Faculty Bibliography

The simplicity of programming the CRISPR (clustered regularly interspaced short palindromic repeats)-associated nuclease Cas9 to modify specific genomic loci suggests a new way to interrogate gene function on a genome-wide scale. We show that lentiviral delivery of a genome-scale CRISPR-Cas9 knockout (GeCKO) library targeting 18,080 genes with 64,751 unique guide sequences enables both negative and positive selection screening in human cells. First, we used the GeCKO library to identify genes essential for cell viability in cancer and pluripotent stem cells. Next, in a melanoma model, we screened for genes whose loss is involved in resistance to vemurafenib, a therapeutic RAF inhibitor. Our highest-ranking candidates include previously validated genes NF1 and MED12, as well as novel hits NF2, CUL3, TADA2B, and TADA1. We observe a high level of consistency between independent guide RNAs targeting the same gene and a high rate of hit confirmation, demonstrating the promise of genome-scale screening with Cas9.

Advances in cellular reprogramming and stem cell differentiation now enable ex vivo studies of human neuronal differentiation. However, it remains challenging to elucidate the underlying regulatory programs because differentiation protocols are laborious and often result in low neuron yields. Here, we overexpressed two Neurogenin transcription factors in human-induced pluripotent stem cells and obtained neurons with bipolar morphology in 4 days, at greater than 90% purity. The high purity enabled mRNA and microRNA expression profiling during neurogenesis, thus revealing the genetic programs involved in the rapid transition from stem cell to neuron. The resulting cells exhibited transcriptional, morphological and functional signatures of differentiated neurons, with greatest transcriptional similarity to prenatal human brain samples. Our analysis revealed a network of key transcription factors and microRNAs that promoted loss of pluripotency and rapid neurogenesis via progenitor states. Perturbations of key transcription factors affected homogeneity and phenotypic properties of the resulting neurons, suggesting that a systems-level view of the molecular biology of differentiation may guide subsequent manipulation of human stem cells to rapidly obtain diverse neuronal types.

The entorhinal cortex has been implicated in the early stages of Alzheimer's disease, which is characterized by changes in the tau protein and in the cleaved fragments of the amyloid precursor protein (APP). We used a high-resolution functional magnetic resonance imaging (fMRI) variant that can map metabolic defects in patients and mouse models to address basic questions about entorhinal cortex pathophysiology. The entorhinal cortex is divided into functionally distinct regions, the medial entorhinal cortex (MEC) and the lateral entorhinal cortex (LEC), and we exploited the high-resolution capabilities of the fMRI variant to ask whether either of them was affected in patients with preclinical Alzheimer's disease. Next, we imaged three mouse models of disease to clarify how tau and APP relate to entorhinal cortex dysfunction and to determine whether the entorhinal cortex can act as a source of dysfunction observed in other cortical areas. We found that the LEC was affected in preclinical disease, that LEC dysfunction could spread to the parietal cortex during preclinical disease and that APP expression potentiated tau toxicity in driving LEC dysfunction, thereby helping to explain regional vulnerability in the disease.

Three-dimensional (3D) bioimaging, visualization and data analysis are in strong need of powerful 3D exploration techniques. We develop virtual finger (VF) to generate 3D curves, points and regions-of-interest in the 3D space of a volumetric image with a single finger operation, such as a computer mouse stroke, or click or zoom from the 2D-projection plane of an image as visualized with a computer. VF provides efficient methods for acquisition, visualization and analysis of 3D images for roundworm, fruitfly, dragonfly, mouse, rat and human. Specifically, VF enables instant 3D optical zoom-in imaging, 3D free-form optical microsurgery, and 3D visualization and annotation of terabytes of whole-brain image volumes. VF also leads to orders of magnitude better efficiency of automated 3D reconstruction of neurons and similar biostructures over our previous systems. We use VF to generate from images of 1,107 Drosophila GAL4 lines a projectome of a Drosophila brain.

The perception of complex visual patterns emerges from neuronal activity in a cascade of areas in the primate cerebral cortex. We have probed the early stages of this cascade with "naturalistic" texture stimuli designed to capture key statistical features of natural images. Humans can recognize and classify these synthetic images and are insensitive to distortions that do not alter the local values of these statistics. The responses of neurons in the primary visual cortex, V1, are relatively insensitive to the statistical information in these textures. However, in the area immediately downstream, V2, cells respond more vigorously to these stimuli than to matched control stimuli. Humans show blood-oxygen-level-dependent functional magnetic resonance imaging (BOLD fMRI responses in V1 and V2) that are consistent with the neuronal measurements in macaque. These fMRI measurements, as well as neurophysiological work by others, show that true natural scenes become a more prominent driving feature of cortex downstream from V2. These results suggest a framework for thinking about how information about elementary visual features is transformed into the specific representations of scenes and objects found in areas higher in the visual pathway.

Oral flora are frequently found in normal individuals' lungs without known harm. We hypothesize that a lung microbiome enriched by oral taxa would be associated with a higher degree of inflammation. We studied 29 asymptomatic subjects (9 nonsmokers and 20 smokers) with preserved lung function. Nasal bronchoscopy was performed with two separate bronchoscopes to retrieve supraglotic and lower airway samples. Bronchoalveolar lavage (BAL) cell count, BAL cytokines (Luminex), and exhaled nitric oxide defined pulmonary inflammation. Quantitative PCR measured 16S rRNA gene concentration and 454 sequences defined the microbiome. Supraglotic samples had the highest 16S rRNA concentration, BAL was intermediate, and saline used for the BAL had the lowest concentration. Nonsmokers and smokers were similar in BAL cell differential and lung microbiome. BAL samples segregated into two distinct groups that we called pneumotypes. Pneumotype background predominant taxa (pneumotypeBPT) was similar to the saline background in rDNA concentration or microbial community. Pneumotype supraglotic-characteristic taxa (pneumotypeSCT) has higher rDNA concentration and high relative abundance of SCT, such as Prevotella and Veillonella. PneumotypeSCT was associated with multiple measures of lung inflammation, including higher BAL neutrophils, IL-8, and levels of exhaled nitric oxide. PneumotypeSCT also had higher BAL lymphocytes and fractalkine, a chemokine that correlates with T helper type 17:T regulatory cell ratio in the BAL. These data suggest that a pneumotype with high relative abundance of supraglotic bacteria, such as Prevotella and Veillonella, is associated with increased innate and cellular inflammation.

PURPOSE: Repeated computed tomography (CT) scans are required for some clinical applications such as image-guided interventions. To optimize radiation dose utility, a normal-dose scan is often first performed to set up reference, followed by a series of low-dose scans for intervention. One common strategy to achieve the low-dose scan is to lower the x-ray tube current and exposure time (mAs) or tube voltage (kVp) setting in the scanning protocol, but the resulted image quality by the conventional filtered back-projection (FBP) method may be severely degraded due to the excessive noise. Penalized weighted least-squares (PWLS) image reconstruction has shown the potential to significantly improve the image quality from low-mAs acquisitions, where the penalty plays an important role. In this work, the authors' explore an adaptive Markov random field (MRF)-based penalty term by utilizing previous normal-dose scan to improve the subsequent low-dose scans image reconstruction. METHODS: In this work, the authors employ the widely-used quadratic-form MRF as the penalty model and explore a novel idea of using the previous normal-dose scan to obtain the MRF coefficients for adaptive reconstruction of the low-dose images. In the coefficients determination, the authors further explore another novel idea of using the normal-dose scan to obtain a scale map, which describes an optimal neighborhood for the coefficients determination such that a local uniform region has a small spread of frequency spectrum and, therefore, a small MRF window, and vice versa. The proposed penalty term is incorporated into the PWLS image reconstruction framework, and the low-dose images are reconstructed via the PWLS minimization. RESULTS: The presented adaptive MRF based PWLS algorithm was validated by physical phantom and patient data. The experimental results demonstrated that the presented algorithm is superior to the PWLS reconstruction using the conventional Gaussian MRF penalty or the edge-preserving Huber penalty and the conventional FBP method, in terms of image noise reduction and edge/detail/contrast preservation. CONCLUSIONS: This study demonstrated the feasibility and efficacy of the proposed scheme in utilizing previous normal-dose CT scan to improve the subsequent low-dose scans.