Biology subjects

Wood, K. C.

Publications and source records attributed to Wood, K. C..

28 records · Page 2Linked to original sources

bioRxiv2020

Massively parallel quantification of phenotypic heterogeneity in single cell drug responses

Single cell analysis tools have made significant advances in characterizing genomic heterogeneity, however tools for measuring phenotypic heterogeneity have lagged due to the increased difficulty of handling live biology. Here, we report a single cell phenotyping tool capable of measuring image-based clonal properties at scales approaching 100,000 clones per experiment. These advances are achieved by exploiting a novel flow regime in ladder microfluidic networks that, under appropriate conditions, yield a mathematically perfect cell trap. Machine learning and computer vision tools are used to control the imaging hardware and analyze the cellular phenotypic parameters within these images. Using this platform, we quantified the responses of tens of thousands of single cell-derived acute myeloid leukemia (AML) clones to targeted therapy, identifying rare resistance and morphological phenotypes at frequencies down to 0.05%. This approach can be extended to higher-level cellular architectures such as cell pairs and organoids and on-chip live-cell fluorescence assays.

bioengineering↗

bioRxiv2020

Neuronal activity in sensory cortex predicts the specificity of learning.

Learning to avoid dangerous signals while preserving normal responses to safe stimuli is essential for everyday behavior and survival. Fear learning has a high level of inter-subject variability. Following identical experiences, subjects exhibit fear specificities ranging from high (specializing fear to only the dangerous stimulus) to low (generalizing fear to safe stimuli). Pathological fear generalization underlies emotional disorders, such as post-traumatic stress disorder. The neuronal basis of fear specificity remains unknown. Here, we identified the neuronal code that underlies inter-subject variability in fear specificity using longitudinal imaging of neuronal activity before and after differential fear conditioning in the auditory cortex of mice. Neuronal activity prior to, but not after learning predicted the level of specificity following fear conditioning across subjects. Stimulus representation in auditory cortex was reorganized following conditioning. However, the reorganized neuronal activity did not relate to the specificity of learning. These results present a novel neuronal code that determines individual patterns in learning.

neuroscience↗

bioRxiv2019

Genome-wide profiling of druggable active tumor defense mechanisms to enhance cancer immunotherapy

All current highly effective anti-tumor immunotherapeutics depend on the activity of T cells, but tumor cells can escape immune recognition by several mechanisms including loss of function in antigen presentation and inflammatory response genes, expression of immunomodulatory proteins and an immunosuppressive tumor microenvironment. In contrast, the comprehensive identification of strategies that sensitize tumor cells to immunotherapy in vivo has remained challenging. Here, we combine a two-cell type (2CT) whole-genome CRISPR-Cas9 screen with dynamic transcriptional analysis (DTA) of tumor upon T cell encounter to identify a set of genes that tumor cells express as an active defense against T cell-mediated killing. We then employed small molecule and biologic screens designed to antagonize gene products employed by tumor cells to actively defend against T cell-mediated tumor destruction and found that the inhibition of BIRC2, ITGAV or DNPEP enhanced tumor cell destruction by T cells. Mechanistically, we found that BIRC2 promoted immunotherapy resistance through inhibiting non-canonical NF-{kappa}B signaling and limiting inflammatory chemokine production. These findings show the path forward to improving T cell-mediated tumor destruction in the clinic.

immunology↗

bioRxiv2019

Signal processing in auditory cortex underlies degraded speech sound discrimination in noise

The ability to recognize sounds in noise is a key part of hearing, and the mechanisms by which the brain identifies sounds in noise are of considerable interest to scientists, clinicians and engineers. Yet we know little about the necessity of regions such as auditory cortex for hearing in noise, or how cortical processing of sounds is adversely affected by noise. Here we used reversible cortical inactivation and extracellular electrophysiology in ferrets performing a vowel discrimination task to identify and understand the causal contribution of auditory cortex to hearing in noise. Cortical inactivation by cooling impaired task performance in noisy but not clean conditions, while responses of auditory cortical neurons were less informative about vowel identity in noise. Simulations mimicking cortical inactivation indicated that effects of inactivation were related to the loss of information about sounds represented across neural populations. The addition of noise to target sounds drove spiking activity in auditory cortex and recruitment of additional neural populations that were linked to degraded behavioral performance. To suppress noise-related activity, we used continuous exposure to background noise to adapt the auditory system and recover behavioral performance in both ferrets and humans. Inactivation by cooling revealed that the benefits of continuous exposure were not cortically dependent. Together our results highlight the importance of auditory cortex in sound discrimination in noise and the underlying mechanisms through which noise-related activity and adaptation shape hearing.

neuroscience↗

bioRxiv2019

Evolved resistance to GAPDH inhibition results in loss of the Warburg Effect but retains a different state of glycolysis

Aerobic glycolysis or the Warburg Effect (WE) is characterized by increased glucose uptake and incomplete oxidation to lactate. Although ubiquitous, the biological role of the WE remains controversial and whether glucose metabolism is functionally different during fully oxidative glycolysis or during the WE is unknown. To investigate this question, we evolved resistance to koningic acid (KA), a natural product shown to be a specific inhibitor of glyceraldehyde-3-phosphate dehydrogenase (GAPDH), a rate-controlling glycolytic enzyme during the WE. We find that KA-resistant cells lose the WE but conduct glycolysis and surprisingly remain dependent on glucose and central carbon metabolism. Consequentially this altered state of glycolysis leads to differential metabolic activity and requirements including emergent activities in and dependencies on fatty acid metabolism. Together, these findings reveal that, contrary to some recent reports, aerobic glycolysis is a functionally distinct entity from conventional glucose metabolism and leads to distinct metabolic requirements and biological functions.

systems biology↗

bioRxiv2018

Stability of spontaneous, correlated activity in mouse auditory cortex

Neural systems can be modeled as complex networks in which neural elements are represented as nodes linked to one another through structural or functional connections. The resulting network can be analyzed using mathematical tools from network science and graph theory to quantify the systems topological organization and to better understand its function. While the network-based approach has become common in the analysis of large-scale neural systems probed by non-invasive neuroimaging, few studies have used network science to study the organization of biological neuronal networks reconstructed at the cellular level, and thus many very basic and fundamental questions remain unanswered. Here, we used two-photon calcium imaging to record spontaneous activity from the same set of cells in mouse auditory cortex over the course of several weeks. We reconstruct functional networks in which cells are linked to one another by edges weighted according to the maximum lagged correlation of their fluorescence traces. We show that the networks exhibit modular structure across multiple topological scales and that these multi-scale modules unfold as part of a hierarchy. We also show that, on average, network architecture becomes increasingly dissimilar over time, with similarity decaying monotonically with the distance (in time) between sessions. Finally, we show that a small fraction of cells maintain strongly-correlated activity over multiple days, forming a stable temporal core surrounded by a fluctuating and variable periphery. Our work provides a careful methodological blueprint for future studies of spontaneous activity measured by two-photon calcium imaging using cutting-edge computational methods and machine learning algorithms informed by explicit graphical models from network science. The methods are flexible and easily extended to additional datasets, opening the possibility of studying cellular level network organization of neural systems and how that organization is modulated by stimuli or altered in models of disease.

neuroscience↗

bioRxiv2018

Primary auditory cortex represents the location of sound sources in a cue-invariant manner

Auditory cortex is required for sound localisation, but how neural firing in auditory cortex underlies our perception of sources in space remains unknown. We measured spatial receptive fields in animals actively attending to spatial location while they performed a relative localisation task using stimuli that varied in the spatial cues that they provided. Manipulating the availability of binaural and spectral localisation cues had mild effects on the ferrets performance and little impact on the spatial tuning of neurons in primary auditory cortex (A1). Consistent with a representation of space, a subpopulation of neurons encoded spatial position across localisation cue types. Spatial receptive fields measured in the presence of a competing sound source were sharper than those measured in a single-source configuration. Together these observations suggest that A1 encodes the location of auditory objects as opposed to spatial cue values. We compared our data to predictions generated from two theories about how space is represented in auditory cortex: The two-channel model, where location is encoded by the relative activity in each hemisphere, and the labelled-line model where location is represented by the activity pattern of individual cells. The representation of sound location in A1 was mainly contralateral but peak firing rates were distributed across the hemifield consistent with a labelled line model in each hemisphere representing contralateral space. Comparing reconstructions of sound location from neural activity, we found that a labelled line architecture far outperformed two channel systems. Reconstruction ability increased with increasing channel number, saturating at around 20 channels.\n\nSignificance statementOur perception of a sound scene is one of distinct sound sources each of which can be localised, yet auditory space must be computed from sound location cues that arise principally by comparing the sound at the two ears. Here we ask: (1) do individual neurons in auditory cortex represent space, or sound localisation cues? (2) How is neural activity read out for spatial perception? We recorded from auditory cortex in ferrets performing a localisation task and describe a subpopulation of neurons that represent space across localisation cues. Our data are consistent with auditory space being read out using the pattern of activity across neurons (a labelled line) rather than by averaging activity within each hemisphere (a two-channel model).

neuroscience↗

bioRxiv2018

Label propagation defines signaling networks associated with recurrently mutated cancer genes

Each different tumor type has a distinct profile of genomic perturbations and each of these alterations causes unique changes to cellular homeostasis. Detailed analyses of these changes would reveal downstream effects of genomic alterations, contributing to our understanding of their roles in tumor development and progression. Across a range of tumor types, including bladder, lung, and endometrial carcinoma, we determined genes that are frequently altered in The Cancer Genome Atlas patient populations to study the effects of these alterations on signaling and regulatory pathways. To achieve this, we used a label propagation-based methodology to generate networks from gene expression signatures of mutations. Individual networks offered a comprehensive view of signaling changes represented by gene signatures, which in turn reflect the scope of molecular events that are perturbed in the presence of a given genomic alteration. Comparing different networks to each other revealed commonalities between them and biological pathways distinct genomic alterations converge on, highlighting the critical signaling events tumor dysregulate through multiple mechanisms. Finally, mutations inducing common changes to the signaling network were used to search for genomic markers of drug response, connecting shared perturbations to differential drug response.

bioinformatics↗

bioRxiv2018

Multisensory stimuli improve relative localisation judgments compared to unisensory auditory or visual stimuli

Observers performed a relative localisation task in which they reported whether the second of two sequentially presented signals occurred to the left or right of the first. Stimuli were detectability-matched auditory, visual, or auditory-visual signals and the goal was to compare changes in performance with eccentricity across modalities. Visual performance was superior to auditory at the midline, but inferior in the periphery, while auditory-visual performance exceeded both at all locations. No such advantage was seen when performance for auditory-only trials was contrasted with trials in which the first stimulus was auditory-visual and the second auditory only.

neuroscience↗

bioRxiv2017

Neural correlates of perceptual constancy in Auditory Cortex

Perceptual constancy requires neural representations that are selective for object identity, but also tolerant for identity-preserving transformations. How such representations arise in the brain and contribute to perception remains unclear. Here we studied tolerant representations of sound identity in the auditory system by recording multi-unit activity in tonotopic auditory cortex of ferrets discriminating the identity of vowels which co-varied across orthogonal stimulus dimensions (fundamental frequency, sound level, location and voicing). We found that neural decoding of vowel identity was most successful across the same orthogonal dimensions over which animals generalized their behavior. We also decoded orthogonal sound features and behavioral variables including choice and accuracy to show a behaviorally-relevant, multivariate and multiplexed representation of sound, with each variable represented over a distinct time-course. Finally, information content and timing of sound feature encoding was modulated by task-engagement and training, suggesting that tolerant representations during perceptual constancy are attentionally and experience-dependent.

neuroscience↗