Search PubMed⌕ Search
Home/Archive/PubMed

PubMed · 41017911

Characterization of gut microbiota signatures in Indian preterm infants with necrotizing enterocolitis: a shotgun metagenomic approach.

Prabavathi Devarajalu·Savita Verma Attri·Jogender Kumar·Sourabh Dutta·Jayakanthan Kabeerdoss
View original source ↗Export metadata ↓

Abstract

INTRODUCTION: Necrotizing enterocolitis (NEC) is an inflammatory bowel disease that primarily affects preterm infants. Predisposing risk factors for NEC include prematurity, formula feeding, anemia, and sepsis. To date, no studies have investigated the gut microbiota of preterm infants with NEC in India. METHOD: In the current study, shotgun metagenomic sequencing was performed on fecal samples from premature infants with NEC and healthy preterm infants (n = 24). Sequencing was conducted using the NovaSeq X Plus platform, generating 2 &#xd7; 150 bp paired-end reads. The infants were matched based on gestational age and postnatal age. RESULT: The median time to NEC diagnosis was 9 days (range: 1-30 days). Taxonomic analysis revealed a high prevalence of Enterobacteriaceae at the family level, with the genera Klebsiella and Escherichia particularly prominent in neonates with NEC. No statistically significant differences in alpha or beta diversity were observed between stool samples from infants with and without NEC. Linear regression analysis demonstrated that Enterobacteriaceae were significantly more abundant in stool samples from infants with NEC than without NEC (q < 0.05). Differential abundance analysis using Linear Discriminant Analysis Effect Size (LEfSe) identified Klebsiella pneumoniae and Escherichia coli as enriched in the gut microbiota of preterm infants with NEC. Functional analysis revealed an increase in genes associated with lipopolysaccharide (LPS) O-antigen, the type IV secretion system (T4SS), the L-rhamnose pathway, quorum sensing, and iron transporters, including ABC transporters, in stool samples from infants with NEC. CONCLUSION: The high prevalence of Enterobacteriaceae and enrichment of LPS O-antigen and T4SS genes may be associated with NEC in Indian preterm infants.

Explore related subjects

HumansGastrointestinal MicrobiomeInfant, PrematureIndiaInfant, NewbornEnterocolitis, NecrotizingFecesMetagenomicsMaleFemaleEnterobacteriaceaeLPS O-antigenNecrotizing enterocolitisTLR4gut microbiotapreterm infantsshotgun metagenomicstype IV secretion system (T4SS)Journal Article

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Prabavathi Devarajalu, Savita Verma Attri, Jogender Kumar, Sourabh Dutta, Jayakanthan Kabeerdoss. 2025-09-11. Characterization of gut microbiota signatures in Indian preterm infants with necrotizing enterocolitis: a shotgun metagenomic approach.. https://doi.org/10.3389/fcimb.2025.1649384

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2027

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans↗
PubMed2027

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans↗
PubMed2027

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans↗