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Exon-skipping antisense oligonucleotides for cystic fibrosis therapy
Get PDFMutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene cause cystic fibrosis (CF), and the CFTR-W1282X nonsense mutation causes a severe form of CF. Although Trikafta and other CFTR-modulation therapies benefit most CF patients, targeted therapy for patients with the W1282X mutation is lacking. The CFTR-W1282X protein has residual activity but is expressed at a very low level due to nonsense-mediated messenger RNA (mRNA) decay (NMD). NMD-suppression therapy and read-through therapy are actively being researched for CFTR nonsense mutants. NMD suppression could increase the mutant CFTR mRNA, and read-through therapies may increase the levels of full-length CFTR protein. However, these approaches have limitations and potential side effects: because the NMD machinery also regulates the expression of many normal mRNAs, broad inhibition of the pathway is not desirable, and read-through drugs are inefficient partly because the mutant mRNA template is subject to NMD. To bypass these issues, we pursued an exon-skipping antisense oligonucleotide (ASO) strategy to achieve gene-specific NMD evasion. A cocktail of two splice-site-targeting ASOs induced the expression of CFTR mRNA without the premature-termination-codon-containing exon 23 (CFTR-Δex23), which is an in-frame exon. Treatment of human bronchial epithelial cells with this cocktail of ASOs that target the splice sites flanking exon 23 results in efficient skipping of exon 23 and an increase in CFTR-Δex23 protein. The splice-switching ASO cocktail increases the CFTR-mediated chloride current in human bronchial epithelial cells. Our results set the stage for developing an allele-specific therapy for CF caused by the W1282X mutation
Convergent selection of a WD40 protein that enhances grain yield in maize and rice
No full textA better understanding of the extent of convergent selection among crops could greatly improve breeding programs. We found that the quantitative trait locus KRN2 in maize and its rice ortholog, OsKRN2, experienced convergent selection. These orthologs encode WD40 proteins and interact with a gene of unknown function, DUF1644, to negatively regulate grain number in both crops. Knockout of KRN2 in maize or OsKRN2 in rice increased grain yield by ~10% and ~8%, respectively, with no apparent trade-offs in other agronomic traits. Furthermore, genome-wide scans identified 490 pairs of orthologous genes that underwent convergent selection during maize and rice evolution, and these were enriched for two shared molecular pathways. KRN2, together with other convergently selected genes, provides an excellent target for future crop improvement
Direct and indirect neurogenesis generate a mosaic of distinct glutamatergic projection neuron types and cortical subnetworks
No full textVariations in size and complexity of the cerebral cortex result from differences in neuron number and composition, which are rooted in evolutionary changes in direct and indirect neurogenesis (dNG and iNG) mediated by radial glial progenitors and intermediate progenitors, respectively. How dNG and iNG differentially contribute to cortical neuronal number, diversity, and connectivity are unknown. Establishing a genetic fate-mapping method to differentially visualize dNG and iNG in mice, we found that while both dNG and iNG contribute to all cortical structures, iNG contributes the largest relative proportions to the hippocampus and neocortex compared to insular and piriform cortex, claustrum, and the pallial amygdala. Within the neocortex, whereas dNG generates all major glutamatergic projection neuron (PN) classes, iNG differentially amplifies and diversifies PNs within each class; the two neurogenic pathways generate distinct PN types and assemble fine mosaics of lineage-based cortical subnetworks. Our results establish a ground-level lineage framework for understanding cortical development and evolution by linking foundational progenitor types and neurogenic pathways to PN types
Standard metadata for 3D microscopy
Get PDFRecent advances in fluorescence microscopy techniques and tissue clearing, labeling, and staining provide unprecedented opportunities to investigate brain structure and function. These experiments' images make it possible to catalog brain cell types and define their location, morphology, and connectivity in a native context, leading to a better understanding of normal development and disease etiology. Consistent annotation of metadata is needed to provide the context necessary to understand, reuse, and integrate these data. This report describes an effort to establish metadata standards for three-dimensional (3D) microscopy datasets for use by the Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative and the neuroscience research community. These standards were built on existing efforts and developed with input from the brain microscopy community to promote adoption. The resulting 3D Microscopy Metadata Standards (3D-MMS) includes 91 fields organized into seven categories: Contributors, Funders, Publication, Instrument, Dataset, Specimen, and Image. Adoption of these metadata standards will ensure that investigators receive credit for their work, promote data reuse, facilitate downstream analysis of shared data, and encourage collaboration
Higher-order epistasis and phenotypic prediction
Get PDFContemporary high-throughput mutagenesis experiments are providing an increasingly detailed view of the complex patterns of genetic interaction that occur between multiple mutations within a single protein or regulatory element. By simultaneously measuring the effects of thousands of combinations of mutations, these experiments have revealed that the genotype-phenotype relationship typically reflects not only genetic interactions between pairs of sites but also higher-order interactions among larger numbers of sites. However, modeling and understanding these higher-order interactions remains challenging. Here we present a method for reconstructing sequence-to-function mappings from partially observed data that can accommodate all orders of genetic interaction. The main idea is to make predictions for unobserved genotypes that match the type and extent of epistasis found in the observed data. This information on the type and extent of epistasis can be extracted by considering how phenotypic correlations change as a function of mutational distance, which is equivalent to estimating the fraction of phenotypic variance due to each order of genetic interaction (additive, pairwise, three-way, etc.). Using these estimated variance components, we then define an empirical Bayes prior that in expectation matches the observed pattern of epistasis and reconstruct the genotype-phenotype mapping by conducting Gaussian process regression under this prior. To demonstrate the power of this approach, we present an application to the antibody-binding domain GB1 and also provide a detailed exploration of a dataset consisting of high-throughput measurements for the splicing efficiency of human pre-mRNA [Formula: see text] splice sites, for which we also validate our model predictions via additional low-throughput experiments
High-throughput sequencing of single neuron projections reveals spatial organization in the olfactory cortex
No full textIn most sensory modalities, neuronal connectivity reflects behaviorally relevant stimulus features, such as spatial location, orientation, and sound frequency. By contrast, the prevailing view in the olfactory cortex, based on the reconstruction of dozens of neurons, is that connectivity is random. Here, we used high-throughput sequencing-based neuroanatomical techniques to analyze the projections of 5,309 mouse olfactory bulb and 30,433 piriform cortex output neurons at single-cell resolution. Surprisingly, statistical analysis of this much larger dataset revealed that the olfactory cortex connectivity is spatially structured. Single olfactory bulb neurons targeting a particular location along the anterior-posterior axis of piriform cortex also project to matched, functionally distinct, extra-piriform targets. Moreover, single neurons from the targeted piriform locus also project to the same matched extra-piriform targets, forming triadic circuit motifs. Thus, as in other sensory modalities, olfactory information is routed at early stages of processing to functionally diverse targets in a coordinated manner
BRCA mutational status shapes the stromal microenvironment of pancreatic cancer linking clusterin expression in cancer associated fibroblasts with HSF1 signaling
Get PDFTumors initiate by mutations in cancer cells, and progress through interactions of the cancer cells with non-malignant cells of the tumor microenvironment. Major players in the tumor microenvironment are cancer-associated fibroblasts (CAFs), which support tumor malignancy, and comprise up to 90% of the tumor mass in pancreatic cancer. CAFs are transcriptionally rewired by cancer cells. Whether this rewiring is differentially affected by different mutations in cancer cells is largely unknown. Here we address this question by dissecting the stromal landscape of BRCA-mutated and BRCA Wild-type pancreatic ductal adenocarcinoma. We comprehensively analyze pancreatic cancer samples from 42 patients, revealing different CAF subtype compositions in germline BRCA-mutated vs. BRCA Wild-type tumors. In particular, we detect an increase in a subset of immune-regulatory clusterin-positive CAFs in BRCA-mutated tumors. Using cancer organoids and mouse models we show that this process is mediated through activation of heat-shock factor 1, the transcriptional regulator of clusterin. Our findings unravel a dimension of stromal heterogeneity influenced by germline mutations in cancer cells, with direct implications for clinical research
Perceptual Categorization and Neural Representations of Vocal Stimuli
Get PDFThe ability to identify and categorize sensory stimuli is critical for the survival of organisms. While this behavior has been well characterized across multiple sensory modalities and multiple species, from invertebrates to humans, the neural mechanisms that drive this behavior remain a point of interest. In particular, we wanted to focus our efforts on how natural auditory stimuli are categorized, how those categories shift over time, and
how those categories are represented in the auditory cortex. To study this, we took advantage of pup retrieval, a maternal mouse behavior where maternally experienced female mice will locate and retrieve pups separated from their home nest by utilizing ultrasonic vocalizations emitted from the pups. I describe how we studied this in this thesis, divided into five chapters. In the first chapter, I provide an overview of the field in regards to the auditory cortex and how sensory stimuli are categorized, as well as why pup retrieval can be a valuable model to study auditory categorization. In Chapters 2 and 3, I describe two behaviors, one freely moving and one a head-fixed Go No-Go task, which demonstrate how mice categorize auditory cues with pup calls. More specifically, I demonstrate how frequency seems to be one of the most important features in driving mice to categorize sounds as pup calls. However, if other spectrotemporal features of the sound are similar to that of the pup call, mice are more willing to tolerate differences in the frequency. Furthermore, I show that the
presence of a low frequency band can inhibit the mouse’s ability to categorize a sound as a pup call. In Chapter 4, I describe single unit electrophysiology data that demonstrates how auditory cortex neurons respond towards full pup call trains as well as other broadband stimuli. In particular, I show that neurons in the auditory cortex of surrogate females have earlier responses towards pup calls compared to naïve females, and that these early responses also exist in response to narrow, high frequency bands. Furthermore, I show how low frequency sounds seem to be more correlated in their responses compared to high frequency ones both in naïve and surrogate females. I also show that following behavioral training, low frequency bandlimited noise becomes even more correlated, while high frequency bandlimited noise does not change. Finally, in Chapter 5, I describe my results in the context of the field as well as propose several follow up experiments which would support and expand our findings
Sorghum root epigenetic landscape during limiting phosphorus conditions
Get PDFEfficient acquisition and use of available phosphorus from the soil is crucial for plant growth, development, and yield. With an ever-increasing acreage of croplands with suboptimal available soil phosphorus, genetic improvement of sorghum germplasm for enhanced phosphorus acquisition from soil is crucial to increasing agricultural output and reducing inputs, while confronted with a growing world population and uncertain climate. Sorghum bicolor is a globally important commodity for food, fodder, and forage. Known for robust tolerance to heat, drought, and other abiotic stresses, its capacity for optimal phosphorus use efficiency (PUE) is still being investigated for optimized root system architectures (RSA). Whilst a few RSA-influencing genes have been identified in sorghum and other grasses, the epigenetic impact on expression and tissue-specific activation of candidate PUE genes remains elusive. Here, we present transcriptomic, epigenetic, and regulatory network profiling of RSA modulation in the BTx623 sorghum background in response to limiting phosphorus (LP) conditions. We show that during LP, sorghum RSA is remodeled to increase root length and surface area, likely enhancing its ability to acquire P. Global DNA 5-methylcytosine and H3K4 and H3K27 trimethylation levels decrease in response to LP, while H3K4me3 peaks and DNA hypomethylated regions contain recognition motifs of numerous developmental and nutrient responsive transcription factors that display disparate expression patterns between different root tissues (primary root apex, elongation zone, and lateral root apex)
Synthesis and Structure-Activity relationships of cyclin-dependent kinase 11 inhibitors based on a diaminothiazole scaffold
No full textCyclin-dependent kinases (CDK) are attractive targets for drug discovery due to their wide range of cellular functions. CDK11 is an understudied CDK with roles in transcription and splicing, cell cycle regulation, neuronal function, and apoptosis. In this study, we describe a medicinal chemistry campaign to identify a CDK11 inhibitor. Employing a promising but nonselective CDK11-targeting scaffold (JWD-047), extensive structure-guided medicinal chemistry modifications led to the identification of ZNL-05-044. A combination of biochemical evaluations and NanoBRET cellular assays for target engagement guided the SAR towards a 2,4-diaminothiazoles CDK11 probe with significantly improved kinome-wide selectivity over JWD-047. CDK11 inhibition with ZNL-05-044 leads to G2/M cell cycle arrest, consistent with prior work evaluating OTS964, and impacts CDK11-dependent mRNA splicing in cells. Together, ZNL-05-044 serves as a tool compound for further optimization and interrogation of the consequences of CDK11 inhibition