Reversal of the ΔdegP Phenotypes by a Novel rpoE Allele of Escherichia coli

RseA sequesters RpoE (σE) to the inner membrane of Escherichia coli when envelope stress is low. Elevated envelope stress triggers RseA cleavage by the sequential action of two membrane proteases, DegS and RseP, releasing σE to activate an envelope stress reducing pathway. Revertants of a ΔdegP ΔbamB strain, which fails to grow at 37°C due to high envelope stress, harbored mutations in the rseA and rpoE genes. Null and missense rseA mutations constitutively hyper-activated the σE regulon and significantly reduced the major outer membrane protein (OMP) levels. In contrast, a novel rpoE allele, rpoE3, resulting from the partial duplication of the rpoE gene, increased σE levels greater than that seen in the rseA mutant background but did not reduce OMP levels. A σE-dependent RybB::LacZ construct showed only a weak activation of the σE pathway by rpoE3. Despite this, rpoE3 fully reversed the growth and envelope vesiculation phenotypes of ΔdegP. Interestingly, rpoE3 also brought down the modestly activated Cpx envelope stress pathway in the ΔdegP strain to the wild type level, showing the complementary nature of the σE and Cpx pathways. Through employing a labile mutant periplasmic protein, AcrAL222Q, it was determined that the rpoE3 mutation overcomes the ΔdegP phenotypes, in part, by activating a σE-dependent proteolytic pathway. Our data suggest that a reduction in the OMP levels is not intrinsic to the σE-mediated mechanism of lowering envelope stress. They also suggest that under extreme envelope stress, a tight homeostasis loop between RseA and σE may partly be responsible for cell death, and this loop can be broken by mutations that either lower RseA activity or increase σE levels

Feral swine brucellosis in the United States and prospective genomic techniques for disease epidemiology

Brucellosis is a common infection of feral swine throughout the United States. With the recent expansion of feral swine populations across the country, this disease poses an increasing threat to agriculture and hunters. The standard approach to Brucella surveillance in feral swine has been serological testing, which gives an indication of past exposure and is a rapid method of determining populations where Brucella is present. More in-depth analyses require bacterial isolation to determine the Brucella species and biovar involved. Ultimately, for a comprehensive understanding of Brucella epizootiology in feral swine, incorporation of genotyping assays has become essential. Fortunately, the past decade has given rise to an array of genetic tools for assessing Brucella transmission and dispersal. This review aims to synthesize what is known about brucellosis in feral swine and will cover prospective genomic techniques that may be utilized to develop more complete understanding of the disease and its transmission history

Beyond the List: Bioagent-Agnostic Signatures Could Enable a More Flexible and Resilient Biodefense Posture Than an Approach Based on Priority Agent Lists Alone

As of 2021, the biothreat policy and research communities organize their efforts around lists of priority agents, which elides consideration of novel pathogens and biotoxins. For example, the Select Agents and Toxins list is composed of agents that historic biological warfare programs had weaponized or that have previously caused great harm during natural outbreaks. Similarly, lists of priority agents promulgated by the World Health Organization and the National Institute of Allergy and Infectious Diseases are composed of previously known pathogens and biotoxins. To fill this gap, we argue that the research/scientific and biodefense/biosecurity communities should categorize agents based on how they impact their hosts to augment current list-based paradigms. Specifically, we propose integrating the results of multi-omics studies to identify bioagent-agnostic signatures (BASs) of disease—namely, patterns of biomarkers that accurately and reproducibly predict the impacts of infection or intoxication without prior knowledge of the causative agent. Here, we highlight three pathways that investigators might exploit as sources of signals to construct BASs and their applicability to this framework. The research community will need to forge robust interdisciplinary teams to surmount substantial experimental, technical, and data analytic challenges that stand in the way of our long-term vision. However, if successful, our functionality-based BAS model could present a means to more effectively surveil for and treat known and novel agents alike

Identification of the genetic rearrangement in the suppressor strain.

<p>PCR amplifications were carried out to narrow down the site of possible genetic rearrangement in the <i>rpoE</i>-<i>nadB</i> region of the chromosome. (<b>A</b>, <b>B</b>) Approximate drawings showing the <i>rpoE</i> and <i>nadB</i> genes from the wild-type (<b>A</b>) and suppressor (<b>B</b>) strains, as well as the positions of primers (numbered 1 to 4), their orientations, and size of the amplified DNA fragments. (<b>C</b>) Agarose gels showing the results of PCR amplifications from the wild-type and suppressor strains. Numbers 1 to 4 refer to the primers shown in (<b>A</b>) and (<b>B</b>).</p

The suppressor mutation reverses the vesiculation phenotype of a Δ<i>degP</i> strain.

<p>Cultures were grown at 39°C in Luria broth for five hours, after which membranes and vesicles were prepared as described in the Experimental Procedure section. Samples were analyzed by SDS-PAGE and proteins were visualized after Coomassie blue staining. Abbreviations: mem, membrane; ves, vesicle; <i>sup</i>⁺, the unknown suppressor mutation.</p

Laboratory strains of Bacillus anthracis lose their ability to rapidly grow and sporulate compared to wildlife outbreak strains.

Bacillus anthracis is the causative agent of anthrax in animals and humans. The organism lies in a dormant state in the soil until introduced into an animal via, ingestion, cutaneous inoculation or inhalation. Once in the host, spores germinate into rapidly growing vegetative cells elaborating toxins. When animals die of anthrax, vegetative bacteria sporulate upon nutrient limitation in the carcass or soil while in the presence of air. After release into the soil environment, spores form a localized infectious zone (LIZ) at and around the carcass. Laboratory strains of B. anthracis produce fewer proteins associated with growth and sporulation compared to wild strains isolated from recent zoonotic disease events. We verified wild strains grow more rapidly than lab strains demonstrating a greater responsiveness to nutrient availability. Sporulation was significantly more rapid in these wild strains compared to lab strains, indicating wild strains are able to sporulate faster due to nutrient limitation while laboratory strains have a decrease in the speed at which they utilize nutrients and an increase in time to sporulation. These findings have implications for disease control at the LIZ as well as on the infectious cycle of this dangerous zoonotic pathogen

Effects of Δ<i>degP</i> and <i>rpoE3</i> mutations on RybB::LacZ (A) and CpxP::LacZ (B) activities.

<p>For each strain, two independent cultures were grown at 39°C to a mid-log phase and used for β-galactosidase assays. LacZ activities are relative to the wild-type strain. The relevant genotypes of the strains are labeled at the bottom.</p

Growth curves of bacterial cultures grown at 39°C.

<p>Wild type and Δ<i>degP</i> cells, with or without the suppressor mutation, were grown overnight at 30°C. Next day, overnight cultures were diluted to 1∶100 in flasks containing fresh, pre-warmed, Luria broth and growth was resumed at 30°C and 39°C. OD₆₀₀ was measured from bacterial samples withdrawn every 30 minutes. Only 39°C growth curves, obtained from two independent experiments, are shown. All strains grew almost identically at 30°C.</p

Investigation of Yersinia pestis Laboratory Adaptation through a Combined Genomics and Proteomics Approach

The bacterial pathogen Yersinia pestis, the cause of plague in humans and animals, normally has a sylvatic lifestyle, cycling between fleas and mammals. In contrast, laboratory-grown Y. pestis experiences a more constant environment and conditions that it would not normally encounter. The transition from the natural environment to the laboratory results in a vastly different set of selective pressures, and represents what could be considered domestication. Understanding the kinds of adaptations Y. pestis undergoes as it becomes domesticated will contribute to understanding the basic biology of this important pathogen. In this study, we performed a parallel serial passage experiment (PSPE) to explore the mechanisms by which Y. pestis adapts to laboratory conditions, hypothesizing that cells would undergo significant changes in virulence and nutrient acquisition systems. Two wild strains were serially passaged in 12 independent populations each for ~750 generations, after which each population was analyzed using whole-genome sequencing, LC-MS/MS proteomic analysis, and GC/MS metabolomics. We observed considerable parallel evolution in the endpoint populations, detecting multiple independent mutations in ail, pepA, and zwf, suggesting that specific selective pressures are shaping evolutionary responses. Complementary LC-MS/MS proteomic data provide physiological context to the observed mutations, and reveal regulatory changes not necessarily associated with specific mutations, including changes in amino acid metabolism and cell envelope biogenesis. Proteomic data support hypotheses generated by genomic data in addition to suggesting future mechanistic studies, indicating that future whole-genome sequencing studies be designed to leverage proteomics as a critical complement

Protein abundances can distinguish between naturally-occurring and laboratory strains of <i>Yersinia pestis</i>, the causative agent of plague

<div><p>The rapid pace of bacterial evolution enables organisms to adapt to the laboratory environment with repeated passage and thus diverge from naturally-occurring environmental (“wild”) strains. Distinguishing wild and laboratory strains is clearly important for biodefense and bioforensics; however, DNA sequence data alone has thus far not provided a clear signature, perhaps due to lack of understanding of how diverse genome changes lead to convergent phenotypes, difficulty in detecting certain types of mutations, or perhaps because some adaptive modifications are epigenetic. Monitoring protein abundance, a molecular measure of phenotype, can overcome some of these difficulties. We have assembled a collection of <i>Yersinia pestis</i> proteomics datasets from our own published and unpublished work, and from a proteomics data archive, and demonstrated that protein abundance data can clearly distinguish laboratory-adapted from wild. We developed a lasso logistic regression classifier that uses binary (presence/absence) or quantitative protein abundance measures to predict whether a sample is laboratory-adapted or wild that proved to be ~98% accurate, as judged by replicated 10-fold cross-validation. Protein features selected by the classifier accord well with our previous study of laboratory adaptation in <i>Y</i>. <i>pestis</i>. The input data was derived from a variety of unrelated experiments and contained significant confounding variables. We show that the classifier is robust with respect to these variables. The methodology is able to discover signatures for laboratory facility and culture medium that are largely independent of the signature of laboratory adaptation. Going beyond our previous laboratory evolution study, this work suggests that proteomic differences between laboratory-adapted and wild <i>Y</i>. <i>pestis</i> are general, potentially pointing to a process that could apply to other species as well. Additionally, we show that proteomics datasets (even archived data collected for different purposes) contain the information necessary to distinguish wild and laboratory samples. This work has clear applications in biomarker detection as well as biodefense.</p></div