male and female mice show either affiliative or agonistic behavior toward infants depending on prior social experience. In recent work, we uncovered distinct subpopulations of hypothalamic neurons that are involved in the positive and negative regulation of male and female parenting behavior. The identification of these cell types with high granularity provides us with unique entry point to further dissect how changes in the molecular, biophysical and activity dynamics of distinct neuronal populations regulates parental care. We propose here to exploit the precise cell type identification of neuronal populations involved in the control of opposing infant-mediated behaviors and use high resolution molecular (Aim 1), neurophysiological (Aim 2) and systems-level (Aim 3) approaches to dissect the entire circuitry associated with infant-directed social interactions and to explore how these circuits are modulated by the animal’s sex and physiological state.

NIH Research Projects · FY 2025 · 2013-07

PROJECT SUMMARY/ABSTRACT The overall goal of my research program is to understand adaptation in microbial populations, using a  combination of mathematical modeling and high-­throughput experimental evolution in budding yeast. At root,  we aim to predict how evolution chooses probabilistically among different mutational trajectories, to determine  the rate and outcomes of adaptation. In the short term, evolution depends primarily on the distribution of fitness  effects of individual mutations. However, on longer timescales epistatic interactions between mutations can be  crucial. Similarly, mutations often have different fitness effects in different environments (“pleiotropy for  fitness”). This is essential to evolution in fluctuating environments. Recent work shows that epistasis and  pleiotropy are strong and common among specific sets of mutations in many microbial systems. However,  these studies of specific limited sets of mutations cannot fully explain how epistasis and pleiotropy constrain  the rate, repeatability, or dynamics of adaptation. And even given a complete set of epistatic and pleiotropic  interactions, we are still often unable to predict how evolution will act. This severely limits our ability to  understand the evolution of complex phenotypes, such as compensated antibiotic resistance, multiple  mutations required for immune escape, or multiple gene knockouts enabling cancer evolution.   The central objective of this proposal is to examine the role of epistasis and pleiotropy for fitness in the  evolution of microbial populations. Rather than characterizing specific examples, we propose to survey the  overall statistics of epistasis and pleiotropy that are relevant for constraining microbial adaptation, and to  analyze how this epistasis and pleiotropy alters how evolution chooses among possible mutational trajectories.  In Aim 1, we will quantify statistical patterns of epistasis among both natural variants and mutations relevant to  adaptation in laboratory budding yeast populations. We will use our data to test recent theoretical predictions  describing how overall statistical patterns of epistasis emerge from individual idiosyncratic interactions. In Aim  2, we will measure patterns of pleiotropy across hundreds of environmental conditions, and use our data as the  basis for a novel computational method to infer lower-­dimensional statistical structure in the underlying  phenotypic space. Finally, in Aim 3, we will track evolutionary dynamics in fluctuating conditions in both clonally  evolving and outcrossed recombining laboratory budding yeast populations, using genetic systems we have  developed to control mating and to continuously barcode lineages. We will interpret these results within the  context of novel population genetic theory we will develop to predict how epistasis and pleiotropy affect  evolutionary dynamics in fluctuating environments. In contrast to recent work probing epistasis and pleiotropy  between restricted sets of individual mutations, our approach will provide a comprehensive picture of the  degree to which these factors alter the course of microbial evolution.

NIH Research Projects · FY 2026 · 2008-12

PROJECT SUMMARY Antibiotic resistant Gram-negative infections pose a serious threat to human health. The outer membrane of Gram-negative bacteria is a unique structure essential for survival; it also functions as a physical barrier to block entry of many classes of antibiotics and thereby render them ineffective. This research is directed towards understanding the structure and function of two multi-protein machines responsible for the biogenesis of two major components of the outer membrane, lipopolysaccharide (LPS) and outer membrane proteins (OMPs). To understand the protein-protein interactions within each machine and their molecular structures, biochemical and structural studies will be undertaken. To dissect the functions of the individual components of these machines, intermediates in transport and assembly of LPS and OMPs will be characterized structurally, biochemically, and in cells. A better understanding of the protein machinery and the processes in which they are involved may lead to the discovery of inhibitors that could ultimately be developed to treat Gram-negative infections.

NIH Research Projects · FY 2025 · 2004-07

Modified Project Summary/Abstract Section This application proposes continued funding of the Harvard University Center for AIDS Research (HU CFAR). The HU CFAR is the umbrella and coordinating organization for all HIV research at Harvard, operating out of the Harvard University Provost’s Office. The HU CFAR serves to integrate HIV research across Harvard affiliated schools, such as Harvard Medical School and the Harvard TH Chan School of Public Health, as well as Harvard-affiliated hospitals and institutes, including Dana-Farber Cancer Institute, Beth Israel Deaconess Medical Center, Boston Children’s Hospital, Massachusetts General Hospital, Brigham & Women’s Hospital, Ragon Institute of Mass General, MIT and Harvard, and Fenway Health. The HU CFAR also has strong collaborations with the Massachusetts Department of Public Health, Boston Public Health Commission and community-based organizations and with global sites, extending its reach to additional key clinical populations and research sites outside Harvard. The HU CFAR leverages strong institutional support to promote multidisciplinary HIV research through its Cores, Scientific Working Groups and Scientific Programs. The HU CFAR includes an Advanced Laboratory Technologies Core, a Biostatistics and Bioinformatics Core, a Bio- Behavioral and Community Science Core, and a Clinical Core. In addition, the HU CFAR Developmental and Mentoring Core supports innovative pilot projects and provides mentorship to develop the next generation of HIV researchers. These Cores are supported by the HU CFAR Administrative Core, which provides administrative support and fiscal oversight and oversees strategic planning. Based on an inclusive strategic planning process, the HU CFAR has also formed steering committees to promote basic and translational science and research on ending the HIV epidemic as well as integration of diversity, equity and inclusion throughout all aspects of the CFAR. Briefly, we propose to: 1. Support innovative, multidisciplinary research initiatives addressing key HIV-related research priorities aimed at mitigating the effects of infection and bringing an end to the epidemic. 2. Engage, support and mentor the next generation of early career investigators in HIV research. 3. Promote Diversity, Equity and Inclusion (DEI) throughout all aspects of the CFAR and expand Community Engaged Research. 4. Facilitate and expand synergistic multidisciplinary collaborations among Harvard-affiliated HIV researchers and their trainees through innovative leadership, scientific planning and management.

NIH Research Projects · FY 2025 · 2000-03

Project Summary The overarching goals of this project are to illuminate the nature and functions of episodic memory by examining how retrieval of episodic memories supports cognitive functions that extend beyond simple recall of past events, such as imagining future experiences, solving everyday problems, and making inferences about the links among related events. Recent evidence indicates that the same core brain network is involved in both remembering past experiences and imagining or simulating hypothetical future experiences. The proposed experiments will use novel cognitive tasks and neuroscience-based measures, including both functional magnetic resonance imaging (fMRI) and transcranial magnetic stimulation (TMS), to elucidate how specific regions within this core network support constructive uses of episodic retrieval that underly future thinking, problem solving, and associative inferences. The studies will also examine how some of these adaptive functions can also lead to errors in episodic remembering. One set of studies will use a novel fMRI pattern similarity approach to clarify how two key regions in the core brain network – the hippocampus and angular gyrus – reinstate episodic information from past experiences when people imagine various kinds of future experiences. TMS will provide converging evidence by targeting hippocampal activity, which should specifically impact episodic reinstatement. A second set of studies will use a similar combination of fMRI pattern similarity and TMS approaches to revealing, for the first time, how episodic information is reinstated when people try to address everyday personal problems, including problems that are personally worrisome. These studies will draw on novel behavioral paradigms that recruit episodic retrieval processes during personal problem solving. A third set of experiments will attempt to identify the neural mechanisms underlying memory errors that result from adaptive use of episodic retrieval processes that support the ability to make associative inferences about the relations among events by combining novel behavioral paradigms with fMRI pattern similarity analysis. Overall, these experiments should enhance understanding of mechanisms involved in episodic retrieval, simulation, and problem solving by helping to refine recently novel measures developed in recent research, and could also provide insights that are relevant to clinical conditions in which episodic retrieval and simulation deficits contribute to impairments in everyday cognitive function.