Biology subjects

Goyal, S.

Publications and source records attributed to Goyal, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

Representations of carbon dioxide in the mosquito antennal lobe

Carbon dioxide (CO2) is one of the prominent sensory cues used by mosquitoes to find hosts for blood-feeding. CO2 is detected on the maxillary palps by capitate peg sensory neurons, whose axons project to the antennal lobe in the brain. Behavioral studies have shown that mosquitoes prefer non-homogenous plumes of CO2 over homogenous plumes and CO2 greatly enhances the attractiveness of lactic acid, a skin volatile. However, the neural mechanisms underlying these behavioral preferences are not known. Using in vivo intracellular recordings from projection neurons and local neurons in the antennal lobe, along with single sensillum recordings from the maxillary palps, we checked the representations of CO2 in the first two layers of the Aedes aegypti olfactory system. We found that the preference to non-homogeneous plumes of CO2 and its synergistic attraction with lactic acid are encoded in the PN population responses. Our results provide a foundation for understanding CO2-mediated host-attraction in mosquitoes.

neuroscience↗

bioRxiv2023

Limitations and Optimizations of Cellular Lineages Tracking

Tracking cellular lineages using barcodes provides insights across biology and has become an important tool. However, barcoding strategies remain ad-hoc. We show that elevating barcode insertion probability, and thus increasing the average number of barcodes within the cells, adds to the number of traceable lineages but decreases the accuracy of lineages inference due to reading errors. We discuss how this tradeoff informs optimal experimental design under different constraints and limitations. In particular, we explore the trade-off between accuracy and the number of traceable lineages, concerning limited resources, the cells and barcode pool features, and the dropout probability.

biophysics↗

bioRxiv2023

Promoting diversity in ecological systems through toxin production

Toxins are used by microbes to kill and compete, and hence, unlike cross-feeding from secondary metabolites, they are less often considered as a candidate to promote diversity in a microbial community. In contrast, some natural communities hint at the possibility that the presence of toxin genes and externally supplied antibiotics may support higher diversity. We address this gap with a model that shows how toxins in small and medium-sized communities can indeed promote diversity. The central idea of the model emerges from the combination of bacterial growth laws of resource partitioning and recent experiments suggesting a trade-off between toxin sensitivity and nutrient efficiency. The second puzzle in natural data is the presence of both negative and positive regulation of toxin production under similar environmental stress. Our model shows how this diversity in regulation of toxin production can promote toxin-producer fitness. In general, we provide a framework to integrate the role of toxins in microbial communities. Significance statementStructured organization of microbial communities into functional groups (consumers and producers) has been a framework to understand diverse populations. This framework leaves out the impact of toxin producers, which kill rather than provide the others with benefits, on diversification. Surprisingly, natural microbial communities show a correlation between the number of toxin genes in a community and its diversity. Our work shows how physiological constraints and trade-offs for individual bacteria can lead to a diverse, structured population where toxin-producers serve as a keystone species. This provides a pathway towards toxin production being established as a viable strategy in a diverse population: releasing toxins allows the survival of the less competitive strains, which would otherwise be driven towards extinction by competitive exclusion.

biophysics↗

bioRxiv2023

Fluctuations and entropy enable neural crest cell ingression

The second law of thermodynamics explains the dissipative nature of embryonic development as an exchange of energy-dependent order for proportionately greater output of heat and waste. Recent work on granular matter provides a path by which to define the roles of passive, stochastic mechanisms in nonequilibrium systems. Here, we apply such a framework to examine the role of thermodynamic parameters to cell ingression, the movement of cells from one tissue layer to another that has been attributed, in part, to directional cues. Using the murine neural crest as a model system, we provide evidence that a stochastic mechanism, rather than a proposed stiffness gradient, underlies cell ingression. Cortical fluctuations representing effective temperature and cell packing configurations generate an entropic trap that promotes cell ingression. The results imply dissipative mechanisms that transiently disorder tissue underlie some morphogenetic events.

developmental biology↗

bioRxiv2022

Fatecode: Cell fate regulator prediction using classification autoencoder perturbation

Cell reprogramming, which guides the conversion between cell states, is a promising technology for tissue repair and regeneration. Typically, a group of key genes, or master regulators, are manipulated to control cell fate, with the ultimate goal of accelerating recovery from diseases or injuries. Of importance is the ability to correctly identify the master regulators from single-cell transcriptomics datasets. To accomplish that goal, we propose Fatecode, a computational method that combines in silico perturbation experiments with cell trajectory modeling using deep learning to predict master regulators and key pathways controlling cell fate. Fatecode uses only scRNA-seq data from wild-type samples to learn and predict how cell type distribution changes following a perturbation. We assessed Fatecodes performance using simulations from a mechanistic gene regulatory network model and diverse gene expression profiles covering blood and brain development. Our results suggest that Fatecode can detect known master regulators of cell fate from single-cell transcriptomics datasets. That capability points to Fatecodes potential in accelerating the discovery of cell fate regulators that can be used to engineer and grow cells for therapeutic use in regenerative medicine applications.

systems biology↗

bioRxiv2022

Improved Yield for the Enzymatic Synthesis of Radiolabeled Nicotinamide Adenine Dinucleotide

Labeled {beta}-nicotinamide adenine dinucleotide (NAD) analogs have been critical for uncovering new biochemical connections and quantitating enzymatic activity. They function as tracers for enzymology, flux analyses, and in situ measurements. Nevertheless, there is limited availability of specific types of analogs, especially radiolabeled NAD analogs. Here, we describe an improved enzymatic synthesis reaction for 32P-NAD+ with a yield of 98% {+/-} 1%, using lowered concentrations of reactants and standard equipment. This represents the highest reported yield for the enzymatic synthesis of NAD+ to date. With the high yield we were able to directly use the reaction product to generate derivatives, such as 32P-NADP. The high-yield enzymatic synthesis is versatile for a broad variety of labels and NAD derivatives. Its advantages include lowered concentrations of reactants, providing sufficient amounts of product for downstream applications, and minimizing intermediate purification steps.

biochemistry↗

bioRxiv2022

Dynamics of Mitochondrial NAD+ Import Reveal Preference for Oxidized Ligand and Substrate Led Transport

SLC25A51 is a member of the mitochondrial carrier family (MCF) but lacks key residues that have been attributed to the mechanism of other nucleotide MCF transporters. Thus, how SLC25A51 transports NAD+ across the inner mitochondrial membrane remains unclear. To elucidate its mechanism, we used Molecular Dynamic simulations to study reconstituted SLC25A51 homology models in lipid bilayers. We observed spontaneous binding of cardiolipin phospholipids to three distinct sites on the exterior of SLC25A51s central pore and found that mutation of these sites impaired transporter activity. We also observed that stable formation of the required matrix gate was controlled by a single salt bridge. Using simulation data and in-cell activity assays we identified binding sites in SLC25A51 for NAD+ and showed that its binding was guided by an electrostatic interaction between NAD+ and a negatively charged patch in the pore. In turn, interaction of NAD+ with interior residue E132 guided the ligand to dynamically engage and weaken the salt bridge gate, representing a ligand-induced initiation of transport. SignificanceNAD+ is an intermediary metabolite whose multiple functions are entwined with respiration, catabolism, and stress responses in cells. Previous sensor measurements had indicated that its continuous biosynthesis was required to sustain mitochondrial matrix levels in respiring cells, and SLC25A51 was identified as the required importer of NAD+ across the inner mitochondrial membrane. However, SLC25A51 has little homology to other nucleotide carriers at its substrate binding site. By combining modeling approaches and experimental assays, this work provides mechanistic insight into how human SLC25A51 recognizes its ligand, how the transporter can be regulated by its lipid environment, and an observation of ligand-induced gate opening. This represents the first description of the ligand binding site for an NAD+ mitochondrial carrier.

biochemistry↗

bioRxiv2022

A Machine-learning-based Method to Detect Degradation of Motor Control Stability with Applications to Diagnosis of Presymptomatic Parkinson's Disease

Parkinsons disease (PD), a neuro-degenerative disorder, is often detected by onset of its motor symptoms such as rest tremor. Unfortunately, motor symptoms appear only when approximately 40%-60% of the dopaminergic neurons in the substantia nigra are lost. In most cases, by the time PD is clinically diagnosed, the disease may already have started 4 to 6 years beforehand. So there is a need for developing a test for detecting PD before the onset of the motor symptoms. This phase of PD is referred to as Presymptomatic PD (PPD). The motor symptoms of Parkinsons Disease are manifestations of instability in the sensorimotor system that develops gradually due to the neuro-degenerative process. In this paper, based on the above insight, we propose a new method that can potentially be used to detect degradation of motor control stability which can be employed for the detection of PPD. The proposed method tracks the tendency of a feedback control system to transition to an unstable state, and uses machine learning algorithm for its robust detection. This method is explored using simulations of a simple pendulum with PID controller as a conceptual representation for both healthy and PPD individuals. We also propose an example task with physiological measurements that can be used with this method and potentially be employed in a clinical setting. We present representative data collected through such a task, thereby demonstrating the feasibility to generate data for the proposed method. Author summaryParkinsons disease (PD) is a neuro-degenerative disorder that develops and progresses over several years. Currently, one is able to diagnose PD only after the appearance of motor symptoms (symptoms in movements of body parts), which unfortunately may be 4 to 6 years after the neuro-degeneration may have started. It has been shown that there are benefits to diagnosing PD at early stages, motivating the need to explore tools for diagnosing PD in the pre-symptomatic stage referred to as Presymptomatic Parkinsons disease (PPD). In this paper, a novel approach is explored that utilises the insight that the motor symptoms in PD may be seen as an instability in the feedback-control system that controls movements of body parts (sensory-motor loop). The proposed method uses a series of simple movement tasks performed by an individual in a clinic as the input to detect any gradual degradation of movement control that is leading to an instability, but before the instability and consequently the symptoms are manifested. This method is tested through extensive simulations and a potential experimental realisation with preliminary data. While a full-fledged validation will be undertaken as part of future work, initial results show promise and feasibility of further data collection.

bioinformatics↗

bioRxiv2022

Plasticity and interactions in the odor responses of maxillary palps neurons in Aedes aegypti

Maxillary palps, in addition to the antennae, are major olfactory organs in mosquitoes and play an important role in the detection of human hosts. The sensory neurons of the maxillary palps reside in the capitate peg sensilla, each of which contains three neurons. In Aedes aegypti, the neuron with the largest spike amplitude in the sensillum is known to detect carbon dioxide. However, the responses of the other two neurons and the functional consequences of the grouping of these neurons within sensilla are not well understood. Here we identify odorants that activate the other two neurons. We detect a short-term plasticity in the odor-evoked local field potential of the sensillum and show that it originates in the spiking responses of the smallest-amplitude neuron, even though all three neurons contribute to the local field potential. We also detect inhibitory interactions among these neurons within the sensillum. We further show that the plasticity and the lateral interactions are functionally important as they affect the responses of the downstream projection neurons in the antennal lobe.

neuroscience↗

bioRxiv2022

Inferring single-cell dynamics with structured dynamical representations of RNA velocity

Gene expression dynamics provide directional information for trajectory inference from single-cell RNA-sequencing data. Traditional approaches compute local RNA velocity using strict assumptions about the equations describing transcription and splicing of RNA. Not surprisingly, these approaches fail where these assumptions are violated, such as in multiple lineages with distinct gene dynamics or time-dependent kinetic rates of transcription and splicing. In this work we present "LatentVelo", a novel approach to compute a low-dimensional representation of gene dynamics with deep learning. Our approach embeds cells into a latent space with a variational auto-encoder, and describes differentiation dynamics on this latent space with neural ordinary differential equations. These more general dynamics enable accurate trajectory inference, and the latent space approach enables the generation of a latent "dynamics-based" embedding of cell states. To model multiple distinct lineages, LatentVelo infers a latent regulatory state that controls the dynamics of an individual cell. With these lineage-specific dynamics LatentVelo can predict latent trajectories, describing global inferred developmental path for individual cells, rather than just outputting local RNA velocity vectors. The dynamics-based embedding also enables concurrent batch correction of cell states and RNA velocity, outperforming comparable auto-encoder based batch correction methods that do not consider gene expression dynamics. Finally, the flexible structure of LatentVelo enables additional of new regulatory constraints required to integrate multiomic data. LatentVelo is available at https://github.com/Spencerfar/LatentVelo.

bioinformatics↗

bioRxiv2022

The ELF3 transcription factor is associated with an epithelial phenotype and represses epithelial-mesenchymal transition

Epithelial-mesenchymal plasticity (EMP) involves bidirectional transitions between epithelial, mesenchymal and multiple intermediary hybrid epithelial/mesenchymal phenotypes. While the process of epithelial-mesenchymal transition (EMT) and its associated transcription factors are well-characterised, the transcription factors that promote mesenchymal-epithelial transition (MET) and stabilise hybrid E/M phenotypes are less well understood. Here, we analyse multiple publicly-available transcriptomic datasets at bulk and single-cell level and pinpoint ELF3 as a factor that is strongly associated with an epithelial phenotype and is inhibited during EMT. Using mechanism-based mathematical modelling, we also show that ELF3 inhibits the progression of EMT, suggesting ELF3 may be able to counteract EMT induction, including in the presence of EMT-inducing factors, such as WT1. Our model predicts that the MET induction capacity of ELF3 is stronger than that of KLF4, but weaker than that of GRHL2. Finally, we show that ELF3 levels correlates with worse patient survival in a subset of solid tumor types, suggesting cell-of-origin or lineage specificity in the prognostic capacity of ELF3.

cancer biology↗

bioRxiv2022

Dynamics of immune memory and learning in bacterialcommunities

1From bacteria to humans, adaptive immune systems provide learned memories of past infections. Despite their vast biological differences, adaptive immunity shares features from microbes to vertebrates such as emergent immune diversity, long-term coexistence of hosts and pathogens, and fitness pressures from evolving pathogens and adapting hosts, yet there is no conceptual model that addresses all of these together. To address these questions, we propose and solve a simple phenomenological model of CRISPR-based adaptive immunity in microbes. We show that in coexisting phage and bacteria populations, immune diversity in both populations emerges spontaneously and in tandem, that bacteria track phage evolution with a context-dependent lag, and that high levels of diversity are paradoxically linked to low overall CRISPR immunity. We define average immunity, an important summary parameter predicted by our model, and use it to perform synthetic time-shift analyses on available experimental data to reveal different modalities of coevolution. Finally, immune cross-reactivity in our model leads to qualitatively different states of evolutionary dynamics, including an influenza-like traveling wave regime that resembles a similar state in models of vertebrate adaptive immunity. Our results show that CRISPR immunity provides a tractable model, both theoretically and experimentally, to understand general features of adaptive immunity.

biophysics↗

bioRxiv2022

3D-Printing in Radiation Oncology: Development and Validation of Custom 3D-Printed Brachytherapy Alignment Device and Phantom

Brachytherapy seeks to treat cancer through insertion of radioactive sources aligned by needles within standardized blocking templates. However, many patients have anatomy that does not conform to standard tools. We created a 3D printed device to provide customized needle alignment for a patient. Device was validated through CT scan and treatment plan creation on a custom anatomical phantom based on patient data. CT scan of a cervix tumor from anonymized patient data was used to develop a 3D printed brachytherapy alignment tool and phantom anatomical mold. Multiple materials were evaluated to match patient anatomy in density and Hounsfield Units present on CT scan, with additional considerations for toxicity, compliance, and practicality. Alignment device and molds were developed in PLA. Silicone of T20 hardness was used to create relevant anatomical organs (Uterus, Rectum, Bladder). Tumor tissue was mimicked by addition of 1CC of Iodine contrast agent to silicone. Device and needles were arranged, inserted into anatomical phantom, and scanned by CT to mimic brachytherapy procedure. 3D printed Silicone uterus of 1.08 g/cm^3 and 40 HU mimicked human uterus on CT scan. Constructed uterus dimensions of 6.5 cm x 5.5 cm x 3.3 cm were verified on imaging to be within + 1 mm of original patient scan. The 1 CC of contrast agent provided sufficient differentiation of "tumor" ring from "tissue." CT scan and treatment plan creation verified that the alignment device provided correction insertion of needles into the phantom tumor tissue and uterus. This pilot study provides a potential methodology to develop future anatomical phantoms and alignment devices from CT scans of patient data. Additional modifications could make this a viable training tool for future residents and medical students to learn brachytherapy. Key PointsO_LI3D printing can be leveraged to create a Brachytherapy alignment device from patients anatomy. C_LIO_LIAnatomical phantom can be generated from 3D printing for use testing device or for training. C_LIO_LIRelevant materials to create phantom that mimic patients anatomy on CT scan. C_LIO_LIGeneration of a treatment plan based on CT scan was able to validate device and phantom C_LI

bioengineering↗

bioRxiv2022

Combinatorial encoding of odors in the mosquito antennal lobe

Among the cues that a mosquito uses to find a host for blood-feeding, the smell of the host plays an important role. Previous studies have shown that host odors contain hundreds of chemical odorants, which are detected by different receptors on the peripheral sensory organs of mosquitoes. But how individual odorants are encoded by downstream neurons in the mosquito brain is not known. We developed an in vivo preparation for patch-clamp electrophysiology to record from projection neurons and local neurons in the antennal lobe of Aedes aegypti. Combining intracellular recordings with dye-fills, morphological reconstructions, and immunohistochemistry, we identify different sub-classes of antennal lobe neurons and their putative interactions. Our recordings show that an odorant can activate multiple neurons innervating different glomeruli, and that the stimulus identity and its behavioral preference are represented in the population activity of the projection neurons. Our results provide the first detailed description of olfactory neurons in the central nervous system of mosquitoes and lay a foundation for understanding the neural basis of their olfactory behaviors.

neuroscience↗

bioRxiv2022

Characterization of the minimal residual disease state reveals distinct evolutionary trajectories of human glioblastoma

Recurrence of solid tumors renders patients vulnerable to a distinctly advanced, highly treatment-refractory disease state that has an increased mutational burden and novel oncogenic drivers not detected at initial diagnosis. Improving outcomes for recurrent cancers requires a better understanding of cancer cell populations that expand from the post-therapy, minimal residual disease (MRD) state. We profiled barcoded tumor stem cell populations through therapy at tumor initiation/engraftment, MRD and recurrence in our therapy-adapted, patient-derived xenograft models of glioblastoma (GBM). Tumors showed distinct patterns of recurrence in which clonal populations exhibited either an a priori, pre-existing fitness advantage, or a priori equipotency fitness acquired through therapy. Characterization of the MRD state by single-cell and bulk RNA sequencing revealed a tumor-intrinsic immunomodulatory signature with strong prognostic significance at the transcriptomic level and in proteomic analysis of cerebrospinal fluid (CSF) collected from GBM patients at all stages of disease. Our results provide insight into the innate and therapy-driven dynamics of human GBM, and the prognostic value of interrogating the MRD state in solid cancers.

cancer biology↗

bioRxiv2022

Mosquito Olfactory Response Ensemble: a curated database of behavioral and electrophysiological responses enables pattern discovery

Many experimental studies have examined behavioral and electrophysiological responses of mosquitoes to odors. However, the differences across studies in data collection, processing, and reporting make it difficult to perform large-scale analyses combining data from multiple studies. Here we extract and standardize data for 12 mosquito species, along with Drosophila melanogaster for comparison, from over 170 studies and curate the Mosquito Olfactory Response Ensemble (MORE), publicly available at https://neuralsystems.github.io/MORE. We demonstrate the ability of MORE in generating biological insights by finding patterns across studies. Our analyses reveal that ORs are tuned to specific ranges of several physicochemical properties of odorants; the empty-neuron recording technique for measuring OR responses is more sensitive than the Xenopus oocyte technique; there are systematic differences in the behavioral preferences reported by different types of assays; and odorants tend to become less attractive or more aversive at higher concentrations.

neuroscience↗

bioRxiv2021

Contingency and selection in mitochondrial genome dynamics

Eukaryotic cells contain numerous copies of mitochondrial DNA (mtDNA), allowing for the coexistence of mutant and wild-type mtDNA in individual cells. The fate of mutant mtDNA depends on their relative replicative fitness within cells and the resulting cellular fitness within populations of cells. Yet the dynamics of the generation of mutant mtDNA and features that inform their fitness remain unaddressed. Here we utilize long read single-molecule sequencing to track mtDNA mutational trajectories in Saccharomyces cerevisiae. We show a previously unseen pattern that constrains subsequent excision events in mtDNA fragmentation. We also provide evidence for the generation of rare and contentious non-periodic mtDNA structures that lead to persistent diversity within individual cells. Finally, we show that measurements of relative fitness of mtDNA fit a phenomenological model that highlights important biophysical parameters governing mtDNA fitness. Altogether, our study provides techniques and insights into the dynamics of large structural changes in genomes that may be applicable in more complex organisms.

biophysics↗

bioRxiv2021

Vps501, a novel vacuolar SNX-BAR protein cooperates with the SEA complex to induce autophagy

The sorting nexins (SNX), constitute a diverse family of molecules that play varied roles in membrane trafficking, cell signaling, membrane remodeling, organelle motility and autophagy. In particular, the SNX-BAR proteins, a SNX subfamily characterized by a C-terminal dimeric Bin/Amphiphysin/Rvs (BAR) lipid curvature domain and a conserved Phox-homology domain, are of great interest. In budding yeast, many SNX-BARs proteins have well-characterized endo-vacuolar trafficking roles. Phylogenetic analyses allowed us to identify an additional SNX-BAR protein, Vps501, with a novel endo-vacuolar role. We report that Vps501 uniquely localizes to the vacuolar membrane and works with the SEA complex to regulate autophagy. Furthermore, we found cells displayed a severe deficiency in starvation-induced/nonselective autophagy only when SEA complex subunits are ablated in combination with Vps501, indicating a cooperative role with the SEA complex during autophagy. Additionally, we found the SEA complex becomes destabilized in vps501{Delta}sea1{Delta} cells, which resulted in aberrant TORC1 hyperactivity and misregulation of autophagy induction.

cell biology↗