The process of ageing makes death increasingly likely, but involves a random aspect that produces a wide distribution of lifespan even in homogeneous populations1,2. The study of this stochastic behaviour may link molecular mechanisms to the ageing process that determines lifespan. Here, by collecting high-precision mortality statistics from large populations, we observe that interventions as diverse as changes in diet, temperature, exposure to oxidative stress, and disruption of genes including the heat shock factor hsf-1, the hypoxia-inducible factor hif-1, and the insulin/IGF-1 pathway components daf-2, age-1, and daf-16 all alter lifespan distributions by an apparent stretching or shrinking of time. To produce such temporal scaling, each intervention must alter to the same extent throughout adult life all physiological determinants of the risk of death. Organismic ageing in Caenorhabditis elegans therefore appears to involve aspects of physiology that respond in concert to a diverse set of interventions. In this way, temporal scaling identifies a novel state variable, r(t), that governs the risk of death and whose average decay dynamics involves a single effective rate constant of ageing, kr. Interventions that produce temporal scaling influence lifespan exclusively by altering kr. Such interventions, when applied transiently even in early adulthood, temporarily alter kr with an attendant transient increase or decrease in the rate of change in r and a permanent effect on remaining lifespan. The existence of an organismal ageing dynamics that is invariant across genetic and environmental contexts provides the basis for a new, quantitative framework for evaluating how and how much specific molecular processes contribute to the aspect of ageing that determines lifespan.
This review will discuss the gut as a reservoir for antimicrobial resistance, colonization resistance, and how disruption of the microbiome can lead to colonization by pathogenic organisms. There is a focus on the gut as a reservoir for β-lactam and plasmid mediated quinolone resistance. Finally, the role of functional metagenomics and long read sequencing technologies to detect and understand antimicrobial resistance genes within the gut microbiome, and the potential for future microbiome-directed methods to detect and prevent infection is discussed.
The current extraction and use of fossil fuels has been linked to extensive negative health and environmental outcomes. Lignocellulosic biomass-derived biofuels and bioproducts are being actively considered as renewable alternatives to the fuels, chemicals, and materials produced from fossil fuels. A major challenge limiting large-scale, economic deployment of second-generation biorefineries is the insufficient product yield, diversity, and value that current conversion technologies can extract from lignocellulose, in particular from the underutilized lignin fraction. Rhodococcus opacus PD630 is an oleaginous gram-positive bacterium with innate catabolic pathways and tolerance mechanisms for the inhibitory aromatic compounds found in depolymerized lignin, as well as native or engineered pathways for hexose and pentose sugars found in the carbohydrate fractions of biomass. As a result, R. opacus holds potential as a biological chassis for the conversion of lignocellulosic biomass into biodiesel precursors and other value-added products. This review begins by examining the important role that lignin utilization will play in the future of biorefineries and by providing a concise survey of the current lignin conversion technologies. The genetic machinery and capabilities of R. opacus that allow the bacterium to tolerate and metabolize aromatic compounds and depolymerized lignin are also discussed, along with a synopsis of the genetic toolbox and synthetic biology methods now available for engineering this organism. Finally, we summarize the different feedstocks that R. opacus has been demonstrated to consume, and the high-value products that it has been shown to produce. Engineered R. opacus will enable lignin valorization over the coming years, leading to cost-effective conversion of lignocellulose into fuels, chemicals, and materials.
Rhodococcus opacus is a bacterium that has a high tolerance to aromatic compounds and can produce significant amounts of triacylglycerol (TAG). Here, we present iGR1773, the first genome-scale model (GSM) of R. opacus PD630 metabolism based on its genomic sequence and associated data. The model includes 1773 genes, 3025 reactions, and 1956 metabolites, was developed in a reproducible manner using CarveMe, and was evaluated through Metabolic Model tests (MEMOTE). We combine the model with two Constraint-Based Reconstruction and Analysis (COBRA) methods that use transcriptomics data to predict growth rates and fluxes: E-Flux2 and SPOT (Simplified Pearson Correlation with Transcriptomic data). Growth rates are best predicted by E-Flux2. Flux profiles are more accurately predicted by E-Flux2 than flux balance analysis (FBA) and parsimonious FBA (pFBA), when compared to 44 central carbon fluxes measured by 13C-Metabolic Flux Analysis (13C-MFA). Under glucose-fed conditions, E-Flux2 presents an R 2 value of 0.54, while predictions based on pFBA had an inferior R 2 of 0.28. We attribute this improved performance to the extra activity information provided by the transcriptomics data. For phenol-fed metabolism, in which the substrate first enters the TCA cycle, E-Flux2’s flux predictions display a high R 2 of 0.96 while pFBA showed an R 2 of 0.93. We also show that glucose metabolism and phenol metabolism function with similar relative ATP maintenance costs. These findings demonstrate that iGR1773 can help the metabolic engineering community predict aromatic substrate utilization patterns and perform computational strain design.
BackgroundAntibiotics (ABX) are frequently inappropriately used to treat nonbacterial causes of respiratory illnesses. The goal of this prospective cohort study was to characterize the impact of ABX used to treat community-acquired pneumonia (CAP) on the fecal microbiome and resistome in healthy volunteers (HV).MethodsTwenty HVs were randomized to receive 5 days of levofloxacin (LV), azithromycin (AZ), cefpodoxime (CF), or AZ+CF. Stool was collected before, during, and after ABX, then underwent microbiologic culture and shotgun sequencing. DNA was extracted, then sequenced using the Illumina NextSeq platform. Relative abundance of bacterial taxa was estimated by MetaPhlAn and antibiotic resistance gene (ARG) composition by ShortBRED. Analysis was in R.ResultsThe mean HV age was 37 (range 24–59) and 10 were female. Species diversity measured via Shannon Index and richness were significantly lower in samples taken from all HVs 3 days post-ABX (P < 0.01 for all). While nonmetric multidimensional scaling (NDMS) ordination shows high interpatient dissimilarity (Bray–Curtis) for most samples, the post-ABX intrapatient dissimilarity varies by ABX. The AZ group exhibited chronic alterations in taxa dissimilarity and the CF group had increases in dissimilarity directly post-ABX. The CF+AZ group displayed both acute and persistent perturbations (Figure 1). Although there was no significant change in ARG richness post-ABX, there was a significant increase in overall ARG abundance across all samples (P < 0.003). Within each ABX, there were unique changes in ARG abundance, and groups with CF had increases in ARG abundance (Figure 2).ConclusionABX used to treat CAP can cause acute microbiome disruptions, as evidenced by decreased microbiome species diversity and richness, and an increase in ARG abundance post-ABX. The duration of this impact is variable. To prevent microbiome disruptions, measures to prevent inappropriate ABX use via ABX stewardship are necessary. Disclosures E. R. Dubberke, Rebiotix: Consultant and Investigator, Consulting fee and Research support. Pfizer: Consultant and Grant Investigator, Consulting fee and Research grant. Synthetic biologics: Consultant, Consulting fee. Merck: Consultant and Investigator, Consulting fee and Research support. Valneva: Consultant, Consulting fee. Achaogen: Consultant, Consulting fee. Alere: webinar, Speaker honorarium. Biofire: webinar, Speaker honorarium.
Background: Antimicrobial exposure is a significant risk factor for the development of antibiotic-resistant organisms (ARO); however, the depth and duration of this impact is not well described. The study goal is to define impact of antibiotics on the gut microbiome of healthy volunteers (HVs). Methods: HVs were randomized to receive either 5 days of levofloxacin (LVX), azithromycin (AZM), cefpodoxime (CPD), or AZM + CPD (Fig. 1). Stool samples were collected at 15 time points per patient before, during, and after antibiotics. Remnant stool samples from the microbiology laboratory were collected from patients admitted to the medical intensive care unit (MICU) as a comparison of the microbiome in a critically ill state. DNA was extracted from samples and was submitted for shotgun sequencing. Relative abundance, resistome, and metabolic pathway abundance of bacterial taxa were determined and statistical analysis conducted in R software. Results: In total, 289 stool specimens from 20 HVs, and 26 remnant stool specimens were obtained from patients admitted from the MICU (Fig. 1). Community diversity and richness decreased in the first week post-ABX for all HVs (P < .01). Linear discriminant analysis identified Bacteroides and Clostridium as taxonomic groups enriched after CPD, while AZM and LVX produced a relative abundance increase in diverse Firmicutes spp. Longitudinal tracking confirmed that after all antibiotics except LVX, HV microbiomes lost species diversity and shifted toward a state similar to that observed in MICU patients (Fig. 2). The gut microbiome of most HVs exhibited resiliency and returned to a higher diversity level similar to their starting point; however, 10% of HVs did not. Moreover, antibiotic-specific increases in resistance markers reveal innate resistance to β-lactams and macrolides within the gut microbiome of the HVs. Finally, HV microbiomes, which shifted toward a MICU-like taxonomic state, also clustered with microbial metabolic profiles from MICU patients.The HV microbial metabolic profiles were significantly enriched for important biosynthesis pathways producing chorismate and polysaccharides. MICU patient gut microbiomes were enriched for fatty acid regulation and quinolone biosynthesis, and for many degradation pathways important for different aspects of antibiotic resistance such as membrane integrity, alternative respiration, and antibiotic inactivation. Conclusions: Short courses of antibiotics can cause acute and chronic microbiome disruptions in HVs, as evidenced by decreased microbiome diversity and increases in specific innate resistance elements. These data support the need for antimicrobial stewardship to support rationale antibiotic use to prevent gut microbiome disruptions.Funding: CDC BAA 200-2016-91962Disclosures: None
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