Faculty Bibliography

Neurodegenerative disorders, including Alzheimer's disease (AD) and Parkinson's disease (PD), represent debilitating conditions with complex, poorly understood pathologies. Epichaperomes, pathologic protein assemblies nucleated on key chaperones, have emerged as critical players in the molecular dysfunction underlying these disorders. In this study, we introduce the synthesis and characterization of clickable epichaperome probes, PU-TCO, positive control, and PU-NTCO, negative control. Through comprehensive in vitro assays and cell-based investigations, we establish the specificity of the PU-TCO probe for epichaperomes. Furthermore, we demonstrate the efficacy of PU-TCO in detecting epichaperomes in brain tissue with a cellular resolution, underscoring its potential as a valuable tool for dissecting single-cell responses in neurodegenerative diseases. This clickable probe is therefore poised to address a critical need in the field, offering unprecedented precision and versatility in studying epichaperomes and opening avenues for novel insights into their role in disease pathology.

OBJECTIVE/UNASSIGNED:To investigate shared and specific neural correlates of cognitive functions in attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), the authors performed a comprehensive meta-analysis and considered a balanced set of neuropsychological tasks across the two disorders. METHODS/UNASSIGNED:A broad set of electronic databases was searched up to December 4, 2022, for task-based functional MRI studies investigating differences between individuals with ADHD or ASD and typically developing control subjects. Spatial coordinates of brain loci differing significantly between case and control subjects were extracted. To avoid potential diagnosis-driven selection bias of cognitive tasks, the tasks were grouped according to the Research Domain Criteria framework, and stratified sampling was used to match cognitive component profiles. Activation likelihood estimation was used for the meta-analysis. RESULTS/UNASSIGNED:After screening 20,756 potentially relevant references, a meta-analysis of 243 studies was performed, which included 3,084 participants with ADHD (676 females), 2,654 participants with ASD (292 females), and 6,795 control subjects (1,909 females). ASD and ADHD showed shared greater activations in the lingual and rectal gyri and shared lower activations in regions including the middle frontal gyrus, the parahippocampal gyrus, and the insula. By contrast, there were ASD-specific greater and lower activations in regions including the left middle temporal gyrus and the left middle frontal gyrus, respectively, and ADHD-specific greater and lower activations in the amygdala and the global pallidus, respectively. CONCLUSIONS/UNASSIGNED:Although ASD and ADHD showed both shared and disorder-specific standardized neural activations, disorder-specific activations were more prominent than shared ones. Functional brain differences between ADHD and ASD are more likely to reflect diagnosis-related pathophysiology than bias from the selection of specific neuropsychological tasks.

INTRODUCTION/UNASSIGNED:Hyperoxaluria is a risk factor for kidney stone formation and chronic kidney disease progression. The microbiome is an important protective factor against oxalate accumulation through the activity of its oxalate-degrading enzymes (ODEs). In this cross-sectional study, we leverage multiomics to characterize the microbial community of participants with primary and enteric hyperoxaluria, as well as idiopathic calcium oxalate kidney stone (CKS) formers, focusing on the relationship between oxalate degrading functions of the microbiome. METHODS/UNASSIGNED:Patients diagnosed with type 1 primary hyperoxaluria (PH), enteric hyperoxaluria (EH), and CKS were screened for inclusion in the study. Participants completed a food frequency questionnaire recording their dietary oxalate content while fecal oxalate levels were ascertained. DNA and RNA were extracted from stool samples and sequenced. Metagenomic (MTG) and metatranscriptomic (MTT) data were processed through our bioinformatics pipelines, and microbiome diversity, differential abundance, and networks were subject to statistical analysis in relationship with oxalate levels. RESULTS/UNASSIGNED:A total of 38 subjects were recruited, including 13 healthy participants, 12 patients with recurrent CKS, 8 with PH, and 5 with EH. Urinary and fecal oxalate were significantly higher in the PH and the EH population compared to healthy controls. At the community level, alpha-diversity and beta-diversity indices were similar across all populations. The respective contributions of single bacterial species to the total oxalate degradative potential were similar in healthy and PH subjects. MTT-based network analysis identified the most interactive bacterial network in patients with PH. Patients with EH had a decreased abundance of multiple major oxalate degraders. CONCLUSION/UNASSIGNED:The composition and inferred activity of oxalate-degrading microbiota were differentially associated with host clinical conditions. Identifying these changes improves our understanding of the relationships between dietary constituents, microbiota, and oxalate homeostasis, and suggests new therapeutic approaches protecting against hyperoxaluria.

OBJECTIVES/OBJECTIVE:Despite performing well in standard clinical assessments of speech perception, many cochlear implant (CI) users report experiencing significant difficulties when listening in real-world environments. We hypothesize that this disconnect may be related, in part, to the limited ecological validity of tests that are currently used clinically and in research laboratories. The challenges that arise from degraded auditory information provided by a CI, combined with the listener's finite cognitive resources, may lead to difficulties when processing speech material that is more demanding than the single words or single sentences that are used in clinical tests. DESIGN/METHODS:Here, we investigate whether speech identification performance and processing effort (indexed by pupil dilation measures) are affected when CI users or normal-hearing control subjects are asked to repeat two sentences presented sequentially instead of just one sentence. RESULTS:Response accuracy was minimally affected in normal-hearing listeners, but CI users showed a wide range of outcomes, from no change to decrements of up to 45 percentage points. The amount of decrement was not predictable from the CI users' performance in standard clinical tests. Pupillometry measures tracked closely with task difficulty in both the CI group and the normal-hearing group, even though the latter had speech perception scores near ceiling levels for all conditions. CONCLUSIONS:Speech identification performance is significantly degraded in many (but not all) CI users in response to input that is only slightly more challenging than standard clinical tests; specifically, when two sentences are presented sequentially before requesting a response, instead of presenting just a single sentence at a time. This potential "2-sentence problem" represents one of the simplest possible scenarios that go beyond presentation of the single words or sentences used in most clinical tests of speech perception, and it raises the possibility that even good performers in single-sentence tests may be seriously impaired by other ecologically relevant manipulations. The present findings also raise the possibility that a clinical version of a 2-sentence test may provide actionable information for counseling and rehabilitating CI users, and for people who interact with them closely.

Mutations accumulate in the genome of every cell of the body throughout life, causing cancer and other diseases^1,2. Most mutations begin as nucleotide mismatches or damage in one of the two strands of the DNA before becoming double-strand mutations if unrepaired or misrepaired^3,4. However, current DNA-sequencing technologies cannot accurately resolve these initial single-strand events. Here we develop a single-molecule, long-read sequencing method (Hairpin Duplex Enhanced Fidelity sequencing (HiDEF-seq)) that achieves single-molecule fidelity for base substitutions when present in either one or both DNA strands. HiDEF-seq also detects cytosine deamination-a common type of DNA damage-with single-molecule fidelity. We profiled 134 samples from diverse tissues, including from individuals with cancer predisposition syndromes, and derive from them single-strand mismatch and damage signatures. We find correspondences between these single-strand signatures and known double-strand mutational signatures, which resolves the identity of the initiating lesions. Tumours deficient in both mismatch repair and replicative polymerase proofreading show distinct single-strand mismatch patterns compared to samples that are deficient in only polymerase proofreading. We also define a single-strand damage signature for APOBEC3A. In the mitochondrial genome, our findings support a mutagenic mechanism occurring primarily during replication. As double-strand DNA mutations are only the end point of the mutation process, our approach to detect the initiating single-strand events at single-molecule resolution will enable studies of how mutations arise in a variety of contexts, especially in cancer and ageing.

Synucleinopathies are a group of neurodegenerative diseases characterized by the accumulation of α-synuclein (α-syn) in the brain, leading to motor and neuropsychiatric symptoms. Currently, there are no known cures for synucleinopathies, and treatments mainly focus on symptom management. In this study, we developed a single-domain antibody (sdAb)-based protein degrader with features designed to enhance proteasomal degradation of α-syn. This sdAb derivative targets both α-syn and Cereblon (CRBN), a substrate-receptor for the E3-ubiquitin ligase CRL4^CRBN, and thereby induces α-syn ubiquitination and proteasomal degradation. Our results indicate that this therapeutic candidate enhances proteasomal degradation of α-syn, in addition to the endogenous lysosomal degradation machinery. By promoting proteasomal degradation of α-syn, we improved clearance of α-syn in primary culture and mouse models of synucleinopathy. These findings indicate that our sdAb-based protein degrader is a promising therapeutic candidate for synucleinopathies. Considering that only a small percentage of antibodies enter the brain, more potent sdAbs with greater brain entry than whole antibodies could enhance clinical benefits of antibody-based therapies.

The diagnosis and treatment of tumors often depends on molecular-genetic data. However, rapid and iterative access to molecular data is not currently feasible during surgery, complicating intraoperative diagnosis and precluding measurement of tumor cell burdens at surgical margins to guide resections. To address this gap, we developed Ultra-Rapid droplet digital PCR (UR-ddPCR), which can be completed in 15 minutes from tissue to result with an accuracy comparable to standard ddPCR. We demonstrate UR-ddPCR assays for the IDH1 R132H and BRAF V600E clonal mutations that are present in many low-grade gliomas and melanomas, respectively. We illustrate the clinical feasibility of UR-ddPCR by performing it intraoperatively for 13 glioma cases. We further combine UR-ddPCR measurements with UR-stimulated Raman histology intraoperatively to estimate tumor cell densities in addition to tumor cell percentages. We anticipate that UR-ddPCR, along with future refinements in assay instrumentation, will enable novel point-of-care diagnostics and the development of molecularly-guided surgeries that improve clinical outcomes.

Consciousness science is experiencing a coming-of-age moment. Following 3 decades of sustained efforts by a relatively small group of consciousness researchers, the field has seen exponential growth over the past 5 years. It is increasingly recognized that although the investigation of subjective experiences is a difficult task, modern neuroscience need not and cannot shy away from the challenge of peeling away the mysteries of conscious experiences. In June 2023, with the joint support of the U.S. National Institutes of Health and the U.S. National Science Foundation, a 3-day workshop was held at the Bethesda, MD, campus of the National Institutes of Health, convening experts whose work focuses primarily on problems of consciousness, or an adjacent field, to discuss the current state of consciousness science and consider the most fruitful avenues for future research. This Special Focus features empirical and theoretical contributions from some of the invited speakers at the workshop. Here, I will cover the scope of the workshop, the content of this Special Focus, and advocate for stronger bridges between consciousness science and other subdisciplines of cognitive neuroscience.

Recent advances in open neuroimaging data are enhancing our comprehension of neuropsychiatric disorders. By pooling images from various cohorts, statistical power has increased, enabling the detection of subtle abnormalities and robust associations, and fostering new research methods. Global collaborations in imaging have furthered our knowledge of the neurobiological foundations of brain disorders and aided in imaging-based prediction for more targeted treatment. Large-scale magnetic resonance imaging initiatives are driving innovation in analytics and supporting generalizable psychiatric studies. We also emphasize the significant role of big data in understanding neural mechanisms and in the early identification and precise treatment of neuropsychiatric disorders. However, challenges such as data harmonization across different sites, privacy protection, and effective data sharing must be addressed. With proper governance and open science practices, we conclude with a projection of how large-scale imaging resources and collaborations could revolutionize diagnosis, treatment selection, and outcome prediction, contributing to optimal brain health.

High-speed wide-field fluorescence microscopy has the potential to capture biological processes with exceptional spatiotemporal resolution. However, conventional cameras suffer from low signal-to-noise ratio at high frame rates, limiting their ability to detect faint fluorescent events. Here, we introduce an image sensor where each pixel has individually programmable sampling speed and phase, so that pixels can be arranged to simultaneously sample at high speed with a high signal-to-noise ratio. In high-speed voltage imaging experiments, our image sensor significantly increases the output signal-to-noise ratio compared to a low-noise scientific CMOS camera (~2-3 folds). This signal-to-noise ratio gain enables the detection of weak neuronal action potentials and subthreshold activities missed by the standard scientific CMOS cameras. Our camera with flexible pixel exposure configurations offers versatile sampling strategies to improve signal quality in various experimental conditions.