Monitoring of Antimicrobial Resistance Based on Metagenomics Analyses in Pneumonia Patients

Monitoring of Antimicrobial Resistance Based on Metagenomics Analyses in Pneumonia Patients: a Genomic Epidemiology Study

Monitoring of antimicrobial resistance (AMR) based on metagenomics analyses in pneumonia patients is critical for optimizing clinical diagnosis and treatment and improving clinical prognosis. This study is designed to ask the following key questions:

1. What is the microbiome maps of patients with severe pneumonia and mild pneumonia ?
2. How many pathogen resistance genes are carrying in severe pneumonia and mild pneumonia ?
3. What is the genetic diversity of key pathogens detected in severe pneumonia and mild pneumonia during 2019-2025?

Study Overview

• Status: Recruiting
• Conditions: Pneumonia; Antimicrobial Resistance; Microbiome; Next-generation Sequencing

Detailed Description

This is a historical prospective obsevational study. Patients diagnosed with severe and mild pneumonia are recruited continously from four hospitals (Shanghai General Hospital, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuhan Union Hospital, and Huanggang Central Hospital) in China during March, 2019 to March, 2025.

Next-generation sequencing: Metagenomics and metatranscriptomic libraries undergo next-generation sequencing using the Illumina Novaseq 6000 platform.

Microbiome analysis: using KneadData (v0.10.0) reference from the human genome (GRCH38 reference database) to filter out the quality control of illumina sequencing data in Virosaurus download virus genome data sets for reference, bowtie2 (v2.3.4.1) (genome coverage >30%, depth >1X) was used to locate and analyze the post-host sequence, and then the "samtools idxstats" command was used to calculate the classification and relative abundance of viruses. Meanwhile, in order to obtain the annotation information of bacteria at the species level, PhyloFlash (v3.4) was used to calculate read counts for 16S rRNA genes in the SILVA database, selecting similarity greater than or equal to 98% as a threshold. Using eukaryotic pathogen genome database EUPATHDB46 as reference, bowtie2 and samtools were used for qualitative and quantitative analysis of fungal pathogens.

The criteria for determining the cause of respiratory infection are: (1) existing species known to be associated with human disease (ICD-10), (2) previously unidentified potential novel pathogens (only DNA and RNA viruses whose genera or families have previously been shown to infect mammals), and (3) possible symbiotic bacteria not included.

Analysis of AMR: by comparing the sequence similarity between the sequencing fragments and known drug resistance genes, the detection content can determine whether drug resistance genes exist, and suggest drug resistance caused by modification, inactivation, repression and other drug resistance genes.

Drug resistance genes detection: genes related to drug resistance recorded in CARD (Comprehensive Antibiotic Resistance Database) and ARG-ANNOT database. In this assay, only functional genes with drug resistance activities such as modification, inactivation, and repression, as well as pathway and target changes caused by some point mutations, were reported.

Genetic diversity was computed as the mean pairwise genetic distance within a group. Maximum likelihood phylogenetic trees were constructed using RaxML with a general time-reversible nucleotide substitution model and 1000 bootstraps. The genetic distance between sequences was calculated using MEGAX, with a bootstrap method for variance estimation.

• Study Type: Observational
• Enrollment (Estimated): 800

Contacts and Locations

• Study Contact: Name: Mei Kang, MPH; Phone Number: 18501709576; Email: mei.kang@shgh.cn
• Study Contact Backup: Name: Xue Tian, Master; Phone Number: 02163240090; Email: xue.tian@shgh.cn

Study Locations

• China
  • Shanghai Municipality
    • Shanghai, Shanghai Municipality, China, 200080
      • Recruiting
      • Mei Kang
      • Contact: Mei Kang, MPH; Phone Number: +8618501709576; Email: mei.kang@shgh.cn
      • Sub-Investigator: Ruilan Wang, PhD
      • Sub-Investigator: Lehao Ren, PhD
      • Sub-Investigator: Dapeng Wang, PhD
      • Principal Investigator: Shan Gao, Master
      • Sub-Investigator: Jiang Du, PhD
      • Sub-Investigator: Xue Tian, Master

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Pneumonia patients from four centers in China during 2022-2025.

Description

Inclusion Criteria:

• Patients clinically diagnosed as severe pneumonia and mild pneumonia are diagnosed according to the Guidelines for the diagnosis and Treatment of community-acquired pneumonia in Adults (2019 edition) formulated by the American Thoracic Society (ATS) and the Infectious Diseases Society of America (IDSA), who meet 1 of the following major criteria or ≥3 minor criteria can be diagnosed. The diagnostic criteria for severe and mild pneumonia in children were adopted by the British Thoracic Society (BTS) in 2011.
• Clinical examination was performed, and there was biospecimen (nasopharyngeal swab, oropharyngeal swab, bronchoalveolar lavage fluid, sputum, blood, hydrothorax, lung tissue) remaining in the clinical microbiological examination.

Exclusion Criteria:

• Patients whose biological samples may be contaminated;
• Patients with alveolar lavage fluid or hydrothorax volume less than 200μl.

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort
Severe pneumonia; Patients clinically diagnosed as severe pneumonia are diagnosed according to the Guidelines for the diagnosis and Treatment of community-acquired pneumonia in Adults (2019 edition) formulated by the American Thoracic Society (ATS) and the Infectious Diseases Society of America (IDSA), who meet 1 of the following major criteria or ≥3 minor criteria can be diagnosed. The diagnostic criteria for severe pneumonia in children were adopted by the British Thoracic Society (BTS) in 2011.
Mild pneumonia; Patients clinically diagnosed as severe pneumonia and mild pneumonia are diagnosed according to the Guidelines for the diagnosis and Treatment of community-acquired pneumonia in Adults (2019 edition) formulated by the American Thoracic Society (ATS) and the Infectious Diseases Society of America (IDSA). The diagnostic criteria for severe and mild pneumonia in children were adopted by the British Thoracic Society (BTS) in 2011

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Microbiome composition	a collection of microbial communities detected in the biospecimen	during the study period, 2019-2025

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Alpha diversity	the diversity within a particular area or ecosystem	during the study period, 2019-2025
Prevalence of bacterial resistance genes	the number of bacterial resistance genes divided by the number of biospecimen	during the study period, 2019-2025
Beta diversity	a comparison of of diversity between ecosystems, usually measured as the amount of species change between the ecosystems	during the study period, 2019-2025

Collaborators and Investigators

• Sponsor: Shanghai General Hospital, China
• Collaborators: Wuxi People's Hospital Affiliated to Nanjing Medical University; The Central Hospital of Huanggang; Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
• Investigators: Principal Investigator: Mei Kang, MPH, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine

Publications and helpful links

General Publications

• Metlay JP, Waterer GW, Long AC, Anzueto A, Brozek J, Crothers K, Cooley LA, Dean NC, Fine MJ, Flanders SA, Griffin MR, Metersky ML, Musher DM, Restrepo MI, Whitney CG. Diagnosis and Treatment of Adults with Community-acquired Pneumonia. An Official Clinical Practice Guideline of the American Thoracic Society and Infectious Diseases Society of America. Am J Respir Crit Care Med. 2019 Oct 1;200(7):e45-e67. doi: 10.1164/rccm.201908-1581ST.
• Chiu CY, Miller SA. Clinical metagenomics. Nat Rev Genet. 2019 Jun;20(6):341-355. doi: 10.1038/s41576-019-0113-7.
• Charalampous T, Alcolea-Medina A, Snell LB, Williams TGS, Batra R, Alder C, Telatin A, Camporota L, Meadows CIS, Wyncoll D, Barrett NA, Hemsley CJ, Bryan L, Newsholme W, Boyd SE, Green A, Mahadeva U, Patel A, Cliff PR, Page AJ, O'Grady J, Edgeworth JD. Evaluating the potential for respiratory metagenomics to improve treatment of secondary infection and detection of nosocomial transmission on expanded COVID-19 intensive care units. Genome Med. 2021 Nov 17;13(1):182. doi: 10.1186/s13073-021-00991-y.
• File TM Jr, Ramirez JA. Community-Acquired Pneumonia. N Engl J Med. 2023 Aug 17;389(7):632-641. doi: 10.1056/NEJMcp2303286. No abstract available.
• Limmathurotsakul D, Dunachie S, Fukuda K, Feasey NA, Okeke IN, Holmes AH, Moore CE, Dolecek C, van Doorn HR, Shetty N, Lopez AD, Peacock SJ; Surveillance and Epidemiology of Drug Resistant Infections Consortium (SEDRIC). Improving the estimation of the global burden of antimicrobial resistant infections. Lancet Infect Dis. 2019 Nov;19(11):e392-e398. doi: 10.1016/S1473-3099(19)30276-2. Epub 2019 Aug 16.
• Park DE, Higdon MM, Prosperi C, Baggett HC, Brooks WA, Feikin DR, Hammitt LL, Howie SRC, Kotloff KL, Levine OS, Madhi SA, Murdoch DR, O'Brien KL, Scott JAG, Thea DM, Antonio M, Awori JO, Baillie VL, Bunthi C, Kwenda G, Mackenzie GA, Moore DP, Morpeth SC, Mwananyanda L, Paveenkittiporn W, Ziaur Rahman M, Rahman M, Rhodes J, Sow SO, Tapia MD, Deloria Knoll M. Upper Respiratory Tract Co-detection of Human Endemic Coronaviruses and High-density Pneumococcus Associated With Increased Severity Among HIV-Uninfected Children Under 5 Years Old in the PERCH Study. Pediatr Infect Dis J. 2021 Jun 1;40(6):503-512. doi: 10.1097/INF.0000000000003139.
• Li N, Cai Q, Miao Q, Song Z, Fang Y, Hu B. High-Throughput Metagenomics for Identification of Pathogens in the Clinical Settings. Small Methods. 2021 Jan 4;5(1):2000792. doi: 10.1002/smtd.202000792. Epub 2020 Dec 13.
• Zhang YZ, Chen YM, Wang W, Qin XC, Holmes EC. Expanding the RNA Virosphere by Unbiased Metagenomics. Annu Rev Virol. 2019 Sep 29;6(1):119-139. doi: 10.1146/annurev-virology-092818-015851. Epub 2019 May 17.
• Boolchandani M, D'Souza AW, Dantas G. Sequencing-based methods and resources to study antimicrobial resistance. Nat Rev Genet. 2019 Jun;20(6):356-370. doi: 10.1038/s41576-019-0108-4.
• Suzuki S, Horinouchi T, Furusawa C. Prediction of antibiotic resistance by gene expression profiles. Nat Commun. 2014 Dec 17;5:5792. doi: 10.1038/ncomms6792.
• Howard A, Reza N, Aston S, Woods B, Gerada A, Buchan I, Hope W, Martson AG. Antimicrobial treatment imprecision: an outcome-based model to close the data-to-action loop. Lancet Infect Dis. 2024 Jan;24(1):e47-e58. doi: 10.1016/S1473-3099(23)00367-5. Epub 2023 Aug 31.
• Serpa PH, Deng X, Abdelghany M, Crawford E, Malcolm K, Caldera S, Fung M, McGeever A, Kalantar KL, Lyden A, Ghale R, Deiss T, Neff N, Miller SA, Doernberg SB, Chiu CY, DeRisi JL, Calfee CS, Langelier CR. Metagenomic prediction of antimicrobial resistance in critically ill patients with lower respiratory tract infections. Genome Med. 2022 Jul 12;14(1):74. doi: 10.1186/s13073-022-01072-4.
• Shi M, Zhao S, Yu B, Wu WC, Hu Y, Tian JH, Yin W, Ni F, Hu HL, Geng S, Tan L, Peng Y, Song ZG, Wang W, Chen YM, Holmes EC, Zhang YZ. Total infectome characterization of respiratory infections in pre-COVID-19 Wuhan, China. PLoS Pathog. 2022 Feb 17;18(2):e1010259. doi: 10.1371/journal.ppat.1010259. eCollection 2022 Feb.
• Harris M, Clark J, Coote N, Fletcher P, Harnden A, McKean M, Thomson A; British Thoracic Society Standards of Care Committee. British Thoracic Society guidelines for the management of community acquired pneumonia in children: update 2011. Thorax. 2011 Oct;66 Suppl 2:ii1-23. doi: 10.1136/thoraxjnl-2011-200598.
• Li ZJ, Zhang HY, Ren LL, Lu QB, Ren X, Zhang CH, Wang YF, Lin SH, Zhang XA, Li J, Zhao SW, Yi ZG, Chen X, Yang ZS, Meng L, Wang XH, Liu YL, Wang X, Cui AL, Lai SJ, Jiang T, Yuan Y, Shi LS, Liu MY, Zhu YL, Zhang AR, Zhang ZJ, Yang Y, Ward MP, Feng LZ, Jing HQ, Huang LY, Xu WB, Chen Y, Wu JG, Yuan ZH, Li MF, Wang Y, Wang LP, Fang LQ, Liu W, Hay SI, Gao GF, Yang WZ; Chinese Centers for Disease Control and Prevention (CDC) Etiology of Respiratory Infection Surveillance Study Team. Etiological and epidemiological features of acute respiratory infections in China. Nat Commun. 2021 Aug 18;12(1):5026. doi: 10.1038/s41467-021-25120-6.
• Alcock BP, Raphenya AR, Lau TTY, Tsang KK, Bouchard M, Edalatmand A, Huynh W, Nguyen AV, Cheng AA, Liu S, Min SY, Miroshnichenko A, Tran HK, Werfalli RE, Nasir JA, Oloni M, Speicher DJ, Florescu A, Singh B, Faltyn M, Hernandez-Koutoucheva A, Sharma AN, Bordeleau E, Pawlowski AC, Zubyk HL, Dooley D, Griffiths E, Maguire F, Winsor GL, Beiko RG, Brinkman FSL, Hsiao WWL, Domselaar GV, McArthur AG. CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database. Nucleic Acids Res. 2020 Jan 8;48(D1):D517-D525. doi: 10.1093/nar/gkz935.
• Antimicrobial Resistance Collaborators. Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. Lancet. 2022 Feb 12;399(10325):629-655. doi: 10.1016/S0140-6736(21)02724-0. Epub 2022 Jan 19.
• GBD 2019 Diseases and Injuries Collaborators. Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2020 Oct 17;396(10258):1204-1222. doi: 10.1016/S0140-6736(20)30925-9.
• Wu F, Zhao S, Yu B, Chen YM, Wang W, Song ZG, Hu Y, Tao ZW, Tian JH, Pei YY, Yuan ML, Zhang YL, Dai FH, Liu Y, Wang QM, Zheng JJ, Xu L, Holmes EC, Zhang YZ. A new coronavirus associated with human respiratory disease in China. Nature. 2020 Mar;579(7798):265-269. doi: 10.1038/s41586-020-2008-3. Epub 2020 Feb 3.

Study record dates

Study Major Dates

• Study Start (Actual): August 1, 2024
• Primary Completion (Actual): April 15, 2026
• Study Completion (Estimated): September 30, 2026

Study Registration Dates

• First Submitted: August 18, 2024
• First Submitted That Met QC Criteria: August 20, 2024
• First Posted (Actual): August 22, 2024

Study Record Updates

• Last Update Posted (Actual): April 23, 2026
• Last Update Submitted That Met QC Criteria: April 21, 2026
• Last Verified: April 1, 2026

More Information

Terms related to this study

• Keywords: Microbiome; Pneumonia; Next-generation sequencing; Antimicrobial Resistance
• Additional Relevant MeSH Terms: Respiratory Tract Infections; Infections; Respiratory Tract Diseases; Lung Diseases; Pneumonia
• Other Study ID Numbers: 2023234

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED
• IPD Plan Description: The datasets used in this study are available upon request to the principle investigator.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No