Elucidation of the RamA Regulon in Klebsiella pneumoniae Reveals a Role in LPS Regulation

Klebsiella pneumoniae is a significant human pathogen, in part due to high rates of multidrug resistance. RamA is an intrinsic regulator in K. pneumoniae established to be important for the bacterial response to antimicrobial challenge; however, little is known about its possible wider regulatory role in this organism during infection. In this work, we demonstrate that RamA is a global transcriptional regulator that significantly perturbs the transcriptional landscape of K. pneumoniae, resulting in altered microbe-drug or microbe-host response. This is largely due to the direct regulation of 68 genes associated with a myriad of cellular functions. Importantly, RamA directly binds and activates the lpxC, lpxL-2 and lpxO genes associated with lipid A biosynthesis, thus resulting in modifications within the lipid A moiety of the lipopolysaccharide. RamA-mediated alterations decrease susceptibility to colistin E, polymyxin B and human cationic antimicrobial peptide LL-37. Increased RamA levels reduce K. pneumoniae adhesion and uptake into macrophages, which is supported by in vivo infection studies, that demonstrate increased systemic dissemination of ramA overexpressing K. pneumoniae. These data establish that RamA-mediated regulation directly perturbs microbial surface properties, including lipid A biosynthesis, which facilitate evasion from the innate host response. This highlights RamA as a global regulator that confers pathoadaptive phenotypes with implications for our understanding of the pathogenesis of Enterobacter, Salmonella and Citrobacter spp. that express orthologous RamA proteins

Dominant Role of Nucleotide Substitution in the Diversification of Serotype 3 Pneumococci over Decades and during a Single Infection

Streptococcus pneumoniae of serotype 3 possess a mucoid capsule and cause disease associated with high mortality rates relative to other pneumococci. Phylogenetic analysis of a complete reference genome and 81 draft sequences from clonal complex 180, the predominant serotype 3 clone in much of the world, found most sampled isolates belonged to a clade affected by few diversifying recombinations. However, other isolates indicate significant genetic variation has accumulated over the clonal complex’s entire history. Two closely related genomes, one from the blood and another from the cerebrospinal fluid, were obtained from a patient with meningitis. The pair differed in their behaviour in a mouse model of disease and in their susceptibility to antimicrobials, with at least some of these changes attributable to a mutation that upregulated the patAB efflux pump. This indicates clinically important phenotypic variation can accumulate rapidly through small alterations to the genotype

The secondary resistome of multidrug-resistant Klebsiella pneumoniae.

Klebsiella pneumoniae causes severe lung and bloodstream infections that are difficult to treat due to multidrug resistance. We hypothesized that antimicrobial resistance can be reversed by targeting chromosomal non-essential genes that are not responsible for acquired resistance but essential for resistant bacteria under therapeutic concentrations of antimicrobials. Conditional essentiality of individual genes to antimicrobial resistance was evaluated in an epidemic multidrug-resistant clone of K. pneumoniae (ST258). We constructed a high-density transposon mutant library of >430,000 unique Tn5 insertions and measured mutant depletion upon exposure to three clinically relevant antimicrobials (colistin, imipenem or ciprofloxacin) by Transposon Directed Insertion-site Sequencing (TraDIS). Using this high-throughput approach, we defined three sets of chromosomal non-essential genes essential for growth during exposure to colistin (n = 35), imipenem (n = 1) or ciprofloxacin (n = 1) in addition to known resistance determinants, collectively termed the "secondary resistome". As proof of principle, we demonstrated that inactivation of a non-essential gene not previously found linked to colistin resistance (dedA) restored colistin susceptibility by reducing the minimum inhibitory concentration from 8 to 0.5 μg/ml, 4-fold below the susceptibility breakpoint (S ≤ 2 μg/ml). This finding suggests that the secondary resistome is a potential target for developing antimicrobial "helper" drugs that restore the efficacy of existing antimicrobials

A simple method for directional transcriptome sequencing using Illumina technology.

High-throughput sequencing of cDNA has been used to study eukaryotic transcription on a genome-wide scale to single base pair resolution. In order to compensate for the high ribonuclease activity in bacterial cells, we have devised an equivalent technique optimized for studying complete prokaryotic transcriptomes that minimizes the manipulation of the RNA sample. This new approach uses Illumina technology to sequence single-stranded (ss) cDNA, generating information on both the direction and level of transcription throughout the genome. The protocol, and associated data analysis programs, are freely available from http://www.sanger.ac.uk/Projects/Pathogens/Transcriptome/. We have successfully applied this method to the bacterial pathogens Salmonella bongori and Streptococcus pneumoniae and the yeast Schizosaccharomyces pombe. This method enables experimental validation of genetic features predicted in silico and allows the easy identification of novel transcripts throughout the genome. We also show that there is a high correlation between the level of gene expression calculated from ss-cDNA and double-stranded-cDNA sequencing, indicting that ss-cDNA sequencing is both robust and appropriate for use in quantitative studies of transcription. Hence, this simple method should prove a useful tool in aiding genome annotation and gene expression studies in both prokaryotes and eukaryotes

Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms

Importance: Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography screening accuracy by reducing missed cancers and false positives. Objective: To evaluate whether AI can overcome human mammography interpretation limitations with a rigorous, unbiased evaluation of machine learning algorithms. Design, Setting, and Participants: In this diagnostic accuracy study conducted between September 2016 and November 2017, an international, crowdsourced challenge was hosted to foster AI algorithm development focused on interpreting screening mammography. More than 1100 participants comprising 126 teams from 44 countries participated. Analysis began November 18, 2016. Main Outcomes and Measurements: Algorithms used images alone (challenge 1) or combined images, previous examinations (if available), and clinical and demographic risk factor data (challenge 2) and output a score that translated to cancer yes/no within 12 months. Algorithm accuracy for breast cancer detection was evaluated using area under the curve and algorithm specificity compared with radiologists' specificity with radiologists' sensitivity set at 85.9% (United States) and 83.9% (Sweden). An ensemble method aggregating top-performing AI algorithms and radiologists' recall assessment was developed and evaluated. Results: Overall, 144 231 screening mammograms from 85 580 US women (952 cancer positive ≤12 months from screening) were used for algorithm training and validation. A second independent validation cohort included 166 578 examinations from 68 008 Swedish women (780 cancer positive). The top-performing algorithm achieved an area under the curve of 0.858 (United States) and 0.903 (Sweden) and 66.2% (United States) and 81.2% (Sweden) specificity at the radiologists' sensitivity, lower than community-practice radiologists' specificity of 90.5% (United States) and 98.5% (Sweden). Combining top-performing algorithms and US radiologist assessments resulted in a higher area under the curve of 0.942 and achieved a significantly improved specificity (92.0%) at the same sensitivity. Conclusions and Relevance: While no single AI algorithm outperformed radiologists, an ensemble of AI algorithms combined with radiologist assessment in a single-reader screening environment improved overall accuracy. This study underscores the potential of using machine learning methods for enhancing mammography screening interpretation

Distinct Salmonella Enteritidis lineages associated with enterocolitis in high-income settings and invasive disease in low-income settings.

An epidemiological paradox surrounds Salmonella enterica serovar Enteritidis. In high-income settings, it has been responsible for an epidemic of poultry-associated, self-limiting enterocolitis, whereas in sub-Saharan Africa it is a major cause of invasive nontyphoidal Salmonella disease, associated with high case fatality. By whole-genome sequence analysis of 675 isolates of S. Enteritidis from 45 countries, we show the existence of a global epidemic clade and two new clades of S. Enteritidis that are geographically restricted to distinct regions of Africa. The African isolates display genomic degradation, a novel prophage repertoire, and an expanded multidrug resistance plasmid. S. Enteritidis is a further example of a Salmonella serotype that displays niche plasticity, with distinct clades that enable it to become a prominent cause of gastroenteritis in association with the industrial production of eggs and of multidrug-resistant, bloodstream-invasive infection in Africa.This work was supported by the Wellcome Trust. We would like to thank the members of the Pathogen Informatics Team and the core sequencing teams at the Wellcome Trust Sanger Institute (Cambridge, UK). We are grateful to D. Harris for work in managing the sequence data

Elucidation of the RamA Regulon in Klebsiella pneumoniae Reveals a Role in LPS Regulation

Klebsiella pneumoniae is a significant human pathogen, in part due to high rates of multidrug resistance. RamA is an intrinsic regulator in K. pneumoniae established to be important for the bacterial response to antimicrobial challenge; however, little is known about its possible wider regulatory role in this organism during infection. In this work, we demonstrate that RamA is a global transcriptional regulator that significantly perturbs the transcriptional landscape of K. pneumoniae, resulting in altered microbe-drug or microbe-host response. This is largely due to the direct regulation of 68 genes associated with a myriad of cellular functions. Importantly, RamA directly binds and activates the lpxC, lpxL-2 and lpxO genes associated with lipid A biosynthesis, thus resulting in modifications within the lipid A moiety of the lipopolysaccharide. RamA-mediated alterations decrease susceptibility to colistin E, polymyxin B and human cationic antimicrobial peptide LL-37. Increased RamA levels reduce K. pneumoniae adhesion and uptake into macrophages, which is supported by in vivo infection studies, that demonstrate increased systemic dissemination of ramA overexpressing K. pneumoniae. These data establish that RamA-mediated regulation directly perturbs microbial surface properties, including lipid A biosynthesis, which facilitate evasion from the innate host response. This highlights RamA as a global regulator that confers pathoadaptive phenotypes with implications for our understanding of the pathogenesis of Enterobacter, Salmonella and Citrobacter spp. that express orthologous RamA proteins