A comparison between bacterial cultivation and 16S rRNA next generation sequencing approaches for analysis of bacteria in urine and cerebrospinal fluid samples

Accurate identification of bacterial pathogens is essential for effective clinical management; however, bacterial diagnosis remains challenging in routine microbiology laboratories, particularly in emergency settings and outbreak situations. Bacterial meningitis is a life-threatening condition associated with high morbidity and mortality, underscoring the need for sensitive and specific diagnostic approaches. Conventional culture-based methods often fail to identify causative agents, especially in samples with low bacterial load or fastidious organisms. This study aimed to evaluate next-generation sequencing (NGS) as a diagnostic tool compared with classical cultivation methods for bacterial detection in urine and cerebrospinal fluid (CSF) samples. A total of 50 urine samples (30 positive, 15 insignificant, and 5 negative by culture) and 14 CSF samples (4 positive and 10 negative) were collected from the microbiology laboratory at Al-Makassed Hospital in Jerusalem, Palestine. Bacterial identification was performed using both conventional methods and NGS targeting the 16S rRNA gene. Classical culture methods identified common uropathogens, including Escherichia coli, Klebsiella spp., Enterococcus spp., Lactobacillus spp., Group B Streptococcus, Acinetobacter spp., and Proteus mirabilis in urine samples, while CSF cultures detected coagulase-negative Staphylococcus, Enterobacter spp., and methicillin-resistant Staphylococcus aureus (MRSA). In comparison, NGS provided broader bacterial profiling at genus and species levels. In urine samples with significant growth, NGS identified Escherichia coli as the most prevalent species and Enterococcus as the most abundant genus. Importantly, NGS detected multiple bacterial taxa in samples classified as culture-negative or insignificant-growth, including Escherichia, Enterococcus, Pseudomonas, Staphylococcus, and Klebsiella. In CSF samples, NGS additionally identified Pseudomonas, Enterobacter, Escherichia, Staphylococcus, and Rickettsia in culture-negative specimens. Overall, NGS demonstrated substantially higher sensitivity than classical culture methods and provided more comprehensive bacterial identification, highlighting its diagnostic value for detecting slow-growing, fastidious, and low-abundance bacteria missed by conventional techniques.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2026-06-25
DOI
https://doi.org/10.1371/journal.pone.0350939
Primary Topic
Bacterial Identification and Susceptibility Testing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A comparison between bacterial cultivation and 16S rRNA next generation sequencing approaches for analysis of bacteria in urine and cerebrospinal fluid samples

Ibrahim Abbasi, Ghaleb Adwan, Amal Abuhilal, Yasmin Attili et al.
PLoS ONE
Bacterial Identification and Susceptibility Testing
article

A comparison between bacterial cultivation and 16S rRNA next generation sequencing approaches for analysis of bacteria in urine and cerebrospinal fluid samples

Ibrahim Abbasi, Ghaleb Adwan, Amal Abuhilal, Yasmin Attili, Murad Ibrahim, Rasmi Abu-Helu
article en

Abstract

Accurate identification of bacterial pathogens is essential for effective clinical management; however, bacterial diagnosis remains challenging in routine microbiology laboratories, particularly in emergency settings and outbreak situations. Bacterial meningitis is a life-threatening condition associated with high morbidity and mortality, underscoring the need for sensitive and specific diagnostic approaches. Conventional culture-based methods often fail to identify causative agents, especially in samples with low bacterial load or fastidious organisms. This study aimed to evaluate next-generation sequencing (NGS) as a diagnostic tool compared with classical cultivation methods for bacterial detection in urine and cerebrospinal fluid (CSF) samples. A total of 50 urine samples (30 positive, 15 insignificant, and 5 negative by culture) and 14 CSF samples (4 positive and 10 negative) were collected from the microbiology laboratory at Al-Makassed Hospital in Jerusalem, Palestine. Bacterial identification was performed using both conventional methods and NGS targeting the 16S rRNA gene. Classical culture methods identified common uropathogens, including Escherichia coli, Klebsiella spp., Enterococcus spp., Lactobacillus spp., Group B Streptococcus, Acinetobacter spp., and Proteus mirabilis in urine samples, while CSF cultures detected coagulase-negative Staphylococcus, Enterobacter spp., and methicillin-resistant Staphylococcus aureus (MRSA). In comparison, NGS provided broader bacterial profiling at genus and species levels. In urine samples with significant growth, NGS identified Escherichia coli as the most prevalent species and Enterococcus as the most abundant genus. Importantly, NGS detected multiple bacterial taxa in samples classified as culture-negative or insignificant-growth, including Escherichia, Enterococcus, Pseudomonas, Staphylococcus, and Klebsiella. In CSF samples, NGS additionally identified Pseudomonas, Enterobacter, Escherichia, Staphylococcus, and Rickettsia in culture-negative specimens. Overall, NGS demonstrated substantially higher sensitivity than classical culture methods and provided more comprehensive bacterial identification, highlighting its diagnostic value for detecting slow-growing, fastidious, and low-abundance bacteria missed by conventional techniques.

PLoS ONEVol. 21(6)
An-Najah National University (PS), Al-Quds University (PS)
Good health and well-being
Openalex Percentile: Top 9%
Bacterial Identification and Susceptibility Testing
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.