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Details of the Exhibit
No full textDetails of the exhibit E.G.D. Cohen: A Leader in Statistical Physics
Idea, design - Olga Nilova, Special Collections Librarian
Photo by Lubosh Stepanekhttps://digitalcommons.rockefeller.edu/cohen-leader-in-statistical-physics/1023/thumbnail.jp
Details of the Exhibit
No full textDetails of the exhibit E.G.D. Cohen: A Leader in Statistical Physics
Idea, design - Olga Nilova, Special Collections Librarian
Photo by Lubosh Stepanekhttps://digitalcommons.rockefeller.edu/cohen-leader-in-statistical-physics/1016/thumbnail.jp
Details of the Exhibit
No full textDetails of the exhibit E.G.D. Cohen: A Leader in Statistical Physics
Dr. E.G.D. Cohen at the 2007 Honorary Degree Dinner
Dr. E.G.D. Cohen retired from Rockefeller in 1993 but remained scientifically active. He moved to Iowa City, Iowa, in 2015 to be near his family even as he continued to collaborate and publish through 2016. His last paper was published in August of 2017 in Physical Review.https://digitalcommons.rockefeller.edu/cohen-leader-in-statistical-physics/1027/thumbnail.jp
Dissecting Host-Viral Interactons Through Focused or Unbiased High-Throughput Genetic Approaches
Full text linkIn the world around us, viruses surround and vastly outnumber us. Indeed, there are roughly 1 sextillion—or one thousand million million million—times as many viral particles as humans on earth (1). While most of these viruses do not cause disease in humans, those that do present a grave and increasing threat to human health. Fundamental studies in host-viral interactions are thus critical to further our understanding of the parameters of viral infection and elucidate potential new treatments. Since, as obligate intracellular parasites, viruses rely on host resources at every step of the viral lifecycle, in-depth knowledge of how viruses hijack human proteins, and how cells have evolved defense mechanisms to prevent this, can reveal insights with potential therapeutic relevance. In my graduate work, I employed a variety of approaches—targeted mutagenesis and loss of function studies, genome-scale CRISPR screens, and focused CRISPR screens—to gain mechanistic insight of host-viral interactions, focusing on the human immunodeficiency virus type 1 (HIV-1) and the human coronaviruses (HCoVs). I begin this thesis by providing an overview of the viral lifecycle and highlighting the potential utility of targeting each step in the viral lifecycle for therapeutic purposes, exemplified by current FDA-approved therapies. I continue by examining the utility of each of three major methodologies I utilized in my thesis for uncovering new insights with potential significance for designing novel antiviral approaches. Next, I recount the mechanistic insights gained by studies performed in my thesis work using these approaches. Finally, I conclude by discussing potential therapeutic relevance of the insights uncovered by this thesis work
On the High-Dimensional Geometry of Neuronal Population Dynamics
No full textThe brain\u27s remarkable computational properties arise from the collective activity of up to billions of densely interconnected neurons. Neurotechnologies to simultaneously measure the activity of many neurons have been steadily developed over the past decades, with mesoscopic optical imaging now reaching tens of thousands or more neurons in a single experiment. These data have only opened up additional fundamental questions on how the neuronal population code enables robust yet flexible computation from the highly variable activities of single neurons. Here, we utilized large-scale optical imaging to investigate how neuronal population dynamics are structured across diverse brain regions during spontaneous and variable behaviors. In the first part, we investigated the dimensionality and spatiotemporal structure of cortex-wide dynamics during spontaneous and uninstructed behaviors in the mouse, encompassing up to one million neurons recorded simultaneously and at multi-Hertz volume rates. While more than a decade of work has suggested that neuronal population dynamics appear to lie on low-dimensional manifolds that capture a large degree of neural variance and other sensorimotor features, recent evidence has suggested that ongoing dynamics in the brain exhibit higher dimensionality than previously appreciated. We found that the measured dimensionality of neuronal dynamics is even more high-dimensional than previously shown, and that the measured dimensionality scaled in an unbounded fashion with the number of recorded neurons. Within these dimensions, covarying ensembles of neurons were highly distributed across the entire dorsal cortex and relatively few were related to spontaneous behavior, suggesting that the majority of identified neural dimensions uniquely captured by large-scale recording were related to purely internal processing. Next, we switched our focus to the larval zebrafish in order to ask how highdimensional whole-brain dynamics produce population codes that are robust yet flexible enough to generate variable behaviors. To do so, we honed in on a regime of visual object size — between those that elicit hunting and avoidance behaviors — which induced maximum behavioral variability. We found that the visual encoding of object size is robust at the population level, despite the highly variable activity of single neurons. This robustness despite variability was due to the multi-dimensional geometry of the neuronal population dynamics: trial-to-trial noise modes were largely orthogonal to sensory encoding dimensions. Finally, we showed that these many of these noise modes were actually related to the larva\u27s behavior. Within this variability, we identified two brain-wide neuronal populations whose pre-motor activity predicted whether the larva would respond to a stimulus and, if so, which direction it would turn on a single-trial level. These populations were able to predict such single-trial behavior even seconds before the stimulus onset, suggesting they encoded time-varying internal biases that modulated the larva\u27s behavior, perhaps organizing behavior over longer timescales. In both the mouse and larval zebrafish, we found that neuronal population dynamics were extremely high-dimensional; mixed at the single neuron level, which can initially appear as noisy variability, but robust and highly structured at the population level; spatiotemporally structured in covarying ensembles that are distributed brain-wide; and dominated by the encoding of motor behavior and behaviorallyrelevant information, even in non-motor areas such as primary sensory regions
Inter-Organellar Nucleic Acid Communication by a Mitochondrial tRNA Regulates Nuclear Transcription
Full text linkBalancing metabolic demands with transcriptional output requires efficient communication between mitochondria and the nucleus. However, the mitochondrial factors that mediate signals to the nucleus remain poorly defined. In eukaryotes, the mitochondrial genome encodes transfer RNAs (mito-tRNAs) that function in mitochondrial-specific translation. Here, we report the detection of multiple mito-tRNAs within the nucleus of human cells. Focused studies of one such nuclear-transported mito-tRNA-asparagine (mito-tRNA-Asn) revealed that its cognate charging enzyme (NARS2) is also present in the nucleus. Nuclear localization of mito-tRNA-Asn and NARS2 was dependent on the VDAC1 mitochondrial channel and importin-α nuclear transport factor, respectively. Mito-tRNA-Asn promoted the interaction of NARS2 with histone deacetylase 2 (HDAC2) and repressed HDAC2 association with chromatin. Accordingly, inhibiting tRNA-dependent NARS2-HDAC2 complex formation licensed HDAC2 binding to target gene loci and elicited transcriptional silencing. Interfering with the mito-tRNA-Asn/NARS2/HDAC2 axis elicited metabolomic alterations in glycolytic and TCA intermediates, amino acids, and nucleotide biosynthesis. Importantly, mitotRNA- dependent transcriptional repression of glutaminase diverted glutamine towards the synthesis and maintenance of nucleotide pools, and enhanced cancer cell growth. These findings uncover nucleic-acid mediated communication between two organelles and the existence of a machinery for nuclear gene control by a mito-tRNA that restricts growth through metabolic control
Replaying Life\u27s Tape With Intraclonal Germinal Center Evolution
Full text linkBecause high-affinity antibodies produced by germinal centers (GCs) are critical in protecting against the ever-increasing array of pathogens, understanding how GC response allows our immune system to recognize a variety of pathogens and develop specific and effective immunity against each pathogen encounters are important. We gained insight into how GCs modulate clonal diversity in recent years, including a discovery that individual B cells clones can occasionally undergo clonal bursts that eliminate clonal diversity through massive proliferation. However, it remains unclear what are the factors driving such bursts, or whether GCs respond reproducibly to similar magnitude increases in affinity, mainly because answering such a question would require an experiment that repeats the same GC responses many times to disentangle affinity-based GC selection events from stochastic noise influenced by local circumstances. In this thesis, I investigated how GCs might respond to given increases in affinity by exploring how stochasticity and determinism work together in GCs to shape the course of affinity maturation and modulate the resulting clonal diversity. In the first part of this thesis, I demonstrate that a B cell clone (clone 2.1) specific for the model antigen chicken IgY (chIgY) that previously triggered a clonal burst has potential to increase its affinity much further than the 7-fold jump that triggered the burst itself. Affinity maturation in vivo can generate up to a ~90-fold increase in affinity over 10 weeks of immune response, whereas a ~380-fold increase in affinity was achieved by artificially engineering the combination of mutations that has previously occurred in GCs. In the second part of this thesis, I take a reductionist approach to generate reproducible GC responses by starting GCs with the same chIgY-specific B cells so that many GCs with the same starting condition can be replayed and analyzed repeatedly for their outcomes in terms of selection. In the third part of this thesis, I demonstrate that phylogenetic trees structures have low reproducibility based on statistical measures that we employed to describe tree shapes. The outcome of replay GCs were found to be as diverse as polyclonal responses. In the fourth part of this thesis, I interrogate the impact of all possible individual amino acid (aa) mutations on antibody binding and expression of clone 2.1 through deep mutational scanning (DMS) and cryo-electron microscopy (CryoEM). DMS elucidated that chIgY B cells must avoid ~13 deleterious mutations in order to make one affinityincreasing mutations. CryoEM revealed that central paratope of clone 2.1 is largely optimal in its ability to bind chIgY, but it can be further improved by changing the periphery of its contact residues or leverage allosteric fine-tuning to optimize antibody geometry. In the fifth part of this thesis, I investigate how GCs respond to affinity improvements by combining DMS data to replay trees. In contrast to the broad diversity of outcomes observed at the phylogenetic level, GCs were found to reproducibly increase their median affinity. However, clonal bursting was not restricted to B cells with the highest affinity increases, and successful affinity maturation was not favored by specific tree shapes, suggesting that clonal bursts are not a primary driver of affinity increases in GCs. Instead, affinity maturation of clone 2.1 is driven primarily by elimination of B cells that largely lost affinity and marginally stronger expansion of B cells with small improvements in affinity, especially at earlier time points
Details of the Exhibit
No full textDetails of the exhibit E.G.D Cohen: A Leader in Statistical Physics
Idea, design: Olga Nilova, Special Collections Librarian
Photo by Lubosh Stepanekhttps://digitalcommons.rockefeller.edu/cohen-leader-in-statistical-physics/1004/thumbnail.jp
Using Chemical Probes to Examine Cellular Activities
Full text linkChemical probes are valuable tools for investigating rapid cellular processes, such as anaphase in cell division, by allowing for the modulation of protein activity over the course of minutes. In addition, resistance to chemical probes by mutation can provide insight into inhibitor binding interactions and may provide morphological pharmacodynamic markers that allow for the identification of drug resistance or sensitivity. Here, I present a two-part thesis in which I (i) explore the role of spastin during late anaphase and nuclear envelope reformation using our recently developed spastin inhibitor and (ii) use inhibitor resistance to identify morphological markers of drug resistance via high-content microscopy. In the first part of my thesis, I use chemical probes to examine spastin\u27s role in cell division. Spastin is a AAA (ATPases associated with diverse cellular activities) protein that is recruited in anaphase by the endosomal sorting complex required for transport (ESCRT) to the reforming nuclear envelope, where spastin is proposed to sever stable microtubules. However, we currently lack an understanding of spastin\u27s dynamics during anaphase, particularly the roles of microtubules and ESCRT proteins in said dynamics. Using live cell imaging and chemical probes that inhibited spastin\u27s ATPase activity (spastazoline) or affected microtubules (nocodazole, taxol, or monastrol), I quantified spastin dynamics during anaphase. Spastin foci accumulated on the periphery of chromosomes and were similar on the spindle pole-facing and midzone-facing sides of chromosomes. However, foci that colocalized with microtubules persisted longer than microtubule-free foci. Inhibiting spastin with spastazoline resulted in more stable microtubule-proximal foci compared to microtubule-free foci. Spastazoline had no measurable effect on the accumulation of the ESCRT-III protein, charged multivesicular body protein 4B (CHMP4B). Together, these data suggest that spastin dynamics during late anaphase are decoupled from ESCRT dynamics and are instead modulated by the presence of microtubules and spastin\u27s ATPase activity. In the second part of my thesis, I use chemical probes to examine morphological markers of drug resistance. Drug resistance is a confounding factor in the treatment of many diseases, particularly cancers, where uncontrolled and error-prone cell divisions can give rise to resistance-conferring mutations. While identifying drug-resistant cell populations in advance could help personalize therapeutics and prevent delays in administering effective treatments, we currently lack rapid methods for broadly analyzing drug resistance. Here, I help generate drug-resistant cell lines and image these cells using Cell Painting, a high-content microscopy method, to characterize morphological markers of resistance. Working in collaboration with colleagues at the Broad Institute, we found that our data support the identification of resistant cell lines using profiles generated from high-content microscopy. This work suggests that image-based cell profiling may be a valuable method of identifying drug-resistant or -sensitive cells and could be a useful tool to guide therapeutic strategies
Life on the Edge: Insights into the Neural and Behavioral Algorithms of Plume Tracking
No full textAnimals use turbulent odor plumes as chemical beacons to navigate long distances. What are the neural and behavioral algorithms that underlie such a navigational feat? While plume navigation has been conventionally described as a simple sensory reflex, animals may instead rely on their memories of past plume encounters and current assessment of the wind direction to pursue a dynamic odor source. Differentiating between these strategies has been challenging due to the fact that plumes are invisible and spatially complex, precluding an understanding of the exact sensory experience of an animal. We have been leveraging the concise architecture of the Drosophila olfactory and navigational circuitry to elucidate the neural mechanisms underlying odor navigation. We developed a virtual reality environment compatible with two-photon functional imaging that allows a walking head-fixed fly to navigate naturalistic odor landscapes, offering unique insight into the sensory signals and behavioral algorithms animals use for navigation. We find that flies track an appetitive odor plume by ascending upwind along its boundaries through a repeated pattern of upwind counter-turning inside and biased local exploration outside of the plume, a robust navigational strategy we term edge-tracking. Through modeling and behavioral perturbations of the fictive olfactory environment, we demonstrate that edge-tracking represents a form of spatial navigation in which flies must continually remember the direction of the plume\u27s boundary. Using calcium imaging and optogenetic perturbations of specific neuronal populations, we reveal that edge-tracking relies on the mushroom body and central complex, two highly interconnected brain centers implicated in olfactory learning and spatial navigation. In particular, the ongoing activity of dopaminergic neurons of the mushroom body previously implicated in associative learning shapes edge-tracking behavior over multiple timescales and is necessary for continued pursuit of the plume. Moreover, compass neurons within the central complex, a navigational center, carry a high-fidelity representation of the animal\u27s heading relative to the wind direction, and inhibiting these neurons prevents flies from remembering the location of the plume\u27s boundary. Together our work suggests how ongoing neuromodulation ultimately shapes navigational performance by reinforcing sensory, spatial or motor actions necessary to return to the plume\u27s edge. These studies highlight that instead of relying on simple sensory reflexes, flies use their sophisticated learning and navigational circuitry to track odor plumes, a feature likely to be shared between insect and mammalian brains