Skin and soft tissue infections and bacteremia caused by Vibrio cincinnatiensis

Epidemiological and environmental investigation of the 'big four' Vibrio species, 1994 to 2021: a Baltic Sea retrospective study

BackgroundThe Vibrio genus comprises several bacterial species present in the Baltic Sea region (BSR), which are known to cause human infections.AimTo provide a comprehensive retrospective analysis of Vibrio-induced infections in the BSR from 1994 to 2021, focusing on the 'big four' Vibrio species - V. alginolyticus, V. cholerae non-O1/O139, V. parahaemolyticus and V. vulnificus - in eight European countries (Denmark, Estonia, Finland, Germany, Latvia, Lithuania, Poland and Sweden) bordering the Baltic Sea.MethodsOur analysis includes data on infections, Vibrio species distribution in coastal waters and environmental data received from national health agencies or extracted from scientific literature and online databases. A redundancy analysis was performed to determine the potential impact of several independent variables, such as sea surface temperature, salinity, the number of designated coastal beaches and year, on the Vibrio infection rate.ResultsFor BSR countries conducting surveillance, we observed an exponential increase in total Vibrio infections (n = 1,553) across the region over time. In Sweden and Germany, total numbers of Vibrio spp. and infections caused by V. alginolyticus and V. parahaemolyticus positively correlate with increasing sea surface temperature. Salinity emerged as a critical driver of Vibrio spp. distribution and abundance. Furthermore, our proposed statistical model reveals 12 to 20 unreported cases in Lithuania and Poland, respectively, countries with no surveillance.ConclusionsThere are discrepancies in Vibrio surveillance and monitoring among countries, emphasising the need for comprehensive monitoring programmes of these pathogens to protect human health, particularly in the context of climate change.

Metagenomic Next-Generation Sequencing for the Diagnosis of Neonatal Infectious Diseases

Infectious diseases pose a fatal risk to neonates. Timely and accurate pathogen detection is crucial for proper clinical diagnosis and therapeutic strategies. Limited sample volumes from neonatal patients seriously hindered the accurate detection of pathogens. Here, we unravel that metagenomic next-generation sequencing (mNGS) of cell-free DNA (cfDNA) and RNA can achieve unbiased detection of trace pathogens from different kinds of body fluid samples and blood samples. We enrolled 168 neonatal patients with suspected infections from whom blood samples (n = 153), cerebrospinal fluid samples (n = 127), and respiratory tract samples (RTSs) (including bronchoalveolar lavage fluids, sputa, and respiratory secretions) (n = 51) were collected and analyzed using mNGS. High rates of positivity (70.2%; 118/168) of mNGS were observed, and the coincidence rate against the final clinical diagnosis in positive mNGS cases reached 68.6% (81/118). The most common causative pathogens were Klebsiella pneumoniae (n = 12), Escherichia coli (n = 12), and Streptococcus pneumoniae (n = 8). mNGS using cfDNA and RNA can identify microbes that cannot be detected by conventional methods in different body fluid and blood samples, and more than 50% of these microbes were identified as causative pathogens. Further local polynomial regression fitting analysis revealed that the best timing for mNGS detection ranged from 1 to 3 days after the start of continuous antimicrobial therapy. Diagnosed and guided by mNGS results, the therapeutic regimens for 86 out of 117 neonatal patients were changed, most of whom (80/86) completely recovered and were discharged, while 44 out of 86 patients completely or partially stopped unnecessary medication. Our findings highlight the importance of mNGS in detecting causative DNA and RNA pathogens in infected neonatal patients. IMPORTANCE To the best of our knowledge, this is the first report on evaluating the performance of mNGS using cfDNA and RNA from body fluid and blood samples for diagnosing neonatal infections. mNGS of RNA and cfDNA can achieve the unbiased detection and identification of trace pathogens from different kinds of neonatal body fluid and blood samples with a high total coincidence rate (226/331; 68.3%) against final clinical diagnoses by sample. The best timing for mNGS detection in neonatal infections ranged from 1 to 3 days, rather than 0 days, after the start of continuous antimicrobial therapy. Our findings highlight the importance of mNGS in detecting causative DNA and RNA pathogens, and the extensive application of mNGS for the diagnosis of neonatal infections can be expected.