Genomic dataset of multidrug-resistant Klebsiella quasipneumoniae from Indonesia

Abstract

Objectives

Klebsiella pneumoniae is a free-living bacterium found anywhere, including soil, water, and various types of plants, animals, and humans. Due to identical biochemical test results, Klebsiella quasipneumoniae, a member of the Klebsiella pneumoniae complex, is often misidentified as Klebsiella pneumoniae. This distinct species can be accurately identified solely through whole-genome sequencing. This bacterium poses a significant public health threat due to its increasing antibiotic resistance, ability to cause severe disease, and potential for community-acquired and hospital-acquired infections. However, there was no previous report of K. quasipneumoniae from Indonesia. Subsequent research focusing on antimicrobial-resistant gene analysis, virulence determinants, evolutionary relationship, and transmission pathways based on this dataset will enhance understanding of this species and their differences with other Klebsiella pneumoniae complex organisms.

Data description

We present a whole genome sequencing of four Klebsiella quasipneumoniae isolated from hospital wastewater in Jakarta, Indonesia. Initial bacterial identification was conducted which showed Klebsiella pneumoniae. However, the whole genome Average Nucleotide Identity (wgANI) was found to be Klebsiella quasipneumoniae. The genome size of Klebsiella quasipneumoniae I1-1, I1-3, I5-2, and I5-3 isolates were 5.4 Mb (GC = 57.72%), 5.5 Mb (GC = 57.72%), 5.4 Mb (GC = 57.73%), and 5.5 Mb (GC = 57.72%), respectively. Sequence data has been deposited in the GenBank database.

Objective

The genus Klebsiella belongs to the Enterobacteriaceae family, which is nonmotile, rod-shaped, and Gram-negative, and it produces a polysaccharide capsule. K. pneumoniae is a free-living bacterium found anywhere, including soil, water, and various types of plants, animals, and humans. This bacterium poses a significant public health threat due to its increasing antibiotic resistance, ability to cause severe disease, and potential for community-acquired and hospital-acquired infections [1, 2]. The Klebsiella pneumoniae complex is classified into three phylogroups: Klebsiella pneumoniae (KpI), Klebsiella quasipneumoniae (KpII), and Klebsiella variicola (KpIII) in classical taxonomy, but KpII and KpIII are rarely isolated clinically. K. quasipneumoniae is frequently mistaken as K. pneumoniae by conventional microbiology laboratories because of the resemblance in biochemical test findings. Whole-genome sequencing can help distinguish K. quasipneumoniae from K. pneumoniae and greatly increase the genetic understanding of the K. quasipneumoniae strain [3].

Wastewater surveillance has historically been used to track pathogens within a community. Compared with urban wastewater, hospital wastewater generally harbours substantial levels of antibiotic-resistant bacteria due to the intense selection pressure exerted by the frequent use of antibiotics. The presence of high multidrug-resistant (MDR) bacteria in hospital wastewater may impose public health challenges because they can transmit resistance traits to other enteric pathogenic bacteria in the community. Routine monitoring of hospital wastewater for pathogens and antimicrobial resistance genes may provide early detection and guide public health interventions [4].

This study investigates the genomic characteristics of four Klebsiella quasipneumoniae isolates obtained from hospital wastewater in Indonesia. To our knowledge, no previous report of K. quasipneumoniae from Indonesia existed. The data set of the pathogen bacteria presented here can provide valuable resources for genomic studies and future computational studies, including machine learning or deep learning models to understand genomic features or predict phenotypic traits related to Klebsiella quasipneumoniae.

Data description

Sampling sites and sample collection

This study was conducted on hospital wastewater in Jakarta, Indonesia, on 14th October 2024. The representative samples were taken using a “grab sampling technique” following the Indonesian Nasional Standard (SNI) 9063:2022 [5]. At the hospital wastewater treatment site, the covers of the manholes were carefully lifted, and 14 ml wastewater samples, each from the inlet and outlet site, were taken into sterile plastic containers. Samples were collected once at 1:00 P.M. All samples were collected manually and transported with a cold chain within two hours into the microbiology laboratory. Samples were stored in a refrigerator at 4⁰C until they were processed.

Species identification test and antimicrobial susceptibility testing

Table 1 (Data file 1) presents a snapshot of our data analysis workflow. From 14 mL of each sample, 1 mL was taken to be diluted from 10^− 1 to 10^− 4 in sterile water. Then, 100 ul of each sample dilution was streaked onto MacConkey Agar (Oxoid, Cat. No. CM0007) using a sterile inoculating loop and incubated at 37⁰C in the atmosphere for 24 h [6, 7]. A total of ten pink colonies (Gram-negative, lactose-fermenters) were taken randomly from each sample, inlet and outlet. The Clinical and Laboratory Standards Institute (CLSI) 2024 was used as an antimicrobial susceptibility testing reference [8,9,10,11]. Four colonies (I1-1, I1-3, I5-2, I5-3) were identified as Klebsiella pneumoniae and antimicrobial resistance results showed multidrug-resistance organisms (Table 1, Data File 2).

Whole genome sequencing (WGS) and draft genome assembly

Based on phenotypic results, four colonies identified as Klebsiella pneumoniae were processed for WGS library preparation. DNA was extracted using the Quick-DNA Magbead Plus Kit (D4082). The libraries were prepared using the xGen DNA Library Prep EZ UNI Kit (IDT, 10009822). Sequencing was performed using 300 cycles (2 × 150 bp paired-end) of the Illumina sequencing reagent on the NextSeq 2000 platform. The raw reads were imported into Geneious Prime^® 2024.0.3 for streamlined analysis (https://www.geneious.com). The reads were filtered based on base quality (> Q30) and length (> 50 bp) using BBDuk, a tool included in the BBMap package (https://sourceforge.net/projects/bbmap/). Next, the filtered reads were paired and assembled using SPAdes Assembler 3.15.5 [12], and only contigs longer than 1,000 bp were retained for further analysis. Annotation of coding regions, RNA genes, and other genomic features was done through the RAST-tk pipeline [13].

Draft genomes were constructed from contigs using the Mauve MCM algorithm [14] and compared with representative genomes of the Klebsiella spp. in the database. This process used whole-genome Average Nucleotide Identity (wgANI) using FastANI26 v.1.34 by the default setting [15]. The species with the highest wgANI was taxonomically assigned to the assembled genome. For species identification, the 95% identity criteria were considered. There were Klebsiella quasipneumoniae I1-1 (98.7%), Klebsiella quasipneumoniae I1-3 (99.2%), Klebsiella quasipneumoniae I5-2 (98.7%); and Klebsiella quasipneumoniae I5-3 (98.7%) with Klebsiella quasipneumoniae subsp. quasipneumoniae strain KP_NORM_BLD_60803; COP15399 as reference. An overview of the genomic dataset is presented in Table 1 (Data files 3–8).

Table 1 Overview of data files/data sets

Limitations

This data note focuses on the genomic characteristics of multidrug-resistant Klebsiella quasipneumoniae isolates obtained from hospital wastewater. This study has several limitations, including a small sample size (only four isolates) and a limited scope (single hospital wastewater site). More in-depth research is needed to understand phylogenetics, antimicrobial-resistant gene analysis, virulence factors, and one health approach to investigate transmission routes.