Instructor, Psychiatry and Behavioral Sciences
Fellowship:Department of Psychiatry, School of Medicine, Stanford University Hospital
Board Certification: Child and Adolescent Psychiatry, American Board of Psychiatry and Neurology (2014)
Fellowship:New York Presbyterian Hospital of Columbia and Cornell Universities (2014) NY
Residency:Yale University (2012) CT
Medical Education:Harvard Medical School (2009) MA
Massachusetts Institute of Technology (2005) MA
Board Certification: Psychiatry, American Board of Psychiatry and Neurology (2013)
Multiplexed Intact-Tissue Transcriptional Analysis at Cellular Resolution
2016; 164 (4): 792-804
In recently developed approaches for high-resolution imaging within intact tissue, molecular characterization over large volumes has been largely restricted to labeling of proteins. But volumetric nucleic acid labeling may represent a far greater scientific and clinical opportunity, enabling detection of not only diverse coding RNA variants but also non-coding RNAs. Moreover, scaling immunohistochemical detection to large tissue volumes has limitations due to high cost, limited renewability/availability, and restricted multiplexing capability of antibody labels. With the goal of versatile, high-content, and scalable molecular phenotyping of intact tissues, we developed a method using carbodiimide-based chemistry to stably retain RNAs in clarified tissue, coupled with amplification tools for multiplexed detection. The resulting technology enables robust measurement of activity-dependent transcriptional signatures, cell-identity markers, and diverse non-coding RNAs in rodent and human tissue volumes. The growing set of validated probes is deposited in an online resource for nucleating related developments from across the scientific community.
View details for DOI 10.1016/j.cell.2016.01.038
View details for Web of Science ID 000369998300023
View details for PubMedID 26871636
The Three-Dimensional Architecture of a Bacterial Genome and Its Alteration by Genetic Perturbation
2011; 44 (2): 252-264
We have determined the three-dimensional (3D) architecture of the Caulobacter crescentus genome by combining genome-wide chromatin interaction detection, live-cell imaging, and computational modeling. Using chromosome conformation capture carbon copy (5C), we derive ~13 kb resolution 3D models of the Caulobacter genome. The resulting models illustrate that the genome is ellipsoidal with periodically arranged arms. The parS sites, a pair of short contiguous sequence elements known to be involved in chromosome segregation, are positioned at one pole, where they anchor the chromosome to the cell and contribute to the formation of a compact chromatin conformation. Repositioning these elements resulted in rotations of the chromosome that changed the subcellular positions of most genes. Such rotations did not lead to large-scale changes in gene expression, indicating that genome folding does not strongly affect gene regulation. Collectively, our data suggest that genome folding is globally dictated by the parS sites and chromosome segregation.
View details for DOI 10.1016/j.molcel.2011.09.010
View details for Web of Science ID 000296212100011
View details for PubMedID 22017872
Choreography of the Transcriptome, Photophysiology, and Cell Cycle of a Minimal Photoautotroph, Prochlorococcus
2009; 4 (4)
The marine cyanobacterium Prochlorococcus MED4 has the smallest genome and cell size of all known photosynthetic organisms. Like all phototrophs at temperate latitudes, it experiences predictable daily variation in available light energy which leads to temporal regulation and partitioning of key cellular processes. To better understand the tempo and choreography of this minimal phototroph, we studied the entire transcriptome of the cell over a simulated daily light-dark cycle, and placed it in the context of diagnostic physiological and cell cycle parameters. All cells in the culture progressed through their cell cycles in synchrony, thus ensuring that our measurements reflected the behavior of individual cells. Ninety percent of the annotated genes were expressed, and 80% had cyclic expression over the diel cycle. For most genes, expression peaked near sunrise or sunset, although more subtle phasing of gene expression was also evident. Periodicities of the transcripts of genes involved in physiological processes such as in cell cycle progression, photosynthesis, and phosphorus metabolism tracked the timing of these activities relative to the light-dark cycle. Furthermore, the transitions between photosynthesis during the day and catabolic consumption of energy reserves at night- metabolic processes that share some of the same enzymes--appear to be tightly choreographed at the level of RNA expression. In-depth investigation of these patterns identified potential regulatory proteins involved in balancing these opposing pathways. Finally, while this analysis has not helped resolve how a cell with so little regulatory capacity, and a 'deficient' circadian mechanism, aligns its cell cycle and metabolism so tightly to a light-dark cycle, it does provide us with a valuable framework upon which to build when the Prochlorococcus proteome and metabolome become available.
View details for DOI 10.1371/journal.pone.0005135
View details for Web of Science ID 000265505700022
View details for PubMedID 19352512
Chromosomal periodicity of evolutionarily conserved gene pairs
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2007; 104 (25): 10559-10564
Chromosomes are compacted hundreds of times to fit in the cell, packaged into dynamic folds whose structures are largely unknown. Here, we examine patterns in gene locations to infer large-scale features of bacterial chromosomes. Specifically, we analyzed >100 genomes and identified thousands of gene pairs that display two types of evolutionary correlations: a tendency to co-occur and a tendency to be located close together in many genomes. We then analyzed the detailed distribution of these pairs in Escherichia coli and found that genes in a pair tend to be separated by integral multiples of 117 kb along the genome and to be positioned in a 117-kb grid of genomic locations. In addition, the most pair-dense locations coincide with regions of intense transcriptional activity and the positions of top transcribed and conserved genes. These patterns suggest that the E. coli chromosome may be organized into a 117-kb helix-like topology that localizes a subset of the most essential and highly transcribed genes along a specific face of this structure. Our approach indicates an evolutionarily maintained preference in the spacing of genes along the chromosome and offers a general comparative genomics framework for studying chromosome structure, broadly applicable to other organisms.
View details for Web of Science ID 000247500000047
View details for PubMedID 17563360
From annotated genomes to metabolic flux models and kinetic parameter fitting.
Omics : a journal of integrative biology
2003; 7 (3): 301-316
Significant advances in system-level modeling of cellular behavior can be achieved based on constraints derived from genomic information and on optimality hypotheses. For steady-state models of metabolic networks, mass conservation and reaction stoichiometry impose linear constraints on metabolic fluxes. Different objectives, such as maximization of growth rate or minimization of flux distance from a reference state, can be tested in different organisms and conditions. In particular, we have suggested that the metabolic properties of mutant bacterial strains are best described by an algorithm that performs a minimization of metabolic adjustment (MOMA) upon gene deletion. The increasing availability of many annotated genomes paves the way for a systematic application of these flux balance methods to a large variety of organisms. However, such a high throughput goal crucially depends on our capacity to build metabolic flux models in a fully automated fashion. Here we describe a pipeline for generating models from annotated genomes and discuss the current obstacles to full automation. In addition, we propose a framework for the integration of flux modeling results and high throughput proteomic data, which can potentially help in the inference of whole-cell kinetic parameters.
View details for PubMedID 14583118
On the complete determination of biological systems
TRENDS IN BIOTECHNOLOGY
2003; 21 (6): 251-254
The nascent field of systems biology ambitiously proposes to integrate information from large-scale biology projects to create computational models that are, in some sense, complete. However, the details of what would constitute a complete systems-level model of an organism are far from clear. To provide a framework for this difficult question it is useful to define a model as a set of rules that maps a set of inputs (e.g. descriptions of the cell's environment) to a set of outputs (e.g. the concentrations of all its RNAs and proteins). We show how the properties of a model affect the required experimental sampling and estimate the number of experiments needed to "complete" a particular model. Based on these estimates, we suggest that the complete determination of a biological system is a concrete, achievable goal.
View details for DOI 10.1016/S0167-7799(03)00113-6
View details for Web of Science ID 000183621400005
View details for PubMedID 12788544
- An open-source oligomicroarray standard for human and mouse NATURE BIOTECHNOLOGY 2002; 20 (11): 1082-1083