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Lippmann, N.

Publications and source records attributed to Lippmann, N..

2 recordsLinked to original sources

Colonization, translocation, and evolution of opportunistic pathogens during hospital-associated infections

Many commensal bacteria that peacefully reside in the human microbiome are also able to cause acute opportunistic infections. Emerging evidence suggests that within-host evolution contributes to infection, but the genetic mechanisms facilitating the progression of opportunistic pathogens from carriage to acute infection remain unknown. Here, we prospectively collected native samples from four microbiome niches of 13 critically ill patients to assess the evolutionary dynamics leading up to infection. Among three patients we have observed eleven healthcare-associated infections (HAI) caused by nine pathogen species. Leveraging a culture-based approach, we demonstrate that the microbiome is frequently (73%) colonized by the pathogen lineage already before or at the time of diagnosis. Moreover, we identify a short-lived, non-synonymous mutation (F126L) within the fimbriae regulator gene fimZ of Enterobacter hormaechei, first detectable within the gut and subsequently associated with HAI before becoming replaced by body-wide sweeps of independent treatment-associated mutations. Despite fimZ [F126L] being globally undetected, we can show in vitro and in vivo that the F126L mutation leads to elevated biofilm formation, cell adhesion and virulence, suggesting a role during HAI. Our work highlights the power of prospective, population-wide investigation of pathogens to elucidate rapid evolution linked to disease.

microbiology↗

Context-aware genomic surveillance reveals hidden transmission of a carbapenemase-producing Klebsiella pneumoniae

Genomic surveillance can inform effective public health responses to pathogen outbreaks. However, integration of non-local data is rarely done. We investigate two large hospital outbreaks of a carbapenemase-carrying Klebsiella pneumoniae strain in Germany and show the value of contextual data. By screening more than ten thousand genomes, 500 thousand metagenomes, and two culture collections using in silico and in vitro methods, we identify a total of 415 closely related genomes reported in 28 studies. We identify the relationship between the two outbreaks through time-dated phylogeny, including their respective origin. One of the outbreaks presents extensive hidden transmission, with descendant isolates only identified in other studies. We then leverage the genome collection from this meta-analysis to identify genes under positive selection. We thereby identify an inner membrane transporter (ynjC) with a putative role in colistin resistance. Contextual data from other sources can thus enhance local genomic surveillance at multiple levels and should be integrated by default when available.

microbiology↗