Genome of the pathogen Porphyromonas gingivalis recovered from a biofilm in a hospital sink using a high-throughput single-cell genomics platform

Abstract

Although biofilms have been shown to be reservoirs of pathogens, our knowledge of the microbial diversity in biofilms within critical areas, such as health care facilities, is limited. Available methods for pathogen identification and strain typing have some inherent restrictions. In particular, culturing will yield only a fraction of the species present, PCR of virulence or marker genes is mainly focused on a handful of known species, and shotgun metagenomics is limited in the ability to detect strain variations. In this study, we present a single-cell genome sequencing approach to address these limitations and demonstrate it by specifically targeting bacterial cells within a complex biofilm from a hospital bathroom sink drain. A newly developed, automated platform was used to generate genomic DNA by the multiple displacement amplification (MDA) technique from hundreds of single cells in parallel. MDA reactions were screened and classified by 16S rRNA gene PCR sequence, which revealed a broad range of bacteria covering 25 different genera representing environmental species, human commensals, and opportunistic human pathogens. Here we focus on the recovery of a nearly complete genome representing a novel strain of the periodontal pathogen Porphyromonas gingivalis (P. gingivalis JCVI SC001) using the single-cell assembly tool SPAdes. Single-cell genomics is becoming an accepted method to capture novel genomes, primarily in the marine and soil environments. Here we show for the first time that it also enables comparative genomic analysis of strain variation in a pathogen captured from complex biofilm samples in a healthcare facility.

Identification of the Linkage between A-Polysaccharide and the Core in the A-Lipopolysaccharide of Porphyromonas gingivalis W50

“…Interrogation of the fully annotated genomes of P. gingivalis W83 and ATCC 33277 (11,12) using the Carbohydrate-Active Enzymes (CAZy) database (http://www.cazy.org/) has recognized a number of potential glycosyltransferases that are classified into 28 and 29 groups for P. gingivalis strains W83 and ATCC 33277, respectively. In addition, the structures and organizations of open reading frames of the PG0129 genomic loci in all sequenced strains, in particular P. gingivalis W83 (11), ATCC 33277 (12), TDC60 (13), JCVI SC001 (14), HG66 (15), and W50, are identical, i.e., the sequences are homologous and synteny is preserved. Although the complete genome sequence of P. gingivalis W50 is not yet published, the strain appears indistinguishable from P. gingivalis W83 with respect to a range of molecular and biochemical characteristics (16).…”

Candidate phylum TM6 genome recovered from a hospital sink biofilm provides genomic insights into this uncultivated phylum

“…Single-cell sorting was performed on a custom FACS Aria II as described (6). FACS detection was performed on the Nycodenz fractionated bacteria-enriched sample.…”

“…(1), which is accomplished using multiple displacement amplification (MDA) (2-5) of genomic DNA to obtain sufficient template. We applied a high-throughput strategy to capture and sequence genomes of bacteria from a biofilm in a hospital sink including pathogens, such as the oral periodontal pathogen (Porphyromonas gingivalis) (6) and uncultivated members (this study). Despite the fact that a typical person spends ∼90% of their time indoors (7), our knowledge of the microbial diversity of the indoor environment has only recently begun to be explored using culture-independent methods (8,9).…”

Biofilms on Hospital Shower Hoses: Characterization and Implications for Nosocomial Infections

“…Hence, metagenome sequencing (i.e., random sequencing of total community DNA extracts) has recently been used to examine the functional network of complex microbial communities (28,29). In spite of the rise of infections by opportunistic premise plumbing pathogens, relatively few studies have assessed the diversity of biofilms growing in DWDS at the metagenome level, especially in health care units (30)(31)(32)(33). Most previous reports are based on 16S rRNA gene amplicon surveys that are limited in scope as far as accurately predicting exposure risks.…”