Biology subjects

Xu, M.

Publications and source records attributed to Xu, M..

At least 109 records · Page 6Linked to original sources

bioRxiv2024

Discovery and Biosynthesis of Sulfenicin and Its New-to-Nature Acylsulfenic Acid Functional Group

Lifes organic molecules are built with diverse functional groups that enable biology by fine tuning intimate connections through time and space. As such, the discovery of new-to-nature functional groups can expand our understanding of the natural world and motivate new applications in biotechnology and biomedicine. Herein we report the genome-aided discovery of sulfenicin, a novel polyketide-nonribosomal peptide hybrid natural product from a marine Streptomyces bacterium bearing a unique acylsulfenic acid functionality. Through a series of heterologous biosynthesis, functional genetics, and enzymatic reconstitution experiments, we show that this previously described synthetic functional group is biologically assembled by a set of enzymes from both primary and secondary metabolism, including a novel flavin-dependent S-hydroxylase that hydroxylates a thiocarboxylic acids sulfur atom. While the sulfenicin biosynthetic gene cluster is presently without parallel in public databases, acylsulfenic acid-encoding enzymes are widely distributed in bacterial genomes, implying that this labile functional group may similarly have a broad distribution among specialized metabolites.

biochemistry↗

bioRxiv2024

Fully Hyperbolic Neural Networks: A Novel Approach to Studying Aging Trajectories

Characterizing age-related alterations in brain networks is crucial for understanding aging trajectories and identifying deviations indicative of neurodegenerative disorders, such as Alzheimers disease. In this study, we developed a Fully Hyperbolic Neural Network (FHNN) to embed functional brain connectivity graphs derived from magnetoencephalography (MEG) data into low dimensions on a Lorentz model of hyperbolic space. Using this model, we computed hyperbolic embeddings of the MEG brain networks of 587 individuals from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) dataset. Notably, we leveraged a unique metric--the radius of the node embeddings--which effectively captures the hierarchical organization of the brain, to characterize subtle hierarchical organizational changes in various brain subnetworks attributed to the aging process. Our findings revealed that a considerable number of subnetworks exhibited a reduction in hierarchy during aging, with some showing gradual changes and others undergoing rapid transformations in the elderly. Moreover, we demonstrated that hyperbolic features outperform traditional graph-theoretic measures in capturing age-related information in brain networks. Overall, our study represents the first evaluation of hyperbolic embeddings in MEG brain networks for studying aging trajectories, shedding light on critical regions undergoing significant age-related alterations in the large cohort of the Cam-CAN dataset.

bioinformatics↗

bioRxiv2024

TET2 contributes to gluconeogenesis and pathology of type 2 diabetes

The control of gluconeogenesis is critical for glucose homeostasis and the pathology of type 2 diabetes (T2D). Here, we uncover a novel function of TET2 in the regulation of gluconeogenesis. In mice, both fasting and a high-fat diet (HFD) stimulate the expression of TET2, and TET2 knockout impairs glucose production. Mechanistically, FBP1, a rate-limiting enzyme in gluconeogenesis, is positively regulated by TET2 in liver cells. TET2 is recruited by HNF4, contributing to the demethylation of FBP1 promoter and activating its expression in response to glucagon stimulation. Moreover, metformin treatment increases the phosphorylation of HNF4 on Ser313, which prevents its interaction with TET2, thereby decreasing the expression level of FBP1 and ameliorating the pathology of T2D. Collectively, we identify an HNF4-TET2-FBP1 axis in the control of gluconeogenesis, which contributes to the therapeutic effect of metformin on T2D and provides a potential target for the clinical treatment of T2D.

cell biology↗

bioRxiv2024

Exploring the Biological Mechanisms of Severe COVID-19 in the Elderly: Insights from an Aged Mouse Model

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in a global health crisis, particularly affecting the elderly, who are more susceptible to severe outcomes. However, definitive parameters or mechanisms underlying the severity of COVID-19 in elderly people remain confused. Thus, this study seeks to elucidate the mechanism behind the increased vulnerability of elderly individuals to severe COVID-19. We employed an aged mouse model with a mouse-adapted SARS-CoV-2 strain to mimic the severe symptoms observed in elderly patients with COVID-19. Comprehensive analyses of the whole lung were performed using transcriptome and proteome sequencing, comparing data from aged and young mice. For transcriptome analysis, bulk RNA sequencing was conducted using an Illumina sequencing platform. Proteomic analysis was performed using mass spectrometry following protein extraction, digestion, and peptide labeling. We analyzed the transcriptome and proteome profiles of young and aged mice and discovered that aged mice exhibited elevated baseline levels of inflammation and tissue damage repair. After SARS-CoV-2 infection, aged mice showed increased antiviral and inflammatory responses; however, these responses were weaker than those in young mice, with significant complement and coagulation cascade responses. In summary, our study demonstrates that the increased vulnerability of the elderly to severe COVID-19 can be attributed to an attenuated antiviral response and the overactivation of complement and coagulation cascades.

immunology↗

bioRxiv2024

Deep Video Analysis for Bacteria Genotype Prediction

Genetic modification of microbes is central to many biotechnology fields, such as industrial microbiology, bioproduction, and drug discovery. Understanding how specific genetic modifications influence observable bacterial behaviors is crucial for advancing these fields. In this study, we propose a supervised model to classify bacteria harboring single gene modifications to draw connections between phenotype and genotype. In particular, we demonstrate that the spatiotemporal patterns of Vibrio cholerae growth, recorded in terms of low-resolution bright-field microscopy videos, are highly predictive of the genotype class. Additionally, we introduce a weakly supervised approach to identify key moments in culture growth that significantly contribute to prediction accuracy. By focusing on the temporal expressions of bacterial behavior, our findings offer valuable insights into the underlying mechanisms and developmental stages by which specific genes control observable phenotypes. This research opens new avenues for automating the analysis of phenotypes, with potential applications for drug discovery, disease management, etc. Furthermore, this work highlights the potential of using machine learning techniques to explore the functional roles of specific genes using a low-resolution light microscope.

bioinformatics↗

bioRxiv2024

G-CSF and IL-6 drive myeloid dysregulation during severe viral infection

Dysregulated myeloid states are associated with disease severity in both sepsis and COVID-19. However, their relevance in non-COVID-19 viral infection, the factors driving their induction, and their role in tissue injury remain poorly understood. We performed a meta-analysis of 1,622,180 myeloid cells from 890 COVID-19 or sepsis patients and controls across 19 published blood scRNA-seq datasets, which revealed severity-associated gene programs in both neutrophils and monocytes pointing to emergency myelopoiesis (EM). Using published bulk transcriptional data from 562 individuals with non-COVID-19 viral disease, we show that these signatures are similarly upregulated during severe influenza and RSV infection. Analysis of transcriptional and proteomic responses in tocilizumab-treated COVID-19 patients show that IL-6 signaling blockade results in a partial reduction of EM signatures and a compensatory increase in the growth factor G-CSF. Using a cellular model of human myelopoiesis, we show that both IL-6 and G-CSF stimulate the production of myeloid cells that express EM signatures in vitro. Using a mouse model of severe influenza infection, we demonstrate the effect of IL-6 and G-CSF signaling blockade on EM-associated myeloid cells, and highlight the opposing effects of EM-induced neutrophils and monocytes on tissue injury. Our study demonstrates the link between systemic cytokines and myeloid dysregulation during severe infection in humans, and highlights the cooperative role of IL-6 and G-CSF signaling in driving infection-induced myelopoiesis.

immunology↗

bioRxiv2024

Discovery of novel quinoline papain-like protease inhibitors for COVID-19 through topology constrained molecular generative model

The rapid emergence of drug-resistant SARS-CoV-2 variants poses a persistent challenge to current antiviral strategies. Mutations in key viral targets, including RNA-dependent RNA polymerase (RdRp), main protease (3CLpro), and papain-like protease (PLpro), have been shown to markedly reduce the efficacy of approved therapeutics, highlighting the urgent need for next-generation antivirals capable of overcoming resistance. Here, we report the discovery of a novel class of PLpro inhibitors through an AIDD strategy based on a topology-constrained molecular generative model (Tree-Invent) integrated with structure-guided optimization. Scaffold hopping from a previously reported lead enabled the identification of a quinoline-based chemical series with substantially improved metabolic stability and antiviral potency. Structure-guided optimization yielded compound GZNL-2016, which exhibited potent enzymatic inhibition of PLpro (IC50 = 10.5 nM), robust antiviral activity against multiple SARS-CoV-2 variants, including Omicron BA.5 and XBB.1, and favorable pharmacokinetic properties following oral administration. Notably, GZNL-2016 retained substantial inhibitory activity against the clinically relevant drug-resistant mutant PLpro E167K (IC50 = 480.2 nM; Ki = 439.3 nM), in contrast to previously reported inhibitors that exhibit markedly reduced potency. In a SARS-CoV-2 infection mouse model, oral administration of GZNL-2016 significantly reduced pulmonary viral titers, demonstrating in vivo antiviral efficacy. Collectively, this study establishes an AI-enabled strategy for rapid antiviral discovery and identifies GZNL-2016 as a promising lead compound to address the threat of coronavirus infections caused by drug-resistant mutant SARS-CoV-2 variants. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/611841v3_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@ecbd3eorg.highwire.dtl.DTLVardef@7c663corg.highwire.dtl.DTLVardef@11c0e37org.highwire.dtl.DTLVardef@e950f0_HPS_FORMAT_FIGEXP M_FIG C_FIG We leveraged an AI generative model to discover a novel PLpro inhibitor with excellent liver stability, low CYP, hERG inhibition and reasonable oral PK properties. At the same time, the compound 16 exhibits high efficacy for the resistance mutation E167K, which resulted in severe resistance to the previously reported inhibitor Jun12682 and PF-07957472.

microbiology↗

bioRxiv2024

The clinical antiprotozoal drug halofuginone promotes weight loss by elevating GDF15 and FGF21

Obesity is a debilitating disease with increasing worldwide prevalence. Despite its high prevalence, specific pharmacologic intervention for obesity is challenging. Here, we report that halofuginone, an FDA-approved anti-scleroderma and anti-protozoal drug, is a promising anti-obesity agent in rodent models. Halofuginone suppressed food intake, increased energy expenditure, and resulted in weight loss in preclinical diet-induced obese mouse models, while also decreasing insulin resistance and hepatic steatosis. By combining genetic and pharmacological tools with transcriptomics, we identified that halofuginone increases FGF21 and GDF15 levels via ATF4. Using knockout mice, we show these hormones are both necessary for its anti-obesity effects. Thus, our study first reports the beneficial metabolic effects of halofuginone and underscores its utility to treat obesity and its associated metabolic complications.

pharmacology and toxicology↗

bioRxiv2024

Identification of Meibomian gland stem cell populations and mechanisms of aging

Meibomian glands secrete lipid-rich meibum, which prevents tear evaporation. Aging-related Meibomian gland shrinkage may result in part from stem cell exhaustion and is associated with evaporative dry eye disease, a common condition lacking effective treatment. The identities and niche of Meibomian gland stem cells and the signals controlling their activity are poorly defined. Using snRNA-seq, in vivo lineage tracing, ex vivo live imaging, and genetic studies in mice, we identified markers for stem cell populations that maintain distinct regions of the gland and uncovered Hh signaling as a key regulator of stem cell proliferation. Consistent with this, human Meibomian gland carcinoma exhibited increased Hh signaling. Aged glands displayed decreased Hh and EGF signaling, deficient innervation, and loss of collagen I in niche fibroblasts, indicating that alterations in both glandular epithelial cells and their surrounding microenvironment contribute to age-related degeneration. These findings suggest new approaches to treat aging-associated Meibomian gland loss.

cell biology↗

bioRxiv2024

The ameliorative effect of C-Kit pos hepatic endothelial Mertk deficiency on nonalcoholic steatohepatitis

Recently, Mer tyrosine kinase (Mertk) and KIT proto-oncogene (C-Kit) were reported play a role in liver sinusoidal endothelial cells (LSECs) in patients with nonalcoholic steatohepatitis (NASH). In this study, lower levels of C-Kit and higher levels of Mertk/p-Mertk were confirmed in steatotic LSECs and in the livers of patients and mice with NASH. C-Kit was suggested to negatively regulate Mertk signaling in steatotic LSECs. The steatotic LSECs in which Mertk was knocked down displayed high fenestration and reduced expression of procapillarized CD31/VN; showed antiangiogenic features and decreased expression of proangiogenic VEGF/ERK1/2; and exhibited intact mitophagy and upregulation of the Pink1/Parkin pathway. Bone marrow transplantation (BMT) of C-Kitpos-BMCssh-Mertk to MCD mice could equivalently protect endothelial functions. Steatotic hepatocytes (HCs) or hepatic stellate cells (HSCs) cocultured with LSECssh-Mertk exhibited diminished lipid deposition; decreased expression of prolipogenic LXR/SREBP-1c, proinflammatory TNF-/IL-6 and profibrotic -SMA/ColI; and increased expression of prolipolytic FXR/ADPN. Similarly, the BMT of C-Kitpos-BMCssh-Mertk to MCD mice ameliorated NASH. C-Kitpos-LSECs that underwent Mertk cleavage were found to limit NASH progression. Therefore, Mertk deficiency should be a novel therapeutic agent for restoring LSECs in patients with NASH.

molecular biology↗

bioRxiv2024

MetaGXplore: Integrating Multi-Omics Data with Graph Convolutional Networks for Pan-cancer Patient Metastasis Identification

The spread of cancer cells from the primary tumor to distant anatomical sites, known as tumor metastasis, poses a significant challenge in clinical prognosis, impairing treatment efficacy and reducing patient survival time. Current methods for predicting and diagnosing tumor metastasis rely heavily on extensive examinations and subjective clinical judgments. Accurate and rapid prediction of tumor metastasis likelihood remains an unresolved challenge, crucial for guiding effective clinical interventions and extending patient survival. Additionally, identifying key genes highly associated with metastasis probability is a pressing issue, essential for providing valuable insights into the potential identification of tumor metastasis-specific biomarkers. We developed MetaGXplore, a pioneering Graph Convolutional Neural Network (GCN)-based framework designed to predict metastasis probability by integrating pan-cancer multi-omic datasets with a protein-protein interaction network, while also identifying key genes involved in the metastatic process. Multi-omics datasets offer a comprehensive view of cancer biology, enhancing accuracy in metastasis forecasting through superior deep learning algorithms. Our classification model results were interpreted with GNNExplainer. The efficacy of MetaGXplore was validated via model evaluations, graph structure analysis, and multi-omics data assessment. Enrichment analysis of key genes further explored their biological roles.

bioinformatics↗

bioRxiv2024

Unraveling Lineage Roadmaps and Cell Fate Determinants to Postnatal Neural Stem Cells and Ependymal cells in the Developing Ventricular Zone

The ventricular zone (VZ) is made up of adult neural stem cells (NSCs) and multi-ciliated ependymal cells (EPCs). Both NSCs and EPCs are derived from radial glial cells (RGCs). To date, the transcriptomic dynamics and the molecular mechanisms guiding the cell fate commitment during the differentiation remain poorly understood. In this study, we analysed the developing VZ at the single-cell resolution and identified three distinct cellular states of RGCs: bipotent glial progenitor cells (bGPCs), neonatal NSC-neuroblasts (nNSC-NBs) and neonatal EPCs (nEPCs). The differentiation from bGPCs to nNSC-NBs and nEPCs forms a continuous bifurcating trajectory. Further molecular analysis along the NSC branch unveiled a novel intermediate state of cells expressing oligodendrocyte precursor cell (OPC) and neuroblast (NB) marker genes. Several transcription factors (TFs) were proved to be essential for the EPC-lineage differentiation, with TFEB emerging as a key regulator dictating the bGPC fate. The activation of TFEB promoted differentiation towards NSC-NBs while restrained the trajectory towards EPCs. Our findings offer detailed insights into further understanding VZ development and lay the groundwork for investigating potential therapeutic strategies against VZ-related disorders, such as hydrocephalus and neurodegenerative diseases (NDDs).

genomics↗

bioRxiv2024

Inferring single-cell spatial gene expression with tissue morphology via explainable deep learning

Deep learning models trained with spatial omics data uncover complex patterns and relationships among cells, genes, and proteins in a high-dimensional space. State-of-the-art in silico spatial multi-cell gene expression methods using histological images of tissue stained with hematoxylin and eosin (H&E) allow us to characterize cellular heterogeneity. We developed a vision transformer (ViT) framework to map histological signatures to spatial single-cell transcriptomic signatures, named SPiRiT. SPiRiT predicts single-cell spatial gene expression using the matched H&E image tiles of human breast cancer and whole mouse pup, evaluated by Xenium (10x Genomics) datasets. Importantly, SPiRiT incorporates rigorous strategies to ensure reproducibility and robustness of predictions and provides trustworthy interpretation through attention-based model explainability. SPiRiT model interpretation revealed the areas, and attention details it uses to predict gene expressions like marker genes in invasive cancer cells. In an apple-to-apple comparison with ST-Net, SPiRiT improved the predictive accuracy by 40%. These gene predictions and expression levels were highly consistent with the tumor region annotation. In summary, SPiRiT highlights the feasibility to infer spatial single-cell gene expression using tissue morphology in multiple-species.

bioinformatics↗

bioRxiv2024

Mapping Somatosensory Afferent Circuitry to Bone Identifies Neurotrophic Signals Required for Fracture Healing

The profound pain accompanying bone fracture is mediated by somatosensory neurons, which also appear to be required to initiate bone regeneration following fracture. Surprisingly, the precise neuroanatomical circuitry mediating skeletal nociception and regeneration remains incompletely understood. Here, we characterized somatosensory dorsal root ganglia (DRG) afferent neurons innervating murine long bones before and after experimental long bone fracture in mice. Retrograde labeling of DRG neurons by an adeno-associated virus with peripheral nerve tropism showed AAV-tdT signal. Single cell transcriptomic profiling of 6,648 DRG neurons showed highest labeling across CGRP+ neuron clusters (6.9-17.2%) belonging to unmyelinated C fibers, thinly myelinated A{delta} fibers and A{beta}-Field LTMR (9.2%). Gene expression profiles of retrograde labeled DRG neurons over multiple timepoints following experimental stress fracture revealed dynamic changes in gene expression corresponding to the acute inflammatory (S100a8, S100a9) and mechanical force (Piezo2). Reparative phase after fracture included morphogens such as Tgfb1, Fgf9 and Fgf18. Two methods to surgically or genetically denervate fractured bones were used in combination with scRNA-seq to implicate defective mesenchymal cell proliferation and osteodifferentiation as underlying the poor bone repair capacity in the presence of attenuated innervation. Finally, multi-tissue scRNA-seq and interactome analyses implicated neuron-derived FGF9 as a potent regulator of fracture repair, a finding compatible with in vitro assessments of neuron-to-skeletal mesenchyme interactions.

cell biology↗

bioRxiv2024

Coral hosts actively accumulate inorganic carbon for zooxanthellae to maintain symbiotic relationships

High primary productivity of coral reefs is widely attributed to the mutualistic symbiosis between coral hosts and their microalgal partners (Symbiodiniaceae). Although the mechanisms maintaining this symbiosis have been considerable investigated, how the symbiont microalgae within coral get sufficient CO2 for photosynthesis still remains inadquately explored. Here, we hypothesized that corals may actively accumulate dissolved inorganic carbon (DIC) for microalgae to maintain the symbiosis. Carbon (HCO3- and glucose) supply and consumption were evaluated in the scleractinian coral (Goniopora lobata) and its symbiont under light and dark conditions. Results suggest that Symbiodiniaceae were high DIC consumers, requiring about 2-3 fold more DIC than free-living species. The corals were high DIC producers, with internal concentrations up to 4.2 fold higher than in the surrounding seawater. In the absence of microalgae utilization, the excess DIC they produced appeared detrimental to their own growth. Moreover, transcriptomic analysis identified several DIC enrichment pathways are evolved in corals to attact the Symbiodiniaceae, including CO2 concentrating mechanisms, respiration, calcification and phosphoenolpyruvate carboxylase. Increased the CO2 dosage in seawater may induce coral symbiosis bleaching. Our findings can deeper reveal on the mechanisms sustaining coral symbiosis, and may help to predict how some corals respond to DIC imbalance under climate changes.

ecology↗

bioRxiv2024

Structural and Biophysical Dynamics of Fungal Plasma Membrane Proteins and Implications for Echinocandin Action in Candida glabrata

Fungal plasma membrane proteins represent key therapeutic targets for antifungal agents, yet their structure and spatial distribution in the native context remain poorly characterized. Herein, we employ an integrative multimodal approach to elucidate the structural and functional organization of plasma membrane protein complexes in Candida glabrata, focusing on prominent and essential membrane proteins, the polysaccharide synthase {beta}-(1,3)-glucan synthase (GS) and the proton pump Pma1. Cryo-electron tomography (cryo-ET) and live cell imaging reveal that GS and Pma1 are heterogeneously distributed into distinct plasma membrane microdomains. Treatment with caspofungin, an echinocandin antifungal that targets GS, alters the plasma membrane and disrupts the native distribution of GS and Pma1. Based on these findings, we propose a model for echinocandin action that considers how drug interactions with the plasma membrane environment lead to inhibition of GS. Our work underscores the importance of interrogating the structural and dynamic characteristics of fungal plasma membrane proteins in situ to understand function and facilitate precisely targeted development of novel antifungal therapies.

cell biology↗

bioRxiv2024

Excessive Dietary Fructose Aggravates Heart Failure via Impairing Myocardial Fatty Acid Oxidation Metabolism in Diet Induced Obese Mouse

BackgroundAn unhealthy diet and a sedentary lifestyle increase the prevalence of cardiometabolic syndrome. Several cardiovascular diseases (CVDs) have been highly linked to excessive added sugar intake, which alters whole-body metabolism, including heart tissue. However, whether specific added sugars can cause and aggravate severe heart dysfunction is still unknown. MethodsWe examined the association between CVDs and added sugar intake using statistical analyses and Mendelian randomization (MR). Then, we evaluated the effect of added sugar on mouse heart function employing a diet-induced obese (DIO) model with transverse aortic constriction (TAC) challenge. We measured the fatty acid and fructose metabolic flux in mouse hearts employing a mass spectrometry-based in vivo double stable isotopic labeling (DSIL) technique. The results of animal models were also confirmed in aortic stenosis (AS) patient samples. ResultsStatistical analyses and MR estimation on public databases indicated that added sugars, especially fructose, are associated with a high risk of heart failure. Feeding on either ingested or drunk fructose could aggravate heart failure and diastolic and systolic dysfunction in TAC challenged DIO mice. Mechanistically, excessive dietary intake of fructose could suppress heart fatty acid oxidation (FAO) metabolism via both shrinkage of the flux rate of FAO and inhibition of the AMPK-ACC axis. Activation of AMPK or deactivation of ACC could limit such heart dysfunction and myocardial hypertrophy. We also obtained plasma from 27 patients with AS and determined that the high fructose level instead of glucose or sucrose was linked to left ventricular ejection fractions (LVEF) and fractional shortening (FS) decline. ConclusionsFindings from epidemiological statistical analyses and investigations of animal models suggested the harmful effect of excessive fructose intake on heart function. Fructose could directly alter heart metabolism by suppressing FAO. Our results implied that targeting AMPK-ACC mediation could effectively attenuate excessive fructose-induced heart failure in DIO mice.

physiology↗

bioRxiv2024

Kinship analysis and pedigree reconstruction by RAD sequencing in cattle

Kinship and pedigree information, used for estimating inbreeding, heritability, selection, and gene flow, is useful for breeding and animal conservation. However, as the size of the crossbred population increases, inaccurate generation and parentage recoding in livestock farms increases. Restriction-site-associated DNA sequencing (RAD-Seq) is a cost-effective platform for single nucleotide polymorphism (SNP) discovery and genotyping. Here, we performed a kinship analysis and pedigree reconstruction for Angus and Xiangxi yellow cattle, which benefit from good meat quality and yields, providing a basis for livestock management. A total of 975 cattle, including 923 offspring with 24 known sires and 28 known dams, were sampled and subjected to SNP discovery and genotyping. The identified SNPs panel included 7305 SNPs capturing the maximum difference between paternal and maternal genome information allowing us to distinguish between the F1 and F2 generation with 90% accuracy. In addition, parentage assignment software based on different strategies verified that the cross-assignments. In conclusion, we provided a low-cost and efficient SNP panel for kinship analyses and the improvement of local genetic resources, which are valuable for breed improvement, local resource utilization, and conservation.

genomics↗