Biochemical Species Research Articles

Accumulation of Spherical Microplastics in Earthworms Tissues-Mapping Using Raman Microscopy

The presence of microplastics in the environment is now becoming a challenge for many scientific disciplines. Molecular diversity and spatial migration make it difficult to find plastic-free areas. Their negative, often toxic, effects affect plants and animals to varying degrees, causing many biochemical disorders, species degradation, and population changes. This study aimed to determine the possibility of accumulation of spherical low-density polyethylene particles of 38–63 µm (38–45 µm 1.00 g/cm3, and 53–63 µm 1.00 g/cm3) with fluorescent properties in muscle tissues of the cosmopolitan earthworm species Lumbricus terrestris, exposed to plastic contained in the soil at a concentration of 0.1% dry weight for 3 months. Analysis of the tissues by Raman microscopy included the estimation of mapping area size, sampling density, accumulation time, spectra, laser line, and laser power to detect plastic in the samples effectively. Our results demonstrate the ability of low-density polyethylene microparticles to accumulate in earthworm tissues and are presented graphically for the mapping area and images with plastic detection sites marked. In addition, this article highlights the potential of using Raman microscopy for research in the field of tissue analysis.

Efficient probabilistic inference in biochemical networks

Biochemical networks are usually modeled by ordinary differential equations that describe the time evolution of the concentrations of the interacting (biochemical) species for specific initial concentrations and certain values of the interaction rates. They consist, in general, of many variables and parameters. Parameter estimation of such systems using standard optimization algorithms is computationally expensive since a large number of numerical simulations must be performed for numerous values of initial conditions and parameters, making these approaches either inefficient or inaccurate. In this paper, we explain how biochemical networks can be approximated by dynamic Bayesian networks, a class of discrete probabilistic models. This type of approximation enables the use of Bayesian inference for performing tasks such as parameter estimation. We explain how to make this type of approximations and the subsequent parameter estimation task as accurate and computationally efficient as possible. Our approach is applied on concrete examples such as the EGF-NGF cellular signaling pathway.

Inertial effect of cell state velocity on the quiescence-proliferation fate decision

Energy landscapes can provide intuitive depictions of population heterogeneity and dynamics. However, it is unclear whether individual cell behavior, hypothesized to be determined by initial position and noise, is faithfully recapitulated. Using the p21-/Cdk2-dependent quiescence-proliferation decision in breast cancer dormancy as a testbed, we examined single-cell dynamics on the landscape when perturbed by hypoxia, a dormancy-inducing stress. Combining trajectory-based energy landscape generation with single-cell time-lapse microscopy, we found that a combination of initial position and velocity on a p21/Cdk2 landscape, but not position alone, was required to explain the observed cell fate heterogeneity under hypoxia. This is likely due to additional cell state information such as epigenetic features and/or other species encoded in velocity but missing in instantaneous position determined by p21 and Cdk2 levels alone. Here, velocity dependence manifested as inertia: cells with higher cell cycle velocities prior to hypoxia continued progressing along the cell cycle under hypoxia, resisting the change in landscape towards cell cycle exit. Such inertial effects may markedly influence cell fate trajectories in tumors and other dynamically changing microenvironments where cell state transitions are governed by coordination across several biochemical species.

Enhancement of pH imaging of light addressable potentiometric sensor by colloidal spherical lens array

Visualizing the distribution of pH in a solution is an important basis for monitoring reaction processes and metabolic changes in micro-biochemical species. Light addressable potentiometric sensor (LAPS), as a simple structure, flexible imaging, low-cost and label-free electrochemical sensor, has been widely used to pH imaging. However, its spatiotemporal resolution is greatly affected by the frequency of modulation light, thus limiting its imaging performance. In this study, LAPS device modified by well-ordered and low-cost polystyrene (PS) colloidal monolayer as spherical lens array is proposed to obtain higher available modulation frequency of the maximum photoresponse. The morphology, optical properties and the electric field distribution of PS colloidal spherical lens array were tested and analyzed. pH sensing, imaging of uniform pH solution, the spatiotemporal pH imaging and dynamic imaging of enzymatic reactions of LAPS modified by PS colloidal spherical lens array were tested and evaluated. The experimental results show that LAPS modified by PS colloidal spherical lens array not only has acceptable pH sensing, but also widens the modulation frequency of the maximum photoresponse to 40 kHz. LAPS modified by colloidal spherical lens array modulated at the frequency of 40 kHz shows acceptable sensitivity and linearity, good reproducibility and stability, high SNR and high-spatiotemporal pH imaging capability. This work can be suitable for high-spatiotemporal monitoring of the changes in electrolyte environmental pH caused by the reaction and metabolism of the biochemical species.

P3D-BRNS v1.0.0: a three-dimensional, multiphase, multicomponent, pore-scale reactive transport modelling package for simulating biogeochemical processes in subsurface environments

Abstract. The porous microenvironment of soil offers various environmental functions which are governed by physical and reactive processes. Understanding reactive transport processes in porous media is essential for many natural systems (soils, aquifers, aquatic sediments or subsurface reservoirs) or technological processes (water treatment or ceramic and fuel cell technologies). In particular, in the vadose zone of the terrestrial subsurface the spatially and temporally varying saturation of the aqueous and the gas phase leads to systems that involve complex flow and transport processes as well as reactive transformations of chemical compounds in the porous material. To describe these interacting processes and their dynamics at the pore scale requires a well-suited modelling framework accounting for the proper description of all relevant processes at a high spatial resolution. Here we present P3D-BRNS as a new open-source modelling toolbox harnessing the core libraries of OpenFOAM and coupled externally to the Biogeochemical Reaction Network Simulator (BRNS). The native OpenFOAM volume-of-fluid solver is extended to have an improved representation of the fluid–fluid interface. The solvers are further developed to couple the reaction module which can be tailored for a specific reactive transport simulation. P3D-RBNS is benchmarked against three different flow and reactive transport processes: (1) fluid–fluid configuration in a capillary corner, (2) mass transfer across the fluid–fluid interface and (3) microbial growth with a high degree of accuracy. Our model allows for simulation of the spatio-temporal distribution of all biochemical species in the porous structure (obtained from μ-CT images), for conditions that are commonly found in the laboratory and environmental systems. With our coupled computational model, we provide a reliable and efficient tool for simulating multiphase, reactive transport in porous media.

Elucidating the link between thyroid cancer and mercury exposure: a review and meta-analysis.

Mercury (Hg) is a widely distributed and bioavailable metal of public health concern, with many known human toxicities, but data regarding mercury's influence on thyroid cancer (TC) is scarce. Mercury is known to impact several molecular pathways implicated in carcinogenesis, and its proclivity for bioaccumulation in the thyroid suggests a potential modulatory effect. We conducted a literature/systematic review of studies between 1995-2022 intending to define better and establish relationships between these two entities, congregate the evidence for mercury's potential role in thyroid carcinogenesis, and identify populations of interest for further study. Insufficient evidence precludes definitive conclusions on dietary mercury as a TC risk factor; however, several common mechanisms affected by mercury are crucial for TC development, including biochemical, endocrine, and reactive oxygen species effects. Quantitative analysis revealed associations between TC risk and mercury exposure. In three mercury studies, average urine levels were higher in TC patients, with a mean difference of 1.86 µg/g creatinine (95% CI = 0.32-3.41). In two studies investigating exposure to elevated mercury levels, the exposed group exhibited a higher risk of developing TC, with a relative risk of 1.90 (95% CI = 1.76-2.06). In three thyroid tissue studies, mercury levels (ppm) were higher in TC patients, averaging 0.14 (0.06-0.22) in cancerous cases (N = 178) and 0.08 (0.04-0.11) in normal thyroids (N = 257). Our findings suggest an association between mercury exposure and TC risk, implying a possible predisposing factor. Further research is necessary to reveal the clinical relevance of dietary and environmental mercury exposures in TC pathogenesis.

Investigating clot-flow interactions by integrating intravital imaging with in silico modeling for analysis of flow, transport, and hemodynamic forces

As a blood clot forms, grows, deforms, and embolizes following a vascular injury, local clot-flow interactions lead to a highly dynamic flow environment. The local flow influences transport of biochemical species relevant for clotting, and determines the forces on the clot that in turn lead to clot deformation and embolization. Despite this central role, quantitative characterization of this dynamic clot-flow interaction and flow environment in the clot neighborhood remains a major challenge. Here, we propose an approach that integrates dynamic intravital imaging with computer geometric modeling and computational flow and transport modeling to develop a unified in silico framework to quantify the dynamic clot-flow interactions. We outline the development of the methodology referred to as Intravital Integrated In Silico Modeling or IVISim, and then demonstrate the method on a sample set of simulations comprising clot formation following laser injury in two mouse cremaster arteriole injury model data: one wild-type mouse case, and one diYF knockout mouse case. Simulation predictions are verified against experimental observations of transport of caged fluorescent Albumin (cAlb) in both models. Through these simulations, we illustrate how the IVISim methodology can provide insights into hemostatic processes, the role of flow and clot-flow interactions, and enable further investigations comparing and contrasting different biological model scenarios and parameter variations.

Coupled bio-chemo-hydro-mechanical modeling of microbially induced calcite precipitation process considering biomass encapsulation using a micro-scale relationship

Geomaterials with inferior hydraulic and strength characteristics often need improvement to enhance their engineering behaviors. Traditional ground improvement techniques require enormous mechanical effort or synthetic chemicals. Sustainable stabilization technique such as microbially induced calcite precipitation (MICP) utilizes bacterial metabolic processes to precipitate cementitious calcium carbonate. The reactive transport of biochemical species in the soil mass initiates the precipitation of biocement during the MICP process. The precipitated biocement alters the hydro-mechanical performance of the soil mass. Usually, the flow, deformation, and transport phenomena regulate the biocementation technique via coupled bio-chemo-hydro-mechanical (BCHM) processes. Among all, one crucial phenomenon controlling the precipitation mechanism is the encapsulation of biomass by calcium carbonate. Biomass encapsulation can potentially reduce the biochemical reaction rate and decelerate biocementation. Laboratory examination of the encapsulation process demands a thorough analysis of associated coupled effects. Despite this, a numerical model can assist in capturing the coupled processes influencing encapsulation during the MICP treatment. However, most numerical models did not consider biochemical reaction rate kinetics accounting for the influence of bacterial encapsulation. Given this, the current study developed a coupled BCHM model to evaluate the effect of encapsulation on the precipitated calcite content using a micro-scale semiempirical relationship. Firstly, the developed BCHM model was verified and validated using numerical and experimental observations of soil column tests. Later, the encapsulation phenomenon was investigated in the soil columns of variable maximum calcite crystal sizes. The results depict altered reaction rates due to the encapsulation phenomenon and an observable change in the precipitated calcite content for each maximum crystal size. Furthermore, the permeability and deformation of the soil mass were affected by the simultaneous precipitation of calcium carbonate. Overall, the present study comprehended the influence of the encapsulation of bacteria on cement morphology-induced permeability, biocement-induced stresses and displacements.

Exposomic Signatures of Cervical Pain.

We evaluated risk factors associated with cervical pain (CP) among officers and enlisted members of the U.S. Army and Marine Aviation community using an exposomic approach. Specifically, we aimed to determine the factors associated with reported CP. This is a retrospective cohort study that utilized the Medical Assessment and Readiness System housed at Womack Army Medical Center to evaluate the longitudinal data taken from medical and workforce resources. This study included 77,864 active duty AMAC members during October 2015-December 2019. Multivariable mixed-effects logistic regression was used to assess the relationship between the independent variables of rank, service time, deployment, Armed Forces Qualification Test score, tobacco use, alcohol use, age, gender, race, ethnicity, body mass index, marital status, and education level and the dependent variable, incidence occurrence of CP. The total analysis included 77,864 individuals with 218,180 person-years of observations. The incidence rate of CP was 18.8 per 100 person-years, with a 12% period prevalence. Cervical pain was independently associated with rank, service time, Armed Forces Qualification Test score, and alcohol use (all P < .05). Our longitudinal exposomic signatures-based approach aims to complement the outcomes of data science and analytics from Medical Assessment and Readiness System with validations of objective biochemical indicator species observed in Army and Marine Aviation community members suffering from CP. This initial approach using parallel track complementarity has the potential of substantiating the underlying mechanisms foundational to design prospective personalized algorithms that can be used as a predictive model. Finally, a specific evaluation of occupational risk factors may provide insight into factors not readily ascertained from the civilian literature.

BCH modelling studies on biocementation process in mitigating leaks from a CO2 sequestrated aquifer

BCH modelling studies on biocementation process in mitigating leaks from a CO2 sequestrated aquifer

Recent Advances in Bimetallic Nanoporous Gold Electrodes for Electrochemical Sensing.

Bimetallic nanocomposites and nanoparticles have received tremendous interest recently because they often exhibit better properties than single-component materials. Improved electron transfer rates and the synergistic interactions between individual metals are two of the most beneficial attributes of these materials. In this review, we focus on bimetallic nanoporous gold (NPG) because of its importance in the field of electrochemical sensing coupled with the ease with which it can be made. NPG is a particularly important scaffold because of its unique properties, including biofouling resistance and ease of modification. In this review, several different methods to synthesize NPG, along with varying modification approaches are described. These include the use of ternary alloys, immersion-reduction (chemical, electrochemical, hybrid), co-electrodeposition-annealing, and under-potential deposition coupled with surface-limited redox replacement of NPG with different metal nanoparticles (e.g., Pt, Cu, Pd, Ni, Co, Fe, etc.). The review also describes the importance of fully characterizing these bimetallic nanocomposites and critically analyzing their structure, surface morphology, surface composition, and application in electrochemical sensing of chemical and biochemical species. The authors attempt to highlight the most recent and advanced techniques for designing non-enzymatic bimetallic electrochemical nanosensors. The review opens up a window for readers to obtain detailed knowledge about the formation and structure of bimetallic electrodes and their applications in electrochemical sensing.

Optofluidic Sensor Based on Polymer Optical Microresonators for the Specific, Sensitive and Fast Detection of Chemical and Biochemical Species.

The accurate, rapid, and specific detection of DNA strands in solution is becoming increasingly important, especially in biomedical applications such as the trace detection of COVID-19 or cancer diagnosis. In this work we present the design, elaboration and characterization of an optofluidic sensor based on a polymer-based microresonator which shows a quick response time, a low detection limit and good sensitivity. The device is composed of a micro-racetrack waveguide vertically coupled to a bus waveguide and embedded within a microfluidic circuit. The spectral response of the microresonator, in air or immersed in deionised water, shows quality factors up to 72,900 and contrasts up to 0.9. The concentration of DNA strands in water is related to the spectral shift of the microresonator transmission function, as measured at the inflection points of resonance peaks in order to optimize the signal-over-noise ratio. After functionalization by a DNA probe strand on the surface of the microresonator, a specific and real time measurement of the complementary DNA strands in the solution is realized. Additionally, we have inferred the dissociation constant value of the binding equilibrium of the two complementary DNA strands and evidenced a sensitivity of 16.0 pm/µM and a detection limit of 121 nM.

The Sensitivity of a Hexagonal Au Nanohole Array under Different Incident Angles

Surface plasmon resonance sensors have been widely used in various fields for label-free and real-time detection of biochemical species due to their high sensitivity to the refractive index change of the surrounding environment. The common practices to achieve the improvement of sensitivity are to adjust the size and morphology of the sensor structure. This strategy is tedious and, to some extent, limits the applications of surface plasmon resonance sensors. Instead, the effect of the incident angle of excited light on the sensitivity of a hexagonal Au nanohole array sensor with a period of 630 nm and a hole diameter of 320 nm is theoretically investigated in this work. By exploring the peak shift of reflectance spectra of the sensor when facing a refractive index change in (1) the bulk environment and (2) the surface environment adjacent to the sensor, we can obtain the bulk sensitivity and surface sensitivity. The results show that the bulk sensitivity and surface sensitivity of the Au nanohole array sensor can be improved by 80% and 150%, respectively, by simply increasing the incident angle from 0° to 40°. The two sensitivities both remain nearly unchanged when the incident angle further changes from 40° to 50°. This work provides new understanding of the performance improvement and advanced sensing applications of surface plasmon resonance sensors.

#4344 CHANGES IN ENERGY METABOLISM IN THE KIDNEY WITH TUBULOINTERSTITIAL FIBROSIS: AN EX VIVO WHOLE TISSUE 2D-COSY APPROACH

Abstract Background and Aims Tubulointerstitial fibrosis is the common pathological manifestation in chronic kidney disease (CKD) and can indicate whether a patient will progress to kidney failure. The metabolic consequences of developing fibrosis are not well understood. This project aimed to investigate metabolic changes in the kidney cortex using an adenine-diet murine model of progressive CKD. Method C57Bl/6J mice were treated with an adenine-supplemented diet (0.2% adenine) or control diet for eight weeks. At the end of treatment, kidney function was assessed (serum creatinine, proteinuria), animals were euthanised, and the kidneys removed. A transverse section of the kidney was prepared for histology. Whole kidney cortical tissue was analysed using two-dimensional correlated spectroscopy (2D-COSY), a form of proton nuclear magnetic resonance (NMR) spectroscopy. Biochemical species, including metabolites and lipids, within the tissue were identified and compared with respective histological tubulointerstitial fibrosis level and traditional serum markers of kidney function, plasma creatinine and blood urea nitrogen. A 2D-COSY spectrum can be found in Figure 1A. Results The adenine-supplemented diet induced tubulointerstitial fibrosis, mirrored by increases in serum creatinine and blood urea nitrogen, indicating decreased kidney function. The 2D-COSY analysis demonstrated numerous changes in metabolites with parallel increasing levels of fibrosis that were detected. Increases in metabolites belonging to the glycolysis (D-glucose, glucose-6-phosphate and lactate) and pentose-phosphate (myo-inositol, D-ribose-5-phosphate, glucuronic acid) pathways were observed, as well as a decrease in lipid. Additionally, increases in creatinine, creatine and a number of amino acids were also observed. These changes are displayed in Table 1 and Figure 1B. Conclusion The primary cell type of the kidney cortex is the proximal tubular epithelial cell. Due to its unique function in water and solute transport, this cell has a very high metabolic demand and utilizes fatty acid oxidation as its primary source of energy. However, when these cells are under pathological stress that contributes to tubulointerstitial fibrosis, such as those present within this animal model of chronic kidney disease, metabolic dysfunction occurs. We observed significant decreases in various lipid signals belonging to fatty acids within the cell. These fatty acids are not being utilised and are instead esterified to triglycerides that accumulate in the kidney, causing lipotoxicity. Increased levels of glucose-6-phosphate, lactate and D-glucose, as well as increased myo-inositol, glucuronic acid D-ribose-5-phosphate are indicative of increased utilisation of the glycolysis and pentose phosphate pathway respectively as primary methods of energy metabolism. Here, we provide evidence that in tubulointerstitial fibrosis within the kidneys leads to a shift in the primary energy pathway used by proximal tubular epithelial cells. The study provides new insights into the changes in biochemical pathways that occur in the kidney during the development of CKD and its progression.

Shell engineering in soft alginate-based capsules for culturing liver spheroids.

Functional interaction between cancer cells and the surrounding microenvironment is still not sufficiently understood, which motivates the tremendous interest for the development of numerous in vitro tumor models. Diverse parameters, for example, transport of nutrients and metabolites, availability of space in the confinement, etc. make an impact on the size, shape, and metabolism of the tumoroids. We demonstrate the fluidics-based low-cost methodology to reproducibly generate the alginate and alginate-chitosan microcapsules and apply it to grow human hepatoma (HepG2) spheroids of different dimensions and geometries. Focusing specifically on the composition and thickness of the hydrogel shell, permeability of the microcapsules was selectively tuned. The diffusion of the selected benchmark molecules through the shell has been systematically investigated using both, experiments and simulations, which is essential to ensure efficient mass transfer and/or filtering of the biochemical species. Metabolic activity of spheroids in microcapsules was confirmed by tracking the turnover of testosterone to androstenedione with chromatography studies in a metabolic assay. Depending on available space, phenotypically different 3D cell assemblies have been observed inside the capsules, varying in the tightness of cell aggregations and their shapes. Conclusively, we believe that our system with the facile tuning of the shell thickness and permeability, represents a promising platform for studying the formation of cancer spheroids and their functional interaction with the surrounding microenvironment.

Characterization of leaf surface phenotypes based on light interaction

BackgroundLeaf surface phenotypes can indicate plant health and relate to a plant’s adaptations to environmental stresses. Identifying these phenotypes using non-invasive techniques can assist in high-throughput phenotyping and can improve decision making in plant breeding. Identification of these surface phenotypes can also assist in stress identification. Incorporating surface phenotypes into leaf optical modelling can lead to improved biochemical parameter retrieval and species identification.ResultsIn this paper, leaf surface phenotypes are characterized for 349 leaf samples based on polarized light reflectance measured at Brewster’s Angle, and microscopic observation. Four main leaf surface phenotypes (glossy wax, glaucous wax, high trichome density, and glabrous) were identified for the leaf samples. The microscopic and visual observations of the phenotypes were used as ground truth for comparison with the spectral classification. In addition to surface classification, the microscope images were used to assess cell size, shape, and cell cap aspect ratios; these surface attributes were not found to correlate significantly with spectral measurements obtained in this study. Using a quadratic discriminant analysis function, a series of 10,000 classifications were run with the data randomly split between training and testing datasets, with 150 and 199 samples, respectively. The average correct classification rate was 72.9% with a worst-case classification of 60.3%.ConclusionsLeaf surface phenotypes were successfully correlated with spectral measurements that can be obtained remotely. Remote identification of these surface phenotypes will improve leaf optical modelling and biochemical parameter estimations. Phenotyping of leaf surfaces can inform plant breeding decisions and assist with plant health monitoring.

Modelling of thrombus formation using smoothed particle hydrodynamics method.

In this paper a novel model, based on the smoothed particle hydrodynamics (SPH) method, is proposed to simulate thrombus formation. This describes the main phases of the coagulative cascade through the balance of four biochemical species and three type of platelets. SPH particles can switch from fluid to solid phase when specific biochemical and physical conditions are satisfied. The interaction between blood and the forming blood clot is easily handled by an innovative monolithic FSI approach. Fluid-solid coupling is modelled by introducing elastic binds between solid particles, without requiring detention and management of the interface between the two media. The proposed model is able to realistically reproduce the thromboembolic process, as confirmed by the comparison of numerical results with experimental data available in the literature.

Luminescent Polymer Composites for Optical Fiber Sensors.

Optical fiber sensors incorporating luminescent materials are useful for detecting physical parameters and biochemical species. Fluorescent materials integrated on the tips of optical fibers, for example, provide a means to perform fluorescence thermometry while monitoring the intensity or the spectral variations of the fluorescence signal. Similarly, certain molecules can be tracked by monitoring their characteristic emission in the UV wavelength range. A key element for these sensing approaches is the luminescent composite, which may be obtained upon allocating luminescent nanomaterials in glass or polymer hosts. In this work, we explore the fluorescence features of two composites incorporating lanthanide-doped fluorescent powders using polydimethylsiloxane (PDMS) as a host. The composites are obtained by a simple mixing procedure and can be subsequently deposited onto the end faces of optical fibers via dip coating or molding. Whereas one of the composites has shown to be useful for the fabrication of fiber optic temperature sensors, the other shows promising result for detection of UV radiation. The performance of both composites is first evaluated for the fabrication of membranes by examining features such as fluorescent stability. We further explore the influence of parameters such as particle concentration and density on the fluorescence features of the polymer blends. Finally, we demonstrate the incorporation of these PDMS fluorescent composites onto optical fibers and evaluate their sensing capabilities.

A comparative review of the activity of enzymes of the cytochrome P450 system in humans and laboratory animals. Prognostic value of preclinical models in vivo

Cytochrome P450 enzymes play a key role in drug biotransformation. The expression and activity of each CYP450 is influenced by a unique combination of biochemical factors, species and genetic differences, age, sex, nutrition and etc.Cytochromes P450 are a family of heme-containing proteins involved in the metabolism of xenobiotics, drugs, and endogenous compounds. Drugs could act as inducers or inhibitors of cytochrome P450 enzymes. Understanding the mechanisms of inhibition or induction of enzymes is extremely important in preclinical studies and prescribing complex therapy. One of the main challenges in the development of therapeutic agents is to determine which animal species reflects the human ability to metabolize certain drugs. The study of CYPs and their interaction with drugs is an urgent problem in preclinical studies. Thus, an adequate and maximally similar experimental preclinical models are necessary to study the pharmacokinetic and pharmacodynamic properties of promising chemicals and their effect on certain cytochrome P450 enzymes.This review compares the main subfamilies and their enzymes of the cytochrome system of humans and laboratory animals involved in drug metabolism. The problems of choosing biological models in vivo in preclinical studies in the study of medicinal substances are considered. The predictive value of in vivo models of preclinical studies was analyzed from the point of view of the cytochrome P450 system in humans and laboratory animals.

Reference Genome Sequences of the Oriental Armyworm, Mythimna separata (Lepidoptera: Noctuidae)

Lepidopteran insects are an important group of animals, including those used as biochemical and physiological model species in the insect and silk industries as well as others that are major agricultural pests. Therefore, the genome sequences of several lepidopteran insects have been reported. The oriental armyworm, Mythimna separata, is an agricultural pest commonly used to study insect immune reactions and interactions with parasitoid wasps as hosts. To improve our understanding of these research topics, reference genome sequences were constructed in the present study. Using long-read and short-read sequence data, de novo assembly and polishing were performed and haplotigs were purged. Subsequently, gene predictions and functional annotations were performed. To search for orthologs of the Toll and Immune Deficiency (IMD) pathways and for C-type lectins, annotation data analysis, BLASTp, and Hummer scans were performed. The M. separata genome is 682 Mbp; its contig N50 was 2.7 Mbp, with 21,970 genes and 24,452 coding sites predicted. All orthologs of the core components of the Toll and IMD pathways and 105 C-type lectins were identified. These results suggest that the genome data were of sufficient quality for use as reference genome data and could contribute to promoting M. separata and lepidopteran research at the molecular and genome levels.