Competition Between Conjugation and M13 Phage Infection in Escherichia coli in the Absence of Selection Pressure: A Kinetic Study

Inter- and intraspecies horizontal gene transfer enabled by bacterial secretion systems is a powerful mechanism for bacterial genome plasticity. The type IV secretion system of Escherichia coli, encoded by the F plasmid, enables cell-to-cell contact and subsequent DNA transfer known as conjugation. Conjugation is compromised by phage infection that specifically targets the secretion machinery. Hence, the use of phages to regulate the spread of genes, such as acquired antibiotic resistance or as general biosanitation agents, has gained interest. To predict the potential efficacy, the competition kinetics must first be understood. Using quantitative PCR to enumerate genomic loci in a resource-limited batch culture, we quantify the infection kinetics of the nonlytic phage M13 and its impact on conjugation in the absence of selection pressure (isogenic set). Modeling the resulting experimental data reveals the cellular growth rate to be reduced to 60% upon phage infection. We also find a maximum phage infection rate of 3×10−11 mL phage−1 min−1 which is only 1 order of magnitude slower than the maximum conjugation rate (3×10−10 mL cell−1 min−1), suggesting phages must be in significant abundance to be effective antagonists to horizontal gene transfer. In the regime where the number of susceptible cells (F+) and phages are equal upon initial infection, we observe the spread of the conjugative plasmid throughout the cell population despite phage infection, but only at 10% of the uninfected rate. This has interesting evolutionary implications, as even in the absence of selection pressure, cells maintain the ability to conjugate despite phage vulnerability and the associated growth consequences

Discerning Aggregation in Homogeneous Ensembles: A General Description of Photon Counting Spectroscopy in Diffusing Systems

In order to discern aggregation in solutions, we present a quantum mechanical analog of the photon statistics from fluorescent molecules diffusing through a focused beam. A generating functional is developed to fully describe the experimental physical system as well as the statistics. Histograms of the measured time delay between photon counts are fit by an analytical solution describing the static as well as diffusing regimes. To determine empirical fitting parameters, fluorescence correlation spectroscopy is used in parallel to the photon counting. For expedient analysis, we find that the distribution's deviation from a single Poisson shows a difference between two single fluor moments or a double fluor aggregate of the same total intensities. Initial studies were performed on fixed-state aggregates limited to dimerization. However preliminary results on reactive species suggest that the method can be used to characterize any aggregating system.Comment: 30 pages, 5 figure

Harnessing gene expression to identify the genetic basis of drug resistance

The advent of cost-effective genotyping and sequencing methods have recently made it possible to ask questions that address the genetic basis of phenotypic diversity and how natural variants interact with the environment. We developed Camelot (CAusal Modelling with Expression Linkage for cOmplex Traits), a statistical method that integrates genotype, gene expression and phenotype data to automatically build models that both predict complex quantitative phenotypes and identify genes that actively influence these traits. Camelot integrates genotype and gene expression data, both generated under a reference condition, to predict the response to entirely different conditions. We systematically applied our algorithm to data generated from a collection of yeast segregants, using genotype and gene expression data generated under drug-free conditions to predict the response to 94 drugs and experimentally confirmed 14 novel gene–drug interactions. Our approach is robust, applicable to other phenotypes and species, and has potential for applications in personalized medicine, for example, in predicting how an individual will respond to a previously unseen drug

Optimizing Taq Polymerase Concentration for Improved Signal-to-Noise in the Broad Range Detection of Low Abundance Bacteria

BACKGROUND:PCR in principle can detect a single target molecule in a reaction mixture. Contaminating bacterial DNA in reagents creates a practical limit on the use of PCR to detect dilute bacterial DNA in environmental or public health samples. The most pernicious source of contamination is microbial DNA in DNA polymerase preparations. Importantly, all commercial Taq polymerase preparations inevitably contain contaminating microbial DNA. Removal of DNA from an enzyme preparation is problematical. METHODOLOGY/PRINCIPAL FINDINGS:This report demonstrates that the background of contaminating DNA detected by quantitative PCR with broad host range primers can be decreased greater than 10-fold through the simple expedient of Taq enzyme dilution, without altering detection of target microbes in samples. The general method is: For any thermostable polymerase used for high-sensitivity detection, do a dilution series of the polymerase crossed with a dilution series of DNA or bacteria that work well with the test primers. For further work use the concentration of polymerase that gave the least signal in its negative control (H(2)O) while also not changing the threshold cycle for dilutions of spiked DNA or bacteria compared to higher concentrations of Taq polymerase. CONCLUSIONS/SIGNIFICANCE:It is clear from the studies shown in this report that a straightforward procedure of optimizing the Taq polymerase concentration achieved "treatment-free" attenuation of interference by contaminating bacterial DNA in Taq polymerase preparations. This procedure should facilitate detection and quantification with broad host range primers of a small number of bona fide bacteria (as few as one) in a sample

A Unique Combination of Male Germ Cell miRNAs Coordinates Gonocyte Differentiation

The last 100 years have seen a concerning decline in male reproductive health associated with decreased sperm production, sperm function and male fertility. Concomitantly, the incidence of defects in reproductive development, such as undescended testes, hypospadias and testicular cancer has increased. Indeed testicular cancer is now recognised as the most common malignancy in young men. Such cancers develop from the pre-invasive lesion Carcinoma in Situ (CIS), a dysfunctional precursor germ cell or gonocyte which has failed to successfully differentiate into a spermatogonium. It is therefore essential to understand the cellular transition from gonocytes to spermatogonia, in order to gain a better understanding of the aetiology of testicular germ cell tumours. MicroRNA (miRNA) are important regulators of gene expression in differentiation and development and thus highly likely to play a role in the differentiation of gonocytes. In this study we have examined the miRNA profiles of highly enriched populations of gonocytes and spermatogonia, using microarray technology. We identified seven differentially expressed miRNAs between gonocytes and spermatogonia (down-regulated: miR-293, 291a-5p, 290-5p and 294*, up-regulated: miR-136, 743a and 463*). Target prediction software identified many potential targets of several differentially expressed miRNA implicated in germ cell development, including members of the PTEN, and Wnt signalling pathways. These targets converge on the key downstream cell cycle regulator Cyclin D1, indicating that a unique combination of male germ cell miRNAs coordinate the differentiation and maintenance of pluripotency in germ cells

Roadmap on Photovoltaic Absorber Materials for Sustainable Energy Conversion

Photovoltaics (PVs) are a critical technology for curbing growing levels of anthropogenic greenhouse gas emissions, and meeting increases in future demand for low-carbon electricity. In order to fulfil ambitions for net-zero carbon dioxide equivalent (CO2eq) emissions worldwide, the global cumulative capacity of solar PVs must increase by an order of magnitude from 0.9 TWp in 2021 to 8.5 TWp by 2050 according to the International Renewable Energy Agency, which is considered to be a highly conservative estimate. In 2020, the Henry Royce Institute brought together the UK PV community to discuss the critical technological and infrastructure challenges that need to be overcome to address the vast challenges in accelerating PV deployment. Herein, we examine the key developments in the global community, especially the progress made in the field since this earlier roadmap, bringing together experts primarily from the UK across the breadth of the photovoltaics community. The focus is both on the challenges in improving the efficiency, stability and levelized cost of electricity of current technologies for utility-scale PVs, as well as the fundamental questions in novel technologies that can have a significant impact on emerging markets, such as indoor PVs, space PVs, and agrivoltaics. We discuss challenges in advanced metrology and computational tools, as well as the growing synergies between PVs and solar fuels, and offer a perspective on the environmental sustainability of the PV industry. Through this roadmap, we emphasize promising pathways forward in both the short- and long-term, and for communities working on technologies across a range of maturity levels to learn from each other.Comment: 160 pages, 21 figure

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Measuring the Rate of Conjugal Plasmid Transfer in a Bacterial Population Using Quantitative PCR

Horizontal transfer of genes between species is an important mechanism for bacterial genome evolution. In Escherichia coli, conjugation is the transfer from a donor (F+) to a recipient (F−) cell through cell-to-cell contact. We demonstrate what we believe to be a novel qPCR method for quantifying the transfer kinetics of the F plasmid in a population by enumerating the relative abundance of genetic loci unique to the plasmid and the chromosome. This approach allows us to query the plasmid transfer rate without the need for selective culturing with unprecedented single locus resolution. We fit the results to a mass action model where the rate of plasmid growth includes the lag time of newly formed F+ transconjugants and the recovery time between successive conjugation events of the F+ donors. By assaying defined mixtures of genotypically identical donor and recipient cells at constant inoculation densities, we extract an F plasmid transfer rate of 5 × 10−10 (cells/mL · min)−1. We confirm a plasmid/chromosome ratio of 1:1 in homogenous F+ populations throughout batch growth. Surprisingly, in some mixture experiments we observe an excess of F plasmid in the early saturation phase that equilibrates to a final ratio of one plasmid per chromosome

Approximating the copy number of 16S rDNA in commercial Taq polymerases.

<p>Six DNA polymerases were used with primers for 16S rDNA on 7 serial 10-fold dilutions of E. coli genomic DNA (10 ng to 10 fg) with no added DNA in the 8^th sample. The least squares fit equation for each dilution series was used to assign a value to the signal from the 8^th sample, which contains Taq-associated DNA only. The efficiency of the reaction was determined from the slope of the linear fit plotting the base10 log of the DNA concentration vs. the threshold cycle. A slope of −3.322 indicates an average doubling rate of “2,” which is approximately 100% efficiency (2̂3.322∼10). The rDNA values assigned are for “E. coli equivalents.”</p