Biology subjects

Sharpee, T. O.

Publications and source records attributed to Sharpee, T. O..

11 recordsLinked to original sources

bioRxiv2024

Low-dimensional olfactory signatures of fruit ripening and fermentation

Odors provide an important communication channel between plants and animals. Fruits, vital nutrient sources for animals, emit a complex array of monomolecular volatiles. Animals can use the structure of these mixtures to assess properties of fruit predictive of their nutritive and reproductive value. We analyzed the statistics of fruit odor mixtures sampled across stages of ripening and fermentation to find that they fall on a low-dimensional hyperbolic map. Hyperbolic maps, with their negative curvature and an exponentially expanding state options, are adept at describing hierarchical relationships in the data such as those arising from metabolic processes within fruits. In the hyperbolic map, samples followed a striking spiral trajectory. The spiral initiated near the maps core, representing the under-ripe phase with specific profiles of monomolecular volatiles. Progressively mapping along the unfolding spiral trajectory were scent mixtures corresponding to ripening, and then rotting or fermentation. The unfolding process depended on the specific fermentation processes that dominated in the samples, determined largely by the microbes (e.g. bacteria or yeast) present in the sample. These results generalized across fruit types and describe trajectories in the natural odorant space with significant behavioral relevance for insects.

neuroscience↗

bioRxiv2023

A Bayesian Approach to Non-Metric Hyperbolic Multi-Dimensional Scaling

This paper explores the intersection of hyperbolic geometry, non-metric techniques, and Bayesian frameworks to extend the capabilities of Bayesian Hyperbolic Multi-Dimensional Scaling (HMDS). While hyperbolic geometry is gaining attention for its ability to represent hierarchical relationships, traditional metrics impose constraints on distances. Non-metric techniques offer flexibility in capturing complex structures, making them suitable for scenarios where metric distances are less meaningful. The paper introduces a novel extension of Bayesian HMDS, incorporating non-metric techniques, enabling the embedding of Euclidean data within a hyperbolic space. The approach simultaneously fits for curvature and coordinates, leveraging the scaling properties of hyperbolic space. The non-metric Bayesian Hyperbolic MDS is expected to unveil new insights into hierarchical structures within complex datasets, providing a versa-tile tool for analyzing high-dimensional data flexibly and accurately. The efficacy of the proposed method is demonstrated through synthetic data experiments, showcasing its ability to capture non-linear transformations and accurately predict underlying curvature, with an emphasis on its ro-bustness to hyperparameter choices.

neuroscience↗

bioRxiv2023

Restructuring of olfactory representations in the fly brain around odor relationships in natural sources

A core challenge of olfactory neuroscience is to understand how neural representations of odor are generated and progressively transformed across different layers of the olfactory circuit into formats that support perception and behavior. The encoding of odor by odorant receptors in the input layer of the olfactory system reflects, at least in part, the chemical relationships between odor compounds. Neural representations of odor in higher order associative olfactory areas, generated by random feedforward networks, are expected to largely preserve these input odor relationships1-3. We evaluated these ideas by examining how odors are represented at different stages of processing in the olfactory circuit of the vinegar fly D. melanogaster. We found that representations of odor in the mushroom body (MB), a third-order associative olfactory area in the fly brain, are indeed structured and invariant across flies. However, the structure of MB representational space diverged significantly from what is expected in a randomly connected network. In addition, odor relationships encoded in the MB were better correlated with a metric of the similarity of their distribution across natural sources compared to their similarity with respect to chemical features, and the converse was true for odor relationships encoded in primary olfactory receptor neurons (ORNs). Comparison of odor coding at primary, secondary, and tertiary layers of the circuit revealed that odors were significantly regrouped with respect to their representational similarity across successive stages of olfactory processing, with the largest changes occurring in the MB. The non-linear reorganization of odor relationships in the MB indicates that unappreciated structure exists in the fly olfactory circuit, and this structure may facilitate the generalization of odors with respect to their co-occurence in natural sources.

neuroscience↗

bioRxiv2022

Microscopic Imaging of Epigenetic Age

Biomarkers of biological age that predict the risk of disease and expected lifespan better than chronological age are key to efficient and cost-effective healthcare1-3. To advance a personalized approach to healthcare, such biomarkers must perform on the individual rather than population level, demonstrate single cell resolution, and provide scalable and cost-effective measurements. We developed a novel approach - image-based chromatin and epigenetic age (ImAge), that utilizes image texture features based on the patterns of chromatin and epigenetic marks in single nuclei. We observed the emergence of intrinsic trajectories of ImAge using dimensionality reduction without regression on chronological age. ImAge was correlated with chronological age in all tissues and organs examined and was consistent with the expected acceleration and/or deceleration of biological age in chronologically identical mice treated with chemotherapy or following a caloric restriction regimen, respectively. ImAge from chronologically identical mice inversely correlated with their locomotor activity (greater activity for younger ImAge), consistent with the essential role of locomotion as an aging biomarker. Finally, we demonstrated that ImAge is reduced upon partial reprogramming in vivo following transient expression of OSKM cassette in the liver and skeletal muscles of old mice and validated the power of ImAge to assess the heterogeneity of reprogramming. We propose that ImAge represents the first-in-class individual-level biomarker of aging and rejuvenation with single-cell resolution.

systems biology↗

bioRxiv2022

A Bayesian Approach to Hyperbolic Multi-Dimensional Scaling

Recent studies have increasingly demonstrated that hyperbolic geometry confers many advantages for analyzing hierarchical structure in complex systems. However, available embedding methods do not give a precise metric for determining the dimensionality of the data, and do not vary curvature. These parameters are important for obtaining accurate, low dimensional, continuous descriptions of the data. To address this we develop a Bayesian formulation of Multi-Dimensional Scaling for embedding data in hyperbolic spaces that can fit for the optimal values of geometric parameters such as curvature and dimension. We propose a novel model of embedding uncertainty within this Bayesian framework which improves both performance and interpretability of the model. Because the method allows for variable curvature, it can also correctly embed Euclidean data using zero curvature, thus subsuming traditional Euclidean MDS models. We demonstrate that only a small amount of data is needed to constrain the geometry in our model and that the model is robust against false minima when scaling to large datasets. We apply our model to real world datasets and uncover new insights into their hierarchical structure derived from our geometric embeddings.

biophysics↗

bioRxiv2021

State dependence of neural networks on past history and stimulus presentation in Caenorhabditis elegans

Neurons represent changes in external and internal environments by altering their activity patterns. While coherent brain-wide patterns of neural activity have been observed in neuronal populations, very little is known about their dimensionality, geometry, and how they are correlated with sensory inputs. Here, we recorded the activity of most head neurons in Caenorhabditis elegans experiencing changes in bacterial or control buffer stimuli around their nose. We first classified active neurons into six functional clusters: two sensory neuron clusters (ON and OFF responding to addition and removal of stimuli, respectively) and four motor/command neuron clusters (AVA, RME, SMDD and SMDV). Next, we estimated stimulus selectivity for each cluster and found that while sensory neurons exhibit their maximal responses within 15 seconds, changes in bacterial stimuli drive maximal responses in command and motor neuron clusters after tens of seconds. Furthermore, we show that bacterial stimuli induce neural dynamics that are best described by a hyperbolic, not Euclidean, space, of dimensionality eight. The hyperbolic space provided a better description of neural activity than the standard Euclidean space. This space can be separated into three components - one sensory, and two motor directions (forward-backward and dorsal-ventral). Collectively, we show that C. elegans neural activity can be effectively represented in low-dimensional hyperbolic space to describe a sensorimotor transformation. Significance statementA major function of a nervous system is to transform sensory information into behavioral outputs. As the first receiver of sensory input, sensory neuronal activity is often most correlated with stimulus features. However, this sensory activity is modified as it travels to other neurons, where it integrates with network activity before altering motor neurons and driving corresponding behavior. Activity in non-sensory neurons is driven by ongoing network activity and sensory input, but distinguishing between their relative contributions is often difficult. Here, we identify two sensory and four command/motor neuron clusters in the C. elegans neural network responding to bacterial stimuli and define their receptive fields. We then use a hyperbolic embedding to identify how these clusters interact with each other and identify the relevant dimensions that might alter behavior. Our method is fully scalable to other systems, including those without neuronal identities, and allows us to attribute neural activity to network states and behavioral outputs.

neuroscience↗

bioRxiv2020

How inhibitory neurons increase information transmission under threshold modulation

Modulation of neuronal thresholds is ubiquitous in the brain. Phenomena such as figure-ground segmentation, motion detection, stimulus anticipation and shifts in attention all involve changes in a neurons threshold based on signals from larger scales than its primary inputs. However, this modulation reduces the accuracy with which neurons can represent their primary inputs, creating a mystery as to why threshold modulation is so widespread in the brain. We find that modulation is less detrimental than other forms of neuronal variability and that its negative effects can be nearly completely eliminated if modulation is applied selectively to sparsely responding neurons in a circuit by inhibitory neurons. We verify these predictions in the retina where we find that inhibitory amacrine cells selectively deliver modulation signals to sparsely responding ganglion cell types. Our findings elucidate the central role that inhibitory neurons play in maximizing information transmission under modulation.

neuroscience↗

bioRxiv2020

Spontaneous replication fork collapse regulates telomere length homeostasis in wild type cells

In most eukaryotes, the enzyme telomerase maintains the termini of linear chromosomes through the addition of repetitive telomeric sequences. It is widely assumed that the primary site of action for telomerase is the single-stranded G-rich overhang at the ends of linear chromosomes. We show here that a second substrate, created by spontaneous replication fork collapse during duplex telomeric DNA replication in wild type budding yeast, is elongated by telomerase at a much higher frequency ([~]50%) than fully replicated chromosome termini. Furthermore, as much as [~]200 nucleotides can be added in a single cell division to these newly collapsed forks, indicating that spontaneous replication fork collapse and the subsequent response by telomerase is a major determinant of telomere length homeostasis. This challenges a long-standing model for telomere length regulation which posits a length-sensing mechanism that assesses individual telomeres to determine whether chromosome ends are in "telomerase-extendible" or "telomerase-non-extendible" states. We propose that these two states are instead structurally and temporally distinct substrates for telomerase, generated by two different processes (fork collapse vs. completion of DNA replication). We also show that replication fork collapse at telomeres is kept in check by a telomere-dedicated Cdc13/Stn1/Ten1 complex in collaboration with the canonical RPA complex, indicating that these two complexes bind single-stranded DNA exposed at the replication fork to facilitate replisome progression through duplex telomeric DNA. Although failures during DNA replication are often genotoxic events, this represents an opposing example in which fork collapse has been co-opted to promote genome stability. Significance StatementIn most eukaryotes, the termini of linear chromosomes are composed of arrays of short repeats that are continually replenished by the enzyme telomerase. If telomerase is unable to act, gradual loss of these terminal repeats results in an eventual block to cell division. Therefore, in cells that depend on continuous cell division, the mechanism(s) by which telomerase is directed to chromosome ends is tightly regulated. This study shows that in addition to the ends of fully replicated chromosomes, a second site of action for telomerase is generated when replication through duplex telomeric DNA is disrupted. These results suggest that the disparate response of telomerase to two temporally and structurally distinct substrates is a major determinant of telomere length homeostasis.

genetics↗

bioRxiv2020

I ncreased accuracy of signaling by hyperbolic odorant mixtures in a beneficial insect-plant relationship

Animals use odors in many natural contexts, for example, for finding mates or food, or signaling danger. Most analyses of natural odors search for either the most meaningful components of a natural odor mixture, or they use linear metrics to analyze the mixture compositions. However, we have recently shown that the physical space for complex mixtures is hyperbolic, meaning that there are certain combination of variables that have a disproportionately large impact on perception and that these variables have specific interpretation in terms of metabolic processes taking place inside the flower and fruit that produce the odors. Here we show that the statistics of odorants and odorant mixtures produced by inflorescences (Brassica rapa) are also better described with a hyperbolic rather than a linear metric, and that combinations of odorants in the hyperbolic space are better predictors of the nectar and pollen resources sought by bee pollinators than the standard Euclidian combinations. We also show that honey bee and bumble bee antennae can detect most components of the B. rapa odor space, and the strength of responses correlates with positions of odorants in the hyperbolic space. In sum, a hyperbolic representation can be used to guide investigation of how information is represented at different levels of processing in the CNS.

animal behavior and cognition↗

bioRxiv2017

Quantifying the thermostability landscape separating plant sesquiterpene synthase orthologs using Maximum Entropy

As global temperatures rise due to climate change, crops are becoming increasingly vulnerable to failure. We tested the accessibility of thermodynamic phenotypic diversity within limited positional changes using 29=512 mutants of a terpene synthase (TPS), Tobacco 5-epi-Aristolchene synthase. First, we measured the thermal unfolding curves of each mutant and found that mutations shifted the Tms both higher and lower, including a cohort of mutants that failed to fold. The low correlation coefficient between the Tms of these mutants and the proportions of each terpene product output by the enzymes revealed that thermostability and product output are independent traits. Maximum Noise Entropy analyses were used to analyze the impact of the 9 mutational positions on thermostability, revealing that three of these positions were mainly responsible for the trait of increased Tm. These positions form a functional network as measured by the nonlinearity of their combined effects on thermostability. Unexpectedly, the strongly destabilizing positions combine nonlinearly to ameliorate each others deleterious effects resulting in a synergistic dampening. Taken together, our study shows the high potential for specialized metabolic enzyme engineering but also reveals a complex interconnected system of amino acids that will continue to evade perfect predictability.

bioengineering↗

bioRxiv2017

Neural mechanisms driving hunger-induced changes in sensory perception and behavior in Caenorhabditis elegans

Animals integrate changes in external and internal environments to generate behavior. While neural circuits detecting external cues have been mapped, less is known about how internal states like hunger are integrated into behavioral outputs. We use the nematode C. elegans to decode how changes in internal nutritional status affects chemosensory behaviors. We show that acute food deprivation leads to a reversible decline in repellent, but not attractant, sensitivity. This behavioral change requires two conserved transcription factors MML-1 (Mondo A) and HLH-30 (TFEB), both of which translocate from the intestinal nuclei to the cytoplasm upon food deprivation. Next, we identify insulin-like peptides INS-23 and INS-31 as candidate ligands relaying food-status signals from the intestine to other tissues. Furthermore, we show that ASI chemosensory neurons use the DAF-2 insulin receptor, PI-3 Kinase, and the mTOR complex to integrate these intestine-released peptides. Together, our study shows how internal food status signals are integrated by transcription factors and intestine-neuron signaling to generate flexible behaviors. Author SummaryWe have all experienced behavioral changes when we are hungry - the pang in our stomach can cause us to behave erratically. In particular, hungry animals, including humans, are known to pursue behaviors that involve higher risk compared to when they are well-fed. Here we explore the molecular details of this behavior in the invertebrate animal model C. elegans. This behavior, termed sensory integration, shows that C. elegans display reduced copper sensitivity when hungry. Copper is toxic and repellant to C. elegans; reduced avoidance indicates that these animals use riskier food search behaviors when they are hungry. Luckily, like us, this behavioral change is reversible upon re-feeding. This hunger-induced behavioral change is not due to increased attraction to food or depletion of fat stores, but rather insulin signaling between the intestine and specific neurons. We use genetic tools, microscopy, and behavioral tests to determine that this risky behavior involves sensation of "lack of food" in the intestine, release of signaling molecules, and engagement with sensory neurons. Our work highlights new and potentially evolutionarily conserved ways in which intestinal cells and neurons communicate leading to largescale behavioral change, providing further support for the importance of the gut-brain-axis.

neuroscience↗