Application of WGS data for O-specific antigen analysis and <i>in silico </i>serotyping of <i>Pseudomonas aeruginosa </i>isolates

Accurate typing methods are required for efficient infection control. The emergence of whole-genome sequencing (WGS) technologies has enabled the development of genome-based methods applicable for routine typing and surveillance of bacterial pathogens. In this study, we developed the Pseudomonas aeruginosa serotyper (PAst) program, which enabled in silico serotyping of P. aeruginosa isolates using WGS data. PAst has been made publically available as a web service and aptly facilitates high-throughput serotyping analysis. The program overcomes critical issues such as the loss of in vitro typeability often associated with P. aeruginosa isolates from chronic infections and quickly determines the serogroup of an isolate based on the sequence of the O-specific antigen (OSA) gene cluster. Here, PAst analysis of 1,649 genomes resulted in successful serogroup assignments in 99.27% of the cases. This frequency is rarely achievable by conventional serotyping methods. The limited number of nontypeable isolates found using PAst was the result of either a complete absence of OSA genes in the genomes or the artifact of genomic misassembly. With PAst, P. aeruginosa serotype data can be obtained from WGS information alone. PAst is a highly efficient alternative to conventional serotyping methods in relation to outbreak surveillance of serotype O12 and other high-risk clones, while maintaining backward compatibility to historical serotype data

Genetic and Functional Diversity of Pseudomonas aeruginosa Lipopolysaccharide

Lipopolysccharide (LPS) is an integral component of the Pseudomonas aeruginosa cell envelope, occupying the outer leaflet of the outer membrane in this Gram-negative opportunistic pathogen. It is important for bacterium–host interactions and has been shown to be a major virulence factor for this organism. Structurally, P. aeruginosa LPS is composed of three domains, namely, lipid A, core oligosaccharide, and the distal O antigen (O-Ag). Most P. aeruginosa strains produce two distinct forms of O-Ag, one a homopolymer of D-rhamnose that is a common polysaccharide antigen (CPA, formerly termed A band), and the other a heteropolymer of three to five distinct (and often unique dideoxy) sugars in its repeat units, known as O-specific antigen (OSA, formerly termed B band). Compositional differences in the O units among the OSA from different strains form the basis of the International Antigenic Typing Scheme for classification via serotyping of different strains of P. aeruginosa. The focus of this review is to provide state-of-the-art knowledge on the genetic and resultant functional diversity of LPS produced by P. aeruginosa. The underlying factors contributing to this diversity will be thoroughly discussed and presented in the context of its contributions to host–pathogen interactions and the control/prevention of infection

The Widespread Multidrug-Resistant Serotype O12 <i>Pseudomonas aeruginosa</i> Clone Emerged through Concomitant Horizontal Transfer of Serotype Antigen and Antibiotic Resistance Gene Clusters

The O-specific antigen (OSA) in Pseudomonas aeruginosa lipopolysaccharide is highly varied by sugar identity, side chains, and bond between O-repeats. These differences classified P. aeruginosa into 20 distinct serotypes. In the past few decades, O12 has emerged as the predominant serotype in clinical settings and outbreaks. These serotype O12 isolates exhibit high levels of resistance to various classes of antibiotics. Here, we explore how the P. aeruginosa OSA biosynthesis gene clusters evolve in the population by investigating the association between the phylogenetic relationships among 83 P. aeruginosa strains and their serotypes. While most serotypes were closely linked to the core genome phylogeny, we observed horizontal exchange of OSA biosynthesis genes among phylogenetically distinct P. aeruginosa strains. Specifically, we identified a “serotype island” ranging from 62 kb to 185 kb containing the P. aeruginosa O12 OSA gene cluster, an antibiotic resistance determinant (gyrA(C248T)), and other genes that have been transferred between P. aeruginosa strains with distinct core genome architectures. We showed that these genes were likely acquired from an O12 serotype strain that is closely related to P. aeruginosa PA7. Acquisition and recombination of the “serotype island” resulted in displacement of the native OSA gene cluster and expression of the O12 serotype in the recipients. Serotype switching by recombination has apparently occurred multiple times involving bacteria of various genomic backgrounds. In conclusion, serotype switching in combination with acquisition of an antibiotic resistance determinant most likely contributed to the dissemination of the O12 serotype in clinical settings

Semen May Harbor HIV Despite Effective HAART: Another Piece in the Puzzle

The risk of male-to-female intravaginal HIV-1 transmission is estimated at about 1 event per 200–2000 coital acts. The aim of this study was to assess the residual risk of HIV presence in semen in patients under HAART therapy.The study took place in France from October 2001 to March 2009. 394 paired blood and semen samples were provided from 332 HIV-1 infected men. The Roche Cobas AMPLICOR Monitor HIV assay was used to quantify HIV-1 RNA in blood and in seminal plasma. Three percent of 394 HIV-1 infected men enrolled in an assisted reproductive technology program harbored detectable HIV-1 RNA in semen, although they had no other sexually transmitted disease and their blood viral load was undetectable for at least 6 months under antiretroviral treatment.These data suggest that undetectable plasma HIV RNA means a lower risk of viral transmission through seminal fluid on a population level, but not necessarily at the level of the individual

Spectroscopic verification of very luminous galaxy candidates in the early universe

During the first 500 million years of cosmic history, the first stars and galaxies formed and seeded the cosmos with heavy elements. These early galaxies illuminated the transition from the cosmic "dark ages" to the reionization of the intergalactic medium. This transitional period has been largely inaccessible to direct observation until the recent commissioning of JWST, which has extended our observational reach into that epoch. Excitingly, the first JWST science observations uncovered a surprisingly high abundance of early star-forming galaxies. However, the distances (redshifts) of these galaxies were, by necessity, estimated from multi-band photometry. Photometric redshifts, while generally robust, can suffer from uncertainties and/or degeneracies. Spectroscopic measurements of the precise redshifts are required to validate these sources and to reliably quantify their space densities, stellar masses, and star formation rates, which provide powerful constraints on galaxy formation models and cosmology. Here we present the results of JWST follow-up spectroscopy of a small sample of galaxies suspected to be amongst the most distant yet observed. We confirm redshifts z > 10 for two galaxies, including one of the first bright JWST-discovered candidates with z = 11.4, and show that another galaxy with suggested z ~ 16 instead has z = 4.9, with strong emission lines that mimic the expected colors of more distant objects. These results reinforce the evidence for the rapid production of luminous galaxies in the very young Universe, while also highlighting the necessity of spectroscopic verification for remarkable candidates.Comment: Submitted to Natur

CEERS Key Paper. V. Galaxies at 4 &lt; z &lt; 9 Are Bluer than They Appear-Characterizing Galaxy Stellar Populations from Rest-frame ∼1 μm Imaging

We present results from the Cosmic Evolution Early Release Survey on the stellar population parameters for 28 galaxies with redshifts 4 &lt; z &lt; 9 using imaging data from the James Webb Space Telescope (JWST) Mid-Infrared Instrument (MIRI) combined with data from the Hubble Space Telescope and the Spitzer Space Telescope. The JWST/MIRI 5.6 and 7.7 μm data extend the coverage of the rest-frame spectral energy distribution to nearly 1 μm for galaxies in this redshift range. By modeling the galaxies’ SEDs the MIRI data show that the galaxies have, on average, rest-frame UV (1600 Å)—I-band colors 0.4 mag bluer than derived when using photometry that lacks MIRI. Therefore, the galaxies have lower ratios of stellar mass to light. The MIRI data reduce the stellar masses by 〈 Δ log M * 〉 = 0.25 dex at 4 &lt; z &lt; 6 and 0.37 dex at 6 &lt; z &lt; 9. This also reduces the star formation rates (SFRs) by 〈ΔlogSFR〉 = 0.14 dex at 4 &lt; z &lt; 6 and 0.27 dex at 6 &lt; z &lt; 9. The MIRI data also improve constraints on the allowable stellar mass formed in early star formation. We model this using a star formation history that includes both a “burst” at z f = 100 and a slowly varying (“delayed-τ”) model. The MIRI data reduce the allowable stellar mass by 0.6 dex at 4 &lt; z &lt; 6 and by ≈1 dex at 6 &lt; z &lt; 9. Applying these results globally, this reduces the cosmic stellar-mass density by an order of magnitude in the early Universe (z ≈ 9). Therefore, observations of rest-frame ≳1 μm are paramount for constraining the stellar-mass buildup in galaxies at very high redshifts.</p

CEERS Key Paper IV: Galaxies at 4<z<94 < z < 9 are Bluer than They Appear -- Characterizing Galaxy Stellar Populations from Rest-Frame ∼1\sim 1 micron Imaging

We present results from the Cosmic Evolution Early Release Survey (CEERS) on the stellar-population parameters for 28 galaxies with redshifts $4<z<9$ using imaging data from the James Webb Space Telescope (JWST) Mid-Infrared Instrument (MIRI) combined with data from the Hubble Space Telescope and the Spitzer Space Telescope. The JWST/MIRI 5.6 and 7.7 $\mu$m data extend the coverage of the rest-frame spectral-energy distribution (SED) to nearly 1 micron for galaxies in this redshift range. By modeling the galaxies' SEDs the MIRI data show that the galaxies have, on average, rest-frame UV (1600 \r{A}) $-$ $I$-band colors 0.4 mag bluer than derived when using photometry that lacks MIRI. Therefore, the galaxies have lower (stellar)-mass-to-light ratios. The MIRI data reduce the stellar masses by $\langle \Delta\log M_\ast\rangle=0.25$ dex at $4<z<6$ (a factor of 1.8) and 0.37 dex at $6<z<9$ (a factor of 2.3). This also reduces the star-formation rates (SFRs) by $\langle \Delta\log\mathrm{SFR} \rangle=0.14$ dex at $4<z<6$ and 0.27 dex at $6<z<9$. The MIRI data also improve constraints on the allowable stellar mass formed in early star-formation. We model this using a star-formation history that includes both a "burst' at $z_f=100$ and a slowly varying ("delayed-$\tau$") model. The MIRI data reduce the allowable stellar mass by 0.6 dex at $4<z< 6$ and by $\approx$1 dex at $6<z<9$. Applying these results globally, this reduces the cosmic stellar-mass density by an order of magnitude in the early universe ($z\approx9$). Therefore, observations of rest-frame $\gtrsim$1 $\mu$m are paramount for constraining the stellar-mass build-up in galaxies at very high-redshifts.Comment: Updated with accepted ApJ version. Part of the CEERS Focus Issue. 27 pages, many figures (4 Figure Sets, available upon reasonable request

Importance of pre-analytical steps for transcriptome and RT-qPCR analyses in the context of the phase II randomised multicentre trial REMAGUS02 of neoadjuvant chemotherapy in breast cancer patients

<p>Abstract</p> <p>Background</p> <p>Identification of predictive markers of response to treatment is a major objective in breast cancer. A major problem in clinical sampling is the variability of RNA templates, requiring accurate management of tumour material and subsequent analyses for future translation in clinical practice. Our aim was to establish the feasibility and reliability of high throughput RNA analysis in a prospective trial.</p> <p>Methods</p> <p>This study was conducted on RNA from initial biopsies, in a prospective trial of neoadjuvant chemotherapy in 327 patients with inoperable breast cancer. Four independent centres included patients and samples. Human U133 GeneChips plus 2.0 arrays for transcriptome analysis and quantitative RT-qPCR of 45 target genes and 6 reference genes were analysed on total RNA.</p> <p>Results</p> <p>Thirty seven samples were excluded because <it>i) </it>they contained less than 30% malignant cells, or <it>ii) </it>they provided RNA Integrity Number (RIN) of poor quality. Among the 290 remaining cases, taking into account strict quality control criteria initially defined to ensure good quality of sampling, 78% and 82% samples were eligible for transcriptome and RT-qPCR analyses, respectively. For RT-qPCR, efficiency was corrected by using standard curves for each gene and each plate. It was greater than 90% for all genes. Clustering analysis highlighted relevant breast cancer phenotypes for both techniques (ER+, PR+, HER2+, triple negative). Interestingly, clustering on trancriptome data also demonstrated a "centre effect", probably due to the sampling or extraction methods used in on of the centres. Conversely, the calibration of RT-qPCR analysis led to the centre effect withdrawing, allowing multicentre analysis of gene transcripts with high accuracy.</p> <p>Conclusions</p> <p>Our data showed that strict quality criteria for RNA integrity assessment and well calibrated and standardized RT-qPCR allows multicentre analysis of genes transcripts with high accuracy in the clinical context. More stringent criteria are needed for transcriptome analysis for clinical applications.</p