An Optimal DNA Segmentation Based on the MDL Principle

The biological world is highly stochastic as well as inhomogeneous in its behavior. The transition between homogeneous and inhomogeneous regions of DNA, known also as change points, carry important biological information. Our goal is to employ rigorous methods of information theory to quantify structural properties of DNA sequences. In particular, we adopt the Stein-Ziv lemma to find asymptotically optimal discriminant function that determines whether two DNA segments are generated by the same source and assuring exponentially small false positives. Then we apply the Minimum Description Length (MDL) principle to select parameters of our segmentation algorithm. Finally, we perform extensive experimental work on human chromosome 9. After grouping A and G (purines) and T and C (pyrimidines) we discover change points between coding and noncoding regions as well as the beginning of a CpG island

Coordination of axonal transport revealed by particle tracking and quantitative immunofluorescence

Movement is intrinsic to life. Most forms of directed nanoscopic, microscopic and ultimately, macroscopic movement in cells is powered by tiny protein machines known as molecular motors. Microtubule-based motor proteins from the kinesin and dynein superfamilies are essential for many of these transport processes and coordinate to distribute various cellular cargos, including vesicles, organelles, protein complexes, and mRNAs to appropriate destinations within the cell. Due to the extreme compartmentalization of neurons, long range transport is particularly critical and recent advances suggests that these transport systems may fail early in the pathogenesis of a number of neurodegenerative diseases. Although substantial progress has been made to understand the underlying fundamentals, how these two opposite polarity motor protein families cooperate to generate coordinated bidirectional movement is poorly understood. This work reveals a number of novel features of coordinated axonal transport through robust particle tracking and quantitative immunofluorescence for two medically relevant classes of cargos; amyloid precursor protein (APP) and cellular prion protein (PrPC) vesicles. We developed a quantitative approach to analyze the axonal transport of YFP-tagged APP vesicles in Drosophila segmental nerves using heterozygous animals. This allowed us to assess the contribution of individual motor subunits and accessory proteins to coordinated axonal transport. Our approach yielded a novel model for how motor proteins work together to achieve bi-directional transport. We subsequently propose a robust image analysis method to assess relative motor subunit composition of individual endogenous APP vesicles in mouse hippocampal culture. Our data provides new insight on how select motor subunit and cargo attachment protein levels contribute to the overall architecture of these vesicles. Finally, we characterize the intracellular transport and steady-state motor subunit composition of mammalian PrPC vesicles. We suggest a coordination model wherein PrPC vesicles maintain a stable population of associated motors whose activity is modulated by regulatory factors instead of by structural changes to motor-cargo associations. Since disruption of this transport machinery has been implicated in numerous neurodegenerative diseases, such as Alzheimer's, Parkinson's, and ALS, elucidating the underlying fundamentals of this highly coordinated system is an essential part of understanding what happens during the progression of these devastating illnesse

Coordination of axonal transport revealed by particle tracking and quantitative immunofluorescence

Movement is intrinsic to life. Most forms of directed nanoscopic, microscopic and ultimately, macroscopic movement in cells is powered by tiny protein machines known as molecular motors. Microtubule-based motor proteins from the kinesin and dynein superfamilies are essential for many of these transport processes and coordinate to distribute various cellular cargos, including vesicles, organelles, protein complexes, and mRNAs to appropriate destinations within the cell. Due to the extreme compartmentalization of neurons, long range transport is particularly critical and recent advances suggests that these transport systems may fail early in the pathogenesis of a number of neurodegenerative diseases. Although substantial progress has been made to understand the underlying fundamentals, how these two opposite polarity motor protein families cooperate to generate coordinated bidirectional movement is poorly understood. This work reveals a number of novel features of coordinated axonal transport through robust particle tracking and quantitative immunofluorescence for two medically relevant classes of cargos; amyloid precursor protein (APP) and cellular prion protein (PrPC) vesicles. We developed a quantitative approach to analyze the axonal transport of YFP-tagged APP vesicles in Drosophila segmental nerves using heterozygous animals. This allowed us to assess the contribution of individual motor subunits and accessory proteins to coordinated axonal transport. Our approach yielded a novel model for how motor proteins work together to achieve bi-directional transport. We subsequently propose a robust image analysis method to assess relative motor subunit composition of individual endogenous APP vesicles in mouse hippocampal culture. Our data provides new insight on how select motor subunit and cargo attachment protein levels contribute to the overall architecture of these vesicles. Finally, we characterize the intracellular transport and steady-state motor subunit composition of mammalian PrPC vesicles. We suggest a coordination model wherein PrPC vesicles maintain a stable population of associated motors whose activity is modulated by regulatory factors instead of by structural changes to motor-cargo associations. Since disruption of this transport machinery has been implicated in numerous neurodegenerative diseases, such as Alzheimer's, Parkinson's, and ALS, elucidating the underlying fundamentals of this highly coordinated system is an essential part of understanding what happens during the progression of these devastating illnesse

Multimodal Single-Cell Analysis Reveals Physiological Maturation in the Developing Human Neocortex.

In the developing human neocortex, progenitor cells generate diverse cell types prenatally. Progenitor cells and newborn neurons respond to signaling cues, including neurotransmitters. While single-cell RNA sequencing has revealed cellular diversity, physiological heterogeneity has yet to be mapped onto these developing and diverse cell types. By combining measurements of intracellular Ca2+ elevations in response to neurotransmitter receptor agonists and RNA sequencing of the same single cells, we show that Ca2+ responses are cell-type-specific and change dynamically with lineage progression. Physiological response properties predict molecular cell identity and additionally reveal diversity not captured by single-cell transcriptomics. We find that the serotonin receptor HTR2A selectively activates radial glia cells in the developing human, but not mouse, neocortex, and inhibiting HTR2A receptors in human radial glia disrupts the radial glial scaffold. We show highly specific neurotransmitter signaling during neurogenesis in the developing human neocortex and highlight evolutionarily divergent mechanisms of physiological signaling

Fluidic Logic Used in a Systems Approach to Enable Integrated Single-cell Functional Analysis

The study of single cells has evolved over the past several years to include expression and genomic analysis of an increasing number of single cells. Several studies have demonstrated wide-spread variation and heterogeneity within cell populations of similar phenotype. While the characterization of these populations will likely set the foundation for our understanding of genomic- and expression-based diversity, it will not be able to link the functional differences of a single cell to its underlying genomic structure and activity. Currently, it is difficult to perturb single cells in a controlled environment, monitor and measure the response due to perturbation, and link these response measurements to downstream genomic and transcriptomic analysis. In order to address this challenge, we developed a platform to integrate and miniaturize many of the experimental steps required to study single-cell function. The heart of this platform is an elastomer-based Integrated Fluidic Circuit (IFC) that uses fluidic logic to select and sequester specific single cells based on a phenotypic trait for downstream experimentation. Experiments with sequestered cells that have been performed include on-chip culture, exposure to a variety of stimulants, and post-exposure image-based response analysis, followed by preparation of the mRNA transcriptome for massively parallel sequencing analysis. The flexible system embodies experimental design and execution that enable routine functional studies of single cells