ChIP-exo interrogation of Crp, DNA, and RNAP holoenzyme interactions

Numerous in vitro studies have yielded a refined picture of the structural and molecular associations between Cyclic-AMP receptor protein (Crp), the DNA motif, and RNA polymerase (RNAP) holoenzyme. In this study, high-resolution ChIP-exonuclease (ChIP-exo) was applied to study Crp binding in vivo and at genome-scale. Surprisingly, Crp was found to provide little to no protection of the DNA motif under activating conditions. Instead, Crp demonstrated binding patterns that closely resembled those generated by σ70. The binding patterns of both Crp and σ70 are indicative of RNAP holoenzyme DNA footprinting profiles associated with stages during transcription initiation that occur post-recruitment. This is marked by a pronounced advancement of the template strand footprint profile to the +20 position relative to the transcription start site and a multimodal distribution on the nontemplate strand. This trend was also observed in the familial transcription factor, Fnr, but full protection of the motif was seen in the repressor ArcA. Given the time-scale of ChIP studies and that the rate-limiting step in transcription initiation is typically post recruitment, we propose a hypothesis where Crp is absent from the DNA motif but remains associated with RNAP holoenzyme post-recruitment during transcription initiation. The release of Crp from the DNA motif may be a result of energetic changes that occur as RNAP holoenzyme traverses the various stable intermediates towards elongation complex formation

Adaptive Evolution of Thermotoga maritima Reveals Plasticity of the ABC Transporter Network

Thermotoga maritima is a hyperthermophilic anaerobe that utilizes a vast network of ABC transporters to efficiently metabolize a variety of carbon sources to produce hydrogen. For unknown reasons, this organism does not metabolize glucose as readily as it does glucose di- and polysaccharides. The leading hypothesis implicates the thermolability of glucose at the physiological temperatures at which T. maritima lives. After a 25-day laboratory evolution, phenotypes were observed with growth rates up to 1.4 times higher than and glucose utilization rates exceeding 50% those of the wild type. Genome resequencing revealed mutations in evolved cultures related to glucose-responsive ABC transporters. The native glucose ABC transporter, GluEFK, has more abundant transcripts either as a result of gene duplication-amplification or through mutations to the operator sequence regulating this operon. Conversely, BglEFGKL, a transporter of beta-glucosides, is substantially downregulated due to a nonsense mutation to the solute binding protein or due to a deletion of the upstream promoter. Analysis of the ABC2 uptake porter families for carbohydrate and peptide transport revealed that the solute binding protein, often among the transcripts detected at the highest levels, is predominantly downregulated in the evolved cultures, while the membrane-spanning domain and nucleotide binding components are less varied. Similar trends were observed in evolved strains grown on glycerol, a substrate that is not dependent on ABC transporters. Therefore, improved growth on glucose is achieved through mutations favoring GluEFK expression over BglEFGKL, and in lieu of carbon catabolite repression, the ABC transporter network is modulated to achieve improved growth fitness

Contrasting ChIP-exo profiles of repressors and activators.

<p>(A) The TSS aligned ChIP-exo profile for ArcA, a predominantly repressive transcription factor, is shown to lack the characteristic distribution of mean 5’ tag density observed on both the template and nontemplate strand. (B) The TSS aligned mean 5’ tag density profile for Fnr, typically an activator, resembles the profile found for Crp and σ⁷⁰. (C) The ArcA ChIP-exo profile is shown for all peak regions aligned to the peak center position. Also shown is a histogram of the center of the predicted ArcA binding site relative to the peak center position. This illustrates that the ChIP-exo profile is centered on the predicted binding site. (D) A comparison of the peak-pair distance is shown to illustrate the difference in resolution observed between ArcA and Fnr. ArcA, the repressor, is revealed to have shorter footprints compared with Fnr, the activator.</p

TSS aligned and oriented σ⁷⁰ ChIP-exo peaks reveals DNA footprint patterns consistent with stable transcription initiation intermediates.

<p>(A) ChIP-exo peak regions aligned and oriented relative to the TSS. The peak center (blue bars) is shown to be downstream of the TSS with a median of 5 bp. The mean distribution of the 5’ tags is shown for both strands. The template strand distribution shows a unimodal profile that spans +20±7 bp indicative of RPO, ITC, and TEC stable intermediates. The nontemplate strand shows a multimodal distribution with modes centered approximately +5 relative to the TSS (Group III), upstream and over the -10 promoter element (Group II), and slightly downstream of the -35 promoter element (Group I). (B) Examination of the distance between template and nontemplate strand peak maximum shows that the footprint lengths are >40 bp, 21 to 40, <20 and for Group I, Group II, and Group III respectively. (C) A motif search was performed for the -10 and -35 promoter elements for Group I, Group II, and Group III promoters. All three show σ⁷⁰-like promoter sequences with slight differences. Group I has a -35 motif that most closely resembles the consensus (TTGACA), has a highly conserved -11A, and a partial TGn motif. Group III has the least conserved -35 promoter element and no extended -10 promoter element.</p

Crp and σ⁷⁰ have highly similar ChIP-exo footprints.

<p>(A) Gene tracks are shown that exemplify the different Crp ChIP-exo footprint profiles observed for the three different classes of Crp promoters. At the Class III promoter <i>deoC</i> footprints are found over the Crp motif and the CytR motif which sequesters Crp preventing activation. However, under the activating Class I and Class II promoters there are few observed reads over the Crp motif. Instead, the peak is centered on the TSS and the footprint region cooccurs with that found for σ⁷⁰. Examples of this are shown for <i>tnaC</i> (Class I) and <i>adhE</i> (Class II). (B) Shown is the mean 5’ tag density ChIP-exo profile aligned and oriented relative to the TSS generated for Crp grown on glycerol minimal media. The distribution of the center position at +23 across all Crp peak regions (blue bars) shows close proximity to the TSS. The template strand distribution (dashed black trace) corresponds with the downstream region centered at +20 that is associated with stable intermediates of the RPO, the ITC, and the TEC as was observed for σ⁷⁰. The nontemplate strand distribution indicates protection of DNA predominantly occurs downstream of the -35 element with little protection at the predicted binding sites (gray bars). (C) An overlay of the mean 5’ tag density profile of all Crp peak regions (blue traces) and the associated σ⁷⁰ mean 5’ tag density profile in those same peak regions (black traces) illustrates the strong co-occurrence of Crp footprint regions with σ⁷⁰.</p

The effect of genetic perturbation on Crp/RNAP interactions.

<p>(A) Cartoon illustrating the interactions between activating regions (Ar’s) and RNAP for Class I and Class II activators. Crp Class I promoters make a single contact with RNAP at Ar1 whereas Crp Class II activators make upwards of three contacts (Ar1, Ar2, and Ar3). Deletions of Ar1, Ar2, and Ar1+Ar2 where generated. (B) Venn diagram showing pairwise comparison of peaks regions detected for ΔAr1, ΔAr2, and ΔAr1ΔAr2 with wild type Crp. All cultures were grown with glycerol as the carbon source. The mutations to Crp result in fewer detected peaks relative to wild type Crp indicating promoter destabilization. (C) Histogram of the peak center position relative to the TSS for wild type Crp, ΔAr1, ΔAr2, and ΔAr1ΔAr2 mutants. This illustrates that the peak centers nearest the TSS (-15 to +20) are predominantly affected by deletion of Ar1 and Ar2, whereas peak regions centered upstream of the TSS (< -15) are largely unaffected. (D) An alternative view to the histogram shown in (C) that shows the distribution of predicted Crp binding sites relative to the TSS. The ΔAr1 strain shows a reduction in the number of peak regions with -61.5 motifs compared with wild type and ΔAr2 indicating a sensitivity of Class I promoters to mutations to this region. Similarly, the ΔAr2 strain shows a substantial loss of Class II associated peak regions (-41.5 binding sites) compared with Class I (-61.5). The ΔAr1ΔAr2 mutant shows reductions in both -41.5 and -61.5 binding sites compared with the wild type. None of the ΔAr strains showed a reduction in the peak regions with Class III binding sites (e.g., -93.5 binding sites).</p

Acetate reprograms gut microbiota during alcohol consumption.

Liver damage due to chronic alcohol use is among the most prevalent liver diseases. Alcohol consumption frequency is a strong factor of microbiota variance. Here we use isotope labeled [1-13C] ethanol, metagenomics, and metatranscriptomics in ethanol-feeding and intragastric mouse models to investigate the metabolic impacts of alcohol consumption on the gut microbiota. First, we show that although stable isotope labeled [1-13C] ethanol contributes to fatty acid pools in the liver, plasma, and cecum contents of mice, there is no evidence of ethanol metabolism by gut microbiota ex vivo under anaerobic conditions. Next, we observe through metatranscriptomics that the gut microbiota responds to ethanol-feeding by activating acetate dissimilation, not by metabolizing ethanol directly. We demonstrate that blood acetate concentrations are elevated during ethanol consumption. Finally, by increasing systemic acetate levels with glyceryl triacetate supplementation, we do not observe any impact on liver disease, but do induce similar gut microbiota alterations as chronic ethanol-feeding in mice. Our results show that ethanol is not directly metabolized by the gut microbiota, and changes in the gut microbiota linked to ethanol are a side effect of elevated acetate levels. De-trending for these acetate effects may be critical for understanding gut microbiota changes that cause alcohol-related liver disease