Biology subjects

Haney, S.

Publications and source records attributed to Haney, S..

7 recordsLinked to original sources

bioRxiv2026

Time, Not fungicide treatment, influences the resistome of the turf phyllosphere

Antibiotic resistance genes (ARGs) are an emerging class of environmental contaminants with significant implications for public health. Previous studies have linked fungicide exposure to elevated levels of ARGs in soil microbiomes, but research investigating the impacts of fungicide on ARGs within phyllosphere bacterial communities is limited. To address this, creeping bentgrass was treated with the fungicide active ingredients chlorothalonil, fluxapyroxad, and propiconazole and sampled at 4 hours, 96 hours, and one week post-application. Quantitative PCR (qPCR) was performed to quantify the abundance of ARGs and a metal resistance genes (MRG) abundance relative to 16s. Additionally, 16S rRNA gene sequencing was performed to characterize bacterial community composition. Results indicated that fungicide treatments did not significantly alter the relative abundance of ARGs or an MRG within bent grass bacterial communities. However, significant changes were observed over time, with changes in ARG and MRG abundance mirroring temporal shifts in bacterial beta diversity. ARGs and the MRG relative abundance had significant correlations with Proteobacteria, Actinobacteria, Bacteriadota, and Firmicutes, including with genera Pseudoxanthomas, and Dyandobacter, which contain opportunistic human pathogens. This study demonstrates that fungicides have limited influence on the abundance of ARGs and MRGs in the phyllosphere and helps guide further investigations aiming to mitigate the spread of antibiotic resistance. ImportanceAntibiotic resistance makes it harder to treat bacterial infections. Recent evidence suggests that fungicides may increase the abundance of antibiotic resistance genes (ARGs) in soil. Leaves are also treated with fungicides, but it is unclear if there will be increases of antibiotic resistance in this environment because bacteria on leaves face different physiological stresses. Additionally, plants may serve as a route of infection to humans or animals with antibiotic resistant bacteria making it a critical micro-environment to investigate. The purpose of this study was to determine whether the prevalence of antibiotic resistance on plant surfaces changes after short-term exposure to fungicides. This study shows that over short-term application periods, time has a greater effect on the abundance of genes that cause antibiotic resistance than treatment with the fungicides chlorothalonil, fluxapyroxad, and propiconazole on plants. This work helps inform future efforts to mitigate the spread of antibiotic resistance.

microbiology↗

bioRxiv2024

Plasticity in inhibitory networks improves pattern separation in early olfactory processing

Distinguishing between nectar and non-nectar odors is challenging for animals due to shared compounds and varying ratios in complex mixtures. Changes in nectar production throughout the day - and potentially many times within a foragers lifetime - add to the complexity. The honeybee olfactory system, containing fewer than 1,000 principal neurons in the early olfactory relay, the antennal lobe (AL), must learn to associate diverse volatile blends with rewards. Previous studies identified plasticity in the AL circuits, but its role in odor learning remains poorly understood. Using a biophysical computational network model, tuned by in vivo electrophysiological data, and live imaging of the honeybees AL, we explored the neural mechanisms and functions of plasticity in the early olfactory system. Our findings revealed that when trained with a set of rewarded and unrewarded odors, the AL inhibitory network suppresses shared chemical compounds while enhancing responses to distinct compounds. This results in improved pattern separation and a more concise neural code. Our calcium imaging data support these predictions. Analysis of a graph convolutional neural network performing an odor categorization task revealed a similar mechanism for contrast enhancement. Our study provides insights into how inhibitory plasticity in the early olfactory network reshapes the coding for efficient learning of complex odors. Significance StatementBy combining biophysical modeling, machine learning, electrophysiology and analysis of calcium imaging data, we demonstrate that associative and nonassociative plasticity in the honeybee antennal lobe (AL) the first relay of the insect olfactory system - work together to enhance the contrast between rewarded and unrewarded odors. Training the ALs inhibitory network within specific odor environments enables the suppression of neural responses to common odor components while amplifying responses to distinctive ones. This study sheds light on the olfactory systems ability to adapt and efficiently learn new odor-reward associations across varying environments, and it proposes innovative, energy-efficient principles applicable to artificial intelligence.

neuroscience↗

bioRxiv2024

A Phased, Chromosome-scale Genome for Malus domestica 'WA 38'

Genome sequencing for agriculturally important Rosaceous crops has made rapid progress both in completeness and annotation quality. Whole genome sequence and annotation gives breeders, researchers, and growers information about cultivar specific traits such as fruit quality, disease resistance, and informs strategies to enhance postharvest storage. Here we present a haplotype-phased, chromosomal level genome of Malus domestica, WA 38, a new apple cultivar released to market in 2017 as Cosmic Crisp (R). Using both short and long read sequencing data with a k-mer based approach, chromosomes originating from each parent were assembled and segregated. This is the first pome fruit genome fully phased into parental haplotypes in which chromosomes from each parent are identified and separated into their unique, respective haplomes. The two haplome assemblies, Honeycrisp originated HapA and Enterprise originated HapB, are about 650 Megabases each, and both have a BUSCO score of 98.7% complete. A total of 53,028 and 54,235 genes were annotated from HapA and HapB, respectively. Additionally, we provide genome-scale comparisons to Gala, Honeycrisp, and other relevant cultivars highlighting major differences in genome structure and gene family circumscription. This assembly and annotation was done in collaboration with the American Campus Tree Genomes project that includes WA 38 (Washington State University), dAnjou pear (Auburn University), and many more. To ensure transparency, reproducibility, and applicability for any genome project, our genome assembly and annotation workflow is recorded in detail and shared under a public GitLab repository. All software is containerized, offering a simple implementation of the workflow.

genomics↗

bioRxiv2022

Olfactory receptor neurons generate multiple response motifs, increasing coding space dimensionality

Odorants binding to olfactory receptor neurons (ORNs) trigger bursts of action potentials, providing the brain with its only experience of the olfactory environment. Our recordings made in vivo from locust ORNs showed odor-elicited firing patterns comprise four distinct response motifs, each defined by a reliable temporal profile. Different odorants could elicit different response motifs from a given ORN, a property we term motif switching. Further, each motif undergoes its own form of sensory adaptation when activated by repeated plume-like odor pulses. A computational model constrained by our recordings revealed that organizing responses into multiple motifs provides substantial benefits for classifying odors and processing complex odor plumes: each motif contributes uniquely to encode the plumes composition and structure. Multiple motifs and motif switching further improve odor classification by expanding coding dimensionality. Our model demonstrated these response features could provide benefits for olfactory navigation, including determining the distance to an odor source.

neuroscience↗

bioRxiv2021

Novelty detection in early olfactory processing of the honey bee, Apis mellifera

Animals are constantly bombarded with stimuli, which presents a fundamental problem of sorting among pervasive uninformative stimuli and novel, possibly meaningful stimuli. We evaluated novelty detection behaviorally in honey bees as they position their antennae differentially in an air stream carrying familiar or novel odors. We then characterized neuronal responses to familiar and novel odors in the first synaptic integration center in the brain - the antennal lobes. We found that the neurons that exhibited stronger initial responses to the odor that was to be familiarized are the same units that later distinguish familiar and novel odors, independently of chemical identities. These units, including both projection neurons and local neurons, showed a decreased response to the familiar odor but an increased response to the novel odor. Our results suggest that the antennal lobe may assign a category of familiarity or novelty to an odor stimulus in addition to its chemical identity code. Therefore, the mechanisms for novelty detection may be present in early sensory processing, either as a result of local synaptic interaction or via feedback from higher brain centers.

neuroscience↗

bioRxiv2019

Liver-Chip: Reproducing Human and Cross-Species Toxicities

Nonclinical rodent and non-rodent toxicity models used to support clinical trials of candidate drugs may produce discordant results or fail to predict complications in humans contributing to drug failures in the clinic. Here we applied microengineered Organ-on-Chip (Organ-Chip) technology to design rat, dog, and human Liver-Chips containing species-specific primary hepatocytes interfaced with liver sinusoidal endothelial cells, with or without Kupffer cells and hepatic stellate cells, cultured under physiological fluid flow. The Liver-Chips detected diverse phenotypes of liver toxicity including hepatocellular injury, steatosis, cholestasis, and fibrosis as well as species-specific toxicities when treated with tool compounds. Multi-species Liver-Chips may provide a useful platform for prediction of liver toxicity and inform human relevance of liver toxicities detected in animal studies to better determine safety and human risk.\n\nOne Sentence SummaryMicroengineered Organ-Chip technology has been used to design rat, dog and human Liver-Chips that recapitulate species-specific liver toxicities.

pharmacology and toxicology↗

bioRxiv2017

The Complex Ecosystem in Non Small Cell Lung Cancer Invasion

Many tumors are characterized by genetic instability, producing an assortment of genetic variants of tumor cells called subclones. These tumors and their surrounding environments form complex multi-cellular ecosystems, where subclones compete for resources and cooperate to perform multiple tasks, including cancer invasion. Our recent empirical studies revealed existence of such distinct phenotypes of cancer cells, leaders and followers, in lung cancer. These two cellular subclones exchange a complex array of extracellular signals demonstrating a symbiotic relationship at the cellular level. Here, we develop a computational model of the microenvironment of the lung cancer ecosystem to explore how the interactions between subclones can advance or inhibit invasion. We found that, due to the complexity of the ecosystem, invasion may have very different dynamics characterized by the different levels of aggressiveness. By altering the signaling environment, we could alter the ecological relationship between the cell types and the overall ecosystem development. Competition between leader and follower cell populations (defined by the limited amount of resources), positive feedback within the leader cell population (controlled by the focal adhesion kinase and fibronectin signaling), and impact of the follower cells to the leaders (represented by yet undetermined proliferation signal) all had major effects on the outcome of the collective dynamics. Specifically, our analysis revealed a class of tumors (defined by the strengths of fibronectin signaling and competition) that are particularly sensitive to manipulations of the signaling environment. This class can undergo irreversible changes to the tumor ecosystem that outlast these manipulations of feedbacks and have a profound impact on invasive potential. Our study predicts a complex division of labor between cancer cell subclones and suggests new treatment strategies targeting signaling within the tumor ecosystem.\n\nAuthor SummaryCancer is an elusive disease due to the wide variety of cancer types and adaptability to treatment. How is this adaptability accomplished? Loss of genetic stability, a hallmark of cancer, leads to the emergence of many different types of cancer cells within a tumor. This creates a complex ecosystem where cancer cell types can cooperate, compete, and exploit each other. We have previously used an image-guided technology to isolatedistinct cancer subclones and identify how they interact. Here, we have employed mathematical modeling to understand how the dynamic feedbacks between different cancer cell types can impact the success of invasion in lung cancer. We found that successful invasion required for feedbacks to support the less viable but more invasive cell types. These predictions may have implications for novel clinical treatment options and emphasize the need to visualize and probe cancer as a tumor ecosystem.

cancer biology↗