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Abstract Background The emergence of carbapenemase-producing (CP) Citrobacter freundii poses a significant threat to public health, especially in high-risk populations. In this study, whole genome sequencing was used to characterize the carbapenem resistance mechanism of three C. freundii clinical isolates recovered from fecal samples of patients with acute leukemia (AL) from Spain. Materials and methods Twelve fecal samples, collected between 2013 and 2015 from 9 patients with AL, were screened for the presence of CP strains by selecting them on MacConkey agar supplemented with ertapenem (0.5 mg/L). Bacteria were identified by MALDI-TOF mass spectrometry and were phenotypically characterized. Whole genome sequencing of C. freundii isolates was performed using the MinION and MiSeq Illumina sequencers. Bioinformatic analysis was performed in order to identify the molecular support of carbapenem resistance and to study the genetic environment of carbapenem resistance encoding genes. Results Three carbapenem-resistant C. freundii strains (imipenem MIC≥32 mg/L) corresponding to three different AL patients were isolated. Positive modified Carba NP test results suggested carbapenemase production. The genomes of each C. freundii tested were assembled into a single chromosomal contig and plasmids contig. In all the strains, the carbapenem resistance was due to the coproduction of OXA-48 and VIM-1 enzymes encoded by genes located on chromosome and on an IncHI2 plasmid, respectively. According to the MLST and the SNPs analysis, all strains belonged to the same clone ST169. Conclusion We report in our study, the intestinal carrying of C. freundii clone ST169 coproducing OXA-48 and VIM-1 identified in leukemic patients.

The microbiome has a strong impact on human health and disease and is, therefore, increasingly studied in a clinical context. Metaproteomics is also attracting considerable attention, and such data can be efficiently generated today owing to improvements in mass spectrometry-based proteomics. As we will discuss in this study, there are still major challenges notably in data analysis that need to be overcome. Here, we analyzed 212 fecal samples from 56 hospitalized acute leukemia patients with multidrug-resistant Enterobactericeae (MRE) gut colonization using metagenomics and metaproteomics. This is one of the largest clinical metaproteomic studies to date, and the first metaproteomic study addressing the gut microbiome in MRE colonized acute leukemia patients. Based on this substantial data set, we discuss major current limitations in clinical metaproteomic data analysis to provide guidance to researchers in the field. Notably, the results show that public metagenome databases are incomplete and that sample-specific metagenomes improve results. Furthermore, biological variation is tremendous which challenges clinical study designs and argues that longitudinal measurements of individual patients are a valuable future addition to the analysis of patient cohorts.

BackgroundFollowing the initial acute phase of COVID-19, health care resource use has escalated among individuals with SARS-CoV-2 infection. ObjectiveThis study aimed to compare new diagnoses of long COVID and the demand for health services in the general population after the Omicron wave with those observed during the pre-Omicron waves, using similar assessment protocols for both periods and to analyze the influence of vaccination. MethodsThis matched retrospective case-control study included patients of both sexes diagnosed with acute SARS-CoV-2 infection using reverse transcription polymerase chain reaction or antigen tests in the hospital microbiology laboratory during the pandemic period regardless of whether the patients were hospitalized. We included patients of all ages from 2 health care departments that cover 604,000 subjects. The population was stratified into 2 groups, youths (

Multidrug-resistant Enterobacteriaceae (MRE) represent a major threat for patients’ health. Here, the authors describe how cooperation between gut commensal bacteria (Lactobacillus spp. And Clostridiales) restrict MRE colonization in mice and patients

IntroductionDevelopment of Robust and Innovative Vaccine Effectiveness (DRIVE) was a European public–private partnership (PPP) that aimed to provide annual, brand-specific estimates of influenza vaccine effectiveness (IVE) for regulatory and public health purposes. DRIVE was launched in 2017 under the umbrella of the Innovative Medicines Initiative (IMI) and conducted IVE studies from its pilot season in 2017–2018 to its final season in 2021–2022.MethodsIn 2021–2022, DRIVE conducted four primary care-based test-negative design (TND) studies (Austria, Italy, Iceland, and England; involving >1,000 general practitioners), nine hospital-based TND studies (France, Iceland, Italy, Romania, and Spain, for a total of 21 hospitals), and one population-based cohort study in Finland. In the TND studies, patients with influenza-like illness (primary care) or severe acute respiratory infection (hospital) were enrolled, and laboratory tested for influenza using RT-PCR. Study contributor-specific IVE was calculated using logistic regression, adjusting for age, sex, and calendar time, and pooled by meta-analysis.ResultsIn 2021–2022, pooled confounder-adjusted influenza vaccine effectiveness (IVE) estimates against laboratory-confirmed influenza (LCI) overall and per type and subtype/lineage was produced, albeit with wide confidence intervals (CI). The limited circulation of influenza in Europe did not allow the network to reach the optimal sample size to produce precise IVE estimates for all the brands included. The most significant IVE estimates were 76% (95% CI 23%−93%) for any vaccine and 81% (22%−95%) for Vaxigrip Tetra in adults ≥65 years old and 64% (25%−83%) for Fluenz Tetra in children (TND primary care setting), 85% (12%−97%) for any vaccine in adults 18–64 years (TND hospital setting), and 38% (1%−62%) in children 6 months−6 years (population-based cohort, mixed setting).DiscussionOver five seasons, DRIVE collected data on >35,000 patients, more than 60 variables, and 13 influenza vaccines. DRIVE demonstrated that estimating brand-specific IVE across Europe is possible, but achieving sufficient sample size to obtain precise estimates for all relevant stratifications remains a challenge. Finally, DRIVE's network of study contributors and lessons learned have greatly contributed to the development of the COVID-19 vaccine effectiveness platform COVIDRIVE.

Transmission is a driver of tuberculosis (TB) epidemics in high-burden regions, with assumed negligible impact in low-burden areas. However, we still lack a full characterization of transmission dynamics in settings with similar and different burdens. Genomic epidemiology can greatly help to quantify transmission, but the lack of whole genome sequencing population-based studies has hampered its application. Here, we generate a population-based dataset from Valencia region and compare it with available datasets from different TB-burden settings to reveal transmission dynamics heterogeneity and its public health implications. We sequenced the whole genome of 785 Mycobacterium tuberculosis strains and linked genomes to patient epidemiological data. We use a pairwise distance clustering approach and phylodynamic methods to characterize transmission events over the last 150 years, in different TB-burden regions. Our results underscore significant differences in transmission between low-burden TB settings, i.e., clustering in Valencia region is higher (47.4%) than in Oxfordshire (27%), and similar to a high-burden area as Malawi (49.8%). By modeling times of the transmission links, we observed that settings with high transmission rate are associated with decades of uninterrupted transmission, irrespective of burden. Together, our results reveal that burden and transmission are not necessarily linked due to the role of past epidemics in the ongoing TB incidence, and highlight the need for in-depth characterization of transmission dynamics and specifically tailored TB control strategies.

Abstract Incidence of pneumococcal disease has increased worldwide in recent years. Response to pneumococcal vaccine is usually measured using the multiserotype enzyme-linked immunosorbent assay (ELISA) pneumococcal test. However, this approach presents several limitations. Therefore, the introduction of new and more robust analytical approaches able to provide information on the efficacy of the pneumococcal vaccine would be very beneficial for the clinical management of patients. Surface plasmon resonance (SPR) has been shown to offer a valuable understanding of vaccines’ properties over the last years. The aim of this study is to evaluate the reliability of SPR for the anti-pneumococcal capsular polysaccharides (anti-PnPs) IgGs quantification in vaccinated. Fast protein liquid chromatography (FPLC) was used for the isolation of total IgGs from serum samples of vaccinated patients. Binding-SPR assays were performed to study the interaction between anti-PnPs IgGs and PCV13. A robust correlation was found between serum levels of anti-PnPs IgGs, measured by ELISA, and the SPR signal. Moreover, it was possible to correctly classify patients into “non-responder”, “responder” and “high-responder” groups according to their specific SPR PCV13 response profiles. SPR technology provides a valuable tool for reliably characterize the interaction between anti-PnPs IgGs and PCV13 in a very short experimental time.

Abstract Background Leishmaniasis, considered by the World Health Organization as one of the most important tropical diseases, is endemic in the Mediterranean Basin. The aim of this study was to evaluate epidemiological and clinical characteristics of cutaneous (CL) and mucocutaneous leishmaniasis (MCL) in La Fe University Hospital, Valencia, Spain. The particular focus was on diagnosis techniques and clinical differences according to the immunological status of the patients. Methods An eleven-year retrospective observational study of CL and MCL episodes at the hospital was performed. Epidemiological, clinical and therapeutic variables of each case, together with the microbiological and anatomopathological diagnosis, were analyzed. Results A total of 42 patients were included, 30 of them were male and 28 were immunocompetent. Most of the cases (36/42) were diagnosed in the last 5 years (2013–2017). The incidence of CL and MCL increased from 3.6/100,000 (2006–2012) to 13.58/100,000 (2013–2017). The majority of the patients (37/42) exhibited CL, in 30 cases as single lesions (30/37). Ulcerative lesions were more common in immunosuppressed patients (13/14) than in immunocompetent patients (20/28), (P = 0.2302). The length of lesion presence before diagnosis was 7.36 ± 6.72 months in immunocompetent patients and 8.79 ± 6.9 months in immunosuppressed patients (P = 0.1863). Leishmania DNA detection (92.3%) was the most sensitive diagnostic technique followed by Giemsa stain (65%) and histopathological examination (53.8%). Twelve patients (12/42) had close contact with dogs or were living near to kennels, and 10 of them did not present underlying conditions. Intralesional glucantime (21/42) and liposomal amphotericin B (7/42) were the most common treatments administered in monotherapy. All patients evolved successfully and no relapse was reported. Conclusions Some interesting clinical and epidemiological differences were found in our series between immunocompetent and immunosuppressed patients. Future studies can take these results further especially by studying patients with biological therapy. Skin biopsies combining NAAT with histological techniques are the most productive techniques for CL or MCL diagnosis.

BACKGROUND:Whole genome sequencing provides better delineation of transmission clusters in Mycobacterium tuberculosis than traditional methods. However, its ability to reveal individual transmission links within clusters is limited. Here, we used a 2-step approach based on Bayesian transmission reconstruction to (1) identify likely index and missing cases, (2) determine risk factors associated with transmitters, and (3) estimate when transmission happened. METHODS AND FINDINGS:We developed our transmission reconstruction method using genomic and epidemiological data from a population-based study from Valencia Region, Spain. Tuberculosis (TB) incidence during the study period was 8.4 cases per 100,000 people. While the study is ongoing, the sampling frame for this work includes notified TB cases between 1 January 2014 and 31 December 2016. We identified a total of 21 transmission clusters that fulfilled the criteria for analysis. These contained a total of 117 individuals diagnosed with active TB (109 with epidemiological data). Demographic characteristics of the study population were as follows: 80/109 (73%) individuals were Spanish-born, 76/109 (70%) individuals were men, and the mean age was 42.51 years (SD 18.46). We found that 66/109 (61%) TB patients were sputum positive at diagnosis, and 10/109 (9%) were HIV positive. We used the data to reveal individual transmission links, and to identify index cases, missing cases, likely transmitters, and associated transmission risk factors. Our Bayesian inference approach suggests that at least 60% of index cases are likely misidentified by local public health. Our data also suggest that factors associated with likely transmitters are different to those of simply being in a transmission cluster, highlighting the importance of differentiating between these 2 phenomena. Our data suggest that type 2 diabetes mellitus is a risk factor associated with being a transmitter (odds ratio 0.19 [95% CI 0.02-1.10], p < 0.003). Finally, we used the most likely timing for transmission events to study when TB transmission occurred; we identified that 5/14 (35.7%) cases likely transmitted TB well before symptom onset, and these were largely sputum negative at diagnosis. Limited within-cluster diversity does not allow us to extrapolate our findings to the whole TB population in Valencia Region. CONCLUSIONS:In this study, we found that index cases are often misidentified, with downstream consequences for epidemiological investigations because likely transmitters can be missed. Our findings regarding inferred transmission timing suggest that TB transmission can occur before patient symptom onset, suggesting also that TB transmits during sub-clinical disease. This result has direct implications for diagnosing TB and reducing transmission. Overall, we show that a transition to individual-based genomic epidemiology will likely close some of the knowledge gaps in TB transmission and may redirect efforts towards cost-effective contact investigations for improved TB control.