Biology subjects

Dickenson, M. E.

Publications and source records attributed to Dickenson, M. E..

2 recordsLinked to original sources

bioRxiv2021

Genome-scale metabolic modeling reveals increased reliance on valine catabolism in clinical isolates of Klebsiella pneumoniae

Infections due to carbapenem-resistant Enterobacteriaceae have recently emerged as one of the most urgent threats to hospitalized patients within the United States and Europe. By far the most common etiological agent of these infections is Klebsiella pneumoniae, frequently manifesting in hospital-acquired pneumonia with a mortality rate of [~]50% even with antimicrobial intervention. We performed transcriptomic analysis of data collected from in vitro characterization of both laboratory and clinical isolates revealed shifts in expression of multiple master metabolic regulators across isolate types. Metabolism has been previously shown to be an effective target for antibacterial therapy, and GENREs have provided a powerful means to accelerate identification of potential targets in silico. Combining these techniques with the transcriptome meta-analysis, we generated context-specific models of metabolism utilizing a well-curated GENRE of K. pneumoniae (iYL1228) to identify novel therapeutic targets. Functional metabolic analyses revealed that both composition and metabolic activity of clinical isolate-associated context-specific models significantly differs from laboratory isolate-associated models of the bacterium. Additionally, we identified increased consumption of L-valine in clinical isolate-specific growth simulations. Importantly, valine has been shown to augment macrophage phagocytosis, and this result could be indicative of an immunosuppressive strategy Klebsiella pneumoniae evolved for survival during infection. These findings warrant future studies for potential efficacy of valine transaminase inhibition as a target against K. pneumoniae infection. ImportanceIncidences of infection by Klebsiella pneumoniae have grown in frequency to become the leading agents of CRE infection among hospitalized patients in the United States and Europe. Transcriptomic meta-analysis of data collected from both laboratory and clinical isolates indicated significant shifts in expression of key transcription factors related to metabolism. Metabolic network reconstructions have previously proven effective for quickly identifying potential targets in silico, therefore we combined these approaches by integrating the transcriptomic data from each isolate type into a well-curated GENRE of K. pneumoniae to predict emergent metabolic patterns. Leveraging this systems-biology approach we found discordant patterns of active metabolism between clinical and laboratory isolates, with a striking difference in L-valine catabolism. Exogenous valine is known to increase macrophage phagocytosis, and our results may support immunomodulatory activity in K. pneumoniae evolved to avoid host clearance.

microbiology↗

bioRxiv2020

Genome-scale metabolic reconstruction analysis of Clostridioides difficile identifies conserved patterns of virulence-related metabolic reprogramming

The pathogen Clostridioides difficile causes toxin-mediated diarrhea and is the leading cause of hospital-acquired infection in the US. Due to growing antibiotic resistance and recurrent infection, targeting C. difficile metabolism presents a new approach to combat this infection. Genome-scale metabolic network reconstructions (GENREs) have been used to identify therapeutic targets and uncover properties that determine cellular behaviors. Thus, we constructed C. difficile GENREs for a hyper-virulent isolate (str. R20291) and a historic strain (str. 630), validating both with in vitro and in vivo datasets. Growth simulations revealed significant correlations with measured carbon source usage (PPV [≥] 92.7%), and single-gene deletion analysis showed >89.0% accuracy. Next, we utilized each GENRE to identify metabolic drivers of both sporulation and biofilm formation. Through contextualization of each model using transcriptomes generated from in vitro and infection conditions, we discovered reliance on the Pentose Phosphate Pathway as well as increased usage of cytidine and N-acetylneuraminate when virulence expression is reduced, which was subsequently supported experimentally. Our results highlight the ability of GENREs to identify novel metabolite signals in bacterial pathogenesis. ImportanceClostridioides difficile is a Gram-positive, sporulating anaerobe that has become the leading cause of hospital-acquired infections. Numerous studies have demonstrated the importance of specific metabolic pathways in aspects of C. difficile pathophysiology, from initial colonization to regulation of virulence factors. In the past, genome-scale metabolic network reconstruction (GENRE) analysis of bacteria has enabled systematic investigation of the genetic and metabolic properties that contribute to downstream virulence phenotypes. With this in mind, we generated and extensively curated C. difficile GENREs for both a well-studied laboratory strain (str. 630) as well as a more recently characterized hyper-virulent isolate (str. R20291). In silico validation of both GENREs revealed high degrees of agreement with experimental gene essentiality and carbon source utilization datasets. Subsequent exploration of context-specific metabolism during both in vitro growth and infection revealed consistent patterns of metabolism which corresponded with experimentally measured increases in virulence factor expression. Our results support that differential C. difficile virulence is associated with distinct metabolic programs related use of carbon sources and provides a platform for identification of novel therapeutic targets.

bioengineering↗