Characterization of oral and gut microbiome temporal variability in hospitalized cancer patients

From BugSigDB
Reviewed Marked as Reviewed by Claregrieve1 on 2022/11/5
Citation
PMID PubMed identifier for scientific articles.
DOI Digital object identifier for electronic documents.
URI
Authors
Galloway-Peña JR, Smith DP, Sahasrabhojane P, Wadsworth WD, Fellman BM, Ajami NJ, Shpall EJ, Daver N, Guindani M, Petrosino JF, Kontoyiannis DP, Shelburne SA
Journal
Genome medicine
Year
2017
Keywords:
Antibiotics, Chemotherapy, Leukemia, Microbiome, Temporal variability
BACKGROUND: Understanding longitudinal variability of the microbiome in ill patients is critical to moving microbiome-based measurements and therapeutics into clinical practice. However, the vast majority of data regarding microbiome stability are derived from healthy subjects. Herein, we sought to determine intra-patient temporal microbiota variability, the factors driving such variability, and its clinical impact in an extensive longitudinal cohort of hospitalized cancer patients during chemotherapy. METHODS: The stool (n = 365) and oral (n = 483) samples of 59 patients with acute myeloid leukemia (AML) undergoing induction chemotherapy (IC) were sampled from initiation of chemotherapy until neutrophil recovery. Microbiome characterization was performed via analysis of 16S rRNA gene sequencing. Temporal variability was determined using coefficients of variation (CV) of the Shannon diversity index (SDI) and unweighted and weighted UniFrac distances per patient, per site. Measurements of intra-patient temporal variability and patient stability categories were analyzed for their correlations with genera abundances. Groups of patients were analyzed to determine if patients with adverse outcomes had significantly different levels of microbiome temporal variability. Potential clinical drivers of microbiome temporal instability were determined using multivariable regression analyses. RESULTS: Our cohort evidenced a high degree of intra-patient temporal instability of stool and oral microbial diversity based on SDI CV. We identified statistically significant differences in the relative abundance of multiple taxa amongst individuals with different levels of microbiota temporal stability. Increased intra-patient temporal variability of the oral SDI was correlated with increased risk of infection during IC (P = 0.02), and higher stool SDI CVs were correlated with increased risk of infection 90 days post-IC (P = 0.04). Total days on antibiotics was significantly associated with increased temporal variability of both oral microbial diversity (P = 0.03) and community structure (P = 0.002). CONCLUSIONS: These data quantify the longitudinal variability of the oral and gut microbiota in AML patients, show that increased variability was correlated with adverse clinical outcomes, and offer the possibility of using stabilizing taxa as a method of focused microbiome repletion. Furthermore, these results support the importance of longitudinal microbiome sampling and analyses, rather than one time measurements, in research and future clinical practice.

Experiment 2


Reviewed Marked as Reviewed by Claregrieve1 on 2022/11/5

Curated date: 2021/01/10

Curator: WikiWorks

Revision editor(s): Claregrieve1, WikiWorks, Victoria

Differences from previous experiment shown

Subjects

Location of subjects
United States of America
Host species Species from which microbiome was sampled. Contact us to have more species added.
Homo sapiens
Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology
Buccal mucosa Buccal mucosa,buccal mucosa
Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology
Acute myeloid leukemia acute granulocytic leukemia,acute myeloblastic leukemia,acute myelocytic leukemia,acute myelogenous leukemia,acute myelogenous leukemias,acute myeloid leukemia,acute myeloid leukemia (AML),acute non lymphoblastic leukemia,acute Nonlymphocytic leukemia,acute nonlymphocytic leukemia,AML,AML - acute myeloid leukemia,ANLL,hematopoeitic - acute Myleogenous leukemia (AML),leukemia, acute myelogenous,leukemia, acute myeloid,leukemia, acute myeloid, susceptibility to,leukemia, myelocytic, acute,myeloid leukemia, acute,Acute myeloid leukemia
Group 0 name Corresponds to the control (unexposed) group for case-control studies
no infection
Group 1 name Corresponds to the case (exposed) group for case-control studies
infection
Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
acute myeloid leukemia patients that were microbiologically documented with infection during induction chemotherapy before neutrophil recovery
Group 0 sample size Number of subjects in the control (unexposed) group
30
Group 1 sample size Number of subjects in the case (exposed) group
15

Lab analysis

Sequencing type
16S
16S variable region One or more hypervariable region(s) of the bacterial 16S gene
V4
Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance
Illumina

Statistical Analysis

Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).
relative abundances
Statistical test
Mann-Whitney (Wilcoxon)
Significance threshold p-value or FDR threshold used for differential abundance testing (if any)
0.05
MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?
Yes

Alpha Diversity

Shannon Estimator of species richness and species evenness: more weight on species richness
increased

Signature 1

Reviewed Marked as Reviewed by Claregrieve1 on 2022/11/5

Curated date: 2021/01/10

Curator: William Lam

Revision editor(s): Claregrieve1, WikiWorks

Source: Figure 5e

Description: Differential microbial abundance between patients who experienced infection and patients who did not

Abundance in Group 1: increased abundance in infection

NCBI Quality ControlLinks
Stenotrophomonas

Revision editor(s): Claregrieve1, WikiWorks

Signature 2

Reviewed Marked as Reviewed by Claregrieve1 on 2022/11/5

Curated date: 2022/07/28

Curator: Claregrieve1

Revision editor(s): Claregrieve1

Source: Figure 5e

Description: Differential microbial abundance between patients who experienced infection and patients who did not

Abundance in Group 1: decreased abundance in infection

NCBI Quality ControlLinks
Streptococcus

Revision editor(s): Claregrieve1

Experiment 3


Reviewed Marked as Reviewed by Claregrieve1 on 2022/11/5

Curated date: 2021/01/10

Curator: WikiWorks

Revision editor(s): Claregrieve1, WikiWorks, Victoria

Differences from previous experiment shown

Subjects

Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology
Feces Cow dung,Cow pat,Droppings,Dung,Excrement,Excreta,Faeces,Fecal material,Fecal matter,Fewmet,Frass,Guano,Matières fécales@fr,Merde@fr,Ordure,Partie de la merde@fr,Piece of shit,Porción de mierda@es,Portion of dung,Portion of excrement,Portion of faeces,Portion of fecal material,Portion of fecal matter,Portion of feces,Portion of guano,Portion of scat,Portionem cacas,Scat,Spoor,Spraint,Stool,Teil der fäkalien@de,Feces,feces


Lab analysis

Statistical Analysis

Alpha Diversity

Shannon Estimator of species richness and species evenness: more weight on species richness
unchanged

Signature 1

Reviewed Marked as Reviewed by Claregrieve1 on 2022/11/5

Curated date: 2021/01/10

Curator: William Lam

Revision editor(s): Claregrieve1, WikiWorks

Source: Figure 5e

Description: Differential microbial abundance in stool samples between patients with infection and patients with no infection

Abundance in Group 1: increased abundance in infection

NCBI Quality ControlLinks
Stenotrophomonas

Revision editor(s): Claregrieve1, WikiWorks