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Lamb MM, Paniagua-Avila A, Zacarias A, Rojop N, Chacon A, Natrajan MS, Waggoner JJ, Lopez MR, Cordon-Rosales C, Huleatt JW, Bonaparte MI, Asturias EJ, Olson D. Repeated Rapid Active Sampling Surveys Demonstrated a Rapidly Changing Zika Seroprevalence among Children in a Rural Dengue-endemic Region in Southwest Guatemala during the Zika Epidemic (2015-2016). Am J Trop Med Hyg 2022; 107:1099-1106. [PMID: 36252798 PMCID: PMC9709015 DOI: 10.4269/ajtmh.22-0399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 08/08/2022] [Indexed: 11/07/2022] Open
Abstract
Although Central America is largely dengue virus (DENV)-endemic, the 2015-2016 Zika virus (ZIKV) pandemic brought new urgency to develop surveillance approaches capable of characterizing the rapidly changing disease burden in resource-limited settings. We conducted a pediatric DENV surveillance study in rural Guatemala, including serial cross-sectional surveys from April through September 2015 (Survey 1), in October-November 2015 (Survey 2), and January-February 2016 (Survey 3). Serum underwent DENV IgM MAC ELISA and polymerase chain reaction testing. Using banked specimens from Surveys 2 and 3, we expanded testing to include DENV 1-4 and ZIKV microneutralization (MN50), DENV NS1 IgG ELISA, and ZIKV anti-NS1 antibody Blockage of Binding (BoB) ELISA testing. Demographic risk factors for ZIKV BoB positivity were explored using multivariable generalized linear regression models. Of Survey 2 and 3 samples available (N = 382), DENV seroprevalence slightly increased (+1%-10% depending on the assay) during the surveillance period and increased with age. In contrast, ZIKV seroprevalence consistently increased over the 3-month period, including from 6% to 34% (P < 0.0001) and 10%-37% (P < 0.0001) using the MN50 ≥100 and BoB ELISA assays, respectively. Independent risk factors for ZIKV seropositivity included older age (prevalence ratio (PR)/year = 1.12, 95% confidence interval (CI) = 1.07-1.17) and primary caregiver literacy (PR = 2.80, CI = 1.30-6.06). Rapid active surveillance (RAS) surveys demonstrated a nearly 30% increase in ZIKV prevalence and a slight (≤ 10%) increase in DENV seroprevalence from October to November 2015 to January to February 2016 in rural southwest Guatemala, regardless of serologic assay used. RAS surveys may be a useful "off-the-shelf" tool to characterize arboviruses and other emerging pathogens rapidly in resource-limited settings.
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Affiliation(s)
- Molly M. Lamb
- Department of Epidemiology and Center for Global Health, Colorado School of Public Health, Aurora, Colorado
| | - Alejandra Paniagua-Avila
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
- Center for Human Development, Fundacion para la Salud Integral de los Guatemaltecos, FUNSALUD, Coatepeque, Quetzaltenango, Guatemala
| | - Alma Zacarias
- Center for Human Development, Fundacion para la Salud Integral de los Guatemaltecos, FUNSALUD, Coatepeque, Quetzaltenango, Guatemala
| | - Neudy Rojop
- Center for Human Development, Fundacion para la Salud Integral de los Guatemaltecos, FUNSALUD, Coatepeque, Quetzaltenango, Guatemala
| | - Andrea Chacon
- Center for Human Development, Fundacion para la Salud Integral de los Guatemaltecos, FUNSALUD, Coatepeque, Quetzaltenango, Guatemala
| | - Muktha S. Natrajan
- Emory University Department of Medicine, Division of Infectious Diseases, Atlanta, Georgia
| | - Jesse J. Waggoner
- Emory University Department of Medicine, Division of Infectious Diseases, Atlanta, Georgia
| | - Maria Renee Lopez
- Centro de Estudios en Salud, Universidad del Valle de Guatemala, Guatemala City, Guatemala
| | - Celia Cordon-Rosales
- Centro de Estudios en Salud, Universidad del Valle de Guatemala, Guatemala City, Guatemala
| | | | | | - Edwin J. Asturias
- Department of Epidemiology and Center for Global Health, Colorado School of Public Health, Aurora, Colorado
- Department of Pediatrics, University of Colorado School of Medicine, Aurora, Colorado
| | - Daniel Olson
- Department of Epidemiology and Center for Global Health, Colorado School of Public Health, Aurora, Colorado
- Department of Pediatrics, University of Colorado School of Medicine, Aurora, Colorado
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Wang C, Ye Q, Jiang A, Zhang J, Shang Y, Li F, Zhou B, Xiang X, Gu Q, Pang R, Ding Y, Wu S, Chen M, Wu Q, Wang J. Pseudomonas aeruginosa Detection Using Conventional PCR and Quantitative Real-Time PCR Based on Species-Specific Novel Gene Targets Identified by Pangenome Analysis. Front Microbiol 2022; 13:820431. [PMID: 35602063 PMCID: PMC9119647 DOI: 10.3389/fmicb.2022.820431] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 03/14/2022] [Indexed: 12/17/2022] Open
Abstract
Mining novel specific molecular targets and establishing efficient identification methods are significant for detecting Pseudomonas aeruginosa, which can enable P. aeruginosa tracing in food and water. Pangenome analysis was used to analyze the whole genomic sequences of 2017 strains (including 1,000 P. aeruginosa strains and 1,017 other common foodborne pathogen strains) downloaded from gene databases to obtain novel species-specific genes, yielding a total of 11 such genes. Four novel target genes, UCBPP-PA14_00095, UCBPP-PA14_03237, UCBPP-PA14_04976, and UCBPP-PA14_03627, were selected for use, which had 100% coverage in the target strain and were not present in nontarget bacteria. PCR primers (PA1, PA2, PA3, and PA4) and qPCR primers (PA12, PA13, PA14, and PA15) were designed based on these target genes to establish detection methods. For the PCR primer set, the minimum detection limit for DNA was 65.4 fg/μl, which was observed for primer set PA2 of the UCBPP-PA14_03237 gene. The detection limit in pure culture without pre-enrichment was 105 colony-forming units (CFU)/ml for primer set PA1, 103 CFU/ml for primer set PA2, and 104 CFU/ml for primer set PA3 and primer set PA4. Then, qPCR standard curves were established based on the novel species-specific targets. The standard curves showed perfect linear correlations, with R2 values of 0.9901 for primer set PA12, 0.9915 for primer set PA13, 0.9924 for primer set PA14, and 0.9935 for primer set PA15. The minimum detection limit of the real-time PCR (qPCR) assay was 102 CFU/ml for pure cultures of P. aeruginosa. Compared with the endpoint PCR and traditional culture methods, the qPCR assay was more sensitive by one or two orders of magnitude. The feasibility of these methods was satisfactory in terms of sensitivity, specificity, and efficiency after evaluating 29 ready-to-eat vegetable samples and was almost consistent with that of the national standard detection method. The developed assays can be applied for rapid screening and detection of pathogenic P. aeruginosa, providing accurate results to inform effective monitoring measures in order to improve microbiological safety.
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Affiliation(s)
- Chufang Wang
- College of Food Science, South China Agricultural University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, China
| | - Qinghua Ye
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, China
| | - Aiming Jiang
- College of Food Science, South China Agricultural University, Guangzhou, China
| | - Jumei Zhang
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, China
| | - Yuting Shang
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, China
| | - Fan Li
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, China
| | - Baoqing Zhou
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, China
| | - Xinran Xiang
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, China
| | - Qihui Gu
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, China
| | - Rui Pang
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, China
| | - Yu Ding
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, China
| | - Shi Wu
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, China
| | - Moutong Chen
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, China
| | - Qingping Wu
- College of Food Science, South China Agricultural University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, China
| | - Juan Wang
- College of Food Science, South China Agricultural University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, China
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