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PRJNA546227 SRP200375

Gut/respiratory microbiome in LTACH patients, Philadelphia

Metagenomic Study of Gastrointestinal Tract Microbial Community Change During Long-Term Acute Care

335 samples from long-term acute care hospital residents in Philadelphia, PA, profiling gastrointestinal and respiratory microbiome and resistome changes under antibiotic pressure in a longitudinal design. machine-written summary

335 samples · 335 runs · US · Age unknown · 2019 · 2.01 Gbp / sample

One study deposited as 2 BioProjects (902 catalog samples together): PRJNA545794 · PRJNA546227 · show together

Sources
✓Sequence archive 2,345✓Abstract / description 670–Full text–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 archive2,345 sample values (collection date, country, latitude, location locality, location region, longitude, subject id)
✓ Abstract / description670 sample values (lifestyle, lifestyle detail)
– Full textno open-access full text linked
– Supplementary tablesno supplementary tables available (or none open access)
– External resourcesnot covered by the external resources we ingest
– User contributionnothing uploaded yet · share metadata
– Human verifiednot yet checked by a person · I checked this project — verify it
Interventions

intervention — arms not resolved

design observational_with_procedure

Samples at a glance
1 sampling locations · 1 country
Age
unknown335
Country
US335
Body site
primary335
Collected 2017–2018
2017: 291 samples2018: 44 samples20172018
Sequencing depth per sample · this project all projects
all projects, 0–0.03 Gbp: 25,080 samples (4 %)this project, 0–0.03 Gbp: 4 samplesall projects, 0.03–0.1 Gbp: 17,066 samples (3 %)this project, 0.03–0.1 Gbp: 2 samplesall projects, 0.1–0.3 Gbp: 29,179 samples (5 %)this project, 0.1–0.3 Gbp: 7 samplesall projects, 0.3–1 Gbp: 47,044 samples (8 %)this project, 0.3–1 Gbp: 8 samplesall projects, 1–3 Gbp: 124,983 samples (22 %)this project, 1–3 Gbp: 309 samplesall projects, 3–10 Gbp: 253,728 samples (44 %)this project, 3–10 Gbp: 5 samplesall projects, 10–30 Gbp: 72,533 samples (13 %)all 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 2.01 Gbp per sample0130Gbp
Sampling design and relatedness

longitudinal

34 of 42 people sampled more than once (327 samples; median 6, up to 65 per person) · follow-up median 32 d (max 12 mo) · median interval between samples 4 d (time from collection dates). Schedule stated by the source: “Repeated stool swab sampling per subject over time during LTACH stay; median 5, max 65 samples per subject across 42 subjects.”.

MIRA_001MIRA_001: day 0MIRA_001: day 5MIRA_003MIRA_003: day 0MIRA_003: day 4MIRA_003: day 26MIRA_003: day 32MIRA_003: day 34MIRA_003: day 38MIRA_003: day 48MIRA_003: day 61MIRA_003: day 63MIRA_003: day 68MIRA_003: day 70MIRA_003: day 76MIRA_003: day 88MIRA_003: day 89MIRA_003: day 90MIRA_003: day 95MIRA_003: day 97MIRA_003: day 108MIRA_003: day 110MIRA_003: day 118MIRA_003: day 122MIRA_003: day 124MIRA_003: day 138MIRA_003: day 146MIRA_003: day 147MIRA_003: day 154MIRA_003: day 159MIRA_003: day 171MIRA_003: day 175MIRA_003: day 192MIRA_003: day 194MIRA_003: day 200MIRA_003: day 213MIRA_003: day 229MIRA_003: day 230MIRA_003: day 236MIRA_003: day 241MIRA_003: day 242MIRA_003: day 244MIRA_003: day 255MIRA_003: day 259MIRA_003: day 263MIRA_003: day 270MIRA_003: day 272MIRA_003: day 276MIRA_003: day 277MIRA_003: day 278MIRA_003: day 285MIRA_003: day 286MIRA_003: day 290MIRA_003: day 293MIRA_003: day 297MIRA_003: day 299MIRA_003: day 301MIRA_003: day 325MIRA_003: day 328MIRA_003: day 333MIRA_003: day 334MIRA_003: day 335MIRA_003: day 336MIRA_003: day 340MIRA_003: day 343MIRA_003: day 353MIRA_003: day 354MIRA_003: day 357MIRA_005MIRA_005: day 0MIRA_005: day 6MIRA_005: day 27MIRA_005: day 28MIRA_005: day 36MIRA_005: day 40MIRA_005: day 41MIRA_005: day 48MIRA_005: day 50MIRA_005: day 54MIRA_005: day 55MIRA_005: day 57MIRA_005: day 58MIRA_006MIRA_006: day 0MIRA_006: day 17MIRA_006: day 30MIRA_006: day 38MIRA_006: day 41MIRA_006: day 42MIRA_007MIRA_007: day 0MIRA_007: day 7MIRA_007: day 12MIRA_007: day 13MIRA_007: day 27MIRA_007: day 43MIRA_007: day 48MIRA_007: day 49MIRA_007: day 50MIRA_007: day 51MIRA_007: day 205MIRA_007: day 209MIRA_007: day 259MIRA_007: day 260MIRA_007: day 261MIRA_007: day 264MIRA_007: day 271MIRA_007: day 278MIRA_007: day 279MIRA_007: day 282MIRA_010MIRA_010: day 0MIRA_010: day 2MIRA_010: day 6MIRA_010: day 12MIRA_010: day 14MIRA_010: day 16MIRA_010: day 22MIRA_010: day 26MIRA_010: day 40MIRA_010: day 48MIRA_010: day 51MIRA_010: day 54MIRA_010: day 58MIRA_013MIRA_013: day 0MIRA_013: day 6MIRA_013: day 7MIRA_013: day 11MIRA_013: day 14MIRA_013: day 18MIRA_013: day 19MIRA_013: day 20MIRA_013: day 21MIRA_013: day 25MIRA_013: day 26MIRA_013: day 27MIRA_013: day 28MIRA_013: day 31MIRA_013: day 38MIRA_013: day 40MIRA_013: day 41MIRA_013: day 45MIRA_013: day 59MIRA_015MIRA_015: day 0MIRA_015: day 1MIRA_015: day 2MIRA_015: day 4MIRA_015: day 10MIRA_015: day 53MIRA_016MIRA_016: day 0MIRA_016: day 3MIRA_016: day 12MIRA_016: day 14MIRA_016: day 17MIRA_016: day 19MIRA_016: day 20MIRA_016: day 24MIRA_016: day 27MIRA_016: day 39MIRA_016: day 41MIRA_016: day 42MIRA_016: day 54MIRA_016: day 56MIRA_016: day 60MIRA_016: day 63MIRA_022MIRA_022: day 0MIRA_022: day 2MIRA_022: day 4MIRA_022: day 9MIRA_022: day 15MIRA_022: day 17MIRA_022: day 39MIRA_022: day 49MIRA_022: day 50MIRA_022: day 51MIRA_022: day 58MIRA_022: day 71MIRA_022: day 78MIRA_022: day 79MIRA_022: day 81MIRA_022: day 84MIRA_022: day 88MIRA_022: day 108MIRA_023MIRA_023: day 0MIRA_023: day 6MIRA_023: day 9MIRA_023: day 31MIRA_024MIRA_024: day 0MIRA_024: day 2MIRA_024: day 6MIRA_024: day 9MIRA_024: day 14MIRA_024: day 15MIRA_024: day 36MIRA_024: day 41MIRA_024: day 42MIRA_024: day 43MIRA_024: day 44MIRA_024: day 50MIRA_024: day 69MIRA_024: day 70MIRA_024: day 86MIRA_026MIRA_026: day 0MIRA_026: day 1MIRA_026: day 11MIRA_026: day 12MIRA_026: day 18MIRA_028MIRA_028: day 0MIRA_028: day 15MIRA_028: day 18MIRA_028: day 20MIRA_028: day 21MIRA_030MIRA_030: day 0MIRA_030: day 1MIRA_030: day 3MIRA_030: day 8MIRA_030: day 10MIRA_030: day 20MIRA_030: day 27MIRA_031MIRA_031: day 0MIRA_031: day 1MIRA_031: day 2MIRA_031: day 5MIRA_031: day 7MIRA_033MIRA_033: day 0MIRA_033: day 3MIRA_033: day 9MIRA_050MIRA_050: day 0MIRA_050: day 13MIRA_050: day 14MIRA_052MIRA_052: day 0MIRA_052: day 11MIRA_053MIRA_053: day 0MIRA_053: day 12MIRA_053: day 17MIRA_054MIRA_054: day 0MIRA_054: day 12MIRA_054: day 28MIRA_054: day 35MIRA_054: day 40MIRA_054: day 42MIRA_057MIRA_057: day 0MIRA_057: day 8MIRA_057: day 16MIRA_057: day 20MIRA_060MIRA_060: day 0MIRA_060: day 1MIRA_060: day 4MIRA_060: day 6MIRA_060: day 8MIRA_060: day 14MIRA_060: day 15MIRA_060: day 25MIRA_060: day 26MIRA_060: day 27MIRA_060: day 28MIRA_060: day 32MIRA_063MIRA_063: day 0MIRA_063: day 2MIRA_063: day 10MIRA_063: day 14MIRA_063: day 18MIRA_063: day 21MIRA_063: day 22MIRA_063: day 28MIRA_063: day 29MIRA_063: day 32MIRA_064MIRA_064: day 0MIRA_064: day 1MIRA_064: day 4MIRA_064: day 14MIRA_065MIRA_065: day 0MIRA_065: day 17MIRA_065: day 25MIRA_065: day 32MIRA_065: day 41MIRA_065: day 48MIRA_065: day 55MIRA_065: day 59MIRA_065: day 80MIRA_068MIRA_068: day 0MIRA_068: day 2MIRA_068: day 6MIRA_068: day 21MIRA_068: day 26MIRA_068: day 28MIRA_068: day 29MIRA_068: day 33MIRA_070MIRA_070: day 0MIRA_070: day 23MIRA_070: day 27MIRA_070: day 30MIRA_072MIRA_072: day 0MIRA_072: day 1MIRA_072: day 8MIRA_072: day 21MIRA_072: day 22MIRA_072: day 24MIRA_072: day 42MIRA_072: day 51MIRA_072: day 52MIRA_072: day 56MIRA_072: day 57MIRA_072: day 63MIRA_072: day 66MIRA_072: day 67MIRA_072: day 72MIRA_072: day 74MIRA_076MIRA_076: day 0MIRA_076: day 1MIRA_076: day 2MIRA_076: day 3MIRA_076: day 24MIRA_076: day 30MIRA_076: day 31MIRA_076: day 36MIRA_080MIRA_080: day 0MIRA_080: day 2MIRA_080: day 6MIRA_080: day 7MIRA_080: day 8MIRA_080: day 9MIRA_080: day 12MIRA_080: day 13MIRA_080: day 30MIRA_081MIRA_081: day 0MIRA_081: day 5MIRA_081: day 7MIRA_083MIRA_083: day 0MIRA_083: day 5MIRA_089MIRA_089: day 0MIRA_089: day 20 d3 mo6 mo9 mo12 mo

Each row is one person (34 shown); dots are samples at days since that person's first sample.

How longitudinal and relatedness information is derived

Community composition
Bacteroides 20.0%Pseudomonas 6.8%Klebsiella 6.1%Alistipes 5.3%Parabacteroides 4.5%Phocaeicola 3.6%Enterococcus 2.9%Enterocloster 2.8%Enterococcus_B 2.6%Ruthenibacterium 2.3%Akkermansia 2.2%Escherichia 1.7%not assigned to a genus 6.2%other genera 33.0%

Genera, mean relative abundance over 301 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%
country335 100%335
health_condition0 0%
subject_id335 100%335
collection_date335 100%335
detailed_location335 100%
latitude335 100%335
lifestyle335 100%335
lifestyle_detail335 100%335
location_locality335 100%335
location_region335 100%335
longitude335 100%335
Details
Archive description

We applied metagenomic sequencing to respiratory and gastrointestinal tract specimens, collected from a cohort of long-term acute care hospital (LTACH) residents, in order to define microbiome and resistome change under antibiotic pressure, generate microbiome disruption indices (MDIs) to predict risk for multidrug-resistant infection, and contribute to a deeper understanding of how antibiotics and other medications increase risk of specific AMR gene selection and persistence.

How this project entered the registry

Classified as human gut / stool / lower respiratory shotgun DNA metagenome of age unknown by opus_adjudicated with confidence 0.60. Assay shotgun_dna.

  • host run.host_tax_id · “9606”
  • host study.description · “long-term acute care hospital (LTACH) residents”
  • body site study.description · “respiratory and gastrointestinal tract specimens”
Evidence examples (one per field × route)
samplefieldvaluerouteconf.sourcequote
SAMN11954206collection_date2017-07-07R10.90biosample.attribute:collection_date2017-07-07T00:00:00Z
SAMN11954206countryUSR10.90sample.attr.geo_loc_nameUSA: Philadelphia, PA
SAMN11954206latitude39.5700R10.90biosample.attribute:lat_lon39.57 N 75.11 W
SAMN11954206lifestyleinstitutionalizedR40.45ena.study_descriptionlong-term acute care hospital (LTACH) residents
SAMN11954206lifestyle_detaillong-term acute care hospital (LTACH) residentsR40.45ena.study_descriptionlong-term acute care hospital (LTACH) residents
SAMN11954206location_localityPhiladelphiaR10.85biosample.attribute:geo_loc_nameUSA: Philadelphia, PA
SAMN11954206location_regionPennsylvaniaR10.75biosample.attribute:geo_loc_nameUSA: Philadelphia, PA
SAMN11954206longitude-75.1100R10.90biosample.attribute:lat_lon39.57 N 75.11 W
SAMN11954206subject_idMIRA_030R10.85sample.attr.subject_idMIRA_030
Sequencing

335 runs over 335 samples · mean 1.97 Gbp per run (median 2.01 Gbp, total 659.39 Gbp; 335 runs with a base count) · layout PAIRED 335 · platform ILLUMINA 335 · models Illumina HiSeq 2500 (335) · 90% of runs with a Sandpiper profile · first public 2019-06-05

Authors (0)

No author record.

Help complete this project

2 of the 4 core fields are below 50% coverage: age_category, health_condition. Share metadata

Downloads

PRJNA546227.csv.gz (10.0 KB) · parquet (83.4 KB) — all 335 samples, every field with route and confidence · PRJNA546227_determinations.csv.gz (19.2 KB) — 3,015 evidence rows

Samples (335 · every field this project has values for · hover a cell for its source)
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