Distinct microbiota profiles in non-survivors in preterm infants with surgical necrotizing enterocolitis: Insights from FFPE intestinal tissue analysis

BackgroundThe variant microbiome is associated with necrotizing enterocolitis (NEC). We aimed to analyze remnant formalin fixed paraffin-embedded (FFPE) intestine tissue for microbiome profiling in preterm infants with surgical NEC.MethodsWe analyzed FFPE small intestine tissues from 16 infants with NEC (8 survivors and 8 non-survivors). Extracted DNA from FFPE tissue blocks underwent 16S rRNA sequencing. We compared the microbiota profiles in survivors and non-survivors. Alpha- and beta diversity metrics were calculated using QIIME2. To assess differences in overall microbial community structure, we performed a Permutational Multivariate Analysis of Variance (PERMANOVA). The analysis was performed in MaAsLin2 R package to determine the specific microbial taxa whose relative abundances were significantly associated with survival status in a multivariable linear model.ResultsSequencing of FFPE extracted DNA resulted in high-quality sequence reads in 16 cases.AnalysisAnalysis of microbial communities from 16 cases revealed a significant association between microbiome structure and survival status. Beta diversity analysis demonstrated distinct clustering of microbiome profiles between survivor and non-survivor groups. Alpha diversity metrics further characterized these differences: the non-survivor group exhibited a more complex and even microbiota (Shannon entropy, <i>p</i> = 0.02; Pielou's evenness, <i>p</i> = 0.017), whereas the survivor group's microbiome was significantly richer in observed features (<i>p</i> = 0.004). Notably, this association was specific to survival outcome, as overall community structure did not significantly differ when grouped by histological features of disease severity such as necrosis, inflammation, or hemorrhage. Linear mixed effect models and direct comparisons further identified numerous taxa potentially associated with survival status.ConclusionFFPE intestinal tissue enabled retrospective and spatially relevant microbiota assessment at the disease site. The non-survivors had complex microbiota and had distinct bacterial communities compared to survivors. Our findings suggest that the gut microbiome is a key factor related to prognosis, independent of other measures of NEC severity.

Authors

Institutions

Publication Details

Journal
Journal of Neonatal-Perinatal Medicine
Published
2025-06-24
DOI
https://doi.org/10.1177/19345798251353777
Citations
1
Primary Topic
Infant Nutrition and Health
Type
article
Field-Weighted Citation Impact
1.12

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Distinct microbiota profiles in non-survivors in preterm infants with surgical necrotizing enterocolitis: Insights from FFPE intestinal tissue analysis

Kylie Kavanagh, Padma P. Garg, Drew J. Schwartz, Neha Varshney et al.
1 citations
Journal of Neonatal-Perinatal Medicine
Infant Nutrition and Health
1.12
article

Distinct microbiota profiles in non-survivors in preterm infants with surgical necrotizing enterocolitis: Insights from FFPE intestinal tissue analysis

Kylie Kavanagh, Padma P. Garg, Drew J. Schwartz, Neha Varshney, Avinash K. Shetty, David Sawaya, Liang Liu, Wei Zhang, Pengbo Zhang, Greg Hawkins, Tim Howard
article en
1 citations

Abstract

BackgroundThe variant microbiome is associated with necrotizing enterocolitis (NEC). We aimed to analyze remnant formalin fixed paraffin-embedded (FFPE) intestine tissue for microbiome profiling in preterm infants with surgical NEC.MethodsWe analyzed FFPE small intestine tissues from 16 infants with NEC (8 survivors and 8 non-survivors). Extracted DNA from FFPE tissue blocks underwent 16S rRNA sequencing. We compared the microbiota profiles in survivors and non-survivors. Alpha- and beta diversity metrics were calculated using QIIME2. To assess differences in overall microbial community structure, we performed a Permutational Multivariate Analysis of Variance (PERMANOVA). The analysis was performed in MaAsLin2 R package to determine the specific microbial taxa whose relative abundances were significantly associated with survival status in a multivariable linear model.ResultsSequencing of FFPE extracted DNA resulted in high-quality sequence reads in 16 cases.AnalysisAnalysis of microbial communities from 16 cases revealed a significant association between microbiome structure and survival status. Beta diversity analysis demonstrated distinct clustering of microbiome profiles between survivor and non-survivor groups. Alpha diversity metrics further characterized these differences: the non-survivor group exhibited a more complex and even microbiota (Shannon entropy, <i>p</i> = 0.02; Pielou's evenness, <i>p</i> = 0.017), whereas the survivor group's microbiome was significantly richer in observed features (<i>p</i> = 0.004). Notably, this association was specific to survival outcome, as overall community structure did not significantly differ when grouped by histological features of disease severity such as necrosis, inflammation, or hemorrhage. Linear mixed effect models and direct comparisons further identified numerous taxa potentially associated with survival status.ConclusionFFPE intestinal tissue enabled retrospective and spatially relevant microbiota assessment at the disease site. The non-survivors had complex microbiota and had distinct bacterial communities compared to survivors. Our findings suggest that the gut microbiome is a key factor related to prognosis, independent of other measures of NEC severity.

Journal of Neonatal-Perinatal MedicineVol. 18(6)
Northwestern University (US), University of Tasmania (AU), Washington University in St. Louis (US), Jackson Memorial Hospital (US), University of Mississippi Medical Center (US), Wake Forest University (US)
National Institute of General Medical Sciences
Life in Land
Openalex Percentile: Top 23%
Infant Nutrition and Health
1.12
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.