Biology subjects

Indra, A.

Publications and source records attributed to Indra, A..

3 recordsLinked to original sources

bioRxiv2021

Performance of Core Genome Multilocus Sequence Typing Compared to Capillary-Electrophoresis PCR Ribotyping and SNP Analysis of Clostridioides difficile

Clostridioides difficile is the most common cause of antibiotic-associated gastrointestinal infections. Capillary-electrophoresis (CE)-PCR ribotyping is currently the gold standard for C. difficile typing but lacks discriminatory power to study transmission and outbreaks in detail. New molecular methods have the capacity to differentiate better, but backward compatibility with CE-PCR ribotyping must be assessed. Using a well-characterized collection of diverse strains (N=630; 100 unique ribotypes [RTs]), we aimed to investigate PCR ribotyping prediction from core genome multilocus sequence typing (cgMLST). Additionally, we compared the discriminatory power of cgMLST (SeqSphere & EnteroBase) and whole genome MLST (wgMLST) (EnteroBase) with single nucleotide polymorphism (SNP) analysis). A unique cgMLST profile (>6 allele differences) was observed in 82/100 ribotypes, indicating sufficient backward compatibility. Intra-RT allele difference varied per ribotype and MLST clade. Application of cg/wgMLST and SNP analysis in two outbreak settings with ribotypes RT078 and RT181 (known with a low intra-ribotype allele difference) showed no distinction between outbreak- and non-outbreak strains, in contrast to wgMLST and SNP analysis. We conclude that cgMLST has the potential to be an alternative to CE-PCR ribotyping. The method is reproducible, easy to standardize and offers higher discrimination. However, in some ribotype complexes adjusted cut-off thresholds and epidemiological data are necessary to recognize outbreaks. We propose to decrease the current threshold of 6 to 3 alleles to better identify outbreaks.

molecular biology↗

bioRxiv2021

Agricultural fertilization with poultry manure results in persistent environmental contamination with the pathogen Clostridioides difficile

During a field experiment applying broiler manure for fertilization of agricultural land, we detected viable Clostridioides (formerly, Clostridium) difficile in broiler feces, manure, dust, and fertilized soil. A large diversity of toxigenic C. difficile isolates was recovered, including PCR ribotypes common from human disease. Genomic relatedness of C. difficile isolates from dust and from soil, recovered more than two years after fertilization, traced their origins to the specific chicken farm that had delivered the manure. We present evidence of long-term contamination of agricultural soil with manure-derived C. difficile and demonstrate the potential for airborne dispersal of C. difficile through dust emissions during manure application. Clostridioides genome sequences virtually identical to those from manure had been recovered from chicken meat and from human infections in previous studies, suggesting broiler-associated C. difficile are capable of zoonotic transmission.

microbiology↗

bioRxiv2019

Global genomic population structure of Clostridioides difficile

Clostridioides difficile is the primary infectious cause of antibiotic-associated diarrhea. Local transmissions and international outbreaks of this pathogen have been previously elucidated by bacterial whole-genome sequencing, but comparative genomic analyses at the global scale were hampered by the lack of specific bioinformatic tools. Here we introduce EnteroBase, a publicly accessible database (http://enterobase.warwick.ac.uk) that automatically retrieves and assembles C. difficile short-reads from the public domain, and calls alleles for core-genome multilocus sequence typing (cgMLST). We demonstrate that the identification of highly related genomes is 89% consistent between cgMLST and single-nucleotide polymorphisms. EnteroBase currently contains 13,515 quality-controlled genomes which have been assigned to hierarchical sets of single-linkage clusters by cgMLST distances. Hierarchical clustering can be used to identify populations of C. difficile at all epidemiological levels, from recent transmission chains through to pandemic and endemic strains, and is largely compatible with prior ribotyping. Hierarchical clustering thus enables comparisons to earlier surveillance data and will facilitate communication among researchers, clinicians and public-health officials who are combatting disease caused by C. difficile.

microbiology↗