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PRJNA950577 SRP432077

Gut and respiratory resistome in COVID-19 patients, China

Dynamic associations between the respiratory tract and gut antibiotic resistome of patients with COVID-19 and its prediction power for disease severity

218 sputum and fecal samples from 66 COVID-19 patients in Zhejiang, China, sampled across admission, progression, and recovery stages in a cross-sectional metagenomic study comparing ICU and non-ICU antibiotic resistomes. machine-written summary

218 samples · 218 runs · CN · Age unknown · 2024 · 9.95 Gbp / sample

Sources
✓Sequence archive 1,308✓Abstract / description 436✓Full text 218○Supplementary tables–External resources–User contribution–Human verified

Checked this project's papers and archive records yourself? Mark it human-verified.

what each source gave
✓ Sequence archive1,308 sample values (collection date, country, latitude, location region, longitude, subject id)
✓ Abstract / description436 sample values (health condition, health condition detail)
✓ Full text218 sample values (location site) · PMC10262814
○ Supplementary tablesfiles read; no table could be matched to the samples
– External resourcesnot covered by the external resources we ingest
– User contributionnothing uploaded yet
– Human verifiednot yet checked by a person · I checked this project — verify it
Samples at a glance
3 sampling locations · 1 country
Age
unknown218
Condition
other_infection218
Country
CN218
Body site
excluded131
primary87
Sequencing depth per sample · this project all projects
all projects, 0–0.03 Gbp: 25,080 samples (4 %)all projects, 0.03–0.1 Gbp: 17,066 samples (3 %)all projects, 0.1–0.3 Gbp: 29,179 samples (5 %)all projects, 0.3–1 Gbp: 47,044 samples (8 %)all projects, 1–3 Gbp: 124,983 samples (22 %)this project, 1–3 Gbp: 1 samplesall projects, 3–10 Gbp: 253,728 samples (44 %)this project, 3–10 Gbp: 109 samplesall projects, 10–30 Gbp: 72,533 samples (13 %)this project, 10–30 Gbp: 108 samplesall projects, 30–100 Gbp: 3,024 samples (1 %)all projects, 100–300 Gbp: 106 samples (0 %)all projects, ≥ 300 Gbp: 9 samples (0 %)project median 9.95 Gbp per sample0130Gbp
Sampling design and relatedness

longitudinal — not resolved

25 of 60 people sampled more than once (52 samples; median 2, up to 3 per person). Schedule stated by the source: “sputum and fecal samples collected at three disease stages: admission, progression, and recovery” (time origin: admission).

How longitudinal and relatedness information is derived

Community composition
Bacteroides 15.9%Phocaeicola 11.8%Prevotella 5.6%Streptococcus 4.2%Escherichia 3.9%Megamonas 3.2%Enterococcus_B 2.7%Faecalibacterium 2.6%Enterocloster 2.6%Mediterraneibacter 2.5%Parabacteroides 2.4%Alistipes 2.3%not assigned to a genus 3.6%other genera 36.7%

Genera, mean relative abundance over 81 profiled gut samples of this project (Sandpiper SingleM profiles, GTDB R232; low-depth and non-metagenome profiles left out).

Field coverage
fieldsamplescoverageR1R2R3R4
age_category0 0%
country218 100%218
health_condition218 100%218
subject_id218 100%218
collection_date218 100%218
detailed_location218 100%
health_condition_detail218 100%218
latitude218 100%218
location_region218 100%218
location_site218 100%218
longitude218 100%218
Papers (1)
  • Dynamic associations between the respiratory tract and gut antibiotic resistome of patients with COVID-19 and its prediction power for disease severity. 2023 PMID 37306468 PMC10262814 own_data
Details
Archive description

The antibiotic resistome is the collection of all the ARGs present in an individual. Whether an individual susceptibility to infection and the eventual severity of COVID-19 is influenced by their respiratory tract antibiotic resistome is unknown. Additional, whether a relationship exists between the respiratory tract and gut ARGs composition has not been fully explored. We recruited 66 patients with COVID-19 at three disease stages and conducted a metagenome sequencing analysis of 143 sputum and 97 fecal samples obtained from them. Respiratory tract, gut metagenomes, and PBMC transcriptomes are analyzed to compare the gut and respiratory tract ARGs of ICU and non-ICU patients and determine relationships between ARGs and immune response. Among the respiratory tract ARGs, we found that Aminoglycoside, Multidrug and Vancomycin are increased in ICU patients compared with nICU patients. In the gut, we found that Multidrug, Vancomycin and Fosmidomycin were increased in ICU patients. We discovered that the relative abundances of Multidrug were significantly correlated with clinical indices, and there was a significantly positive correlation between ARGs and microbiota in respiratory tract and gut. We found that immune related pathways in PBMC were enhanced, and they were correlated with Multidrug, Vancomycin and Tetracycline ARGs. Based on the ARG types, we built a respiratory tract-gut ARG combined random-forest classifier to distinguish ICU COVID-19 patients from nICU patients with an AUC of 0.969. Cumulatively, our findings provide some of the first insights into the dynamic alterations of respiratory tract and gut antibiotic resistome in the progression of COVID-19 and disease severity. They also provide a better understanding of how this disease affects different cohorts of patients. As such, these findings should contribute to better diagnosis and treatment scenarios.

How this project entered the registry

Classified as human lower respiratory / gut / stool shotgun DNA metagenome of age unknown by opus_adjudicated with confidence 0.75. Assay shotgun_dna.

  • host study.description · “We recruited 66 patients with COVID-19”
  • host run.host_tax_id · “9606”
  • body site study.description · “143 sputum and 97 fecal samples”
Evidence examples (one per field × route)
samplefieldvaluerouteconf.sourcequote
SAMN34003453collection_date2021R10.90biosample.attribute:collection_date2021
SAMN34003453countryCNR10.90sample.attr.geo_loc_nameChina:Zhejiang
SAMN34003453health_conditionother_infectionR40.50paper.abstract66 patients with COVID-19
SAMN34003453health_condition_detailAll subjects are COVID-19 patientsR40.50paper.abstract66 patients with COVID-19
SAMN34003453latitude30.1500R10.90biosample.attribute:lat_lon30.15 N 120.10 E
SAMN34003453location_regionZhejiangR10.85biosample.attribute:geo_loc_nameChina:Zhejiang
SAMN34003453location_siteFirst Affiliated Hospital of Zhejiang UniversityR30.70paper.fulltext.methodsFirst Affiliated Hospital of Zhejiang University were enrolled in this study
SAMN34003453longitude120.1000R10.90biosample.attribute:lat_lon30.15 N 120.10 E
SAMN34003453subject_id15R10.70sample.name_rule:sample_title15-1
SAMN34003496subject_id12R10.70sample.name_rule:alias12-C
Sequencing

218 runs over 218 samples · mean 9.73 Gbp per run (median 9.95 Gbp, total 2,121.24 Gbp; 218 runs with a base count) · layout PAIRED 218 · platform ILLUMINA 218 · models Illumina HiSeq 2500 (218) · 92% of runs with a Sandpiper profile · first public 2024-01-28

Authors (26)

Shen Y first · Qu W · Yu F · Zhang D · Zou Q · Han D · Xie M · Chen X · Yuan L · Lou B · Xie G · Wang R · Yang X · Chen W · Wang Q · Teng Y · Dong Y · Huang L · Bao J · Liu C · Wu W · Shen E · Fan L · Timko MP · Zheng S · Chen Y last

Downloads

PRJNA950577.csv.gz (6.6 KB) · parquet (79.7 KB) — all 218 samples, every field with route and confidence · PRJNA950577_determinations.csv.gz (15.3 KB) — 1,962 evidence rows

Samples (218 · every field this project has values for · hover a cell for its source)
Loading the sample table…