Analysis of the Legionella longbeachae Genome and Transcriptome Uncovers Unique Strategies to Cause Legionnaires' Disease

Legionella pneumophila and L. longbeachae are two species of a large genus of bacteria that are ubiquitous in nature. L. pneumophila is mainly found in natural and artificial water circuits while L. longbeachae is mainly present in soil. Under the appropriate conditions both species are human pathogens, capable of causing a severe form of pneumonia termed Legionnaires' disease. Here we report the sequencing and analysis of four L. longbeachae genomes, one complete genome sequence of L. longbeachae strain NSW150 serogroup (Sg) 1, and three draft genome sequences another belonging to Sg1 and two to Sg2. The genome organization and gene content of the four L. longbeachae genomes are highly conserved, indicating strong pressure for niche adaptation. Analysis and comparison of L. longbeachae strain NSW150 with L. pneumophila revealed common but also unexpected features specific to this pathogen. The interaction with host cells shows distinct features from L. pneumophila, as L. longbeachae possesses a unique repertoire of putative Dot/Icm type IV secretion system substrates, eukaryotic-like and eukaryotic domain proteins, and encodes additional secretion systems. However, analysis of the ability of a dotA mutant of L. longbeachae NSW150 to replicate in the Acanthamoeba castellanii and in a mouse lung infection model showed that the Dot/Icm type IV secretion system is also essential for the virulence of L. longbeachae. In contrast to L. pneumophila, L. longbeachae does not encode flagella, thereby providing a possible explanation for differences in mouse susceptibility to infection between the two pathogens. Furthermore, transcriptome analysis revealed that L. longbeachae has a less pronounced biphasic life cycle as compared to L. pneumophila, and genome analysis and electron microscopy suggested that L. longbeachae is encapsulated. These species-specific differences may account for the different environmental niches and disease epidemiology of these two Legionella species

Role of Legionella pneumophila F-box proteins in modulating host cell functions

PARIS-BIUSJ-Physique recherche (751052113) / SudocSudocFranceF

Formal consensus method to evaluate the conformity of prescription of a recently approved chemotherapy treatment in an observatory study.

Cabazitaxel is a second line chemotherapy drug recently approved for the treatment of metastatic castration-resistant prostate cancer. A first panel of French experts and a second independent panel of European experts were convened to assess the conformity of prescription of cabazitaxel with a Delphi consensus method. A two-round modified Delphi consensus process was conducted. This methodology is based on experts' opinion obtained in a systematic manner. The process was divided into five steps: (i) elaboration of the questionnaire, (ii) rating, (iii) analysis, (iv) discussion of the points with absence of consensus following rating of the questionnaire, and (v) final reporting. Consensus was defined according to RAND method and all analyses were conducted according to the same methodology. At the end of the two rounds of rating and a synthesis meeting, of the 26 items included in the Summary of Product Characteristics (SPC), 11 items were judged appropriate with strong consensus by the two independent panels of experts. These items can therefore be considered of prime importance to evaluate conformity of cabazitaxel prescription in the context of observatory studies as well as in further clinical trials using this new taxane. Our findings further provide important evidence about the value of the Delphi consensus and highlight a requirement for "conformity" standards to assist practitioners in a safe chemotherapy drug prescription

Type 3 secretion effectors

Enterohemorrhagic E. coli (EHEC), enteropathogenic E. coli (EPEC), and Shigella use a type 3 secretion system (T3SS) to inject dozens of effector proteins into the host cell. The effectors manipulate host cell processes including the host cytoskeleton, immune response, cell survival, and gut integrity. EPEC and EHEC share a large number of common effectors and some homologous effectors can be found in Shigella, however there is also considerable variability within and between pathotypes. For many effectors detailed molecular mechanisms of action have been described by identifying host interacting partners, homologous proteins, or enzymatic activities. However, understanding effector biology within the context of infection with multiple effectors, various cell populations, and host genetic differences remains a challenge

Flowchart.

<p>Flowchart.</p

Population variation in NAIP functional copy number confers increased cell death upon Legionella pneumophila infection.

International audienceThe NAIP gene encodes an intracellular innate immunity receptor that senses flagellin. The genomic region containing NAIP presents a complex genomic organization and includes various NAIP paralogs. Here, we assessed the degree of copy number variation of the complete NAIP gene (NAIPFull) in various human populations and studied the functional impact of such variation on host cell fate using Legionella pneumophila as an infection model. We determined that African populations have a NAIPFull duplication at a higher frequency than Europeans and Asians, with an increased transcription of the gene. In addition, we demonstrated that a higher amount of the NAIPFull protein dramatically increases cell death upon infection by L. pneumophila, a mechanism that may account for increased host resistance to infection. We postulate that the NAIPFull gene duplication might have been evolutionary maintained, or even selected for, because it may confer an advantage to the host against flagellated bacteria

Impact of Bacterial Vaginosis on Perineal Tears during Delivery: A Prospective Cohort Study

International audienceOBJECTIVE: Long term effects of perineal tears pose a major worldwide health issue for women during delivery. Since bacterial vaginosis is related to major obstacles in obstetrics the aim of this study was to determine the relationship between bacterial vaginosis and the occurrence of perineal tears during vaginal delivery.METHODS: Between June 2013 and December 2013 pregnant women delivering after 37 weeks were recruited at one University hospital / tertiary care referral center in the course of this single-center, prospective cohort study. Bacterial vaginosis was assessed according to Nugent score method. Logistic-regression model was used to estimate odds ratios, adjusted for other risk factors to test the relationship between bacterial vaginosis and the occurrence of 1st to 4th degree perineal tears in women undergoing vaginal delivery.RESULTS: A total of 728 woman were included, 662 analyzed with a complete Nugent Score of the vaginal swab. The prevalence of 1st to 4th degree perineal tears was 35.8% (95% Confidence Interval (95%CI) = [32.2; 39.6]). The presence of BV was not significantly associated to the incidence of perineal tears neither in the univariate analysis (crude Odds Ratio = 1.43; 95%CI = [0.79; 2.60]; p = 0.235) nor in the multivariate analysis (adjusted Odds Ratio = 1.65; 95%CI = [0.81; 3.36]; p = 0.167). Instrumental delivery was the most important risk factor for perineal lacerations.CONCLUSIONS: There is no evidence that vaginosis is a risk factor for vaginal tears.TRIAL REGISTRATION: ClinicalTrials.gov N° NCT01822782

Nugent scoring system.

<p>Morphotypes are scored as the average number seen per oil immersion field (Note that less weight is given to curved Gram-variable rods). Total score = lactobacilli + <i>G</i>. <i>vaginalis</i> and Bacteroides + curved rods. 0 = No morphotypes present; 1 = <1 morphotype present; 2 = 1 to 4 morphotypes present; 3 = 5 to 30 morphotypes present; 4 = 30 or more morphotypes present.</p><p>Nugent scoring system.</p

Baseline data of non-analysed and analysed population within the study population (n = 728).

<p>BMI, Body Mass Index.</p><p>* mean ± standard deviation.</p><p>^$ n (%).</p><p>^¤ median [25^th percentile − 75^th percentile]</p><p>Baseline data of non-analysed and analysed population within the study population (n = 728).</p