Browsing by Author "Arango-Argoty, Gustavo"

Now showing 1 - 13 of 13
  • Thumbnail Image
    Apigenin Impacts the Growth of the Gut Microbiota and Alters the Gene Expression of Enterococcus
    Wang, Minqian; Firrman, Jenni; Zhang, Liqing; Arango-Argoty, Gustavo; Tomasula, Peggy; Liu, Lin Shu; Xiao, Weidong; Yam, Kit (MDPI, 2017-08-03)
    Apigenin is a major dietary flavonoid with many bioactivities, widely distributed in plants. Apigenin reaches the colon region intact and interacts there with the human gut microbiota, however there is little research on how apigenin affects the gut bacteria. This study investigated the effect of pure apigenin on human gut bacteria, at both the single strain and community levels. The effect of apigenin on the single gut bacteria strains Bacteroides galacturonicus, Bifidobacterium catenulatum, Lactobacillus rhamnosus GG, and Enterococcus caccae, was examined by measuring their anaerobic growth profiles. The effect of apigenin on a gut microbiota community was studied by culturing a fecal inoculum under in vitro conditions simulating the human ascending colon. 16S rRNA gene sequencing and GC-MS analysis quantified changes in the community structure. Single molecule RNA sequencing was used to reveal the response of Enterococcus caccae to apigenin. Enterococcus caccae was effectively inhibited by apigenin when cultured alone, however, the genus Enterococcus was enhanced when tested in a community setting. Single molecule RNA sequencing found that Enterococcus caccae responded to apigenin by up-regulating genes involved in DNA repair, stress response, cell wall synthesis, and protein folding. Taken together, these results demonstrate that apigenin affects both the growth and gene expression of Enterococcus caccae.
  • Thumbnail Image
    Comparison of Whole-Genome Sequences of Legionella pneumophila in Tap Water and in Clinical Strains, Flint, Michigan, USA, 2016
    Garner, Emily; Brown, Connor L.; Schwake, David Otto; Rhoads, William J.; Arango-Argoty, Gustavo; Zhang, Liqing; Jospin, Guillaume; Coil, David A.; Eisen, Jonathan A.; Edwards, Marc A.; Pruden, Amy (Centers for Disease Control and Prevention, 2019-11)
    During the water crisis in Flint, Michigan, USA (2014–2015), 2 outbreaks of Legionnaires’ disease occurred in Genesee County, Michigan. We compared whole-genome sequences of 10 clinical Legionella pneumophila isolates submitted to a laboratory in Genesee County during the second outbreak with 103 water isolates collected the following year. We documented a genetically diverse range of L. pneumophila strains across clinical and water isolates. Isolates belonging to 1 clade (3 clinical isolates, 3 water isolates from a Flint hospital, 1 water isolate from a Flint residence, and the reference Paris strain) had a high degree of similarity (2–1,062 single-nucleotide polymorphisms), all L. pneumophila sequence type 1, serogroup 1. Serogroup 6 isolates belonging to sequence type 2518 were widespread in Flint hospital water samples but bore no resemblance to available clinical isolates. L. pneumophila strains in Flint tap water after the outbreaks were diverse and similar to some disease-causing strains.
  • Thumbnail Image
    Comprehensive off-target analysis of dCas9-SAM-mediated HIV reactivation via long noncoding RNA and mRNA profiling
    Zhang, Yonggang; Arango-Argoty, Gustavo; Li, Fang; Xiao, Xiao; Putatunda, Raj; Yu, Jun; Yang, Xiao-Feng; Wang, Hong; Watson, Layne T.; Zhang, Liqing; Hu, Wenhui (2018-09-10)
    Background CRISPR/CAS9 (epi)genome editing revolutionized the field of gene and cell therapy. Our previous study demonstrated that a rapid and robust reactivation of the HIV latent reservoir by a catalytically-deficient Cas9 (dCas9)-synergistic activation mediator (SAM) via HIV long terminal repeat (LTR)-specific MS2-mediated single guide RNAs (msgRNAs) directly induces cellular suicide without additional immunotherapy. However, potential off-target effect remains a concern for any clinical application of Cas9 genome editing and dCas9 epigenome editing. After dCas9 treatment, potential off-target responses have been analyzed through different strategies such as mRNA sequence analysis, and functional screening. In this study, a comprehensive analysis of the host transcriptome including mRNA, lncRNA, and alternative splicing was performed using human cell lines expressing dCas9-SAM and HIV-targeting msgRNAs. Results The control scrambled msgRNA (LTR_Zero), and two LTR-specific msgRNAs (LTR_L and LTR_O) groups show very similar expression profiles of the whole transcriptome. Among 839 identified lncRNAs, none exhibited significantly different expression in LTR_L vs. LTR_Zero group. In LTR_O group, only TERC and scaRNA2 lncRNAs were significantly decreased. Among 142,791 mRNAs, four genes were differentially expressed in LTR_L vs. LTR_Zero group. There were 21 genes significantly downregulated in LTR_O vs. either LTR_Zero or LTR_L group and one third of them are histone related. The distributions of different types of alternative splicing were very similar either within or between groups. There were no apparent changes in all the lncRNA and mRNA transcripts between the LTR_L and LTR_Zero groups. Conclusion This is an extremely comprehensive study demonstrating the rare off-target effects of the HIV-specific dCas9-SAM system in human cells. This finding is encouraging for the safe application of dCas9-SAM technology to induce target-specific reactivation of latent HIV for an effective “shock-and-kill” strategy.
  • Thumbnail Image
    DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data
    Arango-Argoty, Gustavo; Garner, Emily; Pruden, Amy; Heath, Lenwood S.; Vikesland, Peter J.; Zhang, Liqing (2018-02-01)
    Background Growing concerns about increasing rates of antibiotic resistance call for expanded and comprehensive global monitoring. Advancing methods for monitoring of environmental media (e.g., wastewater, agricultural waste, food, and water) is especially needed for identifying potential resources of novel antibiotic resistance genes (ARGs), hot spots for gene exchange, and as pathways for the spread of ARGs and human exposure. Next-generation sequencing now enables direct access and profiling of the total metagenomic DNA pool, where ARGs are typically identified or predicted based on the “best hits” of sequence searches against existing databases. Unfortunately, this approach produces a high rate of false negatives. To address such limitations, we propose here a deep learning approach, taking into account a dissimilarity matrix created using all known categories of ARGs. Two deep learning models, DeepARG-SS and DeepARG-LS, were constructed for short read sequences and full gene length sequences, respectively. Results Evaluation of the deep learning models over 30 antibiotic resistance categories demonstrates that the DeepARG models can predict ARGs with both high precision (> 0.97) and recall (> 0.90). The models displayed an advantage over the typical best hit approach, yielding consistently lower false negative rates and thus higher overall recall (> 0.9). As more data become available for under-represented ARG categories, the DeepARG models’ performance can be expected to be further enhanced due to the nature of the underlying neural networks. Our newly developed ARG database, DeepARG-DB, encompasses ARGs predicted with a high degree of confidence and extensive manual inspection, greatly expanding current ARG repositories. Conclusions The deep learning models developed here offer more accurate antimicrobial resistance annotation relative to current bioinformatics practice. DeepARG does not require strict cutoffs, which enables identification of a much broader diversity of ARGs. The DeepARG models and database are available as a command line version and as a Web service at http://bench.cs.vt.edu/deeparg.
  • Thumbnail Image
    Demonstrating a Comprehensive Wastewater-Based Surveillance Approach That Differentiates Globally Sourced Resistomes
    Prieto Riquelme, Maria Virginia; Garner, Emily; Gupta, Suraj; Metch, Jake; Zhu, Ni; Blair, Matthew F.; Arango-Argoty, Gustavo; Maile-Moskowitz, Ayella; Li, An-dong; Flach, Carl-Fredrik; Aga, Diana S.; Nambi, Indumathi M.; Larsson, D. G. Joakim; Bürgmann, Helmut; Zhang, Tong; Pruden, Amy; Vikesland, Peter J. (ACS, 2022-06-27)
    Wastewater-based surveillance (WBS) for disease monitoring is highly promising but requires consistent methodologies that incorporate predetermined objectives, targets, and metrics. Herein, we describe a comprehensive metagenomics-based approach for global surveillance of antibiotic resistance in sewage that enables assessment of 1) which antibiotic resistance genes (ARGs) are shared across regions/communities; 2) which ARGs are discriminatory; and 3) factors associated with overall trends in ARGs, such as antibiotic concentrations. Across an internationally sourced transect of sewage samples collected using a centralized, standardized protocol, ARG relative abundances (16S rRNA gene-normalized) were highest in Hong Kong and India and lowest in Sweden and Switzerland, reflecting national policy, measured antibiotic concentrations, and metal resistance genes. Asian versus European/US resistomes were distinct, with macrolide-lincosamide-streptogramin, phenicol, quinolone, and tetracycline versus multidrug resistance ARGs being discriminatory, respectively. Regional trends in measured antibiotic concentrations differed from trends expected from public sales data. This could reflect unaccounted uses, captured only by the WBS approach. If properly benchmarked, antibiotic WBS might complement public sales and consumption statistics in the future. The WBS approach defined herein demonstrates multisite comparability and sensitivity to local/regional factors.
  • Thumbnail Image
    Effects of Dairy Manure-Based Amendments and Soil Texture on Lettuce-and Radish-Associated Microbiota and Resistomes
    Guron, Giselle K.P.; Arango-Argoty, Gustavo; Zhang, Liqing; Pruden, Amy; Ponder, Monica A. (American Society for Microbiology, 2019)
    Dairy cattle are routinely treated with antibiotics, and the resulting manure or composted manure is commonly used as a soil amendment for crop production, raising questions regarding the potential for antibiotic resistance to propagate from “farm to fork.” The objective of this study was to compare the microbiota and “resistomes” (i.e., carriage of antibiotic resistance genes [ARGs]) associated with lettuce leaf and radish taproot surfaces grown in different soils amended with dairy manure, compost, or chemical fertilizer only (control). Manure was collected from antibiotic-free dairy cattle (DC) or antibiotic-treated dairy cattle (DA), with a portion composted for parallel comparison. Amendments were applied to loamy sand or silty clay loam, and lettuce and radishes were cultivated to maturity in a greenhouse. Metagenomes were profiled via shotgun Illumina sequencing. Radishes carried a distinct ARG composition compared to that of lettuce, with greater relative abundance of total ARGs. Taxonomic species richness was also greater for radishes by 1.5-fold. The resistomes of lettuce grown with DC compost were distinct from those grown with DA compost, DC manure, or fertilizer only. Further, compost applied to loamy sand resulted in twofold-greater relative abundance of total ARGs on lettuce than when applied to silty clay loam. The resistomes of radishes grown with biological amendments were distinct from the corresponding fertilizer controls, but effects of composting or antibiotic use were not measureable. Cultivation in loamy sand resulted in higher species richness for both lettuce and radishes than when grown in silty clay loam by 2.2-fold and 1.2-fold, respectively, when amended with compost.
  • Thumbnail Image
    Identification of discriminatory antibiotic resistance genes among environmental resistomes using extremely randomized tree algorithm
    Gupta, Suraj; Arango-Argoty, Gustavo; Zhang, Liqing; Pruden, Amy; Vikesland, Peter J. (2019-08-29)
    Background The interconnectivities of built and natural environments can serve as conduits for the proliferation and dissemination of antibiotic resistance genes (ARGs). Several studies have compared the broad spectrum of ARGs (i.e., “resistomes”) in various environmental compartments, but there is a need to identify unique ARG occurrence patterns (i.e., “discriminatory ARGs”), characteristic of each environment. Such an approach will help to identify factors influencing ARG proliferation, facilitate development of relative comparisons of the ARGs distinguishing various environments, and help pave the way towards ranking environments based on their likelihood of contributing to the spread of clinically relevant antibiotic resistance. Here we formulate and demonstrate an approach using an extremely randomized tree (ERT) algorithm combined with a Bayesian optimization technique to capture ARG variability in environmental samples and identify the discriminatory ARGs. The potential of ERT for identifying discriminatory ARGs was first evaluated using in silico metagenomic datasets (simulated metagenomic Illumina sequencing data) with known variability. The application of ERT was then demonstrated through analyses using publicly available and in-house metagenomic datasets associated with (1) different aquatic habitats (e.g., river, wastewater influent, hospital effluent, and dairy farm effluent) to compare resistomes between distinct environments and (2) different river samples (i.e., Amazon, Kalamas, and Cam Rivers) to compare resistome characteristics of similar environments. Results The approach was found to readily identify discriminatory ARGs in the in silico datasets. Also, it was not found to be biased towards ARGs with high relative abundance, which is a common limitation of feature projection methods, and instead only captured those ARGs that elicited significant profiles. Analyses of publicly available metagenomic datasets further demonstrated that the ERT approach can effectively differentiate real-world environmental samples and identify discriminatory ARGs based on pre-defined categorizing schemes. Conclusions Here a new methodology was formulated to characterize and compare variances in ARG profiles between metagenomic data sets derived from similar/dissimilar environments. Specifically, identification of discriminatory ARGs among samples representing various environments can be identified based on factors of interest. The methodology could prove to be a particularly useful tool for ARG surveillance and the assessment of the effectiveness of strategies for mitigating the spread of antibiotic resistance. The python package is hosted in the Git repository: https://github.com/gaarangoa/ExtrARG
  • Thumbnail Image
    Metagenomic profiling of historic Colorado Front Range flood impact on distribution of riverine antibiotic resistance genes
    Garner, Emily; Wallace, Joshua S.; Arango-Argoty, Gustavo; Wilkinson, Caitlin; Fahrenfeld, Nicole; Heath, Lenwood S.; Zhang, Liqing; Arabi, Mazdak; Aga, Diana S.; Pruden, Amy (Nature Publishing Group, 2016-12-05)
    Record-breaking floods in September 2013 caused massive damage to homes and infrastructure across the Colorado Front Range and heavily impacted the Cache La Poudre River watershed. Given the unique nature of this watershed as a test-bed for tracking environmental pathways of antibiotic resistance gene (ARG) dissemination, we sought to determine the impact of extreme flooding on ARG reservoirs in river water and sediment. We utilized high-throughput DNA sequencing to obtain metagenomic profiles of ARGs before and after flooding, and investigated 23 antibiotics and 14 metals as putative selective agents during post-flood recovery. With 277 ARG subtypes identified across samples, total bulk water ARGs decreased following the flood but recovered to near pre-flood abundances by ten months post-flood at both a pristine site and at a site historically heavily influenced by wastewater treatment plants and animal feeding operations. Network analysis of de novo assembled sequencing reads into 52,556 scaffolds identified ARGs likely located on mobile genetic elements, with up to 11 ARGs per plasmid-associated scaffold. Bulk water bacterial phylogeny correlated with ARG profiles while sediment phylogeny varied along the river’s anthropogenic gradient. This rare flood afforded the opportunity to gain deeper insight into factors influencing the spread of ARGs in watersheds.
  • Thumbnail Image
    MetaStorm: A Public Resource for Customizable Metagenomics Annotation
    Arango-Argoty, Gustavo; Singh, Garhi; Heath, Lenwood S.; Pruden, Amy; Xiao, Weidong; Zhang, Liqing (PLOS, 2016-09-15)
    Metagenomics is a trending research area, calling for the need to analyze large quantities of data generated from next generation DNA sequencing technologies. The need to store, retrieve, analyze, share, and visualize such data challenges current online computational systems. Interpretationand annotation of specific information is especially a challenge for metagenomic data sets derived from environmental samples, because current annotation systems only offer broad classification of microbial diversity and function. Moreover, existing resources are not configured to readily address common questions relevant to environmental systems. Here we developed a new online user-friendly metagenomic analysis server called MetaStorm (http://bench.cs.vt.edu/MetaStorm/), which facilitates customization of computational analysis for metagenomic data sets. Users can upload their own reference databases to tailor the metagenomics annotation to focus on various taxonomic and functional gene markers of interest. MetaStormoffers two major analysis pipelines: an assembly-based annotation pipeline and the standard read annotation pipeline used by existing web servers. These pipelines can be selected individually or together. Overall, MetaStorm provides enhanced interactive visualization to allow researchers to explore and manipulate taxonomy and functional annotation at various levels of resolution.
  • Thumbnail Image
    NanoARG: a web service for detecting and contextualizing antimicrobial resistance genes from nanopore-derived metagenomes
    Arango-Argoty, Gustavo; Dai, Dongjuan; Pruden, Amy; Vikesland, Peter J.; Heath, Lenwood S.; Zhang, Liqing (2019-06-07)
    Background Direct and indirect selection pressures imposed by antibiotics and co-selective agents and horizontal gene transfer are fundamental drivers of the evolution and spread of antibiotic resistance. Therefore, effective environmental monitoring tools should ideally capture not only antibiotic resistance genes (ARGs), but also mobile genetic elements (MGEs) and indicators of co-selective forces, such as metal resistance genes (MRGs). A major challenge towards characterizing the potential human health risk of antibiotic resistance is the ability to identify ARG-carrying microorganisms, of which human pathogens are arguably of greatest risk. Historically, short reads produced by next-generation sequencing technologies have hampered confidence in assemblies for achieving these purposes. Results Here, we introduce NanoARG, an online computational resource that takes advantage of the long reads produced by nanopore sequencing technology. Specifically, long nanopore reads enable identification of ARGs in the context of relevant neighboring genes, thus providing valuable insight into mobility, co-selection, and pathogenicity. NanoARG was applied to study a variety of nanopore sequencing data to demonstrate its functionality. NanoARG was further validated through characterizing its ability to correctly identify ARGs in sequences of varying lengths and a range of sequencing error rates. Conclusions NanoARG allows users to upload sequence data online and provides various means to analyze and visualize the data, including quantitative and simultaneous profiling of ARGs, MRGs, MGEs, and putative pathogens. A user-friendly interface allows users the analysis of long DNA sequences (including assembled contigs), facilitating data processing, analysis, and visualization. NanoARG is publicly available and freely accessible at https://bench.cs.vt.edu/nanoarg .
  • Thumbnail Image
    Secure Coding Practices in Java: Challenges and Vulnerabilities
    Meng, Na; Nagy, Stefan; Yao, Danfeng (Daphne); Zhuang, Wenjie; Arango-Argoty, Gustavo (Virginia Tech, 2017-09-28)
    Java platform and third-party libraries provide various security features to facilitate secure coding. However, misusing these features can cost tremendous time and effort of developers or cause security vulnerabilities in software. Prior research was focused on the misuse of cryptography and SSL APIs, but did not explore the key fundamental research question: what are the biggest challenges and vulnerabilities in secure coding practices? In this paper, we conducted a comprehensive empirical study on StackOverflow posts to understand developers’ concerns on Java secure coding, their programming obstacles, and potential vulnerabilities in their code. We observed that developers have shifted their effort to the usage of authentication and authorization features provided by Spring security—a third-party framework designed to secure enterprise applications. Multiple programming challenges are related to APIs or libraries, including the complicated cross-language data handling of cryptography APIs, and the complex Java-based or XML-based approaches to configure Spring security. More interestingly, we identified security vulnerabilities in the suggested code of accepted answers. The vulnerabilities included using insecure hash functions such as MD5, breaking SSL/TLS security through bypassing certificate validation, and insecurely disabling the default protection against Cross Site Request Forgery (CSRF) attacks. Our findings reveal the insufficiency of secure coding assistance and education, and the gap between security theory and coding practices.
  • Thumbnail Image
    Triclosan has a robust, yet reversible impact on human gut microbial composition in vitro
    Mahalak, Karley K.; Firrman, Jenni; Lee, Jung-Jin; Bittinger, Kyle; Nunez, Alberto; Mattei, Lisa M.; Zhang, Huanjia; Fett, Bryton; Bobokalonov, Jamshed; Arango-Argoty, Gustavo; Zhang, Liqing; Zhang, Guodong; Liu, Lin Shu (2020-06-25)
    The recent ban of the antimicrobial compound triclosan from use in consumer soaps followed research that showcased the risk it poses to the environment and to human health. Triclosan has been found in human plasma, urine and milk, demonstrating that it is present in human tissues. Previous work has also demonstrated that consumption of triclosan disrupts the gut microbial community of mice and zebrafish. Due to the widespread use of triclosan and ubiquity in the environment, it is imperative to understand the impact this chemical has on the human body and its symbiotic resident microbes. To that end, this study is the first to explore how triclosan impacts the human gut microbial communityin vitroboth during and after treatment. Through ourin vitrosystem simulating three regions of the human gut; the ascending colon, transverse colon, and descending colon regions, we found that treatment with triclosan significantly impacted the community structure in terms of reduced population, diversity, and metabolite production, most notably in the ascending colon region. Given a 2 week recovery period, most of the population levels, community structure, and diversity levels were recovered for all colon regions. Our results demonstrate that the human gut microbial community diversity and population size is significantly impacted by triclosan at a high dosein vitro, and that the community is recoverable within this system.
  • Thumbnail Image
    Triclosan has a robust, yet reversible impact on human gut microbial composition in vitro
    Mahalak, Karley K.; Firrman, Jenni; Lee, Jung-Jin; Bittinger, Kyle; Nunez, Alberto; Mattei, Lisa M.; Zhang, Huanjia; Fett, Bryton; Bobokalonov, Jamshed; Arango-Argoty, Gustavo; Zhang, Liqing; Zhang, Guodong; Liu, Lin Shu (2020-06-25)
    The recent ban of the antimicrobial compound triclosan from use in consumer soaps followed research that showcased the risk it poses to the environment and to human health. Triclosan has been found in human plasma, urine and milk, demonstrating that it is present in human tissues. Previous work has also demonstrated that consumption of triclosan disrupts the gut microbial community of mice and zebrafish. Due to the widespread use of triclosan and ubiquity in the environment, it is imperative to understand the impact this chemical has on the human body and its symbiotic resident microbes. To that end, this study is the first to explore how triclosan impacts the human gut microbial communityin vitroboth during and after treatment. Through ourin vitrosystem simulating three regions of the human gut; the ascending colon, transverse colon, and descending colon regions, we found that treatment with triclosan significantly impacted the community structure in terms of reduced population, diversity, and metabolite production, most notably in the ascending colon region. Given a 2 week recovery period, most of the population levels, community structure, and diversity levels were recovered for all colon regions. Our results demonstrate that the human gut microbial community diversity and population size is significantly impacted by triclosan at a high dosein vitro, and that the community is recoverable within this system.